Test Report

Result	Test	Duration
Passed	tests/test_hotstart.py::test_contbox_hotstart	0.87
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ quantiles: [[0.0999987 0.10027959] [0.09999767 0.00994516] [0. 0. ]] quantiles: [[0.10000128 0.90027998] [0.10000232 0.99020105] [1. 1. ]] refined quantiles: [[0.0999987 0.10027959] [0.09999767 0.00994516] [0.09999757 0.00994515] [0.09999667 0.00994507] [0.09998767 0.00994417] [0.09989767 0.00993522] [0.09899769 0.00984571] [0.0899979 0.00895065] [0. 0. ]] refined quantiles: [[0.10000128 0.90027998] [0.10000232 0.99020105] [0.10000322 0.99020106] [0.10001132 0.99020115] [0.10009232 0.99020203] [0.10090232 0.99021085] [0.1090023 0.99029904] [0.19000209 0.99118094] [1. 1. ]] interpolation steps: [0. 0.5 0.57142857 0.64285714 0.71428571 0.78571429 0.85714286 0.92857143 1. ] 1 0 0.1 0.10027868725259927 0.10027958811947346 1 0 0.9 0.900280652474506 0.9002799801464451 1 1 0.01 0.009945123090421873 0.00994516485717889 1 1 0.99 0.9902011121290584 0.9902010491256017 0 0 0.1 0.09999870497200372 0.09999870499119054 0 0 0.9 0.10000128350797187 0.10000128350631807 0 1 0.01 0.0999976704877551 0.09999767048845995 0 1 0.99 0.10000231905758632 0.10000231905671242 -3766372148.7910614 ['mean', 'scatter', 'aux_logweight'] ['mean', 'scatter'] [-5.64488732e+07 -8.79276680e+06 -1.64026327e+04 -1.13847669e+05 -7.71968605e+08 -1.33363614e+10 -4.93868364e+10 -1.32687260e+11 -1.26756527e+06 -6.82926461e+05 -2.90497533e+10] /tmp/tmpuek037wl/weighted_posterior_samples.txt -146788650551.04892 [-4.98040191e+04 -2.25834184e+09 -1.62610556e+07 -7.51537324e+05 -3.53911227e+06 -2.35923077e+08 -2.61869584e+11 -3.28111914e+10 -1.64785408e+11 -3.31346013e+06 -2.77037253e+11]
Passed	tests/test_flatnuts.py::test_singlejumper	0.10
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ make reflect make stuck
Passed	tests/test_netiterintegrate.py::test_singleblock[100]	6.53
[gw10] linux -- Python 3.10.6 /usr/bin/python3 [gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ================================================================================ NLIVE=100 Standard integrator 236.2 +- 0.2 in 740 iter 0.97s Graph integrator 236.1732 +- 0.2430 (main) 236.2408 +- 0.3325 (bs) 236.2 +- 0.2 in 842 iter 1.66s Vectorized graph integrator tree size: (822, 100) 236.1728 +- 0.2432 (main) 236.1499 +- 0.3864 (bs) 236.2 +- 0.2 in 822 iter 1.25s Vectorized graph integrator with insertion order test tree size: (822, 100) 236.1728 +- 0.2432 (main) 236.2381 +- 0.3834 (bs) insertion order: inf 236.2 +- 0.2 in 822 iter 1.57s
Passed	tests/test_clustering.py::test_overclustering_eggbox_update	8.23
[gw4] linux -- Python 3.10.6 /usr/bin/python3 [gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ==== TEST CASE 20 ===================== loading... loading... done u0:960 -> u:960 : 881 points are common initialised with: r=3.861322e-01 nc=18 --- intermediate tests how create_new reacts --- updated to (with same data): r=3.861322e-01 nc=18 updated to (with new data): r=3.861322e-01 nc=19 --- end --- setting maxradiussq to None transitioned to : r=4.254452e-01 nc=18 True cluster 1/18: 82 points @ 0.40067 +- 0.01202 , 0.40022 +- 0.01511 cluster 2/18: 44 points @ 0.60378 +- 0.01234 , 0.98922 +- 0.00757 cluster 3/18: 89 points @ 0.59884 +- 0.01297 , 0.19993 +- 0.01399 cluster 4/18: 70 points @ 0.59770 +- 0.01321 , 0.59970 +- 0.01270 cluster 5/18: 66 points @ 0.79962 +- 0.01283 , 0.40189 +- 0.01364 cluster 6/18: 75 points @ 0.20262 +- 0.01346 , 0.20165 +- 0.01254 cluster 7/18: 32 points @ 0.19776 +- 0.01239 , 0.98809 +- 0.00597 cluster 8/18: 31 points @ 0.01257 +- 0.00703 , 0.39886 +- 0.01234 cluster 9/18: 67 points @ 0.79925 +- 0.01331 , 0.80076 +- 0.01356 cluster 10/18: 42 points @ 0.79877 +- 0.01327 , 0.01046 +- 0.00668 cluster 11/18: 41 points @ 0.99046 +- 0.00685 , 0.19675 +- 0.01388 cluster 12/18: 39 points @ 0.39798 +- 0.01322 , 0.00984 +- 0.00698 cluster 13/18: 23 points @ 0.01097 +- 0.00852 , 0.01041 +- 0.00711 cluster 14/18: 73 points @ 0.20029 +- 0.01323 , 0.59918 +- 0.01368 cluster 15/18: 44 points @ 0.98858 +- 0.00665 , 0.60129 +- 0.01259 cluster 16/18: 41 points @ 0.01238 +- 0.00658 , 0.80156 +- 0.01229 cluster 17/18: 84 points @ 0.40175 +- 0.01292 , 0.79791 +- 0.01272 cluster 18/18: 17 points @ 0.98546 +- 0.00732 , 0.98774 +- 0.00694 ==== TEST CASE 23 ===================== loading... loading... done u0:1040 -> u:1040 : 966 points are common initialised with: r=6.160003e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=6.160003e-03 nc=1 updated to (with new data): r=6.160003e-03 nc=18 found lonely points 1039 18 (array([1]), array([1040])) --- end --- setting maxradiussq to None transitioned to : r=3.440933e-01 nc=18 True cluster 1/18: 73 points @ 0.60558 +- 0.03956 , 0.60161 +- 0.03742 cluster 2/18: 79 points @ 0.40034 +- 0.03940 , 0.40519 +- 0.03757 cluster 3/18: 41 points @ 0.97203 +- 0.02060 , 0.20253 +- 0.03872 cluster 4/18: 84 points @ 0.19581 +- 0.04039 , 0.60134 +- 0.03804 cluster 5/18: 87 points @ 0.20159 +- 0.03605 , 0.20771 +- 0.03841 cluster 6/18: 85 points @ 0.80668 +- 0.03802 , 0.40101 +- 0.03809 cluster 7/18: 39 points @ 0.03874 +- 0.02094 , 0.80033 +- 0.03636 cluster 8/18: 80 points @ 0.79850 +- 0.03921 , 0.79083 +- 0.03705 cluster 9/18: 40 points @ 0.96956 +- 0.02038 , 0.60841 +- 0.03341 cluster 10/18: 99 points @ 0.60042 +- 0.03532 , 0.19601 +- 0.03848 cluster 11/18: 19 points @ 0.04123 +- 0.02000 , 0.02673 +- 0.02228 cluster 12/18: 40 points @ 0.40610 +- 0.03892 , 0.03809 +- 0.02090 cluster 13/18: 87 points @ 0.40176 +- 0.03955 , 0.79885 +- 0.03542 cluster 14/18: 52 points @ 0.20797 +- 0.03841 , 0.96717 +- 0.02119 cluster 15/18: 38 points @ 0.59639 +- 0.03805 , 0.96716 +- 0.01828 cluster 16/18: 44 points @ 0.80236 +- 0.04018 , 0.03255 +- 0.01736 cluster 17/18: 21 points @ 0.96129 +- 0.01684 , 0.96388 +- 0.01766 cluster 18/18: 32 points @ 0.03640 +- 0.01610 , 0.39737 +- 0.03884 ==== TEST CASE 24 ===================== loading... loading... done u0:1080 -> u:1080 : 720 points are common initialised with: r=2.523267e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=2.523267e-03 nc=1 updated to (with new data): r=2.523267e-03 nc=19 --- end --- setting maxradiussq to None transitioned to : r=7.393072e-01 nc=18 True cluster 1/18: 50 points @ 0.80133 +- 0.02367 , 0.40736 +- 0.02143 cluster 2/18: 67 points @ 0.40401 +- 0.02029 , 0.40261 +- 0.02217 cluster 3/18: 23 points @ 0.01998 +- 0.01209 , 0.81024 +- 0.01845 cluster 4/18: 60 points @ 0.20213 +- 0.02305 , 0.20032 +- 0.01965 cluster 5/18: 32 points @ 0.60086 +- 0.02176 , 0.98367 +- 0.01059 cluster 6/18: 47 points @ 0.80338 +- 0.02194 , 0.79993 +- 0.01991 cluster 7/18: 36 points @ 0.98306 +- 0.01107 , 0.59781 +- 0.02273 cluster 8/18: 76 points @ 0.59943 +- 0.01980 , 0.19632 +- 0.02156 cluster 9/18: 56 points @ 0.20016 +- 0.01965 , 0.59828 +- 0.02257 cluster 10/18: 9 points @ 0.01908 +- 0.01199 , 0.01513 +- 0.01132 cluster 11/18: 59 points @ 0.39933 +- 0.02184 , 0.80070 +- 0.02167 cluster 12/18: 29 points @ 0.98462 +- 0.01006 , 0.20604 +- 0.02154 cluster 13/18: 30 points @ 0.80514 +- 0.02107 , 0.01876 +- 0.00936 cluster 14/18: 14 points @ 0.98169 +- 0.01256 , 0.97917 +- 0.01043 cluster 15/18: 49 points @ 0.59988 +- 0.02080 , 0.59826 +- 0.02404 cluster 16/18: 22 points @ 0.02401 +- 0.00978 , 0.40533 +- 0.01845 cluster 17/18: 32 points @ 0.20429 +- 0.02222 , 0.97957 +- 0.00988 cluster 18/18: 29 points @ 0.39559 +- 0.02135 , 0.01376 +- 0.01155 ==== TEST CASE 27 ===================== loading... loading... done u0:1160 -> u:1160 : 790 points are common initialised with: r=4.168517e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=4.168517e-03 nc=1 updated to (with new data): r=4.168517e-03 nc=18 found lonely points 879 18 (array([1]), array([1160])) --- end --- setting maxradiussq to None transitioned to : r=4.282518e-01 nc=18 True cluster 1/18: 28 points @ 0.02876 +- 0.01072 , 0.40418 +- 0.02504 cluster 2/18: 72 points @ 0.40427 +- 0.02589 , 0.40337 +- 0.02568 cluster 3/18: 66 points @ 0.80063 +- 0.03025 , 0.79903 +- 0.02314 cluster 4/18: 69 points @ 0.80137 +- 0.02777 , 0.40462 +- 0.02720 cluster 5/18: 31 points @ 0.02746 +- 0.01466 , 0.79860 +- 0.02690 cluster 6/18: 62 points @ 0.59600 +- 0.02452 , 0.59711 +- 0.02909 cluster 7/18: 64 points @ 0.20064 +- 0.02644 , 0.20221 +- 0.02651 cluster 8/18: 36 points @ 0.59915 +- 0.02534 , 0.97793 +- 0.01435 cluster 9/18: 39 points @ 0.97736 +- 0.01458 , 0.59960 +- 0.02338 cluster 10/18: 86 points @ 0.60015 +- 0.02393 , 0.19435 +- 0.02628 cluster 11/18: 32 points @ 0.98151 +- 0.01174 , 0.20348 +- 0.02462 cluster 12/18: 65 points @ 0.19863 +- 0.02526 , 0.59691 +- 0.02542 cluster 13/18: 15 points @ 0.02567 +- 0.01173 , 0.02191 +- 0.01523 cluster 14/18: 41 points @ 0.39375 +- 0.02798 , 0.02135 +- 0.01484 cluster 15/18: 77 points @ 0.40243 +- 0.02649 , 0.80397 +- 0.02748 cluster 16/18: 38 points @ 0.80371 +- 0.02372 , 0.02465 +- 0.01314 cluster 17/18: 18 points @ 0.97856 +- 0.01405 , 0.97604 +- 0.01338 cluster 18/18: 41 points @ 0.19975 +- 0.02576 , 0.97554 +- 0.01299 ==== TEST CASE 42 ===================== loading... loading... done u0:1640 -> u:1640 : 1324 points are common initialised with: r=2.155017e-01 nc=18 --- intermediate tests how create_new reacts --- updated to (with same data): r=2.155017e-01 nc=18 updated to (with new data): r=2.155017e-01 nc=20 --- end --- setting maxradiussq to None transitioned to : r=2.029861e-01 nc=18 True cluster 1/18: 134 points @ 0.20129 +- 0.00945 , 0.20101 +- 0.01049 cluster 2/18: 65 points @ 0.59936 +- 0.00932 , 0.99209 +- 0.00545 cluster 3/18: 85 points @ 0.99089 +- 0.00488 , 0.60043 +- 0.01046 cluster 4/18: 130 points @ 0.60003 +- 0.00928 , 0.20093 +- 0.01017 cluster 5/18: 129 points @ 0.59949 +- 0.00979 , 0.60100 +- 0.01016 cluster 6/18: 70 points @ 0.00947 +- 0.00504 , 0.79955 +- 0.00842 cluster 7/18: 130 points @ 0.40067 +- 0.00968 , 0.40022 +- 0.01000 cluster 8/18: 122 points @ 0.79990 +- 0.00981 , 0.80044 +- 0.00967 cluster 9/18: 65 points @ 0.19964 +- 0.00934 , 0.99144 +- 0.00504 cluster 10/18: 72 points @ 0.00860 +- 0.00543 , 0.40071 +- 0.01088 cluster 11/18: 128 points @ 0.19967 +- 0.01029 , 0.60159 +- 0.01024 cluster 12/18: 79 points @ 0.79941 +- 0.00983 , 0.00749 +- 0.00504 cluster 13/18: 76 points @ 0.99223 +- 0.00521 , 0.19896 +- 0.00995 cluster 14/18: 69 points @ 0.39964 +- 0.00971 , 0.00907 +- 0.00538 cluster 15/18: 126 points @ 0.40202 +- 0.00982 , 0.79926 +- 0.00912 cluster 16/18: 99 points @ 0.80119 +- 0.00999 , 0.39961 +- 0.00929 cluster 17/18: 29 points @ 0.98948 +- 0.00510 , 0.99242 +- 0.00478 cluster 18/18: 32 points @ 0.00711 +- 0.00510 , 0.00782 +- 0.00532
Passed	tests/test_clustering.py::test_overclustering_eggbox_txt	0.61
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ==== TEST CASE 20 ===================== manual: r=2.989717e-03 nc=1 reclustered: nc=18 manual: r=2.989717e-03 nc=1 reclustered: nc=18 manual: r=2.270048e-03 nc=1 reclustered: nc=18 ==== TEST CASE 23 ===================== manual: r=1.212573e-05 nc=1 reclustered: nc=18 manual: r=1.353579e-05 nc=1 reclustered: nc=18 manual: r=1.235571e-05 nc=1 reclustered: nc=18 ==== TEST CASE 24 ===================== manual: r=3.947988e-05 nc=1 reclustered: nc=18 manual: r=4.172909e-05 nc=1 reclustered: nc=18 manual: r=7.273383e-05 nc=1 reclustered: nc=18 ==== TEST CASE 27 ===================== manual: r=1.978904e-08 nc=1 reclustered: nc=18 manual: r=1.890650e-08 nc=1 reclustered: nc=18 manual: r=1.605539e-08 nc=1 reclustered: nc=18 ==== TEST CASE 49 ===================== manual: r=6.815424e-05 nc=1 reclustered: nc=18 manual: r=4.236106e-05 nc=1 reclustered: nc=18 manual: r=5.657479e-05 nc=1 reclustered: nc=18
Passed	tests/test_clustering.py::test_clustering	4.75
[gw0] linux -- Python 3.10.6 /usr/bin/python3 [gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_flatnuts.py::test_detailed_balance	5.53
[gw6] linux -- Python 3.10.6 /usr/bin/python3 [gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ---- seed=1 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 BACKWARD SAMPLING FROM 4 [0.14168242 0.38811823] [0.02821641 0.02835197] -0.1665060917360781 BACKWARD SAMPLING FROM -4 [0.11583903 0.41282151] [-0.02893116 -0.02762223] -0.10171045505355579 BisectSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), None, None, None, 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 1, array([0.02881679, 0.27471034]), array([ 0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.02881679 0.27471034] [ 0.02893116 -0.02762223] new direction: [0.02821641 0.02835197] reversing there [ 0.02893116 -0.02762223] making one step from [0.02881679 0.27471034] [ 0.02893116 -0.02762223] --> [0.0570332 0.30306231] [0.02821641 0.02835197] trying new point, [0.0570332 0.30306231] next() call -0.48643206112737647 goals: [('reflect-at', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09073879959282771 goals: [('bisect', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), None, None, None, 10, array([0.31098087, 0.55823006]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31098087 0.55823006] [0.02821641 0.02835197] -0.09073879959282771 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), None, None, None, 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1016481498381896 goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.25225605758357234 goals: [('bisect', 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3588980473806718 goals: [('bisect', 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4864320611273768 goals: [('bisect', 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 9, array([0.0570332 , 0.30306231]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.02881679 0.27471034] [-0.02821641 -0.02835197] new direction: [-0.02893116 0.02762223] reversing there [-0.02821641 -0.02835197] making one step from [0.02881679 0.27471034] [-0.02821641 -0.02835197] --> [1.14374817e-04 3.02332573e-01] [0.02893116 0.02762223] trying new point, [1.14374817e-04 3.02332573e-01] next() call -0.4884051545701359 goals: [('reflect-at', 10, array([1.14374817e-04, 3.02332573e-01]), array([0.02893116, 0.02762223]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 sampling between (-3, 4) ---- seed=2 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 BACKWARD SAMPLING FROM 4 [0.550579 0.59531977] [0.00022913 0.03999934] -0.2651418446056711 BACKWARD SAMPLING FROM -2 [0.54920422 0.35532371] [0.00022913 0.03999934] -0.4124530140569493 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), None, None, None, 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3805855729471914 goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 6, array([0.55103726, 0.67531846]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.55103726 0.67531846] [0.00022913 0.03999934] new direction: [-0.03532089 0.01877324] reversing there [0.00022913 0.03999934] making one step from [0.55103726 0.67531846] [0.00022913 0.03999934] --> [0.51571637 0.69409169] [-0.03532089 0.01877324] trying new point, [0.51571637 0.69409169] next() call None goals: [('reflect-at', 6, array([0.51571637, 0.69409169]), array([-0.03532089, 0.01877324]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.54989161 0.47532174] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.55080813 0.63531911] [0.00022913 0.03999934] -0.3805855729471914 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2033543310016853 goals: [('bisect', 0, array([0.55080813, 0.63531911]), array([-0.00022913, -0.03999934]), None, None, None, 5, array([0.54966248, 0.43532239]), array([-0.00022913, -0.03999934]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=3 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 BACKWARD SAMPLING FROM 4 [0.23962941 0.66238895] [-0.01281883 0.03789034] -0.3583382577658276 BACKWARD SAMPLING FROM -4 [0.34218007 0.35926626] [-0.01281883 0.03789034] -0.306118410872214 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), None, None, None, 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12894573017062852 goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.22561386347891177 goals: [('bisect', 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3583382577658276 goals: [('bisect', 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 4, array([0.23962941, 0.66238895]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22681058 0.70027928] [-0.01281883 0.03789034] new direction: [-0.03961561 -0.00553205] reversing there [-0.01281883 0.03789034] making one step from [0.22681058 0.70027928] [-0.01281883 0.03789034] --> [0.18719497 0.69474723] [-0.03961561 -0.00553205] trying new point, [0.18719497 0.69474723] next() call -0.4916020278270488 goals: [('reflect-at', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3490349009639423 goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), None, None, None, 10, array([0.01088307, 0.66708697]), array([ 0.03961561, -0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.01088307 0.66708697] [ 0.03961561 -0.00553205] -0.3490349009639423 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), None, None, None, 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4916020278270488 goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 6, array([0.22681058, 0.70027928]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22681058 0.70027928] [0.03961561 0.00553205] new direction: [ 0.01281883 -0.03789034] reversing there [0.03961561 0.00553205] making one step from [0.22681058 0.70027928] [0.03961561 0.00553205] --> [0.23962941 0.66238895] [ 0.01281883 -0.03789034] trying new point, [0.23962941 0.66238895] next() call -0.3583382577658272 goals: [('reflect-at', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04377824648995988 goals: [('bisect', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), None, None, None, 10, array([0.29090474, 0.51082761]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=4 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BACKWARD SAMPLING FROM 4 [0.80905758 0.52184001] [-0.03949306 -0.00634806] -0.33324941010291637 BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16694885584599184 goals: [('bisect', 0, array([0.96702984, 0.54723225]), array([-0.03949306, -0.00634806]), None, None, None, 10, array([0.5720992 , 0.48375165]), array([-0.03949306, -0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.5720992 0.48375165] [-0.03949306 -0.00634806] -0.16694885584599184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.49545942179887775 goals: [('bisect', 0, array([0.5720992 , 0.48375165]), array([0.03949306, 0.00634806]), None, None, None, 10, array([0.96702984, 0.54723225]), array([0.03949306, 0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 sampling between (-4, 3) ---- seed=5 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 BACKWARD SAMPLING FROM 4 [0.63456332 0.54663199] [ 0.03653803 -0.01627797] -0.22851708746536278 BACKWARD SAMPLING FROM -4 [0.34225906 0.67685573] [ 0.03653803 -0.01627797] -0.4495450053329357 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3970381430661767 goals: [('bisect', 0, array([0.48841119, 0.61174386]), array([ 0.03653803, -0.01627797]), None, None, None, 10, array([0.85379151, 0.44896419]), array([ 0.03653803, -0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.85379151 0.44896419] [ 0.03653803 -0.01627797] -0.3970381430661767 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.27535638087505515 goals: [('bisect', 0, array([0.85379151, 0.44896419]), array([-0.03653803, 0.01627797]), None, None, None, 10, array([0.48841119, 0.61174386]), array([-0.03653803, 0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-13, 2) ---- seed=6 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 BACKWARD SAMPLING FROM 4 [0.03716733 0.66306682] [0.036206 0.01700369] -0.3330755453049499 BACKWARD SAMPLING FROM -4 [0.25248069 0.52703731] [-0.036206 0.01700369] -0.041010950598001826 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), None, None, None, 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4080091653243474 goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4914817954950847 goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 6, array([0.10957933, 0.6970742 ]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.14578533 0.71407788] [0.036206 0.01700369] new direction: [ 0.02481099 -0.03137538] reversing there [0.036206 0.01700369] making one step from [0.14578533 0.71407788] [0.036206 0.01700369] --> [0.17059633 0.6827025 ] [ 0.02481099 -0.03137538] trying new point, [0.17059633 0.6827025 ] next() call -0.4318041009131332 goals: [('reflect-at', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12809180647624227 goals: [('bisect', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), None, None, None, 10, array([0.2450293 , 0.58857635]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.2450293 0.58857635] [ 0.02481099 -0.03137538] -0.12809180647624227 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), None, None, None, 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.30534071772163773 goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4318041009131337 goals: [('bisect', 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 4, array([0.14578533, 0.71407788]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.14578533 0.71407788] [-0.02481099 0.03137538] new direction: [-0.036206 -0.01700369] reversing there [-0.02481099 0.03137538] making one step from [0.14578533 0.71407788] [-0.02481099 0.03137538] --> [0.10957933 0.6970742 ] [-0.036206 -0.01700369] trying new point, [0.10957933 0.6970742 ] next() call -0.4914817954950847 goals: [('reflect-at', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1187311667407582 goals: [('bisect', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), None, None, None, 10, array([0.10765668, 0.59505206]), array([ 0.036206 , -0.01700369]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=7 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM -3 [0.91202793 0.42346309] [0.02932044 0.02720867] -0.48912121118231033 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 1, array([0.95598978, 0.57190263]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.95598978 0.57190263] [-0.02199973 0.03340676] new direction: [-0.03029182 0.0261229 ] reversing there [-0.02199973 0.03340676] making one step from [0.95598978 0.57190263] [-0.02199973 0.03340676] --> [0.92569796 0.59802553] [-0.03029182 0.0261229 ] trying new point, [0.92569796 0.59802553] next() call None goals: [('reflect-at', 1, array([0.92569796, 0.59802553]), array([-0.03029182, 0.0261229 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call -0.4882763953959062 goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -2, array([0.97801102, 0.47168235]), array([0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 bisecting gave reflection point -3 [0.95601129 0.43827559] [0.02199973 0.03340676] new direction: [ 0.01936874 -0.03499789] reversing there [0.02199973 0.03340676] making one step from [0.95601129 0.43827559] [0.02199973 0.03340676] --> [0.97538002 0.4032777 ] [-0.01936874 0.03499789] trying new point, [0.97538002 0.4032777 ] next() call None goals: [('reflect-at', -3, array([0.97538002, 0.4032777 ]), array([-0.01936874, 0.03499789]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] reversing at -2... -7 steps to do at -2 -> [from -3, delta=-7] targeting 4. goals: [('sample-at', 4)] reversing at 0... 4 steps to do at 0 -> [from 1, delta=4] targeting -3. goals: [('sample-at', -3)] reversing at -2... -1 steps to do at -2 -> [from -3, delta=-1] targeting -2. goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -2 [0.97801102 0.47168235] [0.02199973 0.03340676] -0.4882763953959062 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -2)] not done yet, continue expanding to -2... goals: [('expand-to', -2), ('sample-at', -2)] next() call -0.49675589327088776 goals: [('bisect', 0, array([0.97801102, 0.47168235]), array([-0.02199973, -0.03340676]), None, None, None, -2, array([0.97798951, 0.53849587]), array([ 0.02199973, -0.03340676]), -1), ('sample-at', -2)] bisecting ... 0 None -2 successfully went all the way in one jump! goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=8 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4375602772906623 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48991371862053074 goals: [('bisect', 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 4, array([0.98770652, 0.42336192]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.98770652 0.42336192] [ 0.02962799 -0.02687344] new direction: [-0.03704999 -0.01507642] reversing there [ 0.02962799 -0.02687344] making one step from [0.98770652 0.42336192] [ 0.02962799 -0.02687344] --> [0.95065653 0.4082855 ] [-0.03704999 -0.01507642] trying new point, [0.95065653 0.4082855 ] next() call None goals: [('reflect-at', 4, array([0.95065653, 0.4082855 ]), array([-0.03704999, -0.01507642]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.45977857566680347 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, -3, array([0.78031056, 0.61147602]), array([ 0.02962799, -0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.95807852, 0.45023536]), array([-0.02962799, 0.02687344]), None, None, None, 3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.78031056, 0.61147602]), array([-0.02962799, 0.02687344]), None, None, None, -3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=9 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 BACKWARD SAMPLING FROM 4 [0.11061846 0.39718082] [ 0.03024815 -0.02617344] -0.13826553062534178 BACKWARD SAMPLING FROM -4 [0.13136677 0.60656837] [-0.03024815 -0.02617344] -0.1505888292401249 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), None, None, None, 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2179104295369838 goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43132376818592777 goals: [('bisect', 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 8, array([0.23161108, 0.29248704]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23161108 0.29248704] [ 0.03024815 -0.02617344] new direction: [0.02396606 0.03202542] reversing there [ 0.03024815 -0.02617344] making one step from [0.23161108 0.29248704] [ 0.03024815 -0.02617344] --> [0.25557714 0.32451246] [0.02396606 0.03202542] trying new point, [0.25557714 0.32451246] next() call -0.41760827984962573 goals: [('reflect-at', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20128562729667512 goals: [('bisect', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), None, None, None, 10, array([0.30350927, 0.38856331]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30350927 0.38856331] [0.02396606 0.03202542] -0.20128562729667512 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), None, None, None, 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.41760827984962573 goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 3, array([0.23161108, 0.29248704]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23161108 0.29248704] [-0.02396606 -0.03202542] new direction: [-0.03024815 0.02617344] reversing there [-0.02396606 -0.03202542] making one step from [0.23161108 0.29248704] [-0.02396606 -0.03202542] --> [0.20136292 0.31866048] [-0.03024815 0.02617344] trying new point, [0.20136292 0.31866048] next() call -0.43132376818592777 goals: [('reflect-at', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -9.773773097349783e-05 goals: [('bisect', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), None, None, None, 10, array([0.01037415, 0.50187459]), array([0.03024815, 0.02617344]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=10 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 BACKWARD SAMPLING FROM -4 [0.03407747 0.35677655] [-0.00950643 0.03885393] -0.25699258899589295 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10128899988595243 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.2077471298760972 goals: [('bisect', 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3520363250591377 goals: [('bisect', 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 4, array([0.041974 , 0.66760798]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.05148044 0.7064619 ] [0.00950643 0.03885393] new direction: [0.03538475 0.01865259] reversing there [0.00950643 0.03885393] making one step from [0.05148044 0.7064619 ] [0.00950643 0.03885393] --> [0.08686519 0.7251145 ] [0.03538475 0.01865259] trying new point, [0.08686519 0.7251145 ] next() call None goals: [('reflect-at', 5, array([0.08686519, 0.7251145 ]), array([0.03538475, 0.01865259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.008901001072892184 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, -1, array([0.00555817, 0.47333834]), array([-0.00950643, 0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.001865935484349968 goals: [('bisect', 0, array([0.041974 , 0.66760798]), array([-0.00950643, -0.03885393]), None, None, None, 4, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.00555817 0.47333834] [-0.00950643 0.03885393] -0.008901001072892184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0018659354843499343 goals: [('bisect', 0, array([0.00555817, 0.47333834]), array([ 0.00950643, -0.03885393]), None, None, None, -1, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=11 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 BACKWARD SAMPLING FROM 4 [0.37163231 0.33297767] [-0.01214282 -0.03811236] -0.4177610370777551 BACKWARD SAMPLING FROM -4 [0.4687749 0.63787653] [-0.01214282 -0.03811236] -0.3474991729078387 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), None, None, None, 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.18142810704210527 goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.28136395006049925 goals: [('bisect', 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4177610370777551 goals: [('bisect', 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 4, array([0.37163231, 0.33297767]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35948949 0.29486531] [-0.01214282 -0.03811236] new direction: [-0.0041129 0.03978799] reversing there [-0.01214282 -0.03811236] making one step from [0.35948949 0.29486531] [-0.01214282 -0.03811236] --> [0.35537659 0.3346533 ] [-0.0041129 0.03978799] trying new point, [0.35537659 0.3346533 ] next() call -0.4048904116037848 goals: [('reflect-at', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07015589586681098 goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), None, None, None, 10, array([0.3348121 , 0.53359324]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.3348121 0.53359324] [-0.0041129 0.03978799] -0.07015589586681098 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), None, None, None, 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.40489041160378453 goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 6, array([0.35948949, 0.29486531]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.35948949 0.29486531] [ 0.0041129 -0.03978799] new direction: [0.01214282 0.03811236] reversing there [ 0.0041129 -0.03978799] making one step from [0.35948949 0.29486531] [ 0.0041129 -0.03978799] --> [0.37163231 0.33297767] [0.01214282 0.03811236] trying new point, [0.37163231 0.33297767] next() call -0.4177610370777547 goals: [('reflect-at', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0909401530019027 goals: [('bisect', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), None, None, None, 10, array([0.4202036, 0.4854271]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=12 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 BACKWARD SAMPLING FROM 4 [0.13496481 0.43820812] [-0.03208755 -0.02388282] -0.05683571304926094 BACKWARD SAMPLING FROM -4 [0.39166522 0.62927067] [-0.03208755 -0.02388282] -0.2855871537311189 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), None, None, None, 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.09704380253434214 goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.22332799455138033 goals: [('bisect', 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3094040970833373 goals: [('bisect', 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.41076953729758614 goals: [('bisect', 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 9, array([0.02547294, 0.31879402]), array([ 0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] new direction: [ 0.02655384 -0.02991477] reversing there [ 0.03208755 -0.02388282] making one step from [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] --> [0.08411434 0.26499643] [ 0.02655384 -0.02991477] trying new point, [0.08411434 0.26499643] next() call None goals: [('reflect-at', 10, array([0.08411434, 0.26499643]), array([ 0.02655384, -0.02991477]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.02547294 0.31879402] [ 0.03208755 -0.02388282] -0.41076953729758614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.04889673193185484 goals: [('bisect', 0, array([0.02547294, 0.31879402]), array([-0.03208755, 0.02388282]), None, None, None, 9, array([0.26331502, 0.53373939]), array([0.03208755, 0.02388282]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=13 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 BACKWARD SAMPLING FROM 4 [0.40042197 0.52612745] [-0.00300128 -0.03988724] -0.08870192535855582 BACKWARD SAMPLING FROM -4 [0.2145617 0.65653403] [0.03957308 0.00582848] -0.32930462797788607 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), None, None, None, 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 1, array([0.41242711, 0.68567643]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.41242711 0.68567643] [0.03957308 0.00582848] new direction: [-0.00300128 -0.03988724] reversing there [0.03957308 0.00582848] making one step from [0.41242711 0.68567643] [0.03957308 0.00582848] --> [0.40942582 0.64578919] [-0.00300128 -0.03988724] trying new point, [0.40942582 0.64578919] next() call -0.3494958457329673 goals: [('reflect-at', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), None, None, None, 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.08133824843659004 goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.18596233939691564 goals: [('bisect', 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.297950107279207 goals: [('bisect', 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4497216900962508 goals: [('bisect', 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 9, array([0.38541555, 0.32669123]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.38241426 0.28680399] [-0.00300128 -0.03988724] new direction: [0.02675467 0.02973529] reversing there [-0.00300128 -0.03988724] making one step from [0.38241426 0.28680399] [-0.00300128 -0.03988724] --> [0.40916893 0.31653928] [0.02675467 0.02973529] trying new point, [0.40916893 0.31653928] next() call None goals: [('reflect-at', 10, array([0.40916893, 0.31653928]), array([0.02675467, 0.02973529]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.38541555 0.32669123] [-0.00300128 -0.03988724] -0.4497216900962508 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call None goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), None, None, None, 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 None 9 continue bisect at 4 next() call -0.08133824843659004 goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 4 9 continue bisect at 6 next() call -0.13584941721527394 goals: [('bisect', 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 4 6 9 continue bisect at 7 next() call -0.22278072400674448 goals: [('bisect', 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 6 7 9 continue bisect at 8 next() call -0.3494958457329673 goals: [('bisect', 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 8, array([0.40942582, 0.64578919]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 7 8 9 bisecting gave reflection point 9 [0.41242711 0.68567643] [0.00300128 0.03988724] new direction: [-0.03957308 -0.00582848] reversing there [0.00300128 0.03988724] making one step from [0.41242711 0.68567643] [0.00300128 0.03988724] --> [0.37285403 0.67984795] [-0.03957308 -0.00582848] trying new point, [0.37285403 0.67984795] next() call -0.47382613413670327 goals: [('reflect-at', 9, array([0.37285403, 0.67984795]), array([-0.03957308, -0.00582848]), 1), ('sample-at', 9)] goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 sampling between (0, 7) ---- seed=14 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 BACKWARD SAMPLING FROM 4 [0.21608397 0.61107718] [-0.021002 0.03404285] -0.17757288486701345 BACKWARD SAMPLING FROM -4 [0.38409999 0.33873435] [-0.021002 0.03404285] -0.39884901225457176 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), None, None, None, 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2822762805921456 goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41639365668362777 goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 6, array([0.17407996, 0.67916288]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.15307796 0.71320574] [-0.021002 0.03404285] new direction: [ 0.01597666 -0.03667078] reversing there [-0.021002 0.03404285] making one step from [0.15307796 0.71320574] [-0.021002 0.03404285] --> [0.16905462 0.67653496] [ 0.01597666 -0.03667078] trying new point, [0.16905462 0.67653496] next() call -0.40384711686066294 goals: [('reflect-at', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07885688368045461 goals: [('bisect', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), None, None, None, 10, array([0.21698461, 0.56652261]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21698461 0.56652261] [ 0.01597666 -0.03667078] -0.07885688368045461 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), None, None, None, 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.2616431298568962 goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.40384711686066294 goals: [('bisect', 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 4, array([0.15307796, 0.71320574]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.15307796 0.71320574] [-0.01597666 0.03667078] new direction: [ 0.021002 -0.03404285] reversing there [-0.01597666 0.03667078] making one step from [0.15307796 0.71320574] [-0.01597666 0.03667078] --> [0.17407996 0.67916288] [ 0.021002 -0.03404285] trying new point, [0.17407996 0.67916288] next() call -0.41639365668362777 goals: [('reflect-at', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05289910562998976 goals: [('bisect', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), None, None, None, 10, array([0.30009198, 0.47490577]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=15 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 BACKWARD SAMPLING FROM 4 [0.10549014 0.35468978] [ 0.03996334 -0.00171217] -0.2695023366962361 BACKWARD SAMPLING FROM -4 [0.21421657 0.36838711] [-0.03996334 -0.00171217] -0.23946877171984182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36218247700975736 goals: [('bisect', 0, array([0.05436321, 0.36153845]), array([-0.03996334, -0.00171217]), None, None, None, 10, array([0.34527018, 0.34441678]), array([ 0.03996334, -0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.34527018 0.34441678] [ 0.03996334 -0.00171217] -0.36218247700975736 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2411227034306628 goals: [('bisect', 0, array([0.34527018, 0.34441678]), array([-0.03996334, 0.00171217]), None, None, None, 10, array([0.05436321, 0.36153845]), array([0.03996334, 0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=16 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 BACKWARD SAMPLING FROM 4 [0.37021116 0.58652334] [0.03673002 0.01584 ] -0.16210675630294513 BACKWARD SAMPLING FROM -4 [0.076371 0.45980334] [0.03673002 0.01584 ] -0.0231134050599264 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), None, None, None, 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.213778728689882 goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33998787578479583 goals: [('bisect', 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.41452505049277283 goals: [('bisect', 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4966839593077631 goals: [('bisect', 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 9, array([0.55386126, 0.66572334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.59059129 0.68156334] [0.03673002 0.01584 ] new direction: [-0.02554864 -0.0307777 ] reversing there [0.03673002 0.01584 ] making one step from [0.59059129 0.68156334] [0.03673002 0.01584 ] --> [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] trying new point, [0.56504265 0.65078563] next() call -0.44384043934656114 goals: [('reflect-at', 10, array([0.56504265, 0.65078563]), array([-0.02554864, -0.0307777 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] -0.44384043934656114 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), None, None, None, 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 1, array([0.59059129, 0.68156334]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.59059129 0.68156334] [0.02554864 0.0307777 ] new direction: [-0.03673002 -0.01584 ] reversing there [0.02554864 0.0307777 ] making one step from [0.59059129 0.68156334] [0.02554864 0.0307777 ] --> [0.55386126 0.66572334] [-0.03673002 -0.01584 ] trying new point, [0.55386126 0.66572334] next() call -0.49668395930776266 goals: [('reflect-at', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.03163620782532951 goals: [('bisect', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), None, None, None, 10, array([0.22329108, 0.52316334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-13, 2) ---- seed=17 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 BACKWARD SAMPLING FROM 4 [0.15857392 0.61472483] [-0.03402277 0.02103452] -0.1770951824864543 BACKWARD SAMPLING FROM -4 [0.43075609 0.44644868] [-0.03402277 0.02103452] -0.12862220436569055 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), None, None, None, 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2381390123527663 goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3968831438195334 goals: [('bisect', 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.49458344541998867 goals: [('bisect', 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 9, array([0.01153994, 0.71989743]), array([0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.01153994 0.71989743] [0.03402277 0.02103452] new direction: [0.01297498 0.03783715] reversing there [0.03402277 0.02103452] making one step from [0.01153994 0.71989743] [0.03402277 0.02103452] --> [0.02451492 0.75773458] [0.01297498 0.03783715] trying new point, [0.02451492 0.75773458] next() call None goals: [('reflect-at', 9, array([0.02451492, 0.75773458]), array([0.01297498, 0.03783715]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.02248283 0.69886291] [-0.03402277 0.02103452] -0.49458344541998867 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.055108102135022076 goals: [('bisect', 0, array([0.02248283, 0.69886291]), array([ 0.03402277, -0.02103452]), None, None, None, 8, array([0.294665 , 0.53058676]), array([ 0.03402277, -0.02103452]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=18 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 BACKWARD SAMPLING FROM 4 [0.49132867 0.52290346] [-0.03976139 0.00436252] -0.12725903771293967 BACKWARD SAMPLING FROM -4 [0.80941982 0.48800328] [-0.03976139 0.00436252] -0.3293792332040737 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0620527440819295 goals: [('bisect', 0, array([0.65037424, 0.50545337]), array([-0.03976139, 0.00436252]), None, None, None, 10, array([0.25276031, 0.5490786 ]), array([-0.03976139, 0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.25276031 0.5490786 ] [-0.03976139 0.00436252] -0.0620527440819295 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21186506822282286 goals: [('bisect', 0, array([0.25276031, 0.5490786 ]), array([ 0.03976139, -0.00436252]), None, None, None, 10, array([0.65037424, 0.50545337]), array([ 0.03976139, -0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-2, 5) ---- seed=19 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 BACKWARD SAMPLING FROM 4 [0.36264649 0.61284195] [0.03668081 0.01595363] -0.22492257200551513 BACKWARD SAMPLING FROM -4 [0.06920002 0.48521291] [0.03668081 0.01595363] -0.005127547303597255 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), None, None, None, 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28708492992102647 goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43453496563722904 goals: [('bisect', 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 8, array([0.50936972, 0.67665648]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.50936972 0.67665648] [0.03668081 0.01595363] new direction: [-0.02514398 -0.03110917] reversing there [0.03668081 0.01595363] making one step from [0.50936972 0.67665648] [0.03668081 0.01595363] --> [0.48422574 0.64554731] [-0.02514398 -0.03110917] trying new point, [0.48422574 0.64554731] next() call -0.38203753202294766 goals: [('reflect-at', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18094748307481168 goals: [('bisect', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), None, None, None, 10, array([0.43393777, 0.58332898]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43393777 0.58332898] [-0.02514398 -0.03110917] -0.18094748307481168 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), None, None, None, 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.38203753202294766 goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 3, array([0.50936972, 0.67665648]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.50936972 0.67665648] [0.02514398 0.03110917] new direction: [-0.03668081 -0.01595363] reversing there [0.02514398 0.03110917] making one step from [0.50936972 0.67665648] [0.02514398 0.03110917] --> [0.47268891 0.66070285] [-0.03668081 -0.01595363] trying new point, [0.47268891 0.66070285] next() call -0.434534965637229 goals: [('reflect-at', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05335753996074122 goals: [('bisect', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), None, None, None, 10, array([0.21592326, 0.54902743]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=20 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 BACKWARD SAMPLING FROM 4 [0.19493603 0.67431541] [ 0.03976161 -0.00436054] -0.3988233188094961 BACKWARD SAMPLING FROM -1 [0.00387202 0.69611812] [-0.03976161 -0.00436054] -0.48078647770574867 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36832687557067506 goals: [('bisect', 0, array([0.03588959, 0.69175758]), array([ 0.03976161, -0.00436054]), None, None, None, 10, array([0.43350569, 0.64815216]), array([ 0.03976161, -0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43350569 0.64815216] [ 0.03976161 -0.00436054] -0.36832687557067506 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4602811582030628 goals: [('bisect', 0, array([0.43350569, 0.64815216]), array([-0.03976161, 0.00436054]), None, None, None, 10, array([0.03588959, 0.69175758]), array([-0.03976161, 0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=21 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 BACKWARD SAMPLING FROM 4 [0.2415294 0.51588884] [-0.01518562 -0.03700536] -0.032323918419140216 BACKWARD SAMPLING FROM -4 [0.17116112 0.6361286 ] [0.0365741 0.01619676] -0.24628550700212182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), None, None, None, 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.031189595628649723 goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.132317524420316 goals: [('bisect', 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2345797760024729 goals: [('bisect', 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3713075523755122 goals: [('bisect', 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 9, array([0.16560129, 0.33086203]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.15041567 0.29385667] [-0.01518562 -0.03700536] new direction: [-0.02472709 0.03144155] reversing there [-0.01518562 -0.03700536] making one step from [0.15041567 0.29385667] [-0.01518562 -0.03700536] --> [0.12568857 0.32529821] [-0.02472709 0.03144155] trying new point, [0.12568857 0.32529821] next() call -0.3894077367200711 goals: [('reflect-at', 10, array([0.12568857, 0.32529821]), array([-0.02472709, 0.03144155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.12568857 0.32529821] [-0.02472709 0.03144155] -0.3894077367200711 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), None, None, None, 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 1, array([0.15041567, 0.29385667]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.15041567 0.29385667] [ 0.02472709 -0.03144155] new direction: [0.01518562 0.03700536] reversing there [ 0.02472709 -0.03144155] making one step from [0.15041567 0.29385667] [ 0.02472709 -0.03144155] --> [0.16560129 0.33086203] [0.01518562 0.03700536] trying new point, [0.16560129 0.33086203] next() call -0.3713075523755125 goals: [('reflect-at', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3815164574899263 goals: [('bisect', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), None, None, None, 10, array([0.30227189, 0.66391029]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 sampling between (-3, 0) ---- seed=22 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 BACKWARD SAMPLING FROM 4 [0.05625556 0.43234909] [-0.03805125 -0.01233299] -0.05879042044402399 BACKWARD SAMPLING FROM -4 [0.36066552 0.53101304] [-0.03805125 -0.01233299] -0.07706241401616516 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.26560598511461014 goals: [('bisect', 0, array([0.20846054, 0.48168106]), array([-0.03805125, -0.01233299]), None, None, None, 10, array([0.17205191, 0.35835112]), array([ 0.03805125, -0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.17205191 0.35835112] [ 0.03805125 -0.01233299] -0.26560598511461014 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.025922691544438898 goals: [('bisect', 0, array([0.17205191, 0.35835112]), array([-0.03805125, 0.01233299]), None, None, None, 10, array([0.20846054, 0.48168106]), array([0.03805125, 0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=23 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM -4 [0.3745104 0.64096191] [-0.03836626 0.01131504] -0.3185072622476324 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 1, array([0.18267911, 0.69753713]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.18267911 0.69753713] [-0.03836626 0.01131504] new direction: [0.00426897 0.03977155] reversing there [-0.03836626 0.01131504] making one step from [0.18267911 0.69753713] [-0.03836626 0.01131504] --> [0.18694807 0.73730868] [0.00426897 0.03977155] trying new point, [0.18694807 0.73730868] next() call None goals: [('reflect-at', 1, array([0.18694807, 0.73730868]), array([0.00426897, 0.03977155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.24938536408337458 goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, -9, array([0.56634169, 0.58438669]), array([-0.03836626, 0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.56634169 0.58438669] [-0.03836626 0.01131504] -0.24938536408337458 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.45791383918711764 goals: [('bisect', 0, array([0.56634169, 0.58438669]), array([ 0.03836626, -0.01131504]), None, None, None, -9, array([0.22104536, 0.68622209]), array([ 0.03836626, -0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=24 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 BACKWARD SAMPLING FROM 4 [0.16900014 0.35473942] [-0.01277137 0.03790636] -0.2780384655059737 BACKWARD SAMPLING FROM -4 [0.05921351 0.52405108] [ 0.01933277 -0.03501777] -0.008983803050778645 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), None, None, None, 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4480575304829881 goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 3, array([0.19454288, 0.2789267 ]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] new direction: [-0.01277137 0.03790636] reversing there [ 0.01933277 -0.03501777] making one step from [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] --> [0.18177151 0.31683306] [-0.01277137 0.03790636] trying new point, [0.18177151 0.31683306] next() call -0.43589702340056663 goals: [('reflect-at', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08868070867983059 goals: [('bisect', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), None, None, None, 10, array([0.0923719 , 0.58217758]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0923719 0.58217758] [-0.01277137 0.03790636] -0.08868070867983059 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), None, None, None, 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.156265316684782 goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43589702340056663 goals: [('bisect', 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 8, array([0.19454288, 0.2789267 ]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] new direction: [-0.01933277 0.03501777] reversing there [ 0.01277137 -0.03790636] making one step from [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] --> [0.17521011 0.31394447] [-0.01933277 0.03501777] trying new point, [0.17521011 0.31394447] next() call -0.44805753048298835 goals: [('reflect-at', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17758018669487677 goals: [('bisect', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), None, None, None, 10, array([0.13654458, 0.38398001]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=25 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BACKWARD SAMPLING FROM 4 [0.78739516 0.44532469] [-0.02068224 -0.03423806] -0.34736293667574614 BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), None, None, None, 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3927441882386654 goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.46785931365597694 goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 6, array([0.74603067, 0.37684857]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.72534842 0.34261051] [-0.02068224 -0.03423806] new direction: [-0.02832621 -0.02824227] reversing there [-0.02068224 -0.03423806] making one step from [0.72534842 0.34261051] [-0.02068224 -0.03423806] --> [0.69702221 0.31436824] [-0.02832621 -0.02824227] trying new point, [0.69702221 0.31436824] next() call None goals: [('reflect-at', 7, array([0.69702221, 0.31436824]), array([-0.02832621, -0.02824227]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.8080774 0.47956275] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.74603067 0.37684857] [-0.02068224 -0.03423806] -0.46785931365597694 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4631766689679939 goals: [('bisect', 0, array([0.74603067, 0.37684857]), array([0.02068224, 0.03423806]), None, None, None, 6, array([0.87012414, 0.58227693]), array([0.02068224, 0.03423806]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=26 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 BACKWARD SAMPLING FROM 4 [0.14894378 0.53733047] [-0.03974779 0.00448475] -0.028511673439282487 BACKWARD SAMPLING FROM -4 [0.46692612 0.50145249] [-0.03974779 0.00448475] -0.10903637436373395 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.055592009781843664 goals: [('bisect', 0, array([0.30793495, 0.51939148]), array([-0.03974779, 0.00448475]), None, None, None, 10, array([0.08954298, 0.56423895]), array([0.03974779, 0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.08954298 0.56423895] [0.03974779 0.00448475] -0.055592009781843664 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.052112335894670306 goals: [('bisect', 0, array([0.08954298, 0.56423895]), array([-0.03974779, -0.00448475]), None, None, None, 10, array([0.30793495, 0.51939148]), array([ 0.03974779, -0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-1, 6) ---- seed=27 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 BACKWARD SAMPLING FROM -4 [0.04213315 0.3940085 ] [ 0.03615567 -0.01711045] -0.14131507902115056 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.48345727148351275 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 1, array([0.22291152, 0.30845627]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.25906719 0.29134583] [ 0.03615567 -0.01711045] new direction: [0.03637517 0.01663872] reversing there [ 0.03615567 -0.01711045] making one step from [0.25906719 0.29134583] [ 0.03615567 -0.01711045] --> [0.29544236 0.30798455] [0.03637517 0.01663872] trying new point, [0.29544236 0.30798455] next() call None goals: [('reflect-at', 2, array([0.29544236, 0.30798455]), array([0.03637517, 0.01663872]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.039546759765486834 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, -7, array([0.06633386, 0.44533984]), array([-0.03615567, -0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.3977760002874148 goals: [('bisect', 0, array([0.22291152, 0.30845627]), array([-0.03615567, 0.01711045]), None, None, None, 1, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.06633386 0.44533984] [-0.03615567 -0.01711045] -0.039546759765486834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.39777600028741444 goals: [('bisect', 0, array([0.06633386, 0.44533984]), array([0.03615567, 0.01711045]), None, None, None, -7, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=28 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 BACKWARD SAMPLING FROM 4 [0.88862101 0.55003599] [ 0.03990182 -0.0028009 ] -0.4261186566116443 BACKWARD SAMPLING FROM -4 [0.56940648 0.57244321] [ 0.03990182 -0.0028009 ] -0.2277121021981689 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39396757347735606 goals: [('bisect', 0, array([0.72901374, 0.5612396 ]), array([ 0.03990182, -0.0028009 ]), None, None, None, 10, array([0.87196809, 0.53323058]), array([-0.03990182, -0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.87196809 0.53323058] [-0.03990182 -0.0028009 ] -0.39396757347735606 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3126091293887884 goals: [('bisect', 0, array([0.87196809, 0.53323058]), array([0.03990182, 0.0028009 ]), None, None, None, 10, array([0.72901374, 0.5612396 ]), array([-0.03990182, 0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-7, 0) ---- seed=29 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.4842195850803701 BACKWARD SAMPLING FROM -4 [0.53072657 0.40260139] [-0.01950188 0.03492387] -0.25941645597282265 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.24278535636599288 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3480663501867237 goals: [('bisect', 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.48421958508036966 goals: [('bisect', 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 4, array([0.37471154, 0.68199235]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35520966 0.71691623] [-0.01950188 0.03492387] new direction: [-0.01424107 0.03737903] reversing there [-0.01950188 0.03492387] making one step from [0.35520966 0.71691623] [-0.01950188 0.03492387] --> [0.34096859 0.75429526] [-0.01424107 0.03737903] trying new point, [0.34096859 0.75429526] next() call None goals: [('reflect-at', 5, array([0.34096859, 0.75429526]), array([-0.01424107, 0.03737903]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.1121758213412904 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, -1, array([0.47222094, 0.507373 ]), array([-0.01950188, 0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.48421958508036966 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.12484009194327635 goals: [('bisect', 0, array([0.37471154, 0.68199235]), array([ 0.01950188, -0.03492387]), None, None, None, 4, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.47222094 0.507373 ] [-0.01950188 0.03492387] -0.1121758213412904 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.12484009194327632 goals: [('bisect', 0, array([0.47222094, 0.507373 ]), array([ 0.01950188, -0.03492387]), None, None, None, -1, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=30 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM -4 [0.59432576 0.53279516] [ 0.01245444 -0.03801167] -0.19005558113344231 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 1, array([0.65659798, 0.34273682]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.65659798 0.34273682] [ 0.01245444 -0.03801167] new direction: [-0.03320369 -0.02230504] reversing there [ 0.01245444 -0.03801167] making one step from [0.65659798 0.34273682] [ 0.01245444 -0.03801167] --> [0.62339429 0.32043178] [-0.03320369 -0.02230504] trying new point, [0.62339429 0.32043178] next() call None goals: [('reflect-at', 1, array([0.62339429, 0.32043178]), array([-0.03320369, -0.02230504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call -0.2319571892828859 goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -7 next() call -0.42459225549601265 goals: [('bisect', -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -5 -7 -9 continue bisect at -8 next() call None goals: [('bisect', -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -8, array([0.54450798, 0.68484182]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -7 -8 -9 bisecting gave reflection point -8 [0.54450798 0.68484182] [ 0.01245444 -0.03801167] new direction: [-0.01383172 -0.03753243] reversing there [ 0.01245444 -0.03801167] making one step from [0.54450798 0.68484182] [ 0.01245444 -0.03801167] --> [0.53067626 0.64730939] [0.01383172 0.03753243] trying new point, [0.53067626 0.64730939] next() call -0.4120593466482403 goals: [('reflect-at', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.2842013875070083 goals: [('bisect', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), None, None, None, -9, array([0.51684455, 0.60977695]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] bisecting ... -8 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.51684455 0.60977695] [0.01383172 0.03753243] -0.2842013875070083 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), None, None, None, -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 continue bisect at -1 next() call -0.4120593466482403 goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -1, array([0.53067626, 0.64730939]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -1 -2 bisecting gave reflection point -2 [0.54450798 0.68484182] [-0.01383172 -0.03753243] new direction: [ 0.01245444 -0.03801167] reversing there [-0.01383172 -0.03753243] making one step from [0.54450798 0.68484182] [-0.01383172 -0.03753243] --> [0.55696242 0.64683016] [-0.01245444 0.03801167] trying new point, [0.55696242 0.64683016] next() call -0.42459225549601265 goals: [('reflect-at', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.38522198158313203 goals: [('bisect', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), None, None, None, -9, array([0.64414354, 0.38074849]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] bisecting ... -2 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -15..0 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-15, 0) ---- seed=31 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 BACKWARD SAMPLING FROM 4 [0.20783379 0.63322006] [0.03312527 0.02242134] -0.24344226375583042 BACKWARD SAMPLING FROM -4 [0.05716835 0.45384931] [-0.03312527 0.02242134] -0.028257682631574084 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), None, None, None, 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33183373572512614 goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4338904075452583 goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 6, array([0.27408433, 0.67806275]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.30720959 0.7004841 ] [0.03312527 0.02242134] new direction: [0.01886481 0.03527207] reversing there [0.03312527 0.02242134] making one step from [0.30720959 0.7004841 ] [0.03312527 0.02242134] --> [0.32607441 0.73575617] [0.01886481 0.03527207] trying new point, [0.32607441 0.73575617] next() call None goals: [('reflect-at', 7, array([0.32607441, 0.73575617]), array([0.01886481, 0.03527207]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.17470852 0.61079872] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.27408433 0.67806275] [0.03312527 0.02242134] -0.4338904075452583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.026528374387011194 goals: [('bisect', 0, array([0.27408433, 0.67806275]), array([-0.03312527, -0.02242134]), None, None, None, 6, array([0.07533272, 0.54353469]), array([-0.03312527, -0.02242134]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=32 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 BACKWARD SAMPLING FROM 4 [0.57413119 0.44042355] [-0.00874449 -0.03903247] -0.20918022823021926 BACKWARD SAMPLING FROM -1 [0.61785366 0.63558591] [-0.00874449 -0.03903247] -0.42066580339605575 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), None, None, None, 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28137754791921 goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.39173967918225305 goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 6, array([0.5566422 , 0.36235861]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.54789771 0.32332614] [-0.00874449 -0.03903247] new direction: [-0.03993719 0.00224073] reversing there [-0.00874449 -0.03903247] making one step from [0.54789771 0.32332614] [-0.00874449 -0.03903247] --> [0.50796052 0.32556687] [-0.03993719 0.00224073] trying new point, [0.50796052 0.32556687] next() call None goals: [('reflect-at', 7, array([0.50796052, 0.32556687]), array([-0.03993719, 0.00224073]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.58287569 0.47945602] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.5566422 0.36235861] [-0.00874449 -0.03903247] -0.39173967918225305 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.3020390652147834 goals: [('bisect', 0, array([0.5566422 , 0.36235861]), array([0.00874449, 0.03903247]), None, None, None, 6, array([0.60910917, 0.59655344]), array([0.00874449, 0.03903247]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=33 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 BACKWARD SAMPLING FROM 4 [0.1119679 0.53337938] [-0.03413556 0.02085099] -0.020195695214487927 BACKWARD SAMPLING FROM -4 [0.38505235 0.36657146] [-0.03413556 0.02085099] -0.2966723492317622 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.31828011334541667 goals: [('bisect', 0, array([0.24851013, 0.44997542]), array([-0.03413556, 0.02085099]), None, None, None, 10, array([0.09284544, 0.65848532]), array([0.03413556, 0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.09284544 0.65848532] [0.03413556 0.02085099] -0.31828011334541667 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.062159372957623346 goals: [('bisect', 0, array([0.09284544, 0.65848532]), array([-0.03413556, -0.02085099]), None, None, None, 10, array([0.24851013, 0.44997542]), array([ 0.03413556, -0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=34 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 BACKWARD SAMPLING FROM 4 [0.00576602 0.5067828 ] [ 0.02461744 -0.03152747] -0.0005917034778301611 BACKWARD SAMPLING FROM -2 [0.14193864 0.69594763] [-0.02461744 -0.03152747] -0.49001670522119156 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.42756666673695237 goals: [('bisect', 0, array([0.09270376, 0.63289269]), array([-0.02461744, -0.03152747]), None, None, None, 10, array([0.15347069, 0.31761797]), array([ 0.02461744, -0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.15347069 0.31761797] [ 0.02461744 -0.03152747] -0.42756666673695237 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.22505281963979504 goals: [('bisect', 0, array([0.15347069, 0.31761797]), array([-0.02461744, 0.03152747]), None, None, None, 10, array([0.09270376, 0.63289269]), array([0.02461744, 0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=35 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 BACKWARD SAMPLING FROM 4 [0.12229223 0.6737271 ] [-0.00640292 0.03948421] -0.3847415272663998 BACKWARD SAMPLING FROM -4 [0.17351559 0.35785345] [-0.00640292 0.03948421] -0.26762436346562096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), None, None, None, 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12136585946729678 goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23354566196277238 goals: [('bisect', 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3847415272663993 goals: [('bisect', 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 4, array([0.12229223, 0.6737271 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.11588931 0.71321131] [-0.00640292 0.03948421] new direction: [-0.01879284 -0.03531047] reversing there [-0.00640292 0.03948421] making one step from [0.11588931 0.71321131] [-0.00640292 0.03948421] --> [0.09709647 0.67790084] [-0.01879284 -0.03531047] trying new point, [0.09709647 0.67790084] next() call -0.400322736376469 goals: [('reflect-at', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -2.7636297378795028e-05 goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), None, None, None, 10, array([0.00313227, 0.5013485 ]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00313227 0.5013485 ] [-0.01879284 -0.03531047] -2.7636297378795028e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), None, None, None, 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.400322736376469 goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 6, array([0.11588931, 0.71321131]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.11588931 0.71321131] [0.01879284 0.03531047] new direction: [ 0.00640292 -0.03948421] reversing there [0.01879284 0.03531047] making one step from [0.11588931 0.71321131] [0.01879284 0.03531047] --> [0.12229223 0.6737271 ] [ 0.00640292 -0.03948421] trying new point, [0.12229223 0.6737271 ] next() call -0.3847415272663989 goals: [('reflect-at', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.014054442900799765 goals: [('bisect', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), None, None, None, 10, array([0.14790391, 0.51579028]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=36 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 BACKWARD SAMPLING FROM 4 [0.7232834 0.53653594] [-0.02732618 -0.02921096] -0.27825536957064223 BACKWARD SAMPLING FROM -4 [0.57499771 0.55650503] [0.03837737 0.0112773 ] -0.20522140882168874 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), None, None, None, 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4533621249956772 goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 1, array([0.76688456, 0.61289151]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] new direction: [-0.02732618 -0.02921096] reversing there [0.03837737 0.0112773 ] making one step from [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] --> [0.77793575 0.59495785] [-0.02732618 -0.02921096] trying new point, [0.77793575 0.59495785] next() call -0.41530443247762705 goals: [('reflect-at', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3969974267345493 goals: [('bisect', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), None, None, None, 10, array([0.55932632, 0.3612702 ]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55932632 0.3612702 ] [-0.02732618 -0.02921096] -0.3969974267345493 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), None, None, None, 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.24284891598495364 goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33574054173486656 goals: [('bisect', 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4153044324776268 goals: [('bisect', 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 9, array([0.80526193, 0.6241688 ]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.80526193 0.6241688 ] [0.02732618 0.02921096] new direction: [-0.03837737 -0.0112773 ] reversing there [0.02732618 0.02921096] making one step from [0.80526193 0.6241688 ] [0.02732618 0.02921096] --> [0.76688456 0.61289151] [-0.03837737 -0.0112773 ] trying new point, [0.76688456 0.61289151] next() call -0.4533621249956771 goals: [('reflect-at', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39442946604858065 goals: [('bisect', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), None, None, None, 10, array([0.72850719, 0.60161421]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=37 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 BACKWARD SAMPLING FROM 4 [0.8979157 0.491777 ] [-0.03939692 0.00691971] -0.40397152289437405 BACKWARD SAMPLING FROM -4 [0.7869089 0.43641935] [0.03939692 0.00691971] -0.360144051361222 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23267087672305614 goals: [('bisect', 0, array([0.9444966 , 0.46409817]), array([0.03939692, 0.00691971]), None, None, None, 10, array([0.66153415, 0.53329524]), array([-0.03939692, 0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.66153415 0.53329524] [-0.03939692 0.00691971] -0.23267087672305614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4621486800079553 goals: [('bisect', 0, array([0.66153415, 0.53329524]), array([ 0.03939692, -0.00691971]), None, None, None, 10, array([0.9444966 , 0.46409817]), array([-0.03939692, -0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=38 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 BACKWARD SAMPLING FROM 4 [0.5006498 0.516994 ] [-0.03324607 -0.02224182] -0.12893506266001822 BACKWARD SAMPLING FROM -4 [0.65441475 0.53949241] [0.01523716 0.03698417] -0.23362496788797535 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21488037935387833 goals: [('bisect', 0, array([0.6336341 , 0.60596128]), array([-0.03324607, -0.02224182]), None, None, None, 10, array([0.30117336, 0.38354308]), array([-0.03324607, -0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30117336 0.38354308] [-0.03324607 -0.02224182] -0.21488037935387833 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.34109350056274995 goals: [('bisect', 0, array([0.30117336, 0.38354308]), array([0.03324607, 0.02224182]), None, None, None, 10, array([0.6336341 , 0.60596128]), array([0.03324607, 0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 sampling between (-7, 0) ---- seed=39 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 BACKWARD SAMPLING FROM 4 [0.76168405 0.53559656] [0.03992051 0.00252049] -0.3059202287204628 BACKWARD SAMPLING FROM -4 [0.44231997 0.51543261] [0.03992051 0.00252049] -0.10080054489174596 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), None, None, None, 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33944630091534117 goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.41175585311595747 goals: [('bisect', 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4505393331216953 goals: [('bisect', 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4910752823977196 goals: [('bisect', 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 9, array([0.9612866 , 0.54819902]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.99879289 0.55071952] [-0.03992051 0.00252049] new direction: [0.03741642 0.01414255] reversing there [-0.03992051 0.00252049] making one step from [0.99879289 0.55071952] [-0.03992051 0.00252049] --> [0.96379069 0.56486207] [-0.03741642 0.01414255] trying new point, [0.96379069 0.56486207] next() call None goals: [('reflect-at', 10, array([0.96379069, 0.56486207]), array([-0.03741642, 0.01414255]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.9612866 0.54819902] [0.03992051 0.00252049] -0.4910752823977196 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.1893406326438129 goals: [('bisect', 0, array([0.9612866 , 0.54819902]), array([-0.03992051, -0.00252049]), None, None, None, 9, array([0.60200201, 0.52551458]), array([-0.03992051, -0.00252049]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=40 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 BACKWARD SAMPLING FROM 4 [0.50385595 0.57055786] [ 0.00847644 -0.03909156] -0.18916555089029924 BACKWARD SAMPLING FROM -4 [0.6223453 0.49577156] [-0.02398644 0.03201016] -0.19388033318836445 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), None, None, None, 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.42971710884526637 goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 1, array([0.50241308, 0.65582238]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.47842664 0.68783254] [-0.02398644 0.03201016] new direction: [ 0.00847644 -0.03909156] reversing there [-0.02398644 0.03201016] making one step from [0.47842664 0.68783254] [-0.02398644 0.03201016] --> [0.48690307 0.64874098] [ 0.00847644 -0.03909156] trying new point, [0.48690307 0.64874098] next() call -0.39508578257867283 goals: [('reflect-at', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.490019265835001 goals: [('bisect', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), None, None, None, 10, array([0.55471457, 0.3360085 ]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55471457 0.3360085 ] [ 0.00847644 -0.03909156] -0.490019265835001 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), None, None, None, 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14361883567172593 goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2729878665259479 goals: [('bisect', 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3950857825786728 goals: [('bisect', 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 9, array([0.47842664, 0.68783254]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.47842664 0.68783254] [-0.00847644 0.03909156] new direction: [ 0.02398644 -0.03201016] reversing there [-0.00847644 0.03909156] making one step from [0.47842664 0.68783254] [-0.00847644 0.03909156] --> [0.50241308 0.65582238] [ 0.02398644 -0.03201016] trying new point, [0.50241308 0.65582238] next() call -0.42971710884526587 goals: [('reflect-at', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3301665303326673 goals: [('bisect', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), None, None, None, 10, array([0.52639952, 0.62381221]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=41 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 BACKWARD SAMPLING FROM -4 [0.22513362 0.48646827] [-0.02717748 0.02934935] -0.027631419475083484 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.33226605088879657 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4609947924113364 goals: [('bisect', 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 4, array([0.00771378, 0.7212631 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.00771378 0.7212631 ] [-0.02717748 0.02934935] new direction: [ 0.03817639 -0.01193998] reversing there [-0.02717748 0.02934935] making one step from [0.00771378 0.7212631 ] [-0.02717748 0.02934935] --> [0.04589017 0.70932312] [ 0.03817639 -0.01193998] trying new point, [0.04589017 0.70932312] next() call None goals: [('reflect-at', 4, array([0.04589017, 0.70932312]), array([ 0.03817639, -0.01193998]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.022720784505758807 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, -3, array([0.19795614, 0.51581763]), array([-0.02717748, 0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.03489126, 0.69191375]), array([ 0.02717748, -0.02934935]), None, None, None, 3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.19795614 0.51581763] [-0.02717748 0.02934935] -0.022720784505758807 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.19795614, 0.51581763]), array([ 0.02717748, -0.02934935]), None, None, None, -3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=42 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 BACKWARD SAMPLING FROM 4 [0.60933098 0.49592681] [-0.03066574 -0.02568292] -0.18584950597376992 BACKWARD SAMPLING FROM -4 [0.77492096 0.53144407] [0.00613482 0.03952675] -0.31261037020419746 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4031802276107923 goals: [('bisect', 0, array([0.73199394, 0.59865848]), array([-0.03066574, -0.02568292]), None, None, None, 10, array([0.42533653, 0.3418293 ]), array([-0.03066574, -0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.42533653 0.3418293 ] [-0.03066574 -0.02568292] -0.4031802276107923 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38957627172501086 goals: [('bisect', 0, array([0.42533653, 0.3418293 ]), array([0.03066574, 0.02568292]), None, None, None, 10, array([0.73199394, 0.59865848]), array([0.03066574, 0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=43 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 BACKWARD SAMPLING FROM 4 [0.25118164 0.52498669] [ 0.03403177 -0.02101996] -0.039350293891790226 BACKWARD SAMPLING FROM -4 [0.02107251 0.69314638] [-0.03403177 -0.02101996] -0.4665410967293263 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23153067175015277 goals: [('bisect', 0, array([0.11505457, 0.60906654]), array([ 0.03403177, -0.02101996]), None, None, None, 10, array([0.45537225, 0.39886693]), array([ 0.03403177, -0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.45537225 0.39886693] [ 0.03403177 -0.02101996] -0.23153067175015277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.15531265150360327 goals: [('bisect', 0, array([0.45537225, 0.39886693]), array([-0.03403177, 0.02101996]), None, None, None, 10, array([0.11505457, 0.60906654]), array([-0.03403177, 0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=44 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 BACKWARD SAMPLING FROM 4 [0.47062097 0.66599703] [-0.02002389 -0.03462721] -0.4551797092301754 BACKWARD SAMPLING FROM -4 [0.22797682 0.51785252] [0.03283351 0.02284646] -0.02997062159932815 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), None, None, None, 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.39034946973740525 goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.49985733022926904 goals: [('bisect', 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 4, array([0.49064486, 0.70062424]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.49064486 0.70062424] [0.03283351 0.02284646] new direction: [-0.02002389 -0.03462721] reversing there [0.03283351 0.02284646] making one step from [0.49064486 0.70062424] [0.03283351 0.02284646] --> [0.47062097 0.66599703] [-0.02002389 -0.03462721] trying new point, [0.47062097 0.66599703] next() call -0.455179709230175 goals: [('reflect-at', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08322252232880438 goals: [('bisect', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), None, None, None, 10, array([0.35047762, 0.45823376]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.35047762 0.45823376] [-0.02002389 -0.03462721] -0.08322252232880438 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), None, None, None, 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3172442164483675 goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.455179709230175 goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 6, array([0.47062097, 0.66599703]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.49064486 0.70062424] [0.02002389 0.03462721] new direction: [-0.03283351 -0.02284646] reversing there [0.02002389 0.03462721] making one step from [0.49064486 0.70062424] [0.02002389 0.03462721] --> [0.45781135 0.67777777] [-0.03283351 -0.02284646] trying new point, [0.45781135 0.67777777] next() call -0.49985733022926904 goals: [('reflect-at', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21371493658412127 goals: [('bisect', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), None, None, None, 10, array([0.35931084, 0.60923838]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=45 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036039 BACKWARD SAMPLING FROM -4 [0.34228361 0.59592598] [ 0.02554647 -0.0307795 ] -0.1736014655895373 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.22125039734136934 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.31437162423426 goals: [('bisect', 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4318299192036037 goals: [('bisect', 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 4, array([0.54665538, 0.34968996]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] new direction: [-0.03976603 -0.00432004] reversing there [ 0.02554647 -0.0307795 ] making one step from [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] --> [0.53243582 0.31459041] [-0.03976603 -0.00432004] trying new point, [0.53243582 0.31459041] next() call None goals: [('reflect-at', 5, array([0.53243582, 0.31459041]), array([-0.03976603, -0.00432004]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.087909125121415 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, -1, array([0.41892303, 0.50358747]), array([ 0.02554647, -0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036037 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.10801914778494678 goals: [('bisect', 0, array([0.54665538, 0.34968996]), array([-0.02554647, 0.0307795 ]), None, None, None, 4, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.41892303 0.50358747] [ 0.02554647 -0.0307795 ] -0.087909125121415 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.10801914778494684 goals: [('bisect', 0, array([0.41892303, 0.50358747]), array([-0.02554647, 0.0307795 ]), None, None, None, -1, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=46 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 BACKWARD SAMPLING FROM 4 [0.15144064 0.55838923] [0.0271438 0.02938051] -0.05408341768692817 BACKWARD SAMPLING FROM -4 [0.06570974 0.32334517] [-0.0271438 0.02938051] -0.3922454873386127 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), None, None, None, 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.11224029674516076 goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2955054800380875 goals: [('bisect', 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4206137842727819 goals: [('bisect', 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 9, array([0.28715963, 0.70529177]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.28715963 0.70529177] [0.0271438 0.02938051] new direction: [ 0.02281179 -0.03285761] reversing there [0.0271438 0.02938051] making one step from [0.28715963 0.70529177] [0.0271438 0.02938051] --> [0.30997142 0.67243417] [ 0.02281179 -0.03285761] trying new point, [0.30997142 0.67243417] next() call -0.41971042152871735 goals: [('reflect-at', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2988925458881023 goals: [('bisect', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), None, None, None, 10, array([0.33278321, 0.63957656]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.33278321 0.63957656] [ 0.02281179 -0.03285761] -0.2988925458881023 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), None, None, None, 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.41971042152871735 goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 1, array([0.30997142, 0.67243417]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.28715963 0.70529177] [-0.02281179 0.03285761] new direction: [-0.0271438 -0.02938051] reversing there [-0.02281179 0.03285761] making one step from [0.28715963 0.70529177] [-0.02281179 0.03285761] --> [0.26001583 0.67591127] [-0.0271438 -0.02938051] trying new point, [0.26001583 0.67591127] next() call -0.4206137842727819 goals: [('reflect-at', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04462731870887185 goals: [('bisect', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), None, None, None, 10, array([0.04286545, 0.4408672 ]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=47 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 BACKWARD SAMPLING FROM 4 [0.56078481 0.55029357] [-0.02119426 0.03392349] -0.18885784622089788 BACKWARD SAMPLING FROM -1 [0.66675612 0.38067612] [-0.02119426 0.03392349] -0.40025922669221325 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), None, None, None, 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23423540704363024 goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4126483656060907 goals: [('bisect', 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 8, array([0.47600776, 0.68598754]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.47600776 0.68598754] [-0.02119426 0.03392349] new direction: [-0.02911927 -0.02742386] reversing there [-0.02119426 0.03392349] making one step from [0.47600776 0.68598754] [-0.02119426 0.03392349] --> [0.44688849 0.65856368] [-0.02911927 -0.02742386] trying new point, [0.44688849 0.65856368] next() call -0.4141351863645779 goals: [('reflect-at', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20998692233081806 goals: [('bisect', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), None, None, None, 10, array([0.38864994, 0.60371597]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.38864994 0.60371597] [-0.02911927 -0.02742386] -0.20998692233081806 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), None, None, None, 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4141351863645779 goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 3, array([0.47600776, 0.68598754]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.47600776 0.68598754] [0.02911927 0.02742386] new direction: [ 0.02119426 -0.03392349] reversing there [0.02911927 0.02742386] making one step from [0.47600776 0.68598754] [0.02911927 0.02742386] --> [0.49720203 0.65206405] [ 0.02119426 -0.03392349] trying new point, [0.49720203 0.65206405] next() call -0.4126483656060907 goals: [('reflect-at', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2995403926532866 goals: [('bisect', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), None, None, None, 10, array([0.64556185, 0.41459961]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=48 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 BACKWARD SAMPLING FROM 4 [0.70528601 0.43395284] [-0.03985609 -0.00338995] -0.3032420227989266 BACKWARD SAMPLING FROM -4 [0.90468504 0.44962923] [0.03979681 0.00402662] -0.44094269508821465 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20193125737173862 goals: [('bisect', 0, array([0.86471039, 0.44751263]), array([-0.03985609, -0.00338995]), None, None, None, 10, array([0.46614944, 0.41361315]), array([-0.03985609, -0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.46614944 0.41361315] [-0.03985609 -0.00338995] -0.20193125737173862 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.40829857363895855 goals: [('bisect', 0, array([0.46614944, 0.41361315]), array([0.03985609, 0.00338995]), None, None, None, 10, array([0.86471039, 0.44751263]), array([0.03985609, 0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 sampling between (-6, 1) ---- seed=49 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 BACKWARD SAMPLING FROM 4 [0.69043306 0.40704478] [ 0.00178908 -0.03995997] -0.3463573209308397 BACKWARD SAMPLING FROM -4 [0.55985875 0.65300213] [ 0.03994662 -0.00206584] -0.44934157693712723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), None, None, None, 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4604163445319175 goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 6, array([0.69401122, 0.32712484]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.69401122 0.32712484] [ 0.00178908 -0.03995997] new direction: [-0.03993708 -0.00224268] reversing there [ 0.00178908 -0.03995997] making one step from [0.69401122 0.32712484] [ 0.00178908 -0.03995997] --> [0.65407414 0.32488216] [-0.03993708 -0.00224268] trying new point, [0.65407414 0.32488216] next() call None goals: [('reflect-at', 6, array([0.65407414, 0.32488216]), array([-0.03993708, -0.00224268]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.68506584 0.52692469] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.69222214 0.36708481] [ 0.00178908 -0.03995997] -0.4604163445319175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2893530363157967 goals: [('bisect', 0, array([0.69222214, 0.36708481]), array([-0.00178908, 0.03995997]), None, None, None, 5, array([0.68327676, 0.56688466]), array([-0.00178908, 0.03995997]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -10..5 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-10, 5) ---- seed=50 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 BACKWARD SAMPLING FROM 4 [0.13808816 0.33647507] [0.00832488 0.03912411] -0.3437892113032023 BACKWARD SAMPLING FROM -4 [0.38118457 0.49530887] [-0.03142766 -0.02474474] -0.07292592188692902 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), None, None, None, 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31177413021896305 goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4086155422937598 goals: [('bisect', 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 4, array([0.12976328, 0.29735095]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.12976328 0.29735095] [-0.03142766 -0.02474474] new direction: [0.00832488 0.03912411] reversing there [-0.03142766 -0.02474474] making one step from [0.12976328 0.29735095] [-0.03142766 -0.02474474] --> [0.13808816 0.33647507] [0.00832488 0.03912411] trying new point, [0.13808816 0.33647507] next() call -0.3437892113032023 goals: [('reflect-at', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08108221261480617 goals: [('bisect', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), None, None, None, 10, array([0.18803745, 0.57121976]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18803745 0.57121976] [0.00832488 0.03912411] -0.08108221261480617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), None, None, None, 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.20416293012453088 goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3437892113032023 goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 6, array([0.13808816, 0.33647507]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.12976328 0.29735095] [-0.00832488 -0.03912411] new direction: [0.03142766 0.02474474] reversing there [-0.00832488 -0.03912411] making one step from [0.12976328 0.29735095] [-0.00832488 -0.03912411] --> [0.16119094 0.32209569] [0.03142766 0.02474474] trying new point, [0.16119094 0.32209569] next() call -0.4086155422937598 goals: [('reflect-at', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16697705808604757 goals: [('bisect', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), None, None, None, 10, array([0.25547392, 0.39632991]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=51 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 BACKWARD SAMPLING FROM -4 [0.40032887 0.49452683] [-0.0142563 0.03737322] -0.08050604831793806 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4654286221899625 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 1, array([0.32904737, 0.68139295]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.31479107 0.71876618] [-0.0142563 0.03737322] new direction: [-0.039365 -0.00709908] reversing there [-0.0142563 0.03737322] making one step from [0.31479107 0.71876618] [-0.0142563 0.03737322] --> [0.27542607 0.7116671 ] [-0.039365 -0.00709908] trying new point, [0.27542607 0.7116671 ] next() call None goals: [('reflect-at', 2, array([0.27542607, 0.7116671 ]), array([-0.039365 , -0.00709908]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.27101878092937887 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, -7, array([0.44309777, 0.38240716]), array([-0.0142563 , 0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.32904737, 0.68139295]), array([ 0.0142563 , -0.03737322]), None, None, None, 1, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.44309777 0.38240716] [-0.0142563 0.03737322] -0.27101878092937887 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.44309777, 0.38240716]), array([ 0.0142563 , -0.03737322]), None, None, None, -7, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=52 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 BACKWARD SAMPLING FROM 4 [0.36003865 0.56081047] [ 0.037317 -0.01440282] -0.11103783451846358 BACKWARD SAMPLING FROM -4 [0.06150263 0.67603307] [ 0.037317 -0.01440282] -0.3892367900814762 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17868949115336583 goals: [('bisect', 0, array([0.21077064, 0.61842177]), array([ 0.037317 , -0.01440282]), None, None, None, 10, array([0.58394066, 0.47439353]), array([ 0.037317 , -0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.58394066 0.47439353] [ 0.037317 -0.01440282] -0.17868949115336583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19750857452717718 goals: [('bisect', 0, array([0.58394066, 0.47439353]), array([-0.037317 , 0.01440282]), None, None, None, 10, array([0.21077064, 0.61842177]), array([-0.037317 , 0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=53 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 BACKWARD SAMPLING FROM 4 [0.72477641 0.45751322] [-0.0304715 -0.02591308] -0.28521449853834674 BACKWARD SAMPLING FROM -1 [0.87713391 0.58707862] [-0.0304715 -0.02591308] -0.4794655207604886 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), None, None, None, 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2995114075574864 goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.38125233905933353 goals: [('bisect', 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4486963615420411 goals: [('bisect', 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 9, array([0.57241891, 0.32794783]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.57241891 0.32794783] [-0.0304715 -0.02591308] new direction: [-0.00163041 -0.03996676] reversing there [-0.0304715 -0.02591308] making one step from [0.57241891 0.32794783] [-0.0304715 -0.02591308] --> [0.5707885 0.28798107] [-0.00163041 -0.03996676] trying new point, [0.5707885 0.28798107] next() call None goals: [('reflect-at', 9, array([0.5707885 , 0.28798107]), array([-0.00163041, -0.03996676]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.60289041 0.3538609 ] [-0.0304715 -0.02591308] -0.4486963615420411 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.40518390734034826 goals: [('bisect', 0, array([0.60289041, 0.3538609 ]), array([0.0304715 , 0.02591308]), None, None, None, 8, array([0.84666241, 0.56116554]), array([0.0304715 , 0.02591308]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=54 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 BACKWARD SAMPLING FROM 4 [0.29205086 0.4590631 ] [-0.03203303 0.0239559 ] -0.06359472404742703 BACKWARD SAMPLING FROM -1 [0.45221599 0.3392836 ] [-0.03203303 0.0239559 ] -0.4251216837222281 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13707944044464876 goals: [('bisect', 0, array([0.42018297, 0.3632395 ]), array([-0.03203303, 0.0239559 ]), None, None, None, 10, array([0.0998527 , 0.60279851]), array([-0.03203303, 0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0998527 0.60279851] [-0.03203303 0.0239559 ] -0.13707944044464876 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.32206980281714764 goals: [('bisect', 0, array([0.0998527 , 0.60279851]), array([ 0.03203303, -0.0239559 ]), None, None, None, 10, array([0.42018297, 0.3632395 ]), array([ 0.03203303, -0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=55 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 BACKWARD SAMPLING FROM 4 [0.06288283 0.47543852] [ 0.01800544 -0.0357184 ] -0.00951795620141871 BACKWARD SAMPLING FROM -2 [0.04514983 0.68974891] [-0.01800544 -0.0357184 ] -0.45107737484070604 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), None, None, None, 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.04869226052335881 goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2236987612488 goals: [('bisect', 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3595309576523012 goals: [('bisect', 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 9, array([0.15291004, 0.29684652]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] new direction: [-0.03842475 0.01111479] reversing there [ 0.01800544 -0.0357184 ] making one step from [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] --> [0.11448528 0.30796131] [-0.03842475 0.01111479] trying new point, [0.11448528 0.30796131] next() call -0.46753918956341406 goals: [('reflect-at', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41206085167620243 goals: [('bisect', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), None, None, None, 10, array([0.07606053, 0.31907609]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.07606053 0.31907609] [-0.03842475 0.01111479] -0.41206085167620243 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), None, None, None, 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.46753918956341406 goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 1, array([0.11448528, 0.30796131]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15291004 0.29684652] [ 0.03842475 -0.01111479] new direction: [-0.01800544 0.0357184 ] reversing there [ 0.03842475 -0.01111479] making one step from [0.15291004 0.29684652] [ 0.03842475 -0.01111479] --> [0.13490459 0.33256492] [-0.01800544 0.0357184 ] trying new point, [0.13490459 0.33256492] next() call -0.3595309576523012 goals: [('reflect-at', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17501371251886214 goals: [('bisect', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), None, None, None, 10, array([0.00913894, 0.61831211]), array([0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=56 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 BACKWARD SAMPLING FROM 4 [0.39113326 0.5298137 ] [0.03582093 0.01780059] -0.08760332684710367 BACKWARD SAMPLING FROM -4 [0.10456585 0.38740895] [0.03582093 0.01780059] -0.16392632784250208 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41695714617072094 goals: [('bisect', 0, array([0.24784955, 0.45861133]), array([0.03582093, 0.01780059]), None, None, None, 10, array([0.60605882, 0.63661727]), array([0.03582093, 0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.60605882 0.63661727] [0.03582093 0.01780059] -0.41695714617072094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05212748066477112 goals: [('bisect', 0, array([0.60605882, 0.63661727]), array([-0.03582093, -0.01780059]), None, None, None, 10, array([0.24784955, 0.45861133]), array([-0.03582093, -0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -5..10 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd new NUTS range: -5..26 NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd sampling between (-5, 26) ---- seed=57 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520403 BACKWARD SAMPLING FROM -4 [0.59526516 0.38777109] [-0.00732732 0.03932315] -0.3346119116596618 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.34326862471080793 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4802014861520402 goals: [('bisect', 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 4, array([0.53664662, 0.70235632]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.53664662 0.70235632] [-0.00732732 0.03932315] new direction: [-0.03991081 -0.00266972] reversing there [-0.00732732 0.03932315] making one step from [0.53664662 0.70235632] [-0.00732732 0.03932315] --> [0.49673582 0.69968659] [-0.03991081 -0.00266972] trying new point, [0.49673582 0.69968659] next() call None goals: [('reflect-at', 4, array([0.49673582, 0.69968659]), array([-0.03991081, -0.00266972]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.23927607150196617 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, -3, array([0.58793784, 0.42709424]), array([-0.00732732, 0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.54397394, 0.66303317]), array([ 0.00732732, -0.03932315]), None, None, None, 3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.58793784 0.42709424] [-0.00732732 0.03932315] -0.23927607150196617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.58793784, 0.42709424]), array([ 0.00732732, -0.03932315]), None, None, None, -3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=58 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 BACKWARD SAMPLING FROM 4 [0.52440832 0.43628484] [ 0.03982568 -0.00373027] -0.18824731253691152 BACKWARD SAMPLING FROM -4 [0.20580285 0.46612699] [ 0.03982568 -0.00373027] -0.03551966453010344 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3840192746128853 goals: [('bisect', 0, array([0.36510558, 0.45120592]), array([ 0.03982568, -0.00373027]), None, None, None, 10, array([0.76336242, 0.41390323]), array([ 0.03982568, -0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76336242 0.41390323] [ 0.03982568 -0.00373027] -0.3840192746128853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09641182642477081 goals: [('bisect', 0, array([0.76336242, 0.41390323]), array([-0.03982568, 0.00373027]), None, None, None, 10, array([0.36510558, 0.45120592]), array([-0.03982568, 0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=59 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 BACKWARD SAMPLING FROM 4 [0.4021635 0.49826765] [ 0.03647074 -0.01642819] -0.08090525343003006 BACKWARD SAMPLING FROM -4 [0.11039762 0.62969317] [ 0.03647074 -0.01642819] -0.2163478092623813 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.318567864176321 goals: [('bisect', 0, array([0.25628056, 0.56398041]), array([ 0.03647074, -0.01642819]), None, None, None, 10, array([0.62098791, 0.39969851]), array([ 0.03647074, -0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.62098791 0.39969851] [ 0.03647074 -0.01642819] -0.318567864176321 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08400852608514758 goals: [('bisect', 0, array([0.62098791, 0.39969851]), array([-0.03647074, 0.01642819]), None, None, None, 10, array([0.25628056, 0.56398041]), array([-0.03647074, 0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=60 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 BACKWARD SAMPLING FROM 4 [0.48306538 0.65962424] [ 0.03997068 -0.00153133] -0.43517479808588755 BACKWARD SAMPLING FROM -4 [0.16329997 0.6718749 ] [ 0.03997068 -0.00153133] -0.3825957187127649 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), None, None, None, 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.44920044099302747 goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.482220565464306 goals: [('bisect', 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 8, array([0.64294809, 0.6534989 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] new direction: [0.0021526 0.03994204] reversing there [ 0.03997068 -0.00153133] making one step from [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] --> [0.64510069 0.69344094] [0.0021526 0.03994204] trying new point, [0.64510069 0.69344094] next() call None goals: [('reflect-at', 8, array([0.64510069, 0.69344094]), array([0.0021526 , 0.03994204]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.60297742 0.65503024] [ 0.03997068 -0.00153133] -0.482220565464306 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.39563502198066103 goals: [('bisect', 0, array([0.60297742, 0.65503024]), array([-0.03997068, 0.00153133]), None, None, None, 7, array([0.32318268, 0.66574957]), array([-0.03997068, 0.00153133]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=61 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 BACKWARD SAMPLING FROM 4 [0.72389146 0.54491217] [-0.03835883 0.01134021] -0.28722320791367995 BACKWARD SAMPLING FROM -4 [0.91257131 0.47071355] [ 0.03991597 -0.00259145] -0.4271143991277972 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2813698847877405 goals: [('bisect', 0, array([0.87732677, 0.49955131]), array([-0.03835883, 0.01134021]), None, None, None, 10, array([0.49373851, 0.61295345]), array([-0.03835883, 0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.49373851 0.61295345] [-0.03835883 0.01134021] -0.2813698847877405 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38485364567003044 goals: [('bisect', 0, array([0.49373851, 0.61295345]), array([ 0.03835883, -0.01134021]), None, None, None, 10, array([0.87732677, 0.49955131]), array([ 0.03835883, -0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=62 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 BACKWARD SAMPLING FROM -4 [0.05117488 0.64815636] [-0.00435504 -0.03976221] -0.2756882768233669 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10250385662007835 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.21204660991891755 goals: [('bisect', 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3611341698842485 goals: [('bisect', 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 4, array([0.01633454, 0.33005865]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.0119795 0.29029644] [-0.00435504 -0.03976221] new direction: [ 0.03630756 -0.01678574] reversing there [-0.00435504 -0.03976221] making one step from [0.0119795 0.29029644] [-0.00435504 -0.03976221] --> [0.04828706 0.2735107 ] [ 0.03630756 -0.01678574] trying new point, [0.04828706 0.2735107 ] next() call None goals: [('reflect-at', 5, array([0.04828706, 0.2735107 ]), array([ 0.03630756, -0.01678574]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.011144436722510533 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, -1, array([0.03810975, 0.52886972]), array([-0.00435504, -0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.0020527700218748433 goals: [('bisect', 0, array([0.01633454, 0.33005865]), array([0.00435504, 0.03976221]), None, None, None, 4, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.03810975 0.52886972] [-0.00435504 -0.03976221] -0.011144436722510533 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0020527700218748585 goals: [('bisect', 0, array([0.03810975, 0.52886972]), array([0.00435504, 0.03976221]), None, None, None, -1, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=63 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 BACKWARD SAMPLING FROM 4 [0.4072226 0.46007348] [-0.03667961 0.0159564 ] -0.10284171548913772 BACKWARD SAMPLING FROM -4 [0.586297 0.36749354] [ 0.03884142 -0.00955742] -0.3913466099390096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05644864986759578 goals: [('bisect', 0, array([0.55394102, 0.39624789]), array([-0.03667961, 0.0159564 ]), None, None, None, 10, array([0.18714497, 0.55581185]), array([-0.03667961, 0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18714497 0.55581185] [-0.03667961 0.0159564 ] -0.05644864986759578 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2879815727116586 goals: [('bisect', 0, array([0.18714497, 0.55581185]), array([ 0.03667961, -0.0159564 ]), None, None, None, 10, array([0.55394102, 0.39624789]), array([ 0.03667961, -0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=64 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 BACKWARD SAMPLING FROM 4 [0.39993594 0.60551572] [ 0.00067241 -0.03999435] -0.21914395901276984 BACKWARD SAMPLING FROM -4 [0.35310841 0.40922317] [0.00649753 0.03946875] -0.16534817926836115 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), None, None, None, 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.343448880085709 goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 3, array([0.39859111, 0.68550441]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.39859111 0.68550441] [0.00649753 0.03946875] new direction: [ 0.00067241 -0.03999435] reversing there [0.00649753 0.03946875] making one step from [0.39859111 0.68550441] [0.00649753 0.03946875] --> [0.39926352 0.64551007] [ 0.00067241 -0.03999435] trying new point, [0.39926352 0.64551007] next() call -0.3443704192313505 goals: [('reflect-at', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.30755732018362913 goals: [('bisect', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), None, None, None, 10, array([0.40397041, 0.36554963]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.40397041 0.36554963] [ 0.00067241 -0.03999435] -0.30755732018362913 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), None, None, None, 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.13390664748382503 goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3443704192313509 goals: [('bisect', 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 8, array([0.39859111, 0.68550441]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.39859111 0.68550441] [-0.00067241 0.03999435] new direction: [-0.00649753 -0.03946875] reversing there [-0.00067241 0.03999435] making one step from [0.39859111 0.68550441] [-0.00067241 0.03999435] --> [0.39209358 0.64603566] [-0.00649753 -0.03946875] trying new point, [0.39209358 0.64603566] next() call -0.3434488800857094 goals: [('reflect-at', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12813489647882276 goals: [('bisect', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), None, None, None, 10, array([0.37909853, 0.56709817]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=65 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 BACKWARD SAMPLING FROM 4 [0.1092311 0.61062131] [-0.03020213 0.02622654] -0.1589291517496356 BACKWARD SAMPLING FROM -4 [0.35084815 0.40080902] [-0.03020213 0.02622654] -0.18453284519551352 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), None, None, None, 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23721446196834403 goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44810893033872173 goals: [('bisect', 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 8, array([0.01157743, 0.71552746]), array([0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.01157743 0.71552746] [0.03020213 0.02622654] new direction: [0.03498847 0.01938573] reversing there [0.03020213 0.02622654] making one step from [0.01157743 0.71552746] [0.03020213 0.02622654] --> [0.0465659 0.73491319] [0.03498847 0.01938573] trying new point, [0.0465659 0.73491319] next() call None goals: [('reflect-at', 8, array([0.0465659 , 0.73491319]), array([0.03498847, 0.01938573]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.0186247 0.68930092] [-0.03020213 0.02622654] -0.44810893033872173 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.026867403984676807 goals: [('bisect', 0, array([0.0186247 , 0.68930092]), array([ 0.03020213, -0.02622654]), None, None, None, 7, array([0.23003963, 0.50571517]), array([ 0.03020213, -0.02622654]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=66 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BACKWARD SAMPLING FROM 4 [0.43880939 0.53837811] [ 0.01903098 -0.03518269] -0.1146878297183696 BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), None, None, None, 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.10493653469527497 goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.17935711354999778 goals: [('bisect', 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2635289874278154 goals: [('bisect', 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.37900858427260387 goals: [('bisect', 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 9, array([0.53396429, 0.36246465]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.55299527 0.32728196] [ 0.01903098 -0.03518269] new direction: [-0.03590325 0.01763396] reversing there [ 0.01903098 -0.03518269] making one step from [0.55299527 0.32728196] [ 0.01903098 -0.03518269] --> [0.51709202 0.34491592] [-0.03590325 0.01763396] trying new point, [0.51709202 0.34491592] next() call -0.4343304840564407 goals: [('reflect-at', 10, array([0.51709202, 0.34491592]), array([-0.03590325, 0.01763396]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.51709202 0.34491592] [-0.03590325 0.01763396] -0.4343304840564407 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), None, None, None, 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 1, array([0.55299527, 0.32728196]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.55299527 0.32728196] [ 0.03590325 -0.01763396] new direction: [-0.01903098 0.03518269] reversing there [ 0.03590325 -0.01763396] making one step from [0.55299527 0.32728196] [ 0.03590325 -0.01763396] --> [0.53396429 0.36246465] [-0.01903098 0.03518269] trying new point, [0.53396429 0.36246465] next() call -0.379008584272604 goals: [('reflect-at', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.46677023948045687 goals: [('bisect', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), None, None, None, 10, array([0.36268547, 0.67910888]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=67 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 BACKWARD SAMPLING FROM 4 [0.08924898 0.33300678] [0.01670024 0.03634697] -0.3525668892829215 BACKWARD SAMPLING FROM -4 [0.1925446 0.47589575] [-0.03313667 -0.02240449] -0.025799396299807646 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), None, None, None, 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31417147356422026 goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4099982344835686 goals: [('bisect', 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 4, array([0.07254874, 0.29665981]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.07254874 0.29665981] [ 0.03313667 -0.02240449] new direction: [0.01670024 0.03634697] reversing there [ 0.03313667 -0.02240449] making one step from [0.07254874 0.29665981] [ 0.03313667 -0.02240449] --> [0.08924898 0.33300678] [0.01670024 0.03634697] trying new point, [0.08924898 0.33300678] next() call -0.3525668892829215 goals: [('reflect-at', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05057127231465654 goals: [('bisect', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), None, None, None, 10, array([0.1894504 , 0.55108859]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.1894504 0.55108859] [0.01670024 0.03634697] -0.05057127231465654 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), None, None, None, 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.218968162054107 goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3525668892829218 goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 6, array([0.08924898, 0.33300678]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.07254874 0.29665981] [-0.01670024 -0.03634697] new direction: [-0.03313667 0.02240449] reversing there [-0.01670024 -0.03634697] making one step from [0.07254874 0.29665981] [-0.01670024 -0.03634697] --> [0.03941207 0.3190643 ] [-0.03313667 0.02240449] trying new point, [0.03941207 0.3190643 ] next() call -0.4099982344835688 goals: [('reflect-at', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16345916433290641 goals: [('bisect', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), None, None, None, 10, array([0.05999793, 0.38627778]), array([0.03313667, 0.02240449]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=68 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592275 BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4554553560620388 goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48725395469592286 goals: [('bisect', 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 4, array([0.90228929, 0.39247251]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.90228929 0.39247251] [-0.0176335 -0.03590348] new direction: [-0.0084219 -0.03910335] reversing there [-0.0176335 -0.03590348] making one step from [0.90228929 0.39247251] [-0.0176335 -0.03590348] --> [0.8938674 0.35336917] [-0.0084219 -0.03910335] trying new point, [0.8938674 0.35336917] next() call None goals: [('reflect-at', 4, array([0.8938674 , 0.35336917]), array([-0.0084219 , -0.03910335]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 None -3 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -2 -3 continue bisect at -1 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -1, array([0.99045679, 0.5719899 ]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -1 -2 bisecting gave reflection point -1 [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] new direction: [-0.03469108 0.01991304] reversing there [-0.0176335 -0.03590348] making one step from [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] --> [0.95576572 0.59190294] [ 0.03469108 -0.01991304] trying new point, [0.95576572 0.59190294] next() call None goals: [('reflect-at', -1, array([0.95576572, 0.59190294]), array([ 0.03469108, -0.01991304]), -1), ('sample-at', -3)] goals: [('sample-at', -3)] reversing at 0... -3 steps to do at 0 -> [from -1, delta=-3] targeting 2. goals: [('sample-at', 2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.4894704551842364 goals: [('bisect', 0, array([0.91992279, 0.42837599]), array([0.0176335 , 0.03590348]), None, None, None, 3, array([0.97282329, 0.53608642]), array([0.0176335 , 0.03590348]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=69 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 BACKWARD SAMPLING FROM 4 [0.08314008 0.33011112] [0.0398791 0.00310763] -0.3642340475299841 BACKWARD SAMPLING FROM -4 [0.23379485 0.34519503] [ 0.00209787 -0.03994495] -0.32688726566612836 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3379065727944484 goals: [('bisect', 0, array([0.07637632, 0.3176806 ]), array([-0.0398791 , 0.00310763]), None, None, None, 10, array([0.32241468, 0.3487569 ]), array([0.0398791 , 0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32241468 0.3487569 ] [0.0398791 0.00310763] -0.3379065727944484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4184212317690846 goals: [('bisect', 0, array([0.32241468, 0.3487569 ]), array([-0.0398791 , -0.00310763]), None, None, None, 10, array([0.07637632, 0.3176806 ]), array([ 0.0398791 , -0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=70 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 BACKWARD SAMPLING FROM -4 [0.72439543 0.5193604 ] [ 0.03378467 -0.02141486] -0.2670596822248383 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.49518079847518337 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 1, array([0.89331877, 0.41228611]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.92710344 0.39087125] [ 0.03378467 -0.02141486] new direction: [-0.03988025 -0.00309289] reversing there [ 0.03378467 -0.02141486] making one step from [0.92710344 0.39087125] [ 0.03378467 -0.02141486] --> [0.88722319 0.38777836] [-0.03988025 -0.00309289] trying new point, [0.88722319 0.38777836] next() call None goals: [('reflect-at', 2, array([0.88722319, 0.38777836]), array([-0.03988025, -0.00309289]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.28146270933833795 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, -7, array([0.62304142, 0.58360498]), array([ 0.03378467, -0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.89331877, 0.41228611]), array([-0.03378467, 0.02141486]), None, None, None, 1, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.62304142 0.58360498] [ 0.03378467 -0.02141486] -0.28146270933833795 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.62304142, 0.58360498]), array([-0.03378467, 0.02141486]), None, None, None, -7, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=71 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 BACKWARD SAMPLING FROM 4 [0.25971764 0.3556196 ] [0.01088008 0.03849187] -0.29429788638027965 BACKWARD SAMPLING FROM -4 [0.11573234 0.53055056] [ 0.01746073 -0.03598781] -0.018363694539417472 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), None, None, None, 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4538641787707029 goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 3, array([0.23795748, 0.27863586]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23795748 0.27863586] [ 0.01746073 -0.03598781] new direction: [0.01088008 0.03849187] reversing there [ 0.01746073 -0.03598781] making one step from [0.23795748 0.27863586] [ 0.01746073 -0.03598781] --> [0.24883756 0.31712773] [0.01088008 0.03849187] trying new point, [0.24883756 0.31712773] next() call -0.44898840843073634 goals: [('reflect-at', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.14649318477587447 goals: [('bisect', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), None, None, None, 10, array([0.32499811, 0.5865708 ]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32499811 0.5865708 ] [0.01088008 0.03849187] -0.14649318477587447 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), None, None, None, 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.17676633722022025 goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44898840843073634 goals: [('bisect', 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 8, array([0.23795748, 0.27863586]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23795748 0.27863586] [-0.01088008 -0.03849187] new direction: [-0.01746073 0.03598781] reversing there [-0.01088008 -0.03849187] making one step from [0.23795748 0.27863586] [-0.01088008 -0.03849187] --> [0.22049674 0.31462368] [-0.01746073 0.03598781] trying new point, [0.22049674 0.31462368] next() call -0.4538641787707029 goals: [('reflect-at', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1779655671937919 goals: [('bisect', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), None, None, None, 10, array([0.18557527, 0.3865993 ]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-7, 0) ---- seed=72 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM -4 [0.20355555 0.55695974] [-0.02420434 0.03184572] -0.06127258297454431 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 1, array([0.08253387, 0.71618836]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.08253387 0.71618836] [-0.02420434 0.03184572] new direction: [-0.03993916 0.0022054 ] reversing there [-0.02420434 0.03184572] making one step from [0.08253387 0.71618836] [-0.02420434 0.03184572] --> [0.04259471 0.71839376] [-0.03993916 0.0022054 ] trying new point, [0.04259471 0.71839376] next() call None goals: [('reflect-at', 1, array([0.04259471, 0.71839376]), array([-0.03993916, 0.0022054 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.1834117210951967 goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, -9, array([0.32457724, 0.39773113]), array([-0.02420434, 0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.32457724 0.39773113] [-0.02420434 0.03184572] -0.1834117210951967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4304741024618556 goals: [('bisect', 0, array([0.32457724, 0.39773113]), array([ 0.02420434, -0.03184572]), None, None, None, -9, array([0.1067382 , 0.68434263]), array([ 0.02420434, -0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=73 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 BACKWARD SAMPLING FROM 4 [0.72214504 0.62997003] [-0.03328493 -0.02218362] -0.4718993295718914 BACKWARD SAMPLING FROM -4 [0.52994985 0.42508821] [0.02818502 0.02838318] -0.21057062182068897 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), None, None, None, 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3580765940944526 goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.45593173307845614 goals: [('bisect', 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 4, array([0.75542998, 0.65215365]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.75542998 0.65215365] [0.02818502 0.02838318] new direction: [-0.03328493 -0.02218362] reversing there [0.02818502 0.02838318] making one step from [0.75542998 0.65215365] [0.02818502 0.02838318] --> [0.72214504 0.62997003] [-0.03328493 -0.02218362] trying new point, [0.72214504 0.62997003] next() call -0.4718993295718915 goals: [('reflect-at', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13659198800339803 goals: [('bisect', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), None, None, None, 10, array([0.52243544, 0.49686829]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.52243544 0.49686829] [-0.03328493 -0.02218362] -0.13659198800339803 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), None, None, None, 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.38248798494168457 goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4718993295718915 goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 6, array([0.72214504, 0.62997003]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.75542998 0.65215365] [0.03328493 0.02218362] new direction: [-0.02818502 -0.02838318] reversing there [0.03328493 0.02218362] making one step from [0.75542998 0.65215365] [0.03328493 0.02218362] --> [0.72724496 0.62377047] [-0.02818502 -0.02838318] trying new point, [0.72724496 0.62377047] next() call -0.4559317330784566 goals: [('reflect-at', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2251698677879109 goals: [('bisect', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), None, None, None, 10, array([0.64268992, 0.53862093]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: 0..15 sampling between (0, 15) ---- seed=74 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 BACKWARD SAMPLING FROM 4 [0.908303 0.46166811] [-0.03985264 0.00343029] -0.4308738435817744 BACKWARD SAMPLING FROM -4 [0.7125903 0.50525487] [ 0.03934543 -0.00720676] -0.2542376365289063 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38560758459709216 goals: [('bisect', 0, array([0.869972 , 0.47642782]), array([ 0.03934543, -0.00720676]), None, None, None, 10, array([0.73657373, 0.4043602 ]), array([-0.03934543, -0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.73657373 0.4043602 ] [-0.03934543 -0.00720676] -0.38560758459709216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3853712408253484 goals: [('bisect', 0, array([0.73657373, 0.4043602 ]), array([0.03934543, 0.00720676]), None, None, None, 10, array([0.869972 , 0.47642782]), array([-0.03934543, 0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -14..1 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-14, 1) ---- seed=75 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 BACKWARD SAMPLING FROM 4 [0.8243863 0.61256616] [0.03617356 0.01707259] -0.49819564920674286 BACKWARD SAMPLING FROM -4 [0.53499778 0.47598547] [0.03617356 0.01707259] -0.15032003434226449 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), None, None, None, 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3596546025768169 goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.42462744731562935 goals: [('bisect', 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49819564920674275 goals: [('bisect', 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 4, array([0.8243863 , 0.61256616]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.86055987 0.62963875] [0.03617356 0.01707259] new direction: [-0.01645837 -0.03645713] reversing there [0.03617356 0.01707259] making one step from [0.86055987 0.62963875] [0.03617356 0.01707259] --> [0.84410149 0.59318162] [-0.01645837 -0.03645713] trying new point, [0.84410149 0.59318162] next() call -0.46478885376243206 goals: [('reflect-at', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3894210121323491 goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), None, None, None, 10, array([0.76180964, 0.41089599]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76180964 0.41089599] [-0.01645837 -0.03645713] -0.3894210121323491 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), None, None, None, 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46478885376243206 goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 6, array([0.86055987, 0.62963875]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.86055987 0.62963875] [0.01645837 0.03645713] new direction: [-0.03617356 -0.01707259] reversing there [0.01645837 0.03645713] making one step from [0.86055987 0.62963875] [0.01645837 0.03645713] --> [0.8243863 0.61256616] [-0.03617356 -0.01707259] trying new point, [0.8243863 0.61256616] next() call -0.4981956492067427 goals: [('reflect-at', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25549498455609504 goals: [('bisect', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), None, None, None, 10, array([0.67969204, 0.54427582]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -12..3 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-12, 3) ---- seed=76 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BACKWARD SAMPLING FROM 4 [0.68160346 0.52744316] [0.0063244 0.03949686] -0.24170572618743733 BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), None, None, None, 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2926344475809864 goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3826032159139785 goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 6, array([0.69425226, 0.60643688]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.70057666 0.64593374] [0.0063244 0.03949686] new direction: [-0.03371121 0.02153031] reversing there [0.0063244 0.03949686] making one step from [0.70057666 0.64593374] [0.0063244 0.03949686] --> [0.66686545 0.66746405] [-0.03371121 0.02153031] trying new point, [0.66686545 0.66746405] next() call None goals: [('reflect-at', 7, array([0.66686545, 0.66746405]), array([-0.03371121, 0.02153031]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.67527906 0.4879463 ] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.69425226 0.60643688] [0.0063244 0.03949686] -0.3826032159139785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4283913100076723 goals: [('bisect', 0, array([0.69425226, 0.60643688]), array([-0.0063244 , -0.03949686]), None, None, None, 6, array([0.65630586, 0.36945572]), array([-0.0063244 , -0.03949686]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=77 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 BACKWARD SAMPLING FROM 4 [0.19450023 0.63199687] [-0.03291268 0.02273226] -0.23670484165889305 BACKWARD SAMPLING FROM -4 [0.45780164 0.45013877] [-0.03291268 0.02273226] -0.1358679463834473 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), None, None, None, 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3123190738073511 goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4019354437867032 goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 6, array([0.12867488, 0.67746139]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.0957622 0.70019366] [-0.03291268 0.02273226] new direction: [-0.01742501 -0.03600513] reversing there [-0.03291268 0.02273226] making one step from [0.0957622 0.70019366] [-0.03291268 0.02273226] --> [0.07833719 0.66418853] [-0.01742501 -0.03600513] trying new point, [0.07833719 0.66418853] next() call -0.34004177980724587 goals: [('reflect-at', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.039782409475446034 goals: [('bisect', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), None, None, None, 10, array([0.02606217, 0.55617315]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.02606217 0.55617315] [-0.01742501 -0.03600513] -0.039782409475446034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), None, None, None, 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.20724246552376055 goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3400417798072463 goals: [('bisect', 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 4, array([0.0957622 , 0.70019366]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.0957622 0.70019366] [0.01742501 0.03600513] new direction: [ 0.03291268 -0.02273226] reversing there [0.01742501 0.03600513] making one step from [0.0957622 0.70019366] [0.01742501 0.03600513] --> [0.12867488 0.67746139] [ 0.03291268 -0.02273226] trying new point, [0.12867488 0.67746139] next() call -0.4019354437867037 goals: [('reflect-at', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07426929137401193 goals: [('bisect', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), None, None, None, 10, array([0.32615094, 0.54106782]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=78 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BACKWARD SAMPLING FROM 4 [0.05987511 0.56296374] [ 0.02701408 -0.02949982] -0.05134792603041273 BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18718326659217294 goals: [('bisect', 0, array([0.04818123, 0.68096301]), array([-0.02701408, -0.02949982]), None, None, None, 10, array([0.22195962, 0.38596484]), array([ 0.02701408, -0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.22195962 0.38596484] [ 0.02701408 -0.02949982] -0.18718326659217294 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41050587019281287 goals: [('bisect', 0, array([0.22195962, 0.38596484]), array([-0.02701408, 0.02949982]), None, None, None, 10, array([0.04818123, 0.68096301]), array([0.02701408, 0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=79 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 BACKWARD SAMPLING FROM 4 [0.57191913 0.61132696] [0.01781275 0.03581488] -0.3184669014578434 BACKWARD SAMPLING FROM -4 [0.42941712 0.32480789] [0.01781275 0.03581488] -0.4758529786384704 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), None, None, None, 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4445258817169163 goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 6, array([0.60754463, 0.68295673]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.60754463 0.68295673] [0.01781275 0.03581488] new direction: [-0.03971424 -0.00477279] reversing there [0.01781275 0.03581488] making one step from [0.60754463 0.68295673] [0.01781275 0.03581488] --> [0.56783039 0.67818395] [-0.03971424 -0.00477279] trying new point, [0.56783039 0.67818395] next() call None goals: [('reflect-at', 6, array([0.56783039, 0.67818395]), array([-0.03971424, -0.00477279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.51848088 0.50388231] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.58973188 0.64714185] [0.01781275 0.03581488] -0.4445258817169163 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.13808040243633282 goals: [('bisect', 0, array([0.58973188, 0.64714185]), array([-0.01781275, -0.03581488]), None, None, None, 5, array([0.50066813, 0.46806743]), array([-0.01781275, -0.03581488]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=80 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 BACKWARD SAMPLING FROM -4 [0.42753547 0.64725549] [-0.03941662 0.0068066 ] -0.36244551853049845 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.46049425869412336 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4863274153461391 goals: [('bisect', 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 4, array([0.11220248, 0.70170826]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.11220248 0.70170826] [-0.03941662 0.0068066 ] new direction: [-0.03348855 0.02187504] reversing there [-0.03941662 0.0068066 ] making one step from [0.11220248 0.70170826] [-0.03941662 0.0068066 ] --> [0.07871393 0.7235833 ] [-0.03348855 0.02187504] trying new point, [0.07871393 0.7235833 ] next() call None goals: [('reflect-at', 4, array([0.07871393, 0.7235833 ]), array([-0.03348855, 0.02187504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.37200718954009426 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, -3, array([0.38811884, 0.65406208]), array([-0.03941662, 0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.1516191 , 0.69490167]), array([ 0.03941662, -0.0068066 ]), None, None, None, 3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.38811884 0.65406208] [-0.03941662 0.0068066 ] -0.37200718954009426 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.38811884, 0.65406208]), array([ 0.03941662, -0.0068066 ]), None, None, None, -3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=81 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 BACKWARD SAMPLING FROM 4 [0.45306473 0.42098814] [0.02672267 0.02976405] -0.18066975294765303 BACKWARD SAMPLING FROM -4 [0.39239943 0.49651665] [-0.00924508 -0.03891694] -0.07714032966931968 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), None, None, None, 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 1, array([0.34617404, 0.30193193]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.34617404 0.30193193] [-0.00924508 -0.03891694] new direction: [0.02672267 0.02976405] reversing there [-0.00924508 -0.03891694] making one step from [0.34617404 0.30193193] [-0.00924508 -0.03891694] --> [0.37289671 0.33169598] [0.02672267 0.02976405] trying new point, [0.37289671 0.33169598] next() call -0.4236039997490474 goals: [('reflect-at', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3120636527905234 goals: [('bisect', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), None, None, None, 10, array([0.61340077, 0.59957245]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.61340077 0.59957245] [0.02672267 0.02976405] -0.3120636527905234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), None, None, None, 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14541481093575562 goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2387862650871675 goals: [('bisect', 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3197643473542989 goals: [('bisect', 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4236039997490474 goals: [('bisect', 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 9, array([0.37289671, 0.33169598]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.34617404 0.30193193] [-0.02672267 -0.02976405] new direction: [0.00924508 0.03891694] reversing there [-0.02672267 -0.02976405] making one step from [0.34617404 0.30193193] [-0.02672267 -0.02976405] --> [0.35541912 0.34084888] [0.00924508 0.03891694] trying new point, [0.35541912 0.34084888] next() call -0.37977487528894 goals: [('reflect-at', 10, array([0.35541912, 0.34084888]), array([0.00924508, 0.03891694]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=82 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 BACKWARD SAMPLING FROM 4 [0.30917537 0.48287406] [ 0.00848742 -0.03908918] -0.051460926903102756 BACKWARD SAMPLING FROM -1 [0.26673825 0.67831994] [ 0.00848742 -0.03908918] -0.433049641425479 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), None, None, None, 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.08995656502013205 goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2817612222756952 goals: [('bisect', 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4350702414142291 goals: [('bisect', 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 9, array([0.35161249, 0.28742818]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.35161249 0.28742818] [ 0.00848742 -0.03908918] new direction: [-0.01853685 0.03544552] reversing there [ 0.00848742 -0.03908918] making one step from [0.35161249 0.28742818] [ 0.00848742 -0.03908918] --> [0.33307564 0.32287371] [-0.01853685 0.03544552] trying new point, [0.33307564 0.32287371] next() call -0.4476412362297438 goals: [('reflect-at', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3003853287533051 goals: [('bisect', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), None, None, None, 10, array([0.31453879, 0.35831923]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31453879 0.35831923] [-0.01853685 0.03544552] -0.3003853287533051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), None, None, None, 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4476412362297438 goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 1, array([0.33307564, 0.32287371]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.35161249 0.28742818] [ 0.01853685 -0.03544552] new direction: [-0.00848742 0.03908918] reversing there [ 0.01853685 -0.03544552] making one step from [0.35161249 0.28742818] [ 0.01853685 -0.03544552] --> [0.34312507 0.32651736] [-0.00848742 0.03908918] trying new point, [0.34312507 0.32651736] next() call -0.43507024141422884 goals: [('reflect-at', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2801896445066674 goals: [('bisect', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), None, None, None, 10, array([0.27522567, 0.63923076]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=83 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM -4 [0.38697777 0.59042374] [-0.03248384 0.02334096] -0.1770815538786539 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 1, array([0.22455859, 0.70712854]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22455859 0.70712854] [-0.03248384 0.02334096] new direction: [-0.03398668 0.02109279] reversing there [-0.03248384 0.02334096] making one step from [0.22455859 0.70712854] [-0.03248384 0.02334096] --> [0.19057191 0.72822133] [-0.03398668 0.02109279] trying new point, [0.19057191 0.72822133] next() call None goals: [('reflect-at', 1, array([0.19057191, 0.72822133]), array([-0.03398668, 0.02109279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.15955218049839826 goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, -9, array([0.54939694, 0.47371893]), array([-0.03248384, 0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.54939694 0.47371893] [-0.03248384 0.02334096] -0.15955218049839826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4552588508048801 goals: [('bisect', 0, array([0.54939694, 0.47371893]), array([ 0.03248384, -0.02334096]), None, None, None, -9, array([0.25704243, 0.68378758]), array([ 0.03248384, -0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=84 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 BACKWARD SAMPLING FROM 4 [0.0588575 0.31191846] [-0.03418324 0.02077272] -0.4439154472871768 BACKWARD SAMPLING FROM -4 [0.18512274 0.4493389 ] [-0.03477044 -0.01977415] -0.049217056098525905 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), None, None, None, 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.35858253304774335 goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4485888583524455 goals: [('bisect', 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 4, array([0.09304075, 0.29114574]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.09304075 0.29114574] [ 0.03477044 -0.01977415] new direction: [-0.03418324 0.02077272] reversing there [ 0.03477044 -0.01977415] making one step from [0.09304075 0.29114574] [ 0.03477044 -0.01977415] --> [0.0588575 0.31191846] [-0.03418324 0.02077272] trying new point, [0.0588575 0.31191846] next() call -0.4439154472871768 goals: [('reflect-at', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.061009567312068635 goals: [('bisect', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), None, None, None, 10, array([0.14624196, 0.43655477]), array([0.03418324, 0.02077272]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.14624196 0.43655477] [0.03418324 0.02077272] -0.061009567312068635 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), None, None, None, 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.35020744828671635 goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4439154472871768 goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 6, array([0.0588575 , 0.31191846]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.09304075 0.29114574] [ 0.03418324 -0.02077272] new direction: [-0.03477044 0.01977415] reversing there [ 0.03418324 -0.02077272] making one step from [0.09304075 0.29114574] [ 0.03418324 -0.02077272] --> [0.05827031 0.31091988] [-0.03477044 0.01977415] trying new point, [0.05827031 0.31091988] next() call -0.4485888583524455 goals: [('reflect-at', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2115230931353383 goals: [('bisect', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), None, None, None, 10, array([0.04604099, 0.37024232]), array([0.03477044, 0.01977415]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=85 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 BACKWARD SAMPLING FROM 4 [0.77064828 0.56388562] [0.03756862 0.01373314] -0.3479665415854334 BACKWARD SAMPLING FROM -4 [0.47009935 0.45402052] [0.03756862 0.01373314] -0.13692311038869834 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), None, None, None, 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4019156709890521 goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4619911782824545 goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 6, array([0.84578551, 0.5913519 ]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.88335413 0.60508503] [0.03756862 0.01373314] new direction: [-0.01499532 -0.03708288] reversing there [0.03756862 0.01373314] making one step from [0.88335413 0.60508503] [0.03756862 0.01373314] --> [0.86835881 0.56800215] [-0.01499532 -0.03708288] trying new point, [0.86835881 0.56800215] next() call -0.43482716294154355 goals: [('reflect-at', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3623496671674091 goals: [('bisect', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), None, None, None, 10, array([0.82337284, 0.4567535 ]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.82337284 0.4567535 ] [-0.01499532 -0.03708288] -0.3623496671674091 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), None, None, None, 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.37606463005047236 goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.43482716294154355 goals: [('bisect', 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 4, array([0.88335413, 0.60508503]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.88335413 0.60508503] [0.01499532 0.03708288] new direction: [-0.03756862 -0.01373314] reversing there [0.01499532 0.03708288] making one step from [0.88335413 0.60508503] [0.01499532 0.03708288] --> [0.84578551 0.5913519 ] [-0.03756862 -0.01373314] trying new point, [0.84578551 0.5913519 ] next() call -0.4619911782824549 goals: [('reflect-at', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19343380286879602 goals: [('bisect', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), None, None, None, 10, array([0.62037381, 0.50895307]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=86 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 BACKWARD SAMPLING FROM 4 [0.22997871 0.54410506] [ 0.00068648 -0.03999411] -0.05076080590070252 BACKWARD SAMPLING FROM -4 [0.22820267 0.50408385] [-0.00019397 0.03999953] -0.026246700683537846 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), None, None, None, 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 1, array([0.22723279, 0.70408149]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22723279 0.70408149] [-0.00019397 0.03999953] new direction: [ 0.00068648 -0.03999411] reversing there [-0.00019397 0.03999953] making one step from [0.22723279 0.70408149] [-0.00019397 0.03999953] --> [0.22791927 0.66408738] [ 0.00068648 -0.03999411] trying new point, [0.22791927 0.66408738] next() call -0.362531970289674 goals: [('reflect-at', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), None, None, None, 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513657 goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.09888785040833842 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.19490757833235206 goals: [('bisect', 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.33091599613376643 goals: [('bisect', 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 9, array([0.23341111, 0.34413451]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] new direction: [0.03260973 0.02316475] reversing there [ 0.00068648 -0.03999411] making one step from [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] --> [0.26670732 0.32730515] [0.03260973 0.02316475] trying new point, [0.26670732 0.32730515] next() call -0.4083602779624293 goals: [('reflect-at', 10, array([0.26670732, 0.32730515]), array([0.03260973, 0.02316475]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.26670732 0.32730515] [0.03260973 0.02316475] -0.4083602779624293 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), None, None, None, 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 1, array([0.23409759, 0.3041404 ]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] new direction: [-0.00068648 0.03999411] reversing there [-0.03260973 -0.02316475] making one step from [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] --> [0.23341111 0.34413451] [-0.00068648 0.03999411] trying new point, [0.23341111 0.34413451] next() call -0.33091599613376643 goals: [('reflect-at', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), None, None, None, 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513682 goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.11469583748629265 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.21861955894928337 goals: [('bisect', 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3625319702896749 goals: [('bisect', 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 9, array([0.22791927, 0.66408738]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.22723279 0.70408149] [-0.00068648 0.03999411] new direction: [ 0.00019397 -0.03999953] reversing there [-0.00068648 0.03999411] making one step from [0.22723279 0.70408149] [-0.00068648 0.03999411] --> [0.22742677 0.66408196] [ 0.00019397 -0.03999953] trying new point, [0.22742677 0.66408196] next() call -0.36239760340404076 goals: [('reflect-at', 10, array([0.22742677, 0.66408196]), array([ 0.00019397, -0.03999953]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=87 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 BACKWARD SAMPLING FROM 4 [0.3391376 0.32791809] [ 0.03905665 -0.00863586] -0.42765944711127135 BACKWARD SAMPLING FROM -4 [0.02668439 0.39700497] [ 0.03905665 -0.00863586] -0.13295572584667534 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), None, None, None, 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4797518449351289 goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 6, array([0.4172509 , 0.31064637]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.4172509 0.31064637] [ 0.03905665 -0.00863586] new direction: [-0.03724409 0.01459033] reversing there [ 0.03905665 -0.00863586] making one step from [0.4172509 0.31064637] [ 0.03905665 -0.00863586] --> [0.3800068 0.3252367] [-0.03724409 0.01459033] trying new point, [0.3800068 0.3252367] next() call -0.45398023973187507 goals: [('reflect-at', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19605535574242375 goals: [('bisect', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), None, None, None, 10, array([0.23103043, 0.383598 ]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23103043 0.383598 ] [-0.03724409 0.01459033] -0.19605535574242375 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), None, None, None, 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3115996729727667 goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37943542516122514 goals: [('bisect', 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.45398023973187507 goals: [('bisect', 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 4, array([0.3800068, 0.3252367]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.4172509 0.31064637] [ 0.03724409 -0.01459033] new direction: [-0.03905665 0.00863586] reversing there [ 0.03724409 -0.01459033] making one step from [0.4172509 0.31064637] [ 0.03724409 -0.01459033] --> [0.37819425 0.31928223] [-0.03905665 0.00863586] trying new point, [0.37819425 0.31928223] next() call -0.4797518449351292 goals: [('reflect-at', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25318859507313635 goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), None, None, None, 10, array([0.18291099, 0.36246153]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=88 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170837 BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.39582616718099384 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28223684347738265 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3768913954170836 goals: [('bisect', 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 4, array([0.67171523, 0.34898492]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.67171523 0.34898492] [ 0.00604104 -0.03954119] new direction: [-0.03138488 -0.02479897] reversing there [ 0.00604104 -0.03954119] making one step from [0.67171523 0.34898492] [ 0.00604104 -0.03954119] --> [0.64033034 0.32418595] [-0.03138488 -0.02479897] trying new point, [0.64033034 0.32418595] next() call None goals: [('reflect-at', 4, array([0.64033034, 0.32418595]), array([-0.03138488, -0.02479897]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.3958261671809942 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, -3, array([0.62942792, 0.62577326]), array([ 0.00604104, -0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170836 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.66567418, 0.38852612]), array([-0.00604104, 0.03954119]), None, None, None, 3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.3958261671809942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.62942792, 0.62577326]), array([-0.00604104, 0.03954119]), None, None, None, -3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=89 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 BACKWARD SAMPLING FROM 4 [0.20913614 0.33057099] [ 0.01413523 -0.03741918] -0.38069631886308075 BACKWARD SAMPLING FROM -4 [0.09605432 0.62992447] [ 0.01413523 -0.03741918] -0.21561781084839587 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), None, None, None, 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12819855855898762 goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23684509426933237 goals: [('bisect', 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.38069631886308075 goals: [('bisect', 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 4, array([0.20913614, 0.33057099]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22327136 0.29315181] [ 0.01413523 -0.03741918] new direction: [-0.03612676 0.0171714 ] reversing there [ 0.01413523 -0.03741918] making one step from [0.22327136 0.29315181] [ 0.01413523 -0.03741918] --> [0.1871446 0.31032321] [-0.03612676 0.0171714 ] trying new point, [0.1871446 0.31032321] next() call -0.46722761628857196 goals: [('reflect-at', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1347530535350935 goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), None, None, None, 10, array([0.00651078, 0.39618021]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00651078 0.39618021] [-0.03612676 0.0171714 ] -0.1347530535350935 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), None, None, None, 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46722761628857196 goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 6, array([0.22327136, 0.29315181]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] new direction: [-0.01413523 0.03741918] reversing there [ 0.03612676 -0.0171714 ] making one step from [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] --> [0.20913614 0.33057099] [-0.01413523 0.03741918] trying new point, [0.20913614 0.33057099] next() call -0.3806963188630805 goals: [('reflect-at', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.016519553788509028 goals: [('bisect', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), None, None, None, 10, array([0.15259523, 0.48024773]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=90 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 BACKWARD SAMPLING FROM 4 [0.17606336 0.66988726] [-0.03949695 0.00632385] -0.37627016306758043 BACKWARD SAMPLING FROM -4 [0.49203895 0.61929648] [-0.03949695 0.00632385] -0.2989468009164582 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), None, None, None, 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3974546157438025 goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4475028760344699 goals: [('bisect', 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4763666836489148 goals: [('bisect', 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 9, array([0.02142138, 0.70150649]), array([0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.02142138 0.70150649] [0.03949695 0.00632385] new direction: [-0.02643714 0.03001795] reversing there [0.03949695 0.00632385] making one step from [0.02142138 0.70150649] [0.03949695 0.00632385] --> [0.00501576 0.73152444] [0.02643714 0.03001795] trying new point, [0.00501576 0.73152444] next() call None goals: [('reflect-at', 9, array([0.00501576, 0.73152444]), array([0.02643714, 0.03001795]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.01807557 0.69518265] [-0.03949695 0.00632385] -0.4763666836489148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.31713020215676097 goals: [('bisect', 0, array([0.01807557, 0.69518265]), array([ 0.03949695, -0.00632385]), None, None, None, 8, array([0.33405116, 0.64459187]), array([ 0.03949695, -0.00632385]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -11..4 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-11, 4) ---- seed=91 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 BACKWARD SAMPLING FROM 4 [0.04151464 0.31624266] [-0.03987224 -0.00319445] -0.42294623725634856 BACKWARD SAMPLING FROM -4 [0.36049255 0.34179827] [-0.03987224 -0.00319445] -0.37782476710495483 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), None, None, None, 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.43688850948485125 goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.47030777958157655 goals: [('bisect', 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.48978477744979876 goals: [('bisect', 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 9, array([0.15784656, 0.3002704 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] new direction: [0.02906527 0.02748108] reversing there [ 0.03987224 -0.00319445] making one step from [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] --> [0.18691183 0.32775148] [0.02906527 0.02748108] trying new point, [0.18691183 0.32775148] next() call -0.38833742025683327 goals: [('reflect-at', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.28529319268566455 goals: [('bisect', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), None, None, None, 10, array([0.21597711, 0.35523256]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21597711 0.35523256] [0.02906527 0.02748108] -0.28529319268566455 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), None, None, None, 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.38833742025683327 goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 1, array([0.18691183, 0.32775148]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] new direction: [-0.03987224 0.00319445] reversing there [-0.02906527 -0.02748108] making one step from [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] --> [0.11797432 0.30346485] [-0.03987224 0.00319445] trying new point, [0.11797432 0.30346485] next() call -0.4897847774497991 goals: [('reflect-at', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3856262338080673 goals: [('bisect', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), None, None, None, 10, array([0.2010036 , 0.32902047]), array([0.03987224, 0.00319445]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=92 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 BACKWARD SAMPLING FROM -4 [0.42647012 0.63886016] [-0.0004355 -0.03999763] -0.3319651929892012 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.21765730389482751 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.33859005788161145 goals: [('bisect', 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49951826010720873 goals: [('bisect', 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 4, array([0.42298615, 0.31887913]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] new direction: [-0.03548521 0.01846077] reversing there [-0.0004355 -0.03999763] making one step from [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] --> [0.38706544 0.29734227] [-0.03548521 0.01846077] trying new point, [0.38706544 0.29734227] next() call None goals: [('reflect-at', 5, array([0.38706544, 0.29734227]), array([-0.03548521, 0.01846077]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09483173136735507 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, -1, array([0.42516363, 0.51886728]), array([-0.0004355 , -0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.09577814063769934 goals: [('bisect', 0, array([0.42298615, 0.31887913]), array([0.0004355 , 0.03999763]), None, None, None, 4, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.42516363 0.51886728] [-0.0004355 -0.03999763] -0.09483173136735507 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09577814063769935 goals: [('bisect', 0, array([0.42516363, 0.51886728]), array([0.0004355 , 0.03999763]), None, None, None, -1, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=93 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 BACKWARD SAMPLING FROM 4 [0.515227 0.56286192] [-0.03275687 -0.02295621] -0.18212468401683823 BACKWARD SAMPLING FROM -4 [0.44675381 0.66881082] [ 0.03990013 -0.00282481] -0.4560081322130549 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), None, None, None, 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 1, array([0.64625447, 0.65468676]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.64625447 0.65468676] [ 0.03990013 -0.00282481] new direction: [-0.03275687 -0.02295621] reversing there [ 0.03990013 -0.00282481] making one step from [0.64625447 0.65468676] [ 0.03990013 -0.00282481] --> [0.6134976 0.63173055] [-0.03275687 -0.02295621] trying new point, [0.6134976 0.63173055] next() call -0.4051013634874946 goals: [('reflect-at', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12085928392615417 goals: [('bisect', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), None, None, None, 10, array([0.31868579, 0.42512465]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31868579 0.42512465] [-0.03275687 -0.02295621] -0.12085928392615417 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), None, None, None, 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1362945285525923 goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.24220254166073774 goals: [('bisect', 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.31652810148428956 goals: [('bisect', 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.40510136348749465 goals: [('bisect', 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 9, array([0.6134976 , 0.63173055]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.64625447 0.65468676] [0.03275687 0.02295621] new direction: [-0.03990013 0.00282481] reversing there [0.03275687 0.02295621] making one step from [0.64625447 0.65468676] [0.03275687 0.02295621] --> [0.60635434 0.65751157] [-0.03990013 0.00282481] trying new point, [0.60635434 0.65751157] next() call -0.49395646957573464 goals: [('reflect-at', 10, array([0.60635434, 0.65751157]), array([-0.03990013, 0.00282481]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -3..12 sampling between (-3, 12) ---- seed=94 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 BACKWARD SAMPLING FROM 4 [0.86227142 0.53522328] [ 0.03572141 -0.01799947] -0.38726449528400564 BACKWARD SAMPLING FROM -2 [0.64794297 0.64322012] [ 0.03572141 -0.01799947] -0.46631508651324616 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4925337817021134 goals: [('bisect', 0, array([0.71938579, 0.60722118]), array([ 0.03572141, -0.01799947]), None, None, None, 10, array([0.92340014, 0.42722645]), array([-0.03572141, -0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.92340014 0.42722645] [-0.03572141 -0.01799947] -0.4925337817021134 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4024627109969381 goals: [('bisect', 0, array([0.92340014, 0.42722645]), array([0.03572141, 0.01799947]), None, None, None, 10, array([0.71938579, 0.60722118]), array([-0.03572141, 0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=95 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 BACKWARD SAMPLING FROM 4 [0.60734111 0.59133529] [-0.02922414 0.02731208] -0.2887083100641112 BACKWARD SAMPLING FROM -4 [0.82122514 0.40753202] [ 0.01990911 -0.03469333] -0.4440844529643073 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), None, None, None, 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.34307459325849876 goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41694366417810785 goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 6, array([0.54889282, 0.64595945]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.51966868 0.67327152] [-0.02922414 0.02731208] new direction: [-0.03257512 0.02321339] reversing there [-0.02922414 0.02731208] making one step from [0.51966868 0.67327152] [-0.02922414 0.02731208] --> [0.48709356 0.69648491] [-0.03257512 0.02321339] trying new point, [0.48709356 0.69648491] next() call None goals: [('reflect-at', 7, array([0.48709356, 0.69648491]), array([-0.03257512, 0.02321339]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.63656525 0.56402322] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.54889282 0.64595945] [-0.02922414 0.02731208] -0.41694366417810785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.2662710545387677 goals: [('bisect', 0, array([0.54889282, 0.64595945]), array([ 0.02922414, -0.02731208]), None, None, None, 6, array([0.72423768, 0.48208699]), array([ 0.02922414, -0.02731208]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=96 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 BACKWARD SAMPLING FROM 4 [0.0396262 0.47159221] [ 0.03300675 -0.02259545] -0.010872647013765053 BACKWARD SAMPLING FROM -4 [0.22442783 0.65235578] [-0.03300675 -0.02259545] -0.3153374835129045 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36436264123928686 goals: [('bisect', 0, array([0.09240082, 0.561974 ]), array([-0.03300675, -0.02259545]), None, None, None, 10, array([0.23766673, 0.33601954]), array([ 0.03300675, -0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23766673 0.33601954] [ 0.03300675 -0.02259545] -0.36436264123928686 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05227866114907242 goals: [('bisect', 0, array([0.23766673, 0.33601954]), array([-0.03300675, 0.02259545]), None, None, None, 10, array([0.09240082, 0.561974 ]), array([0.03300675, 0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=97 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 BACKWARD SAMPLING FROM 4 [0.1641606 0.49992937] [-0.01012837 0.03869646] -0.013474413804503925 BACKWARD SAMPLING FROM -1 [0.21480243 0.30644705] [-0.01012837 0.03869646] -0.4913543244490346 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), None, None, None, 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.030512397919510853 goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.1772023323934378 goals: [('bisect', 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3068542827523578 goals: [('bisect', 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4740442218592488 goals: [('bisect', 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 9, array([0.11351877, 0.69341168]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.1033904 0.73210814] [-0.01012837 0.03869646] new direction: [-0.03691991 0.01539222] reversing there [-0.01012837 0.03869646] making one step from [0.1033904 0.73210814] [-0.01012837 0.03869646] --> [0.0664705 0.74750036] [-0.03691991 0.01539222] trying new point, [0.0664705 0.74750036] next() call None goals: [('reflect-at', 10, array([0.0664705 , 0.74750036]), array([-0.03691991, 0.01539222]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.11351877 0.69341168] [-0.01012837 0.03869646] -0.4740442218592488 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.3207023648241862 goals: [('bisect', 0, array([0.11351877, 0.69341168]), array([ 0.01012837, -0.03869646]), None, None, None, 9, array([0.20467407, 0.34514352]), array([ 0.01012837, -0.03869646]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=98 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 BACKWARD SAMPLING FROM 4 [0.79446178 0.41977178] [ 0.01554863 -0.03685431] -0.39604184352994004 BACKWARD SAMPLING FROM -2 [0.70116998 0.64089763] [ 0.01554863 -0.03685431] -0.4939714550399919 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), None, None, None, 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.49941240374695045 goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 6, array([0.82555904, 0.34606317]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.82555904 0.34606317] [ 0.01554863 -0.03685431] new direction: [-0.03412149 -0.02087401] reversing there [ 0.01554863 -0.03685431] making one step from [0.82555904 0.34606317] [ 0.01554863 -0.03685431] --> [0.79143756 0.32518916] [-0.03412149 -0.02087401] trying new point, [0.79143756 0.32518916] next() call None goals: [('reflect-at', 6, array([0.79143756, 0.32518916]), array([-0.03412149, -0.02087401]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.74781588 0.53033471] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.81001041 0.38291747] [ 0.01554863 -0.03685431] -0.49941240374695045 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.3245372087629051 goals: [('bisect', 0, array([0.81001041, 0.38291747]), array([-0.01554863, 0.03685431]), None, None, None, 5, array([0.73226725, 0.56718902]), array([-0.01554863, 0.03685431]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=99 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.3783905365498532 BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28854490986652237 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37839053654985255 goals: [('bisect', 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 4, array([0.68789813, 0.64731416]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.68789813 0.64731416] [0.00390489 0.03980894] new direction: [-0.01907752 0.03515748] reversing there [0.00390489 0.03980894] making one step from [0.68789813 0.64731416] [0.00390489 0.03980894] --> [0.66882061 0.68247164] [-0.01907752 0.03515748] trying new point, [0.66882061 0.68247164] next() call None goals: [('reflect-at', 4, array([0.66882061, 0.68247164]), array([-0.01907752, 0.03515748]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.4338274302289816 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, -3, array([0.66056388, 0.36865158]), array([0.00390489, 0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.37839053654985255 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.22775578725568393 goals: [('bisect', 0, array([0.68399324, 0.60750522]), array([-0.00390489, -0.03980894]), None, None, None, 3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.2277557872556839 goals: [('bisect', 0, array([0.66056388, 0.36865158]), array([-0.00390489, -0.03980894]), None, None, None, -3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-3, 0)
Passed	tests/test_hotstart.py::test_hotstart_SLOW	28.98
[gw9] linux -- Python 3.10.6 /usr/bin/python3 [gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ -8963077118.743088 96.99934128550026 proposals: [[4.19976674e+01 1.01901282e-01 2.26584579e-02] [4.19936982e+01 9.70120971e-02 1.25468225e-01] [4.20043522e+01 8.81983708e-02 4.16063032e-01] [4.19910425e+01 9.23532542e-02 3.57120722e-01] [4.20010471e+01 1.04769832e-01 5.40934064e-02] [4.20004875e+01 8.44214056e-02 6.57794482e-01] [4.20114084e+01 8.71986004e-02 7.70800710e-01] [4.19997931e+01 1.17497505e-01 5.97616561e-01] [4.19793249e+01 1.16910821e-01 1.62802382e+00] [4.19777034e+01 1.00198605e-01 1.23013202e+00] [4.19809513e+01 9.73026870e-02 9.29402866e-01] [4.20035101e+01 8.39559746e-02 7.31648830e-01] [4.19818445e+01 8.91999970e-02 1.13587040e+00] [4.19944650e+01 8.89373681e-02 4.00203681e-01] [4.19879296e+01 9.87877365e-02 3.79163467e-01] [4.19993921e+01 1.05583972e-01 7.05549601e-02] [4.19958797e+01 1.00198250e-01 4.45624038e-02] [4.20028928e+01 1.13275091e-01 3.83072005e-01] [4.20075672e+01 8.60294765e-02 6.71506433e-01] [4.20000003e+01 1.32876001e-01 1.75531881e+00] [4.19941441e+01 1.20714239e-01 8.95917835e-01] [4.19973837e+01 1.02585211e-01 3.33463863e-02] [4.20109730e+01 9.76256032e-02 3.25050704e-01] [4.20249867e+01 1.01357574e-01 1.52720024e+00] [4.19795771e+01 1.01689723e-01 1.04810966e+00] [4.20151020e+01 9.49699778e-02 6.45034516e-01] [4.19711011e+01 9.64829396e-02 2.02124669e+00] [4.19779289e+01 9.01472311e-02 1.45803800e+00] [4.20283363e+01 1.50686758e-01 5.29231415e+00] [4.20036985e+01 1.13687102e-01 4.17933502e-01] [4.19861307e+01 1.11595948e-01 7.74029950e-01] [4.20008644e+01 9.20834520e-02 1.61590461e-01] [4.19749175e+01 9.45972273e-02 1.60648204e+00] [4.19978867e+01 1.40462497e-01 2.43829897e+00] [4.19934265e+01 1.00151410e-01 1.12874993e-01] [4.19958796e+01 9.06920226e-02 2.67799740e-01] [4.20091161e+01 1.15823745e-01 7.14187136e-01] [4.19660038e+01 9.54604067e-02 2.71598389e+00] [4.19911555e+01 1.13508293e-01 5.76293834e-01] [4.19706547e+01 1.03201725e-01 2.07074602e+00]] 40 [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=77.54..101.10 [77.5411..97.9860] \| it/evals=0/401 eff=0.0000% N=400 Z=86.1(0.00%) \| Like=90.62..101.10 [77.5411..97.9860] \| it/evals=23/425 eff=92.0000% N=400 Z=88.4(0.00%) \| Like=91.98..101.10 [77.5411..97.9860] \| it/evals=40/444 eff=90.9091% N=400 Z=89.8(0.01%) \| Like=93.05..101.10 [77.5411..97.9860] \| it/evals=62/469 eff=89.8551% N=400 Z=90.7(0.02%) \| Like=93.90..101.11 [77.5411..97.9860] \| it/evals=80/491 eff=87.9121% N=400 Z=91.2(0.03%) \| Like=94.28..101.11 [77.5411..97.9860] \| it/evals=90/506 eff=84.9057% N=400 Z=92.0(0.07%) \| Like=94.90..101.11 [77.5411..97.9860] \| it/evals=110/529 eff=85.2713% N=400 Z=92.3(0.10%) \| Like=95.13..101.11 [77.5411..97.9860] \| it/evals=120/540 eff=85.7143% N=400 Z=92.7(0.15%) \| Like=95.50..101.11 [77.5411..97.9860] \| it/evals=134/558 eff=84.8101% N=400 Z=93.5(0.31%) \| Like=96.16..101.11 [77.5411..97.9860] \| it/evals=160/587 eff=85.5615% N=400 Z=93.9(0.50%) \| Like=96.58..101.11 [77.5411..97.9860] \| it/evals=180/610 eff=85.7143% N=400 Z=94.3(0.75%) \| Like=96.86..101.11 [77.5411..97.9860] \| it/evals=200/631 eff=86.5801% N=400 Z=94.8(1.17%) \| Like=97.18..101.11 [77.5411..97.9860] \| it/evals=226/661 eff=86.5900% N=400 Z=95.0(1.44%) \| Like=97.36..101.11 [77.5411..97.9860] \| it/evals=240/676 eff=86.9565% N=400 Z=95.3(1.90%) \| Like=97.63..101.11 [77.5411..97.9860] \| it/evals=259/698 eff=86.9128% N=400 Z=95.4(2.20%) \| Like=97.76..101.11 [77.5411..97.9860] \| it/evals=270/712 eff=86.5385% N=400 Z=95.5(2.52%) \| Like=97.83..101.11 [77.5411..97.9860] \| it/evals=280/725 eff=86.1538% N=400 Z=95.8(3.34%) \| Like=98.09..101.11 [98.0947..98.1005]\| it/evals=305/768 eff=82.8804% N=400 Z=96.0(3.98%) \| Like=98.18..101.11 [98.1782..98.1801]\| it/evals=320/786 eff=82.9016% N=400 Z=96.1(4.68%) \| Like=98.28..101.11 [98.2821..98.2861]\| it/evals=337/807 eff=82.8010% N=400 Z=96.4(5.72%) \| Like=98.49..101.11 [98.4874..98.4975] \| it/evals=360/833 eff=83.1409% N=400 Z=96.6(6.99%) \| Like=98.67..101.11 [98.6690..98.6754]\| it/evals=384/862 eff=83.1169% N=400 Z=96.7(7.90%) \| Like=98.73..101.11 [98.7330..98.7367]\| it/evals=400/883 eff=82.8157% N=400 Z=96.9(10.47%) \| Like=99.00..101.11 [98.9936..99.0036] \| it/evals=439/926 eff=83.4601% N=400 Z=96.9(10.53%) \| Like=99.00..101.11 [99.0049..99.0065]\| it/evals=440/927 eff=83.4915% N=400 Z=97.0(11.16%) \| Like=99.05..101.11 [99.0347..99.0489] \| it/evals=450/942 eff=83.0258% N=400 Z=97.1(12.69%) \| Like=99.17..101.11 [99.1682..99.1804] \| it/evals=472/968 eff=83.0986% N=400 Z=97.2(13.19%) \| Like=99.20..101.11 [99.2022..99.2031]\| it/evals=480/977 eff=83.1889% N=400 Z=97.4(16.22%) \| Like=99.35..101.11 [99.3491..99.3523]\| it/evals=520/1024 eff=83.3333% N=400 Z=97.5(17.72%) \| Like=99.42..101.12 [99.4249..99.4286]\| it/evals=540/1051 eff=82.9493% N=400 Z=97.6(19.30%) \| Like=99.52..101.12 [99.5178..99.5184]\| it/evals=560/1072 eff=83.3333% N=400 Z=97.6(20.74%) \| Like=99.57..101.12 [99.5693..99.5718]\| it/evals=578/1092 eff=83.5260% N=400 Z=97.7(22.62%) \| Like=99.64..101.12 [99.6378..99.6380]\| it/evals=600/1118 eff=83.5655% N=400 Z=97.8(25.22%) \| Like=99.74..101.12 [99.7364..99.7367]\| it/evals=630/1160 eff=82.8947% N=400 Z=97.9(26.14%) \| Like=99.76..101.12 [99.7576..99.7651]\| it/evals=640/1170 eff=83.1169% N=400 Z=98.0(28.97%) \| Like=99.86..101.12 [99.8596..99.8598]\| it/evals=673/1212 eff=82.8818% N=400 Z=98.0(29.59%) \| Like=99.88..101.12 [99.8754..99.8765]\| it/evals=680/1219 eff=83.0281% N=400 Z=98.1(32.77%) \| Like=99.96..101.12 [99.9554..99.9554]\| it/evals=715/1260 eff=83.1395% N=400 Z=98.1(33.21%) \| Like=99.96..101.12 [99.9610..99.9618]\| it/evals=720/1267 eff=83.0450% N=400 Z=98.2(34.92%) \| Like=100.02..101.12 [100.0158..100.0164]\| it/evals=740/1296 eff=82.5893% N=400 Z=98.2(36.67%) \| Like=100.08..101.12 [100.0795..100.0837]\| it/evals=760/1322 eff=82.4295% N=400 Z=98.3(39.53%) \| Like=100.16..101.12 [100.1579..100.1583]\| it/evals=793/1358 eff=82.7766% N=400 Z=98.3(40.21%) \| Like=100.18..101.12 [100.1751..100.1761]\| it/evals=800/1367 eff=82.7301% N=400 Z=98.3(41.10%) \| Like=100.20..101.12 [100.1987..100.1988]\| it/evals=810/1380 eff=82.6531% N=400 Z=98.4(43.27%) \| Like=100.27..101.12 [100.2693..100.2703]\| it/evals=835/1413 eff=82.4284% N=400 Z=98.4(43.67%) \| Like=100.28..101.12 [100.2815..100.2828]\| it/evals=840/1418 eff=82.5147% N=400 Z=98.5(47.23%) \| Like=100.37..101.12 [100.3676..100.3733]\| it/evals=879/1472 eff=81.9963% N=400 Z=98.5(47.32%) \| Like=100.37..101.12 [100.3733..100.3744]\| it/evals=880/1473 eff=82.0130% N=400 Z=98.5(49.03%) \| Like=100.42..101.12 [100.4183..100.4192]\| it/evals=900/1496 eff=82.1168% N=400 [ultranest] Explored until L=1e+02 [ultranest] Likelihood function evaluations: 1508 [ultranest] logZ = 99.21 +- 0.03825 [ultranest] Effective samples strategy satisfied (ESS = 972.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.41, need <0.5) [ultranest] logZ error budget: single: 0.05 bs:0.04 tail:0.41 total:0.41 required:<0.50 [ultranest] done iterating. logZ = 99.218 +- 0.413 single instance: logZ = 99.218 +- 0.049 bootstrapped : logZ = 99.210 +- 0.078 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations mean : 41.9564│ ▁ ▁▁▁▁▁▁▁▂▂▃▄▇▅▆▆▇▇▅▇▆▆▅▅▄▃▂▂▁▁▁▁▁▁ ▁ │42.0216 41.9894 +- 0.0091 scatter : 0.0728│ ▁▁▁▁▁▁▂▃▄▄▅▆▇▆▇▅▅▄▄▄▃▃▂▂▂▁▁▁▁▁ ▁▁▁ ▁ │0.1198 0.0914 +- 0.0065 aux_logweight : 0.00 │▇▆▇▇▆▆▆▄▅▄▄▃▃▃▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁ ▁ ▁ │4.16 0.80 +- 0.63 [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-4.1e+11..-2.8e+02 [-4.059e+11..-3.867e+06] \| it/evals=0/401 eff=0.0000% N=400 Z=-1e+10(0.00%) \| Like=-1.4e+10..-2.8e+02 [-4.059e+11..-3.867e+06] \| it/evals=40/444 eff=90.9091% N=400 Z=-3e+09(0.00%) \| Like=-2.6e+09..-2.8e+02 [-4.059e+11..-3.867e+06] \| it/evals=80/488 eff=90.9091% N=400 Z=-6e+08(0.00%) \| Like=-5.9e+08..-2.8e+02 [-4.059e+11..-3.867e+06] \| it/evals=120/531 eff=91.6031% N=400 Z=-2e+08(0.00%) \| Like=-1.8e+08..-2.8e+02 [-4.059e+11..-3.867e+06] \| it/evals=160/576 eff=90.9091% N=400 Z=-37629480.8(0.00%) \| Like=-37019184.92..-276.64 [-4.059e+11..-3.867e+06] \| it/evals=200/627 eff=88.1057% N=400 Z=-12066612.5(0.00%) \| Like=-11773456.96..-276.64 [-4.059e+11..-3.867e+06] \| it/evals=240/671 eff=88.5609% N=400 Z=-5121053.0(0.00%) \| Like=-5026605.32..-276.64 [-4.059e+11..-3.867e+06] \| it/evals=270/708 eff=87.6623% N=400 Z=-4239114.9(0.00%) \| Like=-4218156.66..-276.64 [-4.059e+11..-3.867e+06] \| it/evals=280/720 eff=87.5000% N=400 Z=-2131925.2(0.00%) \| Like=-2080057.46..-276.64 [-3713236.8402..-67574.4853] \| it/evals=320/772 eff=86.0215% N=400 Z=-1014637.6(0.00%) \| Like=-964900.30..-276.64 [-3713236.8402..-67574.4853] \| it/evals=360/818 eff=86.1244% N=400 Z=-541870.3(0.00%) \| Like=-535492.84..-276.64 [-3713236.8402..-67574.4853] \| it/evals=400/876 eff=84.0336% N=400 Z=-300783.4(0.00%) \| Like=-295422.19..-276.64 [-3713236.8402..-67574.4853] \| it/evals=440/927 eff=83.4915% N=400 Z=-255114.9(0.00%) \| Like=-251465.12..-276.64 [-3713236.8402..-67574.4853] \| it/evals=450/939 eff=83.4879% N=400 Z=-151349.5(0.00%) \| Like=-150202.02..-276.64 [-3713236.8402..-67574.4853] \| it/evals=480/974 eff=83.6237% N=400 Z=-99997.7(0.00%) \| Like=-98049.75..-276.64 [-3713236.8402..-67574.4853] \| it/evals=520/1028 eff=82.8025% N=400 Z=-65129.4(0.00%) \| Like=-65004.43..-276.64 [-67571.4782..-7758.7267] \| it/evals=560/1081 eff=82.2320% N=400 Z=-40261.6(0.00%) \| Like=-40093.67..-276.64 [-67571.4782..-7758.7267] \| it/evals=600/1149 eff=80.1068% N=400 Z=-29839.8(0.00%) \| Like=-29468.85..-276.64 [-67571.4782..-7758.7267] \| it/evals=639/1209 eff=78.9864% N=400 Z=-29476.4(0.00%) \| Like=-28904.97..-276.64 [-67571.4782..-7758.7267] \| it/evals=640/1212 eff=78.8177% N=400 Z=-21665.4(0.00%) \| Like=-21630.82..-276.64 [-67571.4782..-7758.7267] \| it/evals=680/1275 eff=77.7143% N=400 Z=-15756.3(0.00%) \| Like=-15544.83..-276.64 [-67571.4782..-7758.7267] \| it/evals=720/1338 eff=76.7591% N=400 Z=-12939.3(0.00%) \| Like=-12872.54..-276.64 [-67571.4782..-7758.7267] \| it/evals=751/1389 eff=75.9353% N=400 Z=-12015.4(0.00%) \| Like=-12002.51..-276.64 [-67571.4782..-7758.7267] \| it/evals=760/1402 eff=75.8483% N=400 Z=-9473.4(0.00%) \| Like=-9362.21..-276.64 [-67571.4782..-7758.7267] \| it/evals=800/1488 eff=73.5294% N=400 Z=-7725.4(0.00%) \| Like=-7665.90..-276.64 [-7753.2372..-2005.4268] \| it/evals=840/1571 eff=71.7336% N=400 Z=-6168.5(0.00%) \| Like=-6136.23..-276.64 [-7753.2372..-2005.4268] \| it/evals=880/1684 eff=68.5358% N=400 Z=-4952.2(0.00%) \| Like=-4935.58..-249.74 [-7753.2372..-2005.4268] \| it/evals=920/1775 eff=66.9091% N=400 Z=-4041.3(0.00%) \| Like=-4003.76..-249.74 [-7753.2372..-2005.4268] \| it/evals=960/1860 eff=65.7534% N=400 Z=-3518.0(0.00%) \| Like=-3509.78..-249.74 [-7753.2372..-2005.4268] \| it/evals=1000/1957 eff=64.2261% N=400 Z=-2883.7(0.00%) \| Like=-2816.71..-249.74 [-7753.2372..-2005.4268] \| it/evals=1040/2051 eff=62.9921% N=400 Z=-2411.5(0.00%) \| Like=-2394.29..-249.74 [-7753.2372..-2005.4268] \| it/evals=1080/2171 eff=60.9825% N=400 Z=-2097.1(0.00%) \| Like=-2076.89..-249.74 [-7753.2372..-2005.4268] \| it/evals=1120/2298 eff=59.0095% N=400 Z=-1817.5(0.00%) \| Like=-1804.91..-249.74 [-2003.1952..-893.8641] \| it/evals=1160/2387 eff=58.3795% N=400 Z=-1783.6(0.00%) \| Like=-1754.08..-249.74 [-2003.1952..-893.8641] \| it/evals=1170/2406 eff=58.3250% N=400 Z=-1566.1(0.00%) \| Like=-1555.97..-249.74 [-2003.1952..-893.8641] \| it/evals=1200/2475 eff=57.8313% N=400 Z=-1401.3(0.00%) \| Like=-1389.84..-249.74 [-2003.1952..-893.8641] \| it/evals=1240/2557 eff=57.4873% N=400 Z=-1337.9(0.00%) \| Like=-1324.13..-249.74 [-2003.1952..-893.8641] \| it/evals=1260/2604 eff=57.1688% N=400 Z=-1276.9(0.00%) \| Like=-1266.90..-249.74 [-2003.1952..-893.8641] \| it/evals=1280/2643 eff=57.0664% N=400 Z=-1120.2(0.00%) \| Like=-1110.35..-241.79 [-2003.1952..-893.8641] \| it/evals=1320/2726 eff=56.7498% N=400 Z=-1014.1(0.00%) \| Like=-1001.54..-223.34 [-2003.1952..-893.8641] \| it/evals=1350/2781 eff=56.6989% N=400 Z=-996.6(0.00%) \| Like=-984.22..-223.34 [-2003.1952..-893.8641] \| it/evals=1360/2795 eff=56.7850% N=400 Z=-915.5(0.00%) \| Like=-904.91..-223.34 [-2003.1952..-893.8641] \| it/evals=1400/2872 eff=56.6343% N=400 Z=-835.4(0.00%) \| Like=-820.73..-176.99 [-892.8216..-562.4334] \| it/evals=1440/2938 eff=56.7376% N=400 Z=-743.6(0.00%) \| Like=-733.85..-176.99 [-892.8216..-562.4334] \| it/evals=1480/3019 eff=56.5101% N=400 Z=-699.3(0.00%) \| Like=-684.33..-115.14 [-892.8216..-562.4334] \| it/evals=1520/3102 eff=56.2546% N=400 Z=-686.8(0.00%) \| Like=-676.46..-115.14 [-892.8216..-562.4334] \| it/evals=1530/3126 eff=56.1262% N=400 Z=-654.2(0.00%) \| Like=-643.23..-115.14 [-892.8216..-562.4334] \| it/evals=1560/3173 eff=56.2568% N=400 Z=-625.3(0.00%) \| Like=-615.39..-115.14 [-892.8216..-562.4334] \| it/evals=1600/3244 eff=56.2588% N=400 Z=-611.4(0.00%) \| Like=-601.50..-115.14 [-892.8216..-562.4334] \| it/evals=1620/3278 eff=56.2891% N=400 Z=-595.0(0.00%) \| Like=-585.36..-115.14 [-892.8216..-562.4334] \| it/evals=1640/3314 eff=56.2800% N=400 Z=-574.5(0.00%) \| Like=-565.11..-115.14 [-892.8216..-562.4334] \| it/evals=1680/3370 eff=56.5657% N=400 Z=-564.2(0.00%) \| Like=-555.02..-87.70 [-561.9422..-496.7966] \| it/evals=1710/3421 eff=56.6038% N=400 Z=-561.7(0.00%) \| Like=-552.59..-87.70 [-561.9422..-496.7966] \| it/evals=1720/3435 eff=56.6722% N=400 Z=-552.2(0.00%) \| Like=-543.29..-72.54 [-561.9422..-496.7966] \| it/evals=1760/3501 eff=56.7559% N=400 Z=-542.9(0.00%) \| Like=-533.87..-72.54 [-561.9422..-496.7966] \| it/evals=1800/3566 eff=56.8541% N=400 Z=-533.6(0.00%) \| Like=-524.21..-72.54 [-561.9422..-496.7966] \| it/evals=1840/3633 eff=56.9131% N=400 Z=-526.1(0.00%) \| Like=-516.45..-72.54 [-561.9422..-496.7966] \| it/evals=1880/3703 eff=56.9180% N=400 Z=-523.5(0.00%) \| Like=-514.33..-72.54 [-561.9422..-496.7966] \| it/evals=1890/3716 eff=56.9964% N=400 Z=-514.5(0.00%) \| Like=-504.81..-72.54 [-561.9422..-496.7966] \| it/evals=1920/3752 eff=57.2792% N=400 Z=-503.4(0.00%) \| Like=-493.81..-72.54 [-496.7229..-425.4198] \| it/evals=1960/3812 eff=57.4443% N=400 Z=-497.6(0.00%) \| Like=-487.69..-72.54 [-496.7229..-425.4198] \| it/evals=1980/3839 eff=57.5749% N=400 Z=-492.4(0.00%) \| Like=-482.81..-72.54 [-496.7229..-425.4198] \| it/evals=2000/3869 eff=57.6535% N=400 Z=-481.9(0.00%) \| Like=-471.51..-72.54 [-496.7229..-425.4198] \| it/evals=2040/3916 eff=58.0205% N=400 Z=-471.5(0.00%) \| Like=-461.58..-72.54 [-496.7229..-425.4198] \| it/evals=2070/3958 eff=58.1788% N=400 Z=-467.6(0.00%) \| Like=-457.50..-72.54 [-496.7229..-425.4198] \| it/evals=2080/3974 eff=58.1981% N=400 Z=-460.2(0.00%) \| Like=-450.50..-72.54 [-496.7229..-425.4198] \| it/evals=2120/4041 eff=58.2258% N=400 Z=-451.3(0.00%) \| Like=-441.42..-48.30 [-496.7229..-425.4198] \| it/evals=2160/4093 eff=58.4890% N=400 Z=-442.1(0.00%) \| Like=-431.97..-48.30 [-496.7229..-425.4198] \| it/evals=2200/4159 eff=58.5262% N=400 Z=-432.8(0.00%) \| Like=-422.44..-48.30 [-424.9178..-365.3215] \| it/evals=2240/4224 eff=58.5774% N=400 Z=-428.1(0.00%) \| Like=-417.97..-48.30 [-424.9178..-365.3215] \| it/evals=2260/4266 eff=58.4584% N=400 Z=-424.5(0.00%) \| Like=-413.65..-48.30 [-424.9178..-365.3215] \| it/evals=2280/4292 eff=58.5817% N=400 Z=-416.6(0.00%) \| Like=-405.68..-48.30 [-424.9178..-365.3215] \| it/evals=2320/4344 eff=58.8235% N=400 Z=-411.4(0.00%) \| Like=-400.86..-48.30 [-424.9178..-365.3215] \| it/evals=2344/4389 eff=58.7616% N=400 Z=-408.2(0.00%) \| Like=-397.87..-48.30 [-424.9178..-365.3215] \| it/evals=2360/4411 eff=58.8382% N=400 Z=-400.0(0.00%) \| Like=-389.40..-48.30 [-424.9178..-365.3215] \| it/evals=2400/4465 eff=59.0406% N=400 Z=-394.0(0.00%) \| Like=-383.71..-48.30 [-424.9178..-365.3215] \| it/evals=2430/4518 eff=59.0092% N=400 Z=-392.3(0.00%) \| Like=-381.40..-48.30 [-424.9178..-365.3215] \| it/evals=2440/4533 eff=59.0370% N=400 Z=-383.1(0.00%) \| Like=-372.99..-48.30 [-424.9178..-365.3215] \| it/evals=2480/4607 eff=58.9494% N=400 Z=-373.9(0.00%) \| Like=-363.25..-48.30 [-365.1228..-305.6284] \| it/evals=2520/4677 eff=58.9198% N=400 Z=-365.1(0.00%) \| Like=-353.57..-48.30 [-365.1228..-305.6284] \| it/evals=2560/4731 eff=59.1088% N=400 Z=-354.9(0.00%) \| Like=-343.81..-36.34 [-365.1228..-305.6284] \| it/evals=2600/4785 eff=59.2930% N=400 Z=-353.2(0.00%) \| Like=-342.59..-36.34 [-365.1228..-305.6284] \| it/evals=2610/4809 eff=59.1971% N=400 Z=-347.7(0.00%) \| Like=-337.09..-31.02 [-365.1228..-305.6284] \| it/evals=2640/4848 eff=59.3525% N=400 Z=-339.0(0.00%) \| Like=-327.74..4.51 [-365.1228..-305.6284] \| it/evals=2672/4898 eff=59.4042% N=400 Z=-337.5(0.00%) \| Like=-325.86..4.51 [-365.1228..-305.6284] \| it/evals=2680/4910 eff=59.4235% N=400 Z=-333.4(0.00%) \| Like=-322.27..4.51 [-365.1228..-305.6284] \| it/evals=2700/4942 eff=59.4452% N=400 Z=-329.6(0.00%) \| Like=-318.09..4.51 [-365.1228..-305.6284] \| it/evals=2720/4966 eff=59.5707% N=400 Z=-320.1(0.00%) \| Like=-308.11..5.94 [-365.1228..-305.6284] \| it/evals=2760/5022 eff=59.7144% N=400 Z=-312.9(0.00%) \| Like=-301.47..33.15 [-305.4729..-246.0365] \| it/evals=2790/5068 eff=59.7686% N=400 Z=-310.4(0.00%) \| Like=-298.96..33.15 [-305.4729..-246.0365] \| it/evals=2800/5079 eff=59.8418% N=400 Z=-300.0(0.00%) \| Like=-288.26..33.15 [-305.4729..-246.0365] \| it/evals=2840/5135 eff=59.9789% N=400 Z=-291.1(0.00%) \| Like=-278.53..33.15 [-305.4729..-246.0365] \| it/evals=2880/5200 eff=60.0000% N=400 Z=-282.1(0.00%) \| Like=-270.79..33.15 [-305.4729..-246.0365] \| it/evals=2920/5260 eff=60.0823% N=400 Z=-274.2(0.00%) \| Like=-262.16..33.15 [-305.4729..-246.0365] \| it/evals=2960/5318 eff=60.1871% N=400 Z=-271.6(0.00%) \| Like=-259.39..33.15 [-305.4729..-246.0365] \| it/evals=2970/5335 eff=60.1824% N=400 Z=-265.2(0.00%) \| Like=-252.95..33.15 [-305.4729..-246.0365] \| it/evals=3000/5370 eff=60.3622% N=400 Z=-257.2(0.00%) \| Like=-245.23..33.15 [-246.0052..-181.9655] \| it/evals=3040/5425 eff=60.4975% N=400 Z=-252.8(0.00%) \| Like=-240.18..33.15 [-246.0052..-181.9655] \| it/evals=3060/5455 eff=60.5341% N=400 Z=-248.5(0.00%) \| Like=-236.40..33.15 [-246.0052..-181.9655] \| it/evals=3080/5478 eff=60.6538% N=400 Z=-239.8(0.00%) \| Like=-227.58..33.15 [-246.0052..-181.9655] \| it/evals=3120/5527 eff=60.8543% N=400 Z=-231.7(0.00%) \| Like=-219.05..33.15 [-246.0052..-181.9655] \| it/evals=3160/5583 eff=60.9686% N=400 Z=-222.5(0.00%) \| Like=-209.88..58.38 [-246.0052..-181.9655] \| it/evals=3200/5634 eff=61.1387% N=400 Z=-213.3(0.00%) \| Like=-200.38..76.85 [-246.0052..-181.9655] \| it/evals=3240/5700 eff=61.1321% N=400 Z=-203.3(0.00%) \| Like=-190.75..84.22 [-246.0052..-181.9655] \| it/evals=3280/5757 eff=61.2283% N=400 Z=-193.8(0.00%) \| Like=-180.96..84.22 [-181.6575..-127.1559] \| it/evals=3320/5814 eff=61.3225% N=400 Z=-191.5(0.00%) \| Like=-178.74..84.22 [-181.6575..-127.1559] \| it/evals=3330/5829 eff=61.3373% N=400 Z=-186.1(0.00%) \| Like=-173.36..84.22 [-181.6575..-127.1559] \| it/evals=3360/5861 eff=61.5272% N=400 Z=-176.2(0.00%) \| Like=-162.69..84.22 [-181.6575..-127.1559] \| it/evals=3400/5920 eff=61.5942% N=400 Z=-170.0(0.00%) \| Like=-156.47..84.22 [-181.6575..-127.1559] \| it/evals=3420/5947 eff=61.6549% N=400 Z=-165.8(0.00%) \| Like=-152.80..84.22 [-181.6575..-127.1559] \| it/evals=3440/5969 eff=61.7705% N=400 Z=-156.7(0.00%) \| Like=-143.72..87.91 [-181.6575..-127.1559] \| it/evals=3480/6018 eff=61.9438% N=400 Z=-150.4(0.00%) \| Like=-136.95..87.91 [-181.6575..-127.1559] \| it/evals=3511/6059 eff=62.0428% N=400 Z=-148.9(0.00%) \| Like=-136.08..87.91 [-181.6575..-127.1559] \| it/evals=3520/6071 eff=62.0702% N=400 Z=-141.4(0.00%) \| Like=-128.03..95.46 [-181.6575..-127.1559] \| it/evals=3560/6128 eff=62.1508% N=400 Z=-135.4(0.00%) \| Like=-122.57..95.46 [-127.0824..-76.9703] \| it/evals=3600/6175 eff=62.3377% N=400 Z=-129.3(0.00%) \| Like=-115.62..95.46 [-127.0824..-76.9703] \| it/evals=3640/6234 eff=62.3929% N=400 Z=-122.0(0.00%) \| Like=-108.30..95.46 [-127.0824..-76.9703] \| it/evals=3680/6291 eff=62.4682% N=400 Z=-119.5(0.00%) \| Like=-105.57..95.46 [-127.0824..-76.9703] \| it/evals=3690/6307 eff=62.4683% N=400 Z=-114.5(0.00%) \| Like=-101.14..95.46 [-127.0824..-76.9703] \| it/evals=3720/6341 eff=62.6157% N=400 Z=-107.6(0.00%) \| Like=-92.93..95.46 [-127.0824..-76.9703] \| it/evals=3760/6392 eff=62.7503% N=400 Z=-99.8(0.00%) \| Like=-86.14..95.46 [-127.0824..-76.9703] \| it/evals=3800/6451 eff=62.7995% N=400 Z=-93.9(0.00%) \| Like=-79.78..95.46 [-127.0824..-76.9703] \| it/evals=3840/6504 eff=62.9096% N=400 Z=-87.5(0.00%) \| Like=-73.71..95.46 [-76.8329..-31.0885] \| it/evals=3880/6560 eff=62.9870% N=400 Z=-80.8(0.00%) \| Like=-66.10..95.46 [-76.8329..-31.0885] \| it/evals=3920/6611 eff=63.1138% N=400 Z=-72.7(0.00%) \| Like=-58.43..95.46 [-76.8329..-31.0885] \| it/evals=3960/6681 eff=63.0473% N=400 Z=-64.2(0.00%) \| Like=-50.14..95.46 [-76.8329..-31.0885] \| it/evals=4000/6731 eff=63.1812% N=400 Z=-56.6(0.00%) \| Like=-42.25..95.46 [-76.8329..-31.0885] \| it/evals=4040/6794 eff=63.1842% N=400 Z=-54.5(0.00%) \| Like=-40.26..95.46 [-76.8329..-31.0885] \| it/evals=4050/6809 eff=63.1924% N=400 Z=-50.8(0.00%) \| Like=-36.34..95.46 [-76.8329..-31.0885] \| it/evals=4080/6846 eff=63.2951% N=400 Z=-44.9(0.00%) \| Like=-30.73..97.52 [-31.0687..8.7264] \| it/evals=4120/6898 eff=63.4041% N=400 Z=-42.3(0.00%) \| Like=-27.94..97.52 [-31.0687..8.7264] \| it/evals=4140/6929 eff=63.4094% N=400 Z=-39.9(0.00%) \| Like=-25.81..97.52 [-31.0687..8.7264] \| it/evals=4160/6953 eff=63.4824% N=400 Z=-33.8(0.00%) \| Like=-19.11..97.52 [-31.0687..8.7264] \| it/evals=4200/7000 eff=63.6364% N=400 Z=-28.9(0.00%) \| Like=-13.81..97.81 [-31.0687..8.7264] \| it/evals=4230/7038 eff=63.7240% N=400 Z=-27.2(0.00%) \| Like=-12.10..98.13 [-31.0687..8.7264] \| it/evals=4240/7052 eff=63.7402% N=400 Z=-21.6(0.00%) \| Like=-6.73..98.24 [-31.0687..8.7264] \| it/evals=4280/7099 eff=63.8901% N=400 Z=-15.3(0.00%) \| Like=-0.29..98.24 [-31.0687..8.7264] \| it/evals=4320/7151 eff=63.9905% N=400 Z=-9.3(0.00%) \| Like=5.94..98.24 [-31.0687..8.7264] \| it/evals=4360/7203 eff=64.0894% N=400 Z=-4.0(0.00%) \| Like=11.18..98.24 [8.7436..45.4062] \| it/evals=4400/7263 eff=64.1119% N=400 Z=-2.0(0.00%) \| Like=13.40..98.24 [8.7436..45.4062] \| it/evals=4410/7274 eff=64.1548% N=400 Z=3.0(0.00%) \| Like=18.46..98.24 [8.7436..45.4062] \| it/evals=4440/7311 eff=64.2454% N=400 Z=9.0(0.00%) \| Like=24.23..98.39 [8.7436..45.4062] \| it/evals=4480/7358 eff=64.3863% N=400 Z=12.0(0.00%) \| Like=27.45..98.39 [8.7436..45.4062] \| it/evals=4500/7384 eff=64.4330% N=400 Z=14.7(0.00%) \| Like=30.09..98.39 [8.7436..45.4062] \| it/evals=4520/7409 eff=64.4885% N=400 Z=19.8(0.00%) \| Like=35.70..98.39 [8.7436..45.4062] \| it/evals=4560/7463 eff=64.5618% N=400 Z=23.4(0.00%) \| Like=38.68..98.39 [8.7436..45.4062] \| it/evals=4590/7503 eff=64.6206% N=400 Z=24.5(0.00%) \| Like=39.70..98.39 [8.7436..45.4062] \| it/evals=4600/7515 eff=64.6521% N=400 Z=28.0(0.00%) \| Like=43.51..98.39 [8.7436..45.4062] \| it/evals=4640/7565 eff=64.7592% N=400 Z=32.5(0.00%) \| Like=47.97..98.39 [45.5706..67.5478] \| it/evals=4680/7617 eff=64.8469% N=400 Z=35.7(0.00%) \| Like=51.08..98.39 [45.5706..67.5478] \| it/evals=4720/7668 eff=64.9422% N=400 Z=38.7(0.00%) \| Like=54.16..98.39 [45.5706..67.5478] \| it/evals=4760/7724 eff=64.9918% N=400 Z=39.5(0.00%) \| Like=54.86..98.39 [45.5706..67.5478] \| it/evals=4770/7737 eff=65.0129% N=400 Z=41.9(0.00%) \| Like=57.55..98.39 [45.5706..67.5478] \| it/evals=4800/7777 eff=65.0671% N=400 Z=45.3(0.00%) \| Like=60.71..98.39 [45.5706..67.5478] \| it/evals=4840/7829 eff=65.1501% N=400 Z=46.8(0.00%) \| Like=62.54..98.41 [45.5706..67.5478] \| it/evals=4860/7859 eff=65.1562% N=400 Z=48.3(0.00%) \| Like=63.72..98.41 [45.5706..67.5478] \| it/evals=4880/7881 eff=65.2319% N=400 Z=51.0(0.00%) \| Like=66.65..98.41 [45.5706..67.5478] \| it/evals=4920/7928 eff=65.3560% N=400 Z=52.9(0.00%) \| Like=68.31..98.41 [67.5628..80.8524] \| it/evals=4950/7967 eff=65.4156% N=400 Z=53.4(0.00%) \| Like=69.28..98.41 [67.5628..80.8524] \| it/evals=4960/7977 eff=65.4613% N=400 Z=56.1(0.00%) \| Like=71.64..98.41 [67.5628..80.8524] \| it/evals=5000/8026 eff=65.5652% N=400 Z=57.9(0.00%) \| Like=73.74..98.41 [67.5628..80.8524] \| it/evals=5040/8078 eff=65.6421% N=400 Z=59.9(0.00%) \| Like=75.54..98.41 [67.5628..80.8524] \| it/evals=5080/8129 eff=65.7265% N=400 Z=61.7(0.00%) \| Like=77.34..98.41 [67.5628..80.8524] \| it/evals=5120/8182 eff=65.7929% N=400 Z=63.5(0.00%) \| Like=79.26..98.41 [67.5628..80.8524] \| it/evals=5160/8233 eff=65.8751% N=400 Z=65.1(0.00%) \| Like=80.72..98.41 [67.5628..80.8524] \| it/evals=5200/8291 eff=65.8979% N=400 Z=65.7(0.00%) \| Like=81.30..98.41 [80.8533..89.6445] \| it/evals=5220/8319 eff=65.9174% N=400 Z=66.5(0.00%) \| Like=82.32..98.41 [80.8533..89.6445] \| it/evals=5240/8345 eff=65.9534% N=400 Z=67.9(0.00%) \| Like=83.86..98.41 [80.8533..89.6445] \| it/evals=5280/8395 eff=66.0413% N=400 Z=69.0(0.00%) \| Like=84.73..98.41 [80.8533..89.6445] \| it/evals=5310/8433 eff=66.1023% N=400 Z=69.3(0.00%) \| Like=85.11..98.41 [80.8533..89.6445] \| it/evals=5320/8450 eff=66.0870% N=400 Z=70.5(0.00%) \| Like=86.41..98.41 [80.8533..89.6445] \| it/evals=5360/8501 eff=66.1647% N=400 Z=71.5(0.00%) \| Like=87.38..98.41 [80.8533..89.6445] \| it/evals=5400/8557 eff=66.2008% N=400 Z=72.5(0.00%) \| Like=88.23..98.41 [80.8533..89.6445] \| it/evals=5440/8610 eff=66.2607% N=400 Z=73.3(0.01%) \| Like=89.27..98.41 [80.8533..89.6445] \| it/evals=5480/8661 eff=66.3358% N=400 Z=73.5(0.01%) \| Like=89.47..98.41 [80.8533..89.6445] \| it/evals=5490/8675 eff=66.3444% N=400 Z=74.2(0.02%) \| Like=90.07..98.49 [89.6801..90.9753] \| it/evals=5520/8711 eff=66.4180% N=400 Z=75.0(0.05%) \| Like=90.97..98.49 [89.6801..90.9753] \| it/evals=5560/8765 eff=66.4674% N=400 Z=75.6(0.10%) \| Like=91.55..98.49 [91.5384..91.5501] \| it/evals=5594/8811 eff=66.5081% N=400 Z=75.7(0.11%) \| Like=91.67..98.49 [91.6401..91.6716] \| it/evals=5600/8819 eff=66.5162% N=400 Z=76.4(0.21%) \| Like=92.30..98.49 [92.3017..92.3752] \| it/evals=5640/8867 eff=66.6116% N=400 Z=76.8(0.34%) \| Like=92.77..98.49 [92.7745..92.7789]\| it/evals=5670/8909 eff=66.6353% N=400 Z=77.0(0.39%) \| Like=92.95..98.49 [92.9521..92.9647] \| it/evals=5680/8920 eff=66.6667% N=400 Z=77.5(0.68%) \| Like=93.47..98.49 [93.4513..93.4659] \| it/evals=5720/8968 eff=66.7600% N=400 Z=78.0(1.14%) \| Like=93.92..98.49 [93.9203..93.9340] \| it/evals=5760/9021 eff=66.8136% N=400 Z=78.5(1.76%) \| Like=94.42..98.49 [94.4199..94.4316] \| it/evals=5800/9067 eff=66.9205% N=400 Z=78.9(2.61%) \| Like=94.80..98.49 [94.7710..94.7997] \| it/evals=5840/9118 eff=66.9878% N=400 Z=78.9(2.87%) \| Like=94.86..98.49 [94.8620..94.8792] \| it/evals=5850/9130 eff=67.0103% N=400 Z=79.2(3.71%) \| Like=95.08..98.49 [95.0837..95.0846]\| it/evals=5880/9170 eff=67.0468% N=400 Z=79.5(4.97%) \| Like=95.37..98.49 [95.3544..95.3709] \| it/evals=5920/9221 eff=67.1126% N=400 Z=79.6(5.74%) \| Like=95.52..98.49 [95.5150..95.5168]\| it/evals=5940/9247 eff=67.1414% N=400 Z=79.8(6.59%) \| Like=95.66..98.49 [95.6561..95.6587]\| it/evals=5960/9270 eff=67.1928% N=400 Z=80.0(8.27%) \| Like=95.90..98.49 [95.9000..95.9189] \| it/evals=6000/9317 eff=67.2872% N=400 Z=80.3(10.25%) \| Like=96.11..98.49 [96.1056..96.1110]\| it/evals=6040/9376 eff=67.2906% N=400 Z=80.5(12.48%) \| Like=96.30..98.49 [96.2989..96.3076]\| it/evals=6080/9423 eff=67.3834% N=400 Z=80.6(15.04%) \| Like=96.48..98.49 [96.4812..96.4923] \| it/evals=6120/9479 eff=67.4083% N=400 Z=80.8(17.97%) \| Like=96.69..98.49 [96.6875..96.6906]\| it/evals=6160/9527 eff=67.4921% N=400 Z=81.0(20.93%) \| Like=96.85..98.50 [96.8460..96.8468]\| it/evals=6200/9586 eff=67.4940% N=400 Z=81.0(21.78%) \| Like=96.89..98.50 [96.8851..96.8930]\| it/evals=6210/9596 eff=67.5294% N=400 Z=81.1(24.15%) \| Like=97.00..98.50 [96.9983..96.9996]\| it/evals=6240/9636 eff=67.5617% N=400 Z=81.2(27.57%) \| Like=97.13..98.50 [97.1322..97.1413]\| it/evals=6280/9694 eff=67.5705% N=400 Z=81.3(29.36%) \| Like=97.20..98.50 [97.1952..97.1957]\| it/evals=6300/9717 eff=67.6183% N=400 Z=81.3(31.00%) \| Like=97.27..98.50 [97.2717..97.2766]\| it/evals=6320/9741 eff=67.6587% N=400 Z=81.5(34.66%) \| Like=97.39..98.50 [97.3944..97.3960]\| it/evals=6360/9796 eff=67.6884% N=400 Z=81.5(37.34%) \| Like=97.49..98.50 [97.4946..97.4947]\| it/evals=6390/9846 eff=67.6477% N=400 Z=81.6(38.27%) \| Like=97.51..98.50 [97.5113..97.5147]\| it/evals=6400/9859 eff=67.6604% N=400 Z=81.6(42.06%) \| Like=97.59..98.50 [97.5888..97.5898]\| it/evals=6440/9911 eff=67.7111% N=400 Z=81.7(45.73%) \| Like=97.67..98.50 [97.6705..97.6731]\| it/evals=6480/9962 eff=67.7682% N=400 Z=81.8(49.08%) \| Like=97.76..98.50 [97.7636..97.7671]*\| it/evals=6520/10008 eff=67.8601% N=400 [ultranest] Explored until L=1e+02 [ultranest] Likelihood function evaluations: 10026 [ultranest] logZ = 82.54 +- 0.1468 [ultranest] Effective samples strategy satisfied (ESS = 989.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.43, need <0.5) [ultranest] logZ error budget: single: 0.19 bs:0.15 tail:0.41 total:0.43 required:<0.50 [ultranest] done iterating. logZ = 82.511 +- 0.480 single instance: logZ = 82.511 +- 0.193 bootstrapped : logZ = 82.536 +- 0.257 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations mean : 41.9474│ ▁ ▁▁▁▁▁▁▁▁▁▁▂▃▃▄▆▅▆▇▆▅▆▅▅▄▄▂▂▁▁▁▁▁▁▁▁ │42.0252 41.9896 +- 0.0093 scatter : 0.0684│ ▁▁▁▁▁▁▂▂▃▄▆▆▆▆▇▅▅▅▄▃▃▂▂▁▁▁▁▁▁▁▁▁▁▁ ▁ │0.1256 0.0911 +- 0.0068 RECYCLING: ref: {'niter': 6931, 'logz': 82.51126797630579, 'logzerr': 0.48000210459420994, 'logz_bs': 82.53603482383392, 'logz_single': 82.51126797630579, 'logzerr_tail': 0.40526526018403786, 'logzerr_bs': 0.2572199240005233, 'ess': 989.4418387883029, 'H': 14.904885613395052, 'Herr': 0.14344533438670065, 'posterior': {'mean': [41.98963561307596, 0.09112288330816437], 'stdev': [0.009349186585804043, 0.006775975213110563], 'median': [41.98941172473769, 0.0906763001145217], 'errlo': [41.98058131149014, 0.08469946646382202], 'errup': [41.999107688907316, 0.09767389448562613], 'information_gain_bits': [4.14647919764959, 3.592890199934908]}, 'weighted_samples': {'upoints': array([[9.75177245e-01, 8.77828782e-04], [8.18524108e-02, 2.44479339e-03], [9.88480171e-02, 2.02700325e-02], ..., [5.20995235e-01, 2.39361007e-01], [5.20995032e-01, 2.39712725e-01], [5.20995165e-01, 2.39004262e-01]]), 'points': array([[ 9.50354489e+02, 1.00811787e-02], [-8.36295178e+02, 1.02277281e-02], [-8.02303966e+02, 1.20525830e-02], ..., [ 4.19904702e+01, 9.06659110e-02], [ 4.19900633e+01, 9.09600940e-02], [ 4.19903302e+01, 9.03684948e-02]]), 'weights': array([0. , 0. , 0. , ..., 0.00177121, 0.00177125, 0.00177555]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -22.31896455, -22.31896455, -22.31896455]), 'bootstrapped_weights': array([[0. , 0. , 0. , ..., 0. , 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0. , 0. ], ..., [0. , 0.00274031, 0.00279516, ..., 0.00293349, 0.00267692, 0. ], [0.00273848, 0.00274037, 0.00279522, ..., 0.00293356, 0.00267697, 0. ], [0.00274512, 0. , 0.002802 , ..., 0. , 0.00268347, 0.0026264 ]]), 'logl': array([-4.05945790e+11, -3.68707854e+11, -2.45356023e+11, ..., 9.84941424e+01, 9.84941642e+01, 9.84965862e+01])}, 'samples': array([[42.00291904, 0.09197281], [41.9775074 , 0.08824589], [42.00658608, 0.08615179], ..., [42.00145679, 0.10275319], [41.98672294, 0.09255127], [41.98355338, 0.08669633]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': [0.5209951650817852, 0.23900426211224726]}, 'ncall': 10026, 'paramnames': ['mean', 'scatter'], 'logzerr_single': 0.19303423021186586, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} skipping 15 weights: [0. 0. 0. ... 0.99755914 0.9975809 1. ] rec: {'ncall': 2048, 'niter': 6931, 'logz': 82.51126797630566, 'logzerr': 0.4800022347771922, 'ess': 989.4418387882997, 'posterior': {'mean': [41.98968202356687, 0.09114676119272457], 'stdev': [0.009297326255806548, 0.006793819118296698], 'median': [41.98947238149481, 0.09068695842395716], 'errlo': [41.98062812212561, 0.08466827339953377], 'errup': [41.999107688907316, 0.09770985563634536], 'information_gain_bits': [nan, 3.6621734305941214]}, 'weighted_samples': {'upoints': array([[9.75177245e-01, 8.77828782e-04], [8.18524108e-02, 2.44479339e-03], [9.88480171e-02, 2.02700325e-02], ..., [5.20995235e-01, 2.39361007e-01], [5.20995032e-01, 2.39712725e-01], [5.20995165e-01, 2.39004262e-01]]), 'points': array([[ 9.50354489e+02, 1.00811787e-02], [-8.36295178e+02, 1.02277281e-02], [-8.02303966e+02, 1.20525830e-02], ..., [ 4.19904702e+01, 9.06659110e-02], [ 4.19900633e+01, 9.09600940e-02], [ 4.19903302e+01, 9.03684948e-02]]), 'weights': array([0. , 0. , 0. , ..., 0.00177121, 0.00177125, 0.00177555]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -22.31896455, -22.31896455, -22.31896455]), 'logl': array([ -inf, -inf, -inf, ..., 98.49414236, 98.49416417, 98.4965862 ])}, 'samples': array([[41.99261818, 0.08729851], [41.99664389, 0.08319908], [41.97824608, 0.08718514], ..., [41.99975046, 0.10227979], [42.00241764, 0.08860842], [41.97018642, 0.08833478]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': [0.5209951650817852, 0.23900426211224726]}, 'param_names': ['mean', 'scatter']} weights: [0.34167524 0.36965396 0.11394021 ... 0.11309269 0.90291318 0.65861225] rec2: {'ncall': 6931, 'niter': 6931, 'logz': 97.76985434512109, 'logzerr': 8.570688762427586e-05, 'ess': 5123.234668254743, 'posterior': {'mean': [41.989673533632136, 0.09059357409028677], 'stdev': [0.006543754165026486, 0.004596090599814409], 'median': [41.98941172473769, 0.09050115057035493], 'errlo': [41.983044750694944, 0.08599162931708715], 'errup': [41.996458031426755, 0.0952836649169508], 'information_gain_bits': [nan, 3.8393471248186173]}, 'weighted_samples': {'upoints': None, 'points': array([[42.00291904, 0.09197281], [41.9775074 , 0.08824589], [42.00658608, 0.08615179], ..., [42.00145679, 0.10275319], [41.98672294, 0.09255127], [41.98355338, 0.08669633]]), 'weights': array([1.01960801e-04, 1.10310053e-04, 3.40013973e-05, ..., 3.37484848e-05, 2.69442269e-04, 1.96539361e-04]), 'logw': array([-8.84375938, -8.84375938, -8.84375938, ..., -8.84375938, -8.84375938, -8.84375938]), 'logl': array([97.42269161, 97.50139824, 96.32450479, ..., 96.31703869, 98.39445732, 98.07896589])}, 'samples': array([[41.99542553, 0.09237804], [41.97980873, 0.09237831], [41.99767108, 0.09574967], ..., [41.9977458 , 0.09371036], [41.99336497, 0.09418241], [41.98304951, 0.09079366]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': None}, 'param_names': ['mean', 'scatter']} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+1, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=77.54, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=23, ncalls=425, regioncalls=1000, ndraw=40, logz=86.13, remainder_fraction=99.9998%, Lmin=90.62, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=88.39, remainder_fraction=99.9981%, Lmin=91.98, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=62, ncalls=469, regioncalls=2760, ndraw=40, logz=89.78, remainder_fraction=99.9922%, Lmin=93.05, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=491, regioncalls=3640, ndraw=40, logz=90.68, remainder_fraction=99.9808%, Lmin=93.90, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=506, regioncalls=4240, ndraw=40, logz=91.16, remainder_fraction=99.9690%, Lmin=94.28, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=529, regioncalls=5200, ndraw=40, logz=91.98, remainder_fraction=99.9309%, Lmin=94.90, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=540, regioncalls=5640, ndraw=40, logz=92.30, remainder_fraction=99.9044%, Lmin=95.13, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=134, ncalls=558, regioncalls=6360, ndraw=40, logz=92.73, remainder_fraction=99.8517%, Lmin=95.50, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=587, regioncalls=7520, ndraw=40, logz=93.45, remainder_fraction=99.6886%, Lmin=96.16, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=610, regioncalls=8480, ndraw=40, logz=93.91, remainder_fraction=99.5043%, Lmin=96.58, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=631, regioncalls=9320, ndraw=40, logz=94.33, remainder_fraction=99.2526%, Lmin=96.86, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=226, ncalls=661, regioncalls=10520, ndraw=40, logz=94.78, remainder_fraction=98.8330%, Lmin=97.18, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=676, regioncalls=11120, ndraw=40, logz=94.99, remainder_fraction=98.5635%, Lmin=97.36, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=259, ncalls=698, regioncalls=12000, ndraw=40, logz=95.26, remainder_fraction=98.0959%, Lmin=97.63, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=712, regioncalls=12560, ndraw=40, logz=95.41, remainder_fraction=97.7997%, Lmin=97.76, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=725, regioncalls=13120, ndraw=40, logz=95.54, remainder_fraction=97.4838%, Lmin=97.83, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=305, ncalls=768, regioncalls=14840, ndraw=40, logz=95.83, remainder_fraction=96.6564%, Lmin=98.09, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=786, regioncalls=15560, ndraw=40, logz=95.99, remainder_fraction=96.0244%, Lmin=98.18, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=337, ncalls=807, regioncalls=16400, ndraw=40, logz=96.15, remainder_fraction=95.3175%, Lmin=98.28, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=833, regioncalls=17480, ndraw=40, logz=96.35, remainder_fraction=94.2789%, Lmin=98.49, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=862, regioncalls=18680, ndraw=40, logz=96.55, remainder_fraction=93.0074%, Lmin=98.67, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=883, regioncalls=19520, ndraw=40, logz=96.67, remainder_fraction=92.0986%, Lmin=98.73, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=439, ncalls=926, regioncalls=21240, ndraw=40, logz=96.94, remainder_fraction=89.5267%, Lmin=99.00, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=927, regioncalls=21280, ndraw=40, logz=96.95, remainder_fraction=89.4688%, Lmin=99.00, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=942, regioncalls=21880, ndraw=40, logz=97.01, remainder_fraction=88.8368%, Lmin=99.05, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=472, ncalls=968, regioncalls=22920, ndraw=40, logz=97.14, remainder_fraction=87.3079%, Lmin=99.17, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=977, regioncalls=23280, ndraw=40, logz=97.19, remainder_fraction=86.8106%, Lmin=99.20, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1024, regioncalls=25160, ndraw=40, logz=97.39, remainder_fraction=83.7818%, Lmin=99.35, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1051, regioncalls=26240, ndraw=40, logz=97.49, remainder_fraction=82.2832%, Lmin=99.42, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1072, regioncalls=27080, ndraw=40, logz=97.57, remainder_fraction=80.7011%, Lmin=99.52, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=578, ncalls=1092, regioncalls=27920, ndraw=40, logz=97.65, remainder_fraction=79.2556%, Lmin=99.57, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1118, regioncalls=28960, ndraw=40, logz=97.73, remainder_fraction=77.3810%, Lmin=99.64, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1160, regioncalls=30640, ndraw=40, logz=97.84, remainder_fraction=74.7842%, Lmin=99.74, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1170, regioncalls=31040, ndraw=40, logz=97.87, remainder_fraction=73.8575%, Lmin=99.76, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=673, ncalls=1212, regioncalls=32760, ndraw=40, logz=97.98, remainder_fraction=71.0287%, Lmin=99.86, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1219, regioncalls=33040, ndraw=40, logz=98.00, remainder_fraction=70.4083%, Lmin=99.88, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=715, ncalls=1260, regioncalls=34720, ndraw=40, logz=98.10, remainder_fraction=67.2304%, Lmin=99.96, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1267, regioncalls=35040, ndraw=40, logz=98.11, remainder_fraction=66.7902%, Lmin=99.96, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=1296, regioncalls=36280, ndraw=40, logz=98.16, remainder_fraction=65.0817%, Lmin=100.02, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1322, regioncalls=37320, ndraw=40, logz=98.21, remainder_fraction=63.3310%, Lmin=100.08, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=793, ncalls=1358, regioncalls=38800, ndraw=40, logz=98.29, remainder_fraction=60.4678%, Lmin=100.16, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1367, regioncalls=39200, ndraw=40, logz=98.31, remainder_fraction=59.7909%, Lmin=100.18, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1380, regioncalls=39720, ndraw=40, logz=98.33, remainder_fraction=58.8978%, Lmin=100.20, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=835, ncalls=1413, regioncalls=41080, ndraw=40, logz=98.38, remainder_fraction=56.7301%, Lmin=100.27, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1418, regioncalls=41280, ndraw=40, logz=98.39, remainder_fraction=56.3332%, Lmin=100.28, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=879, ncalls=1472, regioncalls=43560, ndraw=40, logz=98.47, remainder_fraction=52.7721%, Lmin=100.37, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1473, regioncalls=43600, ndraw=40, logz=98.47, remainder_fraction=52.6823%, Lmin=100.37, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1496, regioncalls=44520, ndraw=40, logz=98.50, remainder_fraction=50.9723%, Lmin=100.42, Lmax=101.12 INFO ultranest:integrator.py:2654 Explored until L=1e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 1508 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 99.21 +- 0.03825 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 972.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.41, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.05 bs:0.04 tail:0.41 total:0.41 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-405945789829.58, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=-14543780120.47, remainder_fraction=100.0000%, Lmin=-14330281204.24, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=488, regioncalls=3520, ndraw=40, logz=-2695832923.91, remainder_fraction=100.0000%, Lmin=-2578922208.45, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=531, regioncalls=5240, ndraw=40, logz=-621093047.40, remainder_fraction=100.0000%, Lmin=-588559621.47, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=576, regioncalls=7040, ndraw=40, logz=-179312911.40, remainder_fraction=100.0000%, Lmin=-175123183.83, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=627, regioncalls=9080, ndraw=40, logz=-37629480.84, remainder_fraction=100.0000%, Lmin=-37019184.92, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=671, regioncalls=10840, ndraw=40, logz=-12066612.49, remainder_fraction=100.0000%, Lmin=-11773456.96, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=708, regioncalls=12320, ndraw=40, logz=-5121052.97, remainder_fraction=100.0000%, Lmin=-5026605.32, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=720, regioncalls=12800, ndraw=40, logz=-4239114.89, remainder_fraction=100.0000%, Lmin=-4218156.66, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=772, regioncalls=14880, ndraw=40, logz=-2131925.19, remainder_fraction=100.0000%, Lmin=-2080057.46, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=818, regioncalls=16720, ndraw=40, logz=-1014637.58, remainder_fraction=100.0000%, Lmin=-964900.30, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=876, regioncalls=19040, ndraw=40, logz=-541870.28, remainder_fraction=100.0000%, Lmin=-535492.84, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=927, regioncalls=21080, ndraw=40, logz=-300783.39, remainder_fraction=100.0000%, Lmin=-295422.19, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=939, regioncalls=21560, ndraw=40, logz=-255114.89, remainder_fraction=100.0000%, Lmin=-251465.12, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=974, regioncalls=22960, ndraw=40, logz=-151349.49, remainder_fraction=100.0000%, Lmin=-150202.02, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1028, regioncalls=25120, ndraw=40, logz=-99997.74, remainder_fraction=100.0000%, Lmin=-98049.75, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1081, regioncalls=27240, ndraw=40, logz=-65129.44, remainder_fraction=100.0000%, Lmin=-65004.43, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1149, regioncalls=29960, ndraw=40, logz=-40261.62, remainder_fraction=100.0000%, Lmin=-40093.67, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=639, ncalls=1209, regioncalls=32360, ndraw=40, logz=-29839.79, remainder_fraction=100.0000%, Lmin=-29468.85, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1212, regioncalls=32480, ndraw=40, logz=-29476.44, remainder_fraction=100.0000%, Lmin=-28904.97, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1275, regioncalls=35000, ndraw=40, logz=-21665.40, remainder_fraction=100.0000%, Lmin=-21630.82, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1338, regioncalls=37520, ndraw=40, logz=-15756.30, remainder_fraction=100.0000%, Lmin=-15544.83, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=751, ncalls=1389, regioncalls=39560, ndraw=40, logz=-12939.33, remainder_fraction=100.0000%, Lmin=-12872.54, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1402, regioncalls=40080, ndraw=40, logz=-12015.41, remainder_fraction=100.0000%, Lmin=-12002.51, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1488, regioncalls=43520, ndraw=40, logz=-9473.37, remainder_fraction=100.0000%, Lmin=-9362.21, Lmax=-276.64 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([393, 6, 1])) DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1571, regioncalls=46840, ndraw=40, logz=-7725.36, remainder_fraction=100.0000%, Lmin=-7665.90, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1684, regioncalls=51360, ndraw=40, logz=-6168.48, remainder_fraction=100.0000%, Lmin=-6136.23, Lmax=-276.64 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([396, 1, 3])) DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1775, regioncalls=55000, ndraw=40, logz=-4952.17, remainder_fraction=100.0000%, Lmin=-4935.58, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1860, regioncalls=58400, ndraw=40, logz=-4041.29, remainder_fraction=100.0000%, Lmin=-4003.76, Lmax=-249.74 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([397, 1, 2])) DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1957, regioncalls=62280, ndraw=40, logz=-3517.98, remainder_fraction=100.0000%, Lmin=-3509.78, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=2051, regioncalls=66040, ndraw=40, logz=-2883.66, remainder_fraction=100.0000%, Lmin=-2816.71, Lmax=-249.74 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([397, 1, 2])) DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=2171, regioncalls=70840, ndraw=40, logz=-2411.47, remainder_fraction=100.0000%, Lmin=-2394.29, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=2298, regioncalls=75920, ndraw=40, logz=-2097.08, remainder_fraction=100.0000%, Lmin=-2076.89, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=2387, regioncalls=79480, ndraw=40, logz=-1817.46, remainder_fraction=100.0000%, Lmin=-1804.91, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=2406, regioncalls=80240, ndraw=40, logz=-1783.64, remainder_fraction=100.0000%, Lmin=-1754.08, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2475, regioncalls=83080, ndraw=40, logz=-1566.13, remainder_fraction=100.0000%, Lmin=-1555.97, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2557, regioncalls=86360, ndraw=40, logz=-1401.30, remainder_fraction=100.0000%, Lmin=-1389.84, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2604, regioncalls=88240, ndraw=40, logz=-1337.91, remainder_fraction=100.0000%, Lmin=-1324.13, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2643, regioncalls=89800, ndraw=40, logz=-1276.87, remainder_fraction=100.0000%, Lmin=-1266.90, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2726, regioncalls=93160, ndraw=40, logz=-1120.19, remainder_fraction=100.0000%, Lmin=-1110.35, Lmax=-241.79 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2781, regioncalls=95360, ndraw=40, logz=-1014.13, remainder_fraction=100.0000%, Lmin=-1001.54, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2795, regioncalls=95960, ndraw=40, logz=-996.61, remainder_fraction=100.0000%, Lmin=-984.22, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2872, regioncalls=99040, ndraw=40, logz=-915.47, remainder_fraction=100.0000%, Lmin=-904.91, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2938, regioncalls=101680, ndraw=40, logz=-835.37, remainder_fraction=100.0000%, Lmin=-820.73, Lmax=-176.99 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=3019, regioncalls=105000, ndraw=40, logz=-743.56, remainder_fraction=100.0000%, Lmin=-733.85, Lmax=-176.99 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=3102, regioncalls=108320, ndraw=40, logz=-699.33, remainder_fraction=100.0000%, Lmin=-684.33, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3126, regioncalls=109320, ndraw=40, logz=-686.79, remainder_fraction=100.0000%, Lmin=-676.46, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=3173, regioncalls=111200, ndraw=40, logz=-654.22, remainder_fraction=100.0000%, Lmin=-643.23, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=3244, regioncalls=114040, ndraw=40, logz=-625.35, remainder_fraction=100.0000%, Lmin=-615.39, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=3278, regioncalls=115400, ndraw=40, logz=-611.42, remainder_fraction=100.0000%, Lmin=-601.50, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=3314, regioncalls=116920, ndraw=40, logz=-595.00, remainder_fraction=100.0000%, Lmin=-585.36, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=3370, regioncalls=119160, ndraw=40, logz=-574.51, remainder_fraction=100.0000%, Lmin=-565.11, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=3421, regioncalls=121240, ndraw=40, logz=-564.24, remainder_fraction=100.0000%, Lmin=-555.02, Lmax=-87.70 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=3435, regioncalls=121800, ndraw=40, logz=-561.71, remainder_fraction=100.0000%, Lmin=-552.59, Lmax=-87.70 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=3501, regioncalls=124480, ndraw=40, logz=-552.18, remainder_fraction=100.0000%, Lmin=-543.29, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=3566, regioncalls=127160, ndraw=40, logz=-542.89, remainder_fraction=100.0000%, Lmin=-533.87, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=3633, regioncalls=129960, ndraw=40, logz=-533.59, remainder_fraction=100.0000%, Lmin=-524.21, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=3703, regioncalls=132880, ndraw=40, logz=-526.06, remainder_fraction=100.0000%, Lmin=-516.45, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=3716, regioncalls=133480, ndraw=40, logz=-523.48, remainder_fraction=100.0000%, Lmin=-514.33, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3752, regioncalls=135040, ndraw=40, logz=-514.54, remainder_fraction=100.0000%, Lmin=-504.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3812, regioncalls=137480, ndraw=40, logz=-503.35, remainder_fraction=100.0000%, Lmin=-493.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3839, regioncalls=138600, ndraw=40, logz=-497.65, remainder_fraction=100.0000%, Lmin=-487.69, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3869, regioncalls=140000, ndraw=40, logz=-492.38, remainder_fraction=100.0000%, Lmin=-482.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3916, regioncalls=141960, ndraw=40, logz=-481.86, remainder_fraction=100.0000%, Lmin=-471.51, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3958, regioncalls=143760, ndraw=40, logz=-471.49, remainder_fraction=100.0000%, Lmin=-461.58, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3974, regioncalls=144400, ndraw=40, logz=-467.59, remainder_fraction=100.0000%, Lmin=-457.50, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=4041, regioncalls=147160, ndraw=40, logz=-460.25, remainder_fraction=100.0000%, Lmin=-450.50, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=4093, regioncalls=149440, ndraw=40, logz=-451.28, remainder_fraction=100.0000%, Lmin=-441.42, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=4159, regioncalls=152360, ndraw=40, logz=-442.09, remainder_fraction=100.0000%, Lmin=-431.97, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=4224, regioncalls=155080, ndraw=40, logz=-432.78, remainder_fraction=100.0000%, Lmin=-422.44, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2260, ncalls=4266, regioncalls=156800, ndraw=40, logz=-428.15, remainder_fraction=100.0000%, Lmin=-417.97, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=4292, regioncalls=157880, ndraw=40, logz=-424.47, remainder_fraction=100.0000%, Lmin=-413.65, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=4344, regioncalls=160120, ndraw=40, logz=-416.64, remainder_fraction=100.0000%, Lmin=-405.68, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2344, ncalls=4389, regioncalls=161960, ndraw=40, logz=-411.42, remainder_fraction=100.0000%, Lmin=-400.86, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=4411, regioncalls=162960, ndraw=40, logz=-408.18, remainder_fraction=100.0000%, Lmin=-397.87, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=4465, regioncalls=165200, ndraw=40, logz=-400.01, remainder_fraction=100.0000%, Lmin=-389.40, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=4518, regioncalls=167680, ndraw=40, logz=-394.00, remainder_fraction=100.0000%, Lmin=-383.71, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=4533, regioncalls=168280, ndraw=40, logz=-392.25, remainder_fraction=100.0000%, Lmin=-381.40, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=4607, regioncalls=171320, ndraw=40, logz=-383.10, remainder_fraction=100.0000%, Lmin=-372.99, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=4677, regioncalls=174320, ndraw=40, logz=-373.88, remainder_fraction=100.0000%, Lmin=-363.25, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=4731, regioncalls=176640, ndraw=40, logz=-365.06, remainder_fraction=100.0000%, Lmin=-353.57, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=4785, regioncalls=178960, ndraw=40, logz=-354.85, remainder_fraction=100.0000%, Lmin=-343.81, Lmax=-36.34 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=4809, regioncalls=180000, ndraw=40, logz=-353.22, remainder_fraction=100.0000%, Lmin=-342.59, Lmax=-36.34 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4848, regioncalls=181760, ndraw=40, logz=-347.69, remainder_fraction=100.0000%, Lmin=-337.09, Lmax=-31.02 DEBUG ultranest:integrator.py:2610 iteration=2672, ncalls=4898, regioncalls=183840, ndraw=40, logz=-339.03, remainder_fraction=100.0000%, Lmin=-327.74, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4910, regioncalls=184320, ndraw=40, logz=-337.47, remainder_fraction=100.0000%, Lmin=-325.86, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=4942, regioncalls=185720, ndraw=40, logz=-333.44, remainder_fraction=100.0000%, Lmin=-322.27, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4966, regioncalls=186840, ndraw=40, logz=-329.57, remainder_fraction=100.0000%, Lmin=-318.09, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=5022, regioncalls=189240, ndraw=40, logz=-320.11, remainder_fraction=100.0000%, Lmin=-308.11, Lmax=5.94 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=5068, regioncalls=191160, ndraw=40, logz=-312.88, remainder_fraction=100.0000%, Lmin=-301.47, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5079, regioncalls=191640, ndraw=40, logz=-310.36, remainder_fraction=100.0000%, Lmin=-298.96, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=5135, regioncalls=193920, ndraw=40, logz=-299.95, remainder_fraction=100.0000%, Lmin=-288.26, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=5200, regioncalls=196560, ndraw=40, logz=-291.14, remainder_fraction=100.0000%, Lmin=-278.53, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=5260, regioncalls=199040, ndraw=40, logz=-282.12, remainder_fraction=100.0000%, Lmin=-270.79, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=5318, regioncalls=201400, ndraw=40, logz=-274.21, remainder_fraction=100.0000%, Lmin=-262.16, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=5335, regioncalls=202120, ndraw=40, logz=-271.64, remainder_fraction=100.0000%, Lmin=-259.39, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=5370, regioncalls=203640, ndraw=40, logz=-265.19, remainder_fraction=100.0000%, Lmin=-252.95, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=5425, regioncalls=205960, ndraw=40, logz=-257.20, remainder_fraction=100.0000%, Lmin=-245.23, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=5455, regioncalls=207280, ndraw=40, logz=-252.78, remainder_fraction=100.0000%, Lmin=-240.18, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=5478, regioncalls=208320, ndraw=40, logz=-248.52, remainder_fraction=100.0000%, Lmin=-236.40, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=5527, regioncalls=210400, ndraw=40, logz=-239.80, remainder_fraction=100.0000%, Lmin=-227.58, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=5583, regioncalls=212760, ndraw=40, logz=-231.74, remainder_fraction=100.0000%, Lmin=-219.05, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=5634, regioncalls=214840, ndraw=40, logz=-222.54, remainder_fraction=100.0000%, Lmin=-209.88, Lmax=58.38 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=5700, regioncalls=217560, ndraw=40, logz=-213.29, remainder_fraction=100.0000%, Lmin=-200.38, Lmax=76.85 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=5757, regioncalls=219920, ndraw=40, logz=-203.34, remainder_fraction=100.0000%, Lmin=-190.75, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=5814, regioncalls=222280, ndraw=40, logz=-193.80, remainder_fraction=100.0000%, Lmin=-180.96, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5829, regioncalls=222920, ndraw=40, logz=-191.46, remainder_fraction=100.0000%, Lmin=-178.74, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5861, regioncalls=224280, ndraw=40, logz=-186.10, remainder_fraction=100.0000%, Lmin=-173.36, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5920, regioncalls=226680, ndraw=40, logz=-176.23, remainder_fraction=100.0000%, Lmin=-162.69, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=5947, regioncalls=227800, ndraw=40, logz=-170.03, remainder_fraction=100.0000%, Lmin=-156.47, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5969, regioncalls=228920, ndraw=40, logz=-165.77, remainder_fraction=100.0000%, Lmin=-152.80, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=6018, regioncalls=230920, ndraw=40, logz=-156.66, remainder_fraction=100.0000%, Lmin=-143.72, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3511, ncalls=6059, regioncalls=232560, ndraw=40, logz=-150.40, remainder_fraction=100.0000%, Lmin=-136.95, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=6071, regioncalls=233040, ndraw=40, logz=-148.90, remainder_fraction=100.0000%, Lmin=-136.08, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=6128, regioncalls=235440, ndraw=40, logz=-141.40, remainder_fraction=100.0000%, Lmin=-128.03, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=6175, regioncalls=237400, ndraw=40, logz=-135.44, remainder_fraction=100.0000%, Lmin=-122.57, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=6234, regioncalls=239920, ndraw=40, logz=-129.28, remainder_fraction=100.0000%, Lmin=-115.62, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=6291, regioncalls=242280, ndraw=40, logz=-121.98, remainder_fraction=100.0000%, Lmin=-108.30, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=6307, regioncalls=243000, ndraw=40, logz=-119.49, remainder_fraction=100.0000%, Lmin=-105.57, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=6341, regioncalls=244600, ndraw=40, logz=-114.52, remainder_fraction=100.0000%, Lmin=-101.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=6392, regioncalls=246680, ndraw=40, logz=-107.63, remainder_fraction=100.0000%, Lmin=-92.93, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=6451, regioncalls=249240, ndraw=40, logz=-99.84, remainder_fraction=100.0000%, Lmin=-86.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=6504, regioncalls=251600, ndraw=40, logz=-93.94, remainder_fraction=100.0000%, Lmin=-79.78, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=6560, regioncalls=253920, ndraw=40, logz=-87.53, remainder_fraction=100.0000%, Lmin=-73.71, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=6611, regioncalls=256040, ndraw=40, logz=-80.84, remainder_fraction=100.0000%, Lmin=-66.10, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=6681, regioncalls=258920, ndraw=40, logz=-72.71, remainder_fraction=100.0000%, Lmin=-58.43, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=6731, regioncalls=261160, ndraw=40, logz=-64.17, remainder_fraction=100.0000%, Lmin=-50.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=6794, regioncalls=264040, ndraw=40, logz=-56.55, remainder_fraction=100.0000%, Lmin=-42.25, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=6809, regioncalls=264760, ndraw=40, logz=-54.51, remainder_fraction=100.0000%, Lmin=-40.26, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=6846, regioncalls=266360, ndraw=40, logz=-50.77, remainder_fraction=100.0000%, Lmin=-36.34, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=6898, regioncalls=268640, ndraw=40, logz=-44.92, remainder_fraction=100.0000%, Lmin=-30.73, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=6929, regioncalls=270040, ndraw=40, logz=-42.30, remainder_fraction=100.0000%, Lmin=-27.94, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=6953, regioncalls=271000, ndraw=40, logz=-39.90, remainder_fraction=100.0000%, Lmin=-25.81, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=7000, regioncalls=272920, ndraw=40, logz=-33.76, remainder_fraction=100.0000%, Lmin=-19.11, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4230, ncalls=7038, regioncalls=274560, ndraw=40, logz=-28.94, remainder_fraction=100.0000%, Lmin=-13.81, Lmax=97.81 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=7052, regioncalls=275160, ndraw=40, logz=-27.24, remainder_fraction=100.0000%, Lmin=-12.10, Lmax=98.13 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=7099, regioncalls=277080, ndraw=40, logz=-21.58, remainder_fraction=100.0000%, Lmin=-6.73, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=7151, regioncalls=279240, ndraw=40, logz=-15.35, remainder_fraction=100.0000%, Lmin=-0.29, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=7203, regioncalls=281360, ndraw=40, logz=-9.28, remainder_fraction=100.0000%, Lmin=5.94, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=7263, regioncalls=283840, ndraw=40, logz=-3.98, remainder_fraction=100.0000%, Lmin=11.18, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4410, ncalls=7274, regioncalls=284360, ndraw=40, logz=-2.04, remainder_fraction=100.0000%, Lmin=13.40, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=7311, regioncalls=285880, ndraw=40, logz=3.00, remainder_fraction=100.0000%, Lmin=18.46, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=7358, regioncalls=287760, ndraw=40, logz=8.96, remainder_fraction=100.0000%, Lmin=24.23, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=7384, regioncalls=288920, ndraw=40, logz=11.95, remainder_fraction=100.0000%, Lmin=27.45, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=7409, regioncalls=290000, ndraw=40, logz=14.74, remainder_fraction=100.0000%, Lmin=30.09, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=7463, regioncalls=292240, ndraw=40, logz=19.80, remainder_fraction=100.0000%, Lmin=35.70, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=7503, regioncalls=293880, ndraw=40, logz=23.43, remainder_fraction=100.0000%, Lmin=38.68, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=7515, regioncalls=294360, ndraw=40, logz=24.45, remainder_fraction=100.0000%, Lmin=39.70, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=7565, regioncalls=296400, ndraw=40, logz=28.05, remainder_fraction=100.0000%, Lmin=43.51, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=7617, regioncalls=298480, ndraw=40, logz=32.49, remainder_fraction=100.0000%, Lmin=47.97, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=7668, regioncalls=300600, ndraw=40, logz=35.71, remainder_fraction=100.0000%, Lmin=51.08, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=7724, regioncalls=302880, ndraw=40, logz=38.70, remainder_fraction=100.0000%, Lmin=54.16, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=7737, regioncalls=303480, ndraw=40, logz=39.50, remainder_fraction=100.0000%, Lmin=54.86, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=7777, regioncalls=305360, ndraw=40, logz=41.88, remainder_fraction=100.0000%, Lmin=57.55, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=7829, regioncalls=307480, ndraw=40, logz=45.28, remainder_fraction=100.0000%, Lmin=60.71, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=7859, regioncalls=308760, ndraw=40, logz=46.79, remainder_fraction=100.0000%, Lmin=62.54, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=7881, regioncalls=309640, ndraw=40, logz=48.27, remainder_fraction=100.0000%, Lmin=63.72, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=7928, regioncalls=311600, ndraw=40, logz=51.04, remainder_fraction=100.0000%, Lmin=66.65, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=7967, regioncalls=313240, ndraw=40, logz=52.87, remainder_fraction=100.0000%, Lmin=68.31, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=7977, regioncalls=313640, ndraw=40, logz=53.45, remainder_fraction=100.0000%, Lmin=69.28, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=8026, regioncalls=315640, ndraw=40, logz=56.08, remainder_fraction=100.0000%, Lmin=71.64, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=8078, regioncalls=317840, ndraw=40, logz=57.95, remainder_fraction=100.0000%, Lmin=73.74, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=8129, regioncalls=319880, ndraw=40, logz=59.93, remainder_fraction=100.0000%, Lmin=75.54, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=8182, regioncalls=322000, ndraw=40, logz=61.74, remainder_fraction=100.0000%, Lmin=77.34, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=8233, regioncalls=324160, ndraw=40, logz=63.47, remainder_fraction=100.0000%, Lmin=79.26, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=8291, regioncalls=326560, ndraw=40, logz=65.13, remainder_fraction=100.0000%, Lmin=80.72, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=8319, regioncalls=327760, ndraw=40, logz=65.73, remainder_fraction=100.0000%, Lmin=81.30, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=8345, regioncalls=328840, ndraw=40, logz=66.46, remainder_fraction=100.0000%, Lmin=82.32, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=8395, regioncalls=330880, ndraw=40, logz=67.94, remainder_fraction=100.0000%, Lmin=83.86, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=8433, regioncalls=332480, ndraw=40, logz=68.97, remainder_fraction=99.9999%, Lmin=84.73, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=8450, regioncalls=333280, ndraw=40, logz=69.28, remainder_fraction=99.9998%, Lmin=85.11, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=8501, regioncalls=335360, ndraw=40, logz=70.49, remainder_fraction=99.9994%, Lmin=86.41, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=8557, regioncalls=337640, ndraw=40, logz=71.52, remainder_fraction=99.9984%, Lmin=87.38, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=8610, regioncalls=339920, ndraw=40, logz=72.47, remainder_fraction=99.9959%, Lmin=88.23, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=8661, regioncalls=342240, ndraw=40, logz=73.31, remainder_fraction=99.9900%, Lmin=89.27, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=8675, regioncalls=342920, ndraw=40, logz=73.54, remainder_fraction=99.9876%, Lmin=89.47, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=8711, regioncalls=344440, ndraw=40, logz=74.18, remainder_fraction=99.9764%, Lmin=90.07, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=8765, regioncalls=346600, ndraw=40, logz=74.98, remainder_fraction=99.9489%, Lmin=90.97, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5594, ncalls=8811, regioncalls=348440, ndraw=40, logz=75.61, remainder_fraction=99.9044%, Lmin=91.55, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=8819, regioncalls=348760, ndraw=40, logz=75.71, remainder_fraction=99.8941%, Lmin=91.67, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=8867, regioncalls=350720, ndraw=40, logz=76.38, remainder_fraction=99.7920%, Lmin=92.30, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=8909, regioncalls=352560, ndraw=40, logz=76.84, remainder_fraction=99.6612%, Lmin=92.77, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=8920, regioncalls=353000, ndraw=40, logz=76.99, remainder_fraction=99.6085%, Lmin=92.95, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=8968, regioncalls=355080, ndraw=40, logz=77.53, remainder_fraction=99.3157%, Lmin=93.47, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=9021, regioncalls=357200, ndraw=40, logz=78.02, remainder_fraction=98.8649%, Lmin=93.92, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=9067, regioncalls=359120, ndraw=40, logz=78.47, remainder_fraction=98.2438%, Lmin=94.42, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=9118, regioncalls=361200, ndraw=40, logz=78.86, remainder_fraction=97.3902%, Lmin=94.80, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5850, ncalls=9130, regioncalls=361720, ndraw=40, logz=78.95, remainder_fraction=97.1280%, Lmin=94.86, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=9170, regioncalls=363320, ndraw=40, logz=79.20, remainder_fraction=96.2870%, Lmin=95.08, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=9221, regioncalls=365400, ndraw=40, logz=79.50, remainder_fraction=95.0289%, Lmin=95.37, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=9247, regioncalls=366480, ndraw=40, logz=79.64, remainder_fraction=94.2645%, Lmin=95.52, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=9270, regioncalls=367400, ndraw=40, logz=79.78, remainder_fraction=93.4054%, Lmin=95.66, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=9317, regioncalls=369280, ndraw=40, logz=80.03, remainder_fraction=91.7288%, Lmin=95.90, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=9376, regioncalls=371640, ndraw=40, logz=80.26, remainder_fraction=89.7527%, Lmin=96.11, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=9423, regioncalls=373560, ndraw=40, logz=80.46, remainder_fraction=87.5220%, Lmin=96.30, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=9479, regioncalls=375840, ndraw=40, logz=80.64, remainder_fraction=84.9630%, Lmin=96.48, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=9527, regioncalls=377840, ndraw=40, logz=80.80, remainder_fraction=82.0315%, Lmin=96.69, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=9586, regioncalls=380280, ndraw=40, logz=80.96, remainder_fraction=79.0690%, Lmin=96.85, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=9596, regioncalls=380720, ndraw=40, logz=80.99, remainder_fraction=78.2190%, Lmin=96.89, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=9636, regioncalls=382520, ndraw=40, logz=81.10, remainder_fraction=75.8492%, Lmin=97.00, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=9694, regioncalls=384880, ndraw=40, logz=81.23, remainder_fraction=72.4337%, Lmin=97.13, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6300, ncalls=9717, regioncalls=385880, ndraw=40, logz=81.29, remainder_fraction=70.6438%, Lmin=97.20, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=9741, regioncalls=386840, ndraw=40, logz=81.35, remainder_fraction=69.0033%, Lmin=97.27, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=9796, regioncalls=389200, ndraw=40, logz=81.45, remainder_fraction=65.3357%, Lmin=97.39, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=9846, regioncalls=391240, ndraw=40, logz=81.53, remainder_fraction=62.6597%, Lmin=97.49, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=9859, regioncalls=391840, ndraw=40, logz=81.55, remainder_fraction=61.7254%, Lmin=97.51, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=9911, regioncalls=393920, ndraw=40, logz=81.64, remainder_fraction=57.9415%, Lmin=97.59, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=9962, regioncalls=396040, ndraw=40, logz=81.73, remainder_fraction=54.2676%, Lmin=97.67, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=10008, regioncalls=397920, ndraw=40, logz=81.80, remainder_fraction=50.9164%, Lmin=97.76, Lmax=98.50 INFO ultranest:integrator.py:2654 Explored until L=1e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 10026 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 82.54 +- 0.1468 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 989.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.43, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.19 bs:0.15 tail:0.41 total:0.43 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_flatnuts.py::test_directjumper	0.04
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ make reflect make stuck
Passed	tests/test_clustering.py::test_clusteringcase_eggbox	0.01
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ maxradius: 4.059180769289128e-10
Passed	tests/test_netiterintegrate.py::test_visualisation	0.00
[gw11] linux -- Python 3.10.6 /usr/bin/python3 [gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ testing tree visualisation... - Node: None - Node: 694 - Node: 1 - Node: 633 - Node: 186 - Node: 804 - Node: 176 - Node: 540 - Node: 224 - Node: 179 - Node: 480 - Node: 730 - Node: 754 - Node: 60 - Node: 609 - Node: 573 Empty Tree ║+║║║ 1 ║║║\\ ║║║ \\ ║║╠╗║║ 186 ║║║║║║ ║║O║║║ 176 ║║ ║║\ ║║ ║║ \ ║║ ║║ \ ║║ ║╠╦╗║ 540 ║║ ║║O║║ 179 ║║ ║║ O║ 224 ║║ ║O ║ 480 ║O ║ ║ 633 O ║ ║ 694 ║ ╠╦╦╗ 730 ║ ║║O║ 60 ║ O║ ║ 573 ║ O ║ 609 ║ O 754 O 804
Passed	tests/test_run.py::test_run	9.90
[gw11] linux -- Python 3.10.6 /usr/bin/python3 [gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ Creating directory for new run logs/test/run10 [ultranest.integrator.NestedSampler] Num live points [400] [ultranest.integrator.NestedSampler] Resuming... [ultranest.integrator.NestedSampler] Starting sampling ... Mono-modal Volume: ~exp(-3.69) Expected Volume: exp(-5.99) Hinz: +0.0e+00\|**************** ******* * **** * * * ** * \| +1.0e+05 Kunz: +0.0e+00\|********* * * * *** * * * \| +1.0e+05 Z=-1e+02+0.5 \| Like=-1e+02..0.5 \| it/evals=0/500 eff=0.0000% Z=-6e+01+0.4 \| Like=-6e+01..0.5 \| it/evals=50/500 eff=10.0000% Z=-5e+01+0.3 \| Like=-5e+01..0.5 \| it/evals=100/625 eff=16.0000% Z=-4e+01+0.1 \| Like=-4e+01..0.5 \| it/evals=150/625 eff=24.0000% Z=-4e+01+0.01 \| Like=-3e+01..0.5 \| it/evals=200/739 eff=27.0636% Mono-modal Volume: ~exp(-5.02) Expected Volume: exp(-6.62) Hinz: +0.0e+00\|************* ** * * +5.9e+04 \| +1.0e+05 Kunz: +0.0e+00\|******** * ** * * +4.3e+04 \| +1.0e+05 Z=-4e+01+-0.1 \| Like=-3e+01..0.5 \| it/evals=250/854 eff=29.2740% Z=-3e+01+-0.2 \| Like=-3e+01..0.5 \| it/evals=300/854 eff=35.1288% Z=-3e+01+-0.4 \| Like=-2e+01..0.5 \| it/evals=350/929 eff=37.6749% Z=-3e+01+-0.5 \| Like=-2e+01..0.5 \| it/evals=400/1004 eff=39.8406% Z=-2e+01+-0.6 \| Like=-2e+01..0.5 \| it/evals=450/1075 eff=41.8605% Z=-2e+01+-0.7 \| Like=-2e+01..0.5 \| it/evals=500/1135 eff=44.0529% Z=-2e+01+-0.9 \| Like=-2e+01..0.5 \| it/evals=550/1199 eff=45.8716% Mono-modal Volume: ~exp(-5.68) Expected Volume: exp(-7.38) Hinz: +0.0e+00\|********** * * * * +3.5e+03 \| +1.0e+04 Kunz: +0.0e+00\|************ +2.6e+03 \| +1.0e+04 Z=-2e+01+-1 \| Like=-1e+01..0.5 \| it/evals=600/1289 eff=46.5477% Z=-2e+01+-1 \| Like=-1e+01..0.5 \| it/evals=650/1362 eff=47.7239% Z=-2e+01+-1 \| Like=-1e+01..0.5 \| it/evals=700/1424 eff=49.1573% Z=-1e+01+-1 \| Like=-1e+01..0.5 \| it/evals=750/1498 eff=50.0668% Z=-1e+01+-1 \| Like=-9..0.5 \| it/evals=800/1588 eff=50.3778% Z=-1e+01+-2 \| Like=-8..0.5 \| it/evals=850/1671 eff=50.8677% Mono-modal Volume: ~exp(-5.95) Expected Volume: exp(-8.12) Hinz: +0.0e+00\|************* * * * +6.1e+02 \| +1.0e+03 Kunz: +0.0e+00\|********* ** * ** * +4.7e+02 \| +1.0e+03 Z=-1e+01+-2 \| Like=-7..0.6 \| it/evals=900/1741 eff=51.6944% Z=-1e+01+-2 \| Like=-6..0.6 \| it/evals=950/1804 eff=52.6608% Z=-1e+01+-2 \| Like=-5..0.6 \| it/evals=1000/1905 eff=52.4934% Z=-9+-2 \| Like=-5..0.6 \| it/evals=1050/1994 eff=52.6580% Z=-8+-2 \| Like=-4..0.6 \| it/evals=1100/2067 eff=53.2172% Mono-modal Volume: ~exp(-6.66) Expected Volume: exp(-8.77) Hinz: +0.0e+00\|******** +1.8e+02 \| +1.0e+03 Kunz: +0.0e+00\|**** +1.5e+02 \| +1.0e+03 Z=-8+-2 \| Like=-4..0.6 \| it/evals=1150/2135 eff=53.8642% Z=-7+-2 \| Like=-3..0.6 \| it/evals=1200/2211 eff=54.2741% Z=-7+-3 \| Like=-3..0.6 \| it/evals=1250/2280 eff=54.8246% Z=-7+-3 \| Like=-2..0.6 \| it/evals=1300/2361 eff=55.0614% Z=-6+-3 \| Like=-2..0.6 \| it/evals=1350/2445 eff=55.2147% Mono-modal Volume: ~exp(-7.38) Expected Volume: exp(-9.44) Hinz: +0.0\|*************************** * +59.1 \| +100.0 Kunz: +0.0\|************************* +49.4 \| +100.0 Z=-6+-3 \| Like=-2..0.6 \| it/evals=1400/2524 eff=55.4675% Z=-6+-3 \| Like=-1..0.6 \| it/evals=1450/2599 eff=55.7907% Z=-5+-3 \| Like=-1..0.6 \| it/evals=1500/2669 eff=56.2008% Z=-5+-3 \| Like=-0.9..0.6 \| it/evals=1550/2735 eff=56.6728% Z=-5+-3 \| Like=-0.7..0.6 \| it/evals=1600/2813 eff=56.8788% Z=-5+-4 \| Like=-0.5..0.6 \| it/evals=1650/2891 eff=57.0737% Mono-modal Volume: ~exp(-8.23) Expected Volume: exp(-10.12) Hinz: +0.0\|********** +25.3 \| +100.0 Kunz: +0.0\|********* +23.7 \| +100.0 Z=-5+-4 \| Like=-0.4..0.6 \| it/evals=1700/2949 eff=57.6467% Z=-5+-4 \| Like=-0.3..0.6 \| it/evals=1750/3086 eff=56.7077% Z=-4+-4 \| Like=-0.2..0.6 \| it/evals=1800/3185 eff=56.5149% Z=-4+-4 \| Like=-0.08..0.6 \| it/evals=1850/3185 eff=58.0848% Z=-4+-4 \| Like=0.0008..0.6 \| it/evals=1900/3271 eff=58.0862% Mono-modal Volume: ~exp(-9.01) Expected Volume: exp(-10.76) Hinz: +0.0\|***** +16.1 \| +100.0 Kunz: +0.0\|***** +15.3 \| +100.0 Z=-4+-4 \| Like=0.06..0.6 \| it/evals=1950/3357 eff=58.0876% Z=-4+-4 \| Like=0.1..0.6 \| it/evals=2000/3463 eff=57.7534% Z=-4+-5 \| Like=0.2..0.6 \| it/evals=2050/3570 eff=57.4230% Z=-4+-5 \| Like=0.2..0.6 \| it/evals=2100/3570 eff=58.8235% Z=-4+-5 \| Like=0.3..0.6 \| it/evals=2150/3657 eff=58.7914% Z=-4+-5 \| Like=0.3..0.6 \| it/evals=2200/3740 eff=58.8235% Mono-modal Volume: ~exp(-9.53) Expected Volume: exp(-11.55) Hinz: +0.0\|** +10.8 \| +100.0 Kunz: +0.0\|** +10.1 \| +100.0 Z=-4+-5 \| Like=0.3..0.6 \| it/evals=2250/3809 eff=59.0706% Z=-4+-5 \| Like=0.4..0.6 \| it/evals=2300/3940 eff=58.3756% Z=-4+-5 \| Like=0.4..0.6 \| it/evals=2350/3940 eff=59.6447% Z=-4+-5 \| Like=0.4..0.6 \| it/evals=2400/4055 eff=59.1862% Z=-4+-6 \| Like=0.4..0.6 \| it/evals=2450/4159 eff=58.9084% Mono-modal Volume: ~exp(-10.45) Expected Volume: exp(-12.23) Hinz: +0.0\| +2.2 ****************************** \| +10.0 Kunz: +0.0\| +2.3 *************************** +8.1 \| +10.0 Z=-4+-6 \| Like=0.4..0.6 \| it/evals=2500/4234 eff=59.0458% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2550/4263 eff=59.8170% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2600/4335 eff=59.9769% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2650/4405 eff=60.1589% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2700/4469 eff=60.4162% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2750/4555 eff=60.3732% Z=-4+-6 \| Like=0.5..0.6 \| it/evals=2800/4624 eff=60.5536% Mono-modal Volume: ~exp(-11.00) Expected Volume: exp(-13.02) Hinz: +0.0\| +2.8 ***************** +6.6 \| +10.0 Kunz: +0.0\| +2.9 *************** +6.3 \| +10.0 Z=-4+-7 \| Like=0.5..0.6 \| it/evals=2850/4770 eff=59.7484% Z=-4+-7 \| Like=0.5..0.6 \| it/evals=2900/4770 eff=60.7966% Z=-4+-7 \| Like=0.6..0.6 \| it/evals=2950/4897 eff=60.2410% Z=-4+-7 \| Like=0.6..0.6 \| it/evals=3000/5015 eff=59.8205% Z=-4+-7 \| Like=0.6..0.6 \| it/evals=3050/5015 eff=60.8175% Mono-modal Volume: ~exp(-11.94) Expected Volume: exp(-13.64) Hinz: +0.0\| +3.1 ************ +5.9 \| +10.0 Kunz: +0.0\| +3.2 ********** +5.8 \| +10.0 Z=-4+-7 \| Like=0.6..0.6 \| it/evals=3100/5106 eff=60.7129% Z=-4+-7 \| Like=0.6..0.6 \| it/evals=3150/5221 eff=60.3333% Z=-4+-7 \| Like=0.6..0.6 \| it/evals=3200/5312 eff=60.2410% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3250/5399 eff=60.1963% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3300/5489 eff=60.1202% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3350/5489 eff=61.0312% Mono-modal Volume: ~exp(-12.75) Expected Volume: exp(-14.40) Hinz: +0.0\| +3.5 ******* +5.3 \| +10.0 Kunz: +0.0\| +3.5 ******* +5.3 \| +10.0 Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3400/5658 eff=60.0919% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3450/5658 eff=60.9756% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3500/5752 eff=60.8484% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3550/5844 eff=60.7461% Z=-4+-8 \| Like=0.6..0.6 \| it/evals=3600/5918 eff=60.8314% Mono-modal Volume: ~exp(-13.22) Expected Volume: exp(-15.07) Hinz: +0.0\| +3.7 **** +5.0 \| +10.0 Kunz: +0.0\| +3.7 **** +5.0 \| +10.0 Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3650/6000 eff=60.8333% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3700/6031 eff=61.3497% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3750/6091 eff=61.5662% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3800/6169 eff=61.5983% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3850/6231 eff=61.7878% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3900/6312 eff=61.7871% Z=-4+-9 \| Like=0.6..0.6 \| it/evals=3950/6393 eff=61.7863% Mono-modal Volume: ~exp(-14.32) Expected Volume: exp(-15.89) Hinz: +0.0\| +3.9 ** +4.8 \| +10.0 Kunz: +0.0\| +3.9 ** +4.7 \| +10.0 Z=-4+-9 \| Like=0.6..0.6 \| it/evals=4000/6518 eff=61.3685% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4050/6615 eff=61.2245% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4100/6615 eff=61.9803% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4150/6701 eff=61.9311% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4200/6780 eff=61.9469% Mono-modal Volume: ~exp(-14.65) Expected Volume: exp(-16.54) Hinz: +0.0\| +4.0 +4.6 \| +10.0 Kunz: +0.0\| +4.0 ** +4.6 \| +10.0 Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4250/6848 eff=62.0619% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4300/6974 eff=61.6576% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4350/7096 eff=61.3021% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4400/7096 eff=62.0068% Z=-4+-1e+01 \| Like=0.6..0.6 \| it/evals=4450/7198 eff=61.8227% niter: 4473 ncall: 7198 nsamples: 4873 logz: -3.678 +/- 0.091 h: 3.293 -------------------------------Captured log call-------------------------------- INFO ultranest.integrator.NestedSampler:integrator.py:518 Num live points [400] INFO ultranest.integrator.NestedSampler:integrator.py:574 Resuming... INFO ultranest.integrator.NestedSampler:integrator.py:665 Starting sampling ... WARNING root:core.py:593 Too few points to create valid contours
Passed	tests/test_clustering.py::test_clusteringcase	0.57
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ maxradius: 11.45313971598804
Passed	tests/test_ordertest.py::test_diff_expand	0.00
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_run.py::test_reactive_run_extraparams	11.26
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.28) * Expected Volume: exp(0.00) Quality: ok Hinz : -5.0\|*******************************************\| +5.0 Kunz : -5.0\|*****************************************\| +5.0 ctr_distance: +0.0e+00\|****************************************** \| +1.0e+01 Z=-inf(0.00%) \| Like=-4.88..-0.03 [-4.8818..-2.5392] \| it/evals=0/401 eff=0.0000% N=400 Z=-6.6(1.05%) \| Like=-3.91..-0.03 [-4.8818..-2.5392] \| it/evals=40/442 eff=95.2381% N=400 Z=-5.6(2.67%) \| Like=-3.50..-0.03 [-4.8818..-2.5392] \| it/evals=80/484 eff=95.2381% N=400 Mono-modal Volume: ~exp(-4.31) * Expected Volume: exp(-0.23) Quality: ok Hinz : -5.0\|*******************************************\| +5.0 Kunz : -5.0\|*****************************************\| +5.0 ctr_distance: +0.0e+00\|***************************** +6.9e+00 \| +1.0e+01 Z=-5.5(3.15%) \| Like=-3.43..-0.03 [-4.8818..-2.5392] \| it/evals=90/495 eff=94.7368% N=400 Z=-5.1(4.70%) \| Like=-3.22..-0.03 [-4.8818..-2.5392] \| it/evals=120/532 eff=90.9091% N=400 Z=-4.7(7.12%) \| Like=-2.94..-0.03 [-4.8818..-2.5392] \| it/evals=160/585 eff=86.4865% N=400 Mono-modal Volume: ~exp(-4.99) * Expected Volume: exp(-0.45) Quality: ok Hinz : -5.0\| ******************************************\| +5.0 Kunz : -5.0\|*****************************************\| +5.0 ctr_distance: +0.0e+00\|********************** +5.7e+00 \| +1.0e+01 Z=-4.5(8.42%) \| Like=-2.86..-0.03 [-4.8818..-2.5392] \| it/evals=180/611 eff=85.3081% N=400 Z=-4.3(9.82%) \| Like=-2.77..-0.03 [-4.8818..-2.5392] \| it/evals=200/636 eff=84.7458% N=400 Z=-4.1(12.76%) \| Like=-2.64..-0.03 [-4.8818..-2.5392] \| it/evals=240/686 eff=83.9161% N=400 Mono-modal Volume: ~exp(-4.99) Expected Volume: exp(-0.67) Quality: ok Hinz : -5.0\| ****************************************\| +5.0 Kunz : -5.0\| *************************************** \| +5.0 ctr_distance: +0.0e+00\|********************** +5.1e+00 \| +1.0e+01 Z=-3.9(14.98%) \| Like=-2.54..-0.03 [-4.8818..-2.5392] \| it/evals=270/726 eff=82.8221% N=400 Z=-3.9(15.74%) \| Like=-2.51..-0.03 [-2.5090..-2.5073]\| it/evals=280/738 eff=82.8402% N=400 Z=-3.7(18.75%) \| Like=-2.38..-0.03 [-2.3841..-2.3821]\| it/evals=320/793 eff=81.4249% N=400 Mono-modal Volume: ~exp(-5.30) * Expected Volume: exp(-0.90) Quality: ok Hinz : -5.0\| ************************************** \| +5.0 Kunz : -5.0\| ********************************** * \| +5.0 ctr_distance: +0.0e+00\|********************* +4.5e+00 \| +1.0e+01 Z=-3.5(21.98%) \| Like=-2.26..-0.03 [-2.2557..-2.2540]\| it/evals=360/850 eff=80.0000% N=400 Z=-3.4(25.37%) \| Like=-2.15..-0.03 [-2.1517..-2.1515]\| it/evals=400/902 eff=79.6813% N=400 Z=-3.3(28.35%) \| Like=-2.04..-0.03 [-2.0444..-2.0393]\| it/evals=440/961 eff=78.4314% N=400 Mono-modal Volume: ~exp(-5.30) Expected Volume: exp(-1.12) Quality: ok Hinz : -5.0\| ********************************* \| +5.0 Kunz : -5.0\| ****************************** \| +5.0 ctr_distance: +0.0e+00\|***************** +4.0e+00 \| +1.0e+01 Z=-3.2(29.21%) \| Like=-2.01..-0.03 [-2.0100..-2.0089]\| it/evals=450/978 eff=77.8547% N=400 Z=-3.2(31.62%) \| Like=-1.93..-0.03 [-1.9328..-1.9317]\| it/evals=480/1017 eff=77.7958% N=400 Z=-3.1(34.96%) \| Like=-1.86..-0.03 [-1.8607..-1.8595]\| it/evals=520/1073 eff=77.2660% N=400 Mono-modal Volume: ~exp(-5.42) Expected Volume: exp(-1.35) Quality: ok Hinz : -5.0\| ****************************** * \| +5.0 Kunz : -5.0\| ****************************** \| +5.0 ctr_distance: +0.0e+00\|*************** +3.6e+00 \| +1.0e+01 Z=-3.0(36.35%) \| Like=-1.82..-0.03 [-1.8240..-1.8218]\| it/evals=540/1096 eff=77.5862% N=400 Z=-3.0(37.93%) \| Like=-1.77..-0.03 [-1.7742..-1.7725]\| it/evals=560/1127 eff=77.0289% N=400 Z=-2.9(41.05%) \| Like=-1.65..-0.03 [-1.6518..-1.6494]\| it/evals=600/1185 eff=76.4331% N=400 Mono-modal Volume: ~exp(-5.42) Expected Volume: exp(-1.57) Quality: ok Hinz : -5.0\| ************************* \| +5.0 Kunz : -5.0\| ************************ * \| +5.0 ctr_distance: +0.0e+00\|*************** +3.2e+00 \| +1.0e+01 Z=-2.8(43.34%) \| Like=-1.60..-0.03 [-1.5969..-1.5965]\| it/evals=630/1233 eff=75.6303% N=400 Z=-2.8(44.24%) \| Like=-1.58..-0.03 [-1.5763..-1.5757]\| it/evals=640/1247 eff=75.5608% N=400 Z=-2.8(47.23%) \| Like=-1.49..-0.03 [-1.4913..-1.4892]\| it/evals=680/1313 eff=74.4797% N=400 Mono-modal Volume: ~exp(-6.24) Expected Volume: exp(-1.80) Quality: ok Hinz : -5.0\| *********************** +2.6 \| +5.0 Kunz : -5.0\| ********************* +2.7 \| +5.0 ctr_distance: +0.0e+00\|*********** +2.9e+00 \| +1.0e+01 Z=-2.7(50.21%) \| Like=-1.43..-0.03 [-1.4292..-1.4283]\| it/evals=720/1367 eff=74.4571% N=400 Z=-2.6(52.99%) \| Like=-1.36..-0.03 [-1.3636..-1.3570]\| it/evals=760/1423 eff=74.2913% N=400 Z=-2.6(55.78%) \| Like=-1.29..-0.03 [-1.2904..-1.2895]\| it/evals=800/1475 eff=74.4186% N=400 Mono-modal Volume: ~exp(-6.24) Expected Volume: exp(-2.02) Quality: ok Hinz : -5.0\| -2.5 ******************* +2.3 \| +5.0 Kunz : -5.0\| -2.4 ******************* +2.4 \| +5.0 ctr_distance: +0.0e+00\|********** +2.5e+00 \| +1.0e+01 Z=-2.6(57.14%) \| Like=-1.25..-0.03 [-1.2545..-1.2523]\| it/evals=820/1506 eff=74.1410% N=400 Z=-2.5(58.45%) \| Like=-1.23..-0.03 [-1.2319..-1.2316]\| it/evals=840/1533 eff=74.1395% N=400 Z=-2.5(61.03%) \| Like=-1.16..-0.03 [-1.1554..-1.1510]\| it/evals=880/1594 eff=73.7018% N=400 Mono-modal Volume: ~exp(-6.24) Expected Volume: exp(-2.25) Quality: ok Hinz : -5.0\| -2.1 ***************** +2.2 \| +5.0 Kunz : -5.0\| -2.1 **************** +2.1 \| +5.0 ctr_distance: +0.0e+00\|********* +2.3e+00 \| +1.0e+01 Z=-2.5(63.43%) \| Like=-1.11..-0.03 [-1.1067..-1.1061]\| it/evals=920/1650 eff=73.6000% N=400 Z=-2.4(65.86%) \| Like=-1.05..-0.03 [-1.0508..-1.0507]\| it/evals=960/1709 eff=73.3384% N=400 Mono-modal Volume: ~exp(-6.98) * Expected Volume: exp(-2.47) Quality: ok Hinz : -5.0\| -1.9 ***************** +1.9 \| +5.0 Kunz : -5.0\| -2.0 *************** +1.9 \| +5.0 ctr_distance: +0.0e+00\|******** +2.0e+00 \| +1.0e+01 Z=-2.4(67.48%) \| Like=-1.02..-0.03 [-1.0220..-1.0201]\| it/evals=990/1759 eff=72.8477% N=400 Z=-2.4(67.95%) \| Like=-1.00..-0.03 [-1.0042..-1.0040]\| it/evals=1000/1772 eff=72.8863% N=400 Z=-2.4(70.19%) \| Like=-0.96..-0.03 [-0.9629..-0.9622]\| it/evals=1040/1829 eff=72.7782% N=400 Mono-modal Volume: ~exp(-7.09) Expected Volume: exp(-2.70) Quality: ok Hinz : -5.0\| -1.8 *************** +1.8 \| +5.0 Kunz : -5.0\| -1.8 ************* +1.7 \| +5.0 ctr_distance: +0.0e+00\|******* +1.8e+00 \| +1.0e+01 Z=-2.3(72.28%) \| Like=-0.92..-0.03 [-0.9249..-0.9246]\| it/evals=1080/1887 eff=72.6295% N=400 Z=-2.3(74.36%) \| Like=-0.89..-0.03 [-0.8918..-0.8907]\| it/evals=1120/1943 eff=72.5859% N=400 Z=-2.3(76.26%) \| Like=-0.86..-0.03 [-0.8639..-0.8631]\| it/evals=1160/1996 eff=72.6817% N=400 Mono-modal Volume: ~exp(-7.09) Expected Volume: exp(-2.92) Quality: ok Hinz : -5.0\| -1.5 ************ +1.6 \| +5.0 Kunz : -5.0\| -1.6 *********** +1.6 \| +5.0 ctr_distance: +0.0e+00\|****** +1.7e+00 \| +1.0e+01 Z=-2.3(77.94%) \| Like=-0.83..-0.03 [-0.8279..-0.8265]\| it/evals=1200/2048 eff=72.8155% N=400 Z=-2.2(79.52%) \| Like=-0.78..-0.03 [-0.7823..-0.7809]\| it/evals=1240/2106 eff=72.6846% N=400 Mono-modal Volume: ~exp(-7.14) * Expected Volume: exp(-3.15) Quality: ok Hinz : -5.0\| -1.4 *********** +1.4 \| +5.0 Kunz : -5.0\| -1.4 ********* +1.4 \| +5.0 ctr_distance: +0.0e+00\|***** +1.5e+00 \| +1.0e+01 Z=-2.2(80.32%) \| Like=-0.76..-0.03 [-0.7590..-0.7563]\| it/evals=1260/2137 eff=72.5389% N=400 Z=-2.2(81.03%) \| Like=-0.74..-0.03 [-0.7362..-0.7354]\| it/evals=1280/2162 eff=72.6447% N=400 Z=-2.2(82.50%) \| Like=-0.69..-0.03 [-0.6928..-0.6909]\| it/evals=1320/2215 eff=72.7273% N=400 Mono-modal Volume: ~exp(-7.52) Expected Volume: exp(-3.37) Quality: ok Hinz : -5.0\| -1.2 ********** +1.2 \| +5.0 Kunz : -5.0\| -1.2 ******** +1.2 \| +5.0 ctr_distance: +0.0e+00\|***** +1.3e+00 \| +1.0e+01 Z=-2.2(83.51%) \| Like=-0.67..-0.03 [-0.6667..-0.6666]\| it/evals=1350/2259 eff=72.6197% N=400 Z=-2.2(83.83%) \| Like=-0.66..-0.03 [-0.6598..-0.6594]\| it/evals=1360/2272 eff=72.6496% N=400 Z=-2.2(85.12%) \| Like=-0.62..-0.03 [-0.6234..-0.6227]\| it/evals=1400/2322 eff=72.8408% N=400 Mono-modal Volume: ~exp(-7.61) Expected Volume: exp(-3.60) Quality: ok Hinz : -5.0\| -1.1 ********* +1.1 \| +5.0 Kunz : -5.0\| -1.1 ******* +1.1 \| +5.0 ctr_distance: +0.0e+00\|**** +1.2e+00 \| +1.0e+01 Z=-2.2(86.25%) \| Like=-0.59..-0.03 [-0.5932..-0.5929]\| it/evals=1440/2382 eff=72.6539% N=400 Z=-2.1(86.94%) \| Like=-0.57..-0.03 [-0.5736..-0.5734]\| it/evals=1465/2415 eff=72.7047% N=400 Z=-2.1(87.33%) \| Like=-0.57..-0.03 [-0.5655..-0.5646]\| it/evals=1480/2436 eff=72.6916% N=400 Z=-2.1(88.35%) \| Like=-0.54..-0.03 [-0.5440..-0.5435]\| it/evals=1520/2489 eff=72.7621% N=400 Mono-modal Volume: ~exp(-8.10) * Expected Volume: exp(-3.82) Quality: ok Hinz : -5.0\| -0.9 ******** +1.0 \| +5.0 Kunz : -1.0\|************************************* \| +1.0 ctr_distance: +0.0e+00\|**** +1.1e+00 \| +1.0e+01 Z=-2.1(88.60%) \| Like=-0.54..-0.03 [-0.5381..-0.5373]\| it/evals=1530/2506 eff=72.6496% N=400 Z=-2.1(89.30%) \| Like=-0.52..-0.03 [-0.5191..-0.5189]\| it/evals=1560/2544 eff=72.7612% N=400 Z=-2.1(90.12%) \| Like=-0.50..-0.03 [-0.4966..-0.4963]\| it/evals=1598/2593 eff=72.8682% N=400 Z=-2.1(90.16%) \| Like=-0.49..-0.03 [-0.4949..-0.4941]\| it/evals=1600/2595 eff=72.8929% N=400 Mono-modal Volume: ~exp(-8.18) * Expected Volume: exp(-4.05) Quality: ok Hinz : -1.0\| *********************************** \| +1.0 Kunz : -1.0\| ************************************ * \| +1.0 ctr_distance: +0.00\| * ************************************** \| +1.00 Z=-2.1(90.57%) \| Like=-0.48..-0.03 [-0.4804..-0.4800]\| it/evals=1620/2627 eff=72.7436% N=400 Z=-2.1(90.95%) \| Like=-0.46..-0.03 [-0.4644..-0.4639]\| it/evals=1640/2652 eff=72.8242% N=400 Z=-2.1(91.68%) \| Like=-0.44..-0.03 [-0.4405..-0.4372]\| it/evals=1680/2701 eff=73.0117% N=400 Mono-modal Volume: ~exp(-8.39) Expected Volume: exp(-4.27) Quality: ok Hinz : -1.0\| ********************************** \| +1.0 Kunz : -1.0\| ******************************** * \| +1.0 ctr_distance: +0.00\| * ****************************** \| +1.00 Z=-2.1(92.21%) \| Like=-0.42..-0.03 [-0.4157..-0.4143]\| it/evals=1710/2740 eff=73.0769% N=400 Z=-2.1(92.38%) \| Like=-0.41..-0.03 [-0.4107..-0.4104]\| it/evals=1720/2753 eff=73.0982% N=400 Z=-2.1(93.01%) \| Like=-0.39..-0.03 [-0.3935..-0.3928]\| it/evals=1759/2812 eff=72.9270% N=400 Z=-2.1(93.02%) \| Like=-0.39..-0.03 [-0.3928..-0.3912]\| it/evals=1760/2814 eff=72.9080% N=400 Mono-modal Volume: ~exp(-8.97) * Expected Volume: exp(-4.50) Quality: ok Hinz : -1.0\| ******************************* \| +1.0 Kunz : -1.0\| ***************************** \| +1.0 ctr_distance: +0.00\| ******************************* +0.75 \| +1.00 Z=-2.1(93.61%) \| Like=-0.37..-0.01 [-0.3749..-0.3747]\| it/evals=1800/2876 eff=72.6979% N=400 Z=-2.1(94.15%) \| Like=-0.36..-0.01 [-0.3577..-0.3575]\| it/evals=1840/2927 eff=72.8136% N=400 Z=-2.1(94.65%) \| Like=-0.34..-0.01 [-0.3425..-0.3424]\| it/evals=1880/2980 eff=72.8682% N=400 Mono-modal Volume: ~exp(-8.97) Expected Volume: exp(-4.73) Quality: ok Hinz : -1.0\| *************************** \| +1.0 Kunz : -1.0\| * ************************** \| +1.0 ctr_distance: +0.00\|***************************** +0.68 \| +1.00 Z=-2.1(95.10%) \| Like=-0.33..-0.01 [-0.3276..-0.3274]\| it/evals=1920/3035 eff=72.8653% N=400 Z=-2.1(95.51%) \| Like=-0.31..-0.01 [-0.3138..-0.3135]\| it/evals=1960/3098 eff=72.6464% N=400 Mono-modal Volume: ~exp(-9.29) * Expected Volume: exp(-4.95) Quality: ok Hinz : -1.0\| ************************** \| +1.0 Kunz : -1.0\| ********************* +0.5 \| +1.0 ctr_distance: +0.00\|************************** +0.61 \| +1.00 Z=-2.1(95.71%) \| Like=-0.31..-0.01 [-0.3064..-0.3063]\| it/evals=1980/3122 eff=72.7406% N=400 Z=-2.0(95.90%) \| Like=-0.30..-0.01 [-0.2985..-0.2975]\| it/evals=2000/3145 eff=72.8597% N=400 Z=-2.0(96.25%) \| Like=-0.28..-0.01 [-0.2826..-0.2825]\| it/evals=2040/3201 eff=72.8311% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.18) Quality: ok Hinz : -1.0\| *********************** +0.5 \| +1.0 Kunz : -1.0\| ********************* +0.5 \| +1.0 ctr_distance: +0.00\|*********************** +0.55 \| +1.00 Z=-2.0(96.50%) \| Like=-0.27..-0.01 [-0.2733..-0.2733]\| it/evals=2070/3249 eff=72.6571% N=400 Z=-2.0(96.57%) \| Like=-0.27..-0.01 [-0.2705..-0.2697]\| it/evals=2080/3261 eff=72.7019% N=400 Z=-2.0(96.87%) \| Like=-0.26..-0.01 [-0.2592..-0.2592]\| it/evals=2120/3320 eff=72.6027% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.40) Quality: ok Hinz : -1.0\| -0.5 ******************** +0.5 \| +1.0 Kunz : -1.0\| -0.5 **************** +0.5 \| +1.0 ctr_distance: +0.00\|*********************** +0.50 \| +1.00 Z=-2.0(97.14%) \| Like=-0.25..-0.01 [-0.2492..-0.2489]\| it/evals=2160/3379 eff=72.5076% N=400 Z=-2.0(97.39%) \| Like=-0.24..-0.01 [-0.2381..-0.2380]\| it/evals=2200/3434 eff=72.5115% N=400 Z=-2.0(97.62%) \| Like=-0.23..-0.01 [-0.2264..-0.2263]\| it/evals=2240/3493 eff=72.4216% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.63) Quality: ok Hinz : -1.0\| -0.4 ****************** +0.4 \| +1.0 Kunz : -1.0\| -0.4 **************** +0.4 \| +1.0 ctr_distance: +0.00\|******************* +0.44 \| +1.00 Z=-2.0(97.68%) \| Like=-0.22..-0.01 [-0.2224..-0.2221]\| it/evals=2250/3510 eff=72.3473% N=400 Z=-2.0(97.83%) \| Like=-0.21..-0.01 [-0.2140..-0.2140]\| it/evals=2280/3561 eff=72.1291% N=400 Z=-2.0(98.02%) \| Like=-0.20..-0.01 [-0.2028..-0.2026]\| it/evals=2320/3621 eff=72.0273% N=400 Mono-modal Volume: ~exp(-9.95) Expected Volume: exp(-5.85) Quality: ok Hinz : -1.0\| -0.4 **************** +0.4 \| +1.0 Kunz : -1.0\| -0.4 ************* +0.3 \| +1.0 ctr_distance: +0.00\|**************** +0.39 \| +1.00 Z=-2.0(98.11%) \| Like=-0.20..-0.01 [-0.1958..-0.1951]\| it/evals=2340/3648 eff=72.0443% N=400 Z=-2.0(98.20%) \| Like=-0.19..-0.01 [-0.1900..-0.1895]\| it/evals=2360/3673 eff=72.1051% N=400 Z=-2.0(98.36%) \| Like=-0.18..-0.01 [-0.1819..-0.1812]\| it/evals=2400/3728 eff=72.1154% N=400 Mono-modal Volume: ~exp(-10.20) Expected Volume: exp(-6.08) Quality: ok Hinz : -1.0\| -0.3 ************* +0.3 \| +1.0 Kunz : -1.0\| -0.3 ************ +0.3 \| +1.0 ctr_distance: +0.00\|************** +0.35 \| +1.00 Z=-2.0(98.47%) \| Like=-0.17..-0.01 [-0.1731..-0.1729]\| it/evals=2430/3770 eff=72.1068% N=400 Z=-2.0(98.51%) \| Like=-0.17..-0.01 [-0.1710..-0.1709]\| it/evals=2440/3783 eff=72.1253% N=400 Z=-2.0(98.64%) \| Like=-0.16..-0.01 [-0.1604..-0.1604]\| it/evals=2480/3829 eff=72.3243% N=400 Mono-modal Volume: ~exp(-10.66) Expected Volume: exp(-6.30) Quality: ok Hinz : -1.0\| -0.3 ************ +0.3 \| +1.0 Kunz : -1.0\| -0.3 ********* +0.3 \| +1.0 ctr_distance: +0.00\|************ +0.30 \| +1.00 Z=-2.0(98.76%) \| Like=-0.15..-0.01 [-0.1520..-0.1519]\| it/evals=2520/3890 eff=72.2063% N=400 Z=-2.0(98.88%) \| Like=-0.14..-0.01 [-0.1423..-0.1422]\| it/evals=2560/3942 eff=72.2756% N=400 Z=-2.0(98.98%) \| Like=-0.14..-0.01 [-0.1363..-0.1363]*\| it/evals=2600/3993 eff=72.3629% N=400 [ultranest] Explored until L=-0.008 [ultranest] Likelihood function evaluations: 4006 [ultranest] logZ = -2.005 +- 0.0327 [ultranest] Effective samples strategy satisfied (ESS = 1721.5, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.10 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) [ultranest] logZ error budget: single: 0.03 bs:0.03 tail:0.01 total:0.03 required:<0.50 [ultranest] done iterating. -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+1, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-4.88, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=442, regioncalls=1680, ndraw=40, logz=-6.59, remainder_fraction=98.9465%, Lmin=-3.91, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=484, regioncalls=3360, ndraw=40, logz=-5.65, remainder_fraction=97.3258%, Lmin=-3.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=495, regioncalls=3800, ndraw=40, logz=-5.48, remainder_fraction=96.8546%, Lmin=-3.43, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=532, regioncalls=5280, ndraw=40, logz=-5.09, remainder_fraction=95.2983%, Lmin=-3.22, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=585, regioncalls=7400, ndraw=40, logz=-4.66, remainder_fraction=92.8770%, Lmin=-2.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=611, regioncalls=8440, ndraw=40, logz=-4.49, remainder_fraction=91.5760%, Lmin=-2.86, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=636, regioncalls=9440, ndraw=40, logz=-4.33, remainder_fraction=90.1842%, Lmin=-2.77, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=686, regioncalls=11440, ndraw=40, logz=-4.08, remainder_fraction=87.2440%, Lmin=-2.64, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=726, regioncalls=13040, ndraw=40, logz=-3.91, remainder_fraction=85.0218%, Lmin=-2.54, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=738, regioncalls=13520, ndraw=40, logz=-3.87, remainder_fraction=84.2565%, Lmin=-2.51, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=793, regioncalls=15720, ndraw=40, logz=-3.69, remainder_fraction=81.2539%, Lmin=-2.38, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=850, regioncalls=18000, ndraw=40, logz=-3.53, remainder_fraction=78.0225%, Lmin=-2.26, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=902, regioncalls=20080, ndraw=40, logz=-3.40, remainder_fraction=74.6320%, Lmin=-2.15, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=961, regioncalls=22440, ndraw=40, logz=-3.28, remainder_fraction=71.6459%, Lmin=-2.04, Lmax=-0.03 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=978, regioncalls=23120, ndraw=40, logz=-3.25, remainder_fraction=70.7912%, Lmin=-2.01, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1017, regioncalls=24680, ndraw=40, logz=-3.17, remainder_fraction=68.3815%, Lmin=-1.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1073, regioncalls=26920, ndraw=40, logz=-3.07, remainder_fraction=65.0380%, Lmin=-1.86, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1096, regioncalls=27840, ndraw=40, logz=-3.03, remainder_fraction=63.6525%, Lmin=-1.82, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1127, regioncalls=29080, ndraw=40, logz=-2.98, remainder_fraction=62.0725%, Lmin=-1.77, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1185, regioncalls=31400, ndraw=40, logz=-2.90, remainder_fraction=58.9521%, Lmin=-1.65, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1233, regioncalls=33320, ndraw=40, logz=-2.85, remainder_fraction=56.6598%, Lmin=-1.60, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1247, regioncalls=33880, ndraw=40, logz=-2.83, remainder_fraction=55.7587%, Lmin=-1.58, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1313, regioncalls=36520, ndraw=40, logz=-2.76, remainder_fraction=52.7681%, Lmin=-1.49, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1367, regioncalls=38680, ndraw=40, logz=-2.70, remainder_fraction=49.7942%, Lmin=-1.43, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1423, regioncalls=40920, ndraw=40, logz=-2.64, remainder_fraction=47.0052%, Lmin=-1.36, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1475, regioncalls=43000, ndraw=40, logz=-2.59, remainder_fraction=44.2174%, Lmin=-1.29, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=1506, regioncalls=44240, ndraw=40, logz=-2.57, remainder_fraction=42.8618%, Lmin=-1.25, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1533, regioncalls=45320, ndraw=40, logz=-2.54, remainder_fraction=41.5534%, Lmin=-1.23, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1594, regioncalls=47800, ndraw=40, logz=-2.50, remainder_fraction=38.9665%, Lmin=-1.16, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1650, regioncalls=50040, ndraw=40, logz=-2.46, remainder_fraction=36.5672%, Lmin=-1.11, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1709, regioncalls=52400, ndraw=40, logz=-2.42, remainder_fraction=34.1354%, Lmin=-1.05, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1759, regioncalls=54400, ndraw=40, logz=-2.40, remainder_fraction=32.5228%, Lmin=-1.02, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1772, regioncalls=54920, ndraw=40, logz=-2.39, remainder_fraction=32.0506%, Lmin=-1.00, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1829, regioncalls=57200, ndraw=40, logz=-2.36, remainder_fraction=29.8139%, Lmin=-0.96, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1887, regioncalls=59520, ndraw=40, logz=-2.33, remainder_fraction=27.7163%, Lmin=-0.92, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1943, regioncalls=61760, ndraw=40, logz=-2.30, remainder_fraction=25.6388%, Lmin=-0.89, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1996, regioncalls=63960, ndraw=40, logz=-2.28, remainder_fraction=23.7363%, Lmin=-0.86, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2048, regioncalls=66040, ndraw=40, logz=-2.26, remainder_fraction=22.0601%, Lmin=-0.83, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2106, regioncalls=68400, ndraw=40, logz=-2.24, remainder_fraction=20.4776%, Lmin=-0.78, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2137, regioncalls=69640, ndraw=40, logz=-2.23, remainder_fraction=19.6779%, Lmin=-0.76, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2162, regioncalls=70840, ndraw=40, logz=-2.22, remainder_fraction=18.9708%, Lmin=-0.74, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2215, regioncalls=72960, ndraw=40, logz=-2.20, remainder_fraction=17.5041%, Lmin=-0.69, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2259, regioncalls=74720, ndraw=40, logz=-2.19, remainder_fraction=16.4925%, Lmin=-0.67, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2272, regioncalls=75360, ndraw=40, logz=-2.18, remainder_fraction=16.1721%, Lmin=-0.66, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2322, regioncalls=77360, ndraw=40, logz=-2.17, remainder_fraction=14.8845%, Lmin=-0.62, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2382, regioncalls=79760, ndraw=40, logz=-2.16, remainder_fraction=13.7459%, Lmin=-0.59, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1465, ncalls=2415, regioncalls=81120, ndraw=40, logz=-2.15, remainder_fraction=13.0634%, Lmin=-0.57, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2436, regioncalls=81960, ndraw=40, logz=-2.14, remainder_fraction=12.6704%, Lmin=-0.57, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2489, regioncalls=84080, ndraw=40, logz=-2.13, remainder_fraction=11.6511%, Lmin=-0.54, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2506, regioncalls=84800, ndraw=40, logz=-2.13, remainder_fraction=11.4027%, Lmin=-0.54, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2544, regioncalls=86400, ndraw=40, logz=-2.12, remainder_fraction=10.6999%, Lmin=-0.52, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1598, ncalls=2593, regioncalls=88360, ndraw=40, logz=-2.11, remainder_fraction=9.8765%, Lmin=-0.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2595, regioncalls=88440, ndraw=40, logz=-2.11, remainder_fraction=9.8352%, Lmin=-0.49, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2627, regioncalls=89720, ndraw=40, logz=-2.11, remainder_fraction=9.4266%, Lmin=-0.48, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2652, regioncalls=90760, ndraw=40, logz=-2.10, remainder_fraction=9.0503%, Lmin=-0.46, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2701, regioncalls=92720, ndraw=40, logz=-2.10, remainder_fraction=8.3166%, Lmin=-0.44, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2740, regioncalls=94280, ndraw=40, logz=-2.09, remainder_fraction=7.7943%, Lmin=-0.42, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2753, regioncalls=94880, ndraw=40, logz=-2.09, remainder_fraction=7.6215%, Lmin=-0.41, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1759, ncalls=2812, regioncalls=97240, ndraw=40, logz=-2.08, remainder_fraction=6.9915%, Lmin=-0.39, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2814, regioncalls=97320, ndraw=40, logz=-2.08, remainder_fraction=6.9783%, Lmin=-0.39, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2876, regioncalls=99840, ndraw=40, logz=-2.07, remainder_fraction=6.3894%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2927, regioncalls=101880, ndraw=40, logz=-2.07, remainder_fraction=5.8521%, Lmin=-0.36, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2980, regioncalls=104040, ndraw=40, logz=-2.06, remainder_fraction=5.3481%, Lmin=-0.34, Lmax=-0.01 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3035, regioncalls=106240, ndraw=40, logz=-2.06, remainder_fraction=4.9017%, Lmin=-0.33, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3098, regioncalls=108760, ndraw=40, logz=-2.05, remainder_fraction=4.4883%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3122, regioncalls=109760, ndraw=40, logz=-2.05, remainder_fraction=4.2872%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3145, regioncalls=110680, ndraw=40, logz=-2.05, remainder_fraction=4.1007%, Lmin=-0.30, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3201, regioncalls=112920, ndraw=40, logz=-2.05, remainder_fraction=3.7481%, Lmin=-0.28, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3249, regioncalls=114880, ndraw=40, logz=-2.04, remainder_fraction=3.5010%, Lmin=-0.27, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3261, regioncalls=115440, ndraw=40, logz=-2.04, remainder_fraction=3.4263%, Lmin=-0.27, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3320, regioncalls=117800, ndraw=40, logz=-2.04, remainder_fraction=3.1296%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3379, regioncalls=120160, ndraw=40, logz=-2.04, remainder_fraction=2.8591%, Lmin=-0.25, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3434, regioncalls=122360, ndraw=40, logz=-2.03, remainder_fraction=2.6105%, Lmin=-0.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3493, regioncalls=124720, ndraw=40, logz=-2.03, remainder_fraction=2.3795%, Lmin=-0.23, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3510, regioncalls=125400, ndraw=40, logz=-2.03, remainder_fraction=2.3246%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3561, regioncalls=127440, ndraw=40, logz=-2.03, remainder_fraction=2.1693%, Lmin=-0.21, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3621, regioncalls=129840, ndraw=40, logz=-2.03, remainder_fraction=1.9813%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3648, regioncalls=131000, ndraw=40, logz=-2.03, remainder_fraction=1.8922%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3673, regioncalls=132000, ndraw=40, logz=-2.03, remainder_fraction=1.8049%, Lmin=-0.19, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3728, regioncalls=134200, ndraw=40, logz=-2.02, remainder_fraction=1.6435%, Lmin=-0.18, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3770, regioncalls=135920, ndraw=40, logz=-2.02, remainder_fraction=1.5314%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3783, regioncalls=136440, ndraw=40, logz=-2.02, remainder_fraction=1.4950%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3829, regioncalls=138280, ndraw=40, logz=-2.02, remainder_fraction=1.3586%, Lmin=-0.16, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3890, regioncalls=140760, ndraw=40, logz=-2.02, remainder_fraction=1.2366%, Lmin=-0.15, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3942, regioncalls=142840, ndraw=40, logz=-2.02, remainder_fraction=1.1247%, Lmin=-0.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3993, regioncalls=144880, ndraw=40, logz=-2.02, remainder_fraction=1.0222%, Lmin=-0.14, Lmax=-0.01 INFO ultranest:integrator.py:2654 Explored until L=-0.008 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 4006 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -2.005 +- 0.0327 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1721.5, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.10 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.03 bs:0.03 tail:0.01 total:0.03 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:2894 Making corner plot ... DEBUG ultranest:integrator.py:2940 Making run plot ... DEBUG ultranest:integrator.py:2916 Making trace plot ...
Passed	tests/test_regionsampling.py::test_region_sampling_affine	0.07
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ enlargement factor: 1.6413050458476683 0.6092712640650781 sampling_method: <bound method MLFriends.sample_from_transformed_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f2fb98f5450>> sampling_method: <bound method MLFriends.sample_from_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f2fb98f5450>> sampling_method: <bound method MLFriends.sample_from_points of <ultranest.mlfriends.MLFriends object at 0x7f2fb98f5450>> sampling_method: <bound method MLFriends.sample_from_wrapping_ellipsoid of <ultranest.mlfriends.MLFriends object at 0x7f2fb98f5450>>
Passed	tests/test_regionsampling.py::test_region_sampling_scaling	0.08
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ enlargement factor: 1.6413050458476675 0.6092712640650785 sampling_method: <bound method MLFriends.sample_from_transformed_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f4fb1269330>> sampling_method: <bound method MLFriends.sample_from_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f4fb1269330>> sampling_method: <bound method MLFriends.sample_from_points of <ultranest.mlfriends.MLFriends object at 0x7f4fb1269330>> sampling_method: <bound method MLFriends.sample_from_wrapping_ellipsoid of <ultranest.mlfriends.MLFriends object at 0x7f4fb1269330>>
Passed	tests/test_run.py::test_reactive_run_resume_eggbox[hdf5]	6.41
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|***************** * * ***** * ******\| +3.1e+01 b: +0.0\| *** * *** * * * **** ********* ***\| +31.4 Z=-inf(0.00%) \| Like=1.20..233.34 [1.1994..29.4283] \| it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) \| Like=2.82..233.34 [1.1994..29.4283] \| it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) \| Like=5.72..241.87 [1.1994..29.4283] \| it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0\|***************** ******* * ****** \| +31.4 b: +0.0\| ** * * * **** ********* ***\| +31.4 Z=5.8(0.00%) \| Like=9.88..241.87 [1.1994..29.4283] \| it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) \| Like=15.15..241.87 [1.1994..29.4283] \| it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0\|********** ** ** * * * ****** \| +31.4 b: +0.0\|* * ** * * * * ******** ******\| +31.4 Z=14.8(0.00%) \| Like=19.62..241.87 [1.1994..29.4283] \| it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) \| Like=25.71..241.87 [1.1994..29.4283] \| it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0\|**** * **** ****** **** * ******\| +31.4 b: +0.0\|****** ** * * ****** ******\| +31.4 Z=25.5(0.00%) \| Like=29.64..241.87 [29.6178..62.1019] \| it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) \| Like=32.87..241.87 [29.6178..62.1019] \| it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) \| Like=35.17..241.87 [29.6178..62.1019] \| it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0\|**** * *** *** **** ****\| +31.4 b: +0.0\|****** *** * ******** * *\| +31.4 Z=34.9(0.00%) \| Like=39.71..241.87 [29.6178..62.1019] \| it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) \| Like=45.13..241.87 [29.6178..62.1019] \| it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0\| ***** * **** * * *** ******** *\| +31.4 b: +0.0\|* ** * ** ***** * *\| +31.4 Z=43.4(0.00%) \| Like=49.11..241.87 [29.6178..62.1019] \| it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) \| Like=54.54..241.87 [29.6178..62.1019] \| it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0\| * * ***** ** ******* * ******* \| +31.4 b: +0.0\|* * ** **** ***** ****** \| +31.4 Z=54.8(0.00%) \| Like=60.32..241.87 [29.6178..62.1019] \| it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) \| Like=69.11..241.87 [62.2053..112.3934] \| it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) \| Like=77.89..241.87 [62.2053..112.3934] \| it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0\| ** * **** *** ***** ***** \| +31.4 b: +0.0\| **** **** ***** * ***** \| +31.4 Z=77.8(0.00%) \| Like=87.30..241.87 [62.2053..112.3934] \| it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) \| Like=94.79..241.87 [62.2053..112.3934] \| it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0\| * * **** * **** **** \| +31.4 b: +0.0\|* ****** *** *** ** \| +31.4 Z=94.6(0.00%) \| Like=100.05..241.87 [62.2053..112.3934] \| it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 12.65 │ ▁ ▇ │19.30 18.98 +- 0.35 b : 5.3 │ ▇ ▁ │26.2 6.3 +- 1.1 pointstore: (300, 7) 626 626 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.897580582291928408e+01,3.482687211659772908e-01,1.899594672309787668e+01,1.899594672309787668e+01,1.899594672309787668e+01,6.316415107809904228e+00,1.095459745550366071e+00,6.253063034987970781e+00,6.253063034987970781e+00,6.253063034987970781e+00 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.975806 0.348269 18.995947 ... 6.253063 6.253063 6.253063 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.975805822919284 checking mean of parameter 'b': 6.316415107809904 checking stdev of parameter 'a': 0.3482687211659773 checking stdev of parameter 'b': 1.095459745550366 checking median of parameter 'a': 18.995946723097877 checking median of parameter 'b': 6.253063034987971 checking errlo of parameter 'a': 18.995946723097877 checking errlo of parameter 'b': 6.253063034987971 checking errup of parameter 'a': 18.995946723097877 checking errup of parameter 'b': 6.253063034987971 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} ====== Running Eggbox problem [2] ===== [ultranest] Resuming from 300 stored points Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|***************** * * ***** * ******\| +3.1e+01 b: +0.0\| *** * *** * * * **** ********* ***\| +31.4 Z=-inf(0.00%) \| Like=1.20..233.34 [1.1994..29.4283] \| it/evals=0/626 eff=inf% N=100 Z=-0.3(0.00%) \| Like=2.82..233.34 [1.1994..29.4283] \| it/evals=10/626 eff=inf% N=100 Z=1.8(0.00%) \| Like=5.72..241.87 [1.1994..29.4283] \| it/evals=20/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.23) Quality: ok a: +0.0\|***************** ******* * ****** \| +31.4 b: +0.0\| ** * * * **** ********* ***\| +31.4 Z=5.8(0.00%) \| Like=9.88..241.87 [1.1994..29.4283] \| it/evals=30/626 eff=inf% N=100 Z=10.9(0.00%) \| Like=15.15..241.87 [1.1994..29.4283] \| it/evals=40/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.46) Quality: ok a: +0.0\|********** ** ** * * * ****** \| +31.4 b: +0.0\|* * ** * * * * ******** ******\| +31.4 Z=14.8(0.00%) \| Like=19.62..241.87 [1.1994..29.4283] \| it/evals=50/626 eff=inf% N=100 Z=21.2(0.00%) \| Like=25.71..241.87 [1.1994..29.4283] \| it/evals=60/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.69) Quality: ok a: +0.0\|**** * **** ****** **** * ******\| +31.4 b: +0.0\|****** ** * * ****** ******\| +31.4 Z=25.5(0.00%) \| Like=29.64..241.87 [29.6178..62.1019] \| it/evals=70/626 eff=inf% N=100 Z=28.4(0.00%) \| Like=32.87..241.87 [29.6178..62.1019] \| it/evals=80/626 eff=inf% N=100 Z=31.0(0.00%) \| Like=35.17..241.87 [29.6178..62.1019] \| it/evals=90/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.92) Quality: ok a: +0.0\|**** * *** *** **** ****\| +31.4 b: +0.0\|****** *** * ******** * **\| +31.4 Z=34.9(0.00%) \| Like=39.71..241.87 [29.6178..62.1019] \| it/evals=100/626 eff=inf% N=100 Z=39.4(0.00%) \| Like=45.13..241.87 [29.6178..62.1019] \| it/evals=110/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.15) Quality: ok a: +0.0\| ** ***** * **** * * *** ******** *\| +31.4 b: +0.0\|* ** * ** ***** * *\| +31.4 Z=41.4(0.00%) \| Like=46.04..241.87 [29.6178..62.1019] \| it/evals=115/626 eff=inf% N=100 Z=43.4(0.00%) \| Like=49.11..241.87 [29.6178..62.1019] \| it/evals=120/626 eff=inf% N=100 Z=48.4(0.00%) \| Like=54.54..241.87 [29.6178..62.1019] \| it/evals=130/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.38) Quality: ok a: +0.0\| * * ***** ** ******* * ******* \| +31.4 b: +0.0\|* * ** **** ***** ****** \| +31.4 Z=54.8(0.00%) \| Like=60.32..241.87 [29.6178..62.1019] \| it/evals=140/626 eff=inf% N=100 Z=63.7(0.00%) \| Like=69.11..241.87 [62.2053..112.3934] \| it/evals=150/626 eff=inf% N=100 Z=71.7(0.00%) \| Like=77.89..241.87 [62.2053..112.3934] \| it/evals=160/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.61) Quality: ok a: +0.0\| ** * **** *** ***** ***** \| +31.4 b: +0.0\| **** **** ***** * ***** \| +31.4 Z=77.8(0.00%) \| Like=87.30..241.87 [62.2053..112.3934] \| it/evals=170/626 eff=inf% N=100 Z=88.7(0.00%) \| Like=94.79..241.87 [62.2053..112.3934] \| it/evals=180/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.84) Quality: ok a: +0.0\| * * **** * **** **** \| +31.4 b: +0.0\|* ****** *** *** ** \| +31.4 Z=94.6(0.00%) \| Like=100.05..241.87 [62.2053..112.3934] \| it/evals=190/626 eff=inf% N=100 Z=102.1(0.00%) \| Like=108.02..241.87 [62.2053..112.3934] \| it/evals=200/635 eff=2222.2222% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.07) Quality: ok a: +0.0\| * ***** ** ** *** \| +31.4 b: +0.0\| *** * *** ** \| +31.4 Z=107.6(0.00%) \| Like=113.25..241.87 [112.8373..172.1226] \| it/evals=210/686 eff=350.0000% N=100 Z=115.9(0.00%) \| Like=122.26..241.87 [112.8373..172.1226] \| it/evals=220/773 eff=149.6599% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.30) Quality: ok a: +0.0\| * *** ** ** \| +31.4 b: +0.0\| ** ** ** \| +31.4 Z=122.3(0.00%) \| Like=129.85..241.87 [112.8373..172.1226] \| it/evals=230/847 eff=104.0724% N=100 Z=129.8(0.00%) \| Like=136.55..241.87 [112.8373..172.1226] \| it/evals=240/970 eff=69.7674% N=100 Z=137.3(0.00%) \| Like=144.23..241.87 [112.8373..172.1226] \| it/evals=250/1051 eff=58.8235% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.53) Quality: ok a: +3.1e-05\| * * * * \| +3.1e+01 b: +0.0\| ** * ** \| +31.4 Z=142.6(0.00%) \| Like=149.88..241.87 [112.8373..172.1226] \| it/evals=260/1113 eff=53.3881% N=100 Z=150.6(0.00%) \| Like=158.76..242.08 [112.8373..172.1226] \| it/evals=270/1240 eff=43.9739% N=100 Have 17 modes Volume: ~exp(-3.30) Expected Volume: exp(-2.76) Quality: ok a: +3.1e-05\|66 HAFAH 3343 522D5 11191 G77\| +3.1e+01 b: +3.1e-05\|66E 2H22C 94 44 55A75 31131 DDF\| +3.1e+01 Z=155.4(0.00%) \| Like=161.77..242.08 [112.8373..172.1226] \| it/evals=276/1298 eff=41.0714% N=100 Z=157.4(0.00%) \| Like=165.84..242.08 [112.8373..172.1226] \| it/evals=280/1339 eff=39.2707% N=100 Z=163.4(0.00%) \| Like=169.78..242.08 [112.8373..172.1226] \| it/evals=290/1390 eff=37.9581% N=100 Have 11 modes Volume: ~exp(-3.97) * Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05\|61 1AB31 33432 22221 1112 87\| +3.1e+01 b: +3.1e-05\|61 12228 94221 173A1 31131 3B\| +3.1e+01 Z=169.2(0.00%) \| Like=176.32..242.08 [173.9486..199.8262] \| it/evals=299/1456 eff=36.0241% N=100 Z=169.7(0.00%) \| Like=176.48..242.08 [173.9486..199.8262] \| it/evals=300/1464 eff=35.7995% N=100 Z=177.0(0.00%) \| Like=183.98..242.08 [173.9486..199.8262] \| it/evals=310/1544 eff=33.7691% N=100 Z=182.0(0.00%) \| Like=189.03..242.08 [173.9486..199.8262] \| it/evals=320/1653 eff=31.1587% N=100 Have 11 modes Volume: ~exp(-4.06) * Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05\|61 1A111 33432 22221 8112 87\| +3.1e+01 b: +3.1e-05\|61 12288 9421 173A3 1133 3B\| +3.1e+01 Z=182.7(0.00%) \| Like=189.52..242.08 [173.9486..199.8262] \| it/evals=322/1678 eff=30.6084% N=100 Z=185.5(0.00%) \| Like=192.14..242.08 [173.9486..199.8262] \| it/evals=330/1823 eff=27.5689% N=100 Z=187.8(0.00%) \| Like=194.77..242.08 [173.9486..199.8262] \| it/evals=340/1954 eff=25.6024% N=100 Have 9 modes Volume: ~exp(-4.40) * Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05\|69 1311 3432 22221 1112 27\| +3.1e+01 b: +3.1e-05\|82 1221 42 17233 1139 9\| +3.1e+01 Z=189.3(0.00%) \| Like=196.24..242.08 [173.9486..199.8262] \| it/evals=345/2018 eff=24.7845% N=100 Z=190.7(0.00%) \| Like=197.56..242.08 [173.9486..199.8262] \| it/evals=350/2076 eff=24.1379% N=100 Z=193.4(0.00%) \| Like=201.00..242.08 [200.0805..218.4468] \| it/evals=360/2164 eff=23.4070% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05\|69 9391 343 222 1112 27\| +3.1e+01 b: +3.1e-05\|82 221 420 7233 1133 9\| +3.1e+01 Z=197.1(0.00%) \| Like=204.14..242.08 [200.0805..218.4468] \| it/evals=370/2261 eff=22.6300% N=100 Z=200.0(0.00%) \| Like=206.82..242.86 [200.0805..218.4468] \| it/evals=380/2354 eff=21.9907% N=100 Z=203.2(0.00%) \| Like=210.59..242.86 [200.0805..218.4468] \| it/evals=390/2534 eff=20.4403% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05\|69 9391 343 222 1111 27\| +3.1e+01 b: +3.1e-05\|82 221 430 723 113 09\| +3.1e+01 Z=204.7(0.00%) \| Like=211.79..242.86 [200.0805..218.4468] \| it/evals=396/2674 eff=19.3359% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 2692 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.433 +- 0.793 single instance: logZ = 235.433 +- 0.246 bootstrapped : logZ = 235.293 +- 0.385 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 0.0 │▁ ▁ ▇ ▇ ▄ ▃│31.4 18.3 +- 7.5 b : 0 │▄ ▃ ▅ ▁▇ ▃│31 18 +- 11 pointstore: (500, 7) 2066 2692 626 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.830718091502420819e+01,7.461548357996892200e+00,1.886508287133898776e+01,1.252215863233727511e+01,2.522619436377484803e+01,1.764800129533112383e+01,1.076980339796848973e+01,1.894881784854014484e+01,1.822050496151064736e-01,2.510396508290707729e+01 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.307181 7.461548 18.865083 ... 18.948818 0.182205 25.103965 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.307180915024208 checking mean of parameter 'b': 17.648001295331124 checking stdev of parameter 'a': 7.461548357996892 checking stdev of parameter 'b': 10.76980339796849 checking median of parameter 'a': 18.865082871338988 checking median of parameter 'b': 18.948817848540145 checking errlo of parameter 'a': 12.522158632337275 checking errlo of parameter 'b': 0.18220504961510647 checking errup of parameter 'a': 25.226194363774848 checking errup of parameter 'b': 25.103965082907077 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} sampler results: ****************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7927566606506654, 'logz_bs': 235.29290858222754, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.38472081967040594, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22556685337143384, 'posterior': {'mean': [18.307180915024208, 17.648001295331124], 'stdev': [7.461548357996892, 10.76980339796849], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'ncall': 2692, 'paramnames': ['a', 'b'], 'logzerr_single': 0.24562688650372005, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} reader results: ****************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7656270015727977, 'logz_bs': 235.75786154760183, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.32516409952395975, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22000811918063334, 'posterior': {'mean': [18.307180915024208, 17.648001295331113], 'stdev': [7.461548357996893, 10.769803397968483], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () weighted_samples :: upoints (500, 2) weighted_samples :: points (500, 2) weighted_samples :: weights (500,) weighted_samples :: logw (500,) weighted_samples :: logl (500,) maximum_likelihood :: logl () maximum_likelihood :: point (2,) maximum_likelihood :: point_untransformed (2,) insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpgpmiyyvf, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=123, regioncalls=920, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=137, regioncalls=1480, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=149, regioncalls=1960, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=162, regioncalls=2480, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=175, regioncalls=3000, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=188, regioncalls=3520, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=206, regioncalls=4240, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=223, regioncalls=4920, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=244, regioncalls=5760, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=284, regioncalls=7360, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=309, regioncalls=8360, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=341, regioncalls=9640, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=377, regioncalls=11080, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=396, regioncalls=11840, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=441, regioncalls=13640, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=502, regioncalls=16080, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=553, regioncalls=18120, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=584, regioncalls=19360, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 626 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpgpmiyyvf, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [107.94292989 191.2912043 0. 0.57032947 0.98250479 17.91742875 30.86629839]: u=[0.57032947 0.98250479] -> p=[17.91742875 30.86629839] -> L=191.29120430116933 INFO ultranest:integrator.py:2364 Resuming from 300 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=626, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=626, regioncalls=0, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=626, regioncalls=0, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=626, regioncalls=0, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=626, regioncalls=0, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=626, regioncalls=0, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=626, regioncalls=0, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=626, regioncalls=0, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=626, regioncalls=0, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=626, regioncalls=0, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=626, regioncalls=0, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=626, regioncalls=0, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=626, regioncalls=0, ndraw=40, logz=41.41, remainder_fraction=100.0000%, Lmin=46.04, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=626, regioncalls=0, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=626, regioncalls=0, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=626, regioncalls=0, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=626, regioncalls=0, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=626, regioncalls=0, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=626, regioncalls=0, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=626, regioncalls=0, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=626, regioncalls=0, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=635, regioncalls=360, ndraw=40, logz=102.10, remainder_fraction=100.0000%, Lmin=108.02, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=686, regioncalls=2400, ndraw=40, logz=107.58, remainder_fraction=100.0000%, Lmin=113.25, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=773, regioncalls=5880, ndraw=40, logz=115.88, remainder_fraction=100.0000%, Lmin=122.26, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), array([13, 18, 18, 14, 9, 15, 4, 6, 2, 1])) DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=847, regioncalls=8840, ndraw=40, logz=122.33, remainder_fraction=100.0000%, Lmin=129.85, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=970, regioncalls=13760, ndraw=40, logz=129.76, remainder_fraction=100.0000%, Lmin=136.55, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1051, regioncalls=17000, ndraw=40, logz=137.33, remainder_fraction=100.0000%, Lmin=144.23, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]), array([ 8, 13, 5, 6, 8, 3, 8, 5, 8, 6, 9, 5, 5, 4, 6, 1])) DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1113, regioncalls=19480, ndraw=40, logz=142.65, remainder_fraction=100.0000%, Lmin=149.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1240, regioncalls=24560, ndraw=40, logz=150.61, remainder_fraction=100.0000%, Lmin=158.76, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]), array([ 7, 14, 8, 5, 8, 4, 6, 5, 8, 10, 3, 5, 4, 5, 2, 1, 5])) DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=1298, regioncalls=26880, ndraw=40, logz=155.38, remainder_fraction=100.0000%, Lmin=161.77, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1339, regioncalls=28520, ndraw=40, logz=157.41, remainder_fraction=100.0000%, Lmin=165.84, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1390, regioncalls=30560, ndraw=40, logz=163.43, remainder_fraction=100.0000%, Lmin=169.78, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([25, 33, 23, 1, 1, 1, 1, 8, 1, 1, 5])) DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=1456, regioncalls=33200, ndraw=40, logz=169.15, remainder_fraction=100.0000%, Lmin=176.32, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1464, regioncalls=33520, ndraw=40, logz=169.65, remainder_fraction=100.0000%, Lmin=176.48, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1544, regioncalls=36720, ndraw=40, logz=177.02, remainder_fraction=100.0000%, Lmin=183.98, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1653, regioncalls=41080, ndraw=40, logz=182.02, remainder_fraction=100.0000%, Lmin=189.03, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([26, 35, 22, 1, 1, 1, 1, 7, 1, 1, 4])) DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=1678, regioncalls=42080, ndraw=40, logz=182.71, remainder_fraction=100.0000%, Lmin=189.52, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=1823, regioncalls=47880, ndraw=40, logz=185.51, remainder_fraction=100.0000%, Lmin=192.14, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=1954, regioncalls=53120, ndraw=40, logz=187.85, remainder_fraction=100.0000%, Lmin=194.77, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([27, 34, 24, 1, 1, 1, 1, 5, 6])) DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=2018, regioncalls=55680, ndraw=40, logz=189.30, remainder_fraction=100.0000%, Lmin=196.24, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2076, regioncalls=58000, ndraw=40, logz=190.69, remainder_fraction=100.0000%, Lmin=197.56, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2164, regioncalls=61520, ndraw=40, logz=193.38, remainder_fraction=100.0000%, Lmin=201.00, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([29, 28, 28, 1, 1, 1, 1, 6, 5])) DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=2261, regioncalls=65400, ndraw=40, logz=197.14, remainder_fraction=100.0000%, Lmin=204.14, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=2354, regioncalls=69120, ndraw=40, logz=200.04, remainder_fraction=100.0000%, Lmin=206.82, Lmax=242.86 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=2534, regioncalls=76320, ndraw=40, logz=203.21, remainder_fraction=100.0000%, Lmin=210.59, Lmax=242.86 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([35, 23, 27, 1, 1, 1, 1, 6, 5])) DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=2674, regioncalls=81920, ndraw=40, logz=204.73, remainder_fraction=100.0000%, Lmin=211.79, Lmax=242.86 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2692 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_run.py::test_run_resume[0.1]	23.76
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.23) * Expected Volume: exp(0.00) Quality: ok a: +0.000\|*******************************************************\| +1.000 Z=-inf(0.00%) \| Like=-1226.65..3.68 [-1226.6504..-307.9035] \| it/evals=0/528 eff=0.0000% N=400 Z=-951.8(0.00%) \| Like=-945.36..3.68 [-1226.6504..-307.9035] \| it/evals=50/528 eff=39.0625% N=400 Mono-modal Volume: ~exp(-4.49) Expected Volume: exp(-0.23) Quality: ok a: +0.0\| ********************************************** \| +1.0 Z=-786.4(0.00%) \| Like=-779.24..3.68 [-1226.6504..-307.9035] \| it/evals=90/528 eff=70.3125% N=400 Z=-746.9(0.00%) \| Like=-740.63..3.68 [-1226.6504..-307.9035] \| it/evals=100/528 eff=78.1250% N=400 Z=-725.7(0.00%) \| Like=-717.99..3.68 [-1226.6504..-307.9035] \| it/evals=107/629 eff=46.7249% N=400 Z=-573.3(0.00%) \| Like=-561.83..3.69 [-1226.6504..-307.9035] \| it/evals=150/629 eff=65.5022% N=400 Have 2 modes Volume: ~exp(-4.72) * Expected Volume: exp(-0.45) Quality: ok a: +0.0\| 222222111111111111111111111111111111 +0.8 \| +1.0 Z=-499.7(0.00%) \| Like=-493.61..3.69 [-1226.6504..-307.9035] \| it/evals=180/629 eff=78.6026% N=400 Z=-463.6(0.00%) \| Like=-456.60..3.69 [-1226.6504..-307.9035] \| it/evals=200/717 eff=63.0915% N=400 Z=-374.7(0.00%) \| Like=-364.11..3.69 [-1226.6504..-307.9035] \| it/evals=250/717 eff=78.8644% N=400 Have 2 modes Volume: ~exp(-4.91) * Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.2 222111111111111111111111111111 +0.8 \| +1.0 Z=-327.4(0.00%) \| Like=-320.54..3.69 [-1226.6504..-307.9035] \| it/evals=270/783 eff=70.4961% N=400 Z=-278.7(0.00%) \| Like=-269.85..3.69 [-307.6123..-69.3248] \| it/evals=300/783 eff=78.3290% N=400 Z=-208.4(0.00%) \| Like=-201.38..3.69 [-307.6123..-69.3248] \| it/evals=350/842 eff=79.1855% N=400 Mono-modal Volume: ~exp(-5.13) * Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 Z=-201.8(0.00%) \| Like=-195.89..3.69 [-307.6123..-69.3248] \| it/evals=360/842 eff=81.4480% N=400 Z=-168.6(0.00%) \| Like=-162.35..3.69 [-307.6123..-69.3248] \| it/evals=400/890 eff=81.6327% N=400 Mono-modal Volume: ~exp(-5.45) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 **************** +0.7 \| +1.0 Z=-127.9(0.00%) \| Like=-120.12..3.69 [-307.6123..-69.3248] \| it/evals=450/938 eff=83.6431% N=400 Z=-102.3(0.00%) \| Like=-95.31..3.69 [-307.6123..-69.3248] \| it/evals=500/983 eff=85.7633% N=400 Mono-modal Volume: ~exp(-5.45) Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 ************* +0.6 \| +1.0 Z=-81.9(0.00%) \| Like=-75.87..3.69 [-307.6123..-69.3248] \| it/evals=540/1015 eff=87.8049% N=400 Z=-76.3(0.00%) \| Like=-67.48..3.69 [-67.4783..-14.2446] \| it/evals=550/1045 eff=85.2713% N=400 Z=-61.9(0.00%) \| Like=-54.84..3.69 [-67.4783..-14.2446] \| it/evals=594/1097 eff=85.2224% N=400 Z=-59.7(0.00%) \| Like=-53.11..3.69 [-67.4783..-14.2446] \| it/evals=600/1097 eff=86.0832% N=400 Mono-modal Volume: ~exp(-5.73) * Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 ************ +0.6 \| +1.0 Z=-50.8(0.00%) \| Like=-44.90..3.69 [-67.4783..-14.2446] \| it/evals=630/1119 eff=87.6217% N=400 Z=-46.9(0.00%) \| Like=-40.98..3.69 [-67.4783..-14.2446] \| it/evals=650/1149 eff=86.7824% N=400 Z=-37.7(0.00%) \| Like=-31.30..3.69 [-67.4783..-14.2446] \| it/evals=692/1202 eff=86.2843% N=400 Z=-36.3(0.00%) \| Like=-30.34..3.69 [-67.4783..-14.2446] \| it/evals=700/1202 eff=87.2818% N=400 Have 2 modes Volume: ~exp(-5.93) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 1111111111 +0.6 \| +1.0 Z=-33.3(0.00%) \| Like=-27.63..3.69 [-67.4783..-14.2446] \| it/evals=720/1220 eff=87.8049% N=400 Z=-28.5(0.00%) \| Like=-22.72..3.69 [-67.4783..-14.2446] \| it/evals=750/1241 eff=89.1795% N=400 Z=-22.7(0.00%) \| Like=-17.23..3.69 [-67.4783..-14.2446] \| it/evals=800/1304 eff=88.4956% N=400 Mono-modal Volume: ~exp(-5.99) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-21.8(0.00%) \| Like=-15.95..3.69 [-67.4783..-14.2446] \| it/evals=810/1321 eff=87.9479% N=400 Z=-18.2(0.00%) \| Like=-12.48..3.69 [-14.1709..-1.0696] \| it/evals=850/1358 eff=88.7265% N=400 Z=-14.8(0.00%) \| Like=-9.25..3.69 [-14.1709..-1.0696] \| it/evals=899/1408 eff=89.1865% N=400 Mono-modal Volume: ~exp(-6.39) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 Z=-14.7(0.00%) \| Like=-9.22..3.69 [-14.1709..-1.0696] \| it/evals=900/1408 eff=89.2857% N=400 Z=-12.3(0.00%) \| Like=-6.68..3.69 [-14.1709..-1.0696] \| it/evals=943/1454 eff=89.4687% N=400 Z=-11.8(0.00%) \| Like=-6.10..3.69 [-14.1709..-1.0696] \| it/evals=950/1454 eff=90.1328% N=400 Mono-modal Volume: ~exp(-6.42) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.46 ****** +0.54 \| +1.00 Z=-10.0(0.00%) \| Like=-4.75..3.69 [-14.1709..-1.0696] \| it/evals=990/1495 eff=90.4110% N=400 Z=-9.6(0.01%) \| Like=-4.29..3.69 [-14.1709..-1.0696] \| it/evals=1000/1510 eff=90.0901% N=400 Z=-7.8(0.04%) \| Like=-2.56..3.69 [-14.1709..-1.0696] \| it/evals=1050/1560 eff=90.5172% N=400 Mono-modal Volume: ~exp(-6.94) * Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-6.9(0.10%) \| Like=-1.64..3.69 [-14.1709..-1.0696] \| it/evals=1080/1589 eff=90.8326% N=400 Z=-6.3(0.18%) \| Like=-1.10..3.69 [-14.1709..-1.0696] \| it/evals=1100/1608 eff=91.0596% N=400 Z=-5.5(0.41%) \| Like=-0.43..3.69 [-1.0251..1.4019] \| it/evals=1133/1647 eff=90.8581% N=400 Z=-5.1(0.58%) \| Like=-0.12..3.69 [-1.0251..1.4019] \| it/evals=1150/1662 eff=91.1252% N=400 Mono-modal Volume: ~exp(-6.94) Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-4.7(0.87%) \| Like=0.36..3.69 [-1.0251..1.4019] \| it/evals=1170/1688 eff=90.8385% N=400 Z=-4.1(1.56%) \| Like=0.95..3.69 [-1.0251..1.4019] \| it/evals=1200/1714 eff=91.3242% N=400 Z=-3.4(3.05%) \| Like=1.50..3.69 [1.4141..1.7303] \| it/evals=1240/1753 eff=91.6482% N=400 Z=-3.3(3.55%) \| Like=1.65..3.69 [1.4141..1.7303] \| it/evals=1250/1768 eff=91.3743% N=400 Mono-modal Volume: ~exp(-7.60) * Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.48 **** +0.52 \| +1.00 Z=-3.1(4.13%) \| Like=1.78..3.69 [1.7755..1.7957] \| it/evals=1260/1785 eff=90.9747% N=400 Z=-2.7(6.23%) \| Like=2.01..3.69 [2.0136..2.0168]\| it/evals=1293/1817 eff=91.2491% N=400 Z=-2.6(6.75%) \| Like=2.07..3.69 [2.0671..2.0678]\| it/evals=1300/1820 eff=91.5493% N=400 Z=-2.4(8.84%) \| Like=2.21..3.69 [2.1969..2.2100] \| it/evals=1328/1851 eff=91.5231% N=400 Mono-modal Volume: ~exp(-7.60) Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.2(10.66%) \| Like=2.32..3.69 [2.3213..2.3252]\| it/evals=1350/1878 eff=91.3396% N=400 Z=-2.0(13.43%) \| Like=2.52..3.69 [2.5109..2.5211] \| it/evals=1382/1910 eff=91.5232% N=400 Z=-1.8(15.17%) \| Like=2.60..3.69 [2.5988..2.6022]\| it/evals=1400/1928 eff=91.6230% N=400 Mono-modal Volume: ~exp(-7.81) * Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.6(19.27%) \| Like=2.78..3.69 [2.7802..2.7819]\| it/evals=1440/1969 eff=91.7782% N=400 Z=-1.5(20.35%) \| Like=2.83..3.69 [2.8275..2.8304]\| it/evals=1450/1978 eff=91.8885% N=400 Z=-1.3(25.82%) \| Like=3.03..3.69 [3.0320..3.0340]\| it/evals=1499/2029 eff=92.0196% N=400 Z=-1.3(25.93%) \| Like=3.03..3.69 [3.0340..3.0340]\| it/evals=1500/2029 eff=92.0810% N=400 Mono-modal Volume: ~exp(-8.19) * Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.2(29.56%) \| Like=3.15..3.69 [3.1450..3.1456]\| it/evals=1530/2062 eff=92.0578% N=400 Z=-1.1(31.96%) \| Like=3.20..3.69 [3.2018..3.2042]\| it/evals=1550/2080 eff=92.2619% N=400 Z=-1.0(35.28%) \| Like=3.26..3.69 [3.2569..3.2604]\| it/evals=1577/2219 eff=86.6960% N=400 Z=-0.9(38.04%) \| Like=3.31..3.69 [3.3108..3.3130]\| it/evals=1600/2219 eff=87.9604% N=400 Mono-modal Volume: ~exp(-8.23) * Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.9(40.40%) \| Like=3.34..3.69 [3.3439..3.3448]\| it/evals=1620/2219 eff=89.0599% N=400 Z=-0.8(43.85%) \| Like=3.40..3.69 [3.3956..3.3965]\| it/evals=1650/2219 eff=90.7092% N=400 Z=-0.7(47.86%) \| Like=3.44..3.69 [3.4382..3.4385]\| it/evals=1685/2336 eff=87.0351% N=400 Z=-0.7(49.50%) \| Like=3.45..3.69 [3.4511..3.4523]\| it/evals=1700/2336 eff=87.8099% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(50.57%) \| Like=3.46..3.69 [3.4593..3.4621]\| it/evals=1710/2336 eff=88.3264% N=400 Z=-0.6(54.69%) \| Like=3.50..3.69 [3.5027..3.5030]\| it/evals=1750/2336 eff=90.3926% N=400 Z=-0.5(57.91%) \| Like=3.53..3.69 [3.5284..3.5286]\| it/evals=1783/2439 eff=87.4448% N=400 Mono-modal Volume: ~exp(-8.57) Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.5(59.50%) \| Like=3.54..3.69 [3.5412..3.5415]\| it/evals=1800/2439 eff=88.2786% N=400 Z=-0.4(63.91%) \| Like=3.57..3.69 [3.5739..3.5746]\| it/evals=1850/2439 eff=90.7308% N=400 Mono-modal Volume: ~exp(-8.57) Expected Volume: exp(-4.73) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.3(67.80%) \| Like=3.60..3.69 [3.5966..3.5972]\| it/evals=1899/2479 eff=91.3420% N=400 Z=-0.3(67.87%) \| Like=3.60..3.69 [3.5972..3.5973]\| it/evals=1900/2479 eff=91.3901% N=400 Z=-0.3(71.47%) \| Like=3.62..3.69 [3.6209..3.6212]\| it/evals=1950/2531 eff=91.5063% N=400 Mono-modal Volume: ~exp(-9.06) Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.3(73.46%) \| Like=3.63..3.69 [3.6274..3.6276]\| it/evals=1980/2559 eff=91.7091% N=400 Z=-0.2(74.71%) \| Like=3.63..3.69 [3.6330..3.6334]\| it/evals=2000/2586 eff=91.4913% N=400 Z=-0.2(77.60%) \| Like=3.65..3.69 [3.6475..3.6477]\| it/evals=2050/2641 eff=91.4770% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.2(78.67%) \| Like=3.65..3.69 [3.6506..3.6507]\| it/evals=2070/2655 eff=91.7960% N=400 Z=-0.2(80.17%) \| Like=3.66..3.69 [3.6553..3.6553]\| it/evals=2100/2687 eff=91.8233% N=400 Z=-0.2(81.80%) \| Like=3.66..3.69 [3.6603..3.6604]\| it/evals=2135/2729 eff=91.6702% N=400 Z=-0.1(82.46%) \| Like=3.66..3.69 [3.6619..3.6620]\| it/evals=2150/2739 eff=91.9196% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.1(84.49%) \| Like=3.67..3.69 [3.6671..3.6671]\| it/evals=2200/2790 eff=92.0502% N=400 Have 2 modes Volume: ~exp(-9.64) Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 21 +0.502 \| +1.000 Z=-0.1(86.30%) \| Like=3.67..3.69 [3.6702..3.6703]\| it/evals=2250/2849 eff=91.8742% N=400 Z=-0.1(87.89%) \| Like=3.67..3.69 [3.6740..3.6740]\| it/evals=2300/2965 eff=89.6686% N=400 Mono-modal Volume: ~exp(-10.03) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(89.04%) \| Like=3.68..3.69 [3.6757..3.6757]\| it/evals=2340/2965 eff=91.2281% N=400 Z=-0.1(89.31%) \| Like=3.68..3.69 [3.6761..3.6761]\| it/evals=2350/2965 eff=91.6179% N=400 Z=-0.1(90.56%) \| Like=3.68..3.69 [3.6781..3.6781]\| it/evals=2400/3088 eff=89.2857% N=400 Mono-modal Volume: ~exp(-10.26) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(91.23%) \| Like=3.68..3.69 [3.6794..3.6795]\| it/evals=2430/3088 eff=90.4018% N=400 Z=-0.0(91.66%) \| Like=3.68..3.69 [3.6800..3.6801]\| it/evals=2450/3088 eff=91.1458% N=400 Z=-0.0(92.64%) \| Like=3.68..3.69 [3.6811..3.6812]\| it/evals=2500/3207 eff=89.0631% N=400 Mono-modal Volume: ~exp(-10.26) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 * +0.501 \| +1.000 Z=-0.0(93.50%) \| Like=3.68..3.69 [3.6822..3.6822]\| it/evals=2550/3207 eff=90.8443% N=400 Z=-0.0(94.26%) \| Like=3.68..3.69 [3.6832..3.6832]\| it/evals=2600/3311 eff=89.3164% N=400 Mono-modal Volume: ~exp(-10.31) * Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(94.40%) \| Like=3.68..3.69 [3.6833..3.6833]\| it/evals=2610/3311 eff=89.6599% N=400 Z=-0.0(94.93%) \| Like=3.68..3.69 [3.6836..3.6836]\| it/evals=2650/3311 eff=91.0340% N=400 Z=-0.0(95.39%) \| Like=3.68..3.69 [3.6841..3.6841]\| it/evals=2688/3359 eff=90.8415% N=400 Mono-modal Volume: ~exp(-10.83) Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(95.53%) \| Like=3.68..3.69 [3.6842..3.6842]\| it/evals=2700/3372 eff=90.8479% N=400 Z=-0.0(95.61%) \| Like=3.68..3.69 [3.6842..3.6842]\| it/evals=2707/3486 eff=87.7187% N=400 Z=0.0(96.05%) \| Like=3.68..3.69 [3.6846..3.6846]\| it/evals=2750/3486 eff=89.1121% N=400 Mono-modal Volume: ~exp(-10.98) Expected Volume: exp(-6.98) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=0.0(96.43%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2790/3486 eff=90.4083% N=400 Z=0.0(96.52%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2800/3486 eff=90.7323% N=400 Z=0.0(96.93%) \| Like=3.69..3.69 [3.6852..3.6852]\| it/evals=2850/3537 eff=90.8511% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3551 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.04562 +- 0.06643 [ultranest] Effective samples strategy satisfied (ESS = 1262.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 572 minimum live points (dlogz from 0.05 to 0.16, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 [ultranest] Widening roots to 572 live points (have 400 already) ... [ultranest] Sampling 172 live points from prior ... Mono-modal Volume: ~exp(-4.63) Expected Volume: exp(0.00) Quality: ok a: +0.000\|*******************************************************\| +1.000 Z=-inf(0.00%) \| Like=-1233.27..3.69 [-1233.2658..-318.2188] \| it/evals=0/3851 eff=0.0000% N=572 Z=-899.8(0.00%) \| Like=-891.00..3.69 [-1233.2658..-318.2188] \| it/evals=93/3851 eff=25.7812% N=572 Mono-modal Volume: ~exp(-4.66) Expected Volume: exp(-0.22) Quality: ok a: +0.00\| ********************************************** \| +1.00 Z=-813.2(0.00%) \| Like=-806.92..3.69 [-1233.2658..-318.2188] \| it/evals=128/3851 eff=33.5938% N=572 Z=-623.8(0.00%) \| Like=-616.62..3.69 [-1233.2658..-318.2188] \| it/evals=200/3851 eff=53.1250% N=572 Mono-modal Volume: ~exp(-4.77) * Expected Volume: exp(-0.46) Quality: ok a: +0.0\| ************************************ +0.8 \| +1.0 Z=-511.7(0.00%) \| Like=-503.81..3.69 [-1233.2658..-318.2188] \| it/evals=264/3851 eff=67.9688% N=572 Z=-365.3(0.00%) \| Like=-354.29..3.69 [-1233.2658..-318.2188] \| it/evals=367/3925 eff=55.4455% N=572 Mono-modal Volume: ~exp(-5.12) * Expected Volume: exp(-0.69) Quality: ok a: +0.0\| +0.2 ****************************** +0.8 \| +1.0 Z=-325.4(0.00%) \| Like=-318.31..3.69 [-1233.2658..-318.2188] \| it/evals=392/3925 eff=59.4059% N=572 Z=-265.5(0.00%) \| Like=-258.66..3.69 [-318.1270..-72.8697] \| it/evals=450/3925 eff=69.3069% N=572 Mono-modal Volume: ~exp(-5.23) * Expected Volume: exp(-0.91) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 Z=-203.2(0.00%) \| Like=-196.97..3.69 [-318.1270..-72.8697] \| it/evals=521/3987 eff=62.1212% N=572 Z=-188.1(0.00%) \| Like=-181.88..3.69 [-318.1270..-72.8697] \| it/evals=550/3987 eff=63.2576% N=572 Mono-modal Volume: ~exp(-5.66) * Expected Volume: exp(-1.14) Quality: ok a: +0.0\| +0.3 ****************** +0.7 \| +1.0 Z=-126.4(0.00%) \| Like=-119.36..3.69 [-318.1270..-72.8697] \| it/evals=651/4041 eff=62.5786% N=572 Z=-85.8(0.00%) \| Like=-78.37..3.69 [-318.1270..-72.8697] \| it/evals=764/4081 eff=65.3631% N=572 Mono-modal Volume: ~exp(-5.90) * Expected Volume: exp(-1.37) Quality: ok a: +0.0\| +0.4 *************** +0.6 \| +1.0 Z=-81.5(0.00%) \| Like=-74.83..3.69 [-318.1270..-72.8697] \| it/evals=783/4081 eff=67.3184% N=572 Z=-63.9(0.00%) \| Like=-57.76..3.69 [-72.7839..-14.8005] \| it/evals=850/4112 eff=67.6093% N=572 Mono-modal Volume: ~exp(-6.11) * Expected Volume: exp(-1.60) Quality: ok a: +0.0\| +0.4 ************ +0.6 \| +1.0 Z=-49.8(0.00%) \| Like=-43.68..3.69 [-72.7839..-14.8005] \| it/evals=914/4112 eff=71.2082% N=572 Z=-34.6(0.00%) \| Like=-28.39..3.69 [-72.7839..-14.8005] \| it/evals=1031/4159 eff=72.9358% N=572 Mono-modal Volume: ~exp(-6.17) * Expected Volume: exp(-1.82) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-33.2(0.00%) \| Like=-27.07..3.69 [-72.7839..-14.8005] \| it/evals=1043/4159 eff=73.6239% N=572 Z=-27.4(0.00%) \| Like=-21.42..3.69 [-72.7839..-14.8005] \| it/evals=1100/4189 eff=73.1760% N=572 Mono-modal Volume: ~exp(-6.32) * Expected Volume: exp(-2.05) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-21.6(0.00%) \| Like=-15.84..3.69 [-72.7839..-14.8005] \| it/evals=1173/4209 eff=74.2798% N=572 Z=-19.8(0.00%) \| Like=-13.99..3.69 [-14.7621..-1.1236] \| it/evals=1200/4223 eff=73.8000% N=572 Mono-modal Volume: ~exp(-6.95) * Expected Volume: exp(-2.28) Quality: ok a: +0.0\| +0.5 **** +0.6 \| +1.0 Z=-14.2(0.00%) \| Like=-8.82..3.69 [-14.7621..-1.1236] \| it/evals=1302/4238 eff=76.1165% N=572 Z=-9.9(0.00%) \| Like=-4.80..3.69 [-14.7621..-1.1236] \| it/evals=1419/4282 eff=76.9231% N=572 Mono-modal Volume: ~exp(-6.95) Expected Volume: exp(-2.50) Quality: ok a: +0.00\| +0.46 **** +0.54 \| +1.00 Z=-8.0(0.03%) \| Like=-2.75..3.69 [-14.7621..-1.1236] \| it/evals=1500/4317 eff=76.5993% N=572 Mono-modal Volume: ~exp(-7.44) * Expected Volume: exp(-2.73) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-6.6(0.13%) \| Like=-1.36..3.69 [-14.7621..-1.1236] \| it/evals=1561/4348 eff=75.6800% N=572 Z=-5.0(0.62%) \| Like=0.04..3.69 [-1.1141..1.0398] \| it/evals=1650/4367 eff=76.5528% N=572 Mono-modal Volume: ~exp(-7.44) Expected Volume: exp(-2.95) Quality: ok a: +0.00\| +0.48 +0.52 \| +1.00 Z=-4.4(1.12%) \| Like=0.60..3.69 [-1.1141..1.0398] \| it/evals=1689/4389 eff=75.6757% N=572 Z=-3.7(2.42%) \| Like=1.27..3.69 [1.0412..1.3033] \| it/evals=1750/4416 eff=75.4690% N=572 Z=-3.1(4.09%) \| Like=1.72..3.69 [1.6978..1.7207] \| it/evals=1800/4451 eff=75.0000% N=572 Mono-modal Volume: ~exp(-7.44) Expected Volume: exp(-3.18) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.8(5.71%) \| Like=1.95..3.69 [1.9514..1.9675] \| it/evals=1837/4459 eff=75.2717% N=572 Mono-modal Volume: ~exp(-8.13) * Expected Volume: exp(-3.41) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.1(11.75%) \| Like=2.39..3.69 [2.3870..2.3880]\| it/evals=1948/4503 eff=74.3590% N=572 Z=-2.1(11.89%) \| Like=2.39..3.69 [2.3894..2.3901]\| it/evals=1950/4503 eff=74.6154% N=572 Z=-1.8(15.35%) \| Like=2.60..3.69 [2.5990..2.6022]\| it/evals=2003/4524 eff=75.1561% N=572 Mono-modal Volume: ~exp(-8.13) Expected Volume: exp(-3.64) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 Z=-1.5(21.10%) \| Like=2.86..3.69 [2.8617..2.8623]\| it/evals=2082/4550 eff=75.2116% N=572 Z=-1.1(30.76%) \| Like=3.15..3.69 [3.1517..3.1525]\| it/evals=2201/4618 eff=74.5251% N=572 Mono-modal Volume: ~exp(-8.47) * Expected Volume: exp(-3.86) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.1(31.51%) \| Like=3.18..3.69 [3.1755..3.1764]\| it/evals=2210/4618 eff=74.7486% N=572 Z=-1.0(33.58%) \| Like=3.21..3.69 [3.2093..3.2105]\| it/evals=2235/4756 eff=65.8277% N=572 Mono-modal Volume: ~exp(-8.47) Expected Volume: exp(-4.09) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.8(42.09%) \| Like=3.36..3.69 [3.3631..3.3633]\| it/evals=2338/4756 eff=68.3446% N=572 Z=-0.8(43.08%) \| Like=3.38..3.69 [3.3774..3.3790]\| it/evals=2350/4756 eff=68.9255% N=572 Z=-0.6(50.85%) \| Like=3.46..3.69 [3.4635..3.4638]\| it/evals=2450/4756 eff=71.4424% N=572 Mono-modal Volume: ~exp(-8.88) Expected Volume: exp(-4.31) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(52.11%) \| Like=3.48..3.69 [3.4765..3.4765]\| it/evals=2467/4756 eff=71.9264% N=572 Z=-0.5(60.59%) \| Like=3.55..3.69 [3.5495..3.5499]\| it/evals=2592/4778 eff=74.0284% N=572 Mono-modal Volume: ~exp(-9.09) * Expected Volume: exp(-4.54) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.5(60.97%) \| Like=3.55..3.69 [3.5520..3.5533]\| it/evals=2598/4778 eff=74.1232% N=572 Z=-0.5(61.10%) \| Like=3.55..3.69 [3.5539..3.5550]\| it/evals=2600/4778 eff=74.2180% N=572 Z=-0.4(63.84%) \| Like=3.57..3.69 [3.5736..3.5736]\| it/evals=2645/4911 eff=67.0034% N=572 Mono-modal Volume: ~exp(-9.41) Expected Volume: exp(-4.77) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.3(68.32%) \| Like=3.60..3.69 [3.5992..3.5993]\| it/evals=2726/4911 eff=69.1077% N=572 Z=-0.3(74.24%) \| Like=3.63..3.69 [3.6292..3.6295]\| it/evals=2850/4911 eff=72.7273% N=572 Mono-modal Volume: ~exp(-9.41) Expected Volume: exp(-4.99) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.2(76.33%) \| Like=3.64..3.69 [3.6408..3.6409]\| it/evals=2900/4911 eff=73.9057% N=572 Z=-0.2(78.26%) \| Like=3.65..3.69 [3.6484..3.6485]\| it/evals=2950/4936 eff=73.7840% N=572 Mono-modal Volume: ~exp(-9.50) * Expected Volume: exp(-5.22) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.2(79.52%) \| Like=3.65..3.69 [3.6519..3.6521]\| it/evals=2985/4952 eff=73.3930% N=572 Z=-0.2(80.45%) \| Like=3.66..3.69 [3.6554..3.6554]\| it/evals=3012/5079 eff=67.1091% N=572 Mono-modal Volume: ~exp(-9.95) * Expected Volume: exp(-5.44) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.1(83.59%) \| Like=3.66..3.69 [3.6638..3.6638]\| it/evals=3114/5079 eff=69.8378% N=572 Z=-0.1(85.07%) \| Like=3.67..3.69 [3.6672..3.6672]\| it/evals=3169/5079 eff=71.2389% N=572 Mono-modal Volume: ~exp(-9.95) Expected Volume: exp(-5.67) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.1(86.84%) \| Like=3.67..3.69 [3.6704..3.6704]\| it/evals=3242/5079 eff=72.8614% N=572 Z=-0.1(89.09%) \| Like=3.68..3.69 [3.6751..3.6751]\| it/evals=3350/5113 eff=73.4532% N=572 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-5.90) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(89.59%) \| Like=3.68..3.69 [3.6759..3.6760]\| it/evals=3377/5124 eff=73.5189% N=572 Z=-0.1(90.83%) \| Like=3.68..3.69 [3.6780..3.6781]\| it/evals=3450/5253 eff=68.6275% N=572 Z=-0.0(91.59%) \| Like=3.68..3.69 [3.6796..3.6796]\| it/evals=3500/5253 eff=69.8039% N=572 Have 2 modes Volume: ~exp(-10.52) Expected Volume: exp(-6.13) Quality: ok a: +0.000\| +0.499 11 +0.501 \| +1.000 Z=-0.0(91.71%) \| Like=3.68..3.69 [3.6798..3.6798]\| it/evals=3508/5253 eff=69.9346% N=572 Z=-0.0(92.94%) \| Like=3.68..3.69 [3.6812..3.6812]\| it/evals=3600/5253 eff=71.6340% N=572 Have 2 modes Volume: ~exp(-10.82) * Expected Volume: exp(-6.36) Quality: ok a: +0.000\| +0.499 11 +0.501 \| +1.000 Z=-0.0(93.37%) \| Like=3.68..3.69 [3.6818..3.6818]\| it/evals=3636/5253 eff=72.6144% N=572 Mono-modal Volume: ~exp(-10.97) Expected Volume: exp(-6.58) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(94.69%) \| Like=3.68..3.69 [3.6833..3.6834]\| it/evals=3764/5272 eff=73.9832% N=572 Z=-0.0(94.70%) \| Like=3.68..3.69 [3.6834..3.6834]\| it/evals=3765/5391 eff=68.7650% N=572 Z=-0.0(95.02%) \| Like=3.68..3.69 [3.6836..3.6836]\| it/evals=3800/5391 eff=69.0048% N=572 Z=-0.0(95.43%) \| Like=3.68..3.69 [3.6840..3.6840]\| it/evals=3850/5391 eff=69.7242% N=572 Mono-modal Volume: ~exp(-11.17) * Expected Volume: exp(-6.81) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(95.76%) \| Like=3.68..3.69 [3.6843..3.6843]\| it/evals=3893/5391 eff=70.5036% N=572 Z=0.0(96.16%) \| Like=3.68..3.69 [3.6846..3.6847]\| it/evals=3950/5391 eff=71.5228% N=572 Z=0.0(96.49%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=4000/5391 eff=72.1823% N=572 Mono-modal Volume: ~exp(-11.26) Expected Volume: exp(-7.05) Quality: ok a: +0.0000\| +0.4995 ** +0.5005 \| +1.0000 Z=0.0(96.68%) \| Like=3.69..3.69 [3.6850..3.6850]\| it/evals=4032/5391 eff=72.6619% N=572 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 5391 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.04684 +- 0.05136 [ultranest] Effective samples strategy satisfied (ESS = 1807.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 570 minimum live points (dlogz from 0.04 to 0.18, need <0.1) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.03 total:0.06 required:<0.10 [ultranest] done iterating. logZ = 0.041 +- 0.181 single instance: logZ = 0.041 +- 0.074 bootstrapped : logZ = 0.047 +- 0.178 tail : logZ = +- 0.030 insert order U test : converged: True correlation: inf iterations a : 0.459 │ ▁ ▁▁▁▁▁▁▁▁▂▃▄▄▅▆▇▇▇▇▇▆▅▅▄▃▃▃▁▁▁▁▁▁▁▁▁ │0.539 0.500 +- 0.010 [ultranest] Resuming from 5048 stored points Mono-modal Volume: ~exp(-4.31) Expected Volume: exp(0.00) Quality: ok a: +0.000\|*******************************************************\| +1.000 Z=-inf(0.00%) \| Like=-1226.65..3.68 [-1226.6504..-307.9035] \| it/evals=0/5391 eff=inf% N=400 Z=-951.8(0.00%) \| Like=-945.36..3.68 [-1226.6504..-307.9035] \| it/evals=50/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-4.41) Expected Volume: exp(-0.23) Quality: ok a: +0.0\| ********************************************** \| +1.0 Z=-786.4(0.00%) \| Like=-779.24..3.68 [-1226.6504..-307.9035] \| it/evals=90/5391 eff=inf% N=400 Z=-746.9(0.00%) \| Like=-740.63..3.68 [-1226.6504..-307.9035] \| it/evals=100/5391 eff=inf% N=400 Z=-573.3(0.00%) \| Like=-561.83..3.69 [-1226.6504..-307.9035] \| it/evals=150/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-4.64) * Expected Volume: exp(-0.45) Quality: ok a: +0.0\| 222222111111111111111111111111111111 +0.8 \| +1.0 Z=-499.7(0.00%) \| Like=-493.61..3.69 [-1226.6504..-307.9035] \| it/evals=180/5391 eff=inf% N=400 Z=-463.6(0.00%) \| Like=-456.60..3.69 [-1226.6504..-307.9035] \| it/evals=200/5391 eff=inf% N=400 Z=-374.7(0.00%) \| Like=-364.11..3.69 [-1226.6504..-307.9035] \| it/evals=250/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-4.64) Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.2 222111111111111111111111111111 +0.8 \| +1.0 Z=-278.7(0.00%) \| Like=-269.85..3.69 [-307.6123..-69.3248] \| it/evals=300/5391 eff=inf% N=400 Z=-208.4(0.00%) \| Like=-201.38..3.69 [-307.6123..-69.3248] \| it/evals=350/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-4.82) * Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 Z=-201.8(0.00%) \| Like=-195.89..3.69 [-307.6123..-69.3248] \| it/evals=360/5391 eff=inf% N=400 Z=-168.6(0.00%) \| Like=-162.35..3.69 [-307.6123..-69.3248] \| it/evals=400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.28) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 **************** +0.7 \| +1.0 Z=-127.9(0.00%) \| Like=-120.12..3.69 [-307.6123..-69.3248] \| it/evals=450/5391 eff=inf% N=400 Z=-102.3(0.00%) \| Like=-95.31..3.69 [-307.6123..-69.3248] \| it/evals=500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.28) Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 ************* +0.6 \| +1.0 Z=-76.3(0.00%) \| Like=-67.48..3.69 [-67.4783..-14.2446] \| it/evals=550/5391 eff=inf% N=400 Z=-59.7(0.00%) \| Like=-53.11..3.69 [-67.4783..-14.2446] \| it/evals=600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.89) * Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 ************ +0.6 \| +1.0 Z=-50.8(0.00%) \| Like=-44.90..3.69 [-67.4783..-14.2446] \| it/evals=630/5391 eff=inf% N=400 Z=-46.9(0.00%) \| Like=-40.98..3.69 [-67.4783..-14.2446] \| it/evals=650/5391 eff=inf% N=400 Z=-36.3(0.00%) \| Like=-30.34..3.69 [-67.4783..-14.2446] \| it/evals=700/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-6.17) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 1111111111 +0.6 \| +1.0 Z=-33.3(0.00%) \| Like=-27.63..3.69 [-67.4783..-14.2446] \| it/evals=720/5391 eff=inf% N=400 Z=-28.5(0.00%) \| Like=-22.72..3.69 [-67.4783..-14.2446] \| it/evals=750/5391 eff=inf% N=400 Z=-22.7(0.00%) \| Like=-17.23..3.69 [-67.4783..-14.2446] \| it/evals=800/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.29) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-21.8(0.00%) \| Like=-15.95..3.69 [-67.4783..-14.2446] \| it/evals=810/5391 eff=inf% N=400 Z=-18.2(0.00%) \| Like=-12.48..3.69 [-14.1709..-1.0696] \| it/evals=850/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.40) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 Z=-14.7(0.00%) \| Like=-9.22..3.69 [-14.1709..-1.0696] \| it/evals=900/5391 eff=inf% N=400 Z=-11.8(0.00%) \| Like=-6.10..3.69 [-14.1709..-1.0696] \| it/evals=950/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.75) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.46 **** +0.54 \| +1.00 Z=-10.0(0.00%) \| Like=-4.75..3.69 [-14.1709..-1.0696] \| it/evals=990/5391 eff=inf% N=400 Z=-9.6(0.01%) \| Like=-4.29..3.69 [-14.1709..-1.0696] \| it/evals=1000/5391 eff=inf% N=400 Z=-7.8(0.04%) \| Like=-2.56..3.69 [-14.1709..-1.0696] \| it/evals=1050/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.75) Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-6.3(0.18%) \| Like=-1.10..3.69 [-14.1709..-1.0696] \| it/evals=1100/5391 eff=inf% N=400 Z=-5.1(0.58%) \| Like=-0.12..3.69 [-1.0251..1.4019] \| it/evals=1150/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.01) * Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 **** +0.53 \| +1.00 Z=-4.7(0.87%) \| Like=0.36..3.69 [-1.0251..1.4019] \| it/evals=1170/5391 eff=inf% N=400 Z=-4.1(1.56%) \| Like=0.95..3.69 [-1.0251..1.4019] \| it/evals=1200/5391 eff=inf% N=400 Z=-3.3(3.55%) \| Like=1.65..3.69 [1.4141..1.7303] \| it/evals=1250/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.20) * Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.48 **** +0.52 \| +1.00 Z=-3.1(4.13%) \| Like=1.78..3.69 [1.7755..1.7957] \| it/evals=1260/5391 eff=inf% N=400 Z=-2.6(6.75%) \| Like=2.07..3.69 [2.0671..2.0678]\| it/evals=1300/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.70) Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.2(10.66%) \| Like=2.32..3.69 [2.3213..2.3252]\| it/evals=1350/5391 eff=inf% N=400 Z=-1.8(15.17%) \| Like=2.60..3.69 [2.5988..2.6022]\| it/evals=1400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.72) * Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.6(19.27%) \| Like=2.78..3.69 [2.7802..2.7819]\| it/evals=1440/5391 eff=inf% N=400 Z=-1.5(20.35%) \| Like=2.83..3.69 [2.8275..2.8304]\| it/evals=1450/5391 eff=inf% N=400 Z=-1.3(25.93%) \| Like=3.03..3.69 [3.0340..3.0340]\| it/evals=1500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.95) Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.2(29.56%) \| Like=3.15..3.69 [3.1450..3.1456]\| it/evals=1530/5391 eff=inf% N=400 Z=-1.1(31.96%) \| Like=3.20..3.69 [3.2018..3.2042]\| it/evals=1550/5391 eff=inf% N=400 Z=-0.9(38.04%) \| Like=3.31..3.69 [3.3108..3.3130]\| it/evals=1600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.34) Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.9(40.40%) \| Like=3.34..3.69 [3.3439..3.3448]\| it/evals=1620/5391 eff=inf% N=400 Z=-0.8(43.85%) \| Like=3.40..3.69 [3.3956..3.3965]\| it/evals=1650/5391 eff=inf% N=400 Z=-0.7(49.50%) \| Like=3.45..3.69 [3.4511..3.4523]\| it/evals=1700/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.56) Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(50.57%) \| Like=3.46..3.69 [3.4593..3.4621]\| it/evals=1710/5391 eff=inf% N=400 Z=-0.6(54.69%) \| Like=3.50..3.69 [3.5027..3.5030]\| it/evals=1750/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.56) Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.5(59.50%) \| Like=3.54..3.69 [3.5412..3.5415]\| it/evals=1800/5391 eff=inf% N=400 Z=-0.4(63.91%) \| Like=3.57..3.69 [3.5739..3.5746]\| it/evals=1850/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.58) * Expected Volume: exp(-4.73) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.4(67.12%) \| Like=3.59..3.69 [3.5915..3.5916]\| it/evals=1890/5391 eff=inf% N=400 Z=-0.3(67.87%) \| Like=3.60..3.69 [3.5972..3.5973]\| it/evals=1900/5391 eff=inf% N=400 Z=-0.3(71.47%) \| Like=3.62..3.69 [3.6209..3.6212]\| it/evals=1950/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.02) Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.3(73.46%) \| Like=3.63..3.69 [3.6274..3.6276]\| it/evals=1980/5391 eff=inf% N=400 Z=-0.2(74.71%) \| Like=3.63..3.69 [3.6330..3.6334]\| it/evals=2000/5391 eff=inf% N=400 Z=-0.2(77.60%) \| Like=3.65..3.69 [3.6475..3.6477]\| it/evals=2050/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.33) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.2(78.67%) \| Like=3.65..3.69 [3.6506..3.6507]\| it/evals=2070/5391 eff=inf% N=400 Z=-0.2(80.17%) \| Like=3.66..3.69 [3.6553..3.6553]\| it/evals=2100/5391 eff=inf% N=400 Z=-0.1(82.46%) \| Like=3.66..3.69 [3.6619..3.6620]\| it/evals=2150/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.72) Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.1(82.89%) \| Like=3.66..3.69 [3.6628..3.6632]\| it/evals=2160/5391 eff=inf% N=400 Z=-0.1(84.49%) \| Like=3.67..3.69 [3.6671..3.6671]\| it/evals=2200/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.72) Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.1(86.30%) \| Like=3.67..3.69 [3.6702..3.6703]\| it/evals=2250/5391 eff=inf% N=400 Z=-0.1(87.89%) \| Like=3.67..3.69 [3.6740..3.6740]\| it/evals=2300/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.05) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(89.04%) \| Like=3.68..3.69 [3.6757..3.6757]\| it/evals=2340/5391 eff=inf% N=400 Z=-0.1(89.31%) \| Like=3.68..3.69 [3.6761..3.6761]\| it/evals=2350/5391 eff=inf% N=400 Z=-0.1(90.56%) \| Like=3.68..3.69 [3.6781..3.6781]\| it/evals=2400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.19) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(91.23%) \| Like=3.68..3.69 [3.6794..3.6795]\| it/evals=2430/5391 eff=inf% N=400 Z=-0.0(91.66%) \| Like=3.68..3.69 [3.6800..3.6801]\| it/evals=2450/5391 eff=inf% N=400 Z=-0.0(92.64%) \| Like=3.68..3.69 [3.6811..3.6812]\| it/evals=2500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.27) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(92.99%) \| Like=3.68..3.69 [3.6816..3.6817]\| it/evals=2520/5391 eff=inf% N=400 Z=-0.0(93.50%) \| Like=3.68..3.69 [3.6822..3.6822]\| it/evals=2550/5391 eff=inf% N=400 Z=-0.0(94.26%) \| Like=3.68..3.69 [3.6832..3.6832]\| it/evals=2600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.64) Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(94.40%) \| Like=3.68..3.69 [3.6833..3.6833]\| it/evals=2610/5391 eff=inf% N=400 Z=-0.0(94.93%) \| Like=3.68..3.69 [3.6836..3.6836]\| it/evals=2650/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.82) * Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.0(95.53%) \| Like=3.68..3.69 [3.6842..3.6842]\| it/evals=2700/5391 eff=inf% N=400 Z=0.0(96.05%) \| Like=3.68..3.69 [3.6846..3.6846]\| it/evals=2750/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.89) * Expected Volume: exp(-6.98) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=0.0(96.43%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2790/5391 eff=inf% N=400 Z=0.0(96.52%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2800/5391 eff=inf% N=400 Z=0.0(96.93%) \| Like=3.69..3.69 [3.6852..3.6852]*\| it/evals=2850/5391 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 5391 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.05415 +- 0.07355 [ultranest] Effective samples strategy satisfied (ESS = 1262.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 398 minimum live points (dlogz from 0.05 to 0.28, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.10 [ultranest] done iterating. logZ = 0.043 +- 0.277 single instance: logZ = 0.043 +- 0.089 bootstrapped : logZ = 0.054 +- 0.276 tail : logZ = +- 0.029 insert order U test : converged: True correlation: inf iterations a : 0.459 │ ▁ ▁▁▁▁▁▁▁▁▂▂▃▃▅▅▆▇▇▆▇▅▅▆▃▃▃▃▃▁▁▁▁▁▁▁▁ │0.537 0.500 +- 0.010 ran with dlogz: 0.1 first run gave: {'niter': 4663, 'logz': 0.04097491838788085, 'logzerr': 0.18063136711385278, 'logz_bs': 0.046839054946532954, 'logz_single': 0.04097491838788085, 'logzerr_tail': 0.029540945136971863, 'logzerr_bs': 0.1781993921028741, 'ess': 1807.664188236005, 'H': 3.154130512875934, 'Herr': 0.046845066579135605, 'posterior': {'mean': [0.49970846080869835], 'stdev': [0.01004709239352154], 'median': [0.49935731941479294], 'errlo': [0.4895958650446224], 'errup': [0.5098140852032222], 'information_gain_bits': [3.4619440240408434]}, 'maximum_likelihood': {'logl': 3.686231637806363, 'point': [0.4999982692743935], 'point_untransformed': [0.4999982692743935]}, 'ncall': 5391, 'paramnames': ['a'], 'logzerr_single': 0.07425775503844387, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3261, 'logz': 0.043086985075368095, 'logzerr': 0.2772812105360212, 'logz_bs': 0.05414593490827967, 'logz_single': 0.043086985075368095, 'logzerr_tail': 0.029467881253302547, 'logzerr_bs': 0.27571092414114207, 'ess': 1262.1858737131056, 'H': 3.154512692418824, 'Herr': 0.06253777219135659, 'posterior': {'mean': [0.4997429610264432], 'stdev': [0.010025904571764277], 'median': [0.4993018305586789], 'errlo': [0.490008435684678], 'errup': [0.5097540368099296], 'information_gain_bits': [3.4625603733966566]}, 'maximum_likelihood': {'logl': 3.686231637806363, 'point': [0.4999982692743935], 'point_untransformed': [0.4999982692743935]}, 'ncall': 5391, 'paramnames': ['a'], 'logzerr_single': 0.08880473935014425, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpzqf9taua, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=528, regioncalls=128, ndraw=128, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=528, regioncalls=128, ndraw=128, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=107, ncalls=629, regioncalls=256, ndraw=128, logz=-725.74, remainder_fraction=100.0000%, Lmin=-717.99, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=629, regioncalls=256, ndraw=128, logz=-573.25, remainder_fraction=100.0000%, Lmin=-561.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=629, regioncalls=256, ndraw=128, logz=-499.66, remainder_fraction=100.0000%, Lmin=-493.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=717, regioncalls=384, ndraw=128, logz=-463.56, remainder_fraction=100.0000%, Lmin=-456.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=717, regioncalls=384, ndraw=128, logz=-374.71, remainder_fraction=100.0000%, Lmin=-364.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=783, regioncalls=512, ndraw=128, logz=-327.38, remainder_fraction=100.0000%, Lmin=-320.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=783, regioncalls=512, ndraw=128, logz=-278.70, remainder_fraction=100.0000%, Lmin=-269.85, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=842, regioncalls=640, ndraw=128, logz=-208.44, remainder_fraction=100.0000%, Lmin=-201.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=842, regioncalls=640, ndraw=128, logz=-201.75, remainder_fraction=100.0000%, Lmin=-195.89, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=890, regioncalls=768, ndraw=128, logz=-168.63, remainder_fraction=100.0000%, Lmin=-162.35, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=938, regioncalls=896, ndraw=128, logz=-127.89, remainder_fraction=100.0000%, Lmin=-120.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=983, regioncalls=1024, ndraw=128, logz=-102.29, remainder_fraction=100.0000%, Lmin=-95.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1015, regioncalls=1152, ndraw=128, logz=-81.90, remainder_fraction=100.0000%, Lmin=-75.87, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1045, regioncalls=1280, ndraw=128, logz=-76.26, remainder_fraction=100.0000%, Lmin=-67.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=1097, regioncalls=1536, ndraw=128, logz=-61.88, remainder_fraction=100.0000%, Lmin=-54.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1097, regioncalls=1536, ndraw=128, logz=-59.67, remainder_fraction=100.0000%, Lmin=-53.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1119, regioncalls=1664, ndraw=128, logz=-50.83, remainder_fraction=100.0000%, Lmin=-44.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1149, regioncalls=1792, ndraw=128, logz=-46.91, remainder_fraction=100.0000%, Lmin=-40.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=692, ncalls=1202, regioncalls=2048, ndraw=128, logz=-37.74, remainder_fraction=100.0000%, Lmin=-31.30, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1202, regioncalls=2048, ndraw=128, logz=-36.30, remainder_fraction=100.0000%, Lmin=-30.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1220, regioncalls=2176, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-27.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1241, regioncalls=2304, ndraw=128, logz=-28.46, remainder_fraction=100.0000%, Lmin=-22.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1304, regioncalls=2688, ndraw=128, logz=-22.67, remainder_fraction=100.0000%, Lmin=-17.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1321, regioncalls=2816, ndraw=128, logz=-21.80, remainder_fraction=100.0000%, Lmin=-15.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1358, regioncalls=3072, ndraw=128, logz=-18.22, remainder_fraction=100.0000%, Lmin=-12.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=899, ncalls=1408, regioncalls=3584, ndraw=128, logz=-14.76, remainder_fraction=100.0000%, Lmin=-9.25, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1408, regioncalls=3584, ndraw=128, logz=-14.70, remainder_fraction=100.0000%, Lmin=-9.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1454, regioncalls=4096, ndraw=128, logz=-12.31, remainder_fraction=99.9996%, Lmin=-6.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1454, regioncalls=4096, ndraw=128, logz=-11.83, remainder_fraction=99.9993%, Lmin=-6.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1495, regioncalls=4480, ndraw=128, logz=-9.96, remainder_fraction=99.9955%, Lmin=-4.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1510, regioncalls=4608, ndraw=128, logz=-9.56, remainder_fraction=99.9931%, Lmin=-4.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1560, regioncalls=5248, ndraw=128, logz=-7.83, remainder_fraction=99.9619%, Lmin=-2.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1589, regioncalls=5760, ndraw=128, logz=-6.88, remainder_fraction=99.9019%, Lmin=-1.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1608, regioncalls=6016, ndraw=128, logz=-6.28, remainder_fraction=99.8203%, Lmin=-1.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1133, ncalls=1647, regioncalls=6656, ndraw=128, logz=-5.46, remainder_fraction=99.5937%, Lmin=-0.43, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1662, regioncalls=6912, ndraw=128, logz=-5.10, remainder_fraction=99.4200%, Lmin=-0.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1688, regioncalls=7424, ndraw=128, logz=-4.69, remainder_fraction=99.1264%, Lmin=0.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1714, regioncalls=7936, ndraw=128, logz=-4.10, remainder_fraction=98.4353%, Lmin=0.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1753, regioncalls=8704, ndraw=128, logz=-3.43, remainder_fraction=96.9477%, Lmin=1.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1768, regioncalls=9088, ndraw=128, logz=-3.28, remainder_fraction=96.4486%, Lmin=1.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1785, regioncalls=9344, ndraw=128, logz=-3.13, remainder_fraction=95.8667%, Lmin=1.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1293, ncalls=1817, regioncalls=10112, ndraw=128, logz=-2.71, remainder_fraction=93.7658%, Lmin=2.01, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1820, regioncalls=10240, ndraw=128, logz=-2.63, remainder_fraction=93.2522%, Lmin=2.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1328, ncalls=1851, regioncalls=10880, ndraw=128, logz=-2.36, remainder_fraction=91.1578%, Lmin=2.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1878, regioncalls=11776, ndraw=128, logz=-2.18, remainder_fraction=89.3449%, Lmin=2.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1382, ncalls=1910, regioncalls=12800, ndraw=128, logz=-1.95, remainder_fraction=86.5669%, Lmin=2.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1928, regioncalls=13312, ndraw=128, logz=-1.83, remainder_fraction=84.8291%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1969, regioncalls=14464, ndraw=128, logz=-1.60, remainder_fraction=80.7292%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1978, regioncalls=14720, ndraw=128, logz=-1.54, remainder_fraction=79.6520%, Lmin=2.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1499, ncalls=2029, regioncalls=16640, ndraw=128, logz=-1.31, remainder_fraction=74.1831%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2029, regioncalls=16640, ndraw=128, logz=-1.30, remainder_fraction=74.0684%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2062, regioncalls=17408, ndraw=128, logz=-1.18, remainder_fraction=70.4449%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2080, regioncalls=18048, ndraw=128, logz=-1.10, remainder_fraction=68.0352%, Lmin=3.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1577, ncalls=2219, regioncalls=19456, ndraw=128, logz=-1.00, remainder_fraction=64.7182%, Lmin=3.26, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.92, remainder_fraction=61.9581%, Lmin=3.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.86, remainder_fraction=59.5960%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.78, remainder_fraction=56.1467%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1685, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.69, remainder_fraction=52.1398%, Lmin=3.44, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.66, remainder_fraction=50.5050%, Lmin=3.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.64, remainder_fraction=49.4302%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.56, remainder_fraction=45.3100%, Lmin=3.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1783, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.50, remainder_fraction=42.0902%, Lmin=3.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.48, remainder_fraction=40.5034%, Lmin=3.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.40, remainder_fraction=36.0867%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1899, ncalls=2479, regioncalls=21632, ndraw=128, logz=-0.35, remainder_fraction=32.2019%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2479, regioncalls=21632, ndraw=128, logz=-0.34, remainder_fraction=32.1257%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2531, regioncalls=22528, ndraw=128, logz=-0.29, remainder_fraction=28.5291%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2559, regioncalls=23296, ndraw=128, logz=-0.27, remainder_fraction=26.5391%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2586, regioncalls=24448, ndraw=128, logz=-0.25, remainder_fraction=25.2935%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=2641, regioncalls=25344, ndraw=128, logz=-0.21, remainder_fraction=22.4028%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2655, regioncalls=25600, ndraw=128, logz=-0.20, remainder_fraction=21.3341%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=2687, regioncalls=26112, ndraw=128, logz=-0.18, remainder_fraction=19.8255%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2135, ncalls=2729, regioncalls=26752, ndraw=128, logz=-0.16, remainder_fraction=18.1963%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2739, regioncalls=26880, ndraw=128, logz=-0.15, remainder_fraction=17.5384%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2790, regioncalls=27648, ndraw=128, logz=-0.13, remainder_fraction=15.5068%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=2849, regioncalls=28416, ndraw=128, logz=-0.10, remainder_fraction=13.7044%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.09, remainder_fraction=12.1072%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.07, remainder_fraction=10.9631%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.07, remainder_fraction=10.6942%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.06, remainder_fraction=9.4447%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.05, remainder_fraction=8.7657%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.04, remainder_fraction=8.3401%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3207, regioncalls=29440, ndraw=128, logz=-0.03, remainder_fraction=7.3634%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3207, regioncalls=29440, ndraw=128, logz=-0.02, remainder_fraction=6.5007%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.02, remainder_fraction=5.7383%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.01, remainder_fraction=5.5969%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.01, remainder_fraction=5.0652%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=3359, regioncalls=30592, ndraw=128, logz=-0.00, remainder_fraction=4.6069%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3372, regioncalls=30848, ndraw=128, logz=-0.00, remainder_fraction=4.4709%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2707, ncalls=3486, regioncalls=31232, ndraw=128, logz=-0.00, remainder_fraction=4.3934%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.00, remainder_fraction=3.9462%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.01, remainder_fraction=3.5710%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.01, remainder_fraction=3.4829%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=3537, regioncalls=32128, ndraw=128, logz=0.01, remainder_fraction=3.0740%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3551 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.04562 +- 0.06643 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1262.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 399 and 399, most (1767/1768 iterations) have 398 INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 572 minimum live points (dlogz from 0.05 to 0.16, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 572 live points (have 400 already) ... INFO ultranest:integrator.py:1433 Sampling 172 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 572.0), (inf, 572.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=3851, regioncalls=32512, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1233.27, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=93, ncalls=3851, regioncalls=32512, ndraw=128, logz=-899.81, remainder_fraction=100.0000%, Lmin=-891.00, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=128, ncalls=3851, regioncalls=32512, ndraw=128, logz=-813.16, remainder_fraction=100.0000%, Lmin=-806.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=3851, regioncalls=32512, ndraw=128, logz=-623.76, remainder_fraction=100.0000%, Lmin=-616.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=264, ncalls=3851, regioncalls=32512, ndraw=128, logz=-511.66, remainder_fraction=100.0000%, Lmin=-503.81, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=367, ncalls=3925, regioncalls=32640, ndraw=128, logz=-365.29, remainder_fraction=100.0000%, Lmin=-354.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=392, ncalls=3925, regioncalls=32640, ndraw=128, logz=-325.40, remainder_fraction=100.0000%, Lmin=-318.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3925, regioncalls=32640, ndraw=128, logz=-265.45, remainder_fraction=100.0000%, Lmin=-258.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=521, ncalls=3987, regioncalls=32768, ndraw=128, logz=-203.18, remainder_fraction=100.0000%, Lmin=-196.97, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3987, regioncalls=32768, ndraw=128, logz=-188.11, remainder_fraction=100.0000%, Lmin=-181.88, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=651, ncalls=4041, regioncalls=32896, ndraw=128, logz=-126.37, remainder_fraction=100.0000%, Lmin=-119.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=764, ncalls=4081, regioncalls=33024, ndraw=128, logz=-85.82, remainder_fraction=100.0000%, Lmin=-78.37, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=783, ncalls=4081, regioncalls=33024, ndraw=128, logz=-81.55, remainder_fraction=100.0000%, Lmin=-74.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=4112, regioncalls=33152, ndraw=128, logz=-63.87, remainder_fraction=100.0000%, Lmin=-57.76, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=914, ncalls=4112, regioncalls=33152, ndraw=128, logz=-49.78, remainder_fraction=100.0000%, Lmin=-43.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1031, ncalls=4159, regioncalls=33408, ndraw=128, logz=-34.62, remainder_fraction=100.0000%, Lmin=-28.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1043, ncalls=4159, regioncalls=33408, ndraw=128, logz=-33.25, remainder_fraction=100.0000%, Lmin=-27.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=4189, regioncalls=33536, ndraw=128, logz=-27.41, remainder_fraction=100.0000%, Lmin=-21.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1173, ncalls=4209, regioncalls=33664, ndraw=128, logz=-21.63, remainder_fraction=100.0000%, Lmin=-15.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=4223, regioncalls=33792, ndraw=128, logz=-19.81, remainder_fraction=100.0000%, Lmin=-13.99, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1302, ncalls=4238, regioncalls=33920, ndraw=128, logz=-14.21, remainder_fraction=99.9999%, Lmin=-8.82, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1419, ncalls=4282, regioncalls=34432, ndraw=128, logz=-9.94, remainder_fraction=99.9954%, Lmin=-4.80, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=4317, regioncalls=34816, ndraw=128, logz=-7.98, remainder_fraction=99.9670%, Lmin=-2.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1561, ncalls=4348, regioncalls=35072, ndraw=128, logz=-6.64, remainder_fraction=99.8735%, Lmin=-1.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=4367, regioncalls=35456, ndraw=128, logz=-5.03, remainder_fraction=99.3755%, Lmin=0.04, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1689, ncalls=4389, regioncalls=35840, ndraw=128, logz=-4.44, remainder_fraction=98.8825%, Lmin=0.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=4416, regioncalls=36224, ndraw=128, logz=-3.67, remainder_fraction=97.5793%, Lmin=1.27, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=4451, regioncalls=36736, ndraw=128, logz=-3.14, remainder_fraction=95.9120%, Lmin=1.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1837, ncalls=4459, regioncalls=36992, ndraw=128, logz=-2.81, remainder_fraction=94.2897%, Lmin=1.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=4503, regioncalls=37760, ndraw=128, logz=-2.10, remainder_fraction=88.2499%, Lmin=2.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=4503, regioncalls=37760, ndraw=128, logz=-2.09, remainder_fraction=88.1147%, Lmin=2.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2003, ncalls=4524, regioncalls=38656, ndraw=128, logz=-1.83, remainder_fraction=84.6478%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2082, ncalls=4550, regioncalls=39424, ndraw=128, logz=-1.51, remainder_fraction=78.8970%, Lmin=2.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2201, ncalls=4618, regioncalls=41216, ndraw=128, logz=-1.14, remainder_fraction=69.2387%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2210, ncalls=4618, regioncalls=41216, ndraw=128, logz=-1.11, remainder_fraction=68.4922%, Lmin=3.18, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2235, ncalls=4756, regioncalls=42240, ndraw=128, logz=-1.05, remainder_fraction=66.4217%, Lmin=3.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2338, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.82, remainder_fraction=57.9099%, Lmin=3.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.80, remainder_fraction=56.9172%, Lmin=3.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.63, remainder_fraction=49.1470%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2467, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.61, remainder_fraction=47.8918%, Lmin=3.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2592, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.46, remainder_fraction=39.4142%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2598, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.45, remainder_fraction=39.0289%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.45, remainder_fraction=38.9029%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2645, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.41, remainder_fraction=36.1607%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2726, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.34, remainder_fraction=31.6822%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.26, remainder_fraction=25.7564%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.23, remainder_fraction=23.6731%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=4936, regioncalls=45184, ndraw=128, logz=-0.20, remainder_fraction=21.7394%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2985, ncalls=4952, regioncalls=45312, ndraw=128, logz=-0.19, remainder_fraction=20.4793%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3012, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.18, remainder_fraction=19.5548%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3114, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.14, remainder_fraction=16.4127%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3169, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.12, remainder_fraction=14.9285%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3242, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.10, remainder_fraction=13.1587%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=5113, regioncalls=46464, ndraw=128, logz=-0.07, remainder_fraction=10.9120%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3377, ncalls=5124, regioncalls=46592, ndraw=128, logz=-0.07, remainder_fraction=10.4119%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3450, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.06, remainder_fraction=9.1719%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3500, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.05, remainder_fraction=8.4078%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3508, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.05, remainder_fraction=8.2914%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.03, remainder_fraction=7.0639%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3636, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.03, remainder_fraction=6.6343%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3764, ncalls=5272, regioncalls=48128, ndraw=128, logz=-0.01, remainder_fraction=5.3069%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3765, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=5.2976%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=4.9837%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3850, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=4.5672%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3893, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.00, remainder_fraction=4.2369%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3950, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.00, remainder_fraction=3.8355%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.01, remainder_fraction=3.5148%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.01, remainder_fraction=3.3237%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5391 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.04684 +- 0.05136 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1807.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 683 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 571 and 571, most (3132/3133 iterations) have 570 DEBUG ultranest:integrator.py:1663 at least 570 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 570 minimum live points (dlogz from 0.04 to 0.18, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.03 total:0.06 required:<0.10 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpzqf9taua, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [3.68337942 3.68622715 0. 0.50003002 0.50003002]: u=[0.50003002] -> p=[0.50003002] -> L=3.686227145661632 INFO ultranest:integrator.py:2364 Resuming from 5048 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=5391, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=5391, regioncalls=0, ndraw=128, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=5391, regioncalls=0, ndraw=128, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=5391, regioncalls=0, ndraw=128, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=5391, regioncalls=0, ndraw=128, logz=-573.25, remainder_fraction=100.0000%, Lmin=-561.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=5391, regioncalls=0, ndraw=128, logz=-499.66, remainder_fraction=100.0000%, Lmin=-493.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=5391, regioncalls=0, ndraw=128, logz=-463.56, remainder_fraction=100.0000%, Lmin=-456.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=5391, regioncalls=0, ndraw=128, logz=-374.71, remainder_fraction=100.0000%, Lmin=-364.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=5391, regioncalls=0, ndraw=128, logz=-278.70, remainder_fraction=100.0000%, Lmin=-269.85, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=5391, regioncalls=0, ndraw=128, logz=-208.44, remainder_fraction=100.0000%, Lmin=-201.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=5391, regioncalls=0, ndraw=128, logz=-201.75, remainder_fraction=100.0000%, Lmin=-195.89, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5391, regioncalls=0, ndraw=128, logz=-168.63, remainder_fraction=100.0000%, Lmin=-162.35, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5391, regioncalls=0, ndraw=128, logz=-127.89, remainder_fraction=100.0000%, Lmin=-120.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=5391, regioncalls=0, ndraw=128, logz=-102.29, remainder_fraction=100.0000%, Lmin=-95.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=5391, regioncalls=0, ndraw=128, logz=-76.26, remainder_fraction=100.0000%, Lmin=-67.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=5391, regioncalls=0, ndraw=128, logz=-59.67, remainder_fraction=100.0000%, Lmin=-53.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=5391, regioncalls=0, ndraw=128, logz=-50.83, remainder_fraction=100.0000%, Lmin=-44.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5391, regioncalls=0, ndraw=128, logz=-46.91, remainder_fraction=100.0000%, Lmin=-40.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5391, regioncalls=0, ndraw=128, logz=-36.30, remainder_fraction=100.0000%, Lmin=-30.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5391, regioncalls=0, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-27.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=5391, regioncalls=0, ndraw=128, logz=-28.46, remainder_fraction=100.0000%, Lmin=-22.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=5391, regioncalls=0, ndraw=128, logz=-22.67, remainder_fraction=100.0000%, Lmin=-17.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=5391, regioncalls=0, ndraw=128, logz=-21.80, remainder_fraction=100.0000%, Lmin=-15.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=5391, regioncalls=0, ndraw=128, logz=-18.22, remainder_fraction=100.0000%, Lmin=-12.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=5391, regioncalls=0, ndraw=128, logz=-14.70, remainder_fraction=100.0000%, Lmin=-9.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=5391, regioncalls=0, ndraw=128, logz=-11.83, remainder_fraction=99.9993%, Lmin=-6.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=5391, regioncalls=0, ndraw=128, logz=-9.96, remainder_fraction=99.9955%, Lmin=-4.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=5391, regioncalls=0, ndraw=128, logz=-9.56, remainder_fraction=99.9931%, Lmin=-4.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=5391, regioncalls=0, ndraw=128, logz=-7.83, remainder_fraction=99.9619%, Lmin=-2.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=5391, regioncalls=0, ndraw=128, logz=-6.28, remainder_fraction=99.8203%, Lmin=-1.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=5391, regioncalls=0, ndraw=128, logz=-5.10, remainder_fraction=99.4200%, Lmin=-0.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=5391, regioncalls=0, ndraw=128, logz=-4.69, remainder_fraction=99.1264%, Lmin=0.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=5391, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=98.4353%, Lmin=0.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=5391, regioncalls=0, ndraw=128, logz=-3.28, remainder_fraction=96.4486%, Lmin=1.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=5391, regioncalls=0, ndraw=128, logz=-3.13, remainder_fraction=95.8667%, Lmin=1.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=5391, regioncalls=0, ndraw=128, logz=-2.63, remainder_fraction=93.2522%, Lmin=2.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=5391, regioncalls=0, ndraw=128, logz=-2.18, remainder_fraction=89.3449%, Lmin=2.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.83, remainder_fraction=84.8291%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.60, remainder_fraction=80.7292%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.54, remainder_fraction=79.6520%, Lmin=2.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.30, remainder_fraction=74.0684%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.18, remainder_fraction=70.4449%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.10, remainder_fraction=68.0352%, Lmin=3.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.92, remainder_fraction=61.9581%, Lmin=3.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.86, remainder_fraction=59.5960%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.78, remainder_fraction=56.1467%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.66, remainder_fraction=50.5050%, Lmin=3.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.64, remainder_fraction=49.4302%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.56, remainder_fraction=45.3100%, Lmin=3.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.48, remainder_fraction=40.5034%, Lmin=3.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.40, remainder_fraction=36.0867%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.36, remainder_fraction=32.8840%, Lmin=3.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.34, remainder_fraction=32.1257%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.29, remainder_fraction=28.5291%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.27, remainder_fraction=26.5391%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.25, remainder_fraction=25.2935%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.21, remainder_fraction=22.4028%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.20, remainder_fraction=21.3341%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.18, remainder_fraction=19.8255%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.15, remainder_fraction=17.5384%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.14, remainder_fraction=17.1128%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.13, remainder_fraction=15.5068%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.10, remainder_fraction=13.7044%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.09, remainder_fraction=12.1072%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.07, remainder_fraction=10.9631%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.07, remainder_fraction=10.6942%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.06, remainder_fraction=9.4447%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.05, remainder_fraction=8.7657%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.04, remainder_fraction=8.3401%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.03, remainder_fraction=7.3634%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.03, remainder_fraction=7.0055%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.02, remainder_fraction=6.5007%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.02, remainder_fraction=5.7383%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.01, remainder_fraction=5.5969%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.01, remainder_fraction=5.0652%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.00, remainder_fraction=4.4709%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=5391, regioncalls=0, ndraw=128, logz=0.00, remainder_fraction=3.9462%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.5710%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.4829%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.0740%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5391 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.05415 +- 0.07355 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1262.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.08 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 399 and 399, most (1463/1464 iterations) have 398 DEBUG ultranest:integrator.py:1663 at least 398 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 398 minimum live points (dlogz from 0.05 to 0.28, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.10 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_ordertest.py::test_invalid_order	0.00
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_run.py::test_reactive_run	12.19
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.28) * Expected Volume: exp(0.00) Quality: ok Hinz: -5.0\|***************************************************\| +5.0 Kunz: -5.0\|**************************************************\| +5.0 Z=-inf(0.00%) \| Like=-110.42..0.28 [-110.4238..-29.8742] \| it/evals=0/401 eff=0.0000% N=400 Z=-67.0(0.00%) \| Like=-62.58..0.43 [-110.4238..-29.8742] \| it/evals=50/452 eff=96.1538% N=400 Mono-modal Volume: ~exp(-4.42) Expected Volume: exp(-0.23) Quality: ok Hinz: -5.0\| **************************************************\| +5.0 Kunz: -5.0\| ************************************************\| +5.0 Z=-57.4(0.00%) \| Like=-52.63..0.43 [-110.4238..-29.8742] \| it/evals=90/494 eff=95.7447% N=400 Z=-54.9(0.00%) \| Like=-50.20..0.43 [-110.4238..-29.8742] \| it/evals=100/505 eff=95.2381% N=400 Z=-46.9(0.00%) \| Like=-42.21..0.43 [-110.4238..-29.8742] \| it/evals=150/567 eff=89.8204% N=400 Mono-modal Volume: ~exp(-4.60) Expected Volume: exp(-0.45) Quality: ok Hinz: -5.0\| *********************************************\| +5.0 Kunz: -5.0\| ********************************************\| +5.0 Z=-42.2(0.00%) \| Like=-37.96..0.43 [-110.4238..-29.8742] \| it/evals=180/613 eff=84.5070% N=400 Z=-40.4(0.00%) \| Like=-36.05..0.43 [-110.4238..-29.8742] \| it/evals=200/634 eff=85.4701% N=400 Z=-36.2(0.00%) \| Like=-31.84..0.43 [-110.4238..-29.8742] \| it/evals=250/700 eff=83.3333% N=400 Mono-modal Volume: ~exp(-4.98) Expected Volume: exp(-0.67) Quality: ok Hinz: -5.0\| **************************************** \| +5.0 Kunz: -5.0\| ************************************** \| +5.0 Z=-34.3(0.00%) \| Like=-29.94..0.43 [-110.4238..-29.8742] \| it/evals=270/735 eff=80.5970% N=400 Z=-31.7(0.00%) \| Like=-27.71..0.43 [-29.8121..-13.5243] \| it/evals=300/770 eff=81.0811% N=400 Z=-28.9(0.00%) \| Like=-24.89..0.43 [-29.8121..-13.5243] \| it/evals=350/834 eff=80.6452% N=400 Mono-modal Volume: ~exp(-4.98) Expected Volume: exp(-0.90) Quality: ok Hinz: -5.0\| *********************************** \| +5.0 Kunz: -5.0\| -2.8 ************************************ \| +5.0 Z=-25.6(0.00%) \| Like=-21.07..0.49 [-29.8121..-13.5243] \| it/evals=397/898 eff=79.7189% N=400 Z=-25.4(0.00%) \| Like=-20.82..0.49 [-29.8121..-13.5243] \| it/evals=400/907 eff=78.8955% N=400 Mono-modal Volume: ~exp(-5.43) * Expected Volume: exp(-1.12) Quality: ok Hinz: -5.0\| -2.5 ******************************** \| +5.0 Kunz: -5.0\| -2.5 ******************************** \| +5.0 Z=-22.6(0.00%) \| Like=-18.55..0.49 [-29.8121..-13.5243] \| it/evals=450/976 eff=78.1250% N=400 Z=-20.5(0.00%) \| Like=-16.26..0.49 [-29.8121..-13.5243] \| it/evals=500/1043 eff=77.7605% N=400 Mono-modal Volume: ~exp(-5.80) * Expected Volume: exp(-1.35) Quality: ok Hinz: -5.0\| -2.3 ***************************** \| +5.0 Kunz: -5.0\| -2.1 **************************** \| +5.0 Z=-18.7(0.00%) \| Like=-14.60..0.51 [-29.8121..-13.5243] \| it/evals=540/1105 eff=76.5957% N=400 Z=-18.3(0.00%) \| Like=-14.26..0.55 [-29.8121..-13.5243] \| it/evals=550/1118 eff=76.6017% N=400 Z=-16.6(0.00%) \| Like=-12.62..0.55 [-13.5092..-7.0346] \| it/evals=600/1179 eff=77.0218% N=400 Mono-modal Volume: ~exp(-6.11) * Expected Volume: exp(-1.57) Quality: ok Hinz: -5.0\| -2.0 ************************** \| +5.0 Kunz: -5.0\| -1.9 ************************ \| +5.0 Z=-15.7(0.00%) \| Like=-11.69..0.55 [-13.5092..-7.0346] \| it/evals=630/1225 eff=76.3636% N=400 Z=-15.2(0.00%) \| Like=-11.26..0.55 [-13.5092..-7.0346] \| it/evals=650/1250 eff=76.4706% N=400 Z=-13.8(0.00%) \| Like=-9.78..0.55 [-13.5092..-7.0346] \| it/evals=700/1314 eff=76.5864% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-1.80) Quality: ok Hinz: -5.0\| -1.7 ********************** +2.9 \| +5.0 Kunz: -5.0\| -1.6 ******************** +2.9 \| +5.0 Z=-12.7(0.01%) \| Like=-8.72..0.55 [-13.5092..-7.0346] \| it/evals=750/1378 eff=76.6871% N=400 Z=-11.8(0.03%) \| Like=-7.66..0.55 [-13.5092..-7.0346] \| it/evals=800/1448 eff=76.3359% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-2.02) Quality: ok Hinz: -5.0\| -1.4 ******************* +2.6 \| +5.0 Kunz: -5.0\| -1.4 ******************* +2.5 \| +5.0 Z=-10.9(0.06%) \| Like=-6.78..0.55 [-7.0343..-2.9827] \| it/evals=839/1498 eff=76.4117% N=400 Z=-10.7(0.07%) \| Like=-6.56..0.55 [-7.0343..-2.9827] \| it/evals=850/1516 eff=76.1649% N=400 Z=-9.9(0.16%) \| Like=-5.87..0.56 [-7.0343..-2.9827] \| it/evals=894/1582 eff=75.6345% N=400 Mono-modal Volume: ~exp(-6.54) * Expected Volume: exp(-2.25) Quality: ok Hinz: -5.0\| -1.2 ****************** +2.5 \| +5.0 Kunz: -5.0\| -1.1 ****************** +2.5 \| +5.0 Z=-9.8(0.18%) \| Like=-5.80..0.56 [-7.0343..-2.9827] \| it/evals=900/1588 eff=75.7576% N=400 Z=-9.1(0.37%) \| Like=-4.92..0.57 [-7.0343..-2.9827] \| it/evals=950/1654 eff=75.7576% N=400 Mono-modal Volume: ~exp(-6.86) * Expected Volume: exp(-2.47) Quality: ok Hinz: -5.0\| -1.0 **************** +2.3 \| +5.0 Kunz: -5.0\| -0.9 **************** +2.2 \| +5.0 Z=-8.5(0.69%) \| Like=-4.29..0.57 [-7.0343..-2.9827] \| it/evals=990/1707 eff=75.7460% N=400 Z=-8.4(0.80%) \| Like=-4.17..0.57 [-7.0343..-2.9827] \| it/evals=1000/1719 eff=75.8150% N=400 Z=-7.8(1.42%) \| Like=-3.65..0.59 [-7.0343..-2.9827] \| it/evals=1050/1787 eff=75.7030% N=400 Mono-modal Volume: ~exp(-7.25) * Expected Volume: exp(-2.70) Quality: ok Hinz: -5.0\| -0.8 ************** +2.1 \| +5.0 Kunz: -5.0\| -0.8 ************** +2.0 \| +5.0 Z=-7.4(1.95%) \| Like=-3.36..0.59 [-7.0343..-2.9827] \| it/evals=1080/1835 eff=75.2613% N=400 Z=-7.3(2.35%) \| Like=-3.20..0.59 [-7.0343..-2.9827] \| it/evals=1100/1859 eff=75.3941% N=400 Z=-6.8(3.59%) \| Like=-2.70..0.59 [-2.9806..-2.0814] \| it/evals=1150/1926 eff=75.3604% N=400 Mono-modal Volume: ~exp(-7.32) * Expected Volume: exp(-2.92) Quality: ok Hinz: -5.0\| -0.7 ************** +2.0 \| +5.0 Kunz: -5.0\| -0.7 ************ +1.9 \| +5.0 Z=-6.7(4.17%) \| Like=-2.58..0.59 [-2.9806..-2.0814] \| it/evals=1170/1958 eff=75.0963% N=400 Z=-6.4(5.26%) \| Like=-2.40..0.59 [-2.9806..-2.0814] \| it/evals=1200/1996 eff=75.1880% N=400 Z=-6.2(6.60%) \| Like=-2.15..0.59 [-2.9806..-2.0814] \| it/evals=1234/2034 eff=75.5202% N=400 Z=-6.1(7.29%) \| Like=-2.06..0.59 [-2.0779..-1.8415] \| it/evals=1250/2050 eff=75.7576% N=400 Mono-modal Volume: ~exp(-7.62) * Expected Volume: exp(-3.15) Quality: ok Hinz: -5.0\| -0.6 ************ +1.8 \| +5.0 Kunz: -5.0\| -0.5 ********* +1.7 \| +5.0 Z=-6.0(7.81%) \| Like=-2.00..0.59 [-2.0779..-1.8415] \| it/evals=1260/2061 eff=75.8579% N=400 Z=-5.8(9.88%) \| Like=-1.73..0.59 [-1.7370..-1.7261] \| it/evals=1300/2108 eff=76.1124% N=400 Mono-modal Volume: ~exp(-7.62) Expected Volume: exp(-3.37) Quality: ok Hinz: -5.0\| -0.4 ******** +1.7 \| +5.0 Kunz: -5.0\| -0.4 ********** +1.7 \| +5.0 Z=-5.5(12.75%) \| Like=-1.48..0.59 [-1.4844..-1.4839]\| it/evals=1350/2169 eff=76.3143% N=400 Z=-5.3(16.19%) \| Like=-1.26..0.59 [-1.2643..-1.2571]\| it/evals=1400/2237 eff=76.2112% N=400 Mono-modal Volume: ~exp(-8.00) * Expected Volume: exp(-3.60) Quality: ok Hinz: -5.0\| -0.4 ********** +1.6 \| +5.0 Kunz: -5.0\| -0.3 ******** +1.6 \| +5.0 Z=-5.1(19.40%) \| Like=-1.09..0.59 [-1.1004..-1.0902] \| it/evals=1440/2295 eff=75.9894% N=400 Z=-5.1(20.14%) \| Like=-1.04..0.59 [-1.0447..-1.0442]\| it/evals=1450/2306 eff=76.0756% N=400 Z=-4.9(23.91%) \| Like=-0.91..0.59 [-0.9064..-0.9011]\| it/evals=1500/2374 eff=75.9878% N=400 Mono-modal Volume: ~exp(-8.00) Expected Volume: exp(-3.82) Quality: ok Hinz: -5.0\| -0.2 ******** +1.5 \| +5.0 Kunz: -5.0\| -0.2 ******** +1.5 \| +5.0 Z=-4.8(28.28%) \| Like=-0.70..0.59 [-0.7041..-0.7009]\| it/evals=1550/2436 eff=76.1297% N=400 Z=-4.6(32.78%) \| Like=-0.54..0.59 [-0.5372..-0.5353]\| it/evals=1600/2513 eff=75.7217% N=400 Mono-modal Volume: ~exp(-8.11) * Expected Volume: exp(-4.05) Quality: ok Hinz: -5.0\| -0.1 ******** +1.4 \| +5.0 Kunz: -5.0\| -0.1 ******* +1.4 \| +5.0 Z=-4.6(34.48%) \| Like=-0.49..0.59 [-0.4910..-0.4874]\| it/evals=1620/2546 eff=75.4893% N=400 Z=-4.5(37.16%) \| Like=-0.40..0.59 [-0.3961..-0.3956]\| it/evals=1650/2581 eff=75.6534% N=400 Z=-4.4(40.89%) \| Like=-0.32..0.59 [-0.3208..-0.3194]\| it/evals=1691/2643 eff=75.3901% N=400 Z=-4.4(41.71%) \| Like=-0.30..0.59 [-0.2959..-0.2954]\| it/evals=1700/2654 eff=75.4215% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.27) Quality: ok Hinz: -5.0e+00\| -5.7e-02 ****** +1.3e+00 \| +5.0e+00 Kunz: -5.0e+00\| -4.2e-02 ****** +1.3e+00 \| +5.0e+00 Z=-4.4(42.67%) \| Like=-0.29..0.59 [-0.2858..-0.2837]\| it/evals=1710/2670 eff=75.3304% N=400 Z=-4.3(46.38%) \| Like=-0.20..0.59 [-0.2049..-0.2046]\| it/evals=1750/2723 eff=75.3336% N=400 Mono-modal Volume: ~exp(-9.00) * Expected Volume: exp(-4.50) Quality: ok Hinz: +0.0e+00\|************ +1.2e+00 \| +5.0e+00 Kunz: +0.0e+00\|************ +1.2e+00 \| +5.0e+00 Z=-4.2(50.51%) \| Like=-0.09..0.59 [-0.0892..-0.0827]\| it/evals=1800/2788 eff=75.3769% N=400 Z=-4.1(53.76%) \| Like=-0.03..0.59 [-0.0285..-0.0284]\| it/evals=1838/2833 eff=75.5446% N=400 Z=-4.1(54.67%) \| Like=-0.02..0.59 [-0.0215..-0.0205]\| it/evals=1850/2846 eff=75.6337% N=400 Mono-modal Volume: ~exp(-9.00) Expected Volume: exp(-4.73) Quality: ok Hinz: +0.0e+00\|********** +1.2e+00 \| +5.0e+00 Kunz: +0.0\| ********** +1.2 \| +5.0 Z=-4.1(57.84%) \| Like=0.04..0.59 [0.0405..0.0482]\| it/evals=1890/2897 eff=75.6908% N=400 Z=-4.0(58.61%) \| Like=0.06..0.59 [0.0579..0.0582]\| it/evals=1900/2909 eff=75.7274% N=400 Z=-4.0(62.22%) \| Like=0.14..0.59 [0.1399..0.1401]\| it/evals=1948/2984 eff=75.3870% N=400 Z=-4.0(62.35%) \| Like=0.14..0.59 [0.1411..0.1432]\| it/evals=1950/2986 eff=75.4060% N=400 Mono-modal Volume: ~exp(-9.22) * Expected Volume: exp(-4.95) Quality: ok Hinz: +0.0\| ********* +1.1 \| +5.0 Kunz: +0.0\| ********* +1.1 \| +5.0 Z=-4.0(64.48%) \| Like=0.17..0.59 [0.1744..0.1747]\| it/evals=1980/3032 eff=75.2280% N=400 Z=-3.9(65.91%) \| Like=0.20..0.59 [0.1955..0.1960]\| it/evals=2000/3058 eff=75.2445% N=400 Z=-3.9(69.23%) \| Like=0.25..0.59 [0.2514..0.2534]\| it/evals=2050/3130 eff=75.0916% N=400 Mono-modal Volume: ~exp(-9.22) Expected Volume: exp(-5.18) Quality: ok Hinz: +0.0\| ******* +1.1 \| +5.0 Kunz: +0.0\| ******** +1.0 \| +5.0 Z=-3.9(71.23%) \| Like=0.28..0.59 [0.2809..0.2844]\| it/evals=2082/3175 eff=75.0270% N=400 Z=-3.8(72.35%) \| Like=0.30..0.59 [0.3022..0.3037]\| it/evals=2100/3198 eff=75.0536% N=400 Z=-3.8(75.22%) \| Like=0.34..0.59 [0.3430..0.3442]\| it/evals=2150/3266 eff=75.0174% N=400 Mono-modal Volume: ~exp(-9.28) Expected Volume: exp(-5.40) Quality: ok Hinz: +0.0\| ******* +1.0 \| +5.0 Kunz: +0.0\| +0.3 ***********************************\| +1.0 Z=-3.8(75.76%) \| Like=0.35..0.59 [0.3487..0.3489]\| it/evals=2160/3281 eff=74.9740% N=400 Z=-3.8(77.80%) \| Like=0.37..0.59 [0.3745..0.3752]\| it/evals=2200/3327 eff=75.1623% N=400 Mono-modal Volume: ~exp(-9.98) Expected Volume: exp(-5.63) Quality: ok Hinz: +0.0\| +0.3 *********************************** \| +1.0 Kunz: +0.0\| +0.3 ********************************* \| +1.0 Z=-3.7(80.20%) \| Like=0.40..0.59 [0.3974..0.3977]\| it/evals=2250/3400 eff=75.0000% N=400 Z=-3.7(82.32%) \| Like=0.42..0.59 [0.4190..0.4195]\| it/evals=2300/3462 eff=75.1143% N=400 Mono-modal Volume: ~exp(-10.17) * Expected Volume: exp(-5.85) Quality: ok Hinz: +0.0\| +0.3 ******************************* \| +1.0 Kunz: +0.0\| +0.4 ***************************** \| +1.0 Z=-3.7(83.88%) \| Like=0.43..0.59 [0.4339..0.4339]\| it/evals=2340/3515 eff=75.1204% N=400 Z=-3.7(84.26%) \| Like=0.44..0.59 [0.4383..0.4383]\| it/evals=2350/3529 eff=75.1039% N=400 Z=-3.7(85.96%) \| Like=0.45..0.59 [0.4526..0.4536]\| it/evals=2399/3592 eff=75.1566% N=400 Z=-3.7(85.99%) \| Like=0.45..0.59 [0.4536..0.4538]\| it/evals=2400/3594 eff=75.1409% N=400 Mono-modal Volume: ~exp(-10.48) * Expected Volume: exp(-6.08) Quality: ok Hinz: +0.0\| +0.4 **************************** \| +1.0 Kunz: +0.0\| +0.4 *************************** \| +1.0 Z=-3.7(86.93%) \| Like=0.46..0.59 [0.4626..0.4627]\| it/evals=2430/3634 eff=75.1391% N=400 Z=-3.6(87.52%) \| Like=0.47..0.59 [0.4695..0.4695]\| it/evals=2450/3658 eff=75.1995% N=400 Z=-3.6(88.90%) \| Like=0.49..0.59 [0.4854..0.4862]\| it/evals=2500/3731 eff=75.0525% N=400 Mono-modal Volume: ~exp(-10.68) Expected Volume: exp(-6.30) Quality: ok Hinz: +0.0\| +0.4 ************************* \| +1.0 Kunz: +0.0\| +0.4 *********************** \| +1.0 Z=-3.6(89.42%) \| Like=0.49..0.59 [0.4901..0.4901]\| it/evals=2520/3759 eff=75.0223% N=400 Z=-3.6(90.14%) \| Like=0.50..0.59 [0.4964..0.4965]\| it/evals=2550/3792 eff=75.1769% N=400 Z=-3.6(91.25%) \| Like=0.51..0.59 [0.5081..0.5085]\| it/evals=2600/3852 eff=75.3187% N=400 Mono-modal Volume: ~exp(-10.69) Expected Volume: exp(-6.53) Quality: ok Hinz: +0.0\| +0.4 ********************** \| +1.0 Kunz: +0.0\| +0.4 ********************* \| +1.0 Z=-3.6(91.46%) \| Like=0.51..0.59 [0.5109..0.5110]\| it/evals=2610/3865 eff=75.3247% N=400 Z=-3.6(92.24%) \| Like=0.52..0.59 [0.5188..0.5189]\| it/evals=2650/3919 eff=75.3055% N=400 Mono-modal Volume: ~exp(-11.24) * Expected Volume: exp(-6.75) Quality: ok Hinz: +0.0\| +0.4 ******************* \| +1.0 Kunz: +0.0\| +0.5 ******************* \| +1.0 Z=-3.6(93.12%) \| Like=0.53..0.59 [0.5284..0.5285]\| it/evals=2700/3994 eff=75.1252% N=400 Z=-3.6(93.80%) \| Like=0.54..0.59 [0.5357..0.5357]\| it/evals=2743/4052 eff=75.1095% N=400 Z=-3.6(93.91%) \| Like=0.54..0.59 [0.5365..0.5367]\| it/evals=2750/4066 eff=75.0136% N=400 Mono-modal Volume: ~exp(-11.24) Expected Volume: exp(-6.98) Quality: ok Hinz: +0.0\| +0.5 **************** +0.8 \| +1.0 Kunz: +0.0\| +0.5 **************** +0.8 \| +1.0 Z=-3.6(94.61%) \| Like=0.54..0.59 [0.5416..0.5417]\| it/evals=2800/4137 eff=74.9264% N=400 Z=-3.6(95.23%) \| Like=0.55..0.59 [0.5472..0.5473]\| it/evals=2850/4211 eff=74.7835% N=400 Mono-modal Volume: ~exp(-11.33) * Expected Volume: exp(-7.20) Quality: ok Hinz: +0.0\| +0.5 **************** +0.8 \| +1.0 Kunz: +0.0\| +0.5 *************** +0.8 \| +1.0 Z=-3.6(95.56%) \| Like=0.55..0.59 [0.5497..0.5498]\| it/evals=2880/4259 eff=74.6307% N=400 Z=-3.6(95.78%) \| Like=0.55..0.59 [0.5517..0.5518]\| it/evals=2900/4283 eff=74.6845% N=400 Z=-3.6(96.26%) \| Like=0.56..0.59 [0.5568..0.5568]\| it/evals=2950/4349 eff=74.7025% N=400 Mono-modal Volume: ~exp(-12.05) Expected Volume: exp(-7.43) Quality: ok Hinz: +0.0\| +0.5 ************* +0.8 \| +1.0 Kunz: +0.0\| +0.5 ************* +0.8 \| +1.0 Z=-3.5(96.44%) \| Like=0.56..0.59 [0.5591..0.5592]\| it/evals=2970/4377 eff=74.6794% N=400 Z=-3.5(96.70%) \| Like=0.56..0.59 [0.5616..0.5618]\| it/evals=3000/4417 eff=74.6826% N=400 Z=-3.5(97.06%) \| Like=0.56..0.59 [0.5650..0.5650]\| it/evals=3047/4479 eff=74.6997% N=400 Z=-3.5(97.08%) \| Like=0.57..0.59 [0.5651..0.5652]\| it/evals=3050/4483 eff=74.7000% N=400 Mono-modal Volume: ~exp(-12.05) Expected Volume: exp(-7.65) Quality: ok Hinz: +0.0\| +0.5 ************* +0.8 \| +1.0 Kunz: +0.0\| +0.5 *********** +0.8 \| +1.0 Z=-3.5(97.36%) \| Like=0.57..0.59 [0.5675..0.5675]\| it/evals=3091/4537 eff=74.7160% N=400 Z=-3.5(97.42%) \| Like=0.57..0.59 [0.5679..0.5679]\| it/evals=3100/4552 eff=74.6628% N=400 Mono-modal Volume: ~exp(-12.28) * Expected Volume: exp(-7.88) Quality: ok Hinz: +0.0\| +0.5 *********** +0.7 \| +1.0 Kunz: +0.0\| +0.5 ********** +0.7 \| +1.0 Z=-3.5(97.72%) \| Like=0.57..0.59 [0.5706..0.5707]\| it/evals=3150/4629 eff=74.4857% N=400 Z=-3.5(97.98%) \| Like=0.57..0.59 [0.5730..0.5730]\| it/evals=3200/4692 eff=74.5573% N=400 Mono-modal Volume: ~exp(-12.40) * Expected Volume: exp(-8.10) Quality: ok Hinz: +0.0\| +0.5 ********* +0.7 \| +1.0 Kunz: +0.0\| +0.5 ********* +0.7 \| +1.0 Z=-3.5(98.17%) \| Like=0.57..0.59 [0.5749..0.5749]\| it/evals=3240/4743 eff=74.6028% N=400 Z=-3.5(98.22%) \| Like=0.58..0.59 [0.5752..0.5752]\| it/evals=3250/4757 eff=74.5926% N=400 Z=-3.5(98.43%) \| Like=0.58..0.59 [0.5772..0.5772]\| it/evals=3300/4822 eff=74.6269% N=400 Mono-modal Volume: ~exp(-12.82) Expected Volume: exp(-8.33) Quality: ok Hinz: +0.0\| +0.5 ********* +0.7 \| +1.0 Kunz: +0.0\| +0.5 ******** +0.7 \| +1.0 Z=-3.5(98.54%) \| Like=0.58..0.59 [0.5788..0.5788]\| it/evals=3330/4858 eff=74.6972% N=400 Z=-3.5(98.61%) \| Like=0.58..0.59 [0.5793..0.5793]\| it/evals=3350/4882 eff=74.7434% N=400 Z=-3.5(98.77%) \| Like=0.58..0.59 [0.5811..0.5811]\| it/evals=3400/4940 eff=74.8899% N=400 Mono-modal Volume: ~exp(-12.99) Expected Volume: exp(-8.55) Quality: ok Hinz: +0.0\| +0.6 ******* +0.7 \| +1.0 Kunz: +0.0\| +0.6 ******* +0.7 \| +1.0 Z=-3.5(98.83%) \| Like=0.58..0.59 [0.5817..0.5817]\| it/evals=3420/4973 eff=74.7868% N=400 Z=-3.5(98.92%) \| Like=0.58..0.59 [0.5824..0.5824]\| it/evals=3450/5012 eff=74.8049% N=400 [ultranest] Explored until L=0.6 [ultranest] Likelihood function evaluations: 5053 [ultranest] logZ = -3.495 +- 0.06646 [ultranest] Effective samples strategy satisfied (ESS = 1629.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.07, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 [ultranest] done iterating. ncalls: 5055 nunique: 5055 {'niter': 3883, 'logz': -3.512979739281697, 'logzerr': 0.15019082031188857, 'logz_bs': -3.4946153773041653, 'logz_single': -3.512979739281697, 'logzerr_tail': 0.00993867560773154, 'logzerr_bs': 0.14986162028058514, 'ess': 1629.911652892675, 'H': 3.093626125867617, 'Herr': 0.05327658224759624, 'posterior': {'mean': [0.6528641810663336, 0.6264357937278213], 'stdev': [0.5380843565640636, 0.5207584836042055], 'median': [0.6513496553807023, 0.6346605137507799], 'errlo': [0.11736651751957616, 0.08940050480431339], 'errup': [1.193722161567365, 1.137157590020708], 'information_gain_bits': [0.6859949672653227, 0.7756177953890441]}, 'weighted_samples': {'upoints': array([[0.01988013, 0.02621099], [0.01833264, 0.066725 ], [0.08504421, 0.03905478], ..., [0.56409333, 0.5633068 ], [0.56303122, 0.5635434 ], [0.56347491, 0.56317946]]), 'points': array([[-4.80119866, -4.73789013], [-4.81667357, -4.33275002], [-4.14955789, -4.60945217], ..., [ 0.64093333, 0.63306805], [ 0.63031216, 0.63543397], [ 0.63474906, 0.63179457]]), 'weights': array([9.26018546e-50, 2.47035294e-46, 4.83768179e-43, ..., 2.50932121e-05, 2.50942808e-05, 2.50947339e-05]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -14.69896455, -14.69896455, -14.69896455]), 'bootstrapped_weights': array([[1.40582785e-49, 1.35668842e-49, 0.00000000e+00, ..., 1.36553936e-49, 1.51693786e-49, 1.46025903e-49], [0.00000000e+00, 3.61422607e-46, 4.17988021e-46, ..., 3.63785987e-46, 0.00000000e+00, 3.88958952e-46], [0.00000000e+00, 7.06788512e-43, 8.17277585e-43, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], ..., [0.00000000e+00, 4.11559930e-05, 4.44503916e-05, ..., 0.00000000e+00, 0.00000000e+00, 3.81059410e-05], [4.47343654e-05, 4.11577458e-05, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 4.44530874e-05, ..., 0.00000000e+00, 4.46347506e-05, 0.00000000e+00]]), 'logl': array([-110.42379603, -102.5323187 , -94.94998881, ..., 0.59307162, 0.59311421, 0.59313227])}, 'samples': array([[ 1.29700997, 0.39691822], [-0.25159545, 1.1739252 ], [ 0.49331732, -0.01375432], ..., [ 1.50143774, 0.56239362], [ 0.97385436, 1.10514422], [ 0.65458513, 0.52712821]]), 'maximum_likelihood': {'logl': 0.5931322698047243, 'point': [0.6347490626876349, 0.6317945702385996], 'point_untransformed': [0.5634749062687635, 0.56317945702386]}, 'ncall': 5053, 'paramnames': ['Hinz', 'Kunz'], 'logzerr_single': 0.08794353480881378, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-110.42, Lmax=0.28 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=452, regioncalls=2080, ndraw=40, logz=-66.99, remainder_fraction=100.0000%, Lmin=-62.58, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=494, regioncalls=3760, ndraw=40, logz=-57.38, remainder_fraction=100.0000%, Lmin=-52.63, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=505, regioncalls=4200, ndraw=40, logz=-54.91, remainder_fraction=100.0000%, Lmin=-50.20, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=567, regioncalls=6680, ndraw=40, logz=-46.91, remainder_fraction=100.0000%, Lmin=-42.21, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=613, regioncalls=8520, ndraw=40, logz=-42.21, remainder_fraction=100.0000%, Lmin=-37.96, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=634, regioncalls=9360, ndraw=40, logz=-40.41, remainder_fraction=100.0000%, Lmin=-36.05, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=700, regioncalls=12000, ndraw=40, logz=-36.16, remainder_fraction=100.0000%, Lmin=-31.84, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=735, regioncalls=13400, ndraw=40, logz=-34.25, remainder_fraction=100.0000%, Lmin=-29.94, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=770, regioncalls=14800, ndraw=40, logz=-31.69, remainder_fraction=100.0000%, Lmin=-27.71, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=834, regioncalls=17360, ndraw=40, logz=-28.93, remainder_fraction=100.0000%, Lmin=-24.89, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=397, ncalls=898, regioncalls=19920, ndraw=40, logz=-25.59, remainder_fraction=100.0000%, Lmin=-21.07, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=907, regioncalls=20280, ndraw=40, logz=-25.35, remainder_fraction=100.0000%, Lmin=-20.82, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=976, regioncalls=23040, ndraw=40, logz=-22.62, remainder_fraction=100.0000%, Lmin=-18.55, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=1043, regioncalls=25720, ndraw=40, logz=-20.49, remainder_fraction=100.0000%, Lmin=-16.26, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1105, regioncalls=28200, ndraw=40, logz=-18.69, remainder_fraction=100.0000%, Lmin=-14.60, Lmax=0.51 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1118, regioncalls=28720, ndraw=40, logz=-18.33, remainder_fraction=100.0000%, Lmin=-14.26, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1179, regioncalls=31160, ndraw=40, logz=-16.64, remainder_fraction=99.9998%, Lmin=-12.62, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1225, regioncalls=33000, ndraw=40, logz=-15.74, remainder_fraction=99.9995%, Lmin=-11.69, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1250, regioncalls=34000, ndraw=40, logz=-15.21, remainder_fraction=99.9991%, Lmin=-11.26, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1314, regioncalls=36560, ndraw=40, logz=-13.84, remainder_fraction=99.9968%, Lmin=-9.78, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1378, regioncalls=39120, ndraw=40, logz=-12.73, remainder_fraction=99.9903%, Lmin=-8.72, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1448, regioncalls=41920, ndraw=40, logz=-11.76, remainder_fraction=99.9742%, Lmin=-7.66, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=839, ncalls=1498, regioncalls=43920, ndraw=40, logz=-10.92, remainder_fraction=99.9410%, Lmin=-6.78, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1516, regioncalls=44640, ndraw=40, logz=-10.71, remainder_fraction=99.9267%, Lmin=-6.56, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=1582, regioncalls=47280, ndraw=40, logz=-9.92, remainder_fraction=99.8388%, Lmin=-5.87, Lmax=0.56 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1588, regioncalls=47520, ndraw=40, logz=-9.83, remainder_fraction=99.8233%, Lmin=-5.80, Lmax=0.56 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1654, regioncalls=50160, ndraw=40, logz=-9.11, remainder_fraction=99.6334%, Lmin=-4.92, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1707, regioncalls=52320, ndraw=40, logz=-8.49, remainder_fraction=99.3057%, Lmin=-4.29, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1719, regioncalls=52840, ndraw=40, logz=-8.36, remainder_fraction=99.1963%, Lmin=-4.17, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1787, regioncalls=55560, ndraw=40, logz=-7.76, remainder_fraction=98.5780%, Lmin=-3.65, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1835, regioncalls=57480, ndraw=40, logz=-7.44, remainder_fraction=98.0469%, Lmin=-3.36, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1859, regioncalls=58480, ndraw=40, logz=-7.26, remainder_fraction=97.6487%, Lmin=-3.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1926, regioncalls=61160, ndraw=40, logz=-6.82, remainder_fraction=96.4136%, Lmin=-2.70, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1958, regioncalls=62440, ndraw=40, logz=-6.65, remainder_fraction=95.8254%, Lmin=-2.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1996, regioncalls=64040, ndraw=40, logz=-6.43, remainder_fraction=94.7437%, Lmin=-2.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=2034, regioncalls=65680, ndraw=40, logz=-6.20, remainder_fraction=93.3965%, Lmin=-2.15, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=2050, regioncalls=66360, ndraw=40, logz=-6.10, remainder_fraction=92.7134%, Lmin=-2.06, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2061, regioncalls=66800, ndraw=40, logz=-6.04, remainder_fraction=92.1904%, Lmin=-2.00, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=2108, regioncalls=68720, ndraw=40, logz=-5.80, remainder_fraction=90.1182%, Lmin=-1.73, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2169, regioncalls=71160, ndraw=40, logz=-5.54, remainder_fraction=87.2523%, Lmin=-1.48, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2237, regioncalls=73880, ndraw=40, logz=-5.31, remainder_fraction=83.8089%, Lmin=-1.26, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2295, regioncalls=76200, ndraw=40, logz=-5.14, remainder_fraction=80.6009%, Lmin=-1.09, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=2306, regioncalls=76720, ndraw=40, logz=-5.11, remainder_fraction=79.8571%, Lmin=-1.04, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2374, regioncalls=79440, ndraw=40, logz=-4.93, remainder_fraction=76.0914%, Lmin=-0.91, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2436, regioncalls=81920, ndraw=40, logz=-4.77, remainder_fraction=71.7238%, Lmin=-0.70, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2513, regioncalls=85000, ndraw=40, logz=-4.62, remainder_fraction=67.2236%, Lmin=-0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2546, regioncalls=86360, ndraw=40, logz=-4.57, remainder_fraction=65.5165%, Lmin=-0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2581, regioncalls=87760, ndraw=40, logz=-4.50, remainder_fraction=62.8444%, Lmin=-0.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1691, ncalls=2643, regioncalls=90240, ndraw=40, logz=-4.40, remainder_fraction=59.1080%, Lmin=-0.32, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2654, regioncalls=90680, ndraw=40, logz=-4.38, remainder_fraction=58.2874%, Lmin=-0.30, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2670, regioncalls=91360, ndraw=40, logz=-4.36, remainder_fraction=57.3338%, Lmin=-0.29, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2723, regioncalls=93480, ndraw=40, logz=-4.28, remainder_fraction=53.6176%, Lmin=-0.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2788, regioncalls=96120, ndraw=40, logz=-4.20, remainder_fraction=49.4894%, Lmin=-0.09, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1838, ncalls=2833, regioncalls=97920, ndraw=40, logz=-4.13, remainder_fraction=46.2356%, Lmin=-0.03, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2846, regioncalls=98440, ndraw=40, logz=-4.12, remainder_fraction=45.3322%, Lmin=-0.02, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2897, regioncalls=100480, ndraw=40, logz=-4.06, remainder_fraction=42.1616%, Lmin=0.04, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2909, regioncalls=100960, ndraw=40, logz=-4.05, remainder_fraction=41.3899%, Lmin=0.06, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=2984, regioncalls=103960, ndraw=40, logz=-3.99, remainder_fraction=37.7771%, Lmin=0.14, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2986, regioncalls=104040, ndraw=40, logz=-3.99, remainder_fraction=37.6453%, Lmin=0.14, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3032, regioncalls=105920, ndraw=40, logz=-3.95, remainder_fraction=35.5167%, Lmin=0.17, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3058, regioncalls=107000, ndraw=40, logz=-3.93, remainder_fraction=34.0860%, Lmin=0.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=3130, regioncalls=109960, ndraw=40, logz=-3.88, remainder_fraction=30.7692%, Lmin=0.25, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2082, ncalls=3175, regioncalls=111760, ndraw=40, logz=-3.85, remainder_fraction=28.7658%, Lmin=0.28, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=3198, regioncalls=112680, ndraw=40, logz=-3.84, remainder_fraction=27.6476%, Lmin=0.30, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=3266, regioncalls=115400, ndraw=40, logz=-3.80, remainder_fraction=24.7819%, Lmin=0.34, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3281, regioncalls=116040, ndraw=40, logz=-3.79, remainder_fraction=24.2430%, Lmin=0.35, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3327, regioncalls=117960, ndraw=40, logz=-3.76, remainder_fraction=22.1990%, Lmin=0.37, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3400, regioncalls=121000, ndraw=40, logz=-3.73, remainder_fraction=19.8044%, Lmin=0.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=3462, regioncalls=123480, ndraw=40, logz=-3.71, remainder_fraction=17.6802%, Lmin=0.42, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3515, regioncalls=125680, ndraw=40, logz=-3.69, remainder_fraction=16.1212%, Lmin=0.43, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=3529, regioncalls=126320, ndraw=40, logz=-3.68, remainder_fraction=15.7410%, Lmin=0.44, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2399, ncalls=3592, regioncalls=128840, ndraw=40, logz=-3.66, remainder_fraction=14.0446%, Lmin=0.45, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3594, regioncalls=128920, ndraw=40, logz=-3.66, remainder_fraction=14.0103%, Lmin=0.45, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3634, regioncalls=130560, ndraw=40, logz=-3.65, remainder_fraction=13.0726%, Lmin=0.46, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3658, regioncalls=131520, ndraw=40, logz=-3.65, remainder_fraction=12.4782%, Lmin=0.47, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3731, regioncalls=134440, ndraw=40, logz=-3.63, remainder_fraction=11.0953%, Lmin=0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3759, regioncalls=135600, ndraw=40, logz=-3.62, remainder_fraction=10.5813%, Lmin=0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3792, regioncalls=136920, ndraw=40, logz=-3.62, remainder_fraction=9.8607%, Lmin=0.50, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3852, regioncalls=139320, ndraw=40, logz=-3.60, remainder_fraction=8.7482%, Lmin=0.51, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3865, regioncalls=139880, ndraw=40, logz=-3.60, remainder_fraction=8.5412%, Lmin=0.51, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3919, regioncalls=142160, ndraw=40, logz=-3.59, remainder_fraction=7.7618%, Lmin=0.52, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3994, regioncalls=145160, ndraw=40, logz=-3.58, remainder_fraction=6.8783%, Lmin=0.53, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2743, ncalls=4052, regioncalls=147600, ndraw=40, logz=-3.58, remainder_fraction=6.1985%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=4066, regioncalls=148160, ndraw=40, logz=-3.58, remainder_fraction=6.0943%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4137, regioncalls=151000, ndraw=40, logz=-3.57, remainder_fraction=5.3940%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=4211, regioncalls=153960, ndraw=40, logz=-3.56, remainder_fraction=4.7748%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4259, regioncalls=155960, ndraw=40, logz=-3.56, remainder_fraction=4.4363%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=4283, regioncalls=156920, ndraw=40, logz=-3.56, remainder_fraction=4.2245%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=4349, regioncalls=159560, ndraw=40, logz=-3.55, remainder_fraction=3.7367%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4377, regioncalls=160720, ndraw=40, logz=-3.55, remainder_fraction=3.5573%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4417, regioncalls=162360, ndraw=40, logz=-3.55, remainder_fraction=3.3040%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3047, ncalls=4479, regioncalls=164840, ndraw=40, logz=-3.54, remainder_fraction=2.9426%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=4483, regioncalls=165000, ndraw=40, logz=-3.54, remainder_fraction=2.9209%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3091, ncalls=4537, regioncalls=167160, ndraw=40, logz=-3.54, remainder_fraction=2.6401%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=4552, regioncalls=167760, ndraw=40, logz=-3.54, remainder_fraction=2.5820%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4629, regioncalls=170880, ndraw=40, logz=-3.54, remainder_fraction=2.2817%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4692, regioncalls=173400, ndraw=40, logz=-3.53, remainder_fraction=2.0165%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4743, regioncalls=175480, ndraw=40, logz=-3.53, remainder_fraction=1.8265%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3250, ncalls=4757, regioncalls=176040, ndraw=40, logz=-3.53, remainder_fraction=1.7818%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3300, ncalls=4822, regioncalls=178640, ndraw=40, logz=-3.53, remainder_fraction=1.5739%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=4858, regioncalls=180280, ndraw=40, logz=-3.53, remainder_fraction=1.4610%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=4882, regioncalls=181240, ndraw=40, logz=-3.53, remainder_fraction=1.3902%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4940, regioncalls=183560, ndraw=40, logz=-3.53, remainder_fraction=1.2278%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4973, regioncalls=184960, ndraw=40, logz=-3.52, remainder_fraction=1.1682%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3450, ncalls=5012, regioncalls=186560, ndraw=40, logz=-3.52, remainder_fraction=1.0842%, Lmin=0.58, Lmax=0.59 INFO ultranest:integrator.py:2654 Explored until L=0.6 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5053 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.495 +- 0.06646 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1629.9, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.07, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:2894 Making corner plot ... DEBUG ultranest:integrator.py:2940 Making run plot ... DEBUG ultranest:integrator.py:2916 Making trace plot ...
Passed	tests/test_ordertest.py::test_order_correctness	0.26
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ frac: 1 runlength: [] frac: 0.9 split after 551 split after 445 runlength: [551, 445] number of runs: 0 2
Passed	tests/test_regionsampling.py::test_region_ellipsoid	0.03
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ enlargement factor: 1.641305045847665 0.6092712640650795
Passed	tests/test_run.py::test_return_summary	11.26
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.38) * Expected Volume: exp(0.00) Quality: ok a: +0.000\|******************************************************\| +1.000 b: +0.000\|*****************************************************\| +1.000 Z=-inf(0.00%) \| Like=-2804.34..9.48 [-2804.3432..-295.4123] \| it/evals=0/401 eff=0.0000% N=400 Z=-2192.3(0.00%) \| Like=-2186.44..9.48 [-2804.3432..-295.4123] \| it/evals=40/443 eff=93.0233% N=400 Z=-1580.2(0.00%) \| Like=-1557.39..9.48 [-2804.3432..-295.4123] \| it/evals=80/487 eff=91.9540% N=400 Mono-modal Volume: ~exp(-4.63) Expected Volume: exp(-0.23) Quality: ok a: +0.000\|******************************************************\| +1.000 b: +0.0\| +0.2 *****************************************\| +1.0 Z=-1407.7(0.00%) \| Like=-1382.92..9.48 [-2804.3432..-295.4123] \| it/evals=90/497 eff=92.7835% N=400 Z=-1154.3(0.00%) \| Like=-1134.91..9.48 [-2804.3432..-295.4123] \| it/evals=120/529 eff=93.0233% N=400 Z=-889.6(0.00%) \| Like=-872.40..9.51 [-2804.3432..-295.4123] \| it/evals=160/572 eff=93.0233% N=400 Mono-modal Volume: ~exp(-4.85) Expected Volume: exp(-0.45) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.4 ********************************\| +1.0 Z=-667.9(0.00%) \| Like=-658.26..9.51 [-2804.3432..-295.4123] \| it/evals=180/594 eff=92.7835% N=400 Z=-565.8(0.00%) \| Like=-558.96..10.07 [-2804.3432..-295.4123] \| it/evals=200/614 eff=93.4579% N=400 Z=-377.4(0.00%) \| Like=-370.39..10.07 [-2804.3432..-295.4123] \| it/evals=240/660 eff=92.3077% N=400 Mono-modal Volume: ~exp(-5.07) Expected Volume: exp(-0.67) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.5 *************************\| +1.0 Z=-287.5(0.00%) \| Like=-281.30..10.07 [-293.4733..-70.1425] \| it/evals=270/692 eff=92.4658% N=400 Z=-277.3(0.00%) \| Like=-270.53..10.07 [-293.4733..-70.1425] \| it/evals=280/703 eff=92.4092% N=400 Z=-230.2(0.00%) \| Like=-222.87..10.10 [-293.4733..-70.1425] \| it/evals=320/748 eff=91.9540% N=400 Z=-193.8(0.00%) \| Like=-187.56..10.10 [-293.4733..-70.1425] \| it/evals=352/796 eff=88.8889% N=400 Mono-modal Volume: ~exp(-5.31) Expected Volume: exp(-0.90) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.6 ****************** \| +1.0 Z=-188.0(0.00%) \| Like=-181.22..10.10 [-293.4733..-70.1425] \| it/evals=360/804 eff=89.1089% N=400 Z=-158.3(0.00%) \| Like=-150.51..10.10 [-293.4733..-70.1425] \| it/evals=400/849 eff=89.0869% N=400 Z=-126.5(0.00%) \| Like=-120.40..10.10 [-293.4733..-70.1425] \| it/evals=440/897 eff=88.5312% N=400 Mono-modal Volume: ~exp(-5.31) Expected Volume: exp(-1.12) Quality: ok a: +0.0000\|****************************************************\| +1.0000 b: +0.0\| +0.6 **************** \| +1.0 Z=-110.1(0.00%) \| Like=-103.38..10.10 [-293.4733..-70.1425] \| it/evals=467/929 eff=88.2798% N=400 Z=-102.1(0.00%) \| Like=-95.41..10.10 [-293.4733..-70.1425] \| it/evals=480/944 eff=88.2353% N=400 Z=-85.1(0.00%) \| Like=-79.33..10.10 [-293.4733..-70.1425] \| it/evals=512/990 eff=86.7797% N=400 Z=-82.9(0.00%) \| Like=-76.70..10.10 [-293.4733..-70.1425] \| it/evals=520/998 eff=86.9565% N=400 Mono-modal Volume: ~exp(-5.72) * Expected Volume: exp(-1.35) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.6 ************* \| +1.0 Z=-76.3(0.00%) \| Like=-68.89..10.10 [-69.6174..-13.4580] \| it/evals=540/1022 eff=86.8167% N=400 Z=-69.7(0.00%) \| Like=-63.65..10.10 [-69.6174..-13.4580] \| it/evals=560/1047 eff=86.5533% N=400 Z=-57.2(0.00%) \| Like=-50.92..10.10 [-69.6174..-13.4580] \| it/evals=600/1095 eff=86.3309% N=400 Mono-modal Volume: ~exp(-5.83) * Expected Volume: exp(-1.57) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.6 ********** \| +1.0 Z=-49.6(0.00%) \| Like=-43.45..10.10 [-69.6174..-13.4580] \| it/evals=630/1128 eff=86.5385% N=400 Z=-47.5(0.00%) \| Like=-41.70..10.10 [-69.6174..-13.4580] \| it/evals=640/1142 eff=86.2534% N=400 Z=-40.6(0.00%) \| Like=-34.43..10.10 [-69.6174..-13.4580] \| it/evals=680/1185 eff=86.6242% N=400 Mono-modal Volume: ~exp(-6.37) * Expected Volume: exp(-1.80) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.7 ****** \| +1.0 Z=-33.7(0.00%) \| Like=-27.45..10.12 [-69.6174..-13.4580] \| it/evals=720/1230 eff=86.7470% N=400 Z=-25.8(0.00%) \| Like=-19.82..10.12 [-69.6174..-13.4580] \| it/evals=760/1274 eff=86.9565% N=400 Z=-21.3(0.00%) \| Like=-15.22..10.12 [-69.6174..-13.4580] \| it/evals=800/1323 eff=86.6739% N=400 Mono-modal Volume: ~exp(-6.37) Expected Volume: exp(-2.02) Quality: ok a: +0.0000\|****************************************************\| +1.0000 b: +0.0\| +0.7 ****** +0.8 \| +1.0 Z=-17.3(0.00%) \| Like=-11.83..10.12 [-13.3811..-0.2520] \| it/evals=840/1373 eff=86.3309% N=400 Z=-14.0(0.00%) \| Like=-8.57..10.12 [-13.3811..-0.2520] \| it/evals=880/1421 eff=86.1900% N=400 Mono-modal Volume: ~exp(-6.54) * Expected Volume: exp(-2.25) Quality: ok a: +0.0000\|******************************************************\| +1.0000 b: +0.0\| +0.7 ****** +0.8 \| +1.0 Z=-12.8(0.00%) \| Like=-7.08..10.12 [-13.3811..-0.2520] \| it/evals=900/1451 eff=85.6327% N=400 Z=-11.4(0.00%) \| Like=-5.91..10.12 [-13.3811..-0.2520] \| it/evals=920/1474 eff=85.6611% N=400 Z=-9.2(0.00%) \| Like=-3.59..10.12 [-13.3811..-0.2520] \| it/evals=960/1521 eff=85.6378% N=400 Mono-modal Volume: ~exp(-6.79) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\|******************************************************\| +1.00 b: +0.0\| +0.7 **** +0.8 \| +1.0 Z=-7.9(0.00%) \| Like=-2.76..10.12 [-13.3811..-0.2520] \| it/evals=990/1560 eff=85.3448% N=400 Z=-7.5(0.00%) \| Like=-2.52..10.12 [-13.3811..-0.2520] \| it/evals=1000/1571 eff=85.3971% N=400 Z=-6.3(0.00%) \| Like=-1.31..10.12 [-13.3811..-0.2520] \| it/evals=1040/1618 eff=85.3859% N=400 Mono-modal Volume: ~exp(-7.22) * Expected Volume: exp(-2.70) Quality: ok a: +0.00\| * *********************************************** \| +1.00 b: +0.0\| +0.7 **** +0.8 \| +1.0 Z=-5.4(0.00%) \| Like=-0.31..10.12 [-13.3811..-0.2520] \| it/evals=1080/1678 eff=84.5070% N=400 Z=-4.4(0.01%) \| Like=0.61..10.12 [-0.2347..4.9194] \| it/evals=1120/1726 eff=84.4646% N=400 Z=-3.5(0.02%) \| Like=1.56..10.12 [-0.2347..4.9194] \| it/evals=1160/1779 eff=84.1189% N=400 Mono-modal Volume: ~exp(-7.27) * Expected Volume: exp(-2.92) Quality: ok a: +0.00\| ******************************************** \| +1.00 b: +0.0\| +0.7 **** +0.8 \| +1.0 Z=-3.3(0.03%) \| Like=1.75..10.12 [-0.2347..4.9194] \| it/evals=1170/1790 eff=84.1727% N=400 Z=-2.7(0.04%) \| Like=2.24..10.12 [-0.2347..4.9194] \| it/evals=1200/1832 eff=83.7989% N=400 Z=-2.0(0.09%) \| Like=2.97..10.12 [-0.2347..4.9194] \| it/evals=1240/1889 eff=83.2774% N=400 Mono-modal Volume: ~exp(-7.56) * Expected Volume: exp(-3.15) Quality: ok a: +0.0\| **************************************** \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=-1.7(0.13%) \| Like=3.25..10.12 [-0.2347..4.9194] \| it/evals=1260/1922 eff=82.7858% N=400 Z=-1.4(0.17%) \| Like=3.53..10.12 [-0.2347..4.9194] \| it/evals=1280/1950 eff=82.5806% N=400 Z=-0.9(0.27%) \| Like=4.08..10.12 [-0.2347..4.9194] \| it/evals=1314/1987 eff=82.7977% N=400 Z=-0.8(0.28%) \| Like=4.19..10.12 [-0.2347..4.9194] \| it/evals=1320/1996 eff=82.7068% N=400 Mono-modal Volume: ~exp(-7.56) Expected Volume: exp(-3.37) Quality: ok a: +0.0\| ********************************** \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=-0.5(0.42%) \| Like=4.57..10.12 [-0.2347..4.9194] \| it/evals=1350/2038 eff=82.4176% N=400 Z=-0.3(0.48%) \| Like=4.72..10.12 [-0.2347..4.9194] \| it/evals=1360/2049 eff=82.4742% N=400 Z=0.2(0.79%) \| Like=5.21..10.12 [4.9278..7.0406] \| it/evals=1398/2102 eff=82.1387% N=400 Z=0.2(0.82%) \| Like=5.25..10.12 [4.9278..7.0406] \| it/evals=1400/2104 eff=82.1596% N=400 Mono-modal Volume: ~exp(-7.92) * Expected Volume: exp(-3.60) Quality: ok a: +0.0\| +0.2 ******************************* +0.8 \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=0.6(1.23%) \| Like=5.66..10.12 [4.9278..7.0406] \| it/evals=1440/2166 eff=81.5402% N=400 Z=1.0(1.80%) \| Like=6.08..10.12 [4.9278..7.0406] \| it/evals=1477/2208 eff=81.6925% N=400 Z=1.0(1.86%) \| Like=6.17..10.12 [4.9278..7.0406] \| it/evals=1480/2214 eff=81.5877% N=400 Z=1.4(2.65%) \| Like=6.49..10.12 [4.9278..7.0406] \| it/evals=1515/2255 eff=81.6712% N=400 Z=1.4(2.79%) \| Like=6.53..10.12 [4.9278..7.0406] \| it/evals=1520/2264 eff=81.5451% N=400 Mono-modal Volume: ~exp(-8.18) * Expected Volume: exp(-3.82) Quality: ok a: +0.0\| +0.2 **************************** +0.8 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=1.5(3.06%) \| Like=6.62..10.13 [4.9278..7.0406] \| it/evals=1530/2277 eff=81.5131% N=400 Z=1.8(3.98%) \| Like=6.82..10.13 [4.9278..7.0406] \| it/evals=1560/2318 eff=81.3347% N=400 Z=2.1(5.31%) \| Like=7.12..10.13 [7.0440..7.5457] \| it/evals=1600/2373 eff=81.0948% N=400 Mono-modal Volume: ~exp(-8.18) Expected Volume: exp(-4.05) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=2.2(6.09%) \| Like=7.27..10.13 [7.0440..7.5457] \| it/evals=1620/2398 eff=81.0811% N=400 Z=2.3(7.07%) \| Like=7.38..10.13 [7.0440..7.5457] \| it/evals=1640/2427 eff=80.9077% N=400 Z=2.6(9.06%) \| Like=7.58..10.13 [7.5514..7.6856] \| it/evals=1680/2484 eff=80.6142% N=400 Mono-modal Volume: ~exp(-8.58) * Expected Volume: exp(-4.27) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=2.7(10.74%) \| Like=7.72..10.13 [7.6960..7.7394] \| it/evals=1710/2528 eff=80.3571% N=400 Z=2.8(11.22%) \| Like=7.78..10.13 [7.7823..7.7836]\| it/evals=1720/2543 eff=80.2613% N=400 Z=3.0(13.47%) \| Like=8.01..10.13 [8.0116..8.0157]\| it/evals=1760/2598 eff=80.0728% N=400 Mono-modal Volume: ~exp(-8.58) Expected Volume: exp(-4.50) Quality: ok a: +0.0\| +0.3 ******************** +0.7 \| +1.0 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=3.2(16.00%) \| Like=8.20..10.14 [8.2043..8.2054]\| it/evals=1800/2648 eff=80.0712% N=400 Z=3.3(18.93%) \| Like=8.38..10.14 [8.3768..8.3804]\| it/evals=1840/2700 eff=80.0000% N=400 Z=3.5(22.01%) \| Like=8.55..10.14 [8.5506..8.5521]\| it/evals=1880/2762 eff=79.5936% N=400 Mono-modal Volume: ~exp(-8.58) Expected Volume: exp(-4.73) Quality: ok a: +0.0\| +0.3 ***************** +0.7 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=3.6(25.00%) \| Like=8.68..10.14 [8.6823..8.6844]\| it/evals=1918/2822 eff=79.1908% N=400 Z=3.6(25.18%) \| Like=8.68..10.14 [8.6849..8.6871]\| it/evals=1920/2825 eff=79.1753% N=400 Z=3.7(28.53%) \| Like=8.80..10.14 [8.7995..8.8040]\| it/evals=1960/2886 eff=78.8415% N=400 Mono-modal Volume: ~exp(-9.04) Expected Volume: exp(-4.95) Quality: ok a: +0.0\| +0.3 **************** +0.7 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=3.8(30.22%) \| Like=8.87..10.14 [8.8656..8.8658]\| it/evals=1980/2918 eff=78.6338% N=400 Z=3.8(32.02%) \| Like=8.93..10.14 [8.9262..8.9269]\| it/evals=2000/2941 eff=78.7092% N=400 Z=4.0(35.42%) \| Like=9.05..10.14 [9.0537..9.0575]\| it/evals=2040/2994 eff=78.6430% N=400 Mono-modal Volume: ~exp(-9.44) Expected Volume: exp(-5.18) Quality: ok a: +0.0\| +0.4 ************** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.0(38.23%) \| Like=9.13..10.14 [9.1281..9.1328]\| it/evals=2070/3038 eff=78.4685% N=400 Z=4.0(39.10%) \| Like=9.16..10.14 [9.1617..9.1619]\| it/evals=2080/3051 eff=78.4610% N=400 Z=4.1(42.71%) \| Like=9.27..10.14 [9.2655..9.2680]\| it/evals=2120/3101 eff=78.4894% N=400 Mono-modal Volume: ~exp(-9.48) Expected Volume: exp(-5.40) Quality: ok a: +0.0\| +0.4 ************* +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.2(46.29%) \| Like=9.34..10.14 [9.3425..9.3426]\| it/evals=2160/3151 eff=78.5169% N=400 Z=4.3(49.56%) \| Like=9.42..10.14 [9.4181..9.4192]\| it/evals=2200/3201 eff=78.5434% N=400 Z=4.4(53.04%) \| Like=9.50..10.14 [9.4984..9.5000]\| it/evals=2240/3249 eff=78.6241% N=400 Mono-modal Volume: ~exp(-9.83) Expected Volume: exp(-5.63) Quality: ok a: +0.0\| +0.4 ************ +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.4(53.87%) \| Like=9.51..10.14 [9.5100..9.5134]\| it/evals=2250/3262 eff=78.6164% N=400 Z=4.4(56.43%) \| Like=9.56..10.14 [9.5552..9.5561]\| it/evals=2280/3298 eff=78.6749% N=400 Z=4.5(59.42%) \| Like=9.60..10.14 [9.6043..9.6072]\| it/evals=2320/3356 eff=78.4844% N=400 Mono-modal Volume: ~exp(-9.97) Expected Volume: exp(-5.85) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.5(60.88%) \| Like=9.64..10.14 [9.6377..9.6381]\| it/evals=2340/3383 eff=78.4445% N=400 Z=4.5(62.38%) \| Like=9.66..10.14 [9.6635..9.6647]\| it/evals=2360/3408 eff=78.4574% N=400 Z=4.6(65.25%) \| Like=9.71..10.14 [9.7086..9.7125]\| it/evals=2400/3455 eff=78.5597% N=400 Mono-modal Volume: ~exp(-10.37) Expected Volume: exp(-6.08) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.6(67.30%) \| Like=9.75..10.14 [9.7479..9.7483]\| it/evals=2430/3495 eff=78.5137% N=400 Z=4.6(67.95%) \| Like=9.75..10.14 [9.7537..9.7572]\| it/evals=2440/3508 eff=78.5071% N=400 Z=4.6(70.51%) \| Like=9.79..10.14 [9.7865..9.7886]\| it/evals=2480/3553 eff=78.6552% N=400 Mono-modal Volume: ~exp(-10.50) Expected Volume: exp(-6.30) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.7(72.88%) \| Like=9.82..10.14 [9.8184..9.8199]\| it/evals=2520/3603 eff=78.6762% N=400 Z=4.7(75.12%) \| Like=9.85..10.14 [9.8450..9.8452]\| it/evals=2560/3651 eff=78.7450% N=400 Z=4.7(77.19%) \| Like=9.88..10.14 [9.8832..9.8867]\| it/evals=2600/3704 eff=78.6925% N=400 Mono-modal Volume: ~exp(-10.50) Expected Volume: exp(-6.53) Quality: ok a: +0.0\| +0.4 ***** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.8(79.14%) \| Like=9.91..10.14 [9.9090..9.9097]\| it/evals=2640/3764 eff=78.4780% N=400 Z=4.8(80.93%) \| Like=9.93..10.14 [9.9294..9.9296]\| it/evals=2680/3826 eff=78.2253% N=400 Mono-modal Volume: ~exp(-10.72) * Expected Volume: exp(-6.75) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.8(81.77%) \| Like=9.94..10.14 [9.9368..9.9370]\| it/evals=2700/3851 eff=78.2382% N=400 Z=4.8(82.59%) \| Like=9.95..10.14 [9.9462..9.9470]\| it/evals=2720/3880 eff=78.1609% N=400 Z=4.8(84.12%) \| Like=9.97..10.14 [9.9666..9.9666]\| it/evals=2760/3940 eff=77.9661% N=400 Mono-modal Volume: ~exp(-11.37) Expected Volume: exp(-6.98) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.8(85.18%) \| Like=9.98..10.14 [9.9766..9.9779]\| it/evals=2790/3985 eff=77.8243% N=400 Z=4.8(85.51%) \| Like=9.98..10.14 [9.9831..9.9836]\| it/evals=2800/3996 eff=77.8643% N=400 Z=4.8(86.79%) \| Like=10.00..10.14 [9.9968..9.9970]\| it/evals=2840/4044 eff=77.9363% N=400 Mono-modal Volume: ~exp(-11.37) Expected Volume: exp(-7.20) Quality: ok a: +0.0\| +0.5 *** +0.6 \| +1.0 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(87.96%) \| Like=10.01..10.14 [10.0111..10.0118]\| it/evals=2880/4100 eff=77.8378% N=400 Z=4.9(89.05%) \| Like=10.02..10.14 [10.0212..10.0214]\| it/evals=2920/4156 eff=77.7423% N=400 Z=4.9(90.04%) \| Like=10.03..10.14 [10.0304..10.0308]\| it/evals=2960/4217 eff=77.5478% N=400 Mono-modal Volume: ~exp(-11.78) Expected Volume: exp(-7.43) Quality: ok a: +0.00\| +0.45 **** +0.55 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(90.27%) \| Like=10.03..10.14 [10.0336..10.0337]\| it/evals=2970/4229 eff=77.5659% N=400 Z=4.9(90.94%) \| Like=10.04..10.14 [10.0398..10.0399]\| it/evals=3000/4270 eff=77.5194% N=400 Z=4.9(91.77%) \| Like=10.05..10.14 [10.0470..10.0470]\| it/evals=3040/4331 eff=77.3340% N=400 Mono-modal Volume: ~exp(-11.83) Expected Volume: exp(-7.65) Quality: ok a: +0.00\| +0.46 **** +0.54 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(92.16%) \| Like=10.05..10.14 [10.0507..10.0509]\| it/evals=3060/4356 eff=77.3509% N=400 Z=4.9(92.52%) \| Like=10.06..10.14 [10.0567..10.0568]\| it/evals=3080/4384 eff=77.3092% N=400 Z=4.9(93.20%) \| Like=10.07..10.14 [10.0659..10.0662]\| it/evals=3120/4437 eff=77.2851% N=400 Mono-modal Volume: ~exp(-11.95) Expected Volume: exp(-7.88) Quality: ok a: +0.00\| +0.46 **** +0.54 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(93.68%) \| Like=10.07..10.14 [10.0704..10.0705]\| it/evals=3150/4482 eff=77.1681% N=400 Z=4.9(93.83%) \| Like=10.07..10.14 [10.0722..10.0723]\| it/evals=3160/4495 eff=77.1673% N=400 Z=4.9(94.40%) \| Like=10.08..10.14 [10.0771..10.0772]\| it/evals=3200/4546 eff=77.1828% N=400 Mono-modal Volume: ~exp(-12.34) Expected Volume: exp(-8.10) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(94.92%) \| Like=10.08..10.14 [10.0812..10.0814]\| it/evals=3240/4608 eff=76.9962% N=400 Z=4.9(95.39%) \| Like=10.09..10.14 [10.0862..10.0864]\| it/evals=3280/4651 eff=77.1583% N=400 Z=4.9(95.74%) \| Like=10.09..10.14 [10.0893..10.0894]\| it/evals=3312/4700 eff=77.0233% N=400 Z=4.9(95.82%) \| Like=10.09..10.14 [10.0898..10.0900]\| it/evals=3320/4710 eff=77.0302% N=400 Mono-modal Volume: ~exp(-12.59) * Expected Volume: exp(-8.33) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=4.9(95.92%) \| Like=10.09..10.14 [10.0912..10.0912]\| it/evals=3330/4722 eff=77.0477% N=400 Z=5.0(96.21%) \| Like=10.10..10.14 [10.0950..10.0953]\| it/evals=3360/4760 eff=77.0642% N=400 Z=5.0(96.56%) \| Like=10.10..10.14 [10.0995..10.0996]\| it/evals=3400/4806 eff=77.1675% N=400 Mono-modal Volume: ~exp(-13.05) Expected Volume: exp(-8.55) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=5.0(96.72%) \| Like=10.10..10.14 [10.1021..10.1023]\| it/evals=3420/4832 eff=77.1661% N=400 Z=5.0(96.88%) \| Like=10.10..10.14 [10.1043..10.1043]\| it/evals=3440/4860 eff=77.1300% N=400 Z=5.0(97.17%) \| Like=10.11..10.14 [10.1077..10.1078]\| it/evals=3480/4909 eff=77.1790% N=400 Mono-modal Volume: ~exp(-13.05) Expected Volume: exp(-8.78) Quality: ok a: +0.00\| +0.48 * +0.52 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=5.0(97.40%) \| Like=10.11..10.14 [10.1110..10.1112]\| it/evals=3514/4957 eff=77.1121% N=400 Z=5.0(97.44%) \| Like=10.11..10.14 [10.1114..10.1116]\| it/evals=3520/4963 eff=77.1422% N=400 Z=5.0(97.68%) \| Like=10.11..10.14 [10.1134..10.1134]\| it/evals=3560/5012 eff=77.1899% N=400 Mono-modal Volume: ~exp(-13.05) Expected Volume: exp(-9.00) Quality: ok a: +0.00\| +0.48 * +0.52 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=5.0(97.90%) \| Like=10.12..10.14 [10.1156..10.1157]\| it/evals=3600/5068 eff=77.1208% N=400 Z=5.0(98.10%) \| Like=10.12..10.14 [10.1172..10.1172]\| it/evals=3640/5119 eff=77.1350% N=400 Z=5.0(98.27%) \| Like=10.12..10.14 [10.1192..10.1193]\| it/evals=3680/5175 eff=77.0681% N=400 Mono-modal Volume: ~exp(-13.65) Expected Volume: exp(-9.23) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=5.0(98.32%) \| Like=10.12..10.14 [10.1200..10.1200]\| it/evals=3690/5187 eff=77.0838% N=400 Z=5.0(98.44%) \| Like=10.12..10.14 [10.1214..10.1214]\| it/evals=3720/5221 eff=77.1624% N=400 Z=5.0(98.58%) \| Like=10.12..10.14 [10.1232..10.1232]\| it/evals=3760/5272 eff=77.1757% N=400 Mono-modal Volume: ~exp(-13.65) Expected Volume: exp(-9.45) Quality: ok a: +0.00\| +0.48 * +0.52 \| +1.00 b: +0.0\| +0.7 ** +0.8 \| +1.0 Z=5.0(98.72%) \| Like=10.12..10.14 [10.1248..10.1249]\| it/evals=3800/5320 eff=77.2358% N=400 Z=5.0(98.84%) \| Like=10.13..10.14 [10.1260..10.1261]\| it/evals=3840/5380 eff=77.1084% N=400 Mono-modal Volume: ~exp(-13.65) Expected Volume: exp(-9.68) Quality: ok a: +0.00\| +0.48 +0.52 \| +1.00 b: +0.0\| +0.7 +0.8 \| +1.0 Z=5.0(98.95%) \| Like=10.13..10.14 [10.1272..10.1272]*\| it/evals=3880/5434 eff=77.0759% N=400 [ultranest] Explored until L=1e+01 [ultranest] Likelihood function evaluations: 5460 [ultranest] logZ = 4.99 +- 0.08857 [ultranest] Effective samples strategy satisfied (ESS = 1645.1, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.09, need <0.5) [ultranest] logZ error budget: single: 0.10 bs:0.09 tail:0.01 total:0.09 required:<0.50 [ultranest] done iterating. {'niter': 4301, 'logz': 4.988996819002486, 'logzerr': 0.2588578243783826, 'logz_bs': 4.990187359952544, 'logz_single': 4.988996819002486, 'logzerr_tail': 0.009926293531777652, 'logzerr_bs': 0.2586674350176894, 'ess': 1645.1294279072051, 'H': 4.106903232188296, 'Herr': 0.08138599062924921, 'posterior': {'mean': [0.49857198515338147, 0.7496562404737387], 'stdev': [0.1025818314779487, 0.010163170120468015], 'median': [0.500033611905603, 0.7495818409993013], 'errlo': [0.39681030547126056, 0.7393116656531434], 'errup': [0.5970402949754734, 0.7600851497438345], 'information_gain_bits': [-1.966137296701205, 3.437518878309193]}, 'weighted_samples': {'upoints': array([[0.94101327, 0.00103293], [0.90764465, 0.00250756], [0.05758351, 0.00579739], ..., [0.49839061, 0.74995877], [0.499224 , 0.75013135], [0.50050472, 0.74997285]]), 'points': array([[0.94101327, 0.00103293], [0.90764465, 0.00250756], [0.05758351, 0.00579739], ..., [0.49839061, 0.74995877], [0.499224 , 0.75013135], [0.50050472, 0.74997285]]), 'weights': array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 2.50824302e-05, 2.50829730e-05, 2.50854800e-05]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -15.74396455, -15.74396455, -15.74396455]), 'bootstrapped_weights': array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], ..., [4.08761426e-05, 0.00000000e+00, 3.82501067e-05, ..., 4.34525460e-05, 0.00000000e+00, 4.10582906e-05], [4.08770271e-05, 3.79686775e-05, 0.00000000e+00, ..., 4.34534862e-05, 3.88654131e-05, 4.10591791e-05], [0.00000000e+00, 3.79724724e-05, 3.82547576e-05, ..., 4.34578293e-05, 0.00000000e+00, 4.10632829e-05]]), 'logl': array([-2804.34321847, -2791.89369322, -2768.83446324, ..., 10.13961842, 10.13964006, 10.13974 ])}, 'samples': array([[0.62944772, 0.74253371], [0.61086075, 0.74058649], [0.50898718, 0.75416447], ..., [0.73801608, 0.75270934], [0.52601986, 0.75271483], [0.55160119, 0.74377788]]), 'maximum_likelihood': {'logl': 10.139740001056168, 'point': [0.5005047223216983, 0.7499728454117514], 'point_untransformed': [0.5005047223216983, 0.7499728454117514]}, 'ncall': 5460, 'paramnames': ['a', 'b'], 'logzerr_single': 0.10132747939463776, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-2804.34, Lmax=9.48 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=443, regioncalls=1720, ndraw=40, logz=-2192.34, remainder_fraction=100.0000%, Lmin=-2186.44, Lmax=9.48 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=487, regioncalls=3480, ndraw=40, logz=-1580.24, remainder_fraction=100.0000%, Lmin=-1557.39, Lmax=9.48 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=497, regioncalls=3880, ndraw=40, logz=-1407.73, remainder_fraction=100.0000%, Lmin=-1382.92, Lmax=9.48 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=529, regioncalls=5160, ndraw=40, logz=-1154.34, remainder_fraction=100.0000%, Lmin=-1134.91, Lmax=9.48 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=572, regioncalls=6880, ndraw=40, logz=-889.64, remainder_fraction=100.0000%, Lmin=-872.40, Lmax=9.51 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=594, regioncalls=7760, ndraw=40, logz=-667.92, remainder_fraction=100.0000%, Lmin=-658.26, Lmax=9.51 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=614, regioncalls=8560, ndraw=40, logz=-565.80, remainder_fraction=100.0000%, Lmin=-558.96, Lmax=10.07 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=660, regioncalls=10400, ndraw=40, logz=-377.35, remainder_fraction=100.0000%, Lmin=-370.39, Lmax=10.07 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=692, regioncalls=11680, ndraw=40, logz=-287.53, remainder_fraction=100.0000%, Lmin=-281.30, Lmax=10.07 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=703, regioncalls=12120, ndraw=40, logz=-277.25, remainder_fraction=100.0000%, Lmin=-270.53, Lmax=10.07 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=748, regioncalls=13920, ndraw=40, logz=-230.16, remainder_fraction=100.0000%, Lmin=-222.87, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=796, regioncalls=15840, ndraw=40, logz=-193.81, remainder_fraction=100.0000%, Lmin=-187.56, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=804, regioncalls=16160, ndraw=40, logz=-187.97, remainder_fraction=100.0000%, Lmin=-181.22, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=849, regioncalls=17960, ndraw=40, logz=-158.32, remainder_fraction=100.0000%, Lmin=-150.51, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=897, regioncalls=19880, ndraw=40, logz=-126.53, remainder_fraction=100.0000%, Lmin=-120.40, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=467, ncalls=929, regioncalls=21160, ndraw=40, logz=-110.13, remainder_fraction=100.0000%, Lmin=-103.38, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=944, regioncalls=21760, ndraw=40, logz=-102.13, remainder_fraction=100.0000%, Lmin=-95.41, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=512, ncalls=990, regioncalls=23600, ndraw=40, logz=-85.06, remainder_fraction=100.0000%, Lmin=-79.33, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=998, regioncalls=23920, ndraw=40, logz=-82.92, remainder_fraction=100.0000%, Lmin=-76.70, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1022, regioncalls=24880, ndraw=40, logz=-76.30, remainder_fraction=100.0000%, Lmin=-68.89, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1047, regioncalls=25880, ndraw=40, logz=-69.66, remainder_fraction=100.0000%, Lmin=-63.65, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1095, regioncalls=27800, ndraw=40, logz=-57.18, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1128, regioncalls=29120, ndraw=40, logz=-49.57, remainder_fraction=100.0000%, Lmin=-43.45, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1142, regioncalls=29680, ndraw=40, logz=-47.54, remainder_fraction=100.0000%, Lmin=-41.70, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1185, regioncalls=31400, ndraw=40, logz=-40.60, remainder_fraction=100.0000%, Lmin=-34.43, Lmax=10.10 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1230, regioncalls=33200, ndraw=40, logz=-33.70, remainder_fraction=100.0000%, Lmin=-27.45, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1274, regioncalls=34960, ndraw=40, logz=-25.77, remainder_fraction=100.0000%, Lmin=-19.82, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1323, regioncalls=36920, ndraw=40, logz=-21.28, remainder_fraction=100.0000%, Lmin=-15.22, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1373, regioncalls=38920, ndraw=40, logz=-17.26, remainder_fraction=100.0000%, Lmin=-11.83, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1421, regioncalls=40880, ndraw=40, logz=-14.03, remainder_fraction=100.0000%, Lmin=-8.57, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1451, regioncalls=42080, ndraw=40, logz=-12.78, remainder_fraction=100.0000%, Lmin=-7.08, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1474, regioncalls=43040, ndraw=40, logz=-11.38, remainder_fraction=100.0000%, Lmin=-5.91, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1521, regioncalls=44920, ndraw=40, logz=-9.19, remainder_fraction=99.9999%, Lmin=-3.59, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1560, regioncalls=46480, ndraw=40, logz=-7.85, remainder_fraction=99.9998%, Lmin=-2.76, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1571, regioncalls=46920, ndraw=40, logz=-7.53, remainder_fraction=99.9997%, Lmin=-2.52, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1618, regioncalls=48880, ndraw=40, logz=-6.33, remainder_fraction=99.9988%, Lmin=-1.31, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1678, regioncalls=51280, ndraw=40, logz=-5.35, remainder_fraction=99.9969%, Lmin=-0.31, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1726, regioncalls=53240, ndraw=40, logz=-4.41, remainder_fraction=99.9917%, Lmin=0.61, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1779, regioncalls=55360, ndraw=40, logz=-3.48, remainder_fraction=99.9790%, Lmin=1.56, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1790, regioncalls=55800, ndraw=40, logz=-3.27, remainder_fraction=99.9745%, Lmin=1.75, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1832, regioncalls=57560, ndraw=40, logz=-2.72, remainder_fraction=99.9553%, Lmin=2.24, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1889, regioncalls=59840, ndraw=40, logz=-1.99, remainder_fraction=99.9059%, Lmin=2.97, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1922, regioncalls=61160, ndraw=40, logz=-1.69, remainder_fraction=99.8716%, Lmin=3.25, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1950, regioncalls=62360, ndraw=40, logz=-1.40, remainder_fraction=99.8332%, Lmin=3.53, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1314, ncalls=1987, regioncalls=63920, ndraw=40, logz=-0.93, remainder_fraction=99.7339%, Lmin=4.08, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1996, regioncalls=64280, ndraw=40, logz=-0.85, remainder_fraction=99.7158%, Lmin=4.19, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2038, regioncalls=65960, ndraw=40, logz=-0.45, remainder_fraction=99.5788%, Lmin=4.57, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2049, regioncalls=66400, ndraw=40, logz=-0.32, remainder_fraction=99.5177%, Lmin=4.72, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1398, ncalls=2102, regioncalls=68520, ndraw=40, logz=0.16, remainder_fraction=99.2065%, Lmin=5.21, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2104, regioncalls=68600, ndraw=40, logz=0.18, remainder_fraction=99.1844%, Lmin=5.25, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2166, regioncalls=71080, ndraw=40, logz=0.62, remainder_fraction=98.7733%, Lmin=5.66, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1477, ncalls=2208, regioncalls=72800, ndraw=40, logz=1.01, remainder_fraction=98.1986%, Lmin=6.08, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2214, regioncalls=73040, ndraw=40, logz=1.04, remainder_fraction=98.1370%, Lmin=6.17, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1515, ncalls=2255, regioncalls=74680, ndraw=40, logz=1.38, remainder_fraction=97.3529%, Lmin=6.49, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2264, regioncalls=75040, ndraw=40, logz=1.43, remainder_fraction=97.2123%, Lmin=6.53, Lmax=10.12 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2277, regioncalls=75560, ndraw=40, logz=1.52, remainder_fraction=96.9441%, Lmin=6.62, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2318, regioncalls=77240, ndraw=40, logz=1.77, remainder_fraction=96.0185%, Lmin=6.82, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2373, regioncalls=79440, ndraw=40, logz=2.08, remainder_fraction=94.6926%, Lmin=7.12, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2398, regioncalls=80440, ndraw=40, logz=2.22, remainder_fraction=93.9142%, Lmin=7.27, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2427, regioncalls=81600, ndraw=40, logz=2.35, remainder_fraction=92.9310%, Lmin=7.38, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2484, regioncalls=83880, ndraw=40, logz=2.58, remainder_fraction=90.9365%, Lmin=7.58, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2528, regioncalls=85640, ndraw=40, logz=2.74, remainder_fraction=89.2588%, Lmin=7.72, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2543, regioncalls=86280, ndraw=40, logz=2.79, remainder_fraction=88.7850%, Lmin=7.78, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2598, regioncalls=88480, ndraw=40, logz=2.98, remainder_fraction=86.5273%, Lmin=8.01, Lmax=10.13 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2648, regioncalls=90480, ndraw=40, logz=3.16, remainder_fraction=84.0017%, Lmin=8.20, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2700, regioncalls=92560, ndraw=40, logz=3.33, remainder_fraction=81.0730%, Lmin=8.38, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2762, regioncalls=95040, ndraw=40, logz=3.47, remainder_fraction=77.9929%, Lmin=8.55, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1918, ncalls=2822, regioncalls=97440, ndraw=40, logz=3.61, remainder_fraction=74.9989%, Lmin=8.68, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=2825, regioncalls=97560, ndraw=40, logz=3.61, remainder_fraction=74.8183%, Lmin=8.68, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=2886, regioncalls=100000, ndraw=40, logz=3.74, remainder_fraction=71.4683%, Lmin=8.80, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2918, regioncalls=101360, ndraw=40, logz=3.79, remainder_fraction=69.7848%, Lmin=8.87, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2941, regioncalls=102280, ndraw=40, logz=3.85, remainder_fraction=67.9761%, Lmin=8.93, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=2994, regioncalls=104400, ndraw=40, logz=3.95, remainder_fraction=64.5783%, Lmin=9.05, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3038, regioncalls=106200, ndraw=40, logz=4.03, remainder_fraction=61.7749%, Lmin=9.13, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3051, regioncalls=106720, ndraw=40, logz=4.05, remainder_fraction=60.8992%, Lmin=9.16, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3101, regioncalls=108720, ndraw=40, logz=4.14, remainder_fraction=57.2904%, Lmin=9.27, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3151, regioncalls=110760, ndraw=40, logz=4.22, remainder_fraction=53.7139%, Lmin=9.34, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3201, regioncalls=112760, ndraw=40, logz=4.29, remainder_fraction=50.4378%, Lmin=9.42, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3249, regioncalls=114680, ndraw=40, logz=4.35, remainder_fraction=46.9606%, Lmin=9.50, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3262, regioncalls=115240, ndraw=40, logz=4.37, remainder_fraction=46.1285%, Lmin=9.51, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3298, regioncalls=116680, ndraw=40, logz=4.41, remainder_fraction=43.5700%, Lmin=9.56, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3356, regioncalls=119000, ndraw=40, logz=4.47, remainder_fraction=40.5808%, Lmin=9.60, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3383, regioncalls=120160, ndraw=40, logz=4.49, remainder_fraction=39.1170%, Lmin=9.64, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3408, regioncalls=121360, ndraw=40, logz=4.52, remainder_fraction=37.6185%, Lmin=9.66, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3455, regioncalls=123240, ndraw=40, logz=4.56, remainder_fraction=34.7493%, Lmin=9.71, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3495, regioncalls=124840, ndraw=40, logz=4.59, remainder_fraction=32.6979%, Lmin=9.75, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3508, regioncalls=125440, ndraw=40, logz=4.60, remainder_fraction=32.0500%, Lmin=9.75, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3553, regioncalls=127240, ndraw=40, logz=4.64, remainder_fraction=29.4942%, Lmin=9.79, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3603, regioncalls=129280, ndraw=40, logz=4.67, remainder_fraction=27.1177%, Lmin=9.82, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3651, regioncalls=131200, ndraw=40, logz=4.70, remainder_fraction=24.8808%, Lmin=9.85, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3704, regioncalls=133320, ndraw=40, logz=4.73, remainder_fraction=22.8052%, Lmin=9.88, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=3764, regioncalls=135720, ndraw=40, logz=4.75, remainder_fraction=20.8557%, Lmin=9.91, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=3826, regioncalls=138200, ndraw=40, logz=4.78, remainder_fraction=19.0714%, Lmin=9.93, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3851, regioncalls=139240, ndraw=40, logz=4.79, remainder_fraction=18.2290%, Lmin=9.94, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=3880, regioncalls=140400, ndraw=40, logz=4.80, remainder_fraction=17.4106%, Lmin=9.95, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=3940, regioncalls=142800, ndraw=40, logz=4.82, remainder_fraction=15.8839%, Lmin=9.97, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3985, regioncalls=144640, ndraw=40, logz=4.83, remainder_fraction=14.8243%, Lmin=9.98, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3996, regioncalls=145080, ndraw=40, logz=4.83, remainder_fraction=14.4887%, Lmin=9.98, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4044, regioncalls=147000, ndraw=40, logz=4.85, remainder_fraction=13.2142%, Lmin=10.00, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4100, regioncalls=149240, ndraw=40, logz=4.86, remainder_fraction=12.0374%, Lmin=10.01, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4156, regioncalls=151480, ndraw=40, logz=4.87, remainder_fraction=10.9545%, Lmin=10.02, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4217, regioncalls=153920, ndraw=40, logz=4.88, remainder_fraction=9.9620%, Lmin=10.03, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4229, regioncalls=154480, ndraw=40, logz=4.89, remainder_fraction=9.7257%, Lmin=10.03, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4270, regioncalls=156120, ndraw=40, logz=4.89, remainder_fraction=9.0566%, Lmin=10.04, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4331, regioncalls=158560, ndraw=40, logz=4.90, remainder_fraction=8.2321%, Lmin=10.05, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=4356, regioncalls=159600, ndraw=40, logz=4.91, remainder_fraction=7.8447%, Lmin=10.05, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4384, regioncalls=160800, ndraw=40, logz=4.91, remainder_fraction=7.4767%, Lmin=10.06, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4437, regioncalls=162920, ndraw=40, logz=4.92, remainder_fraction=6.7951%, Lmin=10.07, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4482, regioncalls=164760, ndraw=40, logz=4.92, remainder_fraction=6.3171%, Lmin=10.07, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4495, regioncalls=165280, ndraw=40, logz=4.93, remainder_fraction=6.1654%, Lmin=10.07, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4546, regioncalls=167320, ndraw=40, logz=4.93, remainder_fraction=5.5974%, Lmin=10.08, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4608, regioncalls=169840, ndraw=40, logz=4.94, remainder_fraction=5.0803%, Lmin=10.08, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4651, regioncalls=171560, ndraw=40, logz=4.94, remainder_fraction=4.6102%, Lmin=10.09, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3312, ncalls=4700, regioncalls=173520, ndraw=40, logz=4.95, remainder_fraction=4.2640%, Lmin=10.09, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4710, regioncalls=173920, ndraw=40, logz=4.95, remainder_fraction=4.1814%, Lmin=10.09, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=4722, regioncalls=174520, ndraw=40, logz=4.95, remainder_fraction=4.0809%, Lmin=10.09, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=4760, regioncalls=176040, ndraw=40, logz=4.95, remainder_fraction=3.7933%, Lmin=10.10, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4806, regioncalls=177880, ndraw=40, logz=4.95, remainder_fraction=3.4392%, Lmin=10.10, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4832, regioncalls=178960, ndraw=40, logz=4.96, remainder_fraction=3.2755%, Lmin=10.10, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=4860, regioncalls=180080, ndraw=40, logz=4.96, remainder_fraction=3.1183%, Lmin=10.10, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=4909, regioncalls=182040, ndraw=40, logz=4.96, remainder_fraction=2.8262%, Lmin=10.11, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3514, ncalls=4957, regioncalls=183960, ndraw=40, logz=4.96, remainder_fraction=2.6003%, Lmin=10.11, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=4963, regioncalls=184200, ndraw=40, logz=4.96, remainder_fraction=2.5618%, Lmin=10.11, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=5012, regioncalls=186160, ndraw=40, logz=4.97, remainder_fraction=2.3208%, Lmin=10.11, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5068, regioncalls=188400, ndraw=40, logz=4.97, remainder_fraction=2.1022%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=5119, regioncalls=190440, ndraw=40, logz=4.97, remainder_fraction=1.9042%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=5175, regioncalls=192680, ndraw=40, logz=4.97, remainder_fraction=1.7250%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=5187, regioncalls=193200, ndraw=40, logz=4.97, remainder_fraction=1.6829%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=5221, regioncalls=194560, ndraw=40, logz=4.97, remainder_fraction=1.5627%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=5272, regioncalls=196600, ndraw=40, logz=4.97, remainder_fraction=1.4155%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5320, regioncalls=198520, ndraw=40, logz=4.98, remainder_fraction=1.2818%, Lmin=10.12, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=5380, regioncalls=200920, ndraw=40, logz=4.98, remainder_fraction=1.1607%, Lmin=10.13, Lmax=10.14 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=5434, regioncalls=203080, ndraw=40, logz=4.98, remainder_fraction=1.0510%, Lmin=10.13, Lmax=10.14 INFO ultranest:integrator.py:2654 Explored until L=1e+01 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5460 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 4.99 +- 0.08857 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1645.1, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.09, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.10 bs:0.09 tail:0.01 total:0.09 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_run.py::test_reactive_run_resume_eggbox[tsv]	5.70
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|***************** * * ***** * ******\| +3.1e+01 b: +0.0\| *** * *** * * * **** ********* ***\| +31.4 Z=-inf(0.00%) \| Like=1.20..233.34 [1.1994..29.4283] \| it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) \| Like=2.82..233.34 [1.1994..29.4283] \| it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) \| Like=5.72..241.87 [1.1994..29.4283] \| it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0\|***************** ******* * ****** \| +31.4 b: +0.0\| ** * * * **** ********* ***\| +31.4 Z=5.8(0.00%) \| Like=9.88..241.87 [1.1994..29.4283] \| it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) \| Like=15.15..241.87 [1.1994..29.4283] \| it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0\|********** ** ** * * * ****** \| +31.4 b: +0.0\|* * ** * * * * ******** ******\| +31.4 Z=14.8(0.00%) \| Like=19.62..241.87 [1.1994..29.4283] \| it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) \| Like=25.71..241.87 [1.1994..29.4283] \| it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0\|**** * **** ****** **** * ******\| +31.4 b: +0.0\|****** ** * * ****** ******\| +31.4 Z=25.5(0.00%) \| Like=29.64..241.87 [29.6178..62.1019] \| it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) \| Like=32.87..241.87 [29.6178..62.1019] \| it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) \| Like=35.17..241.87 [29.6178..62.1019] \| it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0\|**** * *** *** **** ****\| +31.4 b: +0.0\|****** *** * ******** * *\| +31.4 Z=34.9(0.00%) \| Like=39.71..241.87 [29.6178..62.1019] \| it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) \| Like=45.13..241.87 [29.6178..62.1019] \| it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0\| ***** * **** * * *** ******** *\| +31.4 b: +0.0\|* ** * ** ***** * *\| +31.4 Z=43.4(0.00%) \| Like=49.11..241.87 [29.6178..62.1019] \| it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) \| Like=54.54..241.87 [29.6178..62.1019] \| it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0\| * * ***** ** ******* * ******* \| +31.4 b: +0.0\|* * ** **** ***** ****** \| +31.4 Z=54.8(0.00%) \| Like=60.32..241.87 [29.6178..62.1019] \| it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) \| Like=69.11..241.87 [62.2053..112.3934] \| it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) \| Like=77.89..241.87 [62.2053..112.3934] \| it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0\| ** * **** *** ***** ***** \| +31.4 b: +0.0\| **** **** ***** * ***** \| +31.4 Z=77.8(0.00%) \| Like=87.30..241.87 [62.2053..112.3934] \| it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) \| Like=94.79..241.87 [62.2053..112.3934] \| it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0\| * * **** * **** **** \| +31.4 b: +0.0\|* ****** *** *** ** \| +31.4 Z=94.6(0.00%) \| Like=100.05..241.87 [62.2053..112.3934] \| it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 12.65 │ ▁ ▇ │19.30 18.98 +- 0.35 b : 5.3 │ ▇ ▁ │26.2 6.3 +- 1.1 626 626 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.897580582291928408e+01,3.482687211659772908e-01,1.899594672309787668e+01,1.899594672309787668e+01,1.899594672309787668e+01,6.316415107809904228e+00,1.095459745550366071e+00,6.253063034987970781e+00,6.253063034987970781e+00,6.253063034987970781e+00 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.975806 0.348269 18.995947 ... 6.253063 6.253063 6.253063 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.975805822919284 checking mean of parameter 'b': 6.316415107809904 checking stdev of parameter 'a': 0.3482687211659773 checking stdev of parameter 'b': 1.095459745550366 checking median of parameter 'a': 18.995946723097877 checking median of parameter 'b': 6.253063034987971 checking errlo of parameter 'a': 18.995946723097877 checking errlo of parameter 'b': 6.253063034987971 checking errup of parameter 'a': 18.995946723097877 checking errup of parameter 'b': 6.253063034987971 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} ====== Running Eggbox problem [2] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|* ** ********** ******** ** * ********\| +3.1e+01 b: +3.1e-05\| ** *** ****** * ** *******\| +3.1e+01 Z=-inf(0.00%) \| Like=1.05..221.09 [1.0467..28.5121] \| it/evals=0/101 eff=0.0000% N=100 Z=0.1(0.00%) \| Like=3.95..221.09 [1.0467..28.5121] \| it/evals=10/111 eff=90.9091% N=100 Z=3.5(0.00%) \| Like=6.71..221.09 [1.0467..28.5121] \| it/evals=20/122 eff=90.9091% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.23) Quality: ok a: +3.1e-05\| **************** ******* *** * ******* \| +3.1e+01 b: +3.1e-05\|** ***** ** *** * * ** * *******\| +3.1e+01 Z=6.4(0.00%) \| Like=10.30..228.18 [1.0467..28.5121] \| it/evals=30/133 eff=90.9091% N=100 Z=10.4(0.00%) \| Like=14.59..228.18 [1.0467..28.5121] \| it/evals=40/145 eff=88.8889% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.46) Quality: ok a: +3.1e-05\| ********* ************** * ** ***\| +3.1e+01 b: +3.1e-05\| *** * ******* * * ** * *****\| +3.1e+01 Z=14.8(0.00%) \| Like=19.71..228.18 [1.0467..28.5121] \| it/evals=50/156 eff=89.2857% N=100 Z=22.2(0.00%) \| Like=26.91..228.18 [1.0467..28.5121] \| it/evals=60/174 eff=81.0811% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.69) Quality: ok a: +3.1e-05\| *** ************** ********* *\| +3.1e+01 b: +3.1e-05\| * ******* * ********* * *****\| +3.1e+01 Z=26.6(0.00%) \| Like=31.35..228.18 [29.1828..62.4284] \| it/evals=70/189 eff=78.6517% N=100 Z=29.7(0.00%) \| Like=34.32..228.18 [29.1828..62.4284] \| it/evals=80/213 eff=70.7965% N=100 Z=33.3(0.00%) \| Like=38.77..228.18 [29.1828..62.4284] \| it/evals=90/240 eff=64.2857% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-0.92) Quality: ok a: +3.1e-05\|* * ******* * ************** *********** * * *\| +3.1e+01 b: +3.1e-05\| **** *** * ******* * ********* * ***\| +3.1e+01 Z=34.5(0.00%) \| Like=39.28..228.18 [29.1828..62.4284] \| it/evals=92/246 eff=63.0137% N=100 Z=37.8(0.00%) \| Like=42.61..228.18 [29.1828..62.4284] \| it/evals=100/273 eff=57.8035% N=100 Z=42.8(0.00%) \| Like=47.95..228.18 [29.1828..62.4284] \| it/evals=110/297 eff=55.8376% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.15) Quality: ok a: +3.1e-05\| * ******* ****** * ********** * *\| +3.1e+01 b: +3.1e-05\| ****** * ********* * *** * * * *\| +3.1e+01 Z=48.9(0.00%) \| Like=54.86..228.18 [29.1828..62.4284] \| it/evals=120/326 eff=53.0973% N=100 Z=55.4(0.00%) \| Like=61.66..228.18 [29.1828..62.4284] \| it/evals=130/368 eff=48.5075% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.38) Quality: ok a: +3.1e-05\| * ******* **** * * ********* * *\| +3.1e+01 b: +3.1e-05\| ***** * ******* * * * * ***\| +3.1e+01 Z=60.1(0.00%) \| Like=68.52..228.18 [62.6017..102.3957] \| it/evals=140/402 eff=46.3576% N=100 Z=67.2(0.00%) \| Like=72.18..228.18 [62.6017..102.3957] \| it/evals=150/452 eff=42.6136% N=100 Z=71.3(0.00%) \| Like=76.78..238.35 [62.6017..102.3957] \| it/evals=160/496 eff=40.4040% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.61) Quality: ok a: +3.1e-05\| ***** *** * ******* \| +3.1e+01 b: +3.1e-05\|* ***** * * **** ***** \| +3.1e+01 Z=71.7(0.00%) \| Like=76.83..238.35 [62.6017..102.3957] \| it/evals=161/501 eff=40.1496% N=100 Z=77.7(0.00%) \| Like=85.32..238.35 [62.6017..102.3957] \| it/evals=170/544 eff=38.2883% N=100 Z=83.6(0.00%) \| Like=91.87..238.35 [62.6017..102.3957] \| it/evals=180/573 eff=38.0550% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.84) Quality: ok a: +3.1e-05\| ** *** **** **** \| +3.1e+01 b: +3.1e-05\| *** *** ***** **** \| +3.1e+01 Z=92.1(0.00%) \| Like=98.48..238.35 [62.6017..102.3957] \| it/evals=190/595 eff=38.3838% N=100 Z=101.4(0.00%) \| Like=108.11..240.89 [102.9564..147.0741] \| it/evals=200/674 eff=34.8432% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.07) Quality: ok a: +0.0\| ** *** ***** \| +31.4 b: +3.1e-05\|* **** *** *** **** \| +3.1e+01 Z=108.2(0.00%) \| Like=114.20..240.89 [102.9564..147.0741] \| it/evals=210/722 eff=33.7621% N=100 Z=114.0(0.00%) \| Like=121.27..240.89 [102.9564..147.0741] \| it/evals=220/778 eff=32.4484% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.30) Quality: ok a: +0.0\| ** ** * *** \| +31.4 b: +3.1e-05\| * * *** ** \| +3.1e+01 Z=122.3(0.00%) \| Like=128.65..240.89 [102.9564..147.0741] \| it/evals=230/849 eff=30.7076% N=100 Z=128.0(0.00%) \| Like=134.37..240.89 [102.9564..147.0741] \| it/evals=240/950 eff=28.2353% N=100 Z=132.5(0.00%) \| Like=139.29..242.00 [102.9564..147.0741] \| it/evals=250/1034 eff=26.7666% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.53) Quality: ok a: +0.0\|* * ** * ** \| +31.4 b: +3.1e-05\| * ** *** ** \| +3.1e+01 Z=140.8(0.00%) \| Like=147.11..242.37 [147.1142..186.4200] \| it/evals=260/1135 eff=25.1208% N=100 Z=148.1(0.00%) \| Like=155.97..242.37 [147.1142..186.4200] \| it/evals=270/1279 eff=22.9008% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.76) Quality: ok a: +0.0\|* ** * * *** \| +31.4 b: +3.1e-05\|* * * * **** * \| +3.1e+01 Z=153.6(0.00%) \| Like=160.75..242.37 [147.1142..186.4200] \| it/evals=277/1369 eff=21.8282% N=100 Z=155.6(0.00%) \| Like=163.08..242.37 [147.1142..186.4200] \| it/evals=280/1411 eff=21.3577% N=100 Z=161.0(0.00%) \| Like=168.19..242.37 [147.1142..186.4200] \| it/evals=290/1566 eff=19.7817% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05\|* ** * * * \| +3.1e+01 b: +3.1e-05\| * * * *** \| +3.1e+01 Z=166.0(0.00%) \| Like=173.84..242.37 [147.1142..186.4200] \| it/evals=300/1700 eff=18.7500% N=100 Z=171.7(0.00%) \| Like=179.38..242.37 [147.1142..186.4200] \| it/evals=310/1793 eff=18.3107% N=100 Z=177.1(0.00%) \| Like=184.35..242.37 [147.1142..186.4200] \| it/evals=320/1938 eff=17.4102% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05\|* ** * \| +3.1e+01 b: +3.1e-05\| * * ** \| +3.1e+01 Z=181.8(0.00%) \| Like=189.01..242.37 [186.7319..216.1536] \| it/evals=328/2114 eff=16.2860% N=100 Z=182.5(0.00%) \| Like=189.50..242.37 [186.7319..216.1536] \| it/evals=330/2226 eff=15.5221% N=100 Z=183.6(0.00%) \| Like=190.73..242.37 [186.7319..216.1536] \| it/evals=334/2506 eff=13.8820% N=100 Z=186.2(0.00%) \| Like=193.29..242.37 [186.7319..216.1536] \| it/evals=340/2654 eff=13.3125% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05\|* ** \| +3.1e+01 b: +3.1e-05\| * \| +3.1e+01 Z=190.9(0.00%) \| Like=197.89..242.37 [186.7319..216.1536] \| it/evals=349/2998 eff=12.0428% N=100 Z=191.2(0.00%) \| Like=198.42..242.37 [186.7319..216.1536] \| it/evals=350/3009 eff=12.0316% N=100 Z=194.7(0.00%) \| Like=201.90..242.37 [186.7319..216.1536] \| it/evals=357/3238 eff=11.3767% N=100 Z=197.3(0.00%) \| Like=205.11..242.37 [186.7319..216.1536] \| it/evals=360/3318 eff=11.1871% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05\|* ** * ** \| +3.1e+01 b: +3.1e-05\| * * * \| +3.1e+01 Z=199.7(0.00%) \| Like=206.32..242.37 [186.7319..216.1536] \| it/evals=368/3563 eff=10.6266% N=100 Z=200.0(0.00%) \| Like=206.86..242.37 [186.7319..216.1536] \| it/evals=370/3667 eff=10.3729% N=100 Z=202.9(0.00%) \| Like=210.14..242.51 [186.7319..216.1536] \| it/evals=379/4169 eff=9.3143% N=100 Z=203.2(0.00%) \| Like=210.98..242.51 [186.7319..216.1536] \| it/evals=380/4187 eff=9.2978% N=100 Z=204.0(0.00%) \| Like=211.48..242.51 [186.7319..216.1536] \| it/evals=382/4358 eff=8.9713% N=100 Z=206.3(0.00%) \| Like=213.44..242.60 [186.7319..216.1536] \| it/evals=390/4799 eff=8.2996% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05\|* ** * * * \| +3.1e+01 b: +3.1e-05\|* ** * * * *\| +3.1e+01 Z=206.5(0.00%) \| Like=213.58..242.60 [186.7319..216.1536] \| it/evals=391/4909 eff=8.1306% N=100 Z=207.4(0.00%) \| Like=214.42..242.60 [186.7319..216.1536] \| it/evals=396/5127 eff=7.8775% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 5287 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 236.030 +- 0.815 single instance: logZ = 236.030 +- 0.247 bootstrapped : logZ = 236.020 +- 0.429 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 0.0 │▁ ▃▁ ▇ ▂ ▁▇ ▁│31.4 16.9 +- 7.9 b : 0 │▆ ▃▁ ▄▁ ▁ ▁▇ ▃│31 14 +- 11 5287 5287 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.692122856244112938e+01,7.903712302185231131e+00,1.276958378640852310e+01,6.412527886198907900e+00,2.524009418967003171e+01,1.427582766036078255e+01,1.146926462371362021e+01,1.263626942277114829e+01,6.172183764370788722e-02,2.514548034712652225e+01 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 16.921229 7.903712 12.769584 ... 12.636269 0.061722 25.14548 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 16.92122856244113 checking mean of parameter 'b': 14.275827660360783 checking stdev of parameter 'a': 7.903712302185231 checking stdev of parameter 'b': 11.46926462371362 checking median of parameter 'a': 12.769583786408523 checking median of parameter 'b': 12.636269422771148 checking errlo of parameter 'a': 6.412527886198908 checking errlo of parameter 'b': 0.06172183764370789 checking errup of parameter 'a': 25.24009418967003 checking errup of parameter 'b': 25.145480347126522 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpmkz0zrf5, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=123, regioncalls=920, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=137, regioncalls=1480, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=149, regioncalls=1960, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=162, regioncalls=2480, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=175, regioncalls=3000, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=188, regioncalls=3520, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=206, regioncalls=4240, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=223, regioncalls=4920, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=244, regioncalls=5760, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=284, regioncalls=7360, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=309, regioncalls=8360, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=341, regioncalls=9640, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=377, regioncalls=11080, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=396, regioncalls=11840, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=441, regioncalls=13640, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=502, regioncalls=16080, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=553, regioncalls=18120, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=584, regioncalls=19360, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 626 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpmkz0zrf5, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.05, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=0.06, remainder_fraction=100.0000%, Lmin=3.95, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=122, regioncalls=880, ndraw=40, logz=3.55, remainder_fraction=100.0000%, Lmin=6.71, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=133, regioncalls=1320, ndraw=40, logz=6.36, remainder_fraction=100.0000%, Lmin=10.30, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=145, regioncalls=1800, ndraw=40, logz=10.43, remainder_fraction=100.0000%, Lmin=14.59, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=156, regioncalls=2240, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.71, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=174, regioncalls=2960, ndraw=40, logz=22.21, remainder_fraction=100.0000%, Lmin=26.91, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=189, regioncalls=3560, ndraw=40, logz=26.59, remainder_fraction=100.0000%, Lmin=31.35, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=213, regioncalls=4520, ndraw=40, logz=29.74, remainder_fraction=100.0000%, Lmin=34.32, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=240, regioncalls=5600, ndraw=40, logz=33.34, remainder_fraction=100.0000%, Lmin=38.77, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=92, ncalls=246, regioncalls=5840, ndraw=40, logz=34.49, remainder_fraction=100.0000%, Lmin=39.28, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=273, regioncalls=6920, ndraw=40, logz=37.85, remainder_fraction=100.0000%, Lmin=42.61, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=297, regioncalls=7880, ndraw=40, logz=42.78, remainder_fraction=100.0000%, Lmin=47.95, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=326, regioncalls=9040, ndraw=40, logz=48.91, remainder_fraction=100.0000%, Lmin=54.86, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=368, regioncalls=10720, ndraw=40, logz=55.41, remainder_fraction=100.0000%, Lmin=61.66, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=402, regioncalls=12080, ndraw=40, logz=60.12, remainder_fraction=100.0000%, Lmin=68.52, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=452, regioncalls=14080, ndraw=40, logz=67.24, remainder_fraction=100.0000%, Lmin=72.18, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=496, regioncalls=15840, ndraw=40, logz=71.34, remainder_fraction=100.0000%, Lmin=76.78, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=501, regioncalls=16040, ndraw=40, logz=71.72, remainder_fraction=100.0000%, Lmin=76.83, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=544, regioncalls=17760, ndraw=40, logz=77.69, remainder_fraction=100.0000%, Lmin=85.32, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=573, regioncalls=18920, ndraw=40, logz=83.64, remainder_fraction=100.0000%, Lmin=91.87, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=595, regioncalls=19800, ndraw=40, logz=92.13, remainder_fraction=100.0000%, Lmin=98.48, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=674, regioncalls=22960, ndraw=40, logz=101.38, remainder_fraction=100.0000%, Lmin=108.11, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=722, regioncalls=24880, ndraw=40, logz=108.20, remainder_fraction=100.0000%, Lmin=114.20, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=778, regioncalls=27120, ndraw=40, logz=114.04, remainder_fraction=100.0000%, Lmin=121.27, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=849, regioncalls=29960, ndraw=40, logz=122.34, remainder_fraction=100.0000%, Lmin=128.65, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=950, regioncalls=34000, ndraw=40, logz=128.02, remainder_fraction=100.0000%, Lmin=134.37, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1034, regioncalls=37360, ndraw=40, logz=132.48, remainder_fraction=100.0000%, Lmin=139.29, Lmax=242.00 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1135, regioncalls=41400, ndraw=40, logz=140.81, remainder_fraction=100.0000%, Lmin=147.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1279, regioncalls=47160, ndraw=40, logz=148.11, remainder_fraction=100.0000%, Lmin=155.97, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=277, ncalls=1369, regioncalls=50760, ndraw=40, logz=153.60, remainder_fraction=100.0000%, Lmin=160.75, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1411, regioncalls=52440, ndraw=40, logz=155.63, remainder_fraction=100.0000%, Lmin=163.08, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1566, regioncalls=58640, ndraw=40, logz=161.05, remainder_fraction=100.0000%, Lmin=168.19, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1700, regioncalls=64000, ndraw=40, logz=166.03, remainder_fraction=100.0000%, Lmin=173.84, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1793, regioncalls=67720, ndraw=40, logz=171.65, remainder_fraction=100.0000%, Lmin=179.38, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1938, regioncalls=73520, ndraw=40, logz=177.14, remainder_fraction=100.0000%, Lmin=184.35, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=328, ncalls=2114, regioncalls=80560, ndraw=40, logz=181.84, remainder_fraction=100.0000%, Lmin=189.01, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=2226, regioncalls=85040, ndraw=40, logz=182.54, remainder_fraction=100.0000%, Lmin=189.50, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=334, ncalls=2506, regioncalls=96240, ndraw=40, logz=183.64, remainder_fraction=100.0000%, Lmin=190.73, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=2654, regioncalls=102160, ndraw=40, logz=186.24, remainder_fraction=100.0000%, Lmin=193.29, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=349, ncalls=2998, regioncalls=115920, ndraw=40, logz=190.86, remainder_fraction=100.0000%, Lmin=197.89, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=3009, regioncalls=116360, ndraw=40, logz=191.15, remainder_fraction=100.0000%, Lmin=198.42, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=357, ncalls=3238, regioncalls=125520, ndraw=40, logz=194.71, remainder_fraction=100.0000%, Lmin=201.90, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=3318, regioncalls=128720, ndraw=40, logz=197.32, remainder_fraction=100.0000%, Lmin=205.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=3563, regioncalls=138520, ndraw=40, logz=199.69, remainder_fraction=100.0000%, Lmin=206.32, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=3667, regioncalls=142680, ndraw=40, logz=200.02, remainder_fraction=100.0000%, Lmin=206.86, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=379, ncalls=4169, regioncalls=162760, ndraw=40, logz=202.87, remainder_fraction=100.0000%, Lmin=210.14, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=4187, regioncalls=163480, ndraw=40, logz=203.15, remainder_fraction=100.0000%, Lmin=210.98, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=382, ncalls=4358, regioncalls=170320, ndraw=40, logz=204.01, remainder_fraction=100.0000%, Lmin=211.48, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=4799, regioncalls=187960, ndraw=40, logz=206.25, remainder_fraction=100.0000%, Lmin=213.44, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=4909, regioncalls=192360, ndraw=40, logz=206.49, remainder_fraction=100.0000%, Lmin=213.58, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=5127, regioncalls=201080, ndraw=40, logz=207.43, remainder_fraction=100.0000%, Lmin=214.42, Lmax=242.60 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5287 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_netiterintegrate.py::test_treedump	0.06
[gw0] linux -- Python 3.10.6 /usr/bin/python3 [gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ testing tree dumping...
Passed	tests/test_run.py::test_dlogz_reactive_run_SLOW	113.80
[gw0] linux -- Python 3.10.6 /usr/bin/python3 [gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ running for ess [ultranest] To achieve the desired logz accuracy, min_num_live_points was increased to 64 [ultranest] Sampling 64 live points from prior ... Z=-inf(0.00%) \| Like=-219160.93..-338.64 [-219160.9259..-66928.1126] \| it/evals=0/192 eff=0.0000% N=64 Z=-126286.0(0.00%) \| Like=-123905.72..-338.64 [-219160.9259..-66928.1126] \| it/evals=6/192 eff=4.6875% N=64 Z=-105163.6(0.00%) \| Like=-104323.03..-338.64 [-219160.9259..-66928.1126] \| it/evals=12/192 eff=9.3750% N=64 Z=-96310.2(0.00%) \| Like=-95825.45..-338.64 [-219160.9259..-66928.1126] \| it/evals=15/192 eff=11.7188% N=64 Z=-92147.5(0.00%) \| Like=-90911.35..-338.64 [-219160.9259..-66928.1126] \| it/evals=18/192 eff=14.0625% N=64 Z=-83359.1(0.00%) \| Like=-82523.24..-338.64 [-219160.9259..-66928.1126] \| it/evals=24/192 eff=18.7500% N=64 Z=-77249.3(0.00%) \| Like=-73174.88..-338.64 [-219160.9259..-66928.1126] \| it/evals=30/192 eff=23.4375% N=64 Z=-68821.4(0.00%) \| Like=-66961.75..-338.64 [-219160.9259..-66928.1126] \| it/evals=36/192 eff=28.1250% N=64 Z=-62913.5(0.00%) \| Like=-62524.24..-338.64 [-66894.4747..-30968.4623] \| it/evals=42/192 eff=32.8125% N=64 Z=-60415.5(0.00%) \| Like=-60348.58..-338.64 [-66894.4747..-30968.4623] \| it/evals=45/192 eff=35.1562% N=64 Z=-59089.1(0.00%) \| Like=-56644.03..-338.64 [-66894.4747..-30968.4623] \| it/evals=48/192 eff=37.5000% N=64 Z=-52753.0(0.00%) \| Like=-51631.51..-338.64 [-66894.4747..-30968.4623] \| it/evals=54/192 eff=42.1875% N=64 Z=-44451.0(0.00%) \| Like=-44202.51..-338.64 [-66894.4747..-30968.4623] \| it/evals=60/271 eff=28.9855% N=64 Z=-42311.4(0.00%) \| Like=-41912.56..-338.64 [-66894.4747..-30968.4623] \| it/evals=66/271 eff=31.8841% N=64 Z=-39346.0(0.00%) \| Like=-38622.07..-338.64 [-66894.4747..-30968.4623] \| it/evals=72/271 eff=34.7826% N=64 Z=-37952.2(0.00%) \| Like=-36783.31..-338.64 [-66894.4747..-30968.4623] \| it/evals=75/271 eff=36.2319% N=64 Z=-36006.7(0.00%) \| Like=-35497.21..-338.64 [-66894.4747..-30968.4623] \| it/evals=78/271 eff=37.6812% N=64 Z=-31115.6(0.00%) \| Like=-30731.78..-338.64 [-30731.7843..-12967.1842] \| it/evals=84/271 eff=40.5797% N=64 Z=-28688.0(0.00%) \| Like=-28421.18..-338.64 [-30731.7843..-12967.1842] \| it/evals=90/271 eff=43.4783% N=64 Z=-25187.3(0.00%) \| Like=-24656.65..-338.64 [-30731.7843..-12967.1842] \| it/evals=96/311 eff=38.8664% N=64 Z=-22113.7(0.00%) \| Like=-21443.24..-298.85 [-30731.7843..-12967.1842] \| it/evals=102/346 eff=36.1702% N=64 Z=-19585.3(0.00%) \| Like=-19464.67..-298.85 [-30731.7843..-12967.1842] \| it/evals=105/346 eff=37.2340% N=64 Z=-18980.4(0.00%) \| Like=-18714.44..-298.85 [-30731.7843..-12967.1842] \| it/evals=108/346 eff=38.2979% N=64 Z=-17101.8(0.00%) \| Like=-16522.06..-298.85 [-30731.7843..-12967.1842] \| it/evals=114/365 eff=37.8738% N=64 Z=-14939.8(0.00%) \| Like=-14867.96..-49.47 [-30731.7843..-12967.1842] \| it/evals=120/365 eff=39.8671% N=64 Z=-13749.8(0.00%) \| Like=-13612.93..-49.47 [-30731.7843..-12967.1842] \| it/evals=126/384 eff=39.3750% N=64 Z=-12095.7(0.00%) \| Like=-12066.44..-49.47 [-12930.5907..-6761.7113] \| it/evals=132/384 eff=41.2500% N=64 Z=-11676.8(0.00%) \| Like=-11455.33..-49.47 [-12930.5907..-6761.7113] \| it/evals=138/399 eff=41.1940% N=64 Z=-9942.7(0.00%) \| Like=-9610.42..-49.47 [-12930.5907..-6761.7113] \| it/evals=144/399 eff=42.9851% N=64 Z=-9087.9(0.00%) \| Like=-8762.61..-47.04 [-12930.5907..-6761.7113] \| it/evals=150/410 eff=43.3526% N=64 Z=-8235.1(0.00%) \| Like=-8086.11..-47.04 [-12930.5907..-6761.7113] \| it/evals=156/410 eff=45.0867% N=64 Z=-7472.4(0.00%) \| Like=-7249.22..-47.04 [-12930.5907..-6761.7113] \| it/evals=162/430 eff=44.2623% N=64 Z=-7233.2(0.00%) \| Like=-7189.85..-47.04 [-12930.5907..-6761.7113] \| it/evals=165/430 eff=45.0820% N=64 Z=-7139.4(0.00%) \| Like=-6909.47..-47.04 [-12930.5907..-6761.7113] \| it/evals=168/446 eff=43.9791% N=64 Z=-6586.4(0.00%) \| Like=-6511.36..-47.04 [-6758.0662..-3869.3843] \| it/evals=174/453 eff=44.7301% N=64 Z=-6229.9(0.00%) \| Like=-6179.54..-47.04 [-6758.0662..-3869.3843] \| it/evals=180/463 eff=45.1128% N=64 Z=-5870.7(0.00%) \| Like=-5704.16..-47.04 [-6758.0662..-3869.3843] \| it/evals=186/470 eff=45.8128% N=64 Z=-5350.2(0.00%) \| Like=-5299.56..-47.04 [-6758.0662..-3869.3843] \| it/evals=192/484 eff=45.7143% N=64 Z=-5230.5(0.00%) \| Like=-5122.84..-47.04 [-6758.0662..-3869.3843] \| it/evals=195/484 eff=46.4286% N=64 Z=-5007.8(0.00%) \| Like=-4993.48..-47.04 [-6758.0662..-3869.3843] \| it/evals=198/488 eff=46.6981% N=64 Z=-4757.0(0.00%) \| Like=-4671.78..-47.04 [-6758.0662..-3869.3843] \| it/evals=204/494 eff=47.4419% N=64 Z=-4376.4(0.00%) \| Like=-4050.17..-47.04 [-6758.0662..-3869.3843] \| it/evals=210/507 eff=47.4041% N=64 Z=-3611.3(0.00%) \| Like=-3538.07..-47.04 [-3844.5238..-2006.9345] \| it/evals=216/519 eff=47.4725% N=64 Z=-3253.1(0.00%) \| Like=-3230.22..-47.04 [-3844.5238..-2006.9345] \| it/evals=222/529 eff=47.7419% N=64 Z=-2973.9(0.00%) \| Like=-2936.21..-47.04 [-3844.5238..-2006.9345] \| it/evals=228/534 eff=48.5106% N=64 Z=-2717.1(0.00%) \| Like=-2689.65..-47.04 [-3844.5238..-2006.9345] \| it/evals=234/546 eff=48.5477% N=64 Z=-2482.7(0.00%) \| Like=-2396.74..-47.04 [-3844.5238..-2006.9345] \| it/evals=240/562 eff=48.1928% N=64 Z=-2251.9(0.00%) \| Like=-2227.96..-47.04 [-3844.5238..-2006.9345] \| it/evals=246/574 eff=48.2353% N=64 Z=-2051.0(0.00%) \| Like=-2020.88..-43.53 [-3844.5238..-2006.9345] \| it/evals=252/586 eff=48.2759% N=64 Z=-1996.9(0.00%) \| Like=-1971.99..-43.53 [-1992.9917..-938.7180] \| it/evals=255/591 eff=48.3871% N=64 Z=-1930.6(0.00%) \| Like=-1893.32..-43.53 [-1992.9917..-938.7180] \| it/evals=258/595 eff=48.5876% N=64 Z=-1661.3(0.00%) \| Like=-1630.36..-43.53 [-1992.9917..-938.7180] \| it/evals=264/607 eff=48.6188% N=64 Z=-1531.4(0.00%) \| Like=-1450.33..-43.53 [-1992.9917..-938.7180] \| it/evals=270/623 eff=48.3005% N=64 Z=-1346.6(0.00%) \| Like=-1304.59..-29.10 [-1992.9917..-938.7180] \| it/evals=276/640 eff=47.9167% N=64 Z=-1210.1(0.00%) \| Like=-1193.96..-7.65 [-1992.9917..-938.7180] \| it/evals=282/656 eff=47.6351% N=64 Z=-1128.8(0.00%) \| Like=-1115.38..-7.65 [-1992.9917..-938.7180] \| it/evals=288/656 eff=48.6486% N=64 Z=-1037.0(0.00%) \| Like=-1001.43..-6.62 [-1992.9917..-938.7180] \| it/evals=294/667 eff=48.7562% N=64 Z=-946.6(0.00%) \| Like=-931.46..-6.62 [-938.4822..-420.6857] \| it/evals=300/681 eff=48.6224% N=64 Z=-860.8(0.00%) \| Like=-851.17..-6.62 [-938.4822..-420.6857] \| it/evals=306/704 eff=47.8125% N=64 Z=-799.9(0.00%) \| Like=-784.81..-6.62 [-938.4822..-420.6857] \| it/evals=312/716 eff=47.8528% N=64 Z=-722.0(0.00%) \| Like=-712.81..-6.62 [-938.4822..-420.6857] \| it/evals=318/728 eff=47.8916% N=64 Z=-711.2(0.00%) \| Like=-681.06..-6.62 [-938.4822..-420.6857] \| it/evals=324/744 eff=47.6471% N=64 Z=-648.6(0.00%) \| Like=-627.61..-6.62 [-938.4822..-420.6857] \| it/evals=330/773 eff=46.5444% N=64 Z=-579.8(0.00%) \| Like=-544.60..-6.62 [-938.4822..-420.6857] \| it/evals=336/773 eff=47.3907% N=64 Z=-507.9(0.00%) \| Like=-491.75..-6.62 [-938.4822..-420.6857] \| it/evals=342/785 eff=47.4341% N=64 Z=-448.9(0.00%) \| Like=-436.99..-6.62 [-938.4822..-420.6857] \| it/evals=345/786 eff=47.7839% N=64 Z=-440.5(0.00%) \| Like=-410.44..-6.62 [-410.4366..-212.6066] \| it/evals=348/794 eff=47.6712% N=64 Z=-391.5(0.00%) \| Like=-381.77..-6.62 [-410.4366..-212.6066] \| it/evals=354/814 eff=47.2000% N=64 Z=-353.2(0.00%) \| Like=-341.64..-6.62 [-410.4366..-212.6066] \| it/evals=360/924 eff=41.8605% N=64 Z=-330.6(0.00%) \| Like=-319.63..-6.62 [-410.4366..-212.6066] \| it/evals=366/924 eff=42.5581% N=64 Z=-319.4(0.00%) \| Like=-308.99..-6.62 [-410.4366..-212.6066] \| it/evals=372/924 eff=43.2558% N=64 Z=-294.6(0.00%) \| Like=-274.35..-6.62 [-410.4366..-212.6066] \| it/evals=378/924 eff=43.9535% N=64 Z=-256.9(0.00%) \| Like=-243.84..-6.62 [-410.4366..-212.6066] \| it/evals=384/924 eff=44.6512% N=64 Z=-231.4(0.00%) \| Like=-216.70..-6.62 [-410.4366..-212.6066] \| it/evals=390/924 eff=45.3488% N=64 Z=-208.6(0.00%) \| Like=-197.50..-6.62 [-209.4358..-92.5441] \| it/evals=396/924 eff=46.0465% N=64 Z=-192.9(0.00%) \| Like=-180.36..-6.62 [-209.4358..-92.5441] \| it/evals=402/924 eff=46.7442% N=64 Z=-181.5(0.00%) \| Like=-170.96..-2.59 [-209.4358..-92.5441] \| it/evals=405/924 eff=47.0930% N=64 Z=-174.8(0.00%) \| Like=-164.65..-2.59 [-209.4358..-92.5441] \| it/evals=408/1052 eff=41.2955% N=64 Z=-162.1(0.00%) \| Like=-151.03..-2.59 [-209.4358..-92.5441] \| it/evals=414/1052 eff=41.9028% N=64 Z=-150.8(0.00%) \| Like=-136.96..-2.59 [-209.4358..-92.5441] \| it/evals=420/1052 eff=42.5101% N=64 Z=-140.3(0.00%) \| Like=-128.55..-2.59 [-209.4358..-92.5441] \| it/evals=426/1052 eff=43.1174% N=64 Z=-126.9(0.00%) \| Like=-115.71..-2.59 [-209.4358..-92.5441] \| it/evals=432/1052 eff=43.7247% N=64 Z=-123.3(0.00%) \| Like=-111.94..-2.59 [-209.4358..-92.5441] \| it/evals=435/1052 eff=44.0283% N=64 Z=-119.5(0.00%) \| Like=-108.01..-2.59 [-209.4358..-92.5441] \| it/evals=438/1052 eff=44.3320% N=64 Z=-110.7(0.00%) \| Like=-94.16..-1.48 [-209.4358..-92.5441] \| it/evals=444/1052 eff=44.9393% N=64 Z=-100.8(0.00%) \| Like=-86.81..-1.48 [-92.3860..-42.0224] \| it/evals=450/1052 eff=45.5466% N=64 Z=-90.8(0.00%) \| Like=-77.75..-1.48 [-92.3860..-42.0224] \| it/evals=456/1052 eff=46.1538% N=64 Z=-82.6(0.00%) \| Like=-69.50..-1.48 [-92.3860..-42.0224] \| it/evals=462/1074 eff=45.7426% N=64 Z=-79.0(0.00%) \| Like=-67.39..-1.48 [-92.3860..-42.0224] \| it/evals=465/1074 eff=46.0396% N=64 Z=-75.8(0.00%) \| Like=-64.18..-1.48 [-92.3860..-42.0224] \| it/evals=468/1074 eff=46.3366% N=64 Z=-70.1(0.00%) \| Like=-54.53..-1.48 [-92.3860..-42.0224] \| it/evals=474/1202 eff=41.6520% N=64 Z=-61.5(0.00%) \| Like=-49.47..-1.48 [-92.3860..-42.0224] \| it/evals=480/1202 eff=42.1793% N=64 Z=-57.8(0.00%) \| Like=-46.40..-1.48 [-92.3860..-42.0224] \| it/evals=486/1202 eff=42.7065% N=64 Z=-54.4(0.00%) \| Like=-43.50..-1.39 [-92.3860..-42.0224] \| it/evals=492/1202 eff=43.2337% N=64 Z=-48.9(0.00%) \| Like=-37.16..-0.90 [-40.5186..-18.1130] \| it/evals=498/1202 eff=43.7610% N=64 Z=-45.5(0.00%) \| Like=-33.14..-0.90 [-40.5186..-18.1130] \| it/evals=504/1202 eff=44.2882% N=64 Z=-41.0(0.00%) \| Like=-29.10..-0.90 [-40.5186..-18.1130] \| it/evals=510/1202 eff=44.8155% N=64 Z=-37.6(0.00%) \| Like=-25.58..-0.90 [-40.5186..-18.1130] \| it/evals=516/1202 eff=45.3427% N=64 Z=-33.7(0.00%) \| Like=-22.16..-0.15 [-40.5186..-18.1130] \| it/evals=522/1202 eff=45.8699% N=64 Z=-32.6(0.00%) \| Like=-21.09..-0.10 [-40.5186..-18.1130] \| it/evals=525/1202 eff=46.1336% N=64 Z=-31.7(0.00%) \| Like=-20.80..-0.10 [-40.5186..-18.1130] \| it/evals=528/1217 eff=45.7936% N=64 Z=-29.7(0.00%) \| Like=-18.32..-0.10 [-40.5186..-18.1130] \| it/evals=534/1217 eff=46.3140% N=64 Z=-28.3(0.00%) \| Like=-17.39..-0.10 [-18.0267..-8.1755] \| it/evals=540/1226 eff=46.4716% N=64 Z=-27.4(0.00%) \| Like=-16.54..-0.10 [-18.0267..-8.1755] \| it/evals=546/1235 eff=46.6268% N=64 Z=-26.6(0.00%) \| Like=-15.76..-0.10 [-18.0267..-8.1755] \| it/evals=552/1249 eff=46.5823% N=64 Z=-26.0(0.00%) \| Like=-13.59..-0.10 [-18.0267..-8.1755] \| it/evals=555/1249 eff=46.8354% N=64 Z=-24.9(0.00%) \| Like=-13.52..-0.10 [-18.0267..-8.1755] \| it/evals=558/1264 eff=46.5000% N=64 Z=-23.6(0.00%) \| Like=-12.01..-0.10 [-18.0267..-8.1755] \| it/evals=564/1264 eff=47.0000% N=64 Z=-22.4(0.00%) \| Like=-11.27..-0.10 [-18.0267..-8.1755] \| it/evals=570/1373 eff=43.5447% N=64 Z=-21.7(0.00%) \| Like=-10.46..-0.00 [-18.0267..-8.1755] \| it/evals=576/1373 eff=44.0031% N=64 Z=-20.9(0.01%) \| Like=-9.74..-0.00 [-18.0267..-8.1755] \| it/evals=582/1373 eff=44.4614% N=64 Z=-20.4(0.01%) \| Like=-8.52..-0.00 [-18.0267..-8.1755] \| it/evals=585/1373 eff=44.6906% N=64 Z=-19.8(0.02%) \| Like=-8.26..-0.00 [-18.0267..-8.1755] \| it/evals=588/1373 eff=44.9198% N=64 Z=-18.9(0.06%) \| Like=-7.18..-0.00 [-8.1724..-3.9366] \| it/evals=594/1373 eff=45.3782% N=64 Z=-18.1(0.14%) \| Like=-6.81..-0.00 [-8.1724..-3.9366] \| it/evals=600/1373 eff=45.8365% N=64 Z=-17.6(0.24%) \| Like=-6.49..-0.00 [-8.1724..-3.9366] \| it/evals=606/1373 eff=46.2949% N=64 Z=-17.2(0.38%) \| Like=-6.15..-0.00 [-8.1724..-3.9366] \| it/evals=612/1373 eff=46.7532% N=64 Z=-17.0(0.45%) \| Like=-6.14..-0.00 [-8.1724..-3.9366] \| it/evals=615/1373 eff=46.9824% N=64 Z=-16.8(0.51%) \| Like=-5.96..-0.00 [-8.1724..-3.9366] \| it/evals=618/1373 eff=47.2116% N=64 Z=-16.5(0.66%) \| Like=-5.47..-0.00 [-8.1724..-3.9366] \| it/evals=624/1389 eff=47.0943% N=64 Z=-16.2(0.95%) \| Like=-4.95..-0.00 [-8.1724..-3.9366] \| it/evals=630/1401 eff=47.1204% N=64 Z=-15.8(1.27%) \| Like=-4.52..-0.00 [-8.1724..-3.9366] \| it/evals=636/1510 eff=43.9834% N=64 Z=-15.4(2.01%) \| Like=-3.77..-0.00 [-3.8031..-2.2559] \| it/evals=642/1510 eff=44.3983% N=64 Z=-15.0(3.08%) \| Like=-3.55..-0.00 [-3.8031..-2.2559] \| it/evals=648/1510 eff=44.8133% N=64 Z=-14.7(4.12%) \| Like=-3.36..-0.00 [-3.8031..-2.2559] \| it/evals=654/1510 eff=45.2282% N=64 Z=-14.4(5.69%) \| Like=-3.01..-0.00 [-3.8031..-2.2559] \| it/evals=660/1510 eff=45.6432% N=64 Z=-14.1(7.42%) \| Like=-2.79..-0.00 [-3.8031..-2.2559] \| it/evals=666/1510 eff=46.0581% N=64 Z=-13.9(9.21%) \| Like=-2.64..-0.00 [-3.8031..-2.2559] \| it/evals=672/1510 eff=46.4730% N=64 Z=-13.8(10.26%) \| Like=-2.59..-0.00 [-3.8031..-2.2559] \| it/evals=675/1510 eff=46.6805% N=64 Z=-13.7(10.91%) \| Like=-2.53..-0.00 [-3.8031..-2.2559] \| it/evals=678/1510 eff=46.8880% N=64 Z=-13.6(12.43%) \| Like=-2.37..-0.00 [-3.8031..-2.2559] \| it/evals=684/1510 eff=47.3029% N=64 Z=-13.4(14.76%) \| Like=-2.10..-0.00 [-2.2114..-1.1496] \| it/evals=690/1605 eff=44.7761% N=64 Z=-13.3(16.68%) \| Like=-1.88..-0.00 [-2.2114..-1.1496] \| it/evals=696/1605 eff=45.1655% N=64 Z=-13.1(19.32%) \| Like=-1.78..-0.00 [-2.2114..-1.1496] \| it/evals=702/1605 eff=45.5548% N=64 Z=-13.0(22.22%) \| Like=-1.62..-0.00 [-2.2114..-1.1496] \| it/evals=708/1605 eff=45.9442% N=64 Z=-12.9(24.61%) \| Like=-1.57..-0.00 [-2.2114..-1.1496] \| it/evals=714/1605 eff=46.3335% N=64 Z=-12.8(27.65%) \| Like=-1.42..-0.00 [-2.2114..-1.1496] \| it/evals=720/1605 eff=46.7229% N=64 Z=-12.7(30.64%) \| Like=-1.24..-0.00 [-2.2114..-1.1496] \| it/evals=726/1605 eff=47.1123% N=64 Z=-12.6(34.09%) \| Like=-1.14..-0.00 [-1.1411..-0.5071] \| it/evals=732/1733 eff=43.8586% N=64 Z=-12.5(35.79%) \| Like=-1.12..-0.00 [-1.1411..-0.5071] \| it/evals=735/1733 eff=44.0383% N=64 Z=-12.5(37.55%) \| Like=-1.07..-0.00 [-1.1411..-0.5071] \| it/evals=738/1733 eff=44.2181% N=64 Z=-12.4(40.90%) \| Like=-0.86..-0.00 [-1.1411..-0.5071] \| it/evals=744/1733 eff=44.5776% N=64 Z=-12.3(44.16%) \| Like=-0.82..-0.00 [-1.1411..-0.5071] \| it/evals=750/1733 eff=44.9371% N=64 Z=-12.2(47.44%) \| Like=-0.73..-0.00 [-1.1411..-0.5071] \| it/evals=756/1733 eff=45.2966% N=64 Z=-12.2(50.70%) \| Like=-0.66..-0.00 [-1.1411..-0.5071] \| it/evals=762/1733 eff=45.6561% N=64 Z=-12.1(52.58%) \| Like=-0.64..-0.00 [-1.1411..-0.5071] \| it/evals=765/1733 eff=45.8358% N=64 Z=-12.1(54.15%) \| Like=-0.61..-0.00 [-1.1411..-0.5071] \| it/evals=768/1733 eff=46.0156% N=64 Z=-12.1(57.35%) \| Like=-0.55..-0.00 [-1.1411..-0.5071] \| it/evals=774/1733 eff=46.3751% N=64 Z=-12.0(60.43%) \| Like=-0.49..-0.00 [-0.4911..-0.2434] \| it/evals=780/1750 eff=46.2633% N=64 Z=-12.0(63.00%) \| Like=-0.48..-0.00 [-0.4911..-0.2434] \| it/evals=786/1862 eff=43.7152% N=64 Z=-11.9(65.72%) \| Like=-0.42..-0.00 [-0.4911..-0.2434] \| it/evals=792/1862 eff=44.0489% N=64 Z=-11.9(66.89%) \| Like=-0.41..-0.00 [-0.4911..-0.2434] \| it/evals=795/1862 eff=44.2158% N=64 Z=-11.9(68.13%) \| Like=-0.36..-0.00 [-0.4911..-0.2434] \| it/evals=798/1862 eff=44.3826% N=64 Z=-11.9(70.44%) \| Like=-0.33..-0.00 [-0.4911..-0.2434] \| it/evals=804/1862 eff=44.7164% N=64 Z=-11.8(72.73%) \| Like=-0.30..-0.00 [-0.4911..-0.2434] \| it/evals=810/1873 eff=44.7761% N=64 Z=-11.8(74.96%) \| Like=-0.28..-0.00 [-0.4911..-0.2434] \| it/evals=816/1873 eff=45.1078% N=64 Z=-11.8(76.96%) \| Like=-0.26..-0.00 [-0.4911..-0.2434] \| it/evals=822/1892 eff=44.9672% N=64 Z=-11.8(77.90%) \| Like=-0.24..-0.00 [-0.2385..-0.1266] \| it/evals=825/1905 eff=44.8126% N=64 Z=-11.7(78.74%) \| Like=-0.23..-0.00 [-0.2385..-0.1266] \| it/evals=828/1914 eff=44.7568% N=64 Z=-11.7(80.46%) \| Like=-0.21..-0.00 [-0.2385..-0.1266] \| it/evals=834/1927 eff=44.7665% N=64 Z=-11.7(82.11%) \| Like=-0.19..-0.00 [-0.2385..-0.1266] \| it/evals=840/1940 eff=44.7761% N=64 Z=-11.7(83.59%) \| Like=-0.18..-0.00 [-0.2385..-0.1266] \| it/evals=846/1958 eff=44.6674% N=64 Z=-11.7(84.89%) \| Like=-0.17..-0.00 [-0.2385..-0.1266] \| it/evals=852/1976 eff=44.5607% N=64 Z=-11.7(86.13%) \| Like=-0.15..-0.00 [-0.2385..-0.1266] \| it/evals=858/1976 eff=44.8745% N=64 Z=-11.6(87.27%) \| Like=-0.14..-0.00 [-0.2385..-0.1266] \| it/evals=864/2001 eff=44.6051% N=64 Z=-11.6(88.33%) \| Like=-0.12..-0.00 [-0.1265..-0.0588] \| it/evals=870/2001 eff=44.9148% N=64 Z=-11.6(89.31%) \| Like=-0.11..-0.00 [-0.1265..-0.0588] \| it/evals=876/2014 eff=44.9231% N=64 Z=-11.6(90.21%) \| Like=-0.10..-0.00 [-0.1265..-0.0588] \| it/evals=882/2027 eff=44.9312% N=64 Z=-11.6(90.65%) \| Like=-0.09..-0.00 [-0.1265..-0.0588] \| it/evals=885/2027 eff=45.0841% N=64 Z=-11.6(91.07%) \| Like=-0.09..-0.00 [-0.1265..-0.0588] \| it/evals=888/2040 eff=44.9393% N=64 Z=-11.6(91.82%) \| Like=-0.09..-0.00 [-0.1265..-0.0588] \| it/evals=894/2050 eff=45.0151% N=64 Z=-11.6(92.53%) \| Like=-0.08..-0.00 [-0.1265..-0.0588] \| it/evals=900/2063 eff=45.0225% N=64 Z=-11.6(93.18%) \| Like=-0.07..-0.00 [-0.1265..-0.0588] \| it/evals=906/2174 eff=42.9384% N=64 Z=-11.6(93.77%) \| Like=-0.06..-0.00 [-0.1265..-0.0588] \| it/evals=912/2174 eff=43.2227% N=64 Z=-11.6(94.05%) \| Like=-0.06..-0.00 [-0.0576..-0.0253] \| it/evals=915/2174 eff=43.3649% N=64 Z=-11.6(94.31%) \| Like=-0.06..-0.00 [-0.0576..-0.0253] \| it/evals=918/2174 eff=43.5071% N=64 Z=-11.6(94.80%) \| Like=-0.05..-0.00 [-0.0576..-0.0253] \| it/evals=924/2174 eff=43.7915% N=64 Z=-11.6(95.26%) \| Like=-0.04..-0.00 [-0.0576..-0.0253] \| it/evals=930/2174 eff=44.0758% N=64 Z=-11.5(95.68%) \| Like=-0.04..-0.00 [-0.0576..-0.0253] \| it/evals=936/2174 eff=44.3602% N=64 Z=-11.5(96.06%) \| Like=-0.03..-0.00 [-0.0576..-0.0253] \| it/evals=942/2174 eff=44.6445% N=64 Z=-11.5(96.24%) \| Like=-0.03..-0.00 [-0.0576..-0.0253] \| it/evals=945/2174 eff=44.7867% N=64 Z=-11.5(96.41%) \| Like=-0.03..-0.00 [-0.0576..-0.0253] \| it/evals=948/2174 eff=44.9289% N=64 Z=-11.5(96.72%) \| Like=-0.03..-0.00 [-0.0576..-0.0253] \| it/evals=954/2191 eff=44.8519% N=64 Z=-11.5(97.01%) \| Like=-0.03..-0.00 [-0.0576..-0.0253] \| it/evals=960/2209 eff=44.7552% N=64 Z=-11.5(97.28%) \| Like=-0.02..-0.00 [-0.0244..-0.0144]\| it/evals=966/2333 eff=42.5738% N=64 Z=-11.5(97.52%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=972/2333 eff=42.8383% N=64 Z=-11.5(97.74%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=978/2333 eff=43.1027% N=64 Z=-11.5(97.94%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=984/2333 eff=43.3671% N=64 Z=-11.5(98.12%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=990/2333 eff=43.6316% N=64 Z=-11.5(98.29%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=996/2333 eff=43.8960% N=64 Z=-11.5(98.44%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=1002/2333 eff=44.1604% N=64 Z=-11.5(98.58%) \| Like=-0.02..-0.00 [-0.0242..-0.0140] \| it/evals=1008/2333 eff=44.4249% N=64 Z=-11.5(98.71%) \| Like=-0.01..-0.00 [-0.0137..-0.0067]\| it/evals=1014/2333 eff=44.6893% N=64 Z=-11.5(98.82%) \| Like=-0.01..-0.00 [-0.0129..-0.0062]\| it/evals=1020/2429 eff=43.1290% N=64 Z=-11.5(98.93%) \| Like=-0.01..-0.00 [-0.0111..-0.0058]\| it/evals=1026/2429 eff=43.3827% N=64 [ultranest] Explored until L=-8e-05 [ultranest] Likelihood function evaluations: 2429 [ultranest] logZ = -11.5 +- 0.2693 [ultranest] Effective samples strategy wants to improve: -11.13..-0.00 (ESS = 267.4, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.48+-0.26 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 62 minimum live points (dlogz from 0.20 to 0.65, need <0.5) [ultranest] logZ error budget: single: 0.40 bs:0.27 tail:0.01 total:0.27 required:<0.50 [ultranest] Widening from 64 to 128 live points before L=-1e+01... [ultranest] Will add 64 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) \| Like=-1213.22..-0.00 [-1213.2190..-0.0011] \| it/evals=280/2433 eff=0.0000% N=64 Z=-1037.1(0.00%) \| Like=-1001.43..-0.00 [-1213.2190..-0.0011] \| it/evals=294/2433 eff=25.0000% N=65 Z=-597.4(0.00%) \| Like=-583.16..-0.00 [-1213.2190..-0.0011] \| it/evals=333/2434 eff=40.0000% N=66 Z=-284.4(0.00%) \| Like=-265.94..-0.00 [-1213.2190..-0.0011] \| it/evals=381/2547 eff=3.3898% N=66 Z=-189.7(0.00%) \| Like=-177.08..-0.00 [-1213.2190..-0.0011] \| it/evals=407/2547 eff=5.0847% N=67 Z=-187.5(0.00%) \| Like=-171.06..-0.00 [-1213.2190..-0.0011] \| it/evals=408/2547 eff=5.9322% N=67 Z=-150.9(0.00%) \| Like=-136.96..-0.00 [-1213.2190..-0.0011] \| it/evals=425/2547 eff=7.6271% N=68 Z=-118.6(0.00%) \| Like=-107.56..-0.00 [-1213.2190..-0.0011] \| it/evals=444/2547 eff=10.1695% N=71 Z=-109.9(0.00%) \| Like=-98.44..-0.00 [-1213.2190..-0.0011] \| it/evals=450/2547 eff=13.5593% N=74 Z=-102.2(0.00%) \| Like=-91.35..-0.00 [-1213.2190..-0.0011] \| it/evals=456/2547 eff=16.1017% N=75 Z=-90.9(0.00%) \| Like=-78.43..-0.00 [-1213.2190..-0.0011] \| it/evals=465/2547 eff=17.7966% N=76 Z=-76.0(0.00%) \| Like=-64.44..-0.00 [-1213.2190..-0.0011] \| it/evals=480/2669 eff=10.8333% N=78 Z=-74.2(0.00%) \| Like=-62.51..-0.00 [-1213.2190..-0.0011] \| it/evals=483/2669 eff=11.6667% N=79 Z=-66.7(0.00%) \| Like=-55.18..-0.00 [-1213.2190..-0.0011] \| it/evals=492/2669 eff=14.1667% N=80 Z=-60.8(0.00%) \| Like=-49.28..-0.00 [-1213.2190..-0.0011] \| it/evals=502/2669 eff=15.8333% N=81 Z=-59.9(0.00%) \| Like=-48.22..-0.00 [-1213.2190..-0.0011] \| it/evals=504/2669 eff=16.2500% N=82 Z=-57.2(0.00%) \| Like=-45.81..-0.00 [-1213.2190..-0.0011] \| it/evals=510/2669 eff=17.5000% N=84 Z=-54.4(0.00%) \| Like=-42.31..-0.00 [-1213.2190..-0.0011] \| it/evals=516/2669 eff=18.3333% N=85 Z=-51.1(0.00%) \| Like=-38.41..-0.00 [-1213.2190..-0.0011] \| it/evals=521/2669 eff=19.5833% N=86 Z=-50.2(0.00%) \| Like=-37.47..-0.00 [-1213.2190..-0.0011] \| it/evals=522/2669 eff=20.0000% N=87 Z=-42.4(0.00%) \| Like=-30.47..-0.00 [-1213.2190..-0.0011] \| it/evals=540/2669 eff=24.5833% N=91 Z=-42.0(0.00%) \| Like=-29.46..-0.00 [-1213.2190..-0.0011] \| it/evals=541/2669 eff=25.0000% N=92 Z=-39.9(0.00%) \| Like=-28.19..-0.00 [-1213.2190..-0.0011] \| it/evals=546/2669 eff=25.8333% N=92 Z=-37.9(0.00%) \| Like=-26.55..-0.00 [-1213.2190..-0.0011] \| it/evals=552/2669 eff=28.3333% N=95 Z=-36.6(0.00%) \| Like=-24.94..-0.00 [-1213.2190..-0.0011] \| it/evals=558/2795 eff=20.2186% N=97 Z=-35.3(0.00%) \| Like=-23.99..-0.00 [-1213.2190..-0.0011] \| it/evals=563/2795 eff=21.5847% N=99 Z=-35.1(0.00%) \| Like=-23.59..-0.00 [-1213.2190..-0.0011] \| it/evals=564/2795 eff=21.8579% N=99 Z=-31.6(0.00%) \| Like=-20.34..-0.00 [-1213.2190..-0.0011] \| it/evals=582/2795 eff=25.1366% N=103 Z=-29.6(0.00%) \| Like=-18.37..-0.00 [-1213.2190..-0.0011] \| it/evals=594/2795 eff=27.0492% N=103 Z=-28.9(0.00%) \| Like=-17.65..-0.00 [-1213.2190..-0.0011] \| it/evals=600/2795 eff=27.5956% N=103 Z=-27.9(0.00%) \| Like=-16.57..-0.00 [-1213.2190..-0.0011] \| it/evals=610/2795 eff=29.7814% N=108 Z=-27.1(0.00%) \| Like=-15.91..-0.00 [-1213.2190..-0.0011] \| it/evals=618/2795 eff=31.4208% N=113 Z=-26.5(0.00%) \| Like=-15.14..-0.00 [-1213.2190..-0.0011] \| it/evals=624/2923 eff=24.2915% N=114 Z=-25.8(0.00%) \| Like=-13.59..-0.00 [-1213.2190..-0.0011] \| it/evals=630/2923 eff=25.5061% N=115 Z=-24.7(0.00%) \| Like=-12.77..-0.00 [-1213.2190..-0.0011] \| it/evals=637/2923 eff=26.1134% N=117 Z=-24.0(0.00%) \| Like=-12.37..-0.00 [-1213.2190..-0.0011] \| it/evals=642/2923 eff=27.1255% N=118 Z=-23.4(0.00%) \| Like=-11.85..-0.00 [-1213.2190..-0.0011] \| it/evals=648/2923 eff=28.3401% N=122 Z=-22.8(0.00%) \| Like=-11.29..-0.00 [-1213.2190..-0.0011] \| it/evals=654/2923 eff=29.5547% N=125 Z=-21.9(0.00%) \| Like=-10.40..-0.00 [-1213.2190..-0.0011] \| it/evals=666/2923 eff=30.9717% N=128 Z=-21.4(0.00%) \| Like=-9.76..-0.00 [-1213.2190..-0.0011] \| it/evals=672/2923 eff=31.1741% N=128 Z=-20.3(0.01%) \| Like=-8.41..-0.00 [-1213.2190..-0.0011] \| it/evals=684/2923 eff=32.5911% N=128 Z=-19.8(0.02%) \| Like=-8.05..-0.00 [-1213.2190..-0.0011] \| it/evals=690/2923 eff=32.9960% N=128 Z=-19.3(0.04%) \| Like=-7.63..-0.00 [-1213.2190..-0.0011] \| it/evals=696/2923 eff=34.0081% N=128 Z=-17.9(0.17%) \| Like=-6.48..-0.00 [-1213.2190..-0.0011] \| it/evals=720/2923 eff=35.8300% N=128 Z=-17.7(0.22%) \| Like=-6.24..-0.00 [-1213.2190..-0.0011] \| it/evals=725/2923 eff=36.0324% N=128 Z=-17.4(0.30%) \| Like=-6.07..-0.00 [-1213.2190..-0.0011] \| it/evals=732/2935 eff=35.5731% N=128 Z=-17.0(0.40%) \| Like=-5.75..-0.00 [-1213.2190..-0.0011] \| it/evals=744/2945 eff=36.4341% N=128 Z=-16.6(0.57%) \| Like=-5.43..-0.00 [-1213.2190..-0.0011] \| it/evals=755/2945 eff=37.2093% N=128 Z=-16.0(1.04%) \| Like=-4.42..-0.00 [-1213.2190..-0.0011] \| it/evals=774/3060 eff=31.8542% N=128 Z=-15.8(1.31%) \| Like=-4.03..-0.00 [-1213.2190..-0.0011] \| it/evals=780/3060 eff=32.4881% N=128 Z=-15.6(1.52%) \| Like=-3.85..-0.00 [-1213.2190..-0.0011] \| it/evals=784/3060 eff=32.8051% N=128 Z=-15.3(2.07%) \| Like=-3.67..-0.00 [-1213.2190..-0.0011] \| it/evals=792/3060 eff=33.1220% N=128 Z=-14.9(3.13%) \| Like=-3.36..-0.00 [-1213.2190..-0.0011] \| it/evals=804/3060 eff=33.9144% N=128 Z=-14.8(3.79%) \| Like=-3.08..-0.00 [-1213.2190..-0.0011] \| it/evals=810/3060 eff=34.3899% N=128 Z=-14.7(4.08%) \| Like=-3.06..-0.00 [-1213.2190..-0.0011] \| it/evals=813/3060 eff=34.7068% N=128 Z=-14.0(8.04%) \| Like=-2.52..-0.00 [-1213.2190..-0.0011] \| it/evals=843/3060 eff=36.1331% N=128 Z=-13.8(9.22%) \| Like=-2.35..-0.00 [-1213.2190..-0.0011] \| it/evals=852/3060 eff=36.6086% N=128 Z=-13.6(11.56%) \| Like=-2.13..-0.00 [-1213.2190..-0.0011] \| it/evals=864/3060 eff=37.8764% N=128 Z=-13.5(13.17%) \| Like=-2.04..-0.00 [-1213.2190..-0.0011] \| it/evals=872/3060 eff=38.5103% N=128 Z=-13.4(14.01%) \| Like=-1.95..-0.00 [-1213.2190..-0.0011] \| it/evals=876/3060 eff=38.9857% N=128 Z=-13.4(15.19%) \| Like=-1.91..-0.00 [-1213.2190..-0.0011] \| it/evals=882/3169 eff=33.7838% N=128 Z=-13.3(16.71%) \| Like=-1.85..-0.00 [-1213.2190..-0.0011] \| it/evals=888/3169 eff=34.1892% N=128 Z=-13.1(19.44%) \| Like=-1.70..-0.00 [-1213.2190..-0.0011] \| it/evals=900/3169 eff=35.0000% N=128 Z=-13.1(19.73%) \| Like=-1.68..-0.00 [-1213.2190..-0.0011] \| it/evals=901/3169 eff=35.1351% N=128 Z=-13.0(22.47%) \| Like=-1.59..-0.00 [-1213.2190..-0.0011] \| it/evals=912/3169 eff=35.6757% N=128 Z=-12.9(23.72%) \| Like=-1.54..-0.00 [-1213.2190..-0.0011] \| it/evals=918/3169 eff=36.0811% N=128 Z=-12.8(27.35%) \| Like=-1.40..-0.00 [-1213.2190..-0.0011] \| it/evals=932/3169 eff=37.1622% N=128 Z=-12.8(28.51%) \| Like=-1.33..-0.00 [-1213.2190..-0.0011] \| it/evals=936/3169 eff=37.4324% N=128 Z=-12.7(30.17%) \| Like=-1.24..-0.00 [-1213.2190..-0.0011] \| it/evals=942/3169 eff=37.7027% N=128 Z=-12.6(35.63%) \| Like=-1.06..-0.00 [-1213.2190..-0.0011] \| it/evals=962/3169 eff=38.7838% N=128 Z=-12.5(36.83%) \| Like=-0.99..-0.00 [-1213.2190..-0.0011] \| it/evals=966/3169 eff=39.1892% N=128 Z=-12.5(38.44%) \| Like=-0.95..-0.00 [-1213.2190..-0.0011] \| it/evals=972/3169 eff=39.8649% N=128 Z=-12.4(43.45%) \| Like=-0.77..-0.00 [-1213.2190..-0.0011] \| it/evals=990/3291 eff=35.1508% N=128 Z=-12.4(43.79%) \| Like=-0.77..-0.00 [-1213.2190..-0.0011] \| it/evals=991/3291 eff=35.2668% N=128 Z=-12.3(46.96%) \| Like=-0.73..-0.00 [-1213.2190..-0.0011] \| it/evals=1002/3291 eff=35.8469% N=128 Z=-12.3(48.61%) \| Like=-0.68..-0.00 [-1213.2190..-0.0011] \| it/evals=1008/3291 eff=36.0789% N=128 Z=-12.2(53.70%) \| Like=-0.59..-0.00 [-1213.2190..-0.0011] \| it/evals=1026/3291 eff=37.1230% N=128 Z=-12.1(55.38%) \| Like=-0.56..-0.00 [-1213.2190..-0.0011] \| it/evals=1032/3291 eff=37.4710% N=128 Z=-12.0(59.99%) \| Like=-0.49..-0.00 [-1213.2190..-0.0011] \| it/evals=1050/3291 eff=38.7471% N=128 Z=-12.0(62.73%) \| Like=-0.47..-0.00 [-1213.2190..-0.0011] \| it/evals=1062/3291 eff=39.2111% N=128 Z=-12.0(64.13%) \| Like=-0.44..-0.00 [-1213.2190..-0.0011] \| it/evals=1068/3291 eff=39.6752% N=128 Z=-12.0(65.48%) \| Like=-0.42..-0.00 [-1213.2190..-0.0011] \| it/evals=1074/3419 eff=34.9495% N=128 Z=-11.9(67.53%) \| Like=-0.40..-0.00 [-1213.2190..-0.0011] \| it/evals=1084/3419 eff=35.3535% N=128 Z=-11.9(67.96%) \| Like=-0.39..-0.00 [-1213.2190..-0.0011] \| it/evals=1086/3419 eff=35.5556% N=128 Z=-11.9(69.19%) \| Like=-0.36..-0.00 [-1213.2190..-0.0011] \| it/evals=1092/3419 eff=36.1616% N=128 Z=-11.9(72.66%) \| Like=-0.32..-0.00 [-1213.2190..-0.0011] \| it/evals=1110/3419 eff=36.9697% N=128 Z=-11.8(74.75%) \| Like=-0.29..-0.00 [-1213.2190..-0.0011] \| it/evals=1122/3419 eff=37.5758% N=128 Z=-11.8(77.97%) \| Like=-0.26..-0.00 [-1213.2190..-0.0011] \| it/evals=1142/3419 eff=38.7879% N=128 Z=-11.7(82.11%) \| Like=-0.19..-0.00 [-1213.2190..-0.0011] \| it/evals=1172/3438 eff=39.4450% N=128 Z=-11.7(82.62%) \| Like=-0.19..-0.00 [-1213.2190..-0.0011] \| it/evals=1176/3563 eff=35.3616% N=128 Z=-11.7(84.03%) \| Like=-0.18..-0.00 [-1213.2190..-0.0011] \| it/evals=1188/3563 eff=35.5379% N=128 Z=-11.7(85.35%) \| Like=-0.16..-0.00 [-1213.2190..-0.0011] \| it/evals=1200/3563 eff=36.2434% N=128 Z=-11.7(85.45%) \| Like=-0.16..-0.00 [-1213.2190..-0.0011] \| it/evals=1201/3563 eff=36.3316% N=128 Z=-11.7(85.96%) \| Like=-0.16..-0.00 [-1213.2190..-0.0011] \| it/evals=1206/3563 eff=36.4198% N=128 Z=-11.7(86.55%) \| Like=-0.15..-0.00 [-1213.2190..-0.0011] \| it/evals=1212/3563 eff=36.5961% N=128 Z=-11.7(88.28%) \| Like=-0.12..-0.00 [-1213.2190..-0.0011] \| it/evals=1231/3563 eff=37.3016% N=128 Z=-11.7(88.70%) \| Like=-0.12..-0.00 [-1213.2190..-0.0011] \| it/evals=1236/3563 eff=37.4780% N=128 Z=-11.7(89.19%) \| Like=-0.11..-0.00 [-1213.2190..-0.0011] \| it/evals=1242/3563 eff=37.9189% N=128 Z=-11.6(90.10%) \| Like=-0.10..-0.00 [-1213.2190..-0.0011] \| it/evals=1254/3563 eff=38.4480% N=128 Z=-11.6(90.54%) \| Like=-0.10..-0.00 [-1213.2190..-0.0011] \| it/evals=1260/3563 eff=38.7125% N=128 Z=-11.6(91.73%) \| Like=-0.08..-0.00 [-1213.2190..-0.0011] \| it/evals=1278/3563 eff=39.3298% N=128 Z=-11.6(93.10%) \| Like=-0.07..-0.00 [-1213.2190..-0.0011] \| it/evals=1302/3576 eff=39.9303% N=128 Z=-11.6(94.50%) \| Like=-0.05..-0.00 [-1213.2190..-0.0011] \| it/evals=1332/3622 eff=39.6479% N=128 Z=-11.6(94.98%) \| Like=-0.05..-0.00 [-1213.2190..-0.0011] \| it/evals=1344/3634 eff=40.0000% N=128 Z=-11.6(95.10%) \| Like=-0.04..-0.00 [-1213.2190..-0.0011] \| it/evals=1347/3634 eff=40.1660% N=128 Z=-11.6(95.21%) \| Like=-0.04..-0.00 [-1213.2190..-0.0011] \| it/evals=1350/3750 eff=36.7903% N=128 Z=-11.6(95.63%) \| Like=-0.04..-0.00 [-1213.2190..-0.0011] \| it/evals=1362/3750 eff=37.3202% N=128 Z=-11.6(96.07%) \| Like=-0.03..-0.00 [-1213.2190..-0.0011] \| it/evals=1376/3750 eff=37.8501% N=128 Z=-11.6(96.19%) \| Like=-0.03..-0.00 [-1213.2190..-0.0011] \| it/evals=1380/3750 eff=38.1529% N=128 Z=-11.6(96.83%) \| Like=-0.03..-0.00 [-1213.2190..-0.0011] \| it/evals=1404/3750 eff=38.8342% N=128 Z=-11.6(96.86%) \| Like=-0.03..-0.00 [-1213.2190..-0.0011] \| it/evals=1405/3750 eff=38.9099% N=128 Z=-11.6(97.24%) \| Like=-0.03..-0.00 [-1213.2190..-0.0011] \| it/evals=1422/3750 eff=39.6669% N=128 Z=-11.6(97.53%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1436/3750 eff=40.0454% N=128 Z=-11.6(97.81%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1452/3750 eff=40.4996% N=128 Z=-11.6(97.91%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1458/3750 eff=40.7267% N=128 Z=-11.6(98.18%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1476/3767 eff=40.6577% N=128 Z=-11.6(98.27%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1482/3767 eff=40.8819% N=128 Z=-11.6(98.42%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1494/3786 eff=40.8990% N=128 Z=-11.6(98.49%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1500/3801 eff=40.7434% N=128 Z=-11.6(98.56%) \| Like=-0.02..-0.00 [-1213.2190..-0.0011] \| it/evals=1506/3816 eff=40.4470% N=128 Z=-11.5(98.75%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1524/3832 eff=40.4847% N=128 Z=-11.5(98.77%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1526/3832 eff=40.5560% N=128 Z=-11.5(98.81%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1530/3958 eff=37.4755% N=128 Z=-11.5(98.91%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1542/3958 eff=37.8679% N=128 Z=-11.5(99.01%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1554/3958 eff=38.3911% N=128 Z=-11.5(99.05%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1560/3958 eff=38.7835% N=128 Z=-11.5(99.10%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1566/3958 eff=39.1759% N=128 Z=-11.5(99.14%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1572/3958 eff=39.5683% N=128 Z=-11.5(99.18%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1578/3958 eff=39.9608% N=128 Z=-11.5(99.21%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1584/3958 eff=40.3532% N=128 Z=-11.5(99.25%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1590/3958 eff=40.7456% N=128 Z=-11.5(99.28%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1596/3958 eff=41.1380% N=128 Z=-11.5(99.32%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1602/3958 eff=41.5304% N=128 Z=-11.5(99.35%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1608/4069 eff=39.0854% N=128 Z=-11.5(99.37%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1613/4069 eff=39.3902% N=128 Z=-11.5(99.38%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1614/4069 eff=39.4512% N=128 Z=-11.5(99.41%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1620/4069 eff=39.8171% N=128 Z=-11.5(99.43%) \| Like=-0.01..-0.00 [-1213.2190..-0.0011] \| it/evals=1626/4069 eff=40.1829% N=128 Z=-11.5(99.46%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1632/4069 eff=40.5488% N=128 Z=-11.5(99.48%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1638/4069 eff=40.9146% N=128 Z=-11.5(99.51%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1644/4069 eff=41.2805% N=128 Z=-11.5(99.53%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1650/4082 eff=41.3188% N=128 Z=-11.5(99.55%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1656/4082 eff=41.6818% N=128 Z=-11.5(99.57%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1662/4108 eff=41.3937% N=128 Z=-11.5(99.59%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1668/4108 eff=41.7510% N=128 Z=-11.5(99.61%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1674/4125 eff=41.6863% N=128 Z=-11.5(99.63%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1680/4125 eff=42.0401% N=128 Z=-11.5(99.65%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1686/4135 eff=42.1454% N=128 Z=-11.5(99.66%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1692/4146 eff=42.2248% N=128 Z=-11.5(99.68%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1698/4166 eff=42.0841% N=128 Z=-11.5(99.68%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1700/4166 eff=42.1992% N=128 Z=-11.5(99.69%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1704/4166 eff=42.4295% N=128 Z=-11.5(99.71%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1710/4284 eff=40.0539% N=128 Z=-11.5(99.72%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1716/4284 eff=40.3774% N=128 Z=-11.5(99.73%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1722/4284 eff=40.7008% N=128 Z=-11.5(99.74%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1728/4284 eff=41.0243% N=128 Z=-11.5(99.75%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1729/4284 eff=41.0782% N=128 Z=-11.5(99.76%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1734/4284 eff=41.3477% N=128 Z=-11.5(99.77%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1740/4284 eff=41.6712% N=128 Z=-11.5(99.78%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1746/4284 eff=41.9946% N=128 Z=-11.5(99.79%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1752/4284 eff=42.3181% N=128 Z=-11.5(99.80%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1758/4284 eff=42.6415% N=128 Z=-11.5(99.81%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1764/4284 eff=42.9650% N=128 Z=-11.5(99.82%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1770/4284 eff=43.2884% N=128 Z=-11.5(99.82%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1776/4394 eff=41.1705% N=128 Z=-11.5(99.83%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1782/4394 eff=41.4758% N=128 Z=-11.5(99.84%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1788/4394 eff=41.7812% N=128 Z=-11.5(99.85%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1794/4394 eff=42.0865% N=128 Z=-11.5(99.85%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1800/4394 eff=42.3919% N=128 Z=-11.5(99.86%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1806/4394 eff=42.6972% N=128 Z=-11.5(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1812/4394 eff=43.0025% N=128 Z=-11.5(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1816/4394 eff=43.2061% N=128 Z=-11.5(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1818/4394 eff=43.3079% N=128 Z=-11.5(99.88%) \| Like=-0.00..-0.00 [-1213.2190..-0.0011] \| it/evals=1824/4394 eff=43.6132% N=128 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 4505 [ultranest] logZ = -11.56 +- 0.3516 [ultranest] Effective samples strategy wants to improve: -10.40..-0.00 (ESS = 519.9, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.17 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 31 minimum live points (dlogz from 0.29 to 0.78, need <0.5) [ultranest] logZ error budget: single: 0.29 bs:0.35 tail:0.00 total:0.35 required:<0.50 [ultranest] Widening from 67 to 256 live points before L=-1e+01... [ultranest] Will add 189 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) \| Like=-1213.22..-0.00 [-1213.2190..-0.0010] \| it/evals=280/4506 eff=0.0000% N=64 Z=-1037.1(0.00%) \| Like=-1001.43..-0.00 [-1213.2190..-0.0010] \| it/evals=295/4509 eff=50.0000% N=66 Z=-682.4(0.00%) \| Like=-672.78..-0.00 [-1213.2190..-0.0010] \| it/evals=328/4512 eff=57.1429% N=68 Z=-238.0(0.00%) \| Like=-222.58..-0.00 [-1213.2190..-0.0010] \| it/evals=395/4611 eff=5.6604% N=68 Z=-187.5(0.00%) \| Like=-171.06..-0.00 [-1213.2190..-0.0010] \| it/evals=413/4611 eff=7.5472% N=70 Z=-150.9(0.00%) \| Like=-136.96..-0.00 [-1213.2190..-0.0010] \| it/evals=430/4611 eff=8.4906% N=72 Z=-119.7(0.00%) \| Like=-108.42..-0.00 [-1213.2190..-0.0010] \| it/evals=448/4611 eff=10.3774% N=77 Z=-118.4(0.00%) \| Like=-107.56..-0.00 [-1213.2190..-0.0010] \| it/evals=450/4611 eff=11.3208% N=77 Z=-81.6(0.00%) \| Like=-69.50..-0.00 [-1213.2190..-0.0010] \| it/evals=480/4611 eff=14.1509% N=84 Z=-66.2(0.00%) \| Like=-55.02..-0.00 [-1213.2190..-0.0010] \| it/evals=501/4611 eff=18.8679% N=92 Z=-51.9(0.00%) \| Like=-40.14..-0.00 [-1213.2190..-0.0010] \| it/evals=530/4739 eff=11.5385% N=102 Z=-50.0(0.00%) \| Like=-37.47..-0.00 [-1213.2190..-0.0010] \| it/evals=534/4739 eff=13.2479% N=106 Z=-43.1(0.00%) \| Like=-31.83..-0.00 [-1213.2190..-0.0010] \| it/evals=552/4739 eff=15.3846% N=114 Z=-42.0(0.00%) \| Like=-30.01..-0.00 [-1213.2190..-0.0010] \| it/evals=555/4739 eff=16.2393% N=116 Z=-39.5(0.00%) \| Like=-27.98..-0.00 [-1213.2190..-0.0010] \| it/evals=564/4739 eff=17.5214% N=116 Z=-36.8(0.00%) \| Like=-25.42..-0.00 [-1213.2190..-0.0010] \| it/evals=576/4739 eff=19.6581% N=125 Z=-35.4(0.00%) \| Like=-23.99..-0.00 [-1213.2190..-0.0010] \| it/evals=583/4739 eff=21.3675% N=129 Z=-29.0(0.00%) \| Like=-17.70..-0.00 [-1213.2190..-0.0010] \| it/evals=624/4855 eff=17.1429% N=139 Z=-28.4(0.00%) \| Like=-17.39..-0.00 [-1213.2190..-0.0010] \| it/evals=630/4855 eff=17.7143% N=141 Z=-27.9(0.00%) \| Like=-16.57..-0.00 [-1213.2190..-0.0010] \| it/evals=636/4855 eff=19.1429% N=149 Z=-27.4(0.00%) \| Like=-16.19..-0.00 [-1213.2190..-0.0010] \| it/evals=642/4855 eff=20.0000% N=153 Z=-26.9(0.00%) \| Like=-15.65..-0.00 [-1213.2190..-0.0010] \| it/evals=648/4855 eff=20.8571% N=160 Z=-26.5(0.00%) \| Like=-15.25..-0.00 [-1213.2190..-0.0010] \| it/evals=653/4855 eff=21.4286% N=160 Z=-26.4(0.00%) \| Like=-15.15..-0.00 [-1213.2190..-0.0010] \| it/evals=654/4855 eff=21.7143% N=160 Z=-25.3(0.00%) \| Like=-13.59..-0.00 [-1213.2190..-0.0010] \| it/evals=666/4855 eff=23.7143% N=162 Z=-24.2(0.00%) \| Like=-12.64..-0.00 [-1213.2190..-0.0010] \| it/evals=678/4855 eff=25.1429% N=168 Z=-23.2(0.00%) \| Like=-11.68..-0.00 [-1213.2190..-0.0010] \| it/evals=690/4855 eff=27.1429% N=176 Z=-22.4(0.00%) \| Like=-11.13..-0.00 [-1213.2190..-0.0010] \| it/evals=702/4855 eff=30.0000% N=188 Z=-22.1(0.00%) \| Like=-10.81..-0.00 [-1213.2190..-0.0010] \| it/evals=708/4855 eff=30.5714% N=190 Z=-21.5(0.00%) \| Like=-10.06..-0.00 [-1213.2190..-0.0010] \| it/evals=720/4983 eff=23.8494% N=191 Z=-21.2(0.00%) \| Like=-9.76..-0.00 [-1213.2190..-0.0010] \| it/evals=726/4983 eff=24.6862% N=191 Z=-20.9(0.01%) \| Like=-9.54..-0.00 [-1213.2190..-0.0010] \| it/evals=732/4983 eff=25.1046% N=191 Z=-20.6(0.01%) \| Like=-9.07..-0.00 [-1213.2190..-0.0010] \| it/evals=738/4983 eff=25.5230% N=191 Z=-19.6(0.02%) \| Like=-8.07..-0.00 [-1213.2190..-0.0010] \| it/evals=756/4983 eff=26.9874% N=191 Z=-19.0(0.05%) \| Like=-7.51..-0.00 [-1213.2190..-0.0010] \| it/evals=768/4983 eff=27.6151% N=191 Z=-18.7(0.06%) \| Like=-7.26..-0.00 [-1213.2190..-0.0010] \| it/evals=774/4983 eff=28.2427% N=191 Z=-18.7(0.06%) \| Like=-7.21..-0.00 [-1213.2190..-0.0010] \| it/evals=775/4983 eff=28.4519% N=191 Z=-18.3(0.10%) \| Like=-6.83..-0.00 [-1213.2190..-0.0010] \| it/evals=786/4983 eff=29.0795% N=191 Z=-17.6(0.19%) \| Like=-6.27..-0.00 [-1213.2190..-0.0010] \| it/evals=804/4983 eff=29.9163% N=191 Z=-17.2(0.29%) \| Like=-6.01..-0.00 [-1213.2190..-0.0010] \| it/evals=820/4983 eff=30.5439% N=191 Z=-16.7(0.45%) \| Like=-5.53..-0.00 [-1213.2190..-0.0010] \| it/evals=840/4983 eff=31.7992% N=191 Z=-16.1(0.88%) \| Like=-4.59..-0.00 [-1213.2190..-0.0010] \| it/evals=867/4983 eff=33.0544% N=191 Z=-14.9(2.72%) \| Like=-3.49..-0.00 [-1213.2190..-0.0010] \| it/evals=913/5013 eff=35.0394% N=191 Z=-14.4(4.69%) \| Like=-2.99..-0.00 [-1213.2190..-0.0010] \| it/evals=942/5029 eff=35.6870% N=191 Z=-14.3(5.16%) \| Like=-2.89..-0.00 [-1213.2190..-0.0010] \| it/evals=948/5029 eff=35.8779% N=191 Z=-14.1(6.50%) \| Like=-2.69..-0.00 [-1213.2190..-0.0010] \| it/evals=963/5150 eff=29.7674% N=191 Z=-13.9(7.41%) \| Like=-2.58..-0.00 [-1213.2190..-0.0010] \| it/evals=972/5150 eff=30.2326% N=191 Z=-13.5(11.77%) \| Like=-2.11..-0.00 [-1213.2190..-0.0010] \| it/evals=1009/5150 eff=31.9380% N=191 Z=-13.4(12.46%) \| Like=-2.07..-0.00 [-1213.2190..-0.0010] \| it/evals=1014/5150 eff=32.4031% N=191 Z=-13.3(14.16%) \| Like=-2.01..-0.00 [-1213.2190..-0.0010] \| it/evals=1026/5150 eff=33.3333% N=191 Z=-13.2(15.72%) \| Like=-1.91..-0.00 [-1213.2190..-0.0010] \| it/evals=1038/5150 eff=33.7984% N=191 Z=-13.0(18.17%) \| Like=-1.79..-0.00 [-1213.2190..-0.0010] \| it/evals=1054/5150 eff=34.4186% N=191 Z=-13.0(18.46%) \| Like=-1.78..-0.00 [-1213.2190..-0.0010] \| it/evals=1056/5150 eff=34.5736% N=191 Z=-13.0(19.39%) \| Like=-1.72..-0.00 [-1213.2190..-0.0010] \| it/evals=1062/5150 eff=35.0388% N=191 Z=-12.8(23.35%) \| Like=-1.52..-0.00 [-1213.2190..-0.0010] \| it/evals=1086/5150 eff=35.6589% N=191 Z=-12.7(25.38%) \| Like=-1.45..-0.00 [-1213.2190..-0.0010] \| it/evals=1098/5150 eff=36.4341% N=191 Z=-12.6(29.78%) \| Like=-1.26..-0.00 [-1213.2190..-0.0010] \| it/evals=1122/5261 eff=32.4074% N=191 Z=-12.5(33.56%) \| Like=-1.14..-0.00 [-1213.2190..-0.0010] \| it/evals=1142/5261 eff=33.2011% N=191 Z=-12.4(34.30%) \| Like=-1.13..-0.00 [-1213.2190..-0.0010] \| it/evals=1146/5261 eff=33.3333% N=191 Z=-12.3(37.68%) \| Like=-1.00..-0.00 [-1213.2190..-0.0010] \| it/evals=1164/5261 eff=34.6561% N=191 Z=-12.3(39.87%) \| Like=-0.91..-0.00 [-1213.2190..-0.0010] \| it/evals=1176/5261 eff=35.0529% N=191 Z=-12.2(41.78%) \| Like=-0.86..-0.00 [-1213.2190..-0.0010] \| it/evals=1187/5261 eff=35.5820% N=191 Z=-12.2(43.05%) \| Like=-0.83..-0.00 [-1213.2190..-0.0010] \| it/evals=1194/5261 eff=35.8466% N=191 Z=-12.2(45.37%) \| Like=-0.77..-0.00 [-1213.2190..-0.0010] \| it/evals=1206/5261 eff=36.3757% N=191 Z=-12.1(46.54%) \| Like=-0.75..-0.00 [-1213.2190..-0.0010] \| it/evals=1212/5261 eff=36.5079% N=191 Z=-12.1(49.85%) \| Like=-0.68..-0.00 [-1213.2190..-0.0010] \| it/evals=1230/5261 eff=37.4339% N=191 Z=-12.0(53.23%) \| Like=-0.61..-0.00 [-1213.2190..-0.0010] \| it/evals=1248/5370 eff=33.4104% N=191 Z=-12.0(54.28%) \| Like=-0.59..-0.00 [-1213.2190..-0.0010] \| it/evals=1254/5370 eff=33.6416% N=191 Z=-12.0(55.37%) \| Like=-0.58..-0.00 [-1213.2190..-0.0010] \| it/evals=1260/5370 eff=34.1040% N=191 Z=-11.9(58.39%) \| Like=-0.53..-0.00 [-1213.2190..-0.0010] \| it/evals=1277/5370 eff=34.3353% N=191 Z=-11.9(60.58%) \| Like=-0.49..-0.00 [-1213.2190..-0.0010] \| it/evals=1290/5370 eff=34.7977% N=191 Z=-11.8(65.27%) \| Like=-0.42..-0.00 [-1213.2190..-0.0010] \| it/evals=1321/5370 eff=36.0694% N=191 Z=-11.8(68.53%) \| Like=-0.37..-0.00 [-1213.2190..-0.0010] \| it/evals=1344/5370 eff=36.6474% N=191 Z=-11.7(70.88%) \| Like=-0.34..-0.00 [-1213.2190..-0.0010] \| it/evals=1362/5370 eff=37.4566% N=191 Z=-11.7(71.66%) \| Like=-0.33..-0.00 [-1213.2190..-0.0010] \| it/evals=1368/5370 eff=37.5723% N=191 Z=-11.6(78.96%) \| Like=-0.24..-0.00 [-1213.2190..-0.0010] \| it/evals=1434/5406 eff=38.5128% N=191 Z=-11.6(79.51%) \| Like=-0.23..-0.00 [-1213.2190..-0.0010] \| it/evals=1440/5406 eff=38.7347% N=191 Z=-11.6(81.08%) \| Like=-0.21..-0.00 [-1213.2190..-0.0010] \| it/evals=1457/5416 eff=38.8584% N=191 Z=-11.6(81.70%) \| Like=-0.20..-0.00 [-1213.2190..-0.0010] \| it/evals=1464/5544 eff=34.1675% N=191 Z=-11.6(82.71%) \| Like=-0.19..-0.00 [-1213.2190..-0.0010] \| it/evals=1476/5544 eff=34.5525% N=191 Z=-11.5(84.12%) \| Like=-0.18..-0.00 [-1213.2190..-0.0010] \| it/evals=1494/5544 eff=35.0337% N=191 Z=-11.5(84.64%) \| Like=-0.17..-0.00 [-1213.2190..-0.0010] \| it/evals=1501/5544 eff=35.2262% N=191 Z=-11.5(86.68%) \| Like=-0.15..-0.00 [-1213.2190..-0.0010] \| it/evals=1530/5544 eff=36.4774% N=191 Z=-11.5(87.06%) \| Like=-0.14..-0.00 [-1213.2190..-0.0010] \| it/evals=1536/5544 eff=36.7661% N=191 Z=-11.5(87.54%) \| Like=-0.13..-0.00 [-1213.2190..-0.0010] \| it/evals=1544/5544 eff=37.1511% N=191 Z=-11.5(87.79%) \| Like=-0.13..-0.00 [-1213.2190..-0.0010] \| it/evals=1548/5544 eff=37.3436% N=191 Z=-11.5(88.48%) \| Like=-0.12..-0.00 [-1213.2190..-0.0010] \| it/evals=1560/5544 eff=37.6323% N=191 Z=-11.5(89.14%) \| Like=-0.11..-0.00 [-1213.2190..-0.0010] \| it/evals=1572/5544 eff=37.9211% N=191 Z=-11.5(91.18%) \| Like=-0.09..-0.00 [-1213.2190..-0.0010] \| it/evals=1614/5544 eff=39.3648% N=191 Z=-11.5(91.69%) \| Like=-0.09..-0.00 [-1213.2190..-0.0010] \| it/evals=1626/5544 eff=39.9423% N=191 Z=-11.5(91.90%) \| Like=-0.09..-0.00 [-1213.2190..-0.0010] \| it/evals=1631/5554 eff=39.8475% N=191 Z=-11.4(92.86%) \| Like=-0.08..-0.00 [-1213.2190..-0.0010] \| it/evals=1656/5663 eff=36.8739% N=191 Z=-11.4(93.07%) \| Like=-0.07..-0.00 [-1213.2190..-0.0010] \| it/evals=1662/5663 eff=37.0466% N=191 Z=-11.4(93.68%) \| Like=-0.07..-0.00 [-1213.2190..-0.0010] \| it/evals=1680/5663 eff=37.6511% N=191 Z=-11.4(94.05%) \| Like=-0.06..-0.00 [-1213.2190..-0.0010] \| it/evals=1692/5663 eff=37.9965% N=191 Z=-11.4(94.73%) \| Like=-0.05..-0.00 [-1213.2190..-0.0010] \| it/evals=1716/5663 eff=38.6874% N=191 Z=-11.4(94.79%) \| Like=-0.05..-0.00 [-1213.2190..-0.0010] \| it/evals=1718/5663 eff=38.7737% N=191 Z=-11.4(95.34%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=1740/5663 eff=39.3782% N=191 Z=-11.4(95.84%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=1762/5663 eff=39.9827% N=191 Z=-11.4(96.01%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=1770/5663 eff=40.2418% N=191 Z=-11.4(96.25%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1782/5663 eff=40.5009% N=191 Z=-11.4(96.36%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1788/5663 eff=40.6736% N=191 Z=-11.4(96.47%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1794/5663 eff=40.8463% N=191 Z=-11.4(96.78%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1812/5675 eff=41.0256% N=191 Z=-11.4(96.98%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1824/5689 eff=40.8784% N=191 Z=-11.4(97.07%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1830/5689 eff=41.0473% N=191 Z=-11.4(97.42%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=1855/5703 eff=40.9850% N=191 Z=-11.4(97.71%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=1878/5820 eff=38.1749% N=191 Z=-11.4(97.78%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=1884/5820 eff=38.3270% N=191 Z=-11.4(97.95%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=1899/5820 eff=38.4791% N=191 Z=-11.4(98.36%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=1942/5820 eff=39.3916% N=191 Z=-11.4(98.52%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=1962/5820 eff=39.8479% N=191 Z=-11.4(98.65%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=1980/5820 eff=40.3042% N=191 Z=-11.4(98.73%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=1992/5820 eff=40.4563% N=191 Z=-11.4(98.88%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2016/5820 eff=40.9125% N=191 Z=-11.4(98.97%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2031/5820 eff=41.5209% N=191 Z=-11.4(99.01%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2040/5832 eff=41.3715% N=191 Z=-11.4(99.07%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2052/5832 eff=41.7483% N=191 Z=-11.4(99.10%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2058/5845 eff=41.7910% N=191 Z=-11.4(99.13%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2064/5858 eff=41.6851% N=191 Z=-11.4(99.16%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2070/5858 eff=41.9069% N=191 Z=-11.4(99.19%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2078/5858 eff=41.9808% N=191 Z=-11.4(99.28%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2100/5973 eff=39.1689% N=191 Z=-11.4(99.36%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2122/5973 eff=39.9183% N=191 Z=-11.4(99.40%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2136/5973 eff=40.3270% N=191 Z=-11.4(99.46%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2154/5973 eff=40.8719% N=191 Z=-11.4(99.56%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2196/5973 eff=41.8256% N=191 Z=-11.4(99.61%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2216/5973 eff=42.0981% N=191 Z=-11.4(99.63%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2226/5973 eff=42.2343% N=191 Z=-11.4(99.64%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2232/5973 eff=42.3025% N=191 Z=-11.4(99.69%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2260/5973 eff=42.7112% N=191 Z=-11.4(99.69%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2262/5973 eff=42.7793% N=191 Z=-11.4(99.70%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2268/6096 eff=39.6606% N=191 Z=-11.4(99.72%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2280/6096 eff=39.9120% N=191 Z=-11.4(99.74%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2292/6096 eff=40.3520% N=191 Z=-11.4(99.75%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2303/6096 eff=40.4777% N=191 Z=-11.4(99.80%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2346/6096 eff=41.3576% N=191 Z=-11.4(99.83%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2382/6096 eff=42.1119% N=191 Z=-11.4(99.84%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2388/6096 eff=42.3633% N=191 Z=-11.4(99.86%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2412/6096 eff=42.6776% N=191 Z=-11.4(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2424/6111 eff=42.4035% N=191 Z=-11.4(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2430/6111 eff=42.4658% N=191 Z=-11.4(99.89%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2452/6111 eff=42.7148% N=191 Z=-11.4(99.89%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2454/6111 eff=42.8394% N=191 Z=-11.4(99.89%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2460/6234 eff=40.1388% N=191 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 6234 [ultranest] logZ = -11.38 +- 0.3175 [ultranest] Effective samples strategy wants to improve: -8.83..-0.00 (ESS = 776.0, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.16 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 20 minimum live points (dlogz from 0.24 to 0.82, need <0.5) [ultranest] logZ error budget: single: 0.23 bs:0.32 tail:0.00 total:0.32 required:<0.50 [ultranest] Widening from 72 to 382 live points before L=-9... [ultranest] Will add 310 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) \| Like=-1213.22..-0.00 [-1213.2190..-0.0010] \| it/evals=280/6361 eff=0.0000% N=64 Z=-1037.1(0.00%) \| Like=-1001.43..-0.00 [-1213.2190..-0.0010] \| it/evals=295/6361 eff=0.7874% N=67 Z=-237.9(0.00%) \| Like=-222.58..-0.00 [-1213.2190..-0.0010] \| it/evals=395/6361 eff=1.5748% N=70 Z=-187.5(0.00%) \| Like=-171.06..-0.00 [-1213.2190..-0.0010] \| it/evals=413/6361 eff=2.3622% N=73 Z=-150.9(0.00%) \| Like=-136.96..-0.00 [-1213.2190..-0.0010] \| it/evals=430/6361 eff=3.1496% N=76 Z=-122.5(0.00%) \| Like=-110.24..-0.00 [-1213.2190..-0.0010] \| it/evals=448/6372 eff=5.7971% N=83 Z=-107.6(0.00%) \| Like=-94.16..-0.00 [-1213.2190..-0.0010] \| it/evals=462/6372 eff=9.4203% N=91 Z=-82.9(0.00%) \| Like=-70.89..-0.00 [-1213.2190..-0.0010] \| it/evals=483/6503 eff=5.5762% N=95 Z=-74.2(0.00%) \| Like=-62.51..-0.00 [-1213.2190..-0.0010] \| it/evals=498/6503 eff=8.1784% N=104 Z=-66.9(0.00%) \| Like=-55.18..-0.00 [-1213.2190..-0.0010] \| it/evals=508/6503 eff=8.5502% N=107 Z=-58.1(0.00%) \| Like=-46.40..-0.00 [-1213.2190..-0.0010] \| it/evals=528/6503 eff=10.7807% N=117 Z=-56.3(0.00%) \| Like=-44.86..-0.00 [-1213.2190..-0.0010] \| it/evals=534/6503 eff=11.8959% N=123 Z=-50.4(0.00%) \| Like=-38.41..-0.00 [-1213.2190..-0.0010] \| it/evals=546/6503 eff=13.0112% N=126 Z=-45.4(0.00%) \| Like=-34.07..-0.00 [-1213.2190..-0.0010] \| it/evals=563/6503 eff=15.9851% N=135 Z=-41.9(0.00%) \| Like=-30.33..-0.00 [-1213.2190..-0.0010] \| it/evals=576/6503 eff=18.2156% N=144 Z=-38.5(0.00%) \| Like=-26.96..-0.00 [-1213.2190..-0.0010] \| it/evals=594/6503 eff=21.1896% N=150 Z=-37.5(0.00%) \| Like=-26.06..-0.00 [-1213.2190..-0.0010] \| it/evals=600/6503 eff=21.5613% N=152 Z=-36.3(0.00%) \| Like=-24.83..-0.00 [-1213.2190..-0.0010] \| it/evals=606/6503 eff=22.6766% N=161 Z=-35.4(0.00%) \| Like=-23.99..-0.00 [-1213.2190..-0.0010] \| it/evals=612/6503 eff=23.7918% N=164 Z=-32.0(0.00%) \| Like=-20.84..-0.00 [-1213.2190..-0.0010] \| it/evals=636/6519 eff=25.9649% N=175 Z=-31.8(0.00%) \| Like=-20.77..-0.00 [-1213.2190..-0.0010] \| it/evals=638/6646 eff=18.2039% N=178 Z=-31.5(0.00%) \| Like=-20.72..-0.00 [-1213.2190..-0.0010] \| it/evals=642/6646 eff=18.6893% N=178 Z=-31.0(0.00%) \| Like=-19.78..-0.00 [-1213.2190..-0.0010] \| it/evals=648/6646 eff=19.4175% N=178 Z=-30.4(0.00%) \| Like=-19.34..-0.00 [-1213.2190..-0.0010] \| it/evals=654/6646 eff=20.1456% N=178 Z=-29.2(0.00%) \| Like=-18.09..-0.00 [-1213.2190..-0.0010] \| it/evals=666/6646 eff=20.6311% N=180 Z=-28.7(0.00%) \| Like=-17.60..-0.00 [-1213.2190..-0.0010] \| it/evals=672/6646 eff=20.8738% N=180 Z=-28.3(0.00%) \| Like=-17.22..-0.00 [-1213.2190..-0.0010] \| it/evals=679/6646 eff=21.8447% N=186 Z=-28.0(0.00%) \| Like=-16.98..-0.00 [-1213.2190..-0.0010] \| it/evals=684/6646 eff=23.0583% N=195 Z=-27.3(0.00%) \| Like=-16.08..-0.00 [-1213.2190..-0.0010] \| it/evals=696/6646 eff=24.7573% N=204 Z=-25.1(0.00%) \| Like=-13.57..-0.00 [-1213.2190..-0.0010] \| it/evals=732/6646 eff=28.8835% N=218 Z=-24.7(0.00%) \| Like=-13.38..-0.00 [-1213.2190..-0.0010] \| it/evals=738/6646 eff=29.3689% N=221 Z=-23.9(0.00%) \| Like=-12.43..-0.00 [-1213.2190..-0.0010] \| it/evals=750/6646 eff=30.5825% N=224 Z=-23.6(0.00%) \| Like=-12.27..-0.00 [-1213.2190..-0.0010] \| it/evals=756/6646 eff=31.3107% N=230 Z=-23.0(0.00%) \| Like=-11.55..-0.00 [-1213.2190..-0.0010] \| it/evals=768/6646 eff=32.7670% N=236 Z=-22.7(0.00%) \| Like=-11.30..-0.00 [-1213.2190..-0.0010] \| it/evals=774/6646 eff=33.7379% N=242 Z=-22.6(0.00%) \| Like=-11.27..-0.00 [-1213.2190..-0.0010] \| it/evals=776/6657 eff=33.3333% N=248 Z=-22.0(0.00%) \| Like=-10.67..-0.00 [-1213.2190..-0.0010] \| it/evals=792/6666 eff=34.4907% N=260 Z=-21.5(0.00%) \| Like=-10.14..-0.00 [-1213.2190..-0.0010] \| it/evals=804/6674 eff=35.6818% N=263 Z=-20.9(0.01%) \| Like=-9.43..-0.00 [-1213.2190..-0.0010] \| it/evals=822/6683 eff=35.8575% N=264 Z=-20.7(0.01%) \| Like=-9.25..-0.00 [-1213.2190..-0.0010] \| it/evals=828/6683 eff=36.5256% N=264 Z=-20.4(0.01%) \| Like=-8.80..-0.00 [-1213.2190..-0.0010] \| it/evals=835/6695 eff=36.6594% N=265 Z=-19.7(0.02%) \| Like=-8.19..-0.00 [-1213.2190..-0.0010] \| it/evals=852/6695 eff=37.5271% N=265 Z=-19.3(0.03%) \| Like=-7.87..-0.00 [-1213.2190..-0.0010] \| it/evals=864/6706 eff=37.5000% N=265 Z=-18.8(0.06%) \| Like=-7.34..-0.00 [-1213.2190..-0.0010] \| it/evals=882/6706 eff=38.9831% N=265 Z=-18.4(0.09%) \| Like=-7.05..-0.00 [-1213.2190..-0.0010] \| it/evals=894/6718 eff=38.4298% N=265 Z=-18.4(0.09%) \| Like=-7.02..-0.00 [-1213.2190..-0.0010] \| it/evals=896/6718 eff=38.6364% N=265 Z=-17.8(0.17%) \| Like=-6.49..-0.00 [-1213.2190..-0.0010] \| it/evals=918/6839 eff=32.0661% N=265 Z=-17.6(0.22%) \| Like=-6.24..-0.00 [-1213.2190..-0.0010] \| it/evals=930/6839 eff=32.7273% N=265 Z=-17.1(0.35%) \| Like=-5.94..-0.00 [-1213.2190..-0.0010] \| it/evals=956/6839 eff=33.7190% N=265 Z=-16.9(0.40%) \| Like=-5.82..-0.00 [-1213.2190..-0.0010] \| it/evals=966/6839 eff=34.3802% N=265 Z=-16.5(0.60%) \| Like=-5.27..-0.00 [-1213.2190..-0.0010] \| it/evals=990/6839 eff=35.2066% N=265 Z=-16.4(0.66%) \| Like=-5.08..-0.00 [-1213.2190..-0.0010] \| it/evals=996/6839 eff=35.8678% N=265 Z=-16.2(0.80%) \| Like=-4.77..-0.00 [-1213.2190..-0.0010] \| it/evals=1008/6839 eff=36.6942% N=265 Z=-16.1(0.87%) \| Like=-4.66..-0.00 [-1213.2190..-0.0010] \| it/evals=1014/6839 eff=36.8595% N=265 Z=-16.1(0.90%) \| Like=-4.65..-0.00 [-1213.2190..-0.0010] \| it/evals=1016/6839 eff=37.1901% N=265 Z=-16.0(0.96%) \| Like=-4.57..-0.00 [-1213.2190..-0.0010] \| it/evals=1020/6839 eff=37.3554% N=265 Z=-15.7(1.34%) \| Like=-4.15..-0.00 [-1213.2190..-0.0010] \| it/evals=1038/6839 eff=38.5124% N=265 Z=-15.5(1.62%) \| Like=-3.99..-0.00 [-1213.2190..-0.0010] \| it/evals=1050/6839 eff=39.3388% N=265 Z=-15.4(1.78%) \| Like=-3.89..-0.00 [-1213.2190..-0.0010] \| it/evals=1056/6839 eff=40.0000% N=265 Z=-15.1(2.40%) \| Like=-3.66..-0.00 [-1213.2190..-0.0010] \| it/evals=1076/6839 eff=40.8264% N=265 Z=-14.8(3.26%) \| Like=-3.36..-0.00 [-1213.2190..-0.0010] \| it/evals=1098/6839 eff=41.3223% N=265 Z=-14.6(3.84%) \| Like=-3.19..-0.00 [-1213.2190..-0.0010] \| it/evals=1110/6839 eff=41.9835% N=265 Z=-14.3(5.12%) \| Like=-2.90..-0.00 [-1213.2190..-0.0010] \| it/evals=1134/6953 eff=36.4395% N=265 Z=-14.3(5.41%) \| Like=-2.85..-0.00 [-1213.2190..-0.0010] \| it/evals=1139/6953 eff=36.5786% N=265 Z=-14.1(6.61%) \| Like=-2.68..-0.00 [-1213.2190..-0.0010] \| it/evals=1158/6953 eff=37.2740% N=265 Z=-13.7(9.82%) \| Like=-2.23..-0.00 [-1213.2190..-0.0010] \| it/evals=1201/6953 eff=38.5257% N=265 Z=-13.4(13.72%) \| Like=-1.98..-0.00 [-1213.2190..-0.0010] \| it/evals=1242/6953 eff=39.7775% N=265 Z=-13.2(16.30%) \| Like=-1.81..-0.00 [-1213.2190..-0.0010] \| it/evals=1266/6953 eff=40.4729% N=265 Z=-13.1(18.13%) \| Like=-1.74..-0.00 [-1213.2190..-0.0010] \| it/evals=1284/6953 eff=41.3074% N=265 Z=-12.9(20.82%) \| Like=-1.58..-0.00 [-1213.2190..-0.0010] \| it/evals=1308/6953 eff=42.0028% N=265 Z=-12.9(21.53%) \| Like=-1.55..-0.00 [-1213.2190..-0.0010] \| it/evals=1314/6953 eff=42.1419% N=265 Z=-12.8(25.46%) \| Like=-1.39..-0.00 [-1213.2190..-0.0010] \| it/evals=1344/6953 eff=42.9764% N=265 Z=-12.6(28.66%) \| Like=-1.24..-0.00 [-1213.2190..-0.0010] \| it/evals=1368/6959 eff=43.3103% N=265 Z=-12.5(32.47%) \| Like=-1.10..-0.00 [-1213.2190..-0.0010] \| it/evals=1396/7064 eff=38.3133% N=265 Z=-12.5(33.66%) \| Like=-1.07..-0.00 [-1213.2190..-0.0010] \| it/evals=1404/7064 eff=38.7952% N=265 Z=-12.5(34.46%) \| Like=-1.04..-0.00 [-1213.2190..-0.0010] \| it/evals=1410/7064 eff=39.1566% N=265 Z=-12.4(35.32%) \| Like=-1.01..-0.00 [-1213.2190..-0.0010] \| it/evals=1416/7064 eff=39.3976% N=265 Z=-12.4(37.79%) \| Like=-0.93..-0.00 [-1213.2190..-0.0010] \| it/evals=1434/7064 eff=40.1205% N=265 Z=-12.3(40.87%) \| Like=-0.83..-0.00 [-1213.2190..-0.0010] \| it/evals=1458/7064 eff=40.8434% N=265 Z=-12.2(44.28%) \| Like=-0.75..-0.00 [-1213.2190..-0.0010] \| it/evals=1482/7064 eff=41.4458% N=265 Z=-12.1(49.36%) \| Like=-0.64..-0.00 [-1213.2190..-0.0010] \| it/evals=1518/7064 eff=42.1687% N=265 Z=-12.1(50.12%) \| Like=-0.63..-0.00 [-1213.2190..-0.0010] \| it/evals=1524/7064 eff=42.5301% N=265 Z=-12.1(51.75%) \| Like=-0.60..-0.00 [-1213.2190..-0.0010] \| it/evals=1536/7064 eff=43.0120% N=265 Z=-12.0(52.52%) \| Like=-0.59..-0.00 [-1213.2190..-0.0010] \| it/evals=1542/7064 eff=43.3735% N=265 Z=-11.9(58.70%) \| Like=-0.49..-0.00 [-1213.2190..-0.0010] \| it/evals=1590/7064 eff=44.9398% N=265 Z=-11.9(60.82%) \| Like=-0.46..-0.00 [-1213.2190..-0.0010] \| it/evals=1608/7064 eff=45.0602% N=265 Z=-11.9(61.54%) \| Like=-0.44..-0.00 [-1213.2190..-0.0010] \| it/evals=1614/7177 eff=39.8727% N=265 Z=-11.8(64.39%) \| Like=-0.40..-0.00 [-1213.2190..-0.0010] \| it/evals=1640/7177 eff=40.1909% N=265 Z=-11.7(72.06%) \| Like=-0.29..-0.00 [-1213.2190..-0.0010] \| it/evals=1716/7177 eff=42.0997% N=265 Z=-11.7(72.61%) \| Like=-0.29..-0.00 [-1213.2190..-0.0010] \| it/evals=1722/7177 eff=42.3118% N=265 Z=-11.7(73.15%) \| Like=-0.28..-0.00 [-1213.2190..-0.0010] \| it/evals=1728/7177 eff=42.5239% N=265 Z=-11.7(74.69%) \| Like=-0.27..-0.00 [-1213.2190..-0.0010] \| it/evals=1746/7177 eff=42.9480% N=265 Z=-11.7(75.66%) \| Like=-0.26..-0.00 [-1213.2190..-0.0010] \| it/evals=1758/7177 eff=43.2662% N=265 Z=-11.7(75.91%) \| Like=-0.25..-0.00 [-1213.2190..-0.0010] \| it/evals=1761/7177 eff=43.3722% N=265 Z=-11.7(76.14%) \| Like=-0.25..-0.00 [-1213.2190..-0.0010] \| it/evals=1764/7177 eff=43.5843% N=265 Z=-11.7(76.60%) \| Like=-0.24..-0.00 [-1213.2190..-0.0010] \| it/evals=1770/7177 eff=43.7964% N=265 Z=-11.7(77.50%) \| Like=-0.23..-0.00 [-1213.2190..-0.0010] \| it/evals=1782/7177 eff=44.1145% N=265 Z=-11.6(80.50%) \| Like=-0.20..-0.00 [-1213.2190..-0.0010] \| it/evals=1824/7289 eff=40.8531% N=265 Z=-11.6(81.68%) \| Like=-0.18..-0.00 [-1213.2190..-0.0010] \| it/evals=1842/7289 eff=41.3270% N=265 Z=-11.6(82.76%) \| Like=-0.18..-0.00 [-1213.2190..-0.0010] \| it/evals=1860/7289 eff=41.6114% N=265 Z=-11.6(83.96%) \| Like=-0.16..-0.00 [-1213.2190..-0.0010] \| it/evals=1881/7289 eff=42.2749% N=265 Z=-11.6(84.79%) \| Like=-0.15..-0.00 [-1213.2190..-0.0010] \| it/evals=1896/7289 eff=42.5592% N=265 Z=-11.6(85.10%) \| Like=-0.15..-0.00 [-1213.2190..-0.0010] \| it/evals=1902/7289 eff=42.8436% N=265 Z=-11.6(85.42%) \| Like=-0.15..-0.00 [-1213.2190..-0.0010] \| it/evals=1908/7289 eff=42.9384% N=265 Z=-11.5(86.02%) \| Like=-0.14..-0.00 [-1213.2190..-0.0010] \| it/evals=1920/7289 eff=43.4123% N=265 Z=-11.5(87.19%) \| Like=-0.12..-0.00 [-1213.2190..-0.0010] \| it/evals=1945/7289 eff=43.6967% N=265 Z=-11.5(87.68%) \| Like=-0.12..-0.00 [-1213.2190..-0.0010] \| it/evals=1956/7289 eff=44.0758% N=265 Z=-11.5(89.16%) \| Like=-0.11..-0.00 [-1213.2190..-0.0010] \| it/evals=1992/7299 eff=44.6948% N=265 Z=-11.5(89.39%) \| Like=-0.10..-0.00 [-1213.2190..-0.0010] \| it/evals=1998/7314 eff=44.2593% N=265 Z=-11.5(89.61%) \| Like=-0.10..-0.00 [-1213.2190..-0.0010] \| it/evals=2004/7314 eff=44.5370% N=265 Z=-11.5(89.76%) \| Like=-0.10..-0.00 [-1213.2190..-0.0010] \| it/evals=2008/7314 eff=44.6296% N=265 Z=-11.5(90.87%) \| Like=-0.09..-0.00 [-1213.2190..-0.0010] \| it/evals=2040/7314 eff=45.2778% N=265 Z=-11.5(91.75%) \| Like=-0.08..-0.00 [-1213.2190..-0.0010] \| it/evals=2068/7331 eff=45.1231% N=265 Z=-11.5(91.81%) \| Like=-0.08..-0.00 [-1213.2190..-0.0010] \| it/evals=2070/7331 eff=45.2142% N=265 Z=-11.5(91.98%) \| Like=-0.08..-0.00 [-1213.2190..-0.0010] \| it/evals=2076/7459 eff=40.7347% N=265 Z=-11.5(92.82%) \| Like=-0.07..-0.00 [-1213.2190..-0.0010] \| it/evals=2106/7459 eff=41.3061% N=265 Z=-11.5(93.27%) \| Like=-0.06..-0.00 [-1213.2190..-0.0010] \| it/evals=2124/7459 eff=41.9592% N=265 Z=-11.5(93.97%) \| Like=-0.06..-0.00 [-1213.2190..-0.0010] \| it/evals=2154/7459 eff=42.8571% N=265 Z=-11.5(94.74%) \| Like=-0.05..-0.00 [-1213.2190..-0.0010] \| it/evals=2191/7459 eff=43.3469% N=265 Z=-11.4(95.27%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=2220/7459 eff=44.0816% N=265 Z=-11.4(95.38%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=2226/7459 eff=44.1633% N=265 Z=-11.4(95.80%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=2252/7459 eff=44.6531% N=265 Z=-11.4(95.86%) \| Like=-0.04..-0.00 [-1213.2190..-0.0010] \| it/evals=2256/7459 eff=44.8163% N=265 Z=-11.4(95.95%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=2262/7471 eff=44.6241% N=265 Z=-11.4(96.61%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=2310/7471 eff=45.3517% N=265 Z=-11.4(96.83%) \| Like=-0.03..-0.00 [-1213.2190..-0.0010] \| it/evals=2328/7484 eff=45.3600% N=265 Z=-11.4(97.38%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2379/7503 eff=45.4689% N=265 Z=-11.4(97.52%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2394/7515 eff=45.2771% N=265 Z=-11.4(97.58%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2400/7515 eff=45.4333% N=265 Z=-11.4(97.63%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2406/7515 eff=45.7455% N=265 Z=-11.4(97.74%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2418/7519 eff=45.8366% N=265 Z=-11.4(97.79%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2424/7525 eff=45.9334% N=265 Z=-11.4(97.84%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2430/7534 eff=45.7692% N=265 Z=-11.4(97.93%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2442/7534 eff=46.0769% N=265 Z=-11.4(98.06%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2460/7551 eff=45.7859% N=265 Z=-11.4(98.15%) \| Like=-0.02..-0.00 [-1213.2190..-0.0010] \| it/evals=2472/7551 eff=45.8618% N=265 Z=-11.4(98.42%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2514/7565 eff=45.8302% N=265 Z=-11.4(98.49%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2526/7573 eff=45.9298% N=265 Z=-11.4(98.55%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2538/7573 eff=46.0792% N=265 Z=-11.4(98.59%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2544/7585 eff=45.8919% N=265 Z=-11.4(98.74%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2575/7600 eff=45.9736% N=265 Z=-11.4(98.79%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2586/7707 eff=42.8377% N=265 Z=-11.4(98.97%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2628/7707 eff=43.6524% N=265 Z=-11.4(99.01%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2640/7707 eff=44.1276% N=265 Z=-11.4(99.06%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2652/7707 eff=44.2634% N=265 Z=-11.4(99.10%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2664/7707 eff=44.5350% N=265 Z=-11.4(99.12%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2670/7707 eff=44.8065% N=265 Z=-11.4(99.18%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2688/7707 eff=45.2817% N=265 Z=-11.4(99.20%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2697/7707 eff=45.3496% N=265 Z=-11.4(99.23%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2706/7707 eff=45.5533% N=265 Z=-11.4(99.25%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2712/7707 eff=45.6212% N=265 Z=-11.4(99.28%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2724/7707 eff=45.8927% N=265 Z=-11.4(99.43%) \| Like=-0.01..-0.00 [-1213.2190..-0.0010] \| it/evals=2784/7815 eff=43.5800% N=265 Z=-11.4(99.53%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2836/7815 eff=44.4655% N=265 Z=-11.4(99.56%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2856/7815 eff=44.8450% N=265 Z=-11.4(99.58%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2868/7815 eff=45.1613% N=265 Z=-11.4(99.61%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2886/7815 eff=45.6673% N=265 Z=-11.4(99.63%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2900/7815 eff=46.1101% N=265 Z=-11.4(99.64%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2904/7815 eff=46.1733% N=265 Z=-11.4(99.68%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2940/7915 eff=44.0214% N=265 Z=-11.4(99.70%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2958/7915 eff=44.4378% N=265 Z=-11.4(99.70%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2960/7915 eff=44.4973% N=265 Z=-11.4(99.72%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2970/7915 eff=44.6758% N=265 Z=-11.4(99.74%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=2994/7915 eff=44.9137% N=265 Z=-11.4(99.76%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3020/7915 eff=45.0922% N=265 Z=-11.4(99.77%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3024/7915 eff=45.2112% N=265 Z=-11.4(99.77%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3030/7915 eff=45.3302% N=265 Z=-11.4(99.78%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3036/7915 eff=45.4491% N=265 Z=-11.4(99.81%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3082/7915 eff=46.2225% N=265 Z=-11.4(99.81%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3084/7915 eff=46.3415% N=265 Z=-11.4(99.82%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3096/7915 eff=46.5794% N=265 Z=-11.4(99.83%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3102/8043 eff=43.5047% N=265 Z=-11.4(99.83%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3114/8043 eff=43.6153% N=265 Z=-11.4(99.85%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3132/8043 eff=44.0575% N=265 Z=-11.4(99.85%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3142/8043 eff=44.2233% N=265 Z=-11.4(99.85%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3144/8043 eff=44.2786% N=265 Z=-11.4(99.86%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3156/8043 eff=44.3892% N=265 Z=-11.4(99.86%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3162/8043 eff=44.5550% N=265 Z=-11.4(99.87%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3186/8043 eff=44.7761% N=265 Z=-11.4(99.88%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3192/8043 eff=44.9420% N=265 Z=-11.4(99.88%) \| Like=-0.00..-0.00 [-1213.2190..-0.0010] \| it/evals=3203/8043 eff=45.1078% N=265 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 8043 [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. {'logzerr': 0.9374094861051898, 'logzerr_tail': 0.0011725337660379864, 'logzerr_bs': 0.9374087527885386, 'logzerr_single': 0.40351303854783166} running again for logz [ultranest] To achieve the desired logz accuracy, min_num_live_points was increased to 317 [ultranest] Widening roots to 317 live points (have 64 already) ... [ultranest] Sampling 253 live points from prior ... Z=-inf(0.00%) \| Like=-241488.71..-3.82 [-241488.7072..-82400.8396] \| it/evals=0/8424 eff=0.0000% N=317 Z=-162015.1(0.00%) \| Like=-161448.65..-3.82 [-241488.7072..-82400.8396] \| it/evals=32/8424 eff=23.4375% N=317 Z=-131996.6(0.00%) \| Like=-131605.67..-3.82 [-241488.7072..-82400.8396] \| it/evals=64/8424 eff=47.6562% N=317 Z=-128725.2(0.00%) \| Like=-128075.71..-3.82 [-241488.7072..-82400.8396] \| it/evals=71/8424 eff=51.5625% N=317 Z=-116039.8(0.00%) \| Like=-114669.88..-3.82 [-241488.7072..-82400.8396] \| it/evals=96/8424 eff=67.1875% N=317 Z=-99426.6(0.00%) \| Like=-98932.41..-3.82 [-241488.7072..-82400.8396] \| it/evals=142/8532 eff=54.6610% N=317 Z=-94469.9(0.00%) \| Like=-94083.98..-3.82 [-241488.7072..-82400.8396] \| it/evals=160/8532 eff=61.0169% N=317 Z=-87325.6(0.00%) \| Like=-86803.89..-3.82 [-241488.7072..-82400.8396] \| it/evals=192/8532 eff=72.0339% N=317 Z=-82682.4(0.00%) \| Like=-82549.78..-3.82 [-241488.7072..-82400.8396] \| it/evals=213/8532 eff=80.0847% N=317 Z=-80003.6(0.00%) \| Like=-79785.50..-3.82 [-82217.8876..-39297.2246] \| it/evals=224/8618 eff=61.1801% N=317 Z=-70498.5(0.00%) \| Like=-70003.16..-3.82 [-82217.8876..-39297.2246] \| it/evals=256/8618 eff=68.9441% N=317 Z=-64668.8(0.00%) \| Like=-64418.55..-3.82 [-82217.8876..-39297.2246] \| it/evals=284/8618 eff=75.7764% N=317 Z=-63638.8(0.00%) \| Like=-63331.41..-3.82 [-82217.8876..-39297.2246] \| it/evals=288/8690 eff=62.9442% N=317 Z=-58374.9(0.00%) \| Like=-58204.04..-3.82 [-82217.8876..-39297.2246] \| it/evals=320/8690 eff=69.0355% N=317 Z=-53117.7(0.00%) \| Like=-53020.86..-3.82 [-82217.8876..-39297.2246] \| it/evals=352/8751 eff=65.7143% N=317 Z=-52754.9(0.00%) \| Like=-52549.25..-3.82 [-82217.8876..-39297.2246] \| it/evals=356/8751 eff=66.3736% N=317 Z=-46729.1(0.00%) \| Like=-46556.06..-3.82 [-82217.8876..-39297.2246] \| it/evals=384/8795 eff=65.9319% N=317 Z=-41641.5(0.00%) \| Like=-41619.23..-3.82 [-82217.8876..-39297.2246] \| it/evals=416/8795 eff=69.9399% N=317 Z=-40285.8(0.00%) \| Like=-40055.45..-3.82 [-82217.8876..-39297.2246] \| it/evals=427/8847 eff=64.9728% N=317 Z=-33470.5(0.00%) \| Like=-33458.45..-3.82 [-39226.8744..-18825.6538] \| it/evals=480/8888 eff=67.5676% N=317 Z=-31546.8(0.00%) \| Like=-31396.11..-3.82 [-39226.8744..-18825.6538] \| it/evals=498/8888 eff=70.4392% N=317 Z=-27877.5(0.00%) \| Like=-27864.29..-3.82 [-39226.8744..-18825.6538] \| it/evals=544/8959 eff=68.0241% N=317 Z=-25189.2(0.00%) \| Like=-25077.39..-3.82 [-39226.8744..-18825.6538] \| it/evals=569/8997 eff=67.4750% N=317 Z=-22115.6(0.00%) \| Like=-22086.43..-3.82 [-39226.8744..-18825.6538] \| it/evals=608/9022 eff=69.6970% N=317 Z=-20053.1(0.00%) \| Like=-20041.42..-3.82 [-39226.8744..-18825.6538] \| it/evals=641/9077 eff=68.7580% N=317 Z=-18174.9(0.00%) \| Like=-18074.66..-3.82 [-18818.8699..-8802.8925] \| it/evals=672/9117 eff=68.5749% N=317 Z=-16363.8(0.00%) \| Like=-16329.53..-3.82 [-18818.8699..-8802.8925] \| it/evals=704/9134 eff=70.2864% N=317 Z=-15518.8(0.00%) \| Like=-15470.57..-3.82 [-18818.8699..-8802.8925] \| it/evals=713/9161 eff=68.9017% N=317 Z=-14427.6(0.00%) \| Like=-14415.73..-3.82 [-18818.8699..-8802.8925] \| it/evals=736/9170 eff=70.0229% N=317 Z=-12734.3(0.00%) \| Like=-12708.83..-3.82 [-18818.8699..-8802.8925] \| it/evals=768/9213 eff=69.4656% N=317 Z=-12142.6(0.00%) \| Like=-12106.51..-3.82 [-18818.8699..-8802.8925] \| it/evals=784/9229 eff=69.9893% N=317 Z=-10709.4(0.00%) \| Like=-10695.44..-3.82 [-18818.8699..-8802.8925] \| it/evals=832/9277 eff=70.2345% N=317 Z=-9925.9(0.00%) \| Like=-9864.47..-3.82 [-18818.8699..-8802.8925] \| it/evals=855/9313 eff=69.9115% N=317 Z=-7688.6(0.00%) \| Like=-7673.33..-3.82 [-8762.6068..-4923.2104] \| it/evals=926/9382 eff=70.5341% N=317 Z=-7668.8(0.00%) \| Like=-7628.51..-3.82 [-8762.6068..-4923.2104] \| it/evals=928/9388 eff=70.3297% N=317 Z=-7017.7(0.00%) \| Like=-6989.00..-3.82 [-8762.6068..-4923.2104] \| it/evals=960/9419 eff=70.5254% N=317 Z=-6547.7(0.00%) \| Like=-6517.63..-3.82 [-8762.6068..-4923.2104] \| it/evals=992/9448 eff=71.0069% N=317 Z=-6493.6(0.00%) \| Like=-6475.15..-3.82 [-8762.6068..-4923.2104] \| it/evals=997/9452 eff=71.0208% N=317 Z=-5491.7(0.00%) \| Like=-5474.86..-3.82 [-8762.6068..-4923.2104] \| it/evals=1056/9527 eff=70.4305% N=317 Z=-5276.7(0.00%) \| Like=-5247.51..-3.82 [-8762.6068..-4923.2104] \| it/evals=1068/9541 eff=70.2811% N=317 Z=-5002.7(0.00%) \| Like=-4977.41..-3.82 [-8762.6068..-4923.2104] \| it/evals=1088/9551 eff=70.8367% N=317 Z=-4662.2(0.00%) \| Like=-4631.19..-3.82 [-4921.7374..-2418.6487] \| it/evals=1120/9589 eff=70.7657% N=317 Z=-4455.0(0.00%) \| Like=-4442.88..-3.82 [-4921.7374..-2418.6487] \| it/evals=1139/9614 eff=70.6373% N=317 Z=-4252.7(0.00%) \| Like=-4222.67..-3.82 [-4921.7374..-2418.6487] \| it/evals=1152/9630 eff=70.6147% N=317 Z=-3824.9(0.00%) \| Like=-3815.29..-3.82 [-4921.7374..-2418.6487] \| it/evals=1184/9667 eff=70.6783% N=317 Z=-3493.1(0.00%) \| Like=-3476.58..-3.82 [-4921.7374..-2418.6487] \| it/evals=1210/9705 eff=70.3336% N=317 Z=-3443.5(0.00%) \| Like=-3429.82..-3.82 [-4921.7374..-2418.6487] \| it/evals=1216/9714 eff=70.2398% N=317 Z=-3058.7(0.00%) \| Like=-3048.73..-3.82 [-4921.7374..-2418.6487] \| it/evals=1248/9747 eff=70.5031% N=317 Z=-2809.0(0.00%) \| Like=-2784.85..-3.82 [-4921.7374..-2418.6487] \| it/evals=1280/9785 eff=70.3156% N=317 Z=-2794.6(0.00%) \| Like=-2783.83..-3.82 [-4921.7374..-2418.6487] \| it/evals=1281/9785 eff=70.3828% N=317 Z=-2506.5(0.00%) \| Like=-2479.05..-3.82 [-4921.7374..-2418.6487] \| it/evals=1312/9816 eff=70.5921% N=317 Z=-2237.6(0.00%) \| Like=-2220.11..-3.82 [-2396.7422..-1225.8972] \| it/evals=1344/9850 eff=70.5920% N=317 Z=-2146.6(0.00%) \| Like=-2126.85..-3.82 [-2396.7422..-1225.8972] \| it/evals=1352/9860 eff=70.5882% N=317 Z=-2008.7(0.00%) \| Like=-1994.21..-3.82 [-2396.7422..-1225.8972] \| it/evals=1376/9995 eff=66.0977% N=317 Z=-1742.5(0.00%) \| Like=-1725.08..-3.82 [-2396.7422..-1225.8972] \| it/evals=1423/9995 eff=68.3343% N=317 Z=-1655.1(0.00%) \| Like=-1637.97..-3.82 [-2396.7422..-1225.8972] \| it/evals=1440/9995 eff=69.2172% N=317 Z=-1484.1(0.00%) \| Like=-1470.82..-3.82 [-2396.7422..-1225.8972] \| it/evals=1472/10127 eff=65.6472% N=317 Z=-1400.3(0.00%) \| Like=-1388.39..-3.82 [-2396.7422..-1225.8972] \| it/evals=1494/10127 eff=66.5756% N=317 Z=-1345.5(0.00%) \| Like=-1329.96..-3.82 [-2396.7422..-1225.8972] \| it/evals=1504/10127 eff=67.0672% N=317 Z=-1202.1(0.00%) \| Like=-1190.79..-3.82 [-1218.4285..-623.5609] \| it/evals=1541/10127 eff=68.5418% N=317 Z=-1105.5(0.00%) \| Like=-1094.12..-3.82 [-1218.4285..-623.5609] \| it/evals=1568/10127 eff=69.6341% N=317 Z=-1002.7(0.00%) \| Like=-991.38..-3.82 [-1218.4285..-623.5609] \| it/evals=1600/10271 eff=65.6709% N=317 Z=-912.7(0.00%) \| Like=-897.72..-1.26 [-1218.4285..-623.5609] \| it/evals=1632/10271 eff=66.8354% N=317 Z=-807.7(0.00%) \| Like=-795.37..-1.26 [-1218.4285..-623.5609] \| it/evals=1671/10271 eff=68.4557% N=317 Z=-749.5(0.00%) \| Like=-730.32..-1.26 [-1218.4285..-623.5609] \| it/evals=1696/10399 eff=65.2877% N=317 Z=-697.8(0.00%) \| Like=-683.69..-1.26 [-1218.4285..-623.5609] \| it/evals=1728/10399 eff=66.3814% N=317 Z=-673.3(0.00%) \| Like=-661.52..-1.26 [-1218.4285..-623.5609] \| it/evals=1742/10399 eff=66.9044% N=317 Z=-627.0(0.00%) \| Like=-609.67..-1.26 [-622.7094..-322.7858] \| it/evals=1760/10399 eff=67.5226% N=317 Z=-581.5(0.00%) \| Like=-564.18..-1.26 [-622.7094..-322.7858] \| it/evals=1792/10399 eff=68.7589% N=317 Z=-540.4(0.00%) \| Like=-527.04..-1.26 [-622.7094..-322.7858] \| it/evals=1813/10527 eff=65.7104% N=317 Z=-517.1(0.00%) \| Like=-505.17..-1.26 [-622.7094..-322.7858] \| it/evals=1824/10527 eff=66.0690% N=317 Z=-465.7(0.00%) \| Like=-452.56..-1.26 [-622.7094..-322.7858] \| it/evals=1856/10527 eff=67.2792% N=317 Z=-427.8(0.00%) \| Like=-414.10..-1.26 [-622.7094..-322.7858] \| it/evals=1884/10529 eff=68.2490% N=317 Z=-414.8(0.00%) \| Like=-401.25..-1.26 [-622.7094..-322.7858] \| it/evals=1888/10532 eff=68.2469% N=317 Z=-381.3(0.00%) \| Like=-368.88..-1.26 [-622.7094..-322.7858] \| it/evals=1920/10663 eff=65.5260% N=317 Z=-348.6(0.00%) \| Like=-336.76..-1.26 [-622.7094..-322.7858] \| it/evals=1955/10663 eff=66.7089% N=317 Z=-318.9(0.00%) \| Like=-306.73..-1.26 [-321.7020..-141.7603] \| it/evals=1984/10663 eff=67.5539% N=317 Z=-288.9(0.00%) \| Like=-277.25..-1.26 [-321.7020..-141.7603] \| it/evals=2016/10791 eff=65.1703% N=317 Z=-277.6(0.00%) \| Like=-264.93..-1.26 [-321.7020..-141.7603] \| it/evals=2026/10791 eff=65.4910% N=317 Z=-261.1(0.00%) \| Like=-248.44..-1.26 [-321.7020..-141.7603] \| it/evals=2048/10791 eff=66.2124% N=317 Z=-230.3(0.00%) \| Like=-217.48..-1.26 [-321.7020..-141.7603] \| it/evals=2080/10791 eff=67.0541% N=317 Z=-205.0(0.00%) \| Like=-193.36..-1.26 [-321.7020..-141.7603] \| it/evals=2112/10919 eff=64.6969% N=317 Z=-181.2(0.00%) \| Like=-169.41..-1.26 [-321.7020..-141.7603] \| it/evals=2155/10919 eff=65.8788% N=317 Z=-167.4(0.00%) \| Like=-155.64..-1.26 [-321.7020..-141.7603] \| it/evals=2176/10919 eff=66.4506% N=317 Z=-146.5(0.00%) \| Like=-134.15..-1.26 [-141.7043..-68.9141] \| it/evals=2224/11047 eff=64.5947% N=317 Z=-142.0(0.00%) \| Like=-129.80..-1.26 [-141.7043..-68.9141] \| it/evals=2240/11047 eff=65.0309% N=317 Z=-127.8(0.00%) \| Like=-115.79..-0.15 [-141.7043..-68.9141] \| it/evals=2270/11047 eff=65.7943% N=317 Z=-127.2(0.00%) \| Like=-115.56..-0.15 [-141.7043..-68.9141] \| it/evals=2272/11047 eff=65.8306% N=317 Z=-122.3(0.00%) \| Like=-110.14..-0.15 [-141.7043..-68.9141] \| it/evals=2286/11047 eff=66.0851% N=317 Z=-117.7(0.00%) \| Like=-105.62..-0.15 [-141.7043..-68.9141] \| it/evals=2306/11047 eff=66.4122% N=317 Z=-110.3(0.00%) \| Like=-97.73..-0.15 [-141.7043..-68.9141] \| it/evals=2324/11047 eff=66.7394% N=317 Z=-105.2(0.00%) \| Like=-93.15..-0.15 [-141.7043..-68.9141] \| it/evals=2336/11047 eff=66.9575% N=317 Z=-101.7(0.00%) \| Like=-89.63..-0.15 [-141.7043..-68.9141] \| it/evals=2345/11047 eff=67.0302% N=317 Z=-93.6(0.00%) \| Like=-81.94..-0.15 [-141.7043..-68.9141] \| it/evals=2368/11175 eff=64.7100% N=317 Z=-85.0(0.00%) \| Like=-72.89..-0.15 [-141.7043..-68.9141] \| it/evals=2400/11175 eff=65.5783% N=317 Z=-81.8(0.00%) \| Like=-70.23..-0.15 [-141.7043..-68.9141] \| it/evals=2416/11175 eff=65.9951% N=317 Z=-80.3(0.00%) \| Like=-68.43..-0.15 [-68.4891..-30.7962] \| it/evals=2424/11175 eff=66.0993% N=317 Z=-78.2(0.00%) \| Like=-66.18..-0.15 [-68.4891..-30.7962] \| it/evals=2436/11175 eff=66.2730% N=317 Z=-75.3(0.00%) \| Like=-63.38..-0.15 [-68.4891..-30.7962] \| it/evals=2451/11175 eff=66.4814% N=317 Z=-73.4(0.00%) \| Like=-61.04..-0.15 [-68.4891..-30.7962] \| it/evals=2458/11175 eff=66.5162% N=317 Z=-72.1(0.00%) \| Like=-60.41..-0.15 [-68.4891..-30.7962] \| it/evals=2464/11175 eff=66.7246% N=317 Z=-66.7(0.00%) \| Like=-54.78..-0.15 [-68.4891..-30.7962] \| it/evals=2498/11303 eff=64.6492% N=317 Z=-62.5(0.00%) \| Like=-50.15..-0.15 [-68.4891..-30.7962] \| it/evals=2515/11303 eff=64.8154% N=317 Z=-60.5(0.00%) \| Like=-48.80..-0.15 [-68.4891..-30.7962] \| it/evals=2525/11303 eff=64.9152% N=317 Z=-60.1(0.00%) \| Like=-48.34..-0.15 [-68.4891..-30.7962] \| it/evals=2528/11303 eff=64.9817% N=317 Z=-56.5(0.00%) \| Like=-44.54..-0.15 [-68.4891..-30.7962] \| it/evals=2553/11303 eff=65.1480% N=317 Z=-47.1(0.00%) \| Like=-35.03..-0.15 [-68.4891..-30.7962] \| it/evals=2609/11303 eff=65.8464% N=317 Z=-45.3(0.00%) \| Like=-33.25..-0.15 [-68.4891..-30.7962] \| it/evals=2626/11303 eff=66.1124% N=317 Z=-43.2(0.00%) \| Like=-30.78..-0.15 [-30.7776..-15.7338] \| it/evals=2643/11303 eff=66.2787% N=317 Z=-41.6(0.00%) \| Like=-29.57..-0.15 [-30.7776..-15.7338] \| it/evals=2655/11303 eff=66.3452% N=317 Z=-41.5(0.00%) \| Like=-29.50..-0.15 [-30.7776..-15.7338] \| it/evals=2656/11303 eff=66.3785% N=317 Z=-38.4(0.00%) \| Like=-26.58..-0.15 [-30.7776..-15.7338] \| it/evals=2688/11431 eff=63.8915% N=317 Z=-37.1(0.00%) \| Like=-25.20..-0.15 [-30.7776..-15.7338] \| it/evals=2704/11431 eff=63.9872% N=317 Z=-35.3(0.00%) \| Like=-23.47..-0.15 [-30.7776..-15.7338] \| it/evals=2725/11431 eff=64.0510% N=317 Z=-34.4(0.00%) \| Like=-22.42..-0.15 [-30.7776..-15.7338] \| it/evals=2734/11431 eff=64.0829% N=317 Z=-33.3(0.00%) \| Like=-21.69..-0.15 [-30.7776..-15.7338] \| it/evals=2749/11431 eff=64.2105% N=317 Z=-33.2(0.00%) \| Like=-21.59..-0.15 [-30.7776..-15.7338] \| it/evals=2752/11431 eff=64.3062% N=317 Z=-31.8(0.00%) \| Like=-20.13..-0.15 [-30.7776..-15.7338] \| it/evals=2776/11431 eff=64.3381% N=317 Z=-31.3(0.00%) \| Like=-19.57..-0.15 [-30.7776..-15.7338] \| it/evals=2784/11431 eff=64.4657% N=317 Z=-29.6(0.00%) \| Like=-17.93..-0.15 [-30.7776..-15.7338] \| it/evals=2814/11431 eff=64.7528% N=317 Z=-29.5(0.00%) \| Like=-17.84..-0.15 [-30.7776..-15.7338] \| it/evals=2816/11431 eff=64.8166% N=317 Z=-25.4(0.00%) \| Like=-13.64..-0.15 [-15.6805..-7.9399] \| it/evals=2919/11431 eff=65.0080% N=317 Z=-24.9(0.00%) \| Like=-13.20..-0.15 [-15.6805..-7.9399] \| it/evals=2935/11431 eff=65.0399% N=317 Z=-18.8(0.10%) \| Like=-6.95..-0.15 [-7.9116..-3.8309] \| it/evals=3143/11431 eff=65.1994% N=317 Z=-17.4(0.37%) \| Like=-5.92..-0.15 [-7.9116..-3.8309] \| it/evals=3217/11431 eff=65.4864% N=317 Z=-17.2(0.44%) \| Like=-5.61..-0.15 [-7.9116..-3.8309] \| it/evals=3232/11559 eff=63.0401% N=317 Z=-16.3(1.05%) \| Like=-4.48..-0.15 [-7.9116..-3.8309] \| it/evals=3292/11559 eff=63.2240% N=317 Z=-15.4(2.77%) \| Like=-3.48..-0.15 [-3.8177..-2.4714] \| it/evals=3363/11559 eff=63.4998% N=317 Z=-15.0(3.92%) \| Like=-3.14..-0.15 [-3.8177..-2.4714] \| it/evals=3392/11559 eff=63.7144% N=317 Z=-14.5(7.07%) \| Like=-2.61..-0.15 [-3.8177..-2.4714] \| it/evals=3453/11559 eff=63.8983% N=317 Z=-14.2(9.23%) \| Like=-2.31..-0.15 [-2.4600..-2.1293] \| it/evals=3488/11559 eff=64.1434% N=317 Z=-13.9(11.80%) \| Like=-2.11..-0.15 [-2.1230..-2.0268] \| it/evals=3520/11559 eff=64.4805% N=317 Z=-13.9(12.26%) \| Like=-2.10..-0.15 [-2.1230..-2.0268] \| it/evals=3525/11687 eff=62.1056% N=317 Z=-13.7(14.47%) \| Like=-2.00..-0.15 [-2.0266..-1.9746] \| it/evals=3552/11687 eff=62.2235% N=317 Z=-13.6(17.27%) \| Like=-1.81..-0.15 [-1.8111..-1.8053]\| it/evals=3584/11687 eff=62.4300% N=317 Z=-13.5(18.57%) \| Like=-1.76..-0.15 [-1.7615..-1.7597]\| it/evals=3600/11687 eff=62.4595% N=317 Z=-13.2(25.71%) \| Like=-1.42..-0.02 [-1.4249..-1.4230]\| it/evals=3672/11687 eff=62.8723% N=317 Z=-12.9(34.00%) \| Like=-1.08..-0.02 [-1.0809..-1.0800]\| it/evals=3745/11687 eff=63.1672% N=317 Z=-12.7(43.03%) \| Like=-0.81..-0.02 [-0.8056..-0.7950] \| it/evals=3825/11687 eff=63.5506% N=317 Z=-12.6(44.75%) \| Like=-0.75..-0.02 [-0.7524..-0.7519]\| it/evals=3840/11815 eff=61.3242% N=317 Z=-12.6(48.49%) \| Like=-0.68..-0.02 [-0.6754..-0.6735]\| it/evals=3872/11815 eff=61.5516% N=317 Z=-12.5(51.50%) \| Like=-0.62..-0.02 [-0.6219..-0.6213]\| it/evals=3898/11815 eff=61.6937% N=317 Z=-12.4(59.23%) \| Like=-0.49..-0.02 [-0.4913..-0.4911]\| it/evals=3971/11815 eff=62.0063% N=317 Z=-12.3(64.94%) \| Like=-0.40..-0.01 [-0.4028..-0.4027]\| it/evals=4032/11815 eff=62.3757% N=317 Z=-12.2(66.31%) \| Like=-0.39..-0.01 [-0.3886..-0.3884]\| it/evals=4047/11815 eff=62.4041% N=317 Z=-12.2(72.11%) \| Like=-0.31..-0.00 [-0.3051..-0.3033]\| it/evals=4119/11815 eff=62.8303% N=317 Z=-12.1(77.02%) \| Like=-0.25..-0.00 [-0.2471..-0.2470]\| it/evals=4190/11943 eff=60.8994% N=317 Z=-12.1(79.08%) \| Like=-0.22..-0.00 [-0.2192..-0.2183]\| it/evals=4224/11943 eff=61.0639% N=317 Z=-12.0(81.72%) \| Like=-0.19..-0.00 [-0.1877..-0.1873]\| it/evals=4271/11943 eff=61.2558% N=317 Z=-12.0(85.49%) \| Like=-0.15..-0.00 [-0.1473..-0.1470]\| it/evals=4351/11943 eff=61.5574% N=317 Z=-12.0(88.74%) \| Like=-0.11..-0.00 [-0.1102..-0.1092]\| it/evals=4437/11943 eff=61.8316% N=317 Z=-11.9(91.00%) \| Like=-0.09..-0.00 [-0.0883..-0.0882]\| it/evals=4512/12071 eff=60.0795% N=317 Z=-11.9(92.79%) \| Like=-0.07..-0.00 [-0.0703..-0.0698]\| it/evals=4585/12071 eff=60.3974% N=317 Z=-11.9(94.25%) \| Like=-0.05..-0.00 [-0.0538..-0.0534]\| it/evals=4659/12071 eff=60.7417% N=317 Z=-11.9(95.41%) \| Like=-0.04..-0.00 [-0.0407..-0.0405]\| it/evals=4732/12071 eff=61.1391% N=317 Z=-11.9(96.44%) \| Like=-0.03..-0.00 [-0.0317..-0.0317]\| it/evals=4814/12199 eff=59.4158% N=317 Z=-11.9(96.95%) \| Like=-0.03..-0.00 [-0.0274..-0.0273]\| it/evals=4864/12199 eff=59.6977% N=317 Z=-11.9(97.15%) \| Like=-0.03..-0.00 [-0.0252..-0.0252]\| it/evals=4886/12199 eff=59.8002% N=317 Z=-11.9(97.77%) \| Like=-0.02..-0.00 [-0.0197..-0.0196]\| it/evals=4965/12199 eff=59.9283% N=317 Z=-11.9(98.24%) \| Like=-0.02..-0.00 [-0.0157..-0.0155]\| it/evals=5041/12199 eff=60.1076% N=317 Z=-11.8(98.48%) \| Like=-0.01..-0.00 [-0.0132..-0.0132]\| it/evals=5088/12199 eff=60.3382% N=317 Z=-11.8(98.62%) \| Like=-0.01..-0.00 [-0.0116..-0.0116]\| it/evals=5118/12199 eff=60.4151% N=317 Z=-11.8(98.91%) \| Like=-0.01..-0.00 [-0.0096..-0.0095]\| it/evals=5193/12327 eff=58.7447% N=317 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 12327 logzerr in iteration 0 0.2196993183606724 [ultranest] logZ = -11.91 +- 0.1636 [ultranest] Effective samples strategy satisfied (ESS = 1275.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.33 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 684 minimum live points (dlogz from 0.14 to 0.39, need <0.1) [ultranest] logZ error budget: single: 0.20 bs:0.16 tail:0.00 total:0.16 required:<0.10 [ultranest] Widening roots to 684 live points (have 317 already) ... [ultranest] Sampling 367 live points from prior ... Z=-inf(0.00%) \| Like=-245997.63..-0.00 [-245997.6291..-81232.4708] \| it/evals=0/12822 eff=0.0000% N=684 Z=-187609.4(0.00%) \| Like=-186405.10..-0.00 [-245997.6291..-81232.4708] \| it/evals=32/12822 eff=12.5000% N=684 Z=-161455.3(0.00%) \| Like=-161381.59..-0.00 [-245997.6291..-81232.4708] \| it/evals=64/12822 eff=24.2188% N=684 Z=-126861.1(0.00%) \| Like=-126691.41..-0.00 [-245997.6291..-81232.4708] \| it/evals=153/12822 eff=60.1562% N=684 Z=-124993.8(0.00%) \| Like=-124623.45..-0.00 [-245997.6291..-81232.4708] \| it/evals=160/12822 eff=64.0625% N=684 Z=-117214.0(0.00%) \| Like=-116938.49..-0.00 [-245997.6291..-81232.4708] \| it/evals=192/12822 eff=75.7812% N=684 Z=-97355.7(0.00%) \| Like=-97219.05..-0.00 [-245997.6291..-81232.4708] \| it/evals=306/12936 eff=65.7025% N=684 Z=-95807.3(0.00%) \| Like=-95734.25..-0.00 [-245997.6291..-81232.4708] \| it/evals=320/12936 eff=68.1818% N=684 Z=-91971.2(0.00%) \| Like=-91886.49..-0.00 [-245997.6291..-81232.4708] \| it/evals=352/12936 eff=76.0331% N=684 Z=-82305.9(0.00%) \| Like=-82247.48..-0.00 [-245997.6291..-81232.4708] \| it/evals=448/13021 eff=70.6422% N=684 Z=-81427.2(0.00%) \| Like=-81363.91..-0.00 [-245997.6291..-81232.4708] \| it/evals=459/13021 eff=73.0887% N=684 Z=-64179.3(0.00%) \| Like=-64076.33..-0.00 [-81125.3031..-39471.8305] \| it/evals=613/13109 eff=78.7952% N=684 Z=-62083.5(0.00%) \| Like=-62055.51..-0.00 [-81125.3031..-39471.8305] \| it/evals=640/13167 eff=71.6702% N=684 Z=-55598.4(0.00%) \| Like=-55501.50..-0.00 [-81125.3031..-39471.8305] \| it/evals=704/13167 eff=77.8013% N=684 Z=-53118.4(0.00%) \| Like=-53083.22..-0.00 [-81125.3031..-39471.8305] \| it/evals=736/13227 eff=72.0450% N=684 Z=-51060.5(0.00%) \| Like=-50944.30..-0.00 [-81125.3031..-39471.8305] \| it/evals=766/13227 eff=75.4221% N=684 Z=-50898.5(0.00%) \| Like=-50831.91..-0.00 [-81125.3031..-39471.8305] \| it/evals=768/13227 eff=75.7974% N=684 Z=-46496.9(0.00%) \| Like=-46183.72..-0.00 [-81125.3031..-39471.8305] \| it/evals=832/13279 eff=76.4103% N=684 Z=-40286.5(0.00%) \| Like=-40211.90..-0.00 [-81125.3031..-39471.8305] \| it/evals=920/13362 eff=73.8024% N=684 Z=-39698.9(0.00%) \| Like=-39683.11..-0.00 [-81125.3031..-39471.8305] \| it/evals=928/13362 eff=74.4012% N=684 Z=-36753.0(0.00%) \| Like=-36476.24..-0.00 [-39431.9524..-20053.8866] \| it/evals=992/13401 eff=75.3890% N=684 Z=-32856.3(0.00%) \| Like=-32828.11..-0.00 [-39431.9524..-20053.8866] \| it/evals=1056/13440 eff=76.1394% N=684 Z=-32044.0(0.00%) \| Like=-32010.20..-0.00 [-39431.9524..-20053.8866] \| it/evals=1073/13481 eff=73.8247% N=684 Z=-31324.1(0.00%) \| Like=-31219.37..-0.00 [-39431.9524..-20053.8866] \| it/evals=1088/13481 eff=74.3329% N=684 Z=-28767.8(0.00%) \| Like=-28745.22..-0.00 [-39431.9524..-20053.8866] \| it/evals=1152/13510 eff=75.4902% N=684 Z=-27662.9(0.00%) \| Like=-27410.93..-0.00 [-39431.9524..-20053.8866] \| it/evals=1184/13538 eff=75.4739% N=684 Z=-26376.7(0.00%) \| Like=-26340.93..-0.00 [-39431.9524..-20053.8866] \| it/evals=1216/13571 eff=75.0285% N=684 Z=-25891.9(0.00%) \| Like=-25883.36..-0.00 [-39431.9524..-20053.8866] \| it/evals=1226/13571 eff=75.8267% N=684 Z=-23501.0(0.00%) \| Like=-23478.71..-0.00 [-39431.9524..-20053.8866] \| it/evals=1280/13599 eff=76.4641% N=684 Z=-20787.7(0.00%) \| Like=-20770.24..-0.00 [-39431.9524..-20053.8866] \| it/evals=1376/13676 eff=75.6619% N=684 Z=-20721.9(0.00%) \| Like=-20701.67..-0.00 [-39431.9524..-20053.8866] \| it/evals=1379/13676 eff=75.9674% N=684 Z=-17968.4(0.00%) \| Like=-17940.01..-0.00 [-20045.2935..-9311.7228] \| it/evals=1472/13748 eff=75.7116% N=684 Z=-17203.8(0.00%) \| Like=-17165.16..-0.00 [-20045.2935..-9311.7228] \| it/evals=1504/13774 eff=75.3704% N=684 Z=-16506.9(0.00%) \| Like=-16495.21..-0.00 [-20045.2935..-9311.7228] \| it/evals=1532/13787 eff=76.0293% N=684 Z=-16431.1(0.00%) \| Like=-16396.53..-0.00 [-20045.2935..-9311.7228] \| it/evals=1536/13801 eff=75.2484% N=684 Z=-15454.6(0.00%) \| Like=-15437.84..-0.00 [-20045.2935..-9311.7228] \| it/evals=1568/13824 eff=75.4867% N=684 Z=-14760.1(0.00%) \| Like=-14716.26..-0.00 [-20045.2935..-9311.7228] \| it/evals=1600/13839 eff=76.0699% N=684 Z=-13227.5(0.00%) \| Like=-13205.51..-0.00 [-20045.2935..-9311.7228] \| it/evals=1664/13896 eff=75.5408% N=684 Z=-12861.1(0.00%) \| Like=-12832.47..-0.00 [-20045.2935..-9311.7228] \| it/evals=1685/13913 eff=75.4717% N=684 Z=-12709.2(0.00%) \| Like=-12690.15..-0.00 [-20045.2935..-9311.7228] \| it/evals=1696/13921 eff=75.5501% N=684 Z=-12143.4(0.00%) \| Like=-12109.35..-0.00 [-20045.2935..-9311.7228] \| it/evals=1728/13946 eff=75.3994% N=684 Z=-11044.1(0.00%) \| Like=-11032.09..-0.00 [-20045.2935..-9311.7228] \| it/evals=1792/13986 eff=75.4644% N=684 Z=-10425.2(0.00%) \| Like=-10391.11..-0.00 [-20045.2935..-9311.7228] \| it/evals=1838/14017 eff=75.4346% N=684 Z=-9665.2(0.00%) \| Like=-9652.87..-0.00 [-20045.2935..-9311.7228] \| it/evals=1888/14056 eff=75.3304% N=684 Z=-9171.3(0.00%) \| Like=-9130.80..-0.00 [-9305.2933..-4646.4641] \| it/evals=1920/14074 eff=75.5797% N=684 Z=-8182.8(0.00%) \| Like=-8144.74..-0.00 [-9305.2933..-4646.4641] \| it/evals=1984/14128 eff=74.8257% N=684 Z=-8087.4(0.00%) \| Like=-8076.70..-0.00 [-9305.2933..-4646.4641] \| it/evals=1991/14128 eff=75.0349% N=684 Z=-7663.8(0.00%) \| Like=-7631.84..-0.00 [-9305.2933..-4646.4641] \| it/evals=2016/14143 eff=75.0863% N=684 Z=-7040.2(0.00%) \| Like=-7029.29..-0.00 [-9305.2933..-4646.4641] \| it/evals=2080/14182 eff=75.4032% N=684 Z=-6723.6(0.00%) \| Like=-6709.37..-0.00 [-9305.2933..-4646.4641] \| it/evals=2112/14197 eff=75.2495% N=684 Z=-6516.9(0.00%) \| Like=-6501.72..-0.00 [-9305.2933..-4646.4641] \| it/evals=2145/14227 eff=74.9511% N=684 Z=-5352.9(0.00%) \| Like=-5336.39..-0.00 [-9305.2933..-4646.4641] \| it/evals=2272/14299 eff=75.2648% N=684 Z=-5178.1(0.00%) \| Like=-5164.18..-0.00 [-9305.2933..-4646.4641] \| it/evals=2298/14310 eff=75.4950% N=684 Z=-4253.4(0.00%) \| Like=-4241.59..-0.00 [-4634.1264..-2467.0091] \| it/evals=2436/14398 eff=75.3521% N=684 Z=-4182.7(0.00%) \| Like=-4170.30..-0.00 [-4634.1264..-2467.0091] \| it/evals=2451/14407 eff=75.4816% N=684 Z=-4081.7(0.00%) \| Like=-4069.29..-0.00 [-4634.1264..-2467.0091] \| it/evals=2464/14416 eff=75.4355% N=684 Z=-3733.5(0.00%) \| Like=-3721.18..-0.00 [-4634.1264..-2467.0091] \| it/evals=2528/14459 eff=75.8074% N=684 Z=-3555.6(0.00%) \| Like=-3543.84..-0.00 [-4634.1264..-2467.0091] \| it/evals=2560/14483 eff=75.9083% N=684 Z=-3408.8(0.00%) \| Like=-3397.38..-0.00 [-4634.1264..-2467.0091] \| it/evals=2592/14504 eff=75.9116% N=684 Z=-3362.3(0.00%) \| Like=-3351.36..-0.00 [-4634.1264..-2467.0091] \| it/evals=2605/14516 eff=75.8507% N=684 Z=-3255.8(0.00%) \| Like=-3242.69..-0.00 [-4634.1264..-2467.0091] \| it/evals=2624/14527 eff=75.9411% N=684 Z=-3054.5(0.00%) \| Like=-3036.35..-0.00 [-4634.1264..-2467.0091] \| it/evals=2656/14546 eff=75.9179% N=684 Z=-2945.7(0.00%) \| Like=-2931.48..-0.00 [-4634.1264..-2467.0091] \| it/evals=2688/14577 eff=75.6240% N=684 Z=-2673.9(0.00%) \| Like=-2660.40..-0.00 [-4634.1264..-2467.0091] \| it/evals=2758/14631 eff=75.5292% N=684 Z=-2579.0(0.00%) \| Like=-2561.40..-0.00 [-4634.1264..-2467.0091] \| it/evals=2784/14652 eff=75.4341% N=684 Z=-2462.3(0.00%) \| Like=-2444.29..-0.00 [-2466.9117..-1268.6170] \| it/evals=2816/14675 eff=75.6689% N=684 Z=-2117.6(0.00%) \| Like=-2106.38..-0.00 [-2466.9117..-1268.6170] \| it/evals=2912/14851 eff=72.0445% N=684 Z=-2035.8(0.00%) \| Like=-2022.74..-0.00 [-2466.9117..-1268.6170] \| it/evals=2944/14851 eff=72.8790% N=684 Z=-1984.8(0.00%) \| Like=-1972.57..-0.00 [-2466.9117..-1268.6170] \| it/evals=2976/14851 eff=73.7135% N=684 Z=-1878.9(0.00%) \| Like=-1863.53..-0.00 [-2466.9117..-1268.6170] \| it/evals=3008/14851 eff=74.4553% N=684 Z=-1806.3(0.00%) \| Like=-1792.98..-0.00 [-2466.9117..-1268.6170] \| it/evals=3040/14863 eff=75.1037% N=684 Z=-1743.3(0.00%) \| Like=-1730.24..-0.00 [-2466.9117..-1268.6170] \| it/evals=3065/14997 eff=71.2983% N=684 Z=-1718.4(0.00%) \| Like=-1702.34..-0.00 [-2466.9117..-1268.6170] \| it/evals=3072/14997 eff=71.4720% N=684 Z=-1484.8(0.00%) \| Like=-1471.64..-0.00 [-2466.9117..-1268.6170] \| it/evals=3168/14997 eff=73.6431% N=684 Z=-1399.2(0.00%) \| Like=-1381.92..-0.00 [-2466.9117..-1268.6170] \| it/evals=3218/15000 eff=74.7181% N=684 Z=-1369.5(0.00%) \| Like=-1356.96..-0.00 [-2466.9117..-1268.6170] \| it/evals=3232/15138 eff=70.9902% N=684 Z=-1269.3(0.00%) \| Like=-1257.57..-0.00 [-1267.9975..-643.9316] \| it/evals=3296/15138 eff=72.3404% N=684 Z=-1218.7(0.00%) \| Like=-1207.31..-0.00 [-1267.9975..-643.9316] \| it/evals=3320/15138 eff=72.8723% N=684 Z=-1211.0(0.00%) \| Like=-1198.20..-0.00 [-1267.9975..-643.9316] \| it/evals=3328/15138 eff=73.1588% N=684 Z=-1108.0(0.00%) \| Like=-1095.95..-0.00 [-1267.9975..-643.9316] \| it/evals=3392/15138 eff=74.6727% N=684 Z=-1053.3(0.00%) \| Like=-1039.44..-0.00 [-1267.9975..-643.9316] \| it/evals=3424/15277 eff=71.3124% N=684 Z=-1009.7(0.00%) \| Like=-997.35..-0.00 [-1267.9975..-643.9316] \| it/evals=3453/15277 eff=71.7770% N=684 Z=-910.8(0.00%) \| Like=-899.90..-0.00 [-1267.9975..-643.9316] \| it/evals=3520/15277 eff=73.0933% N=684 Z=-868.7(0.00%) \| Like=-855.04..-0.00 [-1267.9975..-643.9316] \| it/evals=3552/15277 eff=73.6353% N=684 Z=-830.2(0.00%) \| Like=-818.44..-0.00 [-1267.9975..-643.9316] \| it/evals=3584/15405 eff=70.8963% N=684 Z=-795.5(0.00%) \| Like=-784.17..-0.00 [-1267.9975..-643.9316] \| it/evals=3608/15405 eff=71.2283% N=684 Z=-756.4(0.00%) \| Like=-744.32..-0.00 [-1267.9975..-643.9316] \| it/evals=3648/15405 eff=72.0767% N=684 Z=-725.7(0.00%) \| Like=-713.19..-0.00 [-1267.9975..-643.9316] \| it/evals=3680/15405 eff=72.8882% N=684 Z=-701.4(0.00%) \| Like=-689.19..-0.00 [-1267.9975..-643.9316] \| it/evals=3712/15405 eff=73.2571% N=684 Z=-673.6(0.00%) \| Like=-662.07..-0.00 [-1267.9975..-643.9316] \| it/evals=3744/15535 eff=70.4681% N=684 Z=-655.8(0.00%) \| Like=-643.74..-0.00 [-643.7386..-332.5924] \| it/evals=3761/15535 eff=70.8201% N=684 Z=-614.3(0.00%) \| Like=-602.28..-0.00 [-643.7386..-332.5924] \| it/evals=3808/15535 eff=71.9113% N=684 Z=-592.7(0.00%) \| Like=-582.26..-0.00 [-643.7386..-332.5924] \| it/evals=3840/15535 eff=72.4393% N=684 Z=-531.7(0.00%) \| Like=-519.27..-0.00 [-643.7386..-332.5924] \| it/evals=3915/15666 eff=70.6258% N=684 Z=-430.1(0.00%) \| Like=-418.12..-0.00 [-643.7386..-332.5924] \| it/evals=4054/15794 eff=70.0645% N=684 Z=-425.6(0.00%) \| Like=-413.07..-0.00 [-643.7386..-332.5924] \| it/evals=4064/15794 eff=70.2903% N=684 Z=-421.9(0.00%) \| Like=-409.43..-0.00 [-643.7386..-332.5924] \| it/evals=4069/15794 eff=70.3871% N=684 Z=-389.6(0.00%) \| Like=-376.91..-0.00 [-643.7386..-332.5924] \| it/evals=4128/15794 eff=71.4516% N=684 Z=-372.9(0.00%) \| Like=-361.35..-0.00 [-643.7386..-332.5924] \| it/evals=4160/15794 eff=72.0000% N=684 Z=-337.8(0.00%) \| Like=-324.36..-0.00 [-331.8152..-159.3144] \| it/evals=4226/15922 eff=70.1053% N=684 Z=-296.1(0.00%) \| Like=-284.28..-0.00 [-331.8152..-159.3144] \| it/evals=4320/15922 eff=71.4994% N=684 Z=-279.9(0.00%) \| Like=-267.68..-0.00 [-331.8152..-159.3144] \| it/evals=4352/16050 eff=69.3683% N=684 Z=-268.9(0.00%) \| Like=-257.11..-0.00 [-331.8152..-159.3144] \| it/evals=4379/16050 eff=69.7259% N=684 Z=-267.0(0.00%) \| Like=-254.70..-0.00 [-331.8152..-159.3144] \| it/evals=4384/16050 eff=69.8451% N=684 Z=-255.4(0.00%) \| Like=-242.85..-0.00 [-331.8152..-159.3144] \| it/evals=4416/16050 eff=70.3218% N=684 Z=-243.9(0.00%) \| Like=-232.03..-0.00 [-331.8152..-159.3144] \| it/evals=4448/16050 eff=70.9774% N=684 Z=-233.1(0.00%) \| Like=-221.16..-0.00 [-331.8152..-159.3144] \| it/evals=4473/16050 eff=71.3349% N=684 Z=-230.1(0.00%) \| Like=-217.50..-0.00 [-331.8152..-159.3144] \| it/evals=4480/16050 eff=71.5137% N=684 Z=-218.9(0.00%) \| Like=-207.04..-0.00 [-331.8152..-159.3144] \| it/evals=4512/16178 eff=69.4030% N=684 Z=-209.1(0.00%) \| Like=-196.76..-0.00 [-331.8152..-159.3144] \| it/evals=4544/16178 eff=69.9483% N=684 Z=-186.3(0.00%) \| Like=-174.58..-0.00 [-331.8152..-159.3144] \| it/evals=4626/16178 eff=71.1825% N=684 Z=-181.9(0.00%) \| Like=-170.09..-0.00 [-331.8152..-159.3144] \| it/evals=4643/16178 eff=71.4122% N=684 Z=-175.4(0.00%) \| Like=-163.13..-0.00 [-331.8152..-159.3144] \| it/evals=4672/16306 eff=69.4075% N=684 Z=-148.0(0.00%) \| Like=-135.88..-0.00 [-159.0852..-76.9488] \| it/evals=4804/16306 eff=71.4563% N=684 Z=-143.0(0.00%) \| Like=-131.19..-0.00 [-159.0852..-76.9488] \| it/evals=4832/16306 eff=71.8162% N=684 Z=-130.6(0.00%) \| Like=-118.67..-0.00 [-159.0852..-76.9488] \| it/evals=4896/16434 eff=70.3743% N=684 Z=-128.3(0.00%) \| Like=-115.92..-0.00 [-159.0852..-76.9488] \| it/evals=4907/16434 eff=70.5080% N=684 Z=-124.4(0.00%) \| Like=-112.47..-0.00 [-159.0852..-76.9488] \| it/evals=4928/16434 eff=70.8021% N=684 Z=-123.4(0.00%) \| Like=-111.74..-0.00 [-159.0852..-76.9488] \| it/evals=4934/16434 eff=70.8289% N=684 Z=-118.9(0.00%) \| Like=-107.33..-0.00 [-159.0852..-76.9488] \| it/evals=4965/16434 eff=71.1765% N=684 Z=-118.5(0.00%) \| Like=-106.72..-0.00 [-159.0852..-76.9488] \| it/evals=4969/16434 eff=71.2032% N=684 Z=-115.0(0.00%) \| Like=-103.05..-0.00 [-159.0852..-76.9488] \| it/evals=4992/16434 eff=71.6845% N=684 Z=-111.8(0.00%) \| Like=-99.74..-0.00 [-159.0852..-76.9488] \| it/evals=5006/16562 eff=69.4416% N=684 Z=-111.4(0.00%) \| Like=-99.54..-0.00 [-159.0852..-76.9488] \| it/evals=5009/16562 eff=69.4674% N=684 Z=-105.5(0.00%) \| Like=-93.70..-0.00 [-159.0852..-76.9488] \| it/evals=5048/16562 eff=70.1138% N=684 Z=-102.8(0.00%) \| Like=-90.95..-0.00 [-159.0852..-76.9488] \| it/evals=5070/16562 eff=70.5016% N=684 Z=-99.8(0.00%) \| Like=-87.49..-0.00 [-159.0852..-76.9488] \| it/evals=5088/16562 eff=70.8376% N=684 Z=-90.4(0.00%) \| Like=-78.23..-0.00 [-159.0852..-76.9488] \| it/evals=5152/16562 eff=71.7166% N=684 Z=-86.6(0.00%) \| Like=-74.52..-0.00 [-76.9377..-37.2756] \| it/evals=5184/16691 eff=69.8274% N=684 Z=-83.5(0.00%) \| Like=-71.83..-0.00 [-76.9377..-37.2756] \| it/evals=5216/16691 eff=70.2777% N=684 Z=-82.7(0.00%) \| Like=-70.96..-0.00 [-76.9377..-37.2756] \| it/evals=5225/16691 eff=70.4028% N=684 Z=-81.1(0.00%) \| Like=-68.97..-0.00 [-76.9377..-37.2756] \| it/evals=5242/16691 eff=70.5279% N=684 Z=-80.4(0.00%) \| Like=-68.49..-0.00 [-76.9377..-37.2756] \| it/evals=5248/16691 eff=70.6530% N=684 Z=-78.6(0.00%) \| Like=-66.57..-0.00 [-76.9377..-37.2756] \| it/evals=5268/16691 eff=70.8531% N=684 Z=-77.3(0.00%) \| Like=-65.21..-0.00 [-76.9377..-37.2756] \| it/evals=5280/16691 eff=71.0033% N=684 Z=-75.7(0.00%) \| Like=-63.94..-0.00 [-76.9377..-37.2756] \| it/evals=5299/16691 eff=71.2534% N=684 Z=-74.7(0.00%) \| Like=-62.61..-0.00 [-76.9377..-37.2756] \| it/evals=5312/16691 eff=71.5286% N=684 Z=-74.2(0.00%) \| Like=-62.03..-0.00 [-76.9377..-37.2756] \| it/evals=5317/16691 eff=71.5537% N=684 Z=-69.5(0.00%) \| Like=-57.77..-0.00 [-76.9377..-37.2756] \| it/evals=5376/16819 eff=70.1333% N=684 Z=-67.1(0.00%) \| Like=-55.15..-0.00 [-76.9377..-37.2756] \| it/evals=5409/16819 eff=70.5939% N=684 Z=-62.8(0.00%) \| Like=-50.80..-0.00 [-76.9377..-37.2756] \| it/evals=5454/16819 eff=71.2485% N=684 Z=-61.5(0.00%) \| Like=-49.57..-0.00 [-76.9377..-37.2756] \| it/evals=5472/16819 eff=71.6121% N=684 Z=-60.9(0.00%) \| Like=-48.98..-0.00 [-76.9377..-37.2756] \| it/evals=5480/16819 eff=71.6606% N=684 Z=-58.8(0.00%) \| Like=-46.82..-0.00 [-76.9377..-37.2756] \| it/evals=5510/16947 eff=69.8331% N=684 Z=-58.2(0.00%) \| Like=-46.15..-0.00 [-76.9377..-37.2756] \| it/evals=5518/16947 eff=69.9036% N=684 Z=-57.5(0.00%) \| Like=-45.58..-0.00 [-76.9377..-37.2756] \| it/evals=5527/16947 eff=69.9741% N=684 Z=-54.8(0.00%) \| Like=-42.92..-0.00 [-76.9377..-37.2756] \| it/evals=5568/16947 eff=70.6325% N=684 Z=-51.4(0.00%) \| Like=-39.32..-0.00 [-76.9377..-37.2756] \| it/evals=5617/16947 eff=71.2438% N=684 Z=-50.2(0.00%) \| Like=-38.13..-0.00 [-76.9377..-37.2756] \| it/evals=5634/16947 eff=71.5025% N=684 Z=-49.6(0.00%) \| Like=-37.22..-0.00 [-37.2169..-17.5865] \| it/evals=5641/16947 eff=71.5730% N=684 Z=-48.9(0.00%) \| Like=-36.77..-0.00 [-37.2169..-17.5865] \| it/evals=5650/16947 eff=71.6200% N=684 Z=-47.9(0.00%) \| Like=-35.90..-0.00 [-37.2169..-17.5865] \| it/evals=5664/17075 eff=69.7786% N=684 Z=-46.3(0.00%) \| Like=-34.58..-0.00 [-37.2169..-17.5865] \| it/evals=5696/17075 eff=70.3036% N=684 Z=-45.6(0.00%) \| Like=-33.92..-0.00 [-37.2169..-17.5865] \| it/evals=5713/17075 eff=70.4634% N=684 Z=-44.8(0.00%) \| Like=-32.89..-0.00 [-37.2169..-17.5865] \| it/evals=5728/17075 eff=70.7373% N=684 Z=-43.7(0.00%) \| Like=-31.70..-0.00 [-37.2169..-17.5865] \| it/evals=5754/17075 eff=71.0112% N=684 Z=-43.3(0.00%) \| Like=-31.11..-0.00 [-37.2169..-17.5865] \| it/evals=5760/17075 eff=71.1481% N=684 Z=-42.3(0.00%) \| Like=-30.08..-0.00 [-37.2169..-17.5865] \| it/evals=5779/17075 eff=71.3764% N=684 Z=-39.8(0.00%) \| Like=-27.65..-0.00 [-37.2169..-17.5865] \| it/evals=5826/17075 eff=71.8557% N=684 Z=-39.3(0.00%) \| Like=-27.15..-0.00 [-37.2169..-17.5865] \| it/evals=5836/17075 eff=71.9699% N=684 Z=-38.9(0.00%) \| Like=-26.83..-0.00 [-37.2169..-17.5865] \| it/evals=5843/17204 eff=69.9778% N=684 Z=-38.3(0.00%) \| Like=-26.46..-0.00 [-37.2169..-17.5865] \| it/evals=5856/17204 eff=70.1552% N=684 Z=-38.0(0.00%) \| Like=-25.95..-0.00 [-37.2169..-17.5865] \| it/evals=5864/17204 eff=70.1996% N=684 Z=-37.4(0.00%) \| Like=-25.29..-0.00 [-37.2169..-17.5865] \| it/evals=5875/17204 eff=70.3104% N=684 Z=-36.7(0.00%) \| Like=-24.68..-0.00 [-37.2169..-17.5865] \| it/evals=5891/17204 eff=70.4656% N=684 Z=-36.4(0.00%) \| Like=-24.51..-0.00 [-37.2169..-17.5865] \| it/evals=5898/17204 eff=70.5100% N=684 Z=-35.7(0.00%) \| Like=-23.79..-0.00 [-37.2169..-17.5865] \| it/evals=5917/17204 eff=70.8204% N=684 Z=-35.6(0.00%) \| Like=-23.68..-0.00 [-37.2169..-17.5865] \| it/evals=5920/17204 eff=70.8647% N=684 Z=-35.1(0.00%) \| Like=-23.33..-0.00 [-37.2169..-17.5865] \| it/evals=5933/17204 eff=71.0200% N=684 Z=-33.4(0.00%) \| Like=-21.69..-0.00 [-37.2169..-17.5865] \| it/evals=5982/17204 eff=71.6630% N=684 Z=-33.4(0.00%) \| Like=-21.67..-0.00 [-37.2169..-17.5865] \| it/evals=5984/17204 eff=71.6851% N=684 Z=-33.0(0.00%) \| Like=-21.37..-0.00 [-37.2169..-17.5865] \| it/evals=5997/17204 eff=71.7960% N=684 Z=-32.4(0.00%) \| Like=-20.57..-0.00 [-37.2169..-17.5865] \| it/evals=6016/17204 eff=71.8847% N=684 Z=-31.4(0.00%) \| Like=-19.55..-0.00 [-37.2169..-17.5865] \| it/evals=6048/17332 eff=70.3320% N=684 Z=-30.5(0.00%) \| Like=-18.65..-0.00 [-37.2169..-17.5865] \| it/evals=6080/17332 eff=70.7201% N=684 Z=-29.8(0.00%) \| Like=-18.06..-0.00 [-37.2169..-17.5865] \| it/evals=6106/17332 eff=71.0004% N=684 Z=-28.6(0.00%) \| Like=-16.94..-0.00 [-17.5830..-8.7075] \| it/evals=6156/17332 eff=71.1945% N=684 Z=-28.1(0.00%) \| Like=-16.29..-0.00 [-17.5830..-8.7075] \| it/evals=6180/17332 eff=71.3670% N=684 Z=-27.9(0.00%) \| Like=-16.05..-0.00 [-17.5830..-8.7075] \| it/evals=6189/17332 eff=71.4317% N=684 Z=-27.7(0.00%) \| Like=-15.90..-0.00 [-17.5830..-8.7075] \| it/evals=6198/17332 eff=71.4532% N=684 Z=-27.5(0.00%) \| Like=-15.72..-0.00 [-17.5830..-8.7075] \| it/evals=6207/17332 eff=71.5395% N=684 Z=-27.4(0.00%) \| Like=-15.68..-0.00 [-17.5830..-8.7075] \| it/evals=6208/17332 eff=71.5610% N=684 Z=-26.5(0.00%) \| Like=-14.74..-0.00 [-17.5830..-8.7075] \| it/evals=6247/17332 eff=72.0569% N=684 Z=-26.3(0.00%) \| Like=-14.43..-0.00 [-17.5830..-8.7075] \| it/evals=6261/17332 eff=72.2078% N=684 Z=-25.2(0.00%) \| Like=-13.47..-0.00 [-17.5830..-8.7075] \| it/evals=6317/17460 eff=70.9820% N=684 Z=-24.8(0.00%) \| Like=-13.02..-0.00 [-17.5830..-8.7075] \| it/evals=6336/17460 eff=71.3386% N=684 Z=-24.4(0.00%) \| Like=-12.55..-0.00 [-17.5830..-8.7075] \| it/evals=6364/17460 eff=71.5695% N=684 Z=-24.0(0.00%) \| Like=-12.13..-0.00 [-17.5830..-8.7075] \| it/evals=6382/17460 eff=71.6534% N=684 Z=-23.6(0.00%) \| Like=-11.79..-0.00 [-17.5830..-8.7075] \| it/evals=6404/17460 eff=71.8422% N=684 Z=-22.6(0.00%) \| Like=-10.83..-0.00 [-17.5830..-8.7075] \| it/evals=6465/17460 eff=72.1569% N=684 Z=-22.5(0.00%) \| Like=-10.78..-0.00 [-17.5830..-8.7075] \| it/evals=6473/17460 eff=72.2199% N=684 Z=-22.3(0.00%) \| Like=-10.46..-0.00 [-17.5830..-8.7075] \| it/evals=6489/17588 eff=70.5149% N=684 Z=-22.2(0.00%) \| Like=-10.36..-0.00 [-17.5830..-8.7075] \| it/evals=6496/17588 eff=70.6171% N=684 Z=-22.0(0.00%) \| Like=-10.14..-0.00 [-17.5830..-8.7075] \| it/evals=6508/17588 eff=70.6988% N=684 Z=-21.8(0.00%) \| Like=-10.02..-0.00 [-17.5830..-8.7075] \| it/evals=6518/17588 eff=70.8214% N=684 Z=-21.2(0.01%) \| Like=-9.40..-0.00 [-17.5830..-8.7075] \| it/evals=6560/17588 eff=71.3527% N=684 Z=-21.0(0.01%) \| Like=-9.07..-0.00 [-17.5830..-8.7075] \| it/evals=6579/17588 eff=71.5774% N=684 Z=-20.8(0.01%) \| Like=-8.88..-0.00 [-17.5830..-8.7075] \| it/evals=6592/17588 eff=71.8022% N=684 Z=-20.4(0.02%) \| Like=-8.43..-0.00 [-8.6784..-4.4277] \| it/evals=6624/17588 eff=72.2517% N=684 Z=-19.6(0.04%) \| Like=-7.67..-0.00 [-8.6784..-4.4277] \| it/evals=6688/17716 eff=71.1868% N=684 Z=-19.2(0.07%) \| Like=-7.33..-0.00 [-8.6784..-4.4277] \| it/evals=6720/17716 eff=71.5253% N=684 Z=-19.1(0.08%) \| Like=-7.25..-0.00 [-8.6784..-4.4277] \| it/evals=6732/17716 eff=71.7045% N=684 Z=-18.9(0.09%) \| Like=-7.05..-0.00 [-8.6784..-4.4277] \| it/evals=6752/17716 eff=71.9434% N=684 Z=-18.5(0.13%) \| Like=-6.74..-0.00 [-8.6784..-4.4277] \| it/evals=6784/17844 eff=70.5437% N=684 Z=-18.0(0.23%) \| Like=-6.25..-0.00 [-8.6784..-4.4277] \| it/evals=6848/17844 eff=71.2233% N=684 Z=-17.7(0.30%) \| Like=-6.04..-0.00 [-8.6784..-4.4277] \| it/evals=6885/17844 eff=71.6117% N=684 Z=-17.5(0.37%) \| Like=-5.90..-0.00 [-8.6784..-4.4277] \| it/evals=6912/17844 eff=71.7087% N=684 Z=-17.1(0.56%) \| Like=-5.31..-0.00 [-8.6784..-4.4277] \| it/evals=6976/17972 eff=70.6518% N=684 Z=-16.9(0.70%) \| Like=-5.08..-0.00 [-8.6784..-4.4277] \| it/evals=7008/17972 eff=71.0496% N=684 Z=-16.7(0.86%) \| Like=-4.85..-0.00 [-8.6784..-4.4277] \| it/evals=7038/17972 eff=71.4475% N=684 Z=-16.6(0.87%) \| Like=-4.83..-0.00 [-8.6784..-4.4277] \| it/evals=7040/17972 eff=71.4854% N=684 Z=-16.2(1.30%) \| Like=-4.37..-0.00 [-4.4214..-3.4531] \| it/evals=7104/17972 eff=72.1485% N=684 Z=-16.0(1.57%) \| Like=-4.13..-0.00 [-4.4214..-3.4531] \| it/evals=7136/18100 eff=70.7917% N=684 Z=-15.8(1.88%) \| Like=-3.95..-0.00 [-4.4214..-3.4531] \| it/evals=7168/18100 eff=71.1062% N=684 Z=-15.7(2.18%) \| Like=-3.79..-0.00 [-4.4214..-3.4531] \| it/evals=7193/18100 eff=71.3097% N=684 Z=-15.6(2.28%) \| Like=-3.76..-0.00 [-4.4214..-3.4531] \| it/evals=7200/18100 eff=71.3836% N=684 Z=-15.5(2.71%) \| Like=-3.56..-0.00 [-4.4214..-3.4531] \| it/evals=7232/18100 eff=71.7536% N=684 Z=-15.1(3.76%) \| Like=-3.25..-0.00 [-3.4370..-3.1979] \| it/evals=7296/18228 eff=70.6903% N=684 Z=-14.9(4.84%) \| Like=-3.00..-0.00 [-2.9955..-2.9920]\| it/evals=7346/18228 eff=71.1059% N=684 Z=-14.7(5.85%) \| Like=-2.81..-0.00 [-2.8127..-2.8054]\| it/evals=7392/18228 eff=71.6299% N=684 Z=-14.6(6.67%) \| Like=-2.67..-0.00 [-2.6700..-2.6691]\| it/evals=7424/18228 eff=71.8829% N=684 Z=-14.4(7.58%) \| Like=-2.54..-0.00 [-2.5444..-2.5429]\| it/evals=7456/18356 eff=70.5758% N=684 Z=-14.3(8.46%) \| Like=-2.42..-0.00 [-2.4244..-2.4222]\| it/evals=7488/18356 eff=70.8937% N=684 Z=-14.3(8.78%) \| Like=-2.37..-0.00 [-2.3749..-2.3739]\| it/evals=7499/18356 eff=71.0173% N=684 Z=-14.2(9.54%) \| Like=-2.30..-0.00 [-2.3035..-2.3032]\| it/evals=7520/18356 eff=71.1939% N=684 Z=-13.9(13.11%) \| Like=-2.04..-0.00 [-2.0395..-2.0384]\| it/evals=7616/18356 eff=71.9887% N=684 Z=-13.8(14.40%) \| Like=-1.95..-0.00 [-1.9533..-1.9525]\| it/evals=7648/18484 eff=70.6736% N=684 Z=-13.8(14.62%) \| Like=-1.94..-0.00 [-1.9440..-1.9426]\| it/evals=7655/18484 eff=70.7081% N=684 Z=-13.4(20.12%) \| Like=-1.61..-0.00 [-1.6148..-1.6144]\| it/evals=7782/18484 eff=71.7617% N=684 Z=-13.4(21.32%) \| Like=-1.56..-0.00 [-1.5592..-1.5584]\| it/evals=7809/18612 eff=70.4123% N=684 Z=-13.2(26.31%) \| Like=-1.36..-0.00 [-1.3566..-1.3508]\| it/evals=7904/18612 eff=71.3079% N=684 Z=-13.1(27.90%) \| Like=-1.28..-0.00 [-1.2802..-1.2800]\| it/evals=7936/18612 eff=71.6627% N=684 Z=-13.1(29.34%) \| Like=-1.24..-0.00 [-1.2413..-1.2369]\| it/evals=7963/18740 eff=70.3936% N=684 Z=-13.0(31.31%) \| Like=-1.18..-0.00 [-1.1764..-1.1723]\| it/evals=8000/18740 eff=70.8071% N=684 Z=-13.0(33.05%) \| Like=-1.12..-0.00 [-1.1213..-1.1202]\| it/evals=8032/18740 eff=71.0883% N=684 Z=-12.8(37.69%) \| Like=-1.00..-0.00 [-0.9998..-0.9996]\| it/evals=8118/18868 eff=70.4730% N=684 Z=-12.8(38.20%) \| Like=-0.99..-0.00 [-0.9875..-0.9875]\| it/evals=8128/18868 eff=70.6025% N=684 Z=-12.7(43.08%) \| Like=-0.84..-0.00 [-0.8379..-0.8373]\| it/evals=8224/18996 eff=70.0413% N=684 Z=-12.7(44.83%) \| Like=-0.80..-0.00 [-0.8004..-0.7995]\| it/evals=8256/18996 eff=70.2951% N=684 Z=-12.6(45.57%) \| Like=-0.78..-0.00 [-0.7846..-0.7799]\| it/evals=8271/18996 eff=70.5173% N=684 Z=-12.6(48.06%) \| Like=-0.73..-0.00 [-0.7335..-0.7326]\| it/evals=8320/18996 eff=70.9457% N=684 Z=-12.5(51.33%) \| Like=-0.67..-0.00 [-0.6661..-0.6653]\| it/evals=8384/19124 eff=70.1244% N=684 Z=-12.5(52.90%) \| Like=-0.64..-0.00 [-0.6429..-0.6428]\| it/evals=8416/19124 eff=70.4355% N=684 Z=-12.5(53.31%) \| Like=-0.63..-0.00 [-0.6325..-0.6316]\| it/evals=8425/19124 eff=70.4821% N=684 Z=-12.4(55.98%) \| Like=-0.59..-0.00 [-0.5858..-0.5855]\| it/evals=8480/19124 eff=70.9331% N=684 Z=-12.4(58.96%) \| Like=-0.54..-0.00 [-0.5387..-0.5380]\| it/evals=8544/19252 eff=70.0976% N=684 Z=-12.4(60.42%) \| Like=-0.52..-0.00 [-0.5153..-0.5150]\| it/evals=8576/19252 eff=70.3111% N=684 Z=-12.4(60.51%) \| Like=-0.51..-0.00 [-0.5131..-0.5114]\| it/evals=8578/19252 eff=70.3416% N=684 Z=-12.3(61.79%) \| Like=-0.49..-0.00 [-0.4851..-0.4848]\| it/evals=8608/19252 eff=70.5855% N=684 Z=-12.3(63.15%) \| Like=-0.46..-0.00 [-0.4571..-0.4570]\| it/evals=8640/19252 eff=70.8600% N=684 Z=-12.2(66.94%) \| Like=-0.40..-0.00 [-0.4014..-0.4010]\| it/evals=8734/19380 eff=70.2812% N=684 Z=-12.2(67.02%) \| Like=-0.40..-0.00 [-0.4009..-0.4007]\| it/evals=8736/19380 eff=70.2961% N=684 Z=-12.2(68.27%) \| Like=-0.38..-0.00 [-0.3804..-0.3793]\| it/evals=8768/19380 eff=70.5354% N=684 Z=-12.2(72.52%) \| Like=-0.32..-0.00 [-0.3151..-0.3129]\| it/evals=8887/19508 eff=70.1497% N=684 Z=-12.2(73.90%) \| Like=-0.29..-0.00 [-0.2917..-0.2915]\| it/evals=8928/19508 eff=70.3698% N=684 Z=-12.1(74.92%) \| Like=-0.28..-0.00 [-0.2754..-0.2753]\| it/evals=8960/19508 eff=70.5753% N=684 Z=-12.1(76.89%) \| Like=-0.25..-0.00 [-0.2547..-0.2546]\| it/evals=9024/19636 eff=69.7638% N=684 Z=-12.1(77.42%) \| Like=-0.25..-0.00 [-0.2465..-0.2458]\| it/evals=9042/19636 eff=69.8646% N=684 Z=-12.1(77.82%) \| Like=-0.24..-0.00 [-0.2401..-0.2400]\| it/evals=9056/19636 eff=70.0375% N=684 Z=-12.1(78.71%) \| Like=-0.23..-0.00 [-0.2305..-0.2303]\| it/evals=9088/19636 eff=70.3111% N=684 Z=-12.1(80.41%) \| Like=-0.21..-0.00 [-0.2074..-0.2064]\| it/evals=9152/19636 eff=70.7433% N=684 Z=-12.1(81.22%) \| Like=-0.20..-0.00 [-0.1960..-0.1953]\| it/evals=9184/19764 eff=69.6888% N=684 Z=-12.1(81.50%) \| Like=-0.19..-0.00 [-0.1922..-0.1920]\| it/evals=9195/19764 eff=69.7595% N=684 Z=-12.0(83.47%) \| Like=-0.17..-0.00 [-0.1711..-0.1708]\| it/evals=9280/19764 eff=70.2829% N=684 Z=-12.0(84.83%) \| Like=-0.15..-0.00 [-0.1532..-0.1531]\| it/evals=9344/19892 eff=69.5749% N=684 Z=-12.0(84.94%) \| Like=-0.15..-0.00 [-0.1515..-0.1513]\| it/evals=9349/19892 eff=69.6166% N=684 Z=-12.0(86.10%) \| Like=-0.14..-0.00 [-0.1421..-0.1416]\| it/evals=9408/19892 eff=70.0194% N=684 Z=-12.0(87.26%) \| Like=-0.13..-0.00 [-0.1263..-0.1261]\| it/evals=9472/20020 eff=69.3557% N=684 Z=-12.0(87.79%) \| Like=-0.12..-0.00 [-0.1216..-0.1214]\| it/evals=9503/20020 eff=69.6151% N=684 Z=-12.0(87.81%) \| Like=-0.12..-0.00 [-0.1214..-0.1214]\| it/evals=9504/20020 eff=69.6287% N=684 Z=-12.0(88.33%) \| Like=-0.12..-0.00 [-0.1157..-0.1157]\| it/evals=9536/20020 eff=69.8608% N=684 Z=-12.0(88.84%) \| Like=-0.11..-0.00 [-0.1109..-0.1108]\| it/evals=9568/20020 eff=70.0928% N=684 Z=-12.0(89.32%) \| Like=-0.11..-0.00 [-0.1071..-0.1071]\| it/evals=9600/20020 eff=70.3249% N=684 Z=-12.0(90.12%) \| Like=-0.10..-0.00 [-0.0973..-0.0973]\| it/evals=9656/20148 eff=69.4795% N=684 Z=-11.9(91.45%) \| Like=-0.08..-0.00 [-0.0828..-0.0827]\| it/evals=9760/20148 eff=70.1905% N=684 Z=-11.9(92.06%) \| Like=-0.08..-0.00 [-0.0785..-0.0785]\| it/evals=9812/20276 eff=69.3748% N=684 Z=-11.9(92.19%) \| Like=-0.08..-0.00 [-0.0778..-0.0777]\| it/evals=9824/20276 eff=69.4408% N=684 Z=-11.9(92.53%) \| Like=-0.07..-0.00 [-0.0735..-0.0734]\| it/evals=9856/20276 eff=69.6914% N=684 Z=-11.9(92.86%) \| Like=-0.07..-0.00 [-0.0691..-0.0690]\| it/evals=9888/20276 eff=69.8628% N=684 Z=-11.9(93.60%) \| Like=-0.06..-0.00 [-0.0610..-0.0609]\| it/evals=9965/20404 eff=69.2607% N=684 Z=-11.9(94.04%) \| Like=-0.06..-0.00 [-0.0568..-0.0566]\| it/evals=10016/20404 eff=69.6368% N=684 Z=-11.9(94.56%) \| Like=-0.05..-0.00 [-0.0504..-0.0503]\| it/evals=10080/20404 eff=70.2205% N=684 Z=-11.9(94.81%) \| Like=-0.05..-0.00 [-0.0482..-0.0481]\| it/evals=10112/20532 eff=69.3162% N=684 Z=-11.9(94.86%) \| Like=-0.05..-0.00 [-0.0478..-0.0477]\| it/evals=10119/20532 eff=69.3672% N=684 Z=-11.9(95.04%) \| Like=-0.05..-0.00 [-0.0460..-0.0460]\| it/evals=10144/20532 eff=69.5203% N=684 Z=-11.9(95.26%) \| Like=-0.04..-0.00 [-0.0438..-0.0438]\| it/evals=10176/20532 eff=69.7372% N=684 Z=-11.9(95.47%) \| Like=-0.04..-0.00 [-0.0422..-0.0422]\| it/evals=10208/20532 eff=69.9796% N=684 Z=-11.9(95.87%) \| Like=-0.04..-0.00 [-0.0381..-0.0380]\| it/evals=10272/20660 eff=69.3196% N=684 Z=-11.9(96.05%) \| Like=-0.04..-0.00 [-0.0365..-0.0365]\| it/evals=10304/20660 eff=69.5581% N=684 Z=-11.9(96.23%) \| Like=-0.03..-0.00 [-0.0347..-0.0346]\| it/evals=10336/20660 eff=69.7841% N=684 Z=-11.9(96.69%) \| Like=-0.03..-0.00 [-0.0305..-0.0305]\| it/evals=10426/20788 eff=69.1871% N=684 Z=-11.9(97.01%) \| Like=-0.03..-0.00 [-0.0279..-0.0279]\| it/evals=10496/20788 eff=69.6318% N=684 Z=-11.9(97.14%) \| Like=-0.03..-0.00 [-0.0262..-0.0262]\| it/evals=10528/20788 eff=69.8542% N=684 Z=-11.9(97.34%) \| Like=-0.02..-0.00 [-0.0245..-0.0244]\| it/evals=10579/20916 eff=69.0708% N=684 Z=-11.9(97.51%) \| Like=-0.02..-0.00 [-0.0229..-0.0228]\| it/evals=10624/20916 eff=69.3140% N=684 Z=-11.9(97.62%) \| Like=-0.02..-0.00 [-0.0218..-0.0218]\| it/evals=10656/20916 eff=69.5451% N=684 Z=-11.9(97.73%) \| Like=-0.02..-0.00 [-0.0208..-0.0207]\| it/evals=10688/20916 eff=69.7762% N=684 Z=-11.9(97.88%) \| Like=-0.02..-0.00 [-0.0192..-0.0192]\| it/evals=10734/21044 eff=68.9940% N=684 Z=-11.9(97.93%) \| Like=-0.02..-0.00 [-0.0188..-0.0188]\| it/evals=10752/21044 eff=69.1018% N=684 Z=-11.9(98.03%) \| Like=-0.02..-0.00 [-0.0179..-0.0179]\| it/evals=10784/21044 eff=69.2216% N=684 Z=-11.9(98.12%) \| Like=-0.02..-0.00 [-0.0172..-0.0172]\| it/evals=10816/21044 eff=69.4371% N=684 Z=-11.9(98.30%) \| Like=-0.02..-0.00 [-0.0153..-0.0152]\| it/evals=10888/21172 eff=68.8606% N=684 Z=-11.9(98.36%) \| Like=-0.01..-0.00 [-0.0147..-0.0147]\| it/evals=10912/21172 eff=69.0375% N=684 Z=-11.9(98.43%) \| Like=-0.01..-0.00 [-0.0140..-0.0139]\| it/evals=10944/21172 eff=69.2498% N=684 Z=-11.9(98.51%) \| Like=-0.01..-0.00 [-0.0132..-0.0132]\| it/evals=10976/21172 eff=69.4503% N=684 Z=-11.9(98.64%) \| Like=-0.01..-0.00 [-0.0120..-0.0119]\| it/evals=11040/21300 eff=68.8706% N=684 Z=-11.9(98.64%) \| Like=-0.01..-0.00 [-0.0119..-0.0119]\| it/evals=11042/21300 eff=68.8822% N=684 Z=-11.9(98.76%) \| Like=-0.01..-0.00 [-0.0109..-0.0109]\| it/evals=11104/21300 eff=69.3121% N=684 Z=-11.9(98.91%) \| Like=-0.01..-0.00 [-0.0097..-0.0097]\| it/evals=11196/21428 eff=68.7886% N=684 Z=-11.9(98.97%) \| Like=-0.01..-0.00 [-0.0092..-0.0091]\| it/evals=11232/21428 eff=69.0176% N=684 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 21428 logzerr in iteration 1 0.18154709950658637 [ultranest] logZ = -11.85 +- 0.1011 [ultranest] Effective samples strategy satisfied (ESS = 2747.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 1367 minimum live points (dlogz from 0.08 to 0.21, need <0.1) [ultranest] logZ error budget: single: 0.18 bs:0.10 tail:0.01 total:0.10 required:<0.10 [ultranest] Widening roots to 1367 live points (have 684 already) ... [ultranest] Sampling 683 live points from prior ... Z=-233003.0(0.00%) \| Like=-230589.81..-0.00 [-245997.6291..-81000.4327] \| it/evals=5/22239 eff=0.0000% N=1367 Z=-199426.0(0.00%) \| Like=-198726.43..-0.00 [-245997.6291..-81000.4327] \| it/evals=32/22239 eff=9.3750% N=1367 Z=-149600.3(0.00%) \| Like=-148811.73..-0.00 [-245997.6291..-81000.4327] \| it/evals=157/22239 eff=57.0312% N=1367 Z=-147913.4(0.00%) \| Like=-147895.18..-0.00 [-245997.6291..-81000.4327] \| it/evals=160/22239 eff=58.5938% N=1367 Z=-141385.4(0.00%) \| Like=-141373.63..-0.00 [-245997.6291..-81000.4327] \| it/evals=192/22239 eff=71.0938% N=1367 Z=-124821.4(0.00%) \| Like=-124722.98..-0.00 [-245997.6291..-81000.4327] \| it/evals=311/22367 eff=58.9844% N=1367 Z=-119354.7(0.00%) \| Like=-119332.76..-0.00 [-245997.6291..-81000.4327] \| it/evals=352/22367 eff=68.3594% N=1367 Z=-116564.9(0.00%) \| Like=-116552.15..-0.00 [-245997.6291..-81000.4327] \| it/evals=384/22367 eff=74.2188% N=1367 Z=-105894.0(0.00%) \| Like=-105771.48..-0.00 [-245997.6291..-81000.4327] \| it/evals=509/22475 eff=70.6044% N=1367 Z=-105522.6(0.00%) \| Like=-105358.10..-0.00 [-245997.6291..-81000.4327] \| it/evals=512/22475 eff=71.1538% N=1367 Z=-103558.9(0.00%) \| Like=-103464.97..-0.00 [-245997.6291..-81000.4327] \| it/evals=544/22475 eff=76.0989% N=1367 Z=-98572.9(0.00%) \| Like=-98514.71..-0.00 [-245997.6291..-81000.4327] \| it/evals=608/22583 eff=66.3136% N=1367 Z=-97795.0(0.00%) \| Like=-97702.37..-0.00 [-245997.6291..-81000.4327] \| it/evals=618/22583 eff=67.5847% N=1367 Z=-94853.2(0.00%) \| Like=-94828.90..-0.00 [-245997.6291..-81000.4327] \| it/evals=672/22583 eff=73.3051% N=1367 Z=-93006.2(0.00%) \| Like=-92954.38..-0.00 [-245997.6291..-81000.4327] \| it/evals=704/22583 eff=76.6949% N=1367 Z=-85411.0(0.00%) \| Like=-85395.38..-0.00 [-245997.6291..-81000.4327] \| it/evals=832/22667 eff=75.0000% N=1367 Z=-82306.6(0.00%) \| Like=-82251.50..-0.00 [-245997.6291..-81000.4327] \| it/evals=896/22667 eff=80.5755% N=1367 Z=-81023.2(0.00%) \| Like=-81000.43..-0.00 [-245997.6291..-81000.4327] \| it/evals=926/22743 eff=72.7848% N=1367 Z=-80948.6(0.00%) \| Like=-80888.75..-0.00 [-80940.7496..-40866.8558] \| it/evals=928/22743 eff=72.9430% N=1367 Z=-77582.3(0.00%) \| Like=-77565.22..-0.00 [-80940.7496..-40866.8558] \| it/evals=992/22743 eff=78.3228% N=1367 Z=-73503.6(0.00%) \| Like=-73423.93..-0.00 [-80940.7496..-40866.8558] \| it/evals=1056/22817 eff=75.2125% N=1367 Z=-71606.1(0.00%) \| Like=-71595.62..-0.00 [-80940.7496..-40866.8558] \| it/evals=1088/22817 eff=77.9037% N=1367 Z=-69564.8(0.00%) \| Like=-69507.85..-0.00 [-80940.7496..-40866.8558] \| it/evals=1120/22892 eff=72.3431% N=1367 Z=-68137.5(0.00%) \| Like=-68006.23..-0.00 [-80940.7496..-40866.8558] \| it/evals=1152/22892 eff=74.3918% N=1367 Z=-66557.8(0.00%) \| Like=-66520.87..-0.00 [-80940.7496..-40866.8558] \| it/evals=1184/22892 eff=76.3124% N=1367 Z=-65303.2(0.00%) \| Like=-65261.64..-0.00 [-80940.7496..-40866.8558] \| it/evals=1216/22892 eff=78.7452% N=1367 Z=-64655.7(0.00%) \| Like=-64592.02..-0.00 [-80940.7496..-40866.8558] \| it/evals=1232/22942 eff=75.0903% N=1367 Z=-63771.6(0.00%) \| Like=-63760.11..-0.00 [-80940.7496..-40866.8558] \| it/evals=1248/22942 eff=75.9326% N=1367 Z=-60798.7(0.00%) \| Like=-60781.74..-0.00 [-80940.7496..-40866.8558] \| it/evals=1312/22942 eff=79.7834% N=1367 Z=-55667.6(0.00%) \| Like=-55649.92..-0.00 [-80940.7496..-40866.8558] \| it/evals=1434/23048 eff=78.1217% N=1367 Z=-54246.3(0.00%) \| Like=-54207.42..-0.00 [-80940.7496..-40866.8558] \| it/evals=1472/23111 eff=75.2000% N=1367 Z=-51934.6(0.00%) \| Like=-51913.09..-0.00 [-80940.7496..-40866.8558] \| it/evals=1536/23111 eff=78.4000% N=1367 Z=-51908.7(0.00%) \| Like=-51840.55..-0.00 [-80940.7496..-40866.8558] \| it/evals=1539/23111 eff=78.6000% N=1367 Z=-50702.1(0.00%) \| Like=-50615.28..-0.00 [-80940.7496..-40866.8558] \| it/evals=1568/23111 eff=79.8000% N=1367 Z=-49341.2(0.00%) \| Like=-49307.18..-0.00 [-80940.7496..-40866.8558] \| it/evals=1600/23165 eff=77.2296% N=1367 Z=-45151.9(0.00%) \| Like=-45133.65..-0.00 [-80940.7496..-40866.8558] \| it/evals=1718/23223 eff=78.3273% N=1367 Z=-41409.7(0.00%) \| Like=-41382.37..-0.00 [-80940.7496..-40866.8558] \| it/evals=1843/23302 eff=78.8413% N=1367 Z=-41321.7(0.00%) \| Like=-41294.39..-0.00 [-80940.7496..-40866.8558] \| it/evals=1845/23302 eff=78.9253% N=1367 Z=-40908.4(0.00%) \| Like=-40870.94..-0.00 [-80940.7496..-40866.8558] \| it/evals=1856/23302 eff=79.5130% N=1367 Z=-39979.4(0.00%) \| Like=-39965.82..-0.00 [-40839.0816..-20283.7951] \| it/evals=1888/23344 eff=78.1833% N=1367 Z=-39214.6(0.00%) \| Like=-39202.45..-0.00 [-40839.0816..-20283.7951] \| it/evals=1920/23344 eff=79.3187% N=1367 Z=-38457.5(0.00%) \| Like=-38445.21..-0.00 [-40839.0816..-20283.7951] \| it/evals=1952/23379 eff=78.6278% N=1367 Z=-35102.7(0.00%) \| Like=-35093.29..-0.00 [-40839.0816..-20283.7951] \| it/evals=2075/23442 eff=79.5642% N=1367 Z=-34982.2(0.00%) \| Like=-34917.81..-0.00 [-40839.0816..-20283.7951] \| it/evals=2080/23442 eff=79.8648% N=1367 Z=-33126.3(0.00%) \| Like=-33087.46..-0.00 [-40839.0816..-20283.7951] \| it/evals=2151/23516 eff=78.0783% N=1367 Z=-30972.5(0.00%) \| Like=-30958.08..-0.00 [-40839.0816..-20283.7951] \| it/evals=2240/23568 eff=78.3802% N=1367 Z=-30472.5(0.00%) \| Like=-30381.09..-0.00 [-40839.0816..-20283.7951] \| it/evals=2272/23568 eff=79.3411% N=1367 Z=-27663.6(0.00%) \| Like=-27619.70..-0.00 [-40839.0816..-20283.7951] \| it/evals=2404/23652 eff=79.1694% N=1367 Z=-27023.9(0.00%) \| Like=-26954.52..-0.00 [-40839.0816..-20283.7951] \| it/evals=2432/23652 eff=79.8832% N=1367 Z=-26425.7(0.00%) \| Like=-26407.73..-0.00 [-40839.0816..-20283.7951] \| it/evals=2458/23692 eff=78.6211% N=1367 Z=-26287.4(0.00%) \| Like=-26248.78..-0.00 [-40839.0816..-20283.7951] \| it/evals=2464/23692 eff=78.8741% N=1367 Z=-25544.6(0.00%) \| Like=-25534.48..-0.00 [-40839.0816..-20283.7951] \| it/evals=2496/23692 eff=79.8229% N=1367 Z=-24292.2(0.00%) \| Like=-24270.10..-0.00 [-40839.0816..-20283.7951] \| it/evals=2560/23757 eff=78.8578% N=1367 Z=-23053.4(0.00%) \| Like=-23035.53..-0.00 [-40839.0816..-20283.7951] \| it/evals=2624/23817 eff=78.0188% N=1367 Z=-21981.5(0.00%) \| Like=-21961.22..-0.00 [-40839.0816..-20283.7951] \| it/evals=2688/23817 eff=79.2497% N=1367 Z=-21026.3(0.00%) \| Like=-21006.52..-0.00 [-40839.0816..-20283.7951] \| it/evals=2752/23879 eff=78.2805% N=1367 Z=-20797.4(0.00%) \| Like=-20779.19..-0.00 [-40839.0816..-20283.7951] \| it/evals=2764/23879 eff=78.5633% N=1367 Z=-20576.0(0.00%) \| Like=-20539.90..-0.00 [-40839.0816..-20283.7951] \| it/evals=2784/23898 eff=78.2876% N=1367 Z=-19135.0(0.00%) \| Like=-19112.44..-0.00 [-20246.2291..-10136.9334] \| it/evals=2880/23948 eff=78.6609% N=1367 Z=-18084.0(0.00%) \| Like=-18032.94..-0.00 [-20246.2291..-10136.9334] \| it/evals=2944/23998 eff=78.1664% N=1367 Z=-17224.2(0.00%) \| Like=-17206.57..-0.00 [-20246.2291..-10136.9334] \| it/evals=3008/24037 eff=78.1412% N=1367 Z=-16624.7(0.00%) \| Like=-16607.32..-0.00 [-20246.2291..-10136.9334] \| it/evals=3071/24091 eff=78.0808% N=1367 Z=-15375.4(0.00%) \| Like=-15354.26..-0.00 [-20246.2291..-10136.9334] \| it/evals=3168/24154 eff=78.1204% N=1367 Z=-15007.6(0.00%) \| Like=-14988.86..-0.00 [-20246.2291..-10136.9334] \| it/evals=3200/24170 eff=78.4361% N=1367 Z=-14683.6(0.00%) \| Like=-14655.76..-0.00 [-20246.2291..-10136.9334] \| it/evals=3232/24195 eff=78.2150% N=1367 Z=-13582.1(0.00%) \| Like=-13564.64..-0.00 [-20246.2291..-10136.9334] \| it/evals=3328/24258 eff=78.1090% N=1367 Z=-13277.7(0.00%) \| Like=-13247.86..-0.00 [-20246.2291..-10136.9334] \| it/evals=3360/24286 eff=78.0230% N=1367 Z=-13008.2(0.00%) \| Like=-12998.38..-0.00 [-20246.2291..-10136.9334] \| it/evals=3379/24296 eff=78.1693% N=1367 Z=-12913.2(0.00%) \| Like=-12897.91..-0.00 [-20246.2291..-10136.9334] \| it/evals=3392/24308 eff=77.9700% N=1367 Z=-12664.1(0.00%) \| Like=-12652.44..-0.00 [-20246.2291..-10136.9334] \| it/evals=3424/24320 eff=78.0896% N=1367 Z=-12409.4(0.00%) \| Like=-12388.48..-0.00 [-20246.2291..-10136.9334] \| it/evals=3456/24335 eff=78.5522% N=1367 Z=-11620.5(0.00%) \| Like=-11582.93..-0.00 [-20246.2291..-10136.9334] \| it/evals=3552/24385 eff=78.4960% N=1367 Z=-11082.9(0.00%) \| Like=-11065.76..-0.00 [-20246.2291..-10136.9334] \| it/evals=3616/24441 eff=78.4549% N=1367 Z=-10850.9(0.00%) \| Like=-10838.93..-0.00 [-20246.2291..-10136.9334] \| it/evals=3648/24470 eff=78.1263% N=1367 Z=-10650.6(0.00%) \| Like=-10639.10..-0.00 [-20246.2291..-10136.9334] \| it/evals=3680/24478 eff=78.4115% N=1367 Z=-10628.7(0.00%) \| Like=-10617.44..-0.00 [-20246.2291..-10136.9334] \| it/evals=3685/24488 eff=78.1658% N=1367 Z=-10178.9(0.00%) \| Like=-10167.27..-0.00 [-20246.2291..-10136.9334] \| it/evals=3744/24527 eff=78.5182% N=1367 Z=-9708.3(0.00%) \| Like=-9696.46..-0.00 [-10134.5674..-5086.2764] \| it/evals=3808/24566 eff=78.3707% N=1367 Z=-9465.1(0.00%) \| Like=-9447.09..-0.00 [-10134.5674..-5086.2764] \| it/evals=3840/24579 eff=78.5656% N=1367 Z=-9298.3(0.00%) \| Like=-9287.10..-0.00 [-10134.5674..-5086.2764] \| it/evals=3872/24599 eff=78.7379% N=1367 Z=-8460.0(0.00%) \| Like=-8441.72..-0.00 [-10134.5674..-5086.2764] \| it/evals=3991/24689 eff=78.5881% N=1367 Z=-8430.8(0.00%) \| Like=-8400.14..-0.00 [-10134.5674..-5086.2764] \| it/evals=4000/24698 eff=78.5852% N=1367 Z=-8247.5(0.00%) \| Like=-8236.69..-0.00 [-10134.5674..-5086.2764] \| it/evals=4032/24719 eff=78.7193% N=1367 Z=-7456.4(0.00%) \| Like=-7441.33..-0.00 [-10134.5674..-5086.2764] \| it/evals=4154/24798 eff=78.7868% N=1367 Z=-7421.5(0.00%) \| Like=-7410.18..-0.00 [-10134.5674..-5086.2764] \| it/evals=4160/24798 eff=78.8612% N=1367 Z=-6754.4(0.00%) \| Like=-6731.95..-0.00 [-10134.5674..-5086.2764] \| it/evals=4290/24874 eff=78.9359% N=1367 Z=-6715.0(0.00%) \| Like=-6688.55..-0.00 [-10134.5674..-5086.2764] \| it/evals=4298/24874 eff=79.0445% N=1367 Z=-6632.3(0.00%) \| Like=-6621.66..-0.00 [-10134.5674..-5086.2764] \| it/evals=4320/24888 eff=78.9341% N=1367 Z=-6265.4(0.00%) \| Like=-6249.26..-0.00 [-10134.5674..-5086.2764] \| it/evals=4416/24931 eff=79.1135% N=1367 Z=-5663.0(0.00%) \| Like=-5646.45..-0.00 [-10134.5674..-5086.2764] \| it/evals=4542/25014 eff=79.0561% N=1367 Z=-5475.1(0.00%) \| Like=-5463.30..-0.00 [-10134.5674..-5086.2764] \| it/evals=4576/25038 eff=79.0229% N=1367 Z=-5332.7(0.00%) \| Like=-5311.10..-0.00 [-10134.5674..-5086.2764] \| it/evals=4604/25065 eff=78.8761% N=1367 Z=-5312.4(0.00%) \| Like=-5301.13..-0.00 [-10134.5674..-5086.2764] \| it/evals=4608/25065 eff=78.9100% N=1367 Z=-4957.4(0.00%) \| Like=-4946.54..-0.00 [-5072.1175..-2642.5397] \| it/evals=4713/25220 eff=76.9379% N=1367 Z=-4906.8(0.00%) \| Like=-4894.92..-0.00 [-5072.1175..-2642.5397] \| it/evals=4736/25220 eff=77.2917% N=1367 Z=-4813.7(0.00%) \| Like=-4801.97..-0.00 [-5072.1175..-2642.5397] \| it/evals=4768/25220 eff=77.7420% N=1367 Z=-4682.5(0.00%) \| Like=-4668.12..-0.00 [-5072.1175..-2642.5397] \| it/evals=4800/25220 eff=78.2567% N=1367 Z=-4366.9(0.00%) \| Like=-4356.02..-0.00 [-5072.1175..-2642.5397] \| it/evals=4896/25348 eff=76.5215% N=1367 Z=-4337.6(0.00%) \| Like=-4324.16..-0.00 [-5072.1175..-2642.5397] \| it/evals=4910/25348 eff=76.7995% N=1367 Z=-4181.1(0.00%) \| Like=-4163.43..-0.00 [-5072.1175..-2642.5397] \| it/evals=4960/25348 eff=77.4791% N=1367 Z=-4081.6(0.00%) \| Like=-4070.76..-0.00 [-5072.1175..-2642.5397] \| it/evals=4992/25348 eff=78.0970% N=1367 Z=-3998.4(0.00%) \| Like=-3985.59..-0.00 [-5072.1175..-2642.5397] \| it/evals=5024/25348 eff=78.5604% N=1367 Z=-3720.7(0.00%) \| Like=-3703.78..-0.00 [-5072.1175..-2642.5397] \| it/evals=5120/25414 eff=78.4136% N=1367 Z=-3487.6(0.00%) \| Like=-3475.45..-0.00 [-5072.1175..-2642.5397] \| it/evals=5219/25477 eff=78.4611% N=1367 Z=-3358.5(0.00%) \| Like=-3343.71..-0.00 [-5072.1175..-2642.5397] \| it/evals=5280/25513 eff=78.5714% N=1367 Z=-3286.7(0.00%) \| Like=-3273.52..-0.00 [-5072.1175..-2642.5397] \| it/evals=5312/25540 eff=78.5360% N=1367 Z=-3147.1(0.00%) \| Like=-3132.22..-0.00 [-5072.1175..-2642.5397] \| it/evals=5376/25678 eff=76.6470% N=1367 Z=-3047.1(0.00%) \| Like=-3036.11..-0.00 [-5072.1175..-2642.5397] \| it/evals=5408/25678 eff=77.1236% N=1367 Z=-2823.7(0.00%) \| Like=-2808.69..-0.00 [-5072.1175..-2642.5397] \| it/evals=5525/25806 eff=75.9405% N=1367 Z=-2792.1(0.00%) \| Like=-2777.92..-0.00 [-5072.1175..-2642.5397] \| it/evals=5536/25806 eff=76.0758% N=1367 Z=-2615.9(0.00%) \| Like=-2600.48..-0.00 [-2638.0754..-1326.0440] \| it/evals=5632/25806 eff=77.2395% N=1367 Z=-2461.1(0.00%) \| Like=-2449.05..-0.00 [-2638.0754..-1326.0440] \| it/evals=5696/25806 eff=77.9432% N=1367 Z=-2243.1(0.00%) \| Like=-2231.89..-0.00 [-2638.0754..-1326.0440] \| it/evals=5817/25892 eff=77.8101% N=1367 Z=-2236.1(0.00%) \| Like=-2221.79..-0.00 [-2638.0754..-1326.0440] \| it/evals=5824/25897 eff=77.8394% N=1367 Z=-2225.4(0.00%) \| Like=-2213.82..-0.00 [-2638.0754..-1326.0440] \| it/evals=5832/25900 eff=77.8042% N=1367 Z=-2139.1(0.00%) \| Like=-2127.89..-0.00 [-2638.0754..-1326.0440] \| it/evals=5888/25943 eff=77.8706% N=1367 Z=-2099.1(0.00%) \| Like=-2086.76..-0.00 [-2638.0754..-1326.0440] \| it/evals=5920/26078 eff=75.5231% N=1367 Z=-2050.8(0.00%) \| Like=-2034.23..-0.00 [-2638.0754..-1326.0440] \| it/evals=5952/26078 eff=75.9012% N=1367 Z=-1909.6(0.00%) \| Like=-1897.66..-0.00 [-2638.0754..-1326.0440] \| it/evals=6048/26078 eff=76.9095% N=1367 Z=-1862.7(0.00%) \| Like=-1850.29..-0.00 [-2638.0754..-1326.0440] \| it/evals=6080/26078 eff=77.2372% N=1367 Z=-1816.0(0.00%) \| Like=-1804.71..-0.00 [-2638.0754..-1326.0440] \| it/evals=6112/26078 eff=77.5649% N=1367 Z=-1781.3(0.00%) \| Like=-1768.12..-0.00 [-2638.0754..-1326.0440] \| it/evals=6138/26078 eff=77.9430% N=1367 Z=-1734.1(0.00%) \| Like=-1722.11..-0.00 [-2638.0754..-1326.0440] \| it/evals=6176/26209 eff=75.8175% N=1367 Z=-1701.8(0.00%) \| Like=-1690.14..-0.00 [-2638.0754..-1326.0440] \| it/evals=6208/26209 eff=76.3543% N=1367 Z=-1614.1(0.00%) \| Like=-1601.53..-0.00 [-2638.0754..-1326.0440] \| it/evals=6272/26209 eff=77.0620% N=1367 Z=-1570.6(0.00%) \| Like=-1558.80..-0.00 [-2638.0754..-1326.0440] \| it/evals=6304/26209 eff=77.4524% N=1367 Z=-1536.5(0.00%) \| Like=-1524.46..-0.00 [-2638.0754..-1326.0440] \| it/evals=6336/26209 eff=77.8184% N=1367 Z=-1508.9(0.00%) \| Like=-1496.65..-0.00 [-2638.0754..-1326.0440] \| it/evals=6368/26337 eff=75.9110% N=1367 Z=-1430.0(0.00%) \| Like=-1417.67..-0.00 [-2638.0754..-1326.0440] \| it/evals=6444/26337 eff=76.7156% N=1367 Z=-1299.7(0.00%) \| Like=-1287.21..-0.00 [-1324.5454..-687.8940] \| it/evals=6575/26465 eff=75.9072% N=1367 Z=-1266.1(0.00%) \| Like=-1254.76..-0.00 [-1324.5454..-687.8940] \| it/evals=6624/26465 eff=76.3436% N=1367 Z=-1239.6(0.00%) \| Like=-1226.95..-0.00 [-1324.5454..-687.8940] \| it/evals=6656/26465 eff=76.8718% N=1367 Z=-1221.3(0.00%) \| Like=-1208.32..-0.00 [-1324.5454..-687.8940] \| it/evals=6674/26465 eff=77.0326% N=1367 Z=-1160.7(0.00%) \| Like=-1148.74..-0.00 [-1324.5454..-687.8940] \| it/evals=6752/26465 eff=77.9054% N=1367 Z=-1131.3(0.00%) \| Like=-1120.09..-0.00 [-1324.5454..-687.8940] \| it/evals=6784/26598 eff=75.9305% N=1367 Z=-1110.9(0.00%) \| Like=-1099.55..-0.00 [-1324.5454..-687.8940] \| it/evals=6816/26598 eff=76.3316% N=1367 Z=-1058.7(0.00%) \| Like=-1046.28..-0.00 [-1324.5454..-687.8940] \| it/evals=6880/26598 eff=77.1117% N=1367 Z=-1013.5(0.00%) \| Like=-1001.90..-0.00 [-1324.5454..-687.8940] \| it/evals=6944/26598 eff=77.8917% N=1367 Z=-1011.4(0.00%) \| Like=-999.47..-0.00 [-1324.5454..-687.8940] \| it/evals=6949/26598 eff=77.9140% N=1367 Z=-994.7(0.00%) \| Like=-982.66..-0.00 [-1324.5454..-687.8940] \| it/evals=6976/26729 eff=76.0286% N=1367 Z=-968.5(0.00%) \| Like=-956.23..-0.00 [-1324.5454..-687.8940] \| it/evals=7008/26729 eff=76.5266% N=1367 Z=-947.9(0.00%) \| Like=-935.89..-0.00 [-1324.5454..-687.8940] \| it/evals=7040/26729 eff=76.8298% N=1367 Z=-885.1(0.00%) \| Like=-872.75..-0.00 [-1324.5454..-687.8940] \| it/evals=7136/26729 eff=77.9558% N=1367 Z=-827.5(0.00%) \| Like=-814.60..-0.00 [-1324.5454..-687.8940] \| it/evals=7232/26857 eff=76.8226% N=1367 Z=-811.3(0.00%) \| Like=-799.15..-0.00 [-1324.5454..-687.8940] \| it/evals=7255/26857 eff=77.1176% N=1367 Z=-777.6(0.00%) \| Like=-765.80..-0.00 [-1324.5454..-687.8940] \| it/evals=7328/26857 eff=77.9182% N=1367 Z=-758.4(0.00%) \| Like=-746.72..-0.00 [-1324.5454..-687.8940] \| it/evals=7360/26988 eff=76.1739% N=1367 Z=-715.7(0.00%) \| Like=-703.92..-0.00 [-1324.5454..-687.8940] \| it/evals=7456/26988 eff=77.1171% N=1367 Z=-699.5(0.00%) \| Like=-687.85..-0.00 [-687.8545..-350.2747] \| it/evals=7488/26988 eff=77.3631% N=1367 Z=-671.8(0.00%) \| Like=-658.11..-0.00 [-687.8545..-350.2747] \| it/evals=7552/26988 eff=78.0193% N=1367 Z=-664.6(0.00%) \| Like=-652.30..-0.00 [-687.8545..-350.2747] \| it/evals=7562/27116 eff=76.1239% N=1367 Z=-622.8(0.00%) \| Like=-610.91..-0.00 [-687.8545..-350.2747] \| it/evals=7648/27116 eff=76.9830% N=1367 Z=-596.9(0.00%) \| Like=-584.46..-0.00 [-687.8545..-350.2747] \| it/evals=7712/27116 eff=77.5624% N=1367 Z=-560.6(0.00%) \| Like=-548.04..-0.00 [-687.8545..-350.2747] \| it/evals=7808/27245 eff=76.5095% N=1367 Z=-549.5(0.00%) \| Like=-537.70..-0.00 [-687.8545..-350.2747] \| it/evals=7840/27245 eff=76.8017% N=1367 Z=-534.7(0.00%) \| Like=-522.74..-0.00 [-687.8545..-350.2747] \| it/evals=7873/27245 eff=77.1718% N=1367 Z=-518.8(0.00%) \| Like=-505.87..-0.00 [-687.8545..-350.2747] \| it/evals=7904/27245 eff=77.4640% N=1367 Z=-501.1(0.00%) \| Like=-489.30..-0.00 [-687.8545..-350.2747] \| it/evals=7968/27373 eff=76.2638% N=1367 Z=-488.2(0.00%) \| Like=-475.66..-0.00 [-687.8545..-350.2747] \| it/evals=8000/27373 eff=76.6819% N=1367 Z=-462.8(0.00%) \| Like=-450.94..-0.00 [-687.8545..-350.2747] \| it/evals=8064/27373 eff=77.2140% N=1367 Z=-451.7(0.00%) \| Like=-439.45..-0.00 [-687.8545..-350.2747] \| it/evals=8096/27373 eff=77.5371% N=1367 Z=-432.0(0.00%) \| Like=-419.86..-0.00 [-687.8545..-350.2747] \| it/evals=8160/27501 eff=76.2338% N=1367 Z=-428.2(0.00%) \| Like=-415.99..-0.00 [-687.8545..-350.2747] \| it/evals=8179/27501 eff=76.4378% N=1367 Z=-386.0(0.00%) \| Like=-373.03..-0.00 [-687.8545..-350.2747] \| it/evals=8320/27501 eff=77.6438% N=1367 Z=-369.9(0.00%) \| Like=-358.44..-0.00 [-687.8545..-350.2747] \| it/evals=8384/27629 eff=76.4226% N=1367 Z=-343.9(0.00%) \| Like=-331.86..-0.00 [-350.2058..-170.9640] \| it/evals=8485/27629 eff=77.4012% N=1367 Z=-331.8(0.00%) \| Like=-320.00..-0.00 [-350.2058..-170.9640] \| it/evals=8544/27760 eff=76.2259% N=1367 Z=-325.8(0.00%) \| Like=-313.38..-0.00 [-350.2058..-170.9640] \| it/evals=8576/27760 eff=76.4914% N=1367 Z=-310.3(0.00%) \| Like=-298.21..-0.00 [-350.2058..-170.9640] \| it/evals=8640/27760 eff=77.0579% N=1367 Z=-303.0(0.00%) \| Like=-291.71..-0.00 [-350.2058..-170.9640] \| it/evals=8672/27760 eff=77.3234% N=1367 Z=-276.0(0.00%) \| Like=-264.15..-0.00 [-350.2058..-170.9640] \| it/evals=8791/27888 eff=76.7007% N=1367 Z=-268.2(0.00%) \| Like=-255.71..-0.00 [-350.2058..-170.9640] \| it/evals=8832/27888 eff=77.0296% N=1367 Z=-261.8(0.00%) \| Like=-249.61..-0.00 [-350.2058..-170.9640] \| it/evals=8864/27888 eff=77.2719% N=1367 Z=-256.1(0.00%) \| Like=-243.29..-0.00 [-350.2058..-170.9640] \| it/evals=8896/27888 eff=77.5662% N=1367 Z=-249.1(0.00%) \| Like=-237.18..-0.00 [-350.2058..-170.9640] \| it/evals=8928/28020 eff=76.0535% N=1367 Z=-237.3(0.00%) \| Like=-225.33..-0.00 [-350.2058..-170.9640] \| it/evals=8992/28020 eff=76.6796% N=1367 Z=-233.9(0.00%) \| Like=-222.09..-0.00 [-350.2058..-170.9640] \| it/evals=9012/28020 eff=76.8320% N=1367 Z=-232.0(0.00%) \| Like=-219.92..-0.00 [-350.2058..-170.9640] \| it/evals=9024/28020 eff=76.9673% N=1367 Z=-219.9(0.00%) \| Like=-208.09..-0.00 [-350.2058..-170.9640] \| it/evals=9088/28020 eff=77.4920% N=1367 Z=-214.9(0.00%) \| Like=-203.30..-0.00 [-350.2058..-170.9640] \| it/evals=9120/28149 eff=76.1179% N=1367 Z=-210.5(0.00%) \| Like=-198.78..-0.00 [-350.2058..-170.9640] \| it/evals=9152/28149 eff=76.3995% N=1367 Z=-192.5(0.00%) \| Like=-180.40..-0.00 [-350.2058..-170.9640] \| it/evals=9288/28149 eff=77.5091% N=1367 Z=-188.6(0.00%) \| Like=-175.97..-0.00 [-350.2058..-170.9640] \| it/evals=9318/28277 eff=76.2082% N=1367 Z=-185.3(0.00%) \| Like=-173.61..-0.00 [-350.2058..-170.9640] \| it/evals=9344/28277 eff=76.4677% N=1367 Z=-182.3(0.00%) \| Like=-170.56..-0.00 [-170.9432..-86.0482] \| it/evals=9374/28277 eff=76.7272% N=1367 Z=-182.1(0.00%) \| Like=-170.15..-0.00 [-170.9432..-86.0482] \| it/evals=9376/28277 eff=76.7596% N=1367 Z=-178.6(0.00%) \| Like=-166.48..-0.00 [-170.9432..-86.0482] \| it/evals=9408/28277 eff=77.0029% N=1367 Z=-167.1(0.00%) \| Like=-155.21..-0.00 [-170.9432..-86.0482] \| it/evals=9504/28405 eff=76.1678% N=1367 Z=-164.3(0.00%) \| Like=-152.60..-0.00 [-170.9432..-86.0482] \| it/evals=9536/28405 eff=76.4697% N=1367 Z=-161.5(0.00%) \| Like=-149.99..-0.00 [-170.9432..-86.0482] \| it/evals=9568/28405 eff=76.6444% N=1367 Z=-154.8(0.00%) \| Like=-142.39..-0.00 [-170.9432..-86.0482] \| it/evals=9632/28405 eff=77.2005% N=1367 Z=-150.8(0.00%) \| Like=-138.99..-0.00 [-170.9432..-86.0482] \| it/evals=9664/28405 eff=77.4071% N=1367 Z=-149.1(0.00%) \| Like=-137.07..-0.00 [-170.9432..-86.0482] \| it/evals=9683/28533 eff=76.0355% N=1367 Z=-148.6(0.00%) \| Like=-136.77..-0.00 [-170.9432..-86.0482] \| it/evals=9689/28533 eff=76.0666% N=1367 Z=-147.9(0.00%) \| Like=-135.85..-0.00 [-170.9432..-86.0482] \| it/evals=9696/28533 eff=76.1601% N=1367 Z=-141.8(0.00%) \| Like=-129.59..-0.00 [-170.9432..-86.0482] \| it/evals=9760/28533 eff=76.6116% N=1367 Z=-135.5(0.00%) \| Like=-123.71..-0.00 [-170.9432..-86.0482] \| it/evals=9824/28533 eff=77.1878% N=1367 Z=-132.8(0.00%) \| Like=-121.11..-0.00 [-170.9432..-86.0482] \| it/evals=9856/28661 eff=75.9389% N=1367 Z=-128.0(0.00%) \| Like=-115.94..-0.00 [-170.9432..-86.0482] \| it/evals=9914/28661 eff=76.4427% N=1367 Z=-123.8(0.00%) \| Like=-111.79..-0.00 [-170.9432..-86.0482] \| it/evals=9962/28661 eff=76.7634% N=1367 Z=-119.8(0.00%) \| Like=-107.76..-0.00 [-170.9432..-86.0482] \| it/evals=10016/28661 eff=77.1908% N=1367 Z=-119.0(0.00%) \| Like=-107.07..-0.00 [-170.9432..-86.0482] \| it/evals=10027/28661 eff=77.2214% N=1367 Z=-114.3(0.00%) \| Like=-101.54..-0.00 [-170.9432..-86.0482] \| it/evals=10080/28789 eff=76.1605% N=1367 Z=-112.1(0.00%) \| Like=-99.94..-0.00 [-170.9432..-86.0482] \| it/evals=10100/28789 eff=76.2803% N=1367 Z=-111.4(0.00%) \| Like=-99.38..-0.00 [-170.9432..-86.0482] \| it/evals=10109/28789 eff=76.3252% N=1367 Z=-111.2(0.00%) \| Like=-99.21..-0.00 [-170.9432..-86.0482] \| it/evals=10112/28789 eff=76.3552% N=1367 Z=-108.7(0.00%) \| Like=-96.63..-0.00 [-170.9432..-86.0482] \| it/evals=10144/28789 eff=76.6397% N=1367 Z=-106.4(0.00%) \| Like=-94.45..-0.00 [-170.9432..-86.0482] \| it/evals=10176/28789 eff=76.8943% N=1367 Z=-105.9(0.00%) \| Like=-94.08..-0.00 [-170.9432..-86.0482] \| it/evals=10184/28789 eff=76.9093% N=1367 Z=-104.5(0.00%) \| Like=-92.57..-0.00 [-170.9432..-86.0482] \| it/evals=10208/28789 eff=77.1638% N=1367 Z=-103.1(0.00%) \| Like=-91.10..-0.00 [-170.9432..-86.0482] \| it/evals=10234/28917 eff=75.8742% N=1367 Z=-100.8(0.00%) \| Like=-88.97..-0.00 [-170.9432..-86.0482] \| it/evals=10272/28917 eff=76.2562% N=1367 Z=-93.8(0.00%) \| Like=-81.88..-0.00 [-86.0274..-42.3187] \| it/evals=10394/28917 eff=77.3435% N=1367 Z=-93.4(0.00%) \| Like=-81.44..-0.00 [-86.0274..-42.3187] \| it/evals=10400/28917 eff=77.3729% N=1367 Z=-91.5(0.00%) \| Like=-79.34..-0.00 [-86.0274..-42.3187] \| it/evals=10432/29045 eff=76.2475% N=1367 Z=-89.6(0.00%) \| Like=-77.69..-0.00 [-86.0274..-42.3187] \| it/evals=10464/29045 eff=76.5215% N=1367 Z=-85.8(0.00%) \| Like=-73.89..-0.00 [-86.0274..-42.3187] \| it/evals=10528/29045 eff=76.9253% N=1367 Z=-85.2(0.00%) \| Like=-73.29..-0.00 [-86.0274..-42.3187] \| it/evals=10540/29045 eff=77.0118% N=1367 Z=-84.3(0.00%) \| Like=-72.34..-0.00 [-86.0274..-42.3187] \| it/evals=10560/29045 eff=77.1705% N=1367 Z=-82.8(0.00%) \| Like=-71.10..-0.00 [-86.0274..-42.3187] \| it/evals=10592/29173 eff=76.0125% N=1367 Z=-81.3(0.00%) \| Like=-69.12..-0.00 [-86.0274..-42.3187] \| it/evals=10626/29173 eff=76.2390% N=1367 Z=-79.9(0.00%) \| Like=-67.82..-0.00 [-86.0274..-42.3187] \| it/evals=10656/29173 eff=76.4514% N=1367 Z=-79.1(0.00%) \| Like=-66.91..-0.00 [-86.0274..-42.3187] \| it/evals=10673/29173 eff=76.5364% N=1367 Z=-78.3(0.00%) \| Like=-66.26..-0.00 [-86.0274..-42.3187] \| it/evals=10688/29173 eff=76.7063% N=1367 Z=-75.9(0.00%) \| Like=-63.97..-0.00 [-86.0274..-42.3187] \| it/evals=10747/29173 eff=77.1453% N=1367 Z=-75.7(0.00%) \| Like=-63.71..-0.00 [-86.0274..-42.3187] \| it/evals=10752/29173 eff=77.1878% N=1367 Z=-74.3(0.00%) \| Like=-62.42..-0.00 [-86.0274..-42.3187] \| it/evals=10787/29301 eff=76.0779% N=1367 Z=-73.0(0.00%) \| Like=-60.94..-0.00 [-86.0274..-42.3187] \| it/evals=10816/29301 eff=76.3143% N=1367 Z=-71.5(0.00%) \| Like=-59.38..-0.00 [-86.0274..-42.3187] \| it/evals=10848/29301 eff=76.4812% N=1367 Z=-68.0(0.00%) \| Like=-55.95..-0.00 [-86.0274..-42.3187] \| it/evals=10944/29301 eff=77.0932% N=1367 Z=-67.2(0.00%) \| Like=-55.09..-0.00 [-86.0274..-42.3187] \| it/evals=10962/29301 eff=77.1905% N=1367 Z=-66.6(0.00%) \| Like=-54.48..-0.00 [-86.0274..-42.3187] \| it/evals=10976/29301 eff=77.2879% N=1367 Z=-65.3(0.00%) \| Like=-53.20..-0.00 [-86.0274..-42.3187] \| it/evals=11008/29429 eff=76.2230% N=1367 Z=-64.0(0.00%) \| Like=-51.86..-0.00 [-86.0274..-42.3187] \| it/evals=11040/29429 eff=76.5236% N=1367 Z=-63.1(0.00%) \| Like=-50.92..-0.00 [-86.0274..-42.3187] \| it/evals=11060/29429 eff=76.6193% N=1367 Z=-61.4(0.00%) \| Like=-49.10..-0.00 [-86.0274..-42.3187] \| it/evals=11100/29429 eff=76.8106% N=1367 Z=-61.2(0.00%) \| Like=-48.98..-0.00 [-86.0274..-42.3187] \| it/evals=11104/29429 eff=76.8516% N=1367 Z=-60.0(0.00%) \| Like=-47.75..-0.00 [-86.0274..-42.3187] \| it/evals=11136/29429 eff=77.0292% N=1367 Z=-59.1(0.00%) \| Like=-46.92..-0.00 [-86.0274..-42.3187] \| it/evals=11156/29429 eff=77.1522% N=1367 Z=-58.7(0.00%) \| Like=-46.58..-0.00 [-86.0274..-42.3187] \| it/evals=11168/29429 eff=77.3025% N=1367 Z=-58.4(0.00%) \| Like=-46.33..-0.00 [-86.0274..-42.3187] \| it/evals=11176/29429 eff=77.3299% N=1367 Z=-57.7(0.00%) \| Like=-45.78..-0.00 [-86.0274..-42.3187] \| it/evals=11196/29429 eff=77.4665% N=1367 Z=-57.6(0.00%) \| Like=-45.65..-0.00 [-86.0274..-42.3187] \| it/evals=11200/29429 eff=77.5212% N=1367 Z=-55.4(0.00%) \| Like=-43.42..-0.00 [-86.0274..-42.3187] \| it/evals=11264/29557 eff=76.5915% N=1367 Z=-53.4(0.00%) \| Like=-41.25..-0.00 [-42.3073..-20.4432] \| it/evals=11328/29557 eff=77.0346% N=1367 Z=-51.6(0.00%) \| Like=-39.42..-0.00 [-42.3073..-20.4432] \| it/evals=11383/29557 eff=77.4376% N=1367 Z=-50.4(0.00%) \| Like=-38.29..-0.00 [-42.3073..-20.4432] \| it/evals=11422/29685 eff=76.4193% N=1367 Z=-50.3(0.00%) \| Like=-38.25..-0.00 [-42.3073..-20.4432] \| it/evals=11424/29685 eff=76.4457% N=1367 Z=-49.6(0.00%) \| Like=-37.35..-0.00 [-42.3073..-20.4432] \| it/evals=11447/29685 eff=76.6570% N=1367 Z=-49.2(0.00%) \| Like=-37.13..-0.00 [-42.3073..-20.4432] \| it/evals=11459/29685 eff=76.7230% N=1367 Z=-48.3(0.00%) \| Like=-36.21..-0.00 [-42.3073..-20.4432] \| it/evals=11488/29685 eff=76.9739% N=1367 Z=-46.6(0.00%) \| Like=-34.81..-0.00 [-42.3073..-20.4432] \| it/evals=11552/29685 eff=77.3964% N=1367 Z=-45.9(0.00%) \| Like=-34.04..-0.00 [-42.3073..-20.4432] \| it/evals=11588/29685 eff=77.5680% N=1367 Z=-45.2(0.00%) \| Like=-33.16..-0.00 [-42.3073..-20.4432] \| it/evals=11616/29813 eff=76.5256% N=1367 Z=-44.4(0.00%) \| Like=-32.56..-0.00 [-42.3073..-20.4432] \| it/evals=11648/29813 eff=76.7333% N=1367 Z=-43.8(0.00%) \| Like=-31.99..-0.00 [-42.3073..-20.4432] \| it/evals=11677/29813 eff=76.9151% N=1367 Z=-43.8(0.00%) \| Like=-31.96..-0.00 [-42.3073..-20.4432] \| it/evals=11680/29813 eff=76.9540% N=1367 Z=-42.4(0.00%) \| Like=-30.29..-0.00 [-42.3073..-20.4432] \| it/evals=11744/29813 eff=77.4474% N=1367 Z=-40.0(0.00%) \| Like=-27.87..-0.00 [-42.3073..-20.4432] \| it/evals=11843/29941 eff=76.8582% N=1367 Z=-39.5(0.00%) \| Like=-27.31..-0.00 [-42.3073..-20.4432] \| it/evals=11866/29941 eff=77.0115% N=1367 Z=-39.3(0.00%) \| Like=-27.23..-0.00 [-42.3073..-20.4432] \| it/evals=11872/29941 eff=77.0881% N=1367 Z=-39.0(0.00%) \| Like=-26.83..-0.00 [-42.3073..-20.4432] \| it/evals=11886/29941 eff=77.1775% N=1367 Z=-38.1(0.00%) \| Like=-26.00..-0.00 [-42.3073..-20.4432] \| it/evals=11927/29941 eff=77.4330% N=1367 Z=-37.9(0.00%) \| Like=-25.87..-0.00 [-42.3073..-20.4432] \| it/evals=11936/29941 eff=77.5096% N=1367 Z=-37.6(0.00%) \| Like=-25.52..-0.00 [-42.3073..-20.4432] \| it/evals=11952/29941 eff=77.6373% N=1367 Z=-36.8(0.00%) \| Like=-24.75..-0.00 [-42.3073..-20.4432] \| it/evals=11995/30069 eff=76.7027% N=1367 Z=-36.7(0.00%) \| Like=-24.61..-0.00 [-42.3073..-20.4432] \| it/evals=12000/30069 eff=76.7404% N=1367 Z=-36.6(0.00%) \| Like=-24.53..-0.00 [-42.3073..-20.4432] \| it/evals=12007/30069 eff=76.7655% N=1367 Z=-35.8(0.00%) \| Like=-23.92..-0.00 [-42.3073..-20.4432] \| it/evals=12051/30069 eff=77.0797% N=1367 Z=-35.3(0.00%) \| Like=-23.37..-0.00 [-42.3073..-20.4432] \| it/evals=12086/30069 eff=77.3184% N=1367 Z=-35.1(0.00%) \| Like=-23.14..-0.00 [-42.3073..-20.4432] \| it/evals=12096/30069 eff=77.3938% N=1367 Z=-34.6(0.00%) \| Like=-22.38..-0.00 [-42.3073..-20.4432] \| it/evals=12128/30069 eff=77.5823% N=1367 Z=-33.8(0.00%) \| Like=-21.81..-0.00 [-42.3073..-20.4432] \| it/evals=12169/30069 eff=77.7708% N=1367 Z=-33.5(0.00%) \| Like=-21.57..-0.00 [-42.3073..-20.4432] \| it/evals=12192/30069 eff=77.9467% N=1367 Z=-33.3(0.00%) \| Like=-21.41..-0.00 [-42.3073..-20.4432] \| it/evals=12203/30197 eff=76.7499% N=1367 Z=-32.7(0.00%) \| Like=-20.68..-0.00 [-42.3073..-20.4432] \| it/evals=12240/30197 eff=76.9725% N=1367 Z=-32.0(0.00%) \| Like=-20.00..-0.00 [-20.4335..-10.0318] \| it/evals=12288/30197 eff=77.3312% N=1367 Z=-31.5(0.00%) \| Like=-19.47..-0.00 [-20.4335..-10.0318] \| it/evals=12320/30197 eff=77.5291% N=1367 Z=-31.1(0.00%) \| Like=-19.01..-0.00 [-20.4335..-10.0318] \| it/evals=12352/30197 eff=77.7393% N=1367 Z=-30.6(0.00%) \| Like=-18.56..-0.00 [-20.4335..-10.0318] \| it/evals=12384/30197 eff=77.9372% N=1367 Z=-30.1(0.00%) \| Like=-18.09..-0.00 [-20.4335..-10.0318] \| it/evals=12418/30325 eff=76.8566% N=1367 Z=-29.7(0.00%) \| Like=-17.74..-0.00 [-20.4335..-10.0318] \| it/evals=12448/30325 eff=77.0757% N=1367 Z=-29.3(0.00%) \| Like=-17.36..-0.00 [-20.4335..-10.0318] \| it/evals=12482/30325 eff=77.2096% N=1367 Z=-29.1(0.00%) \| Like=-17.16..-0.00 [-20.4335..-10.0318] \| it/evals=12502/30325 eff=77.3314% N=1367 Z=-28.9(0.00%) \| Like=-17.04..-0.00 [-20.4335..-10.0318] \| it/evals=12514/30325 eff=77.4288% N=1367 Z=-28.3(0.00%) \| Like=-16.45..-0.00 [-20.4335..-10.0318] \| it/evals=12569/30325 eff=77.7940% N=1367 Z=-28.2(0.00%) \| Like=-16.39..-0.00 [-20.4335..-10.0318] \| it/evals=12576/30325 eff=77.8792% N=1367 Z=-28.1(0.00%) \| Like=-16.12..-0.00 [-20.4335..-10.0318] \| it/evals=12593/30325 eff=77.9888% N=1367 Z=-27.9(0.00%) \| Like=-15.99..-0.00 [-20.4335..-10.0318] \| it/evals=12604/30453 eff=76.8521% N=1367 Z=-27.8(0.00%) \| Like=-15.89..-0.00 [-20.4335..-10.0318] \| it/evals=12613/30453 eff=76.8880% N=1367 Z=-27.7(0.00%) \| Like=-15.73..-0.00 [-20.4335..-10.0318] \| it/evals=12628/30453 eff=76.9719% N=1367 Z=-26.8(0.00%) \| Like=-14.77..-0.00 [-20.4335..-10.0318] \| it/evals=12703/30453 eff=77.4275% N=1367 Z=-26.5(0.00%) \| Like=-14.53..-0.00 [-20.4335..-10.0318] \| it/evals=12729/30453 eff=77.5354% N=1367 Z=-26.5(0.00%) \| Like=-14.45..-0.00 [-20.4335..-10.0318] \| it/evals=12736/30453 eff=77.6193% N=1367 Z=-26.1(0.00%) \| Like=-14.13..-0.00 [-20.4335..-10.0318] \| it/evals=12768/30453 eff=77.8351% N=1367 Z=-25.8(0.00%) \| Like=-13.86..-0.00 [-20.4335..-10.0318] \| it/evals=12800/30453 eff=78.0269% N=1367 Z=-25.5(0.00%) \| Like=-13.56..-0.00 [-20.4335..-10.0318] \| it/evals=12833/30581 eff=77.0130% N=1367 Z=-25.4(0.00%) \| Like=-13.51..-0.00 [-20.4335..-10.0318] \| it/evals=12842/30581 eff=77.0484% N=1367 Z=-24.9(0.00%) \| Like=-12.95..-0.00 [-20.4335..-10.0318] \| it/evals=12896/30581 eff=77.3554% N=1367 Z=-24.7(0.00%) \| Like=-12.66..-0.00 [-20.4335..-10.0318] \| it/evals=12920/30581 eff=77.4380% N=1367 Z=-24.6(0.00%) \| Like=-12.57..-0.00 [-20.4335..-10.0318] \| it/evals=12928/30581 eff=77.4970% N=1367 Z=-24.4(0.00%) \| Like=-12.28..-0.00 [-20.4335..-10.0318] \| it/evals=12953/30581 eff=77.6033% N=1367 Z=-24.3(0.00%) \| Like=-12.20..-0.00 [-20.4335..-10.0318] \| it/evals=12960/30581 eff=77.6623% N=1367 Z=-24.1(0.00%) \| Like=-11.98..-0.00 [-20.4335..-10.0318] \| it/evals=12985/30581 eff=77.7804% N=1367 Z=-24.0(0.00%) \| Like=-11.92..-0.00 [-20.4335..-10.0318] \| it/evals=12992/30581 eff=77.8040% N=1367 Z=-23.7(0.00%) \| Like=-11.63..-0.00 [-20.4335..-10.0318] \| it/evals=13024/30581 eff=78.0519% N=1367 Z=-23.4(0.00%) \| Like=-11.37..-0.00 [-20.4335..-10.0318] \| it/evals=13058/30709 eff=77.0993% N=1367 Z=-23.3(0.00%) \| Like=-11.30..-0.00 [-20.4335..-10.0318] \| it/evals=13066/30709 eff=77.1226% N=1367 Z=-23.2(0.00%) \| Like=-11.22..-0.00 [-20.4335..-10.0318] \| it/evals=13079/30709 eff=77.1342% N=1367 Z=-23.1(0.00%) \| Like=-11.13..-0.00 [-20.4335..-10.0318] \| it/evals=13088/30709 eff=77.1807% N=1367 Z=-23.1(0.00%) \| Like=-11.12..-0.00 [-20.4335..-10.0318] \| it/evals=13092/30709 eff=77.1924% N=1367 Z=-23.0(0.00%) \| Like=-11.06..-0.00 [-20.4335..-10.0318] \| it/evals=13099/30709 eff=77.2156% N=1367 Z=-22.9(0.00%) \| Like=-10.93..-0.00 [-20.4335..-10.0318] \| it/evals=13120/30709 eff=77.4250% N=1367 Z=-22.7(0.00%) \| Like=-10.77..-0.00 [-20.4335..-10.0318] \| it/evals=13144/30709 eff=77.5762% N=1367 Z=-22.4(0.00%) \| Like=-10.45..-0.00 [-20.4335..-10.0318] \| it/evals=13179/30709 eff=77.7855% N=1367 Z=-22.4(0.00%) \| Like=-10.41..-0.00 [-20.4335..-10.0318] \| it/evals=13184/30709 eff=77.8204% N=1367 Z=-22.2(0.00%) \| Like=-10.16..-0.00 [-20.4335..-10.0318] \| it/evals=13209/30709 eff=77.9600% N=1367 Z=-22.1(0.00%) \| Like=-10.11..-0.00 [-20.4335..-10.0318] \| it/evals=13216/30709 eff=77.9833% N=1367 Z=-22.1(0.00%) \| Like=-10.03..-0.00 [-20.4335..-10.0318] \| it/evals=13226/30709 eff=78.0181% N=1367 Z=-21.2(0.01%) \| Like=-9.20..-0.00 [-10.0214..-5.1716] \| it/evals=13344/30837 eff=77.5957% N=1367 Z=-21.1(0.01%) \| Like=-9.10..-0.00 [-10.0214..-5.1716] \| it/evals=13353/30837 eff=77.6415% N=1367 Z=-20.3(0.03%) \| Like=-8.27..-0.00 [-10.0214..-5.1716] \| it/evals=13481/30965 eff=77.2758% N=1367 Z=-19.9(0.04%) \| Like=-7.99..-0.00 [-10.0214..-5.1716] \| it/evals=13536/30965 eff=77.5695% N=1367 Z=-19.6(0.05%) \| Like=-7.51..-0.00 [-10.0214..-5.1716] \| it/evals=13600/30965 eff=77.9309% N=1367 Z=-19.4(0.06%) \| Like=-7.35..-0.00 [-10.0214..-5.1716] \| it/evals=13632/30965 eff=78.1003% N=1367 Z=-19.2(0.08%) \| Like=-7.25..-0.00 [-10.0214..-5.1716] \| it/evals=13662/31093 eff=77.1543% N=1367 Z=-18.9(0.11%) \| Like=-6.96..-0.00 [-10.0214..-5.1716] \| it/evals=13728/31093 eff=77.5328% N=1367 Z=-18.7(0.12%) \| Like=-6.79..-0.00 [-10.0214..-5.1716] \| it/evals=13760/31093 eff=77.7221% N=1367 Z=-18.3(0.19%) \| Like=-6.35..-0.00 [-10.0214..-5.1716] \| it/evals=13856/31221 eff=77.0692% N=1367 Z=-18.2(0.22%) \| Like=-6.21..-0.00 [-10.0214..-5.1716] \| it/evals=13888/31221 eff=77.2119% N=1367 Z=-17.9(0.28%) \| Like=-6.04..-0.00 [-10.0214..-5.1716] \| it/evals=13952/31221 eff=77.5741% N=1367 Z=-17.8(0.30%) \| Like=-5.99..-0.00 [-10.0214..-5.1716] \| it/evals=13970/31221 eff=77.6619% N=1367 Z=-17.6(0.40%) \| Like=-5.72..-0.00 [-10.0214..-5.1716] \| it/evals=14048/31349 eff=76.9972% N=1367 Z=-17.4(0.45%) \| Like=-5.58..-0.00 [-10.0214..-5.1716] \| it/evals=14080/31349 eff=77.1812% N=1367 Z=-17.3(0.51%) \| Like=-5.43..-0.00 [-10.0214..-5.1716] \| it/evals=14112/31349 eff=77.3219% N=1367 Z=-17.2(0.57%) \| Like=-5.27..-0.00 [-10.0214..-5.1716] \| it/evals=14144/31349 eff=77.4843% N=1367 Z=-17.1(0.64%) \| Like=-5.17..-0.00 [-10.0214..-5.1716] \| it/evals=14176/31349 eff=77.7225% N=1367 Z=-17.0(0.71%) \| Like=-5.03..-0.00 [-5.1687..-4.2961] \| it/evals=14208/31349 eff=77.8848% N=1367 Z=-16.9(0.79%) \| Like=-4.92..-0.00 [-5.1687..-4.2961] \| it/evals=14240/31349 eff=78.0797% N=1367 Z=-16.8(0.89%) \| Like=-4.81..-0.00 [-5.1687..-4.2961] \| it/evals=14272/31477 eff=77.1514% N=1367 Z=-16.8(0.90%) \| Like=-4.80..-0.00 [-5.1687..-4.2961] \| it/evals=14276/31477 eff=77.1941% N=1367 Z=-16.7(0.98%) \| Like=-4.72..-0.00 [-5.1687..-4.2961] \| it/evals=14304/31477 eff=77.3863% N=1367 Z=-16.5(1.19%) \| Like=-4.50..-0.00 [-5.1687..-4.2961] \| it/evals=14368/31477 eff=77.7386% N=1367 Z=-16.3(1.43%) \| Like=-4.28..-0.00 [-4.2957..-4.0989] \| it/evals=14432/31605 eff=77.0487% N=1367 Z=-16.1(1.71%) \| Like=-4.08..-0.00 [-4.0966..-4.0439] \| it/evals=14496/31605 eff=77.4384% N=1367 Z=-15.9(2.06%) \| Like=-3.90..-0.00 [-3.8990..-3.8887] \| it/evals=14560/31605 eff=77.8070% N=1367 Z=-15.8(2.24%) \| Like=-3.81..-0.00 [-3.8053..-3.8045]\| it/evals=14588/31605 eff=77.9334% N=1367 Z=-15.5(3.07%) \| Like=-3.49..-0.00 [-3.4913..-3.4904]\| it/evals=14705/31733 eff=77.4787% N=1367 Z=-15.4(3.46%) \| Like=-3.36..-0.00 [-3.3600..-3.3593]\| it/evals=14752/31733 eff=77.7593% N=1367 Z=-15.2(4.04%) \| Like=-3.21..-0.00 [-3.2122..-3.2120]\| it/evals=14816/31861 eff=77.0769% N=1367 Z=-15.2(4.35%) \| Like=-3.13..-0.00 [-3.1265..-3.1251]\| it/evals=14848/31861 eff=77.2308% N=1367 Z=-15.0(4.87%) \| Like=-3.01..-0.00 [-3.0075..-3.0072]\| it/evals=14896/31861 eff=77.4564% N=1367 Z=-15.0(5.05%) \| Like=-2.98..-0.00 [-2.9836..-2.9828]\| it/evals=14912/31861 eff=77.5590% N=1367 Z=-14.8(6.35%) \| Like=-2.73..-0.00 [-2.7287..-2.7268]\| it/evals=15024/31989 eff=77.0905% N=1367 Z=-14.7(6.57%) \| Like=-2.70..-0.00 [-2.6955..-2.6910]\| it/evals=15040/31989 eff=77.1614% N=1367 Z=-14.7(7.02%) \| Like=-2.64..-0.00 [-2.6362..-2.6362]\| it/evals=15072/31989 eff=77.3335% N=1367 Z=-14.5(8.41%) \| Like=-2.45..-0.00 [-2.4462..-2.4446]\| it/evals=15168/31989 eff=77.7890% N=1367 Z=-14.4(8.88%) \| Like=-2.38..-0.00 [-2.3771..-2.3767]\| it/evals=15200/31989 eff=77.9712% N=1367 Z=-14.4(8.92%) \| Like=-2.38..-0.00 [-2.3760..-2.3749]\| it/evals=15202/32117 eff=76.9838% N=1367 Z=-14.4(9.45%) \| Like=-2.33..-0.00 [-2.3337..-2.3234] \| it/evals=15232/32117 eff=77.1037% N=1367 Z=-14.3(10.59%) \| Like=-2.22..-0.00 [-2.2167..-2.2136]\| it/evals=15296/32117 eff=77.4835% N=1367 Z=-14.2(11.17%) \| Like=-2.17..-0.00 [-2.1710..-2.1693]\| it/evals=15328/32117 eff=77.6334% N=1367 Z=-14.1(12.37%) \| Like=-2.06..-0.00 [-2.0636..-2.0621]\| it/evals=15392/32117 eff=77.8033% N=1367 Z=-14.0(13.02%) \| Like=-2.03..-0.00 [-2.0268..-2.0267]\| it/evals=15424/32117 eff=77.9832% N=1367 Z=-13.9(14.26%) \| Like=-1.93..-0.00 [-1.9311..-1.9295]\| it/evals=15488/32245 eff=77.2548% N=1367 Z=-13.9(14.70%) \| Like=-1.91..-0.00 [-1.9062..-1.9062]\| it/evals=15509/32245 eff=77.3535% N=1367 Z=-13.9(15.64%) \| Like=-1.83..-0.00 [-1.8308..-1.8308]\| it/evals=15552/32245 eff=77.5607% N=1367 Z=-13.8(17.05%) \| Like=-1.76..-0.00 [-1.7573..-1.7568]\| it/evals=15616/32373 eff=76.8953% N=1367 Z=-13.7(17.72%) \| Like=-1.71..-0.00 [-1.7137..-1.7131]\| it/evals=15648/32373 eff=77.0025% N=1367 Z=-13.7(18.47%) \| Like=-1.68..-0.00 [-1.6798..-1.6797]\| it/evals=15680/32373 eff=77.1974% N=1367 Z=-13.6(20.01%) \| Like=-1.61..-0.00 [-1.6112..-1.6105]\| it/evals=15744/32373 eff=77.5385% N=1367 Z=-13.6(20.75%) \| Like=-1.57..-0.00 [-1.5747..-1.5746]\| it/evals=15776/32373 eff=77.7139% N=1367 Z=-13.5(21.56%) \| Like=-1.53..-0.00 [-1.5321..-1.5277]\| it/evals=15808/32373 eff=77.8406% N=1367 Z=-13.5(21.74%) \| Like=-1.52..-0.00 [-1.5214..-1.5192]\| it/evals=15815/32501 eff=76.9297% N=1367 Z=-13.5(22.37%) \| Like=-1.49..-0.00 [-1.4905..-1.4904]\| it/evals=15840/32501 eff=77.0645% N=1367 Z=-13.4(25.47%) \| Like=-1.38..-0.00 [-1.3774..-1.3766]\| it/evals=15961/32501 eff=77.6131% N=1367 Z=-13.4(25.65%) \| Like=-1.37..-0.00 [-1.3715..-1.3695]\| it/evals=15968/32501 eff=77.6516% N=1367 Z=-13.3(26.51%) \| Like=-1.33..-0.00 [-1.3344..-1.3343]\| it/evals=16000/32501 eff=77.8633% N=1367 Z=-13.3(27.35%) \| Like=-1.31..-0.00 [-1.3112..-1.3110]\| it/evals=16032/32629 eff=77.1439% N=1367 Z=-13.3(28.18%) \| Like=-1.29..-0.00 [-1.2906..-1.2905]\| it/evals=16064/32629 eff=77.3246% N=1367 Z=-13.2(29.77%) \| Like=-1.24..-0.00 [-1.2400..-1.2369]\| it/evals=16125/32629 eff=77.5908% N=1367 Z=-13.2(30.71%) \| Like=-1.21..-0.00 [-1.2051..-1.2047]\| it/evals=16160/32629 eff=77.7809% N=1367 Z=-13.2(31.57%) \| Like=-1.18..-0.00 [-1.1828..-1.1817]\| it/evals=16192/32757 eff=77.0148% N=1367 Z=-13.1(32.42%) \| Like=-1.15..-0.00 [-1.1483..-1.1481]\| it/evals=16224/32757 eff=77.1370% N=1367 Z=-13.1(34.20%) \| Like=-1.11..-0.00 [-1.1053..-1.1044]\| it/evals=16288/32757 eff=77.4281% N=1367 Z=-13.1(35.05%) \| Like=-1.09..-0.00 [-1.0864..-1.0854]\| it/evals=16320/32757 eff=77.5784% N=1367 Z=-13.0(37.58%) \| Like=-1.01..-0.00 [-1.0103..-1.0094]\| it/evals=16416/32885 eff=77.0652% N=1367 Z=-13.0(37.98%) \| Like=-1.00..-0.00 [-0.9999..-0.9998]\| it/evals=16432/32885 eff=77.1673% N=1367 Z=-13.0(38.38%) \| Like=-0.99..-0.00 [-0.9941..-0.9940]\| it/evals=16448/32885 eff=77.2601% N=1367 Z=-12.9(39.23%) \| Like=-0.97..-0.00 [-0.9690..-0.9686]\| it/evals=16480/32885 eff=77.3900% N=1367 Z=-12.9(40.88%) \| Like=-0.92..-0.00 [-0.9221..-0.9210]\| it/evals=16544/32885 eff=77.7613% N=1367 Z=-12.9(42.50%) \| Like=-0.88..-0.00 [-0.8757..-0.8756]\| it/evals=16608/33013 eff=77.1510% N=1367 Z=-12.8(43.29%) \| Like=-0.86..-0.00 [-0.8575..-0.8570]\| it/evals=16640/33013 eff=77.2702% N=1367 Z=-12.8(44.97%) \| Like=-0.81..-0.00 [-0.8137..-0.8134]\| it/evals=16704/33013 eff=77.5729% N=1367 Z=-12.8(45.81%) \| Like=-0.79..-0.00 [-0.7941..-0.7933]\| it/evals=16736/33013 eff=77.7197% N=1367 Z=-12.8(45.87%) \| Like=-0.79..-0.00 [-0.7933..-0.7930]\| it/evals=16738/33013 eff=77.7289% N=1367 Z=-12.8(46.65%) \| Like=-0.78..-0.00 [-0.7759..-0.7747]\| it/evals=16768/33141 eff=77.0082% N=1367 Z=-12.7(49.64%) \| Like=-0.72..-0.00 [-0.7225..-0.7220]\| it/evals=16886/33141 eff=77.5431% N=1367 Z=-12.6(52.64%) \| Like=-0.66..-0.00 [-0.6617..-0.6608]\| it/evals=17006/33269 eff=77.1913% N=1367 Z=-12.6(53.71%) \| Like=-0.64..-0.00 [-0.6412..-0.6412]\| it/evals=17050/33269 eff=77.3526% N=1367 Z=-12.6(53.85%) \| Like=-0.64..-0.00 [-0.6369..-0.6368]\| it/evals=17056/33269 eff=77.3974% N=1367 Z=-12.6(54.60%) \| Like=-0.62..-0.00 [-0.6248..-0.6242]\| it/evals=17088/33269 eff=77.5408% N=1367 Z=-12.6(55.39%) \| Like=-0.61..-0.00 [-0.6094..-0.6089]\| it/evals=17120/33269 eff=77.6842% N=1367 Z=-12.6(56.15%) \| Like=-0.60..-0.00 [-0.5951..-0.5950]\| it/evals=17152/33269 eff=77.8455% N=1367 Z=-12.6(56.91%) \| Like=-0.58..-0.00 [-0.5823..-0.5822]\| it/evals=17184/33397 eff=77.0955% N=1367 Z=-12.5(59.15%) \| Like=-0.54..-0.00 [-0.5411..-0.5410]\| it/evals=17280/33397 eff=77.4677% N=1367 Z=-12.5(59.87%) \| Like=-0.53..-0.00 [-0.5307..-0.5304]\| it/evals=17312/33397 eff=77.5828% N=1367 Z=-12.5(60.85%) \| Like=-0.52..-0.00 [-0.5161..-0.5156]\| it/evals=17356/33525 eff=76.9406% N=1367 Z=-12.5(61.30%) \| Like=-0.51..-0.00 [-0.5099..-0.5097]\| it/evals=17376/33525 eff=77.0370% N=1367 Z=-12.5(62.68%) \| Like=-0.48..-0.00 [-0.4834..-0.4828]\| it/evals=17440/33525 eff=77.3524% N=1367 Z=-12.5(63.36%) \| Like=-0.47..-0.00 [-0.4740..-0.4738]\| it/evals=17472/33525 eff=77.5276% N=1367 Z=-12.4(65.63%) \| Like=-0.44..-0.00 [-0.4375..-0.4373]\| it/evals=17581/33653 eff=77.1877% N=1367 Z=-12.4(67.19%) \| Like=-0.41..-0.00 [-0.4137..-0.4135]\| it/evals=17662/33653 eff=77.5342% N=1367 Z=-12.4(67.83%) \| Like=-0.40..-0.00 [-0.4034..-0.4033]\| it/evals=17696/33653 eff=77.6815% N=1367 Z=-12.4(68.43%) \| Like=-0.39..-0.00 [-0.3937..-0.3937]\| it/evals=17728/33781 eff=76.9580% N=1367 Z=-12.4(69.04%) \| Like=-0.38..-0.00 [-0.3841..-0.3832]\| it/evals=17760/33781 eff=77.1037% N=1367 Z=-12.3(71.17%) \| Like=-0.35..-0.00 [-0.3516..-0.3513]\| it/evals=17879/33781 eff=77.5664% N=1367 Z=-12.3(71.87%) \| Like=-0.34..-0.00 [-0.3414..-0.3412]\| it/evals=17920/33909 eff=76.9029% N=1367 Z=-12.3(72.41%) \| Like=-0.33..-0.00 [-0.3301..-0.3301]\| it/evals=17952/33909 eff=77.0978% N=1367 Z=-12.3(72.69%) \| Like=-0.33..-0.00 [-0.3264..-0.3262]\| it/evals=17969/33909 eff=77.1402% N=1367 Z=-12.3(73.47%) \| Like=-0.31..-0.00 [-0.3129..-0.3129]\| it/evals=18016/33909 eff=77.3606% N=1367 Z=-12.3(74.00%) \| Like=-0.31..-0.00 [-0.3065..-0.3063]\| it/evals=18048/33909 eff=77.5216% N=1367 Z=-12.3(75.02%) \| Like=-0.29..-0.00 [-0.2909..-0.2908]\| it/evals=18112/34037 eff=76.9914% N=1367 Z=-12.3(76.83%) \| Like=-0.27..-0.00 [-0.2680..-0.2680]\| it/evals=18230/34037 eff=77.5029% N=1367 Z=-12.3(77.44%) \| Like=-0.26..-0.00 [-0.2613..-0.2611]\| it/evals=18272/34037 eff=77.6371% N=1367 Z=-12.3(77.48%) \| Like=-0.26..-0.00 [-0.2610..-0.2610]\| it/evals=18275/34037 eff=77.6539% N=1367 Z=-12.2(78.35%) \| Like=-0.25..-0.00 [-0.2479..-0.2479]\| it/evals=18336/34165 eff=77.1362% N=1367 Z=-12.2(78.79%) \| Like=-0.24..-0.00 [-0.2424..-0.2423]\| it/evals=18368/34165 eff=77.2938% N=1367 Z=-12.2(79.22%) \| Like=-0.24..-0.00 [-0.2372..-0.2370]\| it/evals=18400/34165 eff=77.4266% N=1367 Z=-12.2(80.07%) \| Like=-0.23..-0.00 [-0.2271..-0.2269]\| it/evals=18464/34165 eff=77.6672% N=1367 Z=-12.2(80.48%) \| Like=-0.22..-0.00 [-0.2219..-0.2219]\| it/evals=18496/34293 eff=76.9824% N=1367 Z=-12.2(80.88%) \| Like=-0.22..-0.00 [-0.2162..-0.2161]\| it/evals=18528/34293 eff=77.1548% N=1367 Z=-12.2(81.28%) \| Like=-0.21..-0.00 [-0.2117..-0.2116]\| it/evals=18560/34293 eff=77.3108% N=1367 Z=-12.2(81.58%) \| Like=-0.21..-0.00 [-0.2073..-0.2064]\| it/evals=18584/34293 eff=77.4175% N=1367 Z=-12.2(82.05%) \| Like=-0.20..-0.00 [-0.2013..-0.2011]\| it/evals=18624/34293 eff=77.5981% N=1367 Z=-12.2(82.42%) \| Like=-0.20..-0.00 [-0.1969..-0.1968]\| it/evals=18656/34421 eff=76.9618% N=1367 Z=-12.2(82.80%) \| Like=-0.19..-0.00 [-0.1930..-0.1929]\| it/evals=18688/34421 eff=77.1243% N=1367 Z=-12.2(83.16%) \| Like=-0.19..-0.00 [-0.1881..-0.1881]\| it/evals=18720/34421 eff=77.2543% N=1367 Z=-12.2(84.37%) \| Like=-0.18..-0.00 [-0.1750..-0.1748]\| it/evals=18832/34421 eff=77.7092% N=1367 Z=-12.2(84.96%) \| Like=-0.17..-0.00 [-0.1663..-0.1662]\| it/evals=18890/34549 eff=77.1507% N=1367 Z=-12.2(85.18%) \| Like=-0.16..-0.00 [-0.1635..-0.1635]\| it/evals=18912/34549 eff=77.2552% N=1367 Z=-12.2(85.81%) \| Like=-0.16..-0.00 [-0.1566..-0.1566]\| it/evals=18976/34549 eff=77.5446% N=1367 Z=-12.2(86.11%) \| Like=-0.15..-0.00 [-0.1527..-0.1525]\| it/evals=19008/34549 eff=77.6733% N=1367 Z=-12.1(86.71%) \| Like=-0.15..-0.00 [-0.1463..-0.1462]\| it/evals=19072/34677 eff=77.1208% N=1367 Z=-12.1(87.28%) \| Like=-0.14..-0.00 [-0.1404..-0.1402]\| it/evals=19136/34677 eff=77.3755% N=1367 Z=-12.1(87.55%) \| Like=-0.14..-0.00 [-0.1379..-0.1379]\| it/evals=19168/34677 eff=77.5028% N=1367 Z=-12.1(87.80%) \| Like=-0.13..-0.00 [-0.1342..-0.1342]\| it/evals=19198/34677 eff=77.6381% N=1367 Z=-12.1(87.82%) \| Like=-0.13..-0.00 [-0.1341..-0.1338]\| it/evals=19200/34677 eff=77.6540% N=1367 Z=-12.1(88.08%) \| Like=-0.13..-0.00 [-0.1301..-0.1301]\| it/evals=19232/34805 eff=77.0128% N=1367 Z=-12.1(88.34%) \| Like=-0.13..-0.00 [-0.1278..-0.1278]\| it/evals=19264/34805 eff=77.1782% N=1367 Z=-12.1(89.09%) \| Like=-0.12..-0.00 [-0.1196..-0.1196]\| it/evals=19360/34805 eff=77.5406% N=1367 Z=-12.1(89.79%) \| Like=-0.11..-0.00 [-0.1103..-0.1102]\| it/evals=19456/34933 eff=77.0941% N=1367 Z=-12.1(90.13%) \| Like=-0.11..-0.00 [-0.1075..-0.1074]\| it/evals=19505/34933 eff=77.2890% N=1367 Z=-12.1(90.89%) \| Like=-0.10..-0.00 [-0.0986..-0.0985]\| it/evals=19621/34933 eff=77.7648% N=1367 Z=-12.1(91.63%) \| Like=-0.09..-0.00 [-0.0895..-0.0894]\| it/evals=19743/35061 eff=77.4286% N=1367 Z=-12.1(91.64%) \| Like=-0.09..-0.00 [-0.0894..-0.0893]\| it/evals=19744/35061 eff=77.4363% N=1367 Z=-12.1(92.02%) \| Like=-0.08..-0.00 [-0.0844..-0.0844]\| it/evals=19811/35189 eff=76.9307% N=1367 Z=-12.1(92.36%) \| Like=-0.08..-0.00 [-0.0807..-0.0806]\| it/evals=19872/35189 eff=77.1295% N=1367 Z=-12.1(92.53%) \| Like=-0.08..-0.00 [-0.0792..-0.0791]\| it/evals=19904/35189 eff=77.2289% N=1367 Z=-12.1(92.69%) \| Like=-0.08..-0.00 [-0.0779..-0.0779]\| it/evals=19936/35189 eff=77.3207% N=1367 Z=-12.1(92.85%) \| Like=-0.08..-0.00 [-0.0760..-0.0760]\| it/evals=19968/35189 eff=77.4430% N=1367 Z=-12.1(93.17%) \| Like=-0.07..-0.00 [-0.0717..-0.0716]\| it/evals=20032/35317 eff=76.9347% N=1367 Z=-12.1(93.47%) \| Like=-0.07..-0.00 [-0.0680..-0.0680]\| it/evals=20096/35317 eff=77.2679% N=1367 Z=-12.1(93.57%) \| Like=-0.07..-0.00 [-0.0667..-0.0667]\| it/evals=20117/35317 eff=77.3512% N=1367 Z=-12.1(93.62%) \| Like=-0.07..-0.00 [-0.0663..-0.0663]\| it/evals=20128/35317 eff=77.4042% N=1367 Z=-12.1(94.13%) \| Like=-0.06..-0.00 [-0.0610..-0.0610]\| it/evals=20247/35445 eff=77.1111% N=1367 Z=-12.1(94.30%) \| Like=-0.06..-0.00 [-0.0598..-0.0598]\| it/evals=20288/35445 eff=77.2911% N=1367 Z=-12.1(94.43%) \| Like=-0.06..-0.00 [-0.0583..-0.0582]\| it/evals=20320/35445 eff=77.4336% N=1367 Z=-12.1(94.68%) \| Like=-0.06..-0.00 [-0.0556..-0.0555]\| it/evals=20384/35573 eff=76.9276% N=1367 Z=-12.1(94.80%) \| Like=-0.05..-0.00 [-0.0543..-0.0542]\| it/evals=20416/35573 eff=77.0614% N=1367 Z=-12.1(94.82%) \| Like=-0.05..-0.00 [-0.0539..-0.0539]\| it/evals=20423/35573 eff=77.0911% N=1367 Z=-12.1(95.03%) \| Like=-0.05..-0.00 [-0.0515..-0.0515]\| it/evals=20480/35573 eff=77.3213% N=1367 Z=-12.1(95.25%) \| Like=-0.05..-0.00 [-0.0491..-0.0490]\| it/evals=20544/35701 eff=76.8433% N=1367 Z=-12.1(95.56%) \| Like=-0.05..-0.00 [-0.0454..-0.0454]\| it/evals=20640/35701 eff=77.1891% N=1367 Z=-12.0(95.76%) \| Like=-0.04..-0.00 [-0.0434..-0.0433]\| it/evals=20704/35829 eff=76.6730% N=1367 Z=-12.0(95.84%) \| Like=-0.04..-0.00 [-0.0426..-0.0426]\| it/evals=20729/35829 eff=76.7532% N=1367 Z=-12.0(95.86%) \| Like=-0.04..-0.00 [-0.0425..-0.0424]\| it/evals=20736/35829 eff=76.7750% N=1367 Z=-12.0(95.95%) \| Like=-0.04..-0.00 [-0.0416..-0.0416]\| it/evals=20768/35829 eff=76.8917% N=1367 Z=-12.0(96.14%) \| Like=-0.04..-0.00 [-0.0399..-0.0399]\| it/evals=20832/35829 eff=77.1395% N=1367 Z=-12.0(96.22%) \| Like=-0.04..-0.00 [-0.0391..-0.0391]\| it/evals=20864/35829 eff=77.2780% N=1367 Z=-12.0(96.31%) \| Like=-0.04..-0.00 [-0.0379..-0.0379]\| it/evals=20896/35957 eff=76.7153% N=1367 Z=-12.0(96.47%) \| Like=-0.04..-0.00 [-0.0361..-0.0361]\| it/evals=20960/35957 eff=76.9103% N=1367 Z=-12.0(96.55%) \| Like=-0.04..-0.00 [-0.0352..-0.0352]\| it/evals=20992/35957 eff=77.0331% N=1367 Z=-12.0(96.63%) \| Like=-0.03..-0.00 [-0.0345..-0.0345]\| it/evals=21024/35957 eff=77.1486% N=1367 Z=-12.0(96.66%) \| Like=-0.03..-0.00 [-0.0343..-0.0343]\| it/evals=21035/35957 eff=77.1775% N=1367 Z=-12.0(96.86%) \| Like=-0.03..-0.00 [-0.0321..-0.0320]\| it/evals=21120/36085 eff=76.7354% N=1367 Z=-12.0(96.93%) \| Like=-0.03..-0.00 [-0.0312..-0.0312]\| it/evals=21152/36085 eff=76.8427% N=1367 Z=-12.0(97.07%) \| Like=-0.03..-0.00 [-0.0299..-0.0298]\| it/evals=21216/36085 eff=77.0216% N=1367 Z=-12.0(97.20%) \| Like=-0.03..-0.00 [-0.0286..-0.0285]\| it/evals=21280/36085 eff=77.2864% N=1367 Z=-12.0(97.32%) \| Like=-0.03..-0.00 [-0.0271..-0.0271]\| it/evals=21341/36213 eff=76.7763% N=1367 Z=-12.0(97.39%) \| Like=-0.03..-0.00 [-0.0265..-0.0265]\| it/evals=21376/36213 eff=76.9465% N=1367 Z=-12.0(97.45%) \| Like=-0.03..-0.00 [-0.0258..-0.0258]\| it/evals=21408/36213 eff=77.0600% N=1367 Z=-12.0(97.51%) \| Like=-0.03..-0.00 [-0.0252..-0.0252]\| it/evals=21440/36213 eff=77.1593% N=1367 Z=-12.0(97.67%) \| Like=-0.02..-0.00 [-0.0235..-0.0235]\| it/evals=21536/36341 eff=76.8236% N=1367 Z=-12.0(97.78%) \| Like=-0.02..-0.00 [-0.0224..-0.0224]\| it/evals=21600/36341 eff=77.0204% N=1367 Z=-12.0(97.83%) \| Like=-0.02..-0.00 [-0.0218..-0.0218]\| it/evals=21632/36341 eff=77.1188% N=1367 Z=-12.0(97.85%) \| Like=-0.02..-0.00 [-0.0215..-0.0215]\| it/evals=21647/36341 eff=77.1820% N=1367 Z=-12.0(97.93%) \| Like=-0.02..-0.00 [-0.0207..-0.0206]\| it/evals=21696/36469 eff=76.6472% N=1367 Z=-12.0(98.10%) \| Like=-0.02..-0.00 [-0.0190..-0.0190]\| it/evals=21813/36469 eff=77.0790% N=1367 Z=-12.0(98.11%) \| Like=-0.02..-0.00 [-0.0189..-0.0189]\| it/evals=21824/36469 eff=77.1277% N=1367 Z=-12.0(98.15%) \| Like=-0.02..-0.00 [-0.0185..-0.0185]\| it/evals=21856/36469 eff=77.2252% N=1367 Z=-12.0(98.20%) \| Like=-0.02..-0.00 [-0.0181..-0.0181]\| it/evals=21888/36597 eff=76.6947% N=1367 Z=-12.0(98.24%) \| Like=-0.02..-0.00 [-0.0178..-0.0177]\| it/evals=21920/36597 eff=76.8259% N=1367 Z=-12.0(98.28%) \| Like=-0.02..-0.00 [-0.0173..-0.0173]\| it/evals=21952/36597 eff=76.9225% N=1367 Z=-12.0(98.28%) \| Like=-0.02..-0.00 [-0.0173..-0.0173]\| it/evals=21954/36597 eff=76.9294% N=1367 Z=-12.0(98.42%) \| Like=-0.02..-0.00 [-0.0157..-0.0157]\| it/evals=22073/36725 eff=76.6731% N=1367 Z=-12.0(98.43%) \| Like=-0.02..-0.00 [-0.0156..-0.0156]\| it/evals=22080/36725 eff=76.7141% N=1367 Z=-12.0(98.47%) \| Like=-0.02..-0.00 [-0.0153..-0.0153]\| it/evals=22112/36725 eff=76.8099% N=1367 Z=-12.0(98.54%) \| Like=-0.01..-0.00 [-0.0147..-0.0147]\| it/evals=22176/36725 eff=77.0836% N=1367 Z=-12.0(98.57%) \| Like=-0.01..-0.00 [-0.0143..-0.0143]\| it/evals=22208/36725 eff=77.1931% N=1367 Z=-12.0(98.62%) \| Like=-0.01..-0.00 [-0.0137..-0.0137]\| it/evals=22262/36853 eff=76.6992% N=1367 Z=-12.0(98.67%) \| Like=-0.01..-0.00 [-0.0133..-0.0133]\| it/evals=22304/36853 eff=76.8688% N=1367 Z=-12.0(98.73%) \| Like=-0.01..-0.00 [-0.0127..-0.0127]\| it/evals=22368/36853 eff=77.1062% N=1367 Z=-12.0(98.76%) \| Like=-0.01..-0.00 [-0.0123..-0.0123]\| it/evals=22400/36981 eff=76.5501% N=1367 Z=-12.0(98.86%) \| Like=-0.01..-0.00 [-0.0113..-0.0113]\| it/evals=22516/36981 eff=76.9065% N=1367 Z=-12.0(98.89%) \| Like=-0.01..-0.00 [-0.0109..-0.0109]\| it/evals=22560/36981 eff=77.0814% N=1367 Z=-12.0(98.90%) \| Like=-0.01..-0.00 [-0.0109..-0.0109]\| it/evals=22568/36981 eff=77.1083% N=1367 Z=-12.0(98.94%) \| Like=-0.01..-0.00 [-0.0105..-0.0105]\| it/evals=22624/37109 eff=76.6235% N=1367 Z=-12.0(98.99%) \| Like=-0.01..-0.00 [-0.0101..-0.0101]\| it/evals=22688/37109 eff=76.8169% N=1367 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 37109 logzerr in iteration 2 0.1560823420564488 [ultranest] logZ = -12.01 +- 0.08472 [ultranest] Effective samples strategy satisfied (ESS = 5474.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.04 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 1540 minimum live points (dlogz from 0.07 to 0.16, need <0.1) [ultranest] logZ error budget: single: 0.17 bs:0.08 tail:0.01 total:0.08 required:<0.10 [ultranest] Widening roots to 1540 live points (have 1367 already) ... [ultranest] Sampling 173 live points from prior ... Z=-239552.2(0.00%) \| Like=-238281.70..-0.00 [-245997.6291..-79459.9313] \| it/evals=3/37410 eff=0.0000% N=1540 Z=-173988.3(0.00%) \| Like=-173835.02..-0.00 [-245997.6291..-79459.9313] \| it/evals=96/37410 eff=9.3750% N=1540 Z=-133092.2(0.00%) \| Like=-133000.93..-0.00 [-245997.6291..-79459.9313] \| it/evals=284/37410 eff=24.2188% N=1540 Z=-124631.0(0.00%) \| Like=-124520.10..-0.00 [-245997.6291..-79459.9313] \| it/evals=351/37410 eff=29.6875% N=1540 Z=-107627.2(0.00%) \| Like=-107602.24..-0.00 [-245997.6291..-79459.9313] \| it/evals=544/37410 eff=45.3125% N=1540 Z=-96420.1(0.00%) \| Like=-96392.28..-0.00 [-245997.6291..-79459.9313] \| it/evals=710/37410 eff=56.2500% N=1540 Z=-86398.7(0.00%) \| Like=-86298.13..-0.00 [-245997.6291..-79459.9313] \| it/evals=901/37489 eff=43.4783% N=1540 Z=-79505.3(0.00%) \| Like=-79393.60..-0.00 [-79393.5973..-40497.5965] \| it/evals=1060/37489 eff=53.6232% N=1540 Z=-70723.8(0.00%) \| Like=-70710.58..-0.00 [-79393.5973..-40497.5965] \| it/evals=1234/37489 eff=65.2174% N=1540 Z=-63768.3(0.00%) \| Like=-63731.15..-0.00 [-79393.5973..-40497.5965] \| it/evals=1405/37555 eff=57.1429% N=1540 Z=-56835.8(0.00%) \| Like=-56823.71..-0.00 [-79393.5973..-40497.5965] \| it/evals=1585/37555 eff=67.0330% N=1540 Z=-54185.4(0.00%) \| Like=-54153.90..-0.00 [-79393.5973..-40497.5965] \| it/evals=1664/37555 eff=69.5971% N=1540 Z=-51386.9(0.00%) \| Like=-51264.62..-0.00 [-79393.5973..-40497.5965] \| it/evals=1750/37608 eff=60.1227% N=1540 Z=-44798.9(0.00%) \| Like=-44760.93..-0.00 [-79393.5973..-40497.5965] \| it/evals=1948/37608 eff=65.0307% N=1540 Z=-40813.4(0.00%) \| Like=-40791.72..-0.00 [-79393.5973..-40497.5965] \| it/evals=2100/37648 eff=65.5738% N=1540 Z=-36953.2(0.00%) \| Like=-36939.91..-0.00 [-40475.1321..-20327.9432] \| it/evals=2272/37690 eff=63.7255% N=1540 Z=-32241.0(0.00%) \| Like=-32213.31..-0.00 [-40475.1321..-20327.9432] \| it/evals=2470/37690 eff=69.6078% N=1540 Z=-28632.7(0.00%) \| Like=-28561.44..-0.00 [-40475.1321..-20327.9432] \| it/evals=2661/37715 eff=70.2079% N=1540 Z=-25654.7(0.00%) \| Like=-25635.08..-0.00 [-40475.1321..-20327.9432] \| it/evals=2814/37740 eff=70.5240% N=1540 Z=-25635.9(0.00%) \| Like=-25623.18..-0.00 [-40475.1321..-20327.9432] \| it/evals=2816/37740 eff=70.9607% N=1540 Z=-23981.7(0.00%) \| Like=-23963.75..-0.00 [-40475.1321..-20327.9432] \| it/evals=2912/37759 eff=71.2788% N=1540 Z=-22378.2(0.00%) \| Like=-22366.28..-0.00 [-40475.1321..-20327.9432] \| it/evals=3008/37783 eff=69.8603% N=1540 Z=-22028.2(0.00%) \| Like=-22007.25..-0.00 [-40475.1321..-20327.9432] \| it/evals=3040/37783 eff=71.0579% N=1540 Z=-20442.7(0.00%) \| Like=-20426.83..-0.00 [-40475.1321..-20327.9432] \| it/evals=3168/37808 eff=70.5323% N=1540 Z=-17754.6(0.00%) \| Like=-17736.14..-0.00 [-20307.2324..-10019.8323] \| it/evals=3360/37829 eff=71.6636% N=1540 Z=-15901.5(0.00%) \| Like=-15887.14..-0.00 [-20307.2324..-10019.8323] \| it/evals=3529/37847 eff=71.6814% N=1540 Z=-14039.6(0.00%) \| Like=-14029.53..-0.00 [-20307.2324..-10019.8323] \| it/evals=3715/37862 eff=73.2759% N=1540 Z=-12807.1(0.00%) \| Like=-12795.57..-0.00 [-20307.2324..-10019.8323] \| it/evals=3840/37877 eff=72.7731% N=1540 Z=-12574.9(0.00%) \| Like=-12559.04..-0.00 [-20307.2324..-10019.8323] \| it/evals=3876/37885 eff=72.6368% N=1540 Z=-12144.3(0.00%) \| Like=-12127.69..-0.00 [-20307.2324..-10019.8323] \| it/evals=3936/37893 eff=73.1588% N=1540 Z=-10990.0(0.00%) \| Like=-10975.88..-0.00 [-20307.2324..-10019.8323] \| it/evals=4096/37914 eff=73.4177% N=1540 Z=-10144.5(0.00%) \| Like=-10132.46..-0.00 [-20307.2324..-10019.8323] \| it/evals=4231/37929 eff=73.5703% N=1540 Z=-9343.8(0.00%) \| Like=-9327.89..-0.00 [-10016.4147..-5038.6055] \| it/evals=4352/37957 eff=72.7407% N=1540 Z=-8430.9(0.00%) \| Like=-8414.08..-0.00 [-10016.4147..-5038.6055] \| it/evals=4512/37981 eff=73.2475% N=1540 Z=-8123.9(0.00%) \| Like=-8113.96..-0.00 [-10016.4147..-5038.6055] \| it/evals=4576/37993 eff=73.6990% N=1540 Z=-7196.1(0.00%) \| Like=-7180.52..-0.00 [-10016.4147..-5038.6055] \| it/evals=4756/38028 eff=73.5925% N=1540 Z=-6485.3(0.00%) \| Like=-6474.78..-0.00 [-10016.4147..-5038.6055] \| it/evals=4922/38045 eff=73.7877% N=1540 Z=-5765.3(0.00%) \| Like=-5748.02..-0.00 [-10016.4147..-5038.6055] \| it/evals=5103/38067 eff=74.0127% N=1540 Z=-5099.3(0.00%) \| Like=-5086.49..-0.00 [-10016.4147..-5038.6055] \| it/evals=5269/38085 eff=74.5953% N=1540 Z=-5061.0(0.00%) \| Like=-5045.01..-0.00 [-10016.4147..-5038.6055] \| it/evals=5280/38085 eff=74.8443% N=1540 Z=-4514.5(0.00%) \| Like=-4502.57..-0.00 [-5034.2444..-2565.3637] \| it/evals=5466/38106 eff=74.7573% N=1540 Z=-4072.9(0.00%) \| Like=-4061.12..-0.00 [-5034.2444..-2565.3637] \| it/evals=5634/38129 eff=74.9705% N=1540 Z=-3596.9(0.00%) \| Like=-3584.90..-0.00 [-5034.2444..-2565.3637] \| it/evals=5819/38146 eff=75.1157% N=1540 Z=-3272.6(0.00%) \| Like=-3260.34..-0.00 [-5034.2444..-2565.3637] \| it/evals=5983/38165 eff=75.0849% N=1540 Z=-3147.2(0.00%) \| Like=-3135.30..-0.00 [-5034.2444..-2565.3637] \| it/evals=6048/38177 eff=75.0838% N=1540 Z=-2762.7(0.00%) \| Like=-2751.30..-0.00 [-5034.2444..-2565.3637] \| it/evals=6241/38203 eff=74.7014% N=1540 Z=-2629.1(0.00%) \| Like=-2618.04..-0.00 [-5034.2444..-2565.3637] \| it/evals=6327/38220 eff=74.8401% N=1540 Z=-2380.5(0.00%) \| Like=-2367.79..-0.00 [-2563.2706..-1292.2424] \| it/evals=6464/38359 eff=67.0381% N=1540 Z=-2144.8(0.00%) \| Like=-2132.51..-0.00 [-2563.2706..-1292.2424] \| it/evals=6624/38359 eff=68.6165% N=1540 Z=-2089.0(0.00%) \| Like=-2076.26..-0.00 [-2563.2706..-1292.2424] \| it/evals=6676/38359 eff=69.2665% N=1540 Z=-1955.1(0.00%) \| Like=-1941.84..-0.00 [-2563.2706..-1292.2424] \| it/evals=6784/38359 eff=70.2878% N=1540 Z=-1815.6(0.00%) \| Like=-1804.35..-0.00 [-2563.2706..-1292.2424] \| it/evals=6880/38359 eff=71.2163% N=1540 Z=-1655.3(0.00%) \| Like=-1643.27..-0.00 [-2563.2706..-1292.2424] \| it/evals=7020/38359 eff=72.7019% N=1540 Z=-1475.6(0.00%) \| Like=-1463.60..-0.00 [-2563.2706..-1292.2424] \| it/evals=7201/38490 eff=66.8046% N=1540 Z=-1365.7(0.00%) \| Like=-1353.37..-0.00 [-2563.2706..-1292.2424] \| it/evals=7328/38490 eff=67.8808% N=1540 Z=-1332.2(0.00%) \| Like=-1319.18..-0.00 [-2563.2706..-1292.2424] \| it/evals=7366/38490 eff=68.1291% N=1540 Z=-1308.2(0.00%) \| Like=-1296.93..-0.00 [-2563.2706..-1292.2424] \| it/evals=7392/38490 eff=68.4603% N=1540 Z=-1242.1(0.00%) \| Like=-1230.00..-0.00 [-1290.8302..-661.3478] \| it/evals=7488/38490 eff=69.1225% N=1540 Z=-1217.3(0.00%) \| Like=-1205.97..-0.00 [-1290.8302..-661.3478] \| it/evals=7515/38490 eff=69.2053% N=1540 Z=-1080.5(0.00%) \| Like=-1067.45..-0.00 [-1290.8302..-661.3478] \| it/evals=7706/38490 eff=70.4470% N=1540 Z=-1007.6(0.00%) \| Like=-995.29..-0.00 [-1290.8302..-661.3478] \| it/evals=7815/38490 eff=71.1921% N=1540 Z=-970.3(0.00%) \| Like=-957.73..-0.00 [-1290.8302..-661.3478] \| it/evals=7872/38490 eff=71.6887% N=1540 Z=-855.8(0.00%) \| Like=-842.85..-0.00 [-1290.8302..-661.3478] \| it/evals=8080/38620 eff=66.4425% N=1540 Z=-807.8(0.00%) \| Like=-796.55..-0.00 [-1290.8302..-661.3478] \| it/evals=8159/38620 eff=67.0404% N=1540 Z=-724.7(0.00%) \| Like=-712.92..-0.00 [-1290.8302..-661.3478] \| it/evals=8348/38620 eff=68.3857% N=1540 Z=-658.1(0.00%) \| Like=-646.04..-0.00 [-661.3393..-332.5205] \| it/evals=8503/38620 eff=69.3572% N=1540 Z=-587.0(0.00%) \| Like=-575.15..-0.00 [-661.3393..-332.5205] \| it/evals=8698/38620 eff=71.0015% N=1540 Z=-537.9(0.00%) \| Like=-524.84..-0.00 [-661.3393..-332.5205] \| it/evals=8832/38620 eff=72.1973% N=1540 Z=-522.2(0.00%) \| Like=-510.37..-0.00 [-661.3393..-332.5205] \| it/evals=8865/38620 eff=72.2720% N=1540 Z=-461.9(0.00%) \| Like=-449.49..-0.00 [-661.3393..-332.5205] \| it/evals=9054/38748 eff=67.3943% N=1540 Z=-414.0(0.00%) \| Like=-401.66..-0.00 [-661.3393..-332.5205] \| it/evals=9224/38748 eff=68.3492% N=1540 Z=-408.9(0.00%) \| Like=-397.38..-0.00 [-661.3393..-332.5205] \| it/evals=9248/38748 eff=68.4175% N=1540 Z=-376.3(0.00%) \| Like=-364.65..-0.00 [-661.3393..-332.5205] \| it/evals=9376/38748 eff=69.8499% N=1540 Z=-334.8(0.00%) \| Like=-322.80..-0.00 [-332.3972..-163.5867] \| it/evals=9572/38748 eff=71.2824% N=1540 Z=-298.8(0.00%) \| Like=-286.87..-0.00 [-332.3972..-163.5867] \| it/evals=9758/38876 eff=66.8130% N=1540 Z=-267.8(0.00%) \| Like=-255.40..-0.00 [-332.3972..-163.5867] \| it/evals=9919/38876 eff=68.0678% N=1540 Z=-256.5(0.00%) \| Like=-244.28..-0.00 [-332.3972..-163.5867] \| it/evals=9984/38876 eff=68.3187% N=1540 Z=-239.7(0.00%) \| Like=-227.95..-0.00 [-332.3972..-163.5867] \| it/evals=10080/38876 eff=69.1970% N=1540 Z=-233.3(0.00%) \| Like=-221.25..-0.00 [-332.3972..-163.5867] \| it/evals=10125/38876 eff=69.5107% N=1540 Z=-220.0(0.00%) \| Like=-208.20..-0.00 [-332.3972..-163.5867] \| it/evals=10208/38876 eff=70.2635% N=1540 Z=-196.4(0.00%) \| Like=-184.30..-0.00 [-332.3972..-163.5867] \| it/evals=10401/39004 eff=66.3763% N=1540 Z=-188.7(0.00%) \| Like=-176.92..-0.00 [-332.3972..-163.5867] \| it/evals=10471/39004 eff=67.0151% N=1540 Z=-182.4(0.00%) \| Like=-170.58..-0.00 [-332.3972..-163.5867] \| it/evals=10536/39004 eff=67.4797% N=1540 Z=-163.8(0.00%) \| Like=-151.73..-0.00 [-163.5613..-83.2797] \| it/evals=10725/39004 eff=68.6992% N=1540 Z=-161.6(0.00%) \| Like=-150.13..-0.00 [-163.5613..-83.2797] \| it/evals=10752/39004 eff=68.8153% N=1540 Z=-148.4(0.00%) \| Like=-136.39..-0.00 [-163.5613..-83.2797] \| it/evals=10898/39004 eff=70.0348% N=1540 Z=-132.8(0.00%) \| Like=-121.11..-0.00 [-163.5613..-83.2797] \| it/evals=11089/39132 eff=66.6486% N=1540 Z=-127.1(0.00%) \| Like=-115.24..-0.00 [-163.5613..-83.2797] \| it/evals=11169/39132 eff=67.1351% N=1540 Z=-123.8(0.00%) \| Like=-111.82..-0.00 [-163.5613..-83.2797] \| it/evals=11209/39132 eff=67.4054% N=1540 Z=-119.2(0.00%) \| Like=-107.32..-0.00 [-163.5613..-83.2797] \| it/evals=11279/39132 eff=67.8378% N=1540 Z=-118.6(0.00%) \| Like=-106.33..-0.00 [-163.5613..-83.2797] \| it/evals=11288/39132 eff=67.9459% N=1540 Z=-112.2(0.00%) \| Like=-100.21..-0.00 [-163.5613..-83.2797] \| it/evals=11364/39132 eff=68.3243% N=1540 Z=-107.9(0.00%) \| Like=-95.79..-0.00 [-163.5613..-83.2797] \| it/evals=11423/39132 eff=68.4865% N=1540 Z=-105.9(0.00%) \| Like=-93.92..-0.00 [-163.5613..-83.2797] \| it/evals=11455/39132 eff=68.5946% N=1540 Z=-102.5(0.00%) \| Like=-90.59..-0.00 [-163.5613..-83.2797] \| it/evals=11518/39132 eff=68.8108% N=1540 Z=-95.4(0.00%) \| Like=-83.49..-0.00 [-163.5613..-83.2797] \| it/evals=11648/39132 eff=69.4595% N=1540 Z=-93.9(0.00%) \| Like=-82.04..-0.00 [-83.2491..-41.3037] \| it/evals=11680/39132 eff=69.6757% N=1540 Z=-84.7(0.00%) \| Like=-72.75..-0.00 [-83.2491..-41.3037] \| it/evals=11865/39260 eff=66.3802% N=1540 Z=-81.3(0.00%) \| Like=-69.14..-0.00 [-83.2491..-41.3037] \| it/evals=11950/39260 eff=66.9363% N=1540 Z=-79.2(0.00%) \| Like=-67.07..-0.00 [-83.2491..-41.3037] \| it/evals=11999/39260 eff=67.0880% N=1540 Z=-75.6(0.00%) \| Like=-63.71..-0.00 [-83.2491..-41.3037] \| it/evals=12094/39260 eff=67.7958% N=1540 Z=-74.3(0.00%) \| Like=-62.28..-0.00 [-83.2491..-41.3037] \| it/evals=12133/39260 eff=67.9474% N=1540 Z=-67.3(0.00%) \| Like=-55.14..-0.00 [-83.2491..-41.3037] \| it/evals=12321/39260 eff=68.8069% N=1540 Z=-64.9(0.00%) \| Like=-52.79..-0.00 [-83.2491..-41.3037] \| it/evals=12384/39260 eff=69.1608% N=1540 Z=-63.0(0.00%) \| Like=-50.92..-0.00 [-83.2491..-41.3037] \| it/evals=12437/39260 eff=69.5652% N=1540 Z=-61.6(0.00%) \| Like=-49.40..-0.00 [-83.2491..-41.3037] \| it/evals=12480/39388 eff=65.7645% N=1540 Z=-61.3(0.00%) \| Like=-49.14..-0.00 [-83.2491..-41.3037] \| it/evals=12488/39388 eff=65.9069% N=1540 Z=-60.5(0.00%) \| Like=-48.37..-0.00 [-83.2491..-41.3037] \| it/evals=12512/39388 eff=66.0019% N=1540 Z=-59.0(0.00%) \| Like=-46.89..-0.00 [-83.2491..-41.3037] \| it/evals=12554/39388 eff=66.3343% N=1540 Z=-58.3(0.00%) \| Like=-46.18..-0.00 [-83.2491..-41.3037] \| it/evals=12578/39388 eff=66.4767% N=1540 Z=-57.4(0.00%) \| Like=-45.37..-0.00 [-83.2491..-41.3037] \| it/evals=12606/39388 eff=66.5242% N=1540 Z=-56.4(0.00%) \| Like=-44.49..-0.00 [-83.2491..-41.3037] \| it/evals=12640/39388 eff=66.7616% N=1540 Z=-55.5(0.00%) \| Like=-43.53..-0.00 [-83.2491..-41.3037] \| it/evals=12672/39388 eff=66.9516% N=1540 Z=-51.1(0.00%) \| Like=-38.96..-0.00 [-41.2950..-19.8452] \| it/evals=12828/39388 eff=67.8538% N=1540 Z=-50.4(0.00%) \| Like=-38.30..-0.00 [-41.2950..-19.8452] \| it/evals=12852/39388 eff=67.9012% N=1540 Z=-49.1(0.00%) \| Like=-37.07..-0.00 [-41.2950..-19.8452] \| it/evals=12897/39388 eff=68.0912% N=1540 Z=-46.0(0.00%) \| Like=-34.12..-0.00 [-41.2950..-19.8452] \| it/evals=13024/39388 eff=68.3761% N=1540 Z=-45.6(0.00%) \| Like=-33.54..-0.00 [-41.2950..-19.8452] \| it/evals=13042/39388 eff=68.4710% N=1540 Z=-43.8(0.00%) \| Like=-32.05..-0.00 [-41.2950..-19.8452] \| it/evals=13128/39388 eff=68.8984% N=1540 Z=-43.4(0.00%) \| Like=-31.59..-0.00 [-41.2950..-19.8452] \| it/evals=13152/39388 eff=69.1358% N=1540 Z=-42.3(0.00%) \| Like=-30.21..-0.00 [-41.2950..-19.8452] \| it/evals=13209/39388 eff=69.5157% N=1540 Z=-40.8(0.00%) \| Like=-28.77..-0.00 [-41.2950..-19.8452] \| it/evals=13280/39388 eff=69.9905% N=1540 Z=-39.8(0.00%) \| Like=-27.61..-0.00 [-41.2950..-19.8452] \| it/evals=13333/39516 eff=66.2936% N=1540 Z=-39.4(0.00%) \| Like=-27.29..-0.00 [-41.2950..-19.8452] \| it/evals=13354/39516 eff=66.4727% N=1540 Z=-38.9(0.00%) \| Like=-26.84..-0.00 [-41.2950..-19.8452] \| it/evals=13375/39516 eff=66.6517% N=1540 Z=-38.1(0.00%) \| Like=-25.96..-0.00 [-41.2950..-19.8452] \| it/evals=13421/39516 eff=66.7860% N=1540 Z=-37.2(0.00%) \| Like=-25.11..-0.00 [-41.2950..-19.8452] \| it/evals=13471/39516 eff=66.8756% N=1540 Z=-36.6(0.00%) \| Like=-24.53..-0.00 [-41.2950..-19.8452] \| it/evals=13504/39516 eff=67.0098% N=1540 Z=-35.7(0.00%) \| Like=-23.85..-0.00 [-41.2950..-19.8452] \| it/evals=13562/39516 eff=67.2337% N=1540 Z=-35.3(0.00%) \| Like=-23.36..-0.00 [-41.2950..-19.8452] \| it/evals=13594/39516 eff=67.4575% N=1540 Z=-33.5(0.00%) \| Like=-21.52..-0.00 [-41.2950..-19.8452] \| it/evals=13711/39516 eff=67.8603% N=1540 Z=-33.2(0.00%) \| Like=-21.29..-0.00 [-41.2950..-19.8452] \| it/evals=13730/39516 eff=67.9051% N=1540 Z=-32.8(0.00%) \| Like=-20.75..-0.00 [-41.2950..-19.8452] \| it/evals=13757/39516 eff=68.0394% N=1540 Z=-32.8(0.00%) \| Like=-20.74..-0.00 [-41.2950..-19.8452] \| it/evals=13760/39516 eff=68.0842% N=1540 Z=-31.1(0.00%) \| Like=-19.04..-0.00 [-19.8317..-9.6469] \| it/evals=13888/39516 eff=68.8004% N=1540 Z=-30.0(0.00%) \| Like=-18.02..-0.00 [-19.8317..-9.6469] \| it/evals=13973/39516 eff=69.1585% N=1540 Z=-29.9(0.00%) \| Like=-17.90..-0.00 [-19.8317..-9.6469] \| it/evals=13984/39516 eff=69.2032% N=1540 Z=-29.5(0.00%) \| Like=-17.56..-0.00 [-19.8317..-9.6469] \| it/evals=14016/39516 eff=69.3823% N=1540 Z=-29.2(0.00%) \| Like=-17.29..-0.00 [-19.8317..-9.6469] \| it/evals=14040/39516 eff=69.4270% N=1540 Z=-29.1(0.00%) \| Like=-17.18..-0.00 [-19.8317..-9.6469] \| it/evals=14054/39516 eff=69.4718% N=1540 Z=-28.8(0.00%) \| Like=-16.94..-0.00 [-19.8317..-9.6469] \| it/evals=14080/39516 eff=69.6061% N=1540 Z=-28.2(0.00%) \| Like=-16.29..-0.00 [-19.8317..-9.6469] \| it/evals=14142/39516 eff=69.7404% N=1540 Z=-28.1(0.00%) \| Like=-16.15..-0.00 [-19.8317..-9.6469] \| it/evals=14153/39516 eff=69.8299% N=1540 Z=-27.9(0.00%) \| Like=-15.97..-0.00 [-19.8317..-9.6469] \| it/evals=14168/39516 eff=69.9194% N=1540 Z=-27.9(0.00%) \| Like=-15.91..-0.00 [-19.8317..-9.6469] \| it/evals=14175/39516 eff=69.9642% N=1540 Z=-27.7(0.00%) \| Like=-15.71..-0.00 [-19.8317..-9.6469] \| it/evals=14196/39644 eff=66.2997% N=1540 Z=-27.5(0.00%) \| Like=-15.53..-0.00 [-19.8317..-9.6469] \| it/evals=14208/39644 eff=66.3844% N=1540 Z=-26.6(0.00%) \| Like=-14.59..-0.00 [-19.8317..-9.6469] \| it/evals=14301/39644 eff=66.7655% N=1540 Z=-26.5(0.00%) \| Like=-14.54..-0.00 [-19.8317..-9.6469] \| it/evals=14307/39644 eff=66.8078% N=1540 Z=-25.7(0.00%) \| Like=-13.81..-0.00 [-19.8317..-9.6469] \| it/evals=14400/39644 eff=67.3582% N=1540 Z=-25.3(0.00%) \| Like=-13.43..-0.00 [-19.8317..-9.6469] \| it/evals=14449/39644 eff=67.5275% N=1540 Z=-24.7(0.00%) \| Like=-12.68..-0.00 [-19.8317..-9.6469] \| it/evals=14522/39644 eff=67.8239% N=1540 Z=-24.6(0.00%) \| Like=-12.64..-0.00 [-19.8317..-9.6469] \| it/evals=14528/39644 eff=67.8662% N=1540 Z=-24.3(0.00%) \| Like=-12.26..-0.00 [-19.8317..-9.6469] \| it/evals=14568/39644 eff=68.1626% N=1540 Z=-24.0(0.00%) \| Like=-11.99..-0.00 [-19.8317..-9.6469] \| it/evals=14597/39644 eff=68.2472% N=1540 Z=-24.0(0.00%) \| Like=-11.90..-0.00 [-19.8317..-9.6469] \| it/evals=14607/39644 eff=68.2896% N=1540 Z=-23.3(0.00%) \| Like=-11.36..-0.00 [-19.8317..-9.6469] \| it/evals=14683/39644 eff=68.7130% N=1540 Z=-23.3(0.00%) \| Like=-11.31..-0.00 [-19.8317..-9.6469] \| it/evals=14689/39644 eff=68.7553% N=1540 Z=-23.2(0.00%) \| Like=-11.23..-0.00 [-19.8317..-9.6469] \| it/evals=14704/39644 eff=68.7976% N=1540 Z=-23.1(0.00%) \| Like=-11.11..-0.00 [-19.8317..-9.6469] \| it/evals=14722/39644 eff=68.9670% N=1540 Z=-22.9(0.00%) \| Like=-10.96..-0.00 [-19.8317..-9.6469] \| it/evals=14745/39644 eff=69.0093% N=1540 Z=-22.7(0.00%) \| Like=-10.78..-0.00 [-19.8317..-9.6469] \| it/evals=14777/39644 eff=69.1787% N=1540 Z=-22.3(0.00%) \| Like=-10.37..-0.00 [-19.8317..-9.6469] \| it/evals=14829/39644 eff=69.3903% N=1540 Z=-22.2(0.00%) \| Like=-10.17..-0.00 [-19.8317..-9.6469] \| it/evals=14850/39644 eff=69.4750% N=1540 Z=-22.0(0.00%) \| Like=-10.04..-0.00 [-19.8317..-9.6469] \| it/evals=14871/39644 eff=69.6444% N=1540 Z=-21.0(0.01%) \| Like=-9.04..-0.00 [-9.6392..-5.0468] \| it/evals=15031/39772 eff=66.9880% N=1540 Z=-19.9(0.04%) \| Like=-7.92..-0.00 [-9.6392..-5.0468] \| it/evals=15225/39772 eff=67.4699% N=1540 Z=-19.2(0.08%) \| Like=-7.25..-0.00 [-9.6392..-5.0468] \| it/evals=15360/39772 eff=68.1124% N=1540 Z=-19.1(0.08%) \| Like=-7.15..-0.00 [-9.6392..-5.0468] \| it/evals=15382/39772 eff=68.2329% N=1540 Z=-18.8(0.12%) \| Like=-6.86..-0.00 [-9.6392..-5.0468] \| it/evals=15456/39772 eff=68.6747% N=1540 Z=-18.5(0.15%) \| Like=-6.60..-0.00 [-9.6392..-5.0468] \| it/evals=15520/39772 eff=68.9157% N=1540 Z=-17.7(0.34%) \| Like=-5.88..-0.00 [-9.6392..-5.0468] \| it/evals=15741/39772 eff=69.5984% N=1540 Z=-17.1(0.63%) \| Like=-5.16..-0.00 [-9.6392..-5.0468] \| it/evals=15934/39900 eff=67.0359% N=1540 Z=-17.1(0.63%) \| Like=-5.16..-0.00 [-9.6392..-5.0468] \| it/evals=15936/39900 eff=67.0741% N=1540 Z=-16.6(0.99%) \| Like=-4.70..-0.00 [-5.0411..-4.3847] \| it/evals=16086/39900 eff=67.7617% N=1540 Z=-16.0(1.70%) \| Like=-4.07..-0.00 [-4.0750..-4.0730]\| it/evals=16295/39900 eff=68.6402% N=1540 Z=-15.9(1.97%) \| Like=-3.94..-0.00 [-3.9356..-3.9334]\| it/evals=16352/39900 eff=68.7548% N=1540 Z=-15.7(2.50%) \| Like=-3.71..-0.00 [-3.7088..-3.7066]\| it/evals=16447/39900 eff=69.4041% N=1540 Z=-15.6(2.69%) \| Like=-3.64..-0.00 [-3.6363..-3.6359]\| it/evals=16480/39900 eff=69.5569% N=1540 Z=-15.4(3.36%) \| Like=-3.39..-0.00 [-3.3903..-3.3876]\| it/evals=16576/40028 eff=66.9337% N=1540 Z=-15.1(4.39%) \| Like=-3.13..-0.00 [-3.1276..-3.1265]\| it/evals=16704/40028 eff=67.5892% N=1540 Z=-14.9(5.33%) \| Like=-2.93..-0.00 [-2.9337..-2.9326]\| it/evals=16801/40028 eff=67.8077% N=1540 Z=-14.6(7.04%) \| Like=-2.63..-0.00 [-2.6333..-2.6329]\| it/evals=16954/40028 eff=68.3176% N=1540 Z=-14.4(9.11%) \| Like=-2.36..-0.00 [-2.3587..-2.3586]\| it/evals=17109/40028 eff=69.0459% N=1540 Z=-14.3(9.77%) \| Like=-2.29..-0.00 [-2.2916..-2.2901]\| it/evals=17152/40028 eff=69.2280% N=1540 Z=-14.1(12.29%) \| Like=-2.07..-0.00 [-2.0740..-2.0711]\| it/evals=17308/40156 eff=66.7711% N=1540 Z=-14.0(13.49%) \| Like=-1.98..-0.00 [-1.9787..-1.9783]\| it/evals=17376/40156 eff=67.0146% N=1540 Z=-13.8(15.70%) \| Like=-1.83..-0.00 [-1.8263..-1.8261]\| it/evals=17496/40156 eff=67.4322% N=1540 Z=-13.8(15.86%) \| Like=-1.82..-0.00 [-1.8215..-1.8209]\| it/evals=17504/40156 eff=67.4669% N=1540 Z=-13.7(17.07%) \| Like=-1.74..-0.00 [-1.7443..-1.7434]\| it/evals=17568/40156 eff=67.6409% N=1540 Z=-13.6(20.69%) \| Like=-1.56..-0.00 [-1.5648..-1.5646]\| it/evals=17743/40156 eff=68.1280% N=1540 Z=-13.4(23.75%) \| Like=-1.43..-0.00 [-1.4332..-1.4330]\| it/evals=17880/40156 eff=68.7543% N=1540 Z=-13.4(23.91%) \| Like=-1.42..-0.00 [-1.4241..-1.4231]\| it/evals=17888/40156 eff=68.7891% N=1540 Z=-13.4(25.38%) \| Like=-1.37..-0.00 [-1.3731..-1.3715]\| it/evals=17952/40156 eff=69.0327% N=1540 Z=-13.3(26.14%) \| Like=-1.34..-0.00 [-1.3355..-1.3349]\| it/evals=17984/40156 eff=69.0675% N=1540 Z=-13.2(29.97%) \| Like=-1.21..-0.00 [-1.2102..-1.2101]\| it/evals=18148/40284 eff=66.4890% N=1540 Z=-13.1(32.23%) \| Like=-1.14..-0.00 [-1.1351..-1.1348]\| it/evals=18243/40284 eff=66.6889% N=1540 Z=-13.0(34.51%) \| Like=-1.08..-0.00 [-1.0822..-1.0814]\| it/evals=18336/40284 eff=66.9887% N=1540 Z=-12.9(38.24%) \| Like=-0.98..-0.00 [-0.9835..-0.9821]\| it/evals=18494/40284 eff=67.5217% N=1540 Z=-12.9(40.51%) \| Like=-0.92..-0.00 [-0.9163..-0.9160]\| it/evals=18591/40284 eff=67.8881% N=1540 Z=-12.9(41.27%) \| Like=-0.90..-0.00 [-0.9010..-0.9008]\| it/evals=18624/40284 eff=68.1213% N=1540 Z=-12.8(44.62%) \| Like=-0.81..-0.00 [-0.8123..-0.8112]\| it/evals=18771/40284 eff=68.7542% N=1540 Z=-12.7(48.71%) \| Like=-0.73..-0.00 [-0.7278..-0.7277]\| it/evals=18950/40412 eff=66.3898% N=1540 Z=-12.6(52.21%) \| Like=-0.66..-0.00 [-0.6562..-0.6561]\| it/evals=19107/40412 eff=66.7732% N=1540 Z=-12.6(55.60%) \| Like=-0.59..-0.00 [-0.5919..-0.5918]\| it/evals=19264/40412 eff=67.1565% N=1540 Z=-12.6(56.31%) \| Like=-0.58..-0.00 [-0.5792..-0.5785]\| it/evals=19297/40412 eff=67.2843% N=1540 Z=-12.5(56.97%) \| Like=-0.57..-0.00 [-0.5664..-0.5661]\| it/evals=19328/40412 eff=67.3482% N=1540 Z=-12.5(59.99%) \| Like=-0.52..-0.00 [-0.5202..-0.5202]\| it/evals=19474/40412 eff=68.0192% N=1540 Z=-12.4(62.98%) \| Like=-0.47..-0.00 [-0.4722..-0.4719]\| it/evals=19628/40540 eff=65.9914% N=1540 Z=-12.4(63.43%) \| Like=-0.46..-0.00 [-0.4638..-0.4630]\| it/evals=19651/40540 eff=66.1449% N=1540 Z=-12.4(65.70%) \| Like=-0.43..-0.00 [-0.4292..-0.4291]\| it/evals=19776/40540 eff=66.6974% N=1540 Z=-12.4(66.26%) \| Like=-0.42..-0.00 [-0.4222..-0.4222]\| it/evals=19808/40540 eff=66.7894% N=1540 Z=-12.4(66.80%) \| Like=-0.41..-0.00 [-0.4149..-0.4145]\| it/evals=19840/40540 eff=66.8815% N=1540 Z=-12.3(69.64%) \| Like=-0.37..-0.00 [-0.3676..-0.3675]\| it/evals=20009/40540 eff=67.2805% N=1540 Z=-12.3(72.08%) \| Like=-0.33..-0.00 [-0.3285..-0.3284]\| it/evals=20166/40540 eff=67.8023% N=1540 Z=-12.3(72.94%) \| Like=-0.32..-0.00 [-0.3182..-0.3179]\| it/evals=20224/40540 eff=68.1707% N=1540 Z=-12.3(74.98%) \| Like=-0.29..-0.00 [-0.2861..-0.2859]\| it/evals=20366/40668 eff=65.9480% N=1540 Z=-12.2(77.23%) \| Like=-0.26..-0.00 [-0.2589..-0.2588]\| it/evals=20531/40668 eff=66.3320% N=1540 Z=-12.2(77.39%) \| Like=-0.26..-0.00 [-0.2572..-0.2571]\| it/evals=20544/40668 eff=66.3615% N=1540 Z=-12.2(77.80%) \| Like=-0.25..-0.00 [-0.2497..-0.2497]\| it/evals=20576/40668 eff=66.4206% N=1540 Z=-12.2(78.60%) \| Like=-0.24..-0.00 [-0.2398..-0.2398]\| it/evals=20640/40668 eff=66.5682% N=1540 Z=-12.2(79.59%) \| Like=-0.23..-0.00 [-0.2272..-0.2271]\| it/evals=20722/40668 eff=66.6864% N=1540 Z=-12.2(80.48%) \| Like=-0.22..-0.00 [-0.2159..-0.2157]\| it/evals=20800/40668 eff=67.0112% N=1540 Z=-12.2(82.36%) \| Like=-0.19..-0.00 [-0.1936..-0.1932]\| it/evals=20973/40668 eff=67.6905% N=1540 Z=-12.2(83.40%) \| Like=-0.18..-0.00 [-0.1817..-0.1817]\| it/evals=21076/40796 eff=65.5094% N=1540 Z=-12.2(84.13%) \| Like=-0.17..-0.00 [-0.1729..-0.1728]\| it/evals=21152/40796 eff=65.5948% N=1540 Z=-12.1(84.43%) \| Like=-0.17..-0.00 [-0.1692..-0.1692]\| it/evals=21184/40796 eff=65.7371% N=1540 Z=-12.1(85.84%) \| Like=-0.15..-0.00 [-0.1518..-0.1515]\| it/evals=21342/40796 eff=66.1924% N=1540 Z=-12.1(86.50%) \| Like=-0.15..-0.00 [-0.1452..-0.1451]\| it/evals=21421/40796 eff=66.5339% N=1540 Z=-12.1(87.73%) \| Like=-0.13..-0.00 [-0.1306..-0.1306]\| it/evals=21579/40796 eff=66.9607% N=1540 Z=-12.1(87.89%) \| Like=-0.13..-0.00 [-0.1294..-0.1294]\| it/evals=21600/40796 eff=67.0176% N=1540 Z=-12.1(88.97%) \| Like=-0.12..-0.00 [-0.1179..-0.1177]\| it/evals=21753/40924 eff=65.1290% N=1540 Z=-12.1(89.21%) \| Like=-0.11..-0.00 [-0.1144..-0.1143]\| it/evals=21789/40924 eff=65.2114% N=1540 Z=-12.1(89.64%) \| Like=-0.11..-0.00 [-0.1097..-0.1095]\| it/evals=21856/40924 eff=65.4860% N=1540 Z=-12.1(90.54%) \| Like=-0.10..-0.00 [-0.1007..-0.1007]\| it/evals=22003/40924 eff=66.0901% N=1540 Z=-12.1(90.79%) \| Like=-0.10..-0.00 [-0.0974..-0.0974]\| it/evals=22048/40924 eff=66.1999% N=1540 Z=-12.1(90.98%) \| Like=-0.10..-0.00 [-0.0952..-0.0952]\| it/evals=22080/40924 eff=66.3372% N=1540 Z=-12.1(91.34%) \| Like=-0.09..-0.00 [-0.0909..-0.0909]\| it/evals=22148/40924 eff=66.5294% N=1540 Z=-12.1(92.42%) \| Like=-0.08..-0.00 [-0.0786..-0.0786]\| it/evals=22360/40924 eff=67.0511% N=1540 Z=-12.1(92.60%) \| Like=-0.08..-0.00 [-0.0771..-0.0771]\| it/evals=22400/40924 eff=67.1609% N=1540 Z=-12.1(93.03%) \| Like=-0.07..-0.00 [-0.0716..-0.0714]\| it/evals=22495/41052 eff=65.1989% N=1540 Z=-12.0(93.68%) \| Like=-0.06..-0.00 [-0.0642..-0.0639]\| it/evals=22652/41052 eff=65.5968% N=1540 Z=-12.0(94.27%) \| Like=-0.06..-0.00 [-0.0586..-0.0586]\| it/evals=22807/41052 eff=66.1538% N=1540 Z=-12.0(94.30%) \| Like=-0.06..-0.00 [-0.0584..-0.0583]\| it/evals=22816/41052 eff=66.2069% N=1540 Z=-12.0(94.40%) \| Like=-0.06..-0.00 [-0.0571..-0.0571]\| it/evals=22844/41052 eff=66.3130% N=1540 Z=-12.0(94.75%) \| Like=-0.05..-0.00 [-0.0534..-0.0534]\| it/evals=22944/41052 eff=66.5782% N=1540 Z=-12.0(95.23%) \| Like=-0.05..-0.00 [-0.0482..-0.0481]\| it/evals=23097/41180 eff=64.9051% N=1540 Z=-12.0(95.25%) \| Like=-0.05..-0.00 [-0.0479..-0.0479]\| it/evals=23104/41180 eff=64.9307% N=1540 Z=-12.0(95.53%) \| Like=-0.04..-0.00 [-0.0449..-0.0449]\| it/evals=23198/41180 eff=65.1103% N=1540 Z=-12.0(95.99%) \| Like=-0.04..-0.00 [-0.0403..-0.0403]\| it/evals=23371/41180 eff=65.6234% N=1540 Z=-12.0(96.28%) \| Like=-0.04..-0.00 [-0.0374..-0.0373]\| it/evals=23488/41180 eff=66.0339% N=1540 Z=-12.0(96.41%) \| Like=-0.04..-0.00 [-0.0360..-0.0360]\| it/evals=23545/41180 eff=66.1621% N=1540 Z=-12.0(96.57%) \| Like=-0.03..-0.00 [-0.0345..-0.0345]\| it/evals=23616/41180 eff=66.4700% N=1540 Z=-12.0(96.93%) \| Like=-0.03..-0.00 [-0.0306..-0.0305]\| it/evals=23787/41308 eff=64.7541% N=1540 Z=-12.0(97.12%) \| Like=-0.03..-0.00 [-0.0287..-0.0287]\| it/evals=23889/41308 eff=64.9528% N=1540 Z=-12.0(97.15%) \| Like=-0.03..-0.00 [-0.0284..-0.0284]\| it/evals=23904/41308 eff=65.0522% N=1540 Z=-12.0(97.43%) \| Like=-0.03..-0.00 [-0.0254..-0.0254]\| it/evals=24069/41308 eff=65.4496% N=1540 Z=-12.0(97.68%) \| Like=-0.02..-0.00 [-0.0229..-0.0229]\| it/evals=24223/41308 eff=65.8470% N=1540 Z=-12.0(97.69%) \| Like=-0.02..-0.00 [-0.0227..-0.0227]\| it/evals=24234/41308 eff=65.8718% N=1540 Z=-12.0(97.72%) \| Like=-0.02..-0.00 [-0.0224..-0.0224]\| it/evals=24256/41308 eff=65.9215% N=1540 Z=-12.0(97.82%) \| Like=-0.02..-0.00 [-0.0214..-0.0214]\| it/evals=24320/41308 eff=66.1947% N=1540 Z=-12.0(98.02%) \| Like=-0.02..-0.00 [-0.0193..-0.0193]\| it/evals=24474/41436 eff=64.6124% N=1540 Z=-12.0(98.15%) \| Like=-0.02..-0.00 [-0.0181..-0.0181]\| it/evals=24581/41436 eff=64.8772% N=1540 Z=-12.0(98.34%) \| Like=-0.02..-0.00 [-0.0162..-0.0162]\| it/evals=24746/41436 eff=65.2865% N=1540 Z=-12.0(98.36%) \| Like=-0.02..-0.00 [-0.0159..-0.0159]\| it/evals=24768/41436 eff=65.3587% N=1540 Z=-12.0(98.53%) \| Like=-0.01..-0.00 [-0.0144..-0.0143]\| it/evals=24931/41436 eff=65.7198% N=1540 Z=-12.0(98.67%) \| Like=-0.01..-0.00 [-0.0129..-0.0129]\| it/evals=25090/41436 eff=66.0327% N=1540 Z=-12.0(98.77%) \| Like=-0.01..-0.00 [-0.0118..-0.0118]\| it/evals=25216/41564 eff=64.4325% N=1540 Z=-12.0(98.83%) \| Like=-0.01..-0.00 [-0.0112..-0.0111]\| it/evals=25290/41564 eff=64.5493% N=1540 Z=-12.0(98.94%) \| Like=-0.01..-0.00 [-0.0103..-0.0103]\| it/evals=25440/41564 eff=64.8529% N=1540 Z=-12.0(98.96%) \| Like=-0.01..-0.00 [-0.0101..-0.0101]\| it/evals=25472/41564 eff=65.0163% N=1540 Z=-12.0(98.98%) \| Like=-0.01..-0.00 [-0.0098..-0.0098]*\| it/evals=25504/41564 eff=65.2732% N=1540 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 41564 logzerr in iteration 3 0.1717176539312442 [ultranest] logZ = -11.97 +- 0.06439 [ultranest] Effective samples strategy satisfied (ESS = 6150.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 384 minimum live points (dlogz from 0.05 to 0.17, need <0.1) [ultranest] logZ error budget: single: 0.16 bs:0.06 tail:0.01 total:0.06 required:<0.10 {'logzerr': 0.1717176539312442, 'logzerr_tail': 0.007007473961262889, 'logzerr_bs': 0.17157461344946334, 'logzerr_single': 0.08443177925682374} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:2359 To achieve the desired logz accuracy, min_num_live_points was increased to 64 INFO ultranest:integrator.py:1433 Sampling 64 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=10000 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=3, min_num_live_points=64, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=192, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-219160.93, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=6, ncalls=192, regioncalls=128, ndraw=128, logz=-126286.02, remainder_fraction=100.0000%, Lmin=-123905.72, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=12, ncalls=192, regioncalls=128, ndraw=128, logz=-105163.62, remainder_fraction=100.0000%, Lmin=-104323.03, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=15, ncalls=192, regioncalls=128, ndraw=128, logz=-96310.17, remainder_fraction=100.0000%, Lmin=-95825.45, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=18, ncalls=192, regioncalls=128, ndraw=128, logz=-92147.54, remainder_fraction=100.0000%, Lmin=-90911.35, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=24, ncalls=192, regioncalls=128, ndraw=128, logz=-83359.12, remainder_fraction=100.0000%, Lmin=-82523.24, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=192, regioncalls=128, ndraw=128, logz=-77249.29, remainder_fraction=100.0000%, Lmin=-73174.88, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=192, regioncalls=128, ndraw=128, logz=-68821.43, remainder_fraction=100.0000%, Lmin=-66961.75, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=42, ncalls=192, regioncalls=128, ndraw=128, logz=-62913.50, remainder_fraction=100.0000%, Lmin=-62524.24, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=45, ncalls=192, regioncalls=128, ndraw=128, logz=-60415.46, remainder_fraction=100.0000%, Lmin=-60348.58, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=48, ncalls=192, regioncalls=128, ndraw=128, logz=-59089.10, remainder_fraction=100.0000%, Lmin=-56644.03, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=54, ncalls=192, regioncalls=128, ndraw=128, logz=-52753.02, remainder_fraction=100.0000%, Lmin=-51631.51, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=271, regioncalls=256, ndraw=128, logz=-44451.02, remainder_fraction=100.0000%, Lmin=-44202.51, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=66, ncalls=271, regioncalls=256, ndraw=128, logz=-42311.41, remainder_fraction=100.0000%, Lmin=-41912.56, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=72, ncalls=271, regioncalls=256, ndraw=128, logz=-39345.96, remainder_fraction=100.0000%, Lmin=-38622.07, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=75, ncalls=271, regioncalls=256, ndraw=128, logz=-37952.21, remainder_fraction=100.0000%, Lmin=-36783.31, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=78, ncalls=271, regioncalls=256, ndraw=128, logz=-36006.69, remainder_fraction=100.0000%, Lmin=-35497.21, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=84, ncalls=271, regioncalls=256, ndraw=128, logz=-31115.59, remainder_fraction=100.0000%, Lmin=-30731.78, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=271, regioncalls=256, ndraw=128, logz=-28687.96, remainder_fraction=100.0000%, Lmin=-28421.18, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=311, regioncalls=384, ndraw=128, logz=-25187.31, remainder_fraction=100.0000%, Lmin=-24656.65, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=102, ncalls=346, regioncalls=512, ndraw=128, logz=-22113.68, remainder_fraction=100.0000%, Lmin=-21443.24, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=105, ncalls=346, regioncalls=512, ndraw=128, logz=-19585.34, remainder_fraction=100.0000%, Lmin=-19464.67, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=108, ncalls=346, regioncalls=512, ndraw=128, logz=-18980.38, remainder_fraction=100.0000%, Lmin=-18714.44, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=114, ncalls=365, regioncalls=640, ndraw=128, logz=-17101.81, remainder_fraction=100.0000%, Lmin=-16522.06, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=365, regioncalls=640, ndraw=128, logz=-14939.80, remainder_fraction=100.0000%, Lmin=-14867.96, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=126, ncalls=384, regioncalls=768, ndraw=128, logz=-13749.80, remainder_fraction=100.0000%, Lmin=-13612.93, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=132, ncalls=384, regioncalls=768, ndraw=128, logz=-12095.75, remainder_fraction=100.0000%, Lmin=-12066.44, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=138, ncalls=399, regioncalls=896, ndraw=128, logz=-11676.84, remainder_fraction=100.0000%, Lmin=-11455.33, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=144, ncalls=399, regioncalls=896, ndraw=128, logz=-9942.74, remainder_fraction=100.0000%, Lmin=-9610.42, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=410, regioncalls=1024, ndraw=128, logz=-9087.85, remainder_fraction=100.0000%, Lmin=-8762.61, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=156, ncalls=410, regioncalls=1024, ndraw=128, logz=-8235.12, remainder_fraction=100.0000%, Lmin=-8086.11, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=162, ncalls=430, regioncalls=1280, ndraw=128, logz=-7472.39, remainder_fraction=100.0000%, Lmin=-7249.22, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=165, ncalls=430, regioncalls=1280, ndraw=128, logz=-7233.15, remainder_fraction=100.0000%, Lmin=-7189.85, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=168, ncalls=446, regioncalls=1408, ndraw=128, logz=-7139.44, remainder_fraction=100.0000%, Lmin=-6909.47, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=174, ncalls=453, regioncalls=1536, ndraw=128, logz=-6586.35, remainder_fraction=100.0000%, Lmin=-6511.36, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=463, regioncalls=1664, ndraw=128, logz=-6229.86, remainder_fraction=100.0000%, Lmin=-6179.54, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=186, ncalls=470, regioncalls=1792, ndraw=128, logz=-5870.68, remainder_fraction=100.0000%, Lmin=-5704.16, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=484, regioncalls=2048, ndraw=128, logz=-5350.22, remainder_fraction=100.0000%, Lmin=-5299.56, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=195, ncalls=484, regioncalls=2048, ndraw=128, logz=-5230.51, remainder_fraction=100.0000%, Lmin=-5122.84, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=198, ncalls=488, regioncalls=2176, ndraw=128, logz=-5007.77, remainder_fraction=100.0000%, Lmin=-4993.48, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=204, ncalls=494, regioncalls=2304, ndraw=128, logz=-4757.04, remainder_fraction=100.0000%, Lmin=-4671.78, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=507, regioncalls=2560, ndraw=128, logz=-4376.39, remainder_fraction=100.0000%, Lmin=-4050.17, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=216, ncalls=519, regioncalls=2816, ndraw=128, logz=-3611.32, remainder_fraction=100.0000%, Lmin=-3538.07, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=222, ncalls=529, regioncalls=2944, ndraw=128, logz=-3253.14, remainder_fraction=100.0000%, Lmin=-3230.22, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=228, ncalls=534, regioncalls=3072, ndraw=128, logz=-2973.87, remainder_fraction=100.0000%, Lmin=-2936.21, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=234, ncalls=546, regioncalls=3584, ndraw=128, logz=-2717.11, remainder_fraction=100.0000%, Lmin=-2689.65, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=562, regioncalls=4096, ndraw=128, logz=-2482.73, remainder_fraction=100.0000%, Lmin=-2396.74, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=246, ncalls=574, regioncalls=4608, ndraw=128, logz=-2251.88, remainder_fraction=100.0000%, Lmin=-2227.96, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=252, ncalls=586, regioncalls=5120, ndraw=128, logz=-2050.99, remainder_fraction=100.0000%, Lmin=-2020.88, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=255, ncalls=591, regioncalls=5248, ndraw=128, logz=-1996.88, remainder_fraction=100.0000%, Lmin=-1971.99, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=258, ncalls=595, regioncalls=5376, ndraw=128, logz=-1930.62, remainder_fraction=100.0000%, Lmin=-1893.32, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=264, ncalls=607, regioncalls=5760, ndraw=128, logz=-1661.25, remainder_fraction=100.0000%, Lmin=-1630.36, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=623, regioncalls=6400, ndraw=128, logz=-1531.39, remainder_fraction=100.0000%, Lmin=-1450.33, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=640, regioncalls=6784, ndraw=128, logz=-1346.58, remainder_fraction=100.0000%, Lmin=-1304.59, Lmax=-29.10 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=656, regioncalls=6912, ndraw=128, logz=-1210.10, remainder_fraction=100.0000%, Lmin=-1193.96, Lmax=-7.65 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([63, 1])) DEBUG ultranest:integrator.py:2610 iteration=288, ncalls=656, regioncalls=6912, ndraw=128, logz=-1128.82, remainder_fraction=100.0000%, Lmin=-1115.38, Lmax=-7.65 DEBUG ultranest:integrator.py:2610 iteration=294, ncalls=667, regioncalls=7040, ndraw=128, logz=-1037.04, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=681, regioncalls=7168, ndraw=128, logz=-946.58, remainder_fraction=100.0000%, Lmin=-931.46, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=306, ncalls=704, regioncalls=7424, ndraw=128, logz=-860.81, remainder_fraction=100.0000%, Lmin=-851.17, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=312, ncalls=716, regioncalls=7552, ndraw=128, logz=-799.86, remainder_fraction=100.0000%, Lmin=-784.81, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=318, ncalls=728, regioncalls=7680, ndraw=128, logz=-721.99, remainder_fraction=100.0000%, Lmin=-712.81, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=324, ncalls=744, regioncalls=7808, ndraw=128, logz=-711.19, remainder_fraction=100.0000%, Lmin=-681.06, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=773, regioncalls=8064, ndraw=128, logz=-648.60, remainder_fraction=100.0000%, Lmin=-627.61, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=336, ncalls=773, regioncalls=8064, ndraw=128, logz=-579.77, remainder_fraction=100.0000%, Lmin=-544.60, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=342, ncalls=785, regioncalls=8320, ndraw=128, logz=-507.89, remainder_fraction=100.0000%, Lmin=-491.75, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=786, regioncalls=8448, ndraw=128, logz=-448.87, remainder_fraction=100.0000%, Lmin=-436.99, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=348, ncalls=794, regioncalls=8960, ndraw=128, logz=-440.47, remainder_fraction=100.0000%, Lmin=-410.44, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=354, ncalls=814, regioncalls=9216, ndraw=128, logz=-391.49, remainder_fraction=100.0000%, Lmin=-381.77, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=924, regioncalls=9472, ndraw=128, logz=-353.16, remainder_fraction=100.0000%, Lmin=-341.64, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=366, ncalls=924, regioncalls=9472, ndraw=128, logz=-330.60, remainder_fraction=100.0000%, Lmin=-319.63, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=372, ncalls=924, regioncalls=9472, ndraw=128, logz=-319.39, remainder_fraction=100.0000%, Lmin=-308.99, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=378, ncalls=924, regioncalls=9472, ndraw=128, logz=-294.62, remainder_fraction=100.0000%, Lmin=-274.35, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=924, regioncalls=9472, ndraw=128, logz=-256.92, remainder_fraction=100.0000%, Lmin=-243.84, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=924, regioncalls=9472, ndraw=128, logz=-231.44, remainder_fraction=100.0000%, Lmin=-216.70, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=924, regioncalls=9472, ndraw=128, logz=-208.63, remainder_fraction=100.0000%, Lmin=-197.50, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=402, ncalls=924, regioncalls=9472, ndraw=128, logz=-192.88, remainder_fraction=100.0000%, Lmin=-180.36, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=405, ncalls=924, regioncalls=9472, ndraw=128, logz=-181.54, remainder_fraction=100.0000%, Lmin=-170.96, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=408, ncalls=1052, regioncalls=9728, ndraw=128, logz=-174.82, remainder_fraction=100.0000%, Lmin=-164.65, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=414, ncalls=1052, regioncalls=9728, ndraw=128, logz=-162.11, remainder_fraction=100.0000%, Lmin=-151.03, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=1052, regioncalls=9728, ndraw=128, logz=-150.81, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=426, ncalls=1052, regioncalls=9728, ndraw=128, logz=-140.27, remainder_fraction=100.0000%, Lmin=-128.55, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=432, ncalls=1052, regioncalls=9728, ndraw=128, logz=-126.93, remainder_fraction=100.0000%, Lmin=-115.71, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=435, ncalls=1052, regioncalls=9728, ndraw=128, logz=-123.34, remainder_fraction=100.0000%, Lmin=-111.94, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=438, ncalls=1052, regioncalls=9728, ndraw=128, logz=-119.55, remainder_fraction=100.0000%, Lmin=-108.01, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=444, ncalls=1052, regioncalls=9728, ndraw=128, logz=-110.70, remainder_fraction=100.0000%, Lmin=-94.16, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=1052, regioncalls=9728, ndraw=128, logz=-100.78, remainder_fraction=100.0000%, Lmin=-86.81, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=456, ncalls=1052, regioncalls=9728, ndraw=128, logz=-90.78, remainder_fraction=100.0000%, Lmin=-77.75, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=462, ncalls=1074, regioncalls=9984, ndraw=128, logz=-82.64, remainder_fraction=100.0000%, Lmin=-69.50, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=465, ncalls=1074, regioncalls=9984, ndraw=128, logz=-79.02, remainder_fraction=100.0000%, Lmin=-67.39, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=468, ncalls=1074, regioncalls=9984, ndraw=128, logz=-75.79, remainder_fraction=100.0000%, Lmin=-64.18, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=474, ncalls=1202, regioncalls=10368, ndraw=128, logz=-70.13, remainder_fraction=100.0000%, Lmin=-54.53, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1202, regioncalls=10368, ndraw=128, logz=-61.46, remainder_fraction=100.0000%, Lmin=-49.47, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=486, ncalls=1202, regioncalls=10368, ndraw=128, logz=-57.80, remainder_fraction=100.0000%, Lmin=-46.40, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=492, ncalls=1202, regioncalls=10368, ndraw=128, logz=-54.45, remainder_fraction=100.0000%, Lmin=-43.50, Lmax=-1.39 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=1202, regioncalls=10368, ndraw=128, logz=-48.90, remainder_fraction=100.0000%, Lmin=-37.16, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=504, ncalls=1202, regioncalls=10368, ndraw=128, logz=-45.53, remainder_fraction=100.0000%, Lmin=-33.14, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=1202, regioncalls=10368, ndraw=128, logz=-40.98, remainder_fraction=100.0000%, Lmin=-29.10, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=516, ncalls=1202, regioncalls=10368, ndraw=128, logz=-37.56, remainder_fraction=100.0000%, Lmin=-25.58, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=522, ncalls=1202, regioncalls=10368, ndraw=128, logz=-33.72, remainder_fraction=100.0000%, Lmin=-22.16, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=525, ncalls=1202, regioncalls=10368, ndraw=128, logz=-32.64, remainder_fraction=100.0000%, Lmin=-21.09, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=528, ncalls=1217, regioncalls=11008, ndraw=128, logz=-31.71, remainder_fraction=100.0000%, Lmin=-20.80, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=1217, regioncalls=11008, ndraw=128, logz=-29.73, remainder_fraction=100.0000%, Lmin=-18.32, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1226, regioncalls=11136, ndraw=128, logz=-28.30, remainder_fraction=100.0000%, Lmin=-17.39, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=1235, regioncalls=11392, ndraw=128, logz=-27.41, remainder_fraction=100.0000%, Lmin=-16.54, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=1249, regioncalls=11520, ndraw=128, logz=-26.61, remainder_fraction=100.0000%, Lmin=-15.76, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=555, ncalls=1249, regioncalls=11520, ndraw=128, logz=-26.03, remainder_fraction=100.0000%, Lmin=-13.59, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=558, ncalls=1264, regioncalls=11904, ndraw=128, logz=-24.91, remainder_fraction=99.9999%, Lmin=-13.52, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=1264, regioncalls=11904, ndraw=128, logz=-23.57, remainder_fraction=99.9995%, Lmin=-12.01, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=1373, regioncalls=12416, ndraw=128, logz=-22.38, remainder_fraction=99.9981%, Lmin=-11.27, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=1373, regioncalls=12416, ndraw=128, logz=-21.67, remainder_fraction=99.9965%, Lmin=-10.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=582, ncalls=1373, regioncalls=12416, ndraw=128, logz=-20.89, remainder_fraction=99.9929%, Lmin=-9.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=585, ncalls=1373, regioncalls=12416, ndraw=128, logz=-20.38, remainder_fraction=99.9876%, Lmin=-8.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=588, ncalls=1373, regioncalls=12416, ndraw=128, logz=-19.82, remainder_fraction=99.9777%, Lmin=-8.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=1373, regioncalls=12416, ndraw=128, logz=-18.90, remainder_fraction=99.9408%, Lmin=-7.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1373, regioncalls=12416, ndraw=128, logz=-18.12, remainder_fraction=99.8597%, Lmin=-6.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=1373, regioncalls=12416, ndraw=128, logz=-17.58, remainder_fraction=99.7583%, Lmin=-6.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=612, ncalls=1373, regioncalls=12416, ndraw=128, logz=-17.16, remainder_fraction=99.6238%, Lmin=-6.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=615, ncalls=1373, regioncalls=12416, ndraw=128, logz=-16.98, remainder_fraction=99.5543%, Lmin=-6.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=1373, regioncalls=12416, ndraw=128, logz=-16.83, remainder_fraction=99.4874%, Lmin=-5.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=1389, regioncalls=12672, ndraw=128, logz=-16.49, remainder_fraction=99.3352%, Lmin=-5.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1401, regioncalls=12800, ndraw=128, logz=-16.17, remainder_fraction=99.0488%, Lmin=-4.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.81, remainder_fraction=98.7259%, Lmin=-4.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.38, remainder_fraction=97.9879%, Lmin=-3.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.00, remainder_fraction=96.9220%, Lmin=-3.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.68, remainder_fraction=95.8763%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.39, remainder_fraction=94.3145%, Lmin=-3.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.14, remainder_fraction=92.5810%, Lmin=-2.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.92, remainder_fraction=90.7918%, Lmin=-2.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=675, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.82, remainder_fraction=89.7384%, Lmin=-2.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=678, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.73, remainder_fraction=89.0900%, Lmin=-2.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.57, remainder_fraction=87.5680%, Lmin=-2.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.41, remainder_fraction=85.2447%, Lmin=-2.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.26, remainder_fraction=83.3174%, Lmin=-1.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=702, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.11, remainder_fraction=80.6842%, Lmin=-1.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=708, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.98, remainder_fraction=77.7833%, Lmin=-1.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=714, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.87, remainder_fraction=75.3946%, Lmin=-1.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.76, remainder_fraction=72.3463%, Lmin=-1.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.66, remainder_fraction=69.3637%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.56, remainder_fraction=65.9054%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=735, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.52, remainder_fraction=64.2087%, Lmin=-1.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.48, remainder_fraction=62.4469%, Lmin=-1.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=744, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.39, remainder_fraction=59.0976%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.31, remainder_fraction=55.8394%, Lmin=-0.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.24, remainder_fraction=52.5648%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=762, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.17, remainder_fraction=49.2967%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=765, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.14, remainder_fraction=47.4215%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.11, remainder_fraction=45.8487%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.06, remainder_fraction=42.6540%, Lmin=-0.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=1750, regioncalls=14336, ndraw=128, logz=-12.01, remainder_fraction=39.5737%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=786, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.96, remainder_fraction=36.9990%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.92, remainder_fraction=34.2785%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=795, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.90, remainder_fraction=33.1147%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=798, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.89, remainder_fraction=31.8738%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.85, remainder_fraction=29.5577%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1873, regioncalls=14848, ndraw=128, logz=-11.82, remainder_fraction=27.2722%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=816, ncalls=1873, regioncalls=14848, ndraw=128, logz=-11.79, remainder_fraction=25.0354%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=822, ncalls=1892, regioncalls=14976, ndraw=128, logz=-11.77, remainder_fraction=23.0405%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=825, ncalls=1905, regioncalls=15104, ndraw=128, logz=-11.75, remainder_fraction=22.1022%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=1914, regioncalls=15360, ndraw=128, logz=-11.74, remainder_fraction=21.2642%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=834, ncalls=1927, regioncalls=15488, ndraw=128, logz=-11.72, remainder_fraction=19.5390%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1940, regioncalls=15616, ndraw=128, logz=-11.70, remainder_fraction=17.8927%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=846, ncalls=1958, regioncalls=16128, ndraw=128, logz=-11.68, remainder_fraction=16.4115%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=1976, regioncalls=16256, ndraw=128, logz=-11.67, remainder_fraction=15.1147%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=858, ncalls=1976, regioncalls=16256, ndraw=128, logz=-11.65, remainder_fraction=13.8663%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=2001, regioncalls=16512, ndraw=128, logz=-11.64, remainder_fraction=12.7256%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=2001, regioncalls=16512, ndraw=128, logz=-11.63, remainder_fraction=11.6749%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=876, ncalls=2014, regioncalls=16640, ndraw=128, logz=-11.62, remainder_fraction=10.6866%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=2027, regioncalls=16768, ndraw=128, logz=-11.61, remainder_fraction=9.7877%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=885, ncalls=2027, regioncalls=16768, ndraw=128, logz=-11.60, remainder_fraction=9.3465%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=888, ncalls=2040, regioncalls=17152, ndraw=128, logz=-11.60, remainder_fraction=8.9345%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=2050, regioncalls=17280, ndraw=128, logz=-11.59, remainder_fraction=8.1799%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=2063, regioncalls=17408, ndraw=128, logz=-11.58, remainder_fraction=7.4685%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=906, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=6.8186%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=912, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=6.2315%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=915, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=5.9547%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.56, remainder_fraction=5.6925%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=924, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.56, remainder_fraction=5.1954%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.55, remainder_fraction=4.7380%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=936, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.55, remainder_fraction=4.3215%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.9403%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=945, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.7642%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.5937%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=954, ncalls=2191, regioncalls=17920, ndraw=128, logz=-11.54, remainder_fraction=3.2766%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=2209, regioncalls=18048, ndraw=128, logz=-11.53, remainder_fraction=2.9865%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.7226%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.4809%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=978, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.2605%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=984, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=2.0604%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.8777%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=996, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.7113%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1002, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.5594%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.4209%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.2947%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=2429, regioncalls=18560, ndraw=128, logz=-11.52, remainder_fraction=1.1797%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=2429, regioncalls=18560, ndraw=128, logz=-11.51, remainder_fraction=1.0750%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-8e-05 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2429 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.5 +- 0.2693 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -11.13..-0.00 (ESS = 267.4, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.48+-0.26 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 67 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 63 and 63, most (776/777 iterations) have 62 DEBUG ultranest:integrator.py:1663 at least 62 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 62 minimum live points (dlogz from 0.20 to 0.65, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.40 bs:0.27 tail:0.01 total:0.27 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 64 to 128 live points before L=-1e+01... INFO ultranest:integrator.py:1377 Will add 64 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 128.0), (-0.0010811997487929388, 128.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=2433, regioncalls=18688, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=294, ncalls=2433, regioncalls=18688, ndraw=128, logz=-1037.06, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=333, ncalls=2434, regioncalls=18944, ndraw=128, logz=-597.37, remainder_fraction=100.0000%, Lmin=-583.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=381, ncalls=2547, regioncalls=19200, ndraw=128, logz=-284.44, remainder_fraction=100.0000%, Lmin=-265.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=407, ncalls=2547, regioncalls=19200, ndraw=128, logz=-189.66, remainder_fraction=100.0000%, Lmin=-177.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=408, ncalls=2547, regioncalls=19200, ndraw=128, logz=-187.47, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=425, ncalls=2547, regioncalls=19200, ndraw=128, logz=-150.88, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=444, ncalls=2547, regioncalls=19200, ndraw=128, logz=-118.64, remainder_fraction=100.0000%, Lmin=-107.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=2547, regioncalls=19200, ndraw=128, logz=-109.91, remainder_fraction=100.0000%, Lmin=-98.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=456, ncalls=2547, regioncalls=19200, ndraw=128, logz=-102.22, remainder_fraction=100.0000%, Lmin=-91.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=465, ncalls=2547, regioncalls=19200, ndraw=128, logz=-90.95, remainder_fraction=100.0000%, Lmin=-78.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=2669, regioncalls=19456, ndraw=128, logz=-75.95, remainder_fraction=100.0000%, Lmin=-64.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=2669, regioncalls=19456, ndraw=128, logz=-74.17, remainder_fraction=100.0000%, Lmin=-62.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=492, ncalls=2669, regioncalls=19456, ndraw=128, logz=-66.69, remainder_fraction=100.0000%, Lmin=-55.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=502, ncalls=2669, regioncalls=19456, ndraw=128, logz=-60.82, remainder_fraction=100.0000%, Lmin=-49.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=504, ncalls=2669, regioncalls=19456, ndraw=128, logz=-59.92, remainder_fraction=100.0000%, Lmin=-48.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=2669, regioncalls=19456, ndraw=128, logz=-57.17, remainder_fraction=100.0000%, Lmin=-45.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=516, ncalls=2669, regioncalls=19456, ndraw=128, logz=-54.42, remainder_fraction=100.0000%, Lmin=-42.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=521, ncalls=2669, regioncalls=19456, ndraw=128, logz=-51.05, remainder_fraction=100.0000%, Lmin=-38.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=522, ncalls=2669, regioncalls=19456, ndraw=128, logz=-50.16, remainder_fraction=100.0000%, Lmin=-37.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=2669, regioncalls=19456, ndraw=128, logz=-42.42, remainder_fraction=100.0000%, Lmin=-30.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=541, ncalls=2669, regioncalls=19456, ndraw=128, logz=-41.98, remainder_fraction=100.0000%, Lmin=-29.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=2669, regioncalls=19456, ndraw=128, logz=-39.90, remainder_fraction=100.0000%, Lmin=-28.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=2669, regioncalls=19456, ndraw=128, logz=-37.92, remainder_fraction=100.0000%, Lmin=-26.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=558, ncalls=2795, regioncalls=19840, ndraw=128, logz=-36.63, remainder_fraction=100.0000%, Lmin=-24.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=563, ncalls=2795, regioncalls=19840, ndraw=128, logz=-35.35, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=2795, regioncalls=19840, ndraw=128, logz=-35.15, remainder_fraction=100.0000%, Lmin=-23.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=582, ncalls=2795, regioncalls=19840, ndraw=128, logz=-31.58, remainder_fraction=100.0000%, Lmin=-20.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=2795, regioncalls=19840, ndraw=128, logz=-29.59, remainder_fraction=100.0000%, Lmin=-18.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=2795, regioncalls=19840, ndraw=128, logz=-28.89, remainder_fraction=100.0000%, Lmin=-17.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=2795, regioncalls=19840, ndraw=128, logz=-27.92, remainder_fraction=100.0000%, Lmin=-16.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=2795, regioncalls=19840, ndraw=128, logz=-27.11, remainder_fraction=100.0000%, Lmin=-15.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=2923, regioncalls=20096, ndraw=128, logz=-26.54, remainder_fraction=100.0000%, Lmin=-15.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=2923, regioncalls=20096, ndraw=128, logz=-25.80, remainder_fraction=99.9999%, Lmin=-13.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=637, ncalls=2923, regioncalls=20096, ndraw=128, logz=-24.70, remainder_fraction=99.9998%, Lmin=-12.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=2923, regioncalls=20096, ndraw=128, logz=-24.03, remainder_fraction=99.9996%, Lmin=-12.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=2923, regioncalls=20096, ndraw=128, logz=-23.40, remainder_fraction=99.9993%, Lmin=-11.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=2923, regioncalls=20096, ndraw=128, logz=-22.78, remainder_fraction=99.9987%, Lmin=-11.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=2923, regioncalls=20096, ndraw=128, logz=-21.93, remainder_fraction=99.9972%, Lmin=-10.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=2923, regioncalls=20096, ndraw=128, logz=-21.43, remainder_fraction=99.9955%, Lmin=-9.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=2923, regioncalls=20096, ndraw=128, logz=-20.29, remainder_fraction=99.9855%, Lmin=-8.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=2923, regioncalls=20096, ndraw=128, logz=-19.79, remainder_fraction=99.9762%, Lmin=-8.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=2923, regioncalls=20096, ndraw=128, logz=-19.33, remainder_fraction=99.9610%, Lmin=-7.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=2923, regioncalls=20096, ndraw=128, logz=-17.89, remainder_fraction=99.8279%, Lmin=-6.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=725, ncalls=2923, regioncalls=20096, ndraw=128, logz=-17.67, remainder_fraction=99.7839%, Lmin=-6.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=2935, regioncalls=20352, ndraw=128, logz=-17.38, remainder_fraction=99.7043%, Lmin=-6.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=744, ncalls=2945, regioncalls=20480, ndraw=128, logz=-16.99, remainder_fraction=99.5964%, Lmin=-5.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=755, ncalls=2945, regioncalls=20480, ndraw=128, logz=-16.65, remainder_fraction=99.4267%, Lmin=-5.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=3060, regioncalls=20736, ndraw=128, logz=-16.01, remainder_fraction=98.9550%, Lmin=-4.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.78, remainder_fraction=98.6883%, Lmin=-4.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=784, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.63, remainder_fraction=98.4813%, Lmin=-3.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.33, remainder_fraction=97.9290%, Lmin=-3.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.94, remainder_fraction=96.8743%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.77, remainder_fraction=96.2143%, Lmin=-3.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=813, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.69, remainder_fraction=95.9153%, Lmin=-3.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=843, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.00, remainder_fraction=91.9626%, Lmin=-2.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.84, remainder_fraction=90.7842%, Lmin=-2.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.63, remainder_fraction=88.4445%, Lmin=-2.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=872, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.50, remainder_fraction=86.8348%, Lmin=-2.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=876, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.45, remainder_fraction=85.9885%, Lmin=-1.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.36, remainder_fraction=84.8095%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=888, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.28, remainder_fraction=83.2903%, Lmin=-1.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.14, remainder_fraction=80.5574%, Lmin=-1.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=901, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.13, remainder_fraction=80.2663%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=912, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.00, remainder_fraction=77.5329%, Lmin=-1.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.94, remainder_fraction=76.2756%, Lmin=-1.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=932, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.81, remainder_fraction=72.6547%, Lmin=-1.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=936, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.78, remainder_fraction=71.4900%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.72, remainder_fraction=69.8277%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=962, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.56, remainder_fraction=64.3652%, Lmin=-1.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.53, remainder_fraction=63.1678%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.49, remainder_fraction=61.5615%, Lmin=-0.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.36, remainder_fraction=56.5519%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=991, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.35, remainder_fraction=56.2055%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1002, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.28, remainder_fraction=53.0360%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.25, remainder_fraction=51.3933%, Lmin=-0.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.15, remainder_fraction=46.2975%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1032, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.13, remainder_fraction=44.6211%, Lmin=-0.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.05, remainder_fraction=40.0149%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1062, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.00, remainder_fraction=37.2727%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=3291, regioncalls=21248, ndraw=128, logz=-11.98, remainder_fraction=35.8703%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1074, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.96, remainder_fraction=34.5188%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1084, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.93, remainder_fraction=32.4748%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1086, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.92, remainder_fraction=32.0399%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1092, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.90, remainder_fraction=30.8065%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.86, remainder_fraction=27.3363%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1122, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.83, remainder_fraction=25.2494%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.79, remainder_fraction=22.0287%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1172, ncalls=3438, regioncalls=21888, ndraw=128, logz=-11.73, remainder_fraction=17.8873%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.73, remainder_fraction=17.3835%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1188, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.71, remainder_fraction=15.9739%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.70, remainder_fraction=14.6487%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1201, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.69, remainder_fraction=14.5499%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1206, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.69, remainder_fraction=14.0427%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1212, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.68, remainder_fraction=13.4495%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1231, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.66, remainder_fraction=11.7219%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1236, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.66, remainder_fraction=11.2963%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.65, remainder_fraction=10.8058%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1254, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.64, remainder_fraction=9.8969%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.64, remainder_fraction=9.4586%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1278, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.62, remainder_fraction=8.2689%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1302, ncalls=3576, regioncalls=22656, ndraw=128, logz=-11.61, remainder_fraction=6.9033%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1332, ncalls=3622, regioncalls=23040, ndraw=128, logz=-11.59, remainder_fraction=5.4995%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=3634, regioncalls=23168, ndraw=128, logz=-11.59, remainder_fraction=5.0179%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1347, ncalls=3634, regioncalls=23168, ndraw=128, logz=-11.59, remainder_fraction=4.9040%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.59, remainder_fraction=4.7925%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1362, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=4.3724%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=3.9261%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=3.8070%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1404, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.57, remainder_fraction=3.1659%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1405, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.57, remainder_fraction=3.1418%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1422, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.7558%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1436, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.4740%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1452, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.1859%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1458, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.0868%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1476, ncalls=3767, regioncalls=23808, ndraw=128, logz=-11.55, remainder_fraction=1.8154%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1482, ncalls=3767, regioncalls=23808, ndraw=128, logz=-11.55, remainder_fraction=1.7332%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=3786, regioncalls=23936, ndraw=128, logz=-11.55, remainder_fraction=1.5793%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=3801, regioncalls=24064, ndraw=128, logz=-11.55, remainder_fraction=1.5079%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1506, ncalls=3816, regioncalls=24192, ndraw=128, logz=-11.55, remainder_fraction=1.4394%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1524, ncalls=3832, regioncalls=24320, ndraw=128, logz=-11.55, remainder_fraction=1.2519%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1526, ncalls=3832, regioncalls=24320, ndraw=128, logz=-11.55, remainder_fraction=1.2326%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=1.1948%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1542, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=1.0886%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1554, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9918%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9466%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1566, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9034%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1572, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.8622%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1578, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.8229%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1584, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7853%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7495%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1596, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7153%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1602, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.6827%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1608, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6515%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1613, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6266%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6217%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5933%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5663%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1632, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5404%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1638, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5157%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1644, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.4921%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=4082, regioncalls=25088, ndraw=128, logz=-11.54, remainder_fraction=0.4696%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=4082, regioncalls=25088, ndraw=128, logz=-11.54, remainder_fraction=0.4482%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1662, ncalls=4108, regioncalls=25344, ndraw=128, logz=-11.54, remainder_fraction=0.4277%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1668, ncalls=4108, regioncalls=25344, ndraw=128, logz=-11.54, remainder_fraction=0.4082%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1674, ncalls=4125, regioncalls=25472, ndraw=128, logz=-11.54, remainder_fraction=0.3895%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=4125, regioncalls=25472, ndraw=128, logz=-11.54, remainder_fraction=0.3717%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1686, ncalls=4135, regioncalls=25600, ndraw=128, logz=-11.54, remainder_fraction=0.3547%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1692, ncalls=4146, regioncalls=25728, ndraw=128, logz=-11.54, remainder_fraction=0.3385%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1698, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3230%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3180%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1704, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3082%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2941%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2807%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1722, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2679%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2556%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1729, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2536%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1734, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2439%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1740, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2328%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2221%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1752, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2119%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1758, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2022%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1764, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.1930%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.1842%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1776, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1757%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1677%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1600%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1794, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1527%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1457%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1806, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1390%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1812, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1327%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1816, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1286%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1818, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1266%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1208%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 4505 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.56 +- 0.3516 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -10.40..-0.00 (ESS = 519.9, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.17 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 89 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 31 and 127, most (304/962 iterations) have 126 DEBUG ultranest:integrator.py:1663 at least 31 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 31 minimum live points (dlogz from 0.29 to 0.78, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.29 bs:0.35 tail:0.00 total:0.35 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 67 to 256 live points before L=-1e+01... INFO ultranest:integrator.py:1377 Will add 189 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 256.0), (-0.0010811997487929388, 256.0), (-0.001004869805783571, 256.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=4506, regioncalls=27008, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=4509, regioncalls=27264, ndraw=128, logz=-1037.08, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=328, ncalls=4512, regioncalls=27520, ndraw=128, logz=-682.35, remainder_fraction=100.0000%, Lmin=-672.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=395, ncalls=4611, regioncalls=27776, ndraw=128, logz=-237.95, remainder_fraction=100.0000%, Lmin=-222.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=413, ncalls=4611, regioncalls=27776, ndraw=128, logz=-187.53, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=4611, regioncalls=27776, ndraw=128, logz=-150.94, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=4611, regioncalls=27776, ndraw=128, logz=-119.70, remainder_fraction=100.0000%, Lmin=-108.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=4611, regioncalls=27776, ndraw=128, logz=-118.36, remainder_fraction=100.0000%, Lmin=-107.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=4611, regioncalls=27776, ndraw=128, logz=-81.57, remainder_fraction=100.0000%, Lmin=-69.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=501, ncalls=4611, regioncalls=27776, ndraw=128, logz=-66.24, remainder_fraction=100.0000%, Lmin=-55.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=4739, regioncalls=28032, ndraw=128, logz=-51.86, remainder_fraction=100.0000%, Lmin=-40.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=4739, regioncalls=28032, ndraw=128, logz=-49.97, remainder_fraction=100.0000%, Lmin=-37.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=4739, regioncalls=28032, ndraw=128, logz=-43.13, remainder_fraction=100.0000%, Lmin=-31.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=555, ncalls=4739, regioncalls=28032, ndraw=128, logz=-42.04, remainder_fraction=100.0000%, Lmin=-30.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=4739, regioncalls=28032, ndraw=128, logz=-39.46, remainder_fraction=100.0000%, Lmin=-27.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=4739, regioncalls=28032, ndraw=128, logz=-36.75, remainder_fraction=100.0000%, Lmin=-25.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=583, ncalls=4739, regioncalls=28032, ndraw=128, logz=-35.38, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=4855, regioncalls=28288, ndraw=128, logz=-28.98, remainder_fraction=100.0000%, Lmin=-17.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=4855, regioncalls=28288, ndraw=128, logz=-28.39, remainder_fraction=100.0000%, Lmin=-17.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=4855, regioncalls=28288, ndraw=128, logz=-27.90, remainder_fraction=100.0000%, Lmin=-16.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=4855, regioncalls=28288, ndraw=128, logz=-27.40, remainder_fraction=100.0000%, Lmin=-16.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.90, remainder_fraction=100.0000%, Lmin=-15.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=653, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.49, remainder_fraction=100.0000%, Lmin=-15.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.42, remainder_fraction=100.0000%, Lmin=-15.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=4855, regioncalls=28288, ndraw=128, logz=-25.35, remainder_fraction=99.9999%, Lmin=-13.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=678, ncalls=4855, regioncalls=28288, ndraw=128, logz=-24.18, remainder_fraction=99.9997%, Lmin=-12.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=4855, regioncalls=28288, ndraw=128, logz=-23.23, remainder_fraction=99.9992%, Lmin=-11.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=702, ncalls=4855, regioncalls=28288, ndraw=128, logz=-22.44, remainder_fraction=99.9983%, Lmin=-11.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=708, ncalls=4855, regioncalls=28288, ndraw=128, logz=-22.13, remainder_fraction=99.9979%, Lmin=-10.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=4983, regioncalls=28544, ndraw=128, logz=-21.52, remainder_fraction=99.9965%, Lmin=-10.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=4983, regioncalls=28544, ndraw=128, logz=-21.19, remainder_fraction=99.9950%, Lmin=-9.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=4983, regioncalls=28544, ndraw=128, logz=-20.91, remainder_fraction=99.9933%, Lmin=-9.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=4983, regioncalls=28544, ndraw=128, logz=-20.61, remainder_fraction=99.9915%, Lmin=-9.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=4983, regioncalls=28544, ndraw=128, logz=-19.57, remainder_fraction=99.9752%, Lmin=-8.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=4983, regioncalls=28544, ndraw=128, logz=-19.00, remainder_fraction=99.9539%, Lmin=-7.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.74, remainder_fraction=99.9394%, Lmin=-7.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=775, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.70, remainder_fraction=99.9364%, Lmin=-7.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=786, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.27, remainder_fraction=99.9021%, Lmin=-6.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=4983, regioncalls=28544, ndraw=128, logz=-17.64, remainder_fraction=99.8105%, Lmin=-6.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=4983, regioncalls=28544, ndraw=128, logz=-17.18, remainder_fraction=99.7066%, Lmin=-6.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=4983, regioncalls=28544, ndraw=128, logz=-16.72, remainder_fraction=99.5474%, Lmin=-5.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=867, ncalls=4983, regioncalls=28544, ndraw=128, logz=-16.05, remainder_fraction=99.1215%, Lmin=-4.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=913, ncalls=5013, regioncalls=29696, ndraw=128, logz=-14.91, remainder_fraction=97.2821%, Lmin=-3.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=5029, regioncalls=30080, ndraw=128, logz=-14.38, remainder_fraction=95.3083%, Lmin=-2.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=5029, regioncalls=30080, ndraw=128, logz=-14.28, remainder_fraction=94.8380%, Lmin=-2.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=963, ncalls=5150, regioncalls=30336, ndraw=128, logz=-14.05, remainder_fraction=93.5025%, Lmin=-2.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.93, remainder_fraction=92.5870%, Lmin=-2.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1009, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.47, remainder_fraction=88.2266%, Lmin=-2.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.41, remainder_fraction=87.5361%, Lmin=-2.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.29, remainder_fraction=85.8432%, Lmin=-2.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1038, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.18, remainder_fraction=84.2791%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1054, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.04, remainder_fraction=81.8261%, Lmin=-1.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.03, remainder_fraction=81.5433%, Lmin=-1.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1062, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.98, remainder_fraction=80.6121%, Lmin=-1.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1086, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.80, remainder_fraction=76.6455%, Lmin=-1.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1098, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.72, remainder_fraction=74.6206%, Lmin=-1.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1122, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.57, remainder_fraction=70.2203%, Lmin=-1.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.46, remainder_fraction=66.4358%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1146, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.44, remainder_fraction=65.6969%, Lmin=-1.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1164, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.35, remainder_fraction=62.3245%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.29, remainder_fraction=60.1290%, Lmin=-0.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1187, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.24, remainder_fraction=58.2223%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.21, remainder_fraction=56.9507%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1206, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.16, remainder_fraction=54.6266%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1212, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.13, remainder_fraction=53.4593%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.06, remainder_fraction=50.1470%, Lmin=-0.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=5370, regioncalls=30848, ndraw=128, logz=-12.00, remainder_fraction=46.7688%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1254, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.98, remainder_fraction=45.7204%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.96, remainder_fraction=44.6320%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1277, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.91, remainder_fraction=41.6147%, Lmin=-0.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.88, remainder_fraction=39.4202%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1321, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.80, remainder_fraction=34.7283%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.75, remainder_fraction=31.4702%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1362, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.72, remainder_fraction=29.1227%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1368, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.71, remainder_fraction=28.3381%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=5406, regioncalls=31488, ndraw=128, logz=-11.61, remainder_fraction=21.0434%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=5406, regioncalls=31488, ndraw=128, logz=-11.60, remainder_fraction=20.4862%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1457, ncalls=5416, regioncalls=31616, ndraw=128, logz=-11.58, remainder_fraction=18.9227%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1464, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.57, remainder_fraction=18.2990%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1476, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.56, remainder_fraction=17.2881%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.55, remainder_fraction=15.8845%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1501, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.54, remainder_fraction=15.3600%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.52, remainder_fraction=13.3208%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.51, remainder_fraction=12.9431%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1544, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.51, remainder_fraction=12.4551%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1548, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.50, remainder_fraction=12.2101%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.49, remainder_fraction=11.5199%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1572, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.49, remainder_fraction=10.8593%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.46, remainder_fraction=8.8170%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.46, remainder_fraction=8.3070%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1631, ncalls=5554, regioncalls=32256, ndraw=128, logz=-11.46, remainder_fraction=8.0995%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.45, remainder_fraction=7.1425%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1662, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.44, remainder_fraction=6.9287%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.44, remainder_fraction=6.3244%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1692, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.9508%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.2679%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1718, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.2140%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1740, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.42, remainder_fraction=4.6584%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1762, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=4.1613%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.9946%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.7549%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.6402%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1794, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.5303%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1812, ncalls=5675, regioncalls=32768, ndraw=128, logz=-11.40, remainder_fraction=3.2177%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=5689, regioncalls=32896, ndraw=128, logz=-11.40, remainder_fraction=3.0243%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1830, ncalls=5689, regioncalls=32896, ndraw=128, logz=-11.40, remainder_fraction=2.9321%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1855, ncalls=5703, regioncalls=33024, ndraw=128, logz=-11.40, remainder_fraction=2.5769%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1878, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.40, remainder_fraction=2.2880%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1884, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=2.2179%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1899, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=2.0519%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1942, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.6417%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1962, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.4800%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.3478%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1992, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.2663%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.1177%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2031, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.0338%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=5832, regioncalls=33664, ndraw=128, logz=-11.38, remainder_fraction=0.9865%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2052, ncalls=5832, regioncalls=33664, ndraw=128, logz=-11.38, remainder_fraction=0.9266%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2058, ncalls=5845, regioncalls=33792, ndraw=128, logz=-11.38, remainder_fraction=0.8981%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2064, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8705%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8437%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2078, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8092%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.7214%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2122, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.6432%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2136, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.5979%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2154, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.5443%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2196, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.4371%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2216, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3937%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3737%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2232, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3622%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2260, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3129%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2262, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3096%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2268, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.38, remainder_fraction=0.3001%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.38, remainder_fraction=0.2818%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2292, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.2647%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2303, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.2499%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2346, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1995%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2382, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1653%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2388, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1602%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2412, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1413%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1327%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1286%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2452, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1146%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2454, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1134%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2460, ncalls=6234, regioncalls=35072, ndraw=128, logz=-11.37, remainder_fraction=0.1099%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 6234 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.38 +- 0.3175 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -8.83..-0.00 (ESS = 776.0, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.16 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 104 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 21 and 190, most (637/1347 iterations) have 189 DEBUG ultranest:integrator.py:1663 at least 20 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 20 minimum live points (dlogz from 0.24 to 0.82, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.23 bs:0.32 tail:0.00 total:0.32 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 72 to 382 live points before L=-9... INFO ultranest:integrator.py:1377 Will add 310 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 382.0), (-0.0010811997487929388, 382.0), (-0.001004869805783571, 382.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=6361, regioncalls=35456, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=6361, regioncalls=35456, ndraw=138, logz=-1037.10, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=395, ncalls=6361, regioncalls=35456, ndraw=140, logz=-237.94, remainder_fraction=100.0000%, Lmin=-222.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=413, ncalls=6361, regioncalls=35456, ndraw=140, logz=-187.52, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=6361, regioncalls=35456, ndraw=138, logz=-150.93, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=6372, regioncalls=35864, ndraw=136, logz=-122.55, remainder_fraction=100.0000%, Lmin=-110.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=462, ncalls=6372, regioncalls=35864, ndraw=134, logz=-107.59, remainder_fraction=100.0000%, Lmin=-94.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=6503, regioncalls=36126, ndraw=131, logz=-82.94, remainder_fraction=100.0000%, Lmin=-70.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=6503, regioncalls=36126, ndraw=128, logz=-74.24, remainder_fraction=100.0000%, Lmin=-62.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=508, ncalls=6503, regioncalls=36126, ndraw=128, logz=-66.86, remainder_fraction=100.0000%, Lmin=-55.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=528, ncalls=6503, regioncalls=36126, ndraw=128, logz=-58.10, remainder_fraction=100.0000%, Lmin=-46.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=6503, regioncalls=36126, ndraw=128, logz=-56.27, remainder_fraction=100.0000%, Lmin=-44.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=6503, regioncalls=36126, ndraw=128, logz=-50.43, remainder_fraction=100.0000%, Lmin=-38.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=563, ncalls=6503, regioncalls=36126, ndraw=128, logz=-45.44, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=6503, regioncalls=36126, ndraw=128, logz=-41.88, remainder_fraction=100.0000%, Lmin=-30.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=6503, regioncalls=36126, ndraw=128, logz=-38.49, remainder_fraction=100.0000%, Lmin=-26.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=6503, regioncalls=36126, ndraw=128, logz=-37.46, remainder_fraction=100.0000%, Lmin=-26.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=6503, regioncalls=36126, ndraw=128, logz=-36.31, remainder_fraction=100.0000%, Lmin=-24.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=612, ncalls=6503, regioncalls=36126, ndraw=128, logz=-35.38, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=6519, regioncalls=36510, ndraw=128, logz=-32.03, remainder_fraction=100.0000%, Lmin=-20.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=638, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.84, remainder_fraction=100.0000%, Lmin=-20.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.53, remainder_fraction=100.0000%, Lmin=-20.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.00, remainder_fraction=100.0000%, Lmin=-19.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=6646, regioncalls=36894, ndraw=128, logz=-30.41, remainder_fraction=100.0000%, Lmin=-19.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=6646, regioncalls=36894, ndraw=128, logz=-29.25, remainder_fraction=100.0000%, Lmin=-18.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=6646, regioncalls=36894, ndraw=128, logz=-28.75, remainder_fraction=100.0000%, Lmin=-17.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=679, ncalls=6646, regioncalls=36894, ndraw=128, logz=-28.25, remainder_fraction=100.0000%, Lmin=-17.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=6646, regioncalls=36894, ndraw=128, logz=-27.96, remainder_fraction=100.0000%, Lmin=-16.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=6646, regioncalls=36894, ndraw=128, logz=-27.25, remainder_fraction=100.0000%, Lmin=-16.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=6646, regioncalls=36894, ndraw=128, logz=-25.07, remainder_fraction=99.9999%, Lmin=-13.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=6646, regioncalls=36894, ndraw=128, logz=-24.72, remainder_fraction=99.9998%, Lmin=-13.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6646, regioncalls=36894, ndraw=128, logz=-23.95, remainder_fraction=99.9996%, Lmin=-12.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=6646, regioncalls=36894, ndraw=128, logz=-23.61, remainder_fraction=99.9995%, Lmin=-12.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=6646, regioncalls=36894, ndraw=128, logz=-22.98, remainder_fraction=99.9990%, Lmin=-11.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=6646, regioncalls=36894, ndraw=128, logz=-22.68, remainder_fraction=99.9988%, Lmin=-11.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=776, ncalls=6657, regioncalls=37150, ndraw=128, logz=-22.59, remainder_fraction=99.9987%, Lmin=-11.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=6666, regioncalls=37278, ndraw=128, logz=-21.98, remainder_fraction=99.9976%, Lmin=-10.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=6674, regioncalls=37406, ndraw=128, logz=-21.53, remainder_fraction=99.9963%, Lmin=-10.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=822, ncalls=6683, regioncalls=37534, ndraw=128, logz=-20.89, remainder_fraction=99.9928%, Lmin=-9.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=6683, regioncalls=37534, ndraw=128, logz=-20.68, remainder_fraction=99.9912%, Lmin=-9.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=835, ncalls=6695, regioncalls=37662, ndraw=128, logz=-20.40, remainder_fraction=99.9887%, Lmin=-8.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=6695, regioncalls=37662, ndraw=128, logz=-19.75, remainder_fraction=99.9780%, Lmin=-8.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=6706, regioncalls=37918, ndraw=128, logz=-19.34, remainder_fraction=99.9658%, Lmin=-7.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=6706, regioncalls=37918, ndraw=128, logz=-18.77, remainder_fraction=99.9369%, Lmin=-7.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=6718, regioncalls=38046, ndraw=128, logz=-18.44, remainder_fraction=99.9116%, Lmin=-7.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=896, ncalls=6718, regioncalls=38046, ndraw=128, logz=-18.38, remainder_fraction=99.9065%, Lmin=-7.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.82, remainder_fraction=99.8296%, Lmin=-6.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.55, remainder_fraction=99.7768%, Lmin=-6.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=956, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.07, remainder_fraction=99.6489%, Lmin=-5.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.91, remainder_fraction=99.5984%, Lmin=-5.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.53, remainder_fraction=99.4020%, Lmin=-5.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=996, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.43, remainder_fraction=99.3359%, Lmin=-5.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.21, remainder_fraction=99.2037%, Lmin=-4.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.11, remainder_fraction=99.1287%, Lmin=-4.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1016, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.07, remainder_fraction=99.1029%, Lmin=-4.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.00, remainder_fraction=99.0398%, Lmin=-4.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1038, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.69, remainder_fraction=98.6639%, Lmin=-4.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.49, remainder_fraction=98.3777%, Lmin=-3.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.39, remainder_fraction=98.2236%, Lmin=-3.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1076, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.09, remainder_fraction=97.6003%, Lmin=-3.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1098, ncalls=6839, regioncalls=38302, ndraw=128, logz=-14.79, remainder_fraction=96.7437%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=6839, regioncalls=38302, ndraw=128, logz=-14.64, remainder_fraction=96.1617%, Lmin=-3.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1134, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.35, remainder_fraction=94.8765%, Lmin=-2.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1139, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.29, remainder_fraction=94.5864%, Lmin=-2.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1158, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.09, remainder_fraction=93.3880%, Lmin=-2.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1201, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.68, remainder_fraction=90.1803%, Lmin=-2.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.35, remainder_fraction=86.2793%, Lmin=-1.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1266, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.19, remainder_fraction=83.6994%, Lmin=-1.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1284, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.08, remainder_fraction=81.8688%, Lmin=-1.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1308, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.94, remainder_fraction=79.1812%, Lmin=-1.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1314, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.91, remainder_fraction=78.4698%, Lmin=-1.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.76, remainder_fraction=74.5431%, Lmin=-1.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1368, ncalls=6959, regioncalls=39070, ndraw=128, logz=-12.64, remainder_fraction=71.3420%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1396, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.52, remainder_fraction=67.5284%, Lmin=-1.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1404, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.49, remainder_fraction=66.3431%, Lmin=-1.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.46, remainder_fraction=65.5363%, Lmin=-1.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1416, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.44, remainder_fraction=64.6824%, Lmin=-1.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.37, remainder_fraction=62.2065%, Lmin=-0.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1458, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.29, remainder_fraction=59.1336%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1482, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.21, remainder_fraction=55.7232%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.10, remainder_fraction=50.6385%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1524, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.09, remainder_fraction=49.8769%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.06, remainder_fraction=48.2513%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1542, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.04, remainder_fraction=47.4784%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=7064, regioncalls=39326, ndraw=128, logz=-11.93, remainder_fraction=41.2959%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1608, ncalls=7064, regioncalls=39326, ndraw=128, logz=-11.90, remainder_fraction=39.1822%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.89, remainder_fraction=38.4617%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.84, remainder_fraction=35.6138%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.73, remainder_fraction=27.9367%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1722, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.72, remainder_fraction=27.3930%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.71, remainder_fraction=26.8532%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.69, remainder_fraction=25.3058%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1758, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.68, remainder_fraction=24.3436%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1761, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.68, remainder_fraction=24.0906%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1764, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.67, remainder_fraction=23.8601%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.67, remainder_fraction=23.4015%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.65, remainder_fraction=22.5009%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.62, remainder_fraction=19.5045%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1842, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.60, remainder_fraction=18.3242%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1860, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.59, remainder_fraction=17.2409%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1881, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.57, remainder_fraction=16.0354%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1896, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=15.2150%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1902, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=14.8963%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1908, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=14.5770%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.55, remainder_fraction=13.9809%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1945, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.54, remainder_fraction=12.8134%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1956, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.53, remainder_fraction=12.3213%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1992, ncalls=7299, regioncalls=40094, ndraw=128, logz=-11.51, remainder_fraction=10.8408%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1998, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.6135%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2004, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.3875%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2008, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.2385%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.49, remainder_fraction=9.1279%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2068, ncalls=7331, regioncalls=40606, ndraw=128, logz=-11.49, remainder_fraction=8.2488%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=7331, regioncalls=40606, ndraw=128, logz=-11.48, remainder_fraction=8.1912%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2076, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.48, remainder_fraction=8.0155%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2106, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.47, remainder_fraction=7.1843%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2124, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.47, remainder_fraction=6.7270%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2154, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.46, remainder_fraction=6.0304%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2191, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=5.2636%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2220, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=4.7287%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=4.6249%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2252, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.44, remainder_fraction=4.1999%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2256, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.44, remainder_fraction=4.1379%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2262, ncalls=7471, regioncalls=41246, ndraw=128, logz=-11.44, remainder_fraction=4.0465%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2310, ncalls=7471, regioncalls=41246, ndraw=128, logz=-11.43, remainder_fraction=3.3857%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2328, ncalls=7484, regioncalls=41374, ndraw=128, logz=-11.43, remainder_fraction=3.1667%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2379, ncalls=7503, regioncalls=41630, ndraw=128, logz=-11.43, remainder_fraction=2.6188%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2394, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.4757%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.4208%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2406, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.3674%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2418, ncalls=7519, regioncalls=42014, ndraw=128, logz=-11.42, remainder_fraction=2.2637%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=7525, regioncalls=42142, ndraw=128, logz=-11.42, remainder_fraction=2.2136%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=7534, regioncalls=42270, ndraw=128, logz=-11.42, remainder_fraction=2.1647%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2442, ncalls=7534, regioncalls=42270, ndraw=128, logz=-11.42, remainder_fraction=2.0696%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2460, ncalls=7551, regioncalls=42526, ndraw=128, logz=-11.42, remainder_fraction=1.9351%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2472, ncalls=7551, regioncalls=42526, ndraw=128, logz=-11.42, remainder_fraction=1.8500%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2514, ncalls=7565, regioncalls=42654, ndraw=128, logz=-11.42, remainder_fraction=1.5810%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2526, ncalls=7573, regioncalls=42782, ndraw=128, logz=-11.41, remainder_fraction=1.5116%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2538, ncalls=7573, regioncalls=42782, ndraw=128, logz=-11.41, remainder_fraction=1.4451%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2544, ncalls=7585, regioncalls=42910, ndraw=128, logz=-11.41, remainder_fraction=1.4130%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2575, ncalls=7600, regioncalls=43038, ndraw=128, logz=-11.41, remainder_fraction=1.2579%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2586, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=1.2070%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2628, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=1.0309%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9854%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2652, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9420%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2664, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9004%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2670, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.8803%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.8227%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2697, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7953%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2706, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7689%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2712, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7517%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2724, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7186%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.5734%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2836, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4714%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2856, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4372%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2868, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4179%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2886, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3905%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3705%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2904, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3649%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2940, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.3186%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2958, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2977%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2955%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2846%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2994, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2600%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3020, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2357%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3024, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2322%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3030, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2270%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3036, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2219%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3082, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1866%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3084, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1852%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3096, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1770%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3102, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1730%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3114, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1654%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3132, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1545%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3142, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1488%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3144, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1477%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3156, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1411%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3162, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1380%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3186, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1260%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3192, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1232%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3203, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1182%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 8043 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. INFO ultranest:integrator.py:2359 To achieve the desired logz accuracy, min_num_live_points was increased to 317 INFO ultranest:integrator.py:1393 Widening roots to 317 live points (have 64 already) ... INFO ultranest:integrator.py:1433 Sampling 253 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=10, min_num_live_points=317, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 317.0), (inf, 317.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=8424, regioncalls=44190, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-241488.71, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=8424, regioncalls=44190, ndraw=128, logz=-162015.11, remainder_fraction=100.0000%, Lmin=-161448.65, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=8424, regioncalls=44190, ndraw=128, logz=-131996.59, remainder_fraction=100.0000%, Lmin=-131605.67, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=71, ncalls=8424, regioncalls=44190, ndraw=128, logz=-128725.16, remainder_fraction=100.0000%, Lmin=-128075.71, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=8424, regioncalls=44190, ndraw=128, logz=-116039.81, remainder_fraction=100.0000%, Lmin=-114669.88, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=142, ncalls=8532, regioncalls=44318, ndraw=128, logz=-99426.57, remainder_fraction=100.0000%, Lmin=-98932.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=8532, regioncalls=44318, ndraw=128, logz=-94469.85, remainder_fraction=100.0000%, Lmin=-94083.98, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=8532, regioncalls=44318, ndraw=128, logz=-87325.59, remainder_fraction=100.0000%, Lmin=-86803.89, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=213, ncalls=8532, regioncalls=44318, ndraw=128, logz=-82682.38, remainder_fraction=100.0000%, Lmin=-82549.78, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=224, ncalls=8618, regioncalls=44446, ndraw=128, logz=-80003.59, remainder_fraction=100.0000%, Lmin=-79785.50, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=256, ncalls=8618, regioncalls=44446, ndraw=128, logz=-70498.54, remainder_fraction=100.0000%, Lmin=-70003.16, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=284, ncalls=8618, regioncalls=44446, ndraw=128, logz=-64668.85, remainder_fraction=100.0000%, Lmin=-64418.55, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=288, ncalls=8690, regioncalls=44574, ndraw=128, logz=-63638.76, remainder_fraction=100.0000%, Lmin=-63331.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=8690, regioncalls=44574, ndraw=128, logz=-58374.89, remainder_fraction=100.0000%, Lmin=-58204.04, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=8751, regioncalls=44702, ndraw=128, logz=-53117.67, remainder_fraction=100.0000%, Lmin=-53020.86, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=356, ncalls=8751, regioncalls=44702, ndraw=128, logz=-52754.91, remainder_fraction=100.0000%, Lmin=-52549.25, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=8795, regioncalls=44830, ndraw=128, logz=-46729.14, remainder_fraction=100.0000%, Lmin=-46556.06, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=416, ncalls=8795, regioncalls=44830, ndraw=128, logz=-41641.47, remainder_fraction=100.0000%, Lmin=-41619.23, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=427, ncalls=8847, regioncalls=44958, ndraw=128, logz=-40285.78, remainder_fraction=100.0000%, Lmin=-40055.45, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=8888, regioncalls=45086, ndraw=128, logz=-33470.46, remainder_fraction=100.0000%, Lmin=-33458.45, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=8888, regioncalls=45086, ndraw=128, logz=-31546.84, remainder_fraction=100.0000%, Lmin=-31396.11, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=8959, regioncalls=45342, ndraw=128, logz=-27877.51, remainder_fraction=100.0000%, Lmin=-27864.29, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=569, ncalls=8997, regioncalls=45470, ndraw=128, logz=-25189.21, remainder_fraction=100.0000%, Lmin=-25077.39, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=608, ncalls=9022, regioncalls=45598, ndraw=128, logz=-22115.61, remainder_fraction=100.0000%, Lmin=-22086.43, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=641, ncalls=9077, regioncalls=45854, ndraw=128, logz=-20053.07, remainder_fraction=100.0000%, Lmin=-20041.42, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=9117, regioncalls=46110, ndraw=128, logz=-18174.90, remainder_fraction=100.0000%, Lmin=-18074.66, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=9134, regioncalls=46238, ndraw=128, logz=-16363.81, remainder_fraction=100.0000%, Lmin=-16329.53, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=9161, regioncalls=46366, ndraw=128, logz=-15518.76, remainder_fraction=100.0000%, Lmin=-15470.57, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=736, ncalls=9170, regioncalls=46494, ndraw=128, logz=-14427.59, remainder_fraction=100.0000%, Lmin=-14415.73, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=9213, regioncalls=46878, ndraw=128, logz=-12734.27, remainder_fraction=100.0000%, Lmin=-12708.83, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=784, ncalls=9229, regioncalls=47006, ndraw=128, logz=-12142.61, remainder_fraction=100.0000%, Lmin=-12106.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=9277, regioncalls=47646, ndraw=128, logz=-10709.40, remainder_fraction=100.0000%, Lmin=-10695.44, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=855, ncalls=9313, regioncalls=48030, ndraw=128, logz=-9925.89, remainder_fraction=100.0000%, Lmin=-9864.47, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=926, ncalls=9382, regioncalls=48926, ndraw=128, logz=-7688.58, remainder_fraction=100.0000%, Lmin=-7673.33, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=9388, regioncalls=49054, ndraw=128, logz=-7668.77, remainder_fraction=100.0000%, Lmin=-7628.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=9419, regioncalls=49822, ndraw=128, logz=-7017.74, remainder_fraction=100.0000%, Lmin=-6989.00, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=9448, regioncalls=50334, ndraw=128, logz=-6547.73, remainder_fraction=100.0000%, Lmin=-6517.63, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=997, ncalls=9452, regioncalls=50462, ndraw=128, logz=-6493.60, remainder_fraction=100.0000%, Lmin=-6475.15, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=9527, regioncalls=51742, ndraw=128, logz=-5491.72, remainder_fraction=100.0000%, Lmin=-5474.86, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=9541, regioncalls=52126, ndraw=128, logz=-5276.69, remainder_fraction=100.0000%, Lmin=-5247.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=9551, regioncalls=52382, ndraw=128, logz=-5002.67, remainder_fraction=100.0000%, Lmin=-4977.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=9589, regioncalls=53278, ndraw=128, logz=-4662.24, remainder_fraction=100.0000%, Lmin=-4631.19, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1139, ncalls=9614, regioncalls=53662, ndraw=128, logz=-4455.00, remainder_fraction=100.0000%, Lmin=-4442.88, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=9630, regioncalls=54174, ndraw=128, logz=-4252.66, remainder_fraction=100.0000%, Lmin=-4222.67, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=9667, regioncalls=55198, ndraw=128, logz=-3824.87, remainder_fraction=100.0000%, Lmin=-3815.29, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=9705, regioncalls=56478, ndraw=128, logz=-3493.08, remainder_fraction=100.0000%, Lmin=-3476.58, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=9714, regioncalls=56734, ndraw=128, logz=-3443.49, remainder_fraction=100.0000%, Lmin=-3429.82, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=9747, regioncalls=57758, ndraw=128, logz=-3058.70, remainder_fraction=100.0000%, Lmin=-3048.73, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=9785, regioncalls=59166, ndraw=128, logz=-2808.99, remainder_fraction=100.0000%, Lmin=-2784.85, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1281, ncalls=9785, regioncalls=59166, ndraw=128, logz=-2794.65, remainder_fraction=100.0000%, Lmin=-2783.83, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1312, ncalls=9816, regioncalls=60446, ndraw=128, logz=-2506.47, remainder_fraction=100.0000%, Lmin=-2479.05, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=9850, regioncalls=62110, ndraw=128, logz=-2237.57, remainder_fraction=100.0000%, Lmin=-2220.11, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1352, ncalls=9860, regioncalls=62750, ndraw=128, logz=-2146.63, remainder_fraction=100.0000%, Lmin=-2126.85, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=9995, regioncalls=63262, ndraw=128, logz=-2008.67, remainder_fraction=100.0000%, Lmin=-1994.21, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1423, ncalls=9995, regioncalls=63262, ndraw=128, logz=-1742.50, remainder_fraction=100.0000%, Lmin=-1725.08, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=9995, regioncalls=63262, ndraw=128, logz=-1655.08, remainder_fraction=100.0000%, Lmin=-1637.97, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1484.09, remainder_fraction=100.0000%, Lmin=-1470.82, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1400.33, remainder_fraction=100.0000%, Lmin=-1388.39, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1504, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1345.46, remainder_fraction=100.0000%, Lmin=-1329.96, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1202.13, remainder_fraction=100.0000%, Lmin=-1190.79, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1105.47, remainder_fraction=100.0000%, Lmin=-1094.12, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=10271, regioncalls=65694, ndraw=128, logz=-1002.65, remainder_fraction=100.0000%, Lmin=-991.38, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1632, ncalls=10271, regioncalls=65694, ndraw=128, logz=-912.72, remainder_fraction=100.0000%, Lmin=-897.72, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1671, ncalls=10271, regioncalls=65694, ndraw=128, logz=-807.73, remainder_fraction=100.0000%, Lmin=-795.37, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1696, ncalls=10399, regioncalls=65950, ndraw=128, logz=-749.54, remainder_fraction=100.0000%, Lmin=-730.32, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=10399, regioncalls=65950, ndraw=128, logz=-697.79, remainder_fraction=100.0000%, Lmin=-683.69, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1742, ncalls=10399, regioncalls=65950, ndraw=128, logz=-673.31, remainder_fraction=100.0000%, Lmin=-661.52, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=10399, regioncalls=65950, ndraw=128, logz=-627.00, remainder_fraction=100.0000%, Lmin=-609.67, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1792, ncalls=10399, regioncalls=65950, ndraw=128, logz=-581.50, remainder_fraction=100.0000%, Lmin=-564.18, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1813, ncalls=10527, regioncalls=66206, ndraw=128, logz=-540.40, remainder_fraction=100.0000%, Lmin=-527.04, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=10527, regioncalls=66206, ndraw=128, logz=-517.13, remainder_fraction=100.0000%, Lmin=-505.17, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1856, ncalls=10527, regioncalls=66206, ndraw=128, logz=-465.68, remainder_fraction=100.0000%, Lmin=-452.56, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1884, ncalls=10529, regioncalls=66334, ndraw=128, logz=-427.82, remainder_fraction=100.0000%, Lmin=-414.10, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=10532, regioncalls=66718, ndraw=128, logz=-414.81, remainder_fraction=100.0000%, Lmin=-401.25, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=10663, regioncalls=67614, ndraw=128, logz=-381.28, remainder_fraction=100.0000%, Lmin=-368.88, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1955, ncalls=10663, regioncalls=67614, ndraw=128, logz=-348.65, remainder_fraction=100.0000%, Lmin=-336.76, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1984, ncalls=10663, regioncalls=67614, ndraw=128, logz=-318.88, remainder_fraction=100.0000%, Lmin=-306.73, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=10791, regioncalls=67998, ndraw=128, logz=-288.88, remainder_fraction=100.0000%, Lmin=-277.25, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2026, ncalls=10791, regioncalls=67998, ndraw=128, logz=-277.58, remainder_fraction=100.0000%, Lmin=-264.93, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2048, ncalls=10791, regioncalls=67998, ndraw=128, logz=-261.11, remainder_fraction=100.0000%, Lmin=-248.44, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=10791, regioncalls=67998, ndraw=128, logz=-230.34, remainder_fraction=100.0000%, Lmin=-217.48, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2112, ncalls=10919, regioncalls=68510, ndraw=128, logz=-204.99, remainder_fraction=100.0000%, Lmin=-193.36, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2155, ncalls=10919, regioncalls=68510, ndraw=128, logz=-181.19, remainder_fraction=100.0000%, Lmin=-169.41, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2176, ncalls=10919, regioncalls=68510, ndraw=128, logz=-167.36, remainder_fraction=100.0000%, Lmin=-155.64, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2224, ncalls=11047, regioncalls=68766, ndraw=128, logz=-146.53, remainder_fraction=100.0000%, Lmin=-134.15, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=11047, regioncalls=68766, ndraw=128, logz=-142.00, remainder_fraction=100.0000%, Lmin=-129.80, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2270, ncalls=11047, regioncalls=68766, ndraw=128, logz=-127.80, remainder_fraction=100.0000%, Lmin=-115.79, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=11047, regioncalls=68766, ndraw=128, logz=-127.19, remainder_fraction=100.0000%, Lmin=-115.56, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2286, ncalls=11047, regioncalls=68766, ndraw=128, logz=-122.30, remainder_fraction=100.0000%, Lmin=-110.14, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2306, ncalls=11047, regioncalls=68766, ndraw=128, logz=-117.68, remainder_fraction=100.0000%, Lmin=-105.62, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2324, ncalls=11047, regioncalls=68766, ndraw=128, logz=-110.32, remainder_fraction=100.0000%, Lmin=-97.73, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2336, ncalls=11047, regioncalls=68766, ndraw=128, logz=-105.22, remainder_fraction=100.0000%, Lmin=-93.15, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2345, ncalls=11047, regioncalls=68766, ndraw=128, logz=-101.69, remainder_fraction=100.0000%, Lmin=-89.63, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2368, ncalls=11175, regioncalls=69022, ndraw=128, logz=-93.56, remainder_fraction=100.0000%, Lmin=-81.94, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=11175, regioncalls=69022, ndraw=128, logz=-84.98, remainder_fraction=100.0000%, Lmin=-72.89, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2416, ncalls=11175, regioncalls=69022, ndraw=128, logz=-81.78, remainder_fraction=100.0000%, Lmin=-70.23, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=11175, regioncalls=69022, ndraw=128, logz=-80.30, remainder_fraction=100.0000%, Lmin=-68.43, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2436, ncalls=11175, regioncalls=69022, ndraw=128, logz=-78.17, remainder_fraction=100.0000%, Lmin=-66.18, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2451, ncalls=11175, regioncalls=69022, ndraw=128, logz=-75.34, remainder_fraction=100.0000%, Lmin=-63.38, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2458, ncalls=11175, regioncalls=69022, ndraw=128, logz=-73.35, remainder_fraction=100.0000%, Lmin=-61.04, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=11175, regioncalls=69022, ndraw=128, logz=-72.13, remainder_fraction=100.0000%, Lmin=-60.41, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2498, ncalls=11303, regioncalls=69278, ndraw=128, logz=-66.69, remainder_fraction=100.0000%, Lmin=-54.78, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2515, ncalls=11303, regioncalls=69278, ndraw=128, logz=-62.46, remainder_fraction=100.0000%, Lmin=-50.15, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2525, ncalls=11303, regioncalls=69278, ndraw=128, logz=-60.51, remainder_fraction=100.0000%, Lmin=-48.80, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2528, ncalls=11303, regioncalls=69278, ndraw=128, logz=-60.12, remainder_fraction=100.0000%, Lmin=-48.34, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2553, ncalls=11303, regioncalls=69278, ndraw=128, logz=-56.54, remainder_fraction=100.0000%, Lmin=-44.54, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2609, ncalls=11303, regioncalls=69278, ndraw=128, logz=-47.08, remainder_fraction=100.0000%, Lmin=-35.03, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2626, ncalls=11303, regioncalls=69278, ndraw=128, logz=-45.29, remainder_fraction=100.0000%, Lmin=-33.25, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2643, ncalls=11303, regioncalls=69278, ndraw=128, logz=-43.23, remainder_fraction=100.0000%, Lmin=-30.78, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2655, ncalls=11303, regioncalls=69278, ndraw=128, logz=-41.63, remainder_fraction=100.0000%, Lmin=-29.57, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2656, ncalls=11303, regioncalls=69278, ndraw=128, logz=-41.51, remainder_fraction=100.0000%, Lmin=-29.50, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=11431, regioncalls=69662, ndraw=128, logz=-38.38, remainder_fraction=100.0000%, Lmin=-26.58, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2704, ncalls=11431, regioncalls=69662, ndraw=128, logz=-37.05, remainder_fraction=100.0000%, Lmin=-25.20, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2725, ncalls=11431, regioncalls=69662, ndraw=128, logz=-35.33, remainder_fraction=100.0000%, Lmin=-23.47, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2734, ncalls=11431, regioncalls=69662, ndraw=128, logz=-34.44, remainder_fraction=100.0000%, Lmin=-22.42, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2749, ncalls=11431, regioncalls=69662, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-21.69, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2752, ncalls=11431, regioncalls=69662, ndraw=128, logz=-33.16, remainder_fraction=100.0000%, Lmin=-21.59, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2776, ncalls=11431, regioncalls=69662, ndraw=128, logz=-31.77, remainder_fraction=100.0000%, Lmin=-20.13, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=11431, regioncalls=69662, ndraw=128, logz=-31.32, remainder_fraction=100.0000%, Lmin=-19.57, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2814, ncalls=11431, regioncalls=69662, ndraw=128, logz=-29.62, remainder_fraction=100.0000%, Lmin=-17.93, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=11431, regioncalls=69662, ndraw=128, logz=-29.52, remainder_fraction=100.0000%, Lmin=-17.84, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2919, ncalls=11431, regioncalls=69662, ndraw=128, logz=-25.44, remainder_fraction=99.9999%, Lmin=-13.64, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2935, ncalls=11431, regioncalls=69662, ndraw=128, logz=-24.86, remainder_fraction=99.9998%, Lmin=-13.20, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3143, ncalls=11431, regioncalls=69662, ndraw=128, logz=-18.76, remainder_fraction=99.9040%, Lmin=-6.95, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3217, ncalls=11431, regioncalls=69662, ndraw=128, logz=-17.43, remainder_fraction=99.6278%, Lmin=-5.92, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=11559, regioncalls=70046, ndraw=128, logz=-17.23, remainder_fraction=99.5565%, Lmin=-5.61, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3292, ncalls=11559, regioncalls=70046, ndraw=128, logz=-16.35, remainder_fraction=98.9485%, Lmin=-4.48, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3363, ncalls=11559, regioncalls=70046, ndraw=128, logz=-15.37, remainder_fraction=97.2338%, Lmin=-3.48, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=11559, regioncalls=70046, ndraw=128, logz=-15.05, remainder_fraction=96.0776%, Lmin=-3.14, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3453, ncalls=11559, regioncalls=70046, ndraw=128, logz=-14.46, remainder_fraction=92.9309%, Lmin=-2.61, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3488, ncalls=11559, regioncalls=70046, ndraw=128, logz=-14.18, remainder_fraction=90.7736%, Lmin=-2.31, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=11559, regioncalls=70046, ndraw=128, logz=-13.95, remainder_fraction=88.1955%, Lmin=-2.11, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3525, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.91, remainder_fraction=87.7358%, Lmin=-2.10, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.75, remainder_fraction=85.5337%, Lmin=-2.00, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3584, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.58, remainder_fraction=82.7298%, Lmin=-1.81, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.50, remainder_fraction=81.4265%, Lmin=-1.76, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3672, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.18, remainder_fraction=74.2901%, Lmin=-1.42, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3745, ncalls=11687, regioncalls=70430, ndraw=128, logz=-12.92, remainder_fraction=66.0021%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3825, ncalls=11687, regioncalls=70430, ndraw=128, logz=-12.67, remainder_fraction=56.9671%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.63, remainder_fraction=55.2492%, Lmin=-0.75, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3872, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.56, remainder_fraction=51.5108%, Lmin=-0.68, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3898, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.50, remainder_fraction=48.5045%, Lmin=-0.62, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3971, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.36, remainder_fraction=40.7717%, Lmin=-0.49, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.27, remainder_fraction=35.0644%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=4047, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.25, remainder_fraction=33.6862%, Lmin=-0.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=4119, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.16, remainder_fraction=27.8867%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4190, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.09, remainder_fraction=22.9791%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4224, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.07, remainder_fraction=20.9237%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4271, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.03, remainder_fraction=18.2849%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4351, ncalls=11943, regioncalls=71070, ndraw=128, logz=-11.99, remainder_fraction=14.5101%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4437, ncalls=11943, regioncalls=71070, ndraw=128, logz=-11.95, remainder_fraction=11.2584%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.93, remainder_fraction=9.0028%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4585, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.91, remainder_fraction=7.2134%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4659, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.89, remainder_fraction=5.7531%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4732, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.88, remainder_fraction=4.5945%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4814, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.87, remainder_fraction=3.5639%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4864, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.86, remainder_fraction=3.0504%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4886, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.86, remainder_fraction=2.8487%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4965, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=2.2266%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5041, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.7558%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5088, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.5156%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5118, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.3796%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5193, ncalls=12327, regioncalls=72094, ndraw=128, logz=-11.84, remainder_fraction=1.0903%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 12327 INFO ultranest:integrator.py:2697 logZ = -11.91 +- 0.1636 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1275.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.33 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 781 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (4156/4672 iterations) have 315 DEBUG ultranest:integrator.py:1663 at least 684 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 684 minimum live points (dlogz from 0.14 to 0.39, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.20 bs:0.16 tail:0.00 total:0.16 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 684 live points (have 317 already) ... INFO ultranest:integrator.py:1433 Sampling 367 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 684.0), (inf, 684.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=12822, regioncalls=72222, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-245997.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=12822, regioncalls=72222, ndraw=128, logz=-187609.44, remainder_fraction=100.0000%, Lmin=-186405.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=12822, regioncalls=72222, ndraw=128, logz=-161455.27, remainder_fraction=100.0000%, Lmin=-161381.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=153, ncalls=12822, regioncalls=72222, ndraw=128, logz=-126861.12, remainder_fraction=100.0000%, Lmin=-126691.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=12822, regioncalls=72222, ndraw=128, logz=-124993.76, remainder_fraction=100.0000%, Lmin=-124623.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=12822, regioncalls=72222, ndraw=128, logz=-117214.00, remainder_fraction=100.0000%, Lmin=-116938.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=306, ncalls=12936, regioncalls=72350, ndraw=128, logz=-97355.70, remainder_fraction=100.0000%, Lmin=-97219.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=12936, regioncalls=72350, ndraw=128, logz=-95807.34, remainder_fraction=100.0000%, Lmin=-95734.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=12936, regioncalls=72350, ndraw=128, logz=-91971.18, remainder_fraction=100.0000%, Lmin=-91886.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=13021, regioncalls=72478, ndraw=128, logz=-82305.88, remainder_fraction=100.0000%, Lmin=-82247.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=459, ncalls=13021, regioncalls=72478, ndraw=128, logz=-81427.25, remainder_fraction=100.0000%, Lmin=-81363.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=613, ncalls=13109, regioncalls=72606, ndraw=128, logz=-64179.31, remainder_fraction=100.0000%, Lmin=-64076.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=13167, regioncalls=72734, ndraw=128, logz=-62083.49, remainder_fraction=100.0000%, Lmin=-62055.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=13167, regioncalls=72734, ndraw=128, logz=-55598.35, remainder_fraction=100.0000%, Lmin=-55501.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=736, ncalls=13227, regioncalls=72862, ndraw=128, logz=-53118.40, remainder_fraction=100.0000%, Lmin=-53083.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=766, ncalls=13227, regioncalls=72862, ndraw=128, logz=-51060.51, remainder_fraction=100.0000%, Lmin=-50944.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=13227, regioncalls=72862, ndraw=128, logz=-50898.46, remainder_fraction=100.0000%, Lmin=-50831.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=13279, regioncalls=72990, ndraw=128, logz=-46496.86, remainder_fraction=100.0000%, Lmin=-46183.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=13362, regioncalls=73246, ndraw=128, logz=-40286.55, remainder_fraction=100.0000%, Lmin=-40211.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=13362, regioncalls=73246, ndraw=128, logz=-39698.95, remainder_fraction=100.0000%, Lmin=-39683.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=13401, regioncalls=73374, ndraw=128, logz=-36752.96, remainder_fraction=100.0000%, Lmin=-36476.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=13440, regioncalls=73502, ndraw=128, logz=-32856.27, remainder_fraction=100.0000%, Lmin=-32828.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1073, ncalls=13481, regioncalls=73630, ndraw=128, logz=-32044.04, remainder_fraction=100.0000%, Lmin=-32010.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=13481, regioncalls=73630, ndraw=128, logz=-31324.08, remainder_fraction=100.0000%, Lmin=-31219.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=13510, regioncalls=73758, ndraw=128, logz=-28767.77, remainder_fraction=100.0000%, Lmin=-28745.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=13538, regioncalls=73886, ndraw=128, logz=-27662.85, remainder_fraction=100.0000%, Lmin=-27410.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=13571, regioncalls=74014, ndraw=128, logz=-26376.74, remainder_fraction=100.0000%, Lmin=-26340.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1226, ncalls=13571, regioncalls=74014, ndraw=128, logz=-25891.91, remainder_fraction=100.0000%, Lmin=-25883.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=13599, regioncalls=74142, ndraw=128, logz=-23501.00, remainder_fraction=100.0000%, Lmin=-23478.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=13676, regioncalls=74526, ndraw=128, logz=-20787.70, remainder_fraction=100.0000%, Lmin=-20770.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1379, ncalls=13676, regioncalls=74526, ndraw=128, logz=-20721.92, remainder_fraction=100.0000%, Lmin=-20701.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=13748, regioncalls=75038, ndraw=128, logz=-17968.42, remainder_fraction=100.0000%, Lmin=-17940.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1504, ncalls=13774, regioncalls=75166, ndraw=128, logz=-17203.78, remainder_fraction=100.0000%, Lmin=-17165.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1532, ncalls=13787, regioncalls=75294, ndraw=128, logz=-16506.90, remainder_fraction=100.0000%, Lmin=-16495.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=13801, regioncalls=75422, ndraw=128, logz=-16431.14, remainder_fraction=100.0000%, Lmin=-16396.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=13824, regioncalls=75678, ndraw=128, logz=-15454.63, remainder_fraction=100.0000%, Lmin=-15437.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=13839, regioncalls=75806, ndraw=128, logz=-14760.11, remainder_fraction=100.0000%, Lmin=-14716.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1664, ncalls=13896, regioncalls=76318, ndraw=128, logz=-13227.51, remainder_fraction=100.0000%, Lmin=-13205.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1685, ncalls=13913, regioncalls=76446, ndraw=128, logz=-12861.14, remainder_fraction=100.0000%, Lmin=-12832.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1696, ncalls=13921, regioncalls=76574, ndraw=128, logz=-12709.17, remainder_fraction=100.0000%, Lmin=-12690.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=13946, regioncalls=76830, ndraw=128, logz=-12143.44, remainder_fraction=100.0000%, Lmin=-12109.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1792, ncalls=13986, regioncalls=77214, ndraw=128, logz=-11044.06, remainder_fraction=100.0000%, Lmin=-11032.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1838, ncalls=14017, regioncalls=77598, ndraw=128, logz=-10425.17, remainder_fraction=100.0000%, Lmin=-10391.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=14056, regioncalls=78110, ndraw=128, logz=-9665.21, remainder_fraction=100.0000%, Lmin=-9652.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=14074, regioncalls=78366, ndraw=128, logz=-9171.28, remainder_fraction=100.0000%, Lmin=-9130.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1984, ncalls=14128, regioncalls=79006, ndraw=128, logz=-8182.76, remainder_fraction=100.0000%, Lmin=-8144.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1991, ncalls=14128, regioncalls=79006, ndraw=128, logz=-8087.38, remainder_fraction=100.0000%, Lmin=-8076.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=14143, regioncalls=79262, ndraw=128, logz=-7663.77, remainder_fraction=100.0000%, Lmin=-7631.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=14182, regioncalls=79902, ndraw=128, logz=-7040.15, remainder_fraction=100.0000%, Lmin=-7029.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2112, ncalls=14197, regioncalls=80158, ndraw=128, logz=-6723.57, remainder_fraction=100.0000%, Lmin=-6709.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2145, ncalls=14227, regioncalls=80670, ndraw=128, logz=-6516.93, remainder_fraction=100.0000%, Lmin=-6501.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=14299, regioncalls=82206, ndraw=128, logz=-5352.92, remainder_fraction=100.0000%, Lmin=-5336.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2298, ncalls=14310, regioncalls=82334, ndraw=128, logz=-5178.13, remainder_fraction=100.0000%, Lmin=-5164.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2436, ncalls=14398, regioncalls=84510, ndraw=128, logz=-4253.36, remainder_fraction=100.0000%, Lmin=-4241.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2451, ncalls=14407, regioncalls=84766, ndraw=128, logz=-4182.70, remainder_fraction=100.0000%, Lmin=-4170.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=14416, regioncalls=85022, ndraw=128, logz=-4081.69, remainder_fraction=100.0000%, Lmin=-4069.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2528, ncalls=14459, regioncalls=86174, ndraw=128, logz=-3733.52, remainder_fraction=100.0000%, Lmin=-3721.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=14483, regioncalls=87198, ndraw=128, logz=-3555.56, remainder_fraction=100.0000%, Lmin=-3543.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2592, ncalls=14504, regioncalls=88094, ndraw=128, logz=-3408.79, remainder_fraction=100.0000%, Lmin=-3397.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2605, ncalls=14516, regioncalls=88350, ndraw=128, logz=-3362.34, remainder_fraction=100.0000%, Lmin=-3351.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2624, ncalls=14527, regioncalls=88990, ndraw=128, logz=-3255.79, remainder_fraction=100.0000%, Lmin=-3242.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2656, ncalls=14546, regioncalls=89630, ndraw=128, logz=-3054.50, remainder_fraction=100.0000%, Lmin=-3036.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=14577, regioncalls=91166, ndraw=128, logz=-2945.71, remainder_fraction=100.0000%, Lmin=-2931.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2758, ncalls=14631, regioncalls=93086, ndraw=128, logz=-2673.88, remainder_fraction=100.0000%, Lmin=-2660.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=14652, regioncalls=94110, ndraw=128, logz=-2578.97, remainder_fraction=100.0000%, Lmin=-2561.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=14675, regioncalls=95134, ndraw=128, logz=-2462.28, remainder_fraction=100.0000%, Lmin=-2444.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2912, ncalls=14851, regioncalls=97950, ndraw=128, logz=-2117.65, remainder_fraction=100.0000%, Lmin=-2106.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=14851, regioncalls=97950, ndraw=128, logz=-2035.83, remainder_fraction=100.0000%, Lmin=-2022.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2976, ncalls=14851, regioncalls=97950, ndraw=128, logz=-1984.77, remainder_fraction=100.0000%, Lmin=-1972.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=14851, regioncalls=97950, ndraw=128, logz=-1878.87, remainder_fraction=100.0000%, Lmin=-1863.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=14863, regioncalls=98590, ndraw=128, logz=-1806.25, remainder_fraction=100.0000%, Lmin=-1792.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3065, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1743.26, remainder_fraction=100.0000%, Lmin=-1730.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3072, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1718.37, remainder_fraction=100.0000%, Lmin=-1702.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1484.81, remainder_fraction=100.0000%, Lmin=-1471.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3218, ncalls=15000, regioncalls=99486, ndraw=128, logz=-1399.21, remainder_fraction=100.0000%, Lmin=-1381.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1369.52, remainder_fraction=100.0000%, Lmin=-1356.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3296, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1269.28, remainder_fraction=100.0000%, Lmin=-1257.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1218.67, remainder_fraction=100.0000%, Lmin=-1207.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3328, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1211.04, remainder_fraction=100.0000%, Lmin=-1198.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1108.00, remainder_fraction=100.0000%, Lmin=-1095.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3424, ncalls=15277, regioncalls=102174, ndraw=128, logz=-1053.34, remainder_fraction=100.0000%, Lmin=-1039.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3453, ncalls=15277, regioncalls=102174, ndraw=128, logz=-1009.67, remainder_fraction=100.0000%, Lmin=-997.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=15277, regioncalls=102174, ndraw=128, logz=-910.78, remainder_fraction=100.0000%, Lmin=-899.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=15277, regioncalls=102174, ndraw=128, logz=-868.72, remainder_fraction=100.0000%, Lmin=-855.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3584, ncalls=15405, regioncalls=102558, ndraw=128, logz=-830.22, remainder_fraction=100.0000%, Lmin=-818.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3608, ncalls=15405, regioncalls=102558, ndraw=128, logz=-795.53, remainder_fraction=100.0000%, Lmin=-784.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3648, ncalls=15405, regioncalls=102558, ndraw=128, logz=-756.39, remainder_fraction=100.0000%, Lmin=-744.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=15405, regioncalls=102558, ndraw=128, logz=-725.68, remainder_fraction=100.0000%, Lmin=-713.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3712, ncalls=15405, regioncalls=102558, ndraw=128, logz=-701.43, remainder_fraction=100.0000%, Lmin=-689.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3744, ncalls=15535, regioncalls=103070, ndraw=128, logz=-673.57, remainder_fraction=100.0000%, Lmin=-662.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3761, ncalls=15535, regioncalls=103070, ndraw=128, logz=-655.76, remainder_fraction=100.0000%, Lmin=-643.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3808, ncalls=15535, regioncalls=103070, ndraw=128, logz=-614.33, remainder_fraction=100.0000%, Lmin=-602.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=15535, regioncalls=103070, ndraw=128, logz=-592.72, remainder_fraction=100.0000%, Lmin=-582.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3915, ncalls=15666, regioncalls=103966, ndraw=128, logz=-531.69, remainder_fraction=100.0000%, Lmin=-519.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4054, ncalls=15794, regioncalls=104222, ndraw=128, logz=-430.06, remainder_fraction=100.0000%, Lmin=-418.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4064, ncalls=15794, regioncalls=104222, ndraw=128, logz=-425.59, remainder_fraction=100.0000%, Lmin=-413.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4069, ncalls=15794, regioncalls=104222, ndraw=128, logz=-421.91, remainder_fraction=100.0000%, Lmin=-409.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4128, ncalls=15794, regioncalls=104222, ndraw=128, logz=-389.61, remainder_fraction=100.0000%, Lmin=-376.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=15794, regioncalls=104222, ndraw=128, logz=-372.86, remainder_fraction=100.0000%, Lmin=-361.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4226, ncalls=15922, regioncalls=104478, ndraw=128, logz=-337.78, remainder_fraction=100.0000%, Lmin=-324.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=15922, regioncalls=104478, ndraw=128, logz=-296.12, remainder_fraction=100.0000%, Lmin=-284.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4352, ncalls=16050, regioncalls=104734, ndraw=128, logz=-279.88, remainder_fraction=100.0000%, Lmin=-267.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4379, ncalls=16050, regioncalls=104734, ndraw=128, logz=-268.89, remainder_fraction=100.0000%, Lmin=-257.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4384, ncalls=16050, regioncalls=104734, ndraw=128, logz=-267.00, remainder_fraction=100.0000%, Lmin=-254.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4416, ncalls=16050, regioncalls=104734, ndraw=128, logz=-255.39, remainder_fraction=100.0000%, Lmin=-242.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4448, ncalls=16050, regioncalls=104734, ndraw=128, logz=-243.89, remainder_fraction=100.0000%, Lmin=-232.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4473, ncalls=16050, regioncalls=104734, ndraw=128, logz=-233.10, remainder_fraction=100.0000%, Lmin=-221.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=16050, regioncalls=104734, ndraw=128, logz=-230.08, remainder_fraction=100.0000%, Lmin=-217.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=16178, regioncalls=105118, ndraw=128, logz=-218.91, remainder_fraction=100.0000%, Lmin=-207.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4544, ncalls=16178, regioncalls=105118, ndraw=128, logz=-209.11, remainder_fraction=100.0000%, Lmin=-196.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4626, ncalls=16178, regioncalls=105118, ndraw=128, logz=-186.28, remainder_fraction=100.0000%, Lmin=-174.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4643, ncalls=16178, regioncalls=105118, ndraw=128, logz=-181.94, remainder_fraction=100.0000%, Lmin=-170.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4672, ncalls=16306, regioncalls=105374, ndraw=128, logz=-175.41, remainder_fraction=100.0000%, Lmin=-163.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4804, ncalls=16306, regioncalls=105374, ndraw=128, logz=-148.00, remainder_fraction=100.0000%, Lmin=-135.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4832, ncalls=16306, regioncalls=105374, ndraw=128, logz=-143.04, remainder_fraction=100.0000%, Lmin=-131.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4896, ncalls=16434, regioncalls=105630, ndraw=128, logz=-130.59, remainder_fraction=100.0000%, Lmin=-118.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4907, ncalls=16434, regioncalls=105630, ndraw=128, logz=-128.26, remainder_fraction=100.0000%, Lmin=-115.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4928, ncalls=16434, regioncalls=105630, ndraw=128, logz=-124.41, remainder_fraction=100.0000%, Lmin=-112.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4934, ncalls=16434, regioncalls=105630, ndraw=128, logz=-123.43, remainder_fraction=100.0000%, Lmin=-111.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4965, ncalls=16434, regioncalls=105630, ndraw=128, logz=-118.86, remainder_fraction=100.0000%, Lmin=-107.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4969, ncalls=16434, regioncalls=105630, ndraw=128, logz=-118.47, remainder_fraction=100.0000%, Lmin=-106.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4992, ncalls=16434, regioncalls=105630, ndraw=128, logz=-115.01, remainder_fraction=100.0000%, Lmin=-103.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5006, ncalls=16562, regioncalls=105886, ndraw=128, logz=-111.80, remainder_fraction=100.0000%, Lmin=-99.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5009, ncalls=16562, regioncalls=105886, ndraw=128, logz=-111.38, remainder_fraction=100.0000%, Lmin=-99.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5048, ncalls=16562, regioncalls=105886, ndraw=128, logz=-105.52, remainder_fraction=100.0000%, Lmin=-93.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5070, ncalls=16562, regioncalls=105886, ndraw=128, logz=-102.79, remainder_fraction=100.0000%, Lmin=-90.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5088, ncalls=16562, regioncalls=105886, ndraw=128, logz=-99.80, remainder_fraction=100.0000%, Lmin=-87.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5152, ncalls=16562, regioncalls=105886, ndraw=128, logz=-90.35, remainder_fraction=100.0000%, Lmin=-78.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5184, ncalls=16691, regioncalls=106398, ndraw=128, logz=-86.58, remainder_fraction=100.0000%, Lmin=-74.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5216, ncalls=16691, regioncalls=106398, ndraw=128, logz=-83.51, remainder_fraction=100.0000%, Lmin=-71.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5225, ncalls=16691, regioncalls=106398, ndraw=128, logz=-82.71, remainder_fraction=100.0000%, Lmin=-70.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5242, ncalls=16691, regioncalls=106398, ndraw=128, logz=-81.06, remainder_fraction=100.0000%, Lmin=-68.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5248, ncalls=16691, regioncalls=106398, ndraw=128, logz=-80.41, remainder_fraction=100.0000%, Lmin=-68.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5268, ncalls=16691, regioncalls=106398, ndraw=128, logz=-78.58, remainder_fraction=100.0000%, Lmin=-66.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=16691, regioncalls=106398, ndraw=128, logz=-77.28, remainder_fraction=100.0000%, Lmin=-65.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5299, ncalls=16691, regioncalls=106398, ndraw=128, logz=-75.68, remainder_fraction=100.0000%, Lmin=-63.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5312, ncalls=16691, regioncalls=106398, ndraw=128, logz=-74.69, remainder_fraction=100.0000%, Lmin=-62.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5317, ncalls=16691, regioncalls=106398, ndraw=128, logz=-74.16, remainder_fraction=100.0000%, Lmin=-62.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5376, ncalls=16819, regioncalls=106654, ndraw=128, logz=-69.46, remainder_fraction=100.0000%, Lmin=-57.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5409, ncalls=16819, regioncalls=106654, ndraw=128, logz=-67.06, remainder_fraction=100.0000%, Lmin=-55.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5454, ncalls=16819, regioncalls=106654, ndraw=128, logz=-62.82, remainder_fraction=100.0000%, Lmin=-50.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5472, ncalls=16819, regioncalls=106654, ndraw=128, logz=-61.53, remainder_fraction=100.0000%, Lmin=-49.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=16819, regioncalls=106654, ndraw=128, logz=-60.92, remainder_fraction=100.0000%, Lmin=-48.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5510, ncalls=16947, regioncalls=106910, ndraw=128, logz=-58.82, remainder_fraction=100.0000%, Lmin=-46.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5518, ncalls=16947, regioncalls=106910, ndraw=128, logz=-58.19, remainder_fraction=100.0000%, Lmin=-46.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5527, ncalls=16947, regioncalls=106910, ndraw=128, logz=-57.54, remainder_fraction=100.0000%, Lmin=-45.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5568, ncalls=16947, regioncalls=106910, ndraw=128, logz=-54.79, remainder_fraction=100.0000%, Lmin=-42.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5617, ncalls=16947, regioncalls=106910, ndraw=128, logz=-51.43, remainder_fraction=100.0000%, Lmin=-39.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5634, ncalls=16947, regioncalls=106910, ndraw=128, logz=-50.19, remainder_fraction=100.0000%, Lmin=-38.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5641, ncalls=16947, regioncalls=106910, ndraw=128, logz=-49.58, remainder_fraction=100.0000%, Lmin=-37.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5650, ncalls=16947, regioncalls=106910, ndraw=128, logz=-48.93, remainder_fraction=100.0000%, Lmin=-36.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5664, ncalls=17075, regioncalls=107422, ndraw=128, logz=-47.94, remainder_fraction=100.0000%, Lmin=-35.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5696, ncalls=17075, regioncalls=107422, ndraw=128, logz=-46.29, remainder_fraction=100.0000%, Lmin=-34.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5713, ncalls=17075, regioncalls=107422, ndraw=128, logz=-45.59, remainder_fraction=100.0000%, Lmin=-33.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5728, ncalls=17075, regioncalls=107422, ndraw=128, logz=-44.83, remainder_fraction=100.0000%, Lmin=-32.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5754, ncalls=17075, regioncalls=107422, ndraw=128, logz=-43.65, remainder_fraction=100.0000%, Lmin=-31.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=17075, regioncalls=107422, ndraw=128, logz=-43.32, remainder_fraction=100.0000%, Lmin=-31.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5779, ncalls=17075, regioncalls=107422, ndraw=128, logz=-42.25, remainder_fraction=100.0000%, Lmin=-30.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5826, ncalls=17075, regioncalls=107422, ndraw=128, logz=-39.81, remainder_fraction=100.0000%, Lmin=-27.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5836, ncalls=17075, regioncalls=107422, ndraw=128, logz=-39.29, remainder_fraction=100.0000%, Lmin=-27.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5843, ncalls=17204, regioncalls=108062, ndraw=128, logz=-38.92, remainder_fraction=100.0000%, Lmin=-26.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5856, ncalls=17204, regioncalls=108062, ndraw=128, logz=-38.33, remainder_fraction=100.0000%, Lmin=-26.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5864, ncalls=17204, regioncalls=108062, ndraw=128, logz=-37.97, remainder_fraction=100.0000%, Lmin=-25.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5875, ncalls=17204, regioncalls=108062, ndraw=128, logz=-37.44, remainder_fraction=100.0000%, Lmin=-25.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5891, ncalls=17204, regioncalls=108062, ndraw=128, logz=-36.70, remainder_fraction=100.0000%, Lmin=-24.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5898, ncalls=17204, regioncalls=108062, ndraw=128, logz=-36.41, remainder_fraction=100.0000%, Lmin=-24.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5917, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.71, remainder_fraction=100.0000%, Lmin=-23.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.60, remainder_fraction=100.0000%, Lmin=-23.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5933, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.14, remainder_fraction=100.0000%, Lmin=-23.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5982, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.45, remainder_fraction=100.0000%, Lmin=-21.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5984, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.39, remainder_fraction=100.0000%, Lmin=-21.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5997, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.03, remainder_fraction=100.0000%, Lmin=-21.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6016, ncalls=17204, regioncalls=108062, ndraw=128, logz=-32.44, remainder_fraction=100.0000%, Lmin=-20.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=17332, regioncalls=108318, ndraw=128, logz=-31.44, remainder_fraction=100.0000%, Lmin=-19.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=17332, regioncalls=108318, ndraw=128, logz=-30.50, remainder_fraction=100.0000%, Lmin=-18.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6106, ncalls=17332, regioncalls=108318, ndraw=128, logz=-29.81, remainder_fraction=100.0000%, Lmin=-18.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6156, ncalls=17332, regioncalls=108318, ndraw=128, logz=-28.62, remainder_fraction=100.0000%, Lmin=-16.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6180, ncalls=17332, regioncalls=108318, ndraw=128, logz=-28.08, remainder_fraction=100.0000%, Lmin=-16.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6189, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.87, remainder_fraction=100.0000%, Lmin=-16.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6198, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.66, remainder_fraction=100.0000%, Lmin=-15.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6207, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.47, remainder_fraction=100.0000%, Lmin=-15.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6208, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.45, remainder_fraction=100.0000%, Lmin=-15.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6247, ncalls=17332, regioncalls=108318, ndraw=128, logz=-26.55, remainder_fraction=100.0000%, Lmin=-14.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6261, ncalls=17332, regioncalls=108318, ndraw=128, logz=-26.26, remainder_fraction=99.9999%, Lmin=-14.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6317, ncalls=17460, regioncalls=108574, ndraw=128, logz=-25.16, remainder_fraction=99.9998%, Lmin=-13.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6336, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.84, remainder_fraction=99.9998%, Lmin=-13.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6364, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.35, remainder_fraction=99.9996%, Lmin=-12.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6382, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.02, remainder_fraction=99.9995%, Lmin=-12.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6404, ncalls=17460, regioncalls=108574, ndraw=128, logz=-23.63, remainder_fraction=99.9992%, Lmin=-11.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6465, ncalls=17460, regioncalls=108574, ndraw=128, logz=-22.64, remainder_fraction=99.9979%, Lmin=-10.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6473, ncalls=17460, regioncalls=108574, ndraw=128, logz=-22.52, remainder_fraction=99.9976%, Lmin=-10.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6489, ncalls=17588, regioncalls=109086, ndraw=128, logz=-22.28, remainder_fraction=99.9970%, Lmin=-10.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6496, ncalls=17588, regioncalls=109086, ndraw=128, logz=-22.18, remainder_fraction=99.9967%, Lmin=-10.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6508, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.99, remainder_fraction=99.9960%, Lmin=-10.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6518, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.85, remainder_fraction=99.9953%, Lmin=-10.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.23, remainder_fraction=99.9912%, Lmin=-9.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6579, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.97, remainder_fraction=99.9888%, Lmin=-9.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6592, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.79, remainder_fraction=99.9866%, Lmin=-8.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.35, remainder_fraction=99.9792%, Lmin=-8.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6688, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.57, remainder_fraction=99.9553%, Lmin=-7.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.19, remainder_fraction=99.9329%, Lmin=-7.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6732, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.06, remainder_fraction=99.9228%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6752, ncalls=17716, regioncalls=109342, ndraw=128, logz=-18.86, remainder_fraction=99.9055%, Lmin=-7.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=17844, regioncalls=109598, ndraw=128, logz=-18.55, remainder_fraction=99.8702%, Lmin=-6.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6848, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.98, remainder_fraction=99.7729%, Lmin=-6.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6885, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.70, remainder_fraction=99.6976%, Lmin=-6.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6912, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.51, remainder_fraction=99.6343%, Lmin=-5.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6976, ncalls=17972, regioncalls=109854, ndraw=128, logz=-17.08, remainder_fraction=99.4375%, Lmin=-5.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7008, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.86, remainder_fraction=99.2979%, Lmin=-5.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7038, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.66, remainder_fraction=99.1449%, Lmin=-4.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.65, remainder_fraction=99.1322%, Lmin=-4.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7104, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.23, remainder_fraction=98.7000%, Lmin=-4.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7136, ncalls=18100, regioncalls=110110, ndraw=128, logz=-16.03, remainder_fraction=98.4281%, Lmin=-4.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7168, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.83, remainder_fraction=98.1164%, Lmin=-3.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7193, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.68, remainder_fraction=97.8153%, Lmin=-3.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.64, remainder_fraction=97.7212%, Lmin=-3.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7232, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.46, remainder_fraction=97.2928%, Lmin=-3.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7296, ncalls=18228, regioncalls=110366, ndraw=128, logz=-15.13, remainder_fraction=96.2357%, Lmin=-3.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7346, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.89, remainder_fraction=95.1607%, Lmin=-3.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7392, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.69, remainder_fraction=94.1522%, Lmin=-2.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7424, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.55, remainder_fraction=93.3329%, Lmin=-2.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7456, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.43, remainder_fraction=92.4218%, Lmin=-2.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.30, remainder_fraction=91.5439%, Lmin=-2.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7499, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.26, remainder_fraction=91.2163%, Lmin=-2.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.19, remainder_fraction=90.4641%, Lmin=-2.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7616, ncalls=18356, regioncalls=110878, ndraw=128, logz=-13.87, remainder_fraction=86.8875%, Lmin=-2.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7648, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.78, remainder_fraction=85.6003%, Lmin=-1.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7655, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.76, remainder_fraction=85.3763%, Lmin=-1.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7782, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.44, remainder_fraction=79.8800%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7809, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.38, remainder_fraction=78.6786%, Lmin=-1.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7904, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.19, remainder_fraction=73.6927%, Lmin=-1.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7936, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.13, remainder_fraction=72.0994%, Lmin=-1.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7963, ncalls=18740, regioncalls=111646, ndraw=128, logz=-13.08, remainder_fraction=70.6569%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8000, ncalls=18740, regioncalls=111646, ndraw=128, logz=-13.01, remainder_fraction=68.6910%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8032, ncalls=18740, regioncalls=111646, ndraw=128, logz=-12.96, remainder_fraction=66.9543%, Lmin=-1.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8118, ncalls=18868, regioncalls=112030, ndraw=128, logz=-12.83, remainder_fraction=62.3127%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8128, ncalls=18868, regioncalls=112030, ndraw=128, logz=-12.82, remainder_fraction=61.8006%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8224, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.69, remainder_fraction=56.9226%, Lmin=-0.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8256, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.65, remainder_fraction=55.1686%, Lmin=-0.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8271, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.63, remainder_fraction=54.4333%, Lmin=-0.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8320, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.58, remainder_fraction=51.9435%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8384, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.52, remainder_fraction=48.6747%, Lmin=-0.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8416, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.49, remainder_fraction=47.1015%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8425, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.48, remainder_fraction=46.6891%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8480, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.43, remainder_fraction=44.0215%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8544, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.38, remainder_fraction=41.0352%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8576, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.35, remainder_fraction=39.5759%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8578, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.35, remainder_fraction=39.4897%, Lmin=-0.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8608, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.33, remainder_fraction=38.2056%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8640, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.31, remainder_fraction=36.8536%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8734, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.25, remainder_fraction=33.0614%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8736, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.25, remainder_fraction=32.9849%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8768, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.23, remainder_fraction=31.7334%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8887, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.17, remainder_fraction=27.4835%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8928, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.15, remainder_fraction=26.1010%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8960, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.14, remainder_fraction=25.0771%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9024, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.11, remainder_fraction=23.1124%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9042, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.10, remainder_fraction=22.5832%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9056, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.10, remainder_fraction=22.1827%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9088, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.09, remainder_fraction=21.2880%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9152, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.07, remainder_fraction=19.5886%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9184, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.06, remainder_fraction=18.7827%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9195, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.05, remainder_fraction=18.5036%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9280, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.03, remainder_fraction=16.5262%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9344, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.01, remainder_fraction=15.1651%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9349, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.01, remainder_fraction=15.0616%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9408, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.00, remainder_fraction=13.8965%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9472, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.7397%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9503, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.2075%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9504, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.1910%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9536, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.97, remainder_fraction=11.6663%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9568, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.97, remainder_fraction=11.1622%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9600, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.96, remainder_fraction=10.6812%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9656, ncalls=20148, regioncalls=116638, ndraw=128, logz=-11.95, remainder_fraction=9.8847%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9760, ncalls=20148, regioncalls=116638, ndraw=128, logz=-11.94, remainder_fraction=8.5460%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9812, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.9438%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9824, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.8115%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9856, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.4677%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9888, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.92, remainder_fraction=7.1387%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9965, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.91, remainder_fraction=6.4020%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10016, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.91, remainder_fraction=5.9550%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.90, remainder_fraction=5.4369%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10112, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=5.1939%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10119, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=5.1429%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10144, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=4.9628%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10176, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=4.7402%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.89, remainder_fraction=4.5281%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10272, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=4.1317%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10304, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=3.9463%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10336, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=3.7692%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10426, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=3.3117%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10496, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=2.9939%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10528, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=2.8586%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10579, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.88, remainder_fraction=2.6559%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10624, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.4885%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10656, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.3759%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10688, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.2686%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10734, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=2.1225%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=2.0679%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10784, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=1.9742%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10816, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=1.8847%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10888, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.87, remainder_fraction=1.6979%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10912, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.87, remainder_fraction=1.6399%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10944, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.86, remainder_fraction=1.5655%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10976, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.86, remainder_fraction=1.4945%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11040, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.3617%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11042, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.3577%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11104, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.2408%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11196, ncalls=21428, regioncalls=120990, ndraw=128, logz=-11.86, remainder_fraction=1.0854%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11232, ncalls=21428, regioncalls=120990, ndraw=128, logz=-11.86, remainder_fraction=1.0300%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 21428 INFO ultranest:integrator.py:2697 logZ = -11.85 +- 0.1011 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2747.9, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1119 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (9088/9428 iterations) have 682 DEBUG ultranest:integrator.py:1663 at least 1367 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 1367 minimum live points (dlogz from 0.08 to 0.21, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.18 bs:0.10 tail:0.01 total:0.10 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 1367 live points (have 684 already) ... INFO ultranest:integrator.py:1433 Sampling 683 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 1367.0), (inf, 1367.0)] DEBUG ultranest:integrator.py:2610 iteration=5, ncalls=22239, regioncalls=121118, ndraw=128, logz=-233003.00, remainder_fraction=100.0000%, Lmin=-230589.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=22239, regioncalls=121118, ndraw=128, logz=-199426.05, remainder_fraction=100.0000%, Lmin=-198726.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=157, ncalls=22239, regioncalls=121118, ndraw=128, logz=-149600.33, remainder_fraction=100.0000%, Lmin=-148811.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=22239, regioncalls=121118, ndraw=128, logz=-147913.41, remainder_fraction=100.0000%, Lmin=-147895.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=22239, regioncalls=121118, ndraw=128, logz=-141385.44, remainder_fraction=100.0000%, Lmin=-141373.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=311, ncalls=22367, regioncalls=121246, ndraw=128, logz=-124821.42, remainder_fraction=100.0000%, Lmin=-124722.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=22367, regioncalls=121246, ndraw=128, logz=-119354.68, remainder_fraction=100.0000%, Lmin=-119332.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=22367, regioncalls=121246, ndraw=128, logz=-116564.88, remainder_fraction=100.0000%, Lmin=-116552.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=509, ncalls=22475, regioncalls=121374, ndraw=128, logz=-105894.01, remainder_fraction=100.0000%, Lmin=-105771.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=512, ncalls=22475, regioncalls=121374, ndraw=128, logz=-105522.63, remainder_fraction=100.0000%, Lmin=-105358.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=22475, regioncalls=121374, ndraw=128, logz=-103558.95, remainder_fraction=100.0000%, Lmin=-103464.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=608, ncalls=22583, regioncalls=121502, ndraw=128, logz=-98572.93, remainder_fraction=100.0000%, Lmin=-98514.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=22583, regioncalls=121502, ndraw=128, logz=-97795.04, remainder_fraction=100.0000%, Lmin=-97702.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=22583, regioncalls=121502, ndraw=128, logz=-94853.19, remainder_fraction=100.0000%, Lmin=-94828.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=22583, regioncalls=121502, ndraw=128, logz=-93006.22, remainder_fraction=100.0000%, Lmin=-92954.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=22667, regioncalls=121630, ndraw=128, logz=-85410.96, remainder_fraction=100.0000%, Lmin=-85395.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=896, ncalls=22667, regioncalls=121630, ndraw=128, logz=-82306.57, remainder_fraction=100.0000%, Lmin=-82251.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=926, ncalls=22743, regioncalls=121758, ndraw=128, logz=-81023.20, remainder_fraction=100.0000%, Lmin=-81000.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=22743, regioncalls=121758, ndraw=128, logz=-80948.65, remainder_fraction=100.0000%, Lmin=-80888.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=22743, regioncalls=121758, ndraw=128, logz=-77582.27, remainder_fraction=100.0000%, Lmin=-77565.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=22817, regioncalls=121886, ndraw=128, logz=-73503.58, remainder_fraction=100.0000%, Lmin=-73423.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=22817, regioncalls=121886, ndraw=128, logz=-71606.05, remainder_fraction=100.0000%, Lmin=-71595.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=22892, regioncalls=122014, ndraw=128, logz=-69564.78, remainder_fraction=100.0000%, Lmin=-69507.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=22892, regioncalls=122014, ndraw=128, logz=-68137.54, remainder_fraction=100.0000%, Lmin=-68006.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=22892, regioncalls=122014, ndraw=128, logz=-66557.80, remainder_fraction=100.0000%, Lmin=-66520.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=22892, regioncalls=122014, ndraw=128, logz=-65303.22, remainder_fraction=100.0000%, Lmin=-65261.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1232, ncalls=22942, regioncalls=122142, ndraw=128, logz=-64655.71, remainder_fraction=100.0000%, Lmin=-64592.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=22942, regioncalls=122142, ndraw=128, logz=-63771.59, remainder_fraction=100.0000%, Lmin=-63760.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1312, ncalls=22942, regioncalls=122142, ndraw=128, logz=-60798.74, remainder_fraction=100.0000%, Lmin=-60781.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=23048, regioncalls=122398, ndraw=128, logz=-55667.63, remainder_fraction=100.0000%, Lmin=-55649.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=23111, regioncalls=122526, ndraw=128, logz=-54246.26, remainder_fraction=100.0000%, Lmin=-54207.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=23111, regioncalls=122526, ndraw=128, logz=-51934.62, remainder_fraction=100.0000%, Lmin=-51913.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1539, ncalls=23111, regioncalls=122526, ndraw=128, logz=-51908.73, remainder_fraction=100.0000%, Lmin=-51840.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=23111, regioncalls=122526, ndraw=128, logz=-50702.13, remainder_fraction=100.0000%, Lmin=-50615.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=23165, regioncalls=122654, ndraw=128, logz=-49341.16, remainder_fraction=100.0000%, Lmin=-49307.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1718, ncalls=23223, regioncalls=122782, ndraw=128, logz=-45151.88, remainder_fraction=100.0000%, Lmin=-45133.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1843, ncalls=23302, regioncalls=123038, ndraw=128, logz=-41409.71, remainder_fraction=100.0000%, Lmin=-41382.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1845, ncalls=23302, regioncalls=123038, ndraw=128, logz=-41321.71, remainder_fraction=100.0000%, Lmin=-41294.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1856, ncalls=23302, regioncalls=123038, ndraw=128, logz=-40908.42, remainder_fraction=100.0000%, Lmin=-40870.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=23344, regioncalls=123166, ndraw=128, logz=-39979.36, remainder_fraction=100.0000%, Lmin=-39965.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=23344, regioncalls=123166, ndraw=128, logz=-39214.58, remainder_fraction=100.0000%, Lmin=-39202.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1952, ncalls=23379, regioncalls=123294, ndraw=128, logz=-38457.53, remainder_fraction=100.0000%, Lmin=-38445.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2075, ncalls=23442, regioncalls=123550, ndraw=128, logz=-35102.65, remainder_fraction=100.0000%, Lmin=-35093.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=23442, regioncalls=123550, ndraw=128, logz=-34982.19, remainder_fraction=100.0000%, Lmin=-34917.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2151, ncalls=23516, regioncalls=123806, ndraw=128, logz=-33126.27, remainder_fraction=100.0000%, Lmin=-33087.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=23568, regioncalls=124062, ndraw=128, logz=-30972.50, remainder_fraction=100.0000%, Lmin=-30958.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=23568, regioncalls=124062, ndraw=128, logz=-30472.51, remainder_fraction=100.0000%, Lmin=-30381.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2404, ncalls=23652, regioncalls=124446, ndraw=128, logz=-27663.57, remainder_fraction=100.0000%, Lmin=-27619.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2432, ncalls=23652, regioncalls=124446, ndraw=128, logz=-27023.92, remainder_fraction=100.0000%, Lmin=-26954.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2458, ncalls=23692, regioncalls=124574, ndraw=128, logz=-26425.68, remainder_fraction=100.0000%, Lmin=-26407.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=23692, regioncalls=124574, ndraw=128, logz=-26287.45, remainder_fraction=100.0000%, Lmin=-26248.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2496, ncalls=23692, regioncalls=124574, ndraw=128, logz=-25544.59, remainder_fraction=100.0000%, Lmin=-25534.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=23757, regioncalls=124958, ndraw=128, logz=-24292.17, remainder_fraction=100.0000%, Lmin=-24270.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2624, ncalls=23817, regioncalls=125214, ndraw=128, logz=-23053.44, remainder_fraction=100.0000%, Lmin=-23035.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=23817, regioncalls=125214, ndraw=128, logz=-21981.47, remainder_fraction=100.0000%, Lmin=-21961.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2752, ncalls=23879, regioncalls=125598, ndraw=128, logz=-21026.27, remainder_fraction=100.0000%, Lmin=-21006.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2764, ncalls=23879, regioncalls=125598, ndraw=128, logz=-20797.43, remainder_fraction=100.0000%, Lmin=-20779.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=23898, regioncalls=125726, ndraw=128, logz=-20575.98, remainder_fraction=100.0000%, Lmin=-20539.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=23948, regioncalls=126110, ndraw=128, logz=-19134.96, remainder_fraction=100.0000%, Lmin=-19112.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=23998, regioncalls=126494, ndraw=128, logz=-18084.03, remainder_fraction=100.0000%, Lmin=-18032.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=24037, regioncalls=126750, ndraw=128, logz=-17224.20, remainder_fraction=100.0000%, Lmin=-17206.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3071, ncalls=24091, regioncalls=127134, ndraw=128, logz=-16624.71, remainder_fraction=100.0000%, Lmin=-16607.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=24154, regioncalls=127646, ndraw=128, logz=-15375.38, remainder_fraction=100.0000%, Lmin=-15354.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=24170, regioncalls=127774, ndraw=128, logz=-15007.61, remainder_fraction=100.0000%, Lmin=-14988.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=24195, regioncalls=127902, ndraw=128, logz=-14683.63, remainder_fraction=100.0000%, Lmin=-14655.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3328, ncalls=24258, regioncalls=128414, ndraw=128, logz=-13582.10, remainder_fraction=100.0000%, Lmin=-13564.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=24286, regioncalls=128670, ndraw=128, logz=-13277.66, remainder_fraction=100.0000%, Lmin=-13247.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3379, ncalls=24296, regioncalls=128798, ndraw=128, logz=-13008.15, remainder_fraction=100.0000%, Lmin=-12998.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=24308, regioncalls=128926, ndraw=128, logz=-12913.20, remainder_fraction=100.0000%, Lmin=-12897.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3424, ncalls=24320, regioncalls=129054, ndraw=128, logz=-12664.07, remainder_fraction=100.0000%, Lmin=-12652.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3456, ncalls=24335, regioncalls=129182, ndraw=128, logz=-12409.39, remainder_fraction=100.0000%, Lmin=-12388.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=24385, regioncalls=129694, ndraw=128, logz=-11620.47, remainder_fraction=100.0000%, Lmin=-11582.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3616, ncalls=24441, regioncalls=130334, ndraw=128, logz=-11082.91, remainder_fraction=100.0000%, Lmin=-11065.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3648, ncalls=24470, regioncalls=130590, ndraw=128, logz=-10850.90, remainder_fraction=100.0000%, Lmin=-10838.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=24478, regioncalls=130718, ndraw=128, logz=-10650.65, remainder_fraction=100.0000%, Lmin=-10639.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3685, ncalls=24488, regioncalls=130846, ndraw=128, logz=-10628.72, remainder_fraction=100.0000%, Lmin=-10617.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3744, ncalls=24527, regioncalls=131358, ndraw=128, logz=-10178.86, remainder_fraction=100.0000%, Lmin=-10167.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3808, ncalls=24566, regioncalls=131870, ndraw=128, logz=-9708.26, remainder_fraction=100.0000%, Lmin=-9696.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=24579, regioncalls=131998, ndraw=128, logz=-9465.14, remainder_fraction=100.0000%, Lmin=-9447.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3872, ncalls=24599, regioncalls=132382, ndraw=128, logz=-9298.28, remainder_fraction=100.0000%, Lmin=-9287.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3991, ncalls=24689, regioncalls=133662, ndraw=128, logz=-8459.96, remainder_fraction=100.0000%, Lmin=-8441.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=24698, regioncalls=133790, ndraw=128, logz=-8430.80, remainder_fraction=100.0000%, Lmin=-8400.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=24719, regioncalls=134174, ndraw=128, logz=-8247.54, remainder_fraction=100.0000%, Lmin=-8236.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4154, ncalls=24798, regioncalls=135582, ndraw=128, logz=-7456.39, remainder_fraction=100.0000%, Lmin=-7441.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=24798, regioncalls=135582, ndraw=128, logz=-7421.50, remainder_fraction=100.0000%, Lmin=-7410.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4290, ncalls=24874, regioncalls=136734, ndraw=128, logz=-6754.42, remainder_fraction=100.0000%, Lmin=-6731.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4298, ncalls=24874, regioncalls=136734, ndraw=128, logz=-6715.01, remainder_fraction=100.0000%, Lmin=-6688.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=24888, regioncalls=137118, ndraw=128, logz=-6632.30, remainder_fraction=100.0000%, Lmin=-6621.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4416, ncalls=24931, regioncalls=138142, ndraw=128, logz=-6265.39, remainder_fraction=100.0000%, Lmin=-6249.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4542, ncalls=25014, regioncalls=139806, ndraw=128, logz=-5663.02, remainder_fraction=100.0000%, Lmin=-5646.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4576, ncalls=25038, regioncalls=140190, ndraw=128, logz=-5475.07, remainder_fraction=100.0000%, Lmin=-5463.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4604, ncalls=25065, regioncalls=140830, ndraw=128, logz=-5332.69, remainder_fraction=100.0000%, Lmin=-5311.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4608, ncalls=25065, regioncalls=140830, ndraw=128, logz=-5312.35, remainder_fraction=100.0000%, Lmin=-5301.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4713, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4957.43, remainder_fraction=100.0000%, Lmin=-4946.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4736, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4906.82, remainder_fraction=100.0000%, Lmin=-4894.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4768, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4813.69, remainder_fraction=100.0000%, Lmin=-4801.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4682.49, remainder_fraction=100.0000%, Lmin=-4668.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4896, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4366.94, remainder_fraction=100.0000%, Lmin=-4356.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4910, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4337.55, remainder_fraction=100.0000%, Lmin=-4324.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4181.06, remainder_fraction=100.0000%, Lmin=-4163.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4992, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4081.59, remainder_fraction=100.0000%, Lmin=-4070.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5024, ncalls=25348, regioncalls=141854, ndraw=128, logz=-3998.37, remainder_fraction=100.0000%, Lmin=-3985.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=25414, regioncalls=143774, ndraw=128, logz=-3720.66, remainder_fraction=100.0000%, Lmin=-3703.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5219, ncalls=25477, regioncalls=145694, ndraw=128, logz=-3487.62, remainder_fraction=100.0000%, Lmin=-3475.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=25513, regioncalls=147230, ndraw=128, logz=-3358.46, remainder_fraction=100.0000%, Lmin=-3343.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5312, ncalls=25540, regioncalls=148382, ndraw=128, logz=-3286.69, remainder_fraction=100.0000%, Lmin=-3273.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5376, ncalls=25678, regioncalls=149022, ndraw=128, logz=-3147.08, remainder_fraction=100.0000%, Lmin=-3132.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5408, ncalls=25678, regioncalls=149022, ndraw=128, logz=-3047.07, remainder_fraction=100.0000%, Lmin=-3036.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5525, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2823.69, remainder_fraction=100.0000%, Lmin=-2808.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5536, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2792.09, remainder_fraction=100.0000%, Lmin=-2777.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5632, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2615.93, remainder_fraction=100.0000%, Lmin=-2600.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5696, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2461.13, remainder_fraction=100.0000%, Lmin=-2449.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5817, ncalls=25892, regioncalls=152862, ndraw=128, logz=-2243.06, remainder_fraction=100.0000%, Lmin=-2231.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5824, ncalls=25897, regioncalls=153118, ndraw=128, logz=-2236.10, remainder_fraction=100.0000%, Lmin=-2221.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5832, ncalls=25900, regioncalls=153246, ndraw=128, logz=-2225.37, remainder_fraction=100.0000%, Lmin=-2213.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5888, ncalls=25943, regioncalls=155934, ndraw=128, logz=-2139.12, remainder_fraction=100.0000%, Lmin=-2127.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=26078, regioncalls=156702, ndraw=128, logz=-2099.07, remainder_fraction=100.0000%, Lmin=-2086.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5952, ncalls=26078, regioncalls=156702, ndraw=128, logz=-2050.81, remainder_fraction=100.0000%, Lmin=-2034.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1909.60, remainder_fraction=100.0000%, Lmin=-1897.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1862.70, remainder_fraction=100.0000%, Lmin=-1850.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6112, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1815.98, remainder_fraction=100.0000%, Lmin=-1804.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6138, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1781.34, remainder_fraction=100.0000%, Lmin=-1768.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6176, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1734.14, remainder_fraction=100.0000%, Lmin=-1722.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6208, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1701.84, remainder_fraction=100.0000%, Lmin=-1690.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6272, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1614.13, remainder_fraction=100.0000%, Lmin=-1601.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6304, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1570.62, remainder_fraction=100.0000%, Lmin=-1558.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6336, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1536.50, remainder_fraction=100.0000%, Lmin=-1524.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6368, ncalls=26337, regioncalls=157342, ndraw=128, logz=-1508.89, remainder_fraction=100.0000%, Lmin=-1496.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6444, ncalls=26337, regioncalls=157342, ndraw=128, logz=-1430.05, remainder_fraction=100.0000%, Lmin=-1417.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6575, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1299.75, remainder_fraction=100.0000%, Lmin=-1287.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1266.10, remainder_fraction=100.0000%, Lmin=-1254.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6656, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1239.64, remainder_fraction=100.0000%, Lmin=-1226.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6674, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1221.34, remainder_fraction=100.0000%, Lmin=-1208.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6752, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1160.70, remainder_fraction=100.0000%, Lmin=-1148.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1131.34, remainder_fraction=100.0000%, Lmin=-1120.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6816, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1110.89, remainder_fraction=100.0000%, Lmin=-1099.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1058.73, remainder_fraction=100.0000%, Lmin=-1046.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6944, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1013.50, remainder_fraction=100.0000%, Lmin=-1001.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6949, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1011.38, remainder_fraction=100.0000%, Lmin=-999.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6976, ncalls=26729, regioncalls=159262, ndraw=128, logz=-994.70, remainder_fraction=100.0000%, Lmin=-982.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7008, ncalls=26729, regioncalls=159262, ndraw=128, logz=-968.55, remainder_fraction=100.0000%, Lmin=-956.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=26729, regioncalls=159262, ndraw=128, logz=-947.90, remainder_fraction=100.0000%, Lmin=-935.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7136, ncalls=26729, regioncalls=159262, ndraw=128, logz=-885.07, remainder_fraction=100.0000%, Lmin=-872.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7232, ncalls=26857, regioncalls=159390, ndraw=128, logz=-827.46, remainder_fraction=100.0000%, Lmin=-814.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7255, ncalls=26857, regioncalls=159390, ndraw=128, logz=-811.29, remainder_fraction=100.0000%, Lmin=-799.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7328, ncalls=26857, regioncalls=159390, ndraw=128, logz=-777.63, remainder_fraction=100.0000%, Lmin=-765.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=26988, regioncalls=160414, ndraw=128, logz=-758.38, remainder_fraction=100.0000%, Lmin=-746.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7456, ncalls=26988, regioncalls=160414, ndraw=128, logz=-715.72, remainder_fraction=100.0000%, Lmin=-703.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=26988, regioncalls=160414, ndraw=128, logz=-699.47, remainder_fraction=100.0000%, Lmin=-687.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7552, ncalls=26988, regioncalls=160414, ndraw=128, logz=-671.79, remainder_fraction=100.0000%, Lmin=-658.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7562, ncalls=27116, regioncalls=160542, ndraw=128, logz=-664.60, remainder_fraction=100.0000%, Lmin=-652.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7648, ncalls=27116, regioncalls=160542, ndraw=128, logz=-622.81, remainder_fraction=100.0000%, Lmin=-610.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7712, ncalls=27116, regioncalls=160542, ndraw=128, logz=-596.90, remainder_fraction=100.0000%, Lmin=-584.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7808, ncalls=27245, regioncalls=160926, ndraw=128, logz=-560.57, remainder_fraction=100.0000%, Lmin=-548.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7840, ncalls=27245, regioncalls=160926, ndraw=128, logz=-549.54, remainder_fraction=100.0000%, Lmin=-537.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7873, ncalls=27245, regioncalls=160926, ndraw=128, logz=-534.69, remainder_fraction=100.0000%, Lmin=-522.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7904, ncalls=27245, regioncalls=160926, ndraw=128, logz=-518.81, remainder_fraction=100.0000%, Lmin=-505.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7968, ncalls=27373, regioncalls=161182, ndraw=128, logz=-501.05, remainder_fraction=100.0000%, Lmin=-489.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8000, ncalls=27373, regioncalls=161182, ndraw=128, logz=-488.23, remainder_fraction=100.0000%, Lmin=-475.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8064, ncalls=27373, regioncalls=161182, ndraw=128, logz=-462.78, remainder_fraction=100.0000%, Lmin=-450.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8096, ncalls=27373, regioncalls=161182, ndraw=128, logz=-451.71, remainder_fraction=100.0000%, Lmin=-439.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8160, ncalls=27501, regioncalls=161310, ndraw=128, logz=-432.03, remainder_fraction=100.0000%, Lmin=-419.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8179, ncalls=27501, regioncalls=161310, ndraw=128, logz=-428.19, remainder_fraction=100.0000%, Lmin=-415.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8320, ncalls=27501, regioncalls=161310, ndraw=128, logz=-386.01, remainder_fraction=100.0000%, Lmin=-373.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8384, ncalls=27629, regioncalls=161566, ndraw=128, logz=-369.92, remainder_fraction=100.0000%, Lmin=-358.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8485, ncalls=27629, regioncalls=161566, ndraw=128, logz=-343.91, remainder_fraction=100.0000%, Lmin=-331.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8544, ncalls=27760, regioncalls=162590, ndraw=128, logz=-331.85, remainder_fraction=100.0000%, Lmin=-320.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8576, ncalls=27760, regioncalls=162590, ndraw=128, logz=-325.77, remainder_fraction=100.0000%, Lmin=-313.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8640, ncalls=27760, regioncalls=162590, ndraw=128, logz=-310.34, remainder_fraction=100.0000%, Lmin=-298.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8672, ncalls=27760, regioncalls=162590, ndraw=128, logz=-303.00, remainder_fraction=100.0000%, Lmin=-291.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8791, ncalls=27888, regioncalls=162718, ndraw=128, logz=-276.04, remainder_fraction=100.0000%, Lmin=-264.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8832, ncalls=27888, regioncalls=162718, ndraw=128, logz=-268.24, remainder_fraction=100.0000%, Lmin=-255.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8864, ncalls=27888, regioncalls=162718, ndraw=128, logz=-261.85, remainder_fraction=100.0000%, Lmin=-249.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8896, ncalls=27888, regioncalls=162718, ndraw=128, logz=-256.10, remainder_fraction=100.0000%, Lmin=-243.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8928, ncalls=28020, regioncalls=163870, ndraw=128, logz=-249.09, remainder_fraction=100.0000%, Lmin=-237.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8992, ncalls=28020, regioncalls=163870, ndraw=128, logz=-237.30, remainder_fraction=100.0000%, Lmin=-225.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9012, ncalls=28020, regioncalls=163870, ndraw=128, logz=-233.88, remainder_fraction=100.0000%, Lmin=-222.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9024, ncalls=28020, regioncalls=163870, ndraw=128, logz=-232.03, remainder_fraction=100.0000%, Lmin=-219.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9088, ncalls=28020, regioncalls=163870, ndraw=128, logz=-219.93, remainder_fraction=100.0000%, Lmin=-208.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9120, ncalls=28149, regioncalls=164254, ndraw=128, logz=-214.94, remainder_fraction=100.0000%, Lmin=-203.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9152, ncalls=28149, regioncalls=164254, ndraw=128, logz=-210.52, remainder_fraction=100.0000%, Lmin=-198.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9288, ncalls=28149, regioncalls=164254, ndraw=128, logz=-192.50, remainder_fraction=100.0000%, Lmin=-180.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9318, ncalls=28277, regioncalls=164382, ndraw=128, logz=-188.56, remainder_fraction=100.0000%, Lmin=-175.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9344, ncalls=28277, regioncalls=164382, ndraw=128, logz=-185.27, remainder_fraction=100.0000%, Lmin=-173.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9374, ncalls=28277, regioncalls=164382, ndraw=128, logz=-182.35, remainder_fraction=100.0000%, Lmin=-170.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9376, ncalls=28277, regioncalls=164382, ndraw=128, logz=-182.12, remainder_fraction=100.0000%, Lmin=-170.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9408, ncalls=28277, regioncalls=164382, ndraw=128, logz=-178.57, remainder_fraction=100.0000%, Lmin=-166.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9504, ncalls=28405, regioncalls=164638, ndraw=128, logz=-167.11, remainder_fraction=100.0000%, Lmin=-155.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9536, ncalls=28405, regioncalls=164638, ndraw=128, logz=-164.30, remainder_fraction=100.0000%, Lmin=-152.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9568, ncalls=28405, regioncalls=164638, ndraw=128, logz=-161.45, remainder_fraction=100.0000%, Lmin=-149.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9632, ncalls=28405, regioncalls=164638, ndraw=128, logz=-154.84, remainder_fraction=100.0000%, Lmin=-142.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9664, ncalls=28405, regioncalls=164638, ndraw=128, logz=-150.83, remainder_fraction=100.0000%, Lmin=-138.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9683, ncalls=28533, regioncalls=164766, ndraw=128, logz=-149.12, remainder_fraction=100.0000%, Lmin=-137.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9689, ncalls=28533, regioncalls=164766, ndraw=128, logz=-148.58, remainder_fraction=100.0000%, Lmin=-136.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9696, ncalls=28533, regioncalls=164766, ndraw=128, logz=-147.87, remainder_fraction=100.0000%, Lmin=-135.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9760, ncalls=28533, regioncalls=164766, ndraw=128, logz=-141.77, remainder_fraction=100.0000%, Lmin=-129.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9824, ncalls=28533, regioncalls=164766, ndraw=128, logz=-135.50, remainder_fraction=100.0000%, Lmin=-123.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9856, ncalls=28661, regioncalls=165150, ndraw=128, logz=-132.77, remainder_fraction=100.0000%, Lmin=-121.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9914, ncalls=28661, regioncalls=165150, ndraw=128, logz=-128.01, remainder_fraction=100.0000%, Lmin=-115.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9962, ncalls=28661, regioncalls=165150, ndraw=128, logz=-123.77, remainder_fraction=100.0000%, Lmin=-111.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10016, ncalls=28661, regioncalls=165150, ndraw=128, logz=-119.81, remainder_fraction=100.0000%, Lmin=-107.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10027, ncalls=28661, regioncalls=165150, ndraw=128, logz=-118.98, remainder_fraction=100.0000%, Lmin=-107.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=28789, regioncalls=165406, ndraw=128, logz=-114.34, remainder_fraction=100.0000%, Lmin=-101.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10100, ncalls=28789, regioncalls=165406, ndraw=128, logz=-112.10, remainder_fraction=100.0000%, Lmin=-99.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10109, ncalls=28789, regioncalls=165406, ndraw=128, logz=-111.40, remainder_fraction=100.0000%, Lmin=-99.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10112, ncalls=28789, regioncalls=165406, ndraw=128, logz=-111.19, remainder_fraction=100.0000%, Lmin=-99.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10144, ncalls=28789, regioncalls=165406, ndraw=128, logz=-108.74, remainder_fraction=100.0000%, Lmin=-96.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10176, ncalls=28789, regioncalls=165406, ndraw=128, logz=-106.42, remainder_fraction=100.0000%, Lmin=-94.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10184, ncalls=28789, regioncalls=165406, ndraw=128, logz=-105.91, remainder_fraction=100.0000%, Lmin=-94.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=28789, regioncalls=165406, ndraw=128, logz=-104.53, remainder_fraction=100.0000%, Lmin=-92.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10234, ncalls=28917, regioncalls=165662, ndraw=128, logz=-103.06, remainder_fraction=100.0000%, Lmin=-91.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10272, ncalls=28917, regioncalls=165662, ndraw=128, logz=-100.84, remainder_fraction=100.0000%, Lmin=-88.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10394, ncalls=28917, regioncalls=165662, ndraw=128, logz=-93.77, remainder_fraction=100.0000%, Lmin=-81.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10400, ncalls=28917, regioncalls=165662, ndraw=128, logz=-93.44, remainder_fraction=100.0000%, Lmin=-81.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10432, ncalls=29045, regioncalls=165790, ndraw=128, logz=-91.47, remainder_fraction=100.0000%, Lmin=-79.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10464, ncalls=29045, regioncalls=165790, ndraw=128, logz=-89.60, remainder_fraction=100.0000%, Lmin=-77.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10528, ncalls=29045, regioncalls=165790, ndraw=128, logz=-85.83, remainder_fraction=100.0000%, Lmin=-73.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10540, ncalls=29045, regioncalls=165790, ndraw=128, logz=-85.25, remainder_fraction=100.0000%, Lmin=-73.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10560, ncalls=29045, regioncalls=165790, ndraw=128, logz=-84.28, remainder_fraction=100.0000%, Lmin=-72.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10592, ncalls=29173, regioncalls=166046, ndraw=128, logz=-82.82, remainder_fraction=100.0000%, Lmin=-71.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10626, ncalls=29173, regioncalls=166046, ndraw=128, logz=-81.34, remainder_fraction=100.0000%, Lmin=-69.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10656, ncalls=29173, regioncalls=166046, ndraw=128, logz=-79.88, remainder_fraction=100.0000%, Lmin=-67.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10673, ncalls=29173, regioncalls=166046, ndraw=128, logz=-79.07, remainder_fraction=100.0000%, Lmin=-66.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10688, ncalls=29173, regioncalls=166046, ndraw=128, logz=-78.31, remainder_fraction=100.0000%, Lmin=-66.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10747, ncalls=29173, regioncalls=166046, ndraw=128, logz=-75.88, remainder_fraction=100.0000%, Lmin=-63.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=29173, regioncalls=166046, ndraw=128, logz=-75.66, remainder_fraction=100.0000%, Lmin=-63.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10787, ncalls=29301, regioncalls=166302, ndraw=128, logz=-74.31, remainder_fraction=100.0000%, Lmin=-62.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10816, ncalls=29301, regioncalls=166302, ndraw=128, logz=-72.98, remainder_fraction=100.0000%, Lmin=-60.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10848, ncalls=29301, regioncalls=166302, ndraw=128, logz=-71.50, remainder_fraction=100.0000%, Lmin=-59.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10944, ncalls=29301, regioncalls=166302, ndraw=128, logz=-68.01, remainder_fraction=100.0000%, Lmin=-55.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10962, ncalls=29301, regioncalls=166302, ndraw=128, logz=-67.19, remainder_fraction=100.0000%, Lmin=-55.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10976, ncalls=29301, regioncalls=166302, ndraw=128, logz=-66.60, remainder_fraction=100.0000%, Lmin=-54.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11008, ncalls=29429, regioncalls=166558, ndraw=128, logz=-65.27, remainder_fraction=100.0000%, Lmin=-53.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11040, ncalls=29429, regioncalls=166558, ndraw=128, logz=-63.96, remainder_fraction=100.0000%, Lmin=-51.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11060, ncalls=29429, regioncalls=166558, ndraw=128, logz=-63.12, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11100, ncalls=29429, regioncalls=166558, ndraw=128, logz=-61.42, remainder_fraction=100.0000%, Lmin=-49.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11104, ncalls=29429, regioncalls=166558, ndraw=128, logz=-61.24, remainder_fraction=100.0000%, Lmin=-48.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11136, ncalls=29429, regioncalls=166558, ndraw=128, logz=-59.96, remainder_fraction=100.0000%, Lmin=-47.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11156, ncalls=29429, regioncalls=166558, ndraw=128, logz=-59.09, remainder_fraction=100.0000%, Lmin=-46.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11168, ncalls=29429, regioncalls=166558, ndraw=128, logz=-58.66, remainder_fraction=100.0000%, Lmin=-46.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11176, ncalls=29429, regioncalls=166558, ndraw=128, logz=-58.37, remainder_fraction=100.0000%, Lmin=-46.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11196, ncalls=29429, regioncalls=166558, ndraw=128, logz=-57.68, remainder_fraction=100.0000%, Lmin=-45.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11200, ncalls=29429, regioncalls=166558, ndraw=128, logz=-57.56, remainder_fraction=100.0000%, Lmin=-45.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11264, ncalls=29557, regioncalls=166814, ndraw=128, logz=-55.42, remainder_fraction=100.0000%, Lmin=-43.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11328, ncalls=29557, regioncalls=166814, ndraw=128, logz=-53.39, remainder_fraction=100.0000%, Lmin=-41.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11383, ncalls=29557, regioncalls=166814, ndraw=128, logz=-51.59, remainder_fraction=100.0000%, Lmin=-39.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11422, ncalls=29685, regioncalls=167454, ndraw=128, logz=-50.36, remainder_fraction=100.0000%, Lmin=-38.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11424, ncalls=29685, regioncalls=167454, ndraw=128, logz=-50.30, remainder_fraction=100.0000%, Lmin=-38.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11447, ncalls=29685, regioncalls=167454, ndraw=128, logz=-49.59, remainder_fraction=100.0000%, Lmin=-37.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11459, ncalls=29685, regioncalls=167454, ndraw=128, logz=-49.20, remainder_fraction=100.0000%, Lmin=-37.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11488, ncalls=29685, regioncalls=167454, ndraw=128, logz=-48.34, remainder_fraction=100.0000%, Lmin=-36.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11552, ncalls=29685, regioncalls=167454, ndraw=128, logz=-46.64, remainder_fraction=100.0000%, Lmin=-34.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11588, ncalls=29685, regioncalls=167454, ndraw=128, logz=-45.87, remainder_fraction=100.0000%, Lmin=-34.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11616, ncalls=29813, regioncalls=167838, ndraw=128, logz=-45.17, remainder_fraction=100.0000%, Lmin=-33.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11648, ncalls=29813, regioncalls=167838, ndraw=128, logz=-44.43, remainder_fraction=100.0000%, Lmin=-32.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11677, ncalls=29813, regioncalls=167838, ndraw=128, logz=-43.83, remainder_fraction=100.0000%, Lmin=-31.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11680, ncalls=29813, regioncalls=167838, ndraw=128, logz=-43.77, remainder_fraction=100.0000%, Lmin=-31.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11744, ncalls=29813, regioncalls=167838, ndraw=128, logz=-42.38, remainder_fraction=100.0000%, Lmin=-30.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11843, ncalls=29941, regioncalls=168094, ndraw=128, logz=-40.02, remainder_fraction=100.0000%, Lmin=-27.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11866, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.46, remainder_fraction=100.0000%, Lmin=-27.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11872, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.32, remainder_fraction=100.0000%, Lmin=-27.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11886, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.01, remainder_fraction=100.0000%, Lmin=-26.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11927, ncalls=29941, regioncalls=168094, ndraw=128, logz=-38.11, remainder_fraction=100.0000%, Lmin=-26.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11936, ncalls=29941, regioncalls=168094, ndraw=128, logz=-37.92, remainder_fraction=100.0000%, Lmin=-25.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11952, ncalls=29941, regioncalls=168094, ndraw=128, logz=-37.60, remainder_fraction=100.0000%, Lmin=-25.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11995, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.79, remainder_fraction=100.0000%, Lmin=-24.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12000, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.70, remainder_fraction=100.0000%, Lmin=-24.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12007, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.56, remainder_fraction=100.0000%, Lmin=-24.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12051, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.82, remainder_fraction=100.0000%, Lmin=-23.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12086, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.28, remainder_fraction=100.0000%, Lmin=-23.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12096, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.12, remainder_fraction=100.0000%, Lmin=-23.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12128, ncalls=30069, regioncalls=168350, ndraw=128, logz=-34.55, remainder_fraction=100.0000%, Lmin=-22.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12169, ncalls=30069, regioncalls=168350, ndraw=128, logz=-33.82, remainder_fraction=100.0000%, Lmin=-21.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12192, ncalls=30069, regioncalls=168350, ndraw=128, logz=-33.46, remainder_fraction=100.0000%, Lmin=-21.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12203, ncalls=30197, regioncalls=168734, ndraw=128, logz=-33.31, remainder_fraction=100.0000%, Lmin=-21.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12240, ncalls=30197, regioncalls=168734, ndraw=128, logz=-32.75, remainder_fraction=100.0000%, Lmin=-20.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12288, ncalls=30197, regioncalls=168734, ndraw=128, logz=-32.03, remainder_fraction=100.0000%, Lmin=-20.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12320, ncalls=30197, regioncalls=168734, ndraw=128, logz=-31.54, remainder_fraction=100.0000%, Lmin=-19.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12352, ncalls=30197, regioncalls=168734, ndraw=128, logz=-31.06, remainder_fraction=100.0000%, Lmin=-19.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12384, ncalls=30197, regioncalls=168734, ndraw=128, logz=-30.60, remainder_fraction=100.0000%, Lmin=-18.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12418, ncalls=30325, regioncalls=169118, ndraw=128, logz=-30.13, remainder_fraction=100.0000%, Lmin=-18.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12448, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.74, remainder_fraction=100.0000%, Lmin=-17.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12482, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.30, remainder_fraction=100.0000%, Lmin=-17.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12502, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.06, remainder_fraction=100.0000%, Lmin=-17.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12514, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.93, remainder_fraction=100.0000%, Lmin=-17.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12569, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.32, remainder_fraction=100.0000%, Lmin=-16.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12576, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.25, remainder_fraction=100.0000%, Lmin=-16.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12593, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.07, remainder_fraction=100.0000%, Lmin=-16.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12604, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.94, remainder_fraction=100.0000%, Lmin=-15.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12613, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.84, remainder_fraction=100.0000%, Lmin=-15.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12628, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.68, remainder_fraction=100.0000%, Lmin=-15.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12703, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.81, remainder_fraction=100.0000%, Lmin=-14.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12729, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.53, remainder_fraction=99.9999%, Lmin=-14.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12736, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.46, remainder_fraction=99.9999%, Lmin=-14.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12768, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.12, remainder_fraction=99.9999%, Lmin=-14.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12800, ncalls=30453, regioncalls=169374, ndraw=128, logz=-25.79, remainder_fraction=99.9999%, Lmin=-13.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12833, ncalls=30581, regioncalls=169630, ndraw=128, logz=-25.48, remainder_fraction=99.9999%, Lmin=-13.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12842, ncalls=30581, regioncalls=169630, ndraw=128, logz=-25.40, remainder_fraction=99.9998%, Lmin=-13.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12896, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.92, remainder_fraction=99.9997%, Lmin=-12.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12920, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.69, remainder_fraction=99.9997%, Lmin=-12.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12928, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.62, remainder_fraction=99.9997%, Lmin=-12.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12953, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.37, remainder_fraction=99.9996%, Lmin=-12.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12960, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.30, remainder_fraction=99.9995%, Lmin=-12.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12985, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.05, remainder_fraction=99.9994%, Lmin=-11.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12992, ncalls=30581, regioncalls=169630, ndraw=128, logz=-23.98, remainder_fraction=99.9994%, Lmin=-11.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13024, ncalls=30581, regioncalls=169630, ndraw=128, logz=-23.68, remainder_fraction=99.9991%, Lmin=-11.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13058, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.38, remainder_fraction=99.9988%, Lmin=-11.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13066, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.31, remainder_fraction=99.9988%, Lmin=-11.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13079, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.21, remainder_fraction=99.9986%, Lmin=-11.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13088, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.13, remainder_fraction=99.9985%, Lmin=-11.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13092, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.10, remainder_fraction=99.9985%, Lmin=-11.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13099, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.04, remainder_fraction=99.9984%, Lmin=-11.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13120, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.88, remainder_fraction=99.9981%, Lmin=-10.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13144, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.70, remainder_fraction=99.9977%, Lmin=-10.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13179, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.43, remainder_fraction=99.9970%, Lmin=-10.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13184, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.39, remainder_fraction=99.9969%, Lmin=-10.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13209, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.20, remainder_fraction=99.9962%, Lmin=-10.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13216, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.15, remainder_fraction=99.9960%, Lmin=-10.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13226, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.07, remainder_fraction=99.9957%, Lmin=-10.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13344, ncalls=30837, regioncalls=170654, ndraw=128, logz=-21.19, remainder_fraction=99.9894%, Lmin=-9.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13353, ncalls=30837, regioncalls=170654, ndraw=128, logz=-21.13, remainder_fraction=99.9888%, Lmin=-9.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13481, ncalls=30965, regioncalls=171166, ndraw=128, logz=-20.27, remainder_fraction=99.9738%, Lmin=-8.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13536, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.95, remainder_fraction=99.9640%, Lmin=-7.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13600, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.57, remainder_fraction=99.9469%, Lmin=-7.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13632, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.39, remainder_fraction=99.9355%, Lmin=-7.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13662, ncalls=31093, regioncalls=171294, ndraw=128, logz=-19.22, remainder_fraction=99.9236%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13728, ncalls=31093, regioncalls=171294, ndraw=128, logz=-18.89, remainder_fraction=99.8927%, Lmin=-6.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13760, ncalls=31093, regioncalls=171294, ndraw=128, logz=-18.74, remainder_fraction=99.8758%, Lmin=-6.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13856, ncalls=31221, regioncalls=171550, ndraw=128, logz=-18.30, remainder_fraction=99.8078%, Lmin=-6.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13888, ncalls=31221, regioncalls=171550, ndraw=128, logz=-18.16, remainder_fraction=99.7779%, Lmin=-6.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13952, ncalls=31221, regioncalls=171550, ndraw=128, logz=-17.90, remainder_fraction=99.7167%, Lmin=-6.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13970, ncalls=31221, regioncalls=171550, ndraw=128, logz=-17.83, remainder_fraction=99.6980%, Lmin=-5.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14048, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.55, remainder_fraction=99.5963%, Lmin=-5.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14080, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.44, remainder_fraction=99.5485%, Lmin=-5.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14112, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.33, remainder_fraction=99.4927%, Lmin=-5.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14144, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.21, remainder_fraction=99.4301%, Lmin=-5.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14176, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.10, remainder_fraction=99.3623%, Lmin=-5.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14208, ncalls=31349, regioncalls=171806, ndraw=128, logz=-16.99, remainder_fraction=99.2870%, Lmin=-5.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14240, ncalls=31349, regioncalls=171806, ndraw=128, logz=-16.88, remainder_fraction=99.2082%, Lmin=-4.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14272, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.77, remainder_fraction=99.1149%, Lmin=-4.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14276, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.76, remainder_fraction=99.1039%, Lmin=-4.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14304, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.66, remainder_fraction=99.0229%, Lmin=-4.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14368, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.46, remainder_fraction=98.8110%, Lmin=-4.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14432, ncalls=31605, regioncalls=172190, ndraw=128, logz=-16.26, remainder_fraction=98.5695%, Lmin=-4.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14496, ncalls=31605, regioncalls=172190, ndraw=128, logz=-16.07, remainder_fraction=98.2861%, Lmin=-4.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14560, ncalls=31605, regioncalls=172190, ndraw=128, logz=-15.89, remainder_fraction=97.9366%, Lmin=-3.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14588, ncalls=31605, regioncalls=172190, ndraw=128, logz=-15.81, remainder_fraction=97.7613%, Lmin=-3.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14705, ncalls=31733, regioncalls=172446, ndraw=128, logz=-15.50, remainder_fraction=96.9303%, Lmin=-3.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14752, ncalls=31733, regioncalls=172446, ndraw=128, logz=-15.38, remainder_fraction=96.5398%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14816, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.23, remainder_fraction=95.9618%, Lmin=-3.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14848, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.15, remainder_fraction=95.6535%, Lmin=-3.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14896, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.04, remainder_fraction=95.1340%, Lmin=-3.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14912, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.00, remainder_fraction=94.9467%, Lmin=-2.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15024, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.77, remainder_fraction=93.6492%, Lmin=-2.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15040, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.73, remainder_fraction=93.4331%, Lmin=-2.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15072, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.67, remainder_fraction=92.9778%, Lmin=-2.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15168, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.48, remainder_fraction=91.5894%, Lmin=-2.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15200, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.42, remainder_fraction=91.1171%, Lmin=-2.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15202, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.42, remainder_fraction=91.0756%, Lmin=-2.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15232, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.36, remainder_fraction=90.5477%, Lmin=-2.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15296, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.25, remainder_fraction=89.4125%, Lmin=-2.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15328, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.20, remainder_fraction=88.8292%, Lmin=-2.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15392, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.10, remainder_fraction=87.6337%, Lmin=-2.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15424, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.05, remainder_fraction=86.9769%, Lmin=-2.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15488, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.95, remainder_fraction=85.7444%, Lmin=-1.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15509, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.92, remainder_fraction=85.3009%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15552, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.86, remainder_fraction=84.3630%, Lmin=-1.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15616, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.77, remainder_fraction=82.9456%, Lmin=-1.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15648, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.73, remainder_fraction=82.2809%, Lmin=-1.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15680, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.69, remainder_fraction=81.5293%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15744, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.61, remainder_fraction=79.9864%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15776, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.57, remainder_fraction=79.2454%, Lmin=-1.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15808, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.54, remainder_fraction=78.4365%, Lmin=-1.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15815, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.53, remainder_fraction=78.2577%, Lmin=-1.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15840, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.50, remainder_fraction=77.6266%, Lmin=-1.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15961, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.37, remainder_fraction=74.5275%, Lmin=-1.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15968, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.37, remainder_fraction=74.3480%, Lmin=-1.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16000, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.33, remainder_fraction=73.4918%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16032, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.30, remainder_fraction=72.6490%, Lmin=-1.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16064, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.27, remainder_fraction=71.8195%, Lmin=-1.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16125, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.22, remainder_fraction=70.2286%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16160, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.19, remainder_fraction=69.2902%, Lmin=-1.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16192, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.16, remainder_fraction=68.4339%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16224, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.13, remainder_fraction=67.5848%, Lmin=-1.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16288, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.08, remainder_fraction=65.8040%, Lmin=-1.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16320, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.06, remainder_fraction=64.9519%, Lmin=-1.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16416, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.99, remainder_fraction=62.4237%, Lmin=-1.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16432, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.98, remainder_fraction=62.0156%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16448, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.97, remainder_fraction=61.6200%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16480, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.94, remainder_fraction=60.7711%, Lmin=-0.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16544, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.90, remainder_fraction=59.1170%, Lmin=-0.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16608, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.86, remainder_fraction=57.5043%, Lmin=-0.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16640, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.84, remainder_fraction=56.7107%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16704, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.80, remainder_fraction=55.0321%, Lmin=-0.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16736, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.79, remainder_fraction=54.1889%, Lmin=-0.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16738, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.78, remainder_fraction=54.1322%, Lmin=-0.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16768, ncalls=33141, regioncalls=175902, ndraw=128, logz=-12.77, remainder_fraction=53.3550%, Lmin=-0.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16886, ncalls=33141, regioncalls=175902, ndraw=128, logz=-12.70, remainder_fraction=50.3625%, Lmin=-0.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17006, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.65, remainder_fraction=47.3600%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17050, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.63, remainder_fraction=46.2865%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17056, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.62, remainder_fraction=46.1478%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17088, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.61, remainder_fraction=45.4016%, Lmin=-0.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17120, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.60, remainder_fraction=44.6083%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17152, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.58, remainder_fraction=43.8488%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17184, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.57, remainder_fraction=43.0946%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17280, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.53, remainder_fraction=40.8473%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17312, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.52, remainder_fraction=40.1255%, Lmin=-0.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17356, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.50, remainder_fraction=39.1477%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17376, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.50, remainder_fraction=38.7014%, Lmin=-0.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17440, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.47, remainder_fraction=37.3232%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17472, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.46, remainder_fraction=36.6385%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17581, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.43, remainder_fraction=34.3693%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17662, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.40, remainder_fraction=32.8077%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17696, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.39, remainder_fraction=32.1684%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17728, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.39, remainder_fraction=31.5693%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17760, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.38, remainder_fraction=30.9612%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17879, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.35, remainder_fraction=28.8293%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17920, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.34, remainder_fraction=28.1267%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17952, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.33, remainder_fraction=27.5866%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17969, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.32, remainder_fraction=27.3085%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18016, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.31, remainder_fraction=26.5279%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18048, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.31, remainder_fraction=26.0012%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18112, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.29, remainder_fraction=24.9766%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18230, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.27, remainder_fraction=23.1682%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18272, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.26, remainder_fraction=22.5599%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18275, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.26, remainder_fraction=22.5161%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18336, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.25, remainder_fraction=21.6519%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18368, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.24, remainder_fraction=21.2109%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18400, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.24, remainder_fraction=20.7765%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18464, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.23, remainder_fraction=19.9299%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18496, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.22, remainder_fraction=19.5189%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18528, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.22, remainder_fraction=19.1186%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18560, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.21, remainder_fraction=18.7184%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18584, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.21, remainder_fraction=18.4228%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18624, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.20, remainder_fraction=17.9469%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18656, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.20, remainder_fraction=17.5753%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18688, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.19, remainder_fraction=17.2030%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18720, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.19, remainder_fraction=16.8438%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18832, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.18, remainder_fraction=15.6344%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18890, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.17, remainder_fraction=15.0390%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18912, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.17, remainder_fraction=14.8187%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18976, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.16, remainder_fraction=14.1902%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19008, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.15, remainder_fraction=13.8858%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19072, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.15, remainder_fraction=13.2906%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19136, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.7235%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19168, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.4516%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19198, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.1981%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19200, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.1819%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19232, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.13, remainder_fraction=11.9162%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19264, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.13, remainder_fraction=11.6587%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19360, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.12, remainder_fraction=10.9125%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19456, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.11, remainder_fraction=10.2129%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19505, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.11, remainder_fraction=9.8736%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19621, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.10, remainder_fraction=9.1127%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19743, ncalls=35061, regioncalls=179486, ndraw=128, logz=-12.09, remainder_fraction=8.3702%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19744, ncalls=35061, regioncalls=179486, ndraw=128, logz=-12.09, remainder_fraction=8.3643%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19811, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.09, remainder_fraction=7.9789%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19872, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.6438%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19904, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.4733%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19936, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.3070%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19968, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.1451%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20032, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.08, remainder_fraction=6.8310%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20096, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.5276%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20117, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.4312%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20128, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.3814%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20247, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.07, remainder_fraction=5.8657%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20288, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.06, remainder_fraction=5.6980%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20320, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.06, remainder_fraction=5.5698%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20384, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.3221%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20416, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.2017%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20423, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.1758%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20480, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=4.9705%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20544, ncalls=35701, regioncalls=180766, ndraw=128, logz=-12.05, remainder_fraction=4.7491%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20640, ncalls=35701, regioncalls=180766, ndraw=128, logz=-12.05, remainder_fraction=4.4352%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20704, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.2361%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20729, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.1609%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20736, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.1401%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20768, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.0464%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20832, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.04, remainder_fraction=3.8647%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20864, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.04, remainder_fraction=3.7770%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20896, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.6915%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20960, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.5256%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20992, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.4453%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21024, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.3671%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21035, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.3406%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21120, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=3.1425%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21152, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=3.0710%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21216, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=2.9326%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21280, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.03, remainder_fraction=2.8003%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21341, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.6795%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21376, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.6127%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21408, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.5530%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21440, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.4947%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21536, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.3277%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21600, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.2224%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21632, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.1715%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21647, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.1481%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21696, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.03, remainder_fraction=2.0733%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21813, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.9049%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21824, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.8897%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21856, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.8464%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21888, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.8040%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21920, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7627%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21952, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7222%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21954, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7197%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22073, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5775%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22080, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5695%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22112, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5335%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22176, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.4639%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22208, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.4302%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22262, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.3753%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22304, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.3339%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22368, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.2733%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22400, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.2440%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22516, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1433%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22560, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1073%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22568, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1009%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22624, ncalls=37109, regioncalls=184094, ndraw=128, logz=-12.02, remainder_fraction=1.0569%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22688, ncalls=37109, regioncalls=184094, ndraw=128, logz=-12.02, remainder_fraction=1.0089%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 37109 INFO ultranest:integrator.py:2697 logZ = -12.01 +- 0.08472 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 5474.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.04 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (22399/23859 iterations) have 1365 DEBUG ultranest:integrator.py:1663 at least 1540 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 1540 minimum live points (dlogz from 0.07 to 0.16, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.17 bs:0.08 tail:0.01 total:0.08 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 1540 live points (have 1367 already) ... INFO ultranest:integrator.py:1433 Sampling 173 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 1540.0), (inf, 1540.0)] DEBUG ultranest:integrator.py:2610 iteration=3, ncalls=37410, regioncalls=184222, ndraw=128, logz=-239552.19, remainder_fraction=100.0000%, Lmin=-238281.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=37410, regioncalls=184222, ndraw=128, logz=-173988.29, remainder_fraction=100.0000%, Lmin=-173835.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=284, ncalls=37410, regioncalls=184222, ndraw=128, logz=-133092.16, remainder_fraction=100.0000%, Lmin=-133000.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=351, ncalls=37410, regioncalls=184222, ndraw=128, logz=-124631.01, remainder_fraction=100.0000%, Lmin=-124520.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=37410, regioncalls=184222, ndraw=128, logz=-107627.17, remainder_fraction=100.0000%, Lmin=-107602.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=37410, regioncalls=184222, ndraw=128, logz=-96420.06, remainder_fraction=100.0000%, Lmin=-96392.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=901, ncalls=37489, regioncalls=184350, ndraw=128, logz=-86398.70, remainder_fraction=100.0000%, Lmin=-86298.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=37489, regioncalls=184350, ndraw=128, logz=-79505.33, remainder_fraction=100.0000%, Lmin=-79393.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=37489, regioncalls=184350, ndraw=128, logz=-70723.83, remainder_fraction=100.0000%, Lmin=-70710.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1405, ncalls=37555, regioncalls=184478, ndraw=128, logz=-63768.33, remainder_fraction=100.0000%, Lmin=-63731.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1585, ncalls=37555, regioncalls=184478, ndraw=128, logz=-56835.78, remainder_fraction=100.0000%, Lmin=-56823.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1664, ncalls=37555, regioncalls=184478, ndraw=128, logz=-54185.44, remainder_fraction=100.0000%, Lmin=-54153.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=37608, regioncalls=184606, ndraw=128, logz=-51386.89, remainder_fraction=100.0000%, Lmin=-51264.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=37608, regioncalls=184606, ndraw=128, logz=-44798.94, remainder_fraction=100.0000%, Lmin=-44760.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=37648, regioncalls=184734, ndraw=128, logz=-40813.38, remainder_fraction=100.0000%, Lmin=-40791.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=37690, regioncalls=184862, ndraw=128, logz=-36953.24, remainder_fraction=100.0000%, Lmin=-36939.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2470, ncalls=37690, regioncalls=184862, ndraw=128, logz=-32240.95, remainder_fraction=100.0000%, Lmin=-32213.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2661, ncalls=37715, regioncalls=184990, ndraw=128, logz=-28632.75, remainder_fraction=100.0000%, Lmin=-28561.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2814, ncalls=37740, regioncalls=185118, ndraw=128, logz=-25654.65, remainder_fraction=100.0000%, Lmin=-25635.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=37740, regioncalls=185118, ndraw=128, logz=-25635.91, remainder_fraction=100.0000%, Lmin=-25623.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2912, ncalls=37759, regioncalls=185246, ndraw=128, logz=-23981.67, remainder_fraction=100.0000%, Lmin=-23963.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=37783, regioncalls=185374, ndraw=128, logz=-22378.23, remainder_fraction=100.0000%, Lmin=-22366.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=37783, regioncalls=185374, ndraw=128, logz=-22028.21, remainder_fraction=100.0000%, Lmin=-22007.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=37808, regioncalls=185502, ndraw=128, logz=-20442.70, remainder_fraction=100.0000%, Lmin=-20426.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=37829, regioncalls=185630, ndraw=128, logz=-17754.62, remainder_fraction=100.0000%, Lmin=-17736.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3529, ncalls=37847, regioncalls=185758, ndraw=128, logz=-15901.51, remainder_fraction=100.0000%, Lmin=-15887.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3715, ncalls=37862, regioncalls=185886, ndraw=128, logz=-14039.63, remainder_fraction=100.0000%, Lmin=-14029.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=37877, regioncalls=186014, ndraw=128, logz=-12807.13, remainder_fraction=100.0000%, Lmin=-12795.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3876, ncalls=37885, regioncalls=186142, ndraw=128, logz=-12574.92, remainder_fraction=100.0000%, Lmin=-12559.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3936, ncalls=37893, regioncalls=186270, ndraw=128, logz=-12144.28, remainder_fraction=100.0000%, Lmin=-12127.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4096, ncalls=37914, regioncalls=186398, ndraw=128, logz=-10989.99, remainder_fraction=100.0000%, Lmin=-10975.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4231, ncalls=37929, regioncalls=186526, ndraw=128, logz=-10144.50, remainder_fraction=100.0000%, Lmin=-10132.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4352, ncalls=37957, regioncalls=186910, ndraw=128, logz=-9343.82, remainder_fraction=100.0000%, Lmin=-9327.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=37981, regioncalls=187294, ndraw=128, logz=-8430.92, remainder_fraction=100.0000%, Lmin=-8414.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4576, ncalls=37993, regioncalls=187422, ndraw=128, logz=-8123.95, remainder_fraction=100.0000%, Lmin=-8113.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4756, ncalls=38028, regioncalls=187934, ndraw=128, logz=-7196.05, remainder_fraction=100.0000%, Lmin=-7180.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4922, ncalls=38045, regioncalls=188318, ndraw=128, logz=-6485.35, remainder_fraction=100.0000%, Lmin=-6474.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5103, ncalls=38067, regioncalls=188702, ndraw=128, logz=-5765.25, remainder_fraction=100.0000%, Lmin=-5748.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5269, ncalls=38085, regioncalls=189342, ndraw=128, logz=-5099.27, remainder_fraction=100.0000%, Lmin=-5086.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=38085, regioncalls=189342, ndraw=128, logz=-5060.95, remainder_fraction=100.0000%, Lmin=-5045.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5466, ncalls=38106, regioncalls=189854, ndraw=128, logz=-4514.48, remainder_fraction=100.0000%, Lmin=-4502.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5634, ncalls=38129, regioncalls=190622, ndraw=128, logz=-4072.94, remainder_fraction=100.0000%, Lmin=-4061.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5819, ncalls=38146, regioncalls=191262, ndraw=128, logz=-3596.91, remainder_fraction=100.0000%, Lmin=-3584.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5983, ncalls=38165, regioncalls=192030, ndraw=128, logz=-3272.55, remainder_fraction=100.0000%, Lmin=-3260.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=38177, regioncalls=192414, ndraw=128, logz=-3147.20, remainder_fraction=100.0000%, Lmin=-3135.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6241, ncalls=38203, regioncalls=193310, ndraw=128, logz=-2762.69, remainder_fraction=100.0000%, Lmin=-2751.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6327, ncalls=38220, regioncalls=193694, ndraw=128, logz=-2629.08, remainder_fraction=100.0000%, Lmin=-2618.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6464, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2380.46, remainder_fraction=100.0000%, Lmin=-2367.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2144.78, remainder_fraction=100.0000%, Lmin=-2132.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6676, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2088.96, remainder_fraction=100.0000%, Lmin=-2076.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1955.11, remainder_fraction=100.0000%, Lmin=-1941.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1815.59, remainder_fraction=100.0000%, Lmin=-1804.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7020, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1655.30, remainder_fraction=100.0000%, Lmin=-1643.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7201, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1475.64, remainder_fraction=100.0000%, Lmin=-1463.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7328, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1365.72, remainder_fraction=100.0000%, Lmin=-1353.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7366, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1332.19, remainder_fraction=100.0000%, Lmin=-1319.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7392, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1308.19, remainder_fraction=100.0000%, Lmin=-1296.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1242.10, remainder_fraction=100.0000%, Lmin=-1230.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7515, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1217.30, remainder_fraction=100.0000%, Lmin=-1205.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7706, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1080.47, remainder_fraction=100.0000%, Lmin=-1067.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7815, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1007.59, remainder_fraction=100.0000%, Lmin=-995.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7872, ncalls=38490, regioncalls=195230, ndraw=128, logz=-970.25, remainder_fraction=100.0000%, Lmin=-957.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8080, ncalls=38620, regioncalls=195742, ndraw=128, logz=-855.79, remainder_fraction=100.0000%, Lmin=-842.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8159, ncalls=38620, regioncalls=195742, ndraw=128, logz=-807.82, remainder_fraction=100.0000%, Lmin=-796.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8348, ncalls=38620, regioncalls=195742, ndraw=128, logz=-724.70, remainder_fraction=100.0000%, Lmin=-712.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8503, ncalls=38620, regioncalls=195742, ndraw=128, logz=-658.07, remainder_fraction=100.0000%, Lmin=-646.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8698, ncalls=38620, regioncalls=195742, ndraw=128, logz=-586.95, remainder_fraction=100.0000%, Lmin=-575.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8832, ncalls=38620, regioncalls=195742, ndraw=128, logz=-537.89, remainder_fraction=100.0000%, Lmin=-524.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8865, ncalls=38620, regioncalls=195742, ndraw=128, logz=-522.17, remainder_fraction=100.0000%, Lmin=-510.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9054, ncalls=38748, regioncalls=196126, ndraw=128, logz=-461.89, remainder_fraction=100.0000%, Lmin=-449.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9224, ncalls=38748, regioncalls=196126, ndraw=128, logz=-413.98, remainder_fraction=100.0000%, Lmin=-401.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9248, ncalls=38748, regioncalls=196126, ndraw=128, logz=-408.92, remainder_fraction=100.0000%, Lmin=-397.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9376, ncalls=38748, regioncalls=196126, ndraw=128, logz=-376.26, remainder_fraction=100.0000%, Lmin=-364.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9572, ncalls=38748, regioncalls=196126, ndraw=128, logz=-334.76, remainder_fraction=100.0000%, Lmin=-322.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9758, ncalls=38876, regioncalls=196382, ndraw=128, logz=-298.76, remainder_fraction=100.0000%, Lmin=-286.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9919, ncalls=38876, regioncalls=196382, ndraw=128, logz=-267.78, remainder_fraction=100.0000%, Lmin=-255.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9984, ncalls=38876, regioncalls=196382, ndraw=128, logz=-256.46, remainder_fraction=100.0000%, Lmin=-244.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=38876, regioncalls=196382, ndraw=128, logz=-239.70, remainder_fraction=100.0000%, Lmin=-227.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10125, ncalls=38876, regioncalls=196382, ndraw=128, logz=-233.28, remainder_fraction=100.0000%, Lmin=-221.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=38876, regioncalls=196382, ndraw=128, logz=-220.01, remainder_fraction=100.0000%, Lmin=-208.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10401, ncalls=39004, regioncalls=196766, ndraw=128, logz=-196.41, remainder_fraction=100.0000%, Lmin=-184.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10471, ncalls=39004, regioncalls=196766, ndraw=128, logz=-188.68, remainder_fraction=100.0000%, Lmin=-176.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10536, ncalls=39004, regioncalls=196766, ndraw=128, logz=-182.37, remainder_fraction=100.0000%, Lmin=-170.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10725, ncalls=39004, regioncalls=196766, ndraw=128, logz=-163.77, remainder_fraction=100.0000%, Lmin=-151.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=39004, regioncalls=196766, ndraw=128, logz=-161.56, remainder_fraction=100.0000%, Lmin=-150.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10898, ncalls=39004, regioncalls=196766, ndraw=128, logz=-148.42, remainder_fraction=100.0000%, Lmin=-136.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11089, ncalls=39132, regioncalls=197022, ndraw=128, logz=-132.84, remainder_fraction=100.0000%, Lmin=-121.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11169, ncalls=39132, regioncalls=197022, ndraw=128, logz=-127.12, remainder_fraction=100.0000%, Lmin=-115.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11209, ncalls=39132, regioncalls=197022, ndraw=128, logz=-123.83, remainder_fraction=100.0000%, Lmin=-111.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11279, ncalls=39132, regioncalls=197022, ndraw=128, logz=-119.24, remainder_fraction=100.0000%, Lmin=-107.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11288, ncalls=39132, regioncalls=197022, ndraw=128, logz=-118.64, remainder_fraction=100.0000%, Lmin=-106.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11364, ncalls=39132, regioncalls=197022, ndraw=128, logz=-112.19, remainder_fraction=100.0000%, Lmin=-100.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11423, ncalls=39132, regioncalls=197022, ndraw=128, logz=-107.95, remainder_fraction=100.0000%, Lmin=-95.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11455, ncalls=39132, regioncalls=197022, ndraw=128, logz=-105.87, remainder_fraction=100.0000%, Lmin=-93.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11518, ncalls=39132, regioncalls=197022, ndraw=128, logz=-102.53, remainder_fraction=100.0000%, Lmin=-90.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11648, ncalls=39132, regioncalls=197022, ndraw=128, logz=-95.45, remainder_fraction=100.0000%, Lmin=-83.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11680, ncalls=39132, regioncalls=197022, ndraw=128, logz=-93.92, remainder_fraction=100.0000%, Lmin=-82.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11865, ncalls=39260, regioncalls=197278, ndraw=128, logz=-84.74, remainder_fraction=100.0000%, Lmin=-72.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11950, ncalls=39260, regioncalls=197278, ndraw=128, logz=-81.31, remainder_fraction=100.0000%, Lmin=-69.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11999, ncalls=39260, regioncalls=197278, ndraw=128, logz=-79.19, remainder_fraction=100.0000%, Lmin=-67.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12094, ncalls=39260, regioncalls=197278, ndraw=128, logz=-75.61, remainder_fraction=100.0000%, Lmin=-63.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12133, ncalls=39260, regioncalls=197278, ndraw=128, logz=-74.26, remainder_fraction=100.0000%, Lmin=-62.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12321, ncalls=39260, regioncalls=197278, ndraw=128, logz=-67.29, remainder_fraction=100.0000%, Lmin=-55.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12384, ncalls=39260, regioncalls=197278, ndraw=128, logz=-64.95, remainder_fraction=100.0000%, Lmin=-52.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12437, ncalls=39260, regioncalls=197278, ndraw=128, logz=-63.04, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12480, ncalls=39388, regioncalls=197790, ndraw=128, logz=-61.55, remainder_fraction=100.0000%, Lmin=-49.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12488, ncalls=39388, regioncalls=197790, ndraw=128, logz=-61.26, remainder_fraction=100.0000%, Lmin=-49.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12512, ncalls=39388, regioncalls=197790, ndraw=128, logz=-60.46, remainder_fraction=100.0000%, Lmin=-48.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12554, ncalls=39388, regioncalls=197790, ndraw=128, logz=-59.03, remainder_fraction=100.0000%, Lmin=-46.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12578, ncalls=39388, regioncalls=197790, ndraw=128, logz=-58.29, remainder_fraction=100.0000%, Lmin=-46.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12606, ncalls=39388, regioncalls=197790, ndraw=128, logz=-57.44, remainder_fraction=100.0000%, Lmin=-45.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12640, ncalls=39388, regioncalls=197790, ndraw=128, logz=-56.44, remainder_fraction=100.0000%, Lmin=-44.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12672, ncalls=39388, regioncalls=197790, ndraw=128, logz=-55.48, remainder_fraction=100.0000%, Lmin=-43.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12828, ncalls=39388, regioncalls=197790, ndraw=128, logz=-51.09, remainder_fraction=100.0000%, Lmin=-38.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12852, ncalls=39388, regioncalls=197790, ndraw=128, logz=-50.41, remainder_fraction=100.0000%, Lmin=-38.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12897, ncalls=39388, regioncalls=197790, ndraw=128, logz=-49.13, remainder_fraction=100.0000%, Lmin=-37.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13024, ncalls=39388, regioncalls=197790, ndraw=128, logz=-46.02, remainder_fraction=100.0000%, Lmin=-34.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13042, ncalls=39388, regioncalls=197790, ndraw=128, logz=-45.63, remainder_fraction=100.0000%, Lmin=-33.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13128, ncalls=39388, regioncalls=197790, ndraw=128, logz=-43.84, remainder_fraction=100.0000%, Lmin=-32.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13152, ncalls=39388, regioncalls=197790, ndraw=128, logz=-43.42, remainder_fraction=100.0000%, Lmin=-31.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13209, ncalls=39388, regioncalls=197790, ndraw=128, logz=-42.34, remainder_fraction=100.0000%, Lmin=-30.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13280, ncalls=39388, regioncalls=197790, ndraw=128, logz=-40.85, remainder_fraction=100.0000%, Lmin=-28.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13333, ncalls=39516, regioncalls=198046, ndraw=128, logz=-39.79, remainder_fraction=100.0000%, Lmin=-27.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13354, ncalls=39516, regioncalls=198046, ndraw=128, logz=-39.35, remainder_fraction=100.0000%, Lmin=-27.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13375, ncalls=39516, regioncalls=198046, ndraw=128, logz=-38.95, remainder_fraction=100.0000%, Lmin=-26.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13421, ncalls=39516, regioncalls=198046, ndraw=128, logz=-38.08, remainder_fraction=100.0000%, Lmin=-25.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13471, ncalls=39516, regioncalls=198046, ndraw=128, logz=-37.17, remainder_fraction=100.0000%, Lmin=-25.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13504, ncalls=39516, regioncalls=198046, ndraw=128, logz=-36.60, remainder_fraction=100.0000%, Lmin=-24.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13562, ncalls=39516, regioncalls=198046, ndraw=128, logz=-35.71, remainder_fraction=100.0000%, Lmin=-23.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13594, ncalls=39516, regioncalls=198046, ndraw=128, logz=-35.26, remainder_fraction=100.0000%, Lmin=-23.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13711, ncalls=39516, regioncalls=198046, ndraw=128, logz=-33.45, remainder_fraction=100.0000%, Lmin=-21.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13730, ncalls=39516, regioncalls=198046, ndraw=128, logz=-33.20, remainder_fraction=100.0000%, Lmin=-21.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13757, ncalls=39516, regioncalls=198046, ndraw=128, logz=-32.83, remainder_fraction=100.0000%, Lmin=-20.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13760, ncalls=39516, regioncalls=198046, ndraw=128, logz=-32.78, remainder_fraction=100.0000%, Lmin=-20.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13888, ncalls=39516, regioncalls=198046, ndraw=128, logz=-31.06, remainder_fraction=100.0000%, Lmin=-19.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13973, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.99, remainder_fraction=100.0000%, Lmin=-18.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13984, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.86, remainder_fraction=100.0000%, Lmin=-17.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14016, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.50, remainder_fraction=100.0000%, Lmin=-17.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14040, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.23, remainder_fraction=100.0000%, Lmin=-17.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14054, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.08, remainder_fraction=100.0000%, Lmin=-17.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14080, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.81, remainder_fraction=100.0000%, Lmin=-16.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14142, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.19, remainder_fraction=100.0000%, Lmin=-16.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14153, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.08, remainder_fraction=100.0000%, Lmin=-16.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14168, ncalls=39516, regioncalls=198046, ndraw=128, logz=-27.93, remainder_fraction=100.0000%, Lmin=-15.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14175, ncalls=39516, regioncalls=198046, ndraw=128, logz=-27.86, remainder_fraction=100.0000%, Lmin=-15.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14196, ncalls=39644, regioncalls=198302, ndraw=128, logz=-27.65, remainder_fraction=100.0000%, Lmin=-15.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14208, ncalls=39644, regioncalls=198302, ndraw=128, logz=-27.53, remainder_fraction=100.0000%, Lmin=-15.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14301, ncalls=39644, regioncalls=198302, ndraw=128, logz=-26.59, remainder_fraction=100.0000%, Lmin=-14.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14307, ncalls=39644, regioncalls=198302, ndraw=128, logz=-26.53, remainder_fraction=100.0000%, Lmin=-14.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14400, ncalls=39644, regioncalls=198302, ndraw=128, logz=-25.69, remainder_fraction=99.9999%, Lmin=-13.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14449, ncalls=39644, regioncalls=198302, ndraw=128, logz=-25.29, remainder_fraction=99.9998%, Lmin=-13.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14522, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.69, remainder_fraction=99.9997%, Lmin=-12.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14528, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.64, remainder_fraction=99.9997%, Lmin=-12.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14568, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.29, remainder_fraction=99.9995%, Lmin=-12.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14597, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.04, remainder_fraction=99.9994%, Lmin=-11.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14607, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.95, remainder_fraction=99.9994%, Lmin=-11.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14683, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.34, remainder_fraction=99.9988%, Lmin=-11.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14689, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.30, remainder_fraction=99.9988%, Lmin=-11.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14704, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.19, remainder_fraction=99.9986%, Lmin=-11.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14722, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.06, remainder_fraction=99.9985%, Lmin=-11.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14745, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.90, remainder_fraction=99.9982%, Lmin=-10.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14777, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.68, remainder_fraction=99.9977%, Lmin=-10.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14829, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.33, remainder_fraction=99.9968%, Lmin=-10.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14850, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.19, remainder_fraction=99.9963%, Lmin=-10.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14871, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.05, remainder_fraction=99.9957%, Lmin=-10.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15031, ncalls=39772, regioncalls=198558, ndraw=128, logz=-21.02, remainder_fraction=99.9878%, Lmin=-9.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15225, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.91, remainder_fraction=99.9632%, Lmin=-7.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15360, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.20, remainder_fraction=99.9237%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15382, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.10, remainder_fraction=99.9159%, Lmin=-7.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15456, ncalls=39772, regioncalls=198558, ndraw=128, logz=-18.78, remainder_fraction=99.8843%, Lmin=-6.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15520, ncalls=39772, regioncalls=198558, ndraw=128, logz=-18.51, remainder_fraction=99.8491%, Lmin=-6.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15741, ncalls=39772, regioncalls=198558, ndraw=128, logz=-17.70, remainder_fraction=99.6623%, Lmin=-5.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15934, ncalls=39900, regioncalls=198942, ndraw=128, logz=-17.08, remainder_fraction=99.3713%, Lmin=-5.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15936, ncalls=39900, regioncalls=198942, ndraw=128, logz=-17.07, remainder_fraction=99.3675%, Lmin=-5.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16086, ncalls=39900, regioncalls=198942, ndraw=128, logz=-16.62, remainder_fraction=99.0149%, Lmin=-4.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16295, ncalls=39900, regioncalls=198942, ndraw=128, logz=-16.05, remainder_fraction=98.3041%, Lmin=-4.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16352, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.90, remainder_fraction=98.0299%, Lmin=-3.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16447, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.67, remainder_fraction=97.5041%, Lmin=-3.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16480, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.59, remainder_fraction=97.3108%, Lmin=-3.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16576, ncalls=40028, regioncalls=199582, ndraw=128, logz=-15.38, remainder_fraction=96.6421%, Lmin=-3.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16704, ncalls=40028, regioncalls=199582, ndraw=128, logz=-15.11, remainder_fraction=95.6073%, Lmin=-3.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16801, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.92, remainder_fraction=94.6685%, Lmin=-2.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16954, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.64, remainder_fraction=92.9563%, Lmin=-2.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17109, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.37, remainder_fraction=90.8881%, Lmin=-2.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17152, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.31, remainder_fraction=90.2332%, Lmin=-2.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17308, ncalls=40156, regioncalls=200094, ndraw=128, logz=-14.08, remainder_fraction=87.7145%, Lmin=-2.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17376, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.98, remainder_fraction=86.5056%, Lmin=-1.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17496, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.83, remainder_fraction=84.3049%, Lmin=-1.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17504, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.82, remainder_fraction=84.1424%, Lmin=-1.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17568, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.75, remainder_fraction=82.9257%, Lmin=-1.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17743, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.55, remainder_fraction=79.3073%, Lmin=-1.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17880, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.42, remainder_fraction=76.2527%, Lmin=-1.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17888, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.41, remainder_fraction=76.0863%, Lmin=-1.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17952, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.35, remainder_fraction=74.6161%, Lmin=-1.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17984, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.32, remainder_fraction=73.8593%, Lmin=-1.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18148, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.19, remainder_fraction=70.0275%, Lmin=-1.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18243, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.11, remainder_fraction=67.7670%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18336, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.05, remainder_fraction=65.4918%, Lmin=-1.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18494, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.94, remainder_fraction=61.7598%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18591, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.89, remainder_fraction=59.4928%, Lmin=-0.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18624, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.87, remainder_fraction=58.7285%, Lmin=-0.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18771, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.79, remainder_fraction=55.3808%, Lmin=-0.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18950, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.70, remainder_fraction=51.2947%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19107, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.63, remainder_fraction=47.7864%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19264, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.57, remainder_fraction=44.3957%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19297, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.55, remainder_fraction=43.6924%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19328, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.54, remainder_fraction=43.0323%, Lmin=-0.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19474, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.49, remainder_fraction=40.0065%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19628, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.44, remainder_fraction=37.0154%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19651, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.44, remainder_fraction=36.5739%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19776, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.40, remainder_fraction=34.3001%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19808, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.39, remainder_fraction=33.7389%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19840, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.38, remainder_fraction=33.1966%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20009, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.34, remainder_fraction=30.3599%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20166, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.31, remainder_fraction=27.9244%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20224, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.29, remainder_fraction=27.0625%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20366, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.27, remainder_fraction=25.0157%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20531, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.24, remainder_fraction=22.7737%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20544, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.24, remainder_fraction=22.6061%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20576, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.23, remainder_fraction=22.2002%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20640, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.22, remainder_fraction=21.3984%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20722, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.21, remainder_fraction=20.4114%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20800, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.20, remainder_fraction=19.5170%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20973, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.17, remainder_fraction=17.6382%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21076, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.16, remainder_fraction=16.5963%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21152, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.15, remainder_fraction=15.8720%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21184, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.15, remainder_fraction=15.5739%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21342, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.13, remainder_fraction=14.1631%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21421, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.12, remainder_fraction=13.5018%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21579, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.11, remainder_fraction=12.2687%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21600, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.11, remainder_fraction=12.1134%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21753, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.10, remainder_fraction=11.0325%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21789, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.09, remainder_fraction=10.7911%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21856, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.09, remainder_fraction=10.3564%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22003, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.08, remainder_fraction=9.4650%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22048, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.08, remainder_fraction=9.2068%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22080, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.07, remainder_fraction=9.0250%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22148, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.07, remainder_fraction=8.6553%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22360, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.06, remainder_fraction=7.5826%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22400, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.06, remainder_fraction=7.3958%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22495, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.05, remainder_fraction=6.9702%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22652, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=6.3151%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22807, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.7283%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22816, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.6958%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22844, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.5962%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22944, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.03, remainder_fraction=5.2532%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23097, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.03, remainder_fraction=4.7695%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23104, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.03, remainder_fraction=4.7486%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23198, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=4.4739%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23371, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=4.0074%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23488, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=3.7199%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23545, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=3.5870%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23616, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.01, remainder_fraction=3.4284%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23787, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=3.0737%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23889, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=2.8795%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23904, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=2.8520%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24069, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.5657%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24223, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.3245%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24234, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.3081%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24256, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.2758%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24320, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.1842%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24474, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.9784%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24581, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.8467%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24746, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.6606%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24768, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.6372%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24931, ncalls=41436, regioncalls=203038, ndraw=128, logz=-11.99, remainder_fraction=1.4741%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25090, ncalls=41436, regioncalls=203038, ndraw=128, logz=-11.99, remainder_fraction=1.3304%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25216, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.2265%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25290, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.1693%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25440, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0613%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25472, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0396%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25504, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0183%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 41564 INFO ultranest:integrator.py:2697 logZ = -11.97 +- 0.06439 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 6150.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1665 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (20029/20329 iterations) have 1538 DEBUG ultranest:integrator.py:1663 at least 384 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 384 minimum live points (dlogz from 0.05 to 0.17, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.16 bs:0.06 tail:0.01 total:0.06 required:<0.10
Passed	tests/test_popstepsampling.py::test_direction_proposals	0.64
[gw6] linux -- Python 3.10.6 /usr/bin/python3 [gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.AffineLayer'> test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.MLFriends'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.RobustEllipsoidRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_cube_oriented_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_random_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_oriented_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'> test of proposal: <built-in function generate_region_random_direction> with region: <class 'ultranest.mlfriends.SimpleRegion'> layer: <class 'ultranest.mlfriends.ScalingLayer'>
Passed	tests/test_run.py::test_run_resume[0.5]	12.77
[gw6] linux -- Python 3.10.6 /usr/bin/python3 [gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.31) * Expected Volume: exp(0.00) Quality: ok a: +0.000\|*******************************************************\| +1.000 Z=-inf(0.00%) \| Like=-1229.24..3.69 [-1229.2436..-284.2420] \| it/evals=0/528 eff=0.0000% N=400 Z=-947.8(0.00%) \| Like=-936.03..3.69 [-1229.2436..-284.2420] \| it/evals=50/528 eff=39.0625% N=400 Mono-modal Volume: ~exp(-4.46) Expected Volume: exp(-0.23) Quality: ok a: +0.0\| ****************************************** \| +1.0 Z=-794.7(0.00%) \| Like=-767.63..3.69 [-1229.2436..-284.2420] \| it/evals=90/528 eff=70.3125% N=400 Z=-744.3(0.00%) \| Like=-735.03..3.69 [-1229.2436..-284.2420] \| it/evals=100/528 eff=78.1250% N=400 Z=-722.4(0.00%) \| Like=-710.95..3.69 [-1229.2436..-284.2420] \| it/evals=105/635 eff=44.6809% N=400 Z=-573.7(0.00%) \| Like=-562.58..3.69 [-1229.2436..-284.2420] \| it/evals=150/635 eff=63.8298% N=400 Mono-modal Volume: ~exp(-4.46) Expected Volume: exp(-0.45) Quality: ok a: +0.0\| ********************************** +0.8 \| +1.0 Z=-436.3(0.00%) \| Like=-427.78..3.69 [-1229.2436..-284.2420] \| it/evals=200/711 eff=64.3087% N=400 Z=-342.3(0.00%) \| Like=-335.76..3.69 [-1229.2436..-284.2420] \| it/evals=250/711 eff=80.3859% N=400 Mono-modal Volume: ~exp(-4.84) * Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.3 ************************** +0.7 \| +1.0 Z=-312.3(0.00%) \| Like=-306.34..3.69 [-1229.2436..-284.2420] \| it/evals=270/780 eff=71.0526% N=400 Z=-277.8(0.00%) \| Like=-269.37..3.69 [-282.2298..-67.3700] \| it/evals=300/780 eff=78.9474% N=400 Z=-232.0(0.00%) \| Like=-223.10..3.69 [-282.2298..-67.3700] \| it/evals=338/829 eff=78.7879% N=400 Z=-224.0(0.00%) \| Like=-217.57..3.69 [-282.2298..-67.3700] \| it/evals=350/829 eff=81.5851% N=400 Mono-modal Volume: ~exp(-4.84) Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ********************** +0.7 \| +1.0 Z=-174.1(0.00%) \| Like=-164.34..3.69 [-282.2298..-67.3700] \| it/evals=400/877 eff=83.8574% N=400 Mono-modal Volume: ~exp(-5.14) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 ******************** +0.7 \| +1.0 Z=-139.6(0.00%) \| Like=-130.59..3.69 [-282.2298..-67.3700] \| it/evals=450/922 eff=86.2069% N=400 Z=-110.7(0.00%) \| Like=-103.90..3.69 [-282.2298..-67.3700] \| it/evals=500/964 eff=88.6525% N=400 Mono-modal Volume: ~exp(-5.61) * Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 **************** +0.6 \| +1.0 Z=-90.3(0.00%) \| Like=-83.12..3.69 [-282.2298..-67.3700] \| it/evals=540/1002 eff=89.7010% N=400 Z=-84.0(0.00%) \| Like=-76.16..3.69 [-282.2298..-67.3700] \| it/evals=550/1043 eff=85.5365% N=400 Z=-69.0(0.00%) \| Like=-63.34..3.69 [-67.2945..-16.1658] \| it/evals=600/1070 eff=89.5522% N=400 Have 2 modes Volume: ~exp(-5.83) * Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 11111111111122 +0.6 \| +1.0 Z=-62.3(0.00%) \| Like=-56.62..3.69 [-67.2945..-16.1658] \| it/evals=630/1104 eff=89.4886% N=400 Z=-57.4(0.00%) \| Like=-51.00..3.69 [-67.2945..-16.1658] \| it/evals=650/1131 eff=88.9193% N=400 Z=-44.8(0.00%) \| Like=-38.45..3.69 [-67.2945..-16.1658] \| it/evals=700/1175 eff=90.3226% N=400 Mono-modal Volume: ~exp(-6.01) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-40.3(0.00%) \| Like=-34.53..3.69 [-67.2945..-16.1658] \| it/evals=720/1196 eff=90.4523% N=400 Z=-36.3(0.00%) \| Like=-30.32..3.69 [-67.2945..-16.1658] \| it/evals=750/1236 eff=89.7129% N=400 Z=-28.4(0.00%) \| Like=-22.50..3.69 [-67.2945..-16.1658] \| it/evals=800/1287 eff=90.1917% N=400 Mono-modal Volume: ~exp(-6.12) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-27.1(0.00%) \| Like=-21.15..3.69 [-67.2945..-16.1658] \| it/evals=810/1287 eff=91.3191% N=400 Z=-23.0(0.00%) \| Like=-17.36..3.69 [-67.2945..-16.1658] \| it/evals=850/1332 eff=91.2017% N=400 Mono-modal Volume: ~exp(-6.50) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-18.9(0.00%) \| Like=-13.36..3.69 [-16.1569..-1.6640] \| it/evals=900/1385 eff=91.3706% N=400 Z=-15.5(0.00%) \| Like=-10.11..3.69 [-16.1569..-1.6640] \| it/evals=950/1437 eff=91.6104% N=400 Have 2 modes Volume: ~exp(-6.53) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.45 222211 +0.55 \| +1.00 Z=-13.2(0.00%) \| Like=-7.53..3.69 [-16.1569..-1.6640] \| it/evals=990/1477 eff=91.9220% N=400 Z=-12.6(0.00%) \| Like=-7.06..3.69 [-16.1569..-1.6640] \| it/evals=1000/1500 eff=90.9091% N=400 Z=-10.2(0.00%) \| Like=-4.66..3.69 [-16.1569..-1.6640] \| it/evals=1050/1546 eff=91.6230% N=400 Have 2 modes Volume: ~exp(-6.53) Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.46 222211 +0.54 \| +1.00 Z=-8.6(0.02%) \| Like=-3.29..3.69 [-16.1569..-1.6640] \| it/evals=1093/1596 eff=91.3880% N=400 Z=-8.4(0.02%) \| Like=-3.02..3.69 [-16.1569..-1.6640] \| it/evals=1100/1596 eff=91.9732% N=400 Z=-6.8(0.13%) \| Like=-1.40..3.69 [-1.6514..1.3709] \| it/evals=1150/1649 eff=92.0737% N=400 Mono-modal Volume: ~exp(-6.85) * Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 **** +0.53 \| +1.00 Z=-6.2(0.22%) \| Like=-0.98..3.69 [-1.6514..1.3709] \| it/evals=1170/1672 eff=91.9811% N=400 Z=-5.6(0.43%) \| Like=-0.44..3.69 [-1.6514..1.3709] \| it/evals=1200/1699 eff=92.3788% N=400 Z=-4.7(1.06%) \| Like=0.20..3.69 [-1.6514..1.3709] \| it/evals=1250/1748 eff=92.7300% N=400 Mono-modal Volume: ~exp(-7.05) * Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.47 **** +0.53 \| +1.00 Z=-4.5(1.23%) \| Like=0.50..3.69 [-1.6514..1.3709] \| it/evals=1260/1757 eff=92.8519% N=400 Z=-3.9(2.32%) \| Like=1.22..3.69 [-1.6514..1.3709] \| it/evals=1300/1804 eff=92.5926% N=400 Mono-modal Volume: ~exp(-7.13) * Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 **** +0.52 \| +1.00 Z=-3.2(4.75%) \| Like=1.77..3.69 [1.7333..1.7988] \| it/evals=1350/1850 eff=93.1034% N=400 Z=-2.6(8.16%) \| Like=2.17..3.69 [2.1689..2.1707]\| it/evals=1400/1904 eff=93.0851% N=400 Mono-modal Volume: ~exp(-7.62) Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.3(11.57%) \| Like=2.42..3.69 [2.4219..2.4221]\| it/evals=1440/1947 eff=93.0834% N=400 Z=-2.2(12.55%) \| Like=2.47..3.69 [2.4730..2.4768]\| it/evals=1450/1958 eff=93.0680% N=400 Z=-1.9(17.45%) \| Like=2.75..3.69 [2.7491..2.7498]\| it/evals=1500/2012 eff=93.0521% N=400 Mono-modal Volume: ~exp(-7.88) Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.7(20.74%) \| Like=2.91..3.69 [2.9003..2.9129] \| it/evals=1530/2042 eff=93.1790% N=400 Z=-1.6(23.08%) \| Like=2.98..3.69 [2.9833..2.9849]\| it/evals=1550/2064 eff=93.1490% N=400 Z=-1.4(29.11%) \| Like=3.14..3.69 [3.1391..3.1391]\| it/evals=1600/2114 eff=93.3489% N=400 Mono-modal Volume: ~exp(-7.92) * Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.3(31.53%) \| Like=3.18..3.69 [3.1790..3.1792]\| it/evals=1620/2135 eff=93.3718% N=400 Z=-1.2(35.15%) \| Like=3.26..3.69 [3.2566..3.2569]\| it/evals=1650/2267 eff=88.3771% N=400 Z=-1.0(41.06%) \| Like=3.34..3.69 [3.3424..3.3427]\| it/evals=1700/2267 eff=91.0552% N=400 Mono-modal Volume: ~exp(-8.13) Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.0(42.20%) \| Like=3.36..3.69 [3.3572..3.3583]\| it/evals=1710/2267 eff=91.5908% N=400 Z=-0.9(46.74%) \| Like=3.42..3.69 [3.4174..3.4175]\| it/evals=1750/2278 eff=93.1842% N=400 Mono-modal Volume: ~exp(-8.31) * Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.8(52.11%) \| Like=3.47..3.69 [3.4731..3.4751]\| it/evals=1800/2329 eff=93.3126% N=400 Z=-0.7(54.94%) \| Like=3.50..3.69 [3.5017..3.5026]\| it/evals=1828/2457 eff=88.8673% N=400 Z=-0.7(57.09%) \| Like=3.52..3.69 [3.5250..3.5260]\| it/evals=1850/2457 eff=89.9368% N=400 Mono-modal Volume: ~exp(-8.55) Expected Volume: exp(-4.73) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(60.83%) \| Like=3.55..3.69 [3.5540..3.5540]\| it/evals=1890/2457 eff=91.8814% N=400 Z=-0.6(61.73%) \| Like=3.56..3.69 [3.5611..3.5629]\| it/evals=1900/2457 eff=92.3675% N=400 Z=-0.6(65.92%) \| Like=3.59..3.69 [3.5913..3.5926]\| it/evals=1950/2499 eff=92.9014% N=400 Mono-modal Volume: ~exp(-8.55) Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.5(68.26%) \| Like=3.60..3.69 [3.6037..3.6038]\| it/evals=1980/2526 eff=93.1326% N=400 Z=-0.5(69.72%) \| Like=3.61..3.69 [3.6112..3.6113]\| it/evals=2000/2655 eff=88.6918% N=400 Z=-0.5(73.12%) \| Like=3.63..3.69 [3.6294..3.6295]\| it/evals=2050/2655 eff=90.9091% N=400 Mono-modal Volume: ~exp(-9.02) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.4(74.39%) \| Like=3.64..3.69 [3.6359..3.6360]\| it/evals=2070/2655 eff=91.7960% N=400 Z=-0.4(76.19%) \| Like=3.64..3.69 [3.6438..3.6438]\| it/evals=2100/2666 eff=92.6743% N=400 Z=-0.4(77.21%) \| Like=3.65..3.69 [3.6476..3.6476]\| it/evals=2118/2780 eff=88.9916% N=400 Z=-0.4(78.92%) \| Like=3.65..3.69 [3.6533..3.6534]\| it/evals=2150/2780 eff=90.3361% N=400 Mono-modal Volume: ~exp(-9.25) * Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.4(79.43%) \| Like=3.65..3.69 [3.6544..3.6547]\| it/evals=2160/2780 eff=90.7563% N=400 Z=-0.4(81.35%) \| Like=3.66..3.69 [3.6596..3.6596]\| it/evals=2200/2780 eff=92.4370% N=400 Mono-modal Volume: ~exp(-9.60) * Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.3(83.51%) \| Like=3.66..3.69 [3.6638..3.6638]\| it/evals=2250/2835 eff=92.4025% N=400 Z=-0.3(85.43%) \| Like=3.67..3.69 [3.6691..3.6691]\| it/evals=2300/2887 eff=92.4809% N=400 Mono-modal Volume: ~exp(-9.61) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.3(86.80%) \| Like=3.67..3.69 [3.6717..3.6718]\| it/evals=2340/2931 eff=92.4536% N=400 Z=-0.3(87.12%) \| Like=3.67..3.69 [3.6725..3.6726]\| it/evals=2350/2940 eff=92.5197% N=400 Z=-0.3(88.62%) \| Like=3.68..3.69 [3.6752..3.6753]\| it/evals=2400/2994 eff=92.5212% N=400 Mono-modal Volume: ~exp(-10.21) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.3(89.44%) \| Like=3.68..3.69 [3.6771..3.6771]\| it/evals=2430/3029 eff=92.4306% N=400 Z=-0.2(89.95%) \| Like=3.68..3.69 [3.6780..3.6780]\| it/evals=2450/3148 eff=89.1557% N=400 Z=-0.2(91.13%) \| Like=3.68..3.69 [3.6802..3.6802]\| it/evals=2500/3148 eff=90.9753% N=400 Have 2 modes Volume: ~exp(-10.22) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 11 +0.501 \| +1.000 Z=-0.2(91.56%) \| Like=3.68..3.69 [3.6807..3.6807]\| it/evals=2520/3148 eff=91.7031% N=400 Z=-0.2(92.16%) \| Like=3.68..3.69 [3.6815..3.6815]\| it/evals=2550/3273 eff=88.7574% N=400 Z=-0.2(93.08%) \| Like=3.68..3.69 [3.6826..3.6826]\| it/evals=2600/3273 eff=90.4977% N=400 Have 2 modes Volume: ~exp(-10.57) Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 11 +0.501 \| +1.000 Z=-0.2(93.25%) \| Like=3.68..3.69 [3.6827..3.6827]\| it/evals=2610/3273 eff=90.8458% N=400 Z=-0.2(93.89%) \| Like=3.68..3.69 [3.6836..3.6836]\| it/evals=2650/3383 eff=88.8367% N=400 Mono-modal Volume: ~exp(-10.92) * Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.2(94.61%) \| Like=3.68..3.69 [3.6842..3.6842]\| it/evals=2700/3383 eff=90.5129% N=400 Z=-0.2(95.02%) \| Like=3.68..3.69 [3.6845..3.6845]\| it/evals=2732/3503 eff=88.0438% N=400 Z=-0.2(95.24%) \| Like=3.68..3.69 [3.6847..3.6847]\| it/evals=2750/3503 eff=88.6239% N=400 Mono-modal Volume: ~exp(-11.05) Expected Volume: exp(-6.98) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.2(95.70%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2790/3503 eff=89.9130% N=400 Z=-0.2(95.80%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2800/3503 eff=90.2353% N=400 Z=-0.2(96.16%) \| Like=3.69..3.69 [3.6851..3.6852]\| it/evals=2836/3625 eff=87.9380% N=400 Z=-0.2(96.29%) \| Like=3.69..3.69 [3.6852..3.6852]\| it/evals=2850/3625 eff=88.3721% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3625 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.1303 +- 0.07431 [ultranest] Effective samples strategy satisfied (ESS = 1253.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.08, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.04 total:0.08 required:<0.50 [ultranest] done iterating. logZ = -0.144 +- 0.183 single instance: logZ = -0.144 +- 0.092 bootstrapped : logZ = -0.130 +- 0.180 tail : logZ = +- 0.036 insert order U test : converged: True correlation: inf iterations a : 0.4621│ ▁▁▁▁▁▁▁▁▁▂▃▃▅▅▆▆▇▇▇▇▆▅▅▄▃▂▃▂▁▁▁▁▁▁▁ ▁ │0.5400 0.4999 +- 0.0100 [ultranest] Resuming from 3528 stored points Mono-modal Volume: ~exp(-4.24) * Expected Volume: exp(0.00) Quality: ok a: +0.000\|*******************************************************\| +1.000 Z=-inf(0.00%) \| Like=-1229.24..3.69 [-1229.2436..-284.2420] \| it/evals=0/3625 eff=inf% N=400 Z=-947.8(0.00%) \| Like=-936.03..3.69 [-1229.2436..-284.2420] \| it/evals=50/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.23) Quality: ok a: +0.0\| ****************************************** \| +1.0 Z=-794.7(0.00%) \| Like=-767.63..3.69 [-1229.2436..-284.2420] \| it/evals=90/3625 eff=inf% N=400 Z=-744.3(0.00%) \| Like=-735.03..3.69 [-1229.2436..-284.2420] \| it/evals=100/3625 eff=inf% N=400 Z=-573.7(0.00%) \| Like=-562.58..3.69 [-1229.2436..-284.2420] \| it/evals=150/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.45) Quality: ok a: +0.0\| ********************************** +0.8 \| +1.0 Z=-436.3(0.00%) \| Like=-427.78..3.69 [-1229.2436..-284.2420] \| it/evals=200/3625 eff=inf% N=400 Z=-342.3(0.00%) \| Like=-335.76..3.69 [-1229.2436..-284.2420] \| it/evals=250/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-4.84) * Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.3 ************************** +0.7 \| +1.0 Z=-312.3(0.00%) \| Like=-306.34..3.69 [-1229.2436..-284.2420] \| it/evals=270/3625 eff=inf% N=400 Z=-277.8(0.00%) \| Like=-269.37..3.69 [-282.2298..-67.3700] \| it/evals=300/3625 eff=inf% N=400 Z=-224.0(0.00%) \| Like=-217.57..3.69 [-282.2298..-67.3700] \| it/evals=350/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-4.84) Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ********************** +0.7 \| +1.0 Z=-174.1(0.00%) \| Like=-164.34..3.69 [-282.2298..-67.3700] \| it/evals=400/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-5.21) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 ******************** +0.7 \| +1.0 Z=-139.6(0.00%) \| Like=-130.59..3.69 [-282.2298..-67.3700] \| it/evals=450/3625 eff=inf% N=400 Z=-110.7(0.00%) \| Like=-103.90..3.69 [-282.2298..-67.3700] \| it/evals=500/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-5.34) * Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 **************** +0.6 \| +1.0 Z=-90.3(0.00%) \| Like=-83.12..3.69 [-282.2298..-67.3700] \| it/evals=540/3625 eff=inf% N=400 Z=-84.0(0.00%) \| Like=-76.16..3.69 [-282.2298..-67.3700] \| it/evals=550/3625 eff=inf% N=400 Z=-69.0(0.00%) \| Like=-63.34..3.69 [-67.2945..-16.1658] \| it/evals=600/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-5.57) * Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 ************** +0.6 \| +1.0 Z=-62.3(0.00%) \| Like=-56.62..3.69 [-67.2945..-16.1658] \| it/evals=630/3625 eff=inf% N=400 Z=-57.4(0.00%) \| Like=-51.00..3.69 [-67.2945..-16.1658] \| it/evals=650/3625 eff=inf% N=400 Z=-44.8(0.00%) \| Like=-38.45..3.69 [-67.2945..-16.1658] \| it/evals=700/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-5.90) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-40.3(0.00%) \| Like=-34.53..3.69 [-67.2945..-16.1658] \| it/evals=720/3625 eff=inf% N=400 Z=-36.3(0.00%) \| Like=-30.32..3.69 [-67.2945..-16.1658] \| it/evals=750/3625 eff=inf% N=400 Z=-28.4(0.00%) \| Like=-22.50..3.69 [-67.2945..-16.1658] \| it/evals=800/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-5.95) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-27.1(0.00%) \| Like=-21.15..3.69 [-67.2945..-16.1658] \| it/evals=810/3625 eff=inf% N=400 Z=-23.0(0.00%) \| Like=-17.36..3.69 [-67.2945..-16.1658] \| it/evals=850/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-6.15) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-18.9(0.00%) \| Like=-13.36..3.69 [-16.1569..-1.6640] \| it/evals=900/3625 eff=inf% N=400 Z=-15.5(0.00%) \| Like=-10.11..3.69 [-16.1569..-1.6640] \| it/evals=950/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-6.28) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.45 ****** +0.55 \| +1.00 Z=-13.2(0.00%) \| Like=-7.53..3.69 [-16.1569..-1.6640] \| it/evals=990/3625 eff=inf% N=400 Z=-12.6(0.00%) \| Like=-7.06..3.69 [-16.1569..-1.6640] \| it/evals=1000/3625 eff=inf% N=400 Z=-10.2(0.00%) \| Like=-4.66..3.69 [-16.1569..-1.6640] \| it/evals=1050/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-6.66) * Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.46 ****** +0.54 \| +1.00 Z=-9.1(0.01%) \| Like=-3.77..3.69 [-16.1569..-1.6640] \| it/evals=1080/3625 eff=inf% N=400 Z=-8.4(0.02%) \| Like=-3.02..3.69 [-16.1569..-1.6640] \| it/evals=1100/3625 eff=inf% N=400 Z=-6.8(0.13%) \| Like=-1.40..3.69 [-1.6514..1.3709] \| it/evals=1150/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-7.11) * Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-6.2(0.22%) \| Like=-0.98..3.69 [-1.6514..1.3709] \| it/evals=1170/3625 eff=inf% N=400 Z=-5.6(0.43%) \| Like=-0.44..3.69 [-1.6514..1.3709] \| it/evals=1200/3625 eff=inf% N=400 Z=-4.7(1.06%) \| Like=0.20..3.69 [-1.6514..1.3709] \| it/evals=1250/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-7.11) Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-3.9(2.32%) \| Like=1.22..3.69 [-1.6514..1.3709] \| it/evals=1300/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-7.39) * Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 **** +0.52 \| +1.00 Z=-3.2(4.75%) \| Like=1.77..3.69 [1.7333..1.7988] \| it/evals=1350/3625 eff=inf% N=400 Z=-2.6(8.16%) \| Like=2.17..3.69 [2.1689..2.1707]\| it/evals=1400/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-7.51) Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.3(11.57%) \| Like=2.42..3.69 [2.4219..2.4221]\| it/evals=1440/3625 eff=inf% N=400 Z=-2.2(12.55%) \| Like=2.47..3.69 [2.4730..2.4768]\| it/evals=1450/3625 eff=inf% N=400 Z=-1.9(17.45%) \| Like=2.75..3.69 [2.7491..2.7498]\| it/evals=1500/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-7.81) Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.7(20.74%) \| Like=2.91..3.69 [2.9003..2.9129] \| it/evals=1530/3625 eff=inf% N=400 Z=-1.6(23.08%) \| Like=2.98..3.69 [2.9833..2.9849]\| it/evals=1550/3625 eff=inf% N=400 Z=-1.4(29.11%) \| Like=3.14..3.69 [3.1391..3.1391]\| it/evals=1600/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-8.28) * Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.3(31.53%) \| Like=3.18..3.69 [3.1790..3.1792]\| it/evals=1620/3625 eff=inf% N=400 Z=-1.2(35.15%) \| Like=3.26..3.69 [3.2566..3.2569]\| it/evals=1650/3625 eff=inf% N=400 Z=-1.0(41.06%) \| Like=3.34..3.69 [3.3424..3.3427]\| it/evals=1700/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-8.28) Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 Z=-0.9(46.74%) \| Like=3.42..3.69 [3.4174..3.4175]\| it/evals=1750/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-8.49) Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.8(52.11%) \| Like=3.47..3.69 [3.4731..3.4751]\| it/evals=1800/3625 eff=inf% N=400 Z=-0.7(57.09%) \| Like=3.52..3.69 [3.5250..3.5260]\| it/evals=1850/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-8.81) * Expected Volume: exp(-4.73) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(60.83%) \| Like=3.55..3.69 [3.5540..3.5540]\| it/evals=1890/3625 eff=inf% N=400 Z=-0.6(61.73%) \| Like=3.56..3.69 [3.5611..3.5629]\| it/evals=1900/3625 eff=inf% N=400 Z=-0.6(65.92%) \| Like=3.59..3.69 [3.5913..3.5926]\| it/evals=1950/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-8.85) Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.5(68.26%) \| Like=3.60..3.69 [3.6037..3.6038]\| it/evals=1980/3625 eff=inf% N=400 Z=-0.5(69.72%) \| Like=3.61..3.69 [3.6112..3.6113]\| it/evals=2000/3625 eff=inf% N=400 Z=-0.5(73.12%) \| Like=3.63..3.69 [3.6294..3.6295]\| it/evals=2050/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-9.02) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.4(74.39%) \| Like=3.64..3.69 [3.6359..3.6360]\| it/evals=2070/3625 eff=inf% N=400 Z=-0.4(76.19%) \| Like=3.64..3.69 [3.6438..3.6438]\| it/evals=2100/3625 eff=inf% N=400 Z=-0.4(78.92%) \| Like=3.65..3.69 [3.6533..3.6534]\| it/evals=2150/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-9.21) Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.4(79.43%) \| Like=3.65..3.69 [3.6544..3.6547]\| it/evals=2160/3625 eff=inf% N=400 Z=-0.4(81.35%) \| Like=3.66..3.69 [3.6596..3.6596]\| it/evals=2200/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-9.35) * Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.3(83.51%) \| Like=3.66..3.69 [3.6638..3.6638]\| it/evals=2250/3625 eff=inf% N=400 Z=-0.3(85.43%) \| Like=3.67..3.69 [3.6691..3.6691]\| it/evals=2300/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-9.71) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.3(86.80%) \| Like=3.67..3.69 [3.6717..3.6718]\| it/evals=2340/3625 eff=inf% N=400 Z=-0.3(87.12%) \| Like=3.67..3.69 [3.6725..3.6726]\| it/evals=2350/3625 eff=inf% N=400 Z=-0.3(88.62%) \| Like=3.68..3.69 [3.6752..3.6753]\| it/evals=2400/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-10.03) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.3(89.44%) \| Like=3.68..3.69 [3.6771..3.6771]\| it/evals=2430/3625 eff=inf% N=400 Z=-0.2(89.95%) \| Like=3.68..3.69 [3.6780..3.6780]\| it/evals=2450/3625 eff=inf% N=400 Z=-0.2(91.13%) \| Like=3.68..3.69 [3.6802..3.6802]\| it/evals=2500/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-10.03) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 * +0.501 \| +1.000 Z=-0.2(92.16%) \| Like=3.68..3.69 [3.6815..3.6815]\| it/evals=2550/3625 eff=inf% N=400 Z=-0.2(93.08%) \| Like=3.68..3.69 [3.6826..3.6826]\| it/evals=2600/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-10.53) * Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.2(93.25%) \| Like=3.68..3.69 [3.6827..3.6827]\| it/evals=2610/3625 eff=inf% N=400 Z=-0.2(93.89%) \| Like=3.68..3.69 [3.6836..3.6836]\| it/evals=2650/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-10.57) * Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.2(94.61%) \| Like=3.68..3.69 [3.6842..3.6842]\| it/evals=2700/3625 eff=inf% N=400 Z=-0.2(95.24%) \| Like=3.68..3.69 [3.6847..3.6847]\| it/evals=2750/3625 eff=inf% N=400 Mono-modal Volume: ~exp(-11.06) * Expected Volume: exp(-6.98) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.2(95.70%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2790/3625 eff=inf% N=400 Z=-0.2(95.80%) \| Like=3.68..3.69 [3.6849..3.6849]\| it/evals=2800/3625 eff=inf% N=400 Z=-0.2(96.29%) \| Like=3.69..3.69 [3.6852..3.6852]*\| it/evals=2850/3625 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3625 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.1498 +- 0.06794 [ultranest] Effective samples strategy satisfied (ESS = 1253.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.08, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.04 total:0.08 required:<0.50 [ultranest] done iterating. logZ = -0.144 +- 0.152 single instance: logZ = -0.144 +- 0.092 bootstrapped : logZ = -0.150 +- 0.147 tail : logZ = +- 0.036 insert order U test : converged: True correlation: inf iterations a : 0.454 │ ▁ ▁▁▁▁▁▁▁▂▂▄▄▅▆▆▇▇▇▇▆▆▄▃▂▃▂▁▁▁▁▁▁▁▁ │0.540 0.500 +- 0.010 ran with dlogz: 0.5 first run gave: {'niter': 3253, 'logz': -0.14379632207248289, 'logzerr': 0.18310347998957455, 'logz_bs': -0.13026009874484876, 'logz_single': -0.14379632207248289, 'logzerr_tail': 0.03611931453602765, 'logzerr_bs': 0.1795056531191707, 'ess': 1253.420550147623, 'H': 3.348925652085825, 'Herr': 0.06724216689953912, 'posterior': {'mean': [0.4999163415129056], 'stdev': [0.009984478489580171], 'median': [0.4998294515402933], 'errlo': [0.4897722799365294], 'errup': [0.5098152223068952], 'information_gain_bits': [3.463126483234424]}, 'maximum_likelihood': {'logl': 3.6862316474629644, 'point': [0.5000010315477932], 'point_untransformed': [0.5000010315477932]}, 'ncall': 3625, 'paramnames': ['a'], 'logzerr_single': 0.09150035043765986, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3253, 'logz': -0.14379632207248289, 'logzerr': 0.15165994819494222, 'logz_bs': -0.1497862378729898, 'logz_single': -0.14379632207248289, 'logzerr_tail': 0.03611931453602765, 'logzerr_bs': 0.1472960793909331, 'ess': 1253.420550147623, 'H': 3.348925652085825, 'Herr': 0.06614145370598383, 'posterior': {'mean': [0.4999572757254387], 'stdev': [0.010007165175666608], 'median': [0.4998524605198037], 'errlo': [0.48987184730524147], 'errup': [0.5098360100994238], 'information_gain_bits': [3.463126483234424]}, 'maximum_likelihood': {'logl': 3.6862316474629644, 'point': [0.5000010315477932], 'point_untransformed': [0.5000010315477932]}, 'ncall': 3625, 'paramnames': ['a'], 'logzerr_single': 0.09150035043765986, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpp6vlkvdm, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1229.24, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=528, regioncalls=128, ndraw=128, logz=-947.80, remainder_fraction=100.0000%, Lmin=-936.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-794.67, remainder_fraction=100.0000%, Lmin=-767.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=528, regioncalls=128, ndraw=128, logz=-744.35, remainder_fraction=100.0000%, Lmin=-735.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=105, ncalls=635, regioncalls=256, ndraw=128, logz=-722.38, remainder_fraction=100.0000%, Lmin=-710.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=635, regioncalls=256, ndraw=128, logz=-573.67, remainder_fraction=100.0000%, Lmin=-562.58, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=711, regioncalls=384, ndraw=128, logz=-436.35, remainder_fraction=100.0000%, Lmin=-427.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=711, regioncalls=384, ndraw=128, logz=-342.29, remainder_fraction=100.0000%, Lmin=-335.76, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=780, regioncalls=512, ndraw=128, logz=-312.30, remainder_fraction=100.0000%, Lmin=-306.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=780, regioncalls=512, ndraw=128, logz=-277.84, remainder_fraction=100.0000%, Lmin=-269.37, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=338, ncalls=829, regioncalls=640, ndraw=128, logz=-232.03, remainder_fraction=100.0000%, Lmin=-223.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=829, regioncalls=640, ndraw=128, logz=-224.03, remainder_fraction=100.0000%, Lmin=-217.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=877, regioncalls=768, ndraw=128, logz=-174.15, remainder_fraction=100.0000%, Lmin=-164.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=922, regioncalls=896, ndraw=128, logz=-139.64, remainder_fraction=100.0000%, Lmin=-130.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=964, regioncalls=1024, ndraw=128, logz=-110.71, remainder_fraction=100.0000%, Lmin=-103.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1002, regioncalls=1152, ndraw=128, logz=-90.31, remainder_fraction=100.0000%, Lmin=-83.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1043, regioncalls=1280, ndraw=128, logz=-84.03, remainder_fraction=100.0000%, Lmin=-76.16, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1070, regioncalls=1408, ndraw=128, logz=-69.04, remainder_fraction=100.0000%, Lmin=-63.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1104, regioncalls=1536, ndraw=128, logz=-62.34, remainder_fraction=100.0000%, Lmin=-56.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1131, regioncalls=1664, ndraw=128, logz=-57.37, remainder_fraction=100.0000%, Lmin=-51.00, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1175, regioncalls=1920, ndraw=128, logz=-44.82, remainder_fraction=100.0000%, Lmin=-38.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1196, regioncalls=2048, ndraw=128, logz=-40.29, remainder_fraction=100.0000%, Lmin=-34.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1236, regioncalls=2304, ndraw=128, logz=-36.28, remainder_fraction=100.0000%, Lmin=-30.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1287, regioncalls=2688, ndraw=128, logz=-28.45, remainder_fraction=100.0000%, Lmin=-22.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1287, regioncalls=2688, ndraw=128, logz=-27.10, remainder_fraction=100.0000%, Lmin=-21.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1332, regioncalls=3072, ndraw=128, logz=-22.97, remainder_fraction=100.0000%, Lmin=-17.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1385, regioncalls=3456, ndraw=128, logz=-18.87, remainder_fraction=100.0000%, Lmin=-13.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1437, regioncalls=3968, ndraw=128, logz=-15.47, remainder_fraction=100.0000%, Lmin=-10.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1477, regioncalls=4480, ndraw=128, logz=-13.15, remainder_fraction=99.9998%, Lmin=-7.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1500, regioncalls=4736, ndraw=128, logz=-12.63, remainder_fraction=99.9996%, Lmin=-7.06, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1546, regioncalls=5376, ndraw=128, logz=-10.23, remainder_fraction=99.9961%, Lmin=-4.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1093, ncalls=1596, regioncalls=5888, ndraw=128, logz=-8.63, remainder_fraction=99.9803%, Lmin=-3.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1596, regioncalls=5888, ndraw=128, logz=-8.40, remainder_fraction=99.9751%, Lmin=-3.02, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1649, regioncalls=6528, ndraw=128, logz=-6.78, remainder_fraction=99.8748%, Lmin=-1.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1672, regioncalls=6784, ndraw=128, logz=-6.25, remainder_fraction=99.7835%, Lmin=-0.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1699, regioncalls=7168, ndraw=128, logz=-5.57, remainder_fraction=99.5664%, Lmin=-0.44, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1748, regioncalls=8320, ndraw=128, logz=-4.70, remainder_fraction=98.9446%, Lmin=0.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1757, regioncalls=8448, ndraw=128, logz=-4.54, remainder_fraction=98.7719%, Lmin=0.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1804, regioncalls=9344, ndraw=128, logz=-3.89, remainder_fraction=97.6829%, Lmin=1.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1850, regioncalls=10496, ndraw=128, logz=-3.18, remainder_fraction=95.2463%, Lmin=1.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1904, regioncalls=11776, ndraw=128, logz=-2.64, remainder_fraction=91.8392%, Lmin=2.17, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1947, regioncalls=13056, ndraw=128, logz=-2.30, remainder_fraction=88.4330%, Lmin=2.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1958, regioncalls=13440, ndraw=128, logz=-2.22, remainder_fraction=87.4548%, Lmin=2.47, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2012, regioncalls=15104, ndraw=128, logz=-1.89, remainder_fraction=82.5508%, Lmin=2.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2042, regioncalls=16128, ndraw=128, logz=-1.72, remainder_fraction=79.2637%, Lmin=2.91, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2064, regioncalls=16896, ndraw=128, logz=-1.61, remainder_fraction=76.9153%, Lmin=2.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2114, regioncalls=19328, ndraw=128, logz=-1.38, remainder_fraction=70.8937%, Lmin=3.14, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2135, regioncalls=20224, ndraw=128, logz=-1.30, remainder_fraction=68.4742%, Lmin=3.18, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2267, regioncalls=21504, ndraw=128, logz=-1.19, remainder_fraction=64.8523%, Lmin=3.26, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2267, regioncalls=21504, ndraw=128, logz=-1.03, remainder_fraction=58.9386%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2267, regioncalls=21504, ndraw=128, logz=-1.01, remainder_fraction=57.8027%, Lmin=3.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2278, regioncalls=22272, ndraw=128, logz=-0.90, remainder_fraction=53.2588%, Lmin=3.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2329, regioncalls=24832, ndraw=128, logz=-0.80, remainder_fraction=47.8890%, Lmin=3.47, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1828, ncalls=2457, regioncalls=25088, ndraw=128, logz=-0.74, remainder_fraction=45.0585%, Lmin=3.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2457, regioncalls=25088, ndraw=128, logz=-0.70, remainder_fraction=42.9116%, Lmin=3.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2457, regioncalls=25088, ndraw=128, logz=-0.64, remainder_fraction=39.1708%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2457, regioncalls=25088, ndraw=128, logz=-0.63, remainder_fraction=38.2725%, Lmin=3.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2499, regioncalls=25984, ndraw=128, logz=-0.56, remainder_fraction=34.0753%, Lmin=3.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2526, regioncalls=26624, ndraw=128, logz=-0.53, remainder_fraction=31.7411%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2655, regioncalls=27264, ndraw=128, logz=-0.50, remainder_fraction=30.2779%, Lmin=3.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=2655, regioncalls=27264, ndraw=128, logz=-0.46, remainder_fraction=26.8792%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2655, regioncalls=27264, ndraw=128, logz=-0.44, remainder_fraction=25.6086%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=2666, regioncalls=28288, ndraw=128, logz=-0.42, remainder_fraction=23.8096%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2118, ncalls=2780, regioncalls=29312, ndraw=128, logz=-0.40, remainder_fraction=22.7878%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2780, regioncalls=29312, ndraw=128, logz=-0.38, remainder_fraction=21.0780%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=2780, regioncalls=29312, ndraw=128, logz=-0.37, remainder_fraction=20.5695%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2780, regioncalls=29312, ndraw=128, logz=-0.35, remainder_fraction=18.6478%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=2835, regioncalls=30464, ndraw=128, logz=-0.32, remainder_fraction=16.4895%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=2887, regioncalls=31744, ndraw=128, logz=-0.30, remainder_fraction=14.5727%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2931, regioncalls=32384, ndraw=128, logz=-0.29, remainder_fraction=13.2025%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=2940, regioncalls=32640, ndraw=128, logz=-0.28, remainder_fraction=12.8799%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=2994, regioncalls=33536, ndraw=128, logz=-0.26, remainder_fraction=11.3784%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3029, regioncalls=34176, ndraw=128, logz=-0.26, remainder_fraction=10.5619%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3148, regioncalls=34432, ndraw=128, logz=-0.25, remainder_fraction=10.0498%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3148, regioncalls=34432, ndraw=128, logz=-0.24, remainder_fraction=8.8742%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3148, regioncalls=34432, ndraw=128, logz=-0.23, remainder_fraction=8.4432%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3273, regioncalls=34688, ndraw=128, logz=-0.23, remainder_fraction=7.8354%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3273, regioncalls=34688, ndraw=128, logz=-0.22, remainder_fraction=6.9173%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3273, regioncalls=34688, ndraw=128, logz=-0.21, remainder_fraction=6.7470%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3383, regioncalls=34944, ndraw=128, logz=-0.21, remainder_fraction=6.1063%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3383, regioncalls=34944, ndraw=128, logz=-0.20, remainder_fraction=5.3898%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2732, ncalls=3503, regioncalls=35200, ndraw=128, logz=-0.19, remainder_fraction=4.9759%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3503, regioncalls=35200, ndraw=128, logz=-0.19, remainder_fraction=4.7571%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3503, regioncalls=35200, ndraw=128, logz=-0.19, remainder_fraction=4.3048%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3503, regioncalls=35200, ndraw=128, logz=-0.19, remainder_fraction=4.1986%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2836, ncalls=3625, regioncalls=35456, ndraw=128, logz=-0.18, remainder_fraction=3.8375%, Lmin=3.69, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=3625, regioncalls=35456, ndraw=128, logz=-0.18, remainder_fraction=3.7056%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3625 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -0.1303 +- 0.07431 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1253.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.08, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.04 total:0.08 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpp6vlkvdm, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [3.6851476 3.68609358 0. 0.49983383 0.49983383]: u=[0.49983383] -> p=[0.49983383] -> L=3.6860935822797853 INFO ultranest:integrator.py:2364 Resuming from 3528 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=3625, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1229.24, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=3625, regioncalls=0, ndraw=128, logz=-947.80, remainder_fraction=100.0000%, Lmin=-936.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=3625, regioncalls=0, ndraw=128, logz=-794.67, remainder_fraction=100.0000%, Lmin=-767.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=3625, regioncalls=0, ndraw=128, logz=-744.35, remainder_fraction=100.0000%, Lmin=-735.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=3625, regioncalls=0, ndraw=128, logz=-573.67, remainder_fraction=100.0000%, Lmin=-562.58, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=3625, regioncalls=0, ndraw=128, logz=-436.35, remainder_fraction=100.0000%, Lmin=-427.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3625, regioncalls=0, ndraw=128, logz=-342.29, remainder_fraction=100.0000%, Lmin=-335.76, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=3625, regioncalls=0, ndraw=128, logz=-312.30, remainder_fraction=100.0000%, Lmin=-306.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=3625, regioncalls=0, ndraw=128, logz=-277.84, remainder_fraction=100.0000%, Lmin=-269.37, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=3625, regioncalls=0, ndraw=128, logz=-224.03, remainder_fraction=100.0000%, Lmin=-217.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=3625, regioncalls=0, ndraw=128, logz=-174.15, remainder_fraction=100.0000%, Lmin=-164.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3625, regioncalls=0, ndraw=128, logz=-139.64, remainder_fraction=100.0000%, Lmin=-130.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3625, regioncalls=0, ndraw=128, logz=-110.71, remainder_fraction=100.0000%, Lmin=-103.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=3625, regioncalls=0, ndraw=128, logz=-90.31, remainder_fraction=100.0000%, Lmin=-83.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3625, regioncalls=0, ndraw=128, logz=-84.03, remainder_fraction=100.0000%, Lmin=-76.16, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=3625, regioncalls=0, ndraw=128, logz=-69.04, remainder_fraction=100.0000%, Lmin=-63.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=3625, regioncalls=0, ndraw=128, logz=-62.34, remainder_fraction=100.0000%, Lmin=-56.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=3625, regioncalls=0, ndraw=128, logz=-57.37, remainder_fraction=100.0000%, Lmin=-51.00, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=3625, regioncalls=0, ndraw=128, logz=-44.82, remainder_fraction=100.0000%, Lmin=-38.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=3625, regioncalls=0, ndraw=128, logz=-40.29, remainder_fraction=100.0000%, Lmin=-34.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=3625, regioncalls=0, ndraw=128, logz=-36.28, remainder_fraction=100.0000%, Lmin=-30.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=3625, regioncalls=0, ndraw=128, logz=-28.45, remainder_fraction=100.0000%, Lmin=-22.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=3625, regioncalls=0, ndraw=128, logz=-27.10, remainder_fraction=100.0000%, Lmin=-21.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=3625, regioncalls=0, ndraw=128, logz=-22.97, remainder_fraction=100.0000%, Lmin=-17.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=3625, regioncalls=0, ndraw=128, logz=-18.87, remainder_fraction=100.0000%, Lmin=-13.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=3625, regioncalls=0, ndraw=128, logz=-15.47, remainder_fraction=100.0000%, Lmin=-10.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=3625, regioncalls=0, ndraw=128, logz=-13.15, remainder_fraction=99.9998%, Lmin=-7.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=3625, regioncalls=0, ndraw=128, logz=-12.63, remainder_fraction=99.9996%, Lmin=-7.06, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=3625, regioncalls=0, ndraw=128, logz=-10.23, remainder_fraction=99.9961%, Lmin=-4.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=3625, regioncalls=0, ndraw=128, logz=-9.07, remainder_fraction=99.9874%, Lmin=-3.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=3625, regioncalls=0, ndraw=128, logz=-8.40, remainder_fraction=99.9751%, Lmin=-3.02, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=3625, regioncalls=0, ndraw=128, logz=-6.78, remainder_fraction=99.8748%, Lmin=-1.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=3625, regioncalls=0, ndraw=128, logz=-6.25, remainder_fraction=99.7835%, Lmin=-0.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=3625, regioncalls=0, ndraw=128, logz=-5.57, remainder_fraction=99.5664%, Lmin=-0.44, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=3625, regioncalls=0, ndraw=128, logz=-4.70, remainder_fraction=98.9446%, Lmin=0.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=3625, regioncalls=0, ndraw=128, logz=-3.89, remainder_fraction=97.6829%, Lmin=1.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=3625, regioncalls=0, ndraw=128, logz=-3.18, remainder_fraction=95.2463%, Lmin=1.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=3625, regioncalls=0, ndraw=128, logz=-2.64, remainder_fraction=91.8392%, Lmin=2.17, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=3625, regioncalls=0, ndraw=128, logz=-2.30, remainder_fraction=88.4330%, Lmin=2.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=3625, regioncalls=0, ndraw=128, logz=-2.22, remainder_fraction=87.4548%, Lmin=2.47, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.89, remainder_fraction=82.5508%, Lmin=2.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.72, remainder_fraction=79.2637%, Lmin=2.91, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.61, remainder_fraction=76.9153%, Lmin=2.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.38, remainder_fraction=70.8937%, Lmin=3.14, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.30, remainder_fraction=68.4742%, Lmin=3.18, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.19, remainder_fraction=64.8523%, Lmin=3.26, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=3625, regioncalls=0, ndraw=128, logz=-1.03, remainder_fraction=58.9386%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.90, remainder_fraction=53.2588%, Lmin=3.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.80, remainder_fraction=47.8890%, Lmin=3.47, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.70, remainder_fraction=42.9116%, Lmin=3.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.64, remainder_fraction=39.1708%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.63, remainder_fraction=38.2725%, Lmin=3.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.56, remainder_fraction=34.0753%, Lmin=3.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.53, remainder_fraction=31.7411%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.50, remainder_fraction=30.2779%, Lmin=3.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.46, remainder_fraction=26.8792%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.44, remainder_fraction=25.6086%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.42, remainder_fraction=23.8096%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.38, remainder_fraction=21.0780%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.37, remainder_fraction=20.5695%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.35, remainder_fraction=18.6478%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.32, remainder_fraction=16.4895%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.30, remainder_fraction=14.5727%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.29, remainder_fraction=13.2025%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.28, remainder_fraction=12.8799%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.26, remainder_fraction=11.3784%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.26, remainder_fraction=10.5619%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.25, remainder_fraction=10.0498%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.24, remainder_fraction=8.8742%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.23, remainder_fraction=7.8354%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.22, remainder_fraction=6.9173%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.21, remainder_fraction=6.7470%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.21, remainder_fraction=6.1063%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.20, remainder_fraction=5.3898%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.19, remainder_fraction=4.7571%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.19, remainder_fraction=4.3048%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.19, remainder_fraction=4.1986%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=3625, regioncalls=0, ndraw=128, logz=-0.18, remainder_fraction=3.7056%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3625 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -0.1498 +- 0.06794 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1253.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.08, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.04 total:0.08 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_regionsampling.py::test_ellipsoids	0.28
[gw10] linux -- Python 3.10.6 /usr/bin/python3 [gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ Ellipsis 0.6 [[0.41865222 0.5331768 0.51392054] [0.57713039 0.40546347 0.47608582] [0.59134763 0.43563202 0.50341199] ... [0.44144867 0.59911507 0.48584036] [0.47176549 0.45623318 0.45982139] [0.40711484 0.56121512 0.53840946]] [[4. 5.33176802 5.13920541] [5. 4.05463474 4.76085823] [5. 4.35632019 5.03411992] ... [4. 5.99115074 4.85840357] [4. 4.56233182 4.59821386] [4. 5.61215116 5.38409461]] Ellipsis 0.5 [[0.49700161 0.40792034 0.46412425] [0.42440793 0.59065711 0.45978351] [0.45738282 0.49420034 0.44173547] ... [0.44173661 0.49918106 0.45480539] [0.45104862 0.44809618 0.50525352] [0.45809629 0.53638961 0.54502059]] [[4. 4.07920339 4.64124253] [4. 5.90657111 4.59783513] [4. 4.94200337 4.41735475] ... [4. 4.99181057 4.54805394] [4. 4.48096181 5.05253522] [4. 5.3638961 5.45020588]] [False True True]
Passed	tests/test_samplingpath.py::test_wrap	0.01
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_samplingpath.py::test_random	0.74
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_stepsampling.py::test_stepsampler	0.15
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [0.19669413 0.15875824 0.53255916] -0.533599805036657 [0.82144124 0.82377575 0.70716751] -0.7373961297911862
Passed	tests/test_stepsampling.py::test_stepsampler_adapt_when_stuck	0.27
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ CubeMHSampler rejected by region ineffective proposal scale (1). shrinking... rejected by region ineffective proposal scale (0.385543). shrinking... rejected by region ineffective proposal scale (0.148644). shrinking... rejected by region ineffective proposal scale (0.0573086). shrinking... rejected by region ineffective proposal scale (0.0220949). shrinking... CubeSliceSampler
Passed	tests/test_run.py::test_reactive_run_warmstart_gauss	10.30
[gw10] linux -- Python 3.10.6 /usr/bin/python3 [gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ====== Running Gauss problem [1] ===== [ultranest] Sampling 100 live points from prior ... Z=-inf(0.00%) \| Like=-5e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=0/101 eff=0.0000% N=100 Z=-4e+13(0.00%) \| Like=-4.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=10/112 eff=83.3333% N=100 Z=-3e+13(0.00%) \| Like=-3.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=20/122 eff=90.9091% N=100 Z=-3e+13(0.00%) \| Like=-3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=30/132 eff=93.7500% N=100 Z=-3e+13(0.00%) \| Like=-2.6e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=40/143 eff=93.0233% N=100 Z=-2e+13(0.00%) \| Like=-2.2e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=46/151 eff=90.1961% N=100 Z=-2e+13(0.00%) \| Like=-2.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=50/155 eff=90.9091% N=100 Z=-2e+13(0.00%) \| Like=-1.7e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=60/165 eff=92.3077% N=100 Z=-1e+13(0.00%) \| Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=69/174 eff=93.2432% N=100 Z=-1e+13(0.00%) \| Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=70/176 eff=92.1053% N=100 Z=-1e+13(0.00%) \| Like=-1.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=80/186 eff=93.0233% N=100 Z=-1e+13(0.00%) \| Like=-9.6e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=90/197 eff=92.7835% N=100 Z=-8e+12(0.00%) \| Like=-8.1e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=100/208 eff=92.5926% N=100 Z=-7e+12(0.00%) \| Like=-7e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=110/220 eff=91.6667% N=100 Z=-7e+12(0.00%) \| Like=-6.8e+12..-2.1e+09 [-1.232e+13..-4.452e+12] \| it/evals=115/225 eff=92.0000% N=100 Z=-6e+12(0.00%) \| Like=-6.2e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=120/230 eff=92.3077% N=100 Z=-5e+12(0.00%) \| Like=-5e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=130/243 eff=90.9091% N=100 Z=-5e+12(0.00%) \| Like=-4.5e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=140/257 eff=89.1720% N=100 Z=-3e+12(0.00%) \| Like=-3.4e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=150/268 eff=89.2857% N=100 Z=-3e+12(0.00%) \| Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=160/278 eff=89.8876% N=100 Z=-3e+12(0.00%) \| Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=161/279 eff=89.9441% N=100 Z=-2e+12(0.00%) \| Like=-2.1e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=170/289 eff=89.9471% N=100 Z=-2e+12(0.00%) \| Like=-1.8e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=180/299 eff=90.4523% N=100 Z=-1e+12(0.00%) \| Like=-1.5e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=190/309 eff=90.9091% N=100 Z=-1e+12(0.00%) \| Like=-1.1e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=200/319 eff=91.3242% N=100 Z=-1e+12(0.00%) \| Like=-1.1e+12..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=207/326 eff=91.5929% N=100 Z=-1e+12(0.00%) \| Like=-1e+12..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=210/329 eff=91.7031% N=100 Z=-9e+11(0.00%) \| Like=-8.4e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=220/342 eff=90.9091% N=100 Z=-7e+11(0.00%) \| Like=-7.1e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=230/352 eff=91.2698% N=100 Z=-6e+11(0.00%) \| Like=-5.8e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=240/364 eff=90.9091% N=100 Z=-5e+11(0.00%) \| Like=-5e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=250/376 eff=90.5797% N=100 Z=-5e+11(0.00%) \| Like=-4.6e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=253/379 eff=90.6810% N=100 Z=-4e+11(0.00%) \| Like=-4.2e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=260/387 eff=90.5923% N=100 Z=-3e+11(0.00%) \| Like=-3.3e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=270/401 eff=89.7010% N=100 Z=-3e+11(0.00%) \| Like=-3e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=276/408 eff=89.6104% N=100 Z=-3e+11(0.00%) \| Like=-2.7e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=280/412 eff=89.7436% N=100 Z=-2e+11(0.00%) \| Like=-2.2e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=290/422 eff=90.0621% N=100 Z=-2e+11(0.00%) \| Like=-1.9e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=299/431 eff=90.3323% N=100 Z=-2e+11(0.00%) \| Like=-1.8e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=300/432 eff=90.3614% N=100 Z=-1e+11(0.00%) \| Like=-1.3e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=310/446 eff=89.5954% N=100 Z=-1e+11(0.00%) \| Like=-1.1e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=320/458 eff=89.3855% N=100 Z=-1e+11(0.00%) \| Like=-1e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=322/460 eff=89.4444% N=100 Z=-9e+10(0.00%) \| Like=-8.4e+10..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=330/468 eff=89.6739% N=100 Z=-8e+10(0.00%) \| Like=-7.8e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=340/478 eff=89.9471% N=100 Z=-7e+10(0.00%) \| Like=-6.5e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=350/488 eff=90.2062% N=100 Z=-5e+10(0.00%) \| Like=-5.2e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=360/498 eff=90.4523% N=100 Z=-4e+10(0.00%) \| Like=-4.5e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=368/506 eff=90.6404% N=100 Z=-4e+10(0.00%) \| Like=-4.4e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=370/508 eff=90.6863% N=100 Z=-4e+10(0.00%) \| Like=-3.8e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=380/518 eff=90.9091% N=100 Z=-3e+10(0.00%) \| Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=390/528 eff=91.1215% N=100 Z=-3e+10(0.00%) \| Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=391/529 eff=91.1422% N=100 Z=-3e+10(0.00%) \| Like=-2.5e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=400/539 eff=91.1162% N=100 Z=-2e+10(0.00%) \| Like=-2.2e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=410/549 eff=91.3140% N=100 Z=-2e+10(0.00%) \| Like=-2e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=414/553 eff=91.3907% N=100 Z=-2e+10(0.00%) \| Like=-1.7e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=420/559 eff=91.5033% N=100 Z=-1e+10(0.00%) \| Like=-1.3e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=430/569 eff=91.6844% N=100 Z=-1e+10(0.00%) \| Like=-1.1e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=440/581 eff=91.4761% N=100 Z=-9e+09(0.00%) \| Like=-8.8e+09..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=450/591 eff=91.6497% N=100 Z=-7e+09(0.00%) \| Like=-7.3e+09..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=460/603 eff=91.4513% N=100 Z=-6e+09(0.00%) \| Like=-5.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=470/615 eff=91.2621% N=100 Z=-5e+09(0.00%) \| Like=-4.5e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=480/625 eff=91.4286% N=100 Z=-4e+09(0.00%) \| Like=-4.3e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=483/628 eff=91.4773% N=100 Z=-4e+09(0.00%) \| Like=-3.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=490/635 eff=91.5888% N=100 Z=-3e+09(0.00%) \| Like=-3.1e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=500/648 eff=91.2409% N=100 Z=-3e+09(0.00%) \| Like=-2.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=506/656 eff=91.0072% N=100 Z=-2e+09(0.00%) \| Like=-2.5e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=510/660 eff=91.0714% N=100 Z=-2e+09(0.00%) \| Like=-2e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=520/671 eff=91.0683% N=100 Z=-2e+09(0.00%) \| Like=-1.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=529/682 eff=90.8935% N=100 Z=-2e+09(0.00%) \| Like=-1.6e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=530/685 eff=90.5983% N=100 Z=-1e+09(0.00%) \| Like=-1.3e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=540/697 eff=90.4523% N=100 Z=-8e+08(0.00%) \| Like=-8.4e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=550/710 eff=90.1639% N=100 Z=-8e+08(0.00%) \| Like=-8.2e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=552/712 eff=90.1961% N=100 Z=-8e+08(0.00%) \| Like=-7.4e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=560/721 eff=90.1771% N=100 Z=-6e+08(0.00%) \| Like=-5.9e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=570/731 eff=90.3328% N=100 Z=-5e+08(0.00%) \| Like=-5.2e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=580/741 eff=90.4836% N=100 Z=-4e+08(0.00%) \| Like=-3.8e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=590/755 eff=90.0763% N=100 Z=-3e+08(0.00%) \| Like=-3.1e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=598/763 eff=90.1961% N=100 Z=-3e+08(0.00%) \| Like=-2.8e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=600/765 eff=90.2256% N=100 Z=-2e+08(0.00%) \| Like=-2.4e+08..-2e+04 [-2.461e+08..-7.777e+07] \| it/evals=610/775 eff=90.3704% N=100 Z=-2e+08(0.00%) \| Like=-2.2e+08..-2e+04 [-2.461e+08..-7.777e+07] \| it/evals=620/786 eff=90.3790% N=100 Z=-2e+08(0.00%) \| Like=-1.8e+08..-2e+04 [-2.461e+08..-7.777e+07] \| it/evals=630/796 eff=90.5172% N=100 Z=-1e+08(0.00%) \| Like=-1.5e+08..-2e+04 [-2.461e+08..-7.777e+07] \| it/evals=640/806 eff=90.6516% N=100 Z=-1e+08(0.00%) \| Like=-1.4e+08..-6e+03 [-2.461e+08..-7.777e+07] \| it/evals=644/810 eff=90.7042% N=100 Z=-1e+08(0.00%) \| Like=-1.3e+08..-6e+03 [-2.461e+08..-7.777e+07] \| it/evals=650/816 eff=90.7821% N=100 Z=-1e+08(0.00%) \| Like=-1.1e+08..-6e+03 [-2.461e+08..-7.777e+07] \| it/evals=660/827 eff=90.7840% N=100 Z=-99584971.5(0.00%) \| Like=-99056746.97..-6022.96 [-2.461e+08..-7.777e+07] \| it/evals=667/835 eff=90.7483% N=100 Z=-95148616.1(0.00%) \| Like=-93692477.41..-6022.96 [-2.461e+08..-7.777e+07] \| it/evals=670/838 eff=90.7859% N=100 Z=-78681625.8(0.00%) \| Like=-76849640.99..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=680/849 eff=90.7877% N=100 Z=-67129640.5(0.00%) \| Like=-66446442.40..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=690/860 eff=90.7895% N=100 Z=-52437072.4(0.00%) \| Like=-52098992.93..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=700/872 eff=90.6736% N=100 Z=-42467034.5(0.00%) \| Like=-40947576.24..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=710/883 eff=90.6769% N=100 Z=-40875016.2(0.00%) \| Like=-40682265.05..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=713/886 eff=90.7125% N=100 Z=-34273953.3(0.00%) \| Like=-34009302.56..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=720/893 eff=90.7945% N=100 Z=-28150952.9(0.00%) \| Like=-27577294.66..-6022.96 [-76849640.9883..-21157237.0757] \| it/evals=730/904 eff=90.7960% N=100 Z=-24903284.6(0.00%) \| Like=-24585788.12..-26.00 [-76849640.9883..-21157237.0757] \| it/evals=740/917 eff=90.5753% N=100 Z=-18109608.4(0.00%) \| Like=-17736757.48..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=750/927 eff=90.6892% N=100 Z=-15169525.4(0.00%) \| Like=-14227274.47..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=760/937 eff=90.8005% N=100 Z=-11387981.3(0.00%) \| Like=-11171106.07..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=770/949 eff=90.6949% N=100 Z=-9540359.8(0.00%) \| Like=-9254160.55..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=780/959 eff=90.8033% N=100 Z=-9246880.2(0.00%) \| Like=-9220004.55..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=782/961 eff=90.8246% N=100 Z=-8202857.7(0.00%) \| Like=-7968261.52..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=790/969 eff=90.9091% N=100 Z=-6151494.4(0.00%) \| Like=-6110210.34..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=800/980 eff=90.9091% N=100 Z=-5595023.2(0.00%) \| Like=-5544084.40..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=805/986 eff=90.8578% N=100 Z=-5168753.7(0.00%) \| Like=-5104017.56..-26.00 [-19938210.0363..-4653930.8201] \| it/evals=810/991 eff=90.9091% N=100 Z=-4348450.3(0.00%) \| Like=-4124983.59..-26.00 [-4571171.0738..-801360.3533] \| it/evals=820/1001 eff=91.0100% N=100 Z=-3288211.8(0.00%) \| Like=-3052967.15..-26.00 [-4571171.0738..-801360.3533] \| it/evals=828/1010 eff=90.9890% N=100 Z=-2816901.9(0.00%) \| Like=-2813964.84..-26.00 [-4571171.0738..-801360.3533] \| it/evals=830/1012 eff=91.0088% N=100 Z=-2391242.8(0.00%) \| Like=-2352037.02..-26.00 [-4571171.0738..-801360.3533] \| it/evals=840/1022 eff=91.1063% N=100 Z=-1694476.5(0.00%) \| Like=-1688714.15..-26.00 [-4571171.0738..-801360.3533] \| it/evals=850/1033 eff=91.1040% N=100 Z=-1688727.3(0.00%) \| Like=-1641589.55..-26.00 [-4571171.0738..-801360.3533] \| it/evals=851/1034 eff=91.1135% N=100 Z=-1391311.1(0.00%) \| Like=-1378714.97..-26.00 [-4571171.0738..-801360.3533] \| it/evals=860/1044 eff=91.1017% N=100 Z=-1016207.0(0.00%) \| Like=-1005805.90..-26.00 [-4571171.0738..-801360.3533] \| it/evals=870/1056 eff=91.0042% N=100 Z=-921148.4(0.00%) \| Like=-899817.07..-26.00 [-4571171.0738..-801360.3533] \| it/evals=874/1061 eff=90.9469% N=100 Z=-823593.3(0.00%) \| Like=-820443.05..-26.00 [-4571171.0738..-801360.3533] \| it/evals=880/1067 eff=91.0031% N=100 Z=-718128.1(0.00%) \| Like=-716385.20..-26.00 [-793371.7270..-221963.8669] \| it/evals=890/1078 eff=91.0020% N=100 Z=-596455.2(0.00%) \| Like=-575764.61..-26.00 [-793371.7270..-221963.8669] \| it/evals=900/1090 eff=90.9091% N=100 Z=-491331.9(0.00%) \| Like=-490644.03..-26.00 [-793371.7270..-221963.8669] \| it/evals=910/1101 eff=90.9091% N=100 Z=-403815.9(0.00%) \| Like=-396540.01..-26.00 [-793371.7270..-221963.8669] \| it/evals=920/1112 eff=90.9091% N=100 Z=-335464.4(0.00%) \| Like=-335428.11..-4.83 [-793371.7270..-221963.8669] \| it/evals=930/1122 eff=90.9980% N=100 Z=-281288.1(0.00%) \| Like=-269279.55..-4.83 [-793371.7270..-221963.8669] \| it/evals=940/1133 eff=90.9971% N=100 Z=-267112.8(0.00%) \| Like=-259247.40..-4.83 [-793371.7270..-221963.8669] \| it/evals=943/1137 eff=90.9354% N=100 Z=-232361.2(0.00%) \| Like=-227851.27..-4.83 [-793371.7270..-221963.8669] \| it/evals=950/1144 eff=90.9962% N=100 Z=-195082.6(0.00%) \| Like=-192338.76..-4.83 [-221393.3591..-50063.0867] \| it/evals=960/1154 eff=91.0816% N=100 Z=-158846.7(0.00%) \| Like=-156838.84..-4.83 [-221393.3591..-50063.0867] \| it/evals=970/1165 eff=91.0798% N=100 Z=-123015.8(0.00%) \| Like=-122093.92..-4.83 [-221393.3591..-50063.0867] \| it/evals=980/1176 eff=91.0781% N=100 Z=-98769.3(0.00%) \| Like=-94308.81..-4.83 [-221393.3591..-50063.0867] \| it/evals=989/1186 eff=91.0681% N=100 Z=-94323.3(0.00%) \| Like=-93705.11..-4.83 [-221393.3591..-50063.0867] \| it/evals=990/1187 eff=91.0764% N=100 Z=-75793.0(0.00%) \| Like=-75159.71..-4.83 [-221393.3591..-50063.0867] \| it/evals=1000/1198 eff=91.0747% N=100 Z=-69193.8(0.00%) \| Like=-69178.34..-4.43 [-221393.3591..-50063.0867] \| it/evals=1010/1209 eff=91.0730% N=100 Z=-68151.1(0.00%) \| Like=-67031.91..-4.43 [-221393.3591..-50063.0867] \| it/evals=1012/1212 eff=91.0072% N=100 Z=-59478.1(0.00%) \| Like=-56316.63..-4.43 [-221393.3591..-50063.0867] \| it/evals=1020/1221 eff=90.9902% N=100 Z=-49166.7(0.00%) \| Like=-46314.73..-4.43 [-49739.3666..-12576.5127] \| it/evals=1030/1232 eff=90.9894% N=100 Z=-42809.3(0.00%) \| Like=-40722.23..-4.43 [-49739.3666..-12576.5127] \| it/evals=1035/1238 eff=90.9490% N=100 Z=-38197.5(0.00%) \| Like=-36533.18..-4.43 [-49739.3666..-12576.5127] \| it/evals=1040/1243 eff=90.9886% N=100 Z=-33560.9(0.00%) \| Like=-32411.75..-4.43 [-49739.3666..-12576.5127] \| it/evals=1050/1253 eff=91.0668% N=100 Z=-28364.5(0.00%) \| Like=-28235.71..-4.43 [-49739.3666..-12576.5127] \| it/evals=1060/1263 eff=91.1436% N=100 Z=-23735.6(0.00%) \| Like=-21704.04..-4.43 [-49739.3666..-12576.5127] \| it/evals=1070/1273 eff=91.2191% N=100 Z=-17722.4(0.00%) \| Like=-17494.12..-0.07 [-49739.3666..-12576.5127] \| it/evals=1080/1283 eff=91.2933% N=100 Z=-17509.5(0.00%) \| Like=-17033.55..-0.07 [-49739.3666..-12576.5127] \| it/evals=1081/1284 eff=91.3007% N=100 Z=-13805.2(0.00%) \| Like=-13616.77..-0.07 [-49739.3666..-12576.5127] \| it/evals=1090/1293 eff=91.3663% N=100 Z=-11448.5(0.00%) \| Like=-11430.06..-0.07 [-12572.1941..-3639.3566] \| it/evals=1100/1304 eff=91.3621% N=100 Z=-10886.1(0.00%) \| Like=-10406.01..-0.07 [-12572.1941..-3639.3566] \| it/evals=1104/1308 eff=91.3907% N=100 Z=-9677.3(0.00%) \| Like=-9405.45..-0.07 [-12572.1941..-3639.3566] \| it/evals=1110/1314 eff=91.4333% N=100 Z=-7396.0(0.00%) \| Like=-7330.88..-0.07 [-12572.1941..-3639.3566] \| it/evals=1120/1325 eff=91.4286% N=100 Z=-6557.4(0.00%) \| Like=-6502.58..-0.07 [-12572.1941..-3639.3566] \| it/evals=1130/1337 eff=91.3500% N=100 Z=-4918.0(0.00%) \| Like=-4673.62..-0.07 [-12572.1941..-3639.3566] \| it/evals=1140/1348 eff=91.3462% N=100 Z=-4140.2(0.00%) \| Like=-4068.57..-0.07 [-12572.1941..-3639.3566] \| it/evals=1150/1358 eff=91.4149% N=100 Z=-3620.6(0.00%) \| Like=-3375.59..-0.07 [-3604.3797..-802.6300] \| it/evals=1160/1368 eff=91.4826% N=100 Z=-2712.2(0.00%) \| Like=-2672.37..-0.00 [-3604.3797..-802.6300] \| it/evals=1170/1380 eff=91.4062% N=100 Z=-2576.7(0.00%) \| Like=-2536.55..-0.00 [-3604.3797..-802.6300] \| it/evals=1173/1383 eff=91.4263% N=100 Z=-2224.7(0.00%) \| Like=-2201.36..-0.00 [-3604.3797..-802.6300] \| it/evals=1180/1391 eff=91.4020% N=100 Z=-1915.5(0.00%) \| Like=-1898.60..-0.00 [-3604.3797..-802.6300] \| it/evals=1190/1404 eff=91.2577% N=100 Z=-1600.7(0.00%) \| Like=-1576.13..-0.00 [-3604.3797..-802.6300] \| it/evals=1200/1417 eff=91.1162% N=100 Z=-1273.5(0.00%) \| Like=-1210.46..-0.00 [-3604.3797..-802.6300] \| it/evals=1210/1429 eff=91.0459% N=100 Z=-1035.2(0.00%) \| Like=-936.01..-0.00 [-3604.3797..-802.6300] \| it/evals=1220/1440 eff=91.0448% N=100 Z=-747.3(0.00%) \| Like=-722.16..-0.00 [-753.4608..-154.1297] \| it/evals=1230/1454 eff=90.8419% N=100 Z=-637.3(0.00%) \| Like=-618.44..-0.00 [-753.4608..-154.1297] \| it/evals=1240/1466 eff=90.7760% N=100 Z=-622.1(0.00%) \| Like=-567.65..-0.00 [-753.4608..-154.1297] \| it/evals=1242/1468 eff=90.7895% N=100 Z=-453.1(0.00%) \| Like=-420.93..-0.00 [-753.4608..-154.1297] \| it/evals=1250/1476 eff=90.8430% N=100 Z=-343.4(0.00%) \| Like=-321.96..-0.00 [-753.4608..-154.1297] \| it/evals=1260/1487 eff=90.8435% N=100 Z=-324.7(0.00%) \| Like=-304.81..-0.00 [-753.4608..-154.1297] \| it/evals=1265/1493 eff=90.8112% N=100 Z=-293.1(0.00%) \| Like=-269.15..-0.00 [-753.4608..-154.1297] \| it/evals=1270/1498 eff=90.8441% N=100 Z=-245.0(0.00%) \| Like=-220.24..-0.00 [-753.4608..-154.1297] \| it/evals=1280/1508 eff=90.9091% N=100 Z=-198.7(0.00%) \| Like=-179.69..-0.00 [-753.4608..-154.1297] \| it/evals=1288/1517 eff=90.8963% N=100 Z=-190.1(0.00%) \| Like=-163.20..-0.00 [-753.4608..-154.1297] \| it/evals=1290/1519 eff=90.9091% N=100 Z=-156.7(0.00%) \| Like=-138.36..-0.00 [-153.8288..-33.2230] \| it/evals=1300/1532 eff=90.7821% N=100 Z=-144.3(0.00%) \| Like=-124.32..-0.00 [-153.8288..-33.2230] \| it/evals=1310/1544 eff=90.7202% N=100 Z=-107.5(0.00%) \| Like=-88.54..-0.00 [-153.8288..-33.2230] \| it/evals=1320/1555 eff=90.7216% N=100 Z=-94.0(0.00%) \| Like=-70.34..-0.00 [-153.8288..-33.2230] \| it/evals=1330/1566 eff=90.7231% N=100 Z=-84.4(0.00%) \| Like=-66.66..-0.00 [-153.8288..-33.2230] \| it/evals=1334/1572 eff=90.6250% N=100 Z=-78.0(0.00%) \| Like=-59.63..-0.00 [-153.8288..-33.2230] \| it/evals=1340/1578 eff=90.6631% N=100 Z=-68.1(0.00%) \| Like=-47.59..-0.00 [-153.8288..-33.2230] \| it/evals=1350/1591 eff=90.5433% N=100 Z=-55.9(0.00%) \| Like=-36.04..-0.00 [-153.8288..-33.2230] \| it/evals=1357/1598 eff=90.5874% N=100 Z=-51.8(0.00%) \| Like=-34.07..-0.00 [-153.8288..-33.2230] \| it/evals=1360/1601 eff=90.6063% N=100 Z=-46.7(0.00%) \| Like=-28.87..-0.00 [-32.3716..-7.9890] \| it/evals=1370/1613 eff=90.5486% N=100 Z=-42.4(0.00%) \| Like=-24.81..-0.00 [-32.3716..-7.9890] \| it/evals=1380/1626 eff=90.4325% N=100 Z=-38.6(0.00%) \| Like=-21.44..-0.00 [-32.3716..-7.9890] \| it/evals=1390/1637 eff=90.4359% N=100 Z=-35.5(0.00%) \| Like=-18.34..-0.00 [-32.3716..-7.9890] \| it/evals=1400/1648 eff=90.4393% N=100 Z=-34.9(0.00%) \| Like=-17.38..-0.00 [-32.3716..-7.9890] \| it/evals=1403/1652 eff=90.3995% N=100 Z=-32.8(0.00%) \| Like=-15.23..-0.00 [-32.3716..-7.9890] \| it/evals=1410/1662 eff=90.2689% N=100 Z=-30.7(0.00%) \| Like=-13.76..-0.00 [-32.3716..-7.9890] \| it/evals=1420/1673 eff=90.2734% N=100 Z=-29.5(0.00%) \| Like=-12.25..-0.00 [-32.3716..-7.9890] \| it/evals=1426/1680 eff=90.2532% N=100 Z=-28.1(0.00%) \| Like=-10.30..-0.00 [-32.3716..-7.9890] \| it/evals=1430/1684 eff=90.2778% N=100 Z=-26.1(0.00%) \| Like=-8.61..-0.00 [-32.3716..-7.9890] \| it/evals=1440/1697 eff=90.1691% N=100 Z=-24.3(0.01%) \| Like=-7.41..-0.00 [-7.8443..-4.9205] \| it/evals=1450/1710 eff=90.0621% N=100 Z=-23.0(0.05%) \| Like=-5.44..-0.00 [-7.8443..-4.9205] \| it/evals=1460/1720 eff=90.1235% N=100 Z=-21.5(0.26%) \| Like=-4.30..-0.00 [-4.3008..-4.1557] \| it/evals=1470/1731 eff=90.1288% N=100 Z=-21.3(0.32%) \| Like=-3.97..-0.00 [-3.9720..-3.8905] \| it/evals=1472/1733 eff=90.1408% N=100 Z=-20.4(0.80%) \| Like=-3.18..-0.00 [-3.1789..-3.0107] \| it/evals=1480/1741 eff=90.1889% N=100 Z=-19.4(2.05%) \| Like=-2.57..-0.00 [-2.6399..-2.5714] \| it/evals=1490/1751 eff=90.2483% N=100 Z=-19.1(2.82%) \| Like=-2.45..-0.00 [-2.4464..-2.3119] \| it/evals=1495/1756 eff=90.2778% N=100 Z=-18.9(3.62%) \| Like=-2.25..-0.00 [-2.2673..-2.2510] \| it/evals=1500/1761 eff=90.3070% N=100 Z=-18.4(5.61%) \| Like=-1.86..-0.00 [-1.8649..-1.8110] \| it/evals=1510/1774 eff=90.2031% N=100 Z=-18.1(7.76%) \| Like=-1.50..-0.00 [-1.4996..-1.4776] \| it/evals=1518/1782 eff=90.2497% N=100 Z=-18.0(8.38%) \| Like=-1.41..-0.00 [-1.4062..-1.3954] \| it/evals=1520/1784 eff=90.2613% N=100 Z=-17.7(11.75%) \| Like=-1.25..-0.00 [-1.2661..-1.2467] \| it/evals=1530/1795 eff=90.2655% N=100 Z=-17.4(15.70%) \| Like=-0.99..-0.00 [-1.0017..-0.9891] \| it/evals=1540/1806 eff=90.2696% N=100 Z=-17.3(16.14%) \| Like=-0.98..-0.00 [-0.9819..-0.9559] \| it/evals=1541/1807 eff=90.2753% N=100 Z=-17.1(20.25%) \| Like=-0.83..-0.00 [-0.8264..-0.8118] \| it/evals=1550/1816 eff=90.3263% N=100 Z=-16.9(24.79%) \| Like=-0.67..-0.00 [-0.6822..-0.6720] \| it/evals=1560/1826 eff=90.3824% N=100 Z=-16.8(26.54%) \| Like=-0.63..-0.00 [-0.6420..-0.6278] \| it/evals=1564/1830 eff=90.4046% N=100 Z=-16.7(29.30%) \| Like=-0.55..-0.00 [-0.5506..-0.5464]\| it/evals=1570/1837 eff=90.3857% N=100 Z=-16.6(33.97%) \| Like=-0.42..-0.00 [-0.4191..-0.4065] \| it/evals=1580/1849 eff=90.3373% N=100 Z=-16.5(37.23%) \| Like=-0.38..-0.00 [-0.3823..-0.3738]\| it/evals=1587/1858 eff=90.2730% N=100 Z=-16.5(38.67%) \| Like=-0.35..-0.00 [-0.3479..-0.3376] \| it/evals=1590/1861 eff=90.2896% N=100 Z=-16.3(43.36%) \| Like=-0.28..-0.00 [-0.2759..-0.2674]\| it/evals=1600/1872 eff=90.2935% N=100 Z=-16.2(47.93%) \| Like=-0.20..-0.00 [-0.2117..-0.1995] \| it/evals=1610/1883 eff=90.2973% N=100 [ultranest] Explored until L=-4e-06 [ultranest] Likelihood function evaluations: 1887 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -15.512 +- 0.959 single instance: logZ = -15.512 +- 0.391 bootstrapped : logZ = -15.438 +- 0.869 tail : logZ = +- 0.404 insert order U test : converged: True correlation: inf iterations a : -0.00365│ ▁ ▁▁▁▁▁▂▁▂▃▃▃▄▆▄▇▅▇▇▇▆▆▃▃▄▄▂▂▁▁▁▁▁ ▁▁ │0.00350 0.00005 +- 0.00098 pointstore: (1715, 5) 1887 1887 0 ====== Running Gauss problem [2] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.004417743572744871 Exception as expected: Cannot resume because loglikelihood function changed, unless resume=resume-similar. To start from scratch, delete '/tmp/tmpmtve497_'. ====== Running Gauss problem [3] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.018817470773834135 [ultranest] trying to salvage points from previous, different run ... [ultranest] Resuming from 1344 stored points Z=-inf(0.00%) \| Like=-5e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=0/1887 eff=inf% N=100 Z=-4e+13(0.00%) \| Like=-4.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=10/1887 eff=inf% N=100 Z=-3e+13(0.00%) \| Like=-3.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=20/1887 eff=inf% N=100 Z=-3e+13(0.00%) \| Like=-3.2e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=23/1887 eff=inf% N=100 Z=-3e+13(0.00%) \| Like=-3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=30/1887 eff=inf% N=100 Z=-3e+13(0.00%) \| Like=-2.6e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=40/1887 eff=inf% N=100 Z=-2e+13(0.00%) \| Like=-2.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=50/1887 eff=inf% N=100 Z=-2e+13(0.00%) \| Like=-1.7e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=60/1887 eff=inf% N=100 Z=-1e+13(0.00%) \| Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=69/1887 eff=inf% N=100 Z=-1e+13(0.00%) \| Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=70/1887 eff=inf% N=100 Z=-1e+13(0.00%) \| Like=-1.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] \| it/evals=80/1887 eff=inf% N=100 Z=-1e+13(0.00%) \| Like=-9.6e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=90/1887 eff=inf% N=100 Z=-8e+12(0.00%) \| Like=-8.1e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=100/1887 eff=inf% N=100 Z=-7e+12(0.00%) \| Like=-7e+12..-1.4e+10 [-1.232e+13..-4.452e+12] \| it/evals=110/1887 eff=inf% N=100 Z=-7e+12(0.00%) \| Like=-6.8e+12..-2.1e+09 [-1.232e+13..-4.452e+12] \| it/evals=115/1887 eff=inf% N=100 Z=-6e+12(0.00%) \| Like=-6.2e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=120/1887 eff=inf% N=100 Z=-5e+12(0.00%) \| Like=-5e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=130/1887 eff=inf% N=100 Z=-5e+12(0.00%) \| Like=-4.6e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=138/1887 eff=inf% N=100 Z=-5e+12(0.00%) \| Like=-4.5e+12..-2e+04 [-1.232e+13..-4.452e+12] \| it/evals=140/1887 eff=inf% N=100 Z=-3e+12(0.00%) \| Like=-3.4e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=150/1887 eff=inf% N=100 Z=-3e+12(0.00%) \| Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=160/1887 eff=inf% N=100 Z=-3e+12(0.00%) \| Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=161/1887 eff=inf% N=100 Z=-2e+12(0.00%) \| Like=-2.1e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=170/1887 eff=inf% N=100 Z=-2e+12(0.00%) \| Like=-1.8e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=180/1887 eff=inf% N=100 Z=-1e+12(0.00%) \| Like=-1.5e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=190/1887 eff=inf% N=100 Z=-1e+12(0.00%) \| Like=-1.1e+12..-2e+04 [-4.394e+12..-1.143e+12] \| it/evals=200/1887 eff=inf% N=100 Z=-1e+12(0.00%) \| Like=-1.1e+12..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=207/1887 eff=inf% N=100 Z=-1e+12(0.00%) \| Like=-1e+12..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=210/1887 eff=inf% N=100 Z=-9e+11(0.00%) \| Like=-8.4e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=220/1887 eff=inf% N=100 Z=-7e+11(0.00%) \| Like=-7.1e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=230/1887 eff=inf% N=100 Z=-6e+11(0.00%) \| Like=-5.8e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=240/1887 eff=inf% N=100 Z=-5e+11(0.00%) \| Like=-5e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=250/1887 eff=inf% N=100 Z=-5e+11(0.00%) \| Like=-4.6e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=253/1887 eff=inf% N=100 Z=-4e+11(0.00%) \| Like=-4.2e+11..-2e+04 [-1.142e+12..-3.697e+11] \| it/evals=260/1887 eff=inf% N=100 Z=-3e+11(0.00%) \| Like=-3.3e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=270/1887 eff=inf% N=100 Z=-3e+11(0.00%) \| Like=-2.7e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=280/1887 eff=inf% N=100 Z=-2e+11(0.00%) \| Like=-2.2e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=290/1887 eff=inf% N=100 Z=-2e+11(0.00%) \| Like=-1.9e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=299/1887 eff=inf% N=100 Z=-2e+11(0.00%) \| Like=-1.8e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=300/1887 eff=inf% N=100 Z=-1e+11(0.00%) \| Like=-1.3e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=310/1887 eff=inf% N=100 Z=-1e+11(0.00%) \| Like=-1.1e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=320/1887 eff=inf% N=100 Z=-1e+11(0.00%) \| Like=-1e+11..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=322/1887 eff=inf% N=100 Z=-9e+10(0.00%) \| Like=-8.4e+10..-2e+04 [-3.628e+11..-8.168e+10] \| it/evals=330/1887 eff=inf% N=100 Z=-8e+10(0.00%) \| Like=-7.8e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=340/1887 eff=inf% N=100 Z=-7e+10(0.00%) \| Like=-7.1e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=345/1887 eff=inf% N=100 Z=-7e+10(0.00%) \| Like=-6.5e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=350/1887 eff=inf% N=100 Z=-5e+10(0.00%) \| Like=-5.2e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=360/1887 eff=inf% N=100 Z=-4e+10(0.00%) \| Like=-4.5e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=368/1887 eff=inf% N=100 Z=-4e+10(0.00%) \| Like=-4.4e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=370/1887 eff=inf% N=100 Z=-4e+10(0.00%) \| Like=-3.8e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=380/1887 eff=inf% N=100 Z=-3e+10(0.00%) \| Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=390/1887 eff=inf% N=100 Z=-3e+10(0.00%) \| Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] \| it/evals=391/1887 eff=inf% N=100 Z=-3e+10(0.00%) \| Like=-2.5e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=400/1887 eff=inf% N=100 Z=-2e+10(0.00%) \| Like=-2.2e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=410/1887 eff=inf% N=100 Z=-2e+10(0.00%) \| Like=-1.7e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=420/1887 eff=inf% N=100 Z=-1e+10(0.00%) \| Like=-1.3e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=430/1887 eff=inf% N=100 Z=-1e+10(0.00%) \| Like=-1.2e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=437/1887 eff=inf% N=100 Z=-1e+10(0.00%) \| Like=-1.1e+10..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=440/1887 eff=inf% N=100 Z=-9e+09(0.00%) \| Like=-8.8e+09..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=450/1887 eff=inf% N=100 Z=-7e+09(0.00%) \| Like=-7.3e+09..-2e+04 [-2.652e+10..-7.121e+09] \| it/evals=460/1887 eff=inf% N=100 Z=-6e+09(0.00%) \| Like=-5.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=470/1887 eff=inf% N=100 Z=-5e+09(0.00%) \| Like=-4.5e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=480/1887 eff=inf% N=100 Z=-4e+09(0.00%) \| Like=-4.3e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=483/1887 eff=inf% N=100 Z=-4e+09(0.00%) \| Like=-3.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=490/1887 eff=inf% N=100 Z=-3e+09(0.00%) \| Like=-3.1e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=500/1887 eff=inf% N=100 Z=-2e+09(0.00%) \| Like=-2.5e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=510/1887 eff=inf% N=100 Z=-2e+09(0.00%) \| Like=-2e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=520/1887 eff=inf% N=100 Z=-2e+09(0.00%) \| Like=-1.7e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=529/1887 eff=inf% N=100 Z=-2e+09(0.00%) \| Like=-1.6e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=530/1887 eff=inf% N=100 Z=-1e+09(0.00%) \| Like=-1.3e+09..-2e+04 [-6.93e+09..-1.231e+09] \| it/evals=540/1887 eff=inf% N=100 Z=-8e+08(0.00%) \| Like=-8.4e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=550/1887 eff=inf% N=100 Z=-8e+08(0.00%) \| Like=-8.2e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=552/1887 eff=inf% N=100 Z=-8e+08(0.00%) \| Like=-7.4e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=560/1887 eff=inf% N=100 Z=-6e+08(0.00%) \| Like=-5.9e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=570/1887 eff=inf% N=100 Z=-6e+08(0.00%) \| Like=-5.4e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=575/1887 eff=inf% N=100 Z=-5e+08(0.00%) \| Like=-5.2e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=580/1887 eff=inf% N=100 Z=-4e+08(0.00%) \| Like=-3.8e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=590/1887 eff=inf% N=100 Z=-3e+08(0.00%) \| Like=-3.1e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=598/1887 eff=inf% N=100 Z=-3e+08(0.00%) \| Like=-2.8e+08..-2e+04 [-1.215e+09..-2.487e+08] \| it/evals=600/1887 eff=inf% N=100 Z=-2e+08(0.00%) \| Like=-2.4e+08..-2e+04 [-2.462e+08..-7.776e+07] \| it/evals=610/1887 eff=inf% N=100 Z=-2e+08(0.00%) \| Like=-2.2e+08..-2e+04 [-2.462e+08..-7.776e+07] \| it/evals=620/1887 eff=inf% N=100 Z=-2e+08(0.00%) \| Like=-2.2e+08..-2e+04 [-2.462e+08..-7.776e+07] \| it/evals=621/1887 eff=inf% N=100 Z=-2e+08(0.00%) \| Like=-1.8e+08..-2e+04 [-2.462e+08..-7.776e+07] \| it/evals=630/1887 eff=inf% N=100 Z=-1e+08(0.00%) \| Like=-1.5e+08..-2e+04 [-2.462e+08..-7.776e+07] \| it/evals=640/1887 eff=inf% N=100 Z=-1e+08(0.00%) \| Like=-1.4e+08..-6e+03 [-2.462e+08..-7.776e+07] \| it/evals=644/1887 eff=inf% N=100 Z=-1e+08(0.00%) \| Like=-1.3e+08..-6e+03 [-2.462e+08..-7.776e+07] \| it/evals=650/1887 eff=inf% N=100 Z=-1e+08(0.00%) \| Like=-1.1e+08..-6e+03 [-2.462e+08..-7.776e+07] \| it/evals=660/1887 eff=inf% N=100 Z=-99582148.9(0.00%) \| Like=-99059562.04..-6001.03 [-2.462e+08..-7.776e+07] \| it/evals=667/1887 eff=inf% N=100 Z=-95151375.1(0.00%) \| Like=-93695215.20..-6001.03 [-2.462e+08..-7.776e+07] \| it/evals=670/1887 eff=inf% N=100 Z=-78679116.9(0.00%) \| Like=-76847161.50..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=680/1887 eff=inf% N=100 Z=-67131957.9(0.00%) \| Like=-66448748.01..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=690/1887 eff=inf% N=100 Z=-52435024.3(0.00%) \| Like=-52096951.40..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=700/1887 eff=inf% N=100 Z=-42465191.4(0.00%) \| Like=-40949386.18..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=710/1887 eff=inf% N=100 Z=-40873207.9(0.00%) \| Like=-40680461.02..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=713/1887 eff=inf% N=100 Z=-34272297.5(0.00%) \| Like=-34010952.05..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=720/1887 eff=inf% N=100 Z=-28152453.6(0.00%) \| Like=-27575809.36..-6001.03 [-76847161.4980..-21155936.6446] \| it/evals=730/1887 eff=inf% N=100 Z=-24901873.1(0.00%) \| Like=-24584385.70..-24.58 [-76847161.4980..-21155936.6446] \| it/evals=740/1887 eff=inf% N=100 Z=-18110812.1(0.00%) \| Like=-17737948.70..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=750/1887 eff=inf% N=100 Z=-15302856.8(0.00%) \| Like=-15168411.63..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=759/1887 eff=inf% N=100 Z=-15168423.8(0.00%) \| Like=-14226207.64..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=760/1887 eff=inf% N=100 Z=-11388935.8(0.00%) \| Like=-11170160.74..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=770/1887 eff=inf% N=100 Z=-9539486.2(0.00%) \| Like=-9255020.99..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=780/1887 eff=inf% N=100 Z=-9247740.3(0.00%) \| Like=-9220863.41..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=782/1887 eff=inf% N=100 Z=-8203667.8(0.00%) \| Like=-7969059.95..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=790/1887 eff=inf% N=100 Z=-6152195.9(0.00%) \| Like=-6110909.52..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=800/1887 eff=inf% N=100 Z=-5168110.7(0.00%) \| Like=-5104656.58..-24.58 [-19936947.1007..-4653936.2656] \| it/evals=810/1887 eff=inf% N=100 Z=-4349040.1(0.00%) \| Like=-4125558.07..-24.58 [-4570566.3677..-801613.5660] \| it/evals=820/1887 eff=inf% N=100 Z=-2816427.2(0.00%) \| Like=-2814439.32..-24.58 [-4570566.3677..-801613.5660] \| it/evals=830/1887 eff=inf% N=100 Z=-2391680.2(0.00%) \| Like=-2352470.82..-24.58 [-4570566.3677..-801613.5660] \| it/evals=840/1887 eff=inf% N=100 Z=-1694108.3(0.00%) \| Like=-1689081.73..-24.58 [-4570566.3677..-801613.5660] \| it/evals=850/1887 eff=inf% N=100 Z=-1689094.8(0.00%) \| Like=-1641951.96..-24.58 [-4570566.3677..-801613.5660] \| it/evals=851/1887 eff=inf% N=100 Z=-1391644.8(0.00%) \| Like=-1379047.10..-24.58 [-4570566.3677..-801613.5660] \| it/evals=860/1887 eff=inf% N=100 Z=-1016250.7(0.00%) \| Like=-1006089.59..-24.58 [-4570566.3677..-801613.5660] \| it/evals=870/1887 eff=inf% N=100 Z=-920877.0(0.00%) \| Like=-900085.39..-24.58 [-4570566.3677..-801613.5660] \| it/evals=874/1887 eff=inf% N=100 Z=-823336.7(0.00%) \| Like=-820186.88..-24.58 [-4570566.3677..-801613.5660] \| it/evals=880/1887 eff=inf% N=100 Z=-718367.8(0.00%) \| Like=-716624.62..-24.58 [-793119.8150..-221964.0581] \| it/evals=890/1887 eff=inf% N=100 Z=-639630.0(0.00%) \| Like=-639396.18..-24.58 [-793119.8150..-221964.0581] \| it/evals=897/1887 eff=inf% N=100 Z=-596673.7(0.00%) \| Like=-575979.25..-24.58 [-793119.8150..-221964.0581] \| it/evals=900/1887 eff=inf% N=100 Z=-491530.1(0.00%) \| Like=-490445.93..-24.58 [-793119.8150..-221964.0581] \| it/evals=910/1887 eff=inf% N=100 Z=-403995.7(0.00%) \| Like=-396361.92..-24.58 [-793119.8150..-221964.0581] \| it/evals=920/1887 eff=inf% N=100 Z=-335628.3(0.00%) \| Like=-335591.94..-4.23 [-793119.8150..-221964.0581] \| it/evals=930/1887 eff=inf% N=100 Z=-281138.1(0.00%) \| Like=-269426.35..-4.23 [-793119.8150..-221964.0581] \| it/evals=940/1887 eff=inf% N=100 Z=-266966.7(0.00%) \| Like=-259391.44..-4.23 [-793119.8150..-221964.0581] \| it/evals=943/1887 eff=inf% N=100 Z=-232224.9(0.00%) \| Like=-227986.30..-4.23 [-793119.8150..-221964.0581] \| it/evals=950/1887 eff=inf% N=100 Z=-195207.5(0.00%) \| Like=-192214.74..-4.23 [-221260.2947..-49999.8216] \| it/evals=960/1887 eff=inf% N=100 Z=-172769.0(0.00%) \| Like=-171647.55..-4.23 [-221260.2947..-49999.8216] \| it/evals=966/1887 eff=inf% N=100 Z=-158733.9(0.00%) \| Like=-156726.85..-4.23 [-221260.2947..-49999.8216] \| it/evals=970/1887 eff=inf% N=100 Z=-123115.0(0.00%) \| Like=-122192.77..-4.23 [-221260.2947..-49999.8216] \| it/evals=980/1887 eff=inf% N=100 Z=-98858.2(0.00%) \| Like=-94395.69..-4.23 [-221260.2947..-49999.8216] \| it/evals=989/1887 eff=inf% N=100 Z=-94410.2(0.00%) \| Like=-93791.71..-4.23 [-221260.2947..-49999.8216] \| it/evals=990/1887 eff=inf% N=100 Z=-75715.2(0.00%) \| Like=-75082.19..-4.23 [-221260.2947..-49999.8216] \| it/evals=1000/1887 eff=inf% N=100 Z=-69119.4(0.00%) \| Like=-69103.96..-3.86 [-221260.2947..-49999.8216] \| it/evals=1010/1887 eff=inf% N=100 Z=-68077.3(0.00%) \| Like=-66958.70..-3.86 [-221260.2947..-49999.8216] \| it/evals=1012/1887 eff=inf% N=100 Z=-59547.1(0.00%) \| Like=-56249.53..-3.86 [-221260.2947..-49999.8216] \| it/evals=1020/1887 eff=inf% N=100 Z=-49104.0(0.00%) \| Like=-46375.62..-3.86 [-49676.3061..-12608.2519] \| it/evals=1030/1887 eff=inf% N=100 Z=-42750.8(0.00%) \| Like=-40665.18..-3.86 [-49676.3061..-12608.2519] \| it/evals=1035/1887 eff=inf% N=100 Z=-38252.8(0.00%) \| Like=-36587.26..-3.86 [-49676.3061..-12608.2519] \| it/evals=1040/1887 eff=inf% N=100 Z=-33612.8(0.00%) \| Like=-32462.69..-3.86 [-49676.3061..-12608.2519] \| it/evals=1050/1887 eff=inf% N=100 Z=-28541.5(0.00%) \| Like=-28487.57..-3.86 [-49676.3061..-12608.2519] \| it/evals=1058/1887 eff=inf% N=100 Z=-28412.2(0.00%) \| Like=-28188.21..-3.86 [-49676.3061..-12608.2519] \| it/evals=1060/1887 eff=inf% N=100 Z=-23692.0(0.00%) \| Like=-21662.39..-3.86 [-49676.3061..-12608.2519] \| it/evals=1070/1887 eff=inf% N=100 Z=-17760.0(0.00%) \| Like=-17456.73..-0.01 [-49676.3061..-12608.2519] \| it/evals=1080/1887 eff=inf% N=100 Z=-13838.4(0.00%) \| Like=-13583.79..-0.01 [-49676.3061..-12608.2519] \| it/evals=1090/1887 eff=inf% N=100 Z=-11478.8(0.00%) \| Like=-11399.84..-0.01 [-12603.9281..-3639.2946] \| it/evals=1100/1887 eff=inf% N=100 Z=-10856.6(0.00%) \| Like=-10434.89..-0.01 [-12603.9281..-3639.2946] \| it/evals=1104/1887 eff=inf% N=100 Z=-9705.1(0.00%) \| Like=-9378.04..-0.01 [-12603.9281..-3639.2946] \| it/evals=1110/1887 eff=inf% N=100 Z=-7371.7(0.00%) \| Like=-7306.69..-0.01 [-12603.9281..-3639.2946] \| it/evals=1120/1887 eff=inf% N=100 Z=-6854.9(0.00%) \| Like=-6766.39..-0.01 [-12603.9281..-3639.2946] \| it/evals=1127/1887 eff=inf% N=100 Z=-6580.3(0.00%) \| Like=-6479.79..-0.01 [-12603.9281..-3639.2946] \| it/evals=1130/1887 eff=inf% N=100 Z=-4937.8(0.00%) \| Like=-4692.98..-0.01 [-12603.9281..-3639.2946] \| it/evals=1140/1887 eff=inf% N=100 Z=-4122.1(0.00%) \| Like=-4067.70..-0.01 [-12603.9281..-3639.2946] \| it/evals=1150/1887 eff=inf% N=100 Z=-3637.6(0.00%) \| Like=-3359.18..-0.01 [-3621.3806..-807.4065] \| it/evals=1160/1887 eff=inf% N=100 Z=-2706.4(0.00%) \| Like=-2657.76..-0.01 [-3621.3806..-807.4065] \| it/evals=1170/1887 eff=inf% N=100 Z=-2238.0(0.00%) \| Like=-2188.11..-0.01 [-3621.3806..-807.4065] \| it/evals=1180/1887 eff=inf% N=100 Z=-1903.2(0.00%) \| Like=-1886.29..-0.01 [-3621.3806..-807.4065] \| it/evals=1190/1887 eff=inf% N=100 Z=-1581.5(0.00%) \| Like=-1542.77..-0.01 [-3621.3806..-807.4065] \| it/evals=1200/1887 eff=inf% N=100 Z=-1237.0(0.00%) \| Like=-1202.19..-0.01 [-3621.3806..-807.4065] \| it/evals=1210/1887 eff=inf% N=100 Z=-1026.2(0.00%) \| Like=-935.24..-0.01 [-3621.3806..-807.4065] \| it/evals=1219/1887 eff=inf% N=100 Z=-952.0(0.00%) \| Like=-931.89..-0.01 [-3621.3806..-807.4065] \| it/evals=1220/1887 eff=inf% N=100 Z=-743.4(0.00%) \| Like=-707.99..-0.01 [-749.1139..-155.2214] \| it/evals=1230/1887 eff=inf% N=100 Z=-629.1(0.00%) \| Like=-611.43..-0.00 [-749.1139..-155.2214] \| it/evals=1240/1887 eff=inf% N=100 Z=-591.4(0.00%) \| Like=-540.26..-0.00 [-749.1139..-155.2214] \| it/evals=1242/1887 eff=inf% N=100 Z=-443.8(0.00%) \| Like=-423.44..-0.00 [-749.1139..-155.2214] \| it/evals=1250/1894 eff=17857.1429% N=100 Z=-338.3(0.00%) \| Like=-319.03..-0.00 [-749.1139..-155.2214] \| it/evals=1260/1906 eff=6631.5789% N=100 Z=-320.4(0.00%) \| Like=-299.89..-0.00 [-749.1139..-155.2214] \| it/evals=1265/1911 eff=5270.8333% N=100 Z=-309.0(0.00%) \| Like=-274.96..-0.00 [-749.1139..-155.2214] \| it/evals=1270/1916 eff=4379.3103% N=100 Z=-258.4(0.00%) \| Like=-236.24..-0.00 [-749.1139..-155.2214] \| it/evals=1280/1927 eff=3200.0000% N=100 Z=-201.0(0.00%) \| Like=-179.77..-0.00 [-749.1139..-155.2214] \| it/evals=1288/1936 eff=2628.5714% N=100 Z=-193.8(0.00%) \| Like=-169.63..-0.00 [-749.1139..-155.2214] \| it/evals=1290/1938 eff=2529.4118% N=100 Z=-161.9(0.00%) \| Like=-130.03..-0.00 [-154.4051..-26.4873] \| it/evals=1300/1949 eff=2096.7742% N=100 Z=-122.9(0.00%) \| Like=-100.59..-0.00 [-154.4051..-26.4873] \| it/evals=1310/1962 eff=1746.6667% N=100 Z=-102.1(0.00%) \| Like=-82.16..-0.00 [-154.4051..-26.4873] \| it/evals=1320/1972 eff=1552.9412% N=100 Z=-84.0(0.00%) \| Like=-65.28..-0.00 [-154.4051..-26.4873] \| it/evals=1330/1982 eff=1400.0000% N=100 Z=-77.8(0.00%) \| Like=-60.49..-0.00 [-154.4051..-26.4873] \| it/evals=1334/1987 eff=1334.0000% N=100 Z=-74.6(0.00%) \| Like=-54.73..-0.00 [-154.4051..-26.4873] \| it/evals=1340/1993 eff=1264.1509% N=100 Z=-66.2(0.00%) \| Like=-43.45..-0.00 [-154.4051..-26.4873] \| it/evals=1350/2004 eff=1153.8462% N=100 Z=-50.5(0.00%) \| Like=-31.91..-0.00 [-154.4051..-26.4873] \| it/evals=1357/2012 eff=1085.6000% N=100 Z=-48.7(0.00%) \| Like=-31.07..-0.00 [-154.4051..-26.4873] \| it/evals=1360/2015 eff=1062.5000% N=100 Z=-43.6(0.00%) \| Like=-26.08..-0.00 [-26.2958..-5.4409] \| it/evals=1370/2027 eff=978.5714% N=100 Z=-39.1(0.00%) \| Like=-21.30..-0.00 [-26.2958..-5.4409] \| it/evals=1380/2037 eff=920.0000% N=100 Z=-35.6(0.00%) \| Like=-18.42..-0.00 [-26.2958..-5.4409] \| it/evals=1390/2049 eff=858.0247% N=100 Z=-32.6(0.00%) \| Like=-14.44..-0.00 [-26.2958..-5.4409] \| it/evals=1400/2059 eff=813.9535% N=100 Z=-28.9(0.00%) \| Like=-11.08..-0.00 [-26.2958..-5.4409] \| it/evals=1410/2070 eff=770.4918% N=100 Z=-26.6(0.00%) \| Like=-9.33..-0.00 [-26.2958..-5.4409] \| it/evals=1420/2082 eff=728.2051% N=100 Z=-25.7(0.00%) \| Like=-8.50..-0.00 [-26.2958..-5.4409] \| it/evals=1426/2089 eff=705.9406% N=100 Z=-24.9(0.01%) \| Like=-7.55..-0.00 [-26.2958..-5.4409] \| it/evals=1430/2094 eff=690.8213% N=100 Z=-23.4(0.03%) \| Like=-6.42..-0.00 [-26.2958..-5.4409] \| it/evals=1440/2104 eff=663.5945% N=100 Z=-22.1(0.12%) \| Like=-4.83..-0.00 [-4.8274..-4.7523] \| it/evals=1450/2114 eff=638.7665% N=100 Z=-20.9(0.43%) \| Like=-3.80..-0.00 [-3.7974..-3.7761] \| it/evals=1460/2124 eff=616.0338% N=100 Z=-20.0(1.03%) \| Like=-3.40..-0.00 [-3.4030..-3.3651] \| it/evals=1470/2134 eff=595.1417% N=100 Z=-19.9(1.19%) \| Like=-3.36..-0.00 [-3.3576..-3.3270] \| it/evals=1472/2136 eff=591.1647% N=100 Z=-19.5(1.79%) \| Like=-2.90..-0.00 [-2.8996..-2.8747] \| it/evals=1480/2144 eff=575.8755% N=100 Z=-19.0(2.98%) \| Like=-2.28..-0.00 [-2.2828..-2.1849] \| it/evals=1490/2155 eff=555.9701% N=100 Z=-18.4(5.21%) \| Like=-1.61..-0.00 [-1.7463..-1.6139] \| it/evals=1500/2167 eff=535.7143% N=100 Z=-17.9(8.23%) \| Like=-1.33..-0.00 [-1.3875..-1.3339] \| it/evals=1510/2178 eff=518.9003% N=100 Z=-17.6(11.17%) \| Like=-1.18..-0.00 [-1.1805..-1.1732]\| it/evals=1518/2188 eff=504.3189% N=100 Z=-17.5(12.00%) \| Like=-1.17..-0.00 [-1.1726..-1.1180] \| it/evals=1520/2190 eff=501.6502% N=100 Z=-17.2(16.09%) \| Like=-0.89..-0.00 [-0.8888..-0.8881]\| it/evals=1530/2201 eff=487.2611% N=100 Z=-17.0(20.67%) \| Like=-0.77..-0.00 [-0.7738..-0.7474] \| it/evals=1540/2211 eff=475.3086% N=100 Z=-17.0(21.17%) \| Like=-0.75..-0.00 [-0.7738..-0.7474] \| it/evals=1541/2212 eff=474.1538% N=100 Z=-16.8(25.27%) \| Like=-0.66..-0.00 [-0.6833..-0.6582] \| it/evals=1550/2222 eff=462.6866% N=100 Z=-16.6(29.85%) \| Like=-0.54..-0.00 [-0.5355..-0.5234] \| it/evals=1560/2236 eff=446.9914% N=100 Z=-16.5(34.80%) \| Like=-0.41..-0.00 [-0.4471..-0.4112] \| it/evals=1570/2246 eff=437.3259% N=100 Z=-16.3(39.66%) \| Like=-0.35..-0.00 [-0.3542..-0.3495]\| it/evals=1580/2258 eff=425.8760% N=100 Z=-16.3(42.87%) \| Like=-0.28..-0.00 [-0.2820..-0.2808]\| it/evals=1587/2267 eff=417.6316% N=100 Z=-16.2(44.25%) \| Like=-0.26..-0.00 [-0.2561..-0.2521]\| it/evals=1590/2270 eff=415.1436% N=100 Z=-16.1(48.74%) \| Like=-0.23..-0.00 [-0.2337..-0.2135] \| it/evals=1600/2282 eff=405.0633% N=100 [ultranest] Explored until L=-2e-05 [ultranest] Likelihood function evaluations: 2284 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -15.401 +- 0.741 single instance: logZ = -15.401 +- 0.390 bootstrapped : logZ = -15.459 +- 0.620 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations a : -0.00331│ ▁▁▁▁▁▁▁▁▂▂▃▅▄▃▇▇▇▇▇▄▆▄▃▄▂▃▁▁ ▁▁▁ ▁ │0.00440 0.00025 +- 0.00098 pointstore: (1703, 5) 397 2284 1887 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=False, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977128652622.04, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=112, regioncalls=480, ndraw=40, logz=-41932563448515.12, remainder_fraction=100.0000%, Lmin=-40508378723011.33, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=122, regioncalls=880, ndraw=40, logz=-33237565078343.30, remainder_fraction=100.0000%, Lmin=-33004788076548.36, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=132, regioncalls=1280, ndraw=40, logz=-29684133841641.27, remainder_fraction=100.0000%, Lmin=-29654731646156.86, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=143, regioncalls=1720, ndraw=40, logz=-26024311452003.38, remainder_fraction=100.0000%, Lmin=-25864311505807.76, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=46, ncalls=151, regioncalls=2040, ndraw=40, logz=-22394867389307.37, remainder_fraction=100.0000%, Lmin=-22267402908949.62, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=155, regioncalls=2200, ndraw=40, logz=-21618903469091.73, remainder_fraction=100.0000%, Lmin=-20657643852261.66, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=165, regioncalls=2600, ndraw=40, logz=-16736505395315.38, remainder_fraction=100.0000%, Lmin=-16631669273078.86, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=69, ncalls=174, regioncalls=2960, ndraw=40, logz=-14754875235796.48, remainder_fraction=100.0000%, Lmin=-13974010155653.97, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=176, regioncalls=3040, ndraw=40, logz=-13974010155659.27, remainder_fraction=100.0000%, Lmin=-13902692147308.39, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=186, regioncalls=3440, ndraw=40, logz=-12514435159574.19, remainder_fraction=100.0000%, Lmin=-12508279160474.38, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=197, regioncalls=3880, ndraw=40, logz=-10193267488313.77, remainder_fraction=100.0000%, Lmin=-9640968563235.02, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=208, regioncalls=4320, ndraw=40, logz=-8200640852030.98, remainder_fraction=100.0000%, Lmin=-8082128050878.53, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=220, regioncalls=4800, ndraw=40, logz=-7173863638817.49, remainder_fraction=100.0000%, Lmin=-6962107832262.44, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=225, regioncalls=5000, ndraw=40, logz=-6806896849592.72, remainder_fraction=100.0000%, Lmin=-6798572125612.82, Lmax=-2101560050.10 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=230, regioncalls=5200, ndraw=40, logz=-6322457704122.88, remainder_fraction=100.0000%, Lmin=-6247007877914.18, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=243, regioncalls=5720, ndraw=40, logz=-5036135578185.74, remainder_fraction=100.0000%, Lmin=-5013134155411.33, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=257, regioncalls=6280, ndraw=40, logz=-4566342513618.33, remainder_fraction=100.0000%, Lmin=-4489051812244.98, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=268, regioncalls=6720, ndraw=40, logz=-3426886969738.49, remainder_fraction=100.0000%, Lmin=-3417861015794.89, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=278, regioncalls=7120, ndraw=40, logz=-2961969420058.14, remainder_fraction=100.0000%, Lmin=-2922089236302.01, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=279, regioncalls=7160, ndraw=40, logz=-2922089236308.22, remainder_fraction=100.0000%, Lmin=-2889249507418.14, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=289, regioncalls=7560, ndraw=40, logz=-2133520045718.24, remainder_fraction=100.0000%, Lmin=-2131391081808.14, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=299, regioncalls=7960, ndraw=40, logz=-1843764249986.19, remainder_fraction=100.0000%, Lmin=-1836388311150.23, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=309, regioncalls=8360, ndraw=40, logz=-1479338126812.93, remainder_fraction=100.0000%, Lmin=-1477274817822.07, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=319, regioncalls=8760, ndraw=40, logz=-1162164164059.82, remainder_fraction=100.0000%, Lmin=-1149513369148.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=326, regioncalls=9040, ndraw=40, logz=-1098683740545.40, remainder_fraction=100.0000%, Lmin=-1085733203899.34, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=329, regioncalls=9160, ndraw=40, logz=-1062199650048.03, remainder_fraction=100.0000%, Lmin=-1036687340045.72, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=342, regioncalls=9680, ndraw=40, logz=-871674334253.59, remainder_fraction=100.0000%, Lmin=-839966514038.46, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=352, regioncalls=10080, ndraw=40, logz=-715976483973.56, remainder_fraction=100.0000%, Lmin=-706773276409.40, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=364, regioncalls=10560, ndraw=40, logz=-593422182128.55, remainder_fraction=100.0000%, Lmin=-576444441337.76, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=376, regioncalls=11080, ndraw=40, logz=-511876960333.87, remainder_fraction=100.0000%, Lmin=-501758974682.00, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=253, ncalls=379, regioncalls=11200, ndraw=40, logz=-478675075304.45, remainder_fraction=100.0000%, Lmin=-455241053559.73, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=387, regioncalls=11520, ndraw=40, logz=-423629485137.20, remainder_fraction=100.0000%, Lmin=-418959245625.39, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=401, regioncalls=12120, ndraw=40, logz=-337456305895.85, remainder_fraction=100.0000%, Lmin=-332415073979.82, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=408, regioncalls=12400, ndraw=40, logz=-298475456646.05, remainder_fraction=100.0000%, Lmin=-298119333065.73, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=412, regioncalls=12600, ndraw=40, logz=-280041079556.47, remainder_fraction=100.0000%, Lmin=-266139199581.03, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=422, regioncalls=13040, ndraw=40, logz=-219987159145.22, remainder_fraction=100.0000%, Lmin=-217170277506.50, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=431, regioncalls=13400, ndraw=40, logz=-186287571926.49, remainder_fraction=100.0000%, Lmin=-186217150611.38, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=432, regioncalls=13440, ndraw=40, logz=-186217150618.98, remainder_fraction=100.0000%, Lmin=-176257223101.81, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=446, regioncalls=14040, ndraw=40, logz=-136032296082.24, remainder_fraction=100.0000%, Lmin=-134941926834.72, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=458, regioncalls=14520, ndraw=40, logz=-106028758932.65, remainder_fraction=100.0000%, Lmin=-105574617114.81, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=460, regioncalls=14600, ndraw=40, logz=-102631626890.59, remainder_fraction=100.0000%, Lmin=-101211365642.63, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=468, regioncalls=14960, ndraw=40, logz=-85746886310.20, remainder_fraction=100.0000%, Lmin=-84170564177.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=478, regioncalls=15360, ndraw=40, logz=-78454705852.75, remainder_fraction=100.0000%, Lmin=-77856855358.69, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=488, regioncalls=15760, ndraw=40, logz=-65217978077.06, remainder_fraction=100.0000%, Lmin=-65071379682.57, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=498, regioncalls=16160, ndraw=40, logz=-52784301112.17, remainder_fraction=100.0000%, Lmin=-52465515313.79, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=506, regioncalls=16480, ndraw=40, logz=-44886006297.10, remainder_fraction=100.0000%, Lmin=-44881183821.51, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=508, regioncalls=16600, ndraw=40, logz=-44337101807.05, remainder_fraction=100.0000%, Lmin=-43924418108.48, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=518, regioncalls=17080, ndraw=40, logz=-38174116980.61, remainder_fraction=100.0000%, Lmin=-38166134224.94, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=528, regioncalls=17480, ndraw=40, logz=-30564921897.35, remainder_fraction=100.0000%, Lmin=-29014402527.49, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=529, regioncalls=17520, ndraw=40, logz=-29014402536.00, remainder_fraction=100.0000%, Lmin=-28739121812.84, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=539, regioncalls=17960, ndraw=40, logz=-25254381195.53, remainder_fraction=100.0000%, Lmin=-25189070092.02, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=410, ncalls=549, regioncalls=18360, ndraw=40, logz=-21660404181.26, remainder_fraction=100.0000%, Lmin=-21548375173.69, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=414, ncalls=553, regioncalls=18560, ndraw=40, logz=-20472052660.36, remainder_fraction=100.0000%, Lmin=-20078668592.97, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=559, regioncalls=18840, ndraw=40, logz=-17503276366.73, remainder_fraction=100.0000%, Lmin=-16696410598.10, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=569, regioncalls=19240, ndraw=40, logz=-13957975006.86, remainder_fraction=100.0000%, Lmin=-13215545136.09, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=581, regioncalls=19720, ndraw=40, logz=-11354970506.81, remainder_fraction=100.0000%, Lmin=-11308593818.41, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=591, regioncalls=20120, ndraw=40, logz=-8954739289.76, remainder_fraction=100.0000%, Lmin=-8802399549.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=460, ncalls=603, regioncalls=20640, ndraw=40, logz=-7358620740.27, remainder_fraction=100.0000%, Lmin=-7312924005.82, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=470, ncalls=615, regioncalls=21120, ndraw=40, logz=-5913717188.92, remainder_fraction=100.0000%, Lmin=-5686842852.59, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=625, regioncalls=21520, ndraw=40, logz=-4561851573.73, remainder_fraction=100.0000%, Lmin=-4534652974.21, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=628, regioncalls=21680, ndraw=40, logz=-4341443065.59, remainder_fraction=100.0000%, Lmin=-4317184186.04, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=490, ncalls=635, regioncalls=21960, ndraw=40, logz=-3683655620.41, remainder_fraction=100.0000%, Lmin=-3668713486.10, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=648, regioncalls=22520, ndraw=40, logz=-3119287299.14, remainder_fraction=100.0000%, Lmin=-3077114603.52, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=506, ncalls=656, regioncalls=22880, ndraw=40, logz=-2711784349.67, remainder_fraction=100.0000%, Lmin=-2672326802.74, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=660, regioncalls=23040, ndraw=40, logz=-2471295503.35, remainder_fraction=100.0000%, Lmin=-2451644303.44, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=671, regioncalls=23480, ndraw=40, logz=-2046833928.20, remainder_fraction=100.0000%, Lmin=-1963025685.85, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=529, ncalls=682, regioncalls=23960, ndraw=40, logz=-1683061127.53, remainder_fraction=100.0000%, Lmin=-1655504010.18, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=685, regioncalls=24080, ndraw=40, logz=-1655504020.08, remainder_fraction=100.0000%, Lmin=-1587929042.93, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=697, regioncalls=24560, ndraw=40, logz=-1345672698.85, remainder_fraction=100.0000%, Lmin=-1324107214.64, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=710, regioncalls=25080, ndraw=40, logz=-842704557.04, remainder_fraction=100.0000%, Lmin=-842098627.35, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=712, regioncalls=25200, ndraw=40, logz=-829471104.02, remainder_fraction=100.0000%, Lmin=-821755543.39, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=721, regioncalls=25560, ndraw=40, logz=-768681282.57, remainder_fraction=100.0000%, Lmin=-741055451.88, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=731, regioncalls=25960, ndraw=40, logz=-598461526.63, remainder_fraction=100.0000%, Lmin=-588030061.40, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=580, ncalls=741, regioncalls=26360, ndraw=40, logz=-523313989.11, remainder_fraction=100.0000%, Lmin=-520429923.57, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=590, ncalls=755, regioncalls=26920, ndraw=40, logz=-389302279.60, remainder_fraction=100.0000%, Lmin=-384227190.96, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=763, regioncalls=27280, ndraw=40, logz=-330216148.35, remainder_fraction=100.0000%, Lmin=-310871070.23, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=765, regioncalls=27360, ndraw=40, logz=-291718407.06, remainder_fraction=100.0000%, Lmin=-277171076.01, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=775, regioncalls=27760, ndraw=40, logz=-245515440.47, remainder_fraction=100.0000%, Lmin=-244117200.51, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=620, ncalls=786, regioncalls=28200, ndraw=40, logz=-222411923.28, remainder_fraction=100.0000%, Lmin=-218434467.04, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=796, regioncalls=28600, ndraw=40, logz=-179666648.72, remainder_fraction=100.0000%, Lmin=-179079251.49, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=806, regioncalls=29000, ndraw=40, logz=-147157505.55, remainder_fraction=100.0000%, Lmin=-146182858.52, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=810, regioncalls=29160, ndraw=40, logz=-139592730.12, remainder_fraction=100.0000%, Lmin=-139232509.33, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=816, regioncalls=29520, ndraw=40, logz=-128990960.00, remainder_fraction=100.0000%, Lmin=-127079723.98, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=827, regioncalls=29960, ndraw=40, logz=-108091218.09, remainder_fraction=100.0000%, Lmin=-105743831.21, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=667, ncalls=835, regioncalls=30360, ndraw=40, logz=-99584971.45, remainder_fraction=100.0000%, Lmin=-99056746.97, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=670, ncalls=838, regioncalls=30480, ndraw=40, logz=-95148616.12, remainder_fraction=100.0000%, Lmin=-93692477.41, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=849, regioncalls=30920, ndraw=40, logz=-78681625.77, remainder_fraction=100.0000%, Lmin=-76849640.99, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=860, regioncalls=31360, ndraw=40, logz=-67129640.49, remainder_fraction=100.0000%, Lmin=-66446442.40, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=872, regioncalls=31840, ndraw=40, logz=-52437072.43, remainder_fraction=100.0000%, Lmin=-52098992.93, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=883, regioncalls=32280, ndraw=40, logz=-42467034.54, remainder_fraction=100.0000%, Lmin=-40947576.24, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=886, regioncalls=32520, ndraw=40, logz=-40875016.23, remainder_fraction=100.0000%, Lmin=-40682265.05, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=893, regioncalls=32800, ndraw=40, logz=-34273953.31, remainder_fraction=100.0000%, Lmin=-34009302.56, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=730, ncalls=904, regioncalls=33240, ndraw=40, logz=-28150952.86, remainder_fraction=100.0000%, Lmin=-27577294.66, Lmax=-6022.96 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=917, regioncalls=33760, ndraw=40, logz=-24903284.59, remainder_fraction=100.0000%, Lmin=-24585788.12, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=927, regioncalls=34160, ndraw=40, logz=-18109608.41, remainder_fraction=100.0000%, Lmin=-17736757.48, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=937, regioncalls=34640, ndraw=40, logz=-15169525.42, remainder_fraction=100.0000%, Lmin=-14227274.47, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=770, ncalls=949, regioncalls=35120, ndraw=40, logz=-11387981.32, remainder_fraction=100.0000%, Lmin=-11171106.07, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=959, regioncalls=35520, ndraw=40, logz=-9540359.81, remainder_fraction=100.0000%, Lmin=-9254160.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=782, ncalls=961, regioncalls=35640, ndraw=40, logz=-9246880.24, remainder_fraction=100.0000%, Lmin=-9220004.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=790, ncalls=969, regioncalls=35960, ndraw=40, logz=-8202857.71, remainder_fraction=100.0000%, Lmin=-7968261.52, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=980, regioncalls=36440, ndraw=40, logz=-6151494.36, remainder_fraction=100.0000%, Lmin=-6110210.34, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=805, ncalls=986, regioncalls=36760, ndraw=40, logz=-5595023.23, remainder_fraction=100.0000%, Lmin=-5544084.40, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=991, regioncalls=36960, ndraw=40, logz=-5168753.73, remainder_fraction=100.0000%, Lmin=-5104017.56, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=1001, regioncalls=37360, ndraw=40, logz=-4348450.29, remainder_fraction=100.0000%, Lmin=-4124983.59, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=1010, regioncalls=37800, ndraw=40, logz=-3288211.79, remainder_fraction=100.0000%, Lmin=-3052967.15, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=830, ncalls=1012, regioncalls=37880, ndraw=40, logz=-2816901.87, remainder_fraction=100.0000%, Lmin=-2813964.84, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1022, regioncalls=38280, ndraw=40, logz=-2391242.81, remainder_fraction=100.0000%, Lmin=-2352037.02, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1033, regioncalls=38720, ndraw=40, logz=-1694476.49, remainder_fraction=100.0000%, Lmin=-1688714.15, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=851, ncalls=1034, regioncalls=38960, ndraw=40, logz=-1688727.26, remainder_fraction=100.0000%, Lmin=-1641589.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=860, ncalls=1044, regioncalls=39360, ndraw=40, logz=-1391311.12, remainder_fraction=100.0000%, Lmin=-1378714.97, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=1056, regioncalls=39840, ndraw=40, logz=-1016206.97, remainder_fraction=100.0000%, Lmin=-1005805.90, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=874, ncalls=1061, regioncalls=40080, ndraw=40, logz=-921148.44, remainder_fraction=100.0000%, Lmin=-899817.07, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1067, regioncalls=40320, ndraw=40, logz=-823593.32, remainder_fraction=100.0000%, Lmin=-820443.05, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=890, ncalls=1078, regioncalls=40760, ndraw=40, logz=-718128.13, remainder_fraction=100.0000%, Lmin=-716385.20, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1090, regioncalls=41240, ndraw=40, logz=-596455.20, remainder_fraction=100.0000%, Lmin=-575764.61, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=910, ncalls=1101, regioncalls=41680, ndraw=40, logz=-491331.87, remainder_fraction=100.0000%, Lmin=-490644.03, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1112, regioncalls=42200, ndraw=40, logz=-403815.91, remainder_fraction=100.0000%, Lmin=-396540.01, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=1122, regioncalls=42600, ndraw=40, logz=-335464.44, remainder_fraction=100.0000%, Lmin=-335428.11, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=940, ncalls=1133, regioncalls=43080, ndraw=40, logz=-281288.10, remainder_fraction=100.0000%, Lmin=-269279.55, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1137, regioncalls=43280, ndraw=40, logz=-267112.83, remainder_fraction=100.0000%, Lmin=-259247.40, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1144, regioncalls=43560, ndraw=40, logz=-232361.23, remainder_fraction=100.0000%, Lmin=-227851.27, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1154, regioncalls=43960, ndraw=40, logz=-195082.59, remainder_fraction=100.0000%, Lmin=-192338.76, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=970, ncalls=1165, regioncalls=44400, ndraw=40, logz=-158846.65, remainder_fraction=100.0000%, Lmin=-156838.84, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=980, ncalls=1176, regioncalls=44840, ndraw=40, logz=-123015.80, remainder_fraction=100.0000%, Lmin=-122093.92, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=1186, regioncalls=45280, ndraw=40, logz=-98769.27, remainder_fraction=100.0000%, Lmin=-94308.81, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1187, regioncalls=45320, ndraw=40, logz=-94323.31, remainder_fraction=100.0000%, Lmin=-93705.11, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1198, regioncalls=45760, ndraw=40, logz=-75793.03, remainder_fraction=100.0000%, Lmin=-75159.71, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=1010, ncalls=1209, regioncalls=46200, ndraw=40, logz=-69193.78, remainder_fraction=100.0000%, Lmin=-69178.34, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1012, ncalls=1212, regioncalls=46360, ndraw=40, logz=-68151.14, remainder_fraction=100.0000%, Lmin=-67031.91, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=1221, regioncalls=46720, ndraw=40, logz=-59478.14, remainder_fraction=100.0000%, Lmin=-56316.63, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1030, ncalls=1232, regioncalls=47160, ndraw=40, logz=-49166.66, remainder_fraction=100.0000%, Lmin=-46314.73, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1035, ncalls=1238, regioncalls=47480, ndraw=40, logz=-42809.28, remainder_fraction=100.0000%, Lmin=-40722.23, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1243, regioncalls=47680, ndraw=40, logz=-38197.53, remainder_fraction=100.0000%, Lmin=-36533.18, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1253, regioncalls=48080, ndraw=40, logz=-33560.94, remainder_fraction=100.0000%, Lmin=-32411.75, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=1263, regioncalls=48480, ndraw=40, logz=-28364.53, remainder_fraction=100.0000%, Lmin=-28235.71, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1070, ncalls=1273, regioncalls=48880, ndraw=40, logz=-23735.59, remainder_fraction=100.0000%, Lmin=-21704.04, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1283, regioncalls=49280, ndraw=40, logz=-17722.35, remainder_fraction=100.0000%, Lmin=-17494.12, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1081, ncalls=1284, regioncalls=49400, ndraw=40, logz=-17509.53, remainder_fraction=100.0000%, Lmin=-17033.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1090, ncalls=1293, regioncalls=49760, ndraw=40, logz=-13805.21, remainder_fraction=100.0000%, Lmin=-13616.77, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1304, regioncalls=50200, ndraw=40, logz=-11448.52, remainder_fraction=100.0000%, Lmin=-11430.06, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1104, ncalls=1308, regioncalls=50400, ndraw=40, logz=-10886.12, remainder_fraction=100.0000%, Lmin=-10406.01, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=1314, regioncalls=50640, ndraw=40, logz=-9677.28, remainder_fraction=100.0000%, Lmin=-9405.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1325, regioncalls=51080, ndraw=40, logz=-7395.99, remainder_fraction=100.0000%, Lmin=-7330.88, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1130, ncalls=1337, regioncalls=51560, ndraw=40, logz=-6557.37, remainder_fraction=100.0000%, Lmin=-6502.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1140, ncalls=1348, regioncalls=52000, ndraw=40, logz=-4917.95, remainder_fraction=100.0000%, Lmin=-4673.62, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1358, regioncalls=52480, ndraw=40, logz=-4140.24, remainder_fraction=100.0000%, Lmin=-4068.57, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1368, regioncalls=52880, ndraw=40, logz=-3620.58, remainder_fraction=100.0000%, Lmin=-3375.59, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1380, regioncalls=53360, ndraw=40, logz=-2712.22, remainder_fraction=100.0000%, Lmin=-2672.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1173, ncalls=1383, regioncalls=53520, ndraw=40, logz=-2576.74, remainder_fraction=100.0000%, Lmin=-2536.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1180, ncalls=1391, regioncalls=53840, ndraw=40, logz=-2224.70, remainder_fraction=100.0000%, Lmin=-2201.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1190, ncalls=1404, regioncalls=54360, ndraw=40, logz=-1915.51, remainder_fraction=100.0000%, Lmin=-1898.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1417, regioncalls=54880, ndraw=40, logz=-1600.73, remainder_fraction=100.0000%, Lmin=-1576.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=1429, regioncalls=55360, ndraw=40, logz=-1273.46, remainder_fraction=100.0000%, Lmin=-1210.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1220, ncalls=1440, regioncalls=55800, ndraw=40, logz=-1035.19, remainder_fraction=100.0000%, Lmin=-936.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=1454, regioncalls=56360, ndraw=40, logz=-747.28, remainder_fraction=100.0000%, Lmin=-722.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1466, regioncalls=56840, ndraw=40, logz=-637.32, remainder_fraction=100.0000%, Lmin=-618.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=1468, regioncalls=56960, ndraw=40, logz=-622.12, remainder_fraction=100.0000%, Lmin=-567.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1476, regioncalls=57280, ndraw=40, logz=-453.14, remainder_fraction=100.0000%, Lmin=-420.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1487, regioncalls=57720, ndraw=40, logz=-343.36, remainder_fraction=100.0000%, Lmin=-321.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1265, ncalls=1493, regioncalls=58000, ndraw=40, logz=-324.71, remainder_fraction=100.0000%, Lmin=-304.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1270, ncalls=1498, regioncalls=58200, ndraw=40, logz=-293.07, remainder_fraction=100.0000%, Lmin=-269.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1508, regioncalls=58600, ndraw=40, logz=-244.96, remainder_fraction=100.0000%, Lmin=-220.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1288, ncalls=1517, regioncalls=59040, ndraw=40, logz=-198.68, remainder_fraction=100.0000%, Lmin=-179.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=1519, regioncalls=59120, ndraw=40, logz=-190.06, remainder_fraction=100.0000%, Lmin=-163.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1532, regioncalls=59640, ndraw=40, logz=-156.72, remainder_fraction=100.0000%, Lmin=-138.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1310, ncalls=1544, regioncalls=60160, ndraw=40, logz=-144.27, remainder_fraction=100.0000%, Lmin=-124.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1555, regioncalls=60600, ndraw=40, logz=-107.47, remainder_fraction=100.0000%, Lmin=-88.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=1566, regioncalls=61040, ndraw=40, logz=-93.99, remainder_fraction=100.0000%, Lmin=-70.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1334, ncalls=1572, regioncalls=61320, ndraw=40, logz=-84.38, remainder_fraction=100.0000%, Lmin=-66.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1340, ncalls=1578, regioncalls=61560, ndraw=40, logz=-78.05, remainder_fraction=100.0000%, Lmin=-59.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1591, regioncalls=62080, ndraw=40, logz=-68.06, remainder_fraction=100.0000%, Lmin=-47.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=1598, regioncalls=62400, ndraw=40, logz=-55.87, remainder_fraction=100.0000%, Lmin=-36.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=1601, regioncalls=62520, ndraw=40, logz=-51.83, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1370, ncalls=1613, regioncalls=63000, ndraw=40, logz=-46.66, remainder_fraction=100.0000%, Lmin=-28.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=1626, regioncalls=63560, ndraw=40, logz=-42.36, remainder_fraction=100.0000%, Lmin=-24.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1390, ncalls=1637, regioncalls=64000, ndraw=40, logz=-38.60, remainder_fraction=100.0000%, Lmin=-21.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1648, regioncalls=64440, ndraw=40, logz=-35.49, remainder_fraction=100.0000%, Lmin=-18.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1403, ncalls=1652, regioncalls=64640, ndraw=40, logz=-34.86, remainder_fraction=100.0000%, Lmin=-17.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=1662, regioncalls=65040, ndraw=40, logz=-32.76, remainder_fraction=100.0000%, Lmin=-15.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1420, ncalls=1673, regioncalls=65480, ndraw=40, logz=-30.69, remainder_fraction=100.0000%, Lmin=-13.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1426, ncalls=1680, regioncalls=65840, ndraw=40, logz=-29.49, remainder_fraction=99.9999%, Lmin=-12.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1430, ncalls=1684, regioncalls=66000, ndraw=40, logz=-28.14, remainder_fraction=99.9997%, Lmin=-10.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1697, regioncalls=66520, ndraw=40, logz=-26.12, remainder_fraction=99.9977%, Lmin=-8.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1710, regioncalls=67040, ndraw=40, logz=-24.32, remainder_fraction=99.9859%, Lmin=-7.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1460, ncalls=1720, regioncalls=67440, ndraw=40, logz=-23.03, remainder_fraction=99.9451%, Lmin=-5.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1470, ncalls=1731, regioncalls=67880, ndraw=40, logz=-21.49, remainder_fraction=99.7426%, Lmin=-4.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=1733, regioncalls=68040, ndraw=40, logz=-21.26, remainder_fraction=99.6811%, Lmin=-3.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=1741, regioncalls=68360, ndraw=40, logz=-20.36, remainder_fraction=99.1955%, Lmin=-3.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1490, ncalls=1751, regioncalls=68760, ndraw=40, logz=-19.45, remainder_fraction=97.9467%, Lmin=-2.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1495, ncalls=1756, regioncalls=69000, ndraw=40, logz=-19.13, remainder_fraction=97.1779%, Lmin=-2.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=1761, regioncalls=69200, ndraw=40, logz=-18.86, remainder_fraction=96.3847%, Lmin=-2.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1510, ncalls=1774, regioncalls=69720, ndraw=40, logz=-18.41, remainder_fraction=94.3893%, Lmin=-1.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=1782, regioncalls=70080, ndraw=40, logz=-18.08, remainder_fraction=92.2357%, Lmin=-1.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=1784, regioncalls=70160, ndraw=40, logz=-18.01, remainder_fraction=91.6178%, Lmin=-1.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=1795, regioncalls=70600, ndraw=40, logz=-17.66, remainder_fraction=88.2455%, Lmin=-1.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1540, ncalls=1806, regioncalls=71040, ndraw=40, logz=-17.37, remainder_fraction=84.3049%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=1807, regioncalls=71160, ndraw=40, logz=-17.34, remainder_fraction=83.8617%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=1816, regioncalls=71520, ndraw=40, logz=-17.13, remainder_fraction=79.7528%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=1826, regioncalls=71920, ndraw=40, logz=-16.92, remainder_fraction=75.2117%, Lmin=-0.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1564, ncalls=1830, regioncalls=72120, ndraw=40, logz=-16.85, remainder_fraction=73.4569%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1570, ncalls=1837, regioncalls=72400, ndraw=40, logz=-16.75, remainder_fraction=70.7038%, Lmin=-0.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1580, ncalls=1849, regioncalls=72880, ndraw=40, logz=-16.59, remainder_fraction=66.0335%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1587, ncalls=1858, regioncalls=73280, ndraw=40, logz=-16.50, remainder_fraction=62.7706%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=1861, regioncalls=73400, ndraw=40, logz=-16.46, remainder_fraction=61.3265%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=1872, regioncalls=73840, ndraw=40, logz=-16.35, remainder_fraction=56.6426%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1610, ncalls=1883, regioncalls=74400, ndraw=40, logz=-16.25, remainder_fraction=52.0720%, Lmin=-0.20, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-4e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 1887 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [-1.94762221e-01 -1.80163717e-05 0.00000000e+00 5.00000005e-01 1.06002728e-04]: u=[0.50000001] -> p=[0.000106] -> L=-1.801637165560648e-05 WARNING ultranest:integrator.py:1282 Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.004417743572744871 DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [-1.94762221e-01 -1.80163717e-05 0.00000000e+00 5.00000005e-01 1.06002728e-04]: u=[0.50000001] -> p=[0.000106] -> L=-1.801637165560648e-05 WARNING ultranest:integrator.py:1282 Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.018817470773834135 INFO ultranest:integrator.py:1200 trying to salvage points from previous, different run ... INFO ultranest:integrator.py:2364 Resuming from 1344 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=1887, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977130652164.57, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=1887, regioncalls=0, ndraw=40, logz=-41932561616957.05, remainder_fraction=100.0000%, Lmin=-40508380523197.54, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=1887, regioncalls=0, ndraw=40, logz=-33237566708988.97, remainder_fraction=100.0000%, Lmin=-33004789701473.93, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=23, ncalls=1887, regioncalls=0, ndraw=40, logz=-32543005101534.51, remainder_fraction=100.0000%, Lmin=-32265055588306.13, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=1887, regioncalls=0, ndraw=40, logz=-29684135382657.41, remainder_fraction=100.0000%, Lmin=-29654730105904.14, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=1887, regioncalls=0, ndraw=40, logz=-26024312894898.02, remainder_fraction=100.0000%, Lmin=-25864312944260.04, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1887, regioncalls=0, ndraw=40, logz=-21618902153982.53, remainder_fraction=100.0000%, Lmin=-20657642566722.29, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=1887, regioncalls=0, ndraw=40, logz=-16736504238198.11, remainder_fraction=100.0000%, Lmin=-16631670426566.43, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=69, ncalls=1887, regioncalls=0, ndraw=40, logz=-14754876322254.05, remainder_fraction=100.0000%, Lmin=-13974009098336.24, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=1887, regioncalls=0, ndraw=40, logz=-13974009098341.54, remainder_fraction=100.0000%, Lmin=-13902691092692.20, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=1887, regioncalls=0, ndraw=40, logz=-12514434158996.97, remainder_fraction=100.0000%, Lmin=-12508280160805.51, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1887, regioncalls=0, ndraw=40, logz=-10193266585284.78, remainder_fraction=100.0000%, Lmin=-9640969441459.09, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1887, regioncalls=0, ndraw=40, logz=-8200640042061.08, remainder_fraction=100.0000%, Lmin=-8082128854974.46, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=1887, regioncalls=0, ndraw=40, logz=-7173864396385.38, remainder_fraction=100.0000%, Lmin=-6962108578565.77, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=1887, regioncalls=0, ndraw=40, logz=-6806897587530.23, remainder_fraction=100.0000%, Lmin=-6798571388126.72, Lmax=-2101547083.83 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=1887, regioncalls=0, ndraw=40, logz=-6322458415316.69, remainder_fraction=100.0000%, Lmin=-6247007170976.70, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=1887, regioncalls=0, ndraw=40, logz=-5036134943448.93, remainder_fraction=100.0000%, Lmin=-5013134788697.02, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=138, ncalls=1887, regioncalls=0, ndraw=40, logz=-4680998274552.75, remainder_fraction=100.0000%, Lmin=-4635047605209.84, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=1887, regioncalls=0, ndraw=40, logz=-4566343118025.00, remainder_fraction=100.0000%, Lmin=-4489051212975.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1887, regioncalls=0, ndraw=40, logz=-3426887493332.78, remainder_fraction=100.0000%, Lmin=-3417861538699.18, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=1887, regioncalls=0, ndraw=40, logz=-2961968933275.30, remainder_fraction=100.0000%, Lmin=-2922088752807.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=1887, regioncalls=0, ndraw=40, logz=-2922088752813.53, remainder_fraction=100.0000%, Lmin=-2889249026647.98, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=1887, regioncalls=0, ndraw=40, logz=-2133520458854.56, remainder_fraction=100.0000%, Lmin=-2131391494738.28, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=1887, regioncalls=0, ndraw=40, logz=-1843763865927.44, remainder_fraction=100.0000%, Lmin=-1836388694440.05, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=1887, regioncalls=0, ndraw=40, logz=-1479337782796.89, remainder_fraction=100.0000%, Lmin=-1477275161598.16, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1887, regioncalls=0, ndraw=40, logz=-1162163859144.88, remainder_fraction=100.0000%, Lmin=-1149513065897.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=1887, regioncalls=0, ndraw=40, logz=-1098683444075.02, remainder_fraction=100.0000%, Lmin=-1085732909181.43, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=1887, regioncalls=0, ndraw=40, logz=-1062199358541.67, remainder_fraction=100.0000%, Lmin=-1036687628030.10, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=1887, regioncalls=0, ndraw=40, logz=-871674598325.47, remainder_fraction=100.0000%, Lmin=-839966254814.02, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=1887, regioncalls=0, ndraw=40, logz=-715976244645.11, remainder_fraction=100.0000%, Lmin=-706773038624.09, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=1887, regioncalls=0, ndraw=40, logz=-593422400013.35, remainder_fraction=100.0000%, Lmin=-576444226592.45, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1887, regioncalls=0, ndraw=40, logz=-511877162695.34, remainder_fraction=100.0000%, Lmin=-501759175033.50, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=253, ncalls=1887, regioncalls=0, ndraw=40, logz=-478675270993.01, remainder_fraction=100.0000%, Lmin=-455241244398.12, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1887, regioncalls=0, ndraw=40, logz=-423629301043.88, remainder_fraction=100.0000%, Lmin=-418959428701.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1887, regioncalls=0, ndraw=40, logz=-337456141589.74, remainder_fraction=100.0000%, Lmin=-332414910905.61, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1887, regioncalls=0, ndraw=40, logz=-280040929879.21, remainder_fraction=100.0000%, Lmin=-266139053666.23, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1887, regioncalls=0, ndraw=40, logz=-219987026484.12, remainder_fraction=100.0000%, Lmin=-217170145697.48, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=1887, regioncalls=0, ndraw=40, logz=-186287694004.38, remainder_fraction=100.0000%, Lmin=-186217028556.61, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1887, regioncalls=0, ndraw=40, logz=-186217028564.21, remainder_fraction=100.0000%, Lmin=-176257104355.97, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1887, regioncalls=0, ndraw=40, logz=-136032191762.64, remainder_fraction=100.0000%, Lmin=-134941822934.04, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1887, regioncalls=0, ndraw=40, logz=-106028851032.08, remainder_fraction=100.0000%, Lmin=-105574709016.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=1887, regioncalls=0, ndraw=40, logz=-102631536278.64, remainder_fraction=100.0000%, Lmin=-101211275659.83, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=1887, regioncalls=0, ndraw=40, logz=-85746803486.61, remainder_fraction=100.0000%, Lmin=-84170482118.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=1887, regioncalls=0, ndraw=40, logz=-78454626629.19, remainder_fraction=100.0000%, Lmin=-77856776437.56, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=1887, regioncalls=0, ndraw=40, logz=-73766873722.80, remainder_fraction=100.0000%, Lmin=-70940842137.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=1887, regioncalls=0, ndraw=40, logz=-65217905845.25, remainder_fraction=100.0000%, Lmin=-65071451833.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=1887, regioncalls=0, ndraw=40, logz=-52784236129.54, remainder_fraction=100.0000%, Lmin=-52465580099.93, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=1887, regioncalls=0, ndraw=40, logz=-44886066221.08, remainder_fraction=100.0000%, Lmin=-44881243742.26, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=1887, regioncalls=0, ndraw=40, logz=-44337042250.65, remainder_fraction=100.0000%, Lmin=-43924358829.89, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=1887, regioncalls=0, ndraw=40, logz=-38174061718.26, remainder_fraction=100.0000%, Lmin=-38166189481.55, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=1887, regioncalls=0, ndraw=40, logz=-30564872448.47, remainder_fraction=100.0000%, Lmin=-29014354349.17, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=1887, regioncalls=0, ndraw=40, logz=-29014354357.68, remainder_fraction=100.0000%, Lmin=-28739169762.10, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=1887, regioncalls=0, ndraw=40, logz=-25254336247.24, remainder_fraction=100.0000%, Lmin=-25189114982.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=410, ncalls=1887, regioncalls=0, ndraw=40, logz=-21660445808.58, remainder_fraction=100.0000%, Lmin=-21548416693.23, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=1887, regioncalls=0, ndraw=40, logz=-17503238946.67, remainder_fraction=100.0000%, Lmin=-16696447145.52, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=1887, regioncalls=0, ndraw=40, logz=-13958008423.01, remainder_fraction=100.0000%, Lmin=-13215512620.83, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=437, ncalls=1887, regioncalls=0, ndraw=40, logz=-11682652172.69, remainder_fraction=100.0000%, Lmin=-11587026393.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=1887, regioncalls=0, ndraw=40, logz=-11355000646.46, remainder_fraction=100.0000%, Lmin=-11308563740.41, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=1887, regioncalls=0, ndraw=40, logz=-8954712524.52, remainder_fraction=100.0000%, Lmin=-8802373012.54, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=460, ncalls=1887, regioncalls=0, ndraw=40, logz=-7358645003.22, remainder_fraction=100.0000%, Lmin=-7312899818.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=470, ncalls=1887, regioncalls=0, ndraw=40, logz=-5913695438.14, remainder_fraction=100.0000%, Lmin=-5686821523.11, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1887, regioncalls=0, ndraw=40, logz=-4561832470.13, remainder_fraction=100.0000%, Lmin=-4534672020.81, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=1887, regioncalls=0, ndraw=40, logz=-4341461702.01, remainder_fraction=100.0000%, Lmin=-4317165601.80, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=490, ncalls=1887, regioncalls=0, ndraw=40, logz=-3683672787.04, remainder_fraction=100.0000%, Lmin=-3668730617.87, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=1887, regioncalls=0, ndraw=40, logz=-3119303096.09, remainder_fraction=100.0000%, Lmin=-3077098913.76, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=1887, regioncalls=0, ndraw=40, logz=-2471309564.08, remainder_fraction=100.0000%, Lmin=-2451630298.77, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1887, regioncalls=0, ndraw=40, logz=-2046821131.87, remainder_fraction=100.0000%, Lmin=-1963038217.51, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=529, ncalls=1887, regioncalls=0, ndraw=40, logz=-1683072731.21, remainder_fraction=100.0000%, Lmin=-1655492501.92, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=1887, regioncalls=0, ndraw=40, logz=-1655492511.82, remainder_fraction=100.0000%, Lmin=-1587917772.00, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1887, regioncalls=0, ndraw=40, logz=-1345683074.51, remainder_fraction=100.0000%, Lmin=-1324117506.82, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1887, regioncalls=0, ndraw=40, logz=-842696346.31, remainder_fraction=100.0000%, Lmin=-842106835.16, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=1887, regioncalls=0, ndraw=40, logz=-829479250.06, remainder_fraction=100.0000%, Lmin=-821747435.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1887, regioncalls=0, ndraw=40, logz=-768673440.75, remainder_fraction=100.0000%, Lmin=-741047752.26, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=1887, regioncalls=0, ndraw=40, logz=-598454607.33, remainder_fraction=100.0000%, Lmin=-588036920.17, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=575, ncalls=1887, regioncalls=0, ndraw=40, logz=-561645953.60, remainder_fraction=100.0000%, Lmin=-542758608.59, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=580, ncalls=1887, regioncalls=0, ndraw=40, logz=-523320459.46, remainder_fraction=100.0000%, Lmin=-520436376.06, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=590, ncalls=1887, regioncalls=0, ndraw=40, logz=-389296698.92, remainder_fraction=100.0000%, Lmin=-384221646.77, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=1887, regioncalls=0, ndraw=40, logz=-330211008.59, remainder_fraction=100.0000%, Lmin=-310876057.20, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1887, regioncalls=0, ndraw=40, logz=-291723237.97, remainder_fraction=100.0000%, Lmin=-277166367.13, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=1887, regioncalls=0, ndraw=40, logz=-245519872.33, remainder_fraction=100.0000%, Lmin=-244121619.74, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=620, ncalls=1887, regioncalls=0, ndraw=40, logz=-222407705.13, remainder_fraction=100.0000%, Lmin=-218430286.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=621, ncalls=1887, regioncalls=0, ndraw=40, logz=-218430297.59, remainder_fraction=100.0000%, Lmin=-215262149.04, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1887, regioncalls=0, ndraw=40, logz=-179662857.52, remainder_fraction=100.0000%, Lmin=-179075466.49, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1887, regioncalls=0, ndraw=40, logz=-147160936.70, remainder_fraction=100.0000%, Lmin=-146186278.28, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=1887, regioncalls=0, ndraw=40, logz=-139596071.91, remainder_fraction=100.0000%, Lmin=-139229171.90, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1887, regioncalls=0, ndraw=40, logz=-128987747.66, remainder_fraction=100.0000%, Lmin=-127082912.47, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=1887, regioncalls=0, ndraw=40, logz=-108094158.74, remainder_fraction=100.0000%, Lmin=-105746739.75, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=667, ncalls=1887, regioncalls=0, ndraw=40, logz=-99582148.92, remainder_fraction=100.0000%, Lmin=-99059562.04, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=670, ncalls=1887, regioncalls=0, ndraw=40, logz=-95151375.11, remainder_fraction=100.0000%, Lmin=-93695215.20, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1887, regioncalls=0, ndraw=40, logz=-78679116.90, remainder_fraction=100.0000%, Lmin=-76847161.50, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=1887, regioncalls=0, ndraw=40, logz=-67131957.92, remainder_fraction=100.0000%, Lmin=-66448748.01, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1887, regioncalls=0, ndraw=40, logz=-52435024.29, remainder_fraction=100.0000%, Lmin=-52096951.40, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=1887, regioncalls=0, ndraw=40, logz=-42465191.36, remainder_fraction=100.0000%, Lmin=-40949386.18, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=1887, regioncalls=0, ndraw=40, logz=-40873207.94, remainder_fraction=100.0000%, Lmin=-40680461.02, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1887, regioncalls=0, ndraw=40, logz=-34272297.45, remainder_fraction=100.0000%, Lmin=-34010952.05, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=730, ncalls=1887, regioncalls=0, ndraw=40, logz=-28152453.57, remainder_fraction=100.0000%, Lmin=-27575809.36, Lmax=-6001.03 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=1887, regioncalls=0, ndraw=40, logz=-24901873.14, remainder_fraction=100.0000%, Lmin=-24584385.70, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1887, regioncalls=0, ndraw=40, logz=-18110812.08, remainder_fraction=100.0000%, Lmin=-17737948.70, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=759, ncalls=1887, regioncalls=0, ndraw=40, logz=-15302856.79, remainder_fraction=100.0000%, Lmin=-15168411.63, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1887, regioncalls=0, ndraw=40, logz=-15168423.83, remainder_fraction=100.0000%, Lmin=-14226207.64, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=770, ncalls=1887, regioncalls=0, ndraw=40, logz=-11388935.83, remainder_fraction=100.0000%, Lmin=-11170160.74, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=1887, regioncalls=0, ndraw=40, logz=-9539486.20, remainder_fraction=100.0000%, Lmin=-9255020.99, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=782, ncalls=1887, regioncalls=0, ndraw=40, logz=-9247740.34, remainder_fraction=100.0000%, Lmin=-9220863.41, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=790, ncalls=1887, regioncalls=0, ndraw=40, logz=-8203667.81, remainder_fraction=100.0000%, Lmin=-7969059.95, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1887, regioncalls=0, ndraw=40, logz=-6152195.90, remainder_fraction=100.0000%, Lmin=-6110909.52, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1887, regioncalls=0, ndraw=40, logz=-5168110.71, remainder_fraction=100.0000%, Lmin=-5104656.58, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=1887, regioncalls=0, ndraw=40, logz=-4349040.12, remainder_fraction=100.0000%, Lmin=-4125558.07, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=830, ncalls=1887, regioncalls=0, ndraw=40, logz=-2816427.18, remainder_fraction=100.0000%, Lmin=-2814439.32, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1887, regioncalls=0, ndraw=40, logz=-2391680.21, remainder_fraction=100.0000%, Lmin=-2352470.82, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1887, regioncalls=0, ndraw=40, logz=-1694108.33, remainder_fraction=100.0000%, Lmin=-1689081.73, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=851, ncalls=1887, regioncalls=0, ndraw=40, logz=-1689094.84, remainder_fraction=100.0000%, Lmin=-1641951.96, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=860, ncalls=1887, regioncalls=0, ndraw=40, logz=-1391644.76, remainder_fraction=100.0000%, Lmin=-1379047.10, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=1887, regioncalls=0, ndraw=40, logz=-1016250.69, remainder_fraction=100.0000%, Lmin=-1006089.59, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=874, ncalls=1887, regioncalls=0, ndraw=40, logz=-920877.00, remainder_fraction=100.0000%, Lmin=-900085.39, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1887, regioncalls=0, ndraw=40, logz=-823336.66, remainder_fraction=100.0000%, Lmin=-820186.88, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=890, ncalls=1887, regioncalls=0, ndraw=40, logz=-718367.84, remainder_fraction=100.0000%, Lmin=-716624.62, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=897, ncalls=1887, regioncalls=0, ndraw=40, logz=-639629.99, remainder_fraction=100.0000%, Lmin=-639396.18, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1887, regioncalls=0, ndraw=40, logz=-596673.66, remainder_fraction=100.0000%, Lmin=-575979.25, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=910, ncalls=1887, regioncalls=0, ndraw=40, logz=-491530.15, remainder_fraction=100.0000%, Lmin=-490445.93, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1887, regioncalls=0, ndraw=40, logz=-403995.67, remainder_fraction=100.0000%, Lmin=-396361.92, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=1887, regioncalls=0, ndraw=40, logz=-335628.28, remainder_fraction=100.0000%, Lmin=-335591.94, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=940, ncalls=1887, regioncalls=0, ndraw=40, logz=-281138.11, remainder_fraction=100.0000%, Lmin=-269426.35, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1887, regioncalls=0, ndraw=40, logz=-266966.68, remainder_fraction=100.0000%, Lmin=-259391.44, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1887, regioncalls=0, ndraw=40, logz=-232224.92, remainder_fraction=100.0000%, Lmin=-227986.30, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1887, regioncalls=0, ndraw=40, logz=-195207.53, remainder_fraction=100.0000%, Lmin=-192214.74, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=1887, regioncalls=0, ndraw=40, logz=-172769.03, remainder_fraction=100.0000%, Lmin=-171647.55, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=970, ncalls=1887, regioncalls=0, ndraw=40, logz=-158733.95, remainder_fraction=100.0000%, Lmin=-156726.85, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=980, ncalls=1887, regioncalls=0, ndraw=40, logz=-123115.01, remainder_fraction=100.0000%, Lmin=-122192.77, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=1887, regioncalls=0, ndraw=40, logz=-98858.17, remainder_fraction=100.0000%, Lmin=-94395.69, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1887, regioncalls=0, ndraw=40, logz=-94410.19, remainder_fraction=100.0000%, Lmin=-93791.71, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1887, regioncalls=0, ndraw=40, logz=-75715.19, remainder_fraction=100.0000%, Lmin=-75082.19, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=1010, ncalls=1887, regioncalls=0, ndraw=40, logz=-69119.40, remainder_fraction=100.0000%, Lmin=-69103.96, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1012, ncalls=1887, regioncalls=0, ndraw=40, logz=-68077.33, remainder_fraction=100.0000%, Lmin=-66958.70, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=1887, regioncalls=0, ndraw=40, logz=-59547.14, remainder_fraction=100.0000%, Lmin=-56249.53, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1030, ncalls=1887, regioncalls=0, ndraw=40, logz=-49103.98, remainder_fraction=100.0000%, Lmin=-46375.62, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1035, ncalls=1887, regioncalls=0, ndraw=40, logz=-42750.79, remainder_fraction=100.0000%, Lmin=-40665.18, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1887, regioncalls=0, ndraw=40, logz=-38252.82, remainder_fraction=100.0000%, Lmin=-36587.26, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1887, regioncalls=0, ndraw=40, logz=-33612.77, remainder_fraction=100.0000%, Lmin=-32462.69, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1058, ncalls=1887, regioncalls=0, ndraw=40, logz=-28541.51, remainder_fraction=100.0000%, Lmin=-28487.57, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=1887, regioncalls=0, ndraw=40, logz=-28412.18, remainder_fraction=100.0000%, Lmin=-28188.21, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1070, ncalls=1887, regioncalls=0, ndraw=40, logz=-23692.05, remainder_fraction=100.0000%, Lmin=-21662.39, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1887, regioncalls=0, ndraw=40, logz=-17760.01, remainder_fraction=100.0000%, Lmin=-17456.73, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1090, ncalls=1887, regioncalls=0, ndraw=40, logz=-13838.44, remainder_fraction=100.0000%, Lmin=-13583.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1887, regioncalls=0, ndraw=40, logz=-11478.78, remainder_fraction=100.0000%, Lmin=-11399.84, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1104, ncalls=1887, regioncalls=0, ndraw=40, logz=-10856.65, remainder_fraction=100.0000%, Lmin=-10434.89, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=1887, regioncalls=0, ndraw=40, logz=-9705.10, remainder_fraction=100.0000%, Lmin=-9378.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1887, regioncalls=0, ndraw=40, logz=-7371.71, remainder_fraction=100.0000%, Lmin=-7306.69, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1127, ncalls=1887, regioncalls=0, ndraw=40, logz=-6854.87, remainder_fraction=100.0000%, Lmin=-6766.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1130, ncalls=1887, regioncalls=0, ndraw=40, logz=-6580.27, remainder_fraction=100.0000%, Lmin=-6479.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1140, ncalls=1887, regioncalls=0, ndraw=40, logz=-4937.77, remainder_fraction=100.0000%, Lmin=-4692.98, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1887, regioncalls=0, ndraw=40, logz=-4122.10, remainder_fraction=100.0000%, Lmin=-4067.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1887, regioncalls=0, ndraw=40, logz=-3637.58, remainder_fraction=100.0000%, Lmin=-3359.18, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1887, regioncalls=0, ndraw=40, logz=-2706.36, remainder_fraction=100.0000%, Lmin=-2657.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1180, ncalls=1887, regioncalls=0, ndraw=40, logz=-2238.02, remainder_fraction=100.0000%, Lmin=-2188.11, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1190, ncalls=1887, regioncalls=0, ndraw=40, logz=-1903.20, remainder_fraction=100.0000%, Lmin=-1886.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1887, regioncalls=0, ndraw=40, logz=-1581.52, remainder_fraction=100.0000%, Lmin=-1542.77, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=1887, regioncalls=0, ndraw=40, logz=-1237.02, remainder_fraction=100.0000%, Lmin=-1202.19, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1219, ncalls=1887, regioncalls=0, ndraw=40, logz=-1026.17, remainder_fraction=100.0000%, Lmin=-935.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1220, ncalls=1887, regioncalls=0, ndraw=40, logz=-952.04, remainder_fraction=100.0000%, Lmin=-931.89, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=1887, regioncalls=0, ndraw=40, logz=-743.38, remainder_fraction=100.0000%, Lmin=-707.99, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1887, regioncalls=0, ndraw=40, logz=-629.08, remainder_fraction=100.0000%, Lmin=-611.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=1887, regioncalls=0, ndraw=40, logz=-591.43, remainder_fraction=100.0000%, Lmin=-540.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1894, regioncalls=320, ndraw=40, logz=-443.82, remainder_fraction=100.0000%, Lmin=-423.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1906, regioncalls=840, ndraw=40, logz=-338.27, remainder_fraction=100.0000%, Lmin=-319.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1265, ncalls=1911, regioncalls=1080, ndraw=40, logz=-320.42, remainder_fraction=100.0000%, Lmin=-299.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1270, ncalls=1916, regioncalls=1280, ndraw=40, logz=-308.97, remainder_fraction=100.0000%, Lmin=-274.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1927, regioncalls=1720, ndraw=40, logz=-258.39, remainder_fraction=100.0000%, Lmin=-236.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1288, ncalls=1936, regioncalls=2160, ndraw=40, logz=-200.98, remainder_fraction=100.0000%, Lmin=-179.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=1938, regioncalls=2240, ndraw=40, logz=-193.77, remainder_fraction=100.0000%, Lmin=-169.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1949, regioncalls=2680, ndraw=40, logz=-161.93, remainder_fraction=100.0000%, Lmin=-130.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1310, ncalls=1962, regioncalls=3200, ndraw=40, logz=-122.86, remainder_fraction=100.0000%, Lmin=-100.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1972, regioncalls=3600, ndraw=40, logz=-102.14, remainder_fraction=100.0000%, Lmin=-82.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=1982, regioncalls=4000, ndraw=40, logz=-83.98, remainder_fraction=100.0000%, Lmin=-65.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1334, ncalls=1987, regioncalls=4280, ndraw=40, logz=-77.82, remainder_fraction=100.0000%, Lmin=-60.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1340, ncalls=1993, regioncalls=4520, ndraw=40, logz=-74.57, remainder_fraction=100.0000%, Lmin=-54.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2004, regioncalls=4960, ndraw=40, logz=-66.17, remainder_fraction=100.0000%, Lmin=-43.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=2012, regioncalls=5360, ndraw=40, logz=-50.51, remainder_fraction=100.0000%, Lmin=-31.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2015, regioncalls=5480, ndraw=40, logz=-48.69, remainder_fraction=100.0000%, Lmin=-31.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1370, ncalls=2027, regioncalls=5960, ndraw=40, logz=-43.60, remainder_fraction=100.0000%, Lmin=-26.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=2037, regioncalls=6400, ndraw=40, logz=-39.07, remainder_fraction=100.0000%, Lmin=-21.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1390, ncalls=2049, regioncalls=6880, ndraw=40, logz=-35.61, remainder_fraction=100.0000%, Lmin=-18.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2059, regioncalls=7320, ndraw=40, logz=-32.64, remainder_fraction=100.0000%, Lmin=-14.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=2070, regioncalls=7760, ndraw=40, logz=-28.95, remainder_fraction=99.9999%, Lmin=-11.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1420, ncalls=2082, regioncalls=8240, ndraw=40, logz=-26.64, remainder_fraction=99.9987%, Lmin=-9.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1426, ncalls=2089, regioncalls=8560, ndraw=40, logz=-25.66, remainder_fraction=99.9964%, Lmin=-8.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1430, ncalls=2094, regioncalls=8760, ndraw=40, logz=-24.86, remainder_fraction=99.9918%, Lmin=-7.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2104, regioncalls=9160, ndraw=40, logz=-23.41, remainder_fraction=99.9664%, Lmin=-6.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=2114, regioncalls=9560, ndraw=40, logz=-22.13, remainder_fraction=99.8781%, Lmin=-4.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1460, ncalls=2124, regioncalls=9960, ndraw=40, logz=-20.87, remainder_fraction=99.5678%, Lmin=-3.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1470, ncalls=2134, regioncalls=10360, ndraw=40, logz=-20.02, remainder_fraction=98.9715%, Lmin=-3.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=2136, regioncalls=10480, ndraw=40, logz=-19.89, remainder_fraction=98.8134%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2144, regioncalls=10800, ndraw=40, logz=-19.47, remainder_fraction=98.2117%, Lmin=-2.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1490, ncalls=2155, regioncalls=11240, ndraw=40, logz=-18.95, remainder_fraction=97.0160%, Lmin=-2.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2167, regioncalls=11720, ndraw=40, logz=-18.37, remainder_fraction=94.7928%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1510, ncalls=2178, regioncalls=12160, ndraw=40, logz=-17.91, remainder_fraction=91.7658%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=2188, regioncalls=12640, ndraw=40, logz=-17.60, remainder_fraction=88.8301%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2190, regioncalls=12720, ndraw=40, logz=-17.53, remainder_fraction=87.9963%, Lmin=-1.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2201, regioncalls=13160, ndraw=40, logz=-17.23, remainder_fraction=83.9101%, Lmin=-0.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1540, ncalls=2211, regioncalls=13560, ndraw=40, logz=-16.98, remainder_fraction=79.3301%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=2212, regioncalls=13640, ndraw=40, logz=-16.96, remainder_fraction=78.8284%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2222, regioncalls=14040, ndraw=40, logz=-16.78, remainder_fraction=74.7285%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2236, regioncalls=14600, ndraw=40, logz=-16.61, remainder_fraction=70.1478%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1570, ncalls=2246, regioncalls=15000, ndraw=40, logz=-16.46, remainder_fraction=65.2006%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1580, ncalls=2258, regioncalls=15480, ndraw=40, logz=-16.33, remainder_fraction=60.3402%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1587, ncalls=2267, regioncalls=15880, ndraw=40, logz=-16.25, remainder_fraction=57.1348%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=2270, regioncalls=16000, ndraw=40, logz=-16.22, remainder_fraction=55.7549%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2282, regioncalls=16480, ndraw=40, logz=-16.12, remainder_fraction=51.2608%, Lmin=-0.23, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-2e-05 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2284 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_store.py::test_hdf5_store	0.11
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [(1, array([101., 155., 413., 213.])), (2, array([ 99., 156., 413., 213.]))]
Passed	tests/test_store.py::test_nullstore	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_transforms.py::test_affine_transform	0.09
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ settings: corr: 0 scaleratio: 1 covmatrix: [1. 0. 0. 1.] (400, 2) settings: corr: 0.6 scaleratio: 1 covmatrix: [1. 0.6 0.6 1. ] (400, 2) settings: corr: 0.95 scaleratio: 1 covmatrix: [1. 0.95 0.95 1. ] (400, 2) settings: corr: 0.999 scaleratio: 1 covmatrix: [1. 0.999 0.999 1. ] (400, 2)
Passed	tests/test_transforms.py::test_wrap	0.03
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ Npoints=10 wrapped_dims=[] Npoints=10 wrapped_dims=[0] Npoints=10 wrapped_dims=[1] Npoints=10 wrapped_dims=[0, 1] Npoints=100 wrapped_dims=[] Npoints=100 wrapped_dims=[0] Npoints=100 wrapped_dims=[1] Npoints=100 wrapped_dims=[0, 1] Npoints=1000 wrapped_dims=[] Npoints=1000 wrapped_dims=[0] Npoints=1000 wrapped_dims=[1] Npoints=1000 wrapped_dims=[0, 1]
Passed	tests/test_samplingpath.py::test_forward	2.39
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_vectorize	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_is_affine_transform	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[0-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[4-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[10-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[17-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[31-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[100-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[1000-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-1]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-4]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-10]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-37]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-53]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-100]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-1000]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_distributed_work_chunk_size[513-513]	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_viz.py::test_rounding_pos	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_viz.py::test_rounding_u	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_viz.py::test_rounding_negpos	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_viz.py::test_rounding_withguess	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_viz.py::test_fmt	0.00
[gw8] linux -- Python 3.10.6 /usr/bin/python3 [gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_popstepsampling.py::test_stepsampler_cubeslice	53.12
[gw4] linux -- Python 3.10.6 /usr/bin/python3 [gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-29.02..-0.12 [-29.0187..-8.0090] \| it/evals=0/536 eff=0.0000% N=400 Z=-31.3(0.00%) \| Like=-26.51..-0.12 [-29.0187..-8.0090] \| it/evals=7/693 eff=2.3891% N=400 Z=-30.7(0.00%) \| Like=-24.76..-0.12 [-29.0187..-8.0090] \| it/evals=9/954 eff=1.6245% N=400 Z=-28.7(0.00%) \| Like=-24.10..-0.12 [-29.0187..-8.0090] \| it/evals=14/1183 eff=1.7880% N=400 Z=-27.2(0.00%) \| Like=-22.74..-0.12 [-29.0187..-8.0090] \| it/evals=21/1672 eff=1.6509% N=400 Z=-26.2(0.00%) \| Like=-22.14..-0.12 [-29.0187..-8.0090] \| it/evals=28/2101 eff=1.6461% N=400 Z=-25.2(0.00%) \| Like=-21.02..-0.12 [-29.0187..-8.0090] \| it/evals=36/2686 eff=1.5748% N=400 Z=-24.3(0.00%) \| Like=-20.71..-0.12 [-29.0187..-8.0090] \| it/evals=44/3319 eff=1.5074% N=400 Z=-23.8(0.00%) \| Like=-19.89..-0.12 [-29.0187..-8.0090] \| it/evals=50/3720 eff=1.5060% N=400 Z=-23.1(0.00%) \| Like=-18.80..-0.12 [-29.0187..-8.0090] \| it/evals=56/4373 eff=1.4095% N=400 Z=-22.0(0.00%) \| Like=-18.12..-0.12 [-29.0187..-8.0090] \| it/evals=64/5028 eff=1.3829% N=400 Z=-21.2(0.00%) \| Like=-17.32..-0.12 [-29.0187..-8.0090] \| it/evals=72/5864 eff=1.3177% N=400 Z=-20.7(0.00%) \| Like=-16.60..-0.12 [-29.0187..-8.0090] \| it/evals=78/6490 eff=1.2808% N=400 Z=-19.8(0.00%) \| Like=-15.90..-0.12 [-29.0187..-8.0090] \| it/evals=86/7143 eff=1.2754% N=400 Z=-19.5(0.00%) \| Like=-15.75..-0.12 [-29.0187..-8.0090] \| it/evals=90/7541 eff=1.2603% N=400 Z=-18.9(0.00%) \| Like=-15.14..-0.12 [-29.0187..-8.0090] \| it/evals=98/8287 eff=1.2426% N=400 Z=-18.7(0.00%) \| Like=-15.08..-0.12 [-29.0187..-8.0090] \| it/evals=100/8459 eff=1.2408% N=400 Z=-18.3(0.00%) \| Like=-14.69..-0.12 [-29.0187..-8.0090] \| it/evals=107/9217 eff=1.2136% N=400 Z=-17.8(0.00%) \| Like=-14.13..-0.12 [-29.0187..-8.0090] \| it/evals=115/9951 eff=1.2041% N=400 Z=-17.3(0.00%) \| Like=-13.68..-0.07 [-29.0187..-8.0090] \| it/evals=123/10701 eff=1.1941% N=400 Z=-16.9(0.00%) \| Like=-13.17..-0.07 [-29.0187..-8.0090] \| it/evals=129/11262 eff=1.1876% N=400 Z=-16.6(0.00%) \| Like=-12.89..-0.07 [-29.0187..-8.0090] \| it/evals=133/11977 eff=1.1488% N=400 Z=-16.1(0.00%) \| Like=-12.62..-0.07 [-29.0187..-8.0090] \| it/evals=141/12747 eff=1.1420% N=400 Z=-15.7(0.00%) \| Like=-12.35..-0.07 [-29.0187..-8.0090] \| it/evals=148/13404 eff=1.1381% N=400 Z=-15.6(0.00%) \| Like=-12.14..-0.07 [-29.0187..-8.0090] \| it/evals=150/13647 eff=1.1323% N=400 Z=-15.2(0.00%) \| Like=-11.58..-0.07 [-29.0187..-8.0090] \| it/evals=157/14399 eff=1.1215% N=400 Z=-14.8(0.00%) \| Like=-11.33..-0.07 [-29.0187..-8.0090] \| it/evals=164/15197 eff=1.1083% N=400 Z=-14.4(0.00%) \| Like=-10.99..-0.07 [-29.0187..-8.0090] \| it/evals=172/16003 eff=1.1024% N=400 Z=-14.2(0.00%) \| Like=-10.72..-0.07 [-29.0187..-8.0090] \| it/evals=177/16565 eff=1.0950% N=400 Z=-13.9(0.00%) \| Like=-10.55..-0.07 [-29.0187..-8.0090] \| it/evals=183/17159 eff=1.0920% N=400 Z=-13.5(0.00%) \| Like=-10.22..-0.07 [-29.0187..-8.0090] \| it/evals=191/18165 eff=1.0751% N=400 Z=-13.3(0.00%) \| Like=-10.14..-0.07 [-29.0187..-8.0090] \| it/evals=197/18639 eff=1.0801% N=400 Z=-13.2(0.00%) \| Like=-9.97..-0.07 [-29.0187..-8.0090] \| it/evals=200/19033 eff=1.0734% N=400 Z=-12.9(0.01%) \| Like=-9.77..-0.07 [-29.0187..-8.0090] \| it/evals=207/19834 eff=1.0651% N=400 Z=-12.7(0.01%) \| Like=-9.45..-0.07 [-29.0187..-8.0090] \| it/evals=215/20615 eff=1.0636% N=400 Z=-12.4(0.01%) \| Like=-9.24..-0.07 [-29.0187..-8.0090] \| it/evals=223/21453 eff=1.0592% N=400 Z=-12.1(0.01%) \| Like=-8.93..-0.07 [-29.0187..-8.0090] \| it/evals=231/22294 eff=1.0551% N=400 Z=-11.9(0.02%) \| Like=-8.73..-0.07 [-29.0187..-8.0090] \| it/evals=239/23143 eff=1.0509% N=400 Z=-11.6(0.02%) \| Like=-8.58..-0.07 [-29.0187..-8.0090] \| it/evals=246/24075 eff=1.0391% N=400 Z=-11.5(0.02%) \| Like=-8.53..-0.07 [-29.0187..-8.0090] \| it/evals=250/24541 eff=1.0356% N=400 Z=-11.3(0.03%) \| Like=-8.41..-0.07 [-29.0187..-8.0090] \| it/evals=258/25455 eff=1.0297% N=400 Z=-11.2(0.03%) \| Like=-8.29..-0.07 [-29.0187..-8.0090] \| it/evals=263/26214 eff=1.0188% N=400 Z=-11.1(0.04%) \| Like=-8.16..-0.07 [-29.0187..-8.0090] \| it/evals=269/26672 eff=1.0239% N=400 Z=-11.0(0.04%) \| Like=-8.12..-0.07 [-29.0187..-8.0090] \| it/evals=270/26673 eff=1.0277% N=400 Z=-10.9(0.04%) \| Like=-8.02..-0.07 [-29.0187..-8.0090] \| it/evals=275/27576 eff=1.0119% N=400 Z=-10.8(0.05%) \| Like=-7.86..-0.07 [-8.0021..-4.4217] \| it/evals=282/28416 eff=1.0066% N=400 Z=-10.6(0.06%) \| Like=-7.71..-0.07 [-8.0021..-4.4217] \| it/evals=290/29359 eff=1.0014% N=400 Z=-10.4(0.08%) \| Like=-7.58..-0.07 [-8.0021..-4.4217] \| it/evals=298/30265 eff=0.9978% N=400 Z=-10.4(0.08%) \| Like=-7.55..-0.07 [-8.0021..-4.4217] \| it/evals=300/30355 eff=1.0015% N=400 Z=-10.3(0.09%) \| Like=-7.43..-0.07 [-8.0021..-4.4217] \| it/evals=307/31184 eff=0.9973% N=400 Z=-10.2(0.10%) \| Like=-7.31..-0.07 [-8.0021..-4.4217] \| it/evals=312/31933 eff=0.9894% N=400 Z=-10.1(0.11%) \| Like=-7.14..-0.07 [-8.0021..-4.4217] \| it/evals=317/32546 eff=0.9861% N=400 Z=-9.9(0.13%) \| Like=-6.99..-0.07 [-8.0021..-4.4217] \| it/evals=323/33284 eff=0.9822% N=400 Z=-9.8(0.14%) \| Like=-6.90..-0.07 [-8.0021..-4.4217] \| it/evals=327/33982 eff=0.9737% N=400 Z=-9.7(0.15%) \| Like=-6.78..-0.07 [-8.0021..-4.4217] \| it/evals=333/34837 eff=0.9670% N=400 Z=-9.6(0.18%) \| Like=-6.70..-0.07 [-8.0021..-4.4217] \| it/evals=340/35660 eff=0.9643% N=400 Z=-9.5(0.20%) \| Like=-6.60..-0.07 [-8.0021..-4.4217] \| it/evals=346/36402 eff=0.9611% N=400 Z=-9.4(0.22%) \| Like=-6.55..-0.07 [-8.0021..-4.4217] \| it/evals=350/36856 eff=0.9601% N=400 Z=-9.3(0.25%) \| Like=-6.45..-0.07 [-8.0021..-4.4217] \| it/evals=358/37810 eff=0.9570% N=400 Z=-9.2(0.26%) \| Like=-6.43..-0.07 [-8.0021..-4.4217] \| it/evals=360/38137 eff=0.9540% N=400 Z=-9.2(0.27%) \| Like=-6.37..-0.07 [-8.0021..-4.4217] \| it/evals=363/38593 eff=0.9504% N=400 Z=-9.1(0.31%) \| Like=-6.29..-0.07 [-8.0021..-4.4217] \| it/evals=371/39451 eff=0.9500% N=400 Z=-8.9(0.35%) \| Like=-6.21..-0.07 [-8.0021..-4.4217] \| it/evals=379/40337 eff=0.9490% N=400 Z=-8.8(0.39%) \| Like=-6.14..-0.07 [-8.0021..-4.4217] \| it/evals=387/41243 eff=0.9475% N=400 Z=-8.7(0.41%) \| Like=-6.09..-0.07 [-8.0021..-4.4217] \| it/evals=393/42174 eff=0.9408% N=400 Z=-8.6(0.45%) \| Like=-6.04..-0.07 [-8.0021..-4.4217] \| it/evals=400/42784 eff=0.9438% N=400 Z=-8.6(0.50%) \| Like=-5.97..-0.07 [-8.0021..-4.4217] \| it/evals=406/43671 eff=0.9383% N=400 Z=-8.5(0.54%) \| Like=-5.93..-0.07 [-8.0021..-4.4217] \| it/evals=412/44560 eff=0.9330% N=400 Z=-8.4(0.58%) \| Like=-5.84..-0.07 [-8.0021..-4.4217] \| it/evals=418/45405 eff=0.9288% N=400 Z=-8.3(0.63%) \| Like=-5.79..-0.07 [-8.0021..-4.4217] \| it/evals=426/46327 eff=0.9276% N=400 Z=-8.3(0.68%) \| Like=-5.71..-0.07 [-8.0021..-4.4217] \| it/evals=433/47200 eff=0.9252% N=400 Z=-8.2(0.75%) \| Like=-5.65..-0.07 [-8.0021..-4.4217] \| it/evals=441/48250 eff=0.9216% N=400 Z=-8.1(0.79%) \| Like=-5.61..-0.07 [-8.0021..-4.4217] \| it/evals=445/48752 eff=0.9203% N=400 Z=-8.1(0.84%) \| Like=-5.56..-0.07 [-8.0021..-4.4217] \| it/evals=450/49284 eff=0.9205% N=400 Z=-8.1(0.87%) \| Like=-5.48..-0.07 [-8.0021..-4.4217] \| it/evals=453/49769 eff=0.9176% N=400 Z=-8.0(0.92%) \| Like=-5.45..-0.07 [-8.0021..-4.4217] \| it/evals=459/50563 eff=0.9150% N=400 Z=-7.9(0.98%) \| Like=-5.31..-0.07 [-8.0021..-4.4217] \| it/evals=467/51611 eff=0.9119% N=400 Z=-7.8(1.04%) \| Like=-5.24..-0.07 [-8.0021..-4.4217] \| it/evals=473/52558 eff=0.9069% N=400 Z=-7.8(1.13%) \| Like=-5.10..-0.07 [-8.0021..-4.4217] \| it/evals=481/53684 eff=0.9027% N=400 Z=-7.7(1.19%) \| Like=-5.06..-0.07 [-8.0021..-4.4217] \| it/evals=487/54410 eff=0.9017% N=400 Z=-7.6(1.28%) \| Like=-4.95..-0.07 [-8.0021..-4.4217] \| it/evals=493/55309 eff=0.8978% N=400 Z=-7.6(1.32%) \| Like=-4.92..-0.07 [-8.0021..-4.4217] \| it/evals=496/55944 eff=0.8930% N=400 Z=-7.6(1.35%) \| Like=-4.90..-0.07 [-8.0021..-4.4217] \| it/evals=498/56321 eff=0.8905% N=400 Z=-7.6(1.38%) \| Like=-4.88..-0.07 [-8.0021..-4.4217] \| it/evals=500/56392 eff=0.8930% N=400 Z=-7.5(1.47%) \| Like=-4.84..-0.07 [-8.0021..-4.4217] \| it/evals=505/57435 eff=0.8854% N=400 Z=-7.4(1.57%) \| Like=-4.75..-0.04 [-8.0021..-4.4217] \| it/evals=513/58513 eff=0.8828% N=400 Z=-7.4(1.67%) \| Like=-4.68..-0.04 [-8.0021..-4.4217] \| it/evals=519/59253 eff=0.8819% N=400 Z=-7.3(1.76%) \| Like=-4.60..-0.04 [-8.0021..-4.4217] \| it/evals=525/60254 eff=0.8771% N=400 Z=-7.2(1.91%) \| Like=-4.53..-0.04 [-8.0021..-4.4217] \| it/evals=532/61187 eff=0.8752% N=400 Z=-7.2(2.04%) \| Like=-4.47..-0.04 [-8.0021..-4.4217] \| it/evals=539/62196 eff=0.8722% N=400 Z=-7.1(2.16%) \| Like=-4.43..-0.04 [-8.0021..-4.4217] \| it/evals=544/62917 eff=0.8702% N=400 Z=-7.1(2.27%) \| Like=-4.42..-0.04 [-4.4216..-3.3233] \| it/evals=550/63774 eff=0.8679% N=400 Z=-7.1(2.32%) \| Like=-4.38..-0.04 [-4.4216..-3.3233] \| it/evals=552/64225 eff=0.8649% N=400 Z=-7.0(2.47%) \| Like=-4.34..-0.04 [-4.4216..-3.3233] \| it/evals=560/65355 eff=0.8621% N=400 Z=-6.9(2.68%) \| Like=-4.30..-0.04 [-4.4216..-3.3233] \| it/evals=568/66384 eff=0.8608% N=400 Z=-6.9(2.88%) \| Like=-4.24..-0.04 [-4.4216..-3.3233] \| it/evals=576/67504 eff=0.8584% N=400 Z=-6.8(3.02%) \| Like=-4.17..-0.04 [-4.4216..-3.3233] \| it/evals=584/68662 eff=0.8555% N=400 Z=-6.7(3.21%) \| Like=-4.13..-0.04 [-4.4216..-3.3233] \| it/evals=591/69706 eff=0.8527% N=400 Z=-6.7(3.38%) \| Like=-4.10..-0.04 [-4.4216..-3.3233] \| it/evals=598/70919 eff=0.8480% N=400 Z=-6.7(3.44%) \| Like=-4.09..-0.04 [-4.4216..-3.3233] \| it/evals=600/71025 eff=0.8496% N=400 Z=-6.6(3.60%) \| Like=-4.07..-0.04 [-4.4216..-3.3233] \| it/evals=606/72196 eff=0.8441% N=400 Z=-6.6(3.81%) \| Like=-4.00..-0.04 [-4.4216..-3.3233] \| it/evals=613/73252 eff=0.8414% N=400 Z=-6.5(4.06%) \| Like=-3.94..-0.04 [-4.4216..-3.3233] \| it/evals=621/74253 eff=0.8409% N=400 Z=-6.5(4.22%) \| Like=-3.89..-0.04 [-4.4216..-3.3233] \| it/evals=627/75009 eff=0.8404% N=400 Z=-6.5(4.31%) \| Like=-3.88..-0.04 [-4.4216..-3.3233] \| it/evals=630/75437 eff=0.8396% N=400 Z=-6.4(4.44%) \| Like=-3.86..-0.04 [-4.4216..-3.3233] \| it/evals=636/76382 eff=0.8370% N=400 Z=-6.4(4.65%) \| Like=-3.79..-0.04 [-4.4216..-3.3233] \| it/evals=642/77350 eff=0.8343% N=400 Z=-6.3(4.94%) \| Like=-3.75..-0.04 [-4.4216..-3.3233] \| it/evals=650/78496 eff=0.8323% N=400 Z=-6.3(5.23%) \| Like=-3.70..-0.04 [-4.4216..-3.3233] \| it/evals=658/79613 eff=0.8307% N=400 Z=-6.2(5.51%) \| Like=-3.66..-0.04 [-4.4216..-3.3233] \| it/evals=666/80634 eff=0.8301% N=400 Z=-6.2(5.72%) \| Like=-3.62..-0.04 [-4.4216..-3.3233] \| it/evals=673/81568 eff=0.8291% N=400 Z=-6.1(5.96%) \| Like=-3.59..-0.04 [-4.4216..-3.3233] \| it/evals=680/82576 eff=0.8275% N=400 Z=-6.1(6.23%) \| Like=-3.54..-0.04 [-4.4216..-3.3233] \| it/evals=688/83669 eff=0.8262% N=400 Z=-6.0(6.54%) \| Like=-3.48..-0.04 [-4.4216..-3.3233] \| it/evals=696/84584 eff=0.8268% N=400 Z=-6.0(6.64%) \| Like=-3.45..-0.04 [-4.4216..-3.3233] \| it/evals=700/85135 eff=0.8261% N=400 Z=-6.0(6.89%) \| Like=-3.41..-0.04 [-4.4216..-3.3233] \| it/evals=705/86108 eff=0.8226% N=400 Z=-6.0(7.13%) \| Like=-3.37..-0.04 [-4.4216..-3.3233] \| it/evals=712/87277 eff=0.8195% N=400 Z=-5.9(7.36%) \| Like=-3.32..-0.04 [-3.3224..-2.9811] \| it/evals=718/88239 eff=0.8174% N=400 Z=-5.9(7.46%) \| Like=-3.31..-0.04 [-3.3224..-2.9811] \| it/evals=720/88371 eff=0.8185% N=400 Z=-5.9(7.77%) \| Like=-3.27..-0.04 [-3.3224..-2.9811] \| it/evals=726/89374 eff=0.8160% N=400 Z=-5.8(8.08%) \| Like=-3.23..-0.04 [-3.3224..-2.9811] \| it/evals=733/90293 eff=0.8154% N=400 Z=-5.8(8.23%) \| Like=-3.20..-0.04 [-3.3224..-2.9811] \| it/evals=740/91297 eff=0.8141% N=400 Z=-5.8(8.48%) \| Like=-3.14..-0.04 [-3.3224..-2.9811] \| it/evals=746/92331 eff=0.8115% N=400 Z=-5.7(8.70%) \| Like=-3.13..-0.04 [-3.3224..-2.9811] \| it/evals=750/92915 eff=0.8107% N=400 Z=-5.7(8.89%) \| Like=-3.11..-0.04 [-3.3224..-2.9811] \| it/evals=756/94000 eff=0.8077% N=400 Z=-5.7(9.29%) \| Like=-3.06..-0.04 [-3.3224..-2.9811] \| it/evals=764/95164 eff=0.8062% N=400 Z=-5.6(9.72%) \| Like=-3.02..-0.04 [-3.3224..-2.9811] \| it/evals=772/96298 eff=0.8050% N=400 Z=-5.6(10.08%) \| Like=-2.97..-0.04 [-2.9692..-2.8625] \| it/evals=778/97206 eff=0.8037% N=400 Z=-5.6(10.44%) \| Like=-2.94..-0.04 [-2.9692..-2.8625] \| it/evals=785/98334 eff=0.8016% N=400 Z=-5.5(10.85%) \| Like=-2.87..-0.04 [-2.9692..-2.8625] \| it/evals=793/99477 eff=0.8004% N=400 Z=-5.5(11.09%) \| Like=-2.85..-0.04 [-2.8574..-2.8235] \| it/evals=799/100468 eff=0.7985% N=400 Z=-5.5(11.16%) \| Like=-2.85..-0.04 [-2.8574..-2.8235] \| it/evals=800/100506 eff=0.7992% N=400 Z=-5.5(11.42%) \| Like=-2.81..-0.04 [-2.8234..-2.7987] \| it/evals=806/101434 eff=0.7978% N=400 Z=-5.5(11.68%) \| Like=-2.80..-0.04 [-2.7975..-2.7923]\| it/evals=810/102038 eff=0.7969% N=400 Z=-5.4(11.83%) \| Like=-2.78..-0.04 [-2.7782..-2.7749]\| it/evals=814/102776 eff=0.7951% N=400 Z=-5.4(12.25%) \| Like=-2.76..-0.04 [-2.7568..-2.7543]\| it/evals=821/103984 eff=0.7926% N=400 Z=-5.4(12.62%) \| Like=-2.74..-0.04 [-2.7421..-2.7343]\| it/evals=829/105283 eff=0.7904% N=400 Z=-5.3(13.09%) \| Like=-2.71..-0.04 [-2.7101..-2.7091]\| it/evals=836/106162 eff=0.7905% N=400 Z=-5.3(13.38%) \| Like=-2.70..-0.04 [-2.7010..-2.6973]\| it/evals=842/107262 eff=0.7879% N=400 Z=-5.3(13.80%) \| Like=-2.68..-0.04 [-2.6849..-2.6631] \| it/evals=849/108432 eff=0.7859% N=400 Z=-5.3(13.85%) \| Like=-2.66..-0.04 [-2.6849..-2.6631] \| it/evals=850/108444 eff=0.7867% N=400 Z=-5.3(14.28%) \| Like=-2.64..-0.04 [-2.6406..-2.6382]\| it/evals=856/109634 eff=0.7836% N=400 Z=-5.2(14.79%) \| Like=-2.63..-0.04 [-2.6259..-2.6247]\| it/evals=864/110880 eff=0.7820% N=400 Z=-5.2(15.07%) \| Like=-2.60..-0.04 [-2.5996..-2.5972]\| it/evals=869/111876 eff=0.7795% N=400 Z=-5.2(15.53%) \| Like=-2.57..-0.04 [-2.5669..-2.5655]\| it/evals=877/113071 eff=0.7784% N=400 Z=-5.1(16.12%) \| Like=-2.53..-0.04 [-2.5327..-2.5295]\| it/evals=886/114293 eff=0.7779% N=400 Z=-5.1(16.65%) \| Like=-2.49..-0.04 [-2.4943..-2.4929]\| it/evals=894/115521 eff=0.7766% N=400 Z=-5.1(17.09%) \| Like=-2.48..-0.04 [-2.4828..-2.4795]\| it/evals=900/116779 eff=0.7733% N=400 Z=-5.1(17.52%) \| Like=-2.47..-0.04 [-2.4686..-2.4683]\| it/evals=907/117816 eff=0.7725% N=400 Z=-5.0(17.81%) \| Like=-2.45..-0.03 [-2.4528..-2.4519]\| it/evals=915/119020 eff=0.7714% N=400 Z=-5.0(18.29%) \| Like=-2.42..-0.03 [-2.4219..-2.4207]\| it/evals=923/120345 eff=0.7695% N=400 Z=-5.0(18.85%) \| Like=-2.38..-0.03 [-2.3821..-2.3816]\| it/evals=931/121552 eff=0.7685% N=400 Z=-5.0(19.36%) \| Like=-2.34..-0.03 [-2.3443..-2.3378]\| it/evals=939/122806 eff=0.7671% N=400 Z=-4.9(19.97%) \| Like=-2.31..-0.03 [-2.3133..-2.3082]\| it/evals=948/124131 eff=0.7662% N=400 Z=-4.9(20.07%) \| Like=-2.31..-0.03 [-2.3067..-2.3053]\| it/evals=950/124525 eff=0.7654% N=400 Z=-4.9(20.76%) \| Like=-2.28..-0.03 [-2.2752..-2.2715]\| it/evals=959/125834 eff=0.7645% N=400 Z=-4.9(21.47%) \| Like=-2.24..-0.03 [-2.2407..-2.2397]\| it/evals=968/127106 eff=0.7640% N=400 Z=-4.8(21.91%) \| Like=-2.22..-0.03 [-2.2248..-2.2178]\| it/evals=975/128335 eff=0.7621% N=400 Z=-4.8(22.45%) \| Like=-2.20..-0.03 [-2.1973..-2.1911]\| it/evals=982/129796 eff=0.7589% N=400 Z=-4.8(22.88%) \| Like=-2.16..-0.03 [-2.1561..-2.1559]\| it/evals=989/131025 eff=0.7571% N=400 Z=-4.8(22.90%) \| Like=-2.16..-0.03 [-2.1559..-2.1421] \| it/evals=990/131028 eff=0.7579% N=400 Z=-4.8(23.42%) \| Like=-2.13..-0.03 [-2.1280..-2.1250]\| it/evals=997/132268 eff=0.7561% N=400 Z=-4.8(23.67%) \| Like=-2.12..-0.03 [-2.1239..-2.1174]\| it/evals=1000/132303 eff=0.7581% N=400 Z=-4.8(24.09%) \| Like=-2.09..-0.03 [-2.0875..-2.0860]\| it/evals=1005/133447 eff=0.7554% N=400 Z=-4.7(24.82%) \| Like=-2.06..-0.03 [-2.0643..-2.0582]\| it/evals=1014/134816 eff=0.7544% N=400 Z=-4.7(25.35%) \| Like=-2.04..-0.03 [-2.0414..-2.0388]\| it/evals=1021/135885 eff=0.7536% N=400 Z=-4.7(25.71%) \| Like=-2.02..-0.03 [-2.0203..-2.0155]\| it/evals=1028/137173 eff=0.7516% N=400 Z=-4.7(26.30%) \| Like=-2.00..-0.03 [-1.9990..-1.9960]\| it/evals=1036/138360 eff=0.7509% N=400 Z=-4.7(26.77%) \| Like=-1.98..-0.03 [-1.9766..-1.9623] \| it/evals=1043/139538 eff=0.7496% N=400 Z=-4.6(27.21%) \| Like=-1.94..-0.03 [-1.9436..-1.9429]\| it/evals=1048/140562 eff=0.7477% N=400 Z=-4.6(27.38%) \| Like=-1.94..-0.03 [-1.9375..-1.9336]\| it/evals=1050/140682 eff=0.7485% N=400 Z=-4.6(27.77%) \| Like=-1.93..-0.03 [-1.9272..-1.9231]\| it/evals=1055/141823 eff=0.7460% N=400 Z=-4.6(28.07%) \| Like=-1.90..-0.03 [-1.9010..-1.8971]\| it/evals=1060/142697 eff=0.7449% N=400 Z=-4.6(28.68%) \| Like=-1.88..-0.03 [-1.8769..-1.8698]\| it/evals=1068/143907 eff=0.7442% N=400 Z=-4.6(29.11%) \| Like=-1.86..-0.03 [-1.8600..-1.8557]\| it/evals=1073/144733 eff=0.7434% N=400 Z=-4.6(29.60%) \| Like=-1.83..-0.03 [-1.8289..-1.8246]\| it/evals=1079/145847 eff=0.7419% N=400 Z=-4.5(29.87%) \| Like=-1.81..-0.03 [-1.8077..-1.8053]\| it/evals=1083/146495 eff=0.7413% N=400 Z=-4.5(30.53%) \| Like=-1.79..-0.03 [-1.7927..-1.7916]\| it/evals=1091/148031 eff=0.7390% N=400 Z=-4.5(31.06%) \| Like=-1.78..-0.03 [-1.7772..-1.7753]\| it/evals=1099/149288 eff=0.7381% N=400 Z=-4.5(31.15%) \| Like=-1.78..-0.03 [-1.7753..-1.7745]\| it/evals=1100/149295 eff=0.7388% N=400 Z=-4.5(31.59%) \| Like=-1.76..-0.03 [-1.7586..-1.7517]\| it/evals=1106/150295 eff=0.7378% N=400 Z=-4.5(31.92%) \| Like=-1.75..-0.03 [-1.7461..-1.7415]\| it/evals=1111/151105 eff=0.7372% N=400 Z=-4.5(32.32%) \| Like=-1.73..-0.03 [-1.7346..-1.7313]\| it/evals=1116/152390 eff=0.7343% N=400 Z=-4.4(32.75%) \| Like=-1.71..-0.03 [-1.7080..-1.7060]\| it/evals=1123/153502 eff=0.7335% N=400 Z=-4.4(33.46%) \| Like=-1.69..-0.03 [-1.6872..-1.6855]\| it/evals=1131/154756 eff=0.7327% N=400 Z=-4.4(33.89%) \| Like=-1.67..-0.03 [-1.6693..-1.6684]\| it/evals=1136/155670 eff=0.7316% N=400 Z=-4.4(34.37%) \| Like=-1.65..-0.03 [-1.6460..-1.6448]\| it/evals=1142/156840 eff=0.7300% N=400 Z=-4.4(34.70%) \| Like=-1.62..-0.03 [-1.6231..-1.6221]\| it/evals=1147/157659 eff=0.7294% N=400 Z=-4.4(34.85%) \| Like=-1.62..-0.03 [-1.6204..-1.6127]\| it/evals=1150/158021 eff=0.7296% N=400 Z=-4.4(35.43%) \| Like=-1.60..-0.03 [-1.5980..-1.5940]\| it/evals=1158/159283 eff=0.7288% N=400 Z=-4.4(35.82%) \| Like=-1.59..-0.03 [-1.5901..-1.5884]\| it/evals=1163/160304 eff=0.7273% N=400 Z=-4.3(36.36%) \| Like=-1.57..-0.03 [-1.5687..-1.5677]\| it/evals=1170/161116 eff=0.7280% N=400 Z=-4.3(36.87%) \| Like=-1.55..-0.03 [-1.5518..-1.5517]\| it/evals=1176/162144 eff=0.7271% N=400 Z=-4.3(37.46%) \| Like=-1.54..-0.03 [-1.5449..-1.5443]\| it/evals=1183/163297 eff=0.7262% N=400 Z=-4.3(37.88%) \| Like=-1.53..-0.03 [-1.5265..-1.5214]\| it/evals=1189/164331 eff=0.7253% N=400 Z=-4.3(38.17%) \| Like=-1.52..-0.03 [-1.5152..-1.5138]\| it/evals=1194/165292 eff=0.7241% N=400 Z=-4.3(38.68%) \| Like=-1.50..-0.03 [-1.5038..-1.5029]\| it/evals=1200/166312 eff=0.7233% N=400 Z=-4.3(39.44%) \| Like=-1.49..-0.03 [-1.4892..-1.4880]\| it/evals=1208/167575 eff=0.7226% N=400 Z=-4.2(40.03%) \| Like=-1.47..-0.03 [-1.4707..-1.4687]\| it/evals=1216/168949 eff=0.7215% N=400 Z=-4.2(40.34%) \| Like=-1.46..-0.03 [-1.4630..-1.4610]\| it/evals=1221/169986 eff=0.7200% N=400 Z=-4.2(40.76%) \| Like=-1.44..-0.03 [-1.4358..-1.4332]\| it/evals=1229/171180 eff=0.7196% N=400 Z=-4.2(41.14%) \| Like=-1.41..-0.03 [-1.4145..-1.4128]\| it/evals=1234/172349 eff=0.7177% N=400 Z=-4.2(41.54%) \| Like=-1.39..-0.03 [-1.3878..-1.3791]\| it/evals=1239/173329 eff=0.7165% N=400 Z=-4.2(42.23%) \| Like=-1.36..-0.03 [-1.3627..-1.3601]\| it/evals=1247/174627 eff=0.7157% N=400 Z=-4.2(42.48%) \| Like=-1.36..-0.03 [-1.3573..-1.3572]\| it/evals=1250/174686 eff=0.7172% N=400 Z=-4.2(42.67%) \| Like=-1.35..-0.03 [-1.3506..-1.3490]\| it/evals=1252/175596 eff=0.7146% N=400 Z=-4.2(43.21%) \| Like=-1.33..-0.03 [-1.3322..-1.3305]\| it/evals=1259/176652 eff=0.7143% N=400 Z=-4.2(43.31%) \| Like=-1.33..-0.03 [-1.3305..-1.3289]\| it/evals=1260/176886 eff=0.7139% N=400 Z=-4.2(43.89%) \| Like=-1.32..-0.03 [-1.3185..-1.3156]\| it/evals=1267/177902 eff=0.7138% N=400 Z=-4.1(44.33%) \| Like=-1.31..-0.03 [-1.3069..-1.3062]\| it/evals=1273/178998 eff=0.7128% N=400 Z=-4.1(44.96%) \| Like=-1.29..-0.03 [-1.2851..-1.2840]\| it/evals=1282/180274 eff=0.7127% N=400 Z=-4.1(45.42%) \| Like=-1.27..-0.03 [-1.2719..-1.2719]\| it/evals=1289/181554 eff=0.7115% N=400 Z=-4.1(46.03%) \| Like=-1.26..-0.03 [-1.2645..-1.2623]\| it/evals=1298/182819 eff=0.7115% N=400 Z=-4.1(46.21%) \| Like=-1.26..-0.03 [-1.2611..-1.2610]\| it/evals=1300/183109 eff=0.7115% N=400 Z=-4.1(46.69%) \| Like=-1.24..-0.03 [-1.2438..-1.2438]\| it/evals=1306/184349 eff=0.7100% N=400 Z=-4.1(47.27%) \| Like=-1.24..-0.03 [-1.2368..-1.2340]\| it/evals=1315/185624 eff=0.7100% N=400 Z=-4.1(47.87%) \| Like=-1.21..-0.03 [-1.2213..-1.2071] \| it/evals=1322/186767 eff=0.7094% N=400 Z=-4.0(48.59%) \| Like=-1.20..-0.03 [-1.1960..-1.1909]\| it/evals=1330/187985 eff=0.7090% N=400 Z=-4.0(48.87%) \| Like=-1.19..-0.03 [-1.1869..-1.1853]\| it/evals=1335/188900 eff=0.7082% N=400 Z=-4.0(49.26%) \| Like=-1.17..-0.03 [-1.1729..-1.1723]\| it/evals=1341/189874 eff=0.7077% N=400 Z=-4.0(49.95%) \| Like=-1.15..-0.03 [-1.1467..-1.1466]\| it/evals=1349/191131 eff=0.7073% N=400 Z=-4.0(50.01%) \| Like=-1.15..-0.03 [-1.1466..-1.1435]\| it/evals=1350/191558 eff=0.7062% N=400 Z=-4.0(50.55%) \| Like=-1.13..-0.03 [-1.1343..-1.1332]\| it/evals=1357/192760 eff=0.7054% N=400 Z=-4.0(51.18%) \| Like=-1.12..-0.03 [-1.1184..-1.1181]\| it/evals=1365/194107 eff=0.7047% N=400 Z=-4.0(51.83%) \| Like=-1.10..-0.03 [-1.1031..-1.0998]\| it/evals=1373/195417 eff=0.7040% N=400 Z=-4.0(52.30%) \| Like=-1.09..-0.03 [-1.0898..-1.0887]\| it/evals=1381/196696 eff=0.7035% N=400 Z=-4.0(52.94%) \| Like=-1.08..-0.03 [-1.0811..-1.0800]\| it/evals=1389/197982 eff=0.7030% N=400 Z=-4.0(53.43%) \| Like=-1.07..-0.03 [-1.0683..-1.0609]\| it/evals=1395/199016 eff=0.7024% N=400 Z=-3.9(53.81%) \| Like=-1.05..-0.03 [-1.0548..-1.0535]\| it/evals=1400/200002 eff=0.7014% N=400 Z=-3.9(54.37%) \| Like=-1.05..-0.03 [-1.0462..-1.0455]\| it/evals=1408/201398 eff=0.7005% N=400 Z=-3.9(54.91%) \| Like=-1.04..-0.03 [-1.0397..-1.0395]\| it/evals=1416/202794 eff=0.6996% N=400 Z=-3.9(55.48%) \| Like=-1.03..-0.03 [-1.0303..-1.0266]\| it/evals=1424/204211 eff=0.6987% N=400 Z=-3.9(56.10%) \| Like=-1.02..-0.03 [-1.0217..-1.0210]\| it/evals=1432/205426 eff=0.6984% N=400 Z=-3.9(56.68%) \| Like=-1.01..-0.03 [-1.0070..-1.0039]\| it/evals=1440/206860 eff=0.6975% N=400 Z=-3.9(57.15%) \| Like=-0.99..-0.03 [-0.9869..-0.9866]\| it/evals=1446/207891 eff=0.6969% N=400 Z=-3.9(57.44%) \| Like=-0.98..-0.03 [-0.9832..-0.9830]\| it/evals=1450/208561 eff=0.6966% N=400 Z=-3.9(57.95%) \| Like=-0.98..-0.03 [-0.9787..-0.9783]\| it/evals=1457/209885 eff=0.6955% N=400 Z=-3.9(58.48%) \| Like=-0.97..-0.03 [-0.9731..-0.9717]\| it/evals=1464/211060 eff=0.6950% N=400 Z=-3.9(59.01%) \| Like=-0.97..-0.03 [-0.9661..-0.9654]\| it/evals=1472/212368 eff=0.6944% N=400 Z=-3.8(59.48%) \| Like=-0.96..-0.03 [-0.9569..-0.9553]\| it/evals=1480/213760 eff=0.6937% N=400 Z=-3.8(59.89%) \| Like=-0.95..-0.03 [-0.9487..-0.9483]\| it/evals=1487/214932 eff=0.6931% N=400 Z=-3.8(60.27%) \| Like=-0.94..-0.03 [-0.9397..-0.9391]\| it/evals=1492/215921 eff=0.6923% N=400 Z=-3.8(60.61%) \| Like=-0.93..-0.03 [-0.9297..-0.9294]\| it/evals=1498/216880 eff=0.6920% N=400 Z=-3.8(60.77%) \| Like=-0.93..-0.03 [-0.9288..-0.9253]\| it/evals=1500/217236 eff=0.6918% N=400 Z=-3.8(61.38%) \| Like=-0.91..-0.02 [-0.9142..-0.9136]\| it/evals=1508/218630 eff=0.6910% N=400 Z=-3.8(61.93%) \| Like=-0.89..-0.02 [-0.8911..-0.8876]\| it/evals=1516/219890 eff=0.6907% N=400 Z=-3.8(62.26%) \| Like=-0.88..-0.02 [-0.8785..-0.8783]\| it/evals=1522/221352 eff=0.6888% N=400 Z=-3.8(62.68%) \| Like=-0.87..-0.02 [-0.8723..-0.8714]\| it/evals=1529/222535 eff=0.6883% N=400 Z=-3.8(62.74%) \| Like=-0.87..-0.02 [-0.8714..-0.8709]\| it/evals=1530/222727 eff=0.6882% N=400 Z=-3.8(63.17%) \| Like=-0.86..-0.02 [-0.8620..-0.8601]\| it/evals=1537/223922 eff=0.6876% N=400 Z=-3.8(63.61%) \| Like=-0.85..-0.02 [-0.8460..-0.8460]\| it/evals=1545/225297 eff=0.6870% N=400 Z=-3.8(63.94%) \| Like=-0.84..-0.02 [-0.8410..-0.8380]\| it/evals=1550/226001 eff=0.6871% N=400 Z=-3.8(64.37%) \| Like=-0.83..-0.02 [-0.8271..-0.8264]\| it/evals=1557/227211 eff=0.6865% N=400 Z=-3.8(64.82%) \| Like=-0.81..-0.02 [-0.8135..-0.8135]\| it/evals=1565/228491 eff=0.6861% N=400 Z=-3.8(65.30%) \| Like=-0.81..-0.02 [-0.8085..-0.8078]\| it/evals=1573/229851 eff=0.6855% N=400 Z=-3.7(65.81%) \| Like=-0.80..-0.02 [-0.7971..-0.7912]\| it/evals=1582/231405 eff=0.6848% N=400 Z=-3.7(66.14%) \| Like=-0.79..-0.01 [-0.7878..-0.7859]\| it/evals=1588/232425 eff=0.6844% N=400 Z=-3.7(66.49%) \| Like=-0.78..-0.01 [-0.7784..-0.7762]\| it/evals=1594/234014 eff=0.6823% N=400 Z=-3.7(66.87%) \| Like=-0.77..-0.01 [-0.7704..-0.7694]\| it/evals=1600/234722 eff=0.6828% N=400 Z=-3.7(67.24%) \| Like=-0.76..-0.01 [-0.7624..-0.7612]\| it/evals=1606/235930 eff=0.6819% N=400 Z=-3.7(67.74%) \| Like=-0.76..-0.01 [-0.7569..-0.7543]\| it/evals=1614/237299 eff=0.6813% N=400 Z=-3.7(68.06%) \| Like=-0.75..-0.01 [-0.7488..-0.7482]\| it/evals=1620/238351 eff=0.6808% N=400 Z=-3.7(68.40%) \| Like=-0.74..-0.01 [-0.7431..-0.7415]\| it/evals=1626/239603 eff=0.6798% N=400 Z=-3.7(68.86%) \| Like=-0.74..-0.01 [-0.7364..-0.7359]\| it/evals=1634/240903 eff=0.6794% N=400 Z=-3.7(69.23%) \| Like=-0.73..-0.01 [-0.7284..-0.7256]\| it/evals=1641/242354 eff=0.6782% N=400 Z=-3.7(69.63%) \| Like=-0.72..-0.01 [-0.7220..-0.7206]\| it/evals=1648/243473 eff=0.6780% N=400 Z=-3.7(69.73%) \| Like=-0.72..-0.01 [-0.7195..-0.7148]\| it/evals=1650/243713 eff=0.6781% N=400 Z=-3.7(70.06%) \| Like=-0.71..-0.01 [-0.7096..-0.7094]\| it/evals=1656/244993 eff=0.6770% N=400 Z=-3.7(70.48%) \| Like=-0.70..-0.01 [-0.7035..-0.7019]\| it/evals=1663/246209 eff=0.6765% N=400 Z=-3.7(70.74%) \| Like=-0.70..-0.01 [-0.6991..-0.6988]\| it/evals=1668/247247 eff=0.6757% N=400 Z=-3.7(71.18%) \| Like=-0.69..-0.01 [-0.6852..-0.6840]\| it/evals=1676/248747 eff=0.6749% N=400 Z=-3.7(71.62%) \| Like=-0.68..-0.01 [-0.6781..-0.6776]\| it/evals=1684/249958 eff=0.6748% N=400 Z=-3.7(71.98%) \| Like=-0.67..-0.01 [-0.6719..-0.6718]\| it/evals=1691/251223 eff=0.6742% N=400 Z=-3.7(72.41%) \| Like=-0.66..-0.01 [-0.6648..-0.6648]\| it/evals=1699/252454 eff=0.6741% N=400 Z=-3.7(72.45%) \| Like=-0.66..-0.01 [-0.6648..-0.6643]\| it/evals=1700/252456 eff=0.6745% N=400 Z=-3.6(72.83%) \| Like=-0.66..-0.01 [-0.6552..-0.6548]\| it/evals=1708/253741 eff=0.6742% N=400 Z=-3.6(72.93%) \| Like=-0.65..-0.01 [-0.6541..-0.6538]\| it/evals=1710/253762 eff=0.6749% N=400 Z=-3.6(73.20%) \| Like=-0.65..-0.01 [-0.6517..-0.6495]\| it/evals=1715/254976 eff=0.6737% N=400 Z=-3.6(73.51%) \| Like=-0.64..-0.01 [-0.6420..-0.6343]\| it/evals=1721/256099 eff=0.6731% N=400 Z=-3.6(73.95%) \| Like=-0.62..-0.01 [-0.6205..-0.6195]\| it/evals=1729/257675 eff=0.6720% N=400 Z=-3.6(74.36%) \| Like=-0.61..-0.01 [-0.6089..-0.6087]\| it/evals=1737/259026 eff=0.6716% N=400 Z=-3.6(74.83%) \| Like=-0.60..-0.01 [-0.6015..-0.6013]\| it/evals=1746/260451 eff=0.6714% N=400 Z=-3.6(75.02%) \| Like=-0.60..-0.01 [-0.5980..-0.5966]\| it/evals=1750/261074 eff=0.6713% N=400 Z=-3.6(75.38%) \| Like=-0.59..-0.01 [-0.5934..-0.5918]\| it/evals=1757/262618 eff=0.6701% N=400 Z=-3.6(75.72%) \| Like=-0.59..-0.01 [-0.5866..-0.5866]\| it/evals=1765/263914 eff=0.6698% N=400 Z=-3.6(76.13%) \| Like=-0.58..-0.01 [-0.5832..-0.5821]\| it/evals=1773/265169 eff=0.6696% N=400 Z=-3.6(76.51%) \| Like=-0.57..-0.01 [-0.5735..-0.5729]\| it/evals=1781/266465 eff=0.6694% N=400 Z=-3.6(76.84%) \| Like=-0.57..-0.01 [-0.5652..-0.5647]\| it/evals=1788/267765 eff=0.6687% N=400 Z=-3.6(77.17%) \| Like=-0.56..-0.01 [-0.5567..-0.5554]\| it/evals=1795/269142 eff=0.6679% N=400 Z=-3.6(77.40%) \| Like=-0.55..-0.01 [-0.5526..-0.5525]\| it/evals=1800/269863 eff=0.6680% N=400 Z=-3.6(77.58%) \| Like=-0.55..-0.01 [-0.5508..-0.5507]\| it/evals=1804/270731 eff=0.6673% N=400 Z=-3.6(77.88%) \| Like=-0.54..-0.01 [-0.5398..-0.5398]\| it/evals=1811/272311 eff=0.6660% N=400 Z=-3.6(78.23%) \| Like=-0.54..-0.01 [-0.5357..-0.5339]\| it/evals=1819/273696 eff=0.6656% N=400 Z=-3.6(78.53%) \| Like=-0.53..-0.01 [-0.5307..-0.5300]\| it/evals=1826/274507 eff=0.6662% N=400 Z=-3.6(78.71%) \| Like=-0.52..-0.01 [-0.5249..-0.5247]\| it/evals=1830/275651 eff=0.6648% N=400 Z=-3.6(79.00%) \| Like=-0.52..-0.01 [-0.5185..-0.5183]\| it/evals=1837/276935 eff=0.6643% N=400 Z=-3.6(79.30%) \| Like=-0.51..-0.01 [-0.5105..-0.5101]\| it/evals=1845/278293 eff=0.6639% N=400 Z=-3.6(79.49%) \| Like=-0.51..-0.01 [-0.5060..-0.5058]\| it/evals=1850/279113 eff=0.6638% N=400 Z=-3.6(79.79%) \| Like=-0.50..-0.01 [-0.4984..-0.4958]\| it/evals=1857/280450 eff=0.6631% N=400 Z=-3.6(80.13%) \| Like=-0.49..-0.01 [-0.4920..-0.4918]\| it/evals=1865/281972 eff=0.6624% N=400 Z=-3.5(80.56%) \| Like=-0.48..-0.00 [-0.4798..-0.4788]\| it/evals=1876/283256 eff=0.6632% N=400 Z=-3.5(80.92%) \| Like=-0.47..-0.00 [-0.4732..-0.4720]\| it/evals=1885/285070 eff=0.6622% N=400 Z=-3.5(81.11%) \| Like=-0.47..-0.00 [-0.4693..-0.4681]\| it/evals=1890/285727 eff=0.6624% N=400 Z=-3.5(81.34%) \| Like=-0.46..-0.00 [-0.4626..-0.4623]\| it/evals=1896/287050 eff=0.6614% N=400 Z=-3.5(81.48%) \| Like=-0.46..-0.00 [-0.4558..-0.4558]\| it/evals=1900/287684 eff=0.6614% N=400 Z=-3.5(81.84%) \| Like=-0.45..-0.00 [-0.4501..-0.4493]\| it/evals=1910/288941 eff=0.6620% N=400 Z=-3.5(82.09%) \| Like=-0.44..-0.00 [-0.4446..-0.4423]\| it/evals=1917/290248 eff=0.6614% N=400 Z=-3.5(82.38%) \| Like=-0.44..-0.00 [-0.4369..-0.4365]\| it/evals=1925/291586 eff=0.6611% N=400 Z=-3.5(82.69%) \| Like=-0.43..-0.00 [-0.4309..-0.4308]\| it/evals=1933/292876 eff=0.6609% N=400 Z=-3.5(82.94%) \| Like=-0.43..-0.00 [-0.4281..-0.4273]\| it/evals=1940/294179 eff=0.6604% N=400 Z=-3.5(83.21%) \| Like=-0.42..-0.00 [-0.4232..-0.4228]\| it/evals=1948/295516 eff=0.6601% N=400 Z=-3.5(83.28%) \| Like=-0.42..-0.00 [-0.4222..-0.4221]\| it/evals=1950/295613 eff=0.6605% N=400 Z=-3.5(83.56%) \| Like=-0.42..-0.00 [-0.4171..-0.4166]\| it/evals=1958/296901 eff=0.6604% N=400 Z=-3.5(83.83%) \| Like=-0.41..-0.00 [-0.4129..-0.4120]\| it/evals=1966/298201 eff=0.6602% N=400 Z=-3.5(84.13%) \| Like=-0.41..-0.00 [-0.4051..-0.4046]\| it/evals=1975/299993 eff=0.6592% N=400 Z=-3.5(84.30%) \| Like=-0.40..-0.00 [-0.4029..-0.4023]\| it/evals=1980/300651 eff=0.6594% N=400 Z=-3.5(84.53%) \| Like=-0.40..-0.00 [-0.3979..-0.3962]\| it/evals=1987/301913 eff=0.6590% N=400 Z=-3.5(84.82%) \| Like=-0.39..-0.00 [-0.3932..-0.3932]\| it/evals=1995/303133 eff=0.6590% N=400 Z=-3.5(84.98%) \| Like=-0.39..-0.00 [-0.3917..-0.3901]\| it/evals=2000/303776 eff=0.6592% N=400 Z=-3.5(85.19%) \| Like=-0.39..-0.00 [-0.3867..-0.3862]\| it/evals=2007/305031 eff=0.6588% N=400 Z=-3.5(85.36%) \| Like=-0.38..-0.00 [-0.3844..-0.3843]\| it/evals=2012/306273 eff=0.6578% N=400 Z=-3.5(85.61%) \| Like=-0.38..-0.00 [-0.3786..-0.3776]\| it/evals=2020/307636 eff=0.6575% N=400 Z=-3.5(85.84%) \| Like=-0.37..-0.00 [-0.3744..-0.3742]\| it/evals=2028/308755 eff=0.6577% N=400 Z=-3.5(85.99%) \| Like=-0.37..-0.00 [-0.3711..-0.3707]\| it/evals=2033/309871 eff=0.6569% N=400 Z=-3.5(86.24%) \| Like=-0.37..-0.00 [-0.3674..-0.3667]\| it/evals=2041/311163 eff=0.6568% N=400 Z=-3.5(86.44%) \| Like=-0.36..-0.00 [-0.3595..-0.3593]\| it/evals=2047/312307 eff=0.6563% N=400 Z=-3.5(86.52%) \| Like=-0.36..-0.00 [-0.3582..-0.3582]\| it/evals=2050/312313 eff=0.6572% N=400 Z=-3.5(86.67%) \| Like=-0.36..-0.00 [-0.3553..-0.3531]\| it/evals=2055/313463 eff=0.6564% N=400 Z=-3.5(86.81%) \| Like=-0.35..-0.00 [-0.3494..-0.3488]\| it/evals=2060/314447 eff=0.6560% N=400 Z=-3.5(87.02%) \| Like=-0.35..-0.00 [-0.3457..-0.3451]\| it/evals=2068/315751 eff=0.6558% N=400 Z=-3.5(87.08%) \| Like=-0.34..-0.00 [-0.3448..-0.3448]\| it/evals=2070/315963 eff=0.6560% N=400 Z=-3.5(87.28%) \| Like=-0.34..-0.00 [-0.3404..-0.3400]\| it/evals=2077/317183 eff=0.6557% N=400 Z=-3.5(87.46%) \| Like=-0.34..-0.00 [-0.3376..-0.3371]\| it/evals=2084/318371 eff=0.6554% N=400 Z=-3.5(87.60%) \| Like=-0.33..-0.00 [-0.3336..-0.3334]\| it/evals=2089/319341 eff=0.6550% N=400 Z=-3.5(87.78%) \| Like=-0.33..-0.00 [-0.3311..-0.3308]\| it/evals=2096/320561 eff=0.6547% N=400 Z=-3.5(87.89%) \| Like=-0.33..-0.00 [-0.3291..-0.3290]\| it/evals=2100/321161 eff=0.6547% N=400 Z=-3.5(88.07%) \| Like=-0.33..-0.00 [-0.3255..-0.3253]\| it/evals=2107/322344 eff=0.6545% N=400 Z=-3.5(88.23%) \| Like=-0.32..-0.00 [-0.3219..-0.3216]\| it/evals=2113/323486 eff=0.6540% N=400 Z=-3.5(88.38%) \| Like=-0.32..-0.00 [-0.3190..-0.3189]\| it/evals=2119/324648 eff=0.6535% N=400 Z=-3.5(88.56%) \| Like=-0.32..-0.00 [-0.3160..-0.3159]\| it/evals=2126/325819 eff=0.6533% N=400 Z=-3.4(88.67%) \| Like=-0.31..-0.00 [-0.3147..-0.3144]\| it/evals=2130/326780 eff=0.6526% N=400 Z=-3.4(88.84%) \| Like=-0.31..-0.00 [-0.3090..-0.3088]\| it/evals=2137/327927 eff=0.6525% N=400 Z=-3.4(88.96%) \| Like=-0.31..-0.00 [-0.3080..-0.3076]\| it/evals=2142/328771 eff=0.6523% N=400 Z=-3.4(89.14%) \| Like=-0.31..-0.00 [-0.3054..-0.3053]\| it/evals=2149/330050 eff=0.6519% N=400 Z=-3.4(89.16%) \| Like=-0.31..-0.00 [-0.3053..-0.3053]\| it/evals=2150/330154 eff=0.6520% N=400 Z=-3.4(89.31%) \| Like=-0.30..-0.00 [-0.2999..-0.2999]\| it/evals=2156/331014 eff=0.6521% N=400 Z=-3.4(89.40%) \| Like=-0.30..-0.00 [-0.2991..-0.2986]\| it/evals=2160/331682 eff=0.6520% N=400 Z=-3.4(89.51%) \| Like=-0.30..-0.00 [-0.2973..-0.2969]\| it/evals=2165/332818 eff=0.6513% N=400 Z=-3.4(89.66%) \| Like=-0.29..-0.00 [-0.2917..-0.2915]\| it/evals=2172/334125 eff=0.6508% N=400 Z=-3.4(89.84%) \| Like=-0.29..-0.00 [-0.2883..-0.2872]\| it/evals=2180/335600 eff=0.6504% N=400 Z=-3.4(90.01%) \| Like=-0.29..-0.00 [-0.2860..-0.2850]\| it/evals=2188/336929 eff=0.6502% N=400 Z=-3.4(90.19%) \| Like=-0.28..-0.00 [-0.2823..-0.2819]\| it/evals=2196/338257 eff=0.6500% N=400 Z=-3.4(90.28%) \| Like=-0.28..-0.00 [-0.2794..-0.2786]\| it/evals=2200/338933 eff=0.6499% N=400 Z=-3.4(90.40%) \| Like=-0.28..-0.00 [-0.2763..-0.2760]\| it/evals=2206/340016 eff=0.6496% N=400 Z=-3.4(90.49%) \| Like=-0.27..-0.00 [-0.2738..-0.2736]\| it/evals=2210/340940 eff=0.6490% N=400 Z=-3.4(90.66%) \| Like=-0.27..-0.00 [-0.2690..-0.2689]\| it/evals=2218/342183 eff=0.6489% N=400 Z=-3.4(90.83%) \| Like=-0.26..-0.00 [-0.2639..-0.2639]\| it/evals=2226/343509 eff=0.6488% N=400 Z=-3.4(91.00%) \| Like=-0.26..-0.00 [-0.2604..-0.2591]\| it/evals=2234/344612 eff=0.6490% N=400 Z=-3.4(91.13%) \| Like=-0.26..-0.00 [-0.2551..-0.2545]\| it/evals=2241/345805 eff=0.6488% N=400 Z=-3.4(91.25%) \| Like=-0.25..-0.00 [-0.2527..-0.2522]\| it/evals=2247/347049 eff=0.6482% N=400 Z=-3.4(91.31%) \| Like=-0.25..-0.00 [-0.2514..-0.2509]\| it/evals=2250/347629 eff=0.6480% N=400 Z=-3.4(91.42%) \| Like=-0.25..-0.00 [-0.2479..-0.2478]\| it/evals=2256/348869 eff=0.6474% N=400 Z=-3.4(91.58%) \| Like=-0.25..-0.00 [-0.2462..-0.2459]\| it/evals=2264/350130 eff=0.6474% N=400 Z=-3.4(91.73%) \| Like=-0.24..-0.00 [-0.2439..-0.2439]\| it/evals=2272/351422 eff=0.6473% N=400 Z=-3.4(91.86%) \| Like=-0.24..-0.00 [-0.2416..-0.2416]\| it/evals=2279/352749 eff=0.6468% N=400 Z=-3.4(92.00%) \| Like=-0.24..-0.00 [-0.2401..-0.2398]\| it/evals=2287/354025 eff=0.6467% N=400 Z=-3.4(92.17%) \| Like=-0.24..-0.00 [-0.2356..-0.2356]\| it/evals=2296/355385 eff=0.6468% N=400 Z=-3.4(92.24%) \| Like=-0.23..-0.00 [-0.2347..-0.2344]\| it/evals=2300/356045 eff=0.6467% N=400 Z=-3.4(92.38%) \| Like=-0.23..-0.00 [-0.2325..-0.2324]\| it/evals=2308/357389 eff=0.6465% N=400 Z=-3.4(92.50%) \| Like=-0.23..-0.00 [-0.2307..-0.2306]\| it/evals=2315/358620 eff=0.6463% N=400 Z=-3.4(92.63%) \| Like=-0.23..-0.00 [-0.2289..-0.2283]\| it/evals=2323/359956 eff=0.6461% N=400 Z=-3.4(92.75%) \| Like=-0.23..-0.00 [-0.2266..-0.2263]\| it/evals=2330/360972 eff=0.6462% N=400 Z=-3.4(92.83%) \| Like=-0.22..-0.00 [-0.2244..-0.2226]\| it/evals=2335/361933 eff=0.6459% N=400 Z=-3.4(92.91%) \| Like=-0.22..-0.00 [-0.2212..-0.2211]\| it/evals=2340/362725 eff=0.6458% N=400 Z=-3.4(93.01%) \| Like=-0.22..-0.00 [-0.2190..-0.2173]\| it/evals=2346/363977 eff=0.6453% N=400 Z=-3.4(93.07%) \| Like=-0.22..-0.00 [-0.2165..-0.2164]\| it/evals=2350/364638 eff=0.6452% N=400 Z=-3.4(93.20%) \| Like=-0.21..-0.00 [-0.2136..-0.2126]\| it/evals=2358/365992 eff=0.6450% N=400 Z=-3.4(93.31%) \| Like=-0.21..-0.00 [-0.2087..-0.2082]\| it/evals=2365/367191 eff=0.6448% N=400 Z=-3.4(93.46%) \| Like=-0.21..-0.00 [-0.2055..-0.2050]\| it/evals=2375/368621 eff=0.6450% N=400 Z=-3.4(93.58%) \| Like=-0.20..-0.00 [-0.2007..-0.2007]\| it/evals=2383/370241 eff=0.6443% N=400 Z=-3.4(93.72%) \| Like=-0.20..-0.00 [-0.1976..-0.1975]\| it/evals=2393/371563 eff=0.6447% N=400 Z=-3.4(93.82%) \| Like=-0.20..-0.00 [-0.1950..-0.1943]\| it/evals=2400/372823 eff=0.6444% N=400 Z=-3.4(93.93%) \| Like=-0.19..-0.00 [-0.1927..-0.1925]\| it/evals=2408/374076 eff=0.6444% N=400 Z=-3.4(94.05%) \| Like=-0.19..-0.00 [-0.1874..-0.1870]\| it/evals=2416/375751 eff=0.6437% N=400 Z=-3.4(94.19%) \| Like=-0.18..-0.00 [-0.1844..-0.1844]\| it/evals=2427/377177 eff=0.6441% N=400 Z=-3.4(94.23%) \| Like=-0.18..-0.00 [-0.1842..-0.1840]\| it/evals=2430/377883 eff=0.6437% N=400 Z=-3.4(94.34%) \| Like=-0.18..-0.00 [-0.1818..-0.1813]\| it/evals=2438/379251 eff=0.6435% N=400 Z=-3.4(94.41%) \| Like=-0.18..-0.00 [-0.1795..-0.1795]\| it/evals=2444/380555 eff=0.6429% N=400 Z=-3.4(94.49%) \| Like=-0.18..-0.00 [-0.1782..-0.1781]\| it/evals=2450/381211 eff=0.6434% N=400 Z=-3.4(94.57%) \| Like=-0.18..-0.00 [-0.1758..-0.1746]\| it/evals=2456/382575 eff=0.6426% N=400 Z=-3.4(94.67%) \| Like=-0.17..-0.00 [-0.1724..-0.1719]\| it/evals=2464/383831 eff=0.6426% N=400 Z=-3.4(94.75%) \| Like=-0.17..-0.00 [-0.1707..-0.1707]\| it/evals=2471/385167 eff=0.6422% N=400 Z=-3.4(94.85%) \| Like=-0.17..-0.00 [-0.1692..-0.1682]\| it/evals=2479/386483 eff=0.6421% N=400 Z=-3.4(94.96%) \| Like=-0.17..-0.00 [-0.1663..-0.1662]\| it/evals=2488/388095 eff=0.6417% N=400 Z=-3.4(95.06%) \| Like=-0.17..-0.00 [-0.1651..-0.1650]\| it/evals=2497/389615 eff=0.6415% N=400 Z=-3.4(95.09%) \| Like=-0.16..-0.00 [-0.1642..-0.1641]\| it/evals=2500/389953 eff=0.6418% N=400 Z=-3.4(95.18%) \| Like=-0.16..-0.00 [-0.1612..-0.1610]\| it/evals=2508/391758 eff=0.6408% N=400 Z=-3.4(95.28%) \| Like=-0.16..-0.00 [-0.1595..-0.1594]\| it/evals=2517/392934 eff=0.6412% N=400 Z=-3.4(95.34%) \| Like=-0.16..-0.00 [-0.1590..-0.1572]\| it/evals=2522/394145 eff=0.6405% N=400 Z=-3.4(95.43%) \| Like=-0.16..-0.00 [-0.1551..-0.1550]\| it/evals=2530/395380 eff=0.6405% N=400 Z=-3.4(95.50%) \| Like=-0.15..-0.00 [-0.1535..-0.1534]\| it/evals=2537/396686 eff=0.6402% N=400 Z=-3.4(95.59%) \| Like=-0.15..-0.00 [-0.1524..-0.1522]\| it/evals=2546/398301 eff=0.6399% N=400 Z=-3.4(95.64%) \| Like=-0.15..-0.00 [-0.1505..-0.1502]\| it/evals=2550/398948 eff=0.6398% N=400 Z=-3.4(95.72%) \| Like=-0.15..-0.00 [-0.1493..-0.1490]\| it/evals=2558/400259 eff=0.6397% N=400 Z=-3.4(95.79%) \| Like=-0.15..-0.00 [-0.1472..-0.1472]\| it/evals=2565/401596 eff=0.6393% N=400 Z=-3.4(95.86%) \| Like=-0.15..-0.00 [-0.1455..-0.1453]\| it/evals=2573/402884 eff=0.6393% N=400 Z=-3.4(95.94%) \| Like=-0.14..-0.00 [-0.1412..-0.1408]\| it/evals=2581/404180 eff=0.6392% N=400 Z=-3.4(96.02%) \| Like=-0.14..-0.00 [-0.1395..-0.1391]\| it/evals=2589/405476 eff=0.6391% N=400 Z=-3.4(96.07%) \| Like=-0.14..-0.00 [-0.1367..-0.1364]\| it/evals=2595/406855 eff=0.6384% N=400 Z=-3.4(96.12%) \| Like=-0.13..-0.00 [-0.1350..-0.1348]\| it/evals=2600/407511 eff=0.6386% N=400 Z=-3.4(96.18%) \| Like=-0.13..-0.00 [-0.1343..-0.1340]\| it/evals=2607/408762 eff=0.6384% N=400 Z=-3.4(96.21%) \| Like=-0.13..-0.00 [-0.1337..-0.1337]\| it/evals=2610/409074 eff=0.6387% N=400 Z=-3.4(96.27%) \| Like=-0.13..-0.00 [-0.1325..-0.1323]\| it/evals=2617/410438 eff=0.6382% N=400 Z=-3.4(96.34%) \| Like=-0.13..-0.00 [-0.1308..-0.1307]\| it/evals=2625/411842 eff=0.6380% N=400 Z=-3.4(96.42%) \| Like=-0.13..-0.00 [-0.1279..-0.1275]\| it/evals=2634/413543 eff=0.6376% N=400 Z=-3.4(96.49%) \| Like=-0.13..-0.00 [-0.1259..-0.1258]\| it/evals=2642/414800 eff=0.6375% N=400 Z=-3.4(96.55%) \| Like=-0.12..-0.00 [-0.1240..-0.1238]\| it/evals=2650/416076 eff=0.6375% N=400 Z=-3.4(96.62%) \| Like=-0.12..-0.00 [-0.1227..-0.1226]\| it/evals=2658/417597 eff=0.6371% N=400 Z=-3.4(96.68%) \| Like=-0.12..-0.00 [-0.1211..-0.1211]\| it/evals=2666/418866 eff=0.6371% N=400 Z=-3.4(96.74%) \| Like=-0.12..-0.00 [-0.1200..-0.1199]\| it/evals=2674/420228 eff=0.6369% N=400 Z=-3.4(96.81%) \| Like=-0.12..-0.00 [-0.1184..-0.1183]\| it/evals=2682/421691 eff=0.6366% N=400 Z=-3.4(96.84%) \| Like=-0.12..-0.00 [-0.1175..-0.1171]\| it/evals=2687/422859 eff=0.6360% N=400 Z=-3.4(96.90%) \| Like=-0.12..-0.00 [-0.1154..-0.1154]\| it/evals=2695/424153 eff=0.6360% N=400 Z=-3.4(96.94%) \| Like=-0.11..-0.00 [-0.1140..-0.1137]\| it/evals=2700/424853 eff=0.6361% N=400 Z=-3.4(96.99%) \| Like=-0.11..-0.00 [-0.1129..-0.1128]\| it/evals=2707/426081 eff=0.6359% N=400 Z=-3.4(97.05%) \| Like=-0.11..-0.00 [-0.1113..-0.1112]\| it/evals=2716/427783 eff=0.6355% N=400 Z=-3.4(97.12%) \| Like=-0.11..-0.00 [-0.1094..-0.1092]\| it/evals=2725/429087 eff=0.6357% N=400 Z=-3.4(97.18%) \| Like=-0.11..-0.00 [-0.1075..-0.1074]\| it/evals=2734/430734 eff=0.6353% N=400 Z=-3.4(97.24%) \| Like=-0.11..-0.00 [-0.1060..-0.1058]\| it/evals=2743/432084 eff=0.6354% N=400 Z=-3.4(97.28%) \| Like=-0.10..-0.00 [-0.1038..-0.1036]\| it/evals=2750/433209 eff=0.6354% N=400 Z=-3.4(97.34%) \| Like=-0.10..-0.00 [-0.1018..-0.1017]\| it/evals=2759/434541 eff=0.6355% N=400 Z=-3.4(97.39%) \| Like=-0.10..-0.00 [-0.1002..-0.1000]\| it/evals=2767/435865 eff=0.6354% N=400 Z=-3.4(97.42%) \| Like=-0.10..-0.00 [-0.0987..-0.0985]\| it/evals=2772/437051 eff=0.6348% N=400 Z=-3.4(97.48%) \| Like=-0.10..-0.00 [-0.0981..-0.0978]\| it/evals=2781/438375 eff=0.6350% N=400 Z=-3.4(97.53%) \| Like=-0.10..-0.00 [-0.0957..-0.0956]\| it/evals=2790/439611 eff=0.6352% N=400 Z=-3.4(97.57%) \| Like=-0.10..-0.00 [-0.0951..-0.0950]\| it/evals=2797/441134 eff=0.6346% N=400 Z=-3.4(97.59%) \| Like=-0.09..-0.00 [-0.0947..-0.0944]\| it/evals=2800/441273 eff=0.6351% N=400 Z=-3.4(97.64%) \| Like=-0.09..-0.00 [-0.0935..-0.0934]\| it/evals=2808/442474 eff=0.6352% N=400 Z=-3.4(97.68%) \| Like=-0.09..-0.00 [-0.0925..-0.0925]\| it/evals=2816/444228 eff=0.6345% N=400 Z=-3.4(97.72%) \| Like=-0.09..-0.00 [-0.0915..-0.0908]\| it/evals=2822/445500 eff=0.6340% N=400 Z=-3.4(97.75%) \| Like=-0.09..-0.00 [-0.0896..-0.0896]\| it/evals=2829/446603 eff=0.6340% N=400 Z=-3.4(97.78%) \| Like=-0.09..-0.00 [-0.0889..-0.0887]\| it/evals=2834/447455 eff=0.6339% N=400 Z=-3.4(97.82%) \| Like=-0.09..-0.00 [-0.0873..-0.0873]\| it/evals=2842/448706 eff=0.6339% N=400 Z=-3.4(97.86%) \| Like=-0.09..-0.00 [-0.0862..-0.0860]\| it/evals=2849/449926 eff=0.6338% N=400 Z=-3.4(97.87%) \| Like=-0.09..-0.00 [-0.0860..-0.0860]\| it/evals=2850/449954 eff=0.6340% N=400 Z=-3.4(97.90%) \| Like=-0.08..-0.00 [-0.0842..-0.0840]\| it/evals=2857/451220 eff=0.6337% N=400 Z=-3.4(97.94%) \| Like=-0.08..-0.00 [-0.0827..-0.0825]\| it/evals=2865/452703 eff=0.6334% N=400 Z=-3.3(97.98%) \| Like=-0.08..-0.00 [-0.0816..-0.0809]\| it/evals=2873/453977 eff=0.6334% N=400 Z=-3.3(98.02%) \| Like=-0.08..-0.00 [-0.0804..-0.0803]\| it/evals=2880/455237 eff=0.6332% N=400 Z=-3.3(98.05%) \| Like=-0.08..-0.00 [-0.0800..-0.0799]\| it/evals=2888/456550 eff=0.6331% N=400 Z=-3.3(98.09%) \| Like=-0.08..-0.00 [-0.0792..-0.0791]\| it/evals=2896/457846 eff=0.6331% N=400 Z=-3.3(98.11%) \| Like=-0.08..-0.00 [-0.0790..-0.0788]\| it/evals=2900/458521 eff=0.6330% N=400 Z=-3.3(98.14%) \| Like=-0.08..-0.00 [-0.0782..-0.0779]\| it/evals=2907/459673 eff=0.6330% N=400 Z=-3.3(98.15%) \| Like=-0.08..-0.00 [-0.0775..-0.0774]\| it/evals=2910/460517 eff=0.6324% N=400 Z=-3.3(98.19%) \| Like=-0.08..-0.00 [-0.0763..-0.0763]\| it/evals=2919/461802 eff=0.6326% N=400 Z=-3.3(98.22%) \| Like=-0.08..-0.00 [-0.0753..-0.0753]\| it/evals=2926/463176 eff=0.6323% N=400 Z=-3.3(98.26%) \| Like=-0.07..-0.00 [-0.0741..-0.0740]\| it/evals=2934/464523 eff=0.6322% N=400 Z=-3.3(98.29%) \| Like=-0.07..-0.00 [-0.0729..-0.0728]\| it/evals=2942/465875 eff=0.6320% N=400 Z=-3.3(98.33%) \| Like=-0.07..-0.00 [-0.0716..-0.0715]\| it/evals=2950/467204 eff=0.6320% N=400 Z=-3.3(98.37%) \| Like=-0.07..-0.00 [-0.0700..-0.0699]\| it/evals=2960/468947 eff=0.6317% N=400 Z=-3.3(98.40%) \| Like=-0.07..-0.00 [-0.0690..-0.0690]\| it/evals=2969/470091 eff=0.6321% N=400 Z=-3.3(98.40%) \| Like=-0.07..-0.00 [-0.0690..-0.0690]\| it/evals=2970/470696 eff=0.6315% N=400 Z=-3.3(98.44%) \| Like=-0.07..-0.00 [-0.0685..-0.0684]\| it/evals=2978/471947 eff=0.6315% N=400 Z=-3.3(98.47%) \| Like=-0.07..-0.00 [-0.0674..-0.0673]\| it/evals=2986/473395 eff=0.6313% N=400 Z=-3.3(98.50%) \| Like=-0.07..-0.00 [-0.0665..-0.0664]\| it/evals=2994/474732 eff=0.6312% N=400 Z=-3.3(98.52%) \| Like=-0.07..-0.00 [-0.0659..-0.0658]\| it/evals=3000/475462 eff=0.6315% N=400 Z=-3.3(98.54%) \| Like=-0.07..-0.00 [-0.0652..-0.0652]\| it/evals=3006/476748 eff=0.6311% N=400 Z=-3.3(98.57%) \| Like=-0.06..-0.00 [-0.0647..-0.0646]\| it/evals=3014/478046 eff=0.6310% N=400 Z=-3.3(98.60%) \| Like=-0.06..-0.00 [-0.0642..-0.0641]\| it/evals=3022/479427 eff=0.6309% N=400 Z=-3.3(98.63%) \| Like=-0.06..-0.00 [-0.0635..-0.0635]\| it/evals=3031/480765 eff=0.6310% N=400 Z=-3.3(98.65%) \| Like=-0.06..-0.00 [-0.0632..-0.0632]\| it/evals=3038/481985 eff=0.6308% N=400 Z=-3.3(98.68%) \| Like=-0.06..-0.00 [-0.0626..-0.0625]\| it/evals=3046/483313 eff=0.6308% N=400 Z=-3.3(98.69%) \| Like=-0.06..-0.00 [-0.0619..-0.0618]\| it/evals=3050/484209 eff=0.6304% N=400 Z=-3.3(98.71%) \| Like=-0.06..-0.00 [-0.0614..-0.0614]\| it/evals=3058/485486 eff=0.6304% N=400 Z=-3.3(98.72%) \| Like=-0.06..-0.00 [-0.0614..-0.0613]\| it/evals=3060/485700 eff=0.6305% N=400 Z=-3.3(98.73%) \| Like=-0.06..-0.00 [-0.0612..-0.0611]\| it/evals=3064/486716 eff=0.6300% N=400 Z=-3.3(98.75%) \| Like=-0.06..-0.00 [-0.0607..-0.0607]\| it/evals=3071/488011 eff=0.6298% N=400 Z=-3.3(98.78%) \| Like=-0.06..-0.00 [-0.0600..-0.0600]\| it/evals=3079/489356 eff=0.6297% N=400 Z=-3.3(98.80%) \| Like=-0.06..-0.00 [-0.0597..-0.0597]\| it/evals=3087/490653 eff=0.6297% N=400 Z=-3.3(98.82%) \| Like=-0.06..-0.00 [-0.0588..-0.0587]\| it/evals=3094/491929 eff=0.6295% N=400 Z=-3.3(98.84%) \| Like=-0.06..-0.00 [-0.0579..-0.0578]\| it/evals=3100/492690 eff=0.6297% N=400 Z=-3.3(98.86%) \| Like=-0.06..-0.00 [-0.0575..-0.0575]\| it/evals=3107/493971 eff=0.6295% N=400 Z=-3.3(98.89%) \| Like=-0.06..-0.00 [-0.0563..-0.0563]\| it/evals=3117/495411 eff=0.6297% N=400 Z=-3.3(98.91%) \| Like=-0.06..-0.00 [-0.0560..-0.0560]\| it/evals=3125/496783 eff=0.6296% N=400 Z=-3.3(98.93%) \| Like=-0.06..-0.00 [-0.0556..-0.0556]\| it/evals=3132/498266 eff=0.6291% N=400 Z=-3.3(98.95%) \| Like=-0.05..-0.00 [-0.0549..-0.0549]\| it/evals=3142/499798 eff=0.6292% N=400 Z=-3.3(98.97%) \| Like=-0.05..-0.00 [-0.0541..-0.0541]\| it/evals=3150/501237 eff=0.6289% N=400 Z=-3.3(98.99%) \| Like=-0.05..-0.00 [-0.0535..-0.0535]\| it/evals=3158/502625 eff=0.6288% N=400 [ultranest] Explored until L=-0.002 [ultranest] Likelihood function evaluations: 502865 [ultranest] logZ = -3.322 +- 0.04713 [ultranest] Effective samples strategy satisfied (ESS = 1862.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.330 +- 0.087 single instance: logZ = -3.330 +- 0.068 bootstrapped : logZ = -3.322 +- 0.087 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▂▂▃▃▄▅▄▆▅▅▄▃▃▃▂▂▂▃▃▅▆▇▇▇▆▇▆▄▃▃▂▁▁▁▁│1.00 0.53 +- 0.22 param1 : 0.00 │▁▁▁▁▂▂▃▂▄▃▅▅▆▄▄▄▃▂▂▂▂▃▄▃▆▇▇▆▆▆▅▃▃▃▁▁▁▁▁│1.00 0.53 +- 0.22 param2 : 0.00 │▁▁▁▁▁▂▃▃▄▅▅▆▆▅▅▄▃▂▂▂▂▂▄▆▇▇▇▇▇▇▅▄▃▃▁▁▁▁▁│1.00 0.53 +- 0.22 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=536, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-29.02, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=7, ncalls=693, regioncalls=0, ndraw=128, logz=-31.35, remainder_fraction=100.0000%, Lmin=-26.51, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=9, ncalls=954, regioncalls=0, ndraw=128, logz=-30.71, remainder_fraction=100.0000%, Lmin=-24.76, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=14, ncalls=1183, regioncalls=0, ndraw=128, logz=-28.70, remainder_fraction=100.0000%, Lmin=-24.10, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=21, ncalls=1672, regioncalls=0, ndraw=128, logz=-27.16, remainder_fraction=100.0000%, Lmin=-22.74, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=28, ncalls=2101, regioncalls=0, ndraw=128, logz=-26.18, remainder_fraction=100.0000%, Lmin=-22.14, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=2686, regioncalls=0, ndraw=128, logz=-25.18, remainder_fraction=100.0000%, Lmin=-21.02, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=44, ncalls=3319, regioncalls=0, ndraw=128, logz=-24.33, remainder_fraction=100.0000%, Lmin=-20.71, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=3720, regioncalls=0, ndraw=128, logz=-23.83, remainder_fraction=100.0000%, Lmin=-19.89, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=56, ncalls=4373, regioncalls=0, ndraw=128, logz=-23.11, remainder_fraction=100.0000%, Lmin=-18.80, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=5028, regioncalls=0, ndraw=128, logz=-22.01, remainder_fraction=100.0000%, Lmin=-18.12, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=72, ncalls=5864, regioncalls=0, ndraw=128, logz=-21.23, remainder_fraction=100.0000%, Lmin=-17.32, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=78, ncalls=6490, regioncalls=0, ndraw=128, logz=-20.66, remainder_fraction=100.0000%, Lmin=-16.60, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=86, ncalls=7143, regioncalls=0, ndraw=128, logz=-19.84, remainder_fraction=100.0000%, Lmin=-15.90, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=7541, regioncalls=0, ndraw=128, logz=-19.48, remainder_fraction=100.0000%, Lmin=-15.75, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=98, ncalls=8287, regioncalls=0, ndraw=128, logz=-18.89, remainder_fraction=100.0000%, Lmin=-15.14, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=8459, regioncalls=0, ndraw=128, logz=-18.73, remainder_fraction=100.0000%, Lmin=-15.08, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=107, ncalls=9217, regioncalls=0, ndraw=128, logz=-18.25, remainder_fraction=100.0000%, Lmin=-14.69, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=9951, regioncalls=0, ndraw=128, logz=-17.76, remainder_fraction=100.0000%, Lmin=-14.13, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=123, ncalls=10701, regioncalls=0, ndraw=128, logz=-17.27, remainder_fraction=99.9999%, Lmin=-13.68, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=129, ncalls=11262, regioncalls=0, ndraw=128, logz=-16.86, remainder_fraction=99.9999%, Lmin=-13.17, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=133, ncalls=11977, regioncalls=0, ndraw=128, logz=-16.57, remainder_fraction=99.9999%, Lmin=-12.89, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=141, ncalls=12747, regioncalls=0, ndraw=128, logz=-16.08, remainder_fraction=99.9998%, Lmin=-12.62, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=148, ncalls=13404, regioncalls=0, ndraw=128, logz=-15.71, remainder_fraction=99.9996%, Lmin=-12.35, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=13647, regioncalls=0, ndraw=128, logz=-15.61, remainder_fraction=99.9996%, Lmin=-12.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=157, ncalls=14399, regioncalls=0, ndraw=128, logz=-15.20, remainder_fraction=99.9994%, Lmin=-11.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=164, ncalls=15197, regioncalls=0, ndraw=128, logz=-14.79, remainder_fraction=99.9991%, Lmin=-11.33, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=172, ncalls=16003, regioncalls=0, ndraw=128, logz=-14.41, remainder_fraction=99.9987%, Lmin=-10.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=177, ncalls=16565, regioncalls=0, ndraw=128, logz=-14.17, remainder_fraction=99.9983%, Lmin=-10.72, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=183, ncalls=17159, regioncalls=0, ndraw=128, logz=-13.89, remainder_fraction=99.9977%, Lmin=-10.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=191, ncalls=18165, regioncalls=0, ndraw=128, logz=-13.54, remainder_fraction=99.9968%, Lmin=-10.22, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=197, ncalls=18639, regioncalls=0, ndraw=128, logz=-13.31, remainder_fraction=99.9959%, Lmin=-10.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=19033, regioncalls=0, ndraw=128, logz=-13.20, remainder_fraction=99.9955%, Lmin=-9.97, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=19834, regioncalls=0, ndraw=128, logz=-12.95, remainder_fraction=99.9942%, Lmin=-9.77, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=215, ncalls=20615, regioncalls=0, ndraw=128, logz=-12.66, remainder_fraction=99.9924%, Lmin=-9.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=223, ncalls=21453, regioncalls=0, ndraw=128, logz=-12.39, remainder_fraction=99.9899%, Lmin=-9.24, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=231, ncalls=22294, regioncalls=0, ndraw=128, logz=-12.12, remainder_fraction=99.9865%, Lmin=-8.93, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=239, ncalls=23143, regioncalls=0, ndraw=128, logz=-11.86, remainder_fraction=99.9830%, Lmin=-8.73, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=246, ncalls=24075, regioncalls=0, ndraw=128, logz=-11.64, remainder_fraction=99.9786%, Lmin=-8.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=24541, regioncalls=0, ndraw=128, logz=-11.53, remainder_fraction=99.9759%, Lmin=-8.53, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=258, ncalls=25455, regioncalls=0, ndraw=128, logz=-11.33, remainder_fraction=99.9700%, Lmin=-8.41, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=263, ncalls=26214, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9657%, Lmin=-8.29, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=269, ncalls=26672, regioncalls=0, ndraw=128, logz=-11.07, remainder_fraction=99.9610%, Lmin=-8.16, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=26673, regioncalls=0, ndraw=128, logz=-11.05, remainder_fraction=99.9600%, Lmin=-8.12, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=275, ncalls=27576, regioncalls=0, ndraw=128, logz=-10.93, remainder_fraction=99.9550%, Lmin=-8.02, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=28416, regioncalls=0, ndraw=128, logz=-10.78, remainder_fraction=99.9469%, Lmin=-7.86, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=29359, regioncalls=0, ndraw=128, logz=-10.60, remainder_fraction=99.9371%, Lmin=-7.71, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=298, ncalls=30265, regioncalls=0, ndraw=128, logz=-10.43, remainder_fraction=99.9249%, Lmin=-7.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=30355, regioncalls=0, ndraw=128, logz=-10.39, remainder_fraction=99.9214%, Lmin=-7.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=307, ncalls=31184, regioncalls=0, ndraw=128, logz=-10.25, remainder_fraction=99.9102%, Lmin=-7.43, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=312, ncalls=31933, regioncalls=0, ndraw=128, logz=-10.16, remainder_fraction=99.9012%, Lmin=-7.31, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=317, ncalls=32546, regioncalls=0, ndraw=128, logz=-10.06, remainder_fraction=99.8897%, Lmin=-7.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=323, ncalls=33284, regioncalls=0, ndraw=128, logz=-9.93, remainder_fraction=99.8738%, Lmin=-6.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=327, ncalls=33982, regioncalls=0, ndraw=128, logz=-9.85, remainder_fraction=99.8631%, Lmin=-6.90, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=333, ncalls=34837, regioncalls=0, ndraw=128, logz=-9.73, remainder_fraction=99.8454%, Lmin=-6.78, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=35660, regioncalls=0, ndraw=128, logz=-9.59, remainder_fraction=99.8221%, Lmin=-6.70, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=346, ncalls=36402, regioncalls=0, ndraw=128, logz=-9.47, remainder_fraction=99.7992%, Lmin=-6.60, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=36856, regioncalls=0, ndraw=128, logz=-9.40, remainder_fraction=99.7829%, Lmin=-6.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=358, ncalls=37810, regioncalls=0, ndraw=128, logz=-9.26, remainder_fraction=99.7516%, Lmin=-6.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=38137, regioncalls=0, ndraw=128, logz=-9.23, remainder_fraction=99.7420%, Lmin=-6.43, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=363, ncalls=38593, regioncalls=0, ndraw=128, logz=-9.18, remainder_fraction=99.7311%, Lmin=-6.37, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=371, ncalls=39451, regioncalls=0, ndraw=128, logz=-9.05, remainder_fraction=99.6917%, Lmin=-6.29, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=379, ncalls=40337, regioncalls=0, ndraw=128, logz=-8.93, remainder_fraction=99.6519%, Lmin=-6.21, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=387, ncalls=41243, regioncalls=0, ndraw=128, logz=-8.82, remainder_fraction=99.6097%, Lmin=-6.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=393, ncalls=42174, regioncalls=0, ndraw=128, logz=-8.74, remainder_fraction=99.5853%, Lmin=-6.09, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=42784, regioncalls=0, ndraw=128, logz=-8.65, remainder_fraction=99.5452%, Lmin=-6.04, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=406, ncalls=43671, regioncalls=0, ndraw=128, logz=-8.57, remainder_fraction=99.5042%, Lmin=-5.97, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=412, ncalls=44560, regioncalls=0, ndraw=128, logz=-8.50, remainder_fraction=99.4619%, Lmin=-5.93, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=418, ncalls=45405, regioncalls=0, ndraw=128, logz=-8.43, remainder_fraction=99.4174%, Lmin=-5.84, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=426, ncalls=46327, regioncalls=0, ndraw=128, logz=-8.34, remainder_fraction=99.3676%, Lmin=-5.79, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=433, ncalls=47200, regioncalls=0, ndraw=128, logz=-8.26, remainder_fraction=99.3206%, Lmin=-5.71, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=441, ncalls=48250, regioncalls=0, ndraw=128, logz=-8.18, remainder_fraction=99.2511%, Lmin=-5.65, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=445, ncalls=48752, regioncalls=0, ndraw=128, logz=-8.14, remainder_fraction=99.2125%, Lmin=-5.61, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=49284, regioncalls=0, ndraw=128, logz=-8.09, remainder_fraction=99.1649%, Lmin=-5.56, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=453, ncalls=49769, regioncalls=0, ndraw=128, logz=-8.06, remainder_fraction=99.1345%, Lmin=-5.48, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=459, ncalls=50563, regioncalls=0, ndraw=128, logz=-7.99, remainder_fraction=99.0789%, Lmin=-5.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=467, ncalls=51611, regioncalls=0, ndraw=128, logz=-7.91, remainder_fraction=99.0193%, Lmin=-5.31, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=473, ncalls=52558, regioncalls=0, ndraw=128, logz=-7.85, remainder_fraction=98.9621%, Lmin=-5.24, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=481, ncalls=53684, regioncalls=0, ndraw=128, logz=-7.77, remainder_fraction=98.8714%, Lmin=-5.10, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=487, ncalls=54410, regioncalls=0, ndraw=128, logz=-7.70, remainder_fraction=98.8055%, Lmin=-5.06, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=493, ncalls=55309, regioncalls=0, ndraw=128, logz=-7.64, remainder_fraction=98.7227%, Lmin=-4.95, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=496, ncalls=55944, regioncalls=0, ndraw=128, logz=-7.61, remainder_fraction=98.6757%, Lmin=-4.92, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=56321, regioncalls=0, ndraw=128, logz=-7.59, remainder_fraction=98.6515%, Lmin=-4.90, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=56392, regioncalls=0, ndraw=128, logz=-7.57, remainder_fraction=98.6210%, Lmin=-4.88, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=505, ncalls=57435, regioncalls=0, ndraw=128, logz=-7.51, remainder_fraction=98.5343%, Lmin=-4.84, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=513, ncalls=58513, regioncalls=0, ndraw=128, logz=-7.43, remainder_fraction=98.4325%, Lmin=-4.75, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=519, ncalls=59253, regioncalls=0, ndraw=128, logz=-7.37, remainder_fraction=98.3328%, Lmin=-4.68, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=525, ncalls=60254, regioncalls=0, ndraw=128, logz=-7.31, remainder_fraction=98.2373%, Lmin=-4.60, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=532, ncalls=61187, regioncalls=0, ndraw=128, logz=-7.24, remainder_fraction=98.0928%, Lmin=-4.53, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=539, ncalls=62196, regioncalls=0, ndraw=128, logz=-7.18, remainder_fraction=97.9580%, Lmin=-4.47, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=62917, regioncalls=0, ndraw=128, logz=-7.13, remainder_fraction=97.8407%, Lmin=-4.43, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=63774, regioncalls=0, ndraw=128, logz=-7.07, remainder_fraction=97.7294%, Lmin=-4.42, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=64225, regioncalls=0, ndraw=128, logz=-7.05, remainder_fraction=97.6804%, Lmin=-4.38, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=65355, regioncalls=0, ndraw=128, logz=-6.98, remainder_fraction=97.5271%, Lmin=-4.34, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=568, ncalls=66384, regioncalls=0, ndraw=128, logz=-6.92, remainder_fraction=97.3223%, Lmin=-4.30, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=67504, regioncalls=0, ndraw=128, logz=-6.85, remainder_fraction=97.1236%, Lmin=-4.24, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=584, ncalls=68662, regioncalls=0, ndraw=128, logz=-6.79, remainder_fraction=96.9797%, Lmin=-4.17, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=591, ncalls=69706, regioncalls=0, ndraw=128, logz=-6.73, remainder_fraction=96.7874%, Lmin=-4.13, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=70919, regioncalls=0, ndraw=128, logz=-6.68, remainder_fraction=96.6162%, Lmin=-4.10, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=71025, regioncalls=0, ndraw=128, logz=-6.67, remainder_fraction=96.5634%, Lmin=-4.09, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=72196, regioncalls=0, ndraw=128, logz=-6.62, remainder_fraction=96.3981%, Lmin=-4.07, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=613, ncalls=73252, regioncalls=0, ndraw=128, logz=-6.57, remainder_fraction=96.1906%, Lmin=-4.00, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=621, ncalls=74253, regioncalls=0, ndraw=128, logz=-6.52, remainder_fraction=95.9411%, Lmin=-3.94, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=627, ncalls=75009, regioncalls=0, ndraw=128, logz=-6.48, remainder_fraction=95.7792%, Lmin=-3.89, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=75437, regioncalls=0, ndraw=128, logz=-6.46, remainder_fraction=95.6901%, Lmin=-3.88, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=76382, regioncalls=0, ndraw=128, logz=-6.42, remainder_fraction=95.5628%, Lmin=-3.86, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=77350, regioncalls=0, ndraw=128, logz=-6.38, remainder_fraction=95.3460%, Lmin=-3.79, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=78496, regioncalls=0, ndraw=128, logz=-6.32, remainder_fraction=95.0645%, Lmin=-3.75, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=658, ncalls=79613, regioncalls=0, ndraw=128, logz=-6.27, remainder_fraction=94.7749%, Lmin=-3.70, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=80634, regioncalls=0, ndraw=128, logz=-6.22, remainder_fraction=94.4915%, Lmin=-3.66, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=673, ncalls=81568, regioncalls=0, ndraw=128, logz=-6.18, remainder_fraction=94.2776%, Lmin=-3.62, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=82576, regioncalls=0, ndraw=128, logz=-6.14, remainder_fraction=94.0417%, Lmin=-3.59, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=688, ncalls=83669, regioncalls=0, ndraw=128, logz=-6.09, remainder_fraction=93.7668%, Lmin=-3.54, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=84584, regioncalls=0, ndraw=128, logz=-6.05, remainder_fraction=93.4628%, Lmin=-3.48, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=85135, regioncalls=0, ndraw=128, logz=-6.02, remainder_fraction=93.3556%, Lmin=-3.45, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=705, ncalls=86108, regioncalls=0, ndraw=128, logz=-6.00, remainder_fraction=93.1139%, Lmin=-3.41, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=712, ncalls=87277, regioncalls=0, ndraw=128, logz=-5.96, remainder_fraction=92.8651%, Lmin=-3.37, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=718, ncalls=88239, regioncalls=0, ndraw=128, logz=-5.92, remainder_fraction=92.6439%, Lmin=-3.32, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=88371, regioncalls=0, ndraw=128, logz=-5.91, remainder_fraction=92.5366%, Lmin=-3.31, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=89374, regioncalls=0, ndraw=128, logz=-5.88, remainder_fraction=92.2251%, Lmin=-3.27, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=733, ncalls=90293, regioncalls=0, ndraw=128, logz=-5.84, remainder_fraction=91.9199%, Lmin=-3.23, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=91297, regioncalls=0, ndraw=128, logz=-5.80, remainder_fraction=91.7701%, Lmin=-3.20, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=746, ncalls=92331, regioncalls=0, ndraw=128, logz=-5.77, remainder_fraction=91.5238%, Lmin=-3.14, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=92915, regioncalls=0, ndraw=128, logz=-5.75, remainder_fraction=91.3032%, Lmin=-3.13, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=94000, regioncalls=0, ndraw=128, logz=-5.72, remainder_fraction=91.1140%, Lmin=-3.11, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=764, ncalls=95164, regioncalls=0, ndraw=128, logz=-5.68, remainder_fraction=90.7148%, Lmin=-3.06, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=772, ncalls=96298, regioncalls=0, ndraw=128, logz=-5.64, remainder_fraction=90.2795%, Lmin=-3.02, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=778, ncalls=97206, regioncalls=0, ndraw=128, logz=-5.61, remainder_fraction=89.9240%, Lmin=-2.97, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=785, ncalls=98334, regioncalls=0, ndraw=128, logz=-5.57, remainder_fraction=89.5642%, Lmin=-2.94, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=793, ncalls=99477, regioncalls=0, ndraw=128, logz=-5.54, remainder_fraction=89.1546%, Lmin=-2.87, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=799, ncalls=100468, regioncalls=0, ndraw=128, logz=-5.51, remainder_fraction=88.9093%, Lmin=-2.85, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=100506, regioncalls=0, ndraw=128, logz=-5.50, remainder_fraction=88.8449%, Lmin=-2.85, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=806, ncalls=101434, regioncalls=0, ndraw=128, logz=-5.47, remainder_fraction=88.5772%, Lmin=-2.81, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=102038, regioncalls=0, ndraw=128, logz=-5.45, remainder_fraction=88.3182%, Lmin=-2.80, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=814, ncalls=102776, regioncalls=0, ndraw=128, logz=-5.44, remainder_fraction=88.1672%, Lmin=-2.78, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=821, ncalls=103984, regioncalls=0, ndraw=128, logz=-5.40, remainder_fraction=87.7522%, Lmin=-2.76, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=829, ncalls=105283, regioncalls=0, ndraw=128, logz=-5.37, remainder_fraction=87.3842%, Lmin=-2.74, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=836, ncalls=106162, regioncalls=0, ndraw=128, logz=-5.34, remainder_fraction=86.9149%, Lmin=-2.71, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=842, ncalls=107262, regioncalls=0, ndraw=128, logz=-5.31, remainder_fraction=86.6220%, Lmin=-2.70, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=849, ncalls=108432, regioncalls=0, ndraw=128, logz=-5.28, remainder_fraction=86.1965%, Lmin=-2.68, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=108444, regioncalls=0, ndraw=128, logz=-5.28, remainder_fraction=86.1534%, Lmin=-2.66, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=856, ncalls=109634, regioncalls=0, ndraw=128, logz=-5.26, remainder_fraction=85.7233%, Lmin=-2.64, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=110880, regioncalls=0, ndraw=128, logz=-5.22, remainder_fraction=85.2140%, Lmin=-2.63, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=869, ncalls=111876, regioncalls=0, ndraw=128, logz=-5.20, remainder_fraction=84.9304%, Lmin=-2.60, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=877, ncalls=113071, regioncalls=0, ndraw=128, logz=-5.17, remainder_fraction=84.4730%, Lmin=-2.57, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=886, ncalls=114293, regioncalls=0, ndraw=128, logz=-5.14, remainder_fraction=83.8845%, Lmin=-2.53, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=115521, regioncalls=0, ndraw=128, logz=-5.11, remainder_fraction=83.3476%, Lmin=-2.49, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=116779, regioncalls=0, ndraw=128, logz=-5.09, remainder_fraction=82.9070%, Lmin=-2.48, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=907, ncalls=117816, regioncalls=0, ndraw=128, logz=-5.06, remainder_fraction=82.4805%, Lmin=-2.47, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=915, ncalls=119020, regioncalls=0, ndraw=128, logz=-5.04, remainder_fraction=82.1871%, Lmin=-2.45, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=923, ncalls=120345, regioncalls=0, ndraw=128, logz=-5.01, remainder_fraction=81.7142%, Lmin=-2.42, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=931, ncalls=121552, regioncalls=0, ndraw=128, logz=-4.98, remainder_fraction=81.1462%, Lmin=-2.38, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=939, ncalls=122806, regioncalls=0, ndraw=128, logz=-4.96, remainder_fraction=80.6354%, Lmin=-2.34, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=124131, regioncalls=0, ndraw=128, logz=-4.93, remainder_fraction=80.0308%, Lmin=-2.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=124525, regioncalls=0, ndraw=128, logz=-4.92, remainder_fraction=79.9262%, Lmin=-2.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=959, ncalls=125834, regioncalls=0, ndraw=128, logz=-4.89, remainder_fraction=79.2442%, Lmin=-2.28, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=968, ncalls=127106, regioncalls=0, ndraw=128, logz=-4.87, remainder_fraction=78.5322%, Lmin=-2.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=975, ncalls=128335, regioncalls=0, ndraw=128, logz=-4.85, remainder_fraction=78.0921%, Lmin=-2.22, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=982, ncalls=129796, regioncalls=0, ndraw=128, logz=-4.82, remainder_fraction=77.5509%, Lmin=-2.20, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=131025, regioncalls=0, ndraw=128, logz=-4.80, remainder_fraction=77.1161%, Lmin=-2.16, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=131028, regioncalls=0, ndraw=128, logz=-4.80, remainder_fraction=77.0999%, Lmin=-2.16, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=997, ncalls=132268, regioncalls=0, ndraw=128, logz=-4.78, remainder_fraction=76.5821%, Lmin=-2.13, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=132303, regioncalls=0, ndraw=128, logz=-4.77, remainder_fraction=76.3325%, Lmin=-2.12, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1005, ncalls=133447, regioncalls=0, ndraw=128, logz=-4.76, remainder_fraction=75.9134%, Lmin=-2.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=134816, regioncalls=0, ndraw=128, logz=-4.73, remainder_fraction=75.1846%, Lmin=-2.06, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1021, ncalls=135885, regioncalls=0, ndraw=128, logz=-4.71, remainder_fraction=74.6452%, Lmin=-2.04, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1028, ncalls=137173, regioncalls=0, ndraw=128, logz=-4.69, remainder_fraction=74.2930%, Lmin=-2.02, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1036, ncalls=138360, regioncalls=0, ndraw=128, logz=-4.67, remainder_fraction=73.7034%, Lmin=-2.00, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1043, ncalls=139538, regioncalls=0, ndraw=128, logz=-4.65, remainder_fraction=73.2286%, Lmin=-1.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1048, ncalls=140562, regioncalls=0, ndraw=128, logz=-4.64, remainder_fraction=72.7853%, Lmin=-1.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=140682, regioncalls=0, ndraw=128, logz=-4.63, remainder_fraction=72.6208%, Lmin=-1.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1055, ncalls=141823, regioncalls=0, ndraw=128, logz=-4.62, remainder_fraction=72.2291%, Lmin=-1.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=142697, regioncalls=0, ndraw=128, logz=-4.61, remainder_fraction=71.9285%, Lmin=-1.90, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=143907, regioncalls=0, ndraw=128, logz=-4.58, remainder_fraction=71.3196%, Lmin=-1.88, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1073, ncalls=144733, regioncalls=0, ndraw=128, logz=-4.57, remainder_fraction=70.8905%, Lmin=-1.86, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1079, ncalls=145847, regioncalls=0, ndraw=128, logz=-4.56, remainder_fraction=70.3962%, Lmin=-1.83, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1083, ncalls=146495, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=70.1319%, Lmin=-1.81, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1091, ncalls=148031, regioncalls=0, ndraw=128, logz=-4.53, remainder_fraction=69.4710%, Lmin=-1.79, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1099, ncalls=149288, regioncalls=0, ndraw=128, logz=-4.51, remainder_fraction=68.9367%, Lmin=-1.78, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=149295, regioncalls=0, ndraw=128, logz=-4.50, remainder_fraction=68.8495%, Lmin=-1.78, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1106, ncalls=150295, regioncalls=0, ndraw=128, logz=-4.49, remainder_fraction=68.4076%, Lmin=-1.76, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1111, ncalls=151105, regioncalls=0, ndraw=128, logz=-4.48, remainder_fraction=68.0835%, Lmin=-1.75, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1116, ncalls=152390, regioncalls=0, ndraw=128, logz=-4.47, remainder_fraction=67.6795%, Lmin=-1.73, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1123, ncalls=153502, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=67.2453%, Lmin=-1.71, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1131, ncalls=154756, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=66.5362%, Lmin=-1.69, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1136, ncalls=155670, regioncalls=0, ndraw=128, logz=-4.42, remainder_fraction=66.1125%, Lmin=-1.67, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=156840, regioncalls=0, ndraw=128, logz=-4.41, remainder_fraction=65.6280%, Lmin=-1.65, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1147, ncalls=157659, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=65.2970%, Lmin=-1.62, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=158021, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=65.1511%, Lmin=-1.62, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1158, ncalls=159283, regioncalls=0, ndraw=128, logz=-4.37, remainder_fraction=64.5717%, Lmin=-1.60, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1163, ncalls=160304, regioncalls=0, ndraw=128, logz=-4.36, remainder_fraction=64.1816%, Lmin=-1.59, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=161116, regioncalls=0, ndraw=128, logz=-4.34, remainder_fraction=63.6428%, Lmin=-1.57, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=162144, regioncalls=0, ndraw=128, logz=-4.33, remainder_fraction=63.1316%, Lmin=-1.55, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1183, ncalls=163297, regioncalls=0, ndraw=128, logz=-4.32, remainder_fraction=62.5427%, Lmin=-1.54, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1189, ncalls=164331, regioncalls=0, ndraw=128, logz=-4.30, remainder_fraction=62.1219%, Lmin=-1.53, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=165292, regioncalls=0, ndraw=128, logz=-4.29, remainder_fraction=61.8306%, Lmin=-1.52, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=166312, regioncalls=0, ndraw=128, logz=-4.28, remainder_fraction=61.3152%, Lmin=-1.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1208, ncalls=167575, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=60.5636%, Lmin=-1.49, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=168949, regioncalls=0, ndraw=128, logz=-4.25, remainder_fraction=59.9707%, Lmin=-1.47, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1221, ncalls=169986, regioncalls=0, ndraw=128, logz=-4.24, remainder_fraction=59.6611%, Lmin=-1.46, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1229, ncalls=171180, regioncalls=0, ndraw=128, logz=-4.23, remainder_fraction=59.2401%, Lmin=-1.44, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=172349, regioncalls=0, ndraw=128, logz=-4.22, remainder_fraction=58.8625%, Lmin=-1.41, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1239, ncalls=173329, regioncalls=0, ndraw=128, logz=-4.21, remainder_fraction=58.4573%, Lmin=-1.39, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1247, ncalls=174627, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=57.7728%, Lmin=-1.36, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=174686, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=57.5210%, Lmin=-1.36, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1252, ncalls=175596, regioncalls=0, ndraw=128, logz=-4.18, remainder_fraction=57.3282%, Lmin=-1.35, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1259, ncalls=176652, regioncalls=0, ndraw=128, logz=-4.17, remainder_fraction=56.7873%, Lmin=-1.33, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=176886, regioncalls=0, ndraw=128, logz=-4.17, remainder_fraction=56.6865%, Lmin=-1.33, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1267, ncalls=177902, regioncalls=0, ndraw=128, logz=-4.15, remainder_fraction=56.1055%, Lmin=-1.32, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1273, ncalls=178998, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=55.6734%, Lmin=-1.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1282, ncalls=180274, regioncalls=0, ndraw=128, logz=-4.13, remainder_fraction=55.0354%, Lmin=-1.29, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1289, ncalls=181554, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=54.5799%, Lmin=-1.27, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1298, ncalls=182819, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=53.9707%, Lmin=-1.26, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=183109, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=53.7885%, Lmin=-1.26, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1306, ncalls=184349, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=53.3077%, Lmin=-1.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1315, ncalls=185624, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=52.7342%, Lmin=-1.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1322, ncalls=186767, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=52.1344%, Lmin=-1.21, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=187985, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=51.4118%, Lmin=-1.20, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1335, ncalls=188900, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=51.1255%, Lmin=-1.19, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1341, ncalls=189874, regioncalls=0, ndraw=128, logz=-4.03, remainder_fraction=50.7369%, Lmin=-1.17, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1349, ncalls=191131, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=50.0458%, Lmin=-1.15, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=191558, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=49.9925%, Lmin=-1.15, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=192760, regioncalls=0, ndraw=128, logz=-4.01, remainder_fraction=49.4501%, Lmin=-1.13, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1365, ncalls=194107, regioncalls=0, ndraw=128, logz=-4.00, remainder_fraction=48.8177%, Lmin=-1.12, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1373, ncalls=195417, regioncalls=0, ndraw=128, logz=-3.99, remainder_fraction=48.1704%, Lmin=-1.10, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1381, ncalls=196696, regioncalls=0, ndraw=128, logz=-3.97, remainder_fraction=47.7005%, Lmin=-1.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1389, ncalls=197982, regioncalls=0, ndraw=128, logz=-3.96, remainder_fraction=47.0590%, Lmin=-1.08, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1395, ncalls=199016, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=46.5733%, Lmin=-1.07, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=200002, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=46.1871%, Lmin=-1.05, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1408, ncalls=201398, regioncalls=0, ndraw=128, logz=-3.94, remainder_fraction=45.6260%, Lmin=-1.05, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1416, ncalls=202794, regioncalls=0, ndraw=128, logz=-3.93, remainder_fraction=45.0946%, Lmin=-1.04, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1424, ncalls=204211, regioncalls=0, ndraw=128, logz=-3.92, remainder_fraction=44.5176%, Lmin=-1.03, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1432, ncalls=205426, regioncalls=0, ndraw=128, logz=-3.91, remainder_fraction=43.8979%, Lmin=-1.02, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=206860, regioncalls=0, ndraw=128, logz=-3.90, remainder_fraction=43.3227%, Lmin=-1.01, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1446, ncalls=207891, regioncalls=0, ndraw=128, logz=-3.89, remainder_fraction=42.8518%, Lmin=-0.99, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=208561, regioncalls=0, ndraw=128, logz=-3.88, remainder_fraction=42.5588%, Lmin=-0.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1457, ncalls=209885, regioncalls=0, ndraw=128, logz=-3.88, remainder_fraction=42.0478%, Lmin=-0.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1464, ncalls=211060, regioncalls=0, ndraw=128, logz=-3.87, remainder_fraction=41.5226%, Lmin=-0.97, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=212368, regioncalls=0, ndraw=128, logz=-3.86, remainder_fraction=40.9935%, Lmin=-0.97, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=213760, regioncalls=0, ndraw=128, logz=-3.85, remainder_fraction=40.5184%, Lmin=-0.96, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1487, ncalls=214932, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=40.1063%, Lmin=-0.95, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1492, ncalls=215921, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=39.7295%, Lmin=-0.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1498, ncalls=216880, regioncalls=0, ndraw=128, logz=-3.83, remainder_fraction=39.3938%, Lmin=-0.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=217236, regioncalls=0, ndraw=128, logz=-3.83, remainder_fraction=39.2266%, Lmin=-0.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1508, ncalls=218630, regioncalls=0, ndraw=128, logz=-3.82, remainder_fraction=38.6220%, Lmin=-0.91, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1516, ncalls=219890, regioncalls=0, ndraw=128, logz=-3.81, remainder_fraction=38.0736%, Lmin=-0.89, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1522, ncalls=221352, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.7437%, Lmin=-0.88, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1529, ncalls=222535, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.3219%, Lmin=-0.87, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=222727, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.2575%, Lmin=-0.87, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1537, ncalls=223922, regioncalls=0, ndraw=128, logz=-3.79, remainder_fraction=36.8316%, Lmin=-0.86, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1545, ncalls=225297, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=36.3914%, Lmin=-0.85, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=226001, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=36.0648%, Lmin=-0.84, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1557, ncalls=227211, regioncalls=0, ndraw=128, logz=-3.77, remainder_fraction=35.6278%, Lmin=-0.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1565, ncalls=228491, regioncalls=0, ndraw=128, logz=-3.76, remainder_fraction=35.1825%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1573, ncalls=229851, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=34.6997%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1582, ncalls=231405, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=34.1898%, Lmin=-0.80, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1588, ncalls=232425, regioncalls=0, ndraw=128, logz=-3.74, remainder_fraction=33.8591%, Lmin=-0.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1594, ncalls=234014, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=33.5123%, Lmin=-0.78, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=234722, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=33.1344%, Lmin=-0.77, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1606, ncalls=235930, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=32.7584%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=237299, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=32.2649%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=238351, regioncalls=0, ndraw=128, logz=-3.71, remainder_fraction=31.9350%, Lmin=-0.75, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=239603, regioncalls=0, ndraw=128, logz=-3.71, remainder_fraction=31.6011%, Lmin=-0.74, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1634, ncalls=240903, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=31.1443%, Lmin=-0.74, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1641, ncalls=242354, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.7713%, Lmin=-0.73, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1648, ncalls=243473, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.3679%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=243713, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.2673%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=244993, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=29.9417%, Lmin=-0.71, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1663, ncalls=246209, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=29.5216%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1668, ncalls=247247, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=29.2560%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1676, ncalls=248747, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=28.8177%, Lmin=-0.69, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1684, ncalls=249958, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=28.3780%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1691, ncalls=251223, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=28.0201%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1699, ncalls=252454, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=27.5889%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=252456, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=27.5537%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1708, ncalls=253741, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=27.1738%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=253762, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=27.0691%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1715, ncalls=254976, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=26.8026%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1721, ncalls=256099, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=26.4894%, Lmin=-0.64, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1729, ncalls=257675, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=26.0502%, Lmin=-0.62, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1737, ncalls=259026, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=25.6381%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=260451, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=25.1702%, Lmin=-0.60, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=261074, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=24.9783%, Lmin=-0.60, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1757, ncalls=262618, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=24.6173%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1765, ncalls=263914, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=24.2783%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1773, ncalls=265169, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=23.8709%, Lmin=-0.58, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1781, ncalls=266465, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=23.4919%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=267765, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=23.1560%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1795, ncalls=269142, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=22.8337%, Lmin=-0.56, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=269863, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=22.5989%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1804, ncalls=270731, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=22.4159%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1811, ncalls=272311, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=22.1180%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1819, ncalls=273696, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=21.7683%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1826, ncalls=274507, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.4689%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1830, ncalls=275651, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.2920%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1837, ncalls=276935, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.0046%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1845, ncalls=278293, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.6981%, Lmin=-0.51, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=279113, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.5062%, Lmin=-0.51, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1857, ncalls=280450, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.2144%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1865, ncalls=281972, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=19.8721%, Lmin=-0.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1876, ncalls=283256, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=19.4363%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1885, ncalls=285070, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=19.0849%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=285727, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=18.8919%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1896, ncalls=287050, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=18.6619%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=287684, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=18.5192%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1910, ncalls=288941, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=18.1599%, Lmin=-0.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1917, ncalls=290248, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=17.9067%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1925, ncalls=291586, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.6214%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1933, ncalls=292876, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.3105%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1940, ncalls=294179, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.0645%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=295516, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.7943%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=295613, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.7164%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1958, ncalls=296901, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.4389%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1966, ncalls=298201, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.1662%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1975, ncalls=299993, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.8691%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=300651, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.7044%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1987, ncalls=301913, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.4675%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1995, ncalls=303133, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=15.1802%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=303776, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=15.0240%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2007, ncalls=305031, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=14.8057%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2012, ncalls=306273, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=14.6436%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2020, ncalls=307636, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.3950%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2028, ncalls=308755, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.1553%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2033, ncalls=309871, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.0060%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2041, ncalls=311163, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=13.7559%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2047, ncalls=312307, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=13.5648%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=312313, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.4757%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2055, ncalls=313463, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.3297%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2060, ncalls=314447, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.1879%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2068, ncalls=315751, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.9770%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=315963, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.9210%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2077, ncalls=317183, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.7220%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2084, ncalls=318371, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.5351%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2089, ncalls=319341, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.3974%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2096, ncalls=320561, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.2152%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=321161, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.1107%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2107, ncalls=322344, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=11.9295%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2113, ncalls=323486, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.7690%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2119, ncalls=324648, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.6167%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2126, ncalls=325819, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.4403%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2130, ncalls=326780, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.3350%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2137, ncalls=327927, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.1650%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2142, ncalls=328771, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.0415%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2149, ncalls=330050, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.8644%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=330154, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.8411%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2156, ncalls=331014, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.6940%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=331682, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.6029%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2165, ncalls=332818, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.4874%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2172, ncalls=334125, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.3389%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2180, ncalls=335600, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.1603%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2188, ncalls=336929, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.9863%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2196, ncalls=338257, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.8082%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=338933, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.7195%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2206, ncalls=340016, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.5972%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2210, ncalls=340940, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.5115%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2218, ncalls=342183, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.3382%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=343509, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.1733%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2234, ncalls=344612, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=9.0049%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2241, ncalls=345805, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.8679%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2247, ncalls=347049, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.7529%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=347629, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.6917%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2256, ncalls=348869, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.5758%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2264, ncalls=350130, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.4240%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=351422, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.2731%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2279, ncalls=352749, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=8.1448%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2287, ncalls=354025, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=8.0024%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2296, ncalls=355385, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.8321%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=356045, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.7606%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2308, ncalls=357389, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.6169%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2315, ncalls=358620, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.4990%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2323, ncalls=359956, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.3681%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2330, ncalls=360972, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.2513%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2335, ncalls=361933, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.1699%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=362725, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.0919%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2346, ncalls=363977, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.9940%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=364638, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.9298%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2358, ncalls=365992, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.8025%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2365, ncalls=367191, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.6928%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2375, ncalls=368621, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.5371%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2383, ncalls=370241, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.4196%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2393, ncalls=371563, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.2776%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=372823, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.1795%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2408, ncalls=374076, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.0650%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2416, ncalls=375751, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.9542%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2427, ncalls=377177, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.8079%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=377883, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.7682%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2438, ncalls=379251, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.6650%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2444, ncalls=380555, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.5852%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=381211, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.5106%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2456, ncalls=382575, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.4331%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=383831, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.3338%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2471, ncalls=385167, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.2486%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2479, ncalls=386483, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.1495%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2488, ncalls=388095, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.0446%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2497, ncalls=389615, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.9410%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=389953, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.9061%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2508, ncalls=391758, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.8152%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2517, ncalls=392934, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.7156%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2522, ncalls=394145, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.6598%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2530, ncalls=395380, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.5719%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2537, ncalls=396686, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.4993%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2546, ncalls=398301, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.4054%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=398948, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.3647%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2558, ncalls=400259, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.2835%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2565, ncalls=401596, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.2146%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2573, ncalls=402884, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.1356%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2581, ncalls=404180, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.0578%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2589, ncalls=405476, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.9809%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2595, ncalls=406855, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.9256%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=407511, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.8796%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2607, ncalls=408762, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.8162%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=409074, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.7895%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2617, ncalls=410438, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.7267%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2625, ncalls=411842, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.6574%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2634, ncalls=413543, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.5795%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2642, ncalls=414800, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.5123%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=416076, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.4464%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2658, ncalls=417597, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.3812%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2666, ncalls=418866, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.3186%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2674, ncalls=420228, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.2552%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2682, ncalls=421691, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.1934%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2687, ncalls=422859, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.1555%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2695, ncalls=424153, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0957%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=424853, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0593%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2707, ncalls=426081, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0093%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2716, ncalls=427783, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.9460%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2725, ncalls=429087, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.8832%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2734, ncalls=430734, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.8225%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2743, ncalls=432084, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.7615%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=433209, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.7156%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2759, ncalls=434541, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.6579%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2767, ncalls=435865, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.6072%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2772, ncalls=437051, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.5765%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2781, ncalls=438375, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.5208%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=439611, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4670%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2797, ncalls=441134, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4257%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=441273, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4084%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2808, ncalls=442474, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.3627%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=444228, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.3181%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2822, ncalls=445500, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2847%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2829, ncalls=446603, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2460%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2834, ncalls=447455, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2188%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2842, ncalls=448706, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1764%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2849, ncalls=449926, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1400%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=449954, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1349%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2857, ncalls=451220, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0988%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2865, ncalls=452703, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0584%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2873, ncalls=453977, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0191%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=455237, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9850%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2888, ncalls=456550, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9471%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2896, ncalls=457846, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9099%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=458521, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8913%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2907, ncalls=459673, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8592%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2910, ncalls=460517, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8457%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2919, ncalls=461802, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8059%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2926, ncalls=463176, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7757%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2934, ncalls=464523, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7415%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2942, ncalls=465875, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7078%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=467204, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.6746%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=468947, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.6342%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2969, ncalls=470091, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5992%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=470696, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5954%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2978, ncalls=471947, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5644%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2986, ncalls=473395, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.5339%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2994, ncalls=474732, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.5040%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=475462, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4822%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3006, ncalls=476748, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4606%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3014, ncalls=478046, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4323%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3022, ncalls=479427, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4048%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3031, ncalls=480765, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3746%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3038, ncalls=481985, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3512%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3046, ncalls=483313, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3250%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=484209, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3121%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3058, ncalls=485486, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2867%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=485700, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2804%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3064, ncalls=486716, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2679%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3071, ncalls=488011, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2465%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3079, ncalls=489356, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2224%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3087, ncalls=490653, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1986%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3094, ncalls=491929, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1783%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=492690, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1611%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3107, ncalls=493971, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1413%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3117, ncalls=495411, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1138%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3125, ncalls=496783, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0923%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3132, ncalls=498266, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0737%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3142, ncalls=499798, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0475%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=501237, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0273%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3158, ncalls=502625, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0072%, Lmin=-0.05, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 502865 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.322 +- 0.04713 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1862.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_utils.py::test_tau	0.18
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_utils.py::test_make_log_dirs	0.00
[gw7] linux -- Python 3.10.6 /usr/bin/python3 [gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ Creating directory for new run /tmp/tmpd7voxosd/run1 Creating directory for new run /tmp/tmpd7voxosd/run2
Passed	tests/test_run.py::test_run_compat	14.37
[gw11] linux -- Python 3.10.6 /usr/bin/python3 [gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-3.81) * Expected Volume: exp(0.00) Quality: ok a: -5.0\|******************************************************\| +5.0 b: +0.1\|*********************************** ***** ***\| +1.0 Z=-inf(0.00%) \| Like=-150059.97..-44.75 [-150059.9655..-29270.9321] \| it/evals=0/401 eff=0.0000% N=400 Z=-104734.3(0.00%) \| Like=-100947.38..-44.75 [-150059.9655..-29270.9321] \| it/evals=40/444 eff=90.9091% N=400 Z=-86037.1(0.00%) \| Like=-85924.59..-44.75 [-150059.9655..-29270.9321] \| it/evals=80/489 eff=89.8876% N=400 Mono-modal Volume: ~exp(-4.45) Expected Volume: exp(-0.23) Quality: ok a: -5.0\| ******************************************** \| +5.0 b: +0.1\|****************** ******************************\| +1.0 Z=-80369.4(0.00%) \| Like=-80185.87..-44.75 [-150059.9655..-29270.9321] \| it/evals=90/501 eff=89.1089% N=400 Z=-71475.7(0.00%) \| Like=-69443.05..-21.05 [-150059.9655..-29270.9321] \| it/evals=120/534 eff=89.5522% N=400 Z=-58131.3(0.00%) \| Like=-57488.58..-21.05 [-150059.9655..-29270.9321] \| it/evals=160/580 eff=88.8889% N=400 Mono-modal Volume: ~exp(-4.56) Expected Volume: exp(-0.45) Quality: ok a: -5.0\| -2.7 *********************************** \| +5.0 b: +0.1\|*****************************************************\| +1.0 Z=-52991.0(0.00%) \| Like=-52852.75..-21.05 [-150059.9655..-29270.9321] \| it/evals=180/605 eff=87.8049% N=400 Z=-48345.7(0.00%) \| Like=-47845.05..-21.05 [-150059.9655..-29270.9321] \| it/evals=200/626 eff=88.4956% N=400 Z=-37590.2(0.00%) \| Like=-37078.25..-21.05 [-150059.9655..-29270.9321] \| it/evals=240/673 eff=87.9121% N=400 Mono-modal Volume: ~exp(-4.99) Expected Volume: exp(-0.67) Quality: ok a: -5.0\| -2.0 ************************** +2.9 \| +5.0 b: +0.1\|************************************************* \| +1.0 Z=-30372.3(0.00%) \| Like=-30322.16..-21.05 [-150059.9655..-29270.9321] \| it/evals=270/715 eff=85.7143% N=400 Z=-29298.9(0.00%) \| Like=-29249.63..-21.05 [-29249.6268..-7497.7425] \| it/evals=280/726 eff=85.8896% N=400 Z=-23091.8(0.00%) \| Like=-22946.67..-21.05 [-29249.6268..-7497.7425] \| it/evals=320/783 eff=83.5509% N=400 Mono-modal Volume: ~exp(-4.99) Expected Volume: exp(-0.90) Quality: ok a: -5.0\| -1.4 ********************* +2.5 \| +5.0 b: +0.1\|****************************************** ******\| +1.0 Z=-19145.8(0.00%) \| Like=-19121.63..-21.05 [-29249.6268..-7497.7425] \| it/evals=360/836 eff=82.5688% N=400 Z=-15862.1(0.00%) \| Like=-15678.57..-12.03 [-29249.6268..-7497.7425] \| it/evals=400/887 eff=82.1355% N=400 Z=-12827.1(0.00%) \| Like=-12796.21..-12.03 [-29249.6268..-7497.7425] \| it/evals=440/939 eff=81.6327% N=400 Mono-modal Volume: ~exp(-5.56) Expected Volume: exp(-1.12) Quality: ok a: -5.0\| -1.0 **************** +2.0 \| +5.0 b: +0.1\|****************************************** ******\| +1.0 Z=-12184.6(0.00%) \| Like=-12146.12..-12.03 [-29249.6268..-7497.7425] \| it/evals=450/952 eff=81.5217% N=400 Z=-10323.6(0.00%) \| Like=-10274.28..-12.03 [-29249.6268..-7497.7425] \| it/evals=480/985 eff=82.0513% N=400 Z=-8902.1(0.00%) \| Like=-8890.74..-12.03 [-29249.6268..-7497.7425] \| it/evals=520/1035 eff=81.8898% N=400 Mono-modal Volume: ~exp(-5.92) Expected Volume: exp(-1.35) Quality: ok a: -5.0\| -0.8 ************* +1.7 \| +5.0 b: +0.1\|****************************************** *****\| +1.0 Z=-8189.9(0.00%) \| Like=-8169.35..-12.03 [-29249.6268..-7497.7425] \| it/evals=540/1061 eff=81.6944% N=400 Z=-7413.0(0.00%) \| Like=-7382.62..6.94 [-7486.8234..-2586.6868] \| it/evals=560/1088 eff=81.3953% N=400 Z=-6344.0(0.00%) \| Like=-6266.53..6.94 [-7486.8234..-2586.6868] \| it/evals=600/1141 eff=80.9717% N=400 Mono-modal Volume: ~exp(-5.92) Expected Volume: exp(-1.57) Quality: ok a: -5.0\| -0.5 ******** +1.6 \| +5.0 b: +0.1\|****************************************** ** * \| +1.0 Z=-5508.5(0.00%) \| Like=-5472.47..6.94 [-7486.8234..-2586.6868] \| it/evals=640/1194 eff=80.6045% N=400 Z=-4780.2(0.00%) \| Like=-4683.80..6.94 [-7486.8234..-2586.6868] \| it/evals=680/1248 eff=80.1887% N=400 Mono-modal Volume: ~exp(-5.92) Expected Volume: exp(-1.80) Quality: ok a: -5.0\| -0.4 ******* +1.3 \| +5.0 b: +0.1\|****************************************** * ***\| +1.0 Z=-4018.6(0.00%) \| Like=-4000.38..6.94 [-7486.8234..-2586.6868] \| it/evals=720/1298 eff=80.1782% N=400 Z=-3394.1(0.00%) \| Like=-3362.26..6.94 [-7486.8234..-2586.6868] \| it/evals=760/1345 eff=80.4233% N=400 Z=-2872.6(0.00%) \| Like=-2864.26..6.94 [-7486.8234..-2586.6868] \| it/evals=800/1395 eff=80.4020% N=400 Mono-modal Volume: ~exp(-6.21) Expected Volume: exp(-2.02) Quality: ok a: -5.0\| -0.2 ******* +1.2 \| +5.0 b: +0.1\|********************************** *** * ***\| +1.0 Z=-2789.6(0.00%) \| Like=-2774.48..6.94 [-7486.8234..-2586.6868] \| it/evals=810/1410 eff=80.1980% N=400 Z=-2445.5(0.00%) \| Like=-2411.76..6.94 [-2585.0265..-977.3647] \| it/evals=840/1448 eff=80.1527% N=400 Z=-2007.6(0.00%) \| Like=-1991.57..6.94 [-2585.0265..-977.3647] \| it/evals=880/1497 eff=80.2188% N=400 Mono-modal Volume: ~exp(-6.32) Expected Volume: exp(-2.25) Quality: ok a: -5.0\| -0.1 ****** +1.1 \| +5.0 b: +0.1\|********************************** **** * ***\| +1.0 Z=-1899.4(0.00%) \| Like=-1886.20..6.94 [-2585.0265..-977.3647] \| it/evals=900/1519 eff=80.4290% N=400 Z=-1803.2(0.00%) \| Like=-1779.20..6.94 [-2585.0265..-977.3647] \| it/evals=920/1543 eff=80.4899% N=400 Z=-1572.2(0.00%) \| Like=-1555.01..6.94 [-2585.0265..-977.3647] \| it/evals=960/1596 eff=80.2676% N=400 Mono-modal Volume: ~exp(-6.76) Expected Volume: exp(-2.47) Quality: ok a: -5.0e+00\| -6.7e-03 ***** +1.0e+00 \| +5.0e+00 b: +0.1\|********************************** ********** * * \| +1.0 Z=-1474.5(0.00%) \| Like=-1458.46..6.94 [-2585.0265..-977.3647] \| it/evals=990/1632 eff=80.3571% N=400 Z=-1383.0(0.00%) \| Like=-1374.21..6.94 [-2585.0265..-977.3647] \| it/evals=1000/1644 eff=80.3859% N=400 Z=-1226.8(0.00%) \| Like=-1216.61..6.94 [-2585.0265..-977.3647] \| it/evals=1040/1691 eff=80.5577% N=400 Mono-modal Volume: ~exp(-6.76) Expected Volume: exp(-2.70) Quality: ok a: +0.00\| *** * ******************************************* * \| +1.00 b: +0.1\|*************************************************** \| +1.0 Z=-1084.4(0.00%) \| Like=-1075.73..6.94 [-2585.0265..-977.3647] \| it/evals=1080/1748 eff=80.1187% N=400 Z=-963.0(0.00%) \| Like=-953.68..6.94 [-975.7270..-498.6373] \| it/evals=1120/1798 eff=80.1144% N=400 Z=-855.4(0.00%) \| Like=-844.78..6.94 [-975.7270..-498.6373] \| it/evals=1160/1850 eff=80.0000% N=400 Mono-modal Volume: ~exp(-7.18) * Expected Volume: exp(-2.92) Quality: ok a: +0.0\| * ***************************************** \| +1.0 b: +0.1\|********************************************* \| +1.0 Z=-824.7(0.00%) \| Like=-814.00..6.94 [-975.7270..-498.6373] \| it/evals=1170/1861 eff=80.0821% N=400 Z=-763.2(0.00%) \| Like=-753.01..6.94 [-975.7270..-498.6373] \| it/evals=1200/1902 eff=79.8935% N=400 Z=-692.3(0.00%) \| Like=-682.98..6.94 [-975.7270..-498.6373] \| it/evals=1240/1952 eff=79.8969% N=400 Mono-modal Volume: ~exp(-7.18) Expected Volume: exp(-3.15) Quality: ok a: +0.0\| ************************************ \| +1.0 b: +0.1\| ******************************************* \| +1.0 Z=-644.0(0.00%) \| Like=-634.74..6.94 [-975.7270..-498.6373] \| it/evals=1274/2000 eff=79.6250% N=400 Z=-638.6(0.00%) \| Like=-629.70..6.94 [-975.7270..-498.6373] \| it/evals=1280/2006 eff=79.7011% N=400 Z=-586.3(0.00%) \| Like=-575.50..6.94 [-975.7270..-498.6373] \| it/evals=1320/2052 eff=79.9031% N=400 Mono-modal Volume: ~exp(-7.54) * Expected Volume: exp(-3.37) Quality: ok a: +0.0\| ************************************ \| +1.0 b: +0.1\| **************************************** +0.8 \| +1.0 Z=-555.6(0.00%) \| Like=-546.02..6.94 [-975.7270..-498.6373] \| it/evals=1350/2097 eff=79.5522% N=400 Z=-550.8(0.00%) \| Like=-539.31..6.94 [-975.7270..-498.6373] \| it/evals=1360/2108 eff=79.6253% N=400 Z=-511.1(0.00%) \| Like=-502.53..6.94 [-975.7270..-498.6373] \| it/evals=1400/2161 eff=79.5003% N=400 Mono-modal Volume: ~exp(-7.99) * Expected Volume: exp(-3.60) Quality: ok a: +0.0\| +0.2 ******************************** +0.8 \| +1.0 b: +0.1\| ************************************ +0.8 \| +1.0 Z=-460.0(0.00%) \| Like=-448.24..6.94 [-497.7545..-255.3082] \| it/evals=1440/2211 eff=79.5141% N=400 Z=-415.4(0.00%) \| Like=-405.19..6.94 [-497.7545..-255.3082] \| it/evals=1480/2261 eff=79.5271% N=400 Z=-377.3(0.00%) \| Like=-367.12..6.94 [-497.7545..-255.3082] \| it/evals=1520/2315 eff=79.3734% N=400 Mono-modal Volume: ~exp(-8.08) * Expected Volume: exp(-3.82) Quality: ok a: +0.0\| +0.2 **************************** +0.8 \| +1.0 b: +0.1\| ******************************** +0.8 \| +1.0 Z=-362.2(0.00%) \| Like=-352.36..6.94 [-497.7545..-255.3082] \| it/evals=1530/2335 eff=79.0698% N=400 Z=-333.8(0.00%) \| Like=-324.76..6.94 [-497.7545..-255.3082] \| it/evals=1560/2371 eff=79.1476% N=400 Z=-308.7(0.00%) \| Like=-299.15..6.94 [-497.7545..-255.3082] \| it/evals=1600/2424 eff=79.0514% N=400 Mono-modal Volume: ~exp(-8.18) * Expected Volume: exp(-4.05) Quality: ok a: +0.0\| +0.3 ************************** +0.7 \| +1.0 b: +0.1\| ***************************** +0.7 \| +1.0 Z=-293.7(0.00%) \| Like=-284.49..6.94 [-497.7545..-255.3082] \| it/evals=1620/2448 eff=79.1016% N=400 Z=-284.0(0.00%) \| Like=-274.78..6.94 [-497.7545..-255.3082] \| it/evals=1640/2470 eff=79.2271% N=400 Z=-263.4(0.00%) \| Like=-253.48..6.94 [-254.8939..-131.7677] \| it/evals=1680/2519 eff=79.2827% N=400 Mono-modal Volume: ~exp(-8.73) * Expected Volume: exp(-4.27) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 b: +0.1\| +0.3 ************************ +0.7 \| +1.0 Z=-247.2(0.00%) \| Like=-237.91..6.98 [-254.8939..-131.7677] \| it/evals=1710/2562 eff=79.0934% N=400 Z=-241.6(0.00%) \| Like=-231.36..6.98 [-254.8939..-131.7677] \| it/evals=1720/2574 eff=79.1168% N=400 Z=-223.9(0.00%) \| Like=-213.84..6.98 [-254.8939..-131.7677] \| it/evals=1760/2625 eff=79.1011% N=400 Mono-modal Volume: ~exp(-8.73) Expected Volume: exp(-4.50) Quality: ok a: +0.0\| +0.3 ****************** +0.7 \| +1.0 b: +0.1\| +0.3 ************************ +0.7 \| +1.0 Z=-200.6(0.00%) \| Like=-189.89..7.11 [-254.8939..-131.7677] \| it/evals=1800/2682 eff=78.8782% N=400 Z=-181.7(0.00%) \| Like=-172.17..7.11 [-254.8939..-131.7677] \| it/evals=1840/2741 eff=78.5989% N=400 Z=-170.2(0.00%) \| Like=-160.77..7.11 [-254.8939..-131.7677] \| it/evals=1880/2794 eff=78.5297% N=400 Mono-modal Volume: ~exp(-9.04) * Expected Volume: exp(-4.73) Quality: ok a: +0.0\| +0.3 ****************** +0.7 \| +1.0 b: +0.1\| +0.3 ******************** +0.7 \| +1.0 Z=-166.2(0.00%) \| Like=-154.79..7.11 [-254.8939..-131.7677] \| it/evals=1890/2806 eff=78.5536% N=400 Z=-151.6(0.00%) \| Like=-141.60..7.11 [-254.8939..-131.7677] \| it/evals=1920/2841 eff=78.6563% N=400 Z=-140.7(0.00%) \| Like=-130.92..7.11 [-131.5175..-70.4115] \| it/evals=1960/2898 eff=78.4628% N=400 Mono-modal Volume: ~exp(-9.19) * Expected Volume: exp(-4.95) Quality: ok a: +0.0\| +0.3 **************** +0.7 \| +1.0 b: +0.1\| +0.3 ***************** +0.7 \| +1.0 Z=-134.7(0.00%) \| Like=-124.27..7.11 [-131.5175..-70.4115] \| it/evals=1980/2925 eff=78.4158% N=400 Z=-129.5(0.00%) \| Like=-119.73..7.11 [-131.5175..-70.4115] \| it/evals=2000/2948 eff=78.4929% N=400 Z=-118.0(0.00%) \| Like=-108.43..7.11 [-131.5175..-70.4115] \| it/evals=2040/3003 eff=78.3711% N=400 Mono-modal Volume: ~exp(-9.19) Expected Volume: exp(-5.18) Quality: ok a: +0.0\| +0.4 ************** +0.6 \| +1.0 b: +0.1\| +0.4 ***************** +0.6 \| +1.0 Z=-108.7(0.00%) \| Like=-99.45..7.11 [-131.5175..-70.4115] \| it/evals=2080/3054 eff=78.3723% N=400 Z=-100.6(0.00%) \| Like=-90.81..7.11 [-131.5175..-70.4115] \| it/evals=2120/3108 eff=78.2866% N=400 Mono-modal Volume: ~exp(-9.82) * Expected Volume: exp(-5.40) Quality: ok a: +0.0\| +0.4 ************** +0.6 \| +1.0 b: +0.1\| +0.4 ************** +0.6 \| +1.0 Z=-94.2(0.00%) \| Like=-84.22..7.11 [-131.5175..-70.4115] \| it/evals=2160/3168 eff=78.0347% N=400 Z=-85.7(0.00%) \| Like=-75.78..7.11 [-131.5175..-70.4115] \| it/evals=2200/3216 eff=78.1250% N=400 Z=-77.7(0.00%) \| Like=-67.57..7.11 [-70.3405..-32.6129] \| it/evals=2240/3271 eff=78.0216% N=400 Mono-modal Volume: ~exp(-9.82) Expected Volume: exp(-5.63) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 b: +0.1\| +0.4 ************** +0.6 \| +1.0 Z=-69.7(0.00%) \| Like=-59.45..7.11 [-70.3405..-32.6129] \| it/evals=2280/3322 eff=78.0287% N=400 Z=-63.5(0.00%) \| Like=-53.27..7.14 [-70.3405..-32.6129] \| it/evals=2320/3370 eff=78.1145% N=400 Mono-modal Volume: ~exp(-10.21) * Expected Volume: exp(-5.85) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 b: +0.1\| +0.4 ************ +0.6 \| +1.0 Z=-59.4(0.00%) \| Like=-49.34..7.14 [-70.3405..-32.6129] \| it/evals=2340/3397 eff=78.0781% N=400 Z=-57.0(0.00%) \| Like=-47.23..7.14 [-70.3405..-32.6129] \| it/evals=2360/3423 eff=78.0681% N=400 Z=-52.4(0.00%) \| Like=-42.72..7.14 [-70.3405..-32.6129] \| it/evals=2400/3476 eff=78.0234% N=400 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-6.08) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 b: +0.1\| +0.4 *********** +0.6 \| +1.0 Z=-49.6(0.00%) \| Like=-40.08..7.33 [-70.3405..-32.6129] \| it/evals=2430/3513 eff=78.0597% N=400 Z=-48.7(0.00%) \| Like=-38.96..7.33 [-70.3405..-32.6129] \| it/evals=2440/3523 eff=78.1300% N=400 Z=-44.2(0.00%) \| Like=-34.02..7.33 [-70.3405..-32.6129] \| it/evals=2480/3569 eff=78.2581% N=400 Mono-modal Volume: ~exp(-10.38) * Expected Volume: exp(-6.30) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 b: +0.1\| +0.4 ******** +0.6 \| +1.0 Z=-40.5(0.00%) \| Like=-30.69..7.37 [-32.6004..-14.3802] \| it/evals=2520/3623 eff=78.1880% N=400 Z=-37.6(0.00%) \| Like=-28.06..7.37 [-32.6004..-14.3802] \| it/evals=2560/3669 eff=78.3114% N=400 Z=-34.6(0.00%) \| Like=-24.34..7.37 [-32.6004..-14.3802] \| it/evals=2600/3717 eff=78.3841% N=400 Mono-modal Volume: ~exp(-10.38) Expected Volume: exp(-6.53) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.1\| +0.4 ******** +0.6 \| +1.0 Z=-31.2(0.00%) \| Like=-21.05..7.37 [-32.6004..-14.3802] \| it/evals=2640/3765 eff=78.4547% N=400 Z=-28.7(0.00%) \| Like=-18.82..7.37 [-32.6004..-14.3802] \| it/evals=2680/3819 eff=78.3855% N=400 Mono-modal Volume: ~exp(-11.02) * Expected Volume: exp(-6.75) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.1\| +0.4 ******** +0.6 \| +1.0 Z=-27.5(0.00%) \| Like=-17.74..7.37 [-32.6004..-14.3802] \| it/evals=2700/3846 eff=78.3517% N=400 Z=-26.4(0.00%) \| Like=-16.46..7.37 [-32.6004..-14.3802] \| it/evals=2720/3868 eff=78.4314% N=400 Z=-24.1(0.00%) \| Like=-14.05..7.37 [-14.3780..-3.9396] \| it/evals=2760/3915 eff=78.5206% N=400 Mono-modal Volume: ~exp(-11.24) * Expected Volume: exp(-6.98) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.1\| +0.4 ****** +0.6 \| +1.0 Z=-22.4(0.00%) \| Like=-12.21..7.37 [-14.3780..-3.9396] \| it/evals=2790/3959 eff=78.3928% N=400 Z=-21.8(0.00%) \| Like=-11.95..7.37 [-14.3780..-3.9396] \| it/evals=2800/3970 eff=78.4314% N=400 Z=-20.2(0.00%) \| Like=-10.28..7.37 [-14.3780..-3.9396] \| it/evals=2840/4021 eff=78.4314% N=400 Mono-modal Volume: ~exp(-11.40) * Expected Volume: exp(-7.20) Quality: ok a: +0.0\| +0.4 ****** +0.6 \| +1.0 b: +0.1\| +0.4 ****** +0.6 \| +1.0 Z=-18.6(0.00%) \| Like=-8.69..7.37 [-14.3780..-3.9396] \| it/evals=2880/4075 eff=78.3673% N=400 Z=-17.0(0.00%) \| Like=-6.99..7.37 [-14.3780..-3.9396] \| it/evals=2920/4120 eff=78.4946% N=400 Z=-15.7(0.00%) \| Like=-5.68..7.37 [-14.3780..-3.9396] \| it/evals=2960/4178 eff=78.3483% N=400 Mono-modal Volume: ~exp(-11.64) * Expected Volume: exp(-7.43) Quality: ok a: +0.00\| +0.45 **** +0.55 \| +1.00 b: +0.1\| +0.4 *** +0.5 \| +1.0 Z=-15.4(0.00%) \| Like=-5.42..7.37 [-14.3780..-3.9396] \| it/evals=2970/4189 eff=78.3848% N=400 Z=-14.4(0.00%) \| Like=-4.50..7.37 [-14.3780..-3.9396] \| it/evals=3000/4223 eff=78.4724% N=400 Z=-13.3(0.00%) \| Like=-3.36..7.37 [-3.9354..1.6850] \| it/evals=3040/4277 eff=78.4111% N=400 Mono-modal Volume: ~exp(-11.64) Expected Volume: exp(-7.65) Quality: ok a: +0.00\| +0.46 ** +0.54 \| +1.00 b: +0.10\| +0.46 **** +0.54 \| +1.00 Z=-12.3(0.01%) \| Like=-2.41..7.37 [-3.9354..1.6850] \| it/evals=3080/4327 eff=78.4314% N=400 Z=-11.4(0.02%) \| Like=-1.42..7.37 [-3.9354..1.6850] \| it/evals=3120/4378 eff=78.4314% N=400 Mono-modal Volume: ~exp(-12.23) * Expected Volume: exp(-7.88) Quality: ok a: +0.00\| +0.46 **** +0.54 \| +1.00 b: +0.10\| +0.46 ** +0.54 \| +1.00 Z=-10.8(0.03%) \| Like=-0.86..7.37 [-3.9354..1.6850] \| it/evals=3150/4421 eff=78.3387% N=400 Z=-10.6(0.03%) \| Like=-0.62..7.37 [-3.9354..1.6850] \| it/evals=3160/4431 eff=78.3925% N=400 Z=-9.9(0.07%) \| Like=-0.01..7.37 [-3.9354..1.6850] \| it/evals=3200/4485 eff=78.3354% N=400 Mono-modal Volume: ~exp(-12.23) Expected Volume: exp(-8.10) Quality: ok a: +0.00\| +0.46 ** +0.54 \| +1.00 b: +0.10\| +0.47 **** +0.54 \| +1.00 Z=-9.2(0.14%) \| Like=0.70..7.37 [-3.9354..1.6850] \| it/evals=3240/4535 eff=78.3555% N=400 Z=-8.6(0.26%) \| Like=1.42..7.37 [-3.9354..1.6850] \| it/evals=3278/4579 eff=78.4398% N=400 Z=-8.6(0.27%) \| Like=1.50..7.37 [-3.9354..1.6850] \| it/evals=3280/4582 eff=78.4314% N=400 Z=-8.0(0.49%) \| Like=2.05..7.37 [1.6923..4.1587] \| it/evals=3320/4639 eff=78.3204% N=400 Mono-modal Volume: ~exp(-12.39) * Expected Volume: exp(-8.33) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.10\| +0.47 *** +0.53 \| +1.00 Z=-7.9(0.57%) \| Like=2.15..7.37 [1.6923..4.1587] \| it/evals=3330/4653 eff=78.2977% N=400 Z=-7.5(0.84%) \| Like=2.45..7.37 [1.6923..4.1587] \| it/evals=3360/4691 eff=78.3034% N=400 Z=-7.0(1.26%) \| Like=2.91..7.37 [1.6923..4.1587] \| it/evals=3400/4741 eff=78.3230% N=400 Mono-modal Volume: ~exp(-12.71) * Expected Volume: exp(-8.55) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.10\| +0.47 ** +0.53 \| +1.00 Z=-6.8(1.56%) \| Like=3.16..7.37 [1.6923..4.1587] \| it/evals=3420/4773 eff=78.2072% N=400 Z=-6.6(1.90%) \| Like=3.31..7.37 [1.6923..4.1587] \| it/evals=3440/4798 eff=78.2174% N=400 Z=-6.3(2.69%) \| Like=3.70..7.37 [1.6923..4.1587] \| it/evals=3480/4851 eff=78.1847% N=400 Mono-modal Volume: ~exp(-13.21) * Expected Volume: exp(-8.78) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 b: +0.10\| +0.47 ** +0.53 \| +1.00 Z=-6.0(3.47%) \| Like=4.07..7.37 [1.6923..4.1587] \| it/evals=3510/4883 eff=78.2958% N=400 Z=-5.9(3.75%) \| Like=4.14..7.37 [1.6923..4.1587] \| it/evals=3520/4896 eff=78.2918% N=400 Z=-5.6(5.21%) \| Like=4.39..7.37 [4.1659..4.7607] \| it/evals=3560/4944 eff=78.3451% N=400 Mono-modal Volume: ~exp(-13.36) * Expected Volume: exp(-9.00) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 b: +0.10\| +0.48 ** +0.52 \| +1.00 Z=-5.3(6.88%) \| Like=4.68..7.37 [4.1659..4.7607] \| it/evals=3600/4993 eff=78.3801% N=400 Z=-5.0(8.83%) \| Like=4.93..7.37 [4.7746..4.9545] \| it/evals=3640/5041 eff=78.4314% N=400 Z=-4.8(10.87%) \| Like=5.12..7.37 [5.1236..5.1240]\| it/evals=3680/5093 eff=78.4147% N=400 Mono-modal Volume: ~exp(-13.36) Expected Volume: exp(-9.23) Quality: ok a: +0.00\| +0.48 * +0.52 \| +1.00 b: +0.10\| +0.48 ** +0.52 \| +1.00 Z=-4.7(12.70%) \| Like=5.28..7.37 [5.2759..5.2786]\| it/evals=3713/5137 eff=78.3829% N=400 Z=-4.6(13.10%) \| Like=5.33..7.37 [5.3304..5.3354]\| it/evals=3720/5148 eff=78.3488% N=400 Z=-4.4(15.78%) \| Like=5.50..7.37 [5.5014..5.5038]\| it/evals=3760/5199 eff=78.3497% N=400 Mono-modal Volume: ~exp(-13.36) Expected Volume: exp(-9.45) Quality: ok a: +0.00\| +0.48 * +0.52 \| +1.00 b: +0.10\| +0.48 ** +0.52 \| +1.00 Z=-4.3(18.69%) \| Like=5.68..7.37 [5.6814..5.6889]\| it/evals=3800/5245 eff=78.4314% N=400 Z=-4.1(21.95%) \| Like=5.88..7.37 [5.8831..5.8902]\| it/evals=3840/5295 eff=78.4474% N=400 Mono-modal Volume: ~exp(-13.85) * Expected Volume: exp(-9.68) Quality: ok a: +0.00\| +0.48 +0.52 \| +1.00 b: +0.10\| +0.48 * +0.52 \| +1.00 Z=-4.0(24.55%) \| Like=5.99..7.37 [5.9942..5.9960]\| it/evals=3870/5342 eff=78.3084% N=400 Z=-4.0(25.43%) \| Like=6.02..7.37 [6.0202..6.0249]\| it/evals=3880/5354 eff=78.3205% N=400 Z=-3.8(28.82%) \| Like=6.16..7.37 [6.1617..6.1641]\| it/evals=3920/5409 eff=78.2591% N=400 Mono-modal Volume: ~exp(-14.32) Expected Volume: exp(-9.90) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 * +0.51 \| +1.00 Z=-3.7(32.49%) \| Like=6.28..7.37 [6.2842..6.2846]\| it/evals=3960/5460 eff=78.2609% N=400 Z=-3.6(36.14%) \| Like=6.41..7.37 [6.4106..6.4118]\| it/evals=4000/5516 eff=78.1861% N=400 Z=-3.5(39.90%) \| Like=6.49..7.37 [6.4926..6.4949]\| it/evals=4040/5566 eff=78.2036% N=400 Mono-modal Volume: ~exp(-14.32) Expected Volume: exp(-10.13) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 b: +0.10\| +0.49 ** +0.51 \| +1.00 Z=-3.5(42.07%) \| Like=6.56..7.37 [6.5609..6.5625]\| it/evals=4064/5593 eff=78.2592% N=400 Z=-3.4(43.53%) \| Like=6.58..7.37 [6.5825..6.5828]\| it/evals=4080/5610 eff=78.3109% N=400 Z=-3.4(47.11%) \| Like=6.66..7.37 [6.6583..6.6593]\| it/evals=4120/5660 eff=78.3270% N=400 Mono-modal Volume: ~exp(-14.58) Expected Volume: exp(-10.35) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 +0.51 \| +1.00 Z=-3.3(48.91%) \| Like=6.70..7.37 [6.6999..6.7039]\| it/evals=4140/5685 eff=78.3349% N=400 Z=-3.3(50.57%) \| Like=6.73..7.37 [6.7254..6.7256]\| it/evals=4160/5710 eff=78.3427% N=400 Z=-3.2(54.07%) \| Like=6.79..7.37 [6.7935..6.7968]\| it/evals=4200/5759 eff=78.3728% N=400 Mono-modal Volume: ~exp(-14.58) Expected Volume: exp(-10.58) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 b: +0.10\| +0.49 ** +0.51 \| +1.00 Z=-3.2(57.44%) \| Like=6.87..7.37 [6.8738..6.8752]\| it/evals=4240/5814 eff=78.3155% N=400 Z=-3.1(60.63%) \| Like=6.93..7.37 [6.9326..6.9344]\| it/evals=4280/5863 eff=78.3452% N=400 Mono-modal Volume: ~exp(-14.58) Expected Volume: exp(-10.80) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 +0.51 \| +1.00 Z=-3.1(63.70%) \| Like=6.96..7.37 [6.9634..6.9638]\| it/evals=4320/5927 eff=78.1618% N=400 Z=-3.0(66.60%) \| Like=7.01..7.37 [7.0058..7.0065]\| it/evals=4360/5973 eff=78.2343% N=400 Z=-3.0(69.25%) \| Like=7.05..7.37 [7.0472..7.0492]\| it/evals=4400/6026 eff=78.2083% N=400 Mono-modal Volume: ~exp(-15.49) Expected Volume: exp(-11.02) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 +0.51 \| +1.00 Z=-3.0(69.90%) \| Like=7.06..7.37 [7.0585..7.0592]\| it/evals=4410/6039 eff=78.2054% N=400 Z=-2.9(71.75%) \| Like=7.09..7.37 [7.0875..7.0885]\| it/evals=4440/6073 eff=78.2655% N=400 Z=-2.9(74.08%) \| Like=7.11..7.37 [7.1143..7.1150]\| it/evals=4480/6124 eff=78.2669% N=400 Mono-modal Volume: ~exp(-15.49) Expected Volume: exp(-11.25) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 b: +0.10\| +0.49 ** +0.51 \| +1.00 Z=-2.9(76.27%) \| Like=7.13..7.37 [7.1346..7.1370]\| it/evals=4520/6175 eff=78.2684% N=400 Z=-2.9(78.30%) \| Like=7.16..7.37 [7.1624..7.1628]\| it/evals=4560/6226 eff=78.2698% N=400 Mono-modal Volume: ~exp(-15.68) * Expected Volume: exp(-11.47) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 +0.51 \| +1.00 Z=-2.8(79.73%) \| Like=7.18..7.37 [7.1780..7.1784]\| it/evals=4590/6271 eff=78.1809% N=400 Z=-2.8(80.19%) \| Like=7.18..7.37 [7.1828..7.1828]\| it/evals=4600/6283 eff=78.1914% N=400 Z=-2.8(81.92%) \| Like=7.20..7.37 [7.2017..7.2018]\| it/evals=4640/6331 eff=78.2330% N=400 Mono-modal Volume: ~exp(-16.06) Expected Volume: exp(-11.70) Quality: ok a: +0.00\| +0.49 +0.51 \| +1.00 b: +0.10\| +0.49 +0.51 \| +1.00 Z=-2.8(83.50%) \| Like=7.22..7.37 [7.2158..7.2163]\| it/evals=4680/6376 eff=78.3133% N=400 Z=-2.8(84.96%) \| Like=7.23..7.37 [7.2290..7.2296]\| it/evals=4720/6422 eff=78.3793% N=400 Z=-2.8(86.30%) \| Like=7.24..7.37 [7.2418..7.2425]\| it/evals=4760/6472 eff=78.3926% N=400 Mono-modal Volume: ~exp(-16.27) Expected Volume: exp(-11.92) Quality: ok a: +0.000\| +0.495 +0.505 \| +1.000 b: +0.10\| +0.50 +0.51 \| +1.00 Z=-2.8(86.62%) \| Like=7.24..7.37 [7.2443..7.2449]\| it/evals=4770/6486 eff=78.3766% N=400 Z=-2.7(87.54%) \| Like=7.25..7.37 [7.2528..7.2531]\| it/evals=4800/6521 eff=78.4186% N=400 Z=-2.7(88.65%) \| Like=7.26..7.37 [7.2621..7.2623]\| it/evals=4840/6579 eff=78.3298% N=400 Mono-modal Volume: ~exp(-16.38) Expected Volume: exp(-12.15) Quality: ok a: +0.000\| +0.495 +0.504 \| +1.000 b: +0.100\| +0.496 +0.504 \| +1.000 Z=-2.7(89.18%) \| Like=7.27..7.37 [7.2671..7.2675]\| it/evals=4860/6605 eff=78.3239% N=400 Z=-2.7(89.68%) \| Like=7.27..7.37 [7.2729..7.2730]\| it/evals=4880/6628 eff=78.3558% N=400 Z=-2.7(90.61%) \| Like=7.28..7.37 [7.2809..7.2811]\| it/evals=4920/6675 eff=78.4064% N=400 Mono-modal Volume: ~exp(-16.38) Expected Volume: exp(-12.37) Quality: ok a: +0.000\| +0.496 * +0.504 \| +1.000 b: +0.100\| +0.496 ** +0.504 \| +1.000 Z=-2.7(91.37%) \| Like=7.29..7.37 [7.2879..7.2882]\| it/evals=4955/6724 eff=78.3523% N=400 Z=-2.7(91.47%) \| Like=7.29..7.37 [7.2895..7.2899]\| it/evals=4960/6729 eff=78.3694% N=400 Z=-2.7(92.25%) \| Like=7.30..7.37 [7.2977..7.2981]\| it/evals=5000/6783 eff=78.3331% N=400 Mono-modal Volume: ~exp(-16.56) Expected Volume: exp(-12.60) Quality: ok a: +0.000\| +0.497 +0.504 \| +1.000 b: +0.100\| +0.496 +0.504 \| +1.000 Z=-2.7(92.96%) \| Like=7.30..7.37 [7.3042..7.3043]\| it/evals=5040/6838 eff=78.2852% N=400 Z=-2.7(93.52%) \| Like=7.31..7.37 [7.3103..7.3103]\| it/evals=5074/6882 eff=78.2783% N=400 Z=-2.7(93.61%) \| Like=7.31..7.37 [7.3111..7.3111]\| it/evals=5080/6891 eff=78.2622% N=400 Z=-2.7(94.21%) \| Like=7.32..7.37 [7.3152..7.3153]\| it/evals=5120/6948 eff=78.1918% N=400 Mono-modal Volume: ~exp(-17.02) * Expected Volume: exp(-12.82) Quality: ok a: +0.000\| +0.497 +0.503 \| +1.000 b: +0.100\| +0.497 +0.503 \| +1.000 Z=-2.7(94.35%) \| Like=7.32..7.37 [7.3162..7.3164]\| it/evals=5130/6960 eff=78.2012% N=400 Z=-2.7(94.74%) \| Like=7.32..7.37 [7.3203..7.3204]\| it/evals=5160/6997 eff=78.2174% N=400 Z=-2.7(95.23%) \| Like=7.33..7.37 [7.3258..7.3259]\| it/evals=5200/7048 eff=78.2190% N=400 Mono-modal Volume: ~exp(-17.46) Expected Volume: exp(-13.05) Quality: ok a: +0.000\| +0.497 +0.503 \| +1.000 b: +0.100\| +0.497 +0.503 \| +1.000 Z=-2.7(95.46%) \| Like=7.33..7.37 [7.3290..7.3290]\| it/evals=5220/7073 eff=78.2257% N=400 Z=-2.7(95.67%) \| Like=7.33..7.37 [7.3307..7.3310]\| it/evals=5240/7096 eff=78.2557% N=400 Z=-2.6(96.08%) \| Like=7.33..7.37 [7.3350..7.3350]\| it/evals=5280/7145 eff=78.2802% N=400 Mono-modal Volume: ~exp(-17.46) Expected Volume: exp(-13.27) Quality: ok a: +0.000\| +0.497 * +0.503 \| +1.000 b: +0.100\| +0.497 ** +0.503 \| +1.000 Z=-2.6(96.45%) \| Like=7.34..7.37 [7.3383..7.3385]\| it/evals=5320/7199 eff=78.2468% N=400 Z=-2.6(96.78%) \| Like=7.34..7.37 [7.3419..7.3419]\| it/evals=5360/7253 eff=78.2139% N=400 Mono-modal Volume: ~exp(-17.90) * Expected Volume: exp(-13.50) Quality: ok a: +0.000\| +0.498 +0.502 \| +1.000 b: +0.100\| +0.498 +0.502 \| +1.000 Z=-2.6(97.08%) \| Like=7.35..7.37 [7.3454..7.3454]\| it/evals=5400/7305 eff=78.2042% N=400 Z=-2.6(97.35%) \| Like=7.35..7.37 [7.3478..7.3479]\| it/evals=5440/7352 eff=78.2509% N=400 Z=-2.6(97.60%) \| Like=7.35..7.37 [7.3500..7.3500]\| it/evals=5480/7409 eff=78.1852% N=400 Mono-modal Volume: ~exp(-17.98) Expected Volume: exp(-13.72) Quality: ok a: +0.000\| +0.498 +0.502 \| +1.000 b: +0.100\| +0.498 +0.502 \| +1.000 Z=-2.6(97.66%) \| Like=7.35..7.37 [7.3507..7.3507]\| it/evals=5490/7422 eff=78.1829% N=400 Z=-2.6(97.83%) \| Like=7.35..7.37 [7.3524..7.3524]\| it/evals=5520/7462 eff=78.1648% N=400 Z=-2.6(98.03%) \| Like=7.35..7.37 [7.3541..7.3541]\| it/evals=5560/7518 eff=78.1118% N=400 Mono-modal Volume: ~exp(-18.06) Expected Volume: exp(-13.95) Quality: ok a: +0.000\| +0.498 +0.502 \| +1.000 b: +0.100\| +0.498 +0.502 \| +1.000 Z=-2.6(98.13%) \| Like=7.35..7.37 [7.3548..7.3549]\| it/evals=5580/7547 eff=78.0747% N=400 Z=-2.6(98.22%) \| Like=7.36..7.37 [7.3555..7.3555]\| it/evals=5600/7571 eff=78.0923% N=400 Z=-2.6(98.39%) \| Like=7.36..7.37 [7.3573..7.3573]\| it/evals=5640/7620 eff=78.1163% N=400 Mono-modal Volume: ~exp(-18.68) Expected Volume: exp(-14.17) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 b: +0.100\| +0.498 * +0.502 \| +1.000 Z=-2.6(98.50%) \| Like=7.36..7.37 [7.3586..7.3587]\| it/evals=5670/7663 eff=78.0669% N=400 Z=-2.6(98.54%) \| Like=7.36..7.37 [7.3589..7.3589]\| it/evals=5680/7674 eff=78.0863% N=400 Z=-2.6(98.68%) \| Like=7.36..7.37 [7.3603..7.3603]\| it/evals=5720/7724 eff=78.0994% N=400 Mono-modal Volume: ~exp(-18.68) Expected Volume: exp(-14.40) Quality: ok a: +0.000\| +0.499 * +0.501 \| +1.000 b: +0.100\| +0.499 * +0.501 \| +1.000 Z=-2.6(98.80%) \| Like=7.36..7.37 [7.3612..7.3613]\| it/evals=5760/7779 eff=78.0594% N=400 Z=-2.6(98.92%) \| Like=7.36..7.37 [7.3622..7.3622]\| it/evals=5800/7830 eff=78.0619% N=400 [ultranest] Explored until L=7 [ultranest] Likelihood function evaluations: 7875 [ultranest] logZ = -2.61 +- 0.1019 [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.10 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [ultranest] logZ error budget: single: 0.15 bs:0.10 tail:0.01 total:0.10 required:<0.50 [ultranest] done iterating. logZ = -2.607 +- 0.217 single instance: logZ = -2.607 +- 0.150 bootstrapped : logZ = -2.610 +- 0.217 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : 0.4543│ ▁ ▁▁▁▁▁▁▁▁▂▂▂▃▄▄▄▆▇▇▆▆▅▄▄▃▂▂▁▁▁▁▁▁▁ ▁ │0.5399 0.4997 +- 0.0100 b : 0.4567│ ▁ ▁▁▁▁▁▁▁▂▂▃▄▄▅▇▇▇▇▆▆▆▄▄▃▂▂▁▁▁▁▁▁▁▁▁ │0.5410 0.4998 +- 0.0098 evidence: -2.6 +- 0.2 parameter values: a : 0.500 +- 0.010 b : 0.500 +- 0.010 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=0 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-150059.97, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=-104734.27, remainder_fraction=100.0000%, Lmin=-100947.38, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=489, regioncalls=3560, ndraw=40, logz=-86037.10, remainder_fraction=100.0000%, Lmin=-85924.59, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=501, regioncalls=4040, ndraw=40, logz=-80369.36, remainder_fraction=100.0000%, Lmin=-80185.87, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=534, regioncalls=5360, ndraw=40, logz=-71475.71, remainder_fraction=100.0000%, Lmin=-69443.05, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=580, regioncalls=7200, ndraw=40, logz=-58131.26, remainder_fraction=100.0000%, Lmin=-57488.58, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=605, regioncalls=8200, ndraw=40, logz=-52990.96, remainder_fraction=100.0000%, Lmin=-52852.75, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=626, regioncalls=9040, ndraw=40, logz=-48345.67, remainder_fraction=100.0000%, Lmin=-47845.05, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=673, regioncalls=10920, ndraw=40, logz=-37590.25, remainder_fraction=100.0000%, Lmin=-37078.25, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=715, regioncalls=12600, ndraw=40, logz=-30372.34, remainder_fraction=100.0000%, Lmin=-30322.16, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=726, regioncalls=13040, ndraw=40, logz=-29298.93, remainder_fraction=100.0000%, Lmin=-29249.63, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=783, regioncalls=15320, ndraw=40, logz=-23091.82, remainder_fraction=100.0000%, Lmin=-22946.67, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=836, regioncalls=17440, ndraw=40, logz=-19145.77, remainder_fraction=100.0000%, Lmin=-19121.63, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=887, regioncalls=19480, ndraw=40, logz=-15862.07, remainder_fraction=100.0000%, Lmin=-15678.57, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=939, regioncalls=21560, ndraw=40, logz=-12827.12, remainder_fraction=100.0000%, Lmin=-12796.21, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=952, regioncalls=22080, ndraw=40, logz=-12184.58, remainder_fraction=100.0000%, Lmin=-12146.12, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=985, regioncalls=23400, ndraw=40, logz=-10323.61, remainder_fraction=100.0000%, Lmin=-10274.28, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1035, regioncalls=25400, ndraw=40, logz=-8902.07, remainder_fraction=100.0000%, Lmin=-8890.74, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1061, regioncalls=26440, ndraw=40, logz=-8189.90, remainder_fraction=100.0000%, Lmin=-8169.35, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1088, regioncalls=27520, ndraw=40, logz=-7412.95, remainder_fraction=100.0000%, Lmin=-7382.62, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1141, regioncalls=29640, ndraw=40, logz=-6343.98, remainder_fraction=100.0000%, Lmin=-6266.53, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1194, regioncalls=31760, ndraw=40, logz=-5508.53, remainder_fraction=100.0000%, Lmin=-5472.47, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1248, regioncalls=33920, ndraw=40, logz=-4780.23, remainder_fraction=100.0000%, Lmin=-4683.80, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1298, regioncalls=35920, ndraw=40, logz=-4018.64, remainder_fraction=100.0000%, Lmin=-4000.38, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1345, regioncalls=37800, ndraw=40, logz=-3394.13, remainder_fraction=100.0000%, Lmin=-3362.26, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1395, regioncalls=39800, ndraw=40, logz=-2872.61, remainder_fraction=100.0000%, Lmin=-2864.26, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1410, regioncalls=40400, ndraw=40, logz=-2789.64, remainder_fraction=100.0000%, Lmin=-2774.48, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1448, regioncalls=41920, ndraw=40, logz=-2445.48, remainder_fraction=100.0000%, Lmin=-2411.76, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1497, regioncalls=43880, ndraw=40, logz=-2007.65, remainder_fraction=100.0000%, Lmin=-1991.57, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1519, regioncalls=44760, ndraw=40, logz=-1899.35, remainder_fraction=100.0000%, Lmin=-1886.20, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1543, regioncalls=45720, ndraw=40, logz=-1803.23, remainder_fraction=100.0000%, Lmin=-1779.20, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1596, regioncalls=47840, ndraw=40, logz=-1572.18, remainder_fraction=100.0000%, Lmin=-1555.01, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1632, regioncalls=49280, ndraw=40, logz=-1474.50, remainder_fraction=100.0000%, Lmin=-1458.46, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1644, regioncalls=49760, ndraw=40, logz=-1382.97, remainder_fraction=100.0000%, Lmin=-1374.21, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1691, regioncalls=51680, ndraw=40, logz=-1226.78, remainder_fraction=100.0000%, Lmin=-1216.61, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1748, regioncalls=53960, ndraw=40, logz=-1084.45, remainder_fraction=100.0000%, Lmin=-1075.73, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1798, regioncalls=56040, ndraw=40, logz=-963.03, remainder_fraction=100.0000%, Lmin=-953.68, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1850, regioncalls=58200, ndraw=40, logz=-855.36, remainder_fraction=100.0000%, Lmin=-844.78, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1861, regioncalls=58640, ndraw=40, logz=-824.69, remainder_fraction=100.0000%, Lmin=-814.00, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1902, regioncalls=60360, ndraw=40, logz=-763.19, remainder_fraction=100.0000%, Lmin=-753.01, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1952, regioncalls=62360, ndraw=40, logz=-692.35, remainder_fraction=100.0000%, Lmin=-682.98, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1274, ncalls=2000, regioncalls=64280, ndraw=40, logz=-644.03, remainder_fraction=100.0000%, Lmin=-634.74, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2006, regioncalls=64520, ndraw=40, logz=-638.58, remainder_fraction=100.0000%, Lmin=-629.70, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2052, regioncalls=66400, ndraw=40, logz=-586.31, remainder_fraction=100.0000%, Lmin=-575.50, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2097, regioncalls=68200, ndraw=40, logz=-555.60, remainder_fraction=100.0000%, Lmin=-546.02, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2108, regioncalls=68720, ndraw=40, logz=-550.77, remainder_fraction=100.0000%, Lmin=-539.31, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2161, regioncalls=70920, ndraw=40, logz=-511.11, remainder_fraction=100.0000%, Lmin=-502.53, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2211, regioncalls=72960, ndraw=40, logz=-460.01, remainder_fraction=100.0000%, Lmin=-448.24, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2261, regioncalls=75200, ndraw=40, logz=-415.38, remainder_fraction=100.0000%, Lmin=-405.19, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2315, regioncalls=77520, ndraw=40, logz=-377.25, remainder_fraction=100.0000%, Lmin=-367.12, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2335, regioncalls=78360, ndraw=40, logz=-362.18, remainder_fraction=100.0000%, Lmin=-352.36, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2371, regioncalls=79800, ndraw=40, logz=-333.83, remainder_fraction=100.0000%, Lmin=-324.76, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2424, regioncalls=81960, ndraw=40, logz=-308.69, remainder_fraction=100.0000%, Lmin=-299.15, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2448, regioncalls=83000, ndraw=40, logz=-293.74, remainder_fraction=100.0000%, Lmin=-284.49, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2470, regioncalls=83880, ndraw=40, logz=-283.97, remainder_fraction=100.0000%, Lmin=-274.78, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2519, regioncalls=85880, ndraw=40, logz=-263.38, remainder_fraction=100.0000%, Lmin=-253.48, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2562, regioncalls=87600, ndraw=40, logz=-247.25, remainder_fraction=100.0000%, Lmin=-237.91, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2574, regioncalls=88120, ndraw=40, logz=-241.56, remainder_fraction=100.0000%, Lmin=-231.36, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2625, regioncalls=90320, ndraw=40, logz=-223.90, remainder_fraction=100.0000%, Lmin=-213.84, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2682, regioncalls=92640, ndraw=40, logz=-200.63, remainder_fraction=100.0000%, Lmin=-189.89, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2741, regioncalls=95200, ndraw=40, logz=-181.65, remainder_fraction=100.0000%, Lmin=-172.17, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2794, regioncalls=97360, ndraw=40, logz=-170.22, remainder_fraction=100.0000%, Lmin=-160.77, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2806, regioncalls=97840, ndraw=40, logz=-166.23, remainder_fraction=100.0000%, Lmin=-154.79, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=2841, regioncalls=99320, ndraw=40, logz=-151.55, remainder_fraction=100.0000%, Lmin=-141.60, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=2898, regioncalls=101600, ndraw=40, logz=-140.72, remainder_fraction=100.0000%, Lmin=-130.92, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2925, regioncalls=102720, ndraw=40, logz=-134.73, remainder_fraction=100.0000%, Lmin=-124.27, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2948, regioncalls=103640, ndraw=40, logz=-129.51, remainder_fraction=100.0000%, Lmin=-119.73, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3003, regioncalls=105840, ndraw=40, logz=-118.04, remainder_fraction=100.0000%, Lmin=-108.43, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3054, regioncalls=107960, ndraw=40, logz=-108.75, remainder_fraction=100.0000%, Lmin=-99.45, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3108, regioncalls=110160, ndraw=40, logz=-100.55, remainder_fraction=100.0000%, Lmin=-90.81, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3168, regioncalls=112760, ndraw=40, logz=-94.24, remainder_fraction=100.0000%, Lmin=-84.22, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3216, regioncalls=114680, ndraw=40, logz=-85.72, remainder_fraction=100.0000%, Lmin=-75.78, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3271, regioncalls=116880, ndraw=40, logz=-77.65, remainder_fraction=100.0000%, Lmin=-67.57, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3322, regioncalls=119080, ndraw=40, logz=-69.66, remainder_fraction=100.0000%, Lmin=-59.45, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3370, regioncalls=121040, ndraw=40, logz=-63.49, remainder_fraction=100.0000%, Lmin=-53.27, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3397, regioncalls=122200, ndraw=40, logz=-59.38, remainder_fraction=100.0000%, Lmin=-49.34, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3423, regioncalls=123240, ndraw=40, logz=-56.99, remainder_fraction=100.0000%, Lmin=-47.23, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3476, regioncalls=125440, ndraw=40, logz=-52.43, remainder_fraction=100.0000%, Lmin=-42.72, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3513, regioncalls=127000, ndraw=40, logz=-49.58, remainder_fraction=100.0000%, Lmin=-40.08, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3523, regioncalls=127400, ndraw=40, logz=-48.72, remainder_fraction=100.0000%, Lmin=-38.96, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3569, regioncalls=129360, ndraw=40, logz=-44.19, remainder_fraction=100.0000%, Lmin=-34.02, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3623, regioncalls=131600, ndraw=40, logz=-40.55, remainder_fraction=100.0000%, Lmin=-30.69, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3669, regioncalls=133440, ndraw=40, logz=-37.57, remainder_fraction=100.0000%, Lmin=-28.06, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3717, regioncalls=135360, ndraw=40, logz=-34.64, remainder_fraction=100.0000%, Lmin=-24.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=3765, regioncalls=137440, ndraw=40, logz=-31.18, remainder_fraction=100.0000%, Lmin=-21.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=3819, regioncalls=139840, ndraw=40, logz=-28.69, remainder_fraction=100.0000%, Lmin=-18.82, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3846, regioncalls=141080, ndraw=40, logz=-27.51, remainder_fraction=100.0000%, Lmin=-17.74, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=3868, regioncalls=142000, ndraw=40, logz=-26.35, remainder_fraction=100.0000%, Lmin=-16.46, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=3915, regioncalls=143920, ndraw=40, logz=-24.06, remainder_fraction=100.0000%, Lmin=-14.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3959, regioncalls=145720, ndraw=40, logz=-22.35, remainder_fraction=100.0000%, Lmin=-12.21, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3970, regioncalls=146160, ndraw=40, logz=-21.84, remainder_fraction=100.0000%, Lmin=-11.95, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4021, regioncalls=148280, ndraw=40, logz=-20.19, remainder_fraction=100.0000%, Lmin=-10.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4075, regioncalls=150520, ndraw=40, logz=-18.57, remainder_fraction=100.0000%, Lmin=-8.69, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4120, regioncalls=152320, ndraw=40, logz=-17.00, remainder_fraction=99.9999%, Lmin=-6.99, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4178, regioncalls=154720, ndraw=40, logz=-15.70, remainder_fraction=99.9998%, Lmin=-5.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4189, regioncalls=155240, ndraw=40, logz=-15.38, remainder_fraction=99.9997%, Lmin=-5.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4223, regioncalls=156600, ndraw=40, logz=-14.41, remainder_fraction=99.9993%, Lmin=-4.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4277, regioncalls=158800, ndraw=40, logz=-13.32, remainder_fraction=99.9978%, Lmin=-3.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4327, regioncalls=160840, ndraw=40, logz=-12.33, remainder_fraction=99.9941%, Lmin=-2.41, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4378, regioncalls=162960, ndraw=40, logz=-11.38, remainder_fraction=99.9840%, Lmin=-1.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4421, regioncalls=164920, ndraw=40, logz=-10.79, remainder_fraction=99.9719%, Lmin=-0.86, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4431, regioncalls=165320, ndraw=40, logz=-10.59, remainder_fraction=99.9658%, Lmin=-0.62, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4485, regioncalls=167480, ndraw=40, logz=-9.87, remainder_fraction=99.9273%, Lmin=-0.01, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4535, regioncalls=169480, ndraw=40, logz=-9.23, remainder_fraction=99.8568%, Lmin=0.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3278, ncalls=4579, regioncalls=171240, ndraw=40, logz=-8.63, remainder_fraction=99.7381%, Lmin=1.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4582, regioncalls=171360, ndraw=40, logz=-8.60, remainder_fraction=99.7283%, Lmin=1.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4639, regioncalls=173640, ndraw=40, logz=-8.00, remainder_fraction=99.5053%, Lmin=2.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=4653, regioncalls=174240, ndraw=40, logz=-7.87, remainder_fraction=99.4304%, Lmin=2.15, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=4691, regioncalls=175760, ndraw=40, logz=-7.49, remainder_fraction=99.1633%, Lmin=2.45, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4741, regioncalls=177760, ndraw=40, logz=-7.05, remainder_fraction=98.7439%, Lmin=2.91, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4773, regioncalls=179120, ndraw=40, logz=-6.83, remainder_fraction=98.4381%, Lmin=3.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=4798, regioncalls=180120, ndraw=40, logz=-6.63, remainder_fraction=98.0980%, Lmin=3.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=4851, regioncalls=182240, ndraw=40, logz=-6.25, remainder_fraction=97.3054%, Lmin=3.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=4883, regioncalls=183560, ndraw=40, logz=-5.99, remainder_fraction=96.5291%, Lmin=4.07, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=4896, regioncalls=184080, ndraw=40, logz=-5.90, remainder_fraction=96.2471%, Lmin=4.14, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=4944, regioncalls=186000, ndraw=40, logz=-5.58, remainder_fraction=94.7862%, Lmin=4.39, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=4993, regioncalls=188040, ndraw=40, logz=-5.30, remainder_fraction=93.1211%, Lmin=4.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=5041, regioncalls=189960, ndraw=40, logz=-5.05, remainder_fraction=91.1694%, Lmin=4.93, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=5093, regioncalls=192040, ndraw=40, logz=-4.82, remainder_fraction=89.1330%, Lmin=5.12, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3713, ncalls=5137, regioncalls=193960, ndraw=40, logz=-4.66, remainder_fraction=87.3015%, Lmin=5.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=5148, regioncalls=194400, ndraw=40, logz=-4.62, remainder_fraction=86.8964%, Lmin=5.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=5199, regioncalls=196600, ndraw=40, logz=-4.44, remainder_fraction=84.2154%, Lmin=5.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5245, regioncalls=198760, ndraw=40, logz=-4.27, remainder_fraction=81.3149%, Lmin=5.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=5295, regioncalls=200800, ndraw=40, logz=-4.12, remainder_fraction=78.0537%, Lmin=5.88, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3870, ncalls=5342, regioncalls=202720, ndraw=40, logz=-4.01, remainder_fraction=75.4451%, Lmin=5.99, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=5354, regioncalls=203200, ndraw=40, logz=-3.98, remainder_fraction=74.5652%, Lmin=6.02, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=5409, regioncalls=205440, ndraw=40, logz=-3.85, remainder_fraction=71.1762%, Lmin=6.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=5460, regioncalls=207560, ndraw=40, logz=-3.73, remainder_fraction=67.5136%, Lmin=6.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=5516, regioncalls=209800, ndraw=40, logz=-3.62, remainder_fraction=63.8559%, Lmin=6.41, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=5566, regioncalls=211800, ndraw=40, logz=-3.53, remainder_fraction=60.1034%, Lmin=6.49, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4064, ncalls=5593, regioncalls=212920, ndraw=40, logz=-3.47, remainder_fraction=57.9275%, Lmin=6.56, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=5610, regioncalls=213680, ndraw=40, logz=-3.44, remainder_fraction=56.4701%, Lmin=6.58, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=5660, regioncalls=215800, ndraw=40, logz=-3.36, remainder_fraction=52.8938%, Lmin=6.66, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=5685, regioncalls=216840, ndraw=40, logz=-3.32, remainder_fraction=51.0927%, Lmin=6.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=5710, regioncalls=217840, ndraw=40, logz=-3.29, remainder_fraction=49.4302%, Lmin=6.73, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=5759, regioncalls=219800, ndraw=40, logz=-3.22, remainder_fraction=45.9272%, Lmin=6.79, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=5814, regioncalls=222080, ndraw=40, logz=-3.16, remainder_fraction=42.5649%, Lmin=6.87, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=5863, regioncalls=224320, ndraw=40, logz=-3.11, remainder_fraction=39.3748%, Lmin=6.93, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=5927, regioncalls=226960, ndraw=40, logz=-3.06, remainder_fraction=36.2988%, Lmin=6.96, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=5973, regioncalls=229280, ndraw=40, logz=-3.02, remainder_fraction=33.3961%, Lmin=7.01, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=6026, regioncalls=231640, ndraw=40, logz=-2.98, remainder_fraction=30.7454%, Lmin=7.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4410, ncalls=6039, regioncalls=232280, ndraw=40, logz=-2.97, remainder_fraction=30.0950%, Lmin=7.06, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=6073, regioncalls=233640, ndraw=40, logz=-2.94, remainder_fraction=28.2514%, Lmin=7.09, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=6124, regioncalls=235680, ndraw=40, logz=-2.91, remainder_fraction=25.9230%, Lmin=7.11, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=6175, regioncalls=237800, ndraw=40, logz=-2.88, remainder_fraction=23.7342%, Lmin=7.13, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=6226, regioncalls=239920, ndraw=40, logz=-2.85, remainder_fraction=21.6995%, Lmin=7.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=6271, regioncalls=241760, ndraw=40, logz=-2.83, remainder_fraction=20.2731%, Lmin=7.18, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=6283, regioncalls=242240, ndraw=40, logz=-2.83, remainder_fraction=19.8052%, Lmin=7.18, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=6331, regioncalls=244160, ndraw=40, logz=-2.81, remainder_fraction=18.0759%, Lmin=7.20, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=6376, regioncalls=246000, ndraw=40, logz=-2.79, remainder_fraction=16.5029%, Lmin=7.22, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=6422, regioncalls=247880, ndraw=40, logz=-2.77, remainder_fraction=15.0420%, Lmin=7.23, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=6472, regioncalls=249880, ndraw=40, logz=-2.75, remainder_fraction=13.6991%, Lmin=7.24, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=6486, regioncalls=250520, ndraw=40, logz=-2.75, remainder_fraction=13.3817%, Lmin=7.24, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=6521, regioncalls=251960, ndraw=40, logz=-2.74, remainder_fraction=12.4589%, Lmin=7.25, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=6579, regioncalls=254280, ndraw=40, logz=-2.73, remainder_fraction=11.3485%, Lmin=7.26, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=6605, regioncalls=255400, ndraw=40, logz=-2.72, remainder_fraction=10.8204%, Lmin=7.27, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=6628, regioncalls=256320, ndraw=40, logz=-2.72, remainder_fraction=10.3187%, Lmin=7.27, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=6675, regioncalls=258200, ndraw=40, logz=-2.71, remainder_fraction=9.3888%, Lmin=7.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4955, ncalls=6724, regioncalls=260240, ndraw=40, logz=-2.70, remainder_fraction=8.6349%, Lmin=7.29, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=6729, regioncalls=260440, ndraw=40, logz=-2.70, remainder_fraction=8.5328%, Lmin=7.29, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=6783, regioncalls=262760, ndraw=40, logz=-2.69, remainder_fraction=7.7468%, Lmin=7.30, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=6838, regioncalls=265080, ndraw=40, logz=-2.68, remainder_fraction=7.0364%, Lmin=7.30, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5074, ncalls=6882, regioncalls=266840, ndraw=40, logz=-2.67, remainder_fraction=6.4801%, Lmin=7.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=6891, regioncalls=267200, ndraw=40, logz=-2.67, remainder_fraction=6.3868%, Lmin=7.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=6948, regioncalls=269520, ndraw=40, logz=-2.67, remainder_fraction=5.7946%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=6960, regioncalls=270040, ndraw=40, logz=-2.67, remainder_fraction=5.6548%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=6997, regioncalls=271560, ndraw=40, logz=-2.66, remainder_fraction=5.2573%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=7048, regioncalls=273600, ndraw=40, logz=-2.66, remainder_fraction=4.7704%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=7073, regioncalls=274640, ndraw=40, logz=-2.65, remainder_fraction=4.5435%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=7096, regioncalls=275560, ndraw=40, logz=-2.65, remainder_fraction=4.3270%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=7145, regioncalls=277520, ndraw=40, logz=-2.65, remainder_fraction=3.9223%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=7199, regioncalls=279720, ndraw=40, logz=-2.64, remainder_fraction=3.5549%, Lmin=7.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=7253, regioncalls=282160, ndraw=40, logz=-2.64, remainder_fraction=3.2218%, Lmin=7.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=7305, regioncalls=284320, ndraw=40, logz=-2.64, remainder_fraction=2.9192%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=7352, regioncalls=286240, ndraw=40, logz=-2.63, remainder_fraction=2.6453%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=7409, regioncalls=288520, ndraw=40, logz=-2.63, remainder_fraction=2.3966%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=7422, regioncalls=289080, ndraw=40, logz=-2.63, remainder_fraction=2.3382%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=7462, regioncalls=290720, ndraw=40, logz=-2.63, remainder_fraction=2.1709%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=7518, regioncalls=292960, ndraw=40, logz=-2.63, remainder_fraction=1.9659%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5580, ncalls=7547, regioncalls=294160, ndraw=40, logz=-2.63, remainder_fraction=1.8707%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=7571, regioncalls=295120, ndraw=40, logz=-2.63, remainder_fraction=1.7802%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=7620, regioncalls=297080, ndraw=40, logz=-2.62, remainder_fraction=1.6120%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=7663, regioncalls=298880, ndraw=40, logz=-2.62, remainder_fraction=1.4964%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=7674, regioncalls=299360, ndraw=40, logz=-2.62, remainder_fraction=1.4598%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=7724, regioncalls=301440, ndraw=40, logz=-2.62, remainder_fraction=1.3217%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=7779, regioncalls=303760, ndraw=40, logz=-2.62, remainder_fraction=1.1966%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=7830, regioncalls=306040, ndraw=40, logz=-2.62, remainder_fraction=1.0835%, Lmin=7.36, Lmax=7.37 INFO ultranest:integrator.py:2654 Explored until L=7 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 7875 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -2.61 +- 0.1019 INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.10 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.15 bs:0.10 tail:0.01 total:0.10 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:2894 Making corner plot ... DEBUG ultranest:integrator.py:2940 Making run plot ... DEBUG ultranest:integrator.py:2916 Making trace plot ...
Passed	tests/test_run.py::test_run_warmstart_gauss_SLOW	63.51
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ====== Running Gauss problem [1] ===== center: 0 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-5e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=0/528 eff=0.0000% N=400 Z=-4e+13(0.00%) \| Like=-4.2e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=40/528 eff=31.2500% N=400 Z=-4e+13(0.00%) \| Like=-3.5e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=80/528 eff=62.5000% N=400 Z=-3e+13(0.00%) \| Like=-3.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=90/528 eff=70.3125% N=400 Z=-3e+13(0.00%) \| Like=-2.9e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=120/635 eff=51.0638% N=400 Z=-2e+13(0.00%) \| Like=-2.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=160/635 eff=68.0851% N=400 Z=-2e+13(0.00%) \| Like=-2.2e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=180/635 eff=76.5957% N=400 Z=-2e+13(0.00%) \| Like=-1.9e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=200/635 eff=85.1064% N=400 Z=-2e+13(0.00%) \| Like=-1.6e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=240/722 eff=74.5342% N=400 Z=-1e+13(0.00%) \| Like=-1.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] \| it/evals=270/722 eff=83.8509% N=400 Z=-1e+13(0.00%) \| Like=-1.3e+13..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=280/789 eff=71.9794% N=400 Z=-1e+13(0.00%) \| Like=-1.1e+13..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=320/789 eff=82.2622% N=400 Z=-8e+12(0.00%) \| Like=-8.2e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=360/844 eff=81.0811% N=400 Z=-7e+12(0.00%) \| Like=-6.9e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=400/888 eff=81.9672% N=400 Z=-6e+12(0.00%) \| Like=-5.7e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=440/935 eff=82.2430% N=400 Z=-5e+12(0.00%) \| Like=-4.6e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=480/978 eff=83.0450% N=400 Z=-4e+12(0.00%) \| Like=-3.7e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=520/1016 eff=84.4156% N=400 Z=-3e+12(0.00%) \| Like=-3.4e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=540/1016 eff=87.6623% N=400 Z=-3e+12(0.00%) \| Like=-3.1e+12..-3.5e+07 [-1.278e+13..-2.92e+12] \| it/evals=560/1041 eff=87.3635% N=400 Z=-3e+12(0.00%) \| Like=-2.6e+12..-3.5e+07 [-2.896e+12..-8.337e+11] \| it/evals=600/1075 eff=88.8889% N=400 Z=-2e+12(0.00%) \| Like=-2.2e+12..-3.5e+07 [-2.896e+12..-8.337e+11] \| it/evals=630/1104 eff=89.4886% N=400 Z=-2e+12(0.00%) \| Like=-2.1e+12..-3.5e+07 [-2.896e+12..-8.337e+11] \| it/evals=640/1132 eff=87.4317% N=400 Z=-2e+12(0.00%) \| Like=-1.8e+12..-3.3e+07 [-2.896e+12..-8.337e+11] \| it/evals=680/1156 eff=89.9471% N=400 Z=-1e+12(0.00%) \| Like=-1.5e+12..-3.3e+07 [-2.896e+12..-8.337e+11] \| it/evals=720/1205 eff=89.4410% N=400 Z=-1e+12(0.00%) \| Like=-1.2e+12..-3.3e+07 [-2.896e+12..-8.337e+11] \| it/evals=760/1241 eff=90.3686% N=400 Z=-1e+12(0.00%) \| Like=-1e+12..-3.3e+07 [-2.896e+12..-8.337e+11] \| it/evals=800/1284 eff=90.4977% N=400 Z=-1e+12(0.00%) \| Like=-9.7e+11..-3.3e+07 [-2.896e+12..-8.337e+11] \| it/evals=810/1284 eff=91.6290% N=400 Z=-9e+11(0.00%) \| Like=-8.6e+11..-7.6e+06 [-2.896e+12..-8.337e+11] \| it/evals=840/1323 eff=91.0076% N=400 Z=-7e+11(0.00%) \| Like=-6.7e+11..-7.6e+06 [-8.3e+11..-1.89e+11] \| it/evals=880/1367 eff=91.0031% N=400 Z=-6e+11(0.00%) \| Like=-5.9e+11..-7.6e+06 [-8.3e+11..-1.89e+11] \| it/evals=900/1381 eff=91.7431% N=400 Z=-5e+11(0.00%) \| Like=-5.4e+11..-7.6e+06 [-8.3e+11..-1.89e+11] \| it/evals=920/1413 eff=90.8193% N=400 Z=-4e+11(0.00%) \| Like=-4.2e+11..-3.1e+05 [-8.3e+11..-1.89e+11] \| it/evals=960/1455 eff=90.9953% N=400 Z=-3e+11(0.00%) \| Like=-3.5e+11..-3.1e+05 [-8.3e+11..-1.89e+11] \| it/evals=1000/1487 eff=91.9963% N=400 Z=-3e+11(0.00%) \| Like=-3e+11..-3.6e+02 [-8.3e+11..-1.89e+11] \| it/evals=1040/1536 eff=91.5493% N=400 Z=-2e+11(0.00%) \| Like=-2.5e+11..-3.6e+02 [-8.3e+11..-1.89e+11] \| it/evals=1080/1574 eff=91.9932% N=400 Z=-2e+11(0.00%) \| Like=-2e+11..-3.6e+02 [-8.3e+11..-1.89e+11] \| it/evals=1120/1614 eff=92.2570% N=400 Z=-2e+11(0.00%) \| Like=-1.7e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1160/1652 eff=92.6518% N=400 Z=-2e+11(0.00%) \| Like=-1.6e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1170/1664 eff=92.5633% N=400 Z=-1e+11(0.00%) \| Like=-1.4e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1200/1698 eff=92.4499% N=400 Z=-1e+11(0.00%) \| Like=-1.2e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1240/1740 eff=92.5373% N=400 Z=-1e+11(0.00%) \| Like=-1.1e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1260/1762 eff=92.5110% N=400 Z=-1e+11(0.00%) \| Like=-1e+11..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1280/1776 eff=93.0233% N=400 Z=-8e+10(0.00%) \| Like=-8e+10..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1320/1817 eff=93.1546% N=400 Z=-7e+10(0.00%) \| Like=-6.6e+10..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1350/1851 eff=93.0393% N=400 Z=-6e+10(0.00%) \| Like=-6.3e+10..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1360/1859 eff=93.2145% N=400 Z=-5e+10(0.00%) \| Like=-5.1e+10..-3.6e+02 [-1.878e+11..-4.372e+10] \| it/evals=1400/1907 eff=92.8998% N=400 Z=-4e+10(0.00%) \| Like=-4.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1440/1948 eff=93.0233% N=400 Z=-3e+10(0.00%) \| Like=-3.3e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1480/1988 eff=93.1990% N=400 Z=-3e+10(0.00%) \| Like=-2.7e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1520/2029 eff=93.3088% N=400 Z=-2e+10(0.00%) \| Like=-2.5e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1530/2037 eff=93.4637% N=400 Z=-2e+10(0.00%) \| Like=-2.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1560/2075 eff=93.1343% N=400 Z=-2e+10(0.00%) \| Like=-1.7e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1600/2116 eff=93.2401% N=400 Z=-1e+10(0.00%) \| Like=-1.4e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1640/2153 eff=93.5539% N=400 Z=-1e+10(0.00%) \| Like=-1.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] \| it/evals=1680/2195 eff=93.5933% N=400 Z=-1e+10(0.00%) \| Like=-1e+10..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1710/2235 eff=93.1880% N=400 Z=-1e+10(0.00%) \| Like=-9.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1720/2238 eff=93.5800% N=400 Z=-8e+09(0.00%) \| Like=-8.1e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1760/2279 eff=93.6668% N=400 Z=-7e+09(0.00%) \| Like=-6.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1800/2319 eff=93.7989% N=400 Z=-6e+09(0.00%) \| Like=-5.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1840/2362 eff=93.7819% N=400 Z=-5e+09(0.00%) \| Like=-4.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1880/2403 eff=93.8592% N=400 Z=-5e+09(0.00%) \| Like=-4.6e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1892/2422 eff=93.5707% N=400 Z=-4e+09(0.00%) \| Like=-3.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1919/2451 eff=93.5641% N=400 Z=-4e+09(0.00%) \| Like=-3.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1920/2451 eff=93.6129% N=400 Z=-3e+09(0.00%) \| Like=-3.2e+09..-3.6e+02 [-1.076e+10..-3.166e+09] \| it/evals=1949/2485 eff=93.4772% N=400 Z=-3e+09(0.00%) \| Like=-3.1e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=1960/2490 eff=93.7799% N=400 Z=-3e+09(0.00%) \| Like=-2.8e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=1980/2623 eff=89.0688% N=400 Z=-3e+09(0.00%) \| Like=-2.5e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2000/2623 eff=89.9685% N=400 Z=-2e+09(0.00%) \| Like=-2.2e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2040/2623 eff=91.7679% N=400 Z=-2e+09(0.00%) \| Like=-1.9e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2070/2623 eff=93.1174% N=400 Z=-2e+09(0.00%) \| Like=-1.8e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2080/2624 eff=93.5252% N=400 Z=-2e+09(0.00%) \| Like=-1.6e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2119/2671 eff=93.3069% N=400 Z=-2e+09(0.00%) \| Like=-1.5e+09..-3.6e+02 [-3.164e+09..-8.557e+08] \| it/evals=2120/2671 eff=93.3509% N=400 Z=-1e+09(0.00%) \| Like=-1.3e+09..-3.1e+02 [-3.164e+09..-8.557e+08] \| it/evals=2150/2707 eff=93.1946% N=400 Z=-1e+09(0.00%) \| Like=-1.2e+09..-3.1e+02 [-3.164e+09..-8.557e+08] \| it/evals=2160/2707 eff=93.6281% N=400 Z=-1e+09(0.00%) \| Like=-1.2e+09..-3.1e+02 [-3.164e+09..-8.557e+08] \| it/evals=2162/2835 eff=88.7885% N=400 Z=-1e+09(0.00%) \| Like=-9.8e+08..-3.1e+02 [-3.164e+09..-8.557e+08] \| it/evals=2200/2835 eff=90.3491% N=400 Z=-8e+08(0.00%) \| Like=-8.1e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2240/2835 eff=91.9918% N=400 Z=-7e+08(0.00%) \| Like=-7e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2275/2934 eff=89.7790% N=400 Z=-7e+08(0.00%) \| Like=-6.9e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2280/2934 eff=89.9763% N=400 Z=-6e+08(0.00%) \| Like=-5.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2320/2934 eff=91.5549% N=400 Z=-5e+08(0.00%) \| Like=-5.2e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2340/2934 eff=92.3441% N=400 Z=-5e+08(0.00%) \| Like=-4.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2360/2934 eff=93.1334% N=400 Z=-4e+08(0.00%) \| Like=-3.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2400/3050 eff=90.5660% N=400 Z=-3e+08(0.00%) \| Like=-3.1e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2430/3050 eff=91.6981% N=400 Z=-3e+08(0.00%) \| Like=-3e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2440/3050 eff=92.0755% N=400 Z=-3e+08(0.00%) \| Like=-2.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] \| it/evals=2480/3068 eff=92.9535% N=400 Z=-2e+08(0.00%) \| Like=-2.3e+08..-3.1e+02 [-2.41e+08..-5.562e+07] \| it/evals=2520/3121 eff=92.6130% N=400 Z=-2e+08(0.00%) \| Like=-1.9e+08..-3.1e+02 [-2.41e+08..-5.562e+07] \| it/evals=2560/3154 eff=92.9557% N=400 Z=-2e+08(0.00%) \| Like=-1.5e+08..-3.1e+02 [-2.41e+08..-5.562e+07] \| it/evals=2600/3199 eff=92.8903% N=400 Z=-1e+08(0.00%) \| Like=-1.4e+08..-3.1e+02 [-2.41e+08..-5.562e+07] \| it/evals=2610/3208 eff=92.9487% N=400 Z=-1e+08(0.00%) \| Like=-1.2e+08..-3.1e+02 [-2.41e+08..-5.562e+07] \| it/evals=2640/3327 eff=90.1947% N=400 Z=-96060458.7(0.00%) \| Like=-96033237.17..-310.03 [-2.41e+08..-5.562e+07] \| it/evals=2680/3327 eff=91.5613% N=400 Z=-83875005.8(0.00%) \| Like=-83141993.83..-310.03 [-2.41e+08..-5.562e+07] \| it/evals=2700/3327 eff=92.2446% N=400 Z=-76588171.4(0.00%) \| Like=-76540182.09..-310.03 [-2.41e+08..-5.562e+07] \| it/evals=2720/3327 eff=92.9279% N=400 Z=-59897794.8(0.00%) \| Like=-59677779.22..-310.03 [-2.41e+08..-5.562e+07] \| it/evals=2760/3444 eff=90.6702% N=400 Z=-49760498.3(0.00%) \| Like=-49599851.63..-310.03 [-55543211.0406..-12665864.2124] \| it/evals=2800/3444 eff=91.9842% N=400 Z=-38489542.9(0.00%) \| Like=-38441431.28..-310.03 [-55543211.0406..-12665864.2124] \| it/evals=2840/3535 eff=90.5901% N=400 Z=-32469743.9(0.00%) \| Like=-32313765.59..-135.66 [-55543211.0406..-12665864.2124] \| it/evals=2880/3535 eff=91.8660% N=400 Z=-26172602.5(0.00%) \| Like=-25938804.52..-135.66 [-55543211.0406..-12665864.2124] \| it/evals=2920/3658 eff=89.6255% N=400 Z=-19538332.5(0.00%) \| Like=-19450366.38..-135.66 [-55543211.0406..-12665864.2124] \| it/evals=2960/3658 eff=90.8533% N=400 Z=-18348100.4(0.00%) \| Like=-18344493.62..-135.66 [-55543211.0406..-12665864.2124] \| it/evals=2970/3658 eff=91.1602% N=400 Z=-15340466.4(0.00%) \| Like=-14985637.97..-135.66 [-55543211.0406..-12665864.2124] \| it/evals=3000/3677 eff=91.5471% N=400 Z=-12719911.3(0.00%) \| Like=-12647299.74..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3040/3718 eff=91.6215% N=400 Z=-11831095.0(0.00%) \| Like=-11787664.15..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3060/3736 eff=91.7266% N=400 Z=-11141633.0(0.00%) \| Like=-11121830.90..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3080/3864 eff=88.9145% N=400 Z=-8877250.8(0.00%) \| Like=-8874484.68..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3120/3864 eff=90.0693% N=400 Z=-7615450.3(0.00%) \| Like=-7615312.38..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3150/3864 eff=90.9353% N=400 Z=-7380434.6(0.00%) \| Like=-7356864.48..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3160/3864 eff=91.2240% N=400 Z=-7157825.5(0.00%) \| Like=-7156384.89..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3168/3992 eff=88.1960% N=400 Z=-6113566.7(0.00%) \| Like=-6050922.96..-135.66 [-12647299.7429..-3318556.2028] \| it/evals=3200/3992 eff=89.0869% N=400 Z=-4573067.9(0.00%) \| Like=-4566133.63..-3.90 [-12647299.7429..-3318556.2028] \| it/evals=3240/3992 eff=90.2004% N=400 Z=-3863486.2(0.00%) \| Like=-3829448.55..-3.90 [-12647299.7429..-3318556.2028] \| it/evals=3275/4100 eff=88.5135% N=400 Z=-3808107.7(0.00%) \| Like=-3795971.02..-3.90 [-12647299.7429..-3318556.2028] \| it/evals=3280/4100 eff=88.6486% N=400 Z=-3110640.6(0.00%) \| Like=-3107239.98..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3320/4100 eff=89.7297% N=400 Z=-2675252.3(0.00%) \| Like=-2668849.17..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3360/4100 eff=90.8108% N=400 Z=-2564767.2(0.00%) \| Like=-2551402.90..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3370/4195 eff=88.8011% N=400 Z=-2198473.6(0.00%) \| Like=-2196576.76..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3400/4195 eff=89.5916% N=400 Z=-2012812.8(0.00%) \| Like=-2009485.22..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3420/4195 eff=90.1186% N=400 Z=-1847415.7(0.00%) \| Like=-1829858.31..-3.90 [-3317418.8544..-855043.6863] \| it/evals=3440/4195 eff=90.6456% N=400 Z=-1451906.3(0.00%) \| Like=-1442627.27..-0.09 [-3317418.8544..-855043.6863] \| it/evals=3480/4227 eff=90.9328% N=400 Z=-1216639.3(0.00%) \| Like=-1212596.34..-0.09 [-3317418.8544..-855043.6863] \| it/evals=3510/4262 eff=90.8856% N=400 Z=-1180207.6(0.00%) \| Like=-1175032.69..-0.09 [-3317418.8544..-855043.6863] \| it/evals=3520/4385 eff=88.3312% N=400 Z=-946994.7(0.00%) \| Like=-940999.45..-0.09 [-3317418.8544..-855043.6863] \| it/evals=3560/4385 eff=89.3350% N=400 Z=-778747.5(0.00%) \| Like=-771170.46..-0.09 [-851045.7409..-213305.0473] \| it/evals=3600/4385 eff=90.3388% N=400 Z=-635147.0(0.00%) \| Like=-634663.92..-0.09 [-851045.7409..-213305.0473] \| it/evals=3636/4475 eff=89.2270% N=400 Z=-612791.6(0.00%) \| Like=-608833.23..-0.09 [-851045.7409..-213305.0473] \| it/evals=3640/4475 eff=89.3252% N=400 Z=-508846.5(0.00%) \| Like=-506165.20..-0.09 [-851045.7409..-213305.0473] \| it/evals=3680/4475 eff=90.3067% N=400 Z=-490388.8(0.00%) \| Like=-485575.72..-0.09 [-851045.7409..-213305.0473] \| it/evals=3690/4475 eff=90.5521% N=400 Z=-429946.8(0.00%) \| Like=-428595.78..-0.09 [-851045.7409..-213305.0473] \| it/evals=3720/4500 eff=90.7317% N=400 Z=-346384.6(0.00%) \| Like=-346198.97..-0.09 [-851045.7409..-213305.0473] \| it/evals=3760/4542 eff=90.7774% N=400 Z=-313687.0(0.00%) \| Like=-313029.66..-0.09 [-851045.7409..-213305.0473] \| it/evals=3780/4561 eff=90.8435% N=400 Z=-282186.4(0.00%) \| Like=-281568.56..-0.09 [-851045.7409..-213305.0473] \| it/evals=3800/4689 eff=88.5987% N=400 Z=-227408.1(0.00%) \| Like=-227371.78..-0.09 [-851045.7409..-213305.0473] \| it/evals=3840/4689 eff=89.5314% N=400 Z=-194507.7(0.00%) \| Like=-194017.43..-0.09 [-213262.9865..-46727.2354] \| it/evals=3880/4689 eff=90.4640% N=400 Z=-160420.8(0.00%) \| Like=-159571.94..-0.09 [-213262.9865..-46727.2354] \| it/evals=3920/4790 eff=89.2938% N=400 Z=-125606.0(0.00%) \| Like=-124767.18..-0.09 [-213262.9865..-46727.2354] \| it/evals=3960/4790 eff=90.2050% N=400 Z=-111728.7(0.00%) \| Like=-109892.50..-0.09 [-213262.9865..-46727.2354] \| it/evals=3983/4914 eff=88.2366% N=400 Z=-99628.7(0.00%) \| Like=-98796.75..-0.09 [-213262.9865..-46727.2354] \| it/evals=4000/4914 eff=88.6132% N=400 Z=-79563.3(0.00%) \| Like=-79495.58..-0.09 [-213262.9865..-46727.2354] \| it/evals=4040/4914 eff=89.4993% N=400 Z=-77992.0(0.00%) \| Like=-77957.02..-0.09 [-213262.9865..-46727.2354] \| it/evals=4050/4914 eff=89.7209% N=400 Z=-67526.6(0.00%) \| Like=-67417.47..-0.09 [-213262.9865..-46727.2354] \| it/evals=4080/4925 eff=90.1657% N=400 Z=-55235.3(0.00%) \| Like=-55056.05..-0.09 [-213262.9865..-46727.2354] \| it/evals=4120/4955 eff=90.4501% N=400 Z=-48939.9(0.00%) \| Like=-48543.38..-0.09 [-213262.9865..-46727.2354] \| it/evals=4140/4979 eff=90.4128% N=400 Z=-43455.7(0.00%) \| Like=-43364.58..-0.09 [-46275.4307..-11188.2679] \| it/evals=4160/5102 eff=88.4730% N=400 Z=-36008.2(0.00%) \| Like=-35757.46..-0.09 [-46275.4307..-11188.2679] \| it/evals=4200/5102 eff=89.3237% N=400 Z=-30396.8(0.00%) \| Like=-30282.97..-0.09 [-46275.4307..-11188.2679] \| it/evals=4230/5102 eff=89.9617% N=400 Z=-29056.5(0.00%) \| Like=-28855.17..-0.09 [-46275.4307..-11188.2679] \| it/evals=4240/5102 eff=90.1744% N=400 Z=-24102.7(0.00%) \| Like=-23927.05..-0.09 [-46275.4307..-11188.2679] \| it/evals=4280/5138 eff=90.3335% N=400 Z=-19450.2(0.00%) \| Like=-19344.73..-0.09 [-46275.4307..-11188.2679] \| it/evals=4320/5174 eff=90.4902% N=400 Z=-16094.6(0.00%) \| Like=-15916.99..-0.07 [-46275.4307..-11188.2679] \| it/evals=4360/5219 eff=90.4752% N=400 Z=-12625.4(0.00%) \| Like=-12576.55..-0.00 [-46275.4307..-11188.2679] \| it/evals=4400/5261 eff=90.5164% N=400 Z=-10993.4(0.00%) \| Like=-10899.62..-0.00 [-11181.5477..-3229.8137] \| it/evals=4440/5301 eff=90.5938% N=400 Z=-8992.4(0.00%) \| Like=-8974.20..-0.00 [-11181.5477..-3229.8137] \| it/evals=4480/5337 eff=90.7434% N=400 Z=-8243.3(0.00%) \| Like=-8189.63..-0.00 [-11181.5477..-3229.8137] \| it/evals=4500/5485 eff=88.4956% N=400 Z=-7716.0(0.00%) \| Like=-7682.92..-0.00 [-11181.5477..-3229.8137] \| it/evals=4520/5485 eff=88.8889% N=400 Z=-6371.8(0.00%) \| Like=-6328.55..-0.00 [-11181.5477..-3229.8137] \| it/evals=4560/5485 eff=89.6755% N=400 Z=-5676.5(0.00%) \| Like=-5634.43..-0.00 [-11181.5477..-3229.8137] \| it/evals=4590/5485 eff=90.2655% N=400 Z=-5463.7(0.00%) \| Like=-5444.29..-0.00 [-11181.5477..-3229.8137] \| it/evals=4600/5485 eff=90.4621% N=400 Z=-4563.9(0.00%) \| Like=-4536.39..-0.00 [-11181.5477..-3229.8137] \| it/evals=4640/5524 eff=90.5543% N=400 Z=-3732.2(0.00%) \| Like=-3678.91..-0.00 [-11181.5477..-3229.8137] \| it/evals=4680/5568 eff=90.5573% N=400 Z=-2979.6(0.00%) \| Like=-2953.36..-0.00 [-3184.0781..-809.5316] \| it/evals=4720/5685 eff=89.3094% N=400 Z=-2401.3(0.00%) \| Like=-2380.68..-0.00 [-3184.0781..-809.5316] \| it/evals=4760/5685 eff=90.0662% N=400 Z=-2354.8(0.00%) \| Like=-2328.48..-0.00 [-3184.0781..-809.5316] \| it/evals=4770/5685 eff=90.2554% N=400 Z=-2084.0(0.00%) \| Like=-2062.99..-0.00 [-3184.0781..-809.5316] \| it/evals=4800/5813 eff=88.6754% N=400 Z=-1671.7(0.00%) \| Like=-1641.27..-0.00 [-3184.0781..-809.5316] \| it/evals=4840/5813 eff=89.4144% N=400 Z=-1525.2(0.00%) \| Like=-1482.31..-0.00 [-3184.0781..-809.5316] \| it/evals=4860/5813 eff=89.7839% N=400 Z=-1305.5(0.00%) \| Like=-1279.17..-0.00 [-3184.0781..-809.5316] \| it/evals=4880/5813 eff=90.1533% N=400 Z=-1056.9(0.00%) \| Like=-1031.76..-0.00 [-3184.0781..-809.5316] \| it/evals=4920/5843 eff=90.3913% N=400 Z=-900.7(0.00%) \| Like=-869.80..-0.00 [-3184.0781..-809.5316] \| it/evals=4950/5872 eff=90.4605% N=400 Z=-863.9(0.00%) \| Like=-843.51..-0.00 [-3184.0781..-809.5316] \| it/evals=4960/5995 eff=88.6506% N=400 Z=-739.9(0.00%) \| Like=-720.07..-0.00 [-808.6368..-200.7839] \| it/evals=5000/5995 eff=89.3655% N=400 Z=-590.5(0.00%) \| Like=-571.07..-0.00 [-808.6368..-200.7839] \| it/evals=5040/5995 eff=90.0804% N=400 Z=-461.2(0.00%) \| Like=-440.89..-0.00 [-808.6368..-200.7839] \| it/evals=5080/6087 eff=89.3265% N=400 Z=-379.9(0.00%) \| Like=-357.65..-0.00 [-808.6368..-200.7839] \| it/evals=5120/6087 eff=90.0299% N=400 Z=-362.9(0.00%) \| Like=-337.70..-0.00 [-808.6368..-200.7839] \| it/evals=5130/6087 eff=90.2057% N=400 Z=-313.5(0.00%) \| Like=-293.65..-0.00 [-808.6368..-200.7839] \| it/evals=5160/6215 eff=88.7360% N=400 Z=-262.5(0.00%) \| Like=-244.16..-0.00 [-808.6368..-200.7839] \| it/evals=5200/6215 eff=89.4239% N=400 Z=-235.8(0.00%) \| Like=-218.07..-0.00 [-808.6368..-200.7839] \| it/evals=5220/6215 eff=89.7678% N=400 Z=-218.7(0.00%) \| Like=-199.82..-0.00 [-200.5435..-50.2258] \| it/evals=5240/6215 eff=90.1118% N=400 Z=-186.1(0.00%) \| Like=-166.86..-0.00 [-200.5435..-50.2258] \| it/evals=5280/6254 eff=90.1947% N=400 Z=-163.8(0.00%) \| Like=-144.80..-0.00 [-200.5435..-50.2258] \| it/evals=5310/6410 eff=88.3527% N=400 Z=-157.3(0.00%) \| Like=-137.86..-0.00 [-200.5435..-50.2258] \| it/evals=5320/6410 eff=88.5191% N=400 Z=-130.3(0.00%) \| Like=-110.84..-0.00 [-200.5435..-50.2258] \| it/evals=5360/6410 eff=89.1847% N=400 Z=-108.3(0.00%) \| Like=-88.95..-0.00 [-200.5435..-50.2258] \| it/evals=5400/6410 eff=89.8502% N=400 Z=-91.7(0.00%) \| Like=-73.04..-0.00 [-200.5435..-50.2258] \| it/evals=5440/6528 eff=88.7728% N=400 Z=-78.2(0.00%) \| Like=-58.61..-0.00 [-200.5435..-50.2258] \| it/evals=5480/6528 eff=89.4256% N=400 Z=-74.9(0.00%) \| Like=-56.74..-0.00 [-200.5435..-50.2258] \| it/evals=5490/6528 eff=89.5888% N=400 Z=-67.8(0.00%) \| Like=-48.78..-0.00 [-50.0590..-13.4702] \| it/evals=5520/6528 eff=90.0783% N=400 Z=-59.7(0.00%) \| Like=-41.06..-0.00 [-50.0590..-13.4702] \| it/evals=5560/6640 eff=89.1026% N=400 Z=-56.2(0.00%) \| Like=-38.29..-0.00 [-50.0590..-13.4702] \| it/evals=5580/6640 eff=89.4231% N=400 Z=-53.2(0.00%) \| Like=-34.68..-0.00 [-50.0590..-13.4702] \| it/evals=5600/6640 eff=89.7436% N=400 Z=-47.0(0.00%) \| Like=-28.44..-0.00 [-50.0590..-13.4702] \| it/evals=5640/6755 eff=88.7490% N=400 Z=-41.5(0.00%) \| Like=-23.57..-0.00 [-50.0590..-13.4702] \| it/evals=5680/6755 eff=89.3784% N=400 Z=-37.9(0.00%) \| Like=-20.01..-0.00 [-50.0590..-13.4702] \| it/evals=5720/6852 eff=88.6547% N=400 Z=-34.1(0.00%) \| Like=-15.85..-0.00 [-50.0590..-13.4702] \| it/evals=5760/6852 eff=89.2746% N=400 Z=-30.9(0.00%) \| Like=-13.28..-0.00 [-13.4688..-3.1923] \| it/evals=5800/6977 eff=88.1861% N=400 Z=-28.8(0.00%) \| Like=-11.09..-0.00 [-13.4688..-3.1923] \| it/evals=5840/6977 eff=88.7943% N=400 Z=-26.9(0.00%) \| Like=-9.15..-0.00 [-13.4688..-3.1923] \| it/evals=5880/6977 eff=89.4025% N=400 Z=-24.9(0.01%) \| Like=-7.23..-0.00 [-13.4688..-3.1923] \| it/evals=5920/7073 eff=88.7157% N=400 Z=-24.2(0.03%) \| Like=-6.80..-0.00 [-13.4688..-3.1923] \| it/evals=5940/7073 eff=89.0154% N=400 Z=-23.5(0.05%) \| Like=-6.03..-0.00 [-13.4688..-3.1923] \| it/evals=5960/7073 eff=89.3152% N=400 Z=-22.4(0.15%) \| Like=-4.86..-0.00 [-13.4688..-3.1923] \| it/evals=6000/7184 eff=88.4434% N=400 Z=-21.5(0.36%) \| Like=-4.13..-0.00 [-13.4688..-3.1923] \| it/evals=6030/7184 eff=88.8856% N=400 Z=-21.3(0.46%) \| Like=-3.90..-0.00 [-13.4688..-3.1923] \| it/evals=6040/7184 eff=89.0330% N=400 Z=-20.4(1.09%) \| Like=-3.17..-0.00 [-3.1816..-2.1117] \| it/evals=6080/7299 eff=88.1287% N=400 Z=-19.7(2.17%) \| Like=-2.60..-0.00 [-3.1816..-2.1117] \| it/evals=6120/7299 eff=88.7085% N=400 Z=-19.2(3.76%) \| Like=-2.15..-0.00 [-3.1816..-2.1117] \| it/evals=6160/7299 eff=89.2883% N=400 Z=-18.7(6.01%) \| Like=-1.75..-0.00 [-1.7610..-1.7500] \| it/evals=6200/7380 eff=88.8252% N=400 Z=-18.6(6.67%) \| Like=-1.68..-0.00 [-1.6793..-1.6740]\| it/evals=6210/7380 eff=88.9685% N=400 Z=-18.3(8.94%) \| Like=-1.44..-0.00 [-1.4423..-1.4353]\| it/evals=6240/7380 eff=89.3983% N=400 Z=-18.0(12.51%) \| Like=-1.10..-0.00 [-1.0978..-1.0911]\| it/evals=6280/7422 eff=89.4332% N=400 Z=-17.8(14.60%) \| Like=-0.98..-0.00 [-0.9788..-0.9589] \| it/evals=6300/7556 eff=88.0380% N=400 Z=-17.7(16.90%) \| Like=-0.88..-0.00 [-0.8820..-0.8818]\| it/evals=6320/7556 eff=88.3175% N=400 Z=-17.4(21.49%) \| Like=-0.73..-0.00 [-0.7336..-0.7293]\| it/evals=6360/7556 eff=88.8765% N=400 Z=-17.3(25.14%) \| Like=-0.62..-0.00 [-0.6150..-0.6139]\| it/evals=6390/7556 eff=89.2957% N=400 Z=-17.2(26.34%) \| Like=-0.60..-0.00 [-0.6036..-0.5966]\| it/evals=6400/7556 eff=89.4354% N=400 Z=-17.1(31.18%) \| Like=-0.52..-0.00 [-0.5169..-0.5159]\| it/evals=6440/7684 eff=88.4130% N=400 Z=-16.9(35.88%) \| Like=-0.41..-0.00 [-0.4129..-0.4080]\| it/evals=6480/7684 eff=88.9621% N=400 Z=-16.8(40.68%) \| Like=-0.35..-0.00 [-0.3522..-0.3507]\| it/evals=6520/7789 eff=88.2393% N=400 Z=-16.7(45.25%) \| Like=-0.28..-0.00 [-0.2764..-0.2754]\| it/evals=6560/7789 eff=88.7806% N=400 Z=-16.7(46.40%) \| Like=-0.27..-0.00 [-0.2675..-0.2657]\| it/evals=6570/7789 eff=88.9160% N=400 Z=-16.6(49.71%) \| Like=-0.23..-0.00 [-0.2340..-0.2338]\| it/evals=6600/7789 eff=89.3220% N=400 Z=-16.5(53.87%) \| Like=-0.20..-0.00 [-0.1973..-0.1961]\| it/evals=6640/7899 eff=88.5451% N=400 Z=-16.5(55.88%) \| Like=-0.18..-0.00 [-0.1796..-0.1778]\| it/evals=6660/7899 eff=88.8118% N=400 Z=-16.4(57.81%) \| Like=-0.16..-0.00 [-0.1601..-0.1601]\| it/evals=6680/7899 eff=89.0785% N=400 Z=-16.4(61.48%) \| Like=-0.13..-0.00 [-0.1326..-0.1321]\| it/evals=6720/7918 eff=89.3855% N=400 Z=-16.3(64.05%) \| Like=-0.12..-0.00 [-0.1170..-0.1168]\| it/evals=6750/7951 eff=89.3921% N=400 Z=-16.3(64.86%) \| Like=-0.11..-0.00 [-0.1117..-0.1115]\| it/evals=6760/7963 eff=89.3825% N=400 Z=-16.3(67.99%) \| Like=-0.09..-0.00 [-0.0907..-0.0904]\| it/evals=6800/7999 eff=89.4855% N=400 Z=-16.2(70.89%) \| Like=-0.08..-0.00 [-0.0757..-0.0752]\| it/evals=6840/8045 eff=89.4702% N=400 Z=-16.2(73.55%) \| Like=-0.06..-0.00 [-0.0598..-0.0597]\| it/evals=6880/8085 eff=89.5250% N=400 Z=-16.2(75.99%) \| Like=-0.05..-0.00 [-0.0483..-0.0483]\| it/evals=6920/8131 eff=89.5098% N=400 Z=-16.2(76.56%) \| Like=-0.05..-0.00 [-0.0454..-0.0452]\| it/evals=6930/8138 eff=89.5580% N=400 Z=-16.1(78.21%) \| Like=-0.04..-0.00 [-0.0389..-0.0389]\| it/evals=6960/8266 eff=88.4821% N=400 Z=-16.1(80.24%) \| Like=-0.03..-0.00 [-0.0330..-0.0330]\| it/evals=7000/8266 eff=88.9906% N=400 Z=-16.1(81.18%) \| Like=-0.03..-0.00 [-0.0297..-0.0297]\| it/evals=7020/8266 eff=89.2449% N=400 Z=-16.1(82.08%) \| Like=-0.03..-0.00 [-0.0270..-0.0269]\| it/evals=7040/8266 eff=89.4991% N=400 Z=-16.1(83.76%) \| Like=-0.02..-0.00 [-0.0229..-0.0229]\| it/evals=7080/8313 eff=89.4730% N=400 Z=-16.1(84.92%) \| Like=-0.02..-0.00 [-0.0205..-0.0204]\| it/evals=7110/8337 eff=89.5804% N=400 Z=-16.0(85.28%) \| Like=-0.02..-0.00 [-0.0197..-0.0196]\| it/evals=7120/8465 eff=88.2827% N=400 Z=-16.0(86.67%) \| Like=-0.02..-0.00 [-0.0157..-0.0157]\| it/evals=7160/8465 eff=88.7787% N=400 Z=-16.0(87.93%) \| Like=-0.01..-0.00 [-0.0133..-0.0132]\| it/evals=7200/8465 eff=89.2746% N=400 Z=-16.0(89.07%) \| Like=-0.01..-0.00 [-0.0110..-0.0110]\| it/evals=7240/8580 eff=88.5086% N=400 Z=-16.0(90.10%) \| Like=-0.01..-0.00 [-0.0093..-0.0093]\| it/evals=7280/8580 eff=88.9976% N=400 Z=-16.0(90.34%) \| Like=-0.01..-0.00 [-0.0088..-0.0088]\| it/evals=7290/8580 eff=89.1198% N=400 Z=-16.0(91.04%) \| Like=-0.01..-0.00 [-0.0077..-0.0077]\| it/evals=7320/8580 eff=89.4866% N=400 Z=-16.0(91.89%) \| Like=-0.01..-0.00 [-0.0060..-0.0060]\| it/evals=7360/8703 eff=88.6427% N=400 Z=-16.0(92.66%) \| Like=-0.00..-0.00 [-0.0048..-0.0047]\| it/evals=7400/8703 eff=89.1244% N=400 Z=-16.0(93.35%) \| Like=-0.00..-0.00 [-0.0037..-0.0037]\| it/evals=7440/8703 eff=89.6062% N=400 Z=-16.0(93.83%) \| Like=-0.00..-0.00 [-0.0031..-0.0031]\| it/evals=7470/8786 eff=89.0770% N=400 Z=-16.0(93.98%) \| Like=-0.00..-0.00 [-0.0030..-0.0030]\| it/evals=7480/8786 eff=89.1963% N=400 Z=-15.9(94.56%) \| Like=-0.00..-0.00 [-0.0024..-0.0024]\| it/evals=7520/8802 eff=89.5025% N=400 Z=-15.9(95.07%) \| Like=-0.00..-0.00 [-0.0020..-0.0020]\| it/evals=7560/8853 eff=89.4357% N=400 Z=-15.9(95.54%) \| Like=-0.00..-0.00 [-0.0016..-0.0016]\| it/evals=7600/8981 eff=88.5678% N=400 Z=-15.9(95.97%) \| Like=-0.00..-0.00 [-0.0014..-0.0014]\| it/evals=7640/8981 eff=89.0339% N=400 Z=-15.9(96.06%) \| Like=-0.00..-0.00 [-0.0013..-0.0013]\| it/evals=7650/8981 eff=89.1504% N=400 Z=-15.9(96.35%) \| Like=-0.00..-0.00 [-0.0012..-0.0012]\| it/evals=7680/8981 eff=89.5001% N=400 [ultranest] Explored until L=-2e-07 [ultranest] Likelihood function evaluations: 9102 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -15.87 +- 0.1519 [ultranest] Effective samples strategy satisfied (ESS = 1239.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.5) [ultranest] logZ error budget: single: 0.20 bs:0.15 tail:0.03 total:0.16 required:<0.50 [ultranest] done iterating. logZ = -15.890 +- 0.249 single instance: logZ = -15.890 +- 0.196 bootstrapped : logZ = -15.868 +- 0.246 tail : logZ = +- 0.033 insert order U test : converged: True correlation: inf iterations a : -0.00381│ ▁▁▁▁▁▁▁▁▂▁▃▅▅▆▆▇▇▇▇▇▇▆▅▃▂▃▂▁▁▁▁▁▁▁▁▁▁ │0.00422 -0.00002 +- 0.00099 expected posterior: 0 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [-2.2975248259440545e-05] [0.0009885788563336665] [[1.14374817e-04] [4.02024891e-04] [9.97322850e-01] ... [5.00000000e-01] [5.00000000e-01] [5.00000000e-01]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 8.32523583e-05 8.32523694e-05 8.32523752e-05] ====== Running Gauss problem [2] ===== center: 0 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-2.6e+13..-14 [-2.637e+13..-16.51] \| it/evals=0/528 eff=0.0000% N=400 Z=-1027058.7(0.00%) \| Like=-367803.47..-13.70 [-2.637e+13..-16.51] \| it/evals=40/528 eff=31.2500% N=400 Z=-60.4(0.00%) \| Like=-50.38..-13.70 [-2.637e+13..-16.51] \| it/evals=80/528 eff=62.5000% N=400 Z=-29.3(0.00%) \| Like=-21.93..-13.70 [-2.637e+13..-16.51] \| it/evals=90/528 eff=70.3125% N=400 Z=-22.5(0.18%) \| Like=-19.03..-13.70 [-2.637e+13..-16.51] \| it/evals=120/631 eff=51.9481% N=400 Z=-20.7(1.07%) \| Like=-17.74..-13.70 [-2.637e+13..-16.51] \| it/evals=160/631 eff=69.2641% N=400 Z=-20.1(1.99%) \| Like=-17.26..-13.70 [-2.637e+13..-16.51] \| it/evals=180/631 eff=77.9221% N=400 Z=-19.6(3.12%) \| Like=-17.08..-13.70 [-2.637e+13..-16.51] \| it/evals=200/719 eff=62.6959% N=400 Z=-18.9(6.18%) \| Like=-16.60..-13.70 [-2.637e+13..-16.51] \| it/evals=240/719 eff=75.2351% N=400 Z=-18.5(9.73%) \| Like=-16.43..-13.70 [-16.4311..-16.4298]\| it/evals=280/796 eff=70.7071% N=400 Z=-18.1(13.67%) \| Like=-16.28..-13.70 [-16.2781..-16.2756]\| it/evals=320/867 eff=68.5225% N=400 Z=-17.9(17.63%) \| Like=-16.18..-13.70 [-16.1754..-16.1748]\| it/evals=360/867 eff=77.0878% N=400 Z=-17.7(21.60%) \| Like=-16.05..-13.70 [-16.0474..-16.0417]\| it/evals=400/936 eff=74.6269% N=400 Z=-17.5(25.56%) \| Like=-15.95..-13.70 [-15.9463..-15.9461]\| it/evals=440/992 eff=74.3243% N=400 Z=-17.5(26.64%) \| Like=-15.93..-13.70 [-15.9250..-15.9249]\| it/evals=450/992 eff=76.0135% N=400 Z=-17.4(29.58%) \| Like=-15.86..-13.70 [-15.8649..-15.8597]\| it/evals=480/1054 eff=73.3945% N=400 Z=-17.2(33.49%) \| Like=-15.76..-13.62 [-15.7628..-15.7623]\| it/evals=520/1144 eff=69.8925% N=400 Z=-17.2(35.58%) \| Like=-15.73..-13.62 [-15.7282..-15.7241]\| it/evals=540/1144 eff=72.5806% N=400 Z=-17.1(37.48%) \| Like=-15.69..-13.62 [-15.6919..-15.6890]\| it/evals=560/1180 eff=71.7949% N=400 Z=-17.0(41.12%) \| Like=-15.63..-13.49 [-15.6301..-15.6282]\| it/evals=600/1222 eff=72.9927% N=400 Z=-17.0(43.89%) \| Like=-15.58..-13.49 [-15.5796..-15.5769]\| it/evals=630/1266 eff=72.7483% N=400 Z=-16.9(44.89%) \| Like=-15.56..-13.49 [-15.5584..-15.5526]\| it/evals=640/1266 eff=73.9030% N=400 Z=-16.9(48.56%) \| Like=-15.48..-13.49 [-15.4782..-15.4778]\| it/evals=680/1325 eff=73.5135% N=400 Z=-16.8(52.03%) \| Like=-15.43..-13.49 [-15.4259..-15.4258]\| it/evals=720/1399 eff=72.0721% N=400 Z=-16.7(55.28%) \| Like=-15.38..-13.49 [-15.3840..-15.3834]\| it/evals=760/1418 eff=74.6562% N=400 Z=-16.7(58.33%) \| Like=-15.34..-13.49 [-15.3392..-15.3376]\| it/evals=800/1489 eff=73.4619% N=400 Z=-16.7(58.94%) \| Like=-15.33..-13.49 [-15.3305..-15.3287]\| it/evals=810/1489 eff=74.3802% N=400 Z=-16.6(61.15%) \| Like=-15.30..-13.49 [-15.2987..-15.2985]\| it/evals=840/1522 eff=74.8663% N=400 Z=-16.6(63.99%) \| Like=-15.26..-13.49 [-15.2561..-15.2551]\| it/evals=880/1580 eff=74.5763% N=400 Z=-16.6(65.11%) \| Like=-15.24..-13.21 [-15.2369..-15.2337]\| it/evals=900/1617 eff=73.9523% N=400 Z=-16.5(66.43%) \| Like=-15.22..-13.21 [-15.2153..-15.2151]\| it/evals=920/1636 eff=74.4337% N=400 Z=-16.5(69.03%) \| Like=-15.18..-13.21 [-15.1819..-15.1808]\| it/evals=960/1692 eff=74.3034% N=400 Z=-16.5(70.66%) \| Like=-15.16..-13.21 [-15.1630..-15.1630]\| it/evals=990/1740 eff=73.8806% N=400 Z=-16.5(71.06%) \| Like=-15.16..-13.21 [-15.1554..-15.1554]\| it/evals=1000/1750 eff=74.0741% N=400 Z=-16.5(73.36%) \| Like=-15.13..-13.21 [-15.1262..-15.1248]\| it/evals=1040/1797 eff=74.4452% N=400 Z=-16.4(75.42%) \| Like=-15.10..-13.21 [-15.1019..-15.1009]\| it/evals=1080/1852 eff=74.3802% N=400 Z=-16.4(77.32%) \| Like=-15.08..-13.21 [-15.0804..-15.0802]\| it/evals=1120/1910 eff=74.1722% N=400 Z=-16.4(79.16%) \| Like=-15.06..-13.21 [-15.0589..-15.0587]\| it/evals=1160/1959 eff=74.4067% N=400 Z=-16.4(79.61%) \| Like=-15.05..-13.21 [-15.0540..-15.0538]\| it/evals=1170/1981 eff=74.0038% N=400 Z=-16.4(80.72%) \| Like=-15.04..-13.05 [-15.0409..-15.0408]\| it/evals=1200/2011 eff=74.4879% N=400 Z=-16.3(82.07%) \| Like=-15.02..-13.05 [-15.0242..-15.0231]\| it/evals=1240/2058 eff=74.7889% N=400 Z=-16.3(82.29%) \| Like=-15.01..-12.00 [-15.0125..-15.0123]\| it/evals=1260/2084 eff=74.8219% N=400 Z=-16.3(82.29%) \| Like=-15.00..-12.00 [-15.0040..-15.0038]\| it/evals=1280/2099 eff=75.3384% N=400 Z=-16.3(83.14%) \| Like=-14.99..-11.86 [-14.9866..-14.9853]\| it/evals=1320/2153 eff=75.2995% N=400 Z=-16.3(84.11%) \| Like=-14.97..-11.86 [-14.9730..-14.9727]\| it/evals=1350/2188 eff=75.5034% N=400 Z=-16.3(84.28%) \| Like=-14.97..-11.86 [-14.9662..-14.9659]\| it/evals=1360/2197 eff=75.6817% N=400 Z=-16.3(84.96%) \| Like=-14.95..-11.85 [-14.9525..-14.9522]\| it/evals=1400/2252 eff=75.5940% N=400 Z=-16.3(86.04%) \| Like=-14.94..-11.85 [-14.9381..-14.9380]\| it/evals=1440/2300 eff=75.7895% N=400 Z=-16.3(86.97%) \| Like=-14.93..-11.85 [-14.9272..-14.9268]\| it/evals=1480/2347 eff=76.0144% N=400 Z=-16.3(88.01%) \| Like=-14.91..-11.85 [-14.9131..-14.9129]\| it/evals=1520/2393 eff=76.2669% N=400 Z=-16.2(88.82%) \| Like=-14.90..-11.85 [-14.9011..-14.9005]\| it/evals=1560/2447 eff=76.2091% N=400 Z=-16.2(89.49%) \| Like=-14.89..-11.85 [-14.8877..-14.8876]\| it/evals=1600/2519 eff=75.5073% N=400 Z=-16.2(89.78%) \| Like=-14.88..-11.85 [-14.8836..-14.8832]\| it/evals=1620/2585 eff=74.1419% N=400 Z=-16.2(90.17%) \| Like=-14.88..-11.85 [-14.8797..-14.8789]\| it/evals=1640/2585 eff=75.0572% N=400 Z=-16.2(90.86%) \| Like=-14.87..-11.85 [-14.8688..-14.8685]\| it/evals=1680/2679 eff=73.7165% N=400 Z=-16.2(91.24%) \| Like=-14.86..-11.85 [-14.8606..-14.8605]\| it/evals=1710/2679 eff=75.0329% N=400 Z=-16.2(91.39%) \| Like=-14.86..-11.85 [-14.8570..-14.8565]\| it/evals=1720/2679 eff=75.4717% N=400 Z=-16.2(91.88%) \| Like=-14.84..-11.85 [-14.8446..-14.8434]\| it/evals=1760/2793 eff=73.5478% N=400 Z=-16.2(91.63%) \| Like=-14.83..-11.54 [-14.8334..-14.8332]\| it/evals=1800/2862 eff=73.1113% N=400 Z=-16.2(92.02%) \| Like=-14.82..-11.54 [-14.8180..-14.8179]\| it/evals=1840/2862 eff=74.7360% N=400 Z=-16.2(92.39%) \| Like=-14.78..-11.54 [-14.7823..-14.7809]\| it/evals=1880/2936 eff=74.1325% N=400 Z=-16.2(92.53%) \| Like=-14.77..-11.54 [-14.7750..-14.7732]\| it/evals=1890/2936 eff=74.5268% N=400 Z=-16.2(92.77%) \| Like=-14.75..-11.54 [-14.7478..-14.7478]\| it/evals=1920/3010 eff=73.5632% N=400 Z=-16.2(92.99%) \| Like=-14.72..-11.54 [-14.7162..-14.7158]\| it/evals=1960/3075 eff=73.2710% N=400 Z=-16.2(93.09%) \| Like=-14.69..-11.54 [-14.6910..-14.6876]\| it/evals=1980/3075 eff=74.0187% N=400 Z=-16.2(93.34%) \| Like=-14.67..-11.54 [-14.6694..-14.6690]\| it/evals=2000/3075 eff=74.7664% N=400 Z=-16.2(93.47%) \| Like=-14.64..-11.54 [-14.6373..-14.6357]\| it/evals=2040/3142 eff=74.3982% N=400 Z=-16.2(93.64%) \| Like=-14.61..-11.54 [-14.6082..-14.6081]\| it/evals=2070/3201 eff=73.9022% N=400 Z=-16.2(93.66%) \| Like=-14.59..-11.54 [-14.5872..-14.5872]\| it/evals=2080/3201 eff=74.2592% N=400 Z=-16.2(93.89%) \| Like=-14.50..-11.54 [-14.5049..-14.5020]\| it/evals=2120/3301 eff=73.0782% N=400 Z=-16.2(94.09%) \| Like=-14.43..-11.54 [-14.4330..-14.4327]\| it/evals=2160/3301 eff=74.4571% N=400 Z=-16.2(94.22%) \| Like=-14.37..-11.54 [-14.3805..-14.3662] \| it/evals=2200/3363 eff=74.2491% N=400 Z=-16.2(94.52%) \| Like=-14.28..-11.54 [-14.2802..-14.2797]\| it/evals=2240/3430 eff=73.9274% N=400 Z=-16.2(94.55%) \| Like=-14.27..-11.54 [-14.2663..-14.2647]\| it/evals=2250/3430 eff=74.2574% N=400 Z=-16.2(94.64%) \| Like=-14.20..-11.50 [-14.1976..-14.1882]\| it/evals=2280/3504 eff=73.4536% N=400 Z=-16.2(94.92%) \| Like=-14.12..-11.50 [-14.1185..-14.1133]\| it/evals=2320/3572 eff=73.1400% N=400 Z=-16.2(94.89%) \| Like=-14.09..-11.30 [-14.0926..-14.0919]\| it/evals=2340/3572 eff=73.7705% N=400 Z=-16.2(94.89%) \| Like=-14.06..-11.30 [-14.0608..-14.0605]\| it/evals=2360/3572 eff=74.4010% N=400 Z=-16.2(95.09%) \| Like=-14.00..-11.20 [-14.0034..-14.0033]\| it/evals=2400/3679 eff=73.1930% N=400 Z=-16.2(95.15%) \| Like=-13.97..-11.20 [-13.9725..-13.9714]\| it/evals=2430/3679 eff=74.1080% N=400 Z=-16.2(95.16%) \| Like=-13.96..-11.20 [-13.9593..-13.9586]\| it/evals=2440/3766 eff=72.4896% N=400 Z=-16.2(95.35%) \| Like=-13.91..-11.20 [-13.9065..-13.9053]\| it/evals=2480/3766 eff=73.6780% N=400 Z=-16.2(95.50%) \| Like=-13.85..-11.20 [-13.8539..-13.8502]\| it/evals=2520/3857 eff=72.8956% N=400 Z=-16.2(95.68%) \| Like=-13.80..-11.20 [-13.8021..-13.7979]\| it/evals=2560/3857 eff=74.0526% N=400 Z=-16.2(95.83%) \| Like=-13.75..-11.20 [-13.7492..-13.7448]\| it/evals=2600/3935 eff=73.5502% N=400 Z=-16.2(95.89%) \| Like=-13.73..-11.20 [-13.7291..-13.7285]\| it/evals=2610/3935 eff=73.8331% N=400 Z=-16.2(96.01%) \| Like=-13.70..-11.20 [-13.6977..-13.6974]\| it/evals=2640/4033 eff=72.6672% N=400 Z=-16.2(96.19%) \| Like=-13.66..-11.20 [-13.6557..-13.6556]\| it/evals=2680/4033 eff=73.7682% N=400 Z=-16.2(96.25%) \| Like=-13.63..-11.20 [-13.6340..-13.6333]\| it/evals=2700/4123 eff=72.5222% N=400 Z=-16.2(96.30%) \| Like=-13.61..-11.20 [-13.6100..-13.6069]\| it/evals=2720/4123 eff=73.0594% N=400 Z=-16.2(96.42%) \| Like=-13.54..-11.20 [-13.5417..-13.5403]\| it/evals=2760/4227 eff=72.1192% N=400 Z=-16.2(96.53%) \| Like=-13.45..-11.20 [-13.4463..-13.4462]\| it/evals=2790/4227 eff=72.9031% N=400 Z=-16.2(96.55%) \| Like=-13.42..-11.20 [-13.4240..-13.4220]\| it/evals=2800/4227 eff=73.1644% N=400 Z=-16.2(96.67%) \| Like=-13.29..-11.20 [-13.2876..-13.2869]\| it/evals=2840/4264 eff=73.4990% N=400 Z=-16.1(96.76%) \| Like=-13.17..-11.16 [-13.1669..-13.1666]\| it/evals=2880/4319 eff=73.4881% N=400 Z=-16.1(96.91%) \| Like=-13.05..-10.83 [-13.0540..-13.0520]\| it/evals=2920/4395 eff=73.0914% N=400 Z=-16.1(97.01%) \| Like=-12.98..-10.78 [-12.9820..-12.9807]\| it/evals=2960/4448 eff=73.1225% N=400 Z=-16.1(97.04%) \| Like=-12.96..-10.78 [-12.9597..-12.9573]\| it/evals=2970/4461 eff=73.1347% N=400 Z=-16.1(97.16%) \| Like=-12.90..-10.78 [-12.9001..-12.8960]\| it/evals=3000/4573 eff=71.8907% N=400 Z=-16.1(97.28%) \| Like=-12.81..-10.71 [-12.8120..-12.8075]\| it/evals=3040/4573 eff=72.8493% N=400 Z=-16.1(97.33%) \| Like=-12.76..-10.71 [-12.7593..-12.7593]\| it/evals=3060/4677 eff=71.5455% N=400 Z=-16.1(97.40%) \| Like=-12.71..-10.71 [-12.7227..-12.7119] \| it/evals=3080/4677 eff=72.0131% N=400 Z=-16.1(97.51%) \| Like=-12.62..-10.71 [-12.6216..-12.6187]\| it/evals=3120/4677 eff=72.9483% N=400 Z=-16.1(97.61%) \| Like=-12.56..-10.71 [-12.5573..-12.5570]\| it/evals=3150/4783 eff=71.8686% N=400 Z=-16.1(97.65%) \| Like=-12.53..-10.71 [-12.5334..-12.5307]\| it/evals=3160/4783 eff=72.0967% N=400 Z=-16.1(97.79%) \| Like=-12.47..-10.67 [-12.4663..-12.4660]\| it/evals=3200/4807 eff=72.6118% N=400 Z=-16.1(97.90%) \| Like=-12.40..-10.67 [-12.4004..-12.3983]\| it/evals=3240/4864 eff=72.5806% N=400 Z=-16.1(98.03%) \| Like=-12.34..-10.67 [-12.3382..-12.3369]\| it/evals=3280/4963 eff=71.8825% N=400 Z=-16.1(98.16%) \| Like=-12.28..-10.67 [-12.2780..-12.2776]\| it/evals=3320/4963 eff=72.7591% N=400 Z=-16.1(98.19%) \| Like=-12.26..-10.67 [-12.2599..-12.2526]\| it/evals=3330/5070 eff=71.3062% N=400 Z=-16.1(98.27%) \| Like=-12.19..-10.41 [-12.1911..-12.1903]\| it/evals=3360/5070 eff=71.9486% N=400 Z=-16.1(98.40%) \| Like=-12.11..-10.41 [-12.1122..-12.1102]\| it/evals=3400/5082 eff=72.6185% N=400 Z=-16.1(98.50%) \| Like=-12.06..-10.41 [-12.0599..-12.0591]\| it/evals=3440/5139 eff=72.5892% N=400 Z=-16.1(98.57%) \| Like=-12.02..-10.27 [-12.0160..-12.0145]\| it/evals=3480/5205 eff=72.4246% N=400 Z=-16.1(98.63%) \| Like=-11.98..-10.27 [-11.9758..-11.9748]\| it/evals=3520/5258 eff=72.4578% N=400 Z=-16.1(98.71%) \| Like=-11.94..-10.27 [-11.9392..-11.9390]\| it/evals=3560/5320 eff=72.3577% N=400 Z=-16.1(98.79%) \| Like=-11.90..-10.27 [-11.9040..-11.9036]\| it/evals=3600/5373 eff=72.3909% N=400 Z=-16.1(98.83%) \| Like=-11.87..-10.07 [-11.8686..-11.8648]\| it/evals=3640/5436 eff=72.2796% N=400 Z=-16.1(98.88%) \| Like=-11.83..-10.04 [-11.8315..-11.8309]\| it/evals=3680/5487 eff=72.3413% N=400 Z=-16.1(98.88%) \| Like=-11.83..-10.04 [-11.8277..-11.8275]\| it/evals=3690/5600 eff=70.9615% N=400 Z=-16.1(98.90%) \| Like=-11.81..-10.04 [-11.8122..-11.8104]\| it/evals=3720/5600 eff=71.5385% N=400 Z=-16.1(98.95%) \| Like=-11.78..-10.04 [-11.7838..-11.7833]\| it/evals=3760/5600 eff=72.3077% N=400 Z=-16.1(98.97%) \| Like=-11.77..-9.95 [-11.7704..-11.7691]\| it/evals=3780/5700 eff=71.3208% N=400 Z=-16.1(98.99%) \| Like=-11.75..-9.95 [-11.7459..-11.7457]\| it/evals=3800/5700 eff=71.6981% N=400 [ultranest] Explored until L=-1e+01 [ultranest] Likelihood function evaluations: 5700 [ultranest] logZ = -16.1 +- 0.031 [ultranest] Effective samples strategy satisfied (ESS = 1540.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) [ultranest] logZ error budget: single: 0.04 bs:0.03 tail:0.01 total:0.03 required:<0.50 [ultranest] done iterating. logZ = -16.113 +- 0.081 single instance: logZ = -16.113 +- 0.040 bootstrapped : logZ = -16.104 +- 0.081 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : -0.00320│▁▁▁▁▁▁▁▁▁▃▂▃▄▅▅▆▆▇▇▇▆▆▅▆▅▄▃▄▂▂▁▁▁▁▁▁▁▁ │0.00332 0.00000 +- 0.00094 aux_logweight : -16.20│▁▂▂▂▃▅▆▇▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ │-9.65 -15.00 +- 0.81 expected posterior: 0 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [3.103301183435752e-07, -15.00417091567436] [0.0009388036712996759, 0.8058161277233461] [[0.12036642 0.99849055] [0.99526706 0.98967293] [0.14897278 0.99923711] ... [0.49959749 0.8562253 ] [0.49994909 0.85537463] [0.50001132 0.85666616]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 7.76359460e-05 7.98804246e-05 8.69500660e-05] ====== Running Gauss problem [3] ===== center: 0.001 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-1.5e+13..-14 [-1.485e+13..-16.89] \| it/evals=0/528 eff=0.0000% N=400 Z=-12164310.7(0.00%) \| Like=-12150372.90..-13.67 [-1.485e+13..-16.89] \| it/evals=40/528 eff=31.2500% N=400 Z=-652.1(0.00%) \| Like=-620.56..-13.67 [-1.485e+13..-16.89] \| it/evals=80/528 eff=62.5000% N=400 Z=-56.8(0.00%) \| Like=-49.94..-13.67 [-1.485e+13..-16.89] \| it/evals=90/528 eff=70.3125% N=400 Z=-26.1(0.00%) \| Like=-21.82..-13.67 [-1.485e+13..-16.89] \| it/evals=120/632 eff=51.7241% N=400 Z=-22.1(0.27%) \| Like=-18.83..-13.67 [-1.485e+13..-16.89] \| it/evals=160/632 eff=68.9655% N=400 Z=-21.4(0.56%) \| Like=-18.34..-13.67 [-1.485e+13..-16.89] \| it/evals=180/632 eff=77.5862% N=400 Z=-20.8(1.00%) \| Like=-17.96..-13.67 [-1.485e+13..-16.89] \| it/evals=200/715 eff=63.4921% N=400 Z=-20.0(2.31%) \| Like=-17.37..-13.67 [-1.485e+13..-16.89] \| it/evals=240/715 eff=76.1905% N=400 Z=-19.3(4.39%) \| Like=-16.92..-13.67 [-1.485e+13..-16.89] \| it/evals=280/791 eff=71.6113% N=400 Z=-18.8(7.19%) \| Like=-16.54..-13.67 [-16.5401..-16.5393]\| it/evals=320/791 eff=81.8414% N=400 Z=-18.5(10.63%) \| Like=-16.31..-13.67 [-16.3150..-16.3083]\| it/evals=360/856 eff=78.9474% N=400 Z=-18.1(14.46%) \| Like=-16.13..-13.67 [-16.1344..-16.1344]\| it/evals=400/918 eff=77.2201% N=400 Z=-17.9(18.72%) \| Like=-16.00..-13.67 [-15.9980..-15.9956]\| it/evals=440/979 eff=75.9931% N=400 Z=-17.7(23.05%) \| Like=-15.83..-13.67 [-15.8259..-15.8212]\| it/evals=480/1031 eff=76.0697% N=400 Z=-17.5(27.56%) \| Like=-15.73..-13.67 [-15.7350..-15.7345]\| it/evals=520/1076 eff=76.9231% N=400 Z=-17.4(29.55%) \| Like=-15.69..-13.67 [-15.6855..-15.6849]\| it/evals=540/1076 eff=79.8817% N=400 Z=-17.4(31.40%) \| Like=-15.65..-13.49 [-15.6502..-15.6481]\| it/evals=560/1112 eff=78.6517% N=400 Z=-17.2(35.65%) \| Like=-15.59..-13.49 [-15.5913..-15.5908]\| it/evals=600/1186 eff=76.3359% N=400 Z=-17.1(39.90%) \| Like=-15.54..-13.49 [-15.5399..-15.5364]\| it/evals=640/1227 eff=77.3881% N=400 Z=-17.0(43.82%) \| Like=-15.48..-13.49 [-15.4766..-15.4740]\| it/evals=680/1287 eff=76.6629% N=400 Z=-17.0(47.61%) \| Like=-15.42..-13.49 [-15.4168..-15.4144]\| it/evals=720/1339 eff=76.6773% N=400 Z=-16.9(51.42%) \| Like=-15.35..-13.49 [-15.3493..-15.3493]\| it/evals=760/1416 eff=74.8031% N=400 Z=-16.8(54.77%) \| Like=-15.31..-13.49 [-15.3112..-15.3108]\| it/evals=800/1471 eff=74.6965% N=400 Z=-16.8(55.65%) \| Like=-15.30..-13.49 [-15.3001..-15.2999]\| it/evals=810/1493 eff=74.1080% N=400 Z=-16.8(57.99%) \| Like=-15.28..-13.49 [-15.2763..-15.2737]\| it/evals=840/1556 eff=72.6644% N=400 Z=-16.7(61.13%) \| Like=-15.23..-13.49 [-15.2320..-15.2308]\| it/evals=880/1606 eff=72.9685% N=400 Z=-16.7(62.67%) \| Like=-15.21..-13.49 [-15.2117..-15.2116]\| it/evals=900/1619 eff=73.8310% N=400 Z=-16.7(64.06%) \| Like=-15.20..-13.49 [-15.1985..-15.1978]\| it/evals=920/1643 eff=74.0145% N=400 Z=-16.6(66.71%) \| Like=-15.17..-13.49 [-15.1695..-15.1685]\| it/evals=960/1708 eff=73.3945% N=400 Z=-16.6(69.19%) \| Like=-15.14..-13.49 [-15.1418..-15.1407]\| it/evals=1000/1762 eff=73.4214% N=400 Z=-16.6(71.62%) \| Like=-15.11..-13.49 [-15.1081..-15.1027]\| it/evals=1040/1807 eff=73.9161% N=400 Z=-16.5(73.92%) \| Like=-15.08..-13.49 [-15.0822..-15.0813]\| it/evals=1080/1868 eff=73.5695% N=400 Z=-16.5(76.00%) \| Like=-15.06..-13.49 [-15.0588..-15.0579]\| it/evals=1120/1916 eff=73.8786% N=400 Z=-16.5(77.87%) \| Like=-15.03..-13.49 [-15.0345..-15.0342]\| it/evals=1160/1974 eff=73.6976% N=400 Z=-16.5(78.37%) \| Like=-15.03..-13.49 [-15.0299..-15.0296]\| it/evals=1170/1984 eff=73.8636% N=400 Z=-16.4(79.57%) \| Like=-15.02..-13.49 [-15.0170..-15.0166]\| it/evals=1200/2027 eff=73.7554% N=400 Z=-16.4(81.16%) \| Like=-15.00..-13.49 [-14.9982..-14.9982]\| it/evals=1240/2080 eff=73.8095% N=400 Z=-16.4(81.91%) \| Like=-14.99..-13.49 [-14.9908..-14.9906]\| it/evals=1260/2108 eff=73.7705% N=400 Z=-16.4(82.58%) \| Like=-14.98..-13.49 [-14.9839..-14.9838]\| it/evals=1280/2137 eff=73.6903% N=400 Z=-16.4(83.85%) \| Like=-14.97..-13.49 [-14.9659..-14.9636]\| it/evals=1320/2184 eff=73.9910% N=400 Z=-16.4(84.64%) \| Like=-14.96..-13.49 [-14.9561..-14.9558]\| it/evals=1350/2232 eff=73.6900% N=400 Z=-16.4(84.98%) \| Like=-14.95..-13.49 [-14.9540..-14.9539]\| it/evals=1360/2249 eff=73.5533% N=400 Z=-16.4(86.09%) \| Like=-14.94..-13.49 [-14.9422..-14.9417]\| it/evals=1400/2300 eff=73.6842% N=400 Z=-16.4(87.08%) \| Like=-14.93..-13.36 [-14.9321..-14.9321]\| it/evals=1440/2361 eff=73.4319% N=400 Z=-16.3(87.89%) \| Like=-14.92..-12.53 [-14.9195..-14.9193]\| it/evals=1480/2412 eff=73.5586% N=400 Z=-16.3(88.89%) \| Like=-14.91..-12.53 [-14.9066..-14.9063]\| it/evals=1520/2476 eff=73.2177% N=400 Z=-16.3(89.09%) \| Like=-14.90..-12.53 [-14.9042..-14.9039]\| it/evals=1530/2490 eff=73.2057% N=400 Z=-16.3(89.66%) \| Like=-14.90..-12.53 [-14.8975..-14.8973]\| it/evals=1560/2532 eff=73.1707% N=400 Z=-16.3(90.44%) \| Like=-14.89..-12.53 [-14.8867..-14.8867]\| it/evals=1600/2618 eff=72.1371% N=400 Z=-16.3(90.60%) \| Like=-14.88..-12.49 [-14.8831..-14.8825]\| it/evals=1620/2618 eff=73.0388% N=400 Z=-16.3(90.61%) \| Like=-14.88..-12.49 [-14.8789..-14.8786]\| it/evals=1640/2644 eff=73.0838% N=400 Z=-16.3(91.28%) \| Like=-14.87..-12.49 [-14.8701..-14.8699]\| it/evals=1680/2748 eff=71.5503% N=400 Z=-16.3(91.74%) \| Like=-14.86..-12.49 [-14.8616..-14.8612]\| it/evals=1710/2748 eff=72.8279% N=400 Z=-16.3(91.91%) \| Like=-14.86..-12.49 [-14.8592..-14.8590]\| it/evals=1720/2759 eff=72.9123% N=400 Z=-16.3(92.22%) \| Like=-14.85..-12.28 [-14.8486..-14.8480]\| it/evals=1760/2832 eff=72.3684% N=400 Z=-16.3(92.64%) \| Like=-14.84..-12.28 [-14.8378..-14.8377]\| it/evals=1800/2881 eff=72.5514% N=400 Z=-16.3(93.08%) \| Like=-14.83..-12.28 [-14.8283..-14.8279]\| it/evals=1840/2932 eff=72.6698% N=400 Z=-16.3(93.27%) \| Like=-14.80..-12.28 [-14.8025..-14.8020]\| it/evals=1880/2986 eff=72.6991% N=400 Z=-16.3(93.38%) \| Like=-14.79..-12.28 [-14.7927..-14.7927]\| it/evals=1890/3026 eff=71.9726% N=400 Z=-16.3(93.57%) \| Like=-14.77..-12.28 [-14.7664..-14.7651]\| it/evals=1920/3035 eff=72.8653% N=400 Z=-16.3(93.80%) \| Like=-14.74..-12.28 [-14.7364..-14.7358]\| it/evals=1960/3089 eff=72.8896% N=400 Z=-16.3(93.98%) \| Like=-14.70..-12.11 [-14.6990..-14.6985]\| it/evals=2000/3138 eff=73.0460% N=400 Z=-16.3(94.11%) \| Like=-14.66..-12.01 [-14.6634..-14.6633]\| it/evals=2040/3198 eff=72.9092% N=400 Z=-16.3(94.17%) \| Like=-14.64..-12.01 [-14.6356..-14.6354]\| it/evals=2070/3238 eff=72.9387% N=400 Z=-16.3(94.07%) \| Like=-14.63..-11.86 [-14.6296..-14.6283]\| it/evals=2080/3332 eff=70.9413% N=400 Z=-16.3(94.32%) \| Like=-14.58..-11.86 [-14.5820..-14.5819]\| it/evals=2120/3332 eff=72.3056% N=400 Z=-16.3(94.49%) \| Like=-14.50..-11.86 [-14.5002..-14.4999]\| it/evals=2160/3418 eff=71.5706% N=400 Z=-16.3(94.68%) \| Like=-14.43..-11.86 [-14.4343..-14.4339]\| it/evals=2200/3418 eff=72.8960% N=400 Z=-16.3(94.87%) \| Like=-14.37..-11.82 [-14.3699..-14.3699]\| it/evals=2240/3505 eff=72.1417% N=400 Z=-16.3(94.95%) \| Like=-14.35..-11.82 [-14.3475..-14.3475]\| it/evals=2250/3505 eff=72.4638% N=400 Z=-16.2(95.05%) \| Like=-14.29..-11.82 [-14.2882..-14.2796]\| it/evals=2280/3534 eff=72.7505% N=400 Z=-16.2(95.34%) \| Like=-14.20..-11.82 [-14.2023..-14.2019]\| it/evals=2320/3587 eff=72.7957% N=400 Z=-16.2(95.47%) \| Like=-14.18..-11.82 [-14.1756..-14.1742]\| it/evals=2340/3618 eff=72.7160% N=400 Z=-16.2(95.52%) \| Like=-14.16..-11.82 [-14.1554..-14.1547]\| it/evals=2360/3638 eff=72.8845% N=400 Z=-16.2(95.68%) \| Like=-14.09..-11.82 [-14.0896..-14.0883]\| it/evals=2400/3687 eff=73.0149% N=400 Z=-16.2(95.78%) \| Like=-14.05..-11.72 [-14.0463..-14.0459]\| it/evals=2430/3810 eff=71.2610% N=400 Z=-16.2(95.81%) \| Like=-14.02..-11.72 [-14.0151..-14.0133]\| it/evals=2440/3810 eff=71.5543% N=400 Z=-16.2(96.00%) \| Like=-13.96..-11.72 [-13.9564..-13.9536]\| it/evals=2480/3810 eff=72.7273% N=400 Z=-16.2(96.14%) \| Like=-13.91..-11.71 [-13.9094..-13.9084]\| it/evals=2520/3877 eff=72.4763% N=400 Z=-16.2(96.29%) \| Like=-13.86..-11.69 [-13.8607..-13.8603]\| it/evals=2560/3898 eff=73.1847% N=400 Z=-16.2(96.46%) \| Like=-13.82..-11.69 [-13.8167..-13.8162]\| it/evals=2600/3950 eff=73.2394% N=400 Z=-16.2(96.63%) \| Like=-13.77..-11.69 [-13.7720..-13.7715]\| it/evals=2640/4004 eff=73.2519% N=400 Z=-16.2(96.82%) \| Like=-13.73..-11.69 [-13.7302..-13.7288]\| it/evals=2680/4063 eff=73.1641% N=400 Z=-16.2(96.95%) \| Like=-13.68..-11.69 [-13.6837..-13.6824]\| it/evals=2720/4127 eff=72.9809% N=400 Z=-16.2(97.02%) \| Like=-13.65..-11.61 [-13.6456..-13.6413]\| it/evals=2760/4182 eff=72.9773% N=400 Z=-16.2(97.13%) \| Like=-13.61..-11.61 [-13.6132..-13.6118]\| it/evals=2790/4235 eff=72.7510% N=400 Z=-16.2(97.16%) \| Like=-13.60..-11.61 [-13.6000..-13.5998]\| it/evals=2800/4307 eff=71.6662% N=400 Z=-16.2(97.28%) \| Like=-13.56..-11.61 [-13.5605..-13.5599]\| it/evals=2840/4307 eff=72.6900% N=400 Z=-16.2(97.32%) \| Like=-13.49..-11.54 [-13.4916..-13.4903]\| it/evals=2880/4374 eff=72.4711% N=400 Z=-16.2(97.41%) \| Like=-13.38..-11.54 [-13.3842..-13.3841]\| it/evals=2920/4432 eff=72.4206% N=400 Z=-16.2(97.51%) \| Like=-13.27..-11.54 [-13.2720..-13.2686]\| it/evals=2960/4486 eff=72.4425% N=400 Z=-16.2(97.54%) \| Like=-13.24..-11.54 [-13.2353..-13.2338]\| it/evals=2970/4486 eff=72.6872% N=400 Z=-16.2(97.61%) \| Like=-13.16..-11.54 [-13.1555..-13.1539]\| it/evals=3000/4523 eff=72.7626% N=400 Z=-16.2(97.72%) \| Like=-13.06..-11.49 [-13.0552..-13.0470]\| it/evals=3040/4574 eff=72.8318% N=400 Z=-16.2(97.77%) \| Like=-13.01..-11.49 [-13.0056..-13.0028]\| it/evals=3060/4600 eff=72.8571% N=400 Z=-16.2(97.84%) \| Like=-12.97..-11.49 [-12.9655..-12.9602]\| it/evals=3080/4698 eff=71.6612% N=400 Z=-16.2(97.95%) \| Like=-12.87..-11.49 [-12.8714..-12.8701]\| it/evals=3120/4698 eff=72.5919% N=400 Z=-16.2(98.01%) \| Like=-12.80..-11.22 [-12.8027..-12.8020]\| it/evals=3150/4780 eff=71.9178% N=400 Z=-16.2(98.04%) \| Like=-12.78..-11.22 [-12.7811..-12.7780]\| it/evals=3160/4780 eff=72.1461% N=400 Z=-16.2(98.14%) \| Like=-12.70..-11.22 [-12.6983..-12.6942]\| it/evals=3200/4869 eff=71.6044% N=400 Z=-16.2(98.24%) \| Like=-12.62..-10.99 [-12.6225..-12.6224]\| it/evals=3240/4869 eff=72.4994% N=400 Z=-16.2(98.33%) \| Like=-12.54..-10.99 [-12.5409..-12.5381]\| it/evals=3280/4948 eff=72.1196% N=400 Z=-16.2(98.41%) \| Like=-12.49..-10.99 [-12.4924..-12.4903]\| it/evals=3320/5013 eff=71.9705% N=400 Z=-16.2(98.44%) \| Like=-12.48..-10.99 [-12.4779..-12.4775]\| it/evals=3330/5013 eff=72.1873% N=400 Z=-16.2(98.50%) \| Like=-12.43..-10.94 [-12.4298..-12.4296]\| it/evals=3360/5129 eff=71.0510% N=400 Z=-16.2(98.59%) \| Like=-12.37..-10.94 [-12.3703..-12.3693]\| it/evals=3400/5129 eff=71.8968% N=400 Z=-16.2(98.64%) \| Like=-12.35..-10.94 [-12.3461..-12.3410]\| it/evals=3420/5129 eff=72.3197% N=400 Z=-16.2(98.69%) \| Like=-12.32..-10.94 [-12.3181..-12.3150]\| it/evals=3440/5235 eff=71.1479% N=400 Z=-16.2(98.78%) \| Like=-12.27..-10.94 [-12.2675..-12.2673]\| it/evals=3480/5235 eff=71.9752% N=400 Z=-16.2(98.84%) \| Like=-12.22..-10.94 [-12.2200..-12.2193]\| it/evals=3510/5341 eff=71.0383% N=400 Z=-16.2(98.85%) \| Like=-12.21..-10.94 [-12.2086..-12.2078]\| it/evals=3520/5341 eff=71.2406% N=400 Z=-16.2(98.92%) \| Like=-12.17..-10.94 [-12.1669..-12.1656]\| it/evals=3560/5341 eff=72.0502% N=400 Z=-16.2(98.99%) \| Like=-12.12..-10.94 [-12.1237..-12.1213]\| it/evals=3600/5456 eff=71.2025% N=400 [ultranest] Explored until L=-1e+01 [ultranest] Likelihood function evaluations: 5456 [ultranest] logZ = -16.18 +- 0.03606 [ultranest] Effective samples strategy satisfied (ESS = 1474.1, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.04, need <0.5) [ultranest] logZ error budget: single: 0.04 bs:0.04 tail:0.01 total:0.04 required:<0.50 [ultranest] done iterating. logZ = -16.194 +- 0.092 single instance: logZ = -16.194 +- 0.043 bootstrapped : logZ = -16.183 +- 0.091 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : -0.00229│▁▁▁▁▁▁▁▂▂▂▃▃▄▅▆▅▇▇▇▆▇▅▅▄▃▂▂▂▂▁▁▁▁ ▁ │0.00454 0.00084 +- 0.00089 aux_logweight : -16.20│▁▁▁▁▂▃▄▅▇▇▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ │-10.68 -15.01 +- 0.67 expected posterior: 0.001 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [0.0008448999199092131, -15.012361700518356] [0.0008942846449051315, 0.6690517874129255] [[0.12340181 0.99040087] [0.88659057 0.98849281] [0.86872833 0.98900429] ... [0.50254808 0.84611492] [0.50338149 0.84606757] [0.50301997 0.84628771]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 5.56604570e-05 5.56804178e-05 5.80766537e-05] ====== Running Gauss problem [4] ===== center: 1 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) \| Like=-2.7e+13..-8.5e+02 [-2.707e+13..-5.001e+05] \| it/evals=0/528 eff=0.0000% N=400 Z=-3316105.2(0.00%) \| Like=-2597981.55..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=40/528 eff=31.2500% N=400 Z=-502427.0(0.00%) \| Like=-502376.73..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=80/528 eff=62.5000% N=400 Z=-502236.7(0.00%) \| Like=-502117.19..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=90/528 eff=70.3125% N=400 Z=-501645.2(0.00%) \| Like=-501629.49..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=120/638 eff=50.4202% N=400 Z=-501135.8(0.00%) \| Like=-501121.91..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=160/638 eff=67.2269% N=400 Z=-500731.1(0.00%) \| Like=-500719.78..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=200/732 eff=60.2410% N=400 Z=-500421.0(0.00%) \| Like=-500412.11..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=240/732 eff=72.2892% N=400 Z=-500230.3(0.00%) \| Like=-500222.16..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=270/813 eff=65.3753% N=400 Z=-500174.1(0.00%) \| Like=-500165.75..-846.67 [-2.707e+13..-5.001e+05] \| it/evals=280/813 eff=67.7966% N=400 Z=-499905.4(0.00%) \| Like=-499898.07..-846.67 [-500135.1572..-498820.1386] \| it/evals=320/873 eff=67.6533% N=400 Z=-499684.3(0.00%) \| Like=-499674.47..-846.67 [-500135.1572..-498820.1386] \| it/evals=360/873 eff=76.1099% N=400 Z=-499526.8(0.00%) \| Like=-499518.11..-846.67 [-500135.1572..-498820.1386] \| it/evals=400/933 eff=75.0469% N=400 Z=-499362.7(0.00%) \| Like=-499354.40..-846.67 [-500135.1572..-498820.1386] \| it/evals=440/990 eff=74.5763% N=400 Z=-499346.1(0.00%) \| Like=-499339.33..-846.67 [-500135.1572..-498820.1386] \| it/evals=450/990 eff=76.2712% N=400 Z=-499217.2(0.00%) \| Like=-499205.12..-846.67 [-500135.1572..-498820.1386] \| it/evals=480/1045 eff=74.4186% N=400 Z=-499029.7(0.00%) \| Like=-499014.37..-846.67 [-500135.1572..-498820.1386] \| it/evals=520/1088 eff=75.5814% N=400 Z=-498940.9(0.00%) \| Like=-498931.16..-846.67 [-500135.1572..-498820.1386] \| it/evals=540/1088 eff=78.4884% N=400 Z=-498843.8(0.00%) \| Like=-498836.53..-846.67 [-500135.1572..-498820.1386] \| it/evals=560/1123 eff=77.4550% N=400 Z=-498726.9(0.00%) \| Like=-498713.18..-846.67 [-498819.3616..-497827.6601] \| it/evals=600/1196 eff=75.3769% N=400 Z=-498594.3(0.00%) \| Like=-498580.76..-846.67 [-498819.3616..-497827.6601] \| it/evals=630/1226 eff=76.2712% N=400 Z=-498550.8(0.00%) \| Like=-498542.58..-846.67 [-498819.3616..-497827.6601] \| it/evals=640/1251 eff=75.2056% N=400 Z=-498370.7(0.00%) \| Like=-498363.17..-846.67 [-498819.3616..-497827.6601] \| it/evals=680/1287 eff=76.6629% N=400 Z=-498250.2(0.00%) \| Like=-498237.06..-846.67 [-498819.3616..-497827.6601] \| it/evals=720/1337 eff=76.8410% N=400 Z=-498145.1(0.00%) \| Like=-498133.69..-846.67 [-498819.3616..-497827.6601] \| it/evals=760/1401 eff=75.9241% N=400 Z=-497991.5(0.00%) \| Like=-497972.61..-846.67 [-498819.3616..-497827.6601] \| it/evals=800/1437 eff=77.1456% N=400 Z=-497947.4(0.00%) \| Like=-497935.76..-846.67 [-498819.3616..-497827.6601] \| it/evals=810/1455 eff=76.7773% N=400 Z=-497859.3(0.00%) \| Like=-497841.61..-846.67 [-498819.3616..-497827.6601] \| it/evals=840/1494 eff=76.7824% N=400 Z=-497720.1(0.00%) \| Like=-497704.25..-846.67 [-497827.6061..-496894.2389] \| it/evals=880/1527 eff=78.0834% N=400 Z=-497633.2(0.00%) \| Like=-497620.88..-846.67 [-497827.6061..-496894.2389] \| it/evals=900/1559 eff=77.6531% N=400 Z=-497569.3(0.00%) \| Like=-497559.10..-846.67 [-497827.6061..-496894.2389] \| it/evals=920/1591 eff=77.2460% N=400 Z=-497435.4(0.00%) \| Like=-497425.78..-846.67 [-497827.6061..-496894.2389] \| it/evals=960/1641 eff=77.3570% N=400 Z=-497308.0(0.00%) \| Like=-497298.81..-846.67 [-497827.6061..-496894.2389] \| it/evals=990/1693 eff=76.5661% N=400 Z=-497281.0(0.00%) \| Like=-497265.98..-846.67 [-497827.6061..-496894.2389] \| it/evals=1000/1704 eff=76.6871% N=400 Z=-497120.5(0.00%) \| Like=-497110.05..-846.67 [-497827.6061..-496894.2389] \| it/evals=1040/1752 eff=76.9231% N=400 Z=-496991.5(0.00%) \| Like=-496980.01..-846.67 [-497827.6061..-496894.2389] \| it/evals=1080/1809 eff=76.6501% N=400 Z=-496828.4(0.00%) \| Like=-496818.80..-229.19 [-496893.1801..-476193.7693] \| it/evals=1120/1860 eff=76.7123% N=400 Z=-496597.7(0.00%) \| Like=-496588.52..-229.19 [-496893.1801..-476193.7693] \| it/evals=1160/1906 eff=77.0252% N=400 Z=-495915.3(0.00%) \| Like=-495883.80..-229.19 [-496893.1801..-476193.7693] \| it/evals=1200/1959 eff=76.9724% N=400 Z=-493922.8(0.00%) \| Like=-493845.25..-229.19 [-496893.1801..-476193.7693] \| it/evals=1240/2018 eff=76.6378% N=400 Z=-492888.7(0.00%) \| Like=-492837.70..-229.19 [-496893.1801..-476193.7693] \| it/evals=1260/2050 eff=76.3636% N=400 Z=-491534.0(0.00%) \| Like=-491486.25..-229.19 [-496893.1801..-476193.7693] \| it/evals=1280/2080 eff=76.1905% N=400 Z=-487814.6(0.00%) \| Like=-487578.52..-229.19 [-496893.1801..-476193.7693] \| it/evals=1320/2130 eff=76.3006% N=400 Z=-479048.0(0.00%) \| Like=-478730.51..-137.91 [-496893.1801..-476193.7693] \| it/evals=1360/2180 eff=76.4045% N=400 Z=-467590.3(0.00%) \| Like=-467197.20..-137.91 [-475937.5598..-338262.0948] \| it/evals=1400/2236 eff=76.2527% N=400 Z=-458117.6(0.00%) \| Like=-458097.65..-137.91 [-475937.5598..-338262.0948] \| it/evals=1440/2304 eff=75.6303% N=400 Z=-446788.8(0.00%) \| Like=-446452.99..-137.91 [-475937.5598..-338262.0948] \| it/evals=1480/2347 eff=76.0144% N=400 Z=-430727.4(0.00%) \| Like=-430448.72..-17.03 [-475937.5598..-338262.0948] \| it/evals=1520/2408 eff=75.6972% N=400 Z=-413498.2(0.00%) \| Like=-413026.67..-17.03 [-475937.5598..-338262.0948] \| it/evals=1560/2458 eff=75.8017% N=400 Z=-379384.8(0.00%) \| Like=-378797.67..-17.03 [-475937.5598..-338262.0948] \| it/evals=1600/2521 eff=75.4361% N=400 Z=-367175.3(0.00%) \| Like=-366497.90..-17.03 [-475937.5598..-338262.0948] \| it/evals=1620/2555 eff=75.1740% N=400 Z=-347124.3(0.00%) \| Like=-346275.59..-13.22 [-475937.5598..-338262.0948] \| it/evals=1640/2592 eff=74.8175% N=400 Z=-315360.1(0.00%) \| Like=-315266.06..-13.22 [-337913.5634..-149146.4481] \| it/evals=1680/2660 eff=74.3363% N=400 Z=-288095.7(0.00%) \| Like=-287308.57..-13.22 [-337913.5634..-149146.4481] \| it/evals=1710/2712 eff=73.9619% N=400 Z=-283381.3(0.00%) \| Like=-279597.31..-13.22 [-337913.5634..-149146.4481] \| it/evals=1720/2726 eff=73.9467% N=400 Z=-251538.8(0.00%) \| Like=-249847.19..-13.22 [-337913.5634..-149146.4481] \| it/evals=1760/2834 eff=72.3090% N=400 Z=-224651.3(0.00%) \| Like=-224588.99..-13.22 [-337913.5634..-149146.4481] \| it/evals=1800/2906 eff=71.8276% N=400 Z=-198168.4(0.00%) \| Like=-197940.18..-13.22 [-337913.5634..-149146.4481] \| it/evals=1840/2971 eff=71.5675% N=400 Z=-178248.9(0.00%) \| Like=-178172.53..-13.22 [-337913.5634..-149146.4481] \| it/evals=1880/3030 eff=71.4829% N=400 Z=-154606.9(0.00%) \| Like=-154562.77..-10.13 [-337913.5634..-149146.4481] \| it/evals=1920/3088 eff=71.4286% N=400 Z=-134803.4(0.00%) \| Like=-134078.66..-10.13 [-148753.5759..-54819.0147] \| it/evals=1960/3197 eff=70.0751% N=400 Z=-118050.8(0.00%) \| Like=-117828.10..-10.13 [-148753.5759..-54819.0147] \| it/evals=2000/3248 eff=70.2247% N=400 Z=-106216.8(0.00%) \| Like=-105342.65..-10.13 [-148753.5759..-54819.0147] \| it/evals=2040/3366 eff=68.7795% N=400 Z=-92006.1(0.00%) \| Like=-91832.14..-10.13 [-148753.5759..-54819.0147] \| it/evals=2080/3485 eff=67.4230% N=400 Z=-77698.2(0.00%) \| Like=-77294.92..-10.13 [-148753.5759..-54819.0147] \| it/evals=2120/3572 eff=66.8348% N=400 Z=-66119.0(0.00%) \| Like=-65995.65..-10.13 [-148753.5759..-54819.0147] \| it/evals=2160/3683 eff=65.7935% N=400 Z=-56368.3(0.00%) \| Like=-56336.47..-10.13 [-148753.5759..-54819.0147] \| it/evals=2200/3758 eff=65.5152% N=400 Z=-48186.8(0.00%) \| Like=-47662.68..-10.13 [-54662.7058..-18363.2862] \| it/evals=2240/3888 eff=64.2202% N=400 Z=-41627.8(0.00%) \| Like=-41542.91..-8.41 [-54662.7058..-18363.2862] \| it/evals=2280/4025 eff=62.8966% N=400 Z=-34854.9(0.00%) \| Like=-34438.03..-8.41 [-54662.7058..-18363.2862] \| it/evals=2320/4158 eff=61.7350% N=400 Z=-32311.4(0.00%) \| Like=-32244.02..-7.88 [-54662.7058..-18363.2862] \| it/evals=2340/4212 eff=61.3851% N=400 Z=-29883.3(0.00%) \| Like=-29757.69..-7.88 [-54662.7058..-18363.2862] \| it/evals=2360/4275 eff=60.9032% N=400 Z=-25256.6(0.00%) \| Like=-25242.32..-7.50 [-54662.7058..-18363.2862] \| it/evals=2400/4378 eff=60.3318% N=400 Z=-20762.8(0.00%) \| Like=-20722.55..-7.50 [-54662.7058..-18363.2862] \| it/evals=2440/4463 eff=60.0541% N=400 Z=-17778.1(0.00%) \| Like=-17743.47..-7.50 [-18300.1333..-4927.9682] \| it/evals=2480/4621 eff=58.7538% N=400 Z=-15116.3(0.00%) \| Like=-15054.41..-7.50 [-18300.1333..-4927.9682] \| it/evals=2520/4763 eff=57.7584% N=400 Z=-12610.8(0.00%) \| Like=-12579.89..-7.30 [-18300.1333..-4927.9682] \| it/evals=2560/4903 eff=56.8510% N=400 Z=-10184.2(0.00%) \| Like=-10150.09..-7.30 [-18300.1333..-4927.9682] \| it/evals=2600/5035 eff=56.0949% N=400 Z=-8631.7(0.00%) \| Like=-8602.91..-7.30 [-18300.1333..-4927.9682] \| it/evals=2640/5178 eff=55.2532% N=400 Z=-7251.3(0.00%) \| Like=-7217.86..-7.30 [-18300.1333..-4927.9682] \| it/evals=2680/5384 eff=53.7721% N=400 Z=-5986.2(0.00%) \| Like=-5967.35..-7.30 [-18300.1333..-4927.9682] \| it/evals=2720/5503 eff=53.3020% N=400 Z=-4915.3(0.00%) \| Like=-4874.76..-7.30 [-4912.3727..-1318.0866] \| it/evals=2760/5644 eff=52.6316% N=400 Z=-3981.6(0.00%) \| Like=-3924.82..-7.30 [-4912.3727..-1318.0866] \| it/evals=2800/5795 eff=51.8999% N=400 Z=-3159.5(0.00%) \| Like=-3140.75..-5.20 [-4912.3727..-1318.0866] \| it/evals=2840/5921 eff=51.4400% N=400 Z=-2626.7(0.00%) \| Like=-2605.14..-5.20 [-4912.3727..-1318.0866] \| it/evals=2880/6090 eff=50.6151% N=400 Z=-2250.5(0.00%) \| Like=-2196.70..-5.20 [-4912.3727..-1318.0866] \| it/evals=2920/6213 eff=50.2322% N=400 Z=-1854.9(0.00%) \| Like=-1817.78..-5.20 [-4912.3727..-1318.0866] \| it/evals=2960/6341 eff=49.8233% N=400 Z=-1554.1(0.00%) \| Like=-1539.31..-5.20 [-4912.3727..-1318.0866] \| it/evals=3000/6475 eff=49.3827% N=400 Z=-1353.4(0.00%) \| Like=-1332.34..-5.20 [-4912.3727..-1318.0866] \| it/evals=3040/6598 eff=49.0481% N=400 Z=-1194.8(0.00%) \| Like=-1163.63..-5.20 [-1310.7086..-300.6940] \| it/evals=3060/6663 eff=48.8584% N=400 Z=-1066.7(0.00%) \| Like=-1041.75..-5.20 [-1310.7086..-300.6940] \| it/evals=3080/6717 eff=48.7573% N=400 Z=-876.0(0.00%) \| Like=-855.57..-5.20 [-1310.7086..-300.6940] \| it/evals=3120/6850 eff=48.3721% N=400 Z=-732.0(0.00%) \| Like=-712.71..-5.20 [-1310.7086..-300.6940] \| it/evals=3150/6928 eff=48.2537% N=400 Z=-689.5(0.00%) \| Like=-670.52..-5.20 [-1310.7086..-300.6940] \| it/evals=3160/6952 eff=48.2295% N=400 Z=-563.9(0.00%) \| Like=-541.75..-5.20 [-1310.7086..-300.6940] \| it/evals=3200/7038 eff=48.2073% N=400 Z=-459.2(0.00%) \| Like=-445.06..-5.20 [-1310.7086..-300.6940] \| it/evals=3240/7131 eff=48.1355% N=400 Z=-367.0(0.00%) \| Like=-350.86..-5.20 [-1310.7086..-300.6940] \| it/evals=3280/7228 eff=48.0375% N=400 Z=-320.3(0.00%) \| Like=-306.59..-5.20 [-1310.7086..-300.6940] \| it/evals=3320/7336 eff=47.8662% N=400 Z=-274.4(0.00%) \| Like=-259.98..-5.20 [-298.9220..-89.8731] \| it/evals=3358/7426 eff=47.7939% N=400 Z=-272.4(0.00%) \| Like=-257.69..-5.20 [-298.9220..-89.8731] \| it/evals=3360/7432 eff=47.7816% N=400 Z=-233.7(0.00%) \| Like=-219.11..-5.20 [-298.9220..-89.8731] \| it/evals=3400/7539 eff=47.6257% N=400 Z=-204.4(0.00%) \| Like=-189.73..-5.20 [-298.9220..-89.8731] \| it/evals=3434/7631 eff=47.4900% N=400 Z=-201.3(0.00%) \| Like=-186.33..-5.20 [-298.9220..-89.8731] \| it/evals=3440/7647 eff=47.4679% N=400 Z=-167.9(0.00%) \| Like=-152.98..-5.11 [-298.9220..-89.8731] \| it/evals=3480/7725 eff=47.5085% N=400 Z=-147.8(0.00%) \| Like=-134.01..-5.11 [-298.9220..-89.8731] \| it/evals=3510/7807 eff=47.3876% N=400 Z=-142.2(0.00%) \| Like=-128.00..-5.11 [-298.9220..-89.8731] \| it/evals=3520/7826 eff=47.4010% N=400 Z=-125.1(0.00%) \| Like=-108.54..-5.11 [-298.9220..-89.8731] \| it/evals=3555/7898 eff=47.4126% N=400 Z=-118.7(0.00%) \| Like=-104.54..-5.11 [-298.9220..-89.8731] \| it/evals=3560/7908 eff=47.4161% N=400 Z=-100.4(0.00%) \| Like=-86.29..-5.11 [-89.6320..-30.8567] \| it/evals=3599/8022 eff=47.2186% N=400 Z=-100.1(0.00%) \| Like=-85.86..-5.11 [-89.6320..-30.8567] \| it/evals=3600/8025 eff=47.2131% N=400 Z=-89.6(0.00%) \| Like=-74.63..-5.11 [-89.6320..-30.8567] \| it/evals=3632/8103 eff=47.1505% N=400 Z=-86.5(0.00%) \| Like=-72.54..-5.11 [-89.6320..-30.8567] \| it/evals=3640/8122 eff=47.1380% N=400 Z=-76.9(0.00%) \| Like=-63.03..-5.11 [-89.6320..-30.8567] \| it/evals=3666/8218 eff=46.8918% N=400 Z=-73.2(0.00%) \| Like=-59.46..-5.11 [-89.6320..-30.8567] \| it/evals=3680/8257 eff=46.8372% N=400 Z=-68.1(0.00%) \| Like=-54.31..-5.11 [-89.6320..-30.8567] \| it/evals=3700/8304 eff=46.8117% N=400 Z=-62.7(0.00%) \| Like=-48.99..-5.11 [-89.6320..-30.8567] \| it/evals=3720/8358 eff=46.7454% N=400 Z=-57.1(0.00%) \| Like=-43.96..-5.11 [-89.6320..-30.8567] \| it/evals=3753/8449 eff=46.6269% N=400 Z=-55.8(0.00%) \| Like=-41.79..-5.11 [-89.6320..-30.8567] \| it/evals=3760/8483 eff=46.5174% N=400 Z=-52.0(0.00%) \| Like=-38.43..-5.11 [-89.6320..-30.8567] \| it/evals=3779/8551 eff=46.3624% N=400 Z=-50.4(0.00%) \| Like=-36.85..-5.11 [-89.6320..-30.8567] \| it/evals=3792/8591 eff=46.2947% N=400 Z=-49.3(0.00%) \| Like=-35.57..-5.11 [-89.6320..-30.8567] \| it/evals=3800/8616 eff=46.2512% N=400 Z=-46.0(0.00%) \| Like=-32.64..-5.11 [-89.6320..-30.8567] \| it/evals=3824/8676 eff=46.2059% N=400 Z=-44.7(0.00%) \| Like=-31.53..-5.11 [-89.6320..-30.8567] \| it/evals=3840/8713 eff=46.1927% N=400 Z=-42.6(0.00%) \| Like=-29.40..-5.11 [-30.3328..-14.1145] \| it/evals=3859/8771 eff=46.0996% N=400 Z=-41.2(0.00%) \| Like=-27.33..-5.11 [-30.3328..-14.1145] \| it/evals=3874/8818 eff=46.0204% N=400 Z=-40.4(0.00%) \| Like=-26.67..-5.11 [-30.3328..-14.1145] \| it/evals=3880/8836 eff=45.9934% N=400 Z=-37.8(0.00%) \| Like=-24.16..-5.11 [-30.3328..-14.1145] \| it/evals=3904/8880 eff=46.0377% N=400 Z=-36.5(0.00%) \| Like=-23.19..-5.11 [-30.3328..-14.1145] \| it/evals=3917/8927 eff=45.9364% N=400 Z=-36.3(0.00%) \| Like=-22.90..-5.11 [-30.3328..-14.1145] \| it/evals=3920/8941 eff=45.8963% N=400 Z=-34.6(0.00%) \| Like=-21.59..-5.11 [-30.3328..-14.1145] \| it/evals=3943/8999 eff=45.8542% N=400 Z=-33.7(0.00%) \| Like=-20.53..-5.11 [-30.3328..-14.1145] \| it/evals=3960/9039 eff=45.8386% N=400 Z=-32.5(0.00%) \| Like=-19.42..-5.11 [-30.3328..-14.1145] \| it/evals=3982/9077 eff=45.8914% N=400 Z=-31.5(0.00%) \| Like=-18.39..-5.11 [-30.3328..-14.1145] \| it/evals=4000/9113 eff=45.9084% N=400 Z=-30.5(0.00%) \| Like=-17.38..-5.11 [-30.3328..-14.1145] \| it/evals=4019/9161 eff=45.8738% N=400 Z=-29.7(0.00%) \| Like=-16.67..-5.11 [-30.3328..-14.1145] \| it/evals=4037/9215 eff=45.7969% N=400 Z=-29.5(0.00%) \| Like=-16.62..-5.11 [-30.3328..-14.1145] \| it/evals=4040/9232 eff=45.7428% N=400 Z=-29.0(0.00%) \| Like=-15.87..-5.11 [-30.3328..-14.1145] \| it/evals=4050/9263 eff=45.6956% N=400 Z=-28.4(0.01%) \| Like=-15.45..-5.11 [-30.3328..-14.1145] \| it/evals=4063/9294 eff=45.6825% N=400 Z=-27.9(0.01%) \| Like=-15.04..-5.11 [-30.3328..-14.1145] \| it/evals=4078/9329 eff=45.6714% N=400 Z=-27.8(0.01%) \| Like=-14.93..-5.11 [-30.3328..-14.1145] \| it/evals=4080/9332 eff=45.6785% N=400 Z=-27.2(0.02%) \| Like=-14.31..-5.11 [-30.3328..-14.1145] \| it/evals=4098/9377 eff=45.6500% N=400 Z=-26.7(0.03%) \| Like=-14.02..-5.11 [-14.0632..-9.8588] \| it/evals=4112/9414 eff=45.6179% N=400 Z=-26.5(0.04%) \| Like=-13.69..-5.11 [-14.0632..-9.8588] \| it/evals=4120/9453 eff=45.5098% N=400 Z=-26.1(0.06%) \| Like=-13.23..-5.11 [-14.0632..-9.8588] \| it/evals=4134/9488 eff=45.4886% N=400 Z=-25.9(0.08%) \| Like=-13.08..-5.11 [-14.0632..-9.8588] \| it/evals=4141/9507 eff=45.4705% N=400 Z=-25.5(0.12%) \| Like=-12.74..-5.11 [-14.0632..-9.8588] \| it/evals=4155/9532 eff=45.4993% N=400 Z=-25.4(0.14%) \| Like=-12.59..-5.11 [-14.0632..-9.8588] \| it/evals=4160/9541 eff=45.5092% N=400 Z=-24.9(0.22%) \| Like=-12.17..-5.11 [-14.0632..-9.8588] \| it/evals=4180/9584 eff=45.5139% N=400 Z=-24.7(0.27%) \| Like=-12.04..-5.11 [-14.0632..-9.8588] \| it/evals=4190/9620 eff=45.4447% N=400 Z=-24.5(0.34%) \| Like=-11.89..-5.11 [-14.0632..-9.8588] \| it/evals=4200/9641 eff=45.4496% N=400 Z=-24.2(0.45%) \| Like=-11.56..-5.11 [-14.0632..-9.8588] \| it/evals=4213/9674 eff=45.4281% N=400 Z=-23.9(0.58%) \| Like=-11.33..-5.11 [-14.0632..-9.8588] \| it/evals=4227/9708 eff=45.4125% N=400 Z=-23.8(0.67%) \| Like=-11.21..-5.11 [-14.0632..-9.8588] \| it/evals=4234/9723 eff=45.4146% N=400 Z=-23.7(0.75%) \| Like=-11.07..-5.11 [-14.0632..-9.8588] \| it/evals=4240/9742 eff=45.3864% N=400 Z=-23.5(0.92%) \| Like=-10.85..-5.11 [-14.0632..-9.8588] \| it/evals=4252/9768 eff=45.3886% N=400 Z=-23.2(1.18%) \| Like=-10.64..-5.11 [-14.0632..-9.8588] \| it/evals=4265/9803 eff=45.3579% N=400 Z=-23.1(1.39%) \| Like=-10.55..-5.11 [-14.0632..-9.8588] \| it/evals=4275/9835 eff=45.3100% N=400 Z=-23.0(1.49%) \| Like=-10.51..-5.11 [-14.0632..-9.8588] \| it/evals=4280/9856 eff=45.2623% N=400 Z=-22.7(1.91%) \| Like=-10.30..-5.11 [-14.0632..-9.8588] \| it/evals=4298/9888 eff=45.2993% N=400 Z=-22.7(2.08%) \| Like=-10.22..-5.11 [-14.0632..-9.8588] \| it/evals=4304/9921 eff=45.2053% N=400 Z=-22.5(2.41%) \| Like=-10.13..-5.11 [-14.0632..-9.8588] \| it/evals=4316/9955 eff=45.1701% N=400 Z=-22.5(2.53%) \| Like=-10.10..-5.11 [-14.0632..-9.8588] \| it/evals=4320/9973 eff=45.1269% N=400 Z=-22.3(2.83%) \| Like=-9.97..-5.11 [-14.0632..-9.8588] \| it/evals=4331/9993 eff=45.1475% N=400 Z=-22.2(3.41%) \| Like=-9.83..-5.11 [-9.8567..-9.3412] \| it/evals=4347/10027 eff=45.1543% N=400 Z=-22.1(3.63%) \| Like=-9.78..-5.11 [-9.8567..-9.3412] \| it/evals=4355/10042 eff=45.1670% N=400 Z=-22.0(3.82%) \| Like=-9.71..-5.11 [-9.8567..-9.3412] \| it/evals=4360/10062 eff=45.1252% N=400 Z=-21.9(4.23%) \| Like=-9.64..-5.11 [-9.8567..-9.3412] \| it/evals=4370/10086 eff=45.1167% N=400 Z=-21.8(4.53%) \| Like=-9.57..-5.11 [-9.8567..-9.3412] \| it/evals=4379/10116 eff=45.0700% N=400 Z=-21.8(4.78%) \| Like=-9.50..-5.11 [-9.8567..-9.3412] \| it/evals=4386/10145 eff=45.0077% N=400 Z=-21.7(5.16%) \| Like=-9.44..-5.11 [-9.8567..-9.3412] \| it/evals=4394/10169 eff=44.9790% N=400 Z=-21.6(5.45%) \| Like=-9.36..-5.11 [-9.8567..-9.3412] \| it/evals=4400/10185 eff=44.9668% N=400 Z=-21.6(5.75%) \| Like=-9.29..-5.11 [-9.3145..-9.1773] \| it/evals=4406/10212 eff=44.9042% N=400 Z=-21.5(5.89%) \| Like=-9.25..-5.11 [-9.3145..-9.1773] \| it/evals=4412/10227 eff=44.8967% N=400 Z=-21.5(6.24%) \| Like=-9.20..-5.05 [-9.3145..-9.1773] \| it/evals=4421/10253 eff=44.8696% N=400 Z=-21.3(6.81%) \| Like=-9.16..-5.05 [-9.1770..-9.0766] \| it/evals=4435/10279 eff=44.8932% N=400 Z=-21.3(7.06%) \| Like=-9.15..-5.05 [-9.1770..-9.0766] \| it/evals=4440/10292 eff=44.8848% N=400 Z=-21.3(7.30%) \| Like=-9.11..-5.05 [-9.1770..-9.0766] \| it/evals=4448/10316 eff=44.8568% N=400 Z=-21.2(7.77%) \| Like=-9.08..-5.05 [-9.1770..-9.0766] \| it/evals=4456/10337 eff=44.8425% N=400 Z=-21.1(8.29%) \| Like=-9.04..-5.05 [-9.0765..-8.9720] \| it/evals=4465/10366 eff=44.8023% N=400 Z=-21.1(8.69%) \| Like=-9.01..-5.05 [-9.0765..-8.9720] \| it/evals=4472/10387 eff=44.7782% N=400 Z=-21.1(9.15%) \| Like=-8.97..-5.05 [-9.0765..-8.9720] \| it/evals=4480/10401 eff=44.7955% N=400 Z=-21.0(9.46%) \| Like=-8.93..-4.93 [-8.9377..-8.9033] \| it/evals=4489/10435 eff=44.7334% N=400 Z=-20.9(10.19%) \| Like=-8.89..-4.93 [-8.8865..-8.8784]\| it/evals=4500/10460 eff=44.7316% N=400 Z=-20.9(10.51%) \| Like=-8.86..-4.93 [-8.8556..-8.8493]\| it/evals=4509/10487 eff=44.7011% N=400 Z=-20.8(11.01%) \| Like=-8.82..-4.93 [-8.8202..-8.8174]\| it/evals=4517/10523 eff=44.6212% N=400 Z=-20.8(11.22%) \| Like=-8.80..-4.93 [-8.8032..-8.8027]\| it/evals=4520/10535 eff=44.5979% N=400 Z=-20.8(11.45%) \| Like=-8.79..-4.93 [-8.7851..-8.7834]\| it/evals=4527/10556 eff=44.5746% N=400 Z=-20.8(11.55%) \| Like=-8.77..-4.93 [-8.7681..-8.7566] \| it/evals=4535/10584 eff=44.5306% N=400 Z=-20.7(11.73%) \| Like=-8.72..-4.93 [-8.7376..-8.7031] \| it/evals=4547/10615 eff=44.5130% N=400 Z=-20.7(12.30%) \| Like=-8.70..-4.93 [-8.7022..-8.6953]\| it/evals=4555/10643 eff=44.4694% N=400 Z=-20.6(12.57%) \| Like=-8.69..-4.93 [-8.6887..-8.6866]\| it/evals=4560/10649 eff=44.4921% N=400 Z=-20.6(13.11%) \| Like=-8.65..-4.93 [-8.6483..-8.6446]\| it/evals=4568/10674 eff=44.4617% N=400 Z=-20.6(13.50%) \| Like=-8.62..-4.93 [-8.6164..-8.6085]\| it/evals=4574/10697 eff=44.4207% N=400 Z=-20.5(14.01%) \| Like=-8.59..-4.93 [-8.5888..-8.5886]\| it/evals=4582/10731 eff=44.3520% N=400 Z=-20.5(14.66%) \| Like=-8.57..-4.93 [-8.5655..-8.5630]\| it/evals=4591/10752 eff=44.3489% N=400 Z=-20.5(15.00%) \| Like=-8.53..-4.93 [-8.5338..-8.5277]\| it/evals=4597/10769 eff=44.3341% N=400 Z=-20.5(15.15%) \| Like=-8.52..-4.93 [-8.5247..-8.5234]\| it/evals=4599/10789 eff=44.2680% N=400 Z=-20.5(15.22%) \| Like=-8.52..-4.93 [-8.5234..-8.5136]\| it/evals=4600/10794 eff=44.2563% N=400 Z=-20.4(15.72%) \| Like=-8.49..-4.93 [-8.4869..-8.4828]\| it/evals=4610/10822 eff=44.2334% N=400 Z=-20.4(16.23%) \| Like=-8.47..-4.93 [-8.4681..-8.4662]\| it/evals=4617/10843 eff=44.2114% N=400 Z=-20.4(16.61%) \| Like=-8.44..-4.93 [-8.4407..-8.4344]\| it/evals=4626/10868 eff=44.1918% N=400 Z=-20.4(16.76%) \| Like=-8.41..-4.93 [-8.4249..-8.4139] \| it/evals=4632/10889 eff=44.1605% N=400 Z=-20.3(17.06%) \| Like=-8.40..-4.93 [-8.4036..-8.4020]\| it/evals=4636/10906 eff=44.1272% N=400 Z=-20.3(17.31%) \| Like=-8.40..-4.93 [-8.3973..-8.3949]\| it/evals=4639/10922 eff=44.0886% N=400 Z=-20.3(17.38%) \| Like=-8.39..-4.93 [-8.3949..-8.3946]\| it/evals=4640/10925 eff=44.0855% N=400 Z=-20.3(17.58%) \| Like=-8.37..-4.93 [-8.3691..-8.3658]\| it/evals=4648/10955 eff=44.0360% N=400 Z=-20.3(18.15%) \| Like=-8.35..-4.93 [-8.3498..-8.3482]\| it/evals=4656/10978 eff=44.0159% N=400 Z=-20.3(18.21%) \| Like=-8.33..-4.93 [-8.3329..-8.3323]\| it/evals=4661/10996 eff=43.9883% N=400 Z=-20.2(18.66%) \| Like=-8.31..-4.93 [-8.3149..-8.3142]\| it/evals=4667/11027 eff=43.9164% N=400 Z=-20.2(18.96%) \| Like=-8.30..-4.93 [-8.3000..-8.2992]\| it/evals=4671/11045 eff=43.8798% N=400 Z=-20.2(19.44%) \| Like=-8.28..-4.93 [-8.2790..-8.2648] \| it/evals=4679/11062 eff=43.8848% N=400 Z=-20.2(19.52%) \| Like=-8.26..-4.93 [-8.2790..-8.2648] \| it/evals=4680/11065 eff=43.8819% N=400 Z=-20.2(20.00%) \| Like=-8.25..-4.93 [-8.2504..-8.2467]\| it/evals=4688/11088 eff=43.8623% N=400 Z=-20.2(20.46%) \| Like=-8.24..-4.93 [-8.2378..-8.2357]\| it/evals=4694/11106 eff=43.8446% N=400 Z=-20.1(20.91%) \| Like=-8.22..-4.93 [-8.2223..-8.2201]\| it/evals=4700/11122 eff=43.8351% N=400 Z=-20.1(21.15%) \| Like=-8.20..-4.93 [-8.2016..-8.2008]\| it/evals=4703/11145 eff=43.7692% N=400 Z=-20.1(21.43%) \| Like=-8.19..-4.93 [-8.1937..-8.1930]\| it/evals=4707/11165 eff=43.7250% N=400 Z=-20.1(21.47%) \| Like=-8.19..-4.87 [-8.1930..-8.1819] \| it/evals=4708/11179 eff=43.6775% N=400 Z=-20.1(21.75%) \| Like=-8.16..-4.87 [-8.1627..-8.1582]\| it/evals=4718/11199 eff=43.6892% N=400 Z=-20.1(21.90%) \| Like=-8.16..-4.87 [-8.1579..-8.1571]\| it/evals=4720/11211 eff=43.6592% N=400 Z=-20.1(22.13%) \| Like=-8.15..-4.87 [-8.1507..-8.1482]\| it/evals=4723/11223 eff=43.6385% N=400 Z=-20.1(22.30%) \| Like=-8.14..-4.87 [-8.1438..-8.1418]\| it/evals=4725/11238 eff=43.5966% N=400 Z=-20.1(22.55%) \| Like=-8.14..-4.87 [-8.1382..-8.1349]\| it/evals=4728/11262 eff=43.5279% N=400 Z=-20.0(22.97%) \| Like=-8.13..-4.87 [-8.1293..-8.1278]\| it/evals=4734/11275 eff=43.5310% N=400 Z=-20.0(23.42%) \| Like=-8.11..-4.87 [-8.1061..-8.1041]\| it/evals=4743/11303 eff=43.5018% N=400 Z=-20.0(23.76%) \| Like=-8.09..-4.87 [-8.0926..-8.0907]\| it/evals=4747/11326 eff=43.4468% N=400 Z=-20.0(24.18%) \| Like=-8.08..-4.87 [-8.0789..-8.0734]\| it/evals=4753/11347 eff=43.4183% N=400 Z=-20.0(24.43%) \| Like=-8.06..-4.87 [-8.0570..-8.0551]\| it/evals=4757/11369 eff=43.3677% N=400 Z=-20.0(24.52%) \| Like=-8.05..-4.87 [-8.0535..-8.0531]\| it/evals=4760/11384 eff=43.3358% N=400 Z=-20.0(24.92%) \| Like=-8.04..-4.87 [-8.0416..-8.0404]\| it/evals=4767/11407 eff=43.3088% N=400 Z=-19.9(25.16%) \| Like=-8.04..-4.87 [-8.0351..-8.0347]\| it/evals=4770/11417 eff=43.2967% N=400 Z=-19.9(27.33%) \| Like=-7.98..-4.87 [-7.9760..-7.9742]\| it/evals=4800/11523 eff=43.1538% N=400 Z=-19.8(29.56%) \| Like=-7.89..-4.87 [-7.8912..-7.8909]\| it/evals=4840/11637 eff=43.0720% N=400 Z=-19.7(31.82%) \| Like=-7.80..-4.87 [-7.7984..-7.7983]\| it/evals=4880/11749 eff=42.9994% N=400 Z=-19.6(34.42%) \| Like=-7.70..-4.87 [-7.6970..-7.6952]\| it/evals=4920/11872 eff=42.8870% N=400 Z=-19.6(36.69%) \| Like=-7.65..-4.87 [-7.6510..-7.6487]\| it/evals=4950/11971 eff=42.7794% N=400 Z=-19.6(37.38%) \| Like=-7.63..-4.87 [-7.6306..-7.6254]\| it/evals=4960/12011 eff=42.7181% N=400 Z=-19.5(39.11%) \| Like=-7.56..-4.87 [-7.5590..-7.5564]\| it/evals=5000/12149 eff=42.5568% N=400 Z=-19.5(41.35%) \| Like=-7.52..-4.79 [-7.5208..-7.5185]\| it/evals=5037/12261 eff=42.4669% N=400 Z=-19.5(41.62%) \| Like=-7.52..-4.79 [-7.5166..-7.5158]\| it/evals=5040/12269 eff=42.4636% N=400 Z=-19.4(43.18%) \| Like=-7.46..-4.79 [-7.4638..-7.4628]\| it/evals=5071/12384 eff=42.3148% N=400 Z=-19.4(43.90%) \| Like=-7.45..-4.79 [-7.4532..-7.4528]\| it/evals=5080/12421 eff=42.2594% N=400 Z=-19.4(45.94%) \| Like=-7.42..-4.79 [-7.4201..-7.4190]\| it/evals=5109/12541 eff=42.0806% N=400 Z=-19.4(46.53%) \| Like=-7.40..-4.79 [-7.4006..-7.4002]\| it/evals=5120/12582 eff=42.0292% N=400 Z=-19.4(46.89%) \| Like=-7.39..-4.79 [-7.3903..-7.3821]\| it/evals=5130/12615 eff=41.9975% N=400 Z=-19.3(47.97%) \| Like=-7.34..-4.79 [-7.3401..-7.3391]\| it/evals=5160/12717 eff=41.8933% N=400 Z=-19.3(49.00%) \| Like=-7.29..-4.79 [-7.2895..-7.2876]\| it/evals=5193/12831 eff=41.7746% N=400 Z=-19.3(49.30%) \| Like=-7.28..-4.79 [-7.2800..-7.2798]\| it/evals=5200/12855 eff=41.7503% N=400 Z=-19.3(50.31%) \| Like=-7.25..-4.79 [-7.2476..-7.2457]\| it/evals=5224/12928 eff=41.6986% N=400 Z=-19.2(51.04%) \| Like=-7.22..-4.79 [-7.2249..-7.2200]\| it/evals=5240/12971 eff=41.6832% N=400 Z=-19.2(52.13%) \| Like=-7.18..-4.79 [-7.1810..-7.1805]\| it/evals=5274/13076 eff=41.6062% N=400 Z=-19.2(52.37%) \| Like=-7.17..-4.79 [-7.1682..-7.1681]\| it/evals=5280/13091 eff=41.6043% N=400 Z=-19.2(52.68%) \| Like=-7.14..-4.77 [-7.1416..-7.1416]\| it/evals=5297/13156 eff=41.5256% N=400 Z=-19.2(52.85%) \| Like=-7.12..-4.77 [-7.1162..-7.1161]\| it/evals=5310/13200 eff=41.4844% N=400 Z=-19.2(53.47%) \| Like=-7.10..-4.77 [-7.0977..-7.0973]\| it/evals=5320/13224 eff=41.4847% N=400 Z=-19.2(54.94%) \| Like=-7.05..-4.77 [-7.0507..-7.0502]\| it/evals=5360/13334 eff=41.4412% N=400 Z=-19.1(56.57%) \| Like=-6.99..-4.77 [-6.9914..-6.9893]\| it/evals=5400/13412 eff=41.5002% N=400 Z=-19.1(58.15%) \| Like=-6.92..-4.77 [-6.9184..-6.9182]\| it/evals=5440/13478 eff=41.5966% N=400 Z=-19.1(59.46%) \| Like=-6.81..-4.77 [-6.8070..-6.8051]\| it/evals=5480/13552 eff=41.6667% N=400 Z=-19.1(61.24%) \| Like=-6.61..-4.77 [-6.6105..-6.6076]\| it/evals=5520/13608 eff=41.7929% N=400 Z=-19.0(62.75%) \| Like=-6.47..-4.77 [-6.4671..-6.4663]\| it/evals=5560/13669 eff=41.9022% N=400 Z=-19.0(64.14%) \| Like=-6.37..-4.77 [-6.3693..-6.3689]\| it/evals=5595/13733 eff=41.9635% N=400 Z=-19.0(64.35%) \| Like=-6.34..-4.77 [-6.3407..-6.3406]\| it/evals=5600/13742 eff=41.9727% N=400 Z=-19.0(66.11%) \| Like=-6.25..-4.77 [-6.2545..-6.2519]\| it/evals=5640/13815 eff=42.0425% N=400 Z=-19.0(67.14%) \| Like=-6.16..-4.77 [-6.1605..-6.1596]\| it/evals=5670/13868 eff=42.0998% N=400 Z=-19.0(67.62%) \| Like=-6.14..-4.77 [-6.1350..-6.1325]\| it/evals=5680/13884 eff=42.1240% N=400 Z=-18.9(69.13%) \| Like=-6.06..-4.73 [-6.0565..-6.0563]\| it/evals=5716/13950 eff=42.1845% N=400 Z=-18.9(69.34%) \| Like=-6.05..-4.73 [-6.0545..-6.0502]\| it/evals=5720/13956 eff=42.1953% N=400 Z=-18.9(70.56%) \| Like=-6.00..-4.73 [-5.9976..-5.9969]\| it/evals=5750/14020 eff=42.2173% N=400 Z=-18.9(70.94%) \| Like=-5.98..-4.73 [-5.9797..-5.9792]\| it/evals=5760/14045 eff=42.2133% N=400 Z=-18.9(72.06%) \| Like=-5.93..-4.73 [-5.9330..-5.9289]\| it/evals=5787/14091 eff=42.2686% N=400 Z=-18.9(72.61%) \| Like=-5.91..-4.73 [-5.9085..-5.9069]\| it/evals=5800/14112 eff=42.2987% N=400 Z=-18.9(73.29%) \| Like=-5.87..-4.73 [-5.8673..-5.8669]\| it/evals=5819/14145 eff=42.3354% N=400 Z=-18.9(74.05%) \| Like=-5.83..-4.73 [-5.8273..-5.8166] \| it/evals=5840/14178 eff=42.3864% N=400 Z=-18.9(74.64%) \| Like=-5.80..-4.73 [-5.7956..-5.7947]\| it/evals=5852/14199 eff=42.4089% N=400 Z=-18.8(75.34%) \| Like=-5.75..-4.68 [-5.7469..-5.7457]\| it/evals=5874/14229 eff=42.4760% N=400 Z=-18.8(75.54%) \| Like=-5.74..-4.68 [-5.7368..-5.7337]\| it/evals=5880/14243 eff=42.4763% N=400 Z=-18.8(76.33%) \| Like=-5.70..-4.64 [-5.7037..-5.7023]\| it/evals=5903/14282 eff=42.5227% N=400 Z=-18.8(76.93%) \| Like=-5.67..-4.64 [-5.6662..-5.6660]\| it/evals=5919/14317 eff=42.5307% N=400 Z=-18.8(76.98%) \| Like=-5.67..-4.64 [-5.6660..-5.6653]\| it/evals=5920/14319 eff=42.5318% N=400 Z=-18.8(77.69%) \| Like=-5.64..-4.64 [-5.6392..-5.6369]\| it/evals=5940/14346 eff=42.5929% N=400 Z=-18.8(78.30%) \| Like=-5.60..-4.64 [-5.5965..-5.5936]\| it/evals=5960/14374 eff=42.6506% N=400 Z=-18.8(78.68%) \| Like=-5.58..-4.64 [-5.5807..-5.5787]\| it/evals=5969/14398 eff=42.6418% N=400 Z=-18.8(79.19%) \| Like=-5.56..-4.64 [-5.5582..-5.5544]\| it/evals=5982/14428 eff=42.6433% N=400 Z=-18.8(79.89%) \| Like=-5.53..-4.64 [-5.5265..-5.5265]\| it/evals=6000/14456 eff=42.6864% N=400 Z=-18.8(80.51%) \| Like=-5.51..-4.62 [-5.5070..-5.5069]\| it/evals=6021/14493 eff=42.7233% N=400 Z=-18.8(80.91%) \| Like=-5.49..-4.62 [-5.4948..-5.4896]\| it/evals=6034/14519 eff=42.7367% N=400 Z=-18.8(81.10%) \| Like=-5.48..-4.62 [-5.4849..-5.4844]\| it/evals=6040/14529 eff=42.7490% N=400 Z=-18.8(81.51%) \| Like=-5.46..-4.62 [-5.4624..-5.4588]\| it/evals=6054/14552 eff=42.7784% N=400 Z=-18.8(82.12%) \| Like=-5.43..-4.62 [-5.4316..-5.4312]\| it/evals=6072/14584 eff=42.8088% N=400 Z=-18.8(82.30%) \| Like=-5.41..-4.62 [-5.4122..-5.4080]\| it/evals=6080/14600 eff=42.8169% N=400 Z=-18.7(82.68%) \| Like=-5.39..-4.50 [-5.3909..-5.3902]\| it/evals=6097/14629 eff=42.8491% N=400 Z=-18.7(83.04%) \| Like=-5.37..-4.50 [-5.3695..-5.3663]\| it/evals=6109/14653 eff=42.8612% N=400 Z=-18.7(83.36%) \| Like=-5.36..-4.50 [-5.3558..-5.3558]\| it/evals=6120/14671 eff=42.8842% N=400 Z=-18.7(83.65%) \| Like=-5.34..-4.50 [-5.3398..-5.3389]\| it/evals=6131/14697 eff=42.8831% N=400 Z=-18.7(84.02%) \| Like=-5.33..-4.47 [-5.3278..-5.3274]\| it/evals=6144/14713 eff=42.9260% N=400 Z=-18.7(84.32%) \| Like=-5.32..-4.47 [-5.3196..-5.3193]\| it/evals=6153/14729 eff=42.9409% N=400 Z=-18.7(84.54%) \| Like=-5.30..-4.47 [-5.3031..-5.3025]\| it/evals=6160/14741 eff=42.9538% N=400 Z=-18.7(84.93%) \| Like=-5.28..-4.47 [-5.2837..-5.2828]\| it/evals=6174/14762 eff=42.9884% N=400 Z=-18.7(85.25%) \| Like=-5.28..-4.47 [-5.2758..-5.2748]\| it/evals=6185/14779 eff=43.0141% N=400 Z=-18.7(85.64%) \| Like=-5.26..-4.47 [-5.2589..-5.2586]\| it/evals=6200/14806 eff=43.0376% N=400 Z=-18.7(85.90%) \| Like=-5.24..-4.47 [-5.2428..-5.2427]\| it/evals=6210/14822 eff=43.0592% N=400 Z=-18.7(86.19%) \| Like=-5.24..-4.47 [-5.2354..-5.2347]\| it/evals=6220/14848 eff=43.0509% N=400 Z=-18.7(86.55%) \| Like=-5.22..-4.47 [-5.2204..-5.2198]\| it/evals=6235/14880 eff=43.0594% N=400 Z=-18.7(86.66%) \| Like=-5.22..-4.47 [-5.2177..-5.2162]\| it/evals=6240/14900 eff=43.0345% N=400 Z=-18.7(87.04%) \| Like=-5.21..-4.47 [-5.2057..-5.2054]\| it/evals=6256/14929 eff=43.0587% N=400 Z=-18.7(87.33%) \| Like=-5.19..-4.47 [-5.1896..-5.1895]\| it/evals=6269/14953 eff=43.0770% N=400 Z=-18.7(87.53%) \| Like=-5.18..-4.47 [-5.1776..-5.1775]\| it/evals=6278/14971 eff=43.0856% N=400 Z=-18.7(87.58%) \| Like=-5.18..-4.47 [-5.1758..-5.1754]\| it/evals=6280/14974 eff=43.0904% N=400 Z=-18.7(87.82%) \| Like=-5.17..-4.47 [-5.1684..-5.1679]\| it/evals=6290/14995 eff=43.0970% N=400 Z=-18.7(87.97%) \| Like=-5.17..-4.47 [-5.1651..-5.1649]\| it/evals=6297/15010 eff=43.1006% N=400 Z=-18.7(88.24%) \| Like=-5.16..-4.47 [-5.1572..-5.1553]\| it/evals=6308/15030 eff=43.1169% N=400 Z=-18.7(88.52%) \| Like=-5.15..-4.47 [-5.1456..-5.1440]\| it/evals=6320/15050 eff=43.1399% N=400 Z=-18.7(88.70%) \| Like=-5.13..-4.29 [-5.1340..-5.1329]\| it/evals=6329/15078 eff=43.1190% N=400 Z=-18.7(88.88%) \| Like=-5.13..-4.29 [-5.1293..-5.1288]\| it/evals=6337/15101 eff=43.1059% N=400 Z=-18.7(89.07%) \| Like=-5.12..-4.29 [-5.1226..-5.1226]\| it/evals=6346/15124 eff=43.0997% N=400 Z=-18.7(89.27%) \| Like=-5.11..-4.29 [-5.1145..-5.1122]\| it/evals=6356/15146 eff=43.1032% N=400 Z=-18.7(89.33%) \| Like=-5.11..-4.28 [-5.1088..-5.1070]\| it/evals=6360/15154 eff=43.1070% N=400 Z=-18.7(89.49%) \| Like=-5.10..-4.28 [-5.1034..-5.1025]\| it/evals=6368/15172 eff=43.1086% N=400 Z=-18.7(89.66%) \| Like=-5.09..-4.28 [-5.0939..-5.0938]\| it/evals=6376/15188 eff=43.1160% N=400 Z=-18.7(89.79%) \| Like=-5.09..-4.28 [-5.0913..-5.0901]\| it/evals=6383/15204 eff=43.1167% N=400 Z=-18.7(89.93%) \| Like=-5.09..-4.28 [-5.0874..-5.0869]\| it/evals=6390/15221 eff=43.1145% N=400 Z=-18.7(90.07%) \| Like=-5.08..-4.28 [-5.0808..-5.0802]\| it/evals=6397/15240 eff=43.1065% N=400 Z=-18.7(90.13%) \| Like=-5.08..-4.28 [-5.0798..-5.0794]\| it/evals=6400/15261 eff=43.0657% N=400 Z=-18.7(90.40%) \| Like=-5.07..-4.28 [-5.0698..-5.0690]\| it/evals=6415/15286 eff=43.0942% N=400 Z=-18.7(90.51%) \| Like=-5.06..-4.28 [-5.0640..-5.0639]\| it/evals=6421/15312 eff=43.0593% N=400 Z=-18.6(90.76%) \| Like=-5.05..-4.28 [-5.0480..-5.0478]\| it/evals=6434/15334 eff=43.0829% N=400 Z=-18.6(90.87%) \| Like=-5.04..-4.28 [-5.0440..-5.0438]\| it/evals=6440/15343 eff=43.0971% N=400 Z=-18.6(90.91%) \| Like=-5.04..-4.28 [-5.0437..-5.0428]\| it/evals=6442/15361 eff=43.0586% N=400 Z=-18.6(91.04%) \| Like=-5.04..-4.28 [-5.0386..-5.0377]\| it/evals=6449/15381 eff=43.0479% N=400 Z=-18.6(91.15%) \| Like=-5.04..-4.28 [-5.0361..-5.0360]\| it/evals=6455/15401 eff=43.0305% N=400 Z=-18.6(91.29%) \| Like=-5.03..-4.28 [-5.0292..-5.0269]\| it/evals=6463/15414 eff=43.0465% N=400 Z=-18.6(91.43%) \| Like=-5.02..-4.28 [-5.0213..-5.0209]\| it/evals=6471/15431 eff=43.0510% N=400 Z=-18.6(91.55%) \| Like=-5.02..-4.28 [-5.0174..-5.0170]\| it/evals=6478/15446 eff=43.0546% N=400 Z=-18.6(91.58%) \| Like=-5.02..-4.18 [-5.0161..-5.0153]\| it/evals=6480/15450 eff=43.0565% N=400 Z=-18.6(91.72%) \| Like=-5.01..-4.18 [-5.0096..-5.0089]\| it/evals=6491/15479 eff=43.0466% N=400 Z=-18.6(91.76%) \| Like=-5.01..-4.18 [-5.0088..-5.0085]\| it/evals=6494/15496 eff=43.0180% N=400 Z=-18.6(91.81%) \| Like=-5.01..-4.18 [-5.0082..-5.0070]\| it/evals=6497/15521 eff=42.9667% N=400 Z=-18.6(91.89%) \| Like=-5.01..-4.18 [-5.0060..-5.0036]\| it/evals=6502/15545 eff=42.9317% N=400 Z=-18.6(92.01%) \| Like=-4.99..-4.18 [-4.9911..-4.9885]\| it/evals=6511/15564 eff=42.9372% N=400 Z=-18.6(92.09%) \| Like=-4.98..-4.13 [-4.9850..-4.9843]\| it/evals=6516/15585 eff=42.9108% N=400 Z=-18.6(92.13%) \| Like=-4.98..-4.13 [-4.9835..-4.9829]\| it/evals=6520/15595 eff=42.9089% N=400 Z=-18.6(92.22%) \| Like=-4.98..-4.13 [-4.9807..-4.9790]\| it/evals=6525/15609 eff=42.9022% N=400 Z=-18.6(92.27%) \| Like=-4.98..-4.13 [-4.9770..-4.9766]\| it/evals=6528/15625 eff=42.8768% N=400 Z=-18.6(92.41%) \| Like=-4.97..-4.13 [-4.9726..-4.9710]\| it/evals=6537/15646 eff=42.8768% N=400 Z=-18.6(92.51%) \| Like=-4.97..-4.13 [-4.9674..-4.9673]\| it/evals=6544/15665 eff=42.8693% N=400 Z=-18.6(92.56%) \| Like=-4.96..-4.13 [-4.9646..-4.9644]\| it/evals=6548/15686 eff=42.8366% N=400 Z=-18.6(92.65%) \| Like=-4.96..-4.13 [-4.9619..-4.9615]\| it/evals=6554/15698 eff=42.8422% N=400 Z=-18.6(92.72%) \| Like=-4.96..-4.13 [-4.9598..-4.9597]\| it/evals=6559/15716 eff=42.8245% N=400 Z=-18.6(92.73%) \| Like=-4.96..-4.13 [-4.9597..-4.9596]\| it/evals=6560/15723 eff=42.8115% N=400 Z=-18.6(92.76%) \| Like=-4.96..-4.13 [-4.9591..-4.9590]\| it/evals=6562/15734 eff=42.7938% N=400 Z=-18.6(92.87%) \| Like=-4.96..-4.13 [-4.9562..-4.9561]\| it/evals=6569/15750 eff=42.7948% N=400 Z=-18.6(92.88%) \| Like=-4.96..-4.13 [-4.9561..-4.9559]\| it/evals=6570/15755 eff=42.7874% N=400 Z=-18.6(93.29%) \| Like=-4.94..-4.13 [-4.9402..-4.9400]\| it/evals=6600/15832 eff=42.7683% N=400 Z=-18.6(93.82%) \| Like=-4.92..-4.13 [-4.9163..-4.9160]\| it/evals=6640/15949 eff=42.7037% N=400 Z=-18.6(94.30%) \| Like=-4.89..-4.13 [-4.8867..-4.8863]\| it/evals=6680/16038 eff=42.7165% N=400 Z=-18.6(94.75%) \| Like=-4.87..-4.13 [-4.8681..-4.8661]\| it/evals=6720/16183 eff=42.5775% N=400 Z=-18.6(95.15%) \| Like=-4.85..-4.13 [-4.8456..-4.8451]\| it/evals=6758/16309 eff=42.4791% N=400 Z=-18.6(95.16%) \| Like=-4.84..-4.13 [-4.8444..-4.8444]\| it/evals=6760/16309 eff=42.4917% N=400 Z=-18.6(95.53%) \| Like=-4.82..-4.10 [-4.8229..-4.8226]\| it/evals=6800/16412 eff=42.4681% N=400 Z=-18.6(95.67%) \| Like=-4.82..-4.07 [-4.8155..-4.8146]\| it/evals=6815/16472 eff=42.4029% N=400 Z=-18.6(95.87%) \| Like=-4.81..-4.07 [-4.8060..-4.8060]\| it/evals=6840/16535 eff=42.3923% N=400 Z=-18.6(96.18%) \| Like=-4.79..-3.94 [-4.7871..-4.7868]\| it/evals=6880/16635 eff=42.3776% N=400 Z=-18.6(96.42%) \| Like=-4.77..-3.94 [-4.7714..-4.7713]\| it/evals=6920/16752 eff=42.3190% N=400 Z=-18.6(96.48%) \| Like=-4.77..-3.89 [-4.7682..-4.7680]\| it/evals=6930/16776 eff=42.3180% N=400 Z=-18.6(96.65%) \| Like=-4.76..-3.89 [-4.7575..-4.7572]\| it/evals=6960/16850 eff=42.3100% N=400 Z=-18.6(96.88%) \| Like=-4.74..-3.84 [-4.7432..-4.7429]\| it/evals=7000/16951 eff=42.2935% N=400 Z=-18.6(97.07%) \| Like=-4.73..-3.81 [-4.7303..-4.7302]\| it/evals=7040/17039 eff=42.3102% N=400 Z=-18.6(97.30%) \| Like=-4.71..-3.81 [-4.7142..-4.7141]\| it/evals=7080/17121 eff=42.3420% N=400 Z=-18.6(97.49%) \| Like=-4.70..-3.81 [-4.7022..-4.7015]\| it/evals=7120/17229 eff=42.3079% N=400 Z=-18.6(97.65%) \| Like=-4.68..-3.80 [-4.6829..-4.6828]\| it/evals=7160/17321 eff=42.3143% N=400 Z=-18.6(97.78%) \| Like=-4.66..-3.72 [-4.6614..-4.6612]\| it/evals=7200/17401 eff=42.3504% N=400 Z=-18.6(97.91%) \| Like=-4.64..-3.72 [-4.6406..-4.6403]\| it/evals=7240/17478 eff=42.3937% N=400 Z=-18.6(98.02%) \| Like=-4.62..-3.67 [-4.6169..-4.6160]\| it/evals=7280/17550 eff=42.4490% N=400 Z=-18.6(98.13%) \| Like=-4.58..-3.65 [-4.5783..-4.5781]\| it/evals=7317/17609 eff=42.5184% N=400 Z=-18.6(98.14%) \| Like=-4.57..-3.65 [-4.5747..-4.5746]\| it/evals=7320/17620 eff=42.5087% N=400 Z=-18.6(98.26%) \| Like=-4.53..-3.65 [-4.5280..-4.5253]\| it/evals=7360/17688 eff=42.5729% N=400 Z=-18.6(98.37%) \| Like=-4.48..-3.64 [-4.4780..-4.4749]\| it/evals=7400/17753 eff=42.6439% N=400 Z=-18.6(98.48%) \| Like=-4.43..-3.64 [-4.4267..-4.4263]\| it/evals=7440/17834 eff=42.6752% N=400 Z=-18.6(98.58%) \| Like=-4.39..-3.64 [-4.3906..-4.3900]\| it/evals=7480/17895 eff=42.7551% N=400 Z=-18.6(98.67%) \| Like=-4.35..-3.57 [-4.3458..-4.3446]\| it/evals=7520/17985 eff=42.7637% N=400 Z=-18.6(98.76%) \| Like=-4.31..-3.53 [-4.3055..-4.3052]\| it/evals=7560/18055 eff=42.8207% N=400 Z=-18.6(98.84%) \| Like=-4.27..-3.51 [-4.2667..-4.2665]\| it/evals=7600/18127 eff=42.8725% N=400 Z=-18.6(98.90%) \| Like=-4.23..-3.51 [-4.2323..-4.2322]\| it/evals=7629/18196 eff=42.8692% N=400 Z=-18.6(98.92%) \| Like=-4.22..-3.51 [-4.2205..-4.2173]\| it/evals=7640/18220 eff=42.8732% N=400 Z=-18.6(98.94%) \| Like=-4.21..-3.51 [-4.2076..-4.2065]\| it/evals=7650/18242 eff=42.8764% N=400 Z=-18.6(98.99%) \| Like=-4.18..-3.51 [-4.1829..-4.1826]*\| it/evals=7680/18285 eff=42.9410% N=400 [ultranest] Explored until L=-4 [ultranest] Likelihood function evaluations: 18296 [ultranest] logZ = -18.54 +- 0.1012 [ultranest] Effective samples strategy satisfied (ESS = 2455.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [ultranest] logZ error budget: single: 0.17 bs:0.10 tail:0.01 total:0.10 required:<0.50 [ultranest] done iterating. logZ = -18.543 +- 0.242 single instance: logZ = -18.543 +- 0.170 bootstrapped : logZ = -18.537 +- 0.242 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 133 iterations a : 0.99616│ ▁▁▁▁▁▁▁▁▂▂▃▄▄▆▆▆▇▇▇▇▅▅▄▂▂▁▁▁▁▁▁▁▁▁▁ ▁ │1.00448 1.00001 +- 0.00096 aux_logweight : -9.5 │ ▁▁▂▂▂▂▃▃▄▃▅▅▅▅▇▂▁▁▂▂▂▂▃▄▃▅▅▅▆▂▁▁▁▁▁▁▁ │-3.2 -6.6 +- 1.3 expected posterior: 1 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [1.0000129282162666, -6.550121410221049] [0.0009588598232977235, 1.3204149055392533] [[0.8883395 0.99817529] [0.13034117 0.99142363] [0.78474881 0.99736353] ... [0.50172998 0.944065 ] [0.50169013 0.94429909] [0.50165847 0.94449494]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 3.65990988e-05 3.76571984e-05 3.82909311e-05] [9102, 5700, 5456, 18296] -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=False, log_dir=/tmp/tmpo5ypz9wy, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977127652850.78, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-42494098572103.11, remainder_fraction=100.0000%, Lmin=-42215979073894.67, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-35539577109063.16, remainder_fraction=100.0000%, Lmin=-35342846910271.16, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-33613237485632.04, remainder_fraction=100.0000%, Lmin=-33560252660467.55, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=635, regioncalls=256, ndraw=128, logz=-29384711911101.59, remainder_fraction=100.0000%, Lmin=-29244181297237.11, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=635, regioncalls=256, ndraw=128, logz=-24734621524258.34, remainder_fraction=100.0000%, Lmin=-24432486117944.29, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=635, regioncalls=256, ndraw=128, logz=-21802390368988.16, remainder_fraction=100.0000%, Lmin=-21645686453768.96, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=635, regioncalls=256, ndraw=128, logz=-18894098943280.38, remainder_fraction=100.0000%, Lmin=-18862720235209.72, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=722, regioncalls=384, ndraw=128, logz=-16143856057425.05, remainder_fraction=100.0000%, Lmin=-15989446312158.34, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=722, regioncalls=384, ndraw=128, logz=-13535837684113.13, remainder_fraction=100.0000%, Lmin=-13504682847649.48, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=789, regioncalls=512, ndraw=128, logz=-12727737770655.03, remainder_fraction=100.0000%, Lmin=-12717546885535.99, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=789, regioncalls=512, ndraw=128, logz=-10598883623681.07, remainder_fraction=100.0000%, Lmin=-10586634997537.11, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=844, regioncalls=640, ndraw=128, logz=-8214913784357.06, remainder_fraction=100.0000%, Lmin=-8210097848813.22, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=888, regioncalls=768, ndraw=128, logz=-6956519205225.25, remainder_fraction=100.0000%, Lmin=-6861252665445.04, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=935, regioncalls=896, ndraw=128, logz=-5701116414373.90, remainder_fraction=100.0000%, Lmin=-5697064810248.16, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=978, regioncalls=1024, ndraw=128, logz=-4635046691812.15, remainder_fraction=100.0000%, Lmin=-4589605457636.64, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1016, regioncalls=1152, ndraw=128, logz=-3732152419982.96, remainder_fraction=100.0000%, Lmin=-3694550010663.56, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1016, regioncalls=1152, ndraw=128, logz=-3434353117102.53, remainder_fraction=100.0000%, Lmin=-3416276968141.32, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1041, regioncalls=1280, ndraw=128, logz=-3127794898135.65, remainder_fraction=100.0000%, Lmin=-3125426459492.65, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1075, regioncalls=1408, ndraw=128, logz=-2641292819157.70, remainder_fraction=100.0000%, Lmin=-2628326533692.18, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1104, regioncalls=1536, ndraw=128, logz=-2261190883104.97, remainder_fraction=100.0000%, Lmin=-2248263800080.57, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1132, regioncalls=1664, ndraw=128, logz=-2137661409200.45, remainder_fraction=100.0000%, Lmin=-2132854392978.04, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1156, regioncalls=1792, ndraw=128, logz=-1777309068832.62, remainder_fraction=100.0000%, Lmin=-1776189008324.79, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1205, regioncalls=2048, ndraw=128, logz=-1477274645941.83, remainder_fraction=100.0000%, Lmin=-1473039555787.20, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1241, regioncalls=2304, ndraw=128, logz=-1228986328760.53, remainder_fraction=100.0000%, Lmin=-1220530275369.51, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1284, regioncalls=2560, ndraw=128, logz=-1008068513965.31, remainder_fraction=100.0000%, Lmin=-1006791737458.03, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1284, regioncalls=2560, ndraw=128, logz=-967911594539.75, remainder_fraction=100.0000%, Lmin=-965894680564.93, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1323, regioncalls=2816, ndraw=128, logz=-866464949430.24, remainder_fraction=100.0000%, Lmin=-863727290145.78, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1367, regioncalls=3072, ndraw=128, logz=-674755956448.05, remainder_fraction=100.0000%, Lmin=-672288777919.19, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1381, regioncalls=3200, ndraw=128, logz=-590520231360.32, remainder_fraction=100.0000%, Lmin=-590264632476.69, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1413, regioncalls=3456, ndraw=128, logz=-545547274549.16, remainder_fraction=100.0000%, Lmin=-543016922876.22, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1455, regioncalls=3840, ndraw=128, logz=-424503798884.03, remainder_fraction=100.0000%, Lmin=-423311078212.85, Lmax=-306369.44 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1487, regioncalls=4224, ndraw=128, logz=-348540245203.58, remainder_fraction=100.0000%, Lmin=-348466153072.81, Lmax=-306369.44 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1536, regioncalls=4736, ndraw=128, logz=-301347767746.06, remainder_fraction=100.0000%, Lmin=-295535831803.94, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1574, regioncalls=5248, ndraw=128, logz=-249139009684.09, remainder_fraction=100.0000%, Lmin=-248826262015.12, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1614, regioncalls=5760, ndraw=128, logz=-204174473489.88, remainder_fraction=100.0000%, Lmin=-203548030042.37, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1652, regioncalls=6400, ndraw=128, logz=-168277592220.41, remainder_fraction=100.0000%, Lmin=-166951449494.73, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1664, regioncalls=6656, ndraw=128, logz=-161350123311.64, remainder_fraction=100.0000%, Lmin=-161016494392.26, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1698, regioncalls=7168, ndraw=128, logz=-139757817034.57, remainder_fraction=100.0000%, Lmin=-139665996555.80, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1740, regioncalls=8192, ndraw=128, logz=-121163576609.50, remainder_fraction=100.0000%, Lmin=-120962215020.88, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1762, regioncalls=8576, ndraw=128, logz=-113404243129.32, remainder_fraction=100.0000%, Lmin=-113256039153.14, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1776, regioncalls=8960, ndraw=128, logz=-102435191408.59, remainder_fraction=100.0000%, Lmin=-102117171296.36, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1817, regioncalls=10112, ndraw=128, logz=-80561498365.26, remainder_fraction=100.0000%, Lmin=-79890825764.41, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1851, regioncalls=11008, ndraw=128, logz=-65980578546.46, remainder_fraction=100.0000%, Lmin=-65934086414.84, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=1859, regioncalls=11264, ndraw=128, logz=-62736742728.29, remainder_fraction=100.0000%, Lmin=-62725499591.66, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1907, regioncalls=12544, ndraw=128, logz=-51120575825.01, remainder_fraction=100.0000%, Lmin=-51101692631.95, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1948, regioncalls=13952, ndraw=128, logz=-42406526059.95, remainder_fraction=100.0000%, Lmin=-41727505290.80, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=1988, regioncalls=15488, ndraw=128, logz=-33363659562.70, remainder_fraction=100.0000%, Lmin=-32924159572.88, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2029, regioncalls=17024, ndraw=128, logz=-26893053278.43, remainder_fraction=100.0000%, Lmin=-26868052278.66, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2037, regioncalls=17408, ndraw=128, logz=-24932869629.00, remainder_fraction=100.0000%, Lmin=-24826507729.08, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2075, regioncalls=18304, ndraw=128, logz=-21544043932.64, remainder_fraction=100.0000%, Lmin=-21517268972.40, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2116, regioncalls=18816, ndraw=128, logz=-16937433908.05, remainder_fraction=100.0000%, Lmin=-16876272169.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2153, regioncalls=19328, ndraw=128, logz=-14363707315.45, remainder_fraction=100.0000%, Lmin=-14361596834.87, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2195, regioncalls=20096, ndraw=128, logz=-11693905440.60, remainder_fraction=100.0000%, Lmin=-11691023694.63, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2235, regioncalls=20608, ndraw=128, logz=-10340175552.09, remainder_fraction=100.0000%, Lmin=-10317453753.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2238, regioncalls=20864, ndraw=128, logz=-9842053945.87, remainder_fraction=100.0000%, Lmin=-9818062632.12, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2279, regioncalls=22144, ndraw=128, logz=-8152308889.97, remainder_fraction=100.0000%, Lmin=-8104310734.91, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2319, regioncalls=22912, ndraw=128, logz=-6835430799.19, remainder_fraction=100.0000%, Lmin=-6811739139.58, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2362, regioncalls=24320, ndraw=128, logz=-5819912443.41, remainder_fraction=100.0000%, Lmin=-5787984622.54, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2403, regioncalls=24832, ndraw=128, logz=-4884810311.13, remainder_fraction=100.0000%, Lmin=-4858215343.46, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1892, ncalls=2422, regioncalls=25216, ndraw=128, logz=-4636067942.28, remainder_fraction=100.0000%, Lmin=-4621133708.26, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1919, ncalls=2451, regioncalls=25984, ndraw=128, logz=-3858382892.65, remainder_fraction=100.0000%, Lmin=-3854669333.61, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=2451, regioncalls=25984, ndraw=128, logz=-3854669344.40, remainder_fraction=100.0000%, Lmin=-3852626167.06, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1949, ncalls=2485, regioncalls=26752, ndraw=128, logz=-3256231187.70, remainder_fraction=100.0000%, Lmin=-3248632067.55, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=2490, regioncalls=26880, ndraw=128, logz=-3111636724.41, remainder_fraction=100.0000%, Lmin=-3098574454.19, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2768588523.53, remainder_fraction=100.0000%, Lmin=-2751589624.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2501023164.86, remainder_fraction=100.0000%, Lmin=-2499560475.77, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2174481162.42, remainder_fraction=100.0000%, Lmin=-2152077450.73, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2623, regioncalls=27520, ndraw=128, logz=-1895190042.95, remainder_fraction=100.0000%, Lmin=-1893014663.83, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=2624, regioncalls=27648, ndraw=128, logz=-1850397210.79, remainder_fraction=100.0000%, Lmin=-1846179058.70, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2119, ncalls=2671, regioncalls=29696, ndraw=128, logz=-1559142759.67, remainder_fraction=100.0000%, Lmin=-1556767683.82, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=2671, regioncalls=29696, ndraw=128, logz=-1556767695.11, remainder_fraction=100.0000%, Lmin=-1546248420.17, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2707, regioncalls=30208, ndraw=128, logz=-1265681926.79, remainder_fraction=100.0000%, Lmin=-1263138337.35, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=2707, regioncalls=30208, ndraw=128, logz=-1218919277.48, remainder_fraction=100.0000%, Lmin=-1216729629.78, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2162, ncalls=2835, regioncalls=30464, ndraw=128, logz=-1215700445.06, remainder_fraction=100.0000%, Lmin=-1215469460.95, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2835, regioncalls=30464, ndraw=128, logz=-987935092.69, remainder_fraction=100.0000%, Lmin=-983795398.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=2835, regioncalls=30464, ndraw=128, logz=-811811706.41, remainder_fraction=100.0000%, Lmin=-809071566.79, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2275, ncalls=2934, regioncalls=30592, ndraw=128, logz=-705861567.39, remainder_fraction=100.0000%, Lmin=-704698526.64, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=2934, regioncalls=30592, ndraw=128, logz=-694647234.99, remainder_fraction=100.0000%, Lmin=-693426148.12, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=2934, regioncalls=30592, ndraw=128, logz=-567705826.45, remainder_fraction=100.0000%, Lmin=-563342394.87, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2934, regioncalls=30592, ndraw=128, logz=-521635225.62, remainder_fraction=100.0000%, Lmin=-520267088.69, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=2934, regioncalls=30592, ndraw=128, logz=-459117643.74, remainder_fraction=100.0000%, Lmin=-455164296.21, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3050, regioncalls=30848, ndraw=128, logz=-364531808.48, remainder_fraction=100.0000%, Lmin=-363659580.69, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3050, regioncalls=30848, ndraw=128, logz=-314130669.64, remainder_fraction=100.0000%, Lmin=-312456213.72, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3050, regioncalls=30848, ndraw=128, logz=-305067137.67, remainder_fraction=100.0000%, Lmin=-302035358.51, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3068, regioncalls=31232, ndraw=128, logz=-268203743.10, remainder_fraction=100.0000%, Lmin=-264563106.06, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3121, regioncalls=31872, ndraw=128, logz=-227680306.46, remainder_fraction=100.0000%, Lmin=-226720712.29, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3154, regioncalls=32256, ndraw=128, logz=-192282494.48, remainder_fraction=100.0000%, Lmin=-191862767.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3199, regioncalls=32768, ndraw=128, logz=-152481573.93, remainder_fraction=100.0000%, Lmin=-150064687.00, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3208, regioncalls=32896, ndraw=128, logz=-141786985.67, remainder_fraction=100.0000%, Lmin=-141208770.10, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=3327, regioncalls=33280, ndraw=128, logz=-123715293.16, remainder_fraction=100.0000%, Lmin=-123273647.93, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=3327, regioncalls=33280, ndraw=128, logz=-96060458.65, remainder_fraction=100.0000%, Lmin=-96033237.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3327, regioncalls=33280, ndraw=128, logz=-83875005.77, remainder_fraction=100.0000%, Lmin=-83141993.83, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=3327, regioncalls=33280, ndraw=128, logz=-76588171.43, remainder_fraction=100.0000%, Lmin=-76540182.09, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=3444, regioncalls=33536, ndraw=128, logz=-59897794.76, remainder_fraction=100.0000%, Lmin=-59677779.22, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3444, regioncalls=33536, ndraw=128, logz=-49760498.26, remainder_fraction=100.0000%, Lmin=-49599851.63, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=3535, regioncalls=33664, ndraw=128, logz=-38489542.92, remainder_fraction=100.0000%, Lmin=-38441431.28, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=3535, regioncalls=33664, ndraw=128, logz=-32469743.87, remainder_fraction=100.0000%, Lmin=-32313765.59, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=3658, regioncalls=33920, ndraw=128, logz=-26172602.52, remainder_fraction=100.0000%, Lmin=-25938804.52, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=3658, regioncalls=33920, ndraw=128, logz=-19538332.47, remainder_fraction=100.0000%, Lmin=-19450366.38, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=3658, regioncalls=33920, ndraw=128, logz=-18348100.45, remainder_fraction=100.0000%, Lmin=-18344493.62, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=3677, regioncalls=34688, ndraw=128, logz=-15340466.36, remainder_fraction=100.0000%, Lmin=-14985637.97, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=3718, regioncalls=35456, ndraw=128, logz=-12719911.28, remainder_fraction=100.0000%, Lmin=-12647299.74, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=3736, regioncalls=35712, ndraw=128, logz=-11831094.99, remainder_fraction=100.0000%, Lmin=-11787664.15, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=3864, regioncalls=35968, ndraw=128, logz=-11141632.98, remainder_fraction=100.0000%, Lmin=-11121830.90, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=3864, regioncalls=35968, ndraw=128, logz=-8877250.79, remainder_fraction=100.0000%, Lmin=-8874484.68, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=3864, regioncalls=35968, ndraw=128, logz=-7615450.32, remainder_fraction=100.0000%, Lmin=-7615312.38, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=3864, regioncalls=35968, ndraw=128, logz=-7380434.58, remainder_fraction=100.0000%, Lmin=-7356864.48, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=3992, regioncalls=36480, ndraw=128, logz=-7157825.53, remainder_fraction=100.0000%, Lmin=-7156384.89, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=3992, regioncalls=36480, ndraw=128, logz=-6113566.67, remainder_fraction=100.0000%, Lmin=-6050922.96, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=3992, regioncalls=36480, ndraw=128, logz=-4573067.94, remainder_fraction=100.0000%, Lmin=-4566133.63, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3275, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3863486.20, remainder_fraction=100.0000%, Lmin=-3829448.55, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3808107.67, remainder_fraction=100.0000%, Lmin=-3795971.02, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3110640.62, remainder_fraction=100.0000%, Lmin=-3107239.98, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=4100, regioncalls=36864, ndraw=128, logz=-2675252.29, remainder_fraction=100.0000%, Lmin=-2668849.17, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3370, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2564767.22, remainder_fraction=100.0000%, Lmin=-2551402.90, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2198473.59, remainder_fraction=100.0000%, Lmin=-2196576.76, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2012812.77, remainder_fraction=100.0000%, Lmin=-2009485.22, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=4195, regioncalls=36992, ndraw=128, logz=-1847415.71, remainder_fraction=100.0000%, Lmin=-1829858.31, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=4227, regioncalls=37504, ndraw=128, logz=-1451906.35, remainder_fraction=100.0000%, Lmin=-1442627.27, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=4262, regioncalls=37888, ndraw=128, logz=-1216639.27, remainder_fraction=100.0000%, Lmin=-1212596.34, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=4385, regioncalls=38144, ndraw=128, logz=-1180207.61, remainder_fraction=100.0000%, Lmin=-1175032.69, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=4385, regioncalls=38144, ndraw=128, logz=-946994.71, remainder_fraction=100.0000%, Lmin=-940999.45, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=4385, regioncalls=38144, ndraw=128, logz=-778747.47, remainder_fraction=100.0000%, Lmin=-771170.46, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3636, ncalls=4475, regioncalls=38272, ndraw=128, logz=-635147.03, remainder_fraction=100.0000%, Lmin=-634663.92, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=4475, regioncalls=38272, ndraw=128, logz=-612791.63, remainder_fraction=100.0000%, Lmin=-608833.23, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=4475, regioncalls=38272, ndraw=128, logz=-508846.48, remainder_fraction=100.0000%, Lmin=-506165.20, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=4475, regioncalls=38272, ndraw=128, logz=-490388.80, remainder_fraction=100.0000%, Lmin=-485575.72, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=4500, regioncalls=38656, ndraw=128, logz=-429946.80, remainder_fraction=100.0000%, Lmin=-428595.78, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=4542, regioncalls=39168, ndraw=128, logz=-346384.62, remainder_fraction=100.0000%, Lmin=-346198.97, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3780, ncalls=4561, regioncalls=39424, ndraw=128, logz=-313687.01, remainder_fraction=100.0000%, Lmin=-313029.66, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=4689, regioncalls=39680, ndraw=128, logz=-282186.40, remainder_fraction=100.0000%, Lmin=-281568.56, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=4689, regioncalls=39680, ndraw=128, logz=-227408.14, remainder_fraction=100.0000%, Lmin=-227371.78, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=4689, regioncalls=39680, ndraw=128, logz=-194507.74, remainder_fraction=100.0000%, Lmin=-194017.43, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=4790, regioncalls=39808, ndraw=128, logz=-160420.77, remainder_fraction=100.0000%, Lmin=-159571.94, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=4790, regioncalls=39808, ndraw=128, logz=-125605.97, remainder_fraction=100.0000%, Lmin=-124767.18, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3983, ncalls=4914, regioncalls=40064, ndraw=128, logz=-111728.69, remainder_fraction=100.0000%, Lmin=-109892.50, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=4914, regioncalls=40064, ndraw=128, logz=-99628.65, remainder_fraction=100.0000%, Lmin=-98796.75, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=4914, regioncalls=40064, ndraw=128, logz=-79563.29, remainder_fraction=100.0000%, Lmin=-79495.58, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=4914, regioncalls=40064, ndraw=128, logz=-77991.97, remainder_fraction=100.0000%, Lmin=-77957.02, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=4925, regioncalls=40320, ndraw=128, logz=-67526.58, remainder_fraction=100.0000%, Lmin=-67417.47, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=4955, regioncalls=40576, ndraw=128, logz=-55235.26, remainder_fraction=100.0000%, Lmin=-55056.05, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=4979, regioncalls=41088, ndraw=128, logz=-48939.88, remainder_fraction=100.0000%, Lmin=-48543.38, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=5102, regioncalls=41344, ndraw=128, logz=-43455.66, remainder_fraction=100.0000%, Lmin=-43364.58, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=5102, regioncalls=41344, ndraw=128, logz=-36008.24, remainder_fraction=100.0000%, Lmin=-35757.46, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4230, ncalls=5102, regioncalls=41344, ndraw=128, logz=-30396.80, remainder_fraction=100.0000%, Lmin=-30282.97, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=5102, regioncalls=41344, ndraw=128, logz=-29056.51, remainder_fraction=100.0000%, Lmin=-28855.17, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=5138, regioncalls=41856, ndraw=128, logz=-24102.75, remainder_fraction=100.0000%, Lmin=-23927.05, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=5174, regioncalls=42368, ndraw=128, logz=-19450.22, remainder_fraction=100.0000%, Lmin=-19344.73, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=5219, regioncalls=43136, ndraw=128, logz=-16094.58, remainder_fraction=100.0000%, Lmin=-15916.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=5261, regioncalls=43648, ndraw=128, logz=-12625.39, remainder_fraction=100.0000%, Lmin=-12576.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=5301, regioncalls=44160, ndraw=128, logz=-10993.45, remainder_fraction=100.0000%, Lmin=-10899.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=5337, regioncalls=44800, ndraw=128, logz=-8992.37, remainder_fraction=100.0000%, Lmin=-8974.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=5485, regioncalls=45440, ndraw=128, logz=-8243.26, remainder_fraction=100.0000%, Lmin=-8189.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=5485, regioncalls=45440, ndraw=128, logz=-7716.04, remainder_fraction=100.0000%, Lmin=-7682.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=5485, regioncalls=45440, ndraw=128, logz=-6371.79, remainder_fraction=100.0000%, Lmin=-6328.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=5485, regioncalls=45440, ndraw=128, logz=-5676.53, remainder_fraction=100.0000%, Lmin=-5634.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=5485, regioncalls=45440, ndraw=128, logz=-5463.72, remainder_fraction=100.0000%, Lmin=-5444.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=5524, regioncalls=45952, ndraw=128, logz=-4563.87, remainder_fraction=100.0000%, Lmin=-4536.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=5568, regioncalls=46464, ndraw=128, logz=-3732.19, remainder_fraction=100.0000%, Lmin=-3678.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2979.60, remainder_fraction=100.0000%, Lmin=-2953.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2401.32, remainder_fraction=100.0000%, Lmin=-2380.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2354.75, remainder_fraction=100.0000%, Lmin=-2328.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=5813, regioncalls=47104, ndraw=128, logz=-2084.03, remainder_fraction=100.0000%, Lmin=-2062.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1671.66, remainder_fraction=100.0000%, Lmin=-1641.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1525.16, remainder_fraction=100.0000%, Lmin=-1482.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1305.51, remainder_fraction=100.0000%, Lmin=-1279.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=5843, regioncalls=47616, ndraw=128, logz=-1056.91, remainder_fraction=100.0000%, Lmin=-1031.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=5872, regioncalls=48128, ndraw=128, logz=-900.70, remainder_fraction=100.0000%, Lmin=-869.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=5995, regioncalls=48384, ndraw=128, logz=-863.90, remainder_fraction=100.0000%, Lmin=-843.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=5995, regioncalls=48384, ndraw=128, logz=-739.95, remainder_fraction=100.0000%, Lmin=-720.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=5995, regioncalls=48384, ndraw=128, logz=-590.48, remainder_fraction=100.0000%, Lmin=-571.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=6087, regioncalls=48512, ndraw=128, logz=-461.16, remainder_fraction=100.0000%, Lmin=-440.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=6087, regioncalls=48512, ndraw=128, logz=-379.85, remainder_fraction=100.0000%, Lmin=-357.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=6087, regioncalls=48512, ndraw=128, logz=-362.86, remainder_fraction=100.0000%, Lmin=-337.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=6215, regioncalls=48896, ndraw=128, logz=-313.48, remainder_fraction=100.0000%, Lmin=-293.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=6215, regioncalls=48896, ndraw=128, logz=-262.54, remainder_fraction=100.0000%, Lmin=-244.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=6215, regioncalls=48896, ndraw=128, logz=-235.82, remainder_fraction=100.0000%, Lmin=-218.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=6215, regioncalls=48896, ndraw=128, logz=-218.72, remainder_fraction=100.0000%, Lmin=-199.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=6254, regioncalls=49536, ndraw=128, logz=-186.07, remainder_fraction=100.0000%, Lmin=-166.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=6410, regioncalls=50304, ndraw=128, logz=-163.79, remainder_fraction=100.0000%, Lmin=-144.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=6410, regioncalls=50304, ndraw=128, logz=-157.35, remainder_fraction=100.0000%, Lmin=-137.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=6410, regioncalls=50304, ndraw=128, logz=-130.32, remainder_fraction=100.0000%, Lmin=-110.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=6410, regioncalls=50304, ndraw=128, logz=-108.33, remainder_fraction=100.0000%, Lmin=-88.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=6528, regioncalls=50560, ndraw=128, logz=-91.69, remainder_fraction=100.0000%, Lmin=-73.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=6528, regioncalls=50560, ndraw=128, logz=-78.22, remainder_fraction=100.0000%, Lmin=-58.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=6528, regioncalls=50560, ndraw=128, logz=-74.92, remainder_fraction=100.0000%, Lmin=-56.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=6528, regioncalls=50560, ndraw=128, logz=-67.83, remainder_fraction=100.0000%, Lmin=-48.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=6640, regioncalls=50816, ndraw=128, logz=-59.68, remainder_fraction=100.0000%, Lmin=-41.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5580, ncalls=6640, regioncalls=50816, ndraw=128, logz=-56.20, remainder_fraction=100.0000%, Lmin=-38.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=6640, regioncalls=50816, ndraw=128, logz=-53.16, remainder_fraction=100.0000%, Lmin=-34.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=6755, regioncalls=51200, ndraw=128, logz=-47.03, remainder_fraction=100.0000%, Lmin=-28.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=6755, regioncalls=51200, ndraw=128, logz=-41.54, remainder_fraction=100.0000%, Lmin=-23.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=6852, regioncalls=51328, ndraw=128, logz=-37.89, remainder_fraction=100.0000%, Lmin=-20.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=6852, regioncalls=51328, ndraw=128, logz=-34.08, remainder_fraction=100.0000%, Lmin=-15.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=6977, regioncalls=51584, ndraw=128, logz=-30.92, remainder_fraction=100.0000%, Lmin=-13.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=6977, regioncalls=51584, ndraw=128, logz=-28.76, remainder_fraction=99.9997%, Lmin=-11.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=6977, regioncalls=51584, ndraw=128, logz=-26.91, remainder_fraction=99.9983%, Lmin=-9.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=7073, regioncalls=51712, ndraw=128, logz=-24.90, remainder_fraction=99.9876%, Lmin=-7.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=7073, regioncalls=51712, ndraw=128, logz=-24.18, remainder_fraction=99.9749%, Lmin=-6.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=7073, regioncalls=51712, ndraw=128, logz=-23.55, remainder_fraction=99.9526%, Lmin=-6.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=7184, regioncalls=52096, ndraw=128, logz=-22.37, remainder_fraction=99.8453%, Lmin=-4.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6030, ncalls=7184, regioncalls=52096, ndraw=128, logz=-21.55, remainder_fraction=99.6444%, Lmin=-4.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=7184, regioncalls=52096, ndraw=128, logz=-21.29, remainder_fraction=99.5447%, Lmin=-3.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=7299, regioncalls=52352, ndraw=128, logz=-20.42, remainder_fraction=98.9077%, Lmin=-3.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=7299, regioncalls=52352, ndraw=128, logz=-19.74, remainder_fraction=97.8310%, Lmin=-2.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=7299, regioncalls=52352, ndraw=128, logz=-19.19, remainder_fraction=96.2426%, Lmin=-2.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.71, remainder_fraction=93.9944%, Lmin=-1.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.61, remainder_fraction=93.3324%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.32, remainder_fraction=91.0625%, Lmin=-1.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=7422, regioncalls=53248, ndraw=128, logz=-17.98, remainder_fraction=87.4935%, Lmin=-1.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6300, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.82, remainder_fraction=85.3959%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.68, remainder_fraction=83.0994%, Lmin=-0.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.43, remainder_fraction=78.5133%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.28, remainder_fraction=74.8625%, Lmin=-0.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.23, remainder_fraction=73.6584%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=7684, regioncalls=54016, ndraw=128, logz=-17.06, remainder_fraction=68.8212%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=7684, regioncalls=54016, ndraw=128, logz=-16.91, remainder_fraction=64.1156%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.79, remainder_fraction=59.3193%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.68, remainder_fraction=54.7469%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6570, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.66, remainder_fraction=53.6018%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6600, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.59, remainder_fraction=50.2886%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6640, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.51, remainder_fraction=46.1265%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6660, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.47, remainder_fraction=44.1182%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6680, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.44, remainder_fraction=42.1888%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=7918, regioncalls=54784, ndraw=128, logz=-16.38, remainder_fraction=38.5249%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6750, ncalls=7951, regioncalls=55168, ndraw=128, logz=-16.34, remainder_fraction=35.9534%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6760, ncalls=7963, regioncalls=55424, ndraw=128, logz=-16.32, remainder_fraction=35.1382%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6800, ncalls=7999, regioncalls=55808, ndraw=128, logz=-16.28, remainder_fraction=32.0091%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6840, ncalls=8045, regioncalls=56448, ndraw=128, logz=-16.23, remainder_fraction=29.1078%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=8085, regioncalls=56960, ndraw=128, logz=-16.20, remainder_fraction=26.4548%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6920, ncalls=8131, regioncalls=57600, ndraw=128, logz=-16.17, remainder_fraction=24.0141%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6930, ncalls=8138, regioncalls=57728, ndraw=128, logz=-16.16, remainder_fraction=23.4390%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6960, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.14, remainder_fraction=21.7938%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7000, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.11, remainder_fraction=19.7631%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7020, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.10, remainder_fraction=18.8221%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.09, remainder_fraction=17.9210%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7080, ncalls=8313, regioncalls=58496, ndraw=128, logz=-16.07, remainder_fraction=16.2402%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7110, ncalls=8337, regioncalls=58880, ndraw=128, logz=-16.05, remainder_fraction=15.0830%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7120, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.05, remainder_fraction=14.7162%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7160, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.03, remainder_fraction=13.3321%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.02, remainder_fraction=12.0743%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7240, ncalls=8580, regioncalls=59520, ndraw=128, logz=-16.01, remainder_fraction=10.9343%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7280, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.99, remainder_fraction=9.8999%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7290, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.99, remainder_fraction=9.6570%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7320, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.98, remainder_fraction=8.9628%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.97, remainder_fraction=8.1140%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7400, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.97, remainder_fraction=7.3446%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7440, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.96, remainder_fraction=6.6475%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7470, ncalls=8786, regioncalls=59904, ndraw=128, logz=-15.95, remainder_fraction=6.1683%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7480, ncalls=8786, regioncalls=59904, ndraw=128, logz=-15.95, remainder_fraction=6.0163%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=8802, regioncalls=60288, ndraw=128, logz=-15.95, remainder_fraction=5.4447%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7560, ncalls=8853, regioncalls=60928, ndraw=128, logz=-15.94, remainder_fraction=4.9272%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7600, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.94, remainder_fraction=4.4589%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7640, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=4.0350%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7650, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=3.9354%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7680, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=3.6513%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-2e-07 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 9102 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -15.87 +- 0.1519 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1239.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.20 bs:0.15 tail:0.03 total:0.16 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-26372698294787.03, Lmax=-13.90 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-1027058.68, remainder_fraction=100.0000%, Lmin=-367803.47, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-60.45, remainder_fraction=100.0000%, Lmin=-50.38, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-29.28, remainder_fraction=99.9998%, Lmin=-21.93, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=631, regioncalls=256, ndraw=128, logz=-22.50, remainder_fraction=99.8222%, Lmin=-19.03, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=631, regioncalls=256, ndraw=128, logz=-20.69, remainder_fraction=98.9330%, Lmin=-17.74, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=631, regioncalls=256, ndraw=128, logz=-20.07, remainder_fraction=98.0088%, Lmin=-17.26, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=719, regioncalls=384, ndraw=128, logz=-19.63, remainder_fraction=96.8814%, Lmin=-17.08, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=719, regioncalls=384, ndraw=128, logz=-18.94, remainder_fraction=93.8205%, Lmin=-16.60, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=796, regioncalls=512, ndraw=128, logz=-18.48, remainder_fraction=90.2741%, Lmin=-16.43, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=867, regioncalls=640, ndraw=128, logz=-18.15, remainder_fraction=86.3264%, Lmin=-16.28, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=867, regioncalls=640, ndraw=128, logz=-17.89, remainder_fraction=82.3716%, Lmin=-16.18, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=936, regioncalls=768, ndraw=128, logz=-17.69, remainder_fraction=78.3963%, Lmin=-16.05, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=992, regioncalls=896, ndraw=128, logz=-17.51, remainder_fraction=74.4446%, Lmin=-15.95, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=992, regioncalls=896, ndraw=128, logz=-17.47, remainder_fraction=73.3637%, Lmin=-15.93, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1054, regioncalls=1024, ndraw=128, logz=-17.36, remainder_fraction=70.4213%, Lmin=-15.86, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1144, regioncalls=1280, ndraw=128, logz=-17.24, remainder_fraction=66.5149%, Lmin=-15.76, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1144, regioncalls=1280, ndraw=128, logz=-17.18, remainder_fraction=64.4159%, Lmin=-15.73, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1180, regioncalls=1408, ndraw=128, logz=-17.13, remainder_fraction=62.5174%, Lmin=-15.69, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1222, regioncalls=1536, ndraw=128, logz=-17.03, remainder_fraction=58.8842%, Lmin=-15.63, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1266, regioncalls=1664, ndraw=128, logz=-16.97, remainder_fraction=56.1143%, Lmin=-15.58, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1266, regioncalls=1664, ndraw=128, logz=-16.94, remainder_fraction=55.1073%, Lmin=-15.56, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1325, regioncalls=1920, ndraw=128, logz=-16.87, remainder_fraction=51.4374%, Lmin=-15.48, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1399, regioncalls=2176, ndraw=128, logz=-16.80, remainder_fraction=47.9747%, Lmin=-15.43, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1418, regioncalls=2304, ndraw=128, logz=-16.74, remainder_fraction=44.7173%, Lmin=-15.38, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1489, regioncalls=2688, ndraw=128, logz=-16.68, remainder_fraction=41.6710%, Lmin=-15.34, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1489, regioncalls=2688, ndraw=128, logz=-16.67, remainder_fraction=41.0579%, Lmin=-15.33, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1522, regioncalls=2944, ndraw=128, logz=-16.63, remainder_fraction=38.8517%, Lmin=-15.30, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1580, regioncalls=3328, ndraw=128, logz=-16.59, remainder_fraction=36.0139%, Lmin=-15.26, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1617, regioncalls=3584, ndraw=128, logz=-16.57, remainder_fraction=34.8946%, Lmin=-15.24, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1636, regioncalls=3712, ndraw=128, logz=-16.55, remainder_fraction=33.5674%, Lmin=-15.22, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1692, regioncalls=4096, ndraw=128, logz=-16.51, remainder_fraction=30.9724%, Lmin=-15.18, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1740, regioncalls=4480, ndraw=128, logz=-16.49, remainder_fraction=29.3425%, Lmin=-15.16, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1750, regioncalls=4608, ndraw=128, logz=-16.48, remainder_fraction=28.9446%, Lmin=-15.16, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1797, regioncalls=5248, ndraw=128, logz=-16.45, remainder_fraction=26.6418%, Lmin=-15.13, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1852, regioncalls=5888, ndraw=128, logz=-16.42, remainder_fraction=24.5757%, Lmin=-15.10, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1910, regioncalls=6656, ndraw=128, logz=-16.40, remainder_fraction=22.6763%, Lmin=-15.08, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1959, regioncalls=7424, ndraw=128, logz=-16.38, remainder_fraction=20.8360%, Lmin=-15.06, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1981, regioncalls=7680, ndraw=128, logz=-16.37, remainder_fraction=20.3949%, Lmin=-15.05, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2011, regioncalls=7936, ndraw=128, logz=-16.36, remainder_fraction=19.2763%, Lmin=-15.04, Lmax=-13.05 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2058, regioncalls=8704, ndraw=128, logz=-16.34, remainder_fraction=17.9343%, Lmin=-15.02, Lmax=-13.05 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2084, regioncalls=9088, ndraw=128, logz=-16.33, remainder_fraction=17.7076%, Lmin=-15.01, Lmax=-12.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2099, regioncalls=9472, ndraw=128, logz=-16.33, remainder_fraction=17.7135%, Lmin=-15.00, Lmax=-12.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2153, regioncalls=10624, ndraw=128, logz=-16.31, remainder_fraction=16.8556%, Lmin=-14.99, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2188, regioncalls=11392, ndraw=128, logz=-16.30, remainder_fraction=15.8899%, Lmin=-14.97, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2197, regioncalls=11648, ndraw=128, logz=-16.30, remainder_fraction=15.7189%, Lmin=-14.97, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2252, regioncalls=13056, ndraw=128, logz=-16.29, remainder_fraction=15.0393%, Lmin=-14.95, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2300, regioncalls=14208, ndraw=128, logz=-16.27, remainder_fraction=13.9593%, Lmin=-14.94, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2347, regioncalls=15872, ndraw=128, logz=-16.26, remainder_fraction=13.0329%, Lmin=-14.93, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2393, regioncalls=17280, ndraw=128, logz=-16.26, remainder_fraction=11.9868%, Lmin=-14.91, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2447, regioncalls=19328, ndraw=128, logz=-16.25, remainder_fraction=11.1844%, Lmin=-14.90, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2519, regioncalls=19840, ndraw=128, logz=-16.24, remainder_fraction=10.5107%, Lmin=-14.89, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2585, regioncalls=19968, ndraw=128, logz=-16.24, remainder_fraction=10.2179%, Lmin=-14.88, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2585, regioncalls=19968, ndraw=128, logz=-16.23, remainder_fraction=9.8265%, Lmin=-14.88, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.23, remainder_fraction=9.1364%, Lmin=-14.87, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.22, remainder_fraction=8.7569%, Lmin=-14.86, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.22, remainder_fraction=8.6061%, Lmin=-14.86, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2793, regioncalls=22272, ndraw=128, logz=-16.22, remainder_fraction=8.1162%, Lmin=-14.84, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2862, regioncalls=22400, ndraw=128, logz=-16.21, remainder_fraction=8.3709%, Lmin=-14.83, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2862, regioncalls=22400, ndraw=128, logz=-16.21, remainder_fraction=7.9819%, Lmin=-14.82, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2936, regioncalls=22528, ndraw=128, logz=-16.20, remainder_fraction=7.6070%, Lmin=-14.78, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2936, regioncalls=22528, ndraw=128, logz=-16.20, remainder_fraction=7.4659%, Lmin=-14.77, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3010, regioncalls=23168, ndraw=128, logz=-16.20, remainder_fraction=7.2276%, Lmin=-14.75, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.20, remainder_fraction=7.0091%, Lmin=-14.72, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.20, remainder_fraction=6.9076%, Lmin=-14.69, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.19, remainder_fraction=6.6638%, Lmin=-14.67, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3142, regioncalls=23552, ndraw=128, logz=-16.19, remainder_fraction=6.5265%, Lmin=-14.64, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3201, regioncalls=23680, ndraw=128, logz=-16.19, remainder_fraction=6.3636%, Lmin=-14.61, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3201, regioncalls=23680, ndraw=128, logz=-16.19, remainder_fraction=6.3383%, Lmin=-14.59, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3301, regioncalls=25216, ndraw=128, logz=-16.19, remainder_fraction=6.1060%, Lmin=-14.50, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3301, regioncalls=25216, ndraw=128, logz=-16.18, remainder_fraction=5.9113%, Lmin=-14.43, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3363, regioncalls=25472, ndraw=128, logz=-16.18, remainder_fraction=5.7821%, Lmin=-14.37, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3430, regioncalls=25600, ndraw=128, logz=-16.18, remainder_fraction=5.4850%, Lmin=-14.28, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3430, regioncalls=25600, ndraw=128, logz=-16.18, remainder_fraction=5.4465%, Lmin=-14.27, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3504, regioncalls=25856, ndraw=128, logz=-16.18, remainder_fraction=5.3598%, Lmin=-14.20, Lmax=-11.50 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.0849%, Lmin=-14.12, Lmax=-11.50 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.1115%, Lmin=-14.09, Lmax=-11.30 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.1050%, Lmin=-14.06, Lmax=-11.30 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3679, regioncalls=26624, ndraw=128, logz=-16.17, remainder_fraction=4.9120%, Lmin=-14.00, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3679, regioncalls=26624, ndraw=128, logz=-16.17, remainder_fraction=4.8491%, Lmin=-13.97, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3766, regioncalls=27264, ndraw=128, logz=-16.17, remainder_fraction=4.8425%, Lmin=-13.96, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3766, regioncalls=27264, ndraw=128, logz=-16.16, remainder_fraction=4.6542%, Lmin=-13.91, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3857, regioncalls=27392, ndraw=128, logz=-16.16, remainder_fraction=4.4993%, Lmin=-13.85, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3857, regioncalls=27392, ndraw=128, logz=-16.16, remainder_fraction=4.3184%, Lmin=-13.80, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3935, regioncalls=27520, ndraw=128, logz=-16.16, remainder_fraction=4.1650%, Lmin=-13.75, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3935, regioncalls=27520, ndraw=128, logz=-16.16, remainder_fraction=4.1110%, Lmin=-13.73, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4033, regioncalls=27904, ndraw=128, logz=-16.16, remainder_fraction=3.9877%, Lmin=-13.70, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4033, regioncalls=27904, ndraw=128, logz=-16.16, remainder_fraction=3.8082%, Lmin=-13.66, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=4123, regioncalls=28032, ndraw=128, logz=-16.16, remainder_fraction=3.7535%, Lmin=-13.63, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4123, regioncalls=28032, ndraw=128, logz=-16.15, remainder_fraction=3.6973%, Lmin=-13.61, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.5760%, Lmin=-13.54, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.4688%, Lmin=-13.45, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.4510%, Lmin=-13.42, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4264, regioncalls=29312, ndraw=128, logz=-16.15, remainder_fraction=3.3256%, Lmin=-13.29, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4319, regioncalls=30336, ndraw=128, logz=-16.15, remainder_fraction=3.2426%, Lmin=-13.17, Lmax=-11.16 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4395, regioncalls=31616, ndraw=128, logz=-16.15, remainder_fraction=3.0915%, Lmin=-13.05, Lmax=-10.83 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4448, regioncalls=32768, ndraw=128, logz=-16.15, remainder_fraction=2.9927%, Lmin=-12.98, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4461, regioncalls=33024, ndraw=128, logz=-16.15, remainder_fraction=2.9557%, Lmin=-12.96, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4573, regioncalls=33280, ndraw=128, logz=-16.14, remainder_fraction=2.8380%, Lmin=-12.90, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4573, regioncalls=33280, ndraw=128, logz=-16.14, remainder_fraction=2.7163%, Lmin=-12.81, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.6739%, Lmin=-12.76, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.6039%, Lmin=-12.71, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.4925%, Lmin=-12.62, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4783, regioncalls=33664, ndraw=128, logz=-16.14, remainder_fraction=2.3941%, Lmin=-12.56, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4783, regioncalls=33664, ndraw=128, logz=-16.14, remainder_fraction=2.3535%, Lmin=-12.53, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4807, regioncalls=34176, ndraw=128, logz=-16.14, remainder_fraction=2.2115%, Lmin=-12.47, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4864, regioncalls=35200, ndraw=128, logz=-16.14, remainder_fraction=2.1043%, Lmin=-12.40, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4963, regioncalls=35584, ndraw=128, logz=-16.13, remainder_fraction=1.9696%, Lmin=-12.34, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4963, regioncalls=35584, ndraw=128, logz=-16.13, remainder_fraction=1.8382%, Lmin=-12.28, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5070, regioncalls=35712, ndraw=128, logz=-16.13, remainder_fraction=1.8081%, Lmin=-12.26, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5070, regioncalls=35712, ndraw=128, logz=-16.13, remainder_fraction=1.7309%, Lmin=-12.19, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5082, regioncalls=36096, ndraw=128, logz=-16.13, remainder_fraction=1.6023%, Lmin=-12.11, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5139, regioncalls=37248, ndraw=128, logz=-16.13, remainder_fraction=1.5003%, Lmin=-12.06, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=5205, regioncalls=38272, ndraw=128, logz=-16.13, remainder_fraction=1.4310%, Lmin=-12.02, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=5258, regioncalls=39168, ndraw=128, logz=-16.13, remainder_fraction=1.3744%, Lmin=-11.98, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=5320, regioncalls=40448, ndraw=128, logz=-16.13, remainder_fraction=1.2919%, Lmin=-11.94, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5373, regioncalls=41728, ndraw=128, logz=-16.13, remainder_fraction=1.2086%, Lmin=-11.90, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=5436, regioncalls=43264, ndraw=128, logz=-16.13, remainder_fraction=1.1708%, Lmin=-11.87, Lmax=-10.07 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=5487, regioncalls=44416, ndraw=128, logz=-16.12, remainder_fraction=1.1240%, Lmin=-11.83, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.1193%, Lmin=-11.83, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.0971%, Lmin=-11.81, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.0474%, Lmin=-11.78, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3780, ncalls=5700, regioncalls=45184, ndraw=128, logz=-16.12, remainder_fraction=1.0309%, Lmin=-11.77, Lmax=-9.95 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5700, regioncalls=45184, ndraw=128, logz=-16.12, remainder_fraction=1.0082%, Lmin=-11.75, Lmax=-9.95 INFO ultranest:integrator.py:2654 Explored until L=-1e+01 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5700 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -16.1 +- 0.031 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1540.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.04 bs:0.03 tail:0.01 total:0.03 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-14849705163238.41, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-12164310.70, remainder_fraction=100.0000%, Lmin=-12150372.90, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-652.11, remainder_fraction=100.0000%, Lmin=-620.56, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-56.81, remainder_fraction=100.0000%, Lmin=-49.94, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=632, regioncalls=256, ndraw=128, logz=-26.15, remainder_fraction=99.9952%, Lmin=-21.82, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=632, regioncalls=256, ndraw=128, logz=-22.12, remainder_fraction=99.7343%, Lmin=-18.83, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=632, regioncalls=256, ndraw=128, logz=-21.38, remainder_fraction=99.4416%, Lmin=-18.34, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=715, regioncalls=384, ndraw=128, logz=-20.80, remainder_fraction=98.9965%, Lmin=-17.96, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=715, regioncalls=384, ndraw=128, logz=-19.97, remainder_fraction=97.6888%, Lmin=-17.37, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=791, regioncalls=512, ndraw=128, logz=-19.34, remainder_fraction=95.6112%, Lmin=-16.92, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=791, regioncalls=512, ndraw=128, logz=-18.84, remainder_fraction=92.8123%, Lmin=-16.54, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=856, regioncalls=640, ndraw=128, logz=-18.45, remainder_fraction=89.3711%, Lmin=-16.31, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=918, regioncalls=768, ndraw=128, logz=-18.14, remainder_fraction=85.5446%, Lmin=-16.13, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=979, regioncalls=896, ndraw=128, logz=-17.90, remainder_fraction=81.2828%, Lmin=-16.00, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1031, regioncalls=1024, ndraw=128, logz=-17.69, remainder_fraction=76.9481%, Lmin=-15.83, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1076, regioncalls=1152, ndraw=128, logz=-17.51, remainder_fraction=72.4432%, Lmin=-15.73, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1076, regioncalls=1152, ndraw=128, logz=-17.44, remainder_fraction=70.4491%, Lmin=-15.69, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1112, regioncalls=1280, ndraw=128, logz=-17.36, remainder_fraction=68.6035%, Lmin=-15.65, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1186, regioncalls=1536, ndraw=128, logz=-17.24, remainder_fraction=64.3482%, Lmin=-15.59, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1227, regioncalls=1664, ndraw=128, logz=-17.13, remainder_fraction=60.1018%, Lmin=-15.54, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1287, regioncalls=1920, ndraw=128, logz=-17.04, remainder_fraction=56.1766%, Lmin=-15.48, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1339, regioncalls=2176, ndraw=128, logz=-16.96, remainder_fraction=52.3925%, Lmin=-15.42, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1416, regioncalls=2560, ndraw=128, logz=-16.88, remainder_fraction=48.5818%, Lmin=-15.35, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1471, regioncalls=2816, ndraw=128, logz=-16.82, remainder_fraction=45.2266%, Lmin=-15.31, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1493, regioncalls=2944, ndraw=128, logz=-16.80, remainder_fraction=44.3521%, Lmin=-15.30, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1556, regioncalls=3328, ndraw=128, logz=-16.76, remainder_fraction=42.0094%, Lmin=-15.28, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1606, regioncalls=3712, ndraw=128, logz=-16.71, remainder_fraction=38.8738%, Lmin=-15.23, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1619, regioncalls=3840, ndraw=128, logz=-16.68, remainder_fraction=37.3284%, Lmin=-15.21, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1643, regioncalls=4224, ndraw=128, logz=-16.66, remainder_fraction=35.9391%, Lmin=-15.20, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1708, regioncalls=4736, ndraw=128, logz=-16.62, remainder_fraction=33.2899%, Lmin=-15.17, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1762, regioncalls=5248, ndraw=128, logz=-16.58, remainder_fraction=30.8116%, Lmin=-15.14, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1807, regioncalls=5760, ndraw=128, logz=-16.55, remainder_fraction=28.3777%, Lmin=-15.11, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1868, regioncalls=6528, ndraw=128, logz=-16.52, remainder_fraction=26.0772%, Lmin=-15.08, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1916, regioncalls=7168, ndraw=128, logz=-16.49, remainder_fraction=23.9965%, Lmin=-15.06, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1974, regioncalls=8064, ndraw=128, logz=-16.47, remainder_fraction=22.1263%, Lmin=-15.03, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1984, regioncalls=8192, ndraw=128, logz=-16.46, remainder_fraction=21.6256%, Lmin=-15.03, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2027, regioncalls=8832, ndraw=128, logz=-16.45, remainder_fraction=20.4266%, Lmin=-15.02, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2080, regioncalls=9728, ndraw=128, logz=-16.43, remainder_fraction=18.8390%, Lmin=-15.00, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2108, regioncalls=10240, ndraw=128, logz=-16.42, remainder_fraction=18.0867%, Lmin=-14.99, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2137, regioncalls=10752, ndraw=128, logz=-16.41, remainder_fraction=17.4153%, Lmin=-14.98, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2184, regioncalls=11776, ndraw=128, logz=-16.39, remainder_fraction=16.1452%, Lmin=-14.97, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2232, regioncalls=13056, ndraw=128, logz=-16.38, remainder_fraction=15.3566%, Lmin=-14.96, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2249, regioncalls=13440, ndraw=128, logz=-16.38, remainder_fraction=15.0174%, Lmin=-14.95, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2300, regioncalls=14592, ndraw=128, logz=-16.37, remainder_fraction=13.9140%, Lmin=-14.94, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2361, regioncalls=16000, ndraw=128, logz=-16.35, remainder_fraction=12.9170%, Lmin=-14.93, Lmax=-13.36 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2412, regioncalls=17792, ndraw=128, logz=-16.34, remainder_fraction=12.1141%, Lmin=-14.92, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2476, regioncalls=19840, ndraw=128, logz=-16.33, remainder_fraction=11.1146%, Lmin=-14.91, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2490, regioncalls=20096, ndraw=128, logz=-16.33, remainder_fraction=10.9083%, Lmin=-14.90, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2532, regioncalls=21888, ndraw=128, logz=-16.33, remainder_fraction=10.3378%, Lmin=-14.90, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2618, regioncalls=22272, ndraw=128, logz=-16.32, remainder_fraction=9.5622%, Lmin=-14.89, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2618, regioncalls=22272, ndraw=128, logz=-16.31, remainder_fraction=9.3973%, Lmin=-14.88, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2644, regioncalls=23680, ndraw=128, logz=-16.31, remainder_fraction=9.3884%, Lmin=-14.88, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2748, regioncalls=24832, ndraw=128, logz=-16.30, remainder_fraction=8.7230%, Lmin=-14.87, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2748, regioncalls=24832, ndraw=128, logz=-16.30, remainder_fraction=8.2577%, Lmin=-14.86, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2759, regioncalls=25472, ndraw=128, logz=-16.30, remainder_fraction=8.0916%, Lmin=-14.86, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2832, regioncalls=25984, ndraw=128, logz=-16.29, remainder_fraction=7.7817%, Lmin=-14.85, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2881, regioncalls=26112, ndraw=128, logz=-16.29, remainder_fraction=7.3639%, Lmin=-14.84, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2932, regioncalls=26240, ndraw=128, logz=-16.28, remainder_fraction=6.9211%, Lmin=-14.83, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2986, regioncalls=26368, ndraw=128, logz=-16.28, remainder_fraction=6.7286%, Lmin=-14.80, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=3026, regioncalls=26496, ndraw=128, logz=-16.28, remainder_fraction=6.6216%, Lmin=-14.79, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3035, regioncalls=27264, ndraw=128, logz=-16.27, remainder_fraction=6.4277%, Lmin=-14.77, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3089, regioncalls=28288, ndraw=128, logz=-16.27, remainder_fraction=6.2005%, Lmin=-14.74, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3138, regioncalls=29056, ndraw=128, logz=-16.27, remainder_fraction=6.0162%, Lmin=-14.70, Lmax=-12.11 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3198, regioncalls=29952, ndraw=128, logz=-16.26, remainder_fraction=5.8900%, Lmin=-14.66, Lmax=-12.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3238, regioncalls=30592, ndraw=128, logz=-16.26, remainder_fraction=5.8281%, Lmin=-14.64, Lmax=-12.01 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3332, regioncalls=31104, ndraw=128, logz=-16.26, remainder_fraction=5.9317%, Lmin=-14.63, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3332, regioncalls=31104, ndraw=128, logz=-16.26, remainder_fraction=5.6781%, Lmin=-14.58, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3418, regioncalls=31232, ndraw=128, logz=-16.26, remainder_fraction=5.5063%, Lmin=-14.50, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3418, regioncalls=31232, ndraw=128, logz=-16.25, remainder_fraction=5.3221%, Lmin=-14.43, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3505, regioncalls=31360, ndraw=128, logz=-16.25, remainder_fraction=5.1279%, Lmin=-14.37, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3505, regioncalls=31360, ndraw=128, logz=-16.25, remainder_fraction=5.0507%, Lmin=-14.35, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3534, regioncalls=32256, ndraw=128, logz=-16.25, remainder_fraction=4.9457%, Lmin=-14.29, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3587, regioncalls=33152, ndraw=128, logz=-16.25, remainder_fraction=4.6605%, Lmin=-14.20, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3618, regioncalls=33664, ndraw=128, logz=-16.25, remainder_fraction=4.5307%, Lmin=-14.18, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3638, regioncalls=34176, ndraw=128, logz=-16.24, remainder_fraction=4.4758%, Lmin=-14.16, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3687, regioncalls=34944, ndraw=128, logz=-16.24, remainder_fraction=4.3247%, Lmin=-14.09, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.2249%, Lmin=-14.05, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.1912%, Lmin=-14.02, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.0032%, Lmin=-13.96, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3877, regioncalls=36096, ndraw=128, logz=-16.24, remainder_fraction=3.8561%, Lmin=-13.91, Lmax=-11.71 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3898, regioncalls=36608, ndraw=128, logz=-16.23, remainder_fraction=3.7150%, Lmin=-13.86, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3950, regioncalls=37632, ndraw=128, logz=-16.23, remainder_fraction=3.5438%, Lmin=-13.82, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4004, regioncalls=38656, ndraw=128, logz=-16.23, remainder_fraction=3.3672%, Lmin=-13.77, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4063, regioncalls=39936, ndraw=128, logz=-16.23, remainder_fraction=3.1812%, Lmin=-13.73, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4127, regioncalls=41216, ndraw=128, logz=-16.23, remainder_fraction=3.0476%, Lmin=-13.68, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=4182, regioncalls=42368, ndraw=128, logz=-16.23, remainder_fraction=2.9796%, Lmin=-13.65, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=4235, regioncalls=43648, ndraw=128, logz=-16.23, remainder_fraction=2.8709%, Lmin=-13.61, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4307, regioncalls=43904, ndraw=128, logz=-16.23, remainder_fraction=2.8404%, Lmin=-13.60, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4307, regioncalls=43904, ndraw=128, logz=-16.22, remainder_fraction=2.7205%, Lmin=-13.56, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4374, regioncalls=44032, ndraw=128, logz=-16.22, remainder_fraction=2.6810%, Lmin=-13.49, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4432, regioncalls=44160, ndraw=128, logz=-16.22, remainder_fraction=2.5938%, Lmin=-13.38, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4486, regioncalls=44288, ndraw=128, logz=-16.22, remainder_fraction=2.4867%, Lmin=-13.27, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4486, regioncalls=44288, ndraw=128, logz=-16.22, remainder_fraction=2.4569%, Lmin=-13.24, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4523, regioncalls=44928, ndraw=128, logz=-16.22, remainder_fraction=2.3929%, Lmin=-13.16, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4574, regioncalls=45824, ndraw=128, logz=-16.22, remainder_fraction=2.2842%, Lmin=-13.06, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=4600, regioncalls=46208, ndraw=128, logz=-16.22, remainder_fraction=2.2311%, Lmin=-13.01, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4698, regioncalls=46464, ndraw=128, logz=-16.22, remainder_fraction=2.1599%, Lmin=-12.97, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4698, regioncalls=46464, ndraw=128, logz=-16.22, remainder_fraction=2.0496%, Lmin=-12.87, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4780, regioncalls=46592, ndraw=128, logz=-16.21, remainder_fraction=1.9867%, Lmin=-12.80, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4780, regioncalls=46592, ndraw=128, logz=-16.21, remainder_fraction=1.9626%, Lmin=-12.78, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4869, regioncalls=46976, ndraw=128, logz=-16.21, remainder_fraction=1.8622%, Lmin=-12.70, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4869, regioncalls=46976, ndraw=128, logz=-16.21, remainder_fraction=1.7643%, Lmin=-12.62, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4948, regioncalls=47104, ndraw=128, logz=-16.21, remainder_fraction=1.6724%, Lmin=-12.54, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=5013, regioncalls=47232, ndraw=128, logz=-16.21, remainder_fraction=1.5873%, Lmin=-12.49, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5013, regioncalls=47232, ndraw=128, logz=-16.21, remainder_fraction=1.5607%, Lmin=-12.48, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.5019%, Lmin=-12.43, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.4067%, Lmin=-12.37, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.3564%, Lmin=-12.35, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5235, regioncalls=47744, ndraw=128, logz=-16.21, remainder_fraction=1.3057%, Lmin=-12.32, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=5235, regioncalls=47744, ndraw=128, logz=-16.21, remainder_fraction=1.2195%, Lmin=-12.27, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.21, remainder_fraction=1.1632%, Lmin=-12.22, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.21, remainder_fraction=1.1480%, Lmin=-12.21, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.20, remainder_fraction=1.0796%, Lmin=-12.17, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5456, regioncalls=48256, ndraw=128, logz=-16.20, remainder_fraction=1.0066%, Lmin=-12.12, Lmax=-10.94 INFO ultranest:integrator.py:2654 Explored until L=-1e+01 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5456 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -16.18 +- 0.03606 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1474.1, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.04, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.04 bs:0.04 tail:0.01 total:0.04 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-27067381821958.52, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-3316105.24, remainder_fraction=100.0000%, Lmin=-2597981.55, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-502426.97, remainder_fraction=100.0000%, Lmin=-502376.73, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-502236.71, remainder_fraction=100.0000%, Lmin=-502117.19, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=638, regioncalls=256, ndraw=128, logz=-501645.16, remainder_fraction=100.0000%, Lmin=-501629.49, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=638, regioncalls=256, ndraw=128, logz=-501135.84, remainder_fraction=100.0000%, Lmin=-501121.91, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=732, regioncalls=384, ndraw=128, logz=-500731.08, remainder_fraction=100.0000%, Lmin=-500719.78, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=732, regioncalls=384, ndraw=128, logz=-500420.99, remainder_fraction=100.0000%, Lmin=-500412.11, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=813, regioncalls=512, ndraw=128, logz=-500230.25, remainder_fraction=100.0000%, Lmin=-500222.16, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=813, regioncalls=512, ndraw=128, logz=-500174.08, remainder_fraction=100.0000%, Lmin=-500165.75, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=873, regioncalls=640, ndraw=128, logz=-499905.42, remainder_fraction=100.0000%, Lmin=-499898.07, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=873, regioncalls=640, ndraw=128, logz=-499684.35, remainder_fraction=100.0000%, Lmin=-499674.47, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=933, regioncalls=768, ndraw=128, logz=-499526.78, remainder_fraction=100.0000%, Lmin=-499518.11, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=990, regioncalls=896, ndraw=128, logz=-499362.75, remainder_fraction=100.0000%, Lmin=-499354.40, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=990, regioncalls=896, ndraw=128, logz=-499346.06, remainder_fraction=100.0000%, Lmin=-499339.33, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1045, regioncalls=1024, ndraw=128, logz=-499217.19, remainder_fraction=100.0000%, Lmin=-499205.12, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1088, regioncalls=1152, ndraw=128, logz=-499029.69, remainder_fraction=100.0000%, Lmin=-499014.37, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1088, regioncalls=1152, ndraw=128, logz=-498940.90, remainder_fraction=100.0000%, Lmin=-498931.16, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1123, regioncalls=1280, ndraw=128, logz=-498843.83, remainder_fraction=100.0000%, Lmin=-498836.53, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1196, regioncalls=1536, ndraw=128, logz=-498726.86, remainder_fraction=100.0000%, Lmin=-498713.18, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1226, regioncalls=1664, ndraw=128, logz=-498594.27, remainder_fraction=100.0000%, Lmin=-498580.76, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1251, regioncalls=1792, ndraw=128, logz=-498550.78, remainder_fraction=100.0000%, Lmin=-498542.58, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1287, regioncalls=1920, ndraw=128, logz=-498370.73, remainder_fraction=100.0000%, Lmin=-498363.17, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1337, regioncalls=2176, ndraw=128, logz=-498250.23, remainder_fraction=100.0000%, Lmin=-498237.06, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1401, regioncalls=2432, ndraw=128, logz=-498145.05, remainder_fraction=100.0000%, Lmin=-498133.69, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1437, regioncalls=2688, ndraw=128, logz=-497991.53, remainder_fraction=100.0000%, Lmin=-497972.61, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1455, regioncalls=2816, ndraw=128, logz=-497947.39, remainder_fraction=100.0000%, Lmin=-497935.76, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1494, regioncalls=3072, ndraw=128, logz=-497859.26, remainder_fraction=100.0000%, Lmin=-497841.61, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1527, regioncalls=3328, ndraw=128, logz=-497720.07, remainder_fraction=100.0000%, Lmin=-497704.25, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1559, regioncalls=3584, ndraw=128, logz=-497633.20, remainder_fraction=100.0000%, Lmin=-497620.88, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1591, regioncalls=3840, ndraw=128, logz=-497569.29, remainder_fraction=100.0000%, Lmin=-497559.10, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1641, regioncalls=4224, ndraw=128, logz=-497435.38, remainder_fraction=100.0000%, Lmin=-497425.78, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1693, regioncalls=4736, ndraw=128, logz=-497308.03, remainder_fraction=100.0000%, Lmin=-497298.81, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1704, regioncalls=4864, ndraw=128, logz=-497280.99, remainder_fraction=100.0000%, Lmin=-497265.98, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1752, regioncalls=5376, ndraw=128, logz=-497120.48, remainder_fraction=100.0000%, Lmin=-497110.05, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1809, regioncalls=6144, ndraw=128, logz=-496991.53, remainder_fraction=100.0000%, Lmin=-496980.01, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1860, regioncalls=6784, ndraw=128, logz=-496828.38, remainder_fraction=100.0000%, Lmin=-496818.80, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1906, regioncalls=7296, ndraw=128, logz=-496597.66, remainder_fraction=100.0000%, Lmin=-496588.52, Lmax=-229.19 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1959, regioncalls=8064, ndraw=128, logz=-495915.27, remainder_fraction=100.0000%, Lmin=-495883.80, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2018, regioncalls=9088, ndraw=128, logz=-493922.82, remainder_fraction=100.0000%, Lmin=-493845.25, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2050, regioncalls=9472, ndraw=128, logz=-492888.69, remainder_fraction=100.0000%, Lmin=-492837.70, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2080, regioncalls=9984, ndraw=128, logz=-491534.02, remainder_fraction=100.0000%, Lmin=-491486.25, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2130, regioncalls=10880, ndraw=128, logz=-487814.63, remainder_fraction=100.0000%, Lmin=-487578.52, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2180, regioncalls=11776, ndraw=128, logz=-479047.95, remainder_fraction=100.0000%, Lmin=-478730.51, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2236, regioncalls=13568, ndraw=128, logz=-467590.29, remainder_fraction=100.0000%, Lmin=-467197.20, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2304, regioncalls=14592, ndraw=128, logz=-458117.57, remainder_fraction=100.0000%, Lmin=-458097.65, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2347, regioncalls=16000, ndraw=128, logz=-446788.79, remainder_fraction=100.0000%, Lmin=-446452.99, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2408, regioncalls=17920, ndraw=128, logz=-430727.37, remainder_fraction=100.0000%, Lmin=-430448.72, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2458, regioncalls=19968, ndraw=128, logz=-413498.20, remainder_fraction=100.0000%, Lmin=-413026.67, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2521, regioncalls=22272, ndraw=128, logz=-379384.75, remainder_fraction=100.0000%, Lmin=-378797.67, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2555, regioncalls=23424, ndraw=128, logz=-367175.35, remainder_fraction=100.0000%, Lmin=-366497.90, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2592, regioncalls=24832, ndraw=128, logz=-347124.34, remainder_fraction=100.0000%, Lmin=-346275.59, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2660, regioncalls=27648, ndraw=128, logz=-315360.05, remainder_fraction=100.0000%, Lmin=-315266.06, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2712, regioncalls=30080, ndraw=128, logz=-288095.70, remainder_fraction=100.0000%, Lmin=-287308.57, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2726, regioncalls=31232, ndraw=128, logz=-283381.27, remainder_fraction=100.0000%, Lmin=-279597.31, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2834, regioncalls=33024, ndraw=128, logz=-251538.82, remainder_fraction=100.0000%, Lmin=-249847.19, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2906, regioncalls=33152, ndraw=128, logz=-224651.30, remainder_fraction=100.0000%, Lmin=-224588.99, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2971, regioncalls=33280, ndraw=128, logz=-198168.36, remainder_fraction=100.0000%, Lmin=-197940.18, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=3030, regioncalls=33408, ndraw=128, logz=-178248.87, remainder_fraction=100.0000%, Lmin=-178172.53, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3088, regioncalls=33536, ndraw=128, logz=-154606.93, remainder_fraction=100.0000%, Lmin=-154562.77, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3197, regioncalls=33792, ndraw=128, logz=-134803.42, remainder_fraction=100.0000%, Lmin=-134078.66, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3248, regioncalls=33920, ndraw=128, logz=-118050.81, remainder_fraction=100.0000%, Lmin=-117828.10, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3366, regioncalls=34304, ndraw=128, logz=-106216.80, remainder_fraction=100.0000%, Lmin=-105342.65, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3485, regioncalls=34688, ndraw=128, logz=-92006.08, remainder_fraction=100.0000%, Lmin=-91832.14, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3572, regioncalls=34944, ndraw=128, logz=-77698.21, remainder_fraction=100.0000%, Lmin=-77294.92, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3683, regioncalls=35328, ndraw=128, logz=-66119.00, remainder_fraction=100.0000%, Lmin=-65995.65, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3758, regioncalls=35584, ndraw=128, logz=-56368.32, remainder_fraction=100.0000%, Lmin=-56336.47, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3888, regioncalls=35968, ndraw=128, logz=-48186.79, remainder_fraction=100.0000%, Lmin=-47662.68, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=4025, regioncalls=36480, ndraw=128, logz=-41627.75, remainder_fraction=100.0000%, Lmin=-41542.91, Lmax=-8.41 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=4158, regioncalls=36992, ndraw=128, logz=-34854.93, remainder_fraction=100.0000%, Lmin=-34438.03, Lmax=-8.41 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=4212, regioncalls=37376, ndraw=128, logz=-32311.38, remainder_fraction=100.0000%, Lmin=-32244.02, Lmax=-7.88 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=4275, regioncalls=39552, ndraw=128, logz=-29883.30, remainder_fraction=100.0000%, Lmin=-29757.69, Lmax=-7.88 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=4378, regioncalls=39936, ndraw=128, logz=-25256.57, remainder_fraction=100.0000%, Lmin=-25242.32, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=4463, regioncalls=40320, ndraw=128, logz=-20762.80, remainder_fraction=100.0000%, Lmin=-20722.55, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=4621, regioncalls=40960, ndraw=128, logz=-17778.12, remainder_fraction=100.0000%, Lmin=-17743.47, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=4763, regioncalls=41600, ndraw=128, logz=-15116.35, remainder_fraction=100.0000%, Lmin=-15054.41, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=4903, regioncalls=42368, ndraw=128, logz=-12610.82, remainder_fraction=100.0000%, Lmin=-12579.89, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=5035, regioncalls=43008, ndraw=128, logz=-10184.21, remainder_fraction=100.0000%, Lmin=-10150.09, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=5178, regioncalls=43776, ndraw=128, logz=-8631.74, remainder_fraction=100.0000%, Lmin=-8602.91, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=5384, regioncalls=45056, ndraw=128, logz=-7251.27, remainder_fraction=100.0000%, Lmin=-7217.86, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=5503, regioncalls=45952, ndraw=128, logz=-5986.16, remainder_fraction=100.0000%, Lmin=-5967.35, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=5644, regioncalls=47232, ndraw=128, logz=-4915.26, remainder_fraction=100.0000%, Lmin=-4874.76, Lmax=-7.30 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([389, 10, 1])) DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5795, regioncalls=48640, ndraw=128, logz=-3981.64, remainder_fraction=100.0000%, Lmin=-3924.82, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=5921, regioncalls=49920, ndraw=128, logz=-3159.55, remainder_fraction=100.0000%, Lmin=-3140.75, Lmax=-5.20 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([388, 11, 1])) DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=6090, regioncalls=51712, ndraw=128, logz=-2626.72, remainder_fraction=100.0000%, Lmin=-2605.14, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=6213, regioncalls=53376, ndraw=128, logz=-2250.49, remainder_fraction=100.0000%, Lmin=-2196.70, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=6341, regioncalls=55296, ndraw=128, logz=-1854.86, remainder_fraction=100.0000%, Lmin=-1817.78, Lmax=-5.20 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=6475, regioncalls=57472, ndraw=128, logz=-1554.06, remainder_fraction=100.0000%, Lmin=-1539.31, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=6598, regioncalls=59904, ndraw=128, logz=-1353.42, remainder_fraction=100.0000%, Lmin=-1332.34, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=6663, regioncalls=61312, ndraw=128, logz=-1194.80, remainder_fraction=100.0000%, Lmin=-1163.63, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=6717, regioncalls=62592, ndraw=128, logz=-1066.69, remainder_fraction=100.0000%, Lmin=-1041.75, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=6850, regioncalls=65408, ndraw=128, logz=-875.97, remainder_fraction=100.0000%, Lmin=-855.57, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=6928, regioncalls=67072, ndraw=128, logz=-732.00, remainder_fraction=100.0000%, Lmin=-712.71, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=6952, regioncalls=70272, ndraw=128, logz=-689.53, remainder_fraction=100.0000%, Lmin=-670.52, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=7038, regioncalls=78976, ndraw=128, logz=-563.92, remainder_fraction=100.0000%, Lmin=-541.75, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=7131, regioncalls=87424, ndraw=128, logz=-459.16, remainder_fraction=100.0000%, Lmin=-445.06, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=7228, regioncalls=98816, ndraw=128, logz=-367.03, remainder_fraction=100.0000%, Lmin=-350.86, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=7336, regioncalls=115200, ndraw=128, logz=-320.34, remainder_fraction=100.0000%, Lmin=-306.59, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3358, ncalls=7426, regioncalls=127872, ndraw=128, logz=-274.37, remainder_fraction=100.0000%, Lmin=-259.98, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=7432, regioncalls=128640, ndraw=128, logz=-272.39, remainder_fraction=100.0000%, Lmin=-257.69, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=7539, regioncalls=146432, ndraw=128, logz=-233.72, remainder_fraction=100.0000%, Lmin=-219.11, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3434, ncalls=7631, regioncalls=160512, ndraw=128, logz=-204.44, remainder_fraction=100.0000%, Lmin=-189.73, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=7647, regioncalls=162432, ndraw=128, logz=-201.29, remainder_fraction=100.0000%, Lmin=-186.33, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=7725, regioncalls=176512, ndraw=128, logz=-167.95, remainder_fraction=100.0000%, Lmin=-152.98, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=7807, regioncalls=193152, ndraw=128, logz=-147.78, remainder_fraction=100.0000%, Lmin=-134.01, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=7826, regioncalls=198144, ndraw=128, logz=-142.17, remainder_fraction=100.0000%, Lmin=-128.00, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3555, ncalls=7898, regioncalls=221568, ndraw=128, logz=-125.08, remainder_fraction=100.0000%, Lmin=-108.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=7908, regioncalls=224128, ndraw=128, logz=-118.71, remainder_fraction=100.0000%, Lmin=-104.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3599, ncalls=8022, regioncalls=249856, ndraw=128, logz=-100.41, remainder_fraction=100.0000%, Lmin=-86.29, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=8025, regioncalls=251136, ndraw=128, logz=-100.06, remainder_fraction=100.0000%, Lmin=-85.86, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3632, ncalls=8103, regioncalls=278272, ndraw=128, logz=-89.63, remainder_fraction=100.0000%, Lmin=-74.63, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=8122, regioncalls=284416, ndraw=128, logz=-86.46, remainder_fraction=100.0000%, Lmin=-72.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3666, ncalls=8218, regioncalls=310144, ndraw=128, logz=-76.89, remainder_fraction=100.0000%, Lmin=-63.03, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=8257, regioncalls=321280, ndraw=128, logz=-73.17, remainder_fraction=100.0000%, Lmin=-59.46, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3700, ncalls=8304, regioncalls=339840, ndraw=128, logz=-68.15, remainder_fraction=100.0000%, Lmin=-54.31, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=8358, regioncalls=357888, ndraw=128, logz=-62.69, remainder_fraction=100.0000%, Lmin=-48.99, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3753, ncalls=8449, regioncalls=382848, ndraw=128, logz=-57.13, remainder_fraction=100.0000%, Lmin=-43.96, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=8483, regioncalls=392960, ndraw=128, logz=-55.79, remainder_fraction=100.0000%, Lmin=-41.79, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3779, ncalls=8551, regioncalls=420608, ndraw=128, logz=-52.00, remainder_fraction=100.0000%, Lmin=-38.43, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3792, ncalls=8591, regioncalls=443136, ndraw=128, logz=-50.36, remainder_fraction=100.0000%, Lmin=-36.85, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=8616, regioncalls=453504, ndraw=128, logz=-49.27, remainder_fraction=100.0000%, Lmin=-35.57, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3824, ncalls=8676, regioncalls=484736, ndraw=128, logz=-45.99, remainder_fraction=100.0000%, Lmin=-32.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=8713, regioncalls=498432, ndraw=128, logz=-44.66, remainder_fraction=100.0000%, Lmin=-31.53, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3859, ncalls=8771, regioncalls=531328, ndraw=128, logz=-42.60, remainder_fraction=100.0000%, Lmin=-29.40, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3874, ncalls=8818, regioncalls=556160, ndraw=128, logz=-41.20, remainder_fraction=100.0000%, Lmin=-27.33, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=8836, regioncalls=566351, ndraw=129, logz=-40.37, remainder_fraction=100.0000%, Lmin=-26.67, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3904, ncalls=8880, regioncalls=594821, ndraw=130, logz=-37.79, remainder_fraction=100.0000%, Lmin=-24.16, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3917, ncalls=8927, regioncalls=621938, ndraw=131, logz=-36.51, remainder_fraction=100.0000%, Lmin=-23.19, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=8941, regioncalls=628802, ndraw=132, logz=-36.26, remainder_fraction=100.0000%, Lmin=-22.90, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3943, ncalls=8999, regioncalls=668569, ndraw=133, logz=-34.63, remainder_fraction=100.0000%, Lmin=-21.59, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=9039, regioncalls=690545, ndraw=134, logz=-33.69, remainder_fraction=100.0000%, Lmin=-20.53, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3982, ncalls=9077, regioncalls=721961, ndraw=136, logz=-32.53, remainder_fraction=99.9999%, Lmin=-19.42, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=9113, regioncalls=748043, ndraw=138, logz=-31.54, remainder_fraction=99.9997%, Lmin=-18.39, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4019, ncalls=9161, regioncalls=783043, ndraw=140, logz=-30.52, remainder_fraction=99.9993%, Lmin=-17.38, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4037, ncalls=9215, regioncalls=817833, ndraw=142, logz=-29.65, remainder_fraction=99.9983%, Lmin=-16.67, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=9232, regioncalls=828921, ndraw=144, logz=-29.52, remainder_fraction=99.9980%, Lmin=-16.62, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=9263, regioncalls=861917, ndraw=146, logz=-29.04, remainder_fraction=99.9968%, Lmin=-15.87, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4063, ncalls=9294, regioncalls=901849, ndraw=149, logz=-28.43, remainder_fraction=99.9940%, Lmin=-15.45, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4078, ncalls=9329, regioncalls=939849, ndraw=152, logz=-27.85, remainder_fraction=99.9894%, Lmin=-15.04, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=9332, regioncalls=945739, ndraw=155, logz=-27.79, remainder_fraction=99.9886%, Lmin=-14.93, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4098, ncalls=9377, regioncalls=985239, ndraw=158, logz=-27.17, remainder_fraction=99.9784%, Lmin=-14.31, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4112, ncalls=9414, regioncalls=1028709, ndraw=161, logz=-26.74, remainder_fraction=99.9667%, Lmin=-14.02, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=9453, regioncalls=1060389, ndraw=165, logz=-26.50, remainder_fraction=99.9573%, Lmin=-13.69, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4134, ncalls=9488, regioncalls=1097907, ndraw=169, logz=-26.09, remainder_fraction=99.9352%, Lmin=-13.23, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4141, ncalls=9507, regioncalls=1123338, ndraw=173, logz=-25.88, remainder_fraction=99.9201%, Lmin=-13.08, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4155, ncalls=9532, regioncalls=1161924, ndraw=177, logz=-25.50, remainder_fraction=99.8810%, Lmin=-12.74, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=9541, regioncalls=1170431, ndraw=181, logz=-25.37, remainder_fraction=99.8629%, Lmin=-12.59, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4180, ncalls=9584, regioncalls=1210946, ndraw=185, logz=-24.88, remainder_fraction=99.7773%, Lmin=-12.17, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4190, ncalls=9620, regioncalls=1251014, ndraw=189, logz=-24.66, remainder_fraction=99.7266%, Lmin=-12.04, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=9641, regioncalls=1277648, ndraw=193, logz=-24.46, remainder_fraction=99.6617%, Lmin=-11.89, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4213, ncalls=9674, regioncalls=1315866, ndraw=197, logz=-24.19, remainder_fraction=99.5512%, Lmin=-11.56, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4227, ncalls=9708, regioncalls=1359498, ndraw=202, logz=-23.92, remainder_fraction=99.4166%, Lmin=-11.33, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4234, ncalls=9723, regioncalls=1389306, ndraw=207, logz=-23.79, remainder_fraction=99.3296%, Lmin=-11.21, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=9742, regioncalls=1410930, ndraw=212, logz=-23.68, remainder_fraction=99.2541%, Lmin=-11.07, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4252, ncalls=9768, regioncalls=1459321, ndraw=217, logz=-23.47, remainder_fraction=99.0787%, Lmin=-10.85, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4265, ncalls=9803, regioncalls=1501723, ndraw=222, logz=-23.23, remainder_fraction=98.8218%, Lmin=-10.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4275, ncalls=9835, regioncalls=1546669, ndraw=227, logz=-23.07, remainder_fraction=98.6134%, Lmin=-10.55, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=9856, regioncalls=1571493, ndraw=232, logz=-23.00, remainder_fraction=98.5096%, Lmin=-10.51, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4298, ncalls=9888, regioncalls=1616049, ndraw=237, logz=-22.75, remainder_fraction=98.0947%, Lmin=-10.30, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4304, ncalls=9921, regioncalls=1661004, ndraw=243, logz=-22.67, remainder_fraction=97.9156%, Lmin=-10.22, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4316, ncalls=9955, regioncalls=1708314, ndraw=249, logz=-22.51, remainder_fraction=97.5853%, Lmin=-10.13, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=9973, regioncalls=1738149, ndraw=255, logz=-22.46, remainder_fraction=97.4659%, Lmin=-10.10, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4331, ncalls=9993, regioncalls=1788000, ndraw=261, logz=-22.33, remainder_fraction=97.1706%, Lmin=-9.97, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4347, ncalls=10027, regioncalls=1836327, ndraw=267, logz=-22.16, remainder_fraction=96.5855%, Lmin=-9.83, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4355, ncalls=10042, regioncalls=1879734, ndraw=273, logz=-22.07, remainder_fraction=96.3666%, Lmin=-9.78, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=10062, regioncalls=1918236, ndraw=279, logz=-22.02, remainder_fraction=96.1811%, Lmin=-9.71, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4370, ncalls=10086, regioncalls=1971531, ndraw=285, logz=-21.92, remainder_fraction=95.7736%, Lmin=-9.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4379, ncalls=10116, regioncalls=2027595, ndraw=292, logz=-21.84, remainder_fraction=95.4674%, Lmin=-9.57, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4386, ncalls=10145, regioncalls=2085302, ndraw=299, logz=-21.77, remainder_fraction=95.2195%, Lmin=-9.50, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4394, ncalls=10169, regioncalls=2121716, ndraw=306, logz=-21.70, remainder_fraction=94.8418%, Lmin=-9.44, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=10185, regioncalls=2139244, ndraw=313, logz=-21.65, remainder_fraction=94.5458%, Lmin=-9.36, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4406, ncalls=10212, regioncalls=2190764, ndraw=320, logz=-21.59, remainder_fraction=94.2499%, Lmin=-9.29, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4412, ncalls=10227, regioncalls=2228369, ndraw=327, logz=-21.54, remainder_fraction=94.1118%, Lmin=-9.25, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4421, ncalls=10253, regioncalls=2286819, ndraw=334, logz=-21.46, remainder_fraction=93.7611%, Lmin=-9.20, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4435, ncalls=10279, regioncalls=2338992, ndraw=341, logz=-21.35, remainder_fraction=93.1867%, Lmin=-9.16, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=10292, regioncalls=2356740, ndraw=348, logz=-21.31, remainder_fraction=92.9450%, Lmin=-9.15, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4448, ncalls=10316, regioncalls=2412120, ndraw=355, logz=-21.26, remainder_fraction=92.7016%, Lmin=-9.11, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4456, ncalls=10337, regioncalls=2474384, ndraw=362, logz=-21.20, remainder_fraction=92.2318%, Lmin=-9.08, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4465, ncalls=10366, regioncalls=2529884, ndraw=370, logz=-21.14, remainder_fraction=91.7119%, Lmin=-9.04, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4472, ncalls=10387, regioncalls=2586584, ndraw=378, logz=-21.10, remainder_fraction=91.3053%, Lmin=-9.01, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=10401, regioncalls=2624026, ndraw=386, logz=-21.05, remainder_fraction=90.8454%, Lmin=-8.97, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4489, ncalls=10435, regioncalls=2676822, ndraw=394, logz=-21.00, remainder_fraction=90.5391%, Lmin=-8.93, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=10460, regioncalls=2732298, ndraw=402, logz=-20.93, remainder_fraction=89.8098%, Lmin=-8.89, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4509, ncalls=10487, regioncalls=2785188, ndraw=410, logz=-20.89, remainder_fraction=89.4904%, Lmin=-8.86, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4517, ncalls=10523, regioncalls=2893868, ndraw=418, logz=-20.84, remainder_fraction=88.9873%, Lmin=-8.82, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=10535, regioncalls=2928882, ndraw=427, logz=-20.83, remainder_fraction=88.7797%, Lmin=-8.80, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4527, ncalls=10556, regioncalls=2989922, ndraw=436, logz=-20.79, remainder_fraction=88.5460%, Lmin=-8.79, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4535, ncalls=10584, regioncalls=3062457, ndraw=445, logz=-20.75, remainder_fraction=88.4498%, Lmin=-8.77, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4547, ncalls=10615, regioncalls=3120115, ndraw=454, logz=-20.70, remainder_fraction=88.2664%, Lmin=-8.72, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4555, ncalls=10643, regioncalls=3184935, ndraw=463, logz=-20.66, remainder_fraction=87.7047%, Lmin=-8.70, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=10649, regioncalls=3193903, ndraw=472, logz=-20.64, remainder_fraction=87.4259%, Lmin=-8.69, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4568, ncalls=10674, regioncalls=3258838, ndraw=481, logz=-20.61, remainder_fraction=86.8895%, Lmin=-8.65, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4574, ncalls=10697, regioncalls=3318618, ndraw=490, logz=-20.58, remainder_fraction=86.4964%, Lmin=-8.62, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4582, ncalls=10731, regioncalls=3392470, ndraw=499, logz=-20.55, remainder_fraction=85.9932%, Lmin=-8.59, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4591, ncalls=10752, regioncalls=3427082, ndraw=509, logz=-20.51, remainder_fraction=85.3417%, Lmin=-8.57, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4597, ncalls=10769, regioncalls=3480436, ndraw=518, logz=-20.49, remainder_fraction=85.0022%, Lmin=-8.53, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4599, ncalls=10789, regioncalls=3556468, ndraw=528, logz=-20.48, remainder_fraction=84.8535%, Lmin=-8.52, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=10794, regioncalls=3570456, ndraw=538, logz=-20.47, remainder_fraction=84.7845%, Lmin=-8.52, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4610, ncalls=10822, regioncalls=3637312, ndraw=548, logz=-20.44, remainder_fraction=84.2754%, Lmin=-8.49, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4617, ncalls=10843, regioncalls=3693670, ndraw=558, logz=-20.41, remainder_fraction=83.7745%, Lmin=-8.47, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4626, ncalls=10868, regioncalls=3752174, ndraw=568, logz=-20.38, remainder_fraction=83.3895%, Lmin=-8.44, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4632, ncalls=10889, regioncalls=3816332, ndraw=578, logz=-20.35, remainder_fraction=83.2442%, Lmin=-8.41, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4636, ncalls=10906, regioncalls=3874544, ndraw=588, logz=-20.34, remainder_fraction=82.9396%, Lmin=-8.40, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4639, ncalls=10922, regioncalls=3936736, ndraw=598, logz=-20.33, remainder_fraction=82.6913%, Lmin=-8.40, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=10925, regioncalls=3946464, ndraw=608, logz=-20.33, remainder_fraction=82.6197%, Lmin=-8.39, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4648, ncalls=10955, regioncalls=4010736, ndraw=618, logz=-20.30, remainder_fraction=82.4187%, Lmin=-8.37, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4656, ncalls=10978, regioncalls=4072908, ndraw=628, logz=-20.27, remainder_fraction=81.8463%, Lmin=-8.35, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4661, ncalls=10996, regioncalls=4135432, ndraw=638, logz=-20.26, remainder_fraction=81.7872%, Lmin=-8.33, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4667, ncalls=11027, regioncalls=4226152, ndraw=648, logz=-20.24, remainder_fraction=81.3443%, Lmin=-8.31, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4671, ncalls=11045, regioncalls=4288004, ndraw=658, logz=-20.22, remainder_fraction=81.0399%, Lmin=-8.30, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4679, ncalls=11062, regioncalls=4352800, ndraw=668, logz=-20.20, remainder_fraction=80.5628%, Lmin=-8.28, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=11065, regioncalls=4372462, ndraw=678, logz=-20.19, remainder_fraction=80.4832%, Lmin=-8.26, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4688, ncalls=11088, regioncalls=4452958, ndraw=688, logz=-20.17, remainder_fraction=79.9959%, Lmin=-8.25, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4694, ncalls=11106, regioncalls=4516476, ndraw=698, logz=-20.15, remainder_fraction=79.5399%, Lmin=-8.24, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4700, ncalls=11122, regioncalls=4588085, ndraw=709, logz=-20.13, remainder_fraction=79.0910%, Lmin=-8.22, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4703, ncalls=11145, regioncalls=4660805, ndraw=720, logz=-20.13, remainder_fraction=78.8509%, Lmin=-8.20, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4707, ncalls=11165, regioncalls=4731712, ndraw=731, logz=-20.11, remainder_fraction=78.5666%, Lmin=-8.19, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4708, ncalls=11179, regioncalls=4799234, ndraw=742, logz=-20.11, remainder_fraction=78.5254%, Lmin=-8.19, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4718, ncalls=11199, regioncalls=4861733, ndraw=753, logz=-20.08, remainder_fraction=78.2526%, Lmin=-8.16, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=11211, regioncalls=4903753, ndraw=764, logz=-20.08, remainder_fraction=78.1027%, Lmin=-8.16, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4723, ncalls=11223, regioncalls=4981253, ndraw=775, logz=-20.07, remainder_fraction=77.8723%, Lmin=-8.15, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4725, ncalls=11238, regioncalls=5044919, ndraw=786, logz=-20.06, remainder_fraction=77.7045%, Lmin=-8.14, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4728, ncalls=11262, regioncalls=5120634, ndraw=797, logz=-20.05, remainder_fraction=77.4463%, Lmin=-8.14, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4734, ncalls=11275, regioncalls=5186890, ndraw=808, logz=-20.04, remainder_fraction=77.0255%, Lmin=-8.13, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4743, ncalls=11303, regioncalls=5258143, ndraw=819, logz=-20.01, remainder_fraction=76.5814%, Lmin=-8.11, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4747, ncalls=11326, regioncalls=5322961, ndraw=831, logz=-20.00, remainder_fraction=76.2444%, Lmin=-8.09, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4753, ncalls=11347, regioncalls=5414848, ndraw=843, logz=-19.99, remainder_fraction=75.8210%, Lmin=-8.08, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4757, ncalls=11369, regioncalls=5497783, ndraw=855, logz=-19.98, remainder_fraction=75.5731%, Lmin=-8.06, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=11384, regioncalls=5581015, ndraw=867, logz=-19.97, remainder_fraction=75.4841%, Lmin=-8.05, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4767, ncalls=11407, regioncalls=5647819, ndraw=879, logz=-19.95, remainder_fraction=75.0766%, Lmin=-8.04, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=11417, regioncalls=5677222, ndraw=891, logz=-19.95, remainder_fraction=74.8395%, Lmin=-8.04, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=11523, regioncalls=5694379, ndraw=903, logz=-19.87, remainder_fraction=72.6733%, Lmin=-7.98, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=11637, regioncalls=5714487, ndraw=914, logz=-19.79, remainder_fraction=70.4414%, Lmin=-7.89, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=11749, regioncalls=5732062, ndraw=925, logz=-19.71, remainder_fraction=68.1763%, Lmin=-7.80, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=11872, regioncalls=5758242, ndraw=935, logz=-19.64, remainder_fraction=65.5779%, Lmin=-7.70, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=11971, regioncalls=5774290, ndraw=944, logz=-19.59, remainder_fraction=63.3101%, Lmin=-7.65, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=12011, regioncalls=5788585, ndraw=953, logz=-19.57, remainder_fraction=62.6248%, Lmin=-7.63, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=12149, regioncalls=5835723, ndraw=962, logz=-19.51, remainder_fraction=60.8928%, Lmin=-7.56, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=5037, ncalls=12261, regioncalls=5886163, ndraw=970, logz=-19.46, remainder_fraction=58.6482%, Lmin=-7.52, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=12269, regioncalls=5890075, ndraw=978, logz=-19.46, remainder_fraction=58.3816%, Lmin=-7.52, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5071, ncalls=12384, regioncalls=5934445, ndraw=986, logz=-19.42, remainder_fraction=56.8168%, Lmin=-7.46, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=12421, regioncalls=5949340, ndraw=993, logz=-19.41, remainder_fraction=56.1009%, Lmin=-7.45, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5109, ncalls=12541, regioncalls=5996340, ndraw=1000, logz=-19.37, remainder_fraction=54.0555%, Lmin=-7.42, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=12582, regioncalls=6013459, ndraw=1007, logz=-19.36, remainder_fraction=53.4702%, Lmin=-7.40, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=12615, regioncalls=6029683, ndraw=1014, logz=-19.35, remainder_fraction=53.1077%, Lmin=-7.39, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=12717, regioncalls=6073543, ndraw=1020, logz=-19.32, remainder_fraction=52.0299%, Lmin=-7.34, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5193, ncalls=12831, regioncalls=6124843, ndraw=1026, logz=-19.29, remainder_fraction=50.9957%, Lmin=-7.29, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=12855, regioncalls=6133099, ndraw=1032, logz=-19.28, remainder_fraction=50.7015%, Lmin=-7.28, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5224, ncalls=12928, regioncalls=6172543, ndraw=1038, logz=-19.26, remainder_fraction=49.6906%, Lmin=-7.25, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=12971, regioncalls=6196555, ndraw=1044, logz=-19.25, remainder_fraction=48.9634%, Lmin=-7.22, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5274, ncalls=13076, regioncalls=6251155, ndraw=1050, logz=-19.22, remainder_fraction=47.8735%, Lmin=-7.18, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=13091, regioncalls=6263815, ndraw=1055, logz=-19.21, remainder_fraction=47.6332%, Lmin=-7.17, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5297, ncalls=13156, regioncalls=6313635, ndraw=1060, logz=-19.20, remainder_fraction=47.3198%, Lmin=-7.14, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=13200, regioncalls=6339195, ndraw=1065, logz=-19.19, remainder_fraction=47.1491%, Lmin=-7.12, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=13224, regioncalls=6352035, ndraw=1070, logz=-19.18, remainder_fraction=46.5334%, Lmin=-7.10, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=13334, regioncalls=6382135, ndraw=1075, logz=-19.16, remainder_fraction=45.0622%, Lmin=-7.05, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=13412, regioncalls=6400495, ndraw=1080, logz=-19.13, remainder_fraction=43.4297%, Lmin=-6.99, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=13478, regioncalls=6423259, ndraw=1084, logz=-19.10, remainder_fraction=41.8477%, Lmin=-6.92, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=13552, regioncalls=6467867, ndraw=1088, logz=-19.08, remainder_fraction=40.5377%, Lmin=-6.81, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=13608, regioncalls=6508271, ndraw=1092, logz=-19.06, remainder_fraction=38.7578%, Lmin=-6.61, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=13669, regioncalls=6541121, ndraw=1095, logz=-19.03, remainder_fraction=37.2477%, Lmin=-6.47, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5595, ncalls=13733, regioncalls=6583943, ndraw=1098, logz=-19.01, remainder_fraction=35.8584%, Lmin=-6.37, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=13742, regioncalls=6591650, ndraw=1101, logz=-19.00, remainder_fraction=35.6499%, Lmin=-6.34, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=13815, regioncalls=6652370, ndraw=1104, logz=-18.98, remainder_fraction=33.8939%, Lmin=-6.25, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=13868, regioncalls=6701078, ndraw=1107, logz=-18.96, remainder_fraction=32.8648%, Lmin=-6.16, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=13884, regioncalls=6713288, ndraw=1110, logz=-18.95, remainder_fraction=32.3776%, Lmin=-6.14, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5716, ncalls=13950, regioncalls=6763373, ndraw=1113, logz=-18.93, remainder_fraction=30.8652%, Lmin=-6.06, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=13956, regioncalls=6770069, ndraw=1116, logz=-18.93, remainder_fraction=30.6636%, Lmin=-6.05, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5750, ncalls=14020, regioncalls=6817067, ndraw=1119, logz=-18.91, remainder_fraction=29.4383%, Lmin=-6.00, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=14045, regioncalls=6832775, ndraw=1122, logz=-18.90, remainder_fraction=29.0635%, Lmin=-5.98, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5787, ncalls=14091, regioncalls=6878900, ndraw=1125, logz=-18.89, remainder_fraction=27.9423%, Lmin=-5.93, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=14112, regioncalls=6900332, ndraw=1128, logz=-18.88, remainder_fraction=27.3878%, Lmin=-5.91, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5819, ncalls=14145, regioncalls=6945532, ndraw=1130, logz=-18.87, remainder_fraction=26.7142%, Lmin=-5.87, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=14178, regioncalls=6985187, ndraw=1133, logz=-18.86, remainder_fraction=25.9455%, Lmin=-5.83, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5852, ncalls=14199, regioncalls=7026083, ndraw=1136, logz=-18.85, remainder_fraction=25.3607%, Lmin=-5.80, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5874, ncalls=14229, regioncalls=7073921, ndraw=1139, logz=-18.84, remainder_fraction=24.6629%, Lmin=-5.75, Lmax=-4.68 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=14243, regioncalls=7088767, ndraw=1142, logz=-18.84, remainder_fraction=24.4625%, Lmin=-5.74, Lmax=-4.68 DEBUG ultranest:integrator.py:2610 iteration=5903, ncalls=14282, regioncalls=7134567, ndraw=1145, logz=-18.83, remainder_fraction=23.6728%, Lmin=-5.70, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5919, ncalls=14317, regioncalls=7189671, ndraw=1148, logz=-18.82, remainder_fraction=23.0676%, Lmin=-5.67, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=14319, regioncalls=7190822, ndraw=1151, logz=-18.82, remainder_fraction=23.0190%, Lmin=-5.67, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=14346, regioncalls=7227750, ndraw=1154, logz=-18.81, remainder_fraction=22.3083%, Lmin=-5.64, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=14374, regioncalls=7260146, ndraw=1157, logz=-18.80, remainder_fraction=21.7002%, Lmin=-5.60, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5969, ncalls=14398, regioncalls=7309983, ndraw=1159, logz=-18.80, remainder_fraction=21.3183%, Lmin=-5.58, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5982, ncalls=14428, regioncalls=7361111, ndraw=1162, logz=-18.79, remainder_fraction=20.8148%, Lmin=-5.56, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=14456, regioncalls=7404216, ndraw=1165, logz=-18.78, remainder_fraction=20.1081%, Lmin=-5.53, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=6021, ncalls=14493, regioncalls=7449768, ndraw=1168, logz=-18.78, remainder_fraction=19.4889%, Lmin=-5.51, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6034, ncalls=14519, regioncalls=7488411, ndraw=1171, logz=-18.77, remainder_fraction=19.0872%, Lmin=-5.49, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=14529, regioncalls=7509543, ndraw=1174, logz=-18.77, remainder_fraction=18.9037%, Lmin=-5.48, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6054, ncalls=14552, regioncalls=7560154, ndraw=1177, logz=-18.76, remainder_fraction=18.4863%, Lmin=-5.46, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6072, ncalls=14584, regioncalls=7610894, ndraw=1180, logz=-18.75, remainder_fraction=17.8775%, Lmin=-5.43, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=14600, regioncalls=7639286, ndraw=1183, logz=-18.75, remainder_fraction=17.6977%, Lmin=-5.41, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6097, ncalls=14629, regioncalls=7684354, ndraw=1186, logz=-18.74, remainder_fraction=17.3184%, Lmin=-5.39, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6109, ncalls=14653, regioncalls=7736670, ndraw=1189, logz=-18.74, remainder_fraction=16.9581%, Lmin=-5.37, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=14671, regioncalls=7761702, ndraw=1192, logz=-18.74, remainder_fraction=16.6429%, Lmin=-5.36, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6131, ncalls=14697, regioncalls=7813087, ndraw=1195, logz=-18.73, remainder_fraction=16.3472%, Lmin=-5.34, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6144, ncalls=14713, regioncalls=7866997, ndraw=1198, logz=-18.73, remainder_fraction=15.9765%, Lmin=-5.33, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6153, ncalls=14729, regioncalls=7916238, ndraw=1201, logz=-18.72, remainder_fraction=15.6767%, Lmin=-5.32, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=14741, regioncalls=7941522, ndraw=1204, logz=-18.72, remainder_fraction=15.4596%, Lmin=-5.30, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6174, ncalls=14762, regioncalls=7987388, ndraw=1207, logz=-18.72, remainder_fraction=15.0667%, Lmin=-5.28, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6185, ncalls=14779, regioncalls=8041838, ndraw=1210, logz=-18.71, remainder_fraction=14.7469%, Lmin=-5.28, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=14806, regioncalls=8081900, ndraw=1214, logz=-18.71, remainder_fraction=14.3593%, Lmin=-5.26, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=14822, regioncalls=8144018, ndraw=1218, logz=-18.71, remainder_fraction=14.1013%, Lmin=-5.24, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6220, ncalls=14848, regioncalls=8201452, ndraw=1222, logz=-18.70, remainder_fraction=13.8115%, Lmin=-5.24, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6235, ncalls=14880, regioncalls=8254170, ndraw=1226, logz=-18.70, remainder_fraction=13.4538%, Lmin=-5.22, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=14900, regioncalls=8289840, ndraw=1230, logz=-18.70, remainder_fraction=13.3422%, Lmin=-5.22, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6256, ncalls=14929, regioncalls=8340434, ndraw=1234, logz=-18.69, remainder_fraction=12.9616%, Lmin=-5.21, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6269, ncalls=14953, regioncalls=8389954, ndraw=1238, logz=-18.69, remainder_fraction=12.6697%, Lmin=-5.19, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6278, ncalls=14971, regioncalls=8443360, ndraw=1242, logz=-18.69, remainder_fraction=12.4724%, Lmin=-5.18, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=14974, regioncalls=8453328, ndraw=1246, logz=-18.68, remainder_fraction=12.4234%, Lmin=-5.18, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6290, ncalls=14995, regioncalls=8507078, ndraw=1250, logz=-18.68, remainder_fraction=12.1763%, Lmin=-5.17, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6297, ncalls=15010, regioncalls=8558492, ndraw=1254, logz=-18.68, remainder_fraction=12.0339%, Lmin=-5.17, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6308, ncalls=15030, regioncalls=8600006, ndraw=1258, logz=-18.68, remainder_fraction=11.7642%, Lmin=-5.16, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=15050, regioncalls=8641652, ndraw=1262, logz=-18.67, remainder_fraction=11.4831%, Lmin=-5.15, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6329, ncalls=15078, regioncalls=8698622, ndraw=1266, logz=-18.67, remainder_fraction=11.2964%, Lmin=-5.13, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6337, ncalls=15101, regioncalls=8755772, ndraw=1270, logz=-18.67, remainder_fraction=11.1156%, Lmin=-5.13, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6346, ncalls=15124, regioncalls=8813102, ndraw=1274, logz=-18.67, remainder_fraction=10.9322%, Lmin=-5.12, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6356, ncalls=15146, regioncalls=8884726, ndraw=1279, logz=-18.67, remainder_fraction=10.7259%, Lmin=-5.11, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=15154, regioncalls=8905270, ndraw=1284, logz=-18.66, remainder_fraction=10.6661%, Lmin=-5.11, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6368, ncalls=15172, regioncalls=8967142, ndraw=1289, logz=-18.66, remainder_fraction=10.5070%, Lmin=-5.10, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6376, ncalls=15188, regioncalls=9027960, ndraw=1294, logz=-18.66, remainder_fraction=10.3402%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6383, ncalls=15204, regioncalls=9082518, ndraw=1299, logz=-18.66, remainder_fraction=10.2111%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=15221, regioncalls=9135982, ndraw=1304, logz=-18.66, remainder_fraction=10.0700%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6397, ncalls=15240, regioncalls=9204050, ndraw=1309, logz=-18.66, remainder_fraction=9.9304%, Lmin=-5.08, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=15261, regioncalls=9247412, ndraw=1314, logz=-18.65, remainder_fraction=9.8669%, Lmin=-5.08, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6415, ncalls=15286, regioncalls=9317319, ndraw=1319, logz=-18.65, remainder_fraction=9.5953%, Lmin=-5.07, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6421, ncalls=15312, regioncalls=9370279, ndraw=1324, logz=-18.65, remainder_fraction=9.4904%, Lmin=-5.06, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6434, ncalls=15334, regioncalls=9427426, ndraw=1329, logz=-18.65, remainder_fraction=9.2431%, Lmin=-5.05, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=15343, regioncalls=9460776, ndraw=1334, logz=-18.65, remainder_fraction=9.1334%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6442, ncalls=15361, regioncalls=9530404, ndraw=1339, logz=-18.65, remainder_fraction=9.0937%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6449, ncalls=15381, regioncalls=9589584, ndraw=1345, logz=-18.64, remainder_fraction=8.9603%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6455, ncalls=15401, regioncalls=9653081, ndraw=1351, logz=-18.64, remainder_fraction=8.8451%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6463, ncalls=15414, regioncalls=9703290, ndraw=1357, logz=-18.64, remainder_fraction=8.7111%, Lmin=-5.03, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6471, ncalls=15431, regioncalls=9759173, ndraw=1363, logz=-18.64, remainder_fraction=8.5736%, Lmin=-5.02, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6478, ncalls=15446, regioncalls=9823516, ndraw=1369, logz=-18.64, remainder_fraction=8.4534%, Lmin=-5.02, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=15450, regioncalls=9827641, ndraw=1375, logz=-18.64, remainder_fraction=8.4185%, Lmin=-5.02, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6491, ncalls=15479, regioncalls=9898072, ndraw=1381, logz=-18.64, remainder_fraction=8.2800%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6494, ncalls=15496, regioncalls=9954939, ndraw=1387, logz=-18.64, remainder_fraction=8.2410%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6497, ncalls=15521, regioncalls=10007873, ndraw=1393, logz=-18.64, remainder_fraction=8.1899%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6502, ncalls=15545, regioncalls=10066631, ndraw=1399, logz=-18.63, remainder_fraction=8.1117%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6511, ncalls=15564, regioncalls=10121426, ndraw=1405, logz=-18.63, remainder_fraction=7.9896%, Lmin=-4.99, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6516, ncalls=15585, regioncalls=10199031, ndraw=1411, logz=-18.63, remainder_fraction=7.9090%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=15595, regioncalls=10234456, ndraw=1417, logz=-18.63, remainder_fraction=7.8652%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6525, ncalls=15609, regioncalls=10282838, ndraw=1423, logz=-18.63, remainder_fraction=7.7826%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6528, ncalls=15625, regioncalls=10335711, ndraw=1429, logz=-18.63, remainder_fraction=7.7349%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6537, ncalls=15646, regioncalls=10387371, ndraw=1435, logz=-18.63, remainder_fraction=7.5932%, Lmin=-4.97, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6544, ncalls=15665, regioncalls=10443570, ndraw=1441, logz=-18.63, remainder_fraction=7.4859%, Lmin=-4.97, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6548, ncalls=15686, regioncalls=10498556, ndraw=1447, logz=-18.63, remainder_fraction=7.4407%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6554, ncalls=15698, regioncalls=10552317, ndraw=1453, logz=-18.63, remainder_fraction=7.3493%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6559, ncalls=15716, regioncalls=10606300, ndraw=1459, logz=-18.62, remainder_fraction=7.2836%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=15723, regioncalls=10620950, ndraw=1465, logz=-18.62, remainder_fraction=7.2683%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6562, ncalls=15734, regioncalls=10685674, ndraw=1471, logz=-18.62, remainder_fraction=7.2362%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6569, ncalls=15750, regioncalls=10749185, ndraw=1477, logz=-18.62, remainder_fraction=7.1337%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6570, ncalls=15755, regioncalls=10752151, ndraw=1483, logz=-18.62, remainder_fraction=7.1162%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6600, ncalls=15832, regioncalls=10768530, ndraw=1489, logz=-18.62, remainder_fraction=6.7089%, Lmin=-4.94, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6640, ncalls=15949, regioncalls=10795440, ndraw=1495, logz=-18.61, remainder_fraction=6.1782%, Lmin=-4.92, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6680, ncalls=16038, regioncalls=10816440, ndraw=1500, logz=-18.61, remainder_fraction=5.7029%, Lmin=-4.89, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=16183, regioncalls=10860085, ndraw=1505, logz=-18.60, remainder_fraction=5.2518%, Lmin=-4.87, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6758, ncalls=16309, regioncalls=10888756, ndraw=1509, logz=-18.60, remainder_fraction=4.8541%, Lmin=-4.85, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6760, ncalls=16309, regioncalls=10888756, ndraw=1513, logz=-18.60, remainder_fraction=4.8403%, Lmin=-4.84, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6800, ncalls=16412, regioncalls=10922130, ndraw=1517, logz=-18.59, remainder_fraction=4.4695%, Lmin=-4.82, Lmax=-4.10 DEBUG ultranest:integrator.py:2610 iteration=6815, ncalls=16472, regioncalls=10944945, ndraw=1521, logz=-18.59, remainder_fraction=4.3337%, Lmin=-4.82, Lmax=-4.07 DEBUG ultranest:integrator.py:2610 iteration=6840, ncalls=16535, regioncalls=10970853, ndraw=1524, logz=-18.59, remainder_fraction=4.1250%, Lmin=-4.81, Lmax=-4.07 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=16635, regioncalls=10984596, ndraw=1527, logz=-18.59, remainder_fraction=3.8232%, Lmin=-4.79, Lmax=-3.94 DEBUG ultranest:integrator.py:2610 iteration=6920, ncalls=16752, regioncalls=11006016, ndraw=1530, logz=-18.58, remainder_fraction=3.5781%, Lmin=-4.77, Lmax=-3.94 DEBUG ultranest:integrator.py:2610 iteration=6930, ncalls=16776, regioncalls=11010612, ndraw=1532, logz=-18.58, remainder_fraction=3.5166%, Lmin=-4.77, Lmax=-3.89 DEBUG ultranest:integrator.py:2610 iteration=6960, ncalls=16850, regioncalls=11024418, ndraw=1534, logz=-18.58, remainder_fraction=3.3495%, Lmin=-4.76, Lmax=-3.89 DEBUG ultranest:integrator.py:2610 iteration=7000, ncalls=16951, regioncalls=11042850, ndraw=1536, logz=-18.58, remainder_fraction=3.1207%, Lmin=-4.74, Lmax=-3.84 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=17039, regioncalls=11056692, ndraw=1538, logz=-18.58, remainder_fraction=2.9255%, Lmin=-4.73, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7080, ncalls=17121, regioncalls=11070543, ndraw=1539, logz=-18.57, remainder_fraction=2.7041%, Lmin=-4.71, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7120, ncalls=17229, regioncalls=11090563, ndraw=1540, logz=-18.57, remainder_fraction=2.5086%, Lmin=-4.70, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7160, ncalls=17321, regioncalls=11110596, ndraw=1541, logz=-18.57, remainder_fraction=2.3511%, Lmin=-4.68, Lmax=-3.80 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=17401, regioncalls=11127547, ndraw=1541, logz=-18.57, remainder_fraction=2.2246%, Lmin=-4.66, Lmax=-3.72 DEBUG ultranest:integrator.py:2610 iteration=7240, ncalls=17478, regioncalls=11144498, ndraw=1541, logz=-18.57, remainder_fraction=2.0928%, Lmin=-4.64, Lmax=-3.72 DEBUG ultranest:integrator.py:2610 iteration=7280, ncalls=17550, regioncalls=11166072, ndraw=1541, logz=-18.56, remainder_fraction=1.9776%, Lmin=-4.62, Lmax=-3.67 DEBUG ultranest:integrator.py:2610 iteration=7317, ncalls=17609, regioncalls=11193810, ndraw=1541, logz=-18.56, remainder_fraction=1.8732%, Lmin=-4.58, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7320, ncalls=17620, regioncalls=11196892, ndraw=1541, logz=-18.56, remainder_fraction=1.8629%, Lmin=-4.57, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=17688, regioncalls=11216925, ndraw=1541, logz=-18.56, remainder_fraction=1.7425%, Lmin=-4.53, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7400, ncalls=17753, regioncalls=11243105, ndraw=1540, logz=-18.56, remainder_fraction=1.6284%, Lmin=-4.48, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7440, ncalls=17834, regioncalls=11278502, ndraw=1539, logz=-18.56, remainder_fraction=1.5243%, Lmin=-4.43, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7480, ncalls=17895, regioncalls=11300034, ndraw=1538, logz=-18.56, remainder_fraction=1.4230%, Lmin=-4.39, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=17985, regioncalls=11329237, ndraw=1537, logz=-18.56, remainder_fraction=1.3283%, Lmin=-4.35, Lmax=-3.57 DEBUG ultranest:integrator.py:2610 iteration=7560, ncalls=18055, regioncalls=11353813, ndraw=1536, logz=-18.56, remainder_fraction=1.2420%, Lmin=-4.31, Lmax=-3.53 DEBUG ultranest:integrator.py:2610 iteration=7600, ncalls=18127, regioncalls=11393723, ndraw=1535, logz=-18.56, remainder_fraction=1.1646%, Lmin=-4.27, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7629, ncalls=18196, regioncalls=11439743, ndraw=1534, logz=-18.55, remainder_fraction=1.1037%, Lmin=-4.23, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7640, ncalls=18220, regioncalls=11455073, ndraw=1533, logz=-18.55, remainder_fraction=1.0833%, Lmin=-4.22, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7650, ncalls=18242, regioncalls=11467329, ndraw=1532, logz=-18.55, remainder_fraction=1.0607%, Lmin=-4.21, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7680, ncalls=18285, regioncalls=11501011, ndraw=1531, logz=-18.55, remainder_fraction=1.0087%, Lmin=-4.18, Lmax=-3.51 INFO ultranest:integrator.py:2654 Explored until L=-4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 18296 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -18.54 +- 0.1012 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2455.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.17 bs:0.10 tail:0.01 total:0.10 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_stepsampling.py::test_stepsampler_cubeslice	11.34
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-3.47) * Expected Volume: exp(0.00) Quality: ok param0: +1.0e-12\|****************************************** **\| +1.0e+00 param1: +1.0e-12\|***********************************************\| +1.0e+00 param2: +1.0e-12\|************************************************\| +1.0e+00 Z=-inf(0.00%) \| Like=-29.79..-0.38 [-29.7909..-8.4581] \| it/evals=0/403 eff=0.0000% N=400 Z=-25.5(0.00%) \| Like=-21.14..-0.38 [-29.7909..-8.4581] \| it/evals=50/610 eff=23.8095% N=400 Mono-modal Volume: ~exp(-4.65) Expected Volume: exp(-0.23) Quality: ok param0: +1.0e-12\|******************************************** * **\| +1.0e+00 param1: +1.0e-12\|******************************************* \| +1.0e+00 param2: +1.0e-12\|******************************************* \| +1.0e+00 Z=-21.2(0.00%) \| Like=-17.35..-0.38 [-29.7909..-8.4581] \| it/evals=90/795 eff=22.7848% N=400 Z=-20.4(0.00%) \| Like=-16.81..-0.38 [-29.7909..-8.4581] \| it/evals=100/837 eff=22.8833% N=400 Z=-16.7(0.00%) \| Like=-12.91..-0.38 [-29.7909..-8.4581] \| it/evals=150/1090 eff=21.7391% N=400 Mono-modal Volume: ~exp(-4.83) Expected Volume: exp(-0.45) Quality: ok param0: +1.0e-12\|******************************************** * **\| +1.0e+00 param1: +1.0e-12\|******************************************* \| +1.0e+00 param2: +1.0e-12\|******************************** ****** * ** \| +1.0e+00 Z=-15.1(0.00%) \| Like=-11.75..-0.38 [-29.7909..-8.4581] \| it/evals=180/1249 eff=21.2014% N=400 Z=-14.2(0.00%) \| Like=-10.89..-0.38 [-29.7909..-8.4581] \| it/evals=200/1383 eff=20.3459% N=400 Z=-12.5(0.02%) \| Like=-9.35..-0.38 [-29.7909..-8.4581] \| it/evals=250/1671 eff=19.6696% N=400 Mono-modal Volume: ~exp(-5.10) * Expected Volume: exp(-0.67) Quality: ok param0: +1.0e-12\|*********************************** * ***** * **\| +1.0e+00 param1: +1.0e-12\|************************************** \| +1.0e+00 param2: +1.0e-12\|******************************** **** \| +1.0e+00 Z=-11.9(0.04%) \| Like=-9.00..-0.09 [-29.7909..-8.4581] \| it/evals=270/1813 eff=19.1083% N=400 Z=-11.3(0.07%) \| Like=-8.45..-0.09 [-8.4564..-5.6145] \| it/evals=300/2027 eff=18.4388% N=400 Z=-10.4(0.17%) \| Like=-7.77..-0.09 [-8.4564..-5.6145] \| it/evals=350/2363 eff=17.8299% N=400 Mono-modal Volume: ~exp(-5.24) * Expected Volume: exp(-0.90) Quality: ok param0: +1.0e-12\|********************************** *** \| +1.0e+00 param1: +1.0e-12\|**************************************** ****\| +1.0e+00 param2: +1.0e-12\|******************************* ****** * ** \| +1.0e+00 Z=-10.3(0.20%) \| Like=-7.63..-0.09 [-8.4564..-5.6145] \| it/evals=360/2429 eff=17.7427% N=400 Z=-9.8(0.35%) \| Like=-7.14..-0.09 [-8.4564..-5.6145] \| it/evals=400/2696 eff=17.4216% N=400 Mono-modal Volume: ~exp(-5.45) * Expected Volume: exp(-1.12) Quality: ok param0: +1.0e-12\|********************************** *** \| +1.0e+00 param1: +1.0e-12\|**************************************** ****\| +1.0e+00 param2: +1.0e-12\|******************************* **** * \| +1.0e+00 Z=-9.2(0.57%) \| Like=-6.70..-0.09 [-8.4564..-5.6145] \| it/evals=450/3055 eff=16.9492% N=400 Z=-8.7(0.91%) \| Like=-6.24..-0.09 [-8.4564..-5.6145] \| it/evals=500/3463 eff=16.3239% N=400 Mono-modal Volume: ~exp(-5.67) * Expected Volume: exp(-1.35) Quality: ok param0: +1.0e-12\|****************************************** \| +1.0e+00 param1: +0.0000\|**************************** **** *****\| +1.0000 param2: +1.0e-12\|******************************* ****** * * \| +1.0e+00 Z=-8.4(1.33%) \| Like=-5.86..-0.09 [-8.4564..-5.6145] \| it/evals=540/3829 eff=15.7480% N=400 Z=-8.3(1.45%) \| Like=-5.77..-0.09 [-8.4564..-5.6145] \| it/evals=550/3922 eff=15.6161% N=400 Z=-8.0(1.91%) \| Like=-5.49..-0.09 [-5.6135..-4.0672] \| it/evals=589/4254 eff=15.2828% N=400 Z=-7.9(2.07%) \| Like=-5.38..-0.09 [-5.6135..-4.0672] \| it/evals=600/4332 eff=15.2594% N=400 Mono-modal Volume: ~exp(-5.67) Expected Volume: exp(-1.57) Quality: ok param0: +0.0000\|**************************** ********* * \| +1.0000 param1: +0.0000\|**************************** **** *****\| +1.0000 param2: +1.0e-12\|**************************************** * \| +1.0e+00 Z=-7.7(2.36%) \| Like=-5.21..-0.09 [-5.6135..-4.0672] \| it/evals=630/4604 eff=14.9857% N=400 Z=-7.6(2.70%) \| Like=-5.04..-0.09 [-5.6135..-4.0672] \| it/evals=650/4777 eff=14.8504% N=400 Z=-7.3(3.56%) \| Like=-4.69..-0.09 [-5.6135..-4.0672] \| it/evals=700/5283 eff=14.3354% N=400 Mono-modal Volume: ~exp(-6.27) * Expected Volume: exp(-1.80) Quality: ok param0: +0.0000\|****************************** ********* * \| +1.0000 param1: +0.000\|**************************** ************* \| +1.000 param2: +0.000\|***************************** ******** * * \| +1.000 Z=-7.2(3.95%) \| Like=-4.63..-0.09 [-5.6135..-4.0672] \| it/evals=720/5475 eff=14.1872% N=400 Z=-7.0(4.63%) \| Like=-4.51..-0.09 [-5.6135..-4.0672] \| it/evals=750/5779 eff=13.9431% N=400 Z=-6.8(5.73%) \| Like=-4.29..-0.09 [-5.6135..-4.0672] \| it/evals=795/6235 eff=13.6247% N=400 Z=-6.8(5.90%) \| Like=-4.26..-0.09 [-5.6135..-4.0672] \| it/evals=800/6303 eff=13.5524% N=400 Mono-modal Volume: ~exp(-6.27) Expected Volume: exp(-2.02) Quality: ok param0: +0.00\|**************************** ********* \| +1.00 param1: +0.00\| ***************************** ********** \| +1.00 param2: +0.00\| ******************************************* * * * \| +1.00 Z=-6.7(6.82%) \| Like=-4.10..-0.09 [-5.6135..-4.0672] \| it/evals=833/6643 eff=13.3429% N=400 Z=-6.6(7.32%) \| Like=-4.02..-0.09 [-4.0647..-3.3420] \| it/evals=850/6812 eff=13.2564% N=400 Mono-modal Volume: ~exp(-6.27) Expected Volume: exp(-2.25) Quality: ok param0: +0.00\| ******************************************** * \| +1.00 param1: +0.00\| ***************************** ********** * * \| +1.00 param2: +0.00\| **************************************** * \| +1.00 Z=-6.4(8.79%) \| Like=-3.72..-0.09 [-4.0647..-3.3420] \| it/evals=900/7355 eff=12.9403% N=400 Z=-6.3(10.10%) \| Like=-3.52..-0.09 [-4.0647..-3.3420] \| it/evals=931/7708 eff=12.7395% N=400 Z=-6.2(10.82%) \| Like=-3.41..-0.09 [-4.0647..-3.3420] \| it/evals=950/7916 eff=12.6397% N=400 Have 2 modes Volume: ~exp(-6.67) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00\| 11111111111111111111111112122222222222222222 \| +1.00 param1: +0.00\| 111111111111111111111211112222 222222222222 2 \| +1.00 param2: +0.00\| 111111111111111111111121222222222 2222222 2 2 \| +1.00 Z=-6.1(12.60%) \| Like=-3.20..-0.09 [-3.3410..-3.0931] \| it/evals=990/8392 eff=12.3874% N=400 Z=-6.0(13.11%) \| Like=-3.16..-0.09 [-3.3410..-3.0931] \| it/evals=1000/8504 eff=12.3396% N=400 Z=-5.9(15.68%) \| Like=-2.92..-0.08 [-2.9200..-2.9077] \| it/evals=1050/9085 eff=12.0898% N=400 Have 2 modes Volume: ~exp(-6.67) Expected Volume: exp(-2.70) Quality: ok param0: +0.00\| 101111111111111111111112202222222222222222 0 \| +1.00 param1: +0.00\| 11111111111111111111111122222022222222 222 2 \| +1.00 param2: +0.00\| 11111111111111111111112122222222202222222 2 2 \| +1.00 Z=-5.8(17.08%) \| Like=-2.79..-0.08 [-2.7904..-2.7895]\| it/evals=1080/9418 eff=11.9760% N=400 Z=-5.7(18.26%) \| Like=-2.71..-0.08 [-2.7141..-2.7100]\| it/evals=1100/9668 eff=11.8688% N=400 Z=-5.5(21.21%) \| Like=-2.53..-0.08 [-2.5297..-2.5250]\| it/evals=1150/10279 eff=11.6409% N=400 Have 2 modes Volume: ~exp(-6.67) Expected Volume: exp(-2.92) Quality: ok param0: +0.00\| 011111111111111111111122 0222222222222222 \| +1.00 param1: +0.00\| 11111111111111111111111022 20222222220202 0 \| +1.00 param2: +0.00\| 11111111111111111111122222222222 2222022 \| +1.00 Z=-5.5(22.48%) \| Like=-2.44..-0.08 [-2.4397..-2.4269] \| it/evals=1170/10530 eff=11.5499% N=400 Z=-5.4(24.15%) \| Like=-2.35..-0.08 [-2.3512..-2.3488]\| it/evals=1194/10825 eff=11.4532% N=400 Z=-5.4(24.62%) \| Like=-2.32..-0.08 [-2.3234..-2.3208]\| it/evals=1200/10907 eff=11.4210% N=400 Z=-5.3(28.27%) \| Like=-2.15..-0.08 [-2.1483..-2.1459]\| it/evals=1250/11508 eff=11.2532% N=400 Have 2 modes Volume: ~exp(-7.01) * Expected Volume: exp(-3.15) Quality: ok param0: +0.0\| 1111111111111111111112222222222222222 22 \| +1.0 param1: +0.0\| 111111111111111111111 222 2222222222222 \| +1.0 param2: +0.0\| 1111111111111111111112222222222 2222222 \| +1.0 Z=-5.2(29.10%) \| Like=-2.10..-0.08 [-2.1042..-2.1039]\| it/evals=1260/11637 eff=11.2130% N=400 Z=-5.2(31.75%) \| Like=-2.01..-0.08 [-2.0129..-2.0080]\| it/evals=1292/12038 eff=11.1016% N=400 Z=-5.2(32.35%) \| Like=-2.00..-0.08 [-2.0000..-1.9986]\| it/evals=1300/12138 eff=11.0751% N=400 Have 2 modes Volume: ~exp(-7.71) Expected Volume: exp(-3.37) Quality: ok param0: +0.0\| 1111111111111111111 22222222222222 22 \| +1.0 param1: +0.0\| 11111111111111111111 222 2222222222222 \| +1.0 param2: +0.0\| 11111111111111111111 2222222222 2222222 \| +1.0 Z=-5.0(35.87%) \| Like=-1.89..-0.08 [-1.8899..-1.8845]\| it/evals=1350/12761 eff=10.9214% N=400 Z=-5.0(38.24%) \| Like=-1.79..-0.02 [-1.7884..-1.7751] \| it/evals=1392/13266 eff=10.8192% N=400 Z=-4.9(38.84%) \| Like=-1.75..-0.02 [-1.7513..-1.7507]\| it/evals=1400/13360 eff=10.8025% N=400 Have 2 modes Volume: ~exp(-7.92) * Expected Volume: exp(-3.60) Quality: ok param0: +0.0\| 1111111111111111111 222222222222222222 \| +1.0 param1: +0.0\| 1111111111111111111 22222222222222 2 \| +1.0 param2: +0.0\| 111111111111111111 22222222222222222 \| +1.0 Z=-4.9(41.59%) \| Like=-1.66..-0.02 [-1.6556..-1.6554]\| it/evals=1440/13844 eff=10.7111% N=400 Z=-4.9(42.40%) \| Like=-1.63..-0.02 [-1.6343..-1.6335]\| it/evals=1450/13973 eff=10.6830% N=400 Z=-4.8(46.01%) \| Like=-1.55..-0.02 [-1.5472..-1.5431]\| it/evals=1495/14551 eff=10.5646% N=400 Z=-4.8(46.29%) \| Like=-1.53..-0.02 [-1.5326..-1.5303]\| it/evals=1500/14614 eff=10.5530% N=400 Have 2 modes Volume: ~exp(-7.92) Expected Volume: exp(-3.82) Quality: ok param0: +0.0\| 1111111111111111 2222222222222222 \| +1.0 param1: +0.0\| 11111111111111111 22222222222222 20 \| +1.0 param2: +0.0\| 11111111111111111 222222222222222 \| +1.0 Z=-4.7(48.36%) \| Like=-1.47..-0.02 [-1.4702..-1.4680]\| it/evals=1530/14979 eff=10.4945% N=400 Z=-4.7(49.71%) \| Like=-1.44..-0.02 [-1.4362..-1.4300]\| it/evals=1550/15211 eff=10.4652% N=400 Z=-4.7(51.78%) \| Like=-1.35..-0.01 [-1.3504..-1.3461]\| it/evals=1583/15605 eff=10.4110% N=400 Z=-4.6(53.06%) \| Like=-1.30..-0.01 [-1.3031..-1.3008]\| it/evals=1600/15817 eff=10.3782% N=400 Have 2 modes Volume: ~exp(-8.30) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0\| 1111111111111111 222222222222222 \| +1.0 param1: +0.0\| 1111111111111111 2222222222222222 \| +1.0 param2: +0.0\| 1111111111111111 222222222222222 \| +1.0 Z=-4.6(54.29%) \| Like=-1.27..-0.01 [-1.2706..-1.2704]\| it/evals=1620/16080 eff=10.3316% N=400 Z=-4.6(56.12%) \| Like=-1.23..-0.01 [-1.2284..-1.2262]\| it/evals=1650/16452 eff=10.2791% N=400 Z=-4.5(59.27%) \| Like=-1.14..-0.01 [-1.1380..-1.1364]\| it/evals=1700/17074 eff=10.1955% N=400 Have 2 modes Volume: ~exp(-8.47) Expected Volume: exp(-4.27) Quality: ok param0: +0.0\| 111111111111111 22222222222222 \| +1.0 param1: +0.0\| 1111111111111111 222222222222222 \| +1.0 param2: +0.0\| 111111111111111 22222222222222 \| +1.0 Z=-4.5(59.87%) \| Like=-1.12..-0.01 [-1.1197..-1.1195]\| it/evals=1710/17194 eff=10.1822% N=400 Z=-4.5(62.46%) \| Like=-1.05..-0.01 [-1.0464..-1.0432]\| it/evals=1750/17702 eff=10.1144% N=400 Have 2 modes Volume: ~exp(-8.60) * Expected Volume: exp(-4.50) Quality: ok param0: +0.0\| 11111111111111 222222222222 \| +1.0 param1: +0.0\| 111111111111111 2222222222222 \| +1.0 param2: +0.0\| 111111111111111 22222222222222 \| +1.0 Z=-4.4(65.56%) \| Like=-0.97..-0.01 [-0.9690..-0.9681]\| it/evals=1800/18336 eff=10.0357% N=400 Z=-4.4(68.37%) \| Like=-0.89..-0.01 [-0.8893..-0.8891]\| it/evals=1850/18945 eff=9.9757% N=400 Have 2 modes Volume: ~exp(-8.60) Expected Volume: exp(-4.73) Quality: ok param0: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111111 2222222222222 \| +1.0 param2: +0.0\| 1111111111111 22222222222 +0.8 \| +1.0 Z=-4.4(70.49%) \| Like=-0.84..-0.01 [-0.8422..-0.8382]\| it/evals=1890/19432 eff=9.9306% N=400 Z=-4.3(71.01%) \| Like=-0.82..-0.01 [-0.8157..-0.8148]\| it/evals=1900/19562 eff=9.9155% N=400 Z=-4.3(73.59%) \| Like=-0.75..-0.01 [-0.7512..-0.7507]\| it/evals=1950/20194 eff=9.8515% N=400 Have 2 modes Volume: ~exp(-9.01) Expected Volume: exp(-4.95) Quality: ok param0: +0.0\| 111111111111 222222222222 \| +1.0 param1: +0.0\| 111111111111 2222222222222 \| +1.0 param2: +0.0\| 1111111111111 22222222222 +0.8 \| +1.0 Z=-4.3(75.00%) \| Like=-0.72..-0.01 [-0.7238..-0.7236]\| it/evals=1980/20581 eff=9.8112% N=400 Z=-4.3(75.95%) \| Like=-0.70..-0.01 [-0.7031..-0.7008]\| it/evals=2000/20822 eff=9.7934% N=400 Z=-4.3(78.02%) \| Like=-0.66..-0.01 [-0.6604..-0.6602]\| it/evals=2050/21453 eff=9.7373% N=400 Have 2 modes Volume: ~exp(-9.28) Expected Volume: exp(-5.18) Quality: ok param0: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111 2222222222 +0.8 \| +1.0 Z=-4.2(78.82%) \| Like=-0.64..-0.01 [-0.6412..-0.6404]\| it/evals=2070/21704 eff=9.7165% N=400 Z=-4.2(80.07%) \| Like=-0.62..-0.01 [-0.6171..-0.6168]\| it/evals=2100/22076 eff=9.6881% N=400 Z=-4.2(81.97%) \| Like=-0.57..-0.01 [-0.5715..-0.5713]\| it/evals=2150/22712 eff=9.6361% N=400 Have 2 modes Volume: ~exp(-9.46) Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-4.2(82.34%) \| Like=-0.57..-0.01 [-0.5655..-0.5624]\| it/evals=2160/22847 eff=9.6227% N=400 Z=-4.2(83.70%) \| Like=-0.53..-0.01 [-0.5311..-0.5304]\| it/evals=2200/23365 eff=9.5798% N=400 Have 2 modes Volume: ~exp(-9.46) Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 2222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 2222222220 +0.8 \| +1.0 Z=-4.2(85.26%) \| Like=-0.48..-0.01 [-0.4844..-0.4836]\| it/evals=2250/24008 eff=9.5307% N=400 Z=-4.2(86.54%) \| Like=-0.45..-0.01 [-0.4549..-0.4543]\| it/evals=2294/24574 eff=9.4895% N=400 Z=-4.1(86.70%) \| Like=-0.45..-0.01 [-0.4495..-0.4490]\| it/evals=2300/24649 eff=9.4849% N=400 Have 2 modes Volume: ~exp(-9.95) Expected Volume: exp(-5.85) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 2222222222 +0.8 \| +1.0 Z=-4.1(87.78%) \| Like=-0.42..-0.01 [-0.4204..-0.4200]\| it/evals=2340/25153 eff=9.4534% N=400 Z=-4.1(88.04%) \| Like=-0.41..-0.01 [-0.4148..-0.4141]\| it/evals=2350/25275 eff=9.4472% N=400 Z=-4.1(89.27%) \| Like=-0.38..-0.01 [-0.3829..-0.3824]\| it/evals=2400/25898 eff=9.4125% N=400 Have 2 modes Volume: ~exp(-9.95) Expected Volume: exp(-6.08) Quality: ok param0: +0.0\| +0.2 111111111 222222220 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-4.1(90.15%) \| Like=-0.36..-0.00 [-0.3624..-0.3604]\| it/evals=2441/26436 eff=9.3755% N=400 Z=-4.1(90.34%) \| Like=-0.36..-0.00 [-0.3568..-0.3566]\| it/evals=2450/26553 eff=9.3680% N=400 Z=-4.1(91.33%) \| Like=-0.33..-0.00 [-0.3285..-0.3283]\| it/evals=2500/27193 eff=9.3308% N=400 Have 2 modes Volume: ~exp(-10.45) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-4.1(91.71%) \| Like=-0.32..-0.00 [-0.3173..-0.3168]\| it/evals=2520/27464 eff=9.3113% N=400 Z=-4.1(92.24%) \| Like=-0.31..-0.00 [-0.3087..-0.3086]\| it/evals=2550/27830 eff=9.2964% N=400 Z=-4.1(93.04%) \| Like=-0.29..-0.00 [-0.2881..-0.2873]\| it/evals=2600/28478 eff=9.2599% N=400 Have 2 modes Volume: ~exp(-10.62) Expected Volume: exp(-6.53) Quality: ok param0: +0.0\| +0.2 11111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 22222222 +0.8 \| +1.0 Z=-4.1(93.20%) \| Like=-0.28..-0.00 [-0.2850..-0.2847]\| it/evals=2610/28600 eff=9.2553% N=400 Z=-4.1(93.79%) \| Like=-0.27..-0.00 [-0.2716..-0.2709]\| it/evals=2650/29105 eff=9.2318% N=400 Z=-4.1(94.36%) \| Like=-0.25..-0.00 [-0.2496..-0.2490]\| it/evals=2693/29648 eff=9.2075% N=400 Have 2 modes Volume: ~exp(-10.83) Expected Volume: exp(-6.75) Quality: ok param0: +0.0\| +0.2 11111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-4.1(94.45%) \| Like=-0.25..-0.00 [-0.2466..-0.2462]\| it/evals=2700/29732 eff=9.2050% N=400 Z=-4.1(94.98%) \| Like=-0.23..-0.00 [-0.2291..-0.2278]\| it/evals=2744/30300 eff=9.1773% N=400 Z=-4.1(95.04%) \| Like=-0.23..-0.00 [-0.2258..-0.2255]\| it/evals=2750/30391 eff=9.1694% N=400 Have 2 modes Volume: ~exp(-11.14) Expected Volume: exp(-6.98) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-4.1(95.48%) \| Like=-0.21..-0.00 [-0.2126..-0.2123]\| it/evals=2790/30921 eff=9.1412% N=400 Z=-4.1(95.58%) \| Like=-0.21..-0.00 [-0.2091..-0.2089]\| it/evals=2800/31041 eff=9.1381% N=400 Z=-4.0(96.01%) \| Like=-0.19..-0.00 [-0.1928..-0.1925]\| it/evals=2844/31594 eff=9.1171% N=400 Z=-4.0(96.07%) \| Like=-0.19..-0.00 [-0.1902..-0.1901]\| it/evals=2850/31675 eff=9.1127% N=400 Have 2 modes Volume: ~exp(-11.42) * Expected Volume: exp(-7.20) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-4.0(96.33%) \| Like=-0.18..-0.00 [-0.1833..-0.1832]\| it/evals=2880/32048 eff=9.1001% N=400 Z=-4.0(96.49%) \| Like=-0.18..-0.00 [-0.1782..-0.1781]\| it/evals=2900/32311 eff=9.0878% N=400 Z=-4.0(96.83%) \| Like=-0.17..-0.00 [-0.1675..-0.1669]\| it/evals=2943/32833 eff=9.0741% N=400 Z=-4.0(96.88%) \| Like=-0.16..-0.00 [-0.1648..-0.1645]\| it/evals=2950/32923 eff=9.0705% N=400 Have 2 modes Volume: ~exp(-11.42) Expected Volume: exp(-7.43) Quality: ok param0: +0.0\| +0.2 1111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 222222 +0.7 \| +1.0 Z=-4.0(97.02%) \| Like=-0.16..-0.00 [-0.1614..-0.1611]\| it/evals=2970/33174 eff=9.0621% N=400 Z=-4.0(97.23%) \| Like=-0.15..-0.00 [-0.1539..-0.1538]\| it/evals=3000/33563 eff=9.0462% N=400 Z=-4.0(97.47%) \| Like=-0.15..-0.00 [-0.1456..-0.1453]\| it/evals=3039/34090 eff=9.0205% N=400 Z=-4.0(97.54%) \| Like=-0.14..-0.00 [-0.1426..-0.1424]\| it/evals=3050/34221 eff=9.0181% N=400 Have 2 modes Volume: ~exp(-11.68) * Expected Volume: exp(-7.65) Quality: ok param0: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 param1: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 Z=-4.0(97.60%) \| Like=-0.14..-0.00 [-0.1394..-0.1392]\| it/evals=3060/34354 eff=9.0122% N=400 Z=-4.0(97.81%) \| Like=-0.13..-0.00 [-0.1322..-0.1321]\| it/evals=3100/34883 eff=8.9899% N=400 Z=-4.0(98.02%) \| Like=-0.12..-0.00 [-0.1223..-0.1220]\| it/evals=3143/35417 eff=8.9756% N=400 Have 2 modes Volume: ~exp(-11.73) Expected Volume: exp(-7.88) Quality: ok param0: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 param1: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.05%) \| Like=-0.12..-0.00 [-0.1206..-0.1205]\| it/evals=3150/35507 eff=8.9726% N=400 Z=-4.0(98.24%) \| Like=-0.11..-0.00 [-0.1100..-0.1097]\| it/evals=3193/36038 eff=8.9595% N=400 Z=-4.0(98.27%) \| Like=-0.11..-0.00 [-0.1078..-0.1076]\| it/evals=3200/36124 eff=8.9576% N=400 Have 2 modes Volume: ~exp(-12.22) Expected Volume: exp(-8.10) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.43%) \| Like=-0.10..-0.00 [-0.1010..-0.1010]\| it/evals=3240/36655 eff=8.9367% N=400 Z=-4.0(98.47%) \| Like=-0.10..-0.00 [-0.0986..-0.0983]\| it/evals=3250/36780 eff=8.9335% N=400 Z=-4.0(98.62%) \| Like=-0.09..-0.00 [-0.0918..-0.0917]\| it/evals=3293/37322 eff=8.9188% N=400 Z=-4.0(98.64%) \| Like=-0.09..-0.00 [-0.0902..-0.0897]\| it/evals=3300/37422 eff=8.9136% N=400 Have 2 modes Volume: ~exp(-12.38) * Expected Volume: exp(-8.33) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.73%) \| Like=-0.09..-0.00 [-0.0855..-0.0854]\| it/evals=3330/37809 eff=8.9016% N=400 Z=-4.0(98.80%) \| Like=-0.08..-0.00 [-0.0822..-0.0821]\| it/evals=3350/38060 eff=8.8954% N=400 Z=-4.0(98.91%) \| Like=-0.08..-0.00 [-0.0762..-0.0761]\| it/evals=3393/38586 eff=8.8855% N=400 Z=-4.0(98.93%) \| Like=-0.08..-0.00 [-0.0756..-0.0756]\| it/evals=3400/38675 eff=8.8831% N=400 Have 2 modes Volume: ~exp(-12.47) * Expected Volume: exp(-8.55) Quality: ok param0: +0.0\| +0.3 1111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 1111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.98%) \| Like=-0.07..-0.00 [-0.0736..-0.0734]*\| it/evals=3420/38930 eff=8.8762% N=400 [ultranest] Explored until L=-0.0002 [ultranest] Likelihood function evaluations: 39002 [ultranest] logZ = -4.026 +- 0.0611 [ultranest] Effective samples strategy satisfied (ESS = 2022.3, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -4.005 +- 0.069 single instance: logZ = -4.005 +- 0.075 bootstrapped : logZ = -4.026 +- 0.068 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▂▂▃▄▅▇▇▇▇▆▆▅▄▂▂▂▁▁▁▁▁▂▂▂▂▂▁▁▁▁▁▁▁▁▁ │1.00 0.34 +- 0.18 param1 : 0.00 │▁▁▁▂▂▃▄▄▆▇▇▆▇▅▅▄▃▂▂▁▁▁▁▂▁▂▁▂▂▂▂▁▁▁▁▁▁▁▁│1.00 0.34 +- 0.18 param2 : 0.00 │▁▁▁▂▃▄▅▅▆▇▆▆▅▆▅▆▄▂▂▂▁▁▁▁▂▁▂▂▂▁▂▁▁▁▁▁▁ ▁│1.00 0.34 +- 0.19 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=403, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-29.79, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=610, regioncalls=0, ndraw=40, logz=-25.50, remainder_fraction=100.0000%, Lmin=-21.14, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=795, regioncalls=0, ndraw=40, logz=-21.17, remainder_fraction=100.0000%, Lmin=-17.35, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=837, regioncalls=0, ndraw=40, logz=-20.38, remainder_fraction=100.0000%, Lmin=-16.81, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1090, regioncalls=0, ndraw=40, logz=-16.72, remainder_fraction=99.9997%, Lmin=-12.91, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=1249, regioncalls=0, ndraw=40, logz=-15.11, remainder_fraction=99.9983%, Lmin=-11.75, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1383, regioncalls=0, ndraw=40, logz=-14.23, remainder_fraction=99.9958%, Lmin=-10.89, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1671, regioncalls=0, ndraw=40, logz=-12.49, remainder_fraction=99.9769%, Lmin=-9.35, Lmax=-0.38 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1813, regioncalls=0, ndraw=40, logz=-11.95, remainder_fraction=99.9607%, Lmin=-9.00, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=2027, regioncalls=0, ndraw=40, logz=-11.29, remainder_fraction=99.9307%, Lmin=-8.45, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2363, regioncalls=0, ndraw=40, logz=-10.44, remainder_fraction=99.8265%, Lmin=-7.77, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2429, regioncalls=0, ndraw=40, logz=-10.29, remainder_fraction=99.7982%, Lmin=-7.63, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=2696, regioncalls=0, ndraw=40, logz=-9.75, remainder_fraction=99.6485%, Lmin=-7.14, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3055, regioncalls=0, ndraw=40, logz=-9.21, remainder_fraction=99.4312%, Lmin=-6.70, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3463, regioncalls=0, ndraw=40, logz=-8.74, remainder_fraction=99.0936%, Lmin=-6.24, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=3829, regioncalls=0, ndraw=40, logz=-8.39, remainder_fraction=98.6729%, Lmin=-5.86, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3922, regioncalls=0, ndraw=40, logz=-8.31, remainder_fraction=98.5540%, Lmin=-5.77, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=589, ncalls=4254, regioncalls=0, ndraw=40, logz=-8.02, remainder_fraction=98.0899%, Lmin=-5.49, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=4332, regioncalls=0, ndraw=40, logz=-7.94, remainder_fraction=97.9334%, Lmin=-5.38, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=4604, regioncalls=0, ndraw=40, logz=-7.74, remainder_fraction=97.6390%, Lmin=-5.21, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=4777, regioncalls=0, ndraw=40, logz=-7.61, remainder_fraction=97.2967%, Lmin=-5.04, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5283, regioncalls=0, ndraw=40, logz=-7.30, remainder_fraction=96.4418%, Lmin=-4.69, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5475, regioncalls=0, ndraw=40, logz=-7.19, remainder_fraction=96.0516%, Lmin=-4.63, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=5779, regioncalls=0, ndraw=40, logz=-7.04, remainder_fraction=95.3727%, Lmin=-4.51, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=795, ncalls=6235, regioncalls=0, ndraw=40, logz=-6.83, remainder_fraction=94.2727%, Lmin=-4.29, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=6303, regioncalls=0, ndraw=40, logz=-6.81, remainder_fraction=94.1019%, Lmin=-4.26, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=833, ncalls=6643, regioncalls=0, ndraw=40, logz=-6.67, remainder_fraction=93.1833%, Lmin=-4.10, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=6812, regioncalls=0, ndraw=40, logz=-6.60, remainder_fraction=92.6813%, Lmin=-4.02, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=7355, regioncalls=0, ndraw=40, logz=-6.41, remainder_fraction=91.2110%, Lmin=-3.72, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=931, ncalls=7708, regioncalls=0, ndraw=40, logz=-6.29, remainder_fraction=89.8998%, Lmin=-3.52, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=7916, regioncalls=0, ndraw=40, logz=-6.22, remainder_fraction=89.1798%, Lmin=-3.41, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=8392, regioncalls=0, ndraw=40, logz=-6.07, remainder_fraction=87.3989%, Lmin=-3.20, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=8504, regioncalls=0, ndraw=40, logz=-6.03, remainder_fraction=86.8950%, Lmin=-3.16, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=9085, regioncalls=0, ndraw=40, logz=-5.85, remainder_fraction=84.3177%, Lmin=-2.92, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=9418, regioncalls=0, ndraw=40, logz=-5.75, remainder_fraction=82.9231%, Lmin=-2.79, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=9668, regioncalls=0, ndraw=40, logz=-5.69, remainder_fraction=81.7374%, Lmin=-2.71, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=10279, regioncalls=0, ndraw=40, logz=-5.54, remainder_fraction=78.7871%, Lmin=-2.53, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=10530, regioncalls=0, ndraw=40, logz=-5.48, remainder_fraction=77.5202%, Lmin=-2.44, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=10825, regioncalls=0, ndraw=40, logz=-5.42, remainder_fraction=75.8531%, Lmin=-2.35, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=10907, regioncalls=0, ndraw=40, logz=-5.40, remainder_fraction=75.3778%, Lmin=-2.32, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=11508, regioncalls=0, ndraw=40, logz=-5.27, remainder_fraction=71.7301%, Lmin=-2.15, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=11637, regioncalls=0, ndraw=40, logz=-5.25, remainder_fraction=70.9030%, Lmin=-2.10, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1292, ncalls=12038, regioncalls=0, ndraw=40, logz=-5.17, remainder_fraction=68.2516%, Lmin=-2.01, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=12138, regioncalls=0, ndraw=40, logz=-5.15, remainder_fraction=67.6453%, Lmin=-2.00, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=12761, regioncalls=0, ndraw=40, logz=-5.04, remainder_fraction=64.1257%, Lmin=-1.89, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=1392, ncalls=13266, regioncalls=0, ndraw=40, logz=-4.96, remainder_fraction=61.7599%, Lmin=-1.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=13360, regioncalls=0, ndraw=40, logz=-4.95, remainder_fraction=61.1587%, Lmin=-1.75, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=13844, regioncalls=0, ndraw=40, logz=-4.88, remainder_fraction=58.4052%, Lmin=-1.66, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=13973, regioncalls=0, ndraw=40, logz=-4.86, remainder_fraction=57.5990%, Lmin=-1.63, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1495, ncalls=14551, regioncalls=0, ndraw=40, logz=-4.79, remainder_fraction=53.9852%, Lmin=-1.55, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=14614, regioncalls=0, ndraw=40, logz=-4.78, remainder_fraction=53.7100%, Lmin=-1.53, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=14979, regioncalls=0, ndraw=40, logz=-4.74, remainder_fraction=51.6443%, Lmin=-1.47, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=15211, regioncalls=0, ndraw=40, logz=-4.71, remainder_fraction=50.2907%, Lmin=-1.44, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1583, ncalls=15605, regioncalls=0, ndraw=40, logz=-4.67, remainder_fraction=48.2218%, Lmin=-1.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=15817, regioncalls=0, ndraw=40, logz=-4.64, remainder_fraction=46.9370%, Lmin=-1.30, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=16080, regioncalls=0, ndraw=40, logz=-4.62, remainder_fraction=45.7066%, Lmin=-1.27, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=16452, regioncalls=0, ndraw=40, logz=-4.58, remainder_fraction=43.8794%, Lmin=-1.23, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=17074, regioncalls=0, ndraw=40, logz=-4.53, remainder_fraction=40.7294%, Lmin=-1.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=17194, regioncalls=0, ndraw=40, logz=-4.52, remainder_fraction=40.1298%, Lmin=-1.12, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=17702, regioncalls=0, ndraw=40, logz=-4.48, remainder_fraction=37.5440%, Lmin=-1.05, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=18336, regioncalls=0, ndraw=40, logz=-4.43, remainder_fraction=34.4414%, Lmin=-0.97, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=18945, regioncalls=0, ndraw=40, logz=-4.39, remainder_fraction=31.6316%, Lmin=-0.89, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=19432, regioncalls=0, ndraw=40, logz=-4.36, remainder_fraction=29.5071%, Lmin=-0.84, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=19562, regioncalls=0, ndraw=40, logz=-4.35, remainder_fraction=28.9938%, Lmin=-0.82, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=20194, regioncalls=0, ndraw=40, logz=-4.31, remainder_fraction=26.4054%, Lmin=-0.75, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=20581, regioncalls=0, ndraw=40, logz=-4.29, remainder_fraction=24.9952%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=20822, regioncalls=0, ndraw=40, logz=-4.28, remainder_fraction=24.0525%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=21453, regioncalls=0, ndraw=40, logz=-4.25, remainder_fraction=21.9843%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=21704, regioncalls=0, ndraw=40, logz=-4.24, remainder_fraction=21.1760%, Lmin=-0.64, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=22076, regioncalls=0, ndraw=40, logz=-4.23, remainder_fraction=19.9257%, Lmin=-0.62, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=22712, regioncalls=0, ndraw=40, logz=-4.20, remainder_fraction=18.0264%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=22847, regioncalls=0, ndraw=40, logz=-4.20, remainder_fraction=17.6635%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=23365, regioncalls=0, ndraw=40, logz=-4.18, remainder_fraction=16.3015%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=24008, regioncalls=0, ndraw=40, logz=-4.17, remainder_fraction=14.7366%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2294, ncalls=24574, regioncalls=0, ndraw=40, logz=-4.15, remainder_fraction=13.4644%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=24649, regioncalls=0, ndraw=40, logz=-4.15, remainder_fraction=13.2953%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=25153, regioncalls=0, ndraw=40, logz=-4.14, remainder_fraction=12.2177%, Lmin=-0.42, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=25275, regioncalls=0, ndraw=40, logz=-4.13, remainder_fraction=11.9556%, Lmin=-0.41, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=25898, regioncalls=0, ndraw=40, logz=-4.12, remainder_fraction=10.7269%, Lmin=-0.38, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2441, ncalls=26436, regioncalls=0, ndraw=40, logz=-4.11, remainder_fraction=9.8469%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=26553, regioncalls=0, ndraw=40, logz=-4.11, remainder_fraction=9.6603%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=27193, regioncalls=0, ndraw=40, logz=-4.10, remainder_fraction=8.6694%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=27464, regioncalls=0, ndraw=40, logz=-4.09, remainder_fraction=8.2863%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=27830, regioncalls=0, ndraw=40, logz=-4.09, remainder_fraction=7.7593%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=28478, regioncalls=0, ndraw=40, logz=-4.08, remainder_fraction=6.9554%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=28600, regioncalls=0, ndraw=40, logz=-4.08, remainder_fraction=6.7989%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=29105, regioncalls=0, ndraw=40, logz=-4.07, remainder_fraction=6.2102%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2693, ncalls=29648, regioncalls=0, ndraw=40, logz=-4.06, remainder_fraction=5.6392%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=29732, regioncalls=0, ndraw=40, logz=-4.06, remainder_fraction=5.5504%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2744, ncalls=30300, regioncalls=0, ndraw=40, logz=-4.06, remainder_fraction=5.0249%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=30391, regioncalls=0, ndraw=40, logz=-4.06, remainder_fraction=4.9592%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=30921, regioncalls=0, ndraw=40, logz=-4.05, remainder_fraction=4.5223%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=31041, regioncalls=0, ndraw=40, logz=-4.05, remainder_fraction=4.4183%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2844, ncalls=31594, regioncalls=0, ndraw=40, logz=-4.05, remainder_fraction=3.9906%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=31675, regioncalls=0, ndraw=40, logz=-4.05, remainder_fraction=3.9339%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=32048, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=3.6723%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=32311, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=3.5053%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2943, ncalls=32833, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=3.1716%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=32923, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=3.1213%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=33174, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=2.9760%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=33563, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=2.7719%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3039, ncalls=34090, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=2.5267%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=34221, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=2.4618%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=34354, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=2.4050%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=34883, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=2.1887%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3143, ncalls=35417, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=1.9788%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=35507, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.9462%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3193, ncalls=36038, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.7571%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=36124, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.7281%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=36655, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.5707%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3250, ncalls=36780, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.5338%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3293, ncalls=37322, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.3831%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3300, ncalls=37422, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.3601%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=37809, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.2652%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=38060, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.2049%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3393, ncalls=38586, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.0853%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=38675, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.0670%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=38930, regioncalls=0, ndraw=40, logz=-4.02, remainder_fraction=1.0167%, Lmin=-0.07, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.0002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39002 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -4.026 +- 0.0611 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2022.3, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_samplingpath.py::test_reversible_gradient	1.67
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 1 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] chose normal [-0.14594849 -0.98929219] 33 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] reflecting with [-0.84015394 -0.54234801] new direction [-0.03645513 0.01646278] re-reflecting gives direction [6.48453852e-06 3.99999995e-02] FORWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] BACKWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] setting seed = 2 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] chose normal [-0.55268598 -0.83338959] 75 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] reflecting with [-0.38762042 -0.92181908] new direction [-0.03999471 0.00065022] re-reflecting gives direction [-0.028441 0.02812667] FORWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] BACKWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] setting seed = 3 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] chose normal [-0.96649142 0.25669891] 45 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] reflecting with [-0.98467624 0.17439239] new direction [-0.02217288 -0.03329209] re-reflecting gives direction [ 0.00939036 -0.03888214] FORWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] BACKWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] setting seed = 4 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] chose normal [-0.97238131 -0.23339792] 0 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] reflecting with [-0.97238131 -0.23339792] new direction [-0.03230892 -0.02358248] re-reflecting gives direction [ 0.03949306 -0.00634806] FORWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] BACKWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] setting seed = 5 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] chose normal [0.31678437 0.94849758] 12 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] reflecting with [-0.33575666 0.94194876] new direction [0.0091709 0.03893449] re-reflecting gives direction [ 0.03173046 -0.02435524] FORWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] BACKWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] setting seed = 6 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] chose normal [0.83159266 0.55538603] 69 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] reflecting with [ 0.43246121 -0.90165254] new direction [-0.03368751 -0.02156737] re-reflecting gives direction [-0.03790637 -0.01277133] FORWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] BACKWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] setting seed = 7 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] chose normal [-0.99882119 0.04854104] 39 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] reflecting with [ 0.77093646 -0.63691206] new direction [0.02773823 0.02881997] re-reflecting gives direction [0.02306847 0.0326779 ] FORWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] BACKWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] setting seed = 8 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] chose normal [0.34627653 0.93813249] 99 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] reflecting with [0.34760793 0.93763998] new direction [ 0.03876506 -0.00986257] re-reflecting gives direction [ 0.03582603 -0.01779032] FORWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] BACKWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] setting seed = 9 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] chose normal [ 0.99593603 -0.09006347] 4 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] reflecting with [0.97389943 0.22697994] new direction [0.02917942 0.02735986] re-reflecting gives direction [-0.03826888 0.01164015] FORWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] BACKWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] setting seed = 10 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] chose normal [ 0.22487937 -0.97438661] 90 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] reflecting with [ 0.22487937 -0.97438661] new direction [0.03996017 0.00178454] re-reflecting gives direction [0.0367006 0.01590805] FORWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] BACKWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] setting seed = 11 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] chose normal [0.54430488 0.83888747] 16 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] reflecting with [0.82811727 0.56055489] new direction [0.0060231 0.03954393] re-reflecting gives direction [-0.03895091 0.0091009 ] FORWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] BACKWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] setting seed = 12 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] chose normal [-0.99011844 0.14023365] 82 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] reflecting with [-0.86634575 0.49944472] new direction [0.00495484 0.03969193] re-reflecting gives direction [0.03186583 0.02417786] FORWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] BACKWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] setting seed = 13 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] chose normal [-0.98685102 0.16163249] 5 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] reflecting with [-0.93229687 0.36169401] new direction [0.00745422 0.0392993 ] re-reflecting gives direction [0.02100007 0.03404404] FORWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] BACKWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] setting seed = 14 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] chose normal [ 0.82456261 -0.56577072] 96 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] reflecting with [0.77339836 0.63392033] new direction [-0.02433225 0.0317481 ] re-reflecting gives direction [-0.02635429 0.03009072] FORWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] BACKWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] setting seed = 15 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] chose normal [ 0.98353428 -0.18072169] 52 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] reflecting with [ 0.95341068 -0.30167545] new direction [ 0.01323002 -0.03774873] re-reflecting gives direction [-0.03253657 -0.0232674 ] FORWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] BACKWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] setting seed = 16 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] chose normal [0.98410666 0.17757839] 28 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] reflecting with [ 0.93475612 -0.35529003] new direction [ 0.01340794 -0.0376859 ] re-reflecting gives direction [-0.03505464 -0.01926583] FORWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] BACKWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] setting seed = 17 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] chose normal [0.77877968 0.62729755] 76 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] reflecting with [ 0.82081006 -0.57120123] new direction [-0.01456347 -0.0372546 ] re-reflecting gives direction [-0.02987327 -0.02660052] FORWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] BACKWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] setting seed = 18 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] chose normal [-0.33803901 -0.9411321 ] 41 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] reflecting with [-0.34524316 0.93851327] new direction [0.03651456 0.01633055] re-reflecting gives direction [0.03839271 0.01122497] FORWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] BACKWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] setting seed = 19 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] chose normal [0.93844564 0.34542696] 79 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] reflecting with [ 0.99641622 -0.08458558] new direction [-0.00263833 -0.0399129 ] re-reflecting gives direction [-0.00412734 -0.03978649] FORWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] BACKWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] setting seed = 20 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] chose normal [ 0.02238176 -0.9997495 ] 63 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] reflecting with [-0.98569607 0.16853264] new direction [-0.0285175 0.02804911] re-reflecting gives direction [0.03621666 0.01698097] FORWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] BACKWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] setting seed = 21 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] chose normal [0.69255841 0.7213618 ] 45 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] reflecting with [0.64446979 0.76462977] new direction [ 0.03965328 -0.00525524] re-reflecting gives direction [ 0.01189335 -0.03819094] FORWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] BACKWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] setting seed = 22 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] chose normal [0.73205365 0.68124698] 97 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] reflecting with [-0.09378428 0.99559254] new direction [-0.03999511 0.00062567] re-reflecting gives direction [-0.03917472 -0.00808342] FORWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] BACKWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] setting seed = 23 reflecting at [0.13591686 0.30336076] with direction [-0.00025999 0.03999916] setting seed = 24 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] chose normal [-0.53400133 0.84548364] 50 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] reflecting with [0.94624486 0.32345119] new direction [ 0.0391631 -0.00813953] re-reflecting gives direction [-0.02598612 -0.03040923] FORWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] BACKWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] setting seed = 25 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] chose normal [-0.97667717 0.21471306] 60 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] reflecting with [-0.63178483 0.77514381] new direction [0.02932087 0.02720821] re-reflecting gives direction [0.03256293 0.02323049] FORWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] BACKWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] setting seed = 26 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] chose normal [-0.50091154 0.86549848] 85 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] reflecting with [-0.85384138 0.52053328] new direction [-0.02180062 0.03353704] re-reflecting gives direction [ 0.03979792 -0.0040157 ] FORWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] BACKWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] setting seed = 27 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] chose normal [ 0.92407929 -0.38220081] 25 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] reflecting with [-0.97547221 -0.22012263] new direction [-0.01602001 0.03665187] re-reflecting gives direction [-0.00127249 0.03997975] FORWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] BACKWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] setting seed = 28 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] chose normal [ 0.25028455 -0.96817232] 53 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] reflecting with [-0.0753835 -0.99715462] new direction [-0.03451679 -0.02021364] re-reflecting gives direction [-0.03108561 0.02517309] FORWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] BACKWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] setting seed = 29 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] chose normal [ 0.93787043 -0.34698568] 15 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] reflecting with [0.8970119 0.44200639] new direction [-0.00691923 0.03939701] re-reflecting gives direction [-0.02702503 0.02948979] FORWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] BACKWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] setting seed = 30 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] chose normal [-0.94320997 -0.33219716] 57 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] reflecting with [-0.53412191 -0.84540746] new direction [-0.03946637 -0.00651194] re-reflecting gives direction [-0.01106701 0.03843854] FORWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] BACKWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] setting seed = 31 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] chose normal [ 0.91849248 -0.39543844] 40 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] reflecting with [-0.99751744 -0.0704199 ] new direction [-0.01171731 0.03824532] re-reflecting gives direction [0.00622801 0.03951217] FORWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] BACKWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] setting seed = 32 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] chose normal [-0.86603501 0.49998337] 44 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] reflecting with [0.78359729 0.6212691 ] new direction [ 0.02794233 -0.02862213] re-reflecting gives direction [ 0.02149569 -0.0337333 ] FORWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] BACKWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] setting seed = 33 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] chose normal [ 0.94116632 -0.33794371] 14 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] reflecting with [ 0.41089806 -0.91168129] new direction [ 0.03504567 -0.01928214] re-reflecting gives direction [0.00876515 0.03902784] FORWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] BACKWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] setting seed = 34 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] chose normal [-0.9662808 -0.2574906] 59 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] reflecting with [-0.99996226 -0.00868732] new direction [-0.02541174 0.03089083] re-reflecting gives direction [0.0248712 0.03132767] FORWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] BACKWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] setting seed = 35 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] chose normal [ 0.81909097 -0.57366365] 13 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] reflecting with [0.99064996 0.13642818] new direction [ 0.03950549 -0.00627028] re-reflecting gives direction [-0.03633999 -0.01671541] FORWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] BACKWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] setting seed = 36 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] chose normal [ 0.99395085 -0.10982581] 7 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] reflecting with [-0.98326229 -0.18219571] new direction [-0.00800478 0.03919086] re-reflecting gives direction [-0.00656845 0.03945701] FORWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] BACKWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] setting seed = 37 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] chose normal [0.24749873 0.96888822] 9 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] reflecting with [0.9968224 0.07965612] new direction [ 0.03964894 -0.00528788] re-reflecting gives direction [-0.03830604 -0.01151726] FORWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] BACKWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] setting seed = 38 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] chose normal [-0.47920534 0.87770282] 91 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] reflecting with [0.07106544 0.99747166] new direction [0.01077519 0.03852136] re-reflecting gives direction [ 0.00520512 -0.03965989] FORWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] BACKWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] setting seed = 39 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] chose normal [-0.96803752 0.25080543] 26 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] reflecting with [ 0.48195217 -0.87619753] new direction [0.03565683 0.01812707] re-reflecting gives direction [0.03440183 0.02040867] FORWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] BACKWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] setting seed = 40 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] chose normal [ 0.99762991 -0.06880816] 34 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] reflecting with [ 0.98422636 -0.17691375] new direction [-0.00574414 -0.03958541] re-reflecting gives direction [-0.0084009 -0.03910786] FORWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] BACKWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] setting seed = 41 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] chose normal [-0.39185582 0.92002664] 4 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] reflecting with [-0.80640044 0.59136988] new direction [-0.03753422 0.01382688] re-reflecting gives direction [ 0.02446896 -0.03164285] FORWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] BACKWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] setting seed = 42 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] chose normal [0.95525297 0.29579006] 28 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] reflecting with [-0.70398882 -0.71021105] new direction [-0.03501649 0.01933508] re-reflecting gives direction [-0.01964246 0.034845 ] FORWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] BACKWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] setting seed = 43 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] chose normal [-0.59139425 0.80638257] 29 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] reflecting with [-0.63872083 0.76943856] new direction [-0.03094035 -0.02535142] re-reflecting gives direction [-0.03061347 -0.0257452 ] FORWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] BACKWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] setting seed = 44 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] chose normal [ 0.99893451 -0.04615032] 29 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] reflecting with [-0.69018106 0.72363672] new direction [-0.03900915 -0.00884794] re-reflecting gives direction [-0.01068318 -0.03854698] FORWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] BACKWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] setting seed = 45 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] chose normal [ 0.06446741 -0.99791981] 84 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] reflecting with [ 0.06446741 -0.99791981] new direction [-0.03980439 -0.00395101] re-reflecting gives direction [-0.0399819 -0.00120333] FORWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] BACKWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] setting seed = 46 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] chose normal [ 0.9478891 -0.31860046] 70 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] reflecting with [0.99984603 0.01754771] new direction [0.02044956 0.03437754] re-reflecting gives direction [-0.02164327 0.0336388 ] FORWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] BACKWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] setting seed = 47 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] chose normal [0.74369889 0.66851474] 81 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] reflecting with [ 0.9436164 -0.33104091] new direction [ 0.0163875 -0.03648904] re-reflecting gives direction [-0.03559232 -0.0182534 ] FORWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] BACKWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] setting seed = 48 reflecting at [0.14141263 0.72381215] with direction [ 0.01008992 -0.03870651] setting seed = 49 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] chose normal [ 0.78315843 -0.62182223] 61 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] reflecting with [0.98231877 0.187216 ] new direction [ 0.0370356 -0.01511173] re-reflecting gives direction [-0.02888115 -0.02767453] FORWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] BACKWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] setting seed = 50 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] chose normal [-0.9091523 -0.4164638] 59 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] reflecting with [-0.95815198 -0.28626 ] new direction [-0.02615101 0.03026755] re-reflecting gives direction [0.00526153 0.03965244] FORWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] BACKWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] setting seed = 51 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] chose normal [-0.99167671 -0.12875285] 11 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] reflecting with [-0.91529383 0.4027868 ] new direction [0.00204569 0.03994765] re-reflecting gives direction [0.02807295 0.02849403] FORWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] BACKWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] setting seed = 52 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] chose normal [0.97430448 0.22523493] 14 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] reflecting with [0.49373504 0.86961239] new direction [-0.00271496 0.03990776] re-reflecting gives direction [-0.03566072 -0.01811941] FORWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] BACKWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] setting seed = 53 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] chose normal [-0.78010783 0.62564509] 68 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] reflecting with [ 0.99116492 -0.13263523] new direction [ 0.00409791 -0.03978954] re-reflecting gives direction [-0.01441546 -0.03731212] FORWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] BACKWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] setting seed = 54 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] chose normal [0.97346802 0.2288231 ] 2 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] reflecting with [ 0.89562093 -0.44481812] new direction [ 0.00894519 -0.03898697] re-reflecting gives direction [-0.03646926 -0.01643148] FORWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] BACKWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] setting seed = 55 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] chose normal [0.7228596 0.69099493] 3 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] reflecting with [-0.98267299 0.18534775] new direction [-0.01147429 -0.03831893] re-reflecting gives direction [-0.00327261 -0.0398659 ] FORWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] BACKWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] setting seed = 56 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] chose normal [0.6437137 0.7652664] 92 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] reflecting with [0.6437137 0.7652664] new direction [ 0.03742321 -0.01412455] re-reflecting gives direction [ 0.02032516 -0.03445124] FORWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] BACKWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] setting seed = 57 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] chose normal [-0.9653418 -0.26098892] 66 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] reflecting with [-0.95158108 -0.30739787] new direction [-0.01673815 -0.03632952] re-reflecting gives direction [ 0.03482865 -0.01967144] FORWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] BACKWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] setting seed = 58 reflecting at [0.00831403 0.22576864] with direction [0.03708157 0.01499858] setting seed = 59 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] chose normal [ 0.96677775 -0.25561844] 29 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] reflecting with [ 0.9754194 -0.22035653] new direction [ 0.02933405 -0.027194 ] re-reflecting gives direction [-0.03817546 -0.01194295] FORWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] BACKWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] setting seed = 60 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] chose normal [-0.99186614 -0.12728533] 21 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] reflecting with [0.11689192 0.99314464] new direction [0.02795024 0.02861441] re-reflecting gives direction [ 0.0205427 -0.03432197] FORWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] BACKWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] setting seed = 61 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] chose normal [-0.96739827 -0.25325991] 26 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] reflecting with [-0.96012904 -0.2795572 ] new direction [-0.00353274 -0.03984369] re-reflecting gives direction [ 0.02436953 -0.03171949] FORWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] BACKWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] setting seed = 62 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] chose normal [0.93863157 0.34492141] 54 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] reflecting with [0.98471485 0.17417424] new direction [0.03829817 0.0115434 ] re-reflecting gives direction [-0.03993416 -0.00229416] FORWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] BACKWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] setting seed = 63 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] chose normal [-0.99656293 0.08283919] 19 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] reflecting with [-0.99966777 -0.02577498] new direction [-0.02770486 -0.02885205] re-reflecting gives direction [ 0.02915488 -0.027386 ] FORWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] BACKWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] setting seed = 64 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] chose normal [0.0269266 0.99963741] 88 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] reflecting with [0.16834631 0.98572791] new direction [0.0379336 0.01269023] re-reflecting gives direction [ 0.03157176 -0.02456061] FORWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] BACKWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] setting seed = 65 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] chose normal [ 0.87714796 -0.48022022] 19 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] reflecting with [ 0.99603093 -0.08900784] new direction [0.03420944 0.02072954] re-reflecting gives direction [-0.02999187 0.02646673] FORWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] BACKWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] setting seed = 66 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] chose normal [ 0.37536664 -0.92687641] 71 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] reflecting with [-0.94506677 0.32687734] new direction [-0.0121731 0.0381027] re-reflecting gives direction [0.03311318 0.02243919] FORWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] BACKWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] setting seed = 67 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] chose normal [0.98377071 0.17943018] 38 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] reflecting with [0.95209698 0.30579625] new direction [ 0.03997674 -0.00136388] re-reflecting gives direction [-0.031706 -0.02438707] FORWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] BACKWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] setting seed = 68 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] chose normal [-0.79459132 0.60714466] 17 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] reflecting with [-0.43881146 0.89857916] new direction [0.0285481 0.02801796] re-reflecting gives direction [0.03964926 0.00528548] FORWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] BACKWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] setting seed = 69 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] chose normal [-0.7961656 -0.60507879] 1 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] reflecting with [-0.86697568 -0.49835046] new direction [-0.02954452 -0.02696519] re-reflecting gives direction [0.0381706 0.01195847] FORWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] BACKWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] setting seed = 70 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] chose normal [ 0.39947727 -0.9167431 ] 42 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] reflecting with [ 0.6826168 -0.73077651] new direction [0.03155141 0.02458676] re-reflecting gives direction [0.0266774 0.02980464] FORWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] BACKWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] setting seed = 71 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] chose normal [-0.97291035 -0.23118274] 69 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] reflecting with [-0.49751035 -0.86745804] new direction [-0.03814895 -0.01202737] re-reflecting gives direction [-0.00888267 0.03900126] FORWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] BACKWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] setting seed = 72 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] chose normal [ 0.99936155 -0.03572801] 44 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] reflecting with [0.20311685 0.97915451] new direction [-0.03319769 0.02231398] re-reflecting gives direction [-0.03933418 -0.00726789] FORWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] BACKWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] setting seed = 73 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] chose normal [ 0.95068267 -0.31016523] 56 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] reflecting with [ 0.98237383 -0.18692688] new direction [ 0.03725902 -0.01455216] re-reflecting gives direction [-0.03999972 0.0001487 ] FORWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] BACKWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] setting seed = 74 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] chose normal [-0.96711996 0.25432065] 26 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] reflecting with [-0.28345858 0.95898448] new direction [0.0376308 0.01356183] re-reflecting gives direction [0.03895671 0.00907606] FORWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] BACKWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] setting seed = 75 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] chose normal [0.96607282 0.25826984] 98 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] reflecting with [0.85293874 0.52201103] new direction [-0.01283057 0.03788636] re-reflecting gives direction [-0.02789929 0.02866409] FORWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] BACKWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] setting seed = 76 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] chose normal [0.99980546 0.01972428] 96 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] reflecting with [ 0.99668345 -0.08137624] new direction [ 0.01928923 -0.03504177] re-reflecting gives direction [-0.02471798 -0.03144871] FORWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] BACKWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] setting seed = 77 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] chose normal [0.99421477 0.10741039] 67 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] reflecting with [ 0.79437479 -0.60742794] new direction [ 0.00021031 -0.03999945] re-reflecting gives direction [-0.03865662 -0.0102794 ] FORWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] BACKWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] setting seed = 78 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] chose normal [-0.00914844 -0.99995815] 42 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] reflecting with [0.81401512 0.58084368] new direction [0.00280365 0.03990162] re-reflecting gives direction [-0.03864408 0.01032644] FORWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] BACKWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] setting seed = 79 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] chose normal [0.11595433 0.99325455] 54 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] reflecting with [-0.11517722 0.99334496] new direction [0.00815767 0.03915932] re-reflecting gives direction [ 0.01690173 -0.03625371] FORWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] BACKWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] setting seed = 80 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] chose normal [-0.99209853 -0.1254612 ] 94 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] reflecting with [-0.97468899 -0.22356515] new direction [ 0.00838404 -0.03911148] re-reflecting gives direction [ 0.00949935 -0.03885566] FORWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] BACKWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] setting seed = 81 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] chose normal [-0.58455495 0.81135412] 52 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] reflecting with [ 0.9366811 -0.35018355] new direction [-0.01353712 -0.03763969] re-reflecting gives direction [-0.01447537 -0.03728892] FORWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] BACKWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] setting seed = 82 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] chose normal [-0.99997753 0.00670296] 37 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] reflecting with [-0.99945421 -0.03303454] new direction [-0.0075057 0.0392895] re-reflecting gives direction [0.00489491 0.03969937] FORWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] BACKWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] setting seed = 83 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] chose normal [-0.83995537 0.54265548] 16 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] reflecting with [-0.94063007 0.33943345] new direction [-0.0399681 -0.00159728] re-reflecting gives direction [ 0.02973828 -0.02675135] FORWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] BACKWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 85 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] chose normal [-0.96043218 0.27851395] 24 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] reflecting with [0.63881082 0.76936385] new direction [ 0.03336656 -0.02206066] re-reflecting gives direction [ 0.02781881 -0.02874219] FORWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] BACKWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] setting seed = 86 reflecting at [0.0772825 0.7321639] with direction [-0.0017544 -0.03996151] setting seed = 87 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] chose normal [-0.12256498 0.99246049] 84 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] reflecting with [-0.96541456 -0.26071962] new direction [-0.02848461 -0.0280825 ] re-reflecting gives direction [ 0.03874902 -0.0099254 ] FORWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] BACKWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] setting seed = 88 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] chose normal [-0.97498227 0.22228264] 41 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] reflecting with [-0.97588769 -0.21827326] new direction [-0.01869452 -0.03536262] re-reflecting gives direction [ 0.03197838 -0.0240288 ] FORWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] BACKWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] setting seed = 89 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] chose normal [-0.73290905 0.68032663] 80 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] reflecting with [-0.99658198 -0.08260969] new direction [-0.03221094 0.02371614] re-reflecting gives direction [0.02786633 0.02869612] FORWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] BACKWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] setting seed = 90 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] chose normal [ 0.8841271 -0.46724648] 74 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] reflecting with [ 0.99881338 -0.04870138] new direction [ 0.02087861 -0.03411867] re-reflecting gives direction [-0.02409888 -0.0319256 ] FORWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] BACKWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] setting seed = 91 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] chose normal [-0.92831744 -0.37178856] 63 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] reflecting with [ 0.50709066 -0.86189272] new direction [ 0.02598594 -0.03040939] re-reflecting gives direction [-0.01395947 0.0374851 ] FORWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] BACKWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] setting seed = 92 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] chose normal [-0.19961852 0.97987369] 68 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] reflecting with [0.80447377 0.59398817] new direction [0.0361881 0.01704175] re-reflecting gives direction [-0.02693892 -0.02956847] FORWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] BACKWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] setting seed = 93 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] chose normal [0.97810947 0.20809099] 55 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] reflecting with [0.99871915 0.05059696] new direction [0.01946991 0.0349417 ] re-reflecting gives direction [-0.02290158 0.03279509] FORWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] BACKWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] setting seed = 94 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] chose normal [-0.99138772 -0.13095947] 38 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] reflecting with [-0.85869194 0.51249211] new direction [-0.01847325 0.03547871] re-reflecting gives direction [0.03999576 0.00058272] FORWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] BACKWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] setting seed = 95 reflecting at [0.1329267 0.27135336] with direction [0.00593512 0.03955723] setting seed = 96 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] chose normal [-0.98828152 0.15264217] 98 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] reflecting with [-0.96810281 0.25055328] new direction [-0.00511631 0.03967144] re-reflecting gives direction [0.02371945 0.0322085 ] FORWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] BACKWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] setting seed = 97 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] chose normal [ 0.97234847 -0.23353469] 26 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] reflecting with [-0.96293126 -0.26974691] new direction [-0.02762979 0.02892395] re-reflecting gives direction [0.00858305 0.03906829] FORWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] BACKWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] setting seed = 98 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] chose normal [0.50785771 0.86144097] 48 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] reflecting with [0.9858335 0.16772692] new direction [ 0.01754476 -0.03594693] re-reflecting gives direction [-0.0046699 -0.03972646] FORWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] BACKWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] setting seed = 99 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] chose normal [0.99595977 0.08980054] 53 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] reflecting with [ 0.8602646 -0.50984784] new direction [ 0.01891779 -0.03524368] re-reflecting gives direction [-0.03999867 -0.00032601] FORWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913] BACKWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913]
Passed	tests/test_stepsampling.py::test_stepsampler_cubemh	11.70
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +1.0e-12\|***************************** ***************\| +1.0e+00 param1: +1.0e-12\|***********************************************\| +1.0e+00 param2: +1.0e-12\|************************************************\| +1.0e+00 Z=-inf(0.00%) \| Like=-30.04..-1.06 [-30.0369..-9.7206] \| it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.0913). shrinking... ineffective proposal scale (1.01601). shrinking... ineffective proposal scale (1.19093). shrinking... ineffective proposal scale (1.1). shrinking... ineffective proposal scale (1.01601). shrinking... ineffective proposal scale (1.21). shrinking... ineffective proposal scale (1.11761). shrinking... ineffective proposal scale (1.04051). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.887686). shrinking... Z=-27.7(0.00%) \| Like=-23.65..-1.06 [-30.0369..-9.7206] \| it/evals=27/736 eff=8.0357% N=400 ineffective proposal scale (0.826446). shrinking... ineffective proposal scale (0.763345). shrinking... ineffective proposal scale (0.873696). shrinking... ineffective proposal scale (0.813422). shrinking... ineffective proposal scale (0.813422). shrinking... Z=-25.1(0.00%) \| Like=-21.40..-1.06 [-30.0369..-9.7206] \| it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (0.846375). shrinking... ineffective proposal scale (0.794269). shrinking... ineffective proposal scale (0.800603). shrinking... ineffective proposal scale (0.901899). shrinking... ineffective proposal scale (0.769432). shrinking... ineffective proposal scale (0.710683). shrinking... ineffective proposal scale (0.656421). shrinking... ineffective proposal scale (0.606301). shrinking... ineffective proposal scale (0.560008). shrinking... Mono-modal Volume: ~exp(-4.22) Expected Volume: exp(-0.23) Quality: ok param0: +0.0000\|***************************************** ***\| +1.0000 param1: +1.0e-12\|******************************************* \| +1.0e+00 param2: +1.0e-12\|****************************************** ** \| +1.0e+00 Z=-21.0(0.00%) \| Like=-16.93..-1.06 [-30.0369..-9.7206] \| it/evals=90/1492 eff=8.2418% N=400 Z=-20.0(0.00%) \| Like=-16.02..-1.06 [-30.0369..-9.7206] \| it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (0.560008). shrinking... ineffective proposal scale (0.51725). shrinking... ineffective proposal scale (0.477757). shrinking... Z=-16.9(0.00%) \| Like=-13.39..-0.56 [-30.0369..-9.7206] \| it/evals=137/2056 eff=8.2729% N=400 Z=-16.2(0.00%) \| Like=-12.90..-0.56 [-30.0369..-9.7206] \| it/evals=150/2212 eff=8.2781% N=400 Mono-modal Volume: ~exp(-4.22) Expected Volume: exp(-0.45) Quality: ok param0: +0.0000\|**************************************** ***\| +1.0000 param1: +1.0e-12\|************************************** \| +1.0e+00 param2: +1.0e-12\|************************************ * * \| +1.0e+00 Z=-15.0(0.00%) \| Like=-11.80..-0.20 [-30.0369..-9.7206] \| it/evals=180/2572 eff=8.2873% N=400 ineffective proposal scale (0.217629). shrinking... Z=-14.3(0.00%) \| Like=-11.20..-0.20 [-30.0369..-9.7206] \| it/evals=200/2812 eff=8.2919% N=400 ineffective proposal scale (0.170132). shrinking... Z=-13.2(0.01%) \| Like=-10.26..-0.11 [-30.0369..-9.7206] \| it/evals=236/3244 eff=8.2982% N=400 Z=-12.9(0.01%) \| Like=-9.98..-0.11 [-30.0369..-9.7206] \| it/evals=250/3412 eff=8.3001% N=400 Mono-modal Volume: ~exp(-4.79) * Expected Volume: exp(-0.67) Quality: ok param0: +1.0e-12\|************************************* * ** \| +1.0e+00 param1: +1.0e-12\|**************************************** \| +1.0e+00 param2: +1.0e-12\|********************************** ******* \| +1.0e+00 Z=-12.4(0.02%) \| Like=-9.71..-0.11 [-9.7132..-6.0704] \| it/evals=270/3652 eff=8.3026% N=400 Z=-12.0(0.04%) \| Like=-9.20..-0.11 [-9.7132..-6.0704] \| it/evals=295/3952 eff=8.3052% N=400 Z=-11.9(0.04%) \| Like=-9.09..-0.11 [-9.7132..-6.0704] \| it/evals=300/4012 eff=8.3056% N=400 Z=-11.2(0.08%) \| Like=-8.53..-0.11 [-9.7132..-6.0704] \| it/evals=339/4480 eff=8.3088% N=400 Z=-11.0(0.09%) \| Like=-8.36..-0.11 [-9.7132..-6.0704] \| it/evals=350/4612 eff=8.3096% N=400 Mono-modal Volume: ~exp(-4.83) * Expected Volume: exp(-0.90) Quality: ok param0: +0.0000\|******************************************* * \| +1.0000 param1: +1.0e-12\|**************************************** \| +1.0e+00 param2: +0.0000\|********************************** ****** \| +1.0000 Z=-10.9(0.11%) \| Like=-8.23..-0.11 [-9.7132..-6.0704] \| it/evals=360/4732 eff=8.3102% N=400 Z=-10.5(0.15%) \| Like=-7.84..-0.11 [-9.7132..-6.0704] \| it/evals=384/5020 eff=8.3117% N=400 Z=-10.3(0.20%) \| Like=-7.64..-0.11 [-9.7132..-6.0704] \| it/evals=400/5212 eff=8.3126% N=400 Z=-9.8(0.29%) \| Like=-7.18..-0.11 [-9.7132..-6.0704] \| it/evals=442/5716 eff=8.3145% N=400 Mono-modal Volume: ~exp(-4.84) * Expected Volume: exp(-1.12) Quality: ok param0: +0.0000\|********************************** **** * ** \| +1.0000 param1: +1.0e-12\|******************************************* \| +1.0e+00 param2: +1.0e-12\|*********************************************** \| +1.0e+00 Z=-9.7(0.32%) \| Like=-7.09..-0.11 [-9.7132..-6.0704] \| it/evals=450/5812 eff=8.3149% N=400 Z=-9.5(0.41%) \| Like=-6.83..-0.11 [-9.7132..-6.0704] \| it/evals=473/6088 eff=8.3158% N=400 Z=-9.2(0.56%) \| Like=-6.57..-0.11 [-9.7132..-6.0704] \| it/evals=500/6412 eff=8.3167% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.35) Quality: ok param0: +1.0e-12\|********************************** **** * \| +1.0e+00 param1: +1.0e-12\|********************************************** \| +1.0e+00 param2: +1.0e-12\|********************************************* \| +1.0e+00 Z=-8.8(0.81%) \| Like=-6.14..-0.11 [-9.7132..-6.0704] \| it/evals=540/6892 eff=8.3179% N=400 Z=-8.7(0.88%) \| Like=-6.02..-0.11 [-6.0299..-4.1927] \| it/evals=550/7012 eff=8.3182% N=400 Z=-8.5(1.14%) \| Like=-5.73..-0.11 [-6.0299..-4.1927] \| it/evals=574/7300 eff=8.3188% N=400 Z=-8.3(1.45%) \| Like=-5.49..-0.11 [-6.0299..-4.1927] \| it/evals=600/7612 eff=8.3195% N=400 Mono-modal Volume: ~exp(-5.79) * Expected Volume: exp(-1.57) Quality: ok param0: +1.0e-12\|******************************************* * \| +1.0e+00 param1: +0.000\|*************************** ************* \| +1.000 param2: +1.0e-12\|********************************* ***** \| +1.0e+00 Z=-8.0(1.81%) \| Like=-5.29..-0.11 [-6.0299..-4.1927] \| it/evals=630/7972 eff=8.3201% N=400 Z=-7.9(2.09%) \| Like=-5.14..-0.11 [-6.0299..-4.1927] \| it/evals=650/8212 eff=8.3205% N=400 Z=-7.6(2.76%) \| Like=-4.93..-0.11 [-6.0299..-4.1927] \| it/evals=688/8668 eff=8.3212% N=400 Z=-7.5(2.99%) \| Like=-4.88..-0.11 [-6.0299..-4.1927] \| it/evals=700/8812 eff=8.3214% N=400 Mono-modal Volume: ~exp(-5.79) Expected Volume: exp(-1.80) Quality: ok param0: +0.000\|***************************************** * * \| +1.000 param1: +0.000\|***************************** ************* \| +1.000 param2: +1.0e-12\|********************************* ***** * \| +1.0e+00 Z=-7.4(3.32%) \| Like=-4.76..-0.11 [-6.0299..-4.1927] \| it/evals=720/9052 eff=8.3218% N=400 Z=-7.2(3.88%) \| Like=-4.57..-0.11 [-6.0299..-4.1927] \| it/evals=750/9412 eff=8.3222% N=400 Z=-7.0(5.09%) \| Like=-4.31..-0.11 [-6.0299..-4.1927] \| it/evals=800/10012 eff=8.3229% N=400 Mono-modal Volume: ~exp(-5.79) Expected Volume: exp(-2.02) Quality: ok param0: +0.000\|***************************************** * \| +1.000 param1: +0.00\| ***************************** ************ \| +1.00 param2: +0.00\| ****************************************** \| +1.00 Z=-6.8(5.86%) \| Like=-4.20..-0.11 [-6.0299..-4.1927] \| it/evals=827/10336 eff=8.3233% N=400 Z=-6.7(6.40%) \| Like=-4.09..-0.06 [-4.1888..-3.3876] \| it/evals=850/10612 eff=8.3235% N=400 Mono-modal Volume: ~exp(-6.66) * Expected Volume: exp(-2.25) Quality: ok param0: +0.00\| *************************************** * * \| +1.00 param1: +0.00\| ********************************************* \| +1.00 param2: +0.00\| ***************************************** * \| +1.00 Z=-6.5(7.81%) \| Like=-3.82..-0.06 [-4.1888..-3.3876] \| it/evals=900/11212 eff=8.3241% N=400 Z=-6.4(9.60%) \| Like=-3.56..-0.06 [-4.1888..-3.3876] \| it/evals=945/11752 eff=8.3245% N=400 Z=-6.3(9.79%) \| Like=-3.54..-0.06 [-4.1888..-3.3876] \| it/evals=950/11812 eff=8.3246% N=400 Mono-modal Volume: ~exp(-6.68) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00\| *************************************** * \| +1.00 param1: +0.00\| ******************************************** \| +1.00 param2: +0.00\| ***************************************** * \| +1.00 Z=-6.2(11.33%) \| Like=-3.29..-0.06 [-3.3856..-3.0945] \| it/evals=990/12292 eff=8.3249% N=400 Z=-6.2(11.73%) \| Like=-3.22..-0.06 [-3.3856..-3.0945] \| it/evals=1000/12412 eff=8.3250% N=400 Z=-6.0(14.31%) \| Like=-3.03..-0.06 [-3.0815..-2.9597] \| it/evals=1050/13012 eff=8.3254% N=400 Mono-modal Volume: ~exp(-6.68) Expected Volume: exp(-2.70) Quality: ok param0: +0.00\| **************************************** * \| +1.00 param1: +0.00\| *********************** ******** *** \| +1.00 param2: +0.00\| * **************************************** * \| +1.00 Z=-5.9(16.05%) \| Like=-2.90..-0.06 [-2.9039..-2.8993]\| it/evals=1080/13372 eff=8.3256% N=400 Z=-5.8(17.09%) \| Like=-2.82..-0.06 [-2.8220..-2.8188]\| it/evals=1100/13612 eff=8.3258% N=400 Z=-5.7(19.97%) \| Like=-2.62..-0.06 [-2.6183..-2.6180]\| it/evals=1150/14212 eff=8.3261% N=400 Mono-modal Volume: ~exp(-6.68) Expected Volume: exp(-2.92) Quality: ok param0: +0.00\| ************************************** * \| +1.00 param1: +0.00\| *********************************** * \| +1.00 param2: +0.00\| ************************************* \| +1.00 Z=-5.6(22.00%) \| Like=-2.50..-0.03 [-2.4972..-2.4851] \| it/evals=1186/14644 eff=8.3263% N=400 Z=-5.5(22.87%) \| Like=-2.46..-0.03 [-2.4581..-2.4551]\| it/evals=1200/14812 eff=8.3264% N=400 Z=-5.4(25.76%) \| Like=-2.28..-0.03 [-2.2759..-2.2634] \| it/evals=1250/15412 eff=8.3267% N=400 Have 2 modes Volume: ~exp(-7.56) Expected Volume: exp(-3.15) Quality: ok param0: +0.0\| 11111111111111111111122222222222222222 \| +1.0 param1: +0.00\| 1111111111111111111111222222 222222222 2222 \| +1.00 param2: +0.0\| 111111111111111111112222222222222222222 \| +1.0 Z=-5.4(26.52%) \| Like=-2.24..-0.03 [-2.2375..-2.2365]\| it/evals=1260/15532 eff=8.3267% N=400 Z=-5.3(28.98%) \| Like=-2.09..-0.03 [-2.0884..-2.0785]\| it/evals=1300/16012 eff=8.3269% N=400 Have 2 modes Volume: ~exp(-7.76) * Expected Volume: exp(-3.37) Quality: ok param0: +0.0\| 11111111111111111111222222222222222222 \| +1.0 param1: +0.0\| 1111111111111111111 22222222 2222222 2 2 \| +1.0 param2: +0.0\| 1111111111111111111 222222222222222222 \| +1.0 Z=-5.2(32.52%) \| Like=-1.90..-0.03 [-1.8971..-1.8900]\| it/evals=1350/16612 eff=8.3272% N=400 Z=-5.1(34.97%) \| Like=-1.81..-0.03 [-1.8113..-1.8108]\| it/evals=1379/16960 eff=8.3273% N=400 Z=-5.0(36.57%) \| Like=-1.73..-0.03 [-1.7344..-1.7328]\| it/evals=1400/17212 eff=8.3274% N=400 Have 2 modes Volume: ~exp(-7.76) Expected Volume: exp(-3.60) Quality: ok param0: +0.0\| 111111111111111111 22222222222222222 \| +1.0 param1: +0.0\| 111111111111111111 2222222202222222 2 \| +1.0 param2: +0.0\| 111111111111111111 22222222222222222 \| +1.0 Z=-5.0(39.24%) \| Like=-1.63..-0.03 [-1.6259..-1.6248]\| it/evals=1440/17692 eff=8.3276% N=400 Z=-4.9(39.95%) \| Like=-1.60..-0.03 [-1.6049..-1.5962]\| it/evals=1450/17812 eff=8.3276% N=400 Z=-4.9(43.52%) \| Like=-1.48..-0.03 [-1.4784..-1.4782]\| it/evals=1496/18364 eff=8.3278% N=400 Z=-4.9(43.72%) \| Like=-1.47..-0.03 [-1.4722..-1.4714]\| it/evals=1500/18412 eff=8.3278% N=400 Have 2 modes Volume: ~exp(-7.76) Expected Volume: exp(-3.82) Quality: ok param0: +0.0\| 111111111111111111 2222222222222 22 \| +1.0 param1: +0.0\| 11111111111111111 22022020222222202 \| +1.0 param2: +0.0\| 11111111111111111 0 02222222222202 \| +1.0 Z=-4.8(46.21%) \| Like=-1.41..-0.03 [-1.4149..-1.4132]\| it/evals=1530/18772 eff=8.3279% N=400 Z=-4.8(47.57%) \| Like=-1.39..-0.01 [-1.3855..-1.3841]\| it/evals=1550/19012 eff=8.3280% N=400 Z=-4.7(50.20%) \| Like=-1.32..-0.01 [-1.3172..-1.3102]\| it/evals=1591/19504 eff=8.3281% N=400 Z=-4.7(50.85%) \| Like=-1.29..-0.01 [-1.2927..-1.2916]\| it/evals=1600/19612 eff=8.3281% N=400 Have 2 modes Volume: ~exp(-8.08) Expected Volume: exp(-4.05) Quality: ok param0: +0.0\| 11111111111111111 22222222 22222 +0.8 \| +1.0 param1: +0.0\| 1111111111111111 222 222222222 \| +1.0 param2: +0.0\| 11111111111111111 2222222222222 \| +1.0 Z=-4.7(52.25%) \| Like=-1.25..-0.01 [-1.2530..-1.2526]\| it/evals=1620/19852 eff=8.3282% N=400 Z=-4.6(54.35%) \| Like=-1.21..-0.01 [-1.2056..-1.2053]\| it/evals=1650/20214 eff=8.3274% N=400 Z=-4.6(56.82%) \| Like=-1.15..-0.01 [-1.1537..-1.1527]\| it/evals=1689/20682 eff=8.3276% N=400 Z=-4.6(57.55%) \| Like=-1.14..-0.01 [-1.1414..-1.1366]\| it/evals=1700/20814 eff=8.3276% N=400 Have 2 modes Volume: ~exp(-8.08) Expected Volume: exp(-4.27) Quality: ok param0: +0.0\| 111111111111111 2202222 22222 +0.8 \| +1.0 param1: +0.0\| 111111111111111 2220222222222 \| +1.0 param2: +0.0\| 111111111111111 02222222222222 \| +1.0 Z=-4.5(59.21%) \| Like=-1.07..-0.01 [-1.0743..-1.0739]\| it/evals=1726/21126 eff=8.3277% N=400 Z=-4.5(60.73%) \| Like=-1.04..-0.01 [-1.0385..-1.0382]\| it/evals=1750/21414 eff=8.3278% N=400 Z=-4.5(63.40%) \| Like=-0.95..-0.01 [-0.9492..-0.9480]\| it/evals=1793/21930 eff=8.3279% N=400 Have 2 modes Volume: ~exp(-8.66) Expected Volume: exp(-4.50) Quality: ok param0: +0.0\| 11111111111111 222222222222 +0.8 \| +1.0 param1: +0.0\| 111111111111111 222222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111111 2222222222222 \| +1.0 Z=-4.5(63.79%) \| Like=-0.94..-0.01 [-0.9390..-0.9389]\| it/evals=1800/22014 eff=8.3279% N=400 Z=-4.5(65.27%) \| Like=-0.90..-0.01 [-0.9042..-0.9011]\| it/evals=1826/22326 eff=8.3280% N=400 Z=-4.4(66.73%) \| Like=-0.88..-0.01 [-0.8812..-0.8805]\| it/evals=1850/22614 eff=8.3281% N=400 Z=-4.4(68.57%) \| Like=-0.82..-0.01 [-0.8240..-0.8228]\| it/evals=1883/23010 eff=8.3282% N=400 Have 2 modes Volume: ~exp(-8.79) * Expected Volume: exp(-4.73) Quality: ok param0: +0.0\| 1111111111111 222222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111111 222222222222 +0.8 \| +1.0 param2: +0.0\| 1111111111111 222222222222 \| +1.0 Z=-4.4(68.99%) \| Like=-0.81..-0.01 [-0.8129..-0.8128]\| it/evals=1890/23094 eff=8.3282% N=400 Z=-4.4(69.61%) \| Like=-0.81..-0.01 [-0.8058..-0.8049]\| it/evals=1900/23214 eff=8.3282% N=400 Z=-4.4(71.90%) \| Like=-0.76..-0.01 [-0.7575..-0.7573]\| it/evals=1942/23718 eff=8.3283% N=400 Z=-4.4(72.36%) \| Like=-0.75..-0.01 [-0.7484..-0.7480]\| it/evals=1950/23814 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-8.79) Expected Volume: exp(-4.95) Quality: ok param0: +0.0\| 111111111111 222222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111 2222222222 +0.8 \| +1.0 Z=-4.3(74.07%) \| Like=-0.70..-0.01 [-0.7006..-0.6990]\| it/evals=1986/24247 eff=8.3281% N=400 Z=-4.3(74.76%) \| Like=-0.68..-0.01 [-0.6830..-0.6808]\| it/evals=2000/24415 eff=8.3281% N=400 Z=-4.3(77.04%) \| Like=-0.63..-0.01 [-0.6341..-0.6341]\| it/evals=2050/25015 eff=8.3283% N=400 Have 2 modes Volume: ~exp(-9.25) Expected Volume: exp(-5.18) Quality: ok param0: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 111111111111 2222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 Z=-4.3(77.92%) \| Like=-0.62..-0.01 [-0.6168..-0.6164]\| it/evals=2070/25255 eff=8.3283% N=400 Z=-4.3(79.18%) \| Like=-0.59..-0.01 [-0.5915..-0.5908]\| it/evals=2100/25615 eff=8.3284% N=400 Z=-4.2(81.19%) \| Like=-0.55..-0.01 [-0.5468..-0.5462]\| it/evals=2150/26215 eff=8.3285% N=400 Have 2 modes Volume: ~exp(-9.25) Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| 11111111111 2222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 022222222 2 +0.8 \| +1.0 param2: +0.0\| 11111111111 2222222222 +0.8 \| +1.0 Z=-4.2(81.77%) \| Like=-0.53..-0.01 [-0.5322..-0.5319]\| it/evals=2166/26407 eff=8.3285% N=400 Z=-4.2(83.00%) \| Like=-0.50..-0.01 [-0.5043..-0.5043]\| it/evals=2200/26815 eff=8.3286% N=400 Have 2 modes Volume: ~exp(-9.58) Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| 11111111111 222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 22222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 222222222 +0.8 \| +1.0 Z=-4.2(84.68%) \| Like=-0.46..-0.01 [-0.4649..-0.4648]\| it/evals=2250/27415 eff=8.3287% N=400 Z=-4.2(86.16%) \| Like=-0.43..-0.01 [-0.4325..-0.4324]\| it/evals=2300/28015 eff=8.3288% N=400 Have 2 modes Volume: ~exp(-9.63) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param2: +0.0\| 1111111111 222222222 +0.8 \| +1.0 Z=-4.2(87.28%) \| Like=-0.40..-0.01 [-0.4025..-0.4017]\| it/evals=2340/28495 eff=8.3289% N=400 Z=-4.2(87.54%) \| Like=-0.40..-0.01 [-0.3971..-0.3969]\| it/evals=2350/28615 eff=8.3289% N=400 Z=-4.1(88.80%) \| Like=-0.37..-0.01 [-0.3664..-0.3656]\| it/evals=2400/29215 eff=8.3290% N=400 Have 2 modes Volume: ~exp(-9.67) Expected Volume: exp(-6.08) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-4.1(89.49%) \| Like=-0.35..-0.01 [-0.3506..-0.3505]\| it/evals=2430/29575 eff=8.3290% N=400 Z=-4.1(89.94%) \| Like=-0.34..-0.01 [-0.3366..-0.3359]\| it/evals=2450/29815 eff=8.3291% N=400 Z=-4.1(90.98%) \| Like=-0.31..-0.01 [-0.3102..-0.3096]\| it/evals=2500/30415 eff=8.3292% N=400 Have 2 modes Volume: ~exp(-10.18) Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-4.1(91.36%) \| Like=-0.30..-0.01 [-0.2977..-0.2975]\| it/evals=2520/30655 eff=8.3292% N=400 Z=-4.1(91.91%) \| Like=-0.28..-0.01 [-0.2806..-0.2805]\| it/evals=2550/31015 eff=8.3293% N=400 Z=-4.1(92.77%) \| Like=-0.26..-0.01 [-0.2624..-0.2624]\| it/evals=2600/31615 eff=8.3293% N=400 Have 2 modes Volume: ~exp(-10.18) Expected Volume: exp(-6.53) Quality: ok param0: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 2222222 +0.7 \| +1.0 param2: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 Z=-4.1(92.94%) \| Like=-0.26..-0.01 [-0.2580..-0.2579]\| it/evals=2610/31735 eff=8.3293% N=400 Z=-4.1(93.55%) \| Like=-0.24..-0.01 [-0.2415..-0.2406]\| it/evals=2650/32215 eff=8.3294% N=400 Have 2 modes Volume: ~exp(-10.52) * Expected Volume: exp(-6.75) Quality: ok param0: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-4.1(94.24%) \| Like=-0.22..-0.01 [-0.2232..-0.2227]\| it/evals=2700/32815 eff=8.3295% N=400 Z=-4.1(94.87%) \| Like=-0.20..-0.01 [-0.2014..-0.2007]\| it/evals=2750/33415 eff=8.3295% N=400 Have 2 modes Volume: ~exp(-11.07) * Expected Volume: exp(-6.98) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.7 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-4.1(95.32%) \| Like=-0.19..-0.00 [-0.1892..-0.1889]\| it/evals=2790/33895 eff=8.3296% N=400 Z=-4.1(95.43%) \| Like=-0.19..-0.00 [-0.1862..-0.1858]\| it/evals=2800/34015 eff=8.3296% N=400 Z=-4.1(95.89%) \| Like=-0.17..-0.00 [-0.1721..-0.1719]\| it/evals=2846/34567 eff=8.3297% N=400 Z=-4.1(95.93%) \| Like=-0.17..-0.00 [-0.1715..-0.1708]\| it/evals=2850/34615 eff=8.3297% N=400 Have 2 modes Volume: ~exp(-11.66) * Expected Volume: exp(-7.20) Quality: ok param0: +0.0\| +0.2 111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.7 \| +1.0 param2: +0.0\| +0.2 1111111 22222 +0.7 \| +1.0 Z=-4.1(96.20%) \| Like=-0.16..-0.00 [-0.1644..-0.1643]\| it/evals=2880/34975 eff=8.3297% N=400 Z=-4.1(96.37%) \| Like=-0.16..-0.00 [-0.1583..-0.1583]\| it/evals=2900/35215 eff=8.3297% N=400 Z=-4.1(96.78%) \| Like=-0.14..-0.00 [-0.1435..-0.1434]\| it/evals=2950/35815 eff=8.3298% N=400 Have 2 modes Volume: ~exp(-11.66) Expected Volume: exp(-7.43) Quality: ok param0: +0.0\| +0.2 111111 222222 +0.7 \| +1.0 param1: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 param2: +0.0\| +0.2 111111 22222 +0.7 \| +1.0 Z=-4.1(97.05%) \| Like=-0.14..-0.00 [-0.1359..-0.1357]\| it/evals=2988/36271 eff=8.3298% N=400 Z=-4.1(97.13%) \| Like=-0.13..-0.00 [-0.1339..-0.1332]\| it/evals=3000/36415 eff=8.3299% N=400 Z=-4.1(97.45%) \| Like=-0.12..-0.00 [-0.1233..-0.1232]\| it/evals=3050/37015 eff=8.3299% N=400 Have 2 modes Volume: ~exp(-11.73) * Expected Volume: exp(-7.65) Quality: ok param0: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 222222 +0.7 \| +1.0 param2: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 Z=-4.1(97.51%) \| Like=-0.12..-0.00 [-0.1212..-0.1211]\| it/evals=3060/37135 eff=8.3299% N=400 Z=-4.1(97.74%) \| Like=-0.11..-0.00 [-0.1138..-0.1127]\| it/evals=3100/37615 eff=8.3300% N=400 Have 2 modes Volume: ~exp(-12.08) * Expected Volume: exp(-7.88) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(97.99%) \| Like=-0.10..-0.00 [-0.1045..-0.1044]\| it/evals=3150/38217 eff=8.3296% N=400 Z=-4.0(98.19%) \| Like=-0.10..-0.00 [-0.0969..-0.0968]\| it/evals=3192/38721 eff=8.3296% N=400 Z=-4.0(98.22%) \| Like=-0.10..-0.00 [-0.0956..-0.0955]\| it/evals=3200/38817 eff=8.3296% N=400 Have 2 modes Volume: ~exp(-12.08) Expected Volume: exp(-8.10) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.38%) \| Like=-0.09..-0.00 [-0.0901..-0.0900]\| it/evals=3240/39298 eff=8.3295% N=400 Z=-4.0(98.42%) \| Like=-0.09..-0.00 [-0.0888..-0.0883]\| it/evals=3250/39418 eff=8.3295% N=400 Z=-4.0(98.59%) \| Like=-0.08..-0.00 [-0.0816..-0.0816]\| it/evals=3296/39970 eff=8.3295% N=400 Z=-4.0(98.60%) \| Like=-0.08..-0.00 [-0.0813..-0.0812]\| it/evals=3300/40018 eff=8.3295% N=400 Have 2 modes Volume: ~exp(-12.47) Expected Volume: exp(-8.33) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.70%) \| Like=-0.08..-0.00 [-0.0774..-0.0773]\| it/evals=3330/40378 eff=8.3296% N=400 Z=-4.0(98.76%) \| Like=-0.07..-0.00 [-0.0747..-0.0747]\| it/evals=3350/40618 eff=8.3296% N=400 Z=-4.0(98.90%) \| Like=-0.07..-0.00 [-0.0675..-0.0675]\| it/evals=3400/41218 eff=8.3297% N=400 Have 2 modes Volume: ~exp(-12.47) Expected Volume: exp(-8.55) Quality: ok param0: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-4.0(98.99%) \| Like=-0.06..-0.00 [-0.0633..-0.0631]\| it/evals=3433/41615 eff=8.3295% N=400 [ultranest] Explored until L=-0.0002 [ultranest] Likelihood function evaluations: 41675 [ultranest] logZ = -4.031 +- 0.05895 [ultranest] Effective samples strategy satisfied (ESS = 2002.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -4.027 +- 0.106 single instance: logZ = -4.027 +- 0.077 bootstrapped : logZ = -4.031 +- 0.106 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▂▃▃▄▄▅▇▇▇▇▆▆▆▅▃▂▂▁▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁│1.00 0.35 +- 0.17 param1 : 0.00 │▁▁▂▂▂▃▅▅▆▇▇▇▇▇▅▄▃▃▁▂▁▁▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▁ │1.00 0.34 +- 0.18 param2 : 0.00 │▁▁▁▁▂▃▄▄▇▇▇▇▇▆▅▄▃▃▂▂▁▁▁▁▁▂▁▂▁▂▁▁▁▁▁▁▁▁ │1.00 0.35 +- 0.18 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=412, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.04, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=27, ncalls=736, regioncalls=0, ndraw=128, logz=-27.68, remainder_fraction=100.0000%, Lmin=-23.65, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1012, regioncalls=0, ndraw=128, logz=-25.06, remainder_fraction=100.0000%, Lmin=-21.40, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1492, regioncalls=0, ndraw=128, logz=-21.02, remainder_fraction=100.0000%, Lmin=-16.93, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1612, regioncalls=0, ndraw=128, logz=-20.00, remainder_fraction=100.0000%, Lmin=-16.02, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=137, ncalls=2056, regioncalls=0, ndraw=128, logz=-16.93, remainder_fraction=99.9997%, Lmin=-13.39, Lmax=-0.56 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=2212, regioncalls=0, ndraw=128, logz=-16.22, remainder_fraction=99.9994%, Lmin=-12.90, Lmax=-0.56 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=2572, regioncalls=0, ndraw=128, logz=-15.05, remainder_fraction=99.9981%, Lmin=-11.80, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=2812, regioncalls=0, ndraw=128, logz=-14.34, remainder_fraction=99.9963%, Lmin=-11.20, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=236, ncalls=3244, regioncalls=0, ndraw=128, logz=-13.22, remainder_fraction=99.9889%, Lmin=-10.26, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3412, regioncalls=0, ndraw=128, logz=-12.87, remainder_fraction=99.9855%, Lmin=-9.98, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=3652, regioncalls=0, ndraw=128, logz=-12.43, remainder_fraction=99.9780%, Lmin=-9.71, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=3952, regioncalls=0, ndraw=128, logz=-11.96, remainder_fraction=99.9641%, Lmin=-9.20, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=4012, regioncalls=0, ndraw=128, logz=-11.87, remainder_fraction=99.9605%, Lmin=-9.09, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=339, ncalls=4480, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9239%, Lmin=-8.53, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=4612, regioncalls=0, ndraw=128, logz=-11.04, remainder_fraction=99.9084%, Lmin=-8.36, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=4732, regioncalls=0, ndraw=128, logz=-10.89, remainder_fraction=99.8920%, Lmin=-8.23, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=5020, regioncalls=0, ndraw=128, logz=-10.55, remainder_fraction=99.8460%, Lmin=-7.84, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5212, regioncalls=0, ndraw=128, logz=-10.33, remainder_fraction=99.8031%, Lmin=-7.64, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=442, ncalls=5716, regioncalls=0, ndraw=128, logz=-9.80, remainder_fraction=99.7068%, Lmin=-7.18, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5812, regioncalls=0, ndraw=128, logz=-9.71, remainder_fraction=99.6800%, Lmin=-7.09, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=473, ncalls=6088, regioncalls=0, ndraw=128, logz=-9.46, remainder_fraction=99.5860%, Lmin=-6.83, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=6412, regioncalls=0, ndraw=128, logz=-9.19, remainder_fraction=99.4440%, Lmin=-6.57, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=6892, regioncalls=0, ndraw=128, logz=-8.81, remainder_fraction=99.1854%, Lmin=-6.14, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=7012, regioncalls=0, ndraw=128, logz=-8.71, remainder_fraction=99.1150%, Lmin=-6.02, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=574, ncalls=7300, regioncalls=0, ndraw=128, logz=-8.49, remainder_fraction=98.8630%, Lmin=-5.73, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=7612, regioncalls=0, ndraw=128, logz=-8.25, remainder_fraction=98.5485%, Lmin=-5.49, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=7972, regioncalls=0, ndraw=128, logz=-8.00, remainder_fraction=98.1910%, Lmin=-5.29, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=8212, regioncalls=0, ndraw=128, logz=-7.85, remainder_fraction=97.9083%, Lmin=-5.14, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=688, ncalls=8668, regioncalls=0, ndraw=128, logz=-7.59, remainder_fraction=97.2384%, Lmin=-4.93, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=8812, regioncalls=0, ndraw=128, logz=-7.52, remainder_fraction=97.0112%, Lmin=-4.88, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=9052, regioncalls=0, ndraw=128, logz=-7.40, remainder_fraction=96.6833%, Lmin=-4.76, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=9412, regioncalls=0, ndraw=128, logz=-7.23, remainder_fraction=96.1230%, Lmin=-4.57, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=10012, regioncalls=0, ndraw=128, logz=-6.97, remainder_fraction=94.9092%, Lmin=-4.31, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=827, ncalls=10336, regioncalls=0, ndraw=128, logz=-6.85, remainder_fraction=94.1393%, Lmin=-4.20, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=10612, regioncalls=0, ndraw=128, logz=-6.75, remainder_fraction=93.6019%, Lmin=-4.09, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=11212, regioncalls=0, ndraw=128, logz=-6.54, remainder_fraction=92.1873%, Lmin=-3.82, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=945, ncalls=11752, regioncalls=0, ndraw=128, logz=-6.36, remainder_fraction=90.4012%, Lmin=-3.56, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=11812, regioncalls=0, ndraw=128, logz=-6.34, remainder_fraction=90.2091%, Lmin=-3.54, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=12292, regioncalls=0, ndraw=128, logz=-6.19, remainder_fraction=88.6691%, Lmin=-3.29, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=12412, regioncalls=0, ndraw=128, logz=-6.15, remainder_fraction=88.2654%, Lmin=-3.22, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=13012, regioncalls=0, ndraw=128, logz=-5.97, remainder_fraction=85.6883%, Lmin=-3.03, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=13372, regioncalls=0, ndraw=128, logz=-5.87, remainder_fraction=83.9463%, Lmin=-2.90, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=13612, regioncalls=0, ndraw=128, logz=-5.81, remainder_fraction=82.9091%, Lmin=-2.82, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=14212, regioncalls=0, ndraw=128, logz=-5.65, remainder_fraction=80.0296%, Lmin=-2.62, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1186, ncalls=14644, regioncalls=0, ndraw=128, logz=-5.55, remainder_fraction=78.0026%, Lmin=-2.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=14812, regioncalls=0, ndraw=128, logz=-5.52, remainder_fraction=77.1306%, Lmin=-2.46, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=15412, regioncalls=0, ndraw=128, logz=-5.39, remainder_fraction=74.2389%, Lmin=-2.28, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=15532, regioncalls=0, ndraw=128, logz=-5.36, remainder_fraction=73.4801%, Lmin=-2.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=16012, regioncalls=0, ndraw=128, logz=-5.27, remainder_fraction=71.0158%, Lmin=-2.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=16612, regioncalls=0, ndraw=128, logz=-5.15, remainder_fraction=67.4832%, Lmin=-1.90, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1379, ncalls=16960, regioncalls=0, ndraw=128, logz=-5.09, remainder_fraction=65.0333%, Lmin=-1.81, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=17212, regioncalls=0, ndraw=128, logz=-5.05, remainder_fraction=63.4313%, Lmin=-1.73, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=17692, regioncalls=0, ndraw=128, logz=-4.97, remainder_fraction=60.7556%, Lmin=-1.63, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=17812, regioncalls=0, ndraw=128, logz=-4.95, remainder_fraction=60.0452%, Lmin=-1.60, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1496, ncalls=18364, regioncalls=0, ndraw=128, logz=-4.86, remainder_fraction=56.4823%, Lmin=-1.48, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=18412, regioncalls=0, ndraw=128, logz=-4.86, remainder_fraction=56.2831%, Lmin=-1.47, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=18772, regioncalls=0, ndraw=128, logz=-4.81, remainder_fraction=53.7911%, Lmin=-1.41, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=19012, regioncalls=0, ndraw=128, logz=-4.77, remainder_fraction=52.4290%, Lmin=-1.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1591, ncalls=19504, regioncalls=0, ndraw=128, logz=-4.71, remainder_fraction=49.7954%, Lmin=-1.32, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=19612, regioncalls=0, ndraw=128, logz=-4.70, remainder_fraction=49.1489%, Lmin=-1.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=19852, regioncalls=0, ndraw=128, logz=-4.67, remainder_fraction=47.7467%, Lmin=-1.25, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=20214, regioncalls=0, ndraw=128, logz=-4.64, remainder_fraction=45.6547%, Lmin=-1.21, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1689, ncalls=20682, regioncalls=0, ndraw=128, logz=-4.59, remainder_fraction=43.1841%, Lmin=-1.15, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=20814, regioncalls=0, ndraw=128, logz=-4.58, remainder_fraction=42.4477%, Lmin=-1.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1726, ncalls=21126, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=40.7851%, Lmin=-1.07, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=21414, regioncalls=0, ndraw=128, logz=-4.52, remainder_fraction=39.2742%, Lmin=-1.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1793, ncalls=21930, regioncalls=0, ndraw=128, logz=-4.48, remainder_fraction=36.5956%, Lmin=-0.95, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=22014, regioncalls=0, ndraw=128, logz=-4.47, remainder_fraction=36.2143%, Lmin=-0.94, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1826, ncalls=22326, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=34.7321%, Lmin=-0.90, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=22614, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=33.2721%, Lmin=-0.88, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1883, ncalls=23010, regioncalls=0, ndraw=128, logz=-4.40, remainder_fraction=31.4290%, Lmin=-0.82, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=23094, regioncalls=0, ndraw=128, logz=-4.40, remainder_fraction=31.0105%, Lmin=-0.81, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=23214, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=30.3880%, Lmin=-0.81, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1942, ncalls=23718, regioncalls=0, ndraw=128, logz=-4.36, remainder_fraction=28.1000%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=23814, regioncalls=0, ndraw=128, logz=-4.35, remainder_fraction=27.6380%, Lmin=-0.75, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1986, ncalls=24247, regioncalls=0, ndraw=128, logz=-4.33, remainder_fraction=25.9258%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=24415, regioncalls=0, ndraw=128, logz=-4.32, remainder_fraction=25.2361%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=25015, regioncalls=0, ndraw=128, logz=-4.29, remainder_fraction=22.9561%, Lmin=-0.63, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=25255, regioncalls=0, ndraw=128, logz=-4.28, remainder_fraction=22.0789%, Lmin=-0.62, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=25615, regioncalls=0, ndraw=128, logz=-4.26, remainder_fraction=20.8188%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=26215, regioncalls=0, ndraw=128, logz=-4.24, remainder_fraction=18.8076%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2166, ncalls=26407, regioncalls=0, ndraw=128, logz=-4.23, remainder_fraction=18.2333%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=26815, regioncalls=0, ndraw=128, logz=-4.21, remainder_fraction=16.9984%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=27415, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=15.3219%, Lmin=-0.46, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=28015, regioncalls=0, ndraw=128, logz=-4.18, remainder_fraction=13.8385%, Lmin=-0.43, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=28495, regioncalls=0, ndraw=128, logz=-4.16, remainder_fraction=12.7169%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=28615, regioncalls=0, ndraw=128, logz=-4.16, remainder_fraction=12.4583%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=29215, regioncalls=0, ndraw=128, logz=-4.15, remainder_fraction=11.2007%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=29575, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=10.5052%, Lmin=-0.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=29815, regioncalls=0, ndraw=128, logz=-4.13, remainder_fraction=10.0624%, Lmin=-0.34, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=30415, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=9.0180%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=30655, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=8.6427%, Lmin=-0.30, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=31015, regioncalls=0, ndraw=128, logz=-4.11, remainder_fraction=8.0937%, Lmin=-0.28, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=31615, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=7.2269%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=31735, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=7.0617%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=32215, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=6.4500%, Lmin=-0.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32815, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=5.7565%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33415, regioncalls=0, ndraw=128, logz=-4.08, remainder_fraction=5.1326%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=33895, regioncalls=0, ndraw=128, logz=-4.08, remainder_fraction=4.6763%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=34015, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.5702%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2846, ncalls=34567, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.1062%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34615, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.0697%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34975, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=3.7990%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35215, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=3.6267%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35815, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=3.2241%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2988, ncalls=36271, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=2.9468%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36415, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=2.8655%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37015, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.5458%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37135, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.4872%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37615, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.2610%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38217, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.0051%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3192, ncalls=38721, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=1.8122%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=38817, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=1.7784%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=39298, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.6161%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3250, ncalls=39418, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.5776%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3296, ncalls=39970, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.4118%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3300, ncalls=40018, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.3983%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=40378, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.3003%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=40618, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.2391%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=41218, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.0976%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3433, ncalls=41615, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.0131%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.0002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 41675 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -4.031 +- 0.05895 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2002.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_store.py::test_storemany	0.70
[gw10] linux -- Python 3.10.6 /usr/bin/python3 [gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ======== <class 'ultranest.store.TextPointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[1]: [(1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] 0 0.1 reading: [0.0, 1.0, 1.0] stack[2]: [(2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[3]: [(3, [1.0, 1.5, 1.5])] 1 1.1 reading: [1.0, 1.5, 1.5] ======== <class 'ultranest.store.TextPointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[1]: [(2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] stack[2]: [(4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[3]: [(6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] ======== <class 'ultranest.store.TextPointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[1]: [(10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] stack[2]: [(20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[3]: [(30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] ======== <class 'ultranest.store.TextPointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [-inf, 9.9, 9.9]), (11, [-inf, 10.9, 10.9]), (12, [-inf, 11.9, 11.9]), (13, [-inf, 12.9, 12.9]), (14, [-inf, 13.9, 13.9]), (15, [-inf, 14.9, 14.9]), (16, [-inf, 15.9, 15.9]), (17, [-inf, 16.9, 16.9]), (18, [-inf, 17.9, 17.9]), (19, [-inf, 18.9, 18.9]), (20, [-inf, 19.9, 19.9]), (21, [-inf, 20.9, 20.9]), (22, [-inf, 21.9, 21.9]), (23, [-inf, 22.9, 22.9]), (24, [-inf, 23.9, 23.9]), (25, [-inf, 24.9, 24.9]), (26, [-inf, 25.9, 25.9]), (27, [-inf, 26.9, 26.9]), (28, [-inf, 27.9, 27.9]), (29, [-inf, 28.9, 28.9]), (30, [-inf, 29.9, 29.9]), (31, [-inf, 30.9, 30.9]), (32, [-inf, 31.9, 31.9]), (33, [-inf, 32.9, 32.9]), (34, [-inf, 33.9, 33.9]), (35, [-inf, 34.9, 34.9]), (36, [-inf, 35.9, 35.9]), (37, [-inf, 36.9, 36.9]), (38, [-inf, 37.9, 37.9]), (39, [-inf, 38.9, 38.9]), (40, [-inf, 39.9, 39.9]), (41, [-inf, 40.9, 40.9]), (42, [-inf, 41.9, 41.9]), (43, [-inf, 42.9, 42.9]), (44, [-inf, 43.9, 43.9]), (45, [-inf, 44.9, 44.9]), (46, [-inf, 45.9, 45.9]), (47, [-inf, 46.9, 46.9]), (48, [-inf, 47.9, 47.9]), (49, [-inf, 48.9, 48.9]), (50, [-inf, 49.9, 49.9]), (51, [-inf, 50.9, 50.9]), (52, [-inf, 51.9, 51.9]), (53, [-inf, 52.9, 52.9]), (54, [-inf, 53.9, 53.9]), (55, [-inf, 54.9, 54.9]), (56, [-inf, 55.9, 55.9]), (57, [-inf, 56.9, 56.9]), (58, [-inf, 57.9, 57.9]), (59, [-inf, 58.9, 58.9]), (60, [-inf, 59.9, 59.9]), (61, [-inf, 60.9, 60.9]), (62, [-inf, 61.9, 61.9]), (63, [-inf, 62.9, 62.9]), (64, [-inf, 63.9, 63.9]), (65, [-inf, 64.9, 64.9]), (66, [-inf, 65.9, 65.9]), (67, [-inf, 66.9, 66.9]), (68, [-inf, 67.9, 67.9]), (69, [-inf, 68.9, 68.9]), (70, [-inf, 69.9, 69.9]), (71, [-inf, 70.9, 70.9]), (72, [-inf, 71.9, 71.9]), (73, [-inf, 72.9, 72.9]), (74, [-inf, 73.9, 73.9]), (75, [-inf, 74.9, 74.9]), (76, [-inf, 75.9, 75.9]), (77, [-inf, 76.9, 76.9]), (78, [-inf, 77.9, 77.9]), (79, [-inf, 78.9, 78.9]), (80, [-inf, 79.9, 79.9]), (81, [-inf, 80.9, 80.9]), (82, [-inf, 81.9, 81.9]), (83, [-inf, 82.9, 82.9]), (84, [-inf, 83.9, 83.9]), (85, [-inf, 84.9, 84.9]), (86, [-inf, 85.9, 85.9]), (87, [-inf, 86.9, 86.9]), (88, [-inf, 87.9, 87.9]), (89, [-inf, 88.9, 88.9]), (90, [-inf, 89.9, 89.9]), (91, [-inf, 90.9, 90.9]), (92, [-inf, 91.9, 91.9]), (93, [-inf, 92.9, 92.9]), (94, [-inf, 93.9, 93.9]), (95, [-inf, 94.9, 94.9]), (96, [-inf, 95.9, 95.9]), (97, [-inf, 96.9, 96.9]), (98, [-inf, 97.9, 97.9]), (99, [-inf, 98.9, 98.9]), (100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[1]: [(100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] 10 10.1 reading: [10.0, 11.0, 11.0] 11 11.1 reading: [11.0, 12.0, 12.0] 12 12.1 reading: [12.0, 13.0, 13.0] 13 13.1 reading: [13.0, 14.0, 14.0] 14 14.1 reading: [14.0, 15.0, 15.0] 15 15.1 reading: [15.0, 16.0, 16.0] 16 16.1 reading: [16.0, 17.0, 17.0] 17 17.1 reading: [17.0, 18.0, 18.0] 18 18.1 reading: [18.0, 19.0, 19.0] 19 19.1 reading: [19.0, 20.0, 20.0] 20 20.1 reading: [20.0, 21.0, 21.0] 21 21.1 reading: [21.0, 22.0, 22.0] 22 22.1 reading: [22.0, 23.0, 23.0] 23 23.1 reading: [23.0, 24.0, 24.0] 24 24.1 reading: [24.0, 25.0, 25.0] 25 25.1 reading: [25.0, 26.0, 26.0] 26 26.1 reading: [26.0, 27.0, 27.0] 27 27.1 reading: [27.0, 28.0, 28.0] 28 28.1 reading: [28.0, 29.0, 29.0] 29 29.1 reading: [29.0, 30.0, 30.0] 30 30.1 reading: [30.0, 31.0, 31.0] 31 31.1 reading: [31.0, 32.0, 32.0] 32 32.1 reading: [32.0, 33.0, 33.0] 33 33.1 reading: [33.0, 34.0, 34.0] 34 34.1 reading: [34.0, 35.0, 35.0] 35 35.1 reading: [35.0, 36.0, 36.0] 36 36.1 reading: [36.0, 37.0, 37.0] 37 37.1 reading: [37.0, 38.0, 38.0] 38 38.1 reading: [38.0, 39.0, 39.0] 39 39.1 reading: [39.0, 40.0, 40.0] 40 40.1 reading: [40.0, 41.0, 41.0] 41 41.1 reading: [41.0, 42.0, 42.0] 42 42.1 reading: [42.0, 43.0, 43.0] 43 43.1 reading: [43.0, 44.0, 44.0] 44 44.1 reading: [44.0, 45.0, 45.0] 45 45.1 reading: [45.0, 46.0, 46.0] 46 46.1 reading: [46.0, 47.0, 47.0] 47 47.1 reading: [47.0, 48.0, 48.0] 48 48.1 reading: [48.0, 49.0, 49.0] 49 49.1 reading: [49.0, 50.0, 50.0] 50 50.1 reading: [50.0, 51.0, 51.0] 51 51.1 reading: [51.0, 52.0, 52.0] 52 52.1 reading: [52.0, 53.0, 53.0] 53 53.1 reading: [53.0, 54.0, 54.0] 54 54.1 reading: [54.0, 55.0, 55.0] 55 55.1 reading: [55.0, 56.0, 56.0] 56 56.1 reading: [56.0, 57.0, 57.0] 57 57.1 reading: [57.0, 58.0, 58.0] 58 58.1 reading: [58.0, 59.0, 59.0] 59 59.1 reading: [59.0, 60.0, 60.0] 60 60.1 reading: [60.0, 61.0, 61.0] 61 61.1 reading: [61.0, 62.0, 62.0] 62 62.1 reading: [62.0, 63.0, 63.0] 63 63.1 reading: [63.0, 64.0, 64.0] 64 64.1 reading: [64.0, 65.0, 65.0] 65 65.1 reading: [65.0, 66.0, 66.0] 66 66.1 reading: [66.0, 67.0, 67.0] 67 67.1 reading: [67.0, 68.0, 68.0] 68 68.1 reading: [68.0, 69.0, 69.0] 69 69.1 reading: [69.0, 70.0, 70.0] 70 70.1 reading: [70.0, 71.0, 71.0] 71 71.1 reading: [71.0, 72.0, 72.0] 72 72.1 reading: [72.0, 73.0, 73.0] 73 73.1 reading: [73.0, 74.0, 74.0] 74 74.1 reading: [74.0, 75.0, 75.0] 75 75.1 reading: [75.0, 76.0, 76.0] 76 76.1 reading: [76.0, 77.0, 77.0] 77 77.1 reading: [77.0, 78.0, 78.0] 78 78.1 reading: [78.0, 79.0, 79.0] 79 79.1 reading: [79.0, 80.0, 80.0] 80 80.1 reading: [80.0, 81.0, 81.0] 81 81.1 reading: [81.0, 82.0, 82.0] 82 82.1 reading: [82.0, 83.0, 83.0] 83 83.1 reading: [83.0, 84.0, 84.0] 84 84.1 reading: [84.0, 85.0, 85.0] 85 85.1 reading: [85.0, 86.0, 86.0] 86 86.1 reading: [86.0, 87.0, 87.0] 87 87.1 reading: [87.0, 88.0, 88.0] 88 88.1 reading: [88.0, 89.0, 89.0] 89 89.1 reading: [89.0, 90.0, 90.0] 90 90.1 reading: [90.0, 91.0, 91.0] 91 91.1 reading: [91.0, 92.0, 92.0] 92 92.1 reading: [92.0, 93.0, 93.0] 93 93.1 reading: [93.0, 94.0, 94.0] 94 94.1 reading: [94.0, 95.0, 95.0] 95 95.1 reading: [95.0, 96.0, 96.0] 96 96.1 reading: [96.0, 97.0, 97.0] 97 97.1 reading: [97.0, 98.0, 98.0] 98 98.1 reading: [98.0, 99.0, 99.0] 99 99.1 reading: [99.0, 100.0, 100.0] stack[2]: [(200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[3]: [(300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] 11 11.1 reading: [11.0, 11.5, 11.5] 12 12.1 reading: [12.0, 12.5, 12.5] 13 13.1 reading: [13.0, 13.5, 13.5] 14 14.1 reading: [14.0, 14.5, 14.5] 15 15.1 reading: [15.0, 15.5, 15.5] 16 16.1 reading: [16.0, 16.5, 16.5] 17 17.1 reading: [17.0, 17.5, 17.5] 18 18.1 reading: [18.0, 18.5, 18.5] 19 19.1 reading: [19.0, 19.5, 19.5] 20 20.1 reading: [20.0, 20.5, 20.5] 21 21.1 reading: [21.0, 21.5, 21.5] 22 22.1 reading: [22.0, 22.5, 22.5] 23 23.1 reading: [23.0, 23.5, 23.5] 24 24.1 reading: [24.0, 24.5, 24.5] 25 25.1 reading: [25.0, 25.5, 25.5] 26 26.1 reading: [26.0, 26.5, 26.5] 27 27.1 reading: [27.0, 27.5, 27.5] 28 28.1 reading: [28.0, 28.5, 28.5] 29 29.1 reading: [29.0, 29.5, 29.5] 30 30.1 reading: [30.0, 30.5, 30.5] 31 31.1 reading: [31.0, 31.5, 31.5] 32 32.1 reading: [32.0, 32.5, 32.5] 33 33.1 reading: [33.0, 33.5, 33.5] 34 34.1 reading: [34.0, 34.5, 34.5] 35 35.1 reading: [35.0, 35.5, 35.5] 36 36.1 reading: [36.0, 36.5, 36.5] 37 37.1 reading: [37.0, 37.5, 37.5] 38 38.1 reading: [38.0, 38.5, 38.5] 39 39.1 reading: [39.0, 39.5, 39.5] 40 40.1 reading: [40.0, 40.5, 40.5] 41 41.1 reading: [41.0, 41.5, 41.5] 42 42.1 reading: [42.0, 42.5, 42.5] 43 43.1 reading: [43.0, 43.5, 43.5] 44 44.1 reading: [44.0, 44.5, 44.5] 45 45.1 reading: [45.0, 45.5, 45.5] 46 46.1 reading: [46.0, 46.5, 46.5] 47 47.1 reading: [47.0, 47.5, 47.5] 48 48.1 reading: [48.0, 48.5, 48.5] 49 49.1 reading: [49.0, 49.5, 49.5] 50 50.1 reading: [50.0, 50.5, 50.5] 51 51.1 reading: [51.0, 51.5, 51.5] 52 52.1 reading: [52.0, 52.5, 52.5] 53 53.1 reading: [53.0, 53.5, 53.5] 54 54.1 reading: [54.0, 54.5, 54.5] 55 55.1 reading: [55.0, 55.5, 55.5] 56 56.1 reading: [56.0, 56.5, 56.5] 57 57.1 reading: [57.0, 57.5, 57.5] 58 58.1 reading: [58.0, 58.5, 58.5] 59 59.1 reading: [59.0, 59.5, 59.5] 60 60.1 reading: [60.0, 60.5, 60.5] 61 61.1 reading: [61.0, 61.5, 61.5] 62 62.1 reading: [62.0, 62.5, 62.5] 63 63.1 reading: [63.0, 63.5, 63.5] 64 64.1 reading: [64.0, 64.5, 64.5] 65 65.1 reading: [65.0, 65.5, 65.5] 66 66.1 reading: [66.0, 66.5, 66.5] 67 67.1 reading: [67.0, 67.5, 67.5] 68 68.1 reading: [68.0, 68.5, 68.5] 69 69.1 reading: [69.0, 69.5, 69.5] 70 70.1 reading: [70.0, 70.5, 70.5] 71 71.1 reading: [71.0, 71.5, 71.5] 72 72.1 reading: [72.0, 72.5, 72.5] 73 73.1 reading: [73.0, 73.5, 73.5] 74 74.1 reading: [74.0, 74.5, 74.5] 75 75.1 reading: [75.0, 75.5, 75.5] 76 76.1 reading: [76.0, 76.5, 76.5] 77 77.1 reading: [77.0, 77.5, 77.5] 78 78.1 reading: [78.0, 78.5, 78.5] 79 79.1 reading: [79.0, 79.5, 79.5] 80 80.1 reading: [80.0, 80.5, 80.5] 81 81.1 reading: [81.0, 81.5, 81.5] 82 82.1 reading: [82.0, 82.5, 82.5] 83 83.1 reading: [83.0, 83.5, 83.5] 84 84.1 reading: [84.0, 84.5, 84.5] 85 85.1 reading: [85.0, 85.5, 85.5] 86 86.1 reading: [86.0, 86.5, 86.5] 87 87.1 reading: [87.0, 87.5, 87.5] 88 88.1 reading: [88.0, 88.5, 88.5] 89 89.1 reading: [89.0, 89.5, 89.5] 90 90.1 reading: [90.0, 90.5, 90.5] 91 91.1 reading: [91.0, 91.5, 91.5] 92 92.1 reading: [92.0, 92.5, 92.5] 93 93.1 reading: [93.0, 93.5, 93.5] 94 94.1 reading: [94.0, 94.5, 94.5] 95 95.1 reading: [95.0, 95.5, 95.5] 96 96.1 reading: [96.0, 96.5, 96.5] 97 97.1 reading: [97.0, 97.5, 97.5] 98 98.1 reading: [98.0, 98.5, 98.5] 99 99.1 reading: [99.0, 99.5, 99.5] 100 100.1 reading: [100.0, 100.5, 100.5] ======== <class 'ultranest.store.HDF5PointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[1]: [(1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] 0 0.1 reading: [0. 1. 1.] stack[2]: [(2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[3]: [(3, array([1. , 1.5, 1.5]))] 1 1.1 reading: [1. 1.5 1.5] ======== <class 'ultranest.store.HDF5PointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[1]: [(2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] stack[2]: [(4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[3]: [(6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] ======== <class 'ultranest.store.HDF5PointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[1]: [(10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] stack[2]: [(20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[3]: [(30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] ======== <class 'ultranest.store.HDF5PointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([-inf, 9.9, 9.9])), (11, array([-inf, 10.9, 10.9])), (12, array([-inf, 11.9, 11.9])), (13, array([-inf, 12.9, 12.9])), (14, array([-inf, 13.9, 13.9])), (15, array([-inf, 14.9, 14.9])), (16, array([-inf, 15.9, 15.9])), (17, array([-inf, 16.9, 16.9])), (18, array([-inf, 17.9, 17.9])), (19, array([-inf, 18.9, 18.9])), (20, array([-inf, 19.9, 19.9])), (21, array([-inf, 20.9, 20.9])), (22, array([-inf, 21.9, 21.9])), (23, array([-inf, 22.9, 22.9])), (24, array([-inf, 23.9, 23.9])), (25, array([-inf, 24.9, 24.9])), (26, array([-inf, 25.9, 25.9])), (27, array([-inf, 26.9, 26.9])), (28, array([-inf, 27.9, 27.9])), (29, array([-inf, 28.9, 28.9])), (30, array([-inf, 29.9, 29.9])), (31, array([-inf, 30.9, 30.9])), (32, array([-inf, 31.9, 31.9])), (33, array([-inf, 32.9, 32.9])), (34, array([-inf, 33.9, 33.9])), (35, array([-inf, 34.9, 34.9])), (36, array([-inf, 35.9, 35.9])), (37, array([-inf, 36.9, 36.9])), (38, array([-inf, 37.9, 37.9])), (39, array([-inf, 38.9, 38.9])), (40, array([-inf, 39.9, 39.9])), (41, array([-inf, 40.9, 40.9])), (42, array([-inf, 41.9, 41.9])), (43, array([-inf, 42.9, 42.9])), (44, array([-inf, 43.9, 43.9])), (45, array([-inf, 44.9, 44.9])), (46, array([-inf, 45.9, 45.9])), (47, array([-inf, 46.9, 46.9])), (48, array([-inf, 47.9, 47.9])), (49, array([-inf, 48.9, 48.9])), (50, array([-inf, 49.9, 49.9])), (51, array([-inf, 50.9, 50.9])), (52, array([-inf, 51.9, 51.9])), (53, array([-inf, 52.9, 52.9])), (54, array([-inf, 53.9, 53.9])), (55, array([-inf, 54.9, 54.9])), (56, array([-inf, 55.9, 55.9])), (57, array([-inf, 56.9, 56.9])), (58, array([-inf, 57.9, 57.9])), (59, array([-inf, 58.9, 58.9])), (60, array([-inf, 59.9, 59.9])), (61, array([-inf, 60.9, 60.9])), (62, array([-inf, 61.9, 61.9])), (63, array([-inf, 62.9, 62.9])), (64, array([-inf, 63.9, 63.9])), (65, array([-inf, 64.9, 64.9])), (66, array([-inf, 65.9, 65.9])), (67, array([-inf, 66.9, 66.9])), (68, array([-inf, 67.9, 67.9])), (69, array([-inf, 68.9, 68.9])), (70, array([-inf, 69.9, 69.9])), (71, array([-inf, 70.9, 70.9])), (72, array([-inf, 71.9, 71.9])), (73, array([-inf, 72.9, 72.9])), (74, array([-inf, 73.9, 73.9])), (75, array([-inf, 74.9, 74.9])), (76, array([-inf, 75.9, 75.9])), (77, array([-inf, 76.9, 76.9])), (78, array([-inf, 77.9, 77.9])), (79, array([-inf, 78.9, 78.9])), (80, array([-inf, 79.9, 79.9])), (81, array([-inf, 80.9, 80.9])), (82, array([-inf, 81.9, 81.9])), (83, array([-inf, 82.9, 82.9])), (84, array([-inf, 83.9, 83.9])), (85, array([-inf, 84.9, 84.9])), (86, array([-inf, 85.9, 85.9])), (87, array([-inf, 86.9, 86.9])), (88, array([-inf, 87.9, 87.9])), (89, array([-inf, 88.9, 88.9])), (90, array([-inf, 89.9, 89.9])), (91, array([-inf, 90.9, 90.9])), (92, array([-inf, 91.9, 91.9])), (93, array([-inf, 92.9, 92.9])), (94, array([-inf, 93.9, 93.9])), (95, array([-inf, 94.9, 94.9])), (96, array([-inf, 95.9, 95.9])), (97, array([-inf, 96.9, 96.9])), (98, array([-inf, 97.9, 97.9])), (99, array([-inf, 98.9, 98.9])), (100, array([0., 1., 1.])), (101, array([1., 2., 2.])), (102, array([2., 3., 3.])), (103, array([3., 4., 4.])), (104, array([4., 5., 5.])), (105, array([5., 6., 6.])), (106, array([6., 7., 7.])), (107, array([7., 8., 8.])), (108, array([8., 9., 9.])), (109, array([ 9., 10., 10.])), (110, array([10., 11., 11.])), (111, array([11., 12., 12.])), (112, array([12., 13., 13.])), (113, array([13., 14., 14.])), (114, array([14., 15., 15.])), (115, array([15., 16., 16.])), (116, array([16., 17., 17.])), (117, array([17., 18., 18.])), (118, array([18., 19., 19.])), (119, array([19., 20., 20.])), (120, array([20., 21., 21.])), (121, array([21., 22., 22.])), (122, array([22., 23., 23.])), (123, array([23., 24., 24.])), (124, array([24., 25., 25.])), (125, array([25., 26., 26.])), (126, array([26., 27., 27.])), (127, array([27., 28., 28.])), (128, array([28., 29., 29.])), (129, array([29., 30., 30.])), (130, array([30., 31., 31.])), (131, array([31., 32., 32.])), (132, array([32., 33., 33.])), (133, array([33., 34., 34.])), (134, array([34., 35., 35.])), (135, array([35., 36., 36.])), (136, array([36., 37., 37.])), (137, array([37., 38., 38.])), (138, array([38., 39., 39.])), (139, array([39., 40., 40.])), (140, array([40., 41., 41.])), (141, array([41., 42., 42.])), (142, array([42., 43., 43.])), (143, array([43., 44., 44.])), (144, array([44., 45., 45.])), (145, array([45., 46., 46.])), (146, array([46., 47., 47.])), (147, array([47., 48., 48.])), (148, array([48., 49., 49.])), (149, array([49., 50., 50.])), (150, array([50., 51., 51.])), (151, array([51., 52., 52.])), (152, array([52., 53., 53.])), (153, array([53., 54., 54.])), (154, array([54., 55., 55.])), (155, array([55., 56., 56.])), (156, array([56., 57., 57.])), (157, array([57., 58., 58.])), (158, array([58., 59., 59.])), (159, array([59., 60., 60.])), (160, array([60., 61., 61.])), (161, array([61., 62., 62.])), (162, array([62., 63., 63.])), (163, array([63., 64., 64.])), (164, array([64., 65., 65.])), (165, array([65., 66., 66.])), (166, array([66., 67., 67.])), (167, array([67., 68., 68.])), (168, array([68., 69., 69.])), (169, array([69., 70., 70.])), (170, array([70., 71., 71.])), (171, array([71., 72., 72.])), (172, array([72., 73., 73.])), (173, array([73., 74., 74.])), (174, array([74., 75., 75.])), (175, array([75., 76., 76.])), (176, array([76., 77., 77.])), (177, array([77., 78., 78.])), (178, array([78., 79., 79.])), (179, array([79., 80., 80.])), (180, array([80., 81., 81.])), (181, array([81., 82., 82.])), (182, array([82., 83., 83.])), (183, array([83., 84., 84.])), (184, array([84., 85., 85.])), (185, array([85., 86., 86.])), (186, array([86., 87., 87.])), (187, array([87., 88., 88.])), (188, array([88., 89., 89.])), (189, array([89., 90., 90.])), (190, array([90., 91., 91.])), (191, array([91., 92., 92.])), (192, array([92., 93., 93.])), (193, array([93., 94., 94.])), (194, array([94., 95., 95.])), (195, array([95., 96., 96.])), (196, array([96., 97., 97.])), (197, array([97., 98., 98.])), (198, array([98., 99., 99.])), (199, array([ 99., 100., 100.])), (200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] stack[1]: [(100, array([0., 1., 1.])), (101, array([1., 2., 2.])), (102, array([2., 3., 3.])), (103, array([3., 4., 4.])), (104, array([4., 5., 5.])), (105, array([5., 6., 6.])), (106, array([6., 7., 7.])), (107, array([7., 8., 8.])), (108, array([8., 9., 9.])), (109, array([ 9., 10., 10.])), (110, array([10., 11., 11.])), (111, array([11., 12., 12.])), (112, array([12., 13., 13.])), (113, array([13., 14., 14.])), (114, array([14., 15., 15.])), (115, array([15., 16., 16.])), (116, array([16., 17., 17.])), (117, array([17., 18., 18.])), (118, array([18., 19., 19.])), (119, array([19., 20., 20.])), (120, array([20., 21., 21.])), (121, array([21., 22., 22.])), (122, array([22., 23., 23.])), (123, array([23., 24., 24.])), (124, array([24., 25., 25.])), (125, array([25., 26., 26.])), (126, array([26., 27., 27.])), (127, array([27., 28., 28.])), (128, array([28., 29., 29.])), (129, array([29., 30., 30.])), (130, array([30., 31., 31.])), (131, array([31., 32., 32.])), (132, array([32., 33., 33.])), (133, array([33., 34., 34.])), (134, array([34., 35., 35.])), (135, array([35., 36., 36.])), (136, array([36., 37., 37.])), (137, array([37., 38., 38.])), (138, array([38., 39., 39.])), (139, array([39., 40., 40.])), (140, array([40., 41., 41.])), (141, array([41., 42., 42.])), (142, array([42., 43., 43.])), (143, array([43., 44., 44.])), (144, array([44., 45., 45.])), (145, array([45., 46., 46.])), (146, array([46., 47., 47.])), (147, array([47., 48., 48.])), (148, array([48., 49., 49.])), (149, array([49., 50., 50.])), (150, array([50., 51., 51.])), (151, array([51., 52., 52.])), (152, array([52., 53., 53.])), (153, array([53., 54., 54.])), (154, array([54., 55., 55.])), (155, array([55., 56., 56.])), (156, array([56., 57., 57.])), (157, array([57., 58., 58.])), (158, array([58., 59., 59.])), (159, array([59., 60., 60.])), (160, array([60., 61., 61.])), (161, array([61., 62., 62.])), (162, array([62., 63., 63.])), (163, array([63., 64., 64.])), (164, array([64., 65., 65.])), (165, array([65., 66., 66.])), (166, array([66., 67., 67.])), (167, array([67., 68., 68.])), (168, array([68., 69., 69.])), (169, array([69., 70., 70.])), (170, array([70., 71., 71.])), (171, array([71., 72., 72.])), (172, array([72., 73., 73.])), (173, array([73., 74., 74.])), (174, array([74., 75., 75.])), (175, array([75., 76., 76.])), (176, array([76., 77., 77.])), (177, array([77., 78., 78.])), (178, array([78., 79., 79.])), (179, array([79., 80., 80.])), (180, array([80., 81., 81.])), (181, array([81., 82., 82.])), (182, array([82., 83., 83.])), (183, array([83., 84., 84.])), (184, array([84., 85., 85.])), (185, array([85., 86., 86.])), (186, array([86., 87., 87.])), (187, array([87., 88., 88.])), (188, array([88., 89., 89.])), (189, array([89., 90., 90.])), (190, array([90., 91., 91.])), (191, array([91., 92., 92.])), (192, array([92., 93., 93.])), (193, array([93., 94., 94.])), (194, array([94., 95., 95.])), (195, array([95., 96., 96.])), (196, array([96., 97., 97.])), (197, array([97., 98., 98.])), (198, array([98., 99., 99.])), (199, array([ 99., 100., 100.])), (200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] 10 10.1 reading: [10. 11. 11.] 11 11.1 reading: [11. 12. 12.] 12 12.1 reading: [12. 13. 13.] 13 13.1 reading: [13. 14. 14.] 14 14.1 reading: [14. 15. 15.] 15 15.1 reading: [15. 16. 16.] 16 16.1 reading: [16. 17. 17.] 17 17.1 reading: [17. 18. 18.] 18 18.1 reading: [18. 19. 19.] 19 19.1 reading: [19. 20. 20.] 20 20.1 reading: [20. 21. 21.] 21 21.1 reading: [21. 22. 22.] 22 22.1 reading: [22. 23. 23.] 23 23.1 reading: [23. 24. 24.] 24 24.1 reading: [24. 25. 25.] 25 25.1 reading: [25. 26. 26.] 26 26.1 reading: [26. 27. 27.] 27 27.1 reading: [27. 28. 28.] 28 28.1 reading: [28. 29. 29.] 29 29.1 reading: [29. 30. 30.] 30 30.1 reading: [30. 31. 31.] 31 31.1 reading: [31. 32. 32.] 32 32.1 reading: [32. 33. 33.] 33 33.1 reading: [33. 34. 34.] 34 34.1 reading: [34. 35. 35.] 35 35.1 reading: [35. 36. 36.] 36 36.1 reading: [36. 37. 37.] 37 37.1 reading: [37. 38. 38.] 38 38.1 reading: [38. 39. 39.] 39 39.1 reading: [39. 40. 40.] 40 40.1 reading: [40. 41. 41.] 41 41.1 reading: [41. 42. 42.] 42 42.1 reading: [42. 43. 43.] 43 43.1 reading: [43. 44. 44.] 44 44.1 reading: [44. 45. 45.] 45 45.1 reading: [45. 46. 46.] 46 46.1 reading: [46. 47. 47.] 47 47.1 reading: [47. 48. 48.] 48 48.1 reading: [48. 49. 49.] 49 49.1 reading: [49. 50. 50.] 50 50.1 reading: [50. 51. 51.] 51 51.1 reading: [51. 52. 52.] 52 52.1 reading: [52. 53. 53.] 53 53.1 reading: [53. 54. 54.] 54 54.1 reading: [54. 55. 55.] 55 55.1 reading: [55. 56. 56.] 56 56.1 reading: [56. 57. 57.] 57 57.1 reading: [57. 58. 58.] 58 58.1 reading: [58. 59. 59.] 59 59.1 reading: [59. 60. 60.] 60 60.1 reading: [60. 61. 61.] 61 61.1 reading: [61. 62. 62.] 62 62.1 reading: [62. 63. 63.] 63 63.1 reading: [63. 64. 64.] 64 64.1 reading: [64. 65. 65.] 65 65.1 reading: [65. 66. 66.] 66 66.1 reading: [66. 67. 67.] 67 67.1 reading: [67. 68. 68.] 68 68.1 reading: [68. 69. 69.] 69 69.1 reading: [69. 70. 70.] 70 70.1 reading: [70. 71. 71.] 71 71.1 reading: [71. 72. 72.] 72 72.1 reading: [72. 73. 73.] 73 73.1 reading: [73. 74. 74.] 74 74.1 reading: [74. 75. 75.] 75 75.1 reading: [75. 76. 76.] 76 76.1 reading: [76. 77. 77.] 77 77.1 reading: [77. 78. 78.] 78 78.1 reading: [78. 79. 79.] 79 79.1 reading: [79. 80. 80.] 80 80.1 reading: [80. 81. 81.] 81 81.1 reading: [81. 82. 82.] 82 82.1 reading: [82. 83. 83.] 83 83.1 reading: [83. 84. 84.] 84 84.1 reading: [84. 85. 85.] 85 85.1 reading: [85. 86. 86.] 86 86.1 reading: [86. 87. 87.] 87 87.1 reading: [87. 88. 88.] 88 88.1 reading: [88. 89. 89.] 89 89.1 reading: [89. 90. 90.] 90 90.1 reading: [90. 91. 91.] 91 91.1 reading: [91. 92. 92.] 92 92.1 reading: [92. 93. 93.] 93 93.1 reading: [93. 94. 94.] 94 94.1 reading: [94. 95. 95.] 95 95.1 reading: [95. 96. 96.] 96 96.1 reading: [96. 97. 97.] 97 97.1 reading: [97. 98. 98.] 98 98.1 reading: [98. 99. 99.] 99 99.1 reading: [ 99. 100. 100.] stack[2]: [(200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] stack[3]: [(300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] 11 11.1 reading: [11. 11.5 11.5] 12 12.1 reading: [12. 12.5 12.5] 13 13.1 reading: [13. 13.5 13.5] 14 14.1 reading: [14. 14.5 14.5] 15 15.1 reading: [15. 15.5 15.5] 16 16.1 reading: [16. 16.5 16.5] 17 17.1 reading: [17. 17.5 17.5] 18 18.1 reading: [18. 18.5 18.5] 19 19.1 reading: [19. 19.5 19.5] 20 20.1 reading: [20. 20.5 20.5] 21 21.1 reading: [21. 21.5 21.5] 22 22.1 reading: [22. 22.5 22.5] 23 23.1 reading: [23. 23.5 23.5] 24 24.1 reading: [24. 24.5 24.5] 25 25.1 reading: [25. 25.5 25.5] 26 26.1 reading: [26. 26.5 26.5] 27 27.1 reading: [27. 27.5 27.5] 28 28.1 reading: [28. 28.5 28.5] 29 29.1 reading: [29. 29.5 29.5] 30 30.1 reading: [30. 30.5 30.5] 31 31.1 reading: [31. 31.5 31.5] 32 32.1 reading: [32. 32.5 32.5] 33 33.1 reading: [33. 33.5 33.5] 34 34.1 reading: [34. 34.5 34.5] 35 35.1 reading: [35. 35.5 35.5] 36 36.1 reading: [36. 36.5 36.5] 37 37.1 reading: [37. 37.5 37.5] 38 38.1 reading: [38. 38.5 38.5] 39 39.1 reading: [39. 39.5 39.5] 40 40.1 reading: [40. 40.5 40.5] 41 41.1 reading: [41. 41.5 41.5] 42 42.1 reading: [42. 42.5 42.5] 43 43.1 reading: [43. 43.5 43.5] 44 44.1 reading: [44. 44.5 44.5] 45 45.1 reading: [45. 45.5 45.5] 46 46.1 reading: [46. 46.5 46.5] 47 47.1 reading: [47. 47.5 47.5] 48 48.1 reading: [48. 48.5 48.5] 49 49.1 reading: [49. 49.5 49.5] 50 50.1 reading: [50. 50.5 50.5] 51 51.1 reading: [51. 51.5 51.5] 52 52.1 reading: [52. 52.5 52.5] 53 53.1 reading: [53. 53.5 53.5] 54 54.1 reading: [54. 54.5 54.5] 55 55.1 reading: [55. 55.5 55.5] 56 56.1 reading: [56. 56.5 56.5] 57 57.1 reading: [57. 57.5 57.5] 58 58.1 reading: [58. 58.5 58.5] 59 59.1 reading: [59. 59.5 59.5] 60 60.1 reading: [60. 60.5 60.5] 61 61.1 reading: [61. 61.5 61.5] 62 62.1 reading: [62. 62.5 62.5] 63 63.1 reading: [63. 63.5 63.5] 64 64.1 reading: [64. 64.5 64.5] 65 65.1 reading: [65. 65.5 65.5] 66 66.1 reading: [66. 66.5 66.5] 67 67.1 reading: [67. 67.5 67.5] 68 68.1 reading: [68. 68.5 68.5] 69 69.1 reading: [69. 69.5 69.5] 70 70.1 reading: [70. 70.5 70.5] 71 71.1 reading: [71. 71.5 71.5] 72 72.1 reading: [72. 72.5 72.5] 73 73.1 reading: [73. 73.5 73.5] 74 74.1 reading: [74. 74.5 74.5] 75 75.1 reading: [75. 75.5 75.5] 76 76.1 reading: [76. 76.5 76.5] 77 77.1 reading: [77. 77.5 77.5] 78 78.1 reading: [78. 78.5 78.5] 79 79.1 reading: [79. 79.5 79.5] 80 80.1 reading: [80. 80.5 80.5] 81 81.1 reading: [81. 81.5 81.5] 82 82.1 reading: [82. 82.5 82.5] 83 83.1 reading: [83. 83.5 83.5] 84 84.1 reading: [84. 84.5 84.5] 85 85.1 reading: [85. 85.5 85.5] 86 86.1 reading: [86. 86.5 86.5] 87 87.1 reading: [87. 87.5 87.5] 88 88.1 reading: [88. 88.5 88.5] 89 89.1 reading: [89. 89.5 89.5] 90 90.1 reading: [90. 90.5 90.5] 91 91.1 reading: [91. 91.5 91.5] 92 92.1 reading: [92. 92.5 92.5] 93 93.1 reading: [93. 93.5 93.5] 94 94.1 reading: [94. 94.5 94.5] 95 95.1 reading: [95. 95.5 95.5] 96 96.1 reading: [96. 96.5 96.5] 97 97.1 reading: [97. 97.5 97.5] 98 98.1 reading: [98. 98.5 98.5] 99 99.1 reading: [99. 99.5 99.5] 100 100.1 reading: [100. 100.5 100.5]
Passed	tests/test_transforms.py::test_transform	0.04
[gw10] linux -- Python 3.10.6 /usr/bin/python3 [gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ -0.999 1 [ 1. -0.999 -0.999 1. ] (1000, 2) -0.999 0.001 [ 1. -0.999 -0.999 1. ] (1000, 2) -0.8991 1 [ 1. -0.8991 -0.8991 1. ] (1000, 2) -0.8991 0.001 [ 1. -0.8991 -0.8991 1. ] (1000, 2) -0.7992 1 [ 1. -0.7992 -0.7992 1. ] (1000, 2) -0.7992 0.001 [ 1. -0.7992 -0.7992 1. ] (1000, 2) -0.6993 1 [ 1. -0.6993 -0.6993 1. ] (1000, 2) -0.6993 0.001 [ 1. -0.6993 -0.6993 1. ] (1000, 2) -0.5994 1 [ 1. -0.5994 -0.5994 1. ] (1000, 2) -0.5994 0.001 [ 1. -0.5994 -0.5994 1. ] (1000, 2) -0.4995000000000001 1 [ 1. -0.4995 -0.4995 1. ] (1000, 2) -0.4995000000000001 0.001 [ 1. -0.4995 -0.4995 1. ] (1000, 2) -0.3996000000000001 1 [ 1. -0.3996 -0.3996 1. ] (1000, 2) -0.3996000000000001 0.001 [ 1. -0.3996 -0.3996 1. ] (1000, 2) -0.29970000000000013 1 [ 1. -0.2997 -0.2997 1. ] (1000, 2) -0.29970000000000013 0.001 [ 1. -0.2997 -0.2997 1. ] (1000, 2) -0.19980000000000017 1 [ 1. -0.1998 -0.1998 1. ] (1000, 2) -0.19980000000000017 0.001 [ 1. -0.1998 -0.1998 1. ] (1000, 2) -0.0999000000000002 1 [ 1. -0.0999 -0.0999 1. ] (1000, 2) -0.0999000000000002 0.001 [ 1. -0.0999 -0.0999 1. ] (1000, 2) -2.2182256032010628e-16 1 [ 1.0000000e+00 -2.2182256e-16 -2.2182256e-16 1.0000000e+00] (1000, 2) -2.2182256032010628e-16 0.001 [ 1.0000000e+00 -2.2182256e-16 -2.2182256e-16 1.0000000e+00] (1000, 2) 0.09989999999999964 1 [1. 0.0999 0.0999 1. ] (1000, 2) 0.09989999999999964 0.001 [1. 0.0999 0.0999 1. ] (1000, 2) 0.19979999999999973 1 [1. 0.1998 0.1998 1. ] (1000, 2) 0.19979999999999973 0.001 [1. 0.1998 0.1998 1. ] (1000, 2) 0.2996999999999998 1 [1. 0.2997 0.2997 1. ] (1000, 2) 0.2996999999999998 0.001 [1. 0.2997 0.2997 1. ] (1000, 2) 0.3995999999999997 1 [1. 0.3996 0.3996 1. ] (1000, 2) 0.3995999999999997 0.001 [1. 0.3996 0.3996 1. ] (1000, 2) 0.49949999999999956 1 [1. 0.4995 0.4995 1. ] (1000, 2) 0.49949999999999956 0.001 [1. 0.4995 0.4995 1. ] (1000, 2) 0.5993999999999996 1 [1. 0.5994 0.5994 1. ] (1000, 2) 0.5993999999999996 0.001 [1. 0.5994 0.5994 1. ] (1000, 2) 0.6992999999999997 1 [1. 0.6993 0.6993 1. ] (1000, 2) 0.6992999999999997 0.001 [1. 0.6993 0.6993 1. ] (1000, 2) 0.7991999999999996 1 [1. 0.7992 0.7992 1. ] (1000, 2) 0.7991999999999996 0.001 [1. 0.7992 0.7992 1. ] (1000, 2) 0.8990999999999995 1 [1. 0.8991 0.8991 1. ] (1000, 2) 0.8990999999999995 0.001 [1. 0.8991 0.8991 1. ] (1000, 2)
Passed	tests/test_stepsampling.py::test_crop_bracket	0.00
[gw6] linux -- Python 3.10.6 /usr/bin/python3 [gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ left: -1.9354937665716845 [1.93780732 1.70985572] right: 2.3302374240517256 [-1.45856722 -0.87105549]
Passed	tests/test_store.py::test_text_store	0.00
[gw6] linux -- Python 3.10.6 /usr/bin/python3 [gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [(1, [101.0, 155.0, 413.0, 213.0]), (2, [99.0, 156.0, 413.0, 213.0])]
Passed	tests/test_stepsampling.py::test_stepsampler_regionslice	8.32
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.24) * Expected Volume: exp(0.00) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.0000\|***********************************************\| +1.0000 param2: +0.00\|************************************************\| +1.00 Z=-inf(0.00%) \| Like=-30.54..-0.16 [-30.5444..-8.3389] \| it/evals=0/403 eff=0.0000% N=400 Z=-23.8(0.00%) \| Like=-19.64..-0.16 [-30.5444..-8.3389] \| it/evals=50/625 eff=22.2222% N=400 Mono-modal Volume: ~exp(-4.56) Expected Volume: exp(-0.23) Quality: ok param0: +0.0000\|*************************************************\| +1.0000 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|***********************************************\| +1.00 Z=-19.9(0.00%) \| Like=-16.25..-0.16 [-30.5444..-8.3389] \| it/evals=90/815 eff=21.6867% N=400 Z=-19.0(0.00%) \| Like=-15.25..-0.16 [-30.5444..-8.3389] \| it/evals=100/859 eff=21.7865% N=400 Z=-15.4(0.00%) \| Like=-11.94..-0.16 [-30.5444..-8.3389] \| it/evals=150/1114 eff=21.0084% N=400 Mono-modal Volume: ~exp(-4.56) Expected Volume: exp(-0.45) Quality: ok param0: +0.0000\|***********************************************\| +1.0000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-13.4(0.01%) \| Like=-10.09..-0.02 [-30.5444..-8.3389] \| it/evals=193/1325 eff=20.8649% N=400 Z=-13.1(0.01%) \| Like=-9.90..-0.02 [-30.5444..-8.3389] \| it/evals=200/1355 eff=20.9424% N=400 Z=-11.7(0.03%) \| Like=-8.71..-0.02 [-30.5444..-8.3389] \| it/evals=250/1615 eff=20.5761% N=400 Mono-modal Volume: ~exp(-4.97) Expected Volume: exp(-0.67) Quality: ok param0: +0.0000\|*************************************************\| +1.0000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-11.2(0.05%) \| Like=-8.28..-0.02 [-8.3047..-4.8735] \| it/evals=270/1733 eff=20.2551% N=400 Z=-10.6(0.09%) \| Like=-7.82..-0.02 [-8.3047..-4.8735] \| it/evals=300/1921 eff=19.7239% N=400 Z=-9.6(0.21%) \| Like=-6.84..-0.02 [-8.3047..-4.8735] \| it/evals=350/2211 eff=19.3263% N=400 Mono-modal Volume: ~exp(-5.10) Expected Volume: exp(-0.90) Quality: ok param0: +0.00\|************************************************ \| +1.00 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|***********************************************\| +1.00 Z=-9.5(0.26%) \| Like=-6.58..-0.02 [-8.3047..-4.8735] \| it/evals=360/2267 eff=19.2823% N=400 Z=-8.8(0.48%) \| Like=-6.11..-0.02 [-8.3047..-4.8735] \| it/evals=400/2529 eff=18.7882% N=400 Mono-modal Volume: ~exp(-5.10) Expected Volume: exp(-1.12) Quality: ok param0: +0.00\|********************************************** \| +1.00 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-8.2(0.90%) \| Like=-5.54..-0.02 [-8.3047..-4.8735] \| it/evals=450/2853 eff=18.3449% N=400 Z=-7.7(1.50%) \| Like=-5.11..-0.02 [-8.3047..-4.8735] \| it/evals=500/3213 eff=17.7746% N=400 Mono-modal Volume: ~exp(-5.15) Expected Volume: exp(-1.35) Quality: ok param0: +0.00\|*************************************************\| +1.00 param1: +0.00\| **********************************************\| +1.00 param2: +0.00\|************************************************\| +1.00 Z=-7.3(2.11%) \| Like=-4.85..-0.02 [-4.8667..-3.5363] \| it/evals=540/3522 eff=17.2966% N=400 Z=-7.3(2.25%) \| Like=-4.79..-0.02 [-4.8667..-3.5363] \| it/evals=550/3583 eff=17.2793% N=400 Z=-6.9(3.26%) \| Like=-4.37..-0.02 [-4.8667..-3.5363] \| it/evals=600/3990 eff=16.7131% N=400 Mono-modal Volume: ~exp(-5.90) Expected Volume: exp(-1.57) Quality: ok param0: +0.00\| *********************************************** \| +1.00 param1: +0.00\| ******************************************** * \| +1.00 param2: +0.00\| ************************************************ \| +1.00 Z=-6.7(4.01%) \| Like=-4.16..-0.02 [-4.8667..-3.5363] \| it/evals=630/4220 eff=16.4921% N=400 Z=-6.6(4.59%) \| Like=-4.07..-0.02 [-4.8667..-3.5363] \| it/evals=650/4402 eff=16.2419% N=400 Z=-6.3(6.01%) \| Like=-3.73..-0.02 [-4.8667..-3.5363] \| it/evals=700/4842 eff=15.7587% N=400 Mono-modal Volume: ~exp(-6.01) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00\| ********************************************* \| +1.00 param1: +0.00\| ********************************************* \| +1.00 param2: +0.00\| * ********************************************** \| +1.00 Z=-6.2(6.84%) \| Like=-3.61..-0.02 [-4.8667..-3.5363] \| it/evals=720/5010 eff=15.6182% N=400 Z=-6.0(7.92%) \| Like=-3.44..-0.02 [-3.5317..-3.1184] \| it/evals=750/5259 eff=15.4353% N=400 Z=-5.8(9.83%) \| Like=-3.16..-0.02 [-3.5317..-3.1184] \| it/evals=800/5704 eff=15.0830% N=400 Mono-modal Volume: ~exp(-6.16) * Expected Volume: exp(-2.02) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.00\| * ****************************************** \| +1.00 param1: +0.00\| ***************************************** \| +1.00 param2: +0.00\| ******************************************* \| +1.00 Z=-5.7(10.42%) \| Like=-3.09..-0.02 [-3.1048..-2.9456] \| it/evals=810/5789 eff=15.0306% N=400 Z=-5.5(12.51%) \| Like=-2.84..-0.02 [-2.8353..-2.8323]\| it/evals=850/6154 eff=14.7723% N=400 Have 2 modes Volume: ~exp(-6.49) Expected Volume: exp(-2.25) Quality: ok positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| 222222222222222222221111111111111111111111 \| +1.0 param1: +0.00\| 2222222222222222222221111111111111111111111 \| +1.00 param2: +0.00\| 2 22222222222222222211111111111111111111111 \| +1.00 Z=-5.3(15.20%) \| Like=-2.66..-0.02 [-2.6627..-2.6606]\| it/evals=900/6627 eff=14.4532% N=400 Z=-5.2(17.92%) \| Like=-2.46..-0.02 [-2.4569..-2.4441] \| it/evals=950/7162 eff=14.0491% N=400 Have 2 modes Volume: ~exp(-6.85) Expected Volume: exp(-2.47) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| 22222222222222222222111111111111111111111 \| +1.0 param1: +0.00\| 2222222222222222222221111111111111111111111 \| +1.00 param2: +0.0\| 2222222222222222222211 111111111111111111 \| +1.0 Z=-5.0(20.47%) \| Like=-2.26..-0.02 [-2.2800..-2.2623] \| it/evals=990/7589 eff=13.7710% N=400 Z=-5.0(21.00%) \| Like=-2.23..-0.02 [-2.2302..-2.2298]\| it/evals=1000/7701 eff=13.6968% N=400 Z=-4.8(24.28%) \| Like=-2.09..-0.02 [-2.0895..-2.0887]\| it/evals=1050/8276 eff=13.3316% N=400 Have 2 modes Volume: ~exp(-6.85) Expected Volume: exp(-2.70) Quality: ok positive degeneracy between param2 and param0: rho=0.78 param0: +0.0\| 20222222222222222222 1111111111111111111 \| +1.0 param1: +0.0\| 2222222222222222222211111111111111111111 \| +1.0 param2: +0.0\| 222222222222222222221011111111111111111 \| +1.0 Z=-4.7(27.83%) \| Like=-1.91..-0.01 [-1.9129..-1.9126]\| it/evals=1100/8869 eff=12.9885% N=400 Z=-4.6(31.84%) \| Like=-1.80..-0.01 [-1.7968..-1.7915]\| it/evals=1150/9487 eff=12.6554% N=400 Have 2 modes Volume: ~exp(-7.07) * Expected Volume: exp(-2.92) Quality: ok positive degeneracy between param2 and param0: rho=0.79 param0: +0.0\| 2222222222222222222 111111111111111111 \| +1.0 param1: +0.0\| 222222222222222222 1111111111111111111 \| +1.0 param2: +0.0\| 2222222222222222222 1111111111111111111 \| +1.0 Z=-4.5(33.40%) \| Like=-1.73..-0.01 [-1.7405..-1.7299] \| it/evals=1170/9717 eff=12.5577% N=400 Z=-4.5(35.63%) \| Like=-1.65..-0.01 [-1.6475..-1.6397]\| it/evals=1200/10066 eff=12.4146% N=400 Z=-4.4(39.40%) \| Like=-1.52..-0.01 [-1.5153..-1.5151]\| it/evals=1250/10690 eff=12.1477% N=400 Have 2 modes Volume: ~exp(-7.36) * Expected Volume: exp(-3.15) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.78 param0: +0.0\| 22222222222222222 1111111111111111 \| +1.0 param1: +0.0\| 2222222222222222 111111111111111111 \| +1.0 param2: +0.0\| 2222222222222222 11111111111111111 \| +1.0 Z=-4.4(40.19%) \| Like=-1.49..-0.01 [-1.4890..-1.4862]\| it/evals=1260/10813 eff=12.1003% N=400 Z=-4.3(43.15%) \| Like=-1.41..-0.01 [-1.4078..-1.3917] \| it/evals=1300/11308 eff=11.9179% N=400 Have 2 modes Volume: ~exp(-7.81) Expected Volume: exp(-3.37) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.77 param0: +0.0\| 222222222222222 1111111111111111 \| +1.0 param1: +0.0\| 222222222222222 1111111111111111 \| +1.0 param2: +0.0\| 222222222222222 1111111111111111 \| +1.0 Z=-4.2(46.96%) \| Like=-1.30..-0.01 [-1.2992..-1.2956]\| it/evals=1350/11939 eff=11.6995% N=400 Z=-4.1(50.50%) \| Like=-1.20..-0.01 [-1.2012..-1.1996]\| it/evals=1400/12583 eff=11.4914% N=400 Have 2 modes Volume: ~exp(-7.81) Expected Volume: exp(-3.60) Quality: ok positive degeneracy between param2 and param0: rho=0.78 param0: +0.0\| 22222222222222 111111111111110 \| +1.0 param1: +0.0\| 22222222222222 111111111111111 \| +1.0 param2: +0.0\| 222222222222220 011111111111111 \| +1.0 Z=-4.1(54.29%) \| Like=-1.09..-0.01 [-1.0913..-1.0910]\| it/evals=1450/13202 eff=11.3264% N=400 Z=-4.0(57.32%) \| Like=-1.00..-0.01 [-0.9959..-0.9958]\| it/evals=1496/13754 eff=11.2026% N=400 Z=-4.0(57.62%) \| Like=-0.99..-0.01 [-0.9915..-0.9898]\| it/evals=1500/13802 eff=11.1924% N=400 Have 2 modes Volume: ~exp(-8.41) Expected Volume: exp(-3.82) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| 22222222222222 1111111111111 \| +1.0 param1: +0.0\| 2222222222222 111111111111111 \| +1.0 param2: +0.0\| 22222222222222 111111111111111 \| +1.0 Z=-4.0(59.69%) \| Like=-0.94..-0.01 [-0.9429..-0.9420]\| it/evals=1530/14187 eff=11.0974% N=400 Z=-3.9(60.99%) \| Like=-0.91..-0.01 [-0.9093..-0.9066]\| it/evals=1550/14429 eff=11.0485% N=400 Z=-3.9(64.14%) \| Like=-0.81..-0.01 [-0.8112..-0.8112]\| it/evals=1600/15075 eff=10.9029% N=400 Have 2 modes Volume: ~exp(-8.64) Expected Volume: exp(-4.05) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| 2222222222222 1111111111111 \| +1.0 param1: +0.0\| 2222222222222 1111111111111 \| +1.0 param2: +0.0\| 2222222222222 1111111111111 \| +1.0 Z=-3.9(65.31%) \| Like=-0.79..-0.01 [-0.7893..-0.7882]\| it/evals=1620/15330 eff=10.8506% N=400 Z=-3.8(67.13%) \| Like=-0.74..-0.01 [-0.7450..-0.7446]\| it/evals=1650/15708 eff=10.7787% N=400 Z=-3.8(69.99%) \| Like=-0.68..-0.01 [-0.6789..-0.6773]\| it/evals=1700/16343 eff=10.6630% N=400 Have 2 modes Volume: ~exp(-8.91) Expected Volume: exp(-4.27) Quality: ok positive degeneracy between param2 and param0: rho=0.78 param0: +0.0\| 222222222222 111111111111 \| +1.0 param1: +0.0\| 22222222222 1111111111111 \| +1.0 param2: +0.0\| 2222222222222 111111111111 \| +1.0 Z=-3.8(70.50%) \| Like=-0.67..-0.01 [-0.6704..-0.6673]\| it/evals=1710/16469 eff=10.6416% N=400 Z=-3.8(72.70%) \| Like=-0.63..-0.01 [-0.6313..-0.6300]\| it/evals=1750/16966 eff=10.5638% N=400 Have 2 modes Volume: ~exp(-8.91) Expected Volume: exp(-4.50) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.77 param0: +0.0\| 222222222222 11111111111 +0.8 \| +1.0 param1: +0.0\| 22222222222 11111111111 +0.8 \| +1.0 param2: +0.0\| 22222222222 01111111111 +0.8 \| +1.0 Z=-3.7(75.28%) \| Like=-0.58..-0.01 [-0.5790..-0.5787]\| it/evals=1800/17586 eff=10.4736% N=400 Z=-3.7(77.32%) \| Like=-0.54..-0.01 [-0.5357..-0.5346]\| it/evals=1844/18126 eff=10.4028% N=400 Z=-3.7(77.57%) \| Like=-0.53..-0.01 [-0.5330..-0.5310]\| it/evals=1850/18198 eff=10.3944% N=400 Have 2 modes Volume: ~exp(-8.91) Expected Volume: exp(-4.73) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| 2222222222 1111111110 +0.8 \| +1.0 param1: +0.0\| 2222222222 1111111111 +0.8 \| +1.0 param2: +0.0\| 2222222222 01111111111 +0.8 \| +1.0 Z=-3.7(79.35%) \| Like=-0.49..-0.01 [-0.4882..-0.4881]\| it/evals=1891/18731 eff=10.3159% N=400 Z=-3.7(79.75%) \| Like=-0.48..-0.01 [-0.4822..-0.4805]\| it/evals=1900/18845 eff=10.3009% N=400 Z=-3.6(81.70%) \| Like=-0.44..-0.01 [-0.4446..-0.4440]\| it/evals=1950/19462 eff=10.2298% N=400 Have 2 modes Volume: ~exp(-9.24) * Expected Volume: exp(-4.95) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0\| 2222222222 111111111 +0.8 \| +1.0 param1: +0.0\| 2222222222 111111111 +0.8 \| +1.0 param2: +0.0\| +0.2 222222222 1111111111 +0.8 \| +1.0 Z=-3.6(82.82%) \| Like=-0.42..-0.01 [-0.4219..-0.4214]\| it/evals=1980/19839 eff=10.1857% N=400 Z=-3.6(83.53%) \| Like=-0.41..-0.01 [-0.4100..-0.4083]\| it/evals=2000/20095 eff=10.1549% N=400 Z=-3.6(85.06%) \| Like=-0.38..-0.01 [-0.3828..-0.3819]\| it/evals=2047/20694 eff=10.0867% N=400 Z=-3.6(85.15%) \| Like=-0.38..-0.01 [-0.3806..-0.3792]\| it/evals=2050/20727 eff=10.0851% N=400 Have 2 modes Volume: ~exp(-9.49) * Expected Volume: exp(-5.18) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0\| +0.2 222222222 111111111 +0.8 \| +1.0 param1: +0.0\| +0.2 222222222 111111111 +0.8 \| +1.0 param2: +0.0\| +0.2 222222222 111111111 +0.8 \| +1.0 Z=-3.6(85.76%) \| Like=-0.37..-0.01 [-0.3668..-0.3667]\| it/evals=2070/20962 eff=10.0671% N=400 Z=-3.6(86.65%) \| Like=-0.35..-0.01 [-0.3478..-0.3475]\| it/evals=2100/21332 eff=10.0325% N=400 Z=-3.6(87.79%) \| Like=-0.32..-0.01 [-0.3213..-0.3203]\| it/evals=2141/21863 eff=9.9753% N=400 Z=-3.6(88.02%) \| Like=-0.32..-0.01 [-0.3164..-0.3163]\| it/evals=2150/21966 eff=9.9694% N=400 Have 2 modes Volume: ~exp(-9.70) * Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| +0.2 22222222 111111111 +0.8 \| +1.0 param1: +0.0\| +0.2 222222222 111111111 +0.8 \| +1.0 param2: +0.0\| +0.2 222222222 111111111 +0.8 \| +1.0 Z=-3.6(88.30%) \| Like=-0.31..-0.01 [-0.3081..-0.3068]\| it/evals=2160/22098 eff=9.9548% N=400 Z=-3.6(89.27%) \| Like=-0.29..-0.01 [-0.2898..-0.2893]\| it/evals=2200/22587 eff=9.9157% N=400 Z=-3.5(90.28%) \| Like=-0.27..-0.01 [-0.2696..-0.2682]\| it/evals=2244/23145 eff=9.8659% N=400 Have 2 modes Volume: ~exp(-9.86) Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| +0.2 22222222 1111111 +0.8 \| +1.0 param1: +0.0\| +0.2 22222222 1111111 +0.8 \| +1.0 param2: +0.0\| +0.2 2222222 111111111 +0.8 \| +1.0 Z=-3.5(90.42%) \| Like=-0.27..-0.01 [-0.2664..-0.2661]\| it/evals=2250/23226 eff=9.8572% N=400 Z=-3.5(91.32%) \| Like=-0.25..-0.00 [-0.2470..-0.2465]\| it/evals=2294/23791 eff=9.8072% N=400 Z=-3.5(91.44%) \| Like=-0.24..-0.00 [-0.2450..-0.2449]\| it/evals=2300/23866 eff=9.8014% N=400 Have 2 modes Volume: ~exp(-10.15) Expected Volume: exp(-5.85) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| +0.2 22222222 1111111 +0.8 \| +1.0 param1: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 param2: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 Z=-3.5(92.18%) \| Like=-0.23..-0.00 [-0.2282..-0.2277]\| it/evals=2340/24371 eff=9.7618% N=400 Z=-3.5(92.35%) \| Like=-0.22..-0.00 [-0.2239..-0.2232]\| it/evals=2350/24502 eff=9.7502% N=400 Z=-3.5(93.18%) \| Like=-0.21..-0.00 [-0.2063..-0.2063]\| it/evals=2400/25122 eff=9.7080% N=400 Have 2 modes Volume: ~exp(-10.37) Expected Volume: exp(-6.08) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 param1: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 param2: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 Z=-3.5(93.63%) \| Like=-0.20..-0.00 [-0.2018..-0.2009]\| it/evals=2430/25495 eff=9.6832% N=400 Z=-3.5(93.91%) \| Like=-0.19..-0.00 [-0.1945..-0.1935]\| it/evals=2450/25764 eff=9.6594% N=400 Z=-3.5(94.58%) \| Like=-0.18..-0.00 [-0.1771..-0.1769]\| it/evals=2500/26395 eff=9.6172% N=400 Have 2 modes Volume: ~exp(-10.61) Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.2 222222 111111 +0.8 \| +1.0 param1: +0.0\| +0.2 2222222 1111111 +0.8 \| +1.0 param2: +0.0\| +0.2 222222 1111111 +0.7 \| +1.0 Z=-3.5(94.83%) \| Like=-0.17..-0.00 [-0.1710..-0.1709]\| it/evals=2520/26644 eff=9.6022% N=400 Z=-3.5(95.18%) \| Like=-0.16..-0.00 [-0.1632..-0.1631]\| it/evals=2550/27018 eff=9.5800% N=400 Z=-3.5(95.71%) \| Like=-0.15..-0.00 [-0.1470..-0.1469]\| it/evals=2600/27635 eff=9.5465% N=400 Have 2 modes Volume: ~exp(-10.71) Expected Volume: exp(-6.53) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| +0.3 222222 111111 +0.8 \| +1.0 param1: +0.0\| +0.3 2222222 1111111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 111111 +0.7 \| +1.0 Z=-3.5(95.81%) \| Like=-0.15..-0.00 [-0.1456..-0.1455]\| it/evals=2610/27762 eff=9.5388% N=400 Z=-3.5(96.18%) \| Like=-0.14..-0.00 [-0.1366..-0.1366]\| it/evals=2650/28264 eff=9.5105% N=400 Z=-3.5(96.54%) \| Like=-0.13..-0.00 [-0.1262..-0.1259]\| it/evals=2692/28803 eff=9.4779% N=400 Have 2 modes Volume: ~exp(-11.00) Expected Volume: exp(-6.75) Quality: ok positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0\| +0.3 222222 111111 +0.7 \| +1.0 param1: +0.0\| +0.3 222222 11111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 111111 +0.7 \| +1.0 Z=-3.5(96.61%) \| Like=-0.12..-0.00 [-0.1246..-0.1245]\| it/evals=2700/28902 eff=9.4730% N=400 Z=-3.5(96.94%) \| Like=-0.12..-0.00 [-0.1188..-0.1188]\| it/evals=2743/29431 eff=9.4485% N=400 Z=-3.5(96.99%) \| Like=-0.12..-0.00 [-0.1164..-0.1162]\| it/evals=2750/29514 eff=9.4456% N=400 Have 2 modes Volume: ~exp(-11.11) Expected Volume: exp(-6.98) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param1: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 Z=-3.5(97.27%) \| Like=-0.11..-0.00 [-0.1081..-0.1080]\| it/evals=2790/30016 eff=9.4206% N=400 Z=-3.5(97.33%) \| Like=-0.11..-0.00 [-0.1060..-0.1056]\| it/evals=2800/30134 eff=9.4168% N=400 Z=-3.5(97.63%) \| Like=-0.10..-0.00 [-0.0983..-0.0980]\| it/evals=2850/30769 eff=9.3846% N=400 Have 2 modes Volume: ~exp(-11.79) Expected Volume: exp(-7.20) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param1: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 Z=-3.5(97.80%) \| Like=-0.09..-0.00 [-0.0931..-0.0929]\| it/evals=2880/31161 eff=9.3625% N=400 Z=-3.5(97.90%) \| Like=-0.09..-0.00 [-0.0895..-0.0894]\| it/evals=2900/31412 eff=9.3512% N=400 Z=-3.5(98.14%) \| Like=-0.08..-0.00 [-0.0833..-0.0833]\| it/evals=2950/32044 eff=9.3225% N=400 Have 2 modes Volume: ~exp(-11.83) Expected Volume: exp(-7.43) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0\| +0.3 2222 11111 +0.7 \| +1.0 param1: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 Z=-3.5(98.23%) \| Like=-0.08..-0.00 [-0.0814..-0.0812]\| it/evals=2970/32295 eff=9.3118% N=400 Z=-3.5(98.35%) \| Like=-0.08..-0.00 [-0.0774..-0.0773]\| it/evals=3000/32698 eff=9.2885% N=400 Z=-3.5(98.54%) \| Like=-0.07..-0.00 [-0.0704..-0.0704]\| it/evals=3050/33312 eff=9.2671% N=400 Have 2 modes Volume: ~exp(-12.21) Expected Volume: exp(-7.65) Quality: ok positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0\| +0.3 2222 11111 +0.7 \| +1.0 param1: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 Z=-3.5(98.58%) \| Like=-0.07..-0.00 [-0.0699..-0.0694]\| it/evals=3060/33442 eff=9.2609% N=400 Z=-3.5(98.71%) \| Like=-0.07..-0.00 [-0.0654..-0.0653]\| it/evals=3100/33942 eff=9.2421% N=400 Have 2 modes Volume: ~exp(-12.21) Expected Volume: exp(-7.88) Quality: ok positive degeneracy between param2 and param0: rho=0.76 param0: +0.0\| +0.3 2222 11111 +0.7 \| +1.0 param1: +0.0\| +0.3 2222 1111 +0.7 \| +1.0 param2: +0.0\| +0.3 22222 11111 +0.7 \| +1.0 Z=-3.5(98.86%) \| Like=-0.06..-0.00 [-0.0608..-0.0608]\| it/evals=3150/34571 eff=9.2183% N=400 Z=-3.5(98.99%) \| Like=-0.06..-0.00 [-0.0557..-0.0557]\| it/evals=3200/35201 eff=9.1951% N=400 [ultranest] Explored until L=-0.001 [ultranest] Likelihood function evaluations: 35252 [ultranest] logZ = -3.422 +- 0.04953 [ultranest] Effective samples strategy satisfied (ESS = 1897.8, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.440 +- 0.141 single instance: logZ = -3.440 +- 0.070 bootstrapped : logZ = -3.422 +- 0.141 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▂▂▃▄▅▇▆▇▆▇▆▅▃▃▃▂▃▃▃▅▅▆▆▇▇▅▄▃▃▂▂▁▁▁▁│1.00 0.50 +- 0.22 param1 : 0.00 │▁▁▁▁▂▂▂▃▅▆▆▆▇▇▅▅▃▃▂▃▃▃▃▅▆▆▆▆▆▅▅▄▃▂▂▁▁▁▁│1.00 0.50 +- 0.22 param2 : 0.00 │▁▁▁▁▂▂▃▄▆▆▇▇▇▇▅▅▄▃▂▃▃▂▃▆▆▆▆▇▆▇▅▄▅▃▁▁▁▁▁│1.00 0.50 +- 0.22 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=403, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.54, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=625, regioncalls=0, ndraw=40, logz=-23.75, remainder_fraction=100.0000%, Lmin=-19.64, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=815, regioncalls=0, ndraw=40, logz=-19.86, remainder_fraction=100.0000%, Lmin=-16.25, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=859, regioncalls=0, ndraw=40, logz=-19.04, remainder_fraction=100.0000%, Lmin=-15.25, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1114, regioncalls=0, ndraw=40, logz=-15.36, remainder_fraction=99.9993%, Lmin=-11.94, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=193, ncalls=1325, regioncalls=0, ndraw=40, logz=-13.38, remainder_fraction=99.9949%, Lmin=-10.09, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1355, regioncalls=0, ndraw=40, logz=-13.12, remainder_fraction=99.9934%, Lmin=-9.90, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1615, regioncalls=0, ndraw=40, logz=-11.65, remainder_fraction=99.9720%, Lmin=-8.71, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1733, regioncalls=0, ndraw=40, logz=-11.17, remainder_fraction=99.9545%, Lmin=-8.28, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1921, regioncalls=0, ndraw=40, logz=-10.55, remainder_fraction=99.9136%, Lmin=-7.82, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2211, regioncalls=0, ndraw=40, logz=-9.62, remainder_fraction=99.7876%, Lmin=-6.84, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2267, regioncalls=0, ndraw=40, logz=-9.45, remainder_fraction=99.7447%, Lmin=-6.58, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=2529, regioncalls=0, ndraw=40, logz=-8.83, remainder_fraction=99.5209%, Lmin=-6.11, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=2853, regioncalls=0, ndraw=40, logz=-8.20, remainder_fraction=99.1042%, Lmin=-5.54, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3213, regioncalls=0, ndraw=40, logz=-7.67, remainder_fraction=98.4983%, Lmin=-5.11, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=3522, regioncalls=0, ndraw=40, logz=-7.33, remainder_fraction=97.8854%, Lmin=-4.85, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3583, regioncalls=0, ndraw=40, logz=-7.26, remainder_fraction=97.7533%, Lmin=-4.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=3990, regioncalls=0, ndraw=40, logz=-6.90, remainder_fraction=96.7382%, Lmin=-4.37, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=4220, regioncalls=0, ndraw=40, logz=-6.70, remainder_fraction=95.9898%, Lmin=-4.16, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=4402, regioncalls=0, ndraw=40, logz=-6.58, remainder_fraction=95.4063%, Lmin=-4.07, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=4842, regioncalls=0, ndraw=40, logz=-6.29, remainder_fraction=93.9898%, Lmin=-3.73, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5010, regioncalls=0, ndraw=40, logz=-6.18, remainder_fraction=93.1566%, Lmin=-3.61, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=5259, regioncalls=0, ndraw=40, logz=-6.02, remainder_fraction=92.0791%, Lmin=-3.44, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=5704, regioncalls=0, ndraw=40, logz=-5.78, remainder_fraction=90.1682%, Lmin=-3.16, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=5789, regioncalls=0, ndraw=40, logz=-5.73, remainder_fraction=89.5817%, Lmin=-3.09, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=6154, regioncalls=0, ndraw=40, logz=-5.55, remainder_fraction=87.4943%, Lmin=-2.84, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=6627, regioncalls=0, ndraw=40, logz=-5.34, remainder_fraction=84.7952%, Lmin=-2.66, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=7162, regioncalls=0, ndraw=40, logz=-5.16, remainder_fraction=82.0757%, Lmin=-2.46, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=7589, regioncalls=0, ndraw=40, logz=-5.02, remainder_fraction=79.5328%, Lmin=-2.26, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=7701, regioncalls=0, ndraw=40, logz=-4.99, remainder_fraction=78.9966%, Lmin=-2.23, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=8276, regioncalls=0, ndraw=40, logz=-4.84, remainder_fraction=75.7192%, Lmin=-2.09, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=8869, regioncalls=0, ndraw=40, logz=-4.70, remainder_fraction=72.1659%, Lmin=-1.91, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=9487, regioncalls=0, ndraw=40, logz=-4.58, remainder_fraction=68.1617%, Lmin=-1.80, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=9717, regioncalls=0, ndraw=40, logz=-4.54, remainder_fraction=66.5956%, Lmin=-1.73, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=10066, regioncalls=0, ndraw=40, logz=-4.47, remainder_fraction=64.3746%, Lmin=-1.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=10690, regioncalls=0, ndraw=40, logz=-4.37, remainder_fraction=60.6010%, Lmin=-1.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=10813, regioncalls=0, ndraw=40, logz=-4.35, remainder_fraction=59.8144%, Lmin=-1.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=11308, regioncalls=0, ndraw=40, logz=-4.28, remainder_fraction=56.8509%, Lmin=-1.41, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=11939, regioncalls=0, ndraw=40, logz=-4.20, remainder_fraction=53.0365%, Lmin=-1.30, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=12583, regioncalls=0, ndraw=40, logz=-4.12, remainder_fraction=49.4982%, Lmin=-1.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=13202, regioncalls=0, ndraw=40, logz=-4.06, remainder_fraction=45.7130%, Lmin=-1.09, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1496, ncalls=13754, regioncalls=0, ndraw=40, logz=-4.00, remainder_fraction=42.6833%, Lmin=-1.00, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=13802, regioncalls=0, ndraw=40, logz=-4.00, remainder_fraction=42.3781%, Lmin=-0.99, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=14187, regioncalls=0, ndraw=40, logz=-3.96, remainder_fraction=40.3075%, Lmin=-0.94, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=14429, regioncalls=0, ndraw=40, logz=-3.94, remainder_fraction=39.0084%, Lmin=-0.91, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=15075, regioncalls=0, ndraw=40, logz=-3.89, remainder_fraction=35.8639%, Lmin=-0.81, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=15330, regioncalls=0, ndraw=40, logz=-3.87, remainder_fraction=34.6938%, Lmin=-0.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=15708, regioncalls=0, ndraw=40, logz=-3.84, remainder_fraction=32.8654%, Lmin=-0.74, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=16343, regioncalls=0, ndraw=40, logz=-3.80, remainder_fraction=30.0146%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=16469, regioncalls=0, ndraw=40, logz=-3.79, remainder_fraction=29.5022%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=16966, regioncalls=0, ndraw=40, logz=-3.76, remainder_fraction=27.2999%, Lmin=-0.63, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=17586, regioncalls=0, ndraw=40, logz=-3.73, remainder_fraction=24.7207%, Lmin=-0.58, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1844, ncalls=18126, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=22.6833%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=18198, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=22.4346%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1891, ncalls=18731, regioncalls=0, ndraw=40, logz=-3.67, remainder_fraction=20.6470%, Lmin=-0.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=18845, regioncalls=0, ndraw=40, logz=-3.67, remainder_fraction=20.2546%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=19462, regioncalls=0, ndraw=40, logz=-3.64, remainder_fraction=18.2996%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=19839, regioncalls=0, ndraw=40, logz=-3.63, remainder_fraction=17.1788%, Lmin=-0.42, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=20095, regioncalls=0, ndraw=40, logz=-3.62, remainder_fraction=16.4663%, Lmin=-0.41, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2047, ncalls=20694, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=14.9385%, Lmin=-0.38, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=20727, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=14.8478%, Lmin=-0.38, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=20962, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=14.2401%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=21332, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=13.3453%, Lmin=-0.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2141, ncalls=21863, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=12.2126%, Lmin=-0.32, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=21966, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=11.9752%, Lmin=-0.32, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=22098, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=11.7028%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=22587, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=10.7251%, Lmin=-0.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2244, ncalls=23145, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=9.7166%, Lmin=-0.27, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=23226, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=9.5834%, Lmin=-0.27, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2294, ncalls=23791, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=8.6819%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=23866, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=8.5645%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=24371, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=7.8193%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=24502, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=7.6509%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=25122, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=6.8163%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=25495, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=6.3662%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=25764, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=6.0859%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=26395, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=5.4178%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=26644, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=5.1745%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=27018, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=4.8242%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=27635, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=4.2939%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=27762, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=4.1950%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=28264, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=3.8177%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2692, ncalls=28803, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=3.4558%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=28902, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=3.3910%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2743, ncalls=29431, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=3.0573%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=29514, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=3.0069%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=30016, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=2.7336%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=30134, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=2.6690%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=30769, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=2.3674%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=31161, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=2.2025%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=31412, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=2.0995%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=32044, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=1.8608%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=32295, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=1.7723%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=32698, regioncalls=0, ndraw=40, logz=-3.46, remainder_fraction=1.6481%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=33312, regioncalls=0, ndraw=40, logz=-3.45, remainder_fraction=1.4594%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=33442, regioncalls=0, ndraw=40, logz=-3.45, remainder_fraction=1.4240%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=33942, regioncalls=0, ndraw=40, logz=-3.45, remainder_fraction=1.2916%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=34571, regioncalls=0, ndraw=40, logz=-3.45, remainder_fraction=1.1434%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=35201, regioncalls=0, ndraw=40, logz=-3.45, remainder_fraction=1.0118%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.001 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 35252 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.422 +- 0.04953 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1897.8, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_samplingpath.py::test_samplingpath	0.00
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_samplingpath.py::test_samplingpath_cubereflect	0.00
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_samplingpath.py::test_samplingpath_oddcase	0.00
[gw5] linux -- Python 3.10.6 /usr/bin/python3 [gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3
Passed	tests/test_stepsampling.py::test_stepsampler_regionmh	9.61
[gw1] linux -- Python 3.10.6 /usr/bin/python3 [gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.13) * Expected Volume: exp(0.00) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-inf(0.00%) \| Like=-28.44..-0.20 [-28.4416..-8.9505] \| it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.61051). shrinking... ineffective proposal scale (1.62335). shrinking... ineffective proposal scale (1.64935). shrinking... ineffective proposal scale (1.52341). shrinking... ineffective proposal scale (1.29966). shrinking... ineffective proposal scale (1.29966). shrinking... ineffective proposal scale (1.84333). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.57259). shrinking... ineffective proposal scale (1.99571). shrinking... ineffective proposal scale (1.84333). shrinking... ineffective proposal scale (1.70259). shrinking... Z=-25.5(0.00%) \| Like=-21.46..-0.20 [-28.4416..-8.9505] \| it/evals=36/844 eff=8.1081% N=400 ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.85803). shrinking... ineffective proposal scale (1.87285). shrinking... ineffective proposal scale (1.72985). shrinking... ineffective proposal scale (1.59777). shrinking... ineffective proposal scale (1.47577). shrinking... ineffective proposal scale (1.3631). shrinking... ineffective proposal scale (1.25902). shrinking... ineffective proposal scale (1.17216). shrinking... Z=-24.0(0.00%) \| Like=-20.02..-0.20 [-28.4416..-8.9505] \| it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (1.53556). shrinking... ineffective proposal scale (1.44103). shrinking... ineffective proposal scale (1.57259). shrinking... ineffective proposal scale (1.58513). shrinking... ineffective proposal scale (1.35231). shrinking... ineffective proposal scale (1.61051). shrinking... ineffective proposal scale (1.62335). shrinking... ineffective proposal scale (1.4994). shrinking... ineffective proposal scale (1.77156). shrinking... ineffective proposal scale (1.78569). shrinking... ineffective proposal scale (1.82875). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.71616). shrinking... ineffective proposal scale (1.59777). shrinking... ineffective proposal scale (1.27918). shrinking... Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.23) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|***********************************************\| +1.000 Z=-20.2(0.00%) \| Like=-16.40..-0.20 [-28.4416..-8.9505] \| it/evals=90/1492 eff=8.2418% N=400 ineffective proposal scale (1.41832). shrinking... Z=-19.5(0.00%) \| Like=-15.84..-0.20 [-28.4416..-8.9505] \| it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (1.22937). shrinking... ineffective proposal scale (0.923647). shrinking... Z=-17.0(0.00%) \| Like=-13.62..-0.20 [-28.4416..-8.9505] \| it/evals=141/2104 eff=8.2746% N=400 ineffective proposal scale (0.880663). shrinking... Z=-16.5(0.00%) \| Like=-12.89..-0.20 [-28.4416..-8.9505] \| it/evals=150/2212 eff=8.2781% N=400 ineffective proposal scale (0.819908). shrinking... ineffective proposal scale (0.448344). shrinking... Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.45) Quality: ok param0: +0.000\|***********************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|***********************************************\| +1.000 Z=-14.7(0.00%) \| Like=-11.19..-0.20 [-28.4416..-8.9505] \| it/evals=180/2572 eff=8.2873% N=400 Z=-13.8(0.00%) \| Like=-10.66..-0.20 [-28.4416..-8.9505] \| it/evals=200/2812 eff=8.2919% N=400 Z=-12.6(0.01%) \| Like=-9.61..-0.20 [-28.4416..-8.9505] \| it/evals=242/3316 eff=8.2990% N=400 Z=-12.4(0.01%) \| Like=-9.44..-0.20 [-28.4416..-8.9505] \| it/evals=250/3412 eff=8.3001% N=400 Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.67) Quality: ok param0: +0.00\|***********************************************\| +1.00 param1: +0.000\|********************************************** \| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-11.6(0.03%) \| Like=-8.73..-0.20 [-8.9485..-4.8498] \| it/evals=282/3797 eff=8.3014% N=400 Z=-11.2(0.04%) \| Like=-8.20..-0.20 [-8.9485..-4.8498] \| it/evals=300/4013 eff=8.3033% N=400 Z=-10.2(0.12%) \| Like=-7.29..-0.17 [-8.9485..-4.8498] \| it/evals=344/4542 eff=8.3052% N=400 Z=-10.1(0.14%) \| Like=-7.23..-0.17 [-8.9485..-4.8498] \| it/evals=350/4614 eff=8.3056% N=400 Mono-modal Volume: ~exp(-4.70) Expected Volume: exp(-0.90) Quality: ok param0: +0.00\|********************************************** \| +1.00 param1: +0.000\|************************************************ \| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-9.9(0.16%) \| Like=-7.11..-0.17 [-8.9485..-4.8498] \| it/evals=360/4734 eff=8.3064% N=400 Z=-9.3(0.29%) \| Like=-6.72..-0.17 [-8.9485..-4.8498] \| it/evals=400/5214 eff=8.3091% N=400 Z=-8.7(0.54%) \| Like=-6.06..-0.17 [-8.9485..-4.8498] \| it/evals=449/5802 eff=8.3117% N=400 Mono-modal Volume: ~exp(-5.10) Expected Volume: exp(-1.12) Quality: ok param0: +0.000\|************************************************ \| +1.000 param1: +0.000\|********************************************** \| +1.000 param2: +0.000\|*********************************************** \| +1.000 Z=-8.7(0.55%) \| Like=-6.05..-0.17 [-8.9485..-4.8498] \| it/evals=450/5814 eff=8.3118% N=400 Z=-8.2(0.92%) \| Like=-5.44..-0.10 [-8.9485..-4.8498] \| it/evals=498/6390 eff=8.3139% N=400 Z=-8.1(0.95%) \| Like=-5.43..-0.10 [-8.9485..-4.8498] \| it/evals=500/6414 eff=8.3139% N=400 Mono-modal Volume: ~exp(-5.49) * Expected Volume: exp(-1.35) Quality: ok param0: +0.000\|******************************************* \| +1.000 param1: +0.000\|********************************************** \| +1.000 param2: +0.000\|********************************************* \| +1.000 Z=-7.7(1.45%) \| Like=-4.92..-0.10 [-8.9485..-4.8498] \| it/evals=540/6894 eff=8.3154% N=400 Z=-7.6(1.61%) \| Like=-4.85..-0.10 [-4.8456..-3.4991] \| it/evals=550/7014 eff=8.3157% N=400 Z=-7.1(2.65%) \| Like=-4.40..-0.10 [-4.8456..-3.4991] \| it/evals=600/7614 eff=8.3172% N=400 Mono-modal Volume: ~exp(-5.49) Expected Volume: exp(-1.57) Quality: ok param0: +0.00\| **************************************** \| +1.00 param1: +0.00\| ********************************************* * \| +1.00 param2: +0.00\| *********************************************** \| +1.00 Z=-6.8(3.83%) \| Like=-4.13..-0.10 [-4.8456..-3.4991] \| it/evals=644/8142 eff=8.3183% N=400 Z=-6.8(3.98%) \| Like=-4.11..-0.10 [-4.8456..-3.4991] \| it/evals=650/8214 eff=8.3184% N=400 Z=-6.4(5.33%) \| Like=-3.80..-0.08 [-4.8456..-3.4991] \| it/evals=700/8814 eff=8.3195% N=400 Mono-modal Volume: ~exp(-5.51) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00\| ******************************************** \| +1.00 param1: +0.00\| ***************************************** \| +1.00 param2: +0.00\| ********************************************* \| +1.00 Z=-6.3(6.08%) \| Like=-3.63..-0.08 [-4.8456..-3.4991] \| it/evals=720/9054 eff=8.3199% N=400 Z=-6.1(7.27%) \| Like=-3.45..-0.08 [-3.4967..-3.1168] \| it/evals=750/9414 eff=8.3204% N=400 Z=-5.9(9.45%) \| Like=-3.22..-0.02 [-3.4967..-3.1168] \| it/evals=800/10015 eff=8.3203% N=400 Mono-modal Volume: ~exp(-5.89) * Expected Volume: exp(-2.02) Quality: ok param0: +0.00\| ******************************************* \| +1.00 param1: +0.00\| ***************************************** \| +1.00 param2: +0.00\| ******************************************* \| +1.00 Z=-5.8(9.89%) \| Like=-3.15..-0.02 [-3.4967..-3.1168] \| it/evals=810/10135 eff=8.3205% N=400 Z=-5.6(11.78%) \| Like=-2.99..-0.02 [-3.1085..-2.9617] \| it/evals=850/10615 eff=8.3211% N=400 Mono-modal Volume: ~exp(-6.00) * Expected Volume: exp(-2.25) Quality: ok positive degeneracy between param2 and param1: rho=0.75 param0: +0.00\| **************************************** \| +1.00 param1: +0.00\| *************************************** \| +1.00 param2: +0.00\| ***************************************** \| +1.00 Z=-5.4(14.48%) \| Like=-2.74..-0.02 [-2.7355..-2.7280]\| it/evals=900/11215 eff=8.3218% N=400 Z=-5.3(17.63%) \| Like=-2.50..-0.02 [-2.4997..-2.4984]\| it/evals=950/11815 eff=8.3224% N=400 Have 2 modes Volume: ~exp(-6.24) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00\| 11111111111111111111 222222222222222222222 \| +1.00 param1: +0.00\| 1111111111111111111112222222222222222222222 \| +1.00 param2: +0.00\| 111111111111111111111222222222222222222222 \| +1.00 Z=-5.1(20.12%) \| Like=-2.36..-0.02 [-2.3603..-2.3592]\| it/evals=990/12295 eff=8.3228% N=400 Z=-5.1(20.62%) \| Like=-2.33..-0.02 [-2.3273..-2.3250]\| it/evals=1000/12415 eff=8.3229% N=400 Z=-4.9(23.80%) \| Like=-2.15..-0.02 [-2.1541..-2.1518]\| it/evals=1050/13015 eff=8.3234% N=400 Have 2 modes Volume: ~exp(-6.64) Expected Volume: exp(-2.70) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0\| 1111111111111111111 222222222222222222222 \| +1.0 param1: +0.0\| 11111111111111111111222222222222222222222 \| +1.0 param2: +0.0\| 11111111111111111111 2222222222222222222 \| +1.0 Z=-4.8(25.85%) \| Like=-2.07..-0.02 [-2.0652..-2.0598]\| it/evals=1080/13375 eff=8.3237% N=400 Z=-4.8(27.24%) \| Like=-1.98..-0.02 [-1.9844..-1.9809]\| it/evals=1100/13615 eff=8.3239% N=400 Z=-4.7(30.95%) \| Like=-1.83..-0.02 [-1.8261..-1.8197]\| it/evals=1150/14216 eff=8.3237% N=400 Have 2 modes Volume: ~exp(-6.64) Expected Volume: exp(-2.92) Quality: ok param0: +0.0\| 1111111111111111110 22222222222222222222 \| +1.0 param1: +0.0\| 11111111111111111111 22222222222222222222 \| +1.0 param2: +0.0\| 1111111111111111111 2222222222222222222 \| +1.0 Z=-4.6(33.67%) \| Like=-1.72..-0.02 [-1.7225..-1.7194]\| it/evals=1194/14745 eff=8.3235% N=400 Z=-4.6(34.10%) \| Like=-1.71..-0.02 [-1.7055..-1.7016]\| it/evals=1200/14817 eff=8.3235% N=400 Z=-4.4(38.12%) \| Like=-1.56..-0.02 [-1.5623..-1.5579]\| it/evals=1250/15418 eff=8.3233% N=400 Have 2 modes Volume: ~exp(-7.07) * Expected Volume: exp(-3.15) Quality: ok param0: +0.0\| 111111111111111111 222222222222222222 \| +1.0 param1: +0.0\| 111111111111111111 222222222222222222 \| +1.0 param2: +0.0\| 111111111111111111 222222222222222222 \| +1.0 Z=-4.4(38.86%) \| Like=-1.54..-0.02 [-1.5369..-1.5335]\| it/evals=1260/15538 eff=8.3234% N=400 Z=-4.4(41.57%) \| Like=-1.45..-0.02 [-1.4458..-1.4450]\| it/evals=1300/16018 eff=8.3237% N=400 Z=-4.3(45.13%) \| Like=-1.32..-0.02 [-1.3215..-1.3211]\| it/evals=1349/16606 eff=8.3241% N=400 Have 2 modes Volume: ~exp(-7.39) Expected Volume: exp(-3.37) Quality: ok param0: +0.0\| 11111111111111111 222222222222222 \| +1.0 param1: +0.0\| 1111111111111111 2222222222222222 \| +1.0 param2: +0.0\| 1111111111111111 222222222222222 \| +1.0 Z=-4.3(45.20%) \| Like=-1.32..-0.02 [-1.3211..-1.3210]\| it/evals=1350/16618 eff=8.3241% N=400 Z=-4.2(48.86%) \| Like=-1.24..-0.02 [-1.2432..-1.2362]\| it/evals=1399/17206 eff=8.3244% N=400 Z=-4.2(48.91%) \| Like=-1.24..-0.02 [-1.2362..-1.2340]\| it/evals=1400/17218 eff=8.3244% N=400 Have 2 modes Volume: ~exp(-7.39) Expected Volume: exp(-3.60) Quality: ok param0: +0.0\| 1111111111111111 222222222222222 \| +1.0 param1: +0.0\| 111111111111111 222222222222222 \| +1.0 param2: +0.0\| 111111111111111 22222222222222 \| +1.0 Z=-4.1(51.81%) \| Like=-1.14..-0.01 [-1.1366..-1.1351]\| it/evals=1440/17698 eff=8.3247% N=400 Z=-4.1(52.50%) \| Like=-1.13..-0.01 [-1.1261..-1.1256]\| it/evals=1450/17818 eff=8.3247% N=400 Z=-4.1(55.27%) \| Like=-1.05..-0.01 [-1.0456..-1.0449]\| it/evals=1494/18347 eff=8.3245% N=400 Z=-4.1(55.74%) \| Like=-1.04..-0.01 [-1.0390..-1.0388]\| it/evals=1500/18419 eff=8.3245% N=400 Have 2 modes Volume: ~exp(-7.84) Expected Volume: exp(-3.82) Quality: ok param0: +0.0\| 111111111111111 222222222222222 \| +1.0 param1: +0.0\| 11111111111111 22222222222222 \| +1.0 param2: +0.0\| 11111111111111 22222222222222 \| +1.0 Z=-4.0(57.85%) \| Like=-0.99..-0.01 [-0.9895..-0.9878]\| it/evals=1530/18779 eff=8.3247% N=400 Z=-4.0(59.20%) \| Like=-0.96..-0.01 [-0.9563..-0.9558]\| it/evals=1550/19019 eff=8.3248% N=400 Z=-4.0(62.05%) \| Like=-0.87..-0.01 [-0.8714..-0.8694]\| it/evals=1596/19571 eff=8.3251% N=400 Z=-3.9(62.31%) \| Like=-0.86..-0.01 [-0.8642..-0.8608]\| it/evals=1600/19619 eff=8.3251% N=400 Have 2 modes Volume: ~exp(-8.48) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0\| 11111111111111 22222222222222 \| +1.0 param1: +0.0\| 111111111111 2222222222222 \| +1.0 param2: +0.0\| 1111111111111 2222222222222 \| +1.0 Z=-3.9(63.51%) \| Like=-0.83..-0.01 [-0.8293..-0.8276]\| it/evals=1620/19859 eff=8.3252% N=400 Z=-3.9(65.45%) \| Like=-0.79..-0.01 [-0.7910..-0.7892]\| it/evals=1650/20219 eff=8.3253% N=400 Z=-3.9(68.48%) \| Like=-0.72..-0.01 [-0.7167..-0.7149]\| it/evals=1700/20819 eff=8.3256% N=400 Have 2 modes Volume: ~exp(-8.48) Expected Volume: exp(-4.27) Quality: ok param0: +0.0\| 111111111111 222222222222 \| +1.0 param1: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111 022222222222 +0.8 \| +1.0 Z=-3.8(70.10%) \| Like=-0.68..-0.01 [-0.6804..-0.6798]\| it/evals=1728/21155 eff=8.3257% N=400 Z=-3.8(71.29%) \| Like=-0.65..-0.01 [-0.6492..-0.6481]\| it/evals=1750/21419 eff=8.3258% N=400 Have 2 modes Volume: ~exp(-8.68) Expected Volume: exp(-4.50) Quality: ok param0: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-3.8(73.94%) \| Like=-0.59..-0.01 [-0.5916..-0.5905]\| it/evals=1800/22019 eff=8.3260% N=400 Z=-3.8(75.92%) \| Like=-0.55..-0.01 [-0.5516..-0.5513]\| it/evals=1840/22499 eff=8.3262% N=400 Z=-3.8(76.41%) \| Like=-0.54..-0.01 [-0.5416..-0.5414]\| it/evals=1850/22619 eff=8.3262% N=400 Have 2 modes Volume: ~exp(-8.80) Expected Volume: exp(-4.73) Quality: ok param0: +0.0\| 1111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-3.7(78.20%) \| Like=-0.50..-0.01 [-0.5016..-0.4995]\| it/evals=1890/23099 eff=8.3264% N=400 Z=-3.7(78.64%) \| Like=-0.49..-0.01 [-0.4937..-0.4928]\| it/evals=1900/23219 eff=8.3264% N=400 Z=-3.7(80.50%) \| Like=-0.45..-0.01 [-0.4494..-0.4489]\| it/evals=1944/23747 eff=8.3266% N=400 Z=-3.7(80.74%) \| Like=-0.44..-0.01 [-0.4427..-0.4397]\| it/evals=1950/23819 eff=8.3266% N=400 Have 2 modes Volume: ~exp(-9.34) * Expected Volume: exp(-4.95) Quality: ok param0: +0.0\| 1111111111 2222222222 +0.8 \| +1.0 param1: +0.0\| 1111111111 222222222 +0.8 \| +1.0 param2: +0.0\| 1111111111 222222222 +0.8 \| +1.0 Z=-3.7(81.89%) \| Like=-0.42..-0.01 [-0.4196..-0.4193]\| it/evals=1980/24179 eff=8.3267% N=400 Z=-3.7(82.61%) \| Like=-0.41..-0.01 [-0.4054..-0.4050]\| it/evals=2000/24419 eff=8.3267% N=400 Z=-3.7(84.09%) \| Like=-0.38..-0.01 [-0.3774..-0.3735]\| it/evals=2042/24923 eff=8.3269% N=400 Z=-3.7(84.36%) \| Like=-0.37..-0.01 [-0.3673..-0.3672]\| it/evals=2050/25019 eff=8.3269% N=400 Have 2 modes Volume: ~exp(-9.77) * Expected Volume: exp(-5.18) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-3.6(85.01%) \| Like=-0.35..-0.01 [-0.3542..-0.3535]\| it/evals=2070/25259 eff=8.3270% N=400 Z=-3.6(85.96%) \| Like=-0.34..-0.01 [-0.3374..-0.3365]\| it/evals=2100/25619 eff=8.3271% N=400 Z=-3.6(87.42%) \| Like=-0.31..-0.01 [-0.3103..-0.3103]\| it/evals=2150/26219 eff=8.3272% N=400 Have 2 modes Volume: ~exp(-9.77) Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111110 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111110 022222220 +0.8 \| +1.0 Z=-3.6(88.20%) \| Like=-0.29..-0.01 [-0.2948..-0.2947]\| it/evals=2179/26567 eff=8.3273% N=400 Z=-3.6(88.75%) \| Like=-0.29..-0.01 [-0.2857..-0.2855]\| it/evals=2200/26819 eff=8.3273% N=400 Have 2 modes Volume: ~exp(-10.02) Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.6(89.93%) \| Like=-0.26..-0.01 [-0.2637..-0.2637]\| it/evals=2250/27419 eff=8.3275% N=400 Z=-3.6(91.01%) \| Like=-0.24..-0.01 [-0.2396..-0.2388]\| it/evals=2300/28019 eff=8.3276% N=400 Have 2 modes Volume: ~exp(-10.24) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0\| +0.2 11111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.6(91.79%) \| Like=-0.22..-0.01 [-0.2243..-0.2243]\| it/evals=2340/28499 eff=8.3277% N=400 Z=-3.6(91.98%) \| Like=-0.22..-0.01 [-0.2186..-0.2184]\| it/evals=2350/28619 eff=8.3277% N=400 Z=-3.6(92.74%) \| Like=-0.21..-0.01 [-0.2057..-0.2049]\| it/evals=2393/29135 eff=8.3278% N=400 Z=-3.6(92.85%) \| Like=-0.20..-0.01 [-0.2033..-0.2033]\| it/evals=2400/29219 eff=8.3278% N=400 Have 2 modes Volume: ~exp(-10.33) * Expected Volume: exp(-6.08) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.6(93.33%) \| Like=-0.19..-0.01 [-0.1920..-0.1919]\| it/evals=2430/29579 eff=8.3279% N=400 Z=-3.5(93.64%) \| Like=-0.18..-0.01 [-0.1837..-0.1836]\| it/evals=2450/29819 eff=8.3280% N=400 Z=-3.5(94.26%) \| Like=-0.17..-0.01 [-0.1734..-0.1731]\| it/evals=2494/30347 eff=8.3280% N=400 Z=-3.5(94.34%) \| Like=-0.17..-0.01 [-0.1726..-0.1722]\| it/evals=2500/30419 eff=8.3281% N=400 Have 2 modes Volume: ~exp(-10.75) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.3 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.7 \| +1.0 Z=-3.5(94.60%) \| Like=-0.17..-0.01 [-0.1685..-0.1685]\| it/evals=2520/30659 eff=8.3281% N=400 Z=-3.5(94.97%) \| Like=-0.16..-0.00 [-0.1610..-0.1610]\| it/evals=2550/31019 eff=8.3282% N=400 Z=-3.5(95.45%) \| Like=-0.15..-0.00 [-0.1481..-0.1480]\| it/evals=2593/31535 eff=8.3282% N=400 Z=-3.5(95.53%) \| Like=-0.15..-0.00 [-0.1465..-0.1465]\| it/evals=2600/31619 eff=8.3283% N=400 Have 2 modes Volume: ~exp(-10.75) Expected Volume: exp(-6.53) Quality: ok param0: +0.0\| +0.3 1111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 param2: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 Z=-3.5(95.80%) \| Like=-0.14..-0.00 [-0.1411..-0.1409]\| it/evals=2627/31943 eff=8.3283% N=400 Z=-3.5(96.02%) \| Like=-0.14..-0.00 [-0.1352..-0.1352]\| it/evals=2650/32219 eff=8.3284% N=400 Z=-3.5(96.46%) \| Like=-0.12..-0.00 [-0.1243..-0.1239]\| it/evals=2699/32807 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.05) Expected Volume: exp(-6.75) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 Z=-3.5(96.47%) \| Like=-0.12..-0.00 [-0.1239..-0.1239]\| it/evals=2700/32819 eff=8.3284% N=400 Z=-3.5(96.85%) \| Like=-0.12..-0.00 [-0.1161..-0.1160]\| it/evals=2749/33408 eff=8.3283% N=400 Z=-3.5(96.86%) \| Like=-0.12..-0.00 [-0.1160..-0.1157]\| it/evals=2750/33420 eff=8.3283% N=400 Z=-3.5(97.13%) \| Like=-0.11..-0.00 [-0.1111..-0.1110]\| it/evals=2788/33876 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.22) * Expected Volume: exp(-6.98) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.15%) \| Like=-0.11..-0.00 [-0.1109..-0.1106]\| it/evals=2790/33900 eff=8.3284% N=400 Z=-3.5(97.21%) \| Like=-0.11..-0.00 [-0.1090..-0.1089]\| it/evals=2800/34020 eff=8.3284% N=400 Z=-3.5(97.49%) \| Like=-0.10..-0.00 [-0.1003..-0.1001]\| it/evals=2843/34537 eff=8.3282% N=400 Z=-3.5(97.53%) \| Like=-0.10..-0.00 [-0.0989..-0.0985]\| it/evals=2850/34621 eff=8.3282% N=400 Have 2 modes Volume: ~exp(-11.71) * Expected Volume: exp(-7.20) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.70%) \| Like=-0.09..-0.00 [-0.0918..-0.0918]\| it/evals=2880/34981 eff=8.3283% N=400 Z=-3.5(97.81%) \| Like=-0.09..-0.00 [-0.0889..-0.0885]\| it/evals=2900/35221 eff=8.3283% N=400 Z=-3.5(98.03%) \| Like=-0.08..-0.00 [-0.0821..-0.0819]\| it/evals=2944/35749 eff=8.3284% N=400 Z=-3.5(98.06%) \| Like=-0.08..-0.00 [-0.0809..-0.0806]\| it/evals=2950/35821 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.71) Expected Volume: exp(-7.43) Quality: ok param0: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.21%) \| Like=-0.08..-0.00 [-0.0780..-0.0780]\| it/evals=2983/36217 eff=8.3284% N=400 Z=-3.5(98.28%) \| Like=-0.08..-0.00 [-0.0757..-0.0757]\| it/evals=3000/36421 eff=8.3285% N=400 Z=-3.5(98.47%) \| Like=-0.07..-0.00 [-0.0695..-0.0692]\| it/evals=3050/37021 eff=8.3286% N=400 Have 2 modes Volume: ~exp(-12.23) Expected Volume: exp(-7.65) Quality: ok param0: +0.0\| +0.3 1111 2222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.51%) \| Like=-0.07..-0.00 [-0.0684..-0.0682]\| it/evals=3060/37141 eff=8.3286% N=400 Z=-3.5(98.65%) \| Like=-0.06..-0.00 [-0.0642..-0.0640]\| it/evals=3100/37622 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-12.23) Expected Volume: exp(-7.88) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0\| +0.3 1111 2222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 Z=-3.5(98.80%) \| Like=-0.06..-0.00 [-0.0584..-0.0584]\| it/evals=3150/38222 eff=8.3285% N=400 Z=-3.5(98.92%) \| Like=-0.05..-0.00 [-0.0531..-0.0529]\| it/evals=3191/38714 eff=8.3285% N=400 Z=-3.5(98.94%) \| Like=-0.05..-0.00 [-0.0523..-0.0522]*\| it/evals=3200/38822 eff=8.3286% N=400 [ultranest] Explored until L=-0.001 [ultranest] Likelihood function evaluations: 39099 [ultranest] logZ = -3.483 +- 0.05779 [ultranest] Effective samples strategy satisfied (ESS = 1904.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.04 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.483 +- 0.142 single instance: logZ = -3.483 +- 0.071 bootstrapped : logZ = -3.483 +- 0.142 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▂▂▄▄▆▆▆▇▇▆▆▄▃▃▂▂▃▃▃▅▅▅▅▅▅▄▄▃▂▁▁▁▁▁▁│1.00 0.46 +- 0.22 param1 : 0.00 │▁▁▁▁▁▂▃▄▅▆▅▇▇▆▅▄▄▃▂▂▂▂▃▃▃▅▅▅▅▄▃▃▃▂▁▁▁▁▁│1.00 0.48 +- 0.22 param2 : 0.00 │▁▁▁▁▂▂▃▄▄▅▇▇▇▆▄▄▃▃▂▂▂▂▃▃▄▅▆▅▅▅▄▃▂▂▁▁▁▁ │1.00 0.47 +- 0.22 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=412, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-28.44, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=844, regioncalls=0, ndraw=128, logz=-25.48, remainder_fraction=100.0000%, Lmin=-21.46, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1012, regioncalls=0, ndraw=128, logz=-23.99, remainder_fraction=100.0000%, Lmin=-20.02, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1492, regioncalls=0, ndraw=128, logz=-20.23, remainder_fraction=100.0000%, Lmin=-16.40, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1612, regioncalls=0, ndraw=128, logz=-19.46, remainder_fraction=100.0000%, Lmin=-15.84, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=141, ncalls=2104, regioncalls=0, ndraw=128, logz=-16.95, remainder_fraction=99.9999%, Lmin=-13.62, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=2212, regioncalls=0, ndraw=128, logz=-16.51, remainder_fraction=99.9998%, Lmin=-12.89, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=2572, regioncalls=0, ndraw=128, logz=-14.74, remainder_fraction=99.9987%, Lmin=-11.19, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=2812, regioncalls=0, ndraw=128, logz=-13.79, remainder_fraction=99.9966%, Lmin=-10.66, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=242, ncalls=3316, regioncalls=0, ndraw=128, logz=-12.58, remainder_fraction=99.9887%, Lmin=-9.61, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3412, regioncalls=0, ndraw=128, logz=-12.38, remainder_fraction=99.9868%, Lmin=-9.44, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=3797, regioncalls=0, ndraw=128, logz=-11.63, remainder_fraction=99.9729%, Lmin=-8.73, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=4013, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9579%, Lmin=-8.20, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=344, ncalls=4542, regioncalls=0, ndraw=128, logz=-10.20, remainder_fraction=99.8792%, Lmin=-7.29, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=4614, regioncalls=0, ndraw=128, logz=-10.08, remainder_fraction=99.8644%, Lmin=-7.23, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=4734, regioncalls=0, ndraw=128, logz=-9.91, remainder_fraction=99.8406%, Lmin=-7.11, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5214, regioncalls=0, ndraw=128, logz=-9.32, remainder_fraction=99.7137%, Lmin=-6.72, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=449, ncalls=5802, regioncalls=0, ndraw=128, logz=-8.71, remainder_fraction=99.4554%, Lmin=-6.06, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5814, regioncalls=0, ndraw=128, logz=-8.70, remainder_fraction=99.4479%, Lmin=-6.05, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=6390, regioncalls=0, ndraw=128, logz=-8.15, remainder_fraction=99.0761%, Lmin=-5.44, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=6414, regioncalls=0, ndraw=128, logz=-8.13, remainder_fraction=99.0523%, Lmin=-5.43, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=6894, regioncalls=0, ndraw=128, logz=-7.70, remainder_fraction=98.5505%, Lmin=-4.92, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=7014, regioncalls=0, ndraw=128, logz=-7.60, remainder_fraction=98.3922%, Lmin=-4.85, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=7614, regioncalls=0, ndraw=128, logz=-7.14, remainder_fraction=97.3546%, Lmin=-4.40, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=8142, regioncalls=0, ndraw=128, logz=-6.80, remainder_fraction=96.1680%, Lmin=-4.13, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=8214, regioncalls=0, ndraw=128, logz=-6.75, remainder_fraction=96.0229%, Lmin=-4.11, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=8814, regioncalls=0, ndraw=128, logz=-6.43, remainder_fraction=94.6659%, Lmin=-3.80, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=9054, regioncalls=0, ndraw=128, logz=-6.31, remainder_fraction=93.9151%, Lmin=-3.63, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=9414, regioncalls=0, ndraw=128, logz=-6.14, remainder_fraction=92.7343%, Lmin=-3.45, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=10015, regioncalls=0, ndraw=128, logz=-5.88, remainder_fraction=90.5501%, Lmin=-3.22, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=10135, regioncalls=0, ndraw=128, logz=-5.83, remainder_fraction=90.1072%, Lmin=-3.15, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=10615, regioncalls=0, ndraw=128, logz=-5.65, remainder_fraction=88.2198%, Lmin=-2.99, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=11215, regioncalls=0, ndraw=128, logz=-5.44, remainder_fraction=85.5171%, Lmin=-2.74, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=11815, regioncalls=0, ndraw=128, logz=-5.25, remainder_fraction=82.3721%, Lmin=-2.50, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=12295, regioncalls=0, ndraw=128, logz=-5.11, remainder_fraction=79.8787%, Lmin=-2.36, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=12415, regioncalls=0, ndraw=128, logz=-5.08, remainder_fraction=79.3756%, Lmin=-2.33, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=13015, regioncalls=0, ndraw=128, logz=-4.93, remainder_fraction=76.2016%, Lmin=-2.15, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=13375, regioncalls=0, ndraw=128, logz=-4.84, remainder_fraction=74.1510%, Lmin=-2.07, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=13615, regioncalls=0, ndraw=128, logz=-4.79, remainder_fraction=72.7610%, Lmin=-1.98, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=14216, regioncalls=0, ndraw=128, logz=-4.66, remainder_fraction=69.0467%, Lmin=-1.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=14745, regioncalls=0, ndraw=128, logz=-4.56, remainder_fraction=66.3291%, Lmin=-1.72, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=14817, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=65.8998%, Lmin=-1.71, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=15418, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=61.8825%, Lmin=-1.56, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=15538, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=61.1404%, Lmin=-1.54, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=16018, regioncalls=0, ndraw=128, logz=-4.35, remainder_fraction=58.4255%, Lmin=-1.45, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1349, ncalls=16606, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=54.8657%, Lmin=-1.32, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=16618, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=54.8003%, Lmin=-1.32, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1399, ncalls=17206, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=51.1372%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=17218, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=51.0867%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=17698, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=48.1882%, Lmin=-1.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=17818, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=47.4966%, Lmin=-1.13, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=18347, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=44.7280%, Lmin=-1.05, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=18419, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=44.2614%, Lmin=-1.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=18779, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=42.1465%, Lmin=-0.99, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=19019, regioncalls=0, ndraw=128, logz=-4.00, remainder_fraction=40.8023%, Lmin=-0.96, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1596, ncalls=19571, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=37.9504%, Lmin=-0.87, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=19619, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=37.6924%, Lmin=-0.86, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=19859, regioncalls=0, ndraw=128, logz=-3.93, remainder_fraction=36.4899%, Lmin=-0.83, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=20219, regioncalls=0, ndraw=128, logz=-3.90, remainder_fraction=34.5530%, Lmin=-0.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=20819, regioncalls=0, ndraw=128, logz=-3.86, remainder_fraction=31.5163%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=21155, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=29.8994%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=21419, regioncalls=0, ndraw=128, logz=-3.82, remainder_fraction=28.7098%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=22019, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=26.0552%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=22499, regioncalls=0, ndraw=128, logz=-3.76, remainder_fraction=24.0787%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=22619, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=23.5926%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=23099, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=21.8028%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=23219, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=21.3594%, Lmin=-0.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1944, ncalls=23747, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=19.4957%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=23819, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=19.2614%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=24179, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=18.1081%, Lmin=-0.42, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=24419, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=17.3866%, Lmin=-0.41, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2042, ncalls=24923, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=15.9086%, Lmin=-0.38, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=25019, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=15.6390%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=25259, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=14.9864%, Lmin=-0.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=25619, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=14.0398%, Lmin=-0.34, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=26219, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=12.5798%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2179, ncalls=26567, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=11.8009%, Lmin=-0.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=26819, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=11.2539%, Lmin=-0.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=27419, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=10.0661%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=28019, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=8.9933%, Lmin=-0.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=28499, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=8.2103%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=28619, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=8.0236%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2393, ncalls=29135, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=7.2645%, Lmin=-0.21, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=29219, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=7.1497%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=29579, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=6.6677%, Lmin=-0.19, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=29819, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=6.3635%, Lmin=-0.18, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2494, ncalls=30347, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.7375%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=30419, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.6567%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=30659, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.3984%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=31019, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=5.0312%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2593, ncalls=31535, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.5486%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=31619, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.4748%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2627, ncalls=31943, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.1971%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=32219, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.9752%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2699, ncalls=32807, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.5427%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32819, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.5342%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2749, ncalls=33408, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=3.1458%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33420, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=3.1380%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2788, ncalls=33876, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.8669%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=33900, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.8535%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=34020, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.7862%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2843, ncalls=34537, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.5142%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34621, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.4729%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34981, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.3022%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35221, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.1933%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=35749, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.9723%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35821, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.9440%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2983, ncalls=36217, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.7946%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36421, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.7223%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37021, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.5264%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37141, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.4895%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37622, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.3513%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38222, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.1963%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3191, ncalls=38714, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.0825%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=38822, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.0589%, Lmin=-0.05, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.001 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39099 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.483 +- 0.05779 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1904.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.04 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_regionsampling.py::test_region_mean_distances	0.31
[gw9] linux -- Python 3.10.6 /usr/bin/python3 [gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ circle: 604 half-circle: 317 enlargement factor: 2.0237675941072473 0.49412788450204137 (0.872214351919518, 43685.72803024098, 50086, array([[ 5.90424248e-01, -1.28168190e-01], [ 5.68326216e-01, -7.99190323e-02], [ 5.73713827e-01, -1.40974066e-01], [-1.19565575e-01, 5.61077247e-01], [-3.96422558e-01, 6.82850299e-01], [-2.59345436e-01, -6.34084337e-01], [-9.34539440e-01, -6.90742582e-01], [-4.54118206e-02, -5.78179518e-01], [-4.02749950e-01, 6.58573234e-01], [ 8.13997364e-02, 4.94366661e-01], [-3.09850782e-01, 6.14532501e-01], [-9.99417973e-02, 5.57440104e-01], [-4.37625549e-01, -6.32032570e-01], [-7.81158726e-01, -7.00564790e-01], [ 1.75458891e-01, 4.95689547e-01], [ 1.72389906e-01, 4.68867481e-01], [-8.01773651e-01, -7.15223858e-01], [ 5.21338908e-01, -2.14590400e-01], [-1.07235208e+00, -7.36808791e-01], [ 4.73338580e-01, 2.56518765e-01], [ 5.63695919e-01, -1.86477123e-01], [-8.70841117e-01, -7.11677665e-01], [-1.82362061e-01, -5.69668582e-01], [ 1.73098757e-01, -4.92037144e-01], [-1.00384656e+00, 7.21061155e-01], [ 4.43217737e-01, 2.93713871e-01], [-4.67073777e-03, -5.54412686e-01], [-6.23929429e-02, -5.55287094e-01], [-3.44813772e-01, -6.27307923e-01], [-1.08124986e+00, 7.05926589e-01], [ 3.94361999e-01, -2.85080745e-01], [ 3.09949304e-01, 4.03277027e-01], [ 4.59621597e-01, -1.96075238e-01], [-1.52726042e-01, -5.65775188e-01], [-6.08038220e-01, 6.84700627e-01], [-9.12413897e-01, -7.18619243e-01], [ 4.86777463e-02, -4.86096498e-01], [ 2.91454928e-01, 4.23042620e-01], [ 2.31918395e-01, -4.62497450e-01], [-1.02176787e+00, -7.36473700e-01], [ 3.27742484e-01, 4.07938102e-01], [-3.10999361e-01, 6.64406143e-01], [-1.06863070e-01, 5.82251954e-01], [ 1.99001281e-01, -4.81705431e-01], [ 5.28069411e-01, 3.43009964e-02], [ 5.27707974e-01, 6.99940502e-02], [-7.79644952e-01, 6.92311241e-01], [-1.28175802e-01, -5.79235117e-01], [ 4.29640240e-01, 3.44927443e-01], [ 3.80488663e-01, -3.37014162e-01], [ 2.11391114e-01, 4.82592387e-01], [ 5.45453354e-01, -4.69543644e-02], [ 5.45493267e-01, -1.72467410e-01], [-1.11318383e-01, -5.94600729e-01], [ 7.36423960e-03, 5.66951095e-01], [ 2.99291218e-01, -3.50666656e-01], [ 7.68501828e-02, -5.19709187e-01], [ 4.77348651e-02, -5.05413071e-01], [ 2.50452451e-02, 5.39406983e-01], [-3.18730924e-01, -6.52554784e-01], [-2.39256777e-01, 6.33617282e-01], [-2.88466757e-01, -6.21474875e-01], [ 4.80469484e-01, -1.58504100e-01], [-7.81309751e-01, -6.99209221e-01], [-7.99809401e-01, -7.19966299e-01], [ 5.61260056e-01, 2.07443092e-01], [ 6.00598496e-01, 1.07023267e-01], [-8.28078470e-01, 7.00202304e-01], [-7.07008910e-01, -6.91468096e-01], [ 5.79643737e-01, -7.94768507e-02], [ 2.31601268e-01, 4.38441077e-01], [-5.88732825e-01, 6.90909274e-01], [ 3.63399194e-01, 3.49554643e-01], [-3.01868015e-01, -6.04559566e-01], [-6.72179399e-01, -6.88365529e-01], [-2.20656209e-01, 6.14106558e-01], [-3.15873900e-01, -6.34460723e-01], [-2.29395363e-02, 5.55827183e-01], [ 1.22068325e-01, -4.81068091e-01], [ 1.60053053e-01, 4.54050443e-01], [ 2.34926635e-01, 4.06907034e-01], [ 6.40572426e-02, 4.96910527e-01], [-1.07581862e+00, 7.10741072e-01], [-7.79059982e-02, 5.81010585e-01], [ 3.13990457e-01, 3.58865342e-01], [-1.06545701e+00, 7.36147059e-01], [ 1.94737500e-01, 4.59040723e-01], [ 5.10198700e-02, 5.48356580e-01], [ 5.67040396e-01, -5.71229985e-02], [-5.32353607e-01, 6.64346344e-01], [ 2.29408539e-01, 4.35118178e-01], [-4.70684001e-01, -6.53176034e-01], [-2.68907819e-01, -6.02284378e-01], [ 5.09058033e-01, -2.12102299e-01], [ 2.90072345e-01, 4.08084343e-01], [-1.12205944e+00, 7.28737094e-01], [ 6.53607804e-02, -5.28177982e-01], [ 5.28723809e-01, 1.93295404e-01], [-1.04125478e+00, -7.12877859e-01], [-4.13773799e-01, 6.76765319e-01], [-3.23951768e-01, 6.66693816e-01], [ 4.51926359e-01, -2.25259849e-01], [ 3.37355863e-01, -3.34292278e-01], [-1.72688147e-01, 6.08087321e-01], [-8.42767128e-01, -6.97224524e-01], [ 5.64114235e-01, -9.35664926e-02], [-5.17747415e-01, -6.87507349e-01], [ 2.85274291e-01, -4.18731788e-01], [ 3.73648106e-01, 3.13017175e-01], [ 5.24885792e-01, -4.80149396e-02], [ 5.74123528e-01, -1.31515348e-01], [ 5.10160640e-01, -1.86260602e-01], [-2.32128947e-01, -6.21459295e-01], [ 8.53606834e-02, -4.90521609e-01], [-1.22126323e-01, 5.71042591e-01], [ 5.61162366e-01, -4.02157071e-02], [ 5.81915438e-01, -1.33557124e-01], [ 2.54251411e-01, 4.42380525e-01], [-2.96656471e-01, 6.27301543e-01], [ 6.12618000e-01, -1.54673577e-02], [ 4.68414253e-01, 3.15996267e-01], [ 1.38443846e-01, 5.06144106e-01], [ 3.38969312e-01, -3.91504214e-01], [-7.36115829e-01, 7.00008604e-01], [ 5.58683694e-01, -6.26853177e-02], [-8.75338415e-02, -5.76960767e-01], [-3.02106731e-01, 6.39277939e-01], [-7.89936457e-01, -7.15965159e-01], [ 6.24131120e-01, 6.76807148e-02], [ 4.83833063e-01, 2.09116673e-01], [-8.76175360e-01, 7.13023744e-01], [-9.50047536e-01, 7.21264422e-01], [-9.40171485e-01, 7.21434643e-01], [ 3.61128428e-01, -3.23874595e-01], [ 5.28527861e-01, -2.07977696e-01], [ 5.91031086e-01, -8.78825272e-02], [-3.31900764e-01, 6.28744257e-01], [ 5.61592717e-01, -8.70877435e-02], [ 1.01711982e-01, -4.90711675e-01], [ 5.98208937e-01, 1.30210229e-01], [ 2.31300459e-01, 4.46747873e-01], [ 5.72396956e-01, 1.45443564e-01], [ 4.82526743e-01, -2.61214652e-01], [-4.65451960e-02, -5.51682756e-01], [-8.56937404e-02, -5.61988808e-01], [ 5.92962781e-01, 9.38652273e-02], [-9.62416037e-01, -7.23512874e-01], [ 6.20222332e-01, -5.16017176e-02], [ 4.16660129e-01, 3.52897971e-01], [ 2.41583904e-02, 5.23144069e-01], [ 6.00141659e-01, -5.75933780e-02], [ 1.56927888e-01, -5.02193794e-01], [-3.93974093e-01, -6.43049126e-01], [ 2.02410228e-01, -4.55275855e-01], [-9.70814676e-04, -5.15726743e-01], [ 4.88659015e-01, 2.92225534e-01], [-1.05525804e+00, -7.30188494e-01], [ 2.52474637e-01, -4.27979784e-01], [ 5.38151632e-01, 6.75691773e-02], [ 2.42572354e-01, -4.12351242e-01], [-1.30226587e-01, 5.75922329e-01], [ 2.11651622e-01, 4.31478420e-01], [-1.08228060e-01, -5.84436143e-01], [-6.84886675e-01, -6.85042919e-01], [-2.56262799e-01, 6.37474619e-01], [ 5.67490271e-01, 1.62710894e-01], [-3.54462948e-01, 6.46586395e-01], [-1.97719948e-01, -6.04179939e-01], [ 2.62341518e-01, 3.94453328e-01], [-6.58017071e-01, 6.83796252e-01], [ 4.15531976e-01, -2.50272400e-01], [-6.10285376e-01, -6.93448002e-01], [-1.30071704e-02, 5.25061960e-01], [ 5.59574319e-01, -1.05796261e-01], [ 5.19595457e-01, 1.24528793e-01], [-8.92188768e-01, 7.05666600e-01], [-1.11557743e-01, 5.69709296e-01], [ 2.79533678e-01, -3.70884022e-01], [ 4.34984565e-01, 3.08947351e-01], [ 3.45974468e-01, 4.12969133e-01], [ 3.13933302e-01, -3.76474657e-01], [-2.75965010e-01, -6.42767643e-01], [ 5.70043451e-01, 6.56624613e-02], [ 7.57441643e-02, -5.01435276e-01], [ 5.25428777e-01, 8.08138545e-02], [-1.01292415e+00, -7.14287399e-01], [ 5.56600088e-01, -1.38665935e-01], [-1.04322227e+00, 7.31390728e-01], [ 5.20570175e-01, -2.11254458e-01], [-1.34117300e-01, -5.84277058e-01], [ 5.63348931e-01, 1.94965923e-01], [ 5.48364164e-01, -1.09980390e-02], [-3.40410352e-01, -6.51432653e-01], [ 4.82640666e-01, -2.73811703e-01], [ 2.92085360e-01, -3.84111012e-01], [-2.97168170e-01, -6.23521430e-01], [-5.18881179e-01, 6.82609666e-01], [-2.18707800e-01, -5.92383081e-01], [ 4.87095196e-01, -1.77017544e-01], [ 4.53688054e-01, -2.82546282e-01], [ 4.31422443e-01, 2.40448711e-01], [-5.21397253e-01, 6.90676472e-01], [-4.21392816e-01, 6.47159091e-01], [-5.44044678e-01, -6.62331621e-01], [-5.07279361e-01, -6.78812897e-01], [-6.52363580e-01, 6.92848286e-01], [-1.42174039e-01, -5.67496779e-01], [ 2.44511627e-01, 4.52886989e-01], [ 6.02900576e-01, 7.79187700e-02], [ 6.19586949e-01, -3.68616455e-02], [-4.35034001e-01, 6.86075529e-01], [-6.80164001e-01, 7.14224230e-01], [-6.79619602e-01, 7.21281074e-01], [ 7.94947538e-02, 5.00351363e-01], [ 2.99037191e-01, 4.21834051e-01], [ 2.45326114e-02, 5.44212568e-01], [-2.36383526e-01, 6.10675449e-01], [ 5.87704961e-01, -1.22705612e-01], [-1.10073316e+00, 7.08902191e-01], [-1.44756302e-01, 5.85217696e-01], [-3.91285306e-01, 6.54446303e-01], [-6.13796840e-01, -6.58699733e-01], [ 5.24678767e-01, 9.66140744e-02], [ 8.40114247e-02, 4.91917261e-01], [ 3.30864872e-02, 5.16473540e-01], [ 2.46226604e-01, -4.09232238e-01], [-1.33034368e-01, -5.94658196e-01], [ 6.03624607e-01, -9.70782567e-02], [-2.47891108e-01, 6.07823792e-01], [ 4.62914363e-01, 2.64549784e-01], [-5.09349525e-01, -6.44150967e-01], [ 1.13591509e-01, -4.73745674e-01], [ 1.48362665e-01, 4.98802454e-01], [-4.05371772e-01, -6.44312188e-01], [ 4.13735449e-01, -3.22718762e-01], [ 5.86936799e-01, 5.59155101e-02], [ 3.40831098e-01, -3.24550582e-01], [-2.76232847e-01, 6.39569251e-01], [ 1.53254495e-01, 4.56171994e-01], [-3.91115920e-01, 6.81134606e-01], [-9.59210936e-01, -7.00127462e-01], [ 5.72735655e-01, -9.50147825e-02], [ 2.30824521e-01, -4.46012440e-01], [ 2.28204223e-01, -4.04798095e-01], [-7.33534876e-01, 6.87691758e-01], [ 4.54868884e-01, -2.82817284e-01], [ 5.46092204e-01, -3.54687801e-03], [ 5.71604916e-01, 1.99084806e-01], [ 4.62990471e-01, 2.71594295e-01], [ 5.19813366e-01, -7.16447092e-02], [-6.74531056e-01, -6.73661254e-01], [ 4.35519314e-01, 3.27782968e-01], [ 4.59759219e-01, -2.97495711e-01], [ 5.36479128e-01, 6.97558942e-02], [ 3.20911096e-01, -3.74970703e-01], [-6.36511978e-01, 7.08221962e-01], [-3.19237142e-01, -6.38166882e-01], [ 3.08440849e-01, -3.97843176e-01], [ 2.15161217e-01, -4.45416491e-01], [ 5.23742183e-01, -6.86027422e-02], [-1.43795898e-01, 6.03843241e-01], [ 4.17881991e-01, 3.38802795e-01], [-9.05525862e-01, -6.91147062e-01], [-9.73625579e-01, 7.37176331e-01], [-1.88283171e-01, 6.24337353e-01], [ 3.17412253e-01, 3.58107852e-01], [-3.08253490e-01, 6.55257540e-01], [ 2.74791820e-01, 4.25170087e-01], [-4.85959091e-01, -6.82191636e-01], [ 4.85531428e-01, -2.17692438e-01], [-2.61347209e-01, 6.06844450e-01], [ 4.52048239e-01, -2.65805090e-01], [ 1.92686620e-01, -4.25541620e-01], [ 5.81632240e-01, 1.05684070e-01], [ 5.44123310e-01, 1.20172110e-01], [ 5.26526195e-01, 2.06299651e-01], [-2.90002911e-01, 6.16411381e-01], [-1.27839148e-01, -5.58561629e-01], [ 3.77309343e-01, 3.88445326e-01], [-6.76423775e-01, 7.04823962e-01], [ 5.12102318e-01, 1.48736261e-01], [-5.02015320e-01, -6.58331246e-01], [ 3.27664480e-01, 4.11424738e-01], [ 1.27090010e-01, -4.72192408e-01], [ 2.01735278e-02, -5.45992810e-01], [ 4.33323589e-01, -2.75800974e-01], [-2.24522422e-01, -5.94273343e-01], [-1.12824059e+00, 7.13459556e-01], [ 1.50616445e-01, -4.67437074e-01], [ 4.74098962e-01, -1.97705703e-01], [-1.38830266e-02, -5.17257962e-01], [ 6.15599276e-01, -2.81078599e-02], [-8.49426337e-01, -6.95820872e-01], [ 9.91674042e-02, 5.28045181e-01], [-7.02400738e-01, 7.13589361e-01], [ 5.30543730e-01, 8.13631383e-02], [ 5.03460184e-01, -2.13761124e-01], [-9.50434114e-01, -7.13216797e-01], [ 2.15097760e-01, -4.14738256e-01], [-6.09043167e-01, 6.74068269e-01], [ 4.26416839e-01, 3.19455107e-01], [ 1.42980694e-01, 5.07039208e-01], [ 2.53103622e-01, 4.31004531e-01], [-7.51466786e-01, -6.98367551e-01], [ 6.06775012e-01, -5.69107304e-02], [-3.31556017e-01, 6.48084055e-01], [-7.20021723e-01, -7.05147717e-01], [ 3.42373787e-01, -3.13355433e-01], [ 5.41800018e-01, -1.43625112e-01], [ 5.92055711e-01, -1.06163740e-02], [ 5.41007418e-01, -1.62003709e-01], [ 6.11496879e-01, -9.55651797e-02], [-8.98704729e-02, -5.93749811e-01], [-5.27060656e-01, -6.66801199e-01], [-1.12398671e-01, -5.82338575e-01], [ 2.39603269e-01, 4.03478432e-01], [ 3.36486746e-01, 4.12896778e-01]]))
Passed	tests/test_run.py::test_reactive_run_resume_eggbox[csv]	2.17
[gw9] linux -- Python 3.10.6 /usr/bin/python3 [gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|***************** * * ***** * ******\| +3.1e+01 b: +0.0\| *** * *** * * * **** ********* ***\| +31.4 Z=-inf(0.00%) \| Like=1.20..233.34 [1.1994..29.4283] \| it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) \| Like=2.82..233.34 [1.1994..29.4283] \| it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) \| Like=5.72..241.87 [1.1994..29.4283] \| it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0\|***************** ******* * ****** \| +31.4 b: +0.0\| ** * * * **** ********* ***\| +31.4 Z=5.8(0.00%) \| Like=9.88..241.87 [1.1994..29.4283] \| it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) \| Like=15.15..241.87 [1.1994..29.4283] \| it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0\|********** ** ** * * * ****** \| +31.4 b: +0.0\|* * ** * * * * ******** ******\| +31.4 Z=14.8(0.00%) \| Like=19.62..241.87 [1.1994..29.4283] \| it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) \| Like=25.71..241.87 [1.1994..29.4283] \| it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0\|**** * **** ****** **** * ******\| +31.4 b: +0.0\|****** ** * * ****** ******\| +31.4 Z=25.5(0.00%) \| Like=29.64..241.87 [29.6178..62.1019] \| it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) \| Like=32.87..241.87 [29.6178..62.1019] \| it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) \| Like=35.17..241.87 [29.6178..62.1019] \| it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0\|**** * *** *** **** ****\| +31.4 b: +0.0\|****** *** * ******** * *\| +31.4 Z=34.9(0.00%) \| Like=39.71..241.87 [29.6178..62.1019] \| it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) \| Like=45.13..241.87 [29.6178..62.1019] \| it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0\| ***** * **** * * *** ******** *\| +31.4 b: +0.0\|* ** * ** ***** * *\| +31.4 Z=43.4(0.00%) \| Like=49.11..241.87 [29.6178..62.1019] \| it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) \| Like=54.54..241.87 [29.6178..62.1019] \| it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0\| * * ***** ** ******* * ******* \| +31.4 b: +0.0\|* * ** **** ***** ****** \| +31.4 Z=54.8(0.00%) \| Like=60.32..241.87 [29.6178..62.1019] \| it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) \| Like=69.11..241.87 [62.2053..112.3934] \| it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) \| Like=77.89..241.87 [62.2053..112.3934] \| it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0\| ** * **** *** ***** ***** \| +31.4 b: +0.0\| **** **** ***** * ***** \| +31.4 Z=77.8(0.00%) \| Like=87.30..241.87 [62.2053..112.3934] \| it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) \| Like=94.79..241.87 [62.2053..112.3934] \| it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0\| * * **** * **** **** \| +31.4 b: +0.0\|* ****** *** *** ** \| +31.4 Z=94.6(0.00%) \| Like=100.05..241.87 [62.2053..112.3934] \| it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 12.65 │ ▁ ▇ │19.30 18.98 +- 0.35 b : 5.3 │ ▇ ▁ │26.2 6.3 +- 1.1 626 626 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.897580582291928408e+01,3.482687211659772908e-01,1.899594672309787668e+01,1.899594672309787668e+01,1.899594672309787668e+01,6.316415107809904228e+00,1.095459745550366071e+00,6.253063034987970781e+00,6.253063034987970781e+00,6.253063034987970781e+00 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.975806 0.348269 18.995947 ... 6.253063 6.253063 6.253063 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.975805822919284 checking mean of parameter 'b': 6.316415107809904 checking stdev of parameter 'a': 0.3482687211659773 checking stdev of parameter 'b': 1.095459745550366 checking median of parameter 'a': 18.995946723097877 checking median of parameter 'b': 6.253063034987971 checking errlo of parameter 'a': 18.995946723097877 checking errlo of parameter 'b': 6.253063034987971 checking errup of parameter 'a': 18.995946723097877 checking errup of parameter 'b': 6.253063034987971 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} ====== Running Eggbox problem [2] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(0.00) Quality: ok a: +3.1e-05\|* ** ********** ******** ** * ********\| +3.1e+01 b: +3.1e-05\| ** *** ****** * ** *******\| +3.1e+01 Z=-inf(0.00%) \| Like=1.05..221.09 [1.0467..28.5121] \| it/evals=0/101 eff=0.0000% N=100 Z=0.1(0.00%) \| Like=3.95..221.09 [1.0467..28.5121] \| it/evals=10/111 eff=90.9091% N=100 Z=3.5(0.00%) \| Like=6.71..221.09 [1.0467..28.5121] \| it/evals=20/122 eff=90.9091% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.23) Quality: ok a: +3.1e-05\| **************** ******* *** * ******* \| +3.1e+01 b: +3.1e-05\|** ***** ** *** * * ** * *******\| +3.1e+01 Z=6.4(0.00%) \| Like=10.30..228.18 [1.0467..28.5121] \| it/evals=30/133 eff=90.9091% N=100 Z=10.4(0.00%) \| Like=14.59..228.18 [1.0467..28.5121] \| it/evals=40/145 eff=88.8889% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.46) Quality: ok a: +3.1e-05\| ********* ************** * ** ***\| +3.1e+01 b: +3.1e-05\| *** * ******* * * ** * *****\| +3.1e+01 Z=14.8(0.00%) \| Like=19.71..228.18 [1.0467..28.5121] \| it/evals=50/156 eff=89.2857% N=100 Z=22.2(0.00%) \| Like=26.91..228.18 [1.0467..28.5121] \| it/evals=60/174 eff=81.0811% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.69) Quality: ok a: +3.1e-05\| *** ************** ********* *\| +3.1e+01 b: +3.1e-05\| * ******* * ********* * *****\| +3.1e+01 Z=26.6(0.00%) \| Like=31.35..228.18 [29.1828..62.4284] \| it/evals=70/189 eff=78.6517% N=100 Z=29.7(0.00%) \| Like=34.32..228.18 [29.1828..62.4284] \| it/evals=80/213 eff=70.7965% N=100 Z=33.3(0.00%) \| Like=38.77..228.18 [29.1828..62.4284] \| it/evals=90/240 eff=64.2857% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-0.92) Quality: ok a: +3.1e-05\|* * ******* * ************** *********** * * *\| +3.1e+01 b: +3.1e-05\| **** *** * ******* * ********* * ***\| +3.1e+01 Z=34.5(0.00%) \| Like=39.28..228.18 [29.1828..62.4284] \| it/evals=92/246 eff=63.0137% N=100 Z=37.8(0.00%) \| Like=42.61..228.18 [29.1828..62.4284] \| it/evals=100/273 eff=57.8035% N=100 Z=42.8(0.00%) \| Like=47.95..228.18 [29.1828..62.4284] \| it/evals=110/297 eff=55.8376% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.15) Quality: ok a: +3.1e-05\| * ******* ****** * ********** * *\| +3.1e+01 b: +3.1e-05\| ****** * ********* * *** * * * *\| +3.1e+01 Z=48.9(0.00%) \| Like=54.86..228.18 [29.1828..62.4284] \| it/evals=120/326 eff=53.0973% N=100 Z=55.4(0.00%) \| Like=61.66..228.18 [29.1828..62.4284] \| it/evals=130/368 eff=48.5075% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.38) Quality: ok a: +3.1e-05\| * ******* **** * * ********* * *\| +3.1e+01 b: +3.1e-05\| ***** * ******* * * * * ***\| +3.1e+01 Z=60.1(0.00%) \| Like=68.52..228.18 [62.6017..102.3957] \| it/evals=140/402 eff=46.3576% N=100 Z=67.2(0.00%) \| Like=72.18..228.18 [62.6017..102.3957] \| it/evals=150/452 eff=42.6136% N=100 Z=71.3(0.00%) \| Like=76.78..238.35 [62.6017..102.3957] \| it/evals=160/496 eff=40.4040% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.61) Quality: ok a: +3.1e-05\| ***** *** * ******* \| +3.1e+01 b: +3.1e-05\|* ***** * * **** ***** \| +3.1e+01 Z=77.7(0.00%) \| Like=85.32..238.35 [62.6017..102.3957] \| it/evals=170/544 eff=38.2883% N=100 Z=83.6(0.00%) \| Like=91.87..238.35 [62.6017..102.3957] \| it/evals=180/573 eff=38.0550% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.84) Quality: ok a: +3.1e-05\| ** *** **** **** \| +3.1e+01 b: +3.1e-05\| *** *** ***** **** \| +3.1e+01 Z=92.1(0.00%) \| Like=98.48..238.35 [62.6017..102.3957] \| it/evals=190/595 eff=38.3838% N=100 Z=101.4(0.00%) \| Like=108.11..240.89 [102.9564..147.0741] \| it/evals=200/674 eff=34.8432% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.07) Quality: ok a: +0.0\| ** *** ***** \| +31.4 b: +3.1e-05\|* **** *** *** **** \| +3.1e+01 Z=108.2(0.00%) \| Like=114.20..240.89 [102.9564..147.0741] \| it/evals=210/722 eff=33.7621% N=100 Z=114.0(0.00%) \| Like=121.27..240.89 [102.9564..147.0741] \| it/evals=220/778 eff=32.4484% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.30) Quality: ok a: +0.0\| ** ** * *** \| +31.4 b: +3.1e-05\| * * *** ** \| +3.1e+01 Z=122.3(0.00%) \| Like=128.65..240.89 [102.9564..147.0741] \| it/evals=230/849 eff=30.7076% N=100 Z=128.0(0.00%) \| Like=134.37..240.89 [102.9564..147.0741] \| it/evals=240/950 eff=28.2353% N=100 Z=132.5(0.00%) \| Like=139.29..242.00 [102.9564..147.0741] \| it/evals=250/1034 eff=26.7666% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.53) Quality: ok a: +0.0\|* * ** * ** \| +31.4 b: +3.1e-05\| * ** *** ** \| +3.1e+01 Z=140.8(0.00%) \| Like=147.11..242.37 [147.1142..186.4200] \| it/evals=260/1135 eff=25.1208% N=100 Z=148.1(0.00%) \| Like=155.97..242.37 [147.1142..186.4200] \| it/evals=270/1279 eff=22.9008% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.76) Quality: ok a: +0.0\|* ** * * *** \| +31.4 b: +3.1e-05\|* * * * **** * \| +3.1e+01 Z=155.6(0.00%) \| Like=163.08..242.37 [147.1142..186.4200] \| it/evals=280/1411 eff=21.3577% N=100 Z=161.0(0.00%) \| Like=168.19..242.37 [147.1142..186.4200] \| it/evals=290/1566 eff=19.7817% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05\|* ** * * * \| +3.1e+01 b: +3.1e-05\| * * * *** \| +3.1e+01 Z=166.0(0.00%) \| Like=173.84..242.37 [147.1142..186.4200] \| it/evals=300/1700 eff=18.7500% N=100 Z=171.7(0.00%) \| Like=179.38..242.37 [147.1142..186.4200] \| it/evals=310/1793 eff=18.3107% N=100 Z=177.1(0.00%) \| Like=184.35..242.37 [147.1142..186.4200] \| it/evals=320/1938 eff=17.4102% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05\|* ** * \| +3.1e+01 b: +3.1e-05\| * * ** \| +3.1e+01 Z=182.5(0.00%) \| Like=189.50..242.37 [186.7319..216.1536] \| it/evals=330/2226 eff=15.5221% N=100 Z=186.2(0.00%) \| Like=193.29..242.37 [186.7319..216.1536] \| it/evals=340/2654 eff=13.3125% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05\|* ** \| +3.1e+01 b: +3.1e-05\| * \| +3.1e+01 Z=191.2(0.00%) \| Like=198.42..242.37 [186.7319..216.1536] \| it/evals=350/3009 eff=12.0316% N=100 Z=197.3(0.00%) \| Like=205.11..242.37 [186.7319..216.1536] \| it/evals=360/3318 eff=11.1871% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05\|* ** * ** \| +3.1e+01 b: +3.1e-05\| * * * \| +3.1e+01 Z=200.0(0.00%) \| Like=206.86..242.37 [186.7319..216.1536] \| it/evals=370/3667 eff=10.3729% N=100 Z=203.2(0.00%) \| Like=210.98..242.51 [186.7319..216.1536] \| it/evals=380/4187 eff=9.2978% N=100 Z=205.5(0.00%) \| Like=212.83..242.60 [186.7319..216.1536] \| it/evals=387/4696 eff=8.4204% N=100 Z=206.3(0.00%) \| Like=213.44..242.60 [186.7319..216.1536] \| it/evals=390/4799 eff=8.2996% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05\|* ** * * * \| +3.1e+01 b: +3.1e-05\|* ** * * * *\| +3.1e+01 Z=207.9(0.00%) \| Like=215.18..242.60 [186.7319..216.1536] \| it/evals=398/5225 eff=7.7659% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 5287 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 236.030 +- 0.815 single instance: logZ = 236.030 +- 0.247 bootstrapped : logZ = 236.020 +- 0.429 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 0.0 │▁ ▃▁ ▇ ▂ ▁▇ ▁│31.4 16.9 +- 7.9 b : 0 │▆ ▃▁ ▄▁ ▁ ▁▇ ▃│31 14 +- 11 5287 5287 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.692122856244112938e+01,7.903712302185231131e+00,1.276958378640852310e+01,6.412527886198907900e+00,2.524009418967003171e+01,1.427582766036078255e+01,1.146926462371362021e+01,1.263626942277114829e+01,6.172183764370788722e-02,2.514548034712652225e+01 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 16.921229 7.903712 12.769584 ... 12.636269 0.061722 25.14548 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 16.92122856244113 checking mean of parameter 'b': 14.275827660360783 checking stdev of parameter 'a': 7.903712302185231 checking stdev of parameter 'b': 11.46926462371362 checking median of parameter 'a': 12.769583786408523 checking median of parameter 'b': 12.636269422771148 checking errlo of parameter 'a': 6.412527886198908 checking errlo of parameter 'b': 0.06172183764370789 checking errup of parameter 'a': 25.24009418967003 checking errup of parameter 'b': 25.145480347126522 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmp103epbmo, backend=csv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=123, regioncalls=920, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=137, regioncalls=1480, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=149, regioncalls=1960, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=162, regioncalls=2480, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=175, regioncalls=3000, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=188, regioncalls=3520, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=206, regioncalls=4240, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=223, regioncalls=4920, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=244, regioncalls=5760, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=284, regioncalls=7360, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=309, regioncalls=8360, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=341, regioncalls=9640, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=377, regioncalls=11080, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=396, regioncalls=11840, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=441, regioncalls=13640, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=502, regioncalls=16080, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=553, regioncalls=18120, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=584, regioncalls=19360, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 626 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmp103epbmo, backend=csv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.05, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=0.06, remainder_fraction=100.0000%, Lmin=3.95, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=122, regioncalls=880, ndraw=40, logz=3.55, remainder_fraction=100.0000%, Lmin=6.71, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=133, regioncalls=1320, ndraw=40, logz=6.36, remainder_fraction=100.0000%, Lmin=10.30, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=145, regioncalls=1800, ndraw=40, logz=10.43, remainder_fraction=100.0000%, Lmin=14.59, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=156, regioncalls=2240, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.71, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=174, regioncalls=2960, ndraw=40, logz=22.21, remainder_fraction=100.0000%, Lmin=26.91, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=189, regioncalls=3560, ndraw=40, logz=26.59, remainder_fraction=100.0000%, Lmin=31.35, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=213, regioncalls=4520, ndraw=40, logz=29.74, remainder_fraction=100.0000%, Lmin=34.32, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=240, regioncalls=5600, ndraw=40, logz=33.34, remainder_fraction=100.0000%, Lmin=38.77, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=92, ncalls=246, regioncalls=5840, ndraw=40, logz=34.49, remainder_fraction=100.0000%, Lmin=39.28, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=273, regioncalls=6920, ndraw=40, logz=37.85, remainder_fraction=100.0000%, Lmin=42.61, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=297, regioncalls=7880, ndraw=40, logz=42.78, remainder_fraction=100.0000%, Lmin=47.95, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=326, regioncalls=9040, ndraw=40, logz=48.91, remainder_fraction=100.0000%, Lmin=54.86, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=368, regioncalls=10720, ndraw=40, logz=55.41, remainder_fraction=100.0000%, Lmin=61.66, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=402, regioncalls=12080, ndraw=40, logz=60.12, remainder_fraction=100.0000%, Lmin=68.52, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=452, regioncalls=14080, ndraw=40, logz=67.24, remainder_fraction=100.0000%, Lmin=72.18, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=496, regioncalls=15840, ndraw=40, logz=71.34, remainder_fraction=100.0000%, Lmin=76.78, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=544, regioncalls=17760, ndraw=40, logz=77.69, remainder_fraction=100.0000%, Lmin=85.32, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=573, regioncalls=18920, ndraw=40, logz=83.64, remainder_fraction=100.0000%, Lmin=91.87, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=595, regioncalls=19800, ndraw=40, logz=92.13, remainder_fraction=100.0000%, Lmin=98.48, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=674, regioncalls=22960, ndraw=40, logz=101.38, remainder_fraction=100.0000%, Lmin=108.11, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=722, regioncalls=24880, ndraw=40, logz=108.20, remainder_fraction=100.0000%, Lmin=114.20, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=778, regioncalls=27120, ndraw=40, logz=114.04, remainder_fraction=100.0000%, Lmin=121.27, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=849, regioncalls=29960, ndraw=40, logz=122.34, remainder_fraction=100.0000%, Lmin=128.65, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=950, regioncalls=34000, ndraw=40, logz=128.02, remainder_fraction=100.0000%, Lmin=134.37, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1034, regioncalls=37360, ndraw=40, logz=132.48, remainder_fraction=100.0000%, Lmin=139.29, Lmax=242.00 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1135, regioncalls=41400, ndraw=40, logz=140.81, remainder_fraction=100.0000%, Lmin=147.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1279, regioncalls=47160, ndraw=40, logz=148.11, remainder_fraction=100.0000%, Lmin=155.97, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1411, regioncalls=52440, ndraw=40, logz=155.63, remainder_fraction=100.0000%, Lmin=163.08, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1566, regioncalls=58640, ndraw=40, logz=161.05, remainder_fraction=100.0000%, Lmin=168.19, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1700, regioncalls=64000, ndraw=40, logz=166.03, remainder_fraction=100.0000%, Lmin=173.84, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1793, regioncalls=67720, ndraw=40, logz=171.65, remainder_fraction=100.0000%, Lmin=179.38, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1938, regioncalls=73520, ndraw=40, logz=177.14, remainder_fraction=100.0000%, Lmin=184.35, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=2226, regioncalls=85040, ndraw=40, logz=182.54, remainder_fraction=100.0000%, Lmin=189.50, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=2654, regioncalls=102160, ndraw=40, logz=186.24, remainder_fraction=100.0000%, Lmin=193.29, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=3009, regioncalls=116360, ndraw=40, logz=191.15, remainder_fraction=100.0000%, Lmin=198.42, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=3318, regioncalls=128720, ndraw=40, logz=197.32, remainder_fraction=100.0000%, Lmin=205.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=3667, regioncalls=142680, ndraw=40, logz=200.02, remainder_fraction=100.0000%, Lmin=206.86, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=4187, regioncalls=163480, ndraw=40, logz=203.15, remainder_fraction=100.0000%, Lmin=210.98, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=387, ncalls=4696, regioncalls=183840, ndraw=40, logz=205.47, remainder_fraction=100.0000%, Lmin=212.83, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=4799, regioncalls=187960, ndraw=40, logz=206.25, remainder_fraction=100.0000%, Lmin=213.44, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=398, ncalls=5225, regioncalls=205000, ndraw=40, logz=207.92, remainder_fraction=100.0000%, Lmin=215.18, Lmax=242.60 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5287 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_stepsampling.py::test_stepsampler_variable_speed_SLOW	16.12
[gw3] linux -- Python 3.10.6 /usr/bin/python3 [gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.34) * Expected Volume: exp(0.00) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-inf(0.00%) \| Like=-28.83..-0.16 [-28.8263..-8.7269] \| it/evals=0/408 eff=0.0000% N=400 Z=-24.2(0.00%) \| Like=-20.35..-0.16 [-28.8263..-8.7269] \| it/evals=50/652 eff=19.8413% N=400 Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.23) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-20.7(0.00%) \| Like=-17.02..-0.16 [-28.8263..-8.7269] \| it/evals=90/855 eff=19.7802% N=400 Z=-20.0(0.00%) \| Like=-16.30..-0.16 [-28.8263..-8.7269] \| it/evals=100/917 eff=19.3424% N=400 Z=-16.9(0.00%) \| Like=-13.55..-0.16 [-28.8263..-8.7269] \| it/evals=150/1204 eff=18.6567% N=400 Mono-modal Volume: ~exp(-4.70) Expected Volume: exp(-0.45) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-15.3(0.00%) \| Like=-11.67..-0.16 [-28.8263..-8.7269] \| it/evals=180/1379 eff=18.3861% N=400 Z=-14.3(0.00%) \| Like=-10.99..-0.16 [-28.8263..-8.7269] \| it/evals=200/1490 eff=18.3486% N=400 Z=-12.6(0.01%) \| Like=-9.48..-0.16 [-28.8263..-8.7269] \| it/evals=250/1831 eff=17.4703% N=400 Mono-modal Volume: ~exp(-4.89) Expected Volume: exp(-0.67) Quality: ok param0: +0.00\|*************************************************\| +1.00 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-12.0(0.02%) \| Like=-9.05..-0.16 [-28.8263..-8.7269] \| it/evals=270/1977 eff=17.1211% N=400 Z=-11.3(0.04%) \| Like=-8.32..-0.16 [-8.6993..-4.7523] \| it/evals=300/2235 eff=16.3488% N=400 Z=-10.3(0.12%) \| Like=-7.39..-0.16 [-8.6993..-4.7523] \| it/evals=350/2662 eff=15.4730% N=400 Mono-modal Volume: ~exp(-5.23) Expected Volume: exp(-0.90) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.0000\|***********************************************\| +1.0000 param2: +0.000\|************************************************\| +1.000 Z=-10.1(0.15%) \| Like=-7.24..-0.16 [-8.6993..-4.7523] \| it/evals=360/2749 eff=15.3257% N=400 Z=-9.4(0.29%) \| Like=-6.61..-0.16 [-8.6993..-4.7523] \| it/evals=400/3082 eff=14.9142% N=400 Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-1.12) Quality: ok param0: +0.000\| ********************************************\| +1.000 param1: +0.0000\|***********************************************\| +1.0000 param2: +0.00\|************************************************\| +1.00 Z=-8.8(0.55%) \| Like=-6.09..-0.16 [-8.6993..-4.7523] \| it/evals=450/3508 eff=14.4788% N=400 Z=-8.2(0.97%) \| Like=-5.48..-0.16 [-8.6993..-4.7523] \| it/evals=500/3947 eff=14.0964% N=400 Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-1.35) Quality: ok param0: +0.000\| * *********************************************\| +1.000 param1: +0.00\| **********************************************\| +1.00 param2: +0.00\| *********************************************** \| +1.00 Z=-7.7(1.64%) \| Like=-4.97..-0.16 [-8.6993..-4.7523] \| it/evals=550/4377 eff=13.8295% N=400 Z=-7.2(2.54%) \| Like=-4.55..-0.16 [-4.7510..-3.5347] \| it/evals=600/4902 eff=13.3274% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.57) Quality: ok param0: +0.00\| ******************************************** \| +1.00 param1: +0.00\| *********************************************** \| +1.00 param2: +0.00\| * *********************************************** \| +1.00 Z=-7.0(3.17%) \| Like=-4.36..-0.16 [-4.7510..-3.5347] \| it/evals=630/5206 eff=13.1086% N=400 Z=-6.9(3.66%) \| Like=-4.24..-0.16 [-4.7510..-3.5347] \| it/evals=650/5391 eff=13.0234% N=400 Z=-6.5(4.86%) \| Like=-3.89..-0.16 [-4.7510..-3.5347] \| it/evals=700/5910 eff=12.7042% N=400 Mono-modal Volume: ~exp(-5.82) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00\| ****************************************** \| +1.00 param1: +0.00\| ********************************************** \| +1.00 param2: +0.00\| * ********************************************** \| +1.00 Z=-6.4(5.40%) \| Like=-3.77..-0.16 [-4.7510..-3.5347] \| it/evals=720/6108 eff=12.6139% N=400 Z=-6.3(6.20%) \| Like=-3.64..-0.16 [-4.7510..-3.5347] \| it/evals=750/6423 eff=12.4523% N=400 Z=-6.0(8.08%) \| Like=-3.22..-0.16 [-3.5248..-3.0127] \| it/evals=800/6932 eff=12.2474% N=400 Mono-modal Volume: ~exp(-6.00) * Expected Volume: exp(-2.02) Quality: ok param0: +0.00\| ******************************************* \| +1.00 param1: +0.00\| ***************************************** \| +1.00 param2: +0.00\| ******************************************* \| +1.00 Z=-5.9(8.38%) \| Like=-3.18..-0.16 [-3.5248..-3.0127] \| it/evals=810/7022 eff=12.2320% N=400 Z=-5.7(10.09%) \| Like=-2.95..-0.16 [-3.0064..-2.8253] \| it/evals=850/7452 eff=12.0533% N=400 Mono-modal Volume: ~exp(-6.14) * Expected Volume: exp(-2.25) Quality: ok param0: +0.00\| ***************************************** \| +1.00 param1: +0.00\| **************************************** \| +1.00 param2: +0.00\| ***************************************** \| +1.00 Z=-5.5(13.03%) \| Like=-2.71..-0.16 [-2.7099..-2.6926] \| it/evals=900/8035 eff=11.7878% N=400 Z=-5.3(15.30%) \| Like=-2.53..-0.07 [-2.5312..-2.5204] \| it/evals=942/8536 eff=11.5782% N=400 Z=-5.3(15.81%) \| Like=-2.49..-0.07 [-2.4875..-2.4820]\| it/evals=950/8630 eff=11.5431% N=400 Have 2 modes Volume: ~exp(-6.44) Expected Volume: exp(-2.47) Quality: ok param0: +0.00\| 1 11111111111111111111222222222222222222222 \| +1.00 param1: +0.0\| 111111111111111111111222222222222222222222 \| +1.0 param2: +0.00\| 1111111111111111111112222222222222222222222 \| +1.00 Z=-5.2(18.09%) \| Like=-2.35..-0.07 [-2.3537..-2.3534]\| it/evals=990/9141 eff=11.3259% N=400 Z=-5.1(18.78%) \| Like=-2.32..-0.07 [-2.3178..-2.3145]\| it/evals=1000/9257 eff=11.2905% N=400 Z=-5.0(21.59%) \| Like=-2.15..-0.07 [-2.1509..-2.1480]\| it/evals=1042/9763 eff=11.1289% N=400 Z=-5.0(22.21%) \| Like=-2.13..-0.07 [-2.1288..-2.1266]\| it/evals=1050/9869 eff=11.0888% N=400 Have 2 modes Volume: ~exp(-6.74) * Expected Volume: exp(-2.70) Quality: ok param0: +0.0\| 11111111111111111111122222222222222222222 \| +1.0 param1: +0.0\| 1111111111111111111122222222222222222222 \| +1.0 param2: +0.0\| 1 111111111111111111 2222222222222222222 \| +1.0 Z=-4.9(24.46%) \| Like=-2.04..-0.07 [-2.0359..-2.0335]\| it/evals=1080/10222 eff=10.9957% N=400 Z=-4.8(25.95%) \| Like=-1.95..-0.05 [-1.9594..-1.9475] \| it/evals=1100/10463 eff=10.9311% N=400 Z=-4.7(29.13%) \| Like=-1.80..-0.05 [-1.7997..-1.7967]\| it/evals=1147/11007 eff=10.8136% N=400 Z=-4.7(29.42%) \| Like=-1.80..-0.05 [-1.7963..-1.7901]\| it/evals=1150/11037 eff=10.8113% N=400 Have 2 modes Volume: ~exp(-7.25) Expected Volume: exp(-2.92) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0\| 111111111111111111 222222222222222222 \| +1.0 param1: +0.0\| 1111111111111111111 2222222222222222222 \| +1.0 param2: +0.0\| 11111111111111111 222222222222222222 \| +1.0 Z=-4.6(31.04%) \| Like=-1.74..-0.05 [-1.7399..-1.7393]\| it/evals=1170/11290 eff=10.7438% N=400 Z=-4.6(33.32%) \| Like=-1.66..-0.05 [-1.6552..-1.6543]\| it/evals=1200/11649 eff=10.6676% N=400 Z=-4.5(37.58%) \| Like=-1.50..-0.05 [-1.4992..-1.4929]\| it/evals=1250/12253 eff=10.5459% N=400 Have 2 modes Volume: ~exp(-7.25) Expected Volume: exp(-3.15) Quality: ok positive degeneracy between param1 and param0: rho=0.75 param0: +0.0\| 1111111111111111 222222222222222222 \| +1.0 param1: +0.0\| 011111111111111111 22222222222222222 \| +1.0 param2: +0.0\| 11111111111111111 22222222222222222 \| +1.0 Z=-4.4(41.19%) \| Like=-1.38..-0.02 [-1.3786..-1.3754]\| it/evals=1298/12799 eff=10.4686% N=400 Z=-4.4(41.34%) \| Like=-1.37..-0.02 [-1.3736..-1.3729]\| it/evals=1300/12818 eff=10.4687% N=400 Have 2 modes Volume: ~exp(-7.59) Expected Volume: exp(-3.37) Quality: ok param0: +0.0\| 111111111111111 22222222222222222 \| +1.0 param1: +0.0\| 11111111111111111 222222222222222 \| +1.0 param2: +0.0\| 111111111111111 22222222222222222 \| +1.0 Z=-4.3(45.17%) \| Like=-1.24..-0.02 [-1.2446..-1.2442]\| it/evals=1350/13420 eff=10.3687% N=400 Z=-4.2(48.94%) \| Like=-1.17..-0.02 [-1.1729..-1.1720]\| it/evals=1400/14103 eff=10.2167% N=400 Have 2 modes Volume: ~exp(-7.67) * Expected Volume: exp(-3.60) Quality: ok param0: +0.0\| 11111111111111 2222222222222222 \| +1.0 param1: +0.0\| 111111111111111 22222222222222 \| +1.0 param2: +0.0\| 111111111111111 222222222222222 \| +1.0 Z=-4.1(51.66%) \| Like=-1.10..-0.02 [-1.0988..-1.0917]\| it/evals=1440/14656 eff=10.1010% N=400 Z=-4.1(52.34%) \| Like=-1.08..-0.02 [-1.0790..-1.0771]\| it/evals=1450/14798 eff=10.0708% N=400 Z=-4.0(56.01%) \| Like=-0.97..-0.02 [-0.9728..-0.9710]\| it/evals=1500/15457 eff=9.9621% N=400 Have 2 modes Volume: ~exp(-8.10) Expected Volume: exp(-3.82) Quality: ok param0: +0.0\| 1111111111111 22222222222222 \| +1.0 param1: +0.0\| 1111111111111 22222222222222 \| +1.0 param2: +0.0\| 11111111111111 22222222222222 \| +1.0 Z=-4.0(58.24%) \| Like=-0.91..-0.02 [-0.9133..-0.9124]\| it/evals=1530/15876 eff=9.8863% N=400 Z=-4.0(59.61%) \| Like=-0.88..-0.02 [-0.8802..-0.8801]\| it/evals=1550/16146 eff=9.8438% N=400 Z=-3.9(63.06%) \| Like=-0.81..-0.02 [-0.8119..-0.8102]\| it/evals=1600/16863 eff=9.7188% N=400 Have 2 modes Volume: ~exp(-8.32) Expected Volume: exp(-4.05) Quality: ok param0: +0.0\| 111111111111 2222222222222 \| +1.0 param1: +0.0\| 1111111111111 2222222222222 \| +1.0 param2: +0.0\| 1111111111111 222222222222 \| +1.0 Z=-3.9(64.35%) \| Like=-0.79..-0.02 [-0.7856..-0.7839]\| it/evals=1620/17112 eff=9.6936% N=400 Z=-3.9(66.11%) \| Like=-0.74..-0.02 [-0.7430..-0.7393]\| it/evals=1650/17513 eff=9.6418% N=400 Z=-3.8(69.01%) \| Like=-0.67..-0.01 [-0.6732..-0.6726]\| it/evals=1698/18256 eff=9.5094% N=400 Z=-3.8(69.13%) \| Like=-0.67..-0.01 [-0.6714..-0.6700]\| it/evals=1700/18286 eff=9.5046% N=400 Have 2 modes Volume: ~exp(-8.58) * Expected Volume: exp(-4.27) Quality: ok param0: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 111111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 111111111111 222222222222 \| +1.0 Z=-3.8(69.71%) \| Like=-0.66..-0.01 [-0.6579..-0.6573]\| it/evals=1710/18415 eff=9.4921% N=400 Z=-3.8(71.97%) \| Like=-0.61..-0.01 [-0.6089..-0.6086]\| it/evals=1750/18982 eff=9.4177% N=400 Have 2 modes Volume: ~exp(-8.80) * Expected Volume: exp(-4.50) Quality: ok param0: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-3.8(74.56%) \| Like=-0.57..-0.01 [-0.5666..-0.5665]\| it/evals=1800/19686 eff=9.3332% N=400 Z=-3.7(77.00%) \| Like=-0.52..-0.01 [-0.5201..-0.5200]\| it/evals=1850/20380 eff=9.2593% N=400 Have 2 modes Volume: ~exp(-8.81) * Expected Volume: exp(-4.73) Quality: ok param0: +0.0\| 1111111111 22222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 2222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-3.7(78.76%) \| Like=-0.48..-0.01 [-0.4809..-0.4805]\| it/evals=1890/20945 eff=9.1993% N=400 Z=-3.7(79.22%) \| Like=-0.47..-0.01 [-0.4748..-0.4739]\| it/evals=1900/21094 eff=9.1814% N=400 Z=-3.7(81.23%) \| Like=-0.44..-0.01 [-0.4430..-0.4430]\| it/evals=1950/21811 eff=9.1075% N=400 Have 2 modes Volume: ~exp(-9.47) Expected Volume: exp(-4.95) Quality: ok param0: +0.0\| +0.2 111111111 2222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 2222222222 +0.8 \| +1.0 param2: +0.0\| 1111111111 2222222222 +0.8 \| +1.0 Z=-3.7(82.39%) \| Like=-0.42..-0.00 [-0.4213..-0.4212]\| it/evals=1980/22248 eff=9.0626% N=400 Z=-3.6(83.11%) \| Like=-0.41..-0.00 [-0.4099..-0.4091]\| it/evals=2000/22514 eff=9.0440% N=400 Z=-3.6(84.80%) \| Like=-0.38..-0.00 [-0.3805..-0.3804]\| it/evals=2050/23230 eff=8.9794% N=400 Have 2 modes Volume: ~exp(-9.47) Expected Volume: exp(-5.18) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-3.6(85.93%) \| Like=-0.35..-0.00 [-0.3545..-0.3535]\| it/evals=2086/23733 eff=8.9401% N=400 Z=-3.6(86.34%) \| Like=-0.35..-0.00 [-0.3465..-0.3464]\| it/evals=2100/23916 eff=8.9301% N=400 Z=-3.6(87.66%) \| Like=-0.32..-0.00 [-0.3200..-0.3198]\| it/evals=2146/24579 eff=8.8755% N=400 Z=-3.6(87.77%) \| Like=-0.32..-0.00 [-0.3165..-0.3164]\| it/evals=2150/24636 eff=8.8711% N=400 Have 2 modes Volume: ~exp(-9.61) Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-3.6(88.03%) \| Like=-0.31..-0.00 [-0.3132..-0.3128]\| it/evals=2160/24786 eff=8.8575% N=400 Z=-3.6(89.05%) \| Like=-0.29..-0.00 [-0.2923..-0.2917]\| it/evals=2200/25324 eff=8.8268% N=400 Have 2 modes Volume: ~exp(-9.75) * Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| +0.2 1111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111111 222222222 +0.8 \| +1.0 Z=-3.6(90.21%) \| Like=-0.27..-0.00 [-0.2700..-0.2698]\| it/evals=2250/26022 eff=8.7815% N=400 Z=-3.6(91.25%) \| Like=-0.25..-0.00 [-0.2519..-0.2516]\| it/evals=2300/26733 eff=8.7343% N=400 Have 2 modes Volume: ~exp(-10.04) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.5(92.01%) \| Like=-0.24..-0.00 [-0.2357..-0.2355]\| it/evals=2340/27302 eff=8.6982% N=400 Z=-3.5(92.19%) \| Like=-0.23..-0.00 [-0.2294..-0.2292]\| it/evals=2350/27437 eff=8.6918% N=400 Z=-3.5(93.02%) \| Like=-0.21..-0.00 [-0.2105..-0.2104]\| it/evals=2400/28149 eff=8.6490% N=400 Have 2 modes Volume: ~exp(-10.19) Expected Volume: exp(-6.08) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.5(93.49%) \| Like=-0.20..-0.00 [-0.1993..-0.1991]\| it/evals=2430/28569 eff=8.6265% N=400 Z=-3.5(93.78%) \| Like=-0.19..-0.00 [-0.1942..-0.1942]\| it/evals=2450/28857 eff=8.6095% N=400 Z=-3.5(94.38%) \| Like=-0.18..-0.00 [-0.1843..-0.1840]\| it/evals=2494/29463 eff=8.5814% N=400 Z=-3.5(94.46%) \| Like=-0.18..-0.00 [-0.1825..-0.1822]\| it/evals=2500/29561 eff=8.5731% N=400 Have 2 modes Volume: ~exp(-10.24) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.2 1111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.5(94.71%) \| Like=-0.18..-0.00 [-0.1772..-0.1767]\| it/evals=2520/29853 eff=8.5560% N=400 Z=-3.5(95.07%) \| Like=-0.17..-0.00 [-0.1693..-0.1691]\| it/evals=2550/30281 eff=8.5339% N=400 Z=-3.5(95.61%) \| Like=-0.16..-0.00 [-0.1558..-0.1558]\| it/evals=2600/30980 eff=8.5023% N=400 Have 2 modes Volume: ~exp(-10.87) Expected Volume: exp(-6.53) Quality: ok param0: +0.0\| +0.3 111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.3 1111111 222222 +0.8 \| +1.0 param2: +0.0\| +0.2 111111 222222 +0.7 \| +1.0 Z=-3.5(95.72%) \| Like=-0.15..-0.00 [-0.1546..-0.1542]\| it/evals=2610/31115 eff=8.4975% N=400 Z=-3.5(96.08%) \| Like=-0.14..-0.00 [-0.1445..-0.1443]\| it/evals=2648/31634 eff=8.4779% N=400 Z=-3.5(96.10%) \| Like=-0.14..-0.00 [-0.1441..-0.1440]\| it/evals=2650/31661 eff=8.4770% N=400 Z=-3.5(96.52%) \| Like=-0.13..-0.00 [-0.1314..-0.1313]\| it/evals=2698/32350 eff=8.4444% N=400 Have 2 modes Volume: ~exp(-11.01) * Expected Volume: exp(-6.75) Quality: ok param0: +0.0\| +0.2 111111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 111111 222222 +0.7 \| +1.0 param2: +0.0\| +0.3 111111 22222 +0.7 \| +1.0 Z=-3.5(96.53%) \| Like=-0.13..-0.00 [-0.1313..-0.1312]\| it/evals=2700/32376 eff=8.4438% N=400 Z=-3.5(96.92%) \| Like=-0.12..-0.00 [-0.1190..-0.1189]\| it/evals=2750/33059 eff=8.4203% N=400 Have 2 modes Volume: ~exp(-11.01) Expected Volume: exp(-6.98) Quality: ok param0: +0.0\| +0.3 11111 222220 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.25%) \| Like=-0.11..-0.00 [-0.1098..-0.1093]\| it/evals=2796/33719 eff=8.3916% N=400 Z=-3.5(97.27%) \| Like=-0.11..-0.00 [-0.1090..-0.1089]\| it/evals=2800/33775 eff=8.3895% N=400 Z=-3.5(97.58%) \| Like=-0.10..-0.00 [-0.1009..-0.1008]\| it/evals=2850/34460 eff=8.3676% N=400 Have 2 modes Volume: ~exp(-11.20) Expected Volume: exp(-7.20) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.75%) \| Like=-0.10..-0.00 [-0.0973..-0.0973]\| it/evals=2880/34872 eff=8.3546% N=400 Z=-3.5(97.85%) \| Like=-0.09..-0.00 [-0.0936..-0.0934]\| it/evals=2900/35140 eff=8.3477% N=400 Z=-3.5(98.10%) \| Like=-0.08..-0.00 [-0.0833..-0.0832]\| it/evals=2950/35853 eff=8.3209% N=400 Have 2 modes Volume: ~exp(-11.50) Expected Volume: exp(-7.43) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.19%) \| Like=-0.08..-0.00 [-0.0804..-0.0803]\| it/evals=2970/36145 eff=8.3089% N=400 Z=-3.5(98.31%) \| Like=-0.08..-0.00 [-0.0768..-0.0767]\| it/evals=3000/36561 eff=8.2962% N=400 Z=-3.5(98.51%) \| Like=-0.07..-0.00 [-0.0714..-0.0713]\| it/evals=3050/37263 eff=8.2739% N=400 Have 2 modes Volume: ~exp(-11.85) Expected Volume: exp(-7.65) Quality: ok param0: +0.0\| +0.3 11111 2222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.54%) \| Like=-0.07..-0.00 [-0.0707..-0.0707]\| it/evals=3060/37393 eff=8.2718% N=400 Z=-3.5(98.68%) \| Like=-0.07..-0.00 [-0.0663..-0.0661]\| it/evals=3100/37983 eff=8.2484% N=400 Have 2 modes Volume: ~exp(-11.85) Expected Volume: exp(-7.88) Quality: ok param0: +0.0\| +0.3 11110 02222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 02222 +0.7 \| +1.0 Z=-3.5(98.83%) \| Like=-0.06..-0.00 [-0.0607..-0.0606]\| it/evals=3150/38670 eff=8.2310% N=400 Z=-3.5(98.96%) \| Like=-0.06..-0.00 [-0.0556..-0.0554]\| it/evals=3200/39390 eff=8.2072% N=400 [ultranest] Explored until L=-0.0009 [ultranest] Likelihood function evaluations: 39576 [ultranest] logZ = -3.454 +- 0.05165 [ultranest] Effective samples strategy satisfied (ESS = 1850.3, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.464 +- 0.118 single instance: logZ = -3.464 +- 0.071 bootstrapped : logZ = -3.454 +- 0.118 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁ ▁▁▁▁▂▃▅▅▆▄▅▅▄▄▃▃▂▃▂▃▃▅▅▇▇▇▇▇▇▄▂▃▂▁▁▁▁│1.00 0.54 +- 0.22 param1 : 0.00 │▁▁▁▁▂▂▂▃▄▄▆▅▅▅▄▄▃▂▂▂▂▃▄▄▅▇▇▇▇▅▇▃▃▂▂▁▁▁▁│1.00 0.53 +- 0.22 param2 : 0.00 │▁▁▁▁▁▂▂▃▄▅▅▆▅▆▃▄▂▃▂▂▃▃▄▄▆▇▇▇▅▇▆▄▃▃▂▂▁▁▁│1.00 0.53 +- 0.22 [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-3.77) * Expected Volume: exp(0.00) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|************************************************\| +1.000 Z=-inf(0.00%) \| Like=-30.72..-0.14 [-30.7155..-8.6130] \| it/evals=0/408 eff=0.0000% N=400 Z=-23.5(0.00%) \| Like=-19.79..-0.14 [-30.7155..-8.6130] \| it/evals=50/643 eff=20.5761% N=400 Mono-modal Volume: ~exp(-4.50) Expected Volume: exp(-0.23) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.000\|***********************************************\| +1.000 Z=-20.3(0.00%) \| Like=-16.75..-0.14 [-30.7155..-8.6130] \| it/evals=90/842 eff=20.3620% N=400 Z=-19.6(0.00%) \| Like=-16.01..-0.14 [-30.7155..-8.6130] \| it/evals=100/881 eff=20.7900% N=400 Z=-16.7(0.00%) \| Like=-13.30..-0.14 [-30.7155..-8.6130] \| it/evals=150/1187 eff=19.0597% N=400 Mono-modal Volume: ~exp(-4.50) Expected Volume: exp(-0.45) Quality: ok param0: +0.000\|***********************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-14.3(0.00%) \| Like=-11.07..-0.14 [-30.7155..-8.6130] \| it/evals=200/1518 eff=17.8891% N=400 Z=-12.5(0.01%) \| Like=-9.36..-0.08 [-30.7155..-8.6130] \| it/evals=250/1856 eff=17.1703% N=400 Mono-modal Volume: ~exp(-4.59) Expected Volume: exp(-0.67) Quality: ok param0: +0.000\|*************************************************\| +1.000 param1: +0.000\|***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-11.9(0.02%) \| Like=-8.82..-0.08 [-30.7155..-8.6130] \| it/evals=270/2017 eff=16.6976% N=400 Z=-11.2(0.04%) \| Like=-8.15..-0.08 [-8.5729..-4.8890] \| it/evals=300/2241 eff=16.2955% N=400 Z=-10.1(0.12%) \| Like=-7.25..-0.08 [-8.5729..-4.8890] \| it/evals=350/2597 eff=15.9308% N=400 Mono-modal Volume: ~exp(-4.78) Expected Volume: exp(-0.90) Quality: ok param0: +0.000\|**************************************************\| +1.000 param1: +0.000\| ***********************************************\| +1.000 param2: +0.00\|************************************************\| +1.00 Z=-9.9(0.14%) \| Like=-7.13..-0.08 [-8.5729..-4.8890] \| it/evals=360/2686 eff=15.7480% N=400 Z=-9.4(0.26%) \| Like=-6.65..-0.08 [-8.5729..-4.8890] \| it/evals=400/2991 eff=15.4381% N=400 Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-1.12) Quality: ok param0: +0.000\|************************************************** \| +1.000 param1: +0.000\|* ***********************************************\| +1.000 param2: +0.00\|******************************************** \| +1.00 Z=-8.7(0.47%) \| Like=-6.15..-0.08 [-8.5729..-4.8890] \| it/evals=450/3421 eff=14.8957% N=400 Z=-8.2(0.80%) \| Like=-5.58..-0.08 [-8.5729..-4.8890] \| it/evals=500/3853 eff=14.4802% N=400 Mono-modal Volume: ~exp(-5.49) * Expected Volume: exp(-1.35) Quality: ok param0: +0.000\|************************************************ \| +1.000 param1: +0.00\| **********************************************\| +1.00 param2: +0.000\|********************************************** \| +1.000 Z=-7.8(1.27%) \| Like=-5.11..-0.08 [-8.5729..-4.8890] \| it/evals=540/4239 eff=14.0662% N=400 Z=-7.7(1.39%) \| Like=-5.07..-0.08 [-8.5729..-4.8890] \| it/evals=550/4360 eff=13.8889% N=400 Z=-7.3(2.18%) \| Like=-4.63..-0.08 [-4.8759..-3.4495] \| it/evals=600/4774 eff=13.7174% N=400 Mono-modal Volume: ~exp(-5.49) Expected Volume: exp(-1.57) Quality: ok param0: +0.00\| * *************************************** \| +1.00 param1: +0.000\|********************************************** \| +1.000 param2: +0.00\| *********************************************** \| +1.00 Z=-6.9(3.19%) \| Like=-4.26..-0.08 [-4.8759..-3.4495] \| it/evals=650/5228 eff=13.4631% N=400 Z=-6.6(4.42%) \| Like=-3.95..-0.08 [-4.8759..-3.4495] \| it/evals=700/5694 eff=13.2225% N=400 Mono-modal Volume: ~exp(-5.51) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00\| ********************************************** \| +1.00 param1: +0.00\| ******************************************** \| +1.00 param2: +0.00\| ******************************************** * \| +1.00 Z=-6.5(5.01%) \| Like=-3.81..-0.08 [-4.8759..-3.4495] \| it/evals=720/5877 eff=13.1459% N=400 Z=-6.3(6.01%) \| Like=-3.57..-0.08 [-4.8759..-3.4495] \| it/evals=750/6185 eff=12.9646% N=400 Z=-6.0(8.07%) \| Like=-3.36..-0.08 [-3.4294..-3.0089] \| it/evals=800/6703 eff=12.6924% N=400 Mono-modal Volume: ~exp(-5.75) * Expected Volume: exp(-2.02) Quality: ok positive degeneracy between param1 and param0: rho=0.75 param0: +0.00\| ******************************************** \| +1.00 param1: +0.00\| ******************************************* \| +1.00 param2: +0.00\| ******************************************* \| +1.00 Z=-6.0(8.46%) \| Like=-3.31..-0.08 [-3.4294..-3.0089] \| it/evals=810/6800 eff=12.6562% N=400 Z=-5.8(10.21%) \| Like=-3.02..-0.08 [-3.4294..-3.0089] \| it/evals=850/7190 eff=12.5184% N=400 Mono-modal Volume: ~exp(-6.34) * Expected Volume: exp(-2.25) Quality: ok positive degeneracy between param2 and param1: rho=0.77 param0: +0.00\| ***************************************** \| +1.00 param1: +0.00\| **************************************** \| +1.00 param2: +0.00\| ****************************************** \| +1.00 Z=-5.6(12.57%) \| Like=-2.82..-0.04 [-2.8656..-2.7934] \| it/evals=900/7734 eff=12.2716% N=400 Z=-5.4(15.40%) \| Like=-2.61..-0.04 [-2.6142..-2.6119]\| it/evals=950/8283 eff=12.0512% N=400 Have 2 modes Volume: ~exp(-6.69) Expected Volume: exp(-2.47) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 111111111111111111112222222222222222222222 \| +1.0 param1: +0.00\| 1111111111111111111111222222222222222222222 \| +1.00 param2: +0.00\| 11 1111111111111111111222222222222222222222 \| +1.00 Z=-5.2(17.59%) \| Like=-2.36..-0.04 [-2.3628..-2.3616]\| it/evals=990/8721 eff=11.8976% N=400 Z=-5.2(18.24%) \| Like=-2.31..-0.04 [-2.3115..-2.3053]\| it/evals=1000/8846 eff=11.8399% N=400 Z=-5.0(21.93%) \| Like=-2.09..-0.02 [-2.0868..-2.0846]\| it/evals=1050/9438 eff=11.6176% N=400 Have 2 modes Volume: ~exp(-7.11) Expected Volume: exp(-2.70) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 1111111111111111111 22222222222222222222 \| +1.0 param1: +0.0\| 11111111111111111111222222222222222222222 \| +1.0 param2: +0.0\| 111111111111111111 22222222222222222222 \| +1.0 Z=-4.9(24.27%) \| Like=-2.01..-0.02 [-2.0281..-2.0083] \| it/evals=1080/9801 eff=11.4881% N=400 Z=-4.9(25.84%) \| Like=-1.93..-0.02 [-1.9348..-1.9280]\| it/evals=1100/10060 eff=11.3872% N=400 Z=-4.7(29.65%) \| Like=-1.79..-0.02 [-1.7887..-1.7871]\| it/evals=1150/10677 eff=11.1900% N=400 Have 2 modes Volume: ~exp(-7.11) Expected Volume: exp(-2.92) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 111111111111111111 2222222222222222222 \| +1.0 param1: +0.0\| 11111111111111111111 2222222222222222222 \| +1.0 param2: +0.0\| 0111111111111111111 2222222222222222222 \| +1.0 Z=-4.6(33.36%) \| Like=-1.68..-0.02 [-1.6826..-1.6768]\| it/evals=1200/11350 eff=10.9589% N=400 Z=-4.5(37.03%) \| Like=-1.54..-0.02 [-1.5525..-1.5411] \| it/evals=1250/12003 eff=10.7731% N=400 Have 2 modes Volume: ~exp(-7.35) Expected Volume: exp(-3.15) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 11111111111111111 222222222222222222 \| +1.0 param1: +0.0\| 1 111111111111111 2222222222222222222 \| +1.0 param2: +0.0\| 111111111111111111 222222222222222222 \| +1.0 Z=-4.5(37.74%) \| Like=-1.50..-0.02 [-1.5030..-1.5016]\| it/evals=1260/12125 eff=10.7463% N=400 Z=-4.4(40.69%) \| Like=-1.38..-0.02 [-1.3932..-1.3832] \| it/evals=1300/12647 eff=10.6148% N=400 Have 2 modes Volume: ~exp(-7.35) Expected Volume: exp(-3.37) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 1111111111111111 2222222222222222 \| +1.0 param1: +0.0\| 111111111111111 22222222222222222 \| +1.0 param2: +0.0\| 1111111111111111 22222222222222222 \| +1.0 Z=-4.3(44.84%) \| Like=-1.27..-0.02 [-1.2720..-1.2711]\| it/evals=1350/13312 eff=10.4554% N=400 Z=-4.2(48.70%) \| Like=-1.18..-0.02 [-1.1835..-1.1824]\| it/evals=1400/14001 eff=10.2934% N=400 Have 2 modes Volume: ~exp(-7.56) Expected Volume: exp(-3.60) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0\| 111111111111111 22222222222222 \| +1.0 param1: +0.0\| 111111111111111 2222222222222222 \| +1.0 param2: +0.0\| 111111111111111 222222222222222 \| +1.0 Z=-4.2(51.68%) \| Like=-1.11..-0.02 [-1.1101..-1.1077]\| it/evals=1440/14526 eff=10.1940% N=400 Z=-4.1(52.42%) \| Like=-1.08..-0.02 [-1.0795..-1.0776]\| it/evals=1450/14675 eff=10.1576% N=400 Z=-4.1(56.27%) \| Like=-0.99..-0.02 [-0.9862..-0.9841]\| it/evals=1500/15383 eff=10.0113% N=400 Have 2 modes Volume: ~exp(-8.10) Expected Volume: exp(-3.82) Quality: ok positive degeneracy between param2 and param1: rho=0.75 param0: +0.0\| 111111111111111 22222222222222 \| +1.0 param1: +0.0\| 11111111111111 22222222222222 \| +1.0 param2: +0.0\| 1111111111111 222222222222222 \| +1.0 Z=-4.0(58.31%) \| Like=-0.96..-0.02 [-0.9583..-0.9577]\| it/evals=1530/15811 eff=9.9280% N=400 Z=-4.0(59.71%) \| Like=-0.93..-0.02 [-0.9327..-0.9319]\| it/evals=1550/16084 eff=9.8827% N=400 Z=-4.0(62.98%) \| Like=-0.86..-0.02 [-0.8610..-0.8608]\| it/evals=1600/16777 eff=9.7698% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.05) Quality: ok param0: +0.0\| 11111111111111 2222222222222 \| +1.0 param1: +0.0\| 1111111111111 2222222222222 \| +1.0 param2: +0.0\| 1111111111111 2222222222222 \| +1.0 Z=-3.9(64.21%) \| Like=-0.83..-0.02 [-0.8319..-0.8302]\| it/evals=1620/17068 eff=9.7192% N=400 Z=-3.9(66.02%) \| Like=-0.78..-0.02 [-0.7844..-0.7819]\| it/evals=1650/17474 eff=9.6638% N=400 Z=-3.9(68.88%) \| Like=-0.72..-0.02 [-0.7185..-0.7171]\| it/evals=1700/18181 eff=9.5608% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.27) Quality: ok param0: +0.0\| 011111111111 222222222222 \| +1.0 param1: +0.0\| 1111111111111 222222222222 \| +1.0 param2: +0.0\| 1111111111111 222222222222 \| +1.0 Z=-3.8(71.69%) \| Like=-0.65..-0.02 [-0.6530..-0.6527]\| it/evals=1750/18873 eff=9.4733% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.50) Quality: ok param0: +0.0\| 011111111101 22222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 222222222222 \| +1.0 Z=-3.8(74.33%) \| Like=-0.61..-0.01 [-0.6079..-0.6078]\| it/evals=1800/19590 eff=9.3799% N=400 Z=-3.8(76.65%) \| Like=-0.56..-0.01 [-0.5608..-0.5607]\| it/evals=1850/20308 eff=9.2927% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.73) Quality: ok param0: +0.0\| 11111111101 2222222222 +0.8 \| +1.0 param1: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 11111111111 22222222222 +0.8 \| +1.0 Z=-3.7(78.46%) \| Like=-0.53..-0.01 [-0.5328..-0.5320]\| it/evals=1890/20890 eff=9.2240% N=400 Z=-3.7(78.88%) \| Like=-0.52..-0.01 [-0.5217..-0.5216]\| it/evals=1900/21039 eff=9.2059% N=400 Z=-3.7(80.75%) \| Like=-0.48..-0.01 [-0.4843..-0.4841]\| it/evals=1946/21688 eff=9.1413% N=400 Z=-3.7(80.91%) \| Like=-0.48..-0.01 [-0.4806..-0.4802]\| it/evals=1950/21739 eff=9.1382% N=400 Have 2 modes Volume: ~exp(-9.10) * Expected Volume: exp(-4.95) Quality: ok param0: +0.0\| 111111111 2222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111111 22222222222 +0.8 \| +1.0 param2: +0.0\| 1111111111 2222222222 +0.8 \| +1.0 Z=-3.7(82.04%) \| Like=-0.45..-0.01 [-0.4530..-0.4516]\| it/evals=1980/22164 eff=9.0976% N=400 Z=-3.7(82.77%) \| Like=-0.44..-0.01 [-0.4359..-0.4357]\| it/evals=2000/22437 eff=9.0756% N=400 Z=-3.7(84.37%) \| Like=-0.40..-0.01 [-0.4047..-0.4046]\| it/evals=2047/23121 eff=9.0093% N=400 Z=-3.7(84.46%) \| Like=-0.40..-0.00 [-0.4038..-0.4036]\| it/evals=2050/23176 eff=9.0007% N=400 Have 2 modes Volume: ~exp(-9.55) * Expected Volume: exp(-5.18) Quality: ok param0: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 11111111 2222222222 +0.8 \| +1.0 Z=-3.7(85.08%) \| Like=-0.38..-0.00 [-0.3835..-0.3834]\| it/evals=2070/23468 eff=8.9735% N=400 Z=-3.6(86.01%) \| Like=-0.36..-0.00 [-0.3626..-0.3625]\| it/evals=2100/23855 eff=8.9533% N=400 Z=-3.6(87.48%) \| Like=-0.33..-0.00 [-0.3325..-0.3324]\| it/evals=2150/24513 eff=8.9164% N=400 Have 2 modes Volume: ~exp(-9.55) Expected Volume: exp(-5.40) Quality: ok param0: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 param2: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 Z=-3.6(88.25%) \| Like=-0.31..-0.00 [-0.3127..-0.3123]\| it/evals=2179/24901 eff=8.8935% N=400 Z=-3.6(88.76%) \| Like=-0.30..-0.00 [-0.3024..-0.3013]\| it/evals=2200/25200 eff=8.8710% N=400 Have 2 modes Volume: ~exp(-9.86) Expected Volume: exp(-5.63) Quality: ok param0: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 11111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 11111111 222222222 +0.8 \| +1.0 Z=-3.6(89.94%) \| Like=-0.28..-0.00 [-0.2765..-0.2764]\| it/evals=2250/25854 eff=8.8395% N=400 Z=-3.6(90.99%) \| Like=-0.26..-0.00 [-0.2586..-0.2586]\| it/evals=2299/26539 eff=8.7953% N=400 Z=-3.6(91.01%) \| Like=-0.26..-0.00 [-0.2586..-0.2575]\| it/evals=2300/26553 eff=8.7944% N=400 Have 2 modes Volume: ~exp(-10.13) Expected Volume: exp(-5.85) Quality: ok param0: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 22222222 +0.8 \| +1.0 param2: +0.0\| +0.2 11111111 2222222 +0.8 \| +1.0 Z=-3.6(91.78%) \| Like=-0.24..-0.00 [-0.2428..-0.2419]\| it/evals=2340/27133 eff=8.7532% N=400 Z=-3.6(91.97%) \| Like=-0.24..-0.00 [-0.2390..-0.2385]\| it/evals=2350/27278 eff=8.7432% N=400 Z=-3.6(92.83%) \| Like=-0.22..-0.00 [-0.2196..-0.2195]\| it/evals=2400/27946 eff=8.7127% N=400 Have 2 modes Volume: ~exp(-10.13) Expected Volume: exp(-6.08) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 Z=-3.6(93.47%) \| Like=-0.20..-0.00 [-0.2011..-0.2010]\| it/evals=2441/28535 eff=8.6760% N=400 Z=-3.6(93.60%) \| Like=-0.20..-0.00 [-0.1984..-0.1984]\| it/evals=2450/28675 eff=8.6649% N=400 Z=-3.6(94.30%) \| Like=-0.19..-0.00 [-0.1856..-0.1851]\| it/evals=2500/29353 eff=8.6347% N=400 Have 2 modes Volume: ~exp(-10.43) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param1: +0.0\| +0.2 1111111 2222222 +0.8 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.7 \| +1.0 Z=-3.5(94.56%) \| Like=-0.18..-0.00 [-0.1800..-0.1799]\| it/evals=2520/29662 eff=8.6119% N=400 Z=-3.5(94.93%) \| Like=-0.17..-0.00 [-0.1693..-0.1687]\| it/evals=2550/30099 eff=8.5861% N=400 Z=-3.5(95.39%) \| Like=-0.16..-0.00 [-0.1575..-0.1574]\| it/evals=2591/30671 eff=8.5593% N=400 Z=-3.5(95.49%) \| Like=-0.16..-0.00 [-0.1552..-0.1549]\| it/evals=2600/30778 eff=8.5588% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.53) Quality: ok param0: +0.0\| +0.2 111111 222222 +0.8 \| +1.0 param1: +0.0\| +0.2 111111 2222222 +0.7 \| +1.0 param2: +0.0\| +0.2 1111111 2222222 +0.7 \| +1.0 Z=-3.5(95.90%) \| Like=-0.15..-0.00 [-0.1482..-0.1482]\| it/evals=2640/31333 eff=8.5346% N=400 Z=-3.5(96.00%) \| Like=-0.15..-0.00 [-0.1462..-0.1460]\| it/evals=2650/31473 eff=8.5283% N=400 Z=-3.5(96.42%) \| Like=-0.14..-0.00 [-0.1367..-0.1360]\| it/evals=2698/32151 eff=8.4974% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.75) Quality: ok param0: +0.0\| +0.3 11111 222222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 222222 +0.7 \| +1.0 param2: +0.0\| +0.3 011111 222222 +0.7 \| +1.0 Z=-3.5(96.44%) \| Like=-0.14..-0.00 [-0.1360..-0.1359]\| it/evals=2700/32188 eff=8.4938% N=400 Z=-3.5(96.84%) \| Like=-0.12..-0.00 [-0.1240..-0.1239]\| it/evals=2750/32861 eff=8.4717% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.98) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 222222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.16%) \| Like=-0.12..-0.00 [-0.1170..-0.1167]\| it/evals=2795/33463 eff=8.4536% N=400 Z=-3.5(97.19%) \| Like=-0.12..-0.00 [-0.1161..-0.1159]\| it/evals=2800/33526 eff=8.4526% N=400 Z=-3.5(97.47%) \| Like=-0.11..-0.00 [-0.1070..-0.1059]\| it/evals=2844/34171 eff=8.4214% N=400 Z=-3.5(97.51%) \| Like=-0.11..-0.00 [-0.1053..-0.1051]\| it/evals=2850/34241 eff=8.4217% N=400 Have 2 modes Volume: ~exp(-10.65) Expected Volume: exp(-7.20) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(97.68%) \| Like=-0.10..-0.00 [-0.1002..-0.0999]\| it/evals=2880/34663 eff=8.4056% N=400 Z=-3.5(97.79%) \| Like=-0.10..-0.00 [-0.0955..-0.0954]\| it/evals=2900/34946 eff=8.3946% N=400 Z=-3.5(97.99%) \| Like=-0.09..-0.00 [-0.0887..-0.0886]\| it/evals=2939/35496 eff=8.3742% N=400 Z=-3.5(98.04%) \| Like=-0.09..-0.00 [-0.0876..-0.0873]\| it/evals=2950/35641 eff=8.3709% N=400 Have 2 modes Volume: ~exp(-11.34) * Expected Volume: exp(-7.43) Quality: ok param0: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.13%) \| Like=-0.08..-0.00 [-0.0850..-0.0839]\| it/evals=2970/35916 eff=8.3624% N=400 Z=-3.5(98.27%) \| Like=-0.08..-0.00 [-0.0810..-0.0810]\| it/evals=3000/36340 eff=8.3472% N=400 Z=-3.5(98.44%) \| Like=-0.07..-0.00 [-0.0748..-0.0746]\| it/evals=3044/36948 eff=8.3288% N=400 Z=-3.5(98.46%) \| Like=-0.07..-0.00 [-0.0740..-0.0738]\| it/evals=3050/37033 eff=8.3258% N=400 Have 2 modes Volume: ~exp(-11.34) Expected Volume: exp(-7.65) Quality: ok param0: +0.0\| +0.3 1111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11110 22222 +0.7 \| +1.0 Z=-3.5(98.57%) \| Like=-0.07..-0.00 [-0.0692..-0.0692]\| it/evals=3080/37466 eff=8.3095% N=400 Z=-3.5(98.64%) \| Like=-0.07..-0.00 [-0.0672..-0.0668]\| it/evals=3100/37717 eff=8.3072% N=400 Z=-3.5(98.78%) \| Like=-0.06..-0.00 [-0.0622..-0.0622]\| it/evals=3146/38392 eff=8.2807% N=400 Have 2 modes Volume: ~exp(-11.58) Expected Volume: exp(-7.88) Quality: ok param0: +0.0\| +0.3 1111 22222 +0.7 \| +1.0 param1: +0.0\| +0.3 1111 22222 +0.7 \| +1.0 param2: +0.0\| +0.3 11111 22222 +0.7 \| +1.0 Z=-3.5(98.80%) \| Like=-0.06..-0.00 [-0.0621..-0.0619]\| it/evals=3150/38452 eff=8.2781% N=400 Z=-3.5(98.93%) \| Like=-0.06..-0.00 [-0.0580..-0.0580]\| it/evals=3200/39146 eff=8.2589% N=400 [ultranest] Explored until L=-0.002 [ultranest] Likelihood function evaluations: 39507 [ultranest] logZ = -3.501 +- 0.06405 [ultranest] Effective samples strategy satisfied (ESS = 1848.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.493 +- 0.164 single instance: logZ = -3.493 +- 0.071 bootstrapped : logZ = -3.501 +- 0.163 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▁▁▂▂▄▄▅▅▅▄▄▄▃▃▁▂▂▂▃▃▅▇▇▇▆▆▄▄▃▂▂▁▁▁▁│1.00 0.54 +- 0.22 param1 : 0.00 │▁▁▁▁▁▂▃▂▄▅▄▆▅▄▃▄▃▂▂▁▃▂▃▅▅▇▇▇▅▅▄▅▃▃▂▁▁▁▁│1.00 0.53 +- 0.23 param2 : 0.00 │▁▁▁▁▁▁▃▄▅▄▄▅▅▅▅▃▃▃▂▂▂▃▃▄▅▇▇▆▆▇▅▅▃▂▁▁▁▁▁│1.00 0.53 +- 0.22 -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=408, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-28.83, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=652, regioncalls=0, ndraw=40, logz=-24.15, remainder_fraction=100.0000%, Lmin=-20.35, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=855, regioncalls=0, ndraw=40, logz=-20.66, remainder_fraction=100.0000%, Lmin=-17.02, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=917, regioncalls=0, ndraw=40, logz=-19.96, remainder_fraction=100.0000%, Lmin=-16.30, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1204, regioncalls=0, ndraw=40, logz=-16.87, remainder_fraction=99.9998%, Lmin=-13.55, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=1379, regioncalls=0, ndraw=40, logz=-15.27, remainder_fraction=99.9992%, Lmin=-11.67, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1490, regioncalls=0, ndraw=40, logz=-14.29, remainder_fraction=99.9978%, Lmin=-10.99, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1831, regioncalls=0, ndraw=40, logz=-12.55, remainder_fraction=99.9876%, Lmin=-9.48, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1977, regioncalls=0, ndraw=40, logz=-12.03, remainder_fraction=99.9788%, Lmin=-9.05, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=2235, regioncalls=0, ndraw=40, logz=-11.29, remainder_fraction=99.9558%, Lmin=-8.32, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2662, regioncalls=0, ndraw=40, logz=-10.29, remainder_fraction=99.8768%, Lmin=-7.39, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2749, regioncalls=0, ndraw=40, logz=-10.10, remainder_fraction=99.8502%, Lmin=-7.24, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=3082, regioncalls=0, ndraw=40, logz=-9.45, remainder_fraction=99.7066%, Lmin=-6.61, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3508, regioncalls=0, ndraw=40, logz=-8.79, remainder_fraction=99.4495%, Lmin=-6.09, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3947, regioncalls=0, ndraw=40, logz=-8.20, remainder_fraction=99.0254%, Lmin=-5.48, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=4377, regioncalls=0, ndraw=40, logz=-7.67, remainder_fraction=98.3560%, Lmin=-4.97, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=4902, regioncalls=0, ndraw=40, logz=-7.23, remainder_fraction=97.4567%, Lmin=-4.55, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=5206, regioncalls=0, ndraw=40, logz=-7.00, remainder_fraction=96.8277%, Lmin=-4.36, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5391, regioncalls=0, ndraw=40, logz=-6.86, remainder_fraction=96.3450%, Lmin=-4.24, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5910, regioncalls=0, ndraw=40, logz=-6.55, remainder_fraction=95.1376%, Lmin=-3.89, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=6108, regioncalls=0, ndraw=40, logz=-6.43, remainder_fraction=94.6041%, Lmin=-3.77, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6423, regioncalls=0, ndraw=40, logz=-6.26, remainder_fraction=93.7974%, Lmin=-3.64, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=6932, regioncalls=0, ndraw=40, logz=-6.00, remainder_fraction=91.9152%, Lmin=-3.22, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=7022, regioncalls=0, ndraw=40, logz=-5.94, remainder_fraction=91.6156%, Lmin=-3.18, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=7452, regioncalls=0, ndraw=40, logz=-5.74, remainder_fraction=89.9117%, Lmin=-2.95, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=8035, regioncalls=0, ndraw=40, logz=-5.51, remainder_fraction=86.9683%, Lmin=-2.71, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=8536, regioncalls=0, ndraw=40, logz=-5.34, remainder_fraction=84.7024%, Lmin=-2.53, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=8630, regioncalls=0, ndraw=40, logz=-5.31, remainder_fraction=84.1905%, Lmin=-2.49, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=9141, regioncalls=0, ndraw=40, logz=-5.16, remainder_fraction=81.9129%, Lmin=-2.35, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=9257, regioncalls=0, ndraw=40, logz=-5.12, remainder_fraction=81.2186%, Lmin=-2.32, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1042, ncalls=9763, regioncalls=0, ndraw=40, logz=-4.99, remainder_fraction=78.4103%, Lmin=-2.15, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=9869, regioncalls=0, ndraw=40, logz=-4.96, remainder_fraction=77.7926%, Lmin=-2.13, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=10222, regioncalls=0, ndraw=40, logz=-4.87, remainder_fraction=75.5443%, Lmin=-2.04, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=10463, regioncalls=0, ndraw=40, logz=-4.82, remainder_fraction=74.0501%, Lmin=-1.95, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1147, ncalls=11007, regioncalls=0, ndraw=40, logz=-4.69, remainder_fraction=70.8707%, Lmin=-1.80, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=11037, regioncalls=0, ndraw=40, logz=-4.68, remainder_fraction=70.5823%, Lmin=-1.80, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=11290, regioncalls=0, ndraw=40, logz=-4.63, remainder_fraction=68.9649%, Lmin=-1.74, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=11649, regioncalls=0, ndraw=40, logz=-4.56, remainder_fraction=66.6778%, Lmin=-1.66, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=12253, regioncalls=0, ndraw=40, logz=-4.45, remainder_fraction=62.4217%, Lmin=-1.50, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1298, ncalls=12799, regioncalls=0, ndraw=40, logz=-4.36, remainder_fraction=58.8052%, Lmin=-1.38, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=12818, regioncalls=0, ndraw=40, logz=-4.35, remainder_fraction=58.6619%, Lmin=-1.37, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=13420, regioncalls=0, ndraw=40, logz=-4.26, remainder_fraction=54.8291%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=14103, regioncalls=0, ndraw=40, logz=-4.18, remainder_fraction=51.0564%, Lmin=-1.17, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=14656, regioncalls=0, ndraw=40, logz=-4.12, remainder_fraction=48.3362%, Lmin=-1.10, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=14798, regioncalls=0, ndraw=40, logz=-4.11, remainder_fraction=47.6584%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=15457, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=43.9916%, Lmin=-0.97, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=15876, regioncalls=0, ndraw=40, logz=-4.00, remainder_fraction=41.7608%, Lmin=-0.91, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=16146, regioncalls=0, ndraw=40, logz=-3.98, remainder_fraction=40.3943%, Lmin=-0.88, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=16863, regioncalls=0, ndraw=40, logz=-3.93, remainder_fraction=36.9419%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=17112, regioncalls=0, ndraw=40, logz=-3.91, remainder_fraction=35.6471%, Lmin=-0.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=17513, regioncalls=0, ndraw=40, logz=-3.88, remainder_fraction=33.8851%, Lmin=-0.74, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1698, ncalls=18256, regioncalls=0, ndraw=40, logz=-3.84, remainder_fraction=30.9943%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=18286, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=30.8667%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=18415, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=30.2875%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=18982, regioncalls=0, ndraw=40, logz=-3.79, remainder_fraction=28.0333%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=19686, regioncalls=0, ndraw=40, logz=-3.76, remainder_fraction=25.4394%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=20380, regioncalls=0, ndraw=40, logz=-3.73, remainder_fraction=22.9973%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=20945, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=21.2394%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=21094, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=20.7811%, Lmin=-0.47, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=21811, regioncalls=0, ndraw=40, logz=-3.67, remainder_fraction=18.7682%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=22248, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=17.6122%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=22514, regioncalls=0, ndraw=40, logz=-3.65, remainder_fraction=16.8935%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=23230, regioncalls=0, ndraw=40, logz=-3.63, remainder_fraction=15.2022%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2086, ncalls=23733, regioncalls=0, ndraw=40, logz=-3.62, remainder_fraction=14.0709%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=23916, regioncalls=0, ndraw=40, logz=-3.61, remainder_fraction=13.6615%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2146, ncalls=24579, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=12.3395%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=24636, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=12.2299%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=24786, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=11.9665%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=25324, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=10.9502%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=26022, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=9.7880%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=26733, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=8.7467%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=27302, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=7.9888%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=27437, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=7.8140%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=28149, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=6.9763%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=28569, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=6.5113%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=28857, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=6.2211%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2494, ncalls=29463, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.6208%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=29561, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.5427%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=29853, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.2866%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=30281, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.9283%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=30980, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.3857%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=31115, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.2832%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2648, ncalls=31634, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.9189%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=31661, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.8998%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2698, ncalls=32350, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.4821%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32376, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.4651%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33059, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=3.0753%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2796, ncalls=33719, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.7542%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=33775, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.7283%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34460, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.4214%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34872, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.2520%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35140, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.1465%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35853, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.9028%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=36145, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.8127%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36561, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.6855%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37263, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.4927%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37393, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.4567%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37983, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.3219%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38670, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.1704%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=39390, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=1.0359%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.0009 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39576 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.454 +- 0.05165 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1850.3, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=408, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.72, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=643, regioncalls=0, ndraw=40, logz=-23.52, remainder_fraction=100.0000%, Lmin=-19.79, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=842, regioncalls=0, ndraw=40, logz=-20.30, remainder_fraction=100.0000%, Lmin=-16.75, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=881, regioncalls=0, ndraw=40, logz=-19.61, remainder_fraction=100.0000%, Lmin=-16.01, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1187, regioncalls=0, ndraw=40, logz=-16.71, remainder_fraction=99.9998%, Lmin=-13.30, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1518, regioncalls=0, ndraw=40, logz=-14.31, remainder_fraction=99.9982%, Lmin=-11.07, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1856, regioncalls=0, ndraw=40, logz=-12.50, remainder_fraction=99.9895%, Lmin=-9.36, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=2017, regioncalls=0, ndraw=40, logz=-11.92, remainder_fraction=99.9811%, Lmin=-8.82, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=2241, regioncalls=0, ndraw=40, logz=-11.17, remainder_fraction=99.9593%, Lmin=-8.15, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2597, regioncalls=0, ndraw=40, logz=-10.12, remainder_fraction=99.8843%, Lmin=-7.25, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2686, regioncalls=0, ndraw=40, logz=-9.94, remainder_fraction=99.8597%, Lmin=-7.13, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=2991, regioncalls=0, ndraw=40, logz=-9.36, remainder_fraction=99.7402%, Lmin=-6.65, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3421, regioncalls=0, ndraw=40, logz=-8.74, remainder_fraction=99.5274%, Lmin=-6.15, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3853, regioncalls=0, ndraw=40, logz=-8.22, remainder_fraction=99.1959%, Lmin=-5.58, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=4239, regioncalls=0, ndraw=40, logz=-7.82, remainder_fraction=98.7327%, Lmin=-5.11, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=4360, regioncalls=0, ndraw=40, logz=-7.72, remainder_fraction=98.6113%, Lmin=-5.07, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=4774, regioncalls=0, ndraw=40, logz=-7.30, remainder_fraction=97.8227%, Lmin=-4.63, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5228, regioncalls=0, ndraw=40, logz=-6.92, remainder_fraction=96.8062%, Lmin=-4.26, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5694, regioncalls=0, ndraw=40, logz=-6.60, remainder_fraction=95.5797%, Lmin=-3.95, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5877, regioncalls=0, ndraw=40, logz=-6.48, remainder_fraction=94.9944%, Lmin=-3.81, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6185, regioncalls=0, ndraw=40, logz=-6.30, remainder_fraction=93.9860%, Lmin=-3.57, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=6703, regioncalls=0, ndraw=40, logz=-6.03, remainder_fraction=91.9307%, Lmin=-3.36, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=6800, regioncalls=0, ndraw=40, logz=-5.98, remainder_fraction=91.5442%, Lmin=-3.31, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=7190, regioncalls=0, ndraw=40, logz=-5.79, remainder_fraction=89.7945%, Lmin=-3.02, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=7734, regioncalls=0, ndraw=40, logz=-5.57, remainder_fraction=87.4320%, Lmin=-2.82, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=8283, regioncalls=0, ndraw=40, logz=-5.38, remainder_fraction=84.5994%, Lmin=-2.61, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=8721, regioncalls=0, ndraw=40, logz=-5.23, remainder_fraction=82.4132%, Lmin=-2.36, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=8846, regioncalls=0, ndraw=40, logz=-5.20, remainder_fraction=81.7602%, Lmin=-2.31, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=9438, regioncalls=0, ndraw=40, logz=-5.02, remainder_fraction=78.0705%, Lmin=-2.09, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=9801, regioncalls=0, ndraw=40, logz=-4.92, remainder_fraction=75.7277%, Lmin=-2.01, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=10060, regioncalls=0, ndraw=40, logz=-4.86, remainder_fraction=74.1624%, Lmin=-1.93, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=10677, regioncalls=0, ndraw=40, logz=-4.72, remainder_fraction=70.3481%, Lmin=-1.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=11350, regioncalls=0, ndraw=40, logz=-4.60, remainder_fraction=66.6382%, Lmin=-1.68, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=12003, regioncalls=0, ndraw=40, logz=-4.49, remainder_fraction=62.9726%, Lmin=-1.54, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=12125, regioncalls=0, ndraw=40, logz=-4.47, remainder_fraction=62.2550%, Lmin=-1.50, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=12647, regioncalls=0, ndraw=40, logz=-4.39, remainder_fraction=59.3069%, Lmin=-1.38, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=13312, regioncalls=0, ndraw=40, logz=-4.30, remainder_fraction=55.1640%, Lmin=-1.27, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=14001, regioncalls=0, ndraw=40, logz=-4.21, remainder_fraction=51.3023%, Lmin=-1.18, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=14526, regioncalls=0, ndraw=40, logz=-4.15, remainder_fraction=48.3174%, Lmin=-1.11, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=14675, regioncalls=0, ndraw=40, logz=-4.14, remainder_fraction=47.5789%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=15383, regioncalls=0, ndraw=40, logz=-4.07, remainder_fraction=43.7293%, Lmin=-0.99, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=15811, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=41.6883%, Lmin=-0.96, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=16084, regioncalls=0, ndraw=40, logz=-4.01, remainder_fraction=40.2892%, Lmin=-0.93, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=16777, regioncalls=0, ndraw=40, logz=-3.96, remainder_fraction=37.0213%, Lmin=-0.86, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=17068, regioncalls=0, ndraw=40, logz=-3.94, remainder_fraction=35.7910%, Lmin=-0.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=17474, regioncalls=0, ndraw=40, logz=-3.91, remainder_fraction=33.9815%, Lmin=-0.78, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=18181, regioncalls=0, ndraw=40, logz=-3.87, remainder_fraction=31.1224%, Lmin=-0.72, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=18873, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=28.3121%, Lmin=-0.65, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=19590, regioncalls=0, ndraw=40, logz=-3.79, remainder_fraction=25.6712%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=20308, regioncalls=0, ndraw=40, logz=-3.76, remainder_fraction=23.3453%, Lmin=-0.56, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=20890, regioncalls=0, ndraw=40, logz=-3.74, remainder_fraction=21.5449%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=21039, regioncalls=0, ndraw=40, logz=-3.73, remainder_fraction=21.1217%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1946, ncalls=21688, regioncalls=0, ndraw=40, logz=-3.71, remainder_fraction=19.2455%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=21739, regioncalls=0, ndraw=40, logz=-3.71, remainder_fraction=19.0872%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=22164, regioncalls=0, ndraw=40, logz=-3.69, remainder_fraction=17.9575%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=22437, regioncalls=0, ndraw=40, logz=-3.68, remainder_fraction=17.2288%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2047, ncalls=23121, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=15.6320%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=23176, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=15.5371%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=23468, regioncalls=0, ndraw=40, logz=-3.65, remainder_fraction=14.9243%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=23855, regioncalls=0, ndraw=40, logz=-3.64, remainder_fraction=13.9892%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=24513, regioncalls=0, ndraw=40, logz=-3.63, remainder_fraction=12.5203%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2179, ncalls=24901, regioncalls=0, ndraw=40, logz=-3.62, remainder_fraction=11.7529%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=25200, regioncalls=0, ndraw=40, logz=-3.61, remainder_fraction=11.2407%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=25854, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=10.0608%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2299, ncalls=26539, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=9.0080%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=26553, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=8.9903%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=27133, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=8.2171%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=27278, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=8.0294%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=27946, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=7.1747%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2441, ncalls=28535, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=6.5330%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=28675, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=6.3952%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=29353, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.6963%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=29662, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.4385%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=30099, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.0740%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2591, ncalls=30671, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.6054%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=30778, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.5081%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=31333, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.0983%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=31473, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=4.0025%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2698, ncalls=32151, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.5774%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32188, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.5598%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=32861, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.1611%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2795, ncalls=33463, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.8408%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=33526, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.8080%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2844, ncalls=34171, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.5277%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34241, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.4920%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34663, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.3185%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=34946, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.2089%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2939, ncalls=35496, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=2.0105%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35641, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.9576%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=35916, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.8662%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36340, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.7348%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3044, ncalls=36948, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.5593%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37033, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.5367%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=37466, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.4286%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37717, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.3611%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3146, ncalls=38392, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.2164%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38452, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.2047%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=39146, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=1.0664%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39507 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.501 +- 0.06405 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1848.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_run.py::test_run_resume[2.0]	8.64
[gw4] linux -- Python 3.10.6 /usr/bin/python3 [gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.32) * Expected Volume: exp(0.00) Quality: ok a: +0.0000\|*******************************************************\| +1.0000 Z=-inf(0.00%) \| Like=-1245.39..3.65 [-1245.3896..-308.0711] \| it/evals=0/528 eff=0.0000% N=400 Z=-990.5(0.00%) \| Like=-981.54..3.68 [-1245.3896..-308.0711] \| it/evals=50/528 eff=39.0625% N=400 Mono-modal Volume: ~exp(-4.49) Expected Volume: exp(-0.23) Quality: ok a: +0.00\| ************************************************ \| +1.00 Z=-861.8(0.00%) \| Like=-854.74..3.68 [-1245.3896..-308.0711] \| it/evals=90/528 eff=70.3125% N=400 Z=-823.2(0.00%) \| Like=-812.27..3.68 [-1245.3896..-308.0711] \| it/evals=100/528 eff=78.1250% N=400 Z=-630.1(0.00%) \| Like=-620.09..3.68 [-1245.3896..-308.0711] \| it/evals=150/633 eff=64.3777% N=400 Mono-modal Volume: ~exp(-4.58) * Expected Volume: exp(-0.45) Quality: ok a: +0.0\| ************************************ \| +1.0 Z=-552.1(0.00%) \| Like=-543.77..3.69 [-1245.3896..-308.0711] \| it/evals=180/633 eff=77.2532% N=400 Z=-513.4(0.00%) \| Like=-505.92..3.69 [-1245.3896..-308.0711] \| it/evals=200/633 eff=85.8369% N=400 Z=-393.4(0.00%) \| Like=-383.84..3.69 [-1245.3896..-308.0711] \| it/evals=250/728 eff=76.2195% N=400 Mono-modal Volume: ~exp(-4.58) Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.2 **************************** +0.8 \| +1.0 Z=-308.5(0.00%) \| Like=-296.59..3.69 [-307.5524..-75.4168] \| it/evals=300/792 eff=76.5306% N=400 Z=-241.3(0.00%) \| Like=-233.94..3.69 [-307.5524..-75.4168] \| it/evals=350/853 eff=77.2627% N=400 Mono-modal Volume: ~exp(-5.21) * Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ************************ +0.7 \| +1.0 Z=-231.2(0.00%) \| Like=-222.15..3.69 [-307.5524..-75.4168] \| it/evals=360/853 eff=79.4702% N=400 Z=-195.0(0.00%) \| Like=-187.11..3.69 [-307.5524..-75.4168] \| it/evals=400/903 eff=79.5229% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 ******************** +0.7 \| +1.0 Z=-148.8(0.00%) \| Like=-141.92..3.69 [-307.5524..-75.4168] \| it/evals=450/951 eff=81.6697% N=400 Z=-119.5(0.00%) \| Like=-113.36..3.69 [-307.5524..-75.4168] \| it/evals=500/986 eff=85.3242% N=400 Mono-modal Volume: ~exp(-5.33) * Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 **************** +0.6 \| +1.0 Z=-98.3(0.00%) \| Like=-90.77..3.69 [-307.5524..-75.4168] \| it/evals=540/1035 eff=85.0394% N=400 Z=-91.6(0.00%) \| Like=-85.36..3.69 [-307.5524..-75.4168] \| it/evals=550/1035 eff=86.6142% N=400 Z=-70.1(0.00%) \| Like=-63.21..3.69 [-75.3486..-15.0754] \| it/evals=600/1076 eff=88.7574% N=400 Mono-modal Volume: ~exp(-5.34) * Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 ************ +0.6 \| +1.0 Z=-60.2(0.00%) \| Like=-53.09..3.69 [-75.3486..-15.0754] \| it/evals=630/1109 eff=88.8575% N=400 Z=-53.3(0.00%) \| Like=-47.34..3.69 [-75.3486..-15.0754] \| it/evals=650/1144 eff=87.3656% N=400 Z=-42.1(0.00%) \| Like=-35.02..3.69 [-75.3486..-15.0754] \| it/evals=700/1194 eff=88.1612% N=400 Mono-modal Volume: ~exp(-5.92) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-37.6(0.00%) \| Like=-31.23..3.69 [-75.3486..-15.0754] \| it/evals=720/1221 eff=87.6979% N=400 Z=-32.8(0.00%) \| Like=-26.86..3.69 [-75.3486..-15.0754] \| it/evals=750/1245 eff=88.7574% N=400 Z=-26.3(0.00%) \| Like=-20.36..3.69 [-75.3486..-15.0754] \| it/evals=800/1305 eff=88.3978% N=400 Mono-modal Volume: ~exp(-6.05) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-25.2(0.00%) \| Like=-19.53..3.69 [-75.3486..-15.0754] \| it/evals=810/1305 eff=89.5028% N=400 Z=-21.1(0.00%) \| Like=-15.13..3.69 [-75.3486..-15.0754] \| it/evals=850/1356 eff=88.9121% N=400 Mono-modal Volume: ~exp(-6.36) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-16.7(0.00%) \| Like=-11.04..3.69 [-14.9390..-1.0650] \| it/evals=900/1405 eff=89.5522% N=400 Z=-13.4(0.00%) \| Like=-8.20..3.69 [-14.9390..-1.0650] \| it/evals=950/1451 eff=90.3901% N=400 Mono-modal Volume: ~exp(-6.63) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.46 ****** +0.54 \| +1.00 Z=-11.5(0.00%) \| Like=-5.86..3.69 [-14.9390..-1.0650] \| it/evals=990/1493 eff=90.5764% N=400 Z=-10.9(0.00%) \| Like=-5.22..3.69 [-14.9390..-1.0650] \| it/evals=1000/1513 eff=89.8473% N=400 Z=-8.3(0.03%) \| Like=-2.98..3.69 [-14.9390..-1.0650] \| it/evals=1050/1562 eff=90.3614% N=400 Mono-modal Volume: ~exp(-7.01) * Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-7.3(0.07%) \| Like=-2.03..3.69 [-14.9390..-1.0650] \| it/evals=1080/1597 eff=90.2256% N=400 Z=-6.7(0.12%) \| Like=-1.69..3.69 [-14.9390..-1.0650] \| it/evals=1100/1613 eff=90.6843% N=400 Z=-5.5(0.40%) \| Like=-0.52..3.69 [-1.0420..1.4103] \| it/evals=1150/1659 eff=91.3423% N=400 Mono-modal Volume: ~exp(-7.01) Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 ** +0.53 \| +1.00 Z=-4.5(1.08%) \| Like=0.49..3.69 [-1.0420..1.4103] \| it/evals=1200/1716 eff=91.1854% N=400 Z=-3.7(2.59%) \| Like=1.31..3.69 [-1.0420..1.4103] \| it/evals=1250/1767 eff=91.4411% N=400 Mono-modal Volume: ~exp(-7.48) * Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-3.5(3.02%) \| Like=1.42..3.69 [1.4124..1.7038] \| it/evals=1260/1774 eff=91.7031% N=400 Z=-3.0(5.15%) \| Like=1.82..3.69 [1.8072..1.8177] \| it/evals=1300/1821 eff=91.4849% N=400 Mono-modal Volume: ~exp(-7.48) Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 +0.52 \| +1.00 Z=-2.5(8.76%) \| Like=2.20..3.69 [2.1997..2.2038]\| it/evals=1350/1868 eff=91.9619% N=400 Z=-2.0(13.34%) \| Like=2.53..3.69 [2.5278..2.5282]\| it/evals=1400/1917 eff=92.2874% N=400 Mono-modal Volume: ~exp(-7.64) * Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.8(17.25%) \| Like=2.72..3.69 [2.7240..2.7290]\| it/evals=1440/1963 eff=92.1305% N=400 Z=-1.7(18.31%) \| Like=2.78..3.69 [2.7629..2.7785] \| it/evals=1450/1973 eff=92.1805% N=400 Z=-1.4(23.98%) \| Like=2.99..3.69 [2.9857..2.9912]\| it/evals=1500/2026 eff=92.2509% N=400 Mono-modal Volume: ~exp(-7.84) * Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.3(27.63%) \| Like=3.09..3.69 [3.0871..3.0878]\| it/evals=1530/2055 eff=92.4471% N=400 Z=-1.2(30.05%) \| Like=3.13..3.69 [3.1343..3.1384]\| it/evals=1550/2073 eff=92.6479% N=400 Z=-1.0(35.91%) \| Like=3.23..3.69 [3.2289..3.2338]\| it/evals=1599/2231 eff=87.3293% N=400 Z=-1.0(36.04%) \| Like=3.23..3.69 [3.2338..3.2374]\| it/evals=1600/2231 eff=87.3839% N=400 Mono-modal Volume: ~exp(-8.21) * Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.0(38.38%) \| Like=3.27..3.69 [3.2718..3.2781]\| it/evals=1620/2231 eff=88.4762% N=400 Z=-0.9(41.87%) \| Like=3.33..3.69 [3.3257..3.3279]\| it/evals=1650/2231 eff=90.1147% N=400 Z=-0.8(47.43%) \| Like=3.40..3.69 [3.4041..3.4052]\| it/evals=1700/2246 eff=92.0910% N=400 Mono-modal Volume: ~exp(-8.53) Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.7(48.51%) \| Like=3.42..3.69 [3.4158..3.4202]\| it/evals=1710/2257 eff=92.0840% N=400 Z=-0.7(52.66%) \| Like=3.46..3.69 [3.4553..3.4578]\| it/evals=1750/2403 eff=87.3689% N=400 Mono-modal Volume: ~exp(-8.53) Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(57.51%) \| Like=3.51..3.69 [3.5118..3.5138]\| it/evals=1800/2403 eff=89.8652% N=400 Z=-0.5(62.04%) \| Like=3.55..3.69 [3.5533..3.5544]\| it/evals=1850/2505 eff=87.8860% N=400 Mono-modal Volume: ~exp(-8.59) * Expected Volume: exp(-4.73) Quality: ok a: +0.000\| +0.495 ** +0.505 \| +1.000 Z=-0.4(65.38%) \| Like=3.57..3.69 [3.5735..3.5736]\| it/evals=1890/2505 eff=89.7862% N=400 Z=-0.4(66.17%) \| Like=3.58..3.69 [3.5809..3.5814]\| it/evals=1900/2505 eff=90.2613% N=400 Z=-0.4(69.91%) \| Like=3.61..3.69 [3.6080..3.6080]\| it/evals=1950/2537 eff=91.2494% N=400 Mono-modal Volume: ~exp(-8.91) Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.3(71.98%) \| Like=3.62..3.69 [3.6159..3.6159]\| it/evals=1980/2569 eff=91.2863% N=400 Z=-0.3(73.29%) \| Like=3.63..3.69 [3.6253..3.6255]\| it/evals=2000/2705 eff=86.7679% N=400 Z=-0.3(76.32%) \| Like=3.64..3.69 [3.6374..3.6374]\| it/evals=2050/2705 eff=88.9371% N=400 Mono-modal Volume: ~exp(-9.26) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.3(77.44%) \| Like=3.64..3.69 [3.6435..3.6437]\| it/evals=2070/2705 eff=89.8048% N=400 Z=-0.2(79.03%) \| Like=3.65..3.69 [3.6499..3.6499]\| it/evals=2100/2722 eff=90.4393% N=400 Z=-0.2(81.44%) \| Like=3.66..3.69 [3.6581..3.6582]\| it/evals=2150/2758 eff=91.1790% N=400 Mono-modal Volume: ~exp(-9.26) Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.2(81.89%) \| Like=3.66..3.69 [3.6591..3.6591]\| it/evals=2160/2776 eff=90.9091% N=400 Z=-0.2(83.59%) \| Like=3.66..3.69 [3.6638..3.6640]\| it/evals=2200/2904 eff=87.8594% N=400 Mono-modal Volume: ~exp(-9.67) * Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.2(85.49%) \| Like=3.67..3.69 [3.6689..3.6690]\| it/evals=2250/2904 eff=89.8562% N=400 Z=-0.2(87.18%) \| Like=3.67..3.69 [3.6731..3.6731]\| it/evals=2300/2926 eff=91.0530% N=400 Mono-modal Volume: ~exp(-10.05) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(88.39%) \| Like=3.68..3.69 [3.6754..3.6754]\| it/evals=2340/2970 eff=91.0506% N=400 Z=-0.1(88.68%) \| Like=3.68..3.69 [3.6759..3.6759]\| it/evals=2350/3090 eff=87.3606% N=400 Z=-0.1(90.00%) \| Like=3.68..3.69 [3.6785..3.6786]\| it/evals=2400/3090 eff=89.2193% N=400 Mono-modal Volume: ~exp(-10.21) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(90.72%) \| Like=3.68..3.69 [3.6795..3.6795]\| it/evals=2430/3090 eff=90.3346% N=400 Z=-0.1(91.17%) \| Like=3.68..3.69 [3.6801..3.6802]\| it/evals=2450/3217 eff=86.9720% N=400 Z=-0.1(92.20%) \| Like=3.68..3.69 [3.6816..3.6817]\| it/evals=2500/3217 eff=88.7469% N=400 Mono-modal Volume: ~exp(-10.21) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 * +0.501 \| +1.000 Z=-0.1(93.12%) \| Like=3.68..3.69 [3.6826..3.6827]\| it/evals=2550/3217 eff=90.5218% N=400 Z=-0.1(93.92%) \| Like=3.68..3.69 [3.6835..3.6835]\| it/evals=2600/3312 eff=89.2857% N=400 Mono-modal Volume: ~exp(-10.64) * Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(94.07%) \| Like=3.68..3.69 [3.6837..3.6837]\| it/evals=2610/3312 eff=89.6291% N=400 Z=-0.1(94.64%) \| Like=3.68..3.69 [3.6840..3.6840]\| it/evals=2650/3330 eff=90.4437% N=400 Mono-modal Volume: ~exp(-10.71) * Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(95.27%) \| Like=3.68..3.69 [3.6845..3.6845]\| it/evals=2700/3384 eff=90.4826% N=400 Z=-0.1(95.82%) \| Like=3.68..3.69 [3.6848..3.6848]\| it/evals=2750/3512 eff=88.3676% N=400 Mono-modal Volume: ~exp(-10.71) Expected Volume: exp(-6.98) Quality: ok a: +0.0000\| +0.4995 ** +0.5005 \| +1.0000 Z=-0.1(96.31%) \| Like=3.69..3.69 [3.6851..3.6851]\| it/evals=2800/3512 eff=89.9743% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3621 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.0125 +- 0.06231 [ultranest] Effective samples strategy satisfied (ESS = 1260.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.07, need <2.0) [ultranest] logZ error budget: single: 0.09 bs:0.06 tail:0.03 total:0.07 required:<2.00 [ultranest] done iterating. logZ = -0.014 +- 0.110 single instance: logZ = -0.014 +- 0.090 bootstrapped : logZ = -0.013 +- 0.104 tail : logZ = +- 0.034 insert order U test : converged: True correlation: inf iterations a : 0.460 │ ▁ ▁▁▁▁▁▁▂▃▃▃▅▆▅▇▇▇▇▇▆▆▄▃▂▂▁▁▁▁▁▁▁ ▁ │0.547 0.500 +- 0.010 [ultranest] Resuming from 3531 stored points Mono-modal Volume: ~exp(-4.29) Expected Volume: exp(0.00) Quality: ok a: +0.0000\|*******************************************************\| +1.0000 Z=-inf(0.00%) \| Like=-1245.39..3.65 [-1245.3896..-308.0711] \| it/evals=0/3621 eff=inf% N=400 Z=-990.5(0.00%) \| Like=-981.54..3.68 [-1245.3896..-308.0711] \| it/evals=50/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-4.34) Expected Volume: exp(-0.23) Quality: ok a: +0.00\| ********************************************** \| +1.00 Z=-861.8(0.00%) \| Like=-854.74..3.68 [-1245.3896..-308.0711] \| it/evals=90/3621 eff=inf% N=400 Z=-823.2(0.00%) \| Like=-812.27..3.68 [-1245.3896..-308.0711] \| it/evals=100/3621 eff=inf% N=400 Z=-630.1(0.00%) \| Like=-620.09..3.68 [-1245.3896..-308.0711] \| it/evals=150/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-4.34) Expected Volume: exp(-0.45) Quality: ok a: +0.0\| ************************************ \| +1.0 Z=-513.4(0.00%) \| Like=-505.92..3.69 [-1245.3896..-308.0711] \| it/evals=200/3621 eff=inf% N=400 Z=-393.4(0.00%) \| Like=-383.84..3.69 [-1245.3896..-308.0711] \| it/evals=250/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-4.93) * Expected Volume: exp(-0.67) Quality: ok a: +0.0\| +0.2 **************************** +0.8 \| +1.0 Z=-354.3(0.00%) \| Like=-347.23..3.69 [-1245.3896..-308.0711] \| it/evals=270/3621 eff=inf% N=400 Z=-308.5(0.00%) \| Like=-296.59..3.69 [-307.5524..-75.4168] \| it/evals=300/3621 eff=inf% N=400 Z=-241.3(0.00%) \| Like=-233.94..3.69 [-307.5524..-75.4168] \| it/evals=350/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-4.93) Expected Volume: exp(-0.90) Quality: ok a: +0.0\| +0.3 ********************** +0.7 \| +1.0 Z=-195.0(0.00%) \| Like=-187.11..3.69 [-307.5524..-75.4168] \| it/evals=400/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.12) Quality: ok a: +0.0\| +0.3 ******************** +0.7 \| +1.0 Z=-148.8(0.00%) \| Like=-141.92..3.69 [-307.5524..-75.4168] \| it/evals=450/3621 eff=inf% N=400 Z=-119.5(0.00%) \| Like=-113.36..3.69 [-307.5524..-75.4168] \| it/evals=500/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-5.40) * Expected Volume: exp(-1.35) Quality: ok a: +0.0\| +0.4 ************** +0.6 \| +1.0 Z=-98.3(0.00%) \| Like=-90.77..3.69 [-307.5524..-75.4168] \| it/evals=540/3621 eff=inf% N=400 Z=-91.6(0.00%) \| Like=-85.36..3.69 [-307.5524..-75.4168] \| it/evals=550/3621 eff=inf% N=400 Z=-70.1(0.00%) \| Like=-63.21..3.69 [-75.3486..-15.0754] \| it/evals=600/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-5.40) Expected Volume: exp(-1.57) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-53.3(0.00%) \| Like=-47.34..3.69 [-75.3486..-15.0754] \| it/evals=650/3621 eff=inf% N=400 Z=-42.1(0.00%) \| Like=-35.02..3.69 [-75.3486..-15.0754] \| it/evals=700/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-6.18) * Expected Volume: exp(-1.80) Quality: ok a: +0.0\| +0.4 ********** +0.6 \| +1.0 Z=-37.6(0.00%) \| Like=-31.23..3.69 [-75.3486..-15.0754] \| it/evals=720/3621 eff=inf% N=400 Z=-32.8(0.00%) \| Like=-26.86..3.69 [-75.3486..-15.0754] \| it/evals=750/3621 eff=inf% N=400 Z=-26.3(0.00%) \| Like=-20.36..3.69 [-75.3486..-15.0754] \| it/evals=800/3621 eff=inf% N=400 Have 2 modes Volume: ~exp(-6.24) * Expected Volume: exp(-2.02) Quality: ok a: +0.0\| +0.4 11111222 +0.6 \| +1.0 Z=-25.2(0.00%) \| Like=-19.53..3.69 [-75.3486..-15.0754] \| it/evals=810/3621 eff=inf% N=400 Z=-21.1(0.00%) \| Like=-15.13..3.69 [-75.3486..-15.0754] \| it/evals=850/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-6.39) * Expected Volume: exp(-2.25) Quality: ok a: +0.0\| +0.4 ******** +0.6 \| +1.0 Z=-16.7(0.00%) \| Like=-11.04..3.69 [-14.9390..-1.0650] \| it/evals=900/3621 eff=inf% N=400 Z=-13.4(0.00%) \| Like=-8.20..3.69 [-14.9390..-1.0650] \| it/evals=950/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-6.52) * Expected Volume: exp(-2.47) Quality: ok a: +0.00\| +0.46 ****** +0.54 \| +1.00 Z=-11.5(0.00%) \| Like=-5.86..3.69 [-14.9390..-1.0650] \| it/evals=990/3621 eff=inf% N=400 Z=-10.9(0.00%) \| Like=-5.22..3.69 [-14.9390..-1.0650] \| it/evals=1000/3621 eff=inf% N=400 Z=-8.3(0.03%) \| Like=-2.98..3.69 [-14.9390..-1.0650] \| it/evals=1050/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-6.96) * Expected Volume: exp(-2.70) Quality: ok a: +0.00\| +0.47 **** +0.53 \| +1.00 Z=-7.3(0.07%) \| Like=-2.03..3.69 [-14.9390..-1.0650] \| it/evals=1080/3621 eff=inf% N=400 Z=-6.7(0.12%) \| Like=-1.69..3.69 [-14.9390..-1.0650] \| it/evals=1100/3621 eff=inf% N=400 Z=-5.5(0.40%) \| Like=-0.52..3.69 [-1.0420..1.4103] \| it/evals=1150/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-6.97) * Expected Volume: exp(-2.92) Quality: ok a: +0.00\| +0.47 **** +0.53 \| +1.00 Z=-5.1(0.60%) \| Like=-0.15..3.69 [-1.0420..1.4103] \| it/evals=1170/3621 eff=inf% N=400 Z=-4.5(1.08%) \| Like=0.49..3.69 [-1.0420..1.4103] \| it/evals=1200/3621 eff=inf% N=400 Z=-3.7(2.59%) \| Like=1.31..3.69 [-1.0420..1.4103] \| it/evals=1250/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-7.41) * Expected Volume: exp(-3.15) Quality: ok a: +0.00\| +0.48 **** +0.52 \| +1.00 Z=-3.5(3.02%) \| Like=1.42..3.69 [1.4124..1.7038] \| it/evals=1260/3621 eff=inf% N=400 Z=-3.0(5.15%) \| Like=1.82..3.69 [1.8072..1.8177] \| it/evals=1300/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-7.73) * Expected Volume: exp(-3.37) Quality: ok a: +0.00\| +0.48 ** +0.52 \| +1.00 Z=-2.5(8.76%) \| Like=2.20..3.69 [2.1997..2.2038]\| it/evals=1350/3621 eff=inf% N=400 Z=-2.0(13.34%) \| Like=2.53..3.69 [2.5278..2.5282]\| it/evals=1400/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-7.73) Expected Volume: exp(-3.60) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.7(18.31%) \| Like=2.78..3.69 [2.7629..2.7785] \| it/evals=1450/3621 eff=inf% N=400 Z=-1.4(23.98%) \| Like=2.99..3.69 [2.9857..2.9912]\| it/evals=1500/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.24) Expected Volume: exp(-3.82) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-1.3(27.63%) \| Like=3.09..3.69 [3.0871..3.0878]\| it/evals=1530/3621 eff=inf% N=400 Z=-1.2(30.05%) \| Like=3.13..3.69 [3.1343..3.1384]\| it/evals=1550/3621 eff=inf% N=400 Z=-1.0(36.04%) \| Like=3.23..3.69 [3.2338..3.2374]\| it/evals=1600/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.24) Expected Volume: exp(-4.05) Quality: ok a: +0.00\| +0.49 * +0.51 \| +1.00 Z=-0.9(41.87%) \| Like=3.33..3.69 [3.3257..3.3279]\| it/evals=1650/3621 eff=inf% N=400 Z=-0.8(47.43%) \| Like=3.40..3.69 [3.4041..3.4052]\| it/evals=1700/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.29) * Expected Volume: exp(-4.27) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.7(48.51%) \| Like=3.42..3.69 [3.4158..3.4202]\| it/evals=1710/3621 eff=inf% N=400 Z=-0.7(52.66%) \| Like=3.46..3.69 [3.4553..3.4578]\| it/evals=1750/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.55) * Expected Volume: exp(-4.50) Quality: ok a: +0.00\| +0.49 ** +0.51 \| +1.00 Z=-0.6(57.51%) \| Like=3.51..3.69 [3.5118..3.5138]\| it/evals=1800/3621 eff=inf% N=400 Z=-0.5(62.04%) \| Like=3.55..3.69 [3.5533..3.5544]\| it/evals=1850/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.55) Expected Volume: exp(-4.73) Quality: ok a: +0.000\| +0.495 ** +0.505 \| +1.000 Z=-0.4(66.17%) \| Like=3.58..3.69 [3.5809..3.5814]\| it/evals=1900/3621 eff=inf% N=400 Z=-0.4(69.91%) \| Like=3.61..3.69 [3.6080..3.6080]\| it/evals=1950/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-8.94) * Expected Volume: exp(-4.95) Quality: ok a: +0.000\| +0.496 ** +0.504 \| +1.000 Z=-0.3(71.98%) \| Like=3.62..3.69 [3.6159..3.6159]\| it/evals=1980/3621 eff=inf% N=400 Z=-0.3(73.29%) \| Like=3.63..3.69 [3.6253..3.6255]\| it/evals=2000/3621 eff=inf% N=400 Z=-0.3(76.32%) \| Like=3.64..3.69 [3.6374..3.6374]\| it/evals=2050/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-9.16) Expected Volume: exp(-5.18) Quality: ok a: +0.000\| +0.497 ** +0.503 \| +1.000 Z=-0.3(77.44%) \| Like=3.64..3.69 [3.6435..3.6437]\| it/evals=2070/3621 eff=inf% N=400 Z=-0.2(79.03%) \| Like=3.65..3.69 [3.6499..3.6499]\| it/evals=2100/3621 eff=inf% N=400 Z=-0.2(81.44%) \| Like=3.66..3.69 [3.6581..3.6582]\| it/evals=2150/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-9.48) Expected Volume: exp(-5.40) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.2(81.89%) \| Like=3.66..3.69 [3.6591..3.6591]\| it/evals=2160/3621 eff=inf% N=400 Z=-0.2(83.59%) \| Like=3.66..3.69 [3.6638..3.6640]\| it/evals=2200/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-9.67) * Expected Volume: exp(-5.63) Quality: ok a: +0.000\| +0.498 ** +0.502 \| +1.000 Z=-0.2(85.49%) \| Like=3.67..3.69 [3.6689..3.6690]\| it/evals=2250/3621 eff=inf% N=400 Z=-0.2(87.18%) \| Like=3.67..3.69 [3.6731..3.6731]\| it/evals=2300/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-9.90) * Expected Volume: exp(-5.85) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(88.39%) \| Like=3.68..3.69 [3.6754..3.6754]\| it/evals=2340/3621 eff=inf% N=400 Z=-0.1(88.68%) \| Like=3.68..3.69 [3.6759..3.6759]\| it/evals=2350/3621 eff=inf% N=400 Z=-0.1(90.00%) \| Like=3.68..3.69 [3.6785..3.6786]\| it/evals=2400/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-10.13) Expected Volume: exp(-6.08) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(90.72%) \| Like=3.68..3.69 [3.6795..3.6795]\| it/evals=2430/3621 eff=inf% N=400 Z=-0.1(91.17%) \| Like=3.68..3.69 [3.6801..3.6802]\| it/evals=2450/3621 eff=inf% N=400 Z=-0.1(92.20%) \| Like=3.68..3.69 [3.6816..3.6817]\| it/evals=2500/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-10.15) Expected Volume: exp(-6.30) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(92.58%) \| Like=3.68..3.69 [3.6821..3.6821]\| it/evals=2520/3621 eff=inf% N=400 Z=-0.1(93.12%) \| Like=3.68..3.69 [3.6826..3.6827]\| it/evals=2550/3621 eff=inf% N=400 Z=-0.1(93.92%) \| Like=3.68..3.69 [3.6835..3.6835]\| it/evals=2600/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-10.65) Expected Volume: exp(-6.53) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(94.07%) \| Like=3.68..3.69 [3.6837..3.6837]\| it/evals=2610/3621 eff=inf% N=400 Z=-0.1(94.64%) \| Like=3.68..3.69 [3.6840..3.6840]\| it/evals=2650/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-10.65) Expected Volume: exp(-6.75) Quality: ok a: +0.000\| +0.499 ** +0.501 \| +1.000 Z=-0.1(95.27%) \| Like=3.68..3.69 [3.6845..3.6845]\| it/evals=2700/3621 eff=inf% N=400 Z=-0.1(95.82%) \| Like=3.68..3.69 [3.6848..3.6848]\| it/evals=2750/3621 eff=inf% N=400 Mono-modal Volume: ~exp(-11.12) * Expected Volume: exp(-6.98) Quality: ok a: +0.0000\| +0.4995 ** +0.5005 \| +1.0000 Z=-0.1(96.22%) \| Like=3.69..3.69 [3.6850..3.6850]\| it/evals=2790/3621 eff=inf% N=400 Z=-0.1(96.31%) \| Like=3.69..3.69 [3.6851..3.6851]\| it/evals=2800/3621 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3621 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.02627 +- 0.05466 [ultranest] Effective samples strategy satisfied (ESS = 1260.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.11 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <2.0) [ultranest] logZ error budget: single: 0.09 bs:0.05 tail:0.03 total:0.06 required:<2.00 [ultranest] done iterating. logZ = -0.014 +- 0.090 single instance: logZ = -0.014 +- 0.090 bootstrapped : logZ = -0.026 +- 0.084 tail : logZ = +- 0.034 insert order U test : converged: True correlation: inf iterations a : 0.463 │ ▁▁▁▁▁▁▁▂▂▃▂▃▄▅▅▆▇▇▆▆▆▆▆▅▃▃▂▂▁▁▁▁▁▁ ▁▁ │0.540 0.500 +- 0.010 ran with dlogz: 2.0 first run gave: {'niter': 3220, 'logz': -0.013974183723283412, 'logzerr': 0.10971812979089553, 'logz_bs': -0.012503866119405762, 'logz_single': -0.013974183723283412, 'logzerr_tail': 0.034478189717984345, 'logzerr_bs': 0.10416008083033766, 'ess': 1260.1962170536074, 'H': 3.2089858433621017, 'Herr': 0.054320577938106775, 'posterior': {'mean': [0.50045629571788], 'stdev': [0.010089509001508892], 'median': [0.5005430939745008], 'errlo': [0.4901097186137824], 'errup': [0.5105344881403425], 'information_gain_bits': [3.4862496598894177]}, 'maximum_likelihood': {'logl': 3.6862314817507196, 'point': [0.5000058486357236], 'point_untransformed': [0.5000058486357236]}, 'ncall': 3621, 'paramnames': ['a'], 'logzerr_single': 0.08956821204202557, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3220, 'logz': -0.013974183723283412, 'logzerr': 0.0903799134925259, 'logz_bs': -0.0262673710346743, 'logz_single': -0.013974183723283412, 'logzerr_tail': 0.034478189717984345, 'logzerr_bs': 0.0835450967842347, 'ess': 1260.1962170536074, 'H': 3.2089858433621017, 'Herr': 0.050998096489361884, 'posterior': {'mean': [0.500204894544299], 'stdev': [0.010073574516258744], 'median': [0.5001395437994671], 'errlo': [0.4899393034588605], 'errup': [0.5105068093450308], 'information_gain_bits': [3.4862496598894177]}, 'maximum_likelihood': {'logl': 3.6862314817507196, 'point': [0.5000058486357236], 'point_untransformed': [0.5000058486357236]}, 'ncall': 3621, 'paramnames': ['a'], 'logzerr_single': 0.08956821204202557, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpvj51xjmp, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=2.0, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1245.39, Lmax=3.65 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=528, regioncalls=128, ndraw=128, logz=-990.55, remainder_fraction=100.0000%, Lmin=-981.54, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-861.82, remainder_fraction=100.0000%, Lmin=-854.74, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=528, regioncalls=128, ndraw=128, logz=-823.22, remainder_fraction=100.0000%, Lmin=-812.27, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=633, regioncalls=256, ndraw=128, logz=-630.08, remainder_fraction=100.0000%, Lmin=-620.09, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=633, regioncalls=256, ndraw=128, logz=-552.14, remainder_fraction=100.0000%, Lmin=-543.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=633, regioncalls=256, ndraw=128, logz=-513.45, remainder_fraction=100.0000%, Lmin=-505.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=728, regioncalls=384, ndraw=128, logz=-393.37, remainder_fraction=100.0000%, Lmin=-383.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=792, regioncalls=512, ndraw=128, logz=-308.52, remainder_fraction=100.0000%, Lmin=-296.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=853, regioncalls=640, ndraw=128, logz=-241.25, remainder_fraction=100.0000%, Lmin=-233.94, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=853, regioncalls=640, ndraw=128, logz=-231.21, remainder_fraction=100.0000%, Lmin=-222.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=903, regioncalls=768, ndraw=128, logz=-195.03, remainder_fraction=100.0000%, Lmin=-187.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=951, regioncalls=896, ndraw=128, logz=-148.82, remainder_fraction=100.0000%, Lmin=-141.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=986, regioncalls=1024, ndraw=128, logz=-119.52, remainder_fraction=100.0000%, Lmin=-113.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1035, regioncalls=1152, ndraw=128, logz=-98.29, remainder_fraction=100.0000%, Lmin=-90.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1035, regioncalls=1152, ndraw=128, logz=-91.55, remainder_fraction=100.0000%, Lmin=-85.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1076, regioncalls=1280, ndraw=128, logz=-70.08, remainder_fraction=100.0000%, Lmin=-63.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1109, regioncalls=1408, ndraw=128, logz=-60.19, remainder_fraction=100.0000%, Lmin=-53.09, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1144, regioncalls=1536, ndraw=128, logz=-53.27, remainder_fraction=100.0000%, Lmin=-47.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1194, regioncalls=1792, ndraw=128, logz=-42.12, remainder_fraction=100.0000%, Lmin=-35.02, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1221, regioncalls=1920, ndraw=128, logz=-37.57, remainder_fraction=100.0000%, Lmin=-31.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1245, regioncalls=2048, ndraw=128, logz=-32.76, remainder_fraction=100.0000%, Lmin=-26.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1305, regioncalls=2432, ndraw=128, logz=-26.30, remainder_fraction=100.0000%, Lmin=-20.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1305, regioncalls=2432, ndraw=128, logz=-25.21, remainder_fraction=100.0000%, Lmin=-19.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1356, regioncalls=2816, ndraw=128, logz=-21.13, remainder_fraction=100.0000%, Lmin=-15.13, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1405, regioncalls=3200, ndraw=128, logz=-16.70, remainder_fraction=100.0000%, Lmin=-11.04, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1451, regioncalls=3584, ndraw=128, logz=-13.44, remainder_fraction=99.9998%, Lmin=-8.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1493, regioncalls=3968, ndraw=128, logz=-11.50, remainder_fraction=99.9989%, Lmin=-5.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1513, regioncalls=4096, ndraw=128, logz=-10.90, remainder_fraction=99.9981%, Lmin=-5.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1562, regioncalls=4608, ndraw=128, logz=-8.32, remainder_fraction=99.9749%, Lmin=-2.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1597, regioncalls=5120, ndraw=128, logz=-7.28, remainder_fraction=99.9295%, Lmin=-2.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1613, regioncalls=5376, ndraw=128, logz=-6.74, remainder_fraction=99.8799%, Lmin=-1.69, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1659, regioncalls=6272, ndraw=128, logz=-5.54, remainder_fraction=99.6023%, Lmin=-0.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1716, regioncalls=7040, ndraw=128, logz=-4.54, remainder_fraction=98.9163%, Lmin=0.49, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1767, regioncalls=8064, ndraw=128, logz=-3.67, remainder_fraction=97.4064%, Lmin=1.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1774, regioncalls=8320, ndraw=128, logz=-3.52, remainder_fraction=96.9803%, Lmin=1.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1821, regioncalls=9344, ndraw=128, logz=-2.98, remainder_fraction=94.8457%, Lmin=1.82, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1868, regioncalls=10752, ndraw=128, logz=-2.46, remainder_fraction=91.2395%, Lmin=2.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1917, regioncalls=12416, ndraw=128, logz=-2.04, remainder_fraction=86.6574%, Lmin=2.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1963, regioncalls=14208, ndraw=128, logz=-1.77, remainder_fraction=82.7497%, Lmin=2.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1973, regioncalls=14464, ndraw=128, logz=-1.71, remainder_fraction=81.6948%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2026, regioncalls=16640, ndraw=128, logz=-1.44, remainder_fraction=76.0250%, Lmin=2.99, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2055, regioncalls=17792, ndraw=128, logz=-1.30, remainder_fraction=72.3720%, Lmin=3.09, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2073, regioncalls=18688, ndraw=128, logz=-1.22, remainder_fraction=69.9531%, Lmin=3.13, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1599, ncalls=2231, regioncalls=20480, ndraw=128, logz=-1.04, remainder_fraction=64.0901%, Lmin=3.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2231, regioncalls=20480, ndraw=128, logz=-1.04, remainder_fraction=63.9580%, Lmin=3.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2231, regioncalls=20480, ndraw=128, logz=-0.97, remainder_fraction=61.6166%, Lmin=3.27, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2231, regioncalls=20480, ndraw=128, logz=-0.89, remainder_fraction=58.1268%, Lmin=3.33, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2246, regioncalls=21120, ndraw=128, logz=-0.76, remainder_fraction=52.5721%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2257, regioncalls=21248, ndraw=128, logz=-0.74, remainder_fraction=51.4935%, Lmin=3.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2403, regioncalls=23040, ndraw=128, logz=-0.66, remainder_fraction=47.3443%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2403, regioncalls=23040, ndraw=128, logz=-0.57, remainder_fraction=42.4866%, Lmin=3.51, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2505, regioncalls=23168, ndraw=128, logz=-0.49, remainder_fraction=37.9595%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2505, regioncalls=23168, ndraw=128, logz=-0.44, remainder_fraction=34.6221%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2505, regioncalls=23168, ndraw=128, logz=-0.43, remainder_fraction=33.8290%, Lmin=3.58, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2537, regioncalls=24448, ndraw=128, logz=-0.37, remainder_fraction=30.0871%, Lmin=3.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2569, regioncalls=25088, ndraw=128, logz=-0.34, remainder_fraction=28.0168%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2705, regioncalls=26240, ndraw=128, logz=-0.32, remainder_fraction=26.7118%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=2705, regioncalls=26240, ndraw=128, logz=-0.28, remainder_fraction=23.6800%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2705, regioncalls=26240, ndraw=128, logz=-0.27, remainder_fraction=22.5589%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=2722, regioncalls=26496, ndraw=128, logz=-0.25, remainder_fraction=20.9745%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2758, regioncalls=27136, ndraw=128, logz=-0.22, remainder_fraction=18.5586%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=2776, regioncalls=27392, ndraw=128, logz=-0.21, remainder_fraction=18.1081%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2904, regioncalls=27648, ndraw=128, logz=-0.19, remainder_fraction=16.4125%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=2904, regioncalls=27648, ndraw=128, logz=-0.17, remainder_fraction=14.5086%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=2926, regioncalls=28032, ndraw=128, logz=-0.15, remainder_fraction=12.8198%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2970, regioncalls=28800, ndraw=128, logz=-0.14, remainder_fraction=11.6097%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=3090, regioncalls=29056, ndraw=128, logz=-0.13, remainder_fraction=11.3250%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3090, regioncalls=29056, ndraw=128, logz=-0.12, remainder_fraction=10.0021%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3090, regioncalls=29056, ndraw=128, logz=-0.11, remainder_fraction=9.2822%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3217, regioncalls=29312, ndraw=128, logz=-0.11, remainder_fraction=8.8316%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3217, regioncalls=29312, ndraw=128, logz=-0.10, remainder_fraction=7.7971%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3217, regioncalls=29312, ndraw=128, logz=-0.09, remainder_fraction=6.8836%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3312, regioncalls=29440, ndraw=128, logz=-0.08, remainder_fraction=6.0763%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3312, regioncalls=29440, ndraw=128, logz=-0.08, remainder_fraction=5.9265%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3330, regioncalls=29824, ndraw=128, logz=-0.07, remainder_fraction=5.3633%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3384, regioncalls=30592, ndraw=128, logz=-0.06, remainder_fraction=4.7339%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3512, regioncalls=30848, ndraw=128, logz=-0.06, remainder_fraction=4.1782%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3512, regioncalls=30848, ndraw=128, logz=-0.05, remainder_fraction=3.6877%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3621 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -0.0125 +- 0.06231 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1260.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.07, need <2.0) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.06 tail:0.03 total:0.07 required:<2.00 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpvj51xjmp, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [3.68518867 3.68614504 0. 0.50013161 0.50013161]: u=[0.50013161] -> p=[0.50013161] -> L=3.6861450405247025 INFO ultranest:integrator.py:2364 Resuming from 3531 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=2.0, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=3621, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1245.39, Lmax=3.65 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=3621, regioncalls=0, ndraw=128, logz=-990.55, remainder_fraction=100.0000%, Lmin=-981.54, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=3621, regioncalls=0, ndraw=128, logz=-861.82, remainder_fraction=100.0000%, Lmin=-854.74, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=3621, regioncalls=0, ndraw=128, logz=-823.22, remainder_fraction=100.0000%, Lmin=-812.27, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=3621, regioncalls=0, ndraw=128, logz=-630.08, remainder_fraction=100.0000%, Lmin=-620.09, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=3621, regioncalls=0, ndraw=128, logz=-513.45, remainder_fraction=100.0000%, Lmin=-505.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3621, regioncalls=0, ndraw=128, logz=-393.37, remainder_fraction=100.0000%, Lmin=-383.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=3621, regioncalls=0, ndraw=128, logz=-354.34, remainder_fraction=100.0000%, Lmin=-347.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=3621, regioncalls=0, ndraw=128, logz=-308.52, remainder_fraction=100.0000%, Lmin=-296.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=3621, regioncalls=0, ndraw=128, logz=-241.25, remainder_fraction=100.0000%, Lmin=-233.94, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=3621, regioncalls=0, ndraw=128, logz=-195.03, remainder_fraction=100.0000%, Lmin=-187.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3621, regioncalls=0, ndraw=128, logz=-148.82, remainder_fraction=100.0000%, Lmin=-141.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3621, regioncalls=0, ndraw=128, logz=-119.52, remainder_fraction=100.0000%, Lmin=-113.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=3621, regioncalls=0, ndraw=128, logz=-98.29, remainder_fraction=100.0000%, Lmin=-90.77, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3621, regioncalls=0, ndraw=128, logz=-91.55, remainder_fraction=100.0000%, Lmin=-85.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=3621, regioncalls=0, ndraw=128, logz=-70.08, remainder_fraction=100.0000%, Lmin=-63.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=3621, regioncalls=0, ndraw=128, logz=-53.27, remainder_fraction=100.0000%, Lmin=-47.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=3621, regioncalls=0, ndraw=128, logz=-42.12, remainder_fraction=100.0000%, Lmin=-35.02, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=3621, regioncalls=0, ndraw=128, logz=-37.57, remainder_fraction=100.0000%, Lmin=-31.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=3621, regioncalls=0, ndraw=128, logz=-32.76, remainder_fraction=100.0000%, Lmin=-26.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=3621, regioncalls=0, ndraw=128, logz=-26.30, remainder_fraction=100.0000%, Lmin=-20.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=3621, regioncalls=0, ndraw=128, logz=-25.21, remainder_fraction=100.0000%, Lmin=-19.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=3621, regioncalls=0, ndraw=128, logz=-21.13, remainder_fraction=100.0000%, Lmin=-15.13, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=3621, regioncalls=0, ndraw=128, logz=-16.70, remainder_fraction=100.0000%, Lmin=-11.04, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=3621, regioncalls=0, ndraw=128, logz=-13.44, remainder_fraction=99.9998%, Lmin=-8.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=3621, regioncalls=0, ndraw=128, logz=-11.50, remainder_fraction=99.9989%, Lmin=-5.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=3621, regioncalls=0, ndraw=128, logz=-10.90, remainder_fraction=99.9981%, Lmin=-5.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=3621, regioncalls=0, ndraw=128, logz=-8.32, remainder_fraction=99.9749%, Lmin=-2.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=3621, regioncalls=0, ndraw=128, logz=-7.28, remainder_fraction=99.9295%, Lmin=-2.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=3621, regioncalls=0, ndraw=128, logz=-6.74, remainder_fraction=99.8799%, Lmin=-1.69, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=3621, regioncalls=0, ndraw=128, logz=-5.54, remainder_fraction=99.6023%, Lmin=-0.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=3621, regioncalls=0, ndraw=128, logz=-5.13, remainder_fraction=99.4025%, Lmin=-0.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=3621, regioncalls=0, ndraw=128, logz=-4.54, remainder_fraction=98.9163%, Lmin=0.49, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=3621, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=97.4064%, Lmin=1.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=3621, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=96.9803%, Lmin=1.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=3621, regioncalls=0, ndraw=128, logz=-2.98, remainder_fraction=94.8457%, Lmin=1.82, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=3621, regioncalls=0, ndraw=128, logz=-2.46, remainder_fraction=91.2395%, Lmin=2.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=3621, regioncalls=0, ndraw=128, logz=-2.04, remainder_fraction=86.6574%, Lmin=2.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=3621, regioncalls=0, ndraw=128, logz=-1.71, remainder_fraction=81.6948%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=3621, regioncalls=0, ndraw=128, logz=-1.44, remainder_fraction=76.0250%, Lmin=2.99, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3621, regioncalls=0, ndraw=128, logz=-1.30, remainder_fraction=72.3720%, Lmin=3.09, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=3621, regioncalls=0, ndraw=128, logz=-1.22, remainder_fraction=69.9531%, Lmin=3.13, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=3621, regioncalls=0, ndraw=128, logz=-1.04, remainder_fraction=63.9580%, Lmin=3.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.89, remainder_fraction=58.1268%, Lmin=3.33, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.76, remainder_fraction=52.5721%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.74, remainder_fraction=51.4935%, Lmin=3.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.66, remainder_fraction=47.3443%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.57, remainder_fraction=42.4866%, Lmin=3.51, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.49, remainder_fraction=37.9595%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.43, remainder_fraction=33.8290%, Lmin=3.58, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.37, remainder_fraction=30.0871%, Lmin=3.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.34, remainder_fraction=28.0168%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.32, remainder_fraction=26.7118%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.28, remainder_fraction=23.6800%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.27, remainder_fraction=22.5589%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.25, remainder_fraction=20.9745%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.22, remainder_fraction=18.5586%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.21, remainder_fraction=18.1081%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.19, remainder_fraction=16.4125%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.17, remainder_fraction=14.5086%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.15, remainder_fraction=12.8198%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.14, remainder_fraction=11.6097%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.13, remainder_fraction=11.3250%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.12, remainder_fraction=10.0021%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.11, remainder_fraction=9.2822%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.11, remainder_fraction=8.8316%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.10, remainder_fraction=7.7971%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.09, remainder_fraction=7.4181%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.09, remainder_fraction=6.8836%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.08, remainder_fraction=6.0763%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.08, remainder_fraction=5.9265%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.07, remainder_fraction=5.3633%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.06, remainder_fraction=4.7339%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.06, remainder_fraction=4.1782%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.05, remainder_fraction=3.7809%, Lmin=3.69, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3621, regioncalls=0, ndraw=128, logz=-0.05, remainder_fraction=3.6877%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3621 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -0.02627 +- 0.05466 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1260.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.11 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <2.0) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.05 tail:0.03 total:0.06 required:<2.00 INFO ultranest:integrator.py:2307 done iterating.
Passed	tests/test_samplingpath.py::test_horizontal	0.00
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ (array([0.5, 0. ]), array([1])) (array([0.5, 1. ]), array([1])) (array([0. , 0.3]), array([0])) (array([1. , 0.3]), array([0]))
Passed	tests/test_samplingpath.py::test_corner	0.00
[gw2] linux -- Python 3.10.6 /usr/bin/python3 [gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ starting ray: [0.6 0.5] [0.4 0.5] (array([0.2, 0. ]), array([1])) (array([1., 1.]), array([0, 1])) restarting ray: [1. 1.] [-0.4 -0.5] (array([1., 1.]), array([0, 1])) (array([0.2, 0. ]), array([1])) (array([0.2, 0. ]), array([1])) (array([0. , 0.25]), array([0]))
Passed	tests/test_stepsampling.py::test_stepsampler_regionmh_adapt	0.25
[gw0] linux -- Python 3.10.6 /usr/bin/python3 [gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ MHSampler(nsteps=3, generate_direction=<function generate_region_random_direction at 0x7f2288204e50>) ineffective proposal scale (1.21). shrinking... ineffective proposal scale (0.880663). shrinking... ineffective proposal scale (0.640965). shrinking... MHSampler(adaptive_nsteps=move-distance, generate_direction=<function generate_region_random_direction at 0x7f2288204e50>) MHSampler(adaptive_nsteps=proposal-total-distances, generate_direction=<function generate_region_random_direction at 0x7f2288204e50>) MHSampler(adaptive_nsteps=proposal-summed-distances, generate_direction=<function generate_region_random_direction at 0x7f2288204e50>) MHSampler(nsteps=3, generate_direction=<function generate_random_direction at 0x7f2288204af0>) ineffective proposal scale (1.21). shrinking... MHSampler(adaptive_nsteps=move-distance, generate_direction=<function generate_random_direction at 0x7f2288204af0>) MHSampler(adaptive_nsteps=proposal-total-distances, generate_direction=<function generate_random_direction at 0x7f2288204af0>) MHSampler(adaptive_nsteps=proposal-summed-distances, generate_direction=<function generate_random_direction at 0x7f2288204af0>) SliceSampler(nsteps=3, generate_direction=<function generate_cube_oriented_direction at 0x7f2288204b80>) SliceSampler(adaptive_nsteps=move-distance, generate_direction=<function generate_cube_oriented_direction at 0x7f2288204b80>) SliceSampler(adaptive_nsteps=proposal-total-distances, generate_direction=<function generate_cube_oriented_direction at 0x7f2288204b80>) SliceSampler(adaptive_nsteps=proposal-summed-distances, generate_direction=<function generate_cube_oriented_direction at 0x7f2288204b80>) SliceSampler(nsteps=3, generate_direction=<function generate_region_oriented_direction at 0x7f2288204dc0>) SliceSampler(adaptive_nsteps=move-distance, generate_direction=<function generate_region_oriented_direction at 0x7f2288204dc0>) SliceSampler(adaptive_nsteps=proposal-total-distances, generate_direction=<function generate_region_oriented_direction at 0x7f2288204dc0>) SliceSampler(adaptive_nsteps=proposal-summed-distances, generate_direction=<function generate_region_oriented_direction at 0x7f2288204dc0>)
Passed	tests/test_stepsampling.py::test_ellipsoid_bracket	0.26
[gw0] linux -- Python 3.10.6 /usr/bin/python3 [gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3 ------------------------------Captured stdout call------------------------------ seed: 0 [0.50992628 0.49615106] 0.8846954103224107 [[0.01926479 0.00029866] [0.00029866 0.02059322]] [[51.91984507 -0.75298154] [-0.75298154 48.57059161]] [[-0.03014079 -0.13548551] [-0.14053046 0.02905876]] [[-7.05626717 1.45908831] [ 1.51341904 6.80295189]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.017174902905080985 0.23786423427151487 seed: 1 [0.50159445 0.47100674] 1.8743099471353246 [[ 0.33611853 -0.03266527] [-0.03266527 0.34105515]] [[3.00309364 0.28762753] [0.28762753 2.95962525]] [[ 0.41434574 -0.40550726] [-0.44683648 -0.37602169]] [[-1.32593047 -1.11579659] [-1.22951834 1.20329128]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6917900617926906 0.8846363293094491 seed: 2 [0.48812653 0.53575766] 20.38450684976214 [[ 0.02882855 -0.00164512] [-0.00164512 0.01039618]] [[35.00392418 5.53912476] [ 5.53912476 97.06571607]] [[-0.16955471 0.00893047] [ 0.01501439 0.10085012]] [[-0.87122291 -5.85191377] [-9.83855613 0.51819813]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6730808254214168 0.8527385288859411 seed: 3 [0.47230407 0.50830476] 2.0192802558538405 [[0.30519242 0.02950729] [0.02950729 0.30154492]] [[ 3.30791723 -0.32369199] [-0.32369199 3.34792997]] [[-0.42039895 -0.35840918] [-0.39521765 0.38124524]] [[ 1.30899395 -1.26271615] [-1.39239654 -1.18708124]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7071890735938766 0.855064597755619 seed: 4 [0.50099605 0.49480303] 1.0789338425112094 [[ 0.02212739 -0.00207538] [-0.00207538 0.01904731]] [[45.65946589 4.9750119 ] [ 4.9750119 53.04291745]] [[-0.1359778 0.06031112] [ 0.06842332 0.11985642]] [[-3.35006084 -5.86826706] [-6.65758288 2.95288126]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.052565699606072866 0.24797734092031085 seed: 5 [0.49104398 0.55215679] 2.0230339684412333 [[0.37506221 0.01679208] [0.01679208 0.33671203]] [[ 2.67219079 -0.13326413] [-0.13326413 2.97654281]] [[-0.57805143 -0.20228385] [-0.21732937 0.53803344]] [[ 0.61224159 -1.5157015 ] [-1.62843674 -0.56985664]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7799365812711072 0.9593158783831075 seed: 6 [0.52418964 0.50030038] 2.1457304801032278 [[ 0.018437 -0.00089551] [-0.00089551 0.0204369 ]] [[54.35445482 2.38173058] [ 2.38173058 49.03546901]] [[ 0.05147825 -0.12564627] [-0.13464496 -0.04803782]] [[-6.94384782 -2.47738415] [-2.65481249 6.47977157]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.07419300769210857 0.3204076821837687 seed: 7 [0.484248 0.51819016] 1.8539629878442634 [[0.3042633 0.01242581] [0.01242581 0.34076343]] [[ 3.29152877 -0.12002437] [-0.12002437 2.93896385]] [[-0.17284996 -0.52381885] [-0.56099455 0.16139563]] [[-1.74353623 0.5016076 ] [ 0.53720694 1.62799648]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6659778758876831 0.8349705094435842 seed: 8 [0.50408499 0.49428346] 0.9655037157675875 [[ 0.02323618 -0.00217529] [-0.00217529 0.01719814]] [[43.55202481 5.50863067] [ 5.50863067 58.8425811 ]] [[-0.14724143 0.03944802] [ 0.04752047 0.12222906]] [[-2.39135596 -6.15088949] [-7.40957792 1.98512876]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.044400678705535615 0.2448003575805587 seed: 9 [0.48904592 0.48752116] 1.5384778143104043 [[ 0.35830766 -0.02034459] [-0.02034459 0.3526576 ]] [[2.80006946 0.16153418] [0.16153418 2.84493043]] [[-0.46246098 0.38004934] [ 0.40268134 0.43646917]] [[-1.13466924 -1.22987608] [-1.3031154 1.07089714]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6534001039705724 0.8271676775022705 seed: 10 [0.48019733 0.48916557] 2.9213240856230063 [[ 0.02687924 -0.00160957] [-0.00160957 0.01361342]] [[37.46870819 4.43008875] [ 4.43008875 73.98069138]] [[-0.1633707 0.01375712] [ 0.01953864 0.11502898]] [[-1.02505008 -6.03473119] [-8.57086863 0.72173568]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.19872037150428723 0.3506413010364053 seed: 11 [0.59345747 0.50405991] 3.7306863239940204 [[ 0.44726794 -0.04617036] [-0.04617036 0.39179286]] [[2.26332908 0.26671929] [0.26671929 2.58380033]] [[-0.59882319 0.29778974] [ 0.33882562 0.52629845]] [[-0.81437012 -1.2649626 ] [-1.43927639 0.71574004]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -1.092686015122924 1.4746656432581782 seed: 12 [0.50346304 0.49828554] 0.7215776662713073 [[ 0.02197582 -0.00051243] [-0.00051243 0.01859843]] [[45.53382294 1.25457289] [ 1.25457289 53.80254874]] [[-0.14689036 0.01997595] [ 0.02179624 0.134623 ]] [[-1.07847582 -6.6611345 ] [-7.26812202 0.98840835]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.019765258396075982 0.22521924489885897 seed: 13 [0.52739261 0.49636814] 3.3812808083835133 [[0.15850363 0.01102533] [0.01102533 0.38344053]] [[ 6.32164766 -0.18177065] [-0.18177065 2.61319295]] [[-0.03026402 -0.39697319] [-0.61892143 0.0194112 ]] [[-2.51305304 0.07881674] [ 0.12288328 1.61186 ]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6029032189790895 0.8593349879630028 seed: 14 [0.49578687 0.49107959] 0.985344450508965 [[0.0229603 0.00218594] [0.00218594 0.01727914]] [[44.08438795 -5.57700003] [-5.57700003 58.57878206]] [[-0.14575598 -0.0414186 ] [-0.04959054 0.12173709]] [[ 2.50484132 -6.1489965 ] [-7.36220173 -2.0920726 ]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.04428553210487171 0.244441630592295 seed: 15 [0.48642319 0.66841006] 99.49049823321974 [[ 0.48236792 -0.18182732] [-0.18182732 0.36665513]] [[2.5497309 1.26443268] [1.26443268 3.35440117]] [[-0.6332046 0.28534166] [ 0.46300505 0.39023257]] [[-1.22096725 -1.02906262] [-1.6697919 0.75246009]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -6.087296453252871 6.4023793076344395 seed: 16 [0.49343334 0.47906169] 29.470736305310133 [[0.02519435 0.00144764] [0.00144764 0.01541777]] [[39.90673801 -3.74700043] [-3.74700043 65.21203037]] [[-0.15773825 -0.01769165] [-0.02286578 0.12204478]] [[ 1.16331785 -6.20914081] [-8.02507871 -0.90007894]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7596099227288234 0.9551032647005249 seed: 17 [0.45822053 0.45620346] 3.867101221747955 [[ 0.31747032 -0.11633444] [-0.11633444 0.32983302]] [[3.61744326 1.27589782] [1.27589782 3.48185534]] [[ 0.45650634 -0.33026093] [-0.48140645 -0.31317861]] [[-1.59428407 -1.03716033] [-1.51182183 1.09373219]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.9980562454409576 1.065967262438615 seed: 18 [0.50867005 0.48928539] 1.987131194992184 [[ 0.01875748 -0.00245339] [-0.00245339 0.02174844]] [[54.11045954 6.10407145] [ 6.10407145 46.66888943]] [[ 0.0744627 -0.11494687] [-0.13259532 -0.06455171]] [[-6.61385603 -3.21983974] [-3.71420034 5.73355084]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.08414368416027168 0.29342603298305664 seed: 19 [0.51301403 0.48323565] 1.6197886971538265 [[ 0.36663328 -0.01367268] [-0.01367268 0.30642217]] [[2.73206723 0.12190594] [0.12190594 3.26891089]] [[-0.59418281 0.11653355] [ 0.12860559 0.53840763]] [[-0.38401258 -1.60766961] [-1.77421269 0.34796581]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6574825285771522 0.8797835081854678

Result

Test

Duration

Links

Passed

tests/test_hotstart.py::test_contbox_hotstart

0.87

Passed

tests/test_flatnuts.py::test_singlejumper

0.10

Passed

tests/test_netiterintegrate.py::test_singleblock[100]

6.53

Passed

tests/test_clustering.py::test_overclustering_eggbox_update

8.23

Passed

tests/test_clustering.py::test_overclustering_eggbox_txt

0.61

Passed

tests/test_clustering.py::test_clustering

4.75

[gw0] linux -- Python 3.10.6 /usr/bin/python3
[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_flatnuts.py::test_detailed_balance

5.53

[gw6] linux -- Python 3.10.6 /usr/bin/python3
[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3[gw6] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
---- seed=1 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 BACKWARD SAMPLING FROM 4 [0.14168242 0.38811823] [0.02821641 0.02835197] -0.1665060917360781 BACKWARD SAMPLING FROM -4 [0.11583903 0.41282151] [-0.02893116 -0.02762223] -0.10171045505355579 BisectSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), None, None, None, 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 1, array([0.02881679, 0.27471034]), array([ 0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.02881679 0.27471034] [ 0.02893116 -0.02762223] new direction: [0.02821641 0.02835197] reversing there [ 0.02893116 -0.02762223] making one step from [0.02881679 0.27471034] [ 0.02893116 -0.02762223] --> [0.0570332 0.30306231] [0.02821641 0.02835197] trying new point, [0.0570332 0.30306231] next() call -0.48643206112737647 goals: [('reflect-at', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09073879959282771 goals: [('bisect', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), None, None, None, 10, array([0.31098087, 0.55823006]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31098087 0.55823006] [0.02821641 0.02835197] -0.09073879959282771 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), None, None, None, 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1016481498381896 goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.25225605758357234 goals: [('bisect', 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3588980473806718 goals: [('bisect', 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4864320611273768 goals: [('bisect', 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 9, array([0.0570332 , 0.30306231]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.02881679 0.27471034] [-0.02821641 -0.02835197] new direction: [-0.02893116 0.02762223] reversing there [-0.02821641 -0.02835197] making one step from [0.02881679 0.27471034] [-0.02821641 -0.02835197] --> [1.14374817e-04 3.02332573e-01] [0.02893116 0.02762223] trying new point, [1.14374817e-04 3.02332573e-01] next() call -0.4884051545701359 goals: [('reflect-at', 10, array([1.14374817e-04, 3.02332573e-01]), array([0.02893116, 0.02762223]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 sampling between (-3, 4) ---- seed=2 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 BACKWARD SAMPLING FROM 4 [0.550579 0.59531977] [0.00022913 0.03999934] -0.2651418446056711 BACKWARD SAMPLING FROM -2 [0.54920422 0.35532371] [0.00022913 0.03999934] -0.4124530140569493 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), None, None, None, 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3805855729471914 goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 6, array([0.55103726, 0.67531846]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.55103726 0.67531846] [0.00022913 0.03999934] new direction: [-0.03532089 0.01877324] reversing there [0.00022913 0.03999934] making one step from [0.55103726 0.67531846] [0.00022913 0.03999934] --> [0.51571637 0.69409169] [-0.03532089 0.01877324] trying new point, [0.51571637 0.69409169] next() call None goals: [('reflect-at', 6, array([0.51571637, 0.69409169]), array([-0.03532089, 0.01877324]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.54989161 0.47532174] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.55080813 0.63531911] [0.00022913 0.03999934] -0.3805855729471914 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2033543310016853 goals: [('bisect', 0, array([0.55080813, 0.63531911]), array([-0.00022913, -0.03999934]), None, None, None, 5, array([0.54966248, 0.43532239]), array([-0.00022913, -0.03999934]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=3 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 BACKWARD SAMPLING FROM 4 [0.23962941 0.66238895] [-0.01281883 0.03789034] -0.3583382577658276 BACKWARD SAMPLING FROM -4 [0.34218007 0.35926626] [-0.01281883 0.03789034] -0.306118410872214 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), None, None, None, 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12894573017062852 goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.22561386347891177 goals: [('bisect', 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3583382577658276 goals: [('bisect', 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 4, array([0.23962941, 0.66238895]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22681058 0.70027928] [-0.01281883 0.03789034] new direction: [-0.03961561 -0.00553205] reversing there [-0.01281883 0.03789034] making one step from [0.22681058 0.70027928] [-0.01281883 0.03789034] --> [0.18719497 0.69474723] [-0.03961561 -0.00553205] trying new point, [0.18719497 0.69474723] next() call -0.4916020278270488 goals: [('reflect-at', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3490349009639423 goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), None, None, None, 10, array([0.01088307, 0.66708697]), array([ 0.03961561, -0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.01088307 0.66708697] [ 0.03961561 -0.00553205] -0.3490349009639423 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), None, None, None, 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4916020278270488 goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 6, array([0.22681058, 0.70027928]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22681058 0.70027928] [0.03961561 0.00553205] new direction: [ 0.01281883 -0.03789034] reversing there [0.03961561 0.00553205] making one step from [0.22681058 0.70027928] [0.03961561 0.00553205] --> [0.23962941 0.66238895] [ 0.01281883 -0.03789034] trying new point, [0.23962941 0.66238895] next() call -0.3583382577658272 goals: [('reflect-at', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04377824648995988 goals: [('bisect', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), None, None, None, 10, array([0.29090474, 0.51082761]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=4 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BACKWARD SAMPLING FROM 4 [0.80905758 0.52184001] [-0.03949306 -0.00634806] -0.33324941010291637 BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16694885584599184 goals: [('bisect', 0, array([0.96702984, 0.54723225]), array([-0.03949306, -0.00634806]), None, None, None, 10, array([0.5720992 , 0.48375165]), array([-0.03949306, -0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.5720992 0.48375165] [-0.03949306 -0.00634806] -0.16694885584599184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.49545942179887775 goals: [('bisect', 0, array([0.5720992 , 0.48375165]), array([0.03949306, 0.00634806]), None, None, None, 10, array([0.96702984, 0.54723225]), array([0.03949306, 0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 sampling between (-4, 3) ---- seed=5 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 BACKWARD SAMPLING FROM 4 [0.63456332 0.54663199] [ 0.03653803 -0.01627797] -0.22851708746536278 BACKWARD SAMPLING FROM -4 [0.34225906 0.67685573] [ 0.03653803 -0.01627797] -0.4495450053329357 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3970381430661767 goals: [('bisect', 0, array([0.48841119, 0.61174386]), array([ 0.03653803, -0.01627797]), None, None, None, 10, array([0.85379151, 0.44896419]), array([ 0.03653803, -0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.85379151 0.44896419] [ 0.03653803 -0.01627797] -0.3970381430661767 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.27535638087505515 goals: [('bisect', 0, array([0.85379151, 0.44896419]), array([-0.03653803, 0.01627797]), None, None, None, 10, array([0.48841119, 0.61174386]), array([-0.03653803, 0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-13, 2) ---- seed=6 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 BACKWARD SAMPLING FROM 4 [0.03716733 0.66306682] [0.036206 0.01700369] -0.3330755453049499 BACKWARD SAMPLING FROM -4 [0.25248069 0.52703731] [-0.036206 0.01700369] -0.041010950598001826 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), None, None, None, 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4080091653243474 goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4914817954950847 goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 6, array([0.10957933, 0.6970742 ]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.14578533 0.71407788] [0.036206 0.01700369] new direction: [ 0.02481099 -0.03137538] reversing there [0.036206 0.01700369] making one step from [0.14578533 0.71407788] [0.036206 0.01700369] --> [0.17059633 0.6827025 ] [ 0.02481099 -0.03137538] trying new point, [0.17059633 0.6827025 ] next() call -0.4318041009131332 goals: [('reflect-at', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12809180647624227 goals: [('bisect', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), None, None, None, 10, array([0.2450293 , 0.58857635]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.2450293 0.58857635] [ 0.02481099 -0.03137538] -0.12809180647624227 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), None, None, None, 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.30534071772163773 goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4318041009131337 goals: [('bisect', 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 4, array([0.14578533, 0.71407788]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.14578533 0.71407788] [-0.02481099 0.03137538] new direction: [-0.036206 -0.01700369] reversing there [-0.02481099 0.03137538] making one step from [0.14578533 0.71407788] [-0.02481099 0.03137538] --> [0.10957933 0.6970742 ] [-0.036206 -0.01700369] trying new point, [0.10957933 0.6970742 ] next() call -0.4914817954950847 goals: [('reflect-at', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1187311667407582 goals: [('bisect', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), None, None, None, 10, array([0.10765668, 0.59505206]), array([ 0.036206 , -0.01700369]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=7 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM -3 [0.91202793 0.42346309] [0.02932044 0.02720867] -0.48912121118231033 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 1, array([0.95598978, 0.57190263]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.95598978 0.57190263] [-0.02199973 0.03340676] new direction: [-0.03029182 0.0261229 ] reversing there [-0.02199973 0.03340676] making one step from [0.95598978 0.57190263] [-0.02199973 0.03340676] --> [0.92569796 0.59802553] [-0.03029182 0.0261229 ] trying new point, [0.92569796 0.59802553] next() call None goals: [('reflect-at', 1, array([0.92569796, 0.59802553]), array([-0.03029182, 0.0261229 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call -0.4882763953959062 goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -2, array([0.97801102, 0.47168235]), array([0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 bisecting gave reflection point -3 [0.95601129 0.43827559] [0.02199973 0.03340676] new direction: [ 0.01936874 -0.03499789] reversing there [0.02199973 0.03340676] making one step from [0.95601129 0.43827559] [0.02199973 0.03340676] --> [0.97538002 0.4032777 ] [-0.01936874 0.03499789] trying new point, [0.97538002 0.4032777 ] next() call None goals: [('reflect-at', -3, array([0.97538002, 0.4032777 ]), array([-0.01936874, 0.03499789]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] reversing at -2... -7 steps to do at -2 -> [from -3, delta=-7] targeting 4. goals: [('sample-at', 4)] reversing at 0... 4 steps to do at 0 -> [from 1, delta=4] targeting -3. goals: [('sample-at', -3)] reversing at -2... -1 steps to do at -2 -> [from -3, delta=-1] targeting -2. goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -2 [0.97801102 0.47168235] [0.02199973 0.03340676] -0.4882763953959062 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -2)] not done yet, continue expanding to -2... goals: [('expand-to', -2), ('sample-at', -2)] next() call -0.49675589327088776 goals: [('bisect', 0, array([0.97801102, 0.47168235]), array([-0.02199973, -0.03340676]), None, None, None, -2, array([0.97798951, 0.53849587]), array([ 0.02199973, -0.03340676]), -1), ('sample-at', -2)] bisecting ... 0 None -2 successfully went all the way in one jump! goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=8 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4375602772906623 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48991371862053074 goals: [('bisect', 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 4, array([0.98770652, 0.42336192]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.98770652 0.42336192] [ 0.02962799 -0.02687344] new direction: [-0.03704999 -0.01507642] reversing there [ 0.02962799 -0.02687344] making one step from [0.98770652 0.42336192] [ 0.02962799 -0.02687344] --> [0.95065653 0.4082855 ] [-0.03704999 -0.01507642] trying new point, [0.95065653 0.4082855 ] next() call None goals: [('reflect-at', 4, array([0.95065653, 0.4082855 ]), array([-0.03704999, -0.01507642]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.45977857566680347 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, -3, array([0.78031056, 0.61147602]), array([ 0.02962799, -0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.95807852, 0.45023536]), array([-0.02962799, 0.02687344]), None, None, None, 3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.78031056, 0.61147602]), array([-0.02962799, 0.02687344]), None, None, None, -3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=9 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 BACKWARD SAMPLING FROM 4 [0.11061846 0.39718082] [ 0.03024815 -0.02617344] -0.13826553062534178 BACKWARD SAMPLING FROM -4 [0.13136677 0.60656837] [-0.03024815 -0.02617344] -0.1505888292401249 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), None, None, None, 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2179104295369838 goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43132376818592777 goals: [('bisect', 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 8, array([0.23161108, 0.29248704]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23161108 0.29248704] [ 0.03024815 -0.02617344] new direction: [0.02396606 0.03202542] reversing there [ 0.03024815 -0.02617344] making one step from [0.23161108 0.29248704] [ 0.03024815 -0.02617344] --> [0.25557714 0.32451246] [0.02396606 0.03202542] trying new point, [0.25557714 0.32451246] next() call -0.41760827984962573 goals: [('reflect-at', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20128562729667512 goals: [('bisect', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), None, None, None, 10, array([0.30350927, 0.38856331]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30350927 0.38856331] [0.02396606 0.03202542] -0.20128562729667512 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), None, None, None, 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.41760827984962573 goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 3, array([0.23161108, 0.29248704]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23161108 0.29248704] [-0.02396606 -0.03202542] new direction: [-0.03024815 0.02617344] reversing there [-0.02396606 -0.03202542] making one step from [0.23161108 0.29248704] [-0.02396606 -0.03202542] --> [0.20136292 0.31866048] [-0.03024815 0.02617344] trying new point, [0.20136292 0.31866048] next() call -0.43132376818592777 goals: [('reflect-at', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -9.773773097349783e-05 goals: [('bisect', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), None, None, None, 10, array([0.01037415, 0.50187459]), array([0.03024815, 0.02617344]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=10 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 BACKWARD SAMPLING FROM -4 [0.03407747 0.35677655] [-0.00950643 0.03885393] -0.25699258899589295 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10128899988595243 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.2077471298760972 goals: [('bisect', 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3520363250591377 goals: [('bisect', 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 4, array([0.041974 , 0.66760798]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.05148044 0.7064619 ] [0.00950643 0.03885393] new direction: [0.03538475 0.01865259] reversing there [0.00950643 0.03885393] making one step from [0.05148044 0.7064619 ] [0.00950643 0.03885393] --> [0.08686519 0.7251145 ] [0.03538475 0.01865259] trying new point, [0.08686519 0.7251145 ] next() call None goals: [('reflect-at', 5, array([0.08686519, 0.7251145 ]), array([0.03538475, 0.01865259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.008901001072892184 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, -1, array([0.00555817, 0.47333834]), array([-0.00950643, 0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.001865935484349968 goals: [('bisect', 0, array([0.041974 , 0.66760798]), array([-0.00950643, -0.03885393]), None, None, None, 4, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.00555817 0.47333834] [-0.00950643 0.03885393] -0.008901001072892184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0018659354843499343 goals: [('bisect', 0, array([0.00555817, 0.47333834]), array([ 0.00950643, -0.03885393]), None, None, None, -1, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=11 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 BACKWARD SAMPLING FROM 4 [0.37163231 0.33297767] [-0.01214282 -0.03811236] -0.4177610370777551 BACKWARD SAMPLING FROM -4 [0.4687749 0.63787653] [-0.01214282 -0.03811236] -0.3474991729078387 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), None, None, None, 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.18142810704210527 goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.28136395006049925 goals: [('bisect', 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4177610370777551 goals: [('bisect', 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 4, array([0.37163231, 0.33297767]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35948949 0.29486531] [-0.01214282 -0.03811236] new direction: [-0.0041129 0.03978799] reversing there [-0.01214282 -0.03811236] making one step from [0.35948949 0.29486531] [-0.01214282 -0.03811236] --> [0.35537659 0.3346533 ] [-0.0041129 0.03978799] trying new point, [0.35537659 0.3346533 ] next() call -0.4048904116037848 goals: [('reflect-at', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07015589586681098 goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), None, None, None, 10, array([0.3348121 , 0.53359324]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.3348121 0.53359324] [-0.0041129 0.03978799] -0.07015589586681098 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), None, None, None, 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.40489041160378453 goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 6, array([0.35948949, 0.29486531]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.35948949 0.29486531] [ 0.0041129 -0.03978799] new direction: [0.01214282 0.03811236] reversing there [ 0.0041129 -0.03978799] making one step from [0.35948949 0.29486531] [ 0.0041129 -0.03978799] --> [0.37163231 0.33297767] [0.01214282 0.03811236] trying new point, [0.37163231 0.33297767] next() call -0.4177610370777547 goals: [('reflect-at', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0909401530019027 goals: [('bisect', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), None, None, None, 10, array([0.4202036, 0.4854271]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=12 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 BACKWARD SAMPLING FROM 4 [0.13496481 0.43820812] [-0.03208755 -0.02388282] -0.05683571304926094 BACKWARD SAMPLING FROM -4 [0.39166522 0.62927067] [-0.03208755 -0.02388282] -0.2855871537311189 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), None, None, None, 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.09704380253434214 goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.22332799455138033 goals: [('bisect', 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3094040970833373 goals: [('bisect', 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.41076953729758614 goals: [('bisect', 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 9, array([0.02547294, 0.31879402]), array([ 0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] new direction: [ 0.02655384 -0.02991477] reversing there [ 0.03208755 -0.02388282] making one step from [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] --> [0.08411434 0.26499643] [ 0.02655384 -0.02991477] trying new point, [0.08411434 0.26499643] next() call None goals: [('reflect-at', 10, array([0.08411434, 0.26499643]), array([ 0.02655384, -0.02991477]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.02547294 0.31879402] [ 0.03208755 -0.02388282] -0.41076953729758614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.04889673193185484 goals: [('bisect', 0, array([0.02547294, 0.31879402]), array([-0.03208755, 0.02388282]), None, None, None, 9, array([0.26331502, 0.53373939]), array([0.03208755, 0.02388282]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=13 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 BACKWARD SAMPLING FROM 4 [0.40042197 0.52612745] [-0.00300128 -0.03988724] -0.08870192535855582 BACKWARD SAMPLING FROM -4 [0.2145617 0.65653403] [0.03957308 0.00582848] -0.32930462797788607 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), None, None, None, 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 1, array([0.41242711, 0.68567643]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.41242711 0.68567643] [0.03957308 0.00582848] new direction: [-0.00300128 -0.03988724] reversing there [0.03957308 0.00582848] making one step from [0.41242711 0.68567643] [0.03957308 0.00582848] --> [0.40942582 0.64578919] [-0.00300128 -0.03988724] trying new point, [0.40942582 0.64578919] next() call -0.3494958457329673 goals: [('reflect-at', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), None, None, None, 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.08133824843659004 goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.18596233939691564 goals: [('bisect', 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.297950107279207 goals: [('bisect', 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4497216900962508 goals: [('bisect', 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 9, array([0.38541555, 0.32669123]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.38241426 0.28680399] [-0.00300128 -0.03988724] new direction: [0.02675467 0.02973529] reversing there [-0.00300128 -0.03988724] making one step from [0.38241426 0.28680399] [-0.00300128 -0.03988724] --> [0.40916893 0.31653928] [0.02675467 0.02973529] trying new point, [0.40916893 0.31653928] next() call None goals: [('reflect-at', 10, array([0.40916893, 0.31653928]), array([0.02675467, 0.02973529]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.38541555 0.32669123] [-0.00300128 -0.03988724] -0.4497216900962508 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call None goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), None, None, None, 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 None 9 continue bisect at 4 next() call -0.08133824843659004 goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 4 9 continue bisect at 6 next() call -0.13584941721527394 goals: [('bisect', 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 4 6 9 continue bisect at 7 next() call -0.22278072400674448 goals: [('bisect', 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 6 7 9 continue bisect at 8 next() call -0.3494958457329673 goals: [('bisect', 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 8, array([0.40942582, 0.64578919]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 7 8 9 bisecting gave reflection point 9 [0.41242711 0.68567643] [0.00300128 0.03988724] new direction: [-0.03957308 -0.00582848] reversing there [0.00300128 0.03988724] making one step from [0.41242711 0.68567643] [0.00300128 0.03988724] --> [0.37285403 0.67984795] [-0.03957308 -0.00582848] trying new point, [0.37285403 0.67984795] next() call -0.47382613413670327 goals: [('reflect-at', 9, array([0.37285403, 0.67984795]), array([-0.03957308, -0.00582848]), 1), ('sample-at', 9)] goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 sampling between (0, 7) ---- seed=14 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 BACKWARD SAMPLING FROM 4 [0.21608397 0.61107718] [-0.021002 0.03404285] -0.17757288486701345 BACKWARD SAMPLING FROM -4 [0.38409999 0.33873435] [-0.021002 0.03404285] -0.39884901225457176 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), None, None, None, 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2822762805921456 goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41639365668362777 goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 6, array([0.17407996, 0.67916288]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.15307796 0.71320574] [-0.021002 0.03404285] new direction: [ 0.01597666 -0.03667078] reversing there [-0.021002 0.03404285] making one step from [0.15307796 0.71320574] [-0.021002 0.03404285] --> [0.16905462 0.67653496] [ 0.01597666 -0.03667078] trying new point, [0.16905462 0.67653496] next() call -0.40384711686066294 goals: [('reflect-at', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07885688368045461 goals: [('bisect', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), None, None, None, 10, array([0.21698461, 0.56652261]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21698461 0.56652261] [ 0.01597666 -0.03667078] -0.07885688368045461 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), None, None, None, 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.2616431298568962 goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.40384711686066294 goals: [('bisect', 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 4, array([0.15307796, 0.71320574]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.15307796 0.71320574] [-0.01597666 0.03667078] new direction: [ 0.021002 -0.03404285] reversing there [-0.01597666 0.03667078] making one step from [0.15307796 0.71320574] [-0.01597666 0.03667078] --> [0.17407996 0.67916288] [ 0.021002 -0.03404285] trying new point, [0.17407996 0.67916288] next() call -0.41639365668362777 goals: [('reflect-at', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05289910562998976 goals: [('bisect', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), None, None, None, 10, array([0.30009198, 0.47490577]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=15 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 BACKWARD SAMPLING FROM 4 [0.10549014 0.35468978] [ 0.03996334 -0.00171217] -0.2695023366962361 BACKWARD SAMPLING FROM -4 [0.21421657 0.36838711] [-0.03996334 -0.00171217] -0.23946877171984182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36218247700975736 goals: [('bisect', 0, array([0.05436321, 0.36153845]), array([-0.03996334, -0.00171217]), None, None, None, 10, array([0.34527018, 0.34441678]), array([ 0.03996334, -0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.34527018 0.34441678] [ 0.03996334 -0.00171217] -0.36218247700975736 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2411227034306628 goals: [('bisect', 0, array([0.34527018, 0.34441678]), array([-0.03996334, 0.00171217]), None, None, None, 10, array([0.05436321, 0.36153845]), array([0.03996334, 0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=16 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 BACKWARD SAMPLING FROM 4 [0.37021116 0.58652334] [0.03673002 0.01584 ] -0.16210675630294513 BACKWARD SAMPLING FROM -4 [0.076371 0.45980334] [0.03673002 0.01584 ] -0.0231134050599264 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), None, None, None, 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.213778728689882 goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33998787578479583 goals: [('bisect', 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.41452505049277283 goals: [('bisect', 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4966839593077631 goals: [('bisect', 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 9, array([0.55386126, 0.66572334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.59059129 0.68156334] [0.03673002 0.01584 ] new direction: [-0.02554864 -0.0307777 ] reversing there [0.03673002 0.01584 ] making one step from [0.59059129 0.68156334] [0.03673002 0.01584 ] --> [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] trying new point, [0.56504265 0.65078563] next() call -0.44384043934656114 goals: [('reflect-at', 10, array([0.56504265, 0.65078563]), array([-0.02554864, -0.0307777 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] -0.44384043934656114 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), None, None, None, 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 1, array([0.59059129, 0.68156334]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.59059129 0.68156334] [0.02554864 0.0307777 ] new direction: [-0.03673002 -0.01584 ] reversing there [0.02554864 0.0307777 ] making one step from [0.59059129 0.68156334] [0.02554864 0.0307777 ] --> [0.55386126 0.66572334] [-0.03673002 -0.01584 ] trying new point, [0.55386126 0.66572334] next() call -0.49668395930776266 goals: [('reflect-at', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.03163620782532951 goals: [('bisect', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), None, None, None, 10, array([0.22329108, 0.52316334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-13, 2) ---- seed=17 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 BACKWARD SAMPLING FROM 4 [0.15857392 0.61472483] [-0.03402277 0.02103452] -0.1770951824864543 BACKWARD SAMPLING FROM -4 [0.43075609 0.44644868] [-0.03402277 0.02103452] -0.12862220436569055 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), None, None, None, 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2381390123527663 goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3968831438195334 goals: [('bisect', 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.49458344541998867 goals: [('bisect', 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 9, array([0.01153994, 0.71989743]), array([0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.01153994 0.71989743] [0.03402277 0.02103452] new direction: [0.01297498 0.03783715] reversing there [0.03402277 0.02103452] making one step from [0.01153994 0.71989743] [0.03402277 0.02103452] --> [0.02451492 0.75773458] [0.01297498 0.03783715] trying new point, [0.02451492 0.75773458] next() call None goals: [('reflect-at', 9, array([0.02451492, 0.75773458]), array([0.01297498, 0.03783715]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.02248283 0.69886291] [-0.03402277 0.02103452] -0.49458344541998867 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.055108102135022076 goals: [('bisect', 0, array([0.02248283, 0.69886291]), array([ 0.03402277, -0.02103452]), None, None, None, 8, array([0.294665 , 0.53058676]), array([ 0.03402277, -0.02103452]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=18 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 BACKWARD SAMPLING FROM 4 [0.49132867 0.52290346] [-0.03976139 0.00436252] -0.12725903771293967 BACKWARD SAMPLING FROM -4 [0.80941982 0.48800328] [-0.03976139 0.00436252] -0.3293792332040737 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0620527440819295 goals: [('bisect', 0, array([0.65037424, 0.50545337]), array([-0.03976139, 0.00436252]), None, None, None, 10, array([0.25276031, 0.5490786 ]), array([-0.03976139, 0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.25276031 0.5490786 ] [-0.03976139 0.00436252] -0.0620527440819295 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21186506822282286 goals: [('bisect', 0, array([0.25276031, 0.5490786 ]), array([ 0.03976139, -0.00436252]), None, None, None, 10, array([0.65037424, 0.50545337]), array([ 0.03976139, -0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-2, 5) ---- seed=19 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 BACKWARD SAMPLING FROM 4 [0.36264649 0.61284195] [0.03668081 0.01595363] -0.22492257200551513 BACKWARD SAMPLING FROM -4 [0.06920002 0.48521291] [0.03668081 0.01595363] -0.005127547303597255 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), None, None, None, 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28708492992102647 goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43453496563722904 goals: [('bisect', 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 8, array([0.50936972, 0.67665648]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.50936972 0.67665648] [0.03668081 0.01595363] new direction: [-0.02514398 -0.03110917] reversing there [0.03668081 0.01595363] making one step from [0.50936972 0.67665648] [0.03668081 0.01595363] --> [0.48422574 0.64554731] [-0.02514398 -0.03110917] trying new point, [0.48422574 0.64554731] next() call -0.38203753202294766 goals: [('reflect-at', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18094748307481168 goals: [('bisect', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), None, None, None, 10, array([0.43393777, 0.58332898]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43393777 0.58332898] [-0.02514398 -0.03110917] -0.18094748307481168 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), None, None, None, 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.38203753202294766 goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 3, array([0.50936972, 0.67665648]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.50936972 0.67665648] [0.02514398 0.03110917] new direction: [-0.03668081 -0.01595363] reversing there [0.02514398 0.03110917] making one step from [0.50936972 0.67665648] [0.02514398 0.03110917] --> [0.47268891 0.66070285] [-0.03668081 -0.01595363] trying new point, [0.47268891 0.66070285] next() call -0.434534965637229 goals: [('reflect-at', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05335753996074122 goals: [('bisect', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), None, None, None, 10, array([0.21592326, 0.54902743]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=20 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 BACKWARD SAMPLING FROM 4 [0.19493603 0.67431541] [ 0.03976161 -0.00436054] -0.3988233188094961 BACKWARD SAMPLING FROM -1 [0.00387202 0.69611812] [-0.03976161 -0.00436054] -0.48078647770574867 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36832687557067506 goals: [('bisect', 0, array([0.03588959, 0.69175758]), array([ 0.03976161, -0.00436054]), None, None, None, 10, array([0.43350569, 0.64815216]), array([ 0.03976161, -0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43350569 0.64815216] [ 0.03976161 -0.00436054] -0.36832687557067506 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4602811582030628 goals: [('bisect', 0, array([0.43350569, 0.64815216]), array([-0.03976161, 0.00436054]), None, None, None, 10, array([0.03588959, 0.69175758]), array([-0.03976161, 0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=21 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 BACKWARD SAMPLING FROM 4 [0.2415294 0.51588884] [-0.01518562 -0.03700536] -0.032323918419140216 BACKWARD SAMPLING FROM -4 [0.17116112 0.6361286 ] [0.0365741 0.01619676] -0.24628550700212182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), None, None, None, 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.031189595628649723 goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.132317524420316 goals: [('bisect', 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2345797760024729 goals: [('bisect', 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3713075523755122 goals: [('bisect', 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 9, array([0.16560129, 0.33086203]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.15041567 0.29385667] [-0.01518562 -0.03700536] new direction: [-0.02472709 0.03144155] reversing there [-0.01518562 -0.03700536] making one step from [0.15041567 0.29385667] [-0.01518562 -0.03700536] --> [0.12568857 0.32529821] [-0.02472709 0.03144155] trying new point, [0.12568857 0.32529821] next() call -0.3894077367200711 goals: [('reflect-at', 10, array([0.12568857, 0.32529821]), array([-0.02472709, 0.03144155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.12568857 0.32529821] [-0.02472709 0.03144155] -0.3894077367200711 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), None, None, None, 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 1, array([0.15041567, 0.29385667]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.15041567 0.29385667] [ 0.02472709 -0.03144155] new direction: [0.01518562 0.03700536] reversing there [ 0.02472709 -0.03144155] making one step from [0.15041567 0.29385667] [ 0.02472709 -0.03144155] --> [0.16560129 0.33086203] [0.01518562 0.03700536] trying new point, [0.16560129 0.33086203] next() call -0.3713075523755125 goals: [('reflect-at', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3815164574899263 goals: [('bisect', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), None, None, None, 10, array([0.30227189, 0.66391029]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 sampling between (-3, 0) ---- seed=22 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 BACKWARD SAMPLING FROM 4 [0.05625556 0.43234909] [-0.03805125 -0.01233299] -0.05879042044402399 BACKWARD SAMPLING FROM -4 [0.36066552 0.53101304] [-0.03805125 -0.01233299] -0.07706241401616516 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.26560598511461014 goals: [('bisect', 0, array([0.20846054, 0.48168106]), array([-0.03805125, -0.01233299]), None, None, None, 10, array([0.17205191, 0.35835112]), array([ 0.03805125, -0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.17205191 0.35835112] [ 0.03805125 -0.01233299] -0.26560598511461014 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.025922691544438898 goals: [('bisect', 0, array([0.17205191, 0.35835112]), array([-0.03805125, 0.01233299]), None, None, None, 10, array([0.20846054, 0.48168106]), array([0.03805125, 0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=23 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM -4 [0.3745104 0.64096191] [-0.03836626 0.01131504] -0.3185072622476324 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 1, array([0.18267911, 0.69753713]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.18267911 0.69753713] [-0.03836626 0.01131504] new direction: [0.00426897 0.03977155] reversing there [-0.03836626 0.01131504] making one step from [0.18267911 0.69753713] [-0.03836626 0.01131504] --> [0.18694807 0.73730868] [0.00426897 0.03977155] trying new point, [0.18694807 0.73730868] next() call None goals: [('reflect-at', 1, array([0.18694807, 0.73730868]), array([0.00426897, 0.03977155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.24938536408337458 goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, -9, array([0.56634169, 0.58438669]), array([-0.03836626, 0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.56634169 0.58438669] [-0.03836626 0.01131504] -0.24938536408337458 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.45791383918711764 goals: [('bisect', 0, array([0.56634169, 0.58438669]), array([ 0.03836626, -0.01131504]), None, None, None, -9, array([0.22104536, 0.68622209]), array([ 0.03836626, -0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=24 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 BACKWARD SAMPLING FROM 4 [0.16900014 0.35473942] [-0.01277137 0.03790636] -0.2780384655059737 BACKWARD SAMPLING FROM -4 [0.05921351 0.52405108] [ 0.01933277 -0.03501777] -0.008983803050778645 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), None, None, None, 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4480575304829881 goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 3, array([0.19454288, 0.2789267 ]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] new direction: [-0.01277137 0.03790636] reversing there [ 0.01933277 -0.03501777] making one step from [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] --> [0.18177151 0.31683306] [-0.01277137 0.03790636] trying new point, [0.18177151 0.31683306] next() call -0.43589702340056663 goals: [('reflect-at', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08868070867983059 goals: [('bisect', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), None, None, None, 10, array([0.0923719 , 0.58217758]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0923719 0.58217758] [-0.01277137 0.03790636] -0.08868070867983059 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), None, None, None, 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.156265316684782 goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43589702340056663 goals: [('bisect', 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 8, array([0.19454288, 0.2789267 ]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] new direction: [-0.01933277 0.03501777] reversing there [ 0.01277137 -0.03790636] making one step from [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] --> [0.17521011 0.31394447] [-0.01933277 0.03501777] trying new point, [0.17521011 0.31394447] next() call -0.44805753048298835 goals: [('reflect-at', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17758018669487677 goals: [('bisect', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), None, None, None, 10, array([0.13654458, 0.38398001]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=25 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BACKWARD SAMPLING FROM 4 [0.78739516 0.44532469] [-0.02068224 -0.03423806] -0.34736293667574614 BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), None, None, None, 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3927441882386654 goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.46785931365597694 goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 6, array([0.74603067, 0.37684857]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.72534842 0.34261051] [-0.02068224 -0.03423806] new direction: [-0.02832621 -0.02824227] reversing there [-0.02068224 -0.03423806] making one step from [0.72534842 0.34261051] [-0.02068224 -0.03423806] --> [0.69702221 0.31436824] [-0.02832621 -0.02824227] trying new point, [0.69702221 0.31436824] next() call None goals: [('reflect-at', 7, array([0.69702221, 0.31436824]), array([-0.02832621, -0.02824227]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.8080774 0.47956275] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.74603067 0.37684857] [-0.02068224 -0.03423806] -0.46785931365597694 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4631766689679939 goals: [('bisect', 0, array([0.74603067, 0.37684857]), array([0.02068224, 0.03423806]), None, None, None, 6, array([0.87012414, 0.58227693]), array([0.02068224, 0.03423806]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=26 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 BACKWARD SAMPLING FROM 4 [0.14894378 0.53733047] [-0.03974779 0.00448475] -0.028511673439282487 BACKWARD SAMPLING FROM -4 [0.46692612 0.50145249] [-0.03974779 0.00448475] -0.10903637436373395 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.055592009781843664 goals: [('bisect', 0, array([0.30793495, 0.51939148]), array([-0.03974779, 0.00448475]), None, None, None, 10, array([0.08954298, 0.56423895]), array([0.03974779, 0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.08954298 0.56423895] [0.03974779 0.00448475] -0.055592009781843664 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.052112335894670306 goals: [('bisect', 0, array([0.08954298, 0.56423895]), array([-0.03974779, -0.00448475]), None, None, None, 10, array([0.30793495, 0.51939148]), array([ 0.03974779, -0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-1, 6) ---- seed=27 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 BACKWARD SAMPLING FROM -4 [0.04213315 0.3940085 ] [ 0.03615567 -0.01711045] -0.14131507902115056 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.48345727148351275 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 1, array([0.22291152, 0.30845627]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.25906719 0.29134583] [ 0.03615567 -0.01711045] new direction: [0.03637517 0.01663872] reversing there [ 0.03615567 -0.01711045] making one step from [0.25906719 0.29134583] [ 0.03615567 -0.01711045] --> [0.29544236 0.30798455] [0.03637517 0.01663872] trying new point, [0.29544236 0.30798455] next() call None goals: [('reflect-at', 2, array([0.29544236, 0.30798455]), array([0.03637517, 0.01663872]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.039546759765486834 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, -7, array([0.06633386, 0.44533984]), array([-0.03615567, -0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.3977760002874148 goals: [('bisect', 0, array([0.22291152, 0.30845627]), array([-0.03615567, 0.01711045]), None, None, None, 1, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.06633386 0.44533984] [-0.03615567 -0.01711045] -0.039546759765486834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.39777600028741444 goals: [('bisect', 0, array([0.06633386, 0.44533984]), array([0.03615567, 0.01711045]), None, None, None, -7, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=28 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 BACKWARD SAMPLING FROM 4 [0.88862101 0.55003599] [ 0.03990182 -0.0028009 ] -0.4261186566116443 BACKWARD SAMPLING FROM -4 [0.56940648 0.57244321] [ 0.03990182 -0.0028009 ] -0.2277121021981689 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39396757347735606 goals: [('bisect', 0, array([0.72901374, 0.5612396 ]), array([ 0.03990182, -0.0028009 ]), None, None, None, 10, array([0.87196809, 0.53323058]), array([-0.03990182, -0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.87196809 0.53323058] [-0.03990182 -0.0028009 ] -0.39396757347735606 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3126091293887884 goals: [('bisect', 0, array([0.87196809, 0.53323058]), array([0.03990182, 0.0028009 ]), None, None, None, 10, array([0.72901374, 0.5612396 ]), array([-0.03990182, 0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-7, 0) ---- seed=29 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.4842195850803701 BACKWARD SAMPLING FROM -4 [0.53072657 0.40260139] [-0.01950188 0.03492387] -0.25941645597282265 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.24278535636599288 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3480663501867237 goals: [('bisect', 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.48421958508036966 goals: [('bisect', 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 4, array([0.37471154, 0.68199235]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35520966 0.71691623] [-0.01950188 0.03492387] new direction: [-0.01424107 0.03737903] reversing there [-0.01950188 0.03492387] making one step from [0.35520966 0.71691623] [-0.01950188 0.03492387] --> [0.34096859 0.75429526] [-0.01424107 0.03737903] trying new point, [0.34096859 0.75429526] next() call None goals: [('reflect-at', 5, array([0.34096859, 0.75429526]), array([-0.01424107, 0.03737903]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.1121758213412904 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, -1, array([0.47222094, 0.507373 ]), array([-0.01950188, 0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.48421958508036966 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.12484009194327635 goals: [('bisect', 0, array([0.37471154, 0.68199235]), array([ 0.01950188, -0.03492387]), None, None, None, 4, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.47222094 0.507373 ] [-0.01950188 0.03492387] -0.1121758213412904 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.12484009194327632 goals: [('bisect', 0, array([0.47222094, 0.507373 ]), array([ 0.01950188, -0.03492387]), None, None, None, -1, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=30 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM -4 [0.59432576 0.53279516] [ 0.01245444 -0.03801167] -0.19005558113344231 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 1, array([0.65659798, 0.34273682]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.65659798 0.34273682] [ 0.01245444 -0.03801167] new direction: [-0.03320369 -0.02230504] reversing there [ 0.01245444 -0.03801167] making one step from [0.65659798 0.34273682] [ 0.01245444 -0.03801167] --> [0.62339429 0.32043178] [-0.03320369 -0.02230504] trying new point, [0.62339429 0.32043178] next() call None goals: [('reflect-at', 1, array([0.62339429, 0.32043178]), array([-0.03320369, -0.02230504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call -0.2319571892828859 goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -7 next() call -0.42459225549601265 goals: [('bisect', -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -5 -7 -9 continue bisect at -8 next() call None goals: [('bisect', -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -8, array([0.54450798, 0.68484182]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -7 -8 -9 bisecting gave reflection point -8 [0.54450798 0.68484182] [ 0.01245444 -0.03801167] new direction: [-0.01383172 -0.03753243] reversing there [ 0.01245444 -0.03801167] making one step from [0.54450798 0.68484182] [ 0.01245444 -0.03801167] --> [0.53067626 0.64730939] [0.01383172 0.03753243] trying new point, [0.53067626 0.64730939] next() call -0.4120593466482403 goals: [('reflect-at', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.2842013875070083 goals: [('bisect', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), None, None, None, -9, array([0.51684455, 0.60977695]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] bisecting ... -8 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.51684455 0.60977695] [0.01383172 0.03753243] -0.2842013875070083 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), None, None, None, -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 continue bisect at -1 next() call -0.4120593466482403 goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -1, array([0.53067626, 0.64730939]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -1 -2 bisecting gave reflection point -2 [0.54450798 0.68484182] [-0.01383172 -0.03753243] new direction: [ 0.01245444 -0.03801167] reversing there [-0.01383172 -0.03753243] making one step from [0.54450798 0.68484182] [-0.01383172 -0.03753243] --> [0.55696242 0.64683016] [-0.01245444 0.03801167] trying new point, [0.55696242 0.64683016] next() call -0.42459225549601265 goals: [('reflect-at', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.38522198158313203 goals: [('bisect', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), None, None, None, -9, array([0.64414354, 0.38074849]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] bisecting ... -2 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -15..0 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-15, 0) ---- seed=31 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 BACKWARD SAMPLING FROM 4 [0.20783379 0.63322006] [0.03312527 0.02242134] -0.24344226375583042 BACKWARD SAMPLING FROM -4 [0.05716835 0.45384931] [-0.03312527 0.02242134] -0.028257682631574084 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), None, None, None, 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33183373572512614 goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4338904075452583 goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 6, array([0.27408433, 0.67806275]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.30720959 0.7004841 ] [0.03312527 0.02242134] new direction: [0.01886481 0.03527207] reversing there [0.03312527 0.02242134] making one step from [0.30720959 0.7004841 ] [0.03312527 0.02242134] --> [0.32607441 0.73575617] [0.01886481 0.03527207] trying new point, [0.32607441 0.73575617] next() call None goals: [('reflect-at', 7, array([0.32607441, 0.73575617]), array([0.01886481, 0.03527207]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.17470852 0.61079872] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.27408433 0.67806275] [0.03312527 0.02242134] -0.4338904075452583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.026528374387011194 goals: [('bisect', 0, array([0.27408433, 0.67806275]), array([-0.03312527, -0.02242134]), None, None, None, 6, array([0.07533272, 0.54353469]), array([-0.03312527, -0.02242134]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=32 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 BACKWARD SAMPLING FROM 4 [0.57413119 0.44042355] [-0.00874449 -0.03903247] -0.20918022823021926 BACKWARD SAMPLING FROM -1 [0.61785366 0.63558591] [-0.00874449 -0.03903247] -0.42066580339605575 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), None, None, None, 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28137754791921 goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.39173967918225305 goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 6, array([0.5566422 , 0.36235861]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.54789771 0.32332614] [-0.00874449 -0.03903247] new direction: [-0.03993719 0.00224073] reversing there [-0.00874449 -0.03903247] making one step from [0.54789771 0.32332614] [-0.00874449 -0.03903247] --> [0.50796052 0.32556687] [-0.03993719 0.00224073] trying new point, [0.50796052 0.32556687] next() call None goals: [('reflect-at', 7, array([0.50796052, 0.32556687]), array([-0.03993719, 0.00224073]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.58287569 0.47945602] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.5566422 0.36235861] [-0.00874449 -0.03903247] -0.39173967918225305 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.3020390652147834 goals: [('bisect', 0, array([0.5566422 , 0.36235861]), array([0.00874449, 0.03903247]), None, None, None, 6, array([0.60910917, 0.59655344]), array([0.00874449, 0.03903247]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=33 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 BACKWARD SAMPLING FROM 4 [0.1119679 0.53337938] [-0.03413556 0.02085099] -0.020195695214487927 BACKWARD SAMPLING FROM -4 [0.38505235 0.36657146] [-0.03413556 0.02085099] -0.2966723492317622 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.31828011334541667 goals: [('bisect', 0, array([0.24851013, 0.44997542]), array([-0.03413556, 0.02085099]), None, None, None, 10, array([0.09284544, 0.65848532]), array([0.03413556, 0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.09284544 0.65848532] [0.03413556 0.02085099] -0.31828011334541667 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.062159372957623346 goals: [('bisect', 0, array([0.09284544, 0.65848532]), array([-0.03413556, -0.02085099]), None, None, None, 10, array([0.24851013, 0.44997542]), array([ 0.03413556, -0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=34 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 BACKWARD SAMPLING FROM 4 [0.00576602 0.5067828 ] [ 0.02461744 -0.03152747] -0.0005917034778301611 BACKWARD SAMPLING FROM -2 [0.14193864 0.69594763] [-0.02461744 -0.03152747] -0.49001670522119156 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.42756666673695237 goals: [('bisect', 0, array([0.09270376, 0.63289269]), array([-0.02461744, -0.03152747]), None, None, None, 10, array([0.15347069, 0.31761797]), array([ 0.02461744, -0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.15347069 0.31761797] [ 0.02461744 -0.03152747] -0.42756666673695237 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.22505281963979504 goals: [('bisect', 0, array([0.15347069, 0.31761797]), array([-0.02461744, 0.03152747]), None, None, None, 10, array([0.09270376, 0.63289269]), array([0.02461744, 0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=35 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 BACKWARD SAMPLING FROM 4 [0.12229223 0.6737271 ] [-0.00640292 0.03948421] -0.3847415272663998 BACKWARD SAMPLING FROM -4 [0.17351559 0.35785345] [-0.00640292 0.03948421] -0.26762436346562096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), None, None, None, 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12136585946729678 goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23354566196277238 goals: [('bisect', 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3847415272663993 goals: [('bisect', 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 4, array([0.12229223, 0.6737271 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.11588931 0.71321131] [-0.00640292 0.03948421] new direction: [-0.01879284 -0.03531047] reversing there [-0.00640292 0.03948421] making one step from [0.11588931 0.71321131] [-0.00640292 0.03948421] --> [0.09709647 0.67790084] [-0.01879284 -0.03531047] trying new point, [0.09709647 0.67790084] next() call -0.400322736376469 goals: [('reflect-at', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -2.7636297378795028e-05 goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), None, None, None, 10, array([0.00313227, 0.5013485 ]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00313227 0.5013485 ] [-0.01879284 -0.03531047] -2.7636297378795028e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), None, None, None, 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.400322736376469 goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 6, array([0.11588931, 0.71321131]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.11588931 0.71321131] [0.01879284 0.03531047] new direction: [ 0.00640292 -0.03948421] reversing there [0.01879284 0.03531047] making one step from [0.11588931 0.71321131] [0.01879284 0.03531047] --> [0.12229223 0.6737271 ] [ 0.00640292 -0.03948421] trying new point, [0.12229223 0.6737271 ] next() call -0.3847415272663989 goals: [('reflect-at', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.014054442900799765 goals: [('bisect', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), None, None, None, 10, array([0.14790391, 0.51579028]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=36 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 BACKWARD SAMPLING FROM 4 [0.7232834 0.53653594] [-0.02732618 -0.02921096] -0.27825536957064223 BACKWARD SAMPLING FROM -4 [0.57499771 0.55650503] [0.03837737 0.0112773 ] -0.20522140882168874 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), None, None, None, 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4533621249956772 goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 1, array([0.76688456, 0.61289151]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] new direction: [-0.02732618 -0.02921096] reversing there [0.03837737 0.0112773 ] making one step from [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] --> [0.77793575 0.59495785] [-0.02732618 -0.02921096] trying new point, [0.77793575 0.59495785] next() call -0.41530443247762705 goals: [('reflect-at', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3969974267345493 goals: [('bisect', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), None, None, None, 10, array([0.55932632, 0.3612702 ]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55932632 0.3612702 ] [-0.02732618 -0.02921096] -0.3969974267345493 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), None, None, None, 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.24284891598495364 goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33574054173486656 goals: [('bisect', 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4153044324776268 goals: [('bisect', 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 9, array([0.80526193, 0.6241688 ]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.80526193 0.6241688 ] [0.02732618 0.02921096] new direction: [-0.03837737 -0.0112773 ] reversing there [0.02732618 0.02921096] making one step from [0.80526193 0.6241688 ] [0.02732618 0.02921096] --> [0.76688456 0.61289151] [-0.03837737 -0.0112773 ] trying new point, [0.76688456 0.61289151] next() call -0.4533621249956771 goals: [('reflect-at', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39442946604858065 goals: [('bisect', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), None, None, None, 10, array([0.72850719, 0.60161421]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=37 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 BACKWARD SAMPLING FROM 4 [0.8979157 0.491777 ] [-0.03939692 0.00691971] -0.40397152289437405 BACKWARD SAMPLING FROM -4 [0.7869089 0.43641935] [0.03939692 0.00691971] -0.360144051361222 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23267087672305614 goals: [('bisect', 0, array([0.9444966 , 0.46409817]), array([0.03939692, 0.00691971]), None, None, None, 10, array([0.66153415, 0.53329524]), array([-0.03939692, 0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.66153415 0.53329524] [-0.03939692 0.00691971] -0.23267087672305614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4621486800079553 goals: [('bisect', 0, array([0.66153415, 0.53329524]), array([ 0.03939692, -0.00691971]), None, None, None, 10, array([0.9444966 , 0.46409817]), array([-0.03939692, -0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=38 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 BACKWARD SAMPLING FROM 4 [0.5006498 0.516994 ] [-0.03324607 -0.02224182] -0.12893506266001822 BACKWARD SAMPLING FROM -4 [0.65441475 0.53949241] [0.01523716 0.03698417] -0.23362496788797535 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21488037935387833 goals: [('bisect', 0, array([0.6336341 , 0.60596128]), array([-0.03324607, -0.02224182]), None, None, None, 10, array([0.30117336, 0.38354308]), array([-0.03324607, -0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30117336 0.38354308] [-0.03324607 -0.02224182] -0.21488037935387833 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.34109350056274995 goals: [('bisect', 0, array([0.30117336, 0.38354308]), array([0.03324607, 0.02224182]), None, None, None, 10, array([0.6336341 , 0.60596128]), array([0.03324607, 0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 sampling between (-7, 0) ---- seed=39 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 BACKWARD SAMPLING FROM 4 [0.76168405 0.53559656] [0.03992051 0.00252049] -0.3059202287204628 BACKWARD SAMPLING FROM -4 [0.44231997 0.51543261] [0.03992051 0.00252049] -0.10080054489174596 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), None, None, None, 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33944630091534117 goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.41175585311595747 goals: [('bisect', 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4505393331216953 goals: [('bisect', 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4910752823977196 goals: [('bisect', 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 9, array([0.9612866 , 0.54819902]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.99879289 0.55071952] [-0.03992051 0.00252049] new direction: [0.03741642 0.01414255] reversing there [-0.03992051 0.00252049] making one step from [0.99879289 0.55071952] [-0.03992051 0.00252049] --> [0.96379069 0.56486207] [-0.03741642 0.01414255] trying new point, [0.96379069 0.56486207] next() call None goals: [('reflect-at', 10, array([0.96379069, 0.56486207]), array([-0.03741642, 0.01414255]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.9612866 0.54819902] [0.03992051 0.00252049] -0.4910752823977196 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.1893406326438129 goals: [('bisect', 0, array([0.9612866 , 0.54819902]), array([-0.03992051, -0.00252049]), None, None, None, 9, array([0.60200201, 0.52551458]), array([-0.03992051, -0.00252049]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=40 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 BACKWARD SAMPLING FROM 4 [0.50385595 0.57055786] [ 0.00847644 -0.03909156] -0.18916555089029924 BACKWARD SAMPLING FROM -4 [0.6223453 0.49577156] [-0.02398644 0.03201016] -0.19388033318836445 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), None, None, None, 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.42971710884526637 goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 1, array([0.50241308, 0.65582238]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.47842664 0.68783254] [-0.02398644 0.03201016] new direction: [ 0.00847644 -0.03909156] reversing there [-0.02398644 0.03201016] making one step from [0.47842664 0.68783254] [-0.02398644 0.03201016] --> [0.48690307 0.64874098] [ 0.00847644 -0.03909156] trying new point, [0.48690307 0.64874098] next() call -0.39508578257867283 goals: [('reflect-at', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.490019265835001 goals: [('bisect', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), None, None, None, 10, array([0.55471457, 0.3360085 ]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55471457 0.3360085 ] [ 0.00847644 -0.03909156] -0.490019265835001 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), None, None, None, 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14361883567172593 goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2729878665259479 goals: [('bisect', 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3950857825786728 goals: [('bisect', 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 9, array([0.47842664, 0.68783254]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.47842664 0.68783254] [-0.00847644 0.03909156] new direction: [ 0.02398644 -0.03201016] reversing there [-0.00847644 0.03909156] making one step from [0.47842664 0.68783254] [-0.00847644 0.03909156] --> [0.50241308 0.65582238] [ 0.02398644 -0.03201016] trying new point, [0.50241308 0.65582238] next() call -0.42971710884526587 goals: [('reflect-at', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3301665303326673 goals: [('bisect', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), None, None, None, 10, array([0.52639952, 0.62381221]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=41 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 BACKWARD SAMPLING FROM -4 [0.22513362 0.48646827] [-0.02717748 0.02934935] -0.027631419475083484 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.33226605088879657 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4609947924113364 goals: [('bisect', 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 4, array([0.00771378, 0.7212631 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.00771378 0.7212631 ] [-0.02717748 0.02934935] new direction: [ 0.03817639 -0.01193998] reversing there [-0.02717748 0.02934935] making one step from [0.00771378 0.7212631 ] [-0.02717748 0.02934935] --> [0.04589017 0.70932312] [ 0.03817639 -0.01193998] trying new point, [0.04589017 0.70932312] next() call None goals: [('reflect-at', 4, array([0.04589017, 0.70932312]), array([ 0.03817639, -0.01193998]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.022720784505758807 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, -3, array([0.19795614, 0.51581763]), array([-0.02717748, 0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.03489126, 0.69191375]), array([ 0.02717748, -0.02934935]), None, None, None, 3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.19795614 0.51581763] [-0.02717748 0.02934935] -0.022720784505758807 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.19795614, 0.51581763]), array([ 0.02717748, -0.02934935]), None, None, None, -3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=42 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 BACKWARD SAMPLING FROM 4 [0.60933098 0.49592681] [-0.03066574 -0.02568292] -0.18584950597376992 BACKWARD SAMPLING FROM -4 [0.77492096 0.53144407] [0.00613482 0.03952675] -0.31261037020419746 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4031802276107923 goals: [('bisect', 0, array([0.73199394, 0.59865848]), array([-0.03066574, -0.02568292]), None, None, None, 10, array([0.42533653, 0.3418293 ]), array([-0.03066574, -0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.42533653 0.3418293 ] [-0.03066574 -0.02568292] -0.4031802276107923 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38957627172501086 goals: [('bisect', 0, array([0.42533653, 0.3418293 ]), array([0.03066574, 0.02568292]), None, None, None, 10, array([0.73199394, 0.59865848]), array([0.03066574, 0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=43 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 BACKWARD SAMPLING FROM 4 [0.25118164 0.52498669] [ 0.03403177 -0.02101996] -0.039350293891790226 BACKWARD SAMPLING FROM -4 [0.02107251 0.69314638] [-0.03403177 -0.02101996] -0.4665410967293263 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23153067175015277 goals: [('bisect', 0, array([0.11505457, 0.60906654]), array([ 0.03403177, -0.02101996]), None, None, None, 10, array([0.45537225, 0.39886693]), array([ 0.03403177, -0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.45537225 0.39886693] [ 0.03403177 -0.02101996] -0.23153067175015277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.15531265150360327 goals: [('bisect', 0, array([0.45537225, 0.39886693]), array([-0.03403177, 0.02101996]), None, None, None, 10, array([0.11505457, 0.60906654]), array([-0.03403177, 0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=44 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 BACKWARD SAMPLING FROM 4 [0.47062097 0.66599703] [-0.02002389 -0.03462721] -0.4551797092301754 BACKWARD SAMPLING FROM -4 [0.22797682 0.51785252] [0.03283351 0.02284646] -0.02997062159932815 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), None, None, None, 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.39034946973740525 goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.49985733022926904 goals: [('bisect', 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 4, array([0.49064486, 0.70062424]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.49064486 0.70062424] [0.03283351 0.02284646] new direction: [-0.02002389 -0.03462721] reversing there [0.03283351 0.02284646] making one step from [0.49064486 0.70062424] [0.03283351 0.02284646] --> [0.47062097 0.66599703] [-0.02002389 -0.03462721] trying new point, [0.47062097 0.66599703] next() call -0.455179709230175 goals: [('reflect-at', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08322252232880438 goals: [('bisect', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), None, None, None, 10, array([0.35047762, 0.45823376]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.35047762 0.45823376] [-0.02002389 -0.03462721] -0.08322252232880438 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), None, None, None, 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3172442164483675 goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.455179709230175 goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 6, array([0.47062097, 0.66599703]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.49064486 0.70062424] [0.02002389 0.03462721] new direction: [-0.03283351 -0.02284646] reversing there [0.02002389 0.03462721] making one step from [0.49064486 0.70062424] [0.02002389 0.03462721] --> [0.45781135 0.67777777] [-0.03283351 -0.02284646] trying new point, [0.45781135 0.67777777] next() call -0.49985733022926904 goals: [('reflect-at', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21371493658412127 goals: [('bisect', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), None, None, None, 10, array([0.35931084, 0.60923838]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=45 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036039 BACKWARD SAMPLING FROM -4 [0.34228361 0.59592598] [ 0.02554647 -0.0307795 ] -0.1736014655895373 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.22125039734136934 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.31437162423426 goals: [('bisect', 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4318299192036037 goals: [('bisect', 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 4, array([0.54665538, 0.34968996]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] new direction: [-0.03976603 -0.00432004] reversing there [ 0.02554647 -0.0307795 ] making one step from [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] --> [0.53243582 0.31459041] [-0.03976603 -0.00432004] trying new point, [0.53243582 0.31459041] next() call None goals: [('reflect-at', 5, array([0.53243582, 0.31459041]), array([-0.03976603, -0.00432004]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.087909125121415 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, -1, array([0.41892303, 0.50358747]), array([ 0.02554647, -0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036037 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.10801914778494678 goals: [('bisect', 0, array([0.54665538, 0.34968996]), array([-0.02554647, 0.0307795 ]), None, None, None, 4, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.41892303 0.50358747] [ 0.02554647 -0.0307795 ] -0.087909125121415 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.10801914778494684 goals: [('bisect', 0, array([0.41892303, 0.50358747]), array([-0.02554647, 0.0307795 ]), None, None, None, -1, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=46 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 BACKWARD SAMPLING FROM 4 [0.15144064 0.55838923] [0.0271438 0.02938051] -0.05408341768692817 BACKWARD SAMPLING FROM -4 [0.06570974 0.32334517] [-0.0271438 0.02938051] -0.3922454873386127 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), None, None, None, 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.11224029674516076 goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2955054800380875 goals: [('bisect', 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4206137842727819 goals: [('bisect', 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 9, array([0.28715963, 0.70529177]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.28715963 0.70529177] [0.0271438 0.02938051] new direction: [ 0.02281179 -0.03285761] reversing there [0.0271438 0.02938051] making one step from [0.28715963 0.70529177] [0.0271438 0.02938051] --> [0.30997142 0.67243417] [ 0.02281179 -0.03285761] trying new point, [0.30997142 0.67243417] next() call -0.41971042152871735 goals: [('reflect-at', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2988925458881023 goals: [('bisect', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), None, None, None, 10, array([0.33278321, 0.63957656]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.33278321 0.63957656] [ 0.02281179 -0.03285761] -0.2988925458881023 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), None, None, None, 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.41971042152871735 goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 1, array([0.30997142, 0.67243417]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.28715963 0.70529177] [-0.02281179 0.03285761] new direction: [-0.0271438 -0.02938051] reversing there [-0.02281179 0.03285761] making one step from [0.28715963 0.70529177] [-0.02281179 0.03285761] --> [0.26001583 0.67591127] [-0.0271438 -0.02938051] trying new point, [0.26001583 0.67591127] next() call -0.4206137842727819 goals: [('reflect-at', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04462731870887185 goals: [('bisect', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), None, None, None, 10, array([0.04286545, 0.4408672 ]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=47 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 BACKWARD SAMPLING FROM 4 [0.56078481 0.55029357] [-0.02119426 0.03392349] -0.18885784622089788 BACKWARD SAMPLING FROM -1 [0.66675612 0.38067612] [-0.02119426 0.03392349] -0.40025922669221325 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), None, None, None, 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23423540704363024 goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4126483656060907 goals: [('bisect', 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 8, array([0.47600776, 0.68598754]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.47600776 0.68598754] [-0.02119426 0.03392349] new direction: [-0.02911927 -0.02742386] reversing there [-0.02119426 0.03392349] making one step from [0.47600776 0.68598754] [-0.02119426 0.03392349] --> [0.44688849 0.65856368] [-0.02911927 -0.02742386] trying new point, [0.44688849 0.65856368] next() call -0.4141351863645779 goals: [('reflect-at', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20998692233081806 goals: [('bisect', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), None, None, None, 10, array([0.38864994, 0.60371597]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.38864994 0.60371597] [-0.02911927 -0.02742386] -0.20998692233081806 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), None, None, None, 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4141351863645779 goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 3, array([0.47600776, 0.68598754]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.47600776 0.68598754] [0.02911927 0.02742386] new direction: [ 0.02119426 -0.03392349] reversing there [0.02911927 0.02742386] making one step from [0.47600776 0.68598754] [0.02911927 0.02742386] --> [0.49720203 0.65206405] [ 0.02119426 -0.03392349] trying new point, [0.49720203 0.65206405] next() call -0.4126483656060907 goals: [('reflect-at', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2995403926532866 goals: [('bisect', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), None, None, None, 10, array([0.64556185, 0.41459961]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=48 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 BACKWARD SAMPLING FROM 4 [0.70528601 0.43395284] [-0.03985609 -0.00338995] -0.3032420227989266 BACKWARD SAMPLING FROM -4 [0.90468504 0.44962923] [0.03979681 0.00402662] -0.44094269508821465 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20193125737173862 goals: [('bisect', 0, array([0.86471039, 0.44751263]), array([-0.03985609, -0.00338995]), None, None, None, 10, array([0.46614944, 0.41361315]), array([-0.03985609, -0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.46614944 0.41361315] [-0.03985609 -0.00338995] -0.20193125737173862 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.40829857363895855 goals: [('bisect', 0, array([0.46614944, 0.41361315]), array([0.03985609, 0.00338995]), None, None, None, 10, array([0.86471039, 0.44751263]), array([0.03985609, 0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 sampling between (-6, 1) ---- seed=49 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 BACKWARD SAMPLING FROM 4 [0.69043306 0.40704478] [ 0.00178908 -0.03995997] -0.3463573209308397 BACKWARD SAMPLING FROM -4 [0.55985875 0.65300213] [ 0.03994662 -0.00206584] -0.44934157693712723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), None, None, None, 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4604163445319175 goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 6, array([0.69401122, 0.32712484]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.69401122 0.32712484] [ 0.00178908 -0.03995997] new direction: [-0.03993708 -0.00224268] reversing there [ 0.00178908 -0.03995997] making one step from [0.69401122 0.32712484] [ 0.00178908 -0.03995997] --> [0.65407414 0.32488216] [-0.03993708 -0.00224268] trying new point, [0.65407414 0.32488216] next() call None goals: [('reflect-at', 6, array([0.65407414, 0.32488216]), array([-0.03993708, -0.00224268]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.68506584 0.52692469] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.69222214 0.36708481] [ 0.00178908 -0.03995997] -0.4604163445319175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2893530363157967 goals: [('bisect', 0, array([0.69222214, 0.36708481]), array([-0.00178908, 0.03995997]), None, None, None, 5, array([0.68327676, 0.56688466]), array([-0.00178908, 0.03995997]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -10..5 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-10, 5) ---- seed=50 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 BACKWARD SAMPLING FROM 4 [0.13808816 0.33647507] [0.00832488 0.03912411] -0.3437892113032023 BACKWARD SAMPLING FROM -4 [0.38118457 0.49530887] [-0.03142766 -0.02474474] -0.07292592188692902 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), None, None, None, 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31177413021896305 goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4086155422937598 goals: [('bisect', 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 4, array([0.12976328, 0.29735095]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.12976328 0.29735095] [-0.03142766 -0.02474474] new direction: [0.00832488 0.03912411] reversing there [-0.03142766 -0.02474474] making one step from [0.12976328 0.29735095] [-0.03142766 -0.02474474] --> [0.13808816 0.33647507] [0.00832488 0.03912411] trying new point, [0.13808816 0.33647507] next() call -0.3437892113032023 goals: [('reflect-at', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08108221261480617 goals: [('bisect', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), None, None, None, 10, array([0.18803745, 0.57121976]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18803745 0.57121976] [0.00832488 0.03912411] -0.08108221261480617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), None, None, None, 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.20416293012453088 goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3437892113032023 goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 6, array([0.13808816, 0.33647507]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.12976328 0.29735095] [-0.00832488 -0.03912411] new direction: [0.03142766 0.02474474] reversing there [-0.00832488 -0.03912411] making one step from [0.12976328 0.29735095] [-0.00832488 -0.03912411] --> [0.16119094 0.32209569] [0.03142766 0.02474474] trying new point, [0.16119094 0.32209569] next() call -0.4086155422937598 goals: [('reflect-at', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16697705808604757 goals: [('bisect', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), None, None, None, 10, array([0.25547392, 0.39632991]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=51 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 BACKWARD SAMPLING FROM -4 [0.40032887 0.49452683] [-0.0142563 0.03737322] -0.08050604831793806 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4654286221899625 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 1, array([0.32904737, 0.68139295]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.31479107 0.71876618] [-0.0142563 0.03737322] new direction: [-0.039365 -0.00709908] reversing there [-0.0142563 0.03737322] making one step from [0.31479107 0.71876618] [-0.0142563 0.03737322] --> [0.27542607 0.7116671 ] [-0.039365 -0.00709908] trying new point, [0.27542607 0.7116671 ] next() call None goals: [('reflect-at', 2, array([0.27542607, 0.7116671 ]), array([-0.039365 , -0.00709908]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.27101878092937887 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, -7, array([0.44309777, 0.38240716]), array([-0.0142563 , 0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.32904737, 0.68139295]), array([ 0.0142563 , -0.03737322]), None, None, None, 1, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.44309777 0.38240716] [-0.0142563 0.03737322] -0.27101878092937887 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.44309777, 0.38240716]), array([ 0.0142563 , -0.03737322]), None, None, None, -7, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=52 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 BACKWARD SAMPLING FROM 4 [0.36003865 0.56081047] [ 0.037317 -0.01440282] -0.11103783451846358 BACKWARD SAMPLING FROM -4 [0.06150263 0.67603307] [ 0.037317 -0.01440282] -0.3892367900814762 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17868949115336583 goals: [('bisect', 0, array([0.21077064, 0.61842177]), array([ 0.037317 , -0.01440282]), None, None, None, 10, array([0.58394066, 0.47439353]), array([ 0.037317 , -0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.58394066 0.47439353] [ 0.037317 -0.01440282] -0.17868949115336583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19750857452717718 goals: [('bisect', 0, array([0.58394066, 0.47439353]), array([-0.037317 , 0.01440282]), None, None, None, 10, array([0.21077064, 0.61842177]), array([-0.037317 , 0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=53 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 BACKWARD SAMPLING FROM 4 [0.72477641 0.45751322] [-0.0304715 -0.02591308] -0.28521449853834674 BACKWARD SAMPLING FROM -1 [0.87713391 0.58707862] [-0.0304715 -0.02591308] -0.4794655207604886 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), None, None, None, 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2995114075574864 goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.38125233905933353 goals: [('bisect', 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4486963615420411 goals: [('bisect', 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 9, array([0.57241891, 0.32794783]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.57241891 0.32794783] [-0.0304715 -0.02591308] new direction: [-0.00163041 -0.03996676] reversing there [-0.0304715 -0.02591308] making one step from [0.57241891 0.32794783] [-0.0304715 -0.02591308] --> [0.5707885 0.28798107] [-0.00163041 -0.03996676] trying new point, [0.5707885 0.28798107] next() call None goals: [('reflect-at', 9, array([0.5707885 , 0.28798107]), array([-0.00163041, -0.03996676]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.60289041 0.3538609 ] [-0.0304715 -0.02591308] -0.4486963615420411 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.40518390734034826 goals: [('bisect', 0, array([0.60289041, 0.3538609 ]), array([0.0304715 , 0.02591308]), None, None, None, 8, array([0.84666241, 0.56116554]), array([0.0304715 , 0.02591308]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=54 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 BACKWARD SAMPLING FROM 4 [0.29205086 0.4590631 ] [-0.03203303 0.0239559 ] -0.06359472404742703 BACKWARD SAMPLING FROM -1 [0.45221599 0.3392836 ] [-0.03203303 0.0239559 ] -0.4251216837222281 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13707944044464876 goals: [('bisect', 0, array([0.42018297, 0.3632395 ]), array([-0.03203303, 0.0239559 ]), None, None, None, 10, array([0.0998527 , 0.60279851]), array([-0.03203303, 0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0998527 0.60279851] [-0.03203303 0.0239559 ] -0.13707944044464876 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.32206980281714764 goals: [('bisect', 0, array([0.0998527 , 0.60279851]), array([ 0.03203303, -0.0239559 ]), None, None, None, 10, array([0.42018297, 0.3632395 ]), array([ 0.03203303, -0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=55 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 BACKWARD SAMPLING FROM 4 [0.06288283 0.47543852] [ 0.01800544 -0.0357184 ] -0.00951795620141871 BACKWARD SAMPLING FROM -2 [0.04514983 0.68974891] [-0.01800544 -0.0357184 ] -0.45107737484070604 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), None, None, None, 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.04869226052335881 goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2236987612488 goals: [('bisect', 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3595309576523012 goals: [('bisect', 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 9, array([0.15291004, 0.29684652]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] new direction: [-0.03842475 0.01111479] reversing there [ 0.01800544 -0.0357184 ] making one step from [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] --> [0.11448528 0.30796131] [-0.03842475 0.01111479] trying new point, [0.11448528 0.30796131] next() call -0.46753918956341406 goals: [('reflect-at', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41206085167620243 goals: [('bisect', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), None, None, None, 10, array([0.07606053, 0.31907609]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.07606053 0.31907609] [-0.03842475 0.01111479] -0.41206085167620243 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), None, None, None, 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.46753918956341406 goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 1, array([0.11448528, 0.30796131]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15291004 0.29684652] [ 0.03842475 -0.01111479] new direction: [-0.01800544 0.0357184 ] reversing there [ 0.03842475 -0.01111479] making one step from [0.15291004 0.29684652] [ 0.03842475 -0.01111479] --> [0.13490459 0.33256492] [-0.01800544 0.0357184 ] trying new point, [0.13490459 0.33256492] next() call -0.3595309576523012 goals: [('reflect-at', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17501371251886214 goals: [('bisect', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), None, None, None, 10, array([0.00913894, 0.61831211]), array([0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=56 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 BACKWARD SAMPLING FROM 4 [0.39113326 0.5298137 ] [0.03582093 0.01780059] -0.08760332684710367 BACKWARD SAMPLING FROM -4 [0.10456585 0.38740895] [0.03582093 0.01780059] -0.16392632784250208 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41695714617072094 goals: [('bisect', 0, array([0.24784955, 0.45861133]), array([0.03582093, 0.01780059]), None, None, None, 10, array([0.60605882, 0.63661727]), array([0.03582093, 0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.60605882 0.63661727] [0.03582093 0.01780059] -0.41695714617072094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05212748066477112 goals: [('bisect', 0, array([0.60605882, 0.63661727]), array([-0.03582093, -0.01780059]), None, None, None, 10, array([0.24784955, 0.45861133]), array([-0.03582093, -0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -5..10 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd new NUTS range: -5..26 NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd sampling between (-5, 26) ---- seed=57 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520403 BACKWARD SAMPLING FROM -4 [0.59526516 0.38777109] [-0.00732732 0.03932315] -0.3346119116596618 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.34326862471080793 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4802014861520402 goals: [('bisect', 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 4, array([0.53664662, 0.70235632]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.53664662 0.70235632] [-0.00732732 0.03932315] new direction: [-0.03991081 -0.00266972] reversing there [-0.00732732 0.03932315] making one step from [0.53664662 0.70235632] [-0.00732732 0.03932315] --> [0.49673582 0.69968659] [-0.03991081 -0.00266972] trying new point, [0.49673582 0.69968659] next() call None goals: [('reflect-at', 4, array([0.49673582, 0.69968659]), array([-0.03991081, -0.00266972]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.23927607150196617 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, -3, array([0.58793784, 0.42709424]), array([-0.00732732, 0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.54397394, 0.66303317]), array([ 0.00732732, -0.03932315]), None, None, None, 3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.58793784 0.42709424] [-0.00732732 0.03932315] -0.23927607150196617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.58793784, 0.42709424]), array([ 0.00732732, -0.03932315]), None, None, None, -3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=58 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 BACKWARD SAMPLING FROM 4 [0.52440832 0.43628484] [ 0.03982568 -0.00373027] -0.18824731253691152 BACKWARD SAMPLING FROM -4 [0.20580285 0.46612699] [ 0.03982568 -0.00373027] -0.03551966453010344 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3840192746128853 goals: [('bisect', 0, array([0.36510558, 0.45120592]), array([ 0.03982568, -0.00373027]), None, None, None, 10, array([0.76336242, 0.41390323]), array([ 0.03982568, -0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76336242 0.41390323] [ 0.03982568 -0.00373027] -0.3840192746128853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09641182642477081 goals: [('bisect', 0, array([0.76336242, 0.41390323]), array([-0.03982568, 0.00373027]), None, None, None, 10, array([0.36510558, 0.45120592]), array([-0.03982568, 0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=59 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 BACKWARD SAMPLING FROM 4 [0.4021635 0.49826765] [ 0.03647074 -0.01642819] -0.08090525343003006 BACKWARD SAMPLING FROM -4 [0.11039762 0.62969317] [ 0.03647074 -0.01642819] -0.2163478092623813 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.318567864176321 goals: [('bisect', 0, array([0.25628056, 0.56398041]), array([ 0.03647074, -0.01642819]), None, None, None, 10, array([0.62098791, 0.39969851]), array([ 0.03647074, -0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.62098791 0.39969851] [ 0.03647074 -0.01642819] -0.318567864176321 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08400852608514758 goals: [('bisect', 0, array([0.62098791, 0.39969851]), array([-0.03647074, 0.01642819]), None, None, None, 10, array([0.25628056, 0.56398041]), array([-0.03647074, 0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=60 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 BACKWARD SAMPLING FROM 4 [0.48306538 0.65962424] [ 0.03997068 -0.00153133] -0.43517479808588755 BACKWARD SAMPLING FROM -4 [0.16329997 0.6718749 ] [ 0.03997068 -0.00153133] -0.3825957187127649 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), None, None, None, 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.44920044099302747 goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.482220565464306 goals: [('bisect', 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 8, array([0.64294809, 0.6534989 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] new direction: [0.0021526 0.03994204] reversing there [ 0.03997068 -0.00153133] making one step from [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] --> [0.64510069 0.69344094] [0.0021526 0.03994204] trying new point, [0.64510069 0.69344094] next() call None goals: [('reflect-at', 8, array([0.64510069, 0.69344094]), array([0.0021526 , 0.03994204]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.60297742 0.65503024] [ 0.03997068 -0.00153133] -0.482220565464306 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.39563502198066103 goals: [('bisect', 0, array([0.60297742, 0.65503024]), array([-0.03997068, 0.00153133]), None, None, None, 7, array([0.32318268, 0.66574957]), array([-0.03997068, 0.00153133]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=61 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 BACKWARD SAMPLING FROM 4 [0.72389146 0.54491217] [-0.03835883 0.01134021] -0.28722320791367995 BACKWARD SAMPLING FROM -4 [0.91257131 0.47071355] [ 0.03991597 -0.00259145] -0.4271143991277972 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2813698847877405 goals: [('bisect', 0, array([0.87732677, 0.49955131]), array([-0.03835883, 0.01134021]), None, None, None, 10, array([0.49373851, 0.61295345]), array([-0.03835883, 0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.49373851 0.61295345] [-0.03835883 0.01134021] -0.2813698847877405 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38485364567003044 goals: [('bisect', 0, array([0.49373851, 0.61295345]), array([ 0.03835883, -0.01134021]), None, None, None, 10, array([0.87732677, 0.49955131]), array([ 0.03835883, -0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=62 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 BACKWARD SAMPLING FROM -4 [0.05117488 0.64815636] [-0.00435504 -0.03976221] -0.2756882768233669 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10250385662007835 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.21204660991891755 goals: [('bisect', 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3611341698842485 goals: [('bisect', 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 4, array([0.01633454, 0.33005865]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.0119795 0.29029644] [-0.00435504 -0.03976221] new direction: [ 0.03630756 -0.01678574] reversing there [-0.00435504 -0.03976221] making one step from [0.0119795 0.29029644] [-0.00435504 -0.03976221] --> [0.04828706 0.2735107 ] [ 0.03630756 -0.01678574] trying new point, [0.04828706 0.2735107 ] next() call None goals: [('reflect-at', 5, array([0.04828706, 0.2735107 ]), array([ 0.03630756, -0.01678574]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.011144436722510533 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, -1, array([0.03810975, 0.52886972]), array([-0.00435504, -0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.0020527700218748433 goals: [('bisect', 0, array([0.01633454, 0.33005865]), array([0.00435504, 0.03976221]), None, None, None, 4, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.03810975 0.52886972] [-0.00435504 -0.03976221] -0.011144436722510533 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0020527700218748585 goals: [('bisect', 0, array([0.03810975, 0.52886972]), array([0.00435504, 0.03976221]), None, None, None, -1, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=63 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 BACKWARD SAMPLING FROM 4 [0.4072226 0.46007348] [-0.03667961 0.0159564 ] -0.10284171548913772 BACKWARD SAMPLING FROM -4 [0.586297 0.36749354] [ 0.03884142 -0.00955742] -0.3913466099390096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05644864986759578 goals: [('bisect', 0, array([0.55394102, 0.39624789]), array([-0.03667961, 0.0159564 ]), None, None, None, 10, array([0.18714497, 0.55581185]), array([-0.03667961, 0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18714497 0.55581185] [-0.03667961 0.0159564 ] -0.05644864986759578 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2879815727116586 goals: [('bisect', 0, array([0.18714497, 0.55581185]), array([ 0.03667961, -0.0159564 ]), None, None, None, 10, array([0.55394102, 0.39624789]), array([ 0.03667961, -0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=64 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 BACKWARD SAMPLING FROM 4 [0.39993594 0.60551572] [ 0.00067241 -0.03999435] -0.21914395901276984 BACKWARD SAMPLING FROM -4 [0.35310841 0.40922317] [0.00649753 0.03946875] -0.16534817926836115 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), None, None, None, 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.343448880085709 goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 3, array([0.39859111, 0.68550441]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.39859111 0.68550441] [0.00649753 0.03946875] new direction: [ 0.00067241 -0.03999435] reversing there [0.00649753 0.03946875] making one step from [0.39859111 0.68550441] [0.00649753 0.03946875] --> [0.39926352 0.64551007] [ 0.00067241 -0.03999435] trying new point, [0.39926352 0.64551007] next() call -0.3443704192313505 goals: [('reflect-at', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.30755732018362913 goals: [('bisect', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), None, None, None, 10, array([0.40397041, 0.36554963]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.40397041 0.36554963] [ 0.00067241 -0.03999435] -0.30755732018362913 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), None, None, None, 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.13390664748382503 goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3443704192313509 goals: [('bisect', 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 8, array([0.39859111, 0.68550441]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.39859111 0.68550441] [-0.00067241 0.03999435] new direction: [-0.00649753 -0.03946875] reversing there [-0.00067241 0.03999435] making one step from [0.39859111 0.68550441] [-0.00067241 0.03999435] --> [0.39209358 0.64603566] [-0.00649753 -0.03946875] trying new point, [0.39209358 0.64603566] next() call -0.3434488800857094 goals: [('reflect-at', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12813489647882276 goals: [('bisect', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), None, None, None, 10, array([0.37909853, 0.56709817]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=65 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 BACKWARD SAMPLING FROM 4 [0.1092311 0.61062131] [-0.03020213 0.02622654] -0.1589291517496356 BACKWARD SAMPLING FROM -4 [0.35084815 0.40080902] [-0.03020213 0.02622654] -0.18453284519551352 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), None, None, None, 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23721446196834403 goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44810893033872173 goals: [('bisect', 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 8, array([0.01157743, 0.71552746]), array([0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.01157743 0.71552746] [0.03020213 0.02622654] new direction: [0.03498847 0.01938573] reversing there [0.03020213 0.02622654] making one step from [0.01157743 0.71552746] [0.03020213 0.02622654] --> [0.0465659 0.73491319] [0.03498847 0.01938573] trying new point, [0.0465659 0.73491319] next() call None goals: [('reflect-at', 8, array([0.0465659 , 0.73491319]), array([0.03498847, 0.01938573]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.0186247 0.68930092] [-0.03020213 0.02622654] -0.44810893033872173 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.026867403984676807 goals: [('bisect', 0, array([0.0186247 , 0.68930092]), array([ 0.03020213, -0.02622654]), None, None, None, 7, array([0.23003963, 0.50571517]), array([ 0.03020213, -0.02622654]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=66 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BACKWARD SAMPLING FROM 4 [0.43880939 0.53837811] [ 0.01903098 -0.03518269] -0.1146878297183696 BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), None, None, None, 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.10493653469527497 goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.17935711354999778 goals: [('bisect', 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2635289874278154 goals: [('bisect', 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.37900858427260387 goals: [('bisect', 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 9, array([0.53396429, 0.36246465]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.55299527 0.32728196] [ 0.01903098 -0.03518269] new direction: [-0.03590325 0.01763396] reversing there [ 0.01903098 -0.03518269] making one step from [0.55299527 0.32728196] [ 0.01903098 -0.03518269] --> [0.51709202 0.34491592] [-0.03590325 0.01763396] trying new point, [0.51709202 0.34491592] next() call -0.4343304840564407 goals: [('reflect-at', 10, array([0.51709202, 0.34491592]), array([-0.03590325, 0.01763396]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.51709202 0.34491592] [-0.03590325 0.01763396] -0.4343304840564407 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), None, None, None, 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 1, array([0.55299527, 0.32728196]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.55299527 0.32728196] [ 0.03590325 -0.01763396] new direction: [-0.01903098 0.03518269] reversing there [ 0.03590325 -0.01763396] making one step from [0.55299527 0.32728196] [ 0.03590325 -0.01763396] --> [0.53396429 0.36246465] [-0.01903098 0.03518269] trying new point, [0.53396429 0.36246465] next() call -0.379008584272604 goals: [('reflect-at', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.46677023948045687 goals: [('bisect', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), None, None, None, 10, array([0.36268547, 0.67910888]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=67 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 BACKWARD SAMPLING FROM 4 [0.08924898 0.33300678] [0.01670024 0.03634697] -0.3525668892829215 BACKWARD SAMPLING FROM -4 [0.1925446 0.47589575] [-0.03313667 -0.02240449] -0.025799396299807646 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), None, None, None, 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31417147356422026 goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4099982344835686 goals: [('bisect', 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 4, array([0.07254874, 0.29665981]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.07254874 0.29665981] [ 0.03313667 -0.02240449] new direction: [0.01670024 0.03634697] reversing there [ 0.03313667 -0.02240449] making one step from [0.07254874 0.29665981] [ 0.03313667 -0.02240449] --> [0.08924898 0.33300678] [0.01670024 0.03634697] trying new point, [0.08924898 0.33300678] next() call -0.3525668892829215 goals: [('reflect-at', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05057127231465654 goals: [('bisect', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), None, None, None, 10, array([0.1894504 , 0.55108859]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.1894504 0.55108859] [0.01670024 0.03634697] -0.05057127231465654 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), None, None, None, 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.218968162054107 goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3525668892829218 goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 6, array([0.08924898, 0.33300678]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.07254874 0.29665981] [-0.01670024 -0.03634697] new direction: [-0.03313667 0.02240449] reversing there [-0.01670024 -0.03634697] making one step from [0.07254874 0.29665981] [-0.01670024 -0.03634697] --> [0.03941207 0.3190643 ] [-0.03313667 0.02240449] trying new point, [0.03941207 0.3190643 ] next() call -0.4099982344835688 goals: [('reflect-at', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16345916433290641 goals: [('bisect', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), None, None, None, 10, array([0.05999793, 0.38627778]), array([0.03313667, 0.02240449]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=68 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592275 BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4554553560620388 goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48725395469592286 goals: [('bisect', 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 4, array([0.90228929, 0.39247251]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.90228929 0.39247251] [-0.0176335 -0.03590348] new direction: [-0.0084219 -0.03910335] reversing there [-0.0176335 -0.03590348] making one step from [0.90228929 0.39247251] [-0.0176335 -0.03590348] --> [0.8938674 0.35336917] [-0.0084219 -0.03910335] trying new point, [0.8938674 0.35336917] next() call None goals: [('reflect-at', 4, array([0.8938674 , 0.35336917]), array([-0.0084219 , -0.03910335]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 None -3 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -2 -3 continue bisect at -1 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -1, array([0.99045679, 0.5719899 ]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -1 -2 bisecting gave reflection point -1 [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] new direction: [-0.03469108 0.01991304] reversing there [-0.0176335 -0.03590348] making one step from [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] --> [0.95576572 0.59190294] [ 0.03469108 -0.01991304] trying new point, [0.95576572 0.59190294] next() call None goals: [('reflect-at', -1, array([0.95576572, 0.59190294]), array([ 0.03469108, -0.01991304]), -1), ('sample-at', -3)] goals: [('sample-at', -3)] reversing at 0... -3 steps to do at 0 -> [from -1, delta=-3] targeting 2. goals: [('sample-at', 2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.4894704551842364 goals: [('bisect', 0, array([0.91992279, 0.42837599]), array([0.0176335 , 0.03590348]), None, None, None, 3, array([0.97282329, 0.53608642]), array([0.0176335 , 0.03590348]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=69 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 BACKWARD SAMPLING FROM 4 [0.08314008 0.33011112] [0.0398791 0.00310763] -0.3642340475299841 BACKWARD SAMPLING FROM -4 [0.23379485 0.34519503] [ 0.00209787 -0.03994495] -0.32688726566612836 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3379065727944484 goals: [('bisect', 0, array([0.07637632, 0.3176806 ]), array([-0.0398791 , 0.00310763]), None, None, None, 10, array([0.32241468, 0.3487569 ]), array([0.0398791 , 0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32241468 0.3487569 ] [0.0398791 0.00310763] -0.3379065727944484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4184212317690846 goals: [('bisect', 0, array([0.32241468, 0.3487569 ]), array([-0.0398791 , -0.00310763]), None, None, None, 10, array([0.07637632, 0.3176806 ]), array([ 0.0398791 , -0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=70 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 BACKWARD SAMPLING FROM -4 [0.72439543 0.5193604 ] [ 0.03378467 -0.02141486] -0.2670596822248383 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.49518079847518337 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 1, array([0.89331877, 0.41228611]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.92710344 0.39087125] [ 0.03378467 -0.02141486] new direction: [-0.03988025 -0.00309289] reversing there [ 0.03378467 -0.02141486] making one step from [0.92710344 0.39087125] [ 0.03378467 -0.02141486] --> [0.88722319 0.38777836] [-0.03988025 -0.00309289] trying new point, [0.88722319 0.38777836] next() call None goals: [('reflect-at', 2, array([0.88722319, 0.38777836]), array([-0.03988025, -0.00309289]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.28146270933833795 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, -7, array([0.62304142, 0.58360498]), array([ 0.03378467, -0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.89331877, 0.41228611]), array([-0.03378467, 0.02141486]), None, None, None, 1, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.62304142 0.58360498] [ 0.03378467 -0.02141486] -0.28146270933833795 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.62304142, 0.58360498]), array([-0.03378467, 0.02141486]), None, None, None, -7, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=71 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 BACKWARD SAMPLING FROM 4 [0.25971764 0.3556196 ] [0.01088008 0.03849187] -0.29429788638027965 BACKWARD SAMPLING FROM -4 [0.11573234 0.53055056] [ 0.01746073 -0.03598781] -0.018363694539417472 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), None, None, None, 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4538641787707029 goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 3, array([0.23795748, 0.27863586]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23795748 0.27863586] [ 0.01746073 -0.03598781] new direction: [0.01088008 0.03849187] reversing there [ 0.01746073 -0.03598781] making one step from [0.23795748 0.27863586] [ 0.01746073 -0.03598781] --> [0.24883756 0.31712773] [0.01088008 0.03849187] trying new point, [0.24883756 0.31712773] next() call -0.44898840843073634 goals: [('reflect-at', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.14649318477587447 goals: [('bisect', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), None, None, None, 10, array([0.32499811, 0.5865708 ]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32499811 0.5865708 ] [0.01088008 0.03849187] -0.14649318477587447 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), None, None, None, 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.17676633722022025 goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44898840843073634 goals: [('bisect', 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 8, array([0.23795748, 0.27863586]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23795748 0.27863586] [-0.01088008 -0.03849187] new direction: [-0.01746073 0.03598781] reversing there [-0.01088008 -0.03849187] making one step from [0.23795748 0.27863586] [-0.01088008 -0.03849187] --> [0.22049674 0.31462368] [-0.01746073 0.03598781] trying new point, [0.22049674 0.31462368] next() call -0.4538641787707029 goals: [('reflect-at', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1779655671937919 goals: [('bisect', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), None, None, None, 10, array([0.18557527, 0.3865993 ]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-7, 0) ---- seed=72 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM -4 [0.20355555 0.55695974] [-0.02420434 0.03184572] -0.06127258297454431 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 1, array([0.08253387, 0.71618836]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.08253387 0.71618836] [-0.02420434 0.03184572] new direction: [-0.03993916 0.0022054 ] reversing there [-0.02420434 0.03184572] making one step from [0.08253387 0.71618836] [-0.02420434 0.03184572] --> [0.04259471 0.71839376] [-0.03993916 0.0022054 ] trying new point, [0.04259471 0.71839376] next() call None goals: [('reflect-at', 1, array([0.04259471, 0.71839376]), array([-0.03993916, 0.0022054 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.1834117210951967 goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, -9, array([0.32457724, 0.39773113]), array([-0.02420434, 0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.32457724 0.39773113] [-0.02420434 0.03184572] -0.1834117210951967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4304741024618556 goals: [('bisect', 0, array([0.32457724, 0.39773113]), array([ 0.02420434, -0.03184572]), None, None, None, -9, array([0.1067382 , 0.68434263]), array([ 0.02420434, -0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=73 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 BACKWARD SAMPLING FROM 4 [0.72214504 0.62997003] [-0.03328493 -0.02218362] -0.4718993295718914 BACKWARD SAMPLING FROM -4 [0.52994985 0.42508821] [0.02818502 0.02838318] -0.21057062182068897 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), None, None, None, 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3580765940944526 goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.45593173307845614 goals: [('bisect', 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 4, array([0.75542998, 0.65215365]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.75542998 0.65215365] [0.02818502 0.02838318] new direction: [-0.03328493 -0.02218362] reversing there [0.02818502 0.02838318] making one step from [0.75542998 0.65215365] [0.02818502 0.02838318] --> [0.72214504 0.62997003] [-0.03328493 -0.02218362] trying new point, [0.72214504 0.62997003] next() call -0.4718993295718915 goals: [('reflect-at', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13659198800339803 goals: [('bisect', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), None, None, None, 10, array([0.52243544, 0.49686829]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.52243544 0.49686829] [-0.03328493 -0.02218362] -0.13659198800339803 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), None, None, None, 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.38248798494168457 goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4718993295718915 goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 6, array([0.72214504, 0.62997003]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.75542998 0.65215365] [0.03328493 0.02218362] new direction: [-0.02818502 -0.02838318] reversing there [0.03328493 0.02218362] making one step from [0.75542998 0.65215365] [0.03328493 0.02218362] --> [0.72724496 0.62377047] [-0.02818502 -0.02838318] trying new point, [0.72724496 0.62377047] next() call -0.4559317330784566 goals: [('reflect-at', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2251698677879109 goals: [('bisect', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), None, None, None, 10, array([0.64268992, 0.53862093]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: 0..15 sampling between (0, 15) ---- seed=74 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 BACKWARD SAMPLING FROM 4 [0.908303 0.46166811] [-0.03985264 0.00343029] -0.4308738435817744 BACKWARD SAMPLING FROM -4 [0.7125903 0.50525487] [ 0.03934543 -0.00720676] -0.2542376365289063 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38560758459709216 goals: [('bisect', 0, array([0.869972 , 0.47642782]), array([ 0.03934543, -0.00720676]), None, None, None, 10, array([0.73657373, 0.4043602 ]), array([-0.03934543, -0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.73657373 0.4043602 ] [-0.03934543 -0.00720676] -0.38560758459709216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3853712408253484 goals: [('bisect', 0, array([0.73657373, 0.4043602 ]), array([0.03934543, 0.00720676]), None, None, None, 10, array([0.869972 , 0.47642782]), array([-0.03934543, 0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -14..1 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-14, 1) ---- seed=75 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 BACKWARD SAMPLING FROM 4 [0.8243863 0.61256616] [0.03617356 0.01707259] -0.49819564920674286 BACKWARD SAMPLING FROM -4 [0.53499778 0.47598547] [0.03617356 0.01707259] -0.15032003434226449 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), None, None, None, 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3596546025768169 goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.42462744731562935 goals: [('bisect', 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49819564920674275 goals: [('bisect', 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 4, array([0.8243863 , 0.61256616]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.86055987 0.62963875] [0.03617356 0.01707259] new direction: [-0.01645837 -0.03645713] reversing there [0.03617356 0.01707259] making one step from [0.86055987 0.62963875] [0.03617356 0.01707259] --> [0.84410149 0.59318162] [-0.01645837 -0.03645713] trying new point, [0.84410149 0.59318162] next() call -0.46478885376243206 goals: [('reflect-at', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3894210121323491 goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), None, None, None, 10, array([0.76180964, 0.41089599]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76180964 0.41089599] [-0.01645837 -0.03645713] -0.3894210121323491 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), None, None, None, 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46478885376243206 goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 6, array([0.86055987, 0.62963875]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.86055987 0.62963875] [0.01645837 0.03645713] new direction: [-0.03617356 -0.01707259] reversing there [0.01645837 0.03645713] making one step from [0.86055987 0.62963875] [0.01645837 0.03645713] --> [0.8243863 0.61256616] [-0.03617356 -0.01707259] trying new point, [0.8243863 0.61256616] next() call -0.4981956492067427 goals: [('reflect-at', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25549498455609504 goals: [('bisect', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), None, None, None, 10, array([0.67969204, 0.54427582]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -12..3 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-12, 3) ---- seed=76 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BACKWARD SAMPLING FROM 4 [0.68160346 0.52744316] [0.0063244 0.03949686] -0.24170572618743733 BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), None, None, None, 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2926344475809864 goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3826032159139785 goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 6, array([0.69425226, 0.60643688]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.70057666 0.64593374] [0.0063244 0.03949686] new direction: [-0.03371121 0.02153031] reversing there [0.0063244 0.03949686] making one step from [0.70057666 0.64593374] [0.0063244 0.03949686] --> [0.66686545 0.66746405] [-0.03371121 0.02153031] trying new point, [0.66686545 0.66746405] next() call None goals: [('reflect-at', 7, array([0.66686545, 0.66746405]), array([-0.03371121, 0.02153031]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.67527906 0.4879463 ] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.69425226 0.60643688] [0.0063244 0.03949686] -0.3826032159139785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4283913100076723 goals: [('bisect', 0, array([0.69425226, 0.60643688]), array([-0.0063244 , -0.03949686]), None, None, None, 6, array([0.65630586, 0.36945572]), array([-0.0063244 , -0.03949686]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=77 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 BACKWARD SAMPLING FROM 4 [0.19450023 0.63199687] [-0.03291268 0.02273226] -0.23670484165889305 BACKWARD SAMPLING FROM -4 [0.45780164 0.45013877] [-0.03291268 0.02273226] -0.1358679463834473 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), None, None, None, 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3123190738073511 goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4019354437867032 goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 6, array([0.12867488, 0.67746139]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.0957622 0.70019366] [-0.03291268 0.02273226] new direction: [-0.01742501 -0.03600513] reversing there [-0.03291268 0.02273226] making one step from [0.0957622 0.70019366] [-0.03291268 0.02273226] --> [0.07833719 0.66418853] [-0.01742501 -0.03600513] trying new point, [0.07833719 0.66418853] next() call -0.34004177980724587 goals: [('reflect-at', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.039782409475446034 goals: [('bisect', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), None, None, None, 10, array([0.02606217, 0.55617315]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.02606217 0.55617315] [-0.01742501 -0.03600513] -0.039782409475446034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), None, None, None, 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.20724246552376055 goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3400417798072463 goals: [('bisect', 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 4, array([0.0957622 , 0.70019366]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.0957622 0.70019366] [0.01742501 0.03600513] new direction: [ 0.03291268 -0.02273226] reversing there [0.01742501 0.03600513] making one step from [0.0957622 0.70019366] [0.01742501 0.03600513] --> [0.12867488 0.67746139] [ 0.03291268 -0.02273226] trying new point, [0.12867488 0.67746139] next() call -0.4019354437867037 goals: [('reflect-at', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07426929137401193 goals: [('bisect', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), None, None, None, 10, array([0.32615094, 0.54106782]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=78 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BACKWARD SAMPLING FROM 4 [0.05987511 0.56296374] [ 0.02701408 -0.02949982] -0.05134792603041273 BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18718326659217294 goals: [('bisect', 0, array([0.04818123, 0.68096301]), array([-0.02701408, -0.02949982]), None, None, None, 10, array([0.22195962, 0.38596484]), array([ 0.02701408, -0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.22195962 0.38596484] [ 0.02701408 -0.02949982] -0.18718326659217294 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41050587019281287 goals: [('bisect', 0, array([0.22195962, 0.38596484]), array([-0.02701408, 0.02949982]), None, None, None, 10, array([0.04818123, 0.68096301]), array([0.02701408, 0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=79 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 BACKWARD SAMPLING FROM 4 [0.57191913 0.61132696] [0.01781275 0.03581488] -0.3184669014578434 BACKWARD SAMPLING FROM -4 [0.42941712 0.32480789] [0.01781275 0.03581488] -0.4758529786384704 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), None, None, None, 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4445258817169163 goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 6, array([0.60754463, 0.68295673]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.60754463 0.68295673] [0.01781275 0.03581488] new direction: [-0.03971424 -0.00477279] reversing there [0.01781275 0.03581488] making one step from [0.60754463 0.68295673] [0.01781275 0.03581488] --> [0.56783039 0.67818395] [-0.03971424 -0.00477279] trying new point, [0.56783039 0.67818395] next() call None goals: [('reflect-at', 6, array([0.56783039, 0.67818395]), array([-0.03971424, -0.00477279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.51848088 0.50388231] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.58973188 0.64714185] [0.01781275 0.03581488] -0.4445258817169163 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.13808040243633282 goals: [('bisect', 0, array([0.58973188, 0.64714185]), array([-0.01781275, -0.03581488]), None, None, None, 5, array([0.50066813, 0.46806743]), array([-0.01781275, -0.03581488]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=80 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 BACKWARD SAMPLING FROM -4 [0.42753547 0.64725549] [-0.03941662 0.0068066 ] -0.36244551853049845 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.46049425869412336 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4863274153461391 goals: [('bisect', 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 4, array([0.11220248, 0.70170826]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.11220248 0.70170826] [-0.03941662 0.0068066 ] new direction: [-0.03348855 0.02187504] reversing there [-0.03941662 0.0068066 ] making one step from [0.11220248 0.70170826] [-0.03941662 0.0068066 ] --> [0.07871393 0.7235833 ] [-0.03348855 0.02187504] trying new point, [0.07871393 0.7235833 ] next() call None goals: [('reflect-at', 4, array([0.07871393, 0.7235833 ]), array([-0.03348855, 0.02187504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.37200718954009426 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, -3, array([0.38811884, 0.65406208]), array([-0.03941662, 0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.1516191 , 0.69490167]), array([ 0.03941662, -0.0068066 ]), None, None, None, 3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.38811884 0.65406208] [-0.03941662 0.0068066 ] -0.37200718954009426 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.38811884, 0.65406208]), array([ 0.03941662, -0.0068066 ]), None, None, None, -3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=81 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 BACKWARD SAMPLING FROM 4 [0.45306473 0.42098814] [0.02672267 0.02976405] -0.18066975294765303 BACKWARD SAMPLING FROM -4 [0.39239943 0.49651665] [-0.00924508 -0.03891694] -0.07714032966931968 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), None, None, None, 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 1, array([0.34617404, 0.30193193]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.34617404 0.30193193] [-0.00924508 -0.03891694] new direction: [0.02672267 0.02976405] reversing there [-0.00924508 -0.03891694] making one step from [0.34617404 0.30193193] [-0.00924508 -0.03891694] --> [0.37289671 0.33169598] [0.02672267 0.02976405] trying new point, [0.37289671 0.33169598] next() call -0.4236039997490474 goals: [('reflect-at', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3120636527905234 goals: [('bisect', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), None, None, None, 10, array([0.61340077, 0.59957245]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.61340077 0.59957245] [0.02672267 0.02976405] -0.3120636527905234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), None, None, None, 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14541481093575562 goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2387862650871675 goals: [('bisect', 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3197643473542989 goals: [('bisect', 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4236039997490474 goals: [('bisect', 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 9, array([0.37289671, 0.33169598]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.34617404 0.30193193] [-0.02672267 -0.02976405] new direction: [0.00924508 0.03891694] reversing there [-0.02672267 -0.02976405] making one step from [0.34617404 0.30193193] [-0.02672267 -0.02976405] --> [0.35541912 0.34084888] [0.00924508 0.03891694] trying new point, [0.35541912 0.34084888] next() call -0.37977487528894 goals: [('reflect-at', 10, array([0.35541912, 0.34084888]), array([0.00924508, 0.03891694]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=82 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 BACKWARD SAMPLING FROM 4 [0.30917537 0.48287406] [ 0.00848742 -0.03908918] -0.051460926903102756 BACKWARD SAMPLING FROM -1 [0.26673825 0.67831994] [ 0.00848742 -0.03908918] -0.433049641425479 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), None, None, None, 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.08995656502013205 goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2817612222756952 goals: [('bisect', 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4350702414142291 goals: [('bisect', 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 9, array([0.35161249, 0.28742818]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.35161249 0.28742818] [ 0.00848742 -0.03908918] new direction: [-0.01853685 0.03544552] reversing there [ 0.00848742 -0.03908918] making one step from [0.35161249 0.28742818] [ 0.00848742 -0.03908918] --> [0.33307564 0.32287371] [-0.01853685 0.03544552] trying new point, [0.33307564 0.32287371] next() call -0.4476412362297438 goals: [('reflect-at', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3003853287533051 goals: [('bisect', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), None, None, None, 10, array([0.31453879, 0.35831923]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31453879 0.35831923] [-0.01853685 0.03544552] -0.3003853287533051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), None, None, None, 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4476412362297438 goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 1, array([0.33307564, 0.32287371]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.35161249 0.28742818] [ 0.01853685 -0.03544552] new direction: [-0.00848742 0.03908918] reversing there [ 0.01853685 -0.03544552] making one step from [0.35161249 0.28742818] [ 0.01853685 -0.03544552] --> [0.34312507 0.32651736] [-0.00848742 0.03908918] trying new point, [0.34312507 0.32651736] next() call -0.43507024141422884 goals: [('reflect-at', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2801896445066674 goals: [('bisect', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), None, None, None, 10, array([0.27522567, 0.63923076]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=83 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM -4 [0.38697777 0.59042374] [-0.03248384 0.02334096] -0.1770815538786539 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 1, array([0.22455859, 0.70712854]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22455859 0.70712854] [-0.03248384 0.02334096] new direction: [-0.03398668 0.02109279] reversing there [-0.03248384 0.02334096] making one step from [0.22455859 0.70712854] [-0.03248384 0.02334096] --> [0.19057191 0.72822133] [-0.03398668 0.02109279] trying new point, [0.19057191 0.72822133] next() call None goals: [('reflect-at', 1, array([0.19057191, 0.72822133]), array([-0.03398668, 0.02109279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.15955218049839826 goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, -9, array([0.54939694, 0.47371893]), array([-0.03248384, 0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.54939694 0.47371893] [-0.03248384 0.02334096] -0.15955218049839826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4552588508048801 goals: [('bisect', 0, array([0.54939694, 0.47371893]), array([ 0.03248384, -0.02334096]), None, None, None, -9, array([0.25704243, 0.68378758]), array([ 0.03248384, -0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=84 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 BACKWARD SAMPLING FROM 4 [0.0588575 0.31191846] [-0.03418324 0.02077272] -0.4439154472871768 BACKWARD SAMPLING FROM -4 [0.18512274 0.4493389 ] [-0.03477044 -0.01977415] -0.049217056098525905 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), None, None, None, 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.35858253304774335 goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4485888583524455 goals: [('bisect', 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 4, array([0.09304075, 0.29114574]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.09304075 0.29114574] [ 0.03477044 -0.01977415] new direction: [-0.03418324 0.02077272] reversing there [ 0.03477044 -0.01977415] making one step from [0.09304075 0.29114574] [ 0.03477044 -0.01977415] --> [0.0588575 0.31191846] [-0.03418324 0.02077272] trying new point, [0.0588575 0.31191846] next() call -0.4439154472871768 goals: [('reflect-at', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.061009567312068635 goals: [('bisect', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), None, None, None, 10, array([0.14624196, 0.43655477]), array([0.03418324, 0.02077272]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.14624196 0.43655477] [0.03418324 0.02077272] -0.061009567312068635 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), None, None, None, 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.35020744828671635 goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4439154472871768 goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 6, array([0.0588575 , 0.31191846]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.09304075 0.29114574] [ 0.03418324 -0.02077272] new direction: [-0.03477044 0.01977415] reversing there [ 0.03418324 -0.02077272] making one step from [0.09304075 0.29114574] [ 0.03418324 -0.02077272] --> [0.05827031 0.31091988] [-0.03477044 0.01977415] trying new point, [0.05827031 0.31091988] next() call -0.4485888583524455 goals: [('reflect-at', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2115230931353383 goals: [('bisect', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), None, None, None, 10, array([0.04604099, 0.37024232]), array([0.03477044, 0.01977415]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=85 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 BACKWARD SAMPLING FROM 4 [0.77064828 0.56388562] [0.03756862 0.01373314] -0.3479665415854334 BACKWARD SAMPLING FROM -4 [0.47009935 0.45402052] [0.03756862 0.01373314] -0.13692311038869834 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), None, None, None, 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4019156709890521 goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4619911782824545 goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 6, array([0.84578551, 0.5913519 ]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.88335413 0.60508503] [0.03756862 0.01373314] new direction: [-0.01499532 -0.03708288] reversing there [0.03756862 0.01373314] making one step from [0.88335413 0.60508503] [0.03756862 0.01373314] --> [0.86835881 0.56800215] [-0.01499532 -0.03708288] trying new point, [0.86835881 0.56800215] next() call -0.43482716294154355 goals: [('reflect-at', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3623496671674091 goals: [('bisect', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), None, None, None, 10, array([0.82337284, 0.4567535 ]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.82337284 0.4567535 ] [-0.01499532 -0.03708288] -0.3623496671674091 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), None, None, None, 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.37606463005047236 goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.43482716294154355 goals: [('bisect', 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 4, array([0.88335413, 0.60508503]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.88335413 0.60508503] [0.01499532 0.03708288] new direction: [-0.03756862 -0.01373314] reversing there [0.01499532 0.03708288] making one step from [0.88335413 0.60508503] [0.01499532 0.03708288] --> [0.84578551 0.5913519 ] [-0.03756862 -0.01373314] trying new point, [0.84578551 0.5913519 ] next() call -0.4619911782824549 goals: [('reflect-at', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19343380286879602 goals: [('bisect', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), None, None, None, 10, array([0.62037381, 0.50895307]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=86 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 BACKWARD SAMPLING FROM 4 [0.22997871 0.54410506] [ 0.00068648 -0.03999411] -0.05076080590070252 BACKWARD SAMPLING FROM -4 [0.22820267 0.50408385] [-0.00019397 0.03999953] -0.026246700683537846 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), None, None, None, 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 1, array([0.22723279, 0.70408149]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22723279 0.70408149] [-0.00019397 0.03999953] new direction: [ 0.00068648 -0.03999411] reversing there [-0.00019397 0.03999953] making one step from [0.22723279 0.70408149] [-0.00019397 0.03999953] --> [0.22791927 0.66408738] [ 0.00068648 -0.03999411] trying new point, [0.22791927 0.66408738] next() call -0.362531970289674 goals: [('reflect-at', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), None, None, None, 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513657 goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.09888785040833842 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.19490757833235206 goals: [('bisect', 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.33091599613376643 goals: [('bisect', 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 9, array([0.23341111, 0.34413451]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] new direction: [0.03260973 0.02316475] reversing there [ 0.00068648 -0.03999411] making one step from [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] --> [0.26670732 0.32730515] [0.03260973 0.02316475] trying new point, [0.26670732 0.32730515] next() call -0.4083602779624293 goals: [('reflect-at', 10, array([0.26670732, 0.32730515]), array([0.03260973, 0.02316475]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.26670732 0.32730515] [0.03260973 0.02316475] -0.4083602779624293 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), None, None, None, 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 1, array([0.23409759, 0.3041404 ]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] new direction: [-0.00068648 0.03999411] reversing there [-0.03260973 -0.02316475] making one step from [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] --> [0.23341111 0.34413451] [-0.00068648 0.03999411] trying new point, [0.23341111 0.34413451] next() call -0.33091599613376643 goals: [('reflect-at', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), None, None, None, 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513682 goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.11469583748629265 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.21861955894928337 goals: [('bisect', 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3625319702896749 goals: [('bisect', 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 9, array([0.22791927, 0.66408738]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.22723279 0.70408149] [-0.00068648 0.03999411] new direction: [ 0.00019397 -0.03999953] reversing there [-0.00068648 0.03999411] making one step from [0.22723279 0.70408149] [-0.00068648 0.03999411] --> [0.22742677 0.66408196] [ 0.00019397 -0.03999953] trying new point, [0.22742677 0.66408196] next() call -0.36239760340404076 goals: [('reflect-at', 10, array([0.22742677, 0.66408196]), array([ 0.00019397, -0.03999953]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=87 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 BACKWARD SAMPLING FROM 4 [0.3391376 0.32791809] [ 0.03905665 -0.00863586] -0.42765944711127135 BACKWARD SAMPLING FROM -4 [0.02668439 0.39700497] [ 0.03905665 -0.00863586] -0.13295572584667534 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), None, None, None, 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4797518449351289 goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 6, array([0.4172509 , 0.31064637]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.4172509 0.31064637] [ 0.03905665 -0.00863586] new direction: [-0.03724409 0.01459033] reversing there [ 0.03905665 -0.00863586] making one step from [0.4172509 0.31064637] [ 0.03905665 -0.00863586] --> [0.3800068 0.3252367] [-0.03724409 0.01459033] trying new point, [0.3800068 0.3252367] next() call -0.45398023973187507 goals: [('reflect-at', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19605535574242375 goals: [('bisect', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), None, None, None, 10, array([0.23103043, 0.383598 ]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23103043 0.383598 ] [-0.03724409 0.01459033] -0.19605535574242375 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), None, None, None, 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3115996729727667 goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37943542516122514 goals: [('bisect', 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.45398023973187507 goals: [('bisect', 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 4, array([0.3800068, 0.3252367]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.4172509 0.31064637] [ 0.03724409 -0.01459033] new direction: [-0.03905665 0.00863586] reversing there [ 0.03724409 -0.01459033] making one step from [0.4172509 0.31064637] [ 0.03724409 -0.01459033] --> [0.37819425 0.31928223] [-0.03905665 0.00863586] trying new point, [0.37819425 0.31928223] next() call -0.4797518449351292 goals: [('reflect-at', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25318859507313635 goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), None, None, None, 10, array([0.18291099, 0.36246153]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=88 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170837 BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.39582616718099384 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28223684347738265 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3768913954170836 goals: [('bisect', 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 4, array([0.67171523, 0.34898492]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.67171523 0.34898492] [ 0.00604104 -0.03954119] new direction: [-0.03138488 -0.02479897] reversing there [ 0.00604104 -0.03954119] making one step from [0.67171523 0.34898492] [ 0.00604104 -0.03954119] --> [0.64033034 0.32418595] [-0.03138488 -0.02479897] trying new point, [0.64033034 0.32418595] next() call None goals: [('reflect-at', 4, array([0.64033034, 0.32418595]), array([-0.03138488, -0.02479897]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.3958261671809942 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, -3, array([0.62942792, 0.62577326]), array([ 0.00604104, -0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170836 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.66567418, 0.38852612]), array([-0.00604104, 0.03954119]), None, None, None, 3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.3958261671809942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.62942792, 0.62577326]), array([-0.00604104, 0.03954119]), None, None, None, -3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=89 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 BACKWARD SAMPLING FROM 4 [0.20913614 0.33057099] [ 0.01413523 -0.03741918] -0.38069631886308075 BACKWARD SAMPLING FROM -4 [0.09605432 0.62992447] [ 0.01413523 -0.03741918] -0.21561781084839587 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), None, None, None, 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12819855855898762 goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23684509426933237 goals: [('bisect', 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.38069631886308075 goals: [('bisect', 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 4, array([0.20913614, 0.33057099]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22327136 0.29315181] [ 0.01413523 -0.03741918] new direction: [-0.03612676 0.0171714 ] reversing there [ 0.01413523 -0.03741918] making one step from [0.22327136 0.29315181] [ 0.01413523 -0.03741918] --> [0.1871446 0.31032321] [-0.03612676 0.0171714 ] trying new point, [0.1871446 0.31032321] next() call -0.46722761628857196 goals: [('reflect-at', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1347530535350935 goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), None, None, None, 10, array([0.00651078, 0.39618021]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00651078 0.39618021] [-0.03612676 0.0171714 ] -0.1347530535350935 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), None, None, None, 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46722761628857196 goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 6, array([0.22327136, 0.29315181]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] new direction: [-0.01413523 0.03741918] reversing there [ 0.03612676 -0.0171714 ] making one step from [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] --> [0.20913614 0.33057099] [-0.01413523 0.03741918] trying new point, [0.20913614 0.33057099] next() call -0.3806963188630805 goals: [('reflect-at', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.016519553788509028 goals: [('bisect', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), None, None, None, 10, array([0.15259523, 0.48024773]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=90 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 BACKWARD SAMPLING FROM 4 [0.17606336 0.66988726] [-0.03949695 0.00632385] -0.37627016306758043 BACKWARD SAMPLING FROM -4 [0.49203895 0.61929648] [-0.03949695 0.00632385] -0.2989468009164582 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), None, None, None, 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3974546157438025 goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4475028760344699 goals: [('bisect', 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4763666836489148 goals: [('bisect', 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 9, array([0.02142138, 0.70150649]), array([0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.02142138 0.70150649] [0.03949695 0.00632385] new direction: [-0.02643714 0.03001795] reversing there [0.03949695 0.00632385] making one step from [0.02142138 0.70150649] [0.03949695 0.00632385] --> [0.00501576 0.73152444] [0.02643714 0.03001795] trying new point, [0.00501576 0.73152444] next() call None goals: [('reflect-at', 9, array([0.00501576, 0.73152444]), array([0.02643714, 0.03001795]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.01807557 0.69518265] [-0.03949695 0.00632385] -0.4763666836489148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.31713020215676097 goals: [('bisect', 0, array([0.01807557, 0.69518265]), array([ 0.03949695, -0.00632385]), None, None, None, 8, array([0.33405116, 0.64459187]), array([ 0.03949695, -0.00632385]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -11..4 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-11, 4) ---- seed=91 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 BACKWARD SAMPLING FROM 4 [0.04151464 0.31624266] [-0.03987224 -0.00319445] -0.42294623725634856 BACKWARD SAMPLING FROM -4 [0.36049255 0.34179827] [-0.03987224 -0.00319445] -0.37782476710495483 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), None, None, None, 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.43688850948485125 goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.47030777958157655 goals: [('bisect', 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.48978477744979876 goals: [('bisect', 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 9, array([0.15784656, 0.3002704 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] new direction: [0.02906527 0.02748108] reversing there [ 0.03987224 -0.00319445] making one step from [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] --> [0.18691183 0.32775148] [0.02906527 0.02748108] trying new point, [0.18691183 0.32775148] next() call -0.38833742025683327 goals: [('reflect-at', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.28529319268566455 goals: [('bisect', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), None, None, None, 10, array([0.21597711, 0.35523256]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21597711 0.35523256] [0.02906527 0.02748108] -0.28529319268566455 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), None, None, None, 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.38833742025683327 goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 1, array([0.18691183, 0.32775148]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] new direction: [-0.03987224 0.00319445] reversing there [-0.02906527 -0.02748108] making one step from [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] --> [0.11797432 0.30346485] [-0.03987224 0.00319445] trying new point, [0.11797432 0.30346485] next() call -0.4897847774497991 goals: [('reflect-at', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3856262338080673 goals: [('bisect', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), None, None, None, 10, array([0.2010036 , 0.32902047]), array([0.03987224, 0.00319445]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=92 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 BACKWARD SAMPLING FROM -4 [0.42647012 0.63886016] [-0.0004355 -0.03999763] -0.3319651929892012 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.21765730389482751 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.33859005788161145 goals: [('bisect', 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49951826010720873 goals: [('bisect', 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 4, array([0.42298615, 0.31887913]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] new direction: [-0.03548521 0.01846077] reversing there [-0.0004355 -0.03999763] making one step from [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] --> [0.38706544 0.29734227] [-0.03548521 0.01846077] trying new point, [0.38706544 0.29734227] next() call None goals: [('reflect-at', 5, array([0.38706544, 0.29734227]), array([-0.03548521, 0.01846077]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09483173136735507 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, -1, array([0.42516363, 0.51886728]), array([-0.0004355 , -0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.09577814063769934 goals: [('bisect', 0, array([0.42298615, 0.31887913]), array([0.0004355 , 0.03999763]), None, None, None, 4, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.42516363 0.51886728] [-0.0004355 -0.03999763] -0.09483173136735507 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09577814063769935 goals: [('bisect', 0, array([0.42516363, 0.51886728]), array([0.0004355 , 0.03999763]), None, None, None, -1, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=93 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 BACKWARD SAMPLING FROM 4 [0.515227 0.56286192] [-0.03275687 -0.02295621] -0.18212468401683823 BACKWARD SAMPLING FROM -4 [0.44675381 0.66881082] [ 0.03990013 -0.00282481] -0.4560081322130549 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), None, None, None, 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 1, array([0.64625447, 0.65468676]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.64625447 0.65468676] [ 0.03990013 -0.00282481] new direction: [-0.03275687 -0.02295621] reversing there [ 0.03990013 -0.00282481] making one step from [0.64625447 0.65468676] [ 0.03990013 -0.00282481] --> [0.6134976 0.63173055] [-0.03275687 -0.02295621] trying new point, [0.6134976 0.63173055] next() call -0.4051013634874946 goals: [('reflect-at', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12085928392615417 goals: [('bisect', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), None, None, None, 10, array([0.31868579, 0.42512465]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31868579 0.42512465] [-0.03275687 -0.02295621] -0.12085928392615417 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), None, None, None, 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1362945285525923 goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.24220254166073774 goals: [('bisect', 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.31652810148428956 goals: [('bisect', 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.40510136348749465 goals: [('bisect', 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 9, array([0.6134976 , 0.63173055]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.64625447 0.65468676] [0.03275687 0.02295621] new direction: [-0.03990013 0.00282481] reversing there [0.03275687 0.02295621] making one step from [0.64625447 0.65468676] [0.03275687 0.02295621] --> [0.60635434 0.65751157] [-0.03990013 0.00282481] trying new point, [0.60635434 0.65751157] next() call -0.49395646957573464 goals: [('reflect-at', 10, array([0.60635434, 0.65751157]), array([-0.03990013, 0.00282481]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -3..12 sampling between (-3, 12) ---- seed=94 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 BACKWARD SAMPLING FROM 4 [0.86227142 0.53522328] [ 0.03572141 -0.01799947] -0.38726449528400564 BACKWARD SAMPLING FROM -2 [0.64794297 0.64322012] [ 0.03572141 -0.01799947] -0.46631508651324616 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4925337817021134 goals: [('bisect', 0, array([0.71938579, 0.60722118]), array([ 0.03572141, -0.01799947]), None, None, None, 10, array([0.92340014, 0.42722645]), array([-0.03572141, -0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.92340014 0.42722645] [-0.03572141 -0.01799947] -0.4925337817021134 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4024627109969381 goals: [('bisect', 0, array([0.92340014, 0.42722645]), array([0.03572141, 0.01799947]), None, None, None, 10, array([0.71938579, 0.60722118]), array([-0.03572141, 0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=95 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 BACKWARD SAMPLING FROM 4 [0.60734111 0.59133529] [-0.02922414 0.02731208] -0.2887083100641112 BACKWARD SAMPLING FROM -4 [0.82122514 0.40753202] [ 0.01990911 -0.03469333] -0.4440844529643073 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), None, None, None, 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.34307459325849876 goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41694366417810785 goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 6, array([0.54889282, 0.64595945]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.51966868 0.67327152] [-0.02922414 0.02731208] new direction: [-0.03257512 0.02321339] reversing there [-0.02922414 0.02731208] making one step from [0.51966868 0.67327152] [-0.02922414 0.02731208] --> [0.48709356 0.69648491] [-0.03257512 0.02321339] trying new point, [0.48709356 0.69648491] next() call None goals: [('reflect-at', 7, array([0.48709356, 0.69648491]), array([-0.03257512, 0.02321339]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.63656525 0.56402322] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.54889282 0.64595945] [-0.02922414 0.02731208] -0.41694366417810785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.2662710545387677 goals: [('bisect', 0, array([0.54889282, 0.64595945]), array([ 0.02922414, -0.02731208]), None, None, None, 6, array([0.72423768, 0.48208699]), array([ 0.02922414, -0.02731208]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=96 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 BACKWARD SAMPLING FROM 4 [0.0396262 0.47159221] [ 0.03300675 -0.02259545] -0.010872647013765053 BACKWARD SAMPLING FROM -4 [0.22442783 0.65235578] [-0.03300675 -0.02259545] -0.3153374835129045 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36436264123928686 goals: [('bisect', 0, array([0.09240082, 0.561974 ]), array([-0.03300675, -0.02259545]), None, None, None, 10, array([0.23766673, 0.33601954]), array([ 0.03300675, -0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23766673 0.33601954] [ 0.03300675 -0.02259545] -0.36436264123928686 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05227866114907242 goals: [('bisect', 0, array([0.23766673, 0.33601954]), array([-0.03300675, 0.02259545]), None, None, None, 10, array([0.09240082, 0.561974 ]), array([0.03300675, 0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=97 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 BACKWARD SAMPLING FROM 4 [0.1641606 0.49992937] [-0.01012837 0.03869646] -0.013474413804503925 BACKWARD SAMPLING FROM -1 [0.21480243 0.30644705] [-0.01012837 0.03869646] -0.4913543244490346 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), None, None, None, 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.030512397919510853 goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.1772023323934378 goals: [('bisect', 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3068542827523578 goals: [('bisect', 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4740442218592488 goals: [('bisect', 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 9, array([0.11351877, 0.69341168]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.1033904 0.73210814] [-0.01012837 0.03869646] new direction: [-0.03691991 0.01539222] reversing there [-0.01012837 0.03869646] making one step from [0.1033904 0.73210814] [-0.01012837 0.03869646] --> [0.0664705 0.74750036] [-0.03691991 0.01539222] trying new point, [0.0664705 0.74750036] next() call None goals: [('reflect-at', 10, array([0.0664705 , 0.74750036]), array([-0.03691991, 0.01539222]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.11351877 0.69341168] [-0.01012837 0.03869646] -0.4740442218592488 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.3207023648241862 goals: [('bisect', 0, array([0.11351877, 0.69341168]), array([ 0.01012837, -0.03869646]), None, None, None, 9, array([0.20467407, 0.34514352]), array([ 0.01012837, -0.03869646]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=98 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 BACKWARD SAMPLING FROM 4 [0.79446178 0.41977178] [ 0.01554863 -0.03685431] -0.39604184352994004 BACKWARD SAMPLING FROM -2 [0.70116998 0.64089763] [ 0.01554863 -0.03685431] -0.4939714550399919 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), None, None, None, 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.49941240374695045 goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 6, array([0.82555904, 0.34606317]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.82555904 0.34606317] [ 0.01554863 -0.03685431] new direction: [-0.03412149 -0.02087401] reversing there [ 0.01554863 -0.03685431] making one step from [0.82555904 0.34606317] [ 0.01554863 -0.03685431] --> [0.79143756 0.32518916] [-0.03412149 -0.02087401] trying new point, [0.79143756 0.32518916] next() call None goals: [('reflect-at', 6, array([0.79143756, 0.32518916]), array([-0.03412149, -0.02087401]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.74781588 0.53033471] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.81001041 0.38291747] [ 0.01554863 -0.03685431] -0.49941240374695045 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.3245372087629051 goals: [('bisect', 0, array([0.81001041, 0.38291747]), array([-0.01554863, 0.03685431]), None, None, None, 5, array([0.73226725, 0.56718902]), array([-0.01554863, 0.03685431]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=99 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.3783905365498532 BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28854490986652237 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37839053654985255 goals: [('bisect', 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 4, array([0.68789813, 0.64731416]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.68789813 0.64731416] [0.00390489 0.03980894] new direction: [-0.01907752 0.03515748] reversing there [0.00390489 0.03980894] making one step from [0.68789813 0.64731416] [0.00390489 0.03980894] --> [0.66882061 0.68247164] [-0.01907752 0.03515748] trying new point, [0.66882061 0.68247164] next() call None goals: [('reflect-at', 4, array([0.66882061, 0.68247164]), array([-0.01907752, 0.03515748]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.4338274302289816 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, -3, array([0.66056388, 0.36865158]), array([0.00390489, 0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.37839053654985255 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.22775578725568393 goals: [('bisect', 0, array([0.68399324, 0.60750522]), array([-0.00390489, -0.03980894]), None, None, None, 3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.2277557872556839 goals: [('bisect', 0, array([0.66056388, 0.36865158]), array([-0.00390489, -0.03980894]), None, None, None, -3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-3, 0)

Passed

tests/test_hotstart.py::test_hotstart_SLOW

28.98

[gw9] linux -- Python 3.10.6 /usr/bin/python3
[gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3[gw9] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
-8963077118.743088 96.99934128550026 proposals: [[4.19976674e+01 1.01901282e-01 2.26584579e-02] [4.19936982e+01 9.70120971e-02 1.25468225e-01] [4.20043522e+01 8.81983708e-02 4.16063032e-01] [4.19910425e+01 9.23532542e-02 3.57120722e-01] [4.20010471e+01 1.04769832e-01 5.40934064e-02] [4.20004875e+01 8.44214056e-02 6.57794482e-01] [4.20114084e+01 8.71986004e-02 7.70800710e-01] [4.19997931e+01 1.17497505e-01 5.97616561e-01] [4.19793249e+01 1.16910821e-01 1.62802382e+00] [4.19777034e+01 1.00198605e-01 1.23013202e+00] [4.19809513e+01 9.73026870e-02 9.29402866e-01] [4.20035101e+01 8.39559746e-02 7.31648830e-01] [4.19818445e+01 8.91999970e-02 1.13587040e+00] [4.19944650e+01 8.89373681e-02 4.00203681e-01] [4.19879296e+01 9.87877365e-02 3.79163467e-01] [4.19993921e+01 1.05583972e-01 7.05549601e-02] [4.19958797e+01 1.00198250e-01 4.45624038e-02] [4.20028928e+01 1.13275091e-01 3.83072005e-01] [4.20075672e+01 8.60294765e-02 6.71506433e-01] [4.20000003e+01 1.32876001e-01 1.75531881e+00] [4.19941441e+01 1.20714239e-01 8.95917835e-01] [4.19973837e+01 1.02585211e-01 3.33463863e-02] [4.20109730e+01 9.76256032e-02 3.25050704e-01] [4.20249867e+01 1.01357574e-01 1.52720024e+00] [4.19795771e+01 1.01689723e-01 1.04810966e+00] [4.20151020e+01 9.49699778e-02 6.45034516e-01] [4.19711011e+01 9.64829396e-02 2.02124669e+00] [4.19779289e+01 9.01472311e-02 1.45803800e+00] [4.20283363e+01 1.50686758e-01 5.29231415e+00] [4.20036985e+01 1.13687102e-01 4.17933502e-01] [4.19861307e+01 1.11595948e-01 7.74029950e-01] [4.20008644e+01 9.20834520e-02 1.61590461e-01] [4.19749175e+01 9.45972273e-02 1.60648204e+00] [4.19978867e+01 1.40462497e-01 2.43829897e+00] [4.19934265e+01 1.00151410e-01 1.12874993e-01] [4.19958796e+01 9.06920226e-02 2.67799740e-01] [4.20091161e+01 1.15823745e-01 7.14187136e-01] [4.19660038e+01 9.54604067e-02 2.71598389e+00] [4.19911555e+01 1.13508293e-01 5.76293834e-01] [4.19706547e+01 1.03201725e-01 2.07074602e+00]] 40 [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=77.54..101.10 [77.5411..97.9860] | it/evals=0/401 eff=0.0000% N=400 Z=86.1(0.00%) | Like=90.62..101.10 [77.5411..97.9860] | it/evals=23/425 eff=92.0000% N=400 Z=88.4(0.00%) | Like=91.98..101.10 [77.5411..97.9860] | it/evals=40/444 eff=90.9091% N=400 Z=89.8(0.01%) | Like=93.05..101.10 [77.5411..97.9860] | it/evals=62/469 eff=89.8551% N=400 Z=90.7(0.02%) | Like=93.90..101.11 [77.5411..97.9860] | it/evals=80/491 eff=87.9121% N=400 Z=91.2(0.03%) | Like=94.28..101.11 [77.5411..97.9860] | it/evals=90/506 eff=84.9057% N=400 Z=92.0(0.07%) | Like=94.90..101.11 [77.5411..97.9860] | it/evals=110/529 eff=85.2713% N=400 Z=92.3(0.10%) | Like=95.13..101.11 [77.5411..97.9860] | it/evals=120/540 eff=85.7143% N=400 Z=92.7(0.15%) | Like=95.50..101.11 [77.5411..97.9860] | it/evals=134/558 eff=84.8101% N=400 Z=93.5(0.31%) | Like=96.16..101.11 [77.5411..97.9860] | it/evals=160/587 eff=85.5615% N=400 Z=93.9(0.50%) | Like=96.58..101.11 [77.5411..97.9860] | it/evals=180/610 eff=85.7143% N=400 Z=94.3(0.75%) | Like=96.86..101.11 [77.5411..97.9860] | it/evals=200/631 eff=86.5801% N=400 Z=94.8(1.17%) | Like=97.18..101.11 [77.5411..97.9860] | it/evals=226/661 eff=86.5900% N=400 Z=95.0(1.44%) | Like=97.36..101.11 [77.5411..97.9860] | it/evals=240/676 eff=86.9565% N=400 Z=95.3(1.90%) | Like=97.63..101.11 [77.5411..97.9860] | it/evals=259/698 eff=86.9128% N=400 Z=95.4(2.20%) | Like=97.76..101.11 [77.5411..97.9860] | it/evals=270/712 eff=86.5385% N=400 Z=95.5(2.52%) | Like=97.83..101.11 [77.5411..97.9860] | it/evals=280/725 eff=86.1538% N=400 Z=95.8(3.34%) | Like=98.09..101.11 [98.0947..98.1005]*| it/evals=305/768 eff=82.8804% N=400 Z=96.0(3.98%) | Like=98.18..101.11 [98.1782..98.1801]*| it/evals=320/786 eff=82.9016% N=400 Z=96.1(4.68%) | Like=98.28..101.11 [98.2821..98.2861]*| it/evals=337/807 eff=82.8010% N=400 Z=96.4(5.72%) | Like=98.49..101.11 [98.4874..98.4975] | it/evals=360/833 eff=83.1409% N=400 Z=96.6(6.99%) | Like=98.67..101.11 [98.6690..98.6754]*| it/evals=384/862 eff=83.1169% N=400 Z=96.7(7.90%) | Like=98.73..101.11 [98.7330..98.7367]*| it/evals=400/883 eff=82.8157% N=400 Z=96.9(10.47%) | Like=99.00..101.11 [98.9936..99.0036] | it/evals=439/926 eff=83.4601% N=400 Z=96.9(10.53%) | Like=99.00..101.11 [99.0049..99.0065]*| it/evals=440/927 eff=83.4915% N=400 Z=97.0(11.16%) | Like=99.05..101.11 [99.0347..99.0489] | it/evals=450/942 eff=83.0258% N=400 Z=97.1(12.69%) | Like=99.17..101.11 [99.1682..99.1804] | it/evals=472/968 eff=83.0986% N=400 Z=97.2(13.19%) | Like=99.20..101.11 [99.2022..99.2031]*| it/evals=480/977 eff=83.1889% N=400 Z=97.4(16.22%) | Like=99.35..101.11 [99.3491..99.3523]*| it/evals=520/1024 eff=83.3333% N=400 Z=97.5(17.72%) | Like=99.42..101.12 [99.4249..99.4286]*| it/evals=540/1051 eff=82.9493% N=400 Z=97.6(19.30%) | Like=99.52..101.12 [99.5178..99.5184]*| it/evals=560/1072 eff=83.3333% N=400 Z=97.6(20.74%) | Like=99.57..101.12 [99.5693..99.5718]*| it/evals=578/1092 eff=83.5260% N=400 Z=97.7(22.62%) | Like=99.64..101.12 [99.6378..99.6380]*| it/evals=600/1118 eff=83.5655% N=400 Z=97.8(25.22%) | Like=99.74..101.12 [99.7364..99.7367]*| it/evals=630/1160 eff=82.8947% N=400 Z=97.9(26.14%) | Like=99.76..101.12 [99.7576..99.7651]*| it/evals=640/1170 eff=83.1169% N=400 Z=98.0(28.97%) | Like=99.86..101.12 [99.8596..99.8598]*| it/evals=673/1212 eff=82.8818% N=400 Z=98.0(29.59%) | Like=99.88..101.12 [99.8754..99.8765]*| it/evals=680/1219 eff=83.0281% N=400 Z=98.1(32.77%) | Like=99.96..101.12 [99.9554..99.9554]*| it/evals=715/1260 eff=83.1395% N=400 Z=98.1(33.21%) | Like=99.96..101.12 [99.9610..99.9618]*| it/evals=720/1267 eff=83.0450% N=400 Z=98.2(34.92%) | Like=100.02..101.12 [100.0158..100.0164]*| it/evals=740/1296 eff=82.5893% N=400 Z=98.2(36.67%) | Like=100.08..101.12 [100.0795..100.0837]*| it/evals=760/1322 eff=82.4295% N=400 Z=98.3(39.53%) | Like=100.16..101.12 [100.1579..100.1583]*| it/evals=793/1358 eff=82.7766% N=400 Z=98.3(40.21%) | Like=100.18..101.12 [100.1751..100.1761]*| it/evals=800/1367 eff=82.7301% N=400 Z=98.3(41.10%) | Like=100.20..101.12 [100.1987..100.1988]*| it/evals=810/1380 eff=82.6531% N=400 Z=98.4(43.27%) | Like=100.27..101.12 [100.2693..100.2703]*| it/evals=835/1413 eff=82.4284% N=400 Z=98.4(43.67%) | Like=100.28..101.12 [100.2815..100.2828]*| it/evals=840/1418 eff=82.5147% N=400 Z=98.5(47.23%) | Like=100.37..101.12 [100.3676..100.3733]*| it/evals=879/1472 eff=81.9963% N=400 Z=98.5(47.32%) | Like=100.37..101.12 [100.3733..100.3744]*| it/evals=880/1473 eff=82.0130% N=400 Z=98.5(49.03%) | Like=100.42..101.12 [100.4183..100.4192]*| it/evals=900/1496 eff=82.1168% N=400 [ultranest] Explored until L=1e+02 [ultranest] Likelihood function evaluations: 1508 [ultranest] logZ = 99.21 +- 0.03825 [ultranest] Effective samples strategy satisfied (ESS = 972.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.41, need <0.5) [ultranest] logZ error budget: single: 0.05 bs:0.04 tail:0.41 total:0.41 required:<0.50 [ultranest] done iterating. logZ = 99.218 +- 0.413 single instance: logZ = 99.218 +- 0.049 bootstrapped : logZ = 99.210 +- 0.078 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations mean : 41.9564│ ▁ ▁▁▁▁▁▁▁▂▂▃▄▇▅▆▆▇▇▅▇▆▆▅▅▄▃▂▂▁▁▁▁▁▁ ▁ │42.0216 41.9894 +- 0.0091 scatter : 0.0728│ ▁▁▁▁▁▁▂▃▄▄▅▆▇▆▇▅▅▄▄▄▃▃▂▂▂▁▁▁▁▁ ▁▁▁ ▁ │0.1198 0.0914 +- 0.0065 aux_logweight : 0.00 │▇▆▇▇▆▆▆▄▅▄▄▃▃▃▂▂▂▁▁▂▁▁▁▁▁▁▁▁▁▁▁ ▁ ▁ │4.16 0.80 +- 0.63 [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-4.1e+11..-2.8e+02 [-4.059e+11..-3.867e+06] | it/evals=0/401 eff=0.0000% N=400 Z=-1e+10(0.00%) | Like=-1.4e+10..-2.8e+02 [-4.059e+11..-3.867e+06] | it/evals=40/444 eff=90.9091% N=400 Z=-3e+09(0.00%) | Like=-2.6e+09..-2.8e+02 [-4.059e+11..-3.867e+06] | it/evals=80/488 eff=90.9091% N=400 Z=-6e+08(0.00%) | Like=-5.9e+08..-2.8e+02 [-4.059e+11..-3.867e+06] | it/evals=120/531 eff=91.6031% N=400 Z=-2e+08(0.00%) | Like=-1.8e+08..-2.8e+02 [-4.059e+11..-3.867e+06] | it/evals=160/576 eff=90.9091% N=400 Z=-37629480.8(0.00%) | Like=-37019184.92..-276.64 [-4.059e+11..-3.867e+06] | it/evals=200/627 eff=88.1057% N=400 Z=-12066612.5(0.00%) | Like=-11773456.96..-276.64 [-4.059e+11..-3.867e+06] | it/evals=240/671 eff=88.5609% N=400 Z=-5121053.0(0.00%) | Like=-5026605.32..-276.64 [-4.059e+11..-3.867e+06] | it/evals=270/708 eff=87.6623% N=400 Z=-4239114.9(0.00%) | Like=-4218156.66..-276.64 [-4.059e+11..-3.867e+06] | it/evals=280/720 eff=87.5000% N=400 Z=-2131925.2(0.00%) | Like=-2080057.46..-276.64 [-3713236.8402..-67574.4853] | it/evals=320/772 eff=86.0215% N=400 Z=-1014637.6(0.00%) | Like=-964900.30..-276.64 [-3713236.8402..-67574.4853] | it/evals=360/818 eff=86.1244% N=400 Z=-541870.3(0.00%) | Like=-535492.84..-276.64 [-3713236.8402..-67574.4853] | it/evals=400/876 eff=84.0336% N=400 Z=-300783.4(0.00%) | Like=-295422.19..-276.64 [-3713236.8402..-67574.4853] | it/evals=440/927 eff=83.4915% N=400 Z=-255114.9(0.00%) | Like=-251465.12..-276.64 [-3713236.8402..-67574.4853] | it/evals=450/939 eff=83.4879% N=400 Z=-151349.5(0.00%) | Like=-150202.02..-276.64 [-3713236.8402..-67574.4853] | it/evals=480/974 eff=83.6237% N=400 Z=-99997.7(0.00%) | Like=-98049.75..-276.64 [-3713236.8402..-67574.4853] | it/evals=520/1028 eff=82.8025% N=400 Z=-65129.4(0.00%) | Like=-65004.43..-276.64 [-67571.4782..-7758.7267] | it/evals=560/1081 eff=82.2320% N=400 Z=-40261.6(0.00%) | Like=-40093.67..-276.64 [-67571.4782..-7758.7267] | it/evals=600/1149 eff=80.1068% N=400 Z=-29839.8(0.00%) | Like=-29468.85..-276.64 [-67571.4782..-7758.7267] | it/evals=639/1209 eff=78.9864% N=400 Z=-29476.4(0.00%) | Like=-28904.97..-276.64 [-67571.4782..-7758.7267] | it/evals=640/1212 eff=78.8177% N=400 Z=-21665.4(0.00%) | Like=-21630.82..-276.64 [-67571.4782..-7758.7267] | it/evals=680/1275 eff=77.7143% N=400 Z=-15756.3(0.00%) | Like=-15544.83..-276.64 [-67571.4782..-7758.7267] | it/evals=720/1338 eff=76.7591% N=400 Z=-12939.3(0.00%) | Like=-12872.54..-276.64 [-67571.4782..-7758.7267] | it/evals=751/1389 eff=75.9353% N=400 Z=-12015.4(0.00%) | Like=-12002.51..-276.64 [-67571.4782..-7758.7267] | it/evals=760/1402 eff=75.8483% N=400 Z=-9473.4(0.00%) | Like=-9362.21..-276.64 [-67571.4782..-7758.7267] | it/evals=800/1488 eff=73.5294% N=400 Z=-7725.4(0.00%) | Like=-7665.90..-276.64 [-7753.2372..-2005.4268] | it/evals=840/1571 eff=71.7336% N=400 Z=-6168.5(0.00%) | Like=-6136.23..-276.64 [-7753.2372..-2005.4268] | it/evals=880/1684 eff=68.5358% N=400 Z=-4952.2(0.00%) | Like=-4935.58..-249.74 [-7753.2372..-2005.4268] | it/evals=920/1775 eff=66.9091% N=400 Z=-4041.3(0.00%) | Like=-4003.76..-249.74 [-7753.2372..-2005.4268] | it/evals=960/1860 eff=65.7534% N=400 Z=-3518.0(0.00%) | Like=-3509.78..-249.74 [-7753.2372..-2005.4268] | it/evals=1000/1957 eff=64.2261% N=400 Z=-2883.7(0.00%) | Like=-2816.71..-249.74 [-7753.2372..-2005.4268] | it/evals=1040/2051 eff=62.9921% N=400 Z=-2411.5(0.00%) | Like=-2394.29..-249.74 [-7753.2372..-2005.4268] | it/evals=1080/2171 eff=60.9825% N=400 Z=-2097.1(0.00%) | Like=-2076.89..-249.74 [-7753.2372..-2005.4268] | it/evals=1120/2298 eff=59.0095% N=400 Z=-1817.5(0.00%) | Like=-1804.91..-249.74 [-2003.1952..-893.8641] | it/evals=1160/2387 eff=58.3795% N=400 Z=-1783.6(0.00%) | Like=-1754.08..-249.74 [-2003.1952..-893.8641] | it/evals=1170/2406 eff=58.3250% N=400 Z=-1566.1(0.00%) | Like=-1555.97..-249.74 [-2003.1952..-893.8641] | it/evals=1200/2475 eff=57.8313% N=400 Z=-1401.3(0.00%) | Like=-1389.84..-249.74 [-2003.1952..-893.8641] | it/evals=1240/2557 eff=57.4873% N=400 Z=-1337.9(0.00%) | Like=-1324.13..-249.74 [-2003.1952..-893.8641] | it/evals=1260/2604 eff=57.1688% N=400 Z=-1276.9(0.00%) | Like=-1266.90..-249.74 [-2003.1952..-893.8641] | it/evals=1280/2643 eff=57.0664% N=400 Z=-1120.2(0.00%) | Like=-1110.35..-241.79 [-2003.1952..-893.8641] | it/evals=1320/2726 eff=56.7498% N=400 Z=-1014.1(0.00%) | Like=-1001.54..-223.34 [-2003.1952..-893.8641] | it/evals=1350/2781 eff=56.6989% N=400 Z=-996.6(0.00%) | Like=-984.22..-223.34 [-2003.1952..-893.8641] | it/evals=1360/2795 eff=56.7850% N=400 Z=-915.5(0.00%) | Like=-904.91..-223.34 [-2003.1952..-893.8641] | it/evals=1400/2872 eff=56.6343% N=400 Z=-835.4(0.00%) | Like=-820.73..-176.99 [-892.8216..-562.4334] | it/evals=1440/2938 eff=56.7376% N=400 Z=-743.6(0.00%) | Like=-733.85..-176.99 [-892.8216..-562.4334] | it/evals=1480/3019 eff=56.5101% N=400 Z=-699.3(0.00%) | Like=-684.33..-115.14 [-892.8216..-562.4334] | it/evals=1520/3102 eff=56.2546% N=400 Z=-686.8(0.00%) | Like=-676.46..-115.14 [-892.8216..-562.4334] | it/evals=1530/3126 eff=56.1262% N=400 Z=-654.2(0.00%) | Like=-643.23..-115.14 [-892.8216..-562.4334] | it/evals=1560/3173 eff=56.2568% N=400 Z=-625.3(0.00%) | Like=-615.39..-115.14 [-892.8216..-562.4334] | it/evals=1600/3244 eff=56.2588% N=400 Z=-611.4(0.00%) | Like=-601.50..-115.14 [-892.8216..-562.4334] | it/evals=1620/3278 eff=56.2891% N=400 Z=-595.0(0.00%) | Like=-585.36..-115.14 [-892.8216..-562.4334] | it/evals=1640/3314 eff=56.2800% N=400 Z=-574.5(0.00%) | Like=-565.11..-115.14 [-892.8216..-562.4334] | it/evals=1680/3370 eff=56.5657% N=400 Z=-564.2(0.00%) | Like=-555.02..-87.70 [-561.9422..-496.7966] | it/evals=1710/3421 eff=56.6038% N=400 Z=-561.7(0.00%) | Like=-552.59..-87.70 [-561.9422..-496.7966] | it/evals=1720/3435 eff=56.6722% N=400 Z=-552.2(0.00%) | Like=-543.29..-72.54 [-561.9422..-496.7966] | it/evals=1760/3501 eff=56.7559% N=400 Z=-542.9(0.00%) | Like=-533.87..-72.54 [-561.9422..-496.7966] | it/evals=1800/3566 eff=56.8541% N=400 Z=-533.6(0.00%) | Like=-524.21..-72.54 [-561.9422..-496.7966] | it/evals=1840/3633 eff=56.9131% N=400 Z=-526.1(0.00%) | Like=-516.45..-72.54 [-561.9422..-496.7966] | it/evals=1880/3703 eff=56.9180% N=400 Z=-523.5(0.00%) | Like=-514.33..-72.54 [-561.9422..-496.7966] | it/evals=1890/3716 eff=56.9964% N=400 Z=-514.5(0.00%) | Like=-504.81..-72.54 [-561.9422..-496.7966] | it/evals=1920/3752 eff=57.2792% N=400 Z=-503.4(0.00%) | Like=-493.81..-72.54 [-496.7229..-425.4198] | it/evals=1960/3812 eff=57.4443% N=400 Z=-497.6(0.00%) | Like=-487.69..-72.54 [-496.7229..-425.4198] | it/evals=1980/3839 eff=57.5749% N=400 Z=-492.4(0.00%) | Like=-482.81..-72.54 [-496.7229..-425.4198] | it/evals=2000/3869 eff=57.6535% N=400 Z=-481.9(0.00%) | Like=-471.51..-72.54 [-496.7229..-425.4198] | it/evals=2040/3916 eff=58.0205% N=400 Z=-471.5(0.00%) | Like=-461.58..-72.54 [-496.7229..-425.4198] | it/evals=2070/3958 eff=58.1788% N=400 Z=-467.6(0.00%) | Like=-457.50..-72.54 [-496.7229..-425.4198] | it/evals=2080/3974 eff=58.1981% N=400 Z=-460.2(0.00%) | Like=-450.50..-72.54 [-496.7229..-425.4198] | it/evals=2120/4041 eff=58.2258% N=400 Z=-451.3(0.00%) | Like=-441.42..-48.30 [-496.7229..-425.4198] | it/evals=2160/4093 eff=58.4890% N=400 Z=-442.1(0.00%) | Like=-431.97..-48.30 [-496.7229..-425.4198] | it/evals=2200/4159 eff=58.5262% N=400 Z=-432.8(0.00%) | Like=-422.44..-48.30 [-424.9178..-365.3215] | it/evals=2240/4224 eff=58.5774% N=400 Z=-428.1(0.00%) | Like=-417.97..-48.30 [-424.9178..-365.3215] | it/evals=2260/4266 eff=58.4584% N=400 Z=-424.5(0.00%) | Like=-413.65..-48.30 [-424.9178..-365.3215] | it/evals=2280/4292 eff=58.5817% N=400 Z=-416.6(0.00%) | Like=-405.68..-48.30 [-424.9178..-365.3215] | it/evals=2320/4344 eff=58.8235% N=400 Z=-411.4(0.00%) | Like=-400.86..-48.30 [-424.9178..-365.3215] | it/evals=2344/4389 eff=58.7616% N=400 Z=-408.2(0.00%) | Like=-397.87..-48.30 [-424.9178..-365.3215] | it/evals=2360/4411 eff=58.8382% N=400 Z=-400.0(0.00%) | Like=-389.40..-48.30 [-424.9178..-365.3215] | it/evals=2400/4465 eff=59.0406% N=400 Z=-394.0(0.00%) | Like=-383.71..-48.30 [-424.9178..-365.3215] | it/evals=2430/4518 eff=59.0092% N=400 Z=-392.3(0.00%) | Like=-381.40..-48.30 [-424.9178..-365.3215] | it/evals=2440/4533 eff=59.0370% N=400 Z=-383.1(0.00%) | Like=-372.99..-48.30 [-424.9178..-365.3215] | it/evals=2480/4607 eff=58.9494% N=400 Z=-373.9(0.00%) | Like=-363.25..-48.30 [-365.1228..-305.6284] | it/evals=2520/4677 eff=58.9198% N=400 Z=-365.1(0.00%) | Like=-353.57..-48.30 [-365.1228..-305.6284] | it/evals=2560/4731 eff=59.1088% N=400 Z=-354.9(0.00%) | Like=-343.81..-36.34 [-365.1228..-305.6284] | it/evals=2600/4785 eff=59.2930% N=400 Z=-353.2(0.00%) | Like=-342.59..-36.34 [-365.1228..-305.6284] | it/evals=2610/4809 eff=59.1971% N=400 Z=-347.7(0.00%) | Like=-337.09..-31.02 [-365.1228..-305.6284] | it/evals=2640/4848 eff=59.3525% N=400 Z=-339.0(0.00%) | Like=-327.74..4.51 [-365.1228..-305.6284] | it/evals=2672/4898 eff=59.4042% N=400 Z=-337.5(0.00%) | Like=-325.86..4.51 [-365.1228..-305.6284] | it/evals=2680/4910 eff=59.4235% N=400 Z=-333.4(0.00%) | Like=-322.27..4.51 [-365.1228..-305.6284] | it/evals=2700/4942 eff=59.4452% N=400 Z=-329.6(0.00%) | Like=-318.09..4.51 [-365.1228..-305.6284] | it/evals=2720/4966 eff=59.5707% N=400 Z=-320.1(0.00%) | Like=-308.11..5.94 [-365.1228..-305.6284] | it/evals=2760/5022 eff=59.7144% N=400 Z=-312.9(0.00%) | Like=-301.47..33.15 [-305.4729..-246.0365] | it/evals=2790/5068 eff=59.7686% N=400 Z=-310.4(0.00%) | Like=-298.96..33.15 [-305.4729..-246.0365] | it/evals=2800/5079 eff=59.8418% N=400 Z=-300.0(0.00%) | Like=-288.26..33.15 [-305.4729..-246.0365] | it/evals=2840/5135 eff=59.9789% N=400 Z=-291.1(0.00%) | Like=-278.53..33.15 [-305.4729..-246.0365] | it/evals=2880/5200 eff=60.0000% N=400 Z=-282.1(0.00%) | Like=-270.79..33.15 [-305.4729..-246.0365] | it/evals=2920/5260 eff=60.0823% N=400 Z=-274.2(0.00%) | Like=-262.16..33.15 [-305.4729..-246.0365] | it/evals=2960/5318 eff=60.1871% N=400 Z=-271.6(0.00%) | Like=-259.39..33.15 [-305.4729..-246.0365] | it/evals=2970/5335 eff=60.1824% N=400 Z=-265.2(0.00%) | Like=-252.95..33.15 [-305.4729..-246.0365] | it/evals=3000/5370 eff=60.3622% N=400 Z=-257.2(0.00%) | Like=-245.23..33.15 [-246.0052..-181.9655] | it/evals=3040/5425 eff=60.4975% N=400 Z=-252.8(0.00%) | Like=-240.18..33.15 [-246.0052..-181.9655] | it/evals=3060/5455 eff=60.5341% N=400 Z=-248.5(0.00%) | Like=-236.40..33.15 [-246.0052..-181.9655] | it/evals=3080/5478 eff=60.6538% N=400 Z=-239.8(0.00%) | Like=-227.58..33.15 [-246.0052..-181.9655] | it/evals=3120/5527 eff=60.8543% N=400 Z=-231.7(0.00%) | Like=-219.05..33.15 [-246.0052..-181.9655] | it/evals=3160/5583 eff=60.9686% N=400 Z=-222.5(0.00%) | Like=-209.88..58.38 [-246.0052..-181.9655] | it/evals=3200/5634 eff=61.1387% N=400 Z=-213.3(0.00%) | Like=-200.38..76.85 [-246.0052..-181.9655] | it/evals=3240/5700 eff=61.1321% N=400 Z=-203.3(0.00%) | Like=-190.75..84.22 [-246.0052..-181.9655] | it/evals=3280/5757 eff=61.2283% N=400 Z=-193.8(0.00%) | Like=-180.96..84.22 [-181.6575..-127.1559] | it/evals=3320/5814 eff=61.3225% N=400 Z=-191.5(0.00%) | Like=-178.74..84.22 [-181.6575..-127.1559] | it/evals=3330/5829 eff=61.3373% N=400 Z=-186.1(0.00%) | Like=-173.36..84.22 [-181.6575..-127.1559] | it/evals=3360/5861 eff=61.5272% N=400 Z=-176.2(0.00%) | Like=-162.69..84.22 [-181.6575..-127.1559] | it/evals=3400/5920 eff=61.5942% N=400 Z=-170.0(0.00%) | Like=-156.47..84.22 [-181.6575..-127.1559] | it/evals=3420/5947 eff=61.6549% N=400 Z=-165.8(0.00%) | Like=-152.80..84.22 [-181.6575..-127.1559] | it/evals=3440/5969 eff=61.7705% N=400 Z=-156.7(0.00%) | Like=-143.72..87.91 [-181.6575..-127.1559] | it/evals=3480/6018 eff=61.9438% N=400 Z=-150.4(0.00%) | Like=-136.95..87.91 [-181.6575..-127.1559] | it/evals=3511/6059 eff=62.0428% N=400 Z=-148.9(0.00%) | Like=-136.08..87.91 [-181.6575..-127.1559] | it/evals=3520/6071 eff=62.0702% N=400 Z=-141.4(0.00%) | Like=-128.03..95.46 [-181.6575..-127.1559] | it/evals=3560/6128 eff=62.1508% N=400 Z=-135.4(0.00%) | Like=-122.57..95.46 [-127.0824..-76.9703] | it/evals=3600/6175 eff=62.3377% N=400 Z=-129.3(0.00%) | Like=-115.62..95.46 [-127.0824..-76.9703] | it/evals=3640/6234 eff=62.3929% N=400 Z=-122.0(0.00%) | Like=-108.30..95.46 [-127.0824..-76.9703] | it/evals=3680/6291 eff=62.4682% N=400 Z=-119.5(0.00%) | Like=-105.57..95.46 [-127.0824..-76.9703] | it/evals=3690/6307 eff=62.4683% N=400 Z=-114.5(0.00%) | Like=-101.14..95.46 [-127.0824..-76.9703] | it/evals=3720/6341 eff=62.6157% N=400 Z=-107.6(0.00%) | Like=-92.93..95.46 [-127.0824..-76.9703] | it/evals=3760/6392 eff=62.7503% N=400 Z=-99.8(0.00%) | Like=-86.14..95.46 [-127.0824..-76.9703] | it/evals=3800/6451 eff=62.7995% N=400 Z=-93.9(0.00%) | Like=-79.78..95.46 [-127.0824..-76.9703] | it/evals=3840/6504 eff=62.9096% N=400 Z=-87.5(0.00%) | Like=-73.71..95.46 [-76.8329..-31.0885] | it/evals=3880/6560 eff=62.9870% N=400 Z=-80.8(0.00%) | Like=-66.10..95.46 [-76.8329..-31.0885] | it/evals=3920/6611 eff=63.1138% N=400 Z=-72.7(0.00%) | Like=-58.43..95.46 [-76.8329..-31.0885] | it/evals=3960/6681 eff=63.0473% N=400 Z=-64.2(0.00%) | Like=-50.14..95.46 [-76.8329..-31.0885] | it/evals=4000/6731 eff=63.1812% N=400 Z=-56.6(0.00%) | Like=-42.25..95.46 [-76.8329..-31.0885] | it/evals=4040/6794 eff=63.1842% N=400 Z=-54.5(0.00%) | Like=-40.26..95.46 [-76.8329..-31.0885] | it/evals=4050/6809 eff=63.1924% N=400 Z=-50.8(0.00%) | Like=-36.34..95.46 [-76.8329..-31.0885] | it/evals=4080/6846 eff=63.2951% N=400 Z=-44.9(0.00%) | Like=-30.73..97.52 [-31.0687..8.7264] | it/evals=4120/6898 eff=63.4041% N=400 Z=-42.3(0.00%) | Like=-27.94..97.52 [-31.0687..8.7264] | it/evals=4140/6929 eff=63.4094% N=400 Z=-39.9(0.00%) | Like=-25.81..97.52 [-31.0687..8.7264] | it/evals=4160/6953 eff=63.4824% N=400 Z=-33.8(0.00%) | Like=-19.11..97.52 [-31.0687..8.7264] | it/evals=4200/7000 eff=63.6364% N=400 Z=-28.9(0.00%) | Like=-13.81..97.81 [-31.0687..8.7264] | it/evals=4230/7038 eff=63.7240% N=400 Z=-27.2(0.00%) | Like=-12.10..98.13 [-31.0687..8.7264] | it/evals=4240/7052 eff=63.7402% N=400 Z=-21.6(0.00%) | Like=-6.73..98.24 [-31.0687..8.7264] | it/evals=4280/7099 eff=63.8901% N=400 Z=-15.3(0.00%) | Like=-0.29..98.24 [-31.0687..8.7264] | it/evals=4320/7151 eff=63.9905% N=400 Z=-9.3(0.00%) | Like=5.94..98.24 [-31.0687..8.7264] | it/evals=4360/7203 eff=64.0894% N=400 Z=-4.0(0.00%) | Like=11.18..98.24 [8.7436..45.4062] | it/evals=4400/7263 eff=64.1119% N=400 Z=-2.0(0.00%) | Like=13.40..98.24 [8.7436..45.4062] | it/evals=4410/7274 eff=64.1548% N=400 Z=3.0(0.00%) | Like=18.46..98.24 [8.7436..45.4062] | it/evals=4440/7311 eff=64.2454% N=400 Z=9.0(0.00%) | Like=24.23..98.39 [8.7436..45.4062] | it/evals=4480/7358 eff=64.3863% N=400 Z=12.0(0.00%) | Like=27.45..98.39 [8.7436..45.4062] | it/evals=4500/7384 eff=64.4330% N=400 Z=14.7(0.00%) | Like=30.09..98.39 [8.7436..45.4062] | it/evals=4520/7409 eff=64.4885% N=400 Z=19.8(0.00%) | Like=35.70..98.39 [8.7436..45.4062] | it/evals=4560/7463 eff=64.5618% N=400 Z=23.4(0.00%) | Like=38.68..98.39 [8.7436..45.4062] | it/evals=4590/7503 eff=64.6206% N=400 Z=24.5(0.00%) | Like=39.70..98.39 [8.7436..45.4062] | it/evals=4600/7515 eff=64.6521% N=400 Z=28.0(0.00%) | Like=43.51..98.39 [8.7436..45.4062] | it/evals=4640/7565 eff=64.7592% N=400 Z=32.5(0.00%) | Like=47.97..98.39 [45.5706..67.5478] | it/evals=4680/7617 eff=64.8469% N=400 Z=35.7(0.00%) | Like=51.08..98.39 [45.5706..67.5478] | it/evals=4720/7668 eff=64.9422% N=400 Z=38.7(0.00%) | Like=54.16..98.39 [45.5706..67.5478] | it/evals=4760/7724 eff=64.9918% N=400 Z=39.5(0.00%) | Like=54.86..98.39 [45.5706..67.5478] | it/evals=4770/7737 eff=65.0129% N=400 Z=41.9(0.00%) | Like=57.55..98.39 [45.5706..67.5478] | it/evals=4800/7777 eff=65.0671% N=400 Z=45.3(0.00%) | Like=60.71..98.39 [45.5706..67.5478] | it/evals=4840/7829 eff=65.1501% N=400 Z=46.8(0.00%) | Like=62.54..98.41 [45.5706..67.5478] | it/evals=4860/7859 eff=65.1562% N=400 Z=48.3(0.00%) | Like=63.72..98.41 [45.5706..67.5478] | it/evals=4880/7881 eff=65.2319% N=400 Z=51.0(0.00%) | Like=66.65..98.41 [45.5706..67.5478] | it/evals=4920/7928 eff=65.3560% N=400 Z=52.9(0.00%) | Like=68.31..98.41 [67.5628..80.8524] | it/evals=4950/7967 eff=65.4156% N=400 Z=53.4(0.00%) | Like=69.28..98.41 [67.5628..80.8524] | it/evals=4960/7977 eff=65.4613% N=400 Z=56.1(0.00%) | Like=71.64..98.41 [67.5628..80.8524] | it/evals=5000/8026 eff=65.5652% N=400 Z=57.9(0.00%) | Like=73.74..98.41 [67.5628..80.8524] | it/evals=5040/8078 eff=65.6421% N=400 Z=59.9(0.00%) | Like=75.54..98.41 [67.5628..80.8524] | it/evals=5080/8129 eff=65.7265% N=400 Z=61.7(0.00%) | Like=77.34..98.41 [67.5628..80.8524] | it/evals=5120/8182 eff=65.7929% N=400 Z=63.5(0.00%) | Like=79.26..98.41 [67.5628..80.8524] | it/evals=5160/8233 eff=65.8751% N=400 Z=65.1(0.00%) | Like=80.72..98.41 [67.5628..80.8524] | it/evals=5200/8291 eff=65.8979% N=400 Z=65.7(0.00%) | Like=81.30..98.41 [80.8533..89.6445] | it/evals=5220/8319 eff=65.9174% N=400 Z=66.5(0.00%) | Like=82.32..98.41 [80.8533..89.6445] | it/evals=5240/8345 eff=65.9534% N=400 Z=67.9(0.00%) | Like=83.86..98.41 [80.8533..89.6445] | it/evals=5280/8395 eff=66.0413% N=400 Z=69.0(0.00%) | Like=84.73..98.41 [80.8533..89.6445] | it/evals=5310/8433 eff=66.1023% N=400 Z=69.3(0.00%) | Like=85.11..98.41 [80.8533..89.6445] | it/evals=5320/8450 eff=66.0870% N=400 Z=70.5(0.00%) | Like=86.41..98.41 [80.8533..89.6445] | it/evals=5360/8501 eff=66.1647% N=400 Z=71.5(0.00%) | Like=87.38..98.41 [80.8533..89.6445] | it/evals=5400/8557 eff=66.2008% N=400 Z=72.5(0.00%) | Like=88.23..98.41 [80.8533..89.6445] | it/evals=5440/8610 eff=66.2607% N=400 Z=73.3(0.01%) | Like=89.27..98.41 [80.8533..89.6445] | it/evals=5480/8661 eff=66.3358% N=400 Z=73.5(0.01%) | Like=89.47..98.41 [80.8533..89.6445] | it/evals=5490/8675 eff=66.3444% N=400 Z=74.2(0.02%) | Like=90.07..98.49 [89.6801..90.9753] | it/evals=5520/8711 eff=66.4180% N=400 Z=75.0(0.05%) | Like=90.97..98.49 [89.6801..90.9753] | it/evals=5560/8765 eff=66.4674% N=400 Z=75.6(0.10%) | Like=91.55..98.49 [91.5384..91.5501] | it/evals=5594/8811 eff=66.5081% N=400 Z=75.7(0.11%) | Like=91.67..98.49 [91.6401..91.6716] | it/evals=5600/8819 eff=66.5162% N=400 Z=76.4(0.21%) | Like=92.30..98.49 [92.3017..92.3752] | it/evals=5640/8867 eff=66.6116% N=400 Z=76.8(0.34%) | Like=92.77..98.49 [92.7745..92.7789]*| it/evals=5670/8909 eff=66.6353% N=400 Z=77.0(0.39%) | Like=92.95..98.49 [92.9521..92.9647] | it/evals=5680/8920 eff=66.6667% N=400 Z=77.5(0.68%) | Like=93.47..98.49 [93.4513..93.4659] | it/evals=5720/8968 eff=66.7600% N=400 Z=78.0(1.14%) | Like=93.92..98.49 [93.9203..93.9340] | it/evals=5760/9021 eff=66.8136% N=400 Z=78.5(1.76%) | Like=94.42..98.49 [94.4199..94.4316] | it/evals=5800/9067 eff=66.9205% N=400 Z=78.9(2.61%) | Like=94.80..98.49 [94.7710..94.7997] | it/evals=5840/9118 eff=66.9878% N=400 Z=78.9(2.87%) | Like=94.86..98.49 [94.8620..94.8792] | it/evals=5850/9130 eff=67.0103% N=400 Z=79.2(3.71%) | Like=95.08..98.49 [95.0837..95.0846]*| it/evals=5880/9170 eff=67.0468% N=400 Z=79.5(4.97%) | Like=95.37..98.49 [95.3544..95.3709] | it/evals=5920/9221 eff=67.1126% N=400 Z=79.6(5.74%) | Like=95.52..98.49 [95.5150..95.5168]*| it/evals=5940/9247 eff=67.1414% N=400 Z=79.8(6.59%) | Like=95.66..98.49 [95.6561..95.6587]*| it/evals=5960/9270 eff=67.1928% N=400 Z=80.0(8.27%) | Like=95.90..98.49 [95.9000..95.9189] | it/evals=6000/9317 eff=67.2872% N=400 Z=80.3(10.25%) | Like=96.11..98.49 [96.1056..96.1110]*| it/evals=6040/9376 eff=67.2906% N=400 Z=80.5(12.48%) | Like=96.30..98.49 [96.2989..96.3076]*| it/evals=6080/9423 eff=67.3834% N=400 Z=80.6(15.04%) | Like=96.48..98.49 [96.4812..96.4923] | it/evals=6120/9479 eff=67.4083% N=400 Z=80.8(17.97%) | Like=96.69..98.49 [96.6875..96.6906]*| it/evals=6160/9527 eff=67.4921% N=400 Z=81.0(20.93%) | Like=96.85..98.50 [96.8460..96.8468]*| it/evals=6200/9586 eff=67.4940% N=400 Z=81.0(21.78%) | Like=96.89..98.50 [96.8851..96.8930]*| it/evals=6210/9596 eff=67.5294% N=400 Z=81.1(24.15%) | Like=97.00..98.50 [96.9983..96.9996]*| it/evals=6240/9636 eff=67.5617% N=400 Z=81.2(27.57%) | Like=97.13..98.50 [97.1322..97.1413]*| it/evals=6280/9694 eff=67.5705% N=400 Z=81.3(29.36%) | Like=97.20..98.50 [97.1952..97.1957]*| it/evals=6300/9717 eff=67.6183% N=400 Z=81.3(31.00%) | Like=97.27..98.50 [97.2717..97.2766]*| it/evals=6320/9741 eff=67.6587% N=400 Z=81.5(34.66%) | Like=97.39..98.50 [97.3944..97.3960]*| it/evals=6360/9796 eff=67.6884% N=400 Z=81.5(37.34%) | Like=97.49..98.50 [97.4946..97.4947]*| it/evals=6390/9846 eff=67.6477% N=400 Z=81.6(38.27%) | Like=97.51..98.50 [97.5113..97.5147]*| it/evals=6400/9859 eff=67.6604% N=400 Z=81.6(42.06%) | Like=97.59..98.50 [97.5888..97.5898]*| it/evals=6440/9911 eff=67.7111% N=400 Z=81.7(45.73%) | Like=97.67..98.50 [97.6705..97.6731]*| it/evals=6480/9962 eff=67.7682% N=400 Z=81.8(49.08%) | Like=97.76..98.50 [97.7636..97.7671]*| it/evals=6520/10008 eff=67.8601% N=400 [ultranest] Explored until L=1e+02 [ultranest] Likelihood function evaluations: 10026 [ultranest] logZ = 82.54 +- 0.1468 [ultranest] Effective samples strategy satisfied (ESS = 989.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.43, need <0.5) [ultranest] logZ error budget: single: 0.19 bs:0.15 tail:0.41 total:0.43 required:<0.50 [ultranest] done iterating. logZ = 82.511 +- 0.480 single instance: logZ = 82.511 +- 0.193 bootstrapped : logZ = 82.536 +- 0.257 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations mean : 41.9474│ ▁ ▁▁▁▁▁▁▁▁▁▁▂▃▃▄▆▅▆▇▆▅▆▅▅▄▄▂▂▁▁▁▁▁▁▁▁ │42.0252 41.9896 +- 0.0093 scatter : 0.0684│ ▁▁▁▁▁▁▂▂▃▄▆▆▆▆▇▅▅▅▄▃▃▂▂▁▁▁▁▁▁▁▁▁▁▁ ▁ │0.1256 0.0911 +- 0.0068 RECYCLING: ref: {'niter': 6931, 'logz': 82.51126797630579, 'logzerr': 0.48000210459420994, 'logz_bs': 82.53603482383392, 'logz_single': 82.51126797630579, 'logzerr_tail': 0.40526526018403786, 'logzerr_bs': 0.2572199240005233, 'ess': 989.4418387883029, 'H': 14.904885613395052, 'Herr': 0.14344533438670065, 'posterior': {'mean': [41.98963561307596, 0.09112288330816437], 'stdev': [0.009349186585804043, 0.006775975213110563], 'median': [41.98941172473769, 0.0906763001145217], 'errlo': [41.98058131149014, 0.08469946646382202], 'errup': [41.999107688907316, 0.09767389448562613], 'information_gain_bits': [4.14647919764959, 3.592890199934908]}, 'weighted_samples': {'upoints': array([[9.75177245e-01, 8.77828782e-04], [8.18524108e-02, 2.44479339e-03], [9.88480171e-02, 2.02700325e-02], ..., [5.20995235e-01, 2.39361007e-01], [5.20995032e-01, 2.39712725e-01], [5.20995165e-01, 2.39004262e-01]]), 'points': array([[ 9.50354489e+02, 1.00811787e-02], [-8.36295178e+02, 1.02277281e-02], [-8.02303966e+02, 1.20525830e-02], ..., [ 4.19904702e+01, 9.06659110e-02], [ 4.19900633e+01, 9.09600940e-02], [ 4.19903302e+01, 9.03684948e-02]]), 'weights': array([0. , 0. , 0. , ..., 0.00177121, 0.00177125, 0.00177555]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -22.31896455, -22.31896455, -22.31896455]), 'bootstrapped_weights': array([[0. , 0. , 0. , ..., 0. , 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0. , 0. ], ..., [0. , 0.00274031, 0.00279516, ..., 0.00293349, 0.00267692, 0. ], [0.00273848, 0.00274037, 0.00279522, ..., 0.00293356, 0.00267697, 0. ], [0.00274512, 0. , 0.002802 , ..., 0. , 0.00268347, 0.0026264 ]]), 'logl': array([-4.05945790e+11, -3.68707854e+11, -2.45356023e+11, ..., 9.84941424e+01, 9.84941642e+01, 9.84965862e+01])}, 'samples': array([[42.00291904, 0.09197281], [41.9775074 , 0.08824589], [42.00658608, 0.08615179], ..., [42.00145679, 0.10275319], [41.98672294, 0.09255127], [41.98355338, 0.08669633]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': [0.5209951650817852, 0.23900426211224726]}, 'ncall': 10026, 'paramnames': ['mean', 'scatter'], 'logzerr_single': 0.19303423021186586, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} skipping 15 weights: [0. 0. 0. ... 0.99755914 0.9975809 1. ] rec: {'ncall': 2048, 'niter': 6931, 'logz': 82.51126797630566, 'logzerr': 0.4800022347771922, 'ess': 989.4418387882997, 'posterior': {'mean': [41.98968202356687, 0.09114676119272457], 'stdev': [0.009297326255806548, 0.006793819118296698], 'median': [41.98947238149481, 0.09068695842395716], 'errlo': [41.98062812212561, 0.08466827339953377], 'errup': [41.999107688907316, 0.09770985563634536], 'information_gain_bits': [nan, 3.6621734305941214]}, 'weighted_samples': {'upoints': array([[9.75177245e-01, 8.77828782e-04], [8.18524108e-02, 2.44479339e-03], [9.88480171e-02, 2.02700325e-02], ..., [5.20995235e-01, 2.39361007e-01], [5.20995032e-01, 2.39712725e-01], [5.20995165e-01, 2.39004262e-01]]), 'points': array([[ 9.50354489e+02, 1.00811787e-02], [-8.36295178e+02, 1.02277281e-02], [-8.02303966e+02, 1.20525830e-02], ..., [ 4.19904702e+01, 9.06659110e-02], [ 4.19900633e+01, 9.09600940e-02], [ 4.19903302e+01, 9.03684948e-02]]), 'weights': array([0. , 0. , 0. , ..., 0.00177121, 0.00177125, 0.00177555]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -22.31896455, -22.31896455, -22.31896455]), 'logl': array([ -inf, -inf, -inf, ..., 98.49414236, 98.49416417, 98.4965862 ])}, 'samples': array([[41.99261818, 0.08729851], [41.99664389, 0.08319908], [41.97824608, 0.08718514], ..., [41.99975046, 0.10227979], [42.00241764, 0.08860842], [41.97018642, 0.08833478]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': [0.5209951650817852, 0.23900426211224726]}, 'param_names': ['mean', 'scatter']} weights: [0.34167524 0.36965396 0.11394021 ... 0.11309269 0.90291318 0.65861225] rec2: {'ncall': 6931, 'niter': 6931, 'logz': 97.76985434512109, 'logzerr': 8.570688762427586e-05, 'ess': 5123.234668254743, 'posterior': {'mean': [41.989673533632136, 0.09059357409028677], 'stdev': [0.006543754165026486, 0.004596090599814409], 'median': [41.98941172473769, 0.09050115057035493], 'errlo': [41.983044750694944, 0.08599162931708715], 'errup': [41.996458031426755, 0.0952836649169508], 'information_gain_bits': [nan, 3.8393471248186173]}, 'weighted_samples': {'upoints': None, 'points': array([[42.00291904, 0.09197281], [41.9775074 , 0.08824589], [42.00658608, 0.08615179], ..., [42.00145679, 0.10275319], [41.98672294, 0.09255127], [41.98355338, 0.08669633]]), 'weights': array([1.01960801e-04, 1.10310053e-04, 3.40013973e-05, ..., 3.37484848e-05, 2.69442269e-04, 1.96539361e-04]), 'logw': array([-8.84375938, -8.84375938, -8.84375938, ..., -8.84375938, -8.84375938, -8.84375938]), 'logl': array([97.42269161, 97.50139824, 96.32450479, ..., 96.31703869, 98.39445732, 98.07896589])}, 'samples': array([[41.99542553, 0.09237804], [41.97980873, 0.09237831], [41.99767108, 0.09574967], ..., [41.9977458 , 0.09371036], [41.99336497, 0.09418241], [41.98304951, 0.09079366]]), 'maximum_likelihood': {'logl': 98.49658620114383, 'point': [41.990330163570434, 0.09036849476345528], 'point_untransformed': None}, 'param_names': ['mean', 'scatter']}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+1, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=77.54, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=23, ncalls=425, regioncalls=1000, ndraw=40, logz=86.13, remainder_fraction=99.9998%, Lmin=90.62, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=88.39, remainder_fraction=99.9981%, Lmin=91.98, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=62, ncalls=469, regioncalls=2760, ndraw=40, logz=89.78, remainder_fraction=99.9922%, Lmin=93.05, Lmax=101.10 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=491, regioncalls=3640, ndraw=40, logz=90.68, remainder_fraction=99.9808%, Lmin=93.90, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=506, regioncalls=4240, ndraw=40, logz=91.16, remainder_fraction=99.9690%, Lmin=94.28, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=529, regioncalls=5200, ndraw=40, logz=91.98, remainder_fraction=99.9309%, Lmin=94.90, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=540, regioncalls=5640, ndraw=40, logz=92.30, remainder_fraction=99.9044%, Lmin=95.13, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=134, ncalls=558, regioncalls=6360, ndraw=40, logz=92.73, remainder_fraction=99.8517%, Lmin=95.50, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=587, regioncalls=7520, ndraw=40, logz=93.45, remainder_fraction=99.6886%, Lmin=96.16, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=610, regioncalls=8480, ndraw=40, logz=93.91, remainder_fraction=99.5043%, Lmin=96.58, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=631, regioncalls=9320, ndraw=40, logz=94.33, remainder_fraction=99.2526%, Lmin=96.86, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=226, ncalls=661, regioncalls=10520, ndraw=40, logz=94.78, remainder_fraction=98.8330%, Lmin=97.18, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=676, regioncalls=11120, ndraw=40, logz=94.99, remainder_fraction=98.5635%, Lmin=97.36, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=259, ncalls=698, regioncalls=12000, ndraw=40, logz=95.26, remainder_fraction=98.0959%, Lmin=97.63, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=712, regioncalls=12560, ndraw=40, logz=95.41, remainder_fraction=97.7997%, Lmin=97.76, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=725, regioncalls=13120, ndraw=40, logz=95.54, remainder_fraction=97.4838%, Lmin=97.83, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=305, ncalls=768, regioncalls=14840, ndraw=40, logz=95.83, remainder_fraction=96.6564%, Lmin=98.09, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=786, regioncalls=15560, ndraw=40, logz=95.99, remainder_fraction=96.0244%, Lmin=98.18, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=337, ncalls=807, regioncalls=16400, ndraw=40, logz=96.15, remainder_fraction=95.3175%, Lmin=98.28, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=833, regioncalls=17480, ndraw=40, logz=96.35, remainder_fraction=94.2789%, Lmin=98.49, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=862, regioncalls=18680, ndraw=40, logz=96.55, remainder_fraction=93.0074%, Lmin=98.67, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=883, regioncalls=19520, ndraw=40, logz=96.67, remainder_fraction=92.0986%, Lmin=98.73, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=439, ncalls=926, regioncalls=21240, ndraw=40, logz=96.94, remainder_fraction=89.5267%, Lmin=99.00, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=927, regioncalls=21280, ndraw=40, logz=96.95, remainder_fraction=89.4688%, Lmin=99.00, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=942, regioncalls=21880, ndraw=40, logz=97.01, remainder_fraction=88.8368%, Lmin=99.05, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=472, ncalls=968, regioncalls=22920, ndraw=40, logz=97.14, remainder_fraction=87.3079%, Lmin=99.17, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=977, regioncalls=23280, ndraw=40, logz=97.19, remainder_fraction=86.8106%, Lmin=99.20, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1024, regioncalls=25160, ndraw=40, logz=97.39, remainder_fraction=83.7818%, Lmin=99.35, Lmax=101.11 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1051, regioncalls=26240, ndraw=40, logz=97.49, remainder_fraction=82.2832%, Lmin=99.42, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1072, regioncalls=27080, ndraw=40, logz=97.57, remainder_fraction=80.7011%, Lmin=99.52, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=578, ncalls=1092, regioncalls=27920, ndraw=40, logz=97.65, remainder_fraction=79.2556%, Lmin=99.57, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1118, regioncalls=28960, ndraw=40, logz=97.73, remainder_fraction=77.3810%, Lmin=99.64, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1160, regioncalls=30640, ndraw=40, logz=97.84, remainder_fraction=74.7842%, Lmin=99.74, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1170, regioncalls=31040, ndraw=40, logz=97.87, remainder_fraction=73.8575%, Lmin=99.76, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=673, ncalls=1212, regioncalls=32760, ndraw=40, logz=97.98, remainder_fraction=71.0287%, Lmin=99.86, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1219, regioncalls=33040, ndraw=40, logz=98.00, remainder_fraction=70.4083%, Lmin=99.88, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=715, ncalls=1260, regioncalls=34720, ndraw=40, logz=98.10, remainder_fraction=67.2304%, Lmin=99.96, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1267, regioncalls=35040, ndraw=40, logz=98.11, remainder_fraction=66.7902%, Lmin=99.96, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=1296, regioncalls=36280, ndraw=40, logz=98.16, remainder_fraction=65.0817%, Lmin=100.02, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1322, regioncalls=37320, ndraw=40, logz=98.21, remainder_fraction=63.3310%, Lmin=100.08, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=793, ncalls=1358, regioncalls=38800, ndraw=40, logz=98.29, remainder_fraction=60.4678%, Lmin=100.16, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1367, regioncalls=39200, ndraw=40, logz=98.31, remainder_fraction=59.7909%, Lmin=100.18, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1380, regioncalls=39720, ndraw=40, logz=98.33, remainder_fraction=58.8978%, Lmin=100.20, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=835, ncalls=1413, regioncalls=41080, ndraw=40, logz=98.38, remainder_fraction=56.7301%, Lmin=100.27, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1418, regioncalls=41280, ndraw=40, logz=98.39, remainder_fraction=56.3332%, Lmin=100.28, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=879, ncalls=1472, regioncalls=43560, ndraw=40, logz=98.47, remainder_fraction=52.7721%, Lmin=100.37, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1473, regioncalls=43600, ndraw=40, logz=98.47, remainder_fraction=52.6823%, Lmin=100.37, Lmax=101.12 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1496, regioncalls=44520, ndraw=40, logz=98.50, remainder_fraction=50.9723%, Lmin=100.42, Lmax=101.12 INFO ultranest:integrator.py:2654 Explored until L=1e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 1508 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 99.21 +- 0.03825 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 972.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.41, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.05 bs:0.04 tail:0.41 total:0.41 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-405945789829.58, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=-14543780120.47, remainder_fraction=100.0000%, Lmin=-14330281204.24, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=488, regioncalls=3520, ndraw=40, logz=-2695832923.91, remainder_fraction=100.0000%, Lmin=-2578922208.45, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=531, regioncalls=5240, ndraw=40, logz=-621093047.40, remainder_fraction=100.0000%, Lmin=-588559621.47, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=576, regioncalls=7040, ndraw=40, logz=-179312911.40, remainder_fraction=100.0000%, Lmin=-175123183.83, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=627, regioncalls=9080, ndraw=40, logz=-37629480.84, remainder_fraction=100.0000%, Lmin=-37019184.92, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=671, regioncalls=10840, ndraw=40, logz=-12066612.49, remainder_fraction=100.0000%, Lmin=-11773456.96, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=708, regioncalls=12320, ndraw=40, logz=-5121052.97, remainder_fraction=100.0000%, Lmin=-5026605.32, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=720, regioncalls=12800, ndraw=40, logz=-4239114.89, remainder_fraction=100.0000%, Lmin=-4218156.66, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=772, regioncalls=14880, ndraw=40, logz=-2131925.19, remainder_fraction=100.0000%, Lmin=-2080057.46, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=818, regioncalls=16720, ndraw=40, logz=-1014637.58, remainder_fraction=100.0000%, Lmin=-964900.30, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=876, regioncalls=19040, ndraw=40, logz=-541870.28, remainder_fraction=100.0000%, Lmin=-535492.84, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=927, regioncalls=21080, ndraw=40, logz=-300783.39, remainder_fraction=100.0000%, Lmin=-295422.19, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=939, regioncalls=21560, ndraw=40, logz=-255114.89, remainder_fraction=100.0000%, Lmin=-251465.12, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=974, regioncalls=22960, ndraw=40, logz=-151349.49, remainder_fraction=100.0000%, Lmin=-150202.02, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1028, regioncalls=25120, ndraw=40, logz=-99997.74, remainder_fraction=100.0000%, Lmin=-98049.75, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1081, regioncalls=27240, ndraw=40, logz=-65129.44, remainder_fraction=100.0000%, Lmin=-65004.43, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1149, regioncalls=29960, ndraw=40, logz=-40261.62, remainder_fraction=100.0000%, Lmin=-40093.67, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=639, ncalls=1209, regioncalls=32360, ndraw=40, logz=-29839.79, remainder_fraction=100.0000%, Lmin=-29468.85, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1212, regioncalls=32480, ndraw=40, logz=-29476.44, remainder_fraction=100.0000%, Lmin=-28904.97, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1275, regioncalls=35000, ndraw=40, logz=-21665.40, remainder_fraction=100.0000%, Lmin=-21630.82, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1338, regioncalls=37520, ndraw=40, logz=-15756.30, remainder_fraction=100.0000%, Lmin=-15544.83, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=751, ncalls=1389, regioncalls=39560, ndraw=40, logz=-12939.33, remainder_fraction=100.0000%, Lmin=-12872.54, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1402, regioncalls=40080, ndraw=40, logz=-12015.41, remainder_fraction=100.0000%, Lmin=-12002.51, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1488, regioncalls=43520, ndraw=40, logz=-9473.37, remainder_fraction=100.0000%, Lmin=-9362.21, Lmax=-276.64 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([393, 6, 1])) DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1571, regioncalls=46840, ndraw=40, logz=-7725.36, remainder_fraction=100.0000%, Lmin=-7665.90, Lmax=-276.64 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1684, regioncalls=51360, ndraw=40, logz=-6168.48, remainder_fraction=100.0000%, Lmin=-6136.23, Lmax=-276.64 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([396, 1, 3])) DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1775, regioncalls=55000, ndraw=40, logz=-4952.17, remainder_fraction=100.0000%, Lmin=-4935.58, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1860, regioncalls=58400, ndraw=40, logz=-4041.29, remainder_fraction=100.0000%, Lmin=-4003.76, Lmax=-249.74 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([397, 1, 2])) DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1957, regioncalls=62280, ndraw=40, logz=-3517.98, remainder_fraction=100.0000%, Lmin=-3509.78, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=2051, regioncalls=66040, ndraw=40, logz=-2883.66, remainder_fraction=100.0000%, Lmin=-2816.71, Lmax=-249.74 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([397, 1, 2])) DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=2171, regioncalls=70840, ndraw=40, logz=-2411.47, remainder_fraction=100.0000%, Lmin=-2394.29, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=2298, regioncalls=75920, ndraw=40, logz=-2097.08, remainder_fraction=100.0000%, Lmin=-2076.89, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=2387, regioncalls=79480, ndraw=40, logz=-1817.46, remainder_fraction=100.0000%, Lmin=-1804.91, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=2406, regioncalls=80240, ndraw=40, logz=-1783.64, remainder_fraction=100.0000%, Lmin=-1754.08, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2475, regioncalls=83080, ndraw=40, logz=-1566.13, remainder_fraction=100.0000%, Lmin=-1555.97, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2557, regioncalls=86360, ndraw=40, logz=-1401.30, remainder_fraction=100.0000%, Lmin=-1389.84, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2604, regioncalls=88240, ndraw=40, logz=-1337.91, remainder_fraction=100.0000%, Lmin=-1324.13, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2643, regioncalls=89800, ndraw=40, logz=-1276.87, remainder_fraction=100.0000%, Lmin=-1266.90, Lmax=-249.74 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2726, regioncalls=93160, ndraw=40, logz=-1120.19, remainder_fraction=100.0000%, Lmin=-1110.35, Lmax=-241.79 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2781, regioncalls=95360, ndraw=40, logz=-1014.13, remainder_fraction=100.0000%, Lmin=-1001.54, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2795, regioncalls=95960, ndraw=40, logz=-996.61, remainder_fraction=100.0000%, Lmin=-984.22, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2872, regioncalls=99040, ndraw=40, logz=-915.47, remainder_fraction=100.0000%, Lmin=-904.91, Lmax=-223.34 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2938, regioncalls=101680, ndraw=40, logz=-835.37, remainder_fraction=100.0000%, Lmin=-820.73, Lmax=-176.99 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=3019, regioncalls=105000, ndraw=40, logz=-743.56, remainder_fraction=100.0000%, Lmin=-733.85, Lmax=-176.99 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=3102, regioncalls=108320, ndraw=40, logz=-699.33, remainder_fraction=100.0000%, Lmin=-684.33, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3126, regioncalls=109320, ndraw=40, logz=-686.79, remainder_fraction=100.0000%, Lmin=-676.46, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=3173, regioncalls=111200, ndraw=40, logz=-654.22, remainder_fraction=100.0000%, Lmin=-643.23, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=3244, regioncalls=114040, ndraw=40, logz=-625.35, remainder_fraction=100.0000%, Lmin=-615.39, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=3278, regioncalls=115400, ndraw=40, logz=-611.42, remainder_fraction=100.0000%, Lmin=-601.50, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=3314, regioncalls=116920, ndraw=40, logz=-595.00, remainder_fraction=100.0000%, Lmin=-585.36, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=3370, regioncalls=119160, ndraw=40, logz=-574.51, remainder_fraction=100.0000%, Lmin=-565.11, Lmax=-115.14 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=3421, regioncalls=121240, ndraw=40, logz=-564.24, remainder_fraction=100.0000%, Lmin=-555.02, Lmax=-87.70 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=3435, regioncalls=121800, ndraw=40, logz=-561.71, remainder_fraction=100.0000%, Lmin=-552.59, Lmax=-87.70 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=3501, regioncalls=124480, ndraw=40, logz=-552.18, remainder_fraction=100.0000%, Lmin=-543.29, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=3566, regioncalls=127160, ndraw=40, logz=-542.89, remainder_fraction=100.0000%, Lmin=-533.87, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=3633, regioncalls=129960, ndraw=40, logz=-533.59, remainder_fraction=100.0000%, Lmin=-524.21, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=3703, regioncalls=132880, ndraw=40, logz=-526.06, remainder_fraction=100.0000%, Lmin=-516.45, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=3716, regioncalls=133480, ndraw=40, logz=-523.48, remainder_fraction=100.0000%, Lmin=-514.33, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3752, regioncalls=135040, ndraw=40, logz=-514.54, remainder_fraction=100.0000%, Lmin=-504.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3812, regioncalls=137480, ndraw=40, logz=-503.35, remainder_fraction=100.0000%, Lmin=-493.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3839, regioncalls=138600, ndraw=40, logz=-497.65, remainder_fraction=100.0000%, Lmin=-487.69, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3869, regioncalls=140000, ndraw=40, logz=-492.38, remainder_fraction=100.0000%, Lmin=-482.81, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3916, regioncalls=141960, ndraw=40, logz=-481.86, remainder_fraction=100.0000%, Lmin=-471.51, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3958, regioncalls=143760, ndraw=40, logz=-471.49, remainder_fraction=100.0000%, Lmin=-461.58, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3974, regioncalls=144400, ndraw=40, logz=-467.59, remainder_fraction=100.0000%, Lmin=-457.50, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=4041, regioncalls=147160, ndraw=40, logz=-460.25, remainder_fraction=100.0000%, Lmin=-450.50, Lmax=-72.54 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=4093, regioncalls=149440, ndraw=40, logz=-451.28, remainder_fraction=100.0000%, Lmin=-441.42, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=4159, regioncalls=152360, ndraw=40, logz=-442.09, remainder_fraction=100.0000%, Lmin=-431.97, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=4224, regioncalls=155080, ndraw=40, logz=-432.78, remainder_fraction=100.0000%, Lmin=-422.44, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2260, ncalls=4266, regioncalls=156800, ndraw=40, logz=-428.15, remainder_fraction=100.0000%, Lmin=-417.97, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=4292, regioncalls=157880, ndraw=40, logz=-424.47, remainder_fraction=100.0000%, Lmin=-413.65, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=4344, regioncalls=160120, ndraw=40, logz=-416.64, remainder_fraction=100.0000%, Lmin=-405.68, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2344, ncalls=4389, regioncalls=161960, ndraw=40, logz=-411.42, remainder_fraction=100.0000%, Lmin=-400.86, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=4411, regioncalls=162960, ndraw=40, logz=-408.18, remainder_fraction=100.0000%, Lmin=-397.87, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=4465, regioncalls=165200, ndraw=40, logz=-400.01, remainder_fraction=100.0000%, Lmin=-389.40, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=4518, regioncalls=167680, ndraw=40, logz=-394.00, remainder_fraction=100.0000%, Lmin=-383.71, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=4533, regioncalls=168280, ndraw=40, logz=-392.25, remainder_fraction=100.0000%, Lmin=-381.40, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=4607, regioncalls=171320, ndraw=40, logz=-383.10, remainder_fraction=100.0000%, Lmin=-372.99, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=4677, regioncalls=174320, ndraw=40, logz=-373.88, remainder_fraction=100.0000%, Lmin=-363.25, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=4731, regioncalls=176640, ndraw=40, logz=-365.06, remainder_fraction=100.0000%, Lmin=-353.57, Lmax=-48.30 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=4785, regioncalls=178960, ndraw=40, logz=-354.85, remainder_fraction=100.0000%, Lmin=-343.81, Lmax=-36.34 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=4809, regioncalls=180000, ndraw=40, logz=-353.22, remainder_fraction=100.0000%, Lmin=-342.59, Lmax=-36.34 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4848, regioncalls=181760, ndraw=40, logz=-347.69, remainder_fraction=100.0000%, Lmin=-337.09, Lmax=-31.02 DEBUG ultranest:integrator.py:2610 iteration=2672, ncalls=4898, regioncalls=183840, ndraw=40, logz=-339.03, remainder_fraction=100.0000%, Lmin=-327.74, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4910, regioncalls=184320, ndraw=40, logz=-337.47, remainder_fraction=100.0000%, Lmin=-325.86, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=4942, regioncalls=185720, ndraw=40, logz=-333.44, remainder_fraction=100.0000%, Lmin=-322.27, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4966, regioncalls=186840, ndraw=40, logz=-329.57, remainder_fraction=100.0000%, Lmin=-318.09, Lmax=4.51 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=5022, regioncalls=189240, ndraw=40, logz=-320.11, remainder_fraction=100.0000%, Lmin=-308.11, Lmax=5.94 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=5068, regioncalls=191160, ndraw=40, logz=-312.88, remainder_fraction=100.0000%, Lmin=-301.47, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5079, regioncalls=191640, ndraw=40, logz=-310.36, remainder_fraction=100.0000%, Lmin=-298.96, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=5135, regioncalls=193920, ndraw=40, logz=-299.95, remainder_fraction=100.0000%, Lmin=-288.26, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=5200, regioncalls=196560, ndraw=40, logz=-291.14, remainder_fraction=100.0000%, Lmin=-278.53, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=5260, regioncalls=199040, ndraw=40, logz=-282.12, remainder_fraction=100.0000%, Lmin=-270.79, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=5318, regioncalls=201400, ndraw=40, logz=-274.21, remainder_fraction=100.0000%, Lmin=-262.16, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=5335, regioncalls=202120, ndraw=40, logz=-271.64, remainder_fraction=100.0000%, Lmin=-259.39, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=5370, regioncalls=203640, ndraw=40, logz=-265.19, remainder_fraction=100.0000%, Lmin=-252.95, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=5425, regioncalls=205960, ndraw=40, logz=-257.20, remainder_fraction=100.0000%, Lmin=-245.23, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=5455, regioncalls=207280, ndraw=40, logz=-252.78, remainder_fraction=100.0000%, Lmin=-240.18, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=5478, regioncalls=208320, ndraw=40, logz=-248.52, remainder_fraction=100.0000%, Lmin=-236.40, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=5527, regioncalls=210400, ndraw=40, logz=-239.80, remainder_fraction=100.0000%, Lmin=-227.58, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=5583, regioncalls=212760, ndraw=40, logz=-231.74, remainder_fraction=100.0000%, Lmin=-219.05, Lmax=33.15 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=5634, regioncalls=214840, ndraw=40, logz=-222.54, remainder_fraction=100.0000%, Lmin=-209.88, Lmax=58.38 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=5700, regioncalls=217560, ndraw=40, logz=-213.29, remainder_fraction=100.0000%, Lmin=-200.38, Lmax=76.85 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=5757, regioncalls=219920, ndraw=40, logz=-203.34, remainder_fraction=100.0000%, Lmin=-190.75, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=5814, regioncalls=222280, ndraw=40, logz=-193.80, remainder_fraction=100.0000%, Lmin=-180.96, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5829, regioncalls=222920, ndraw=40, logz=-191.46, remainder_fraction=100.0000%, Lmin=-178.74, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5861, regioncalls=224280, ndraw=40, logz=-186.10, remainder_fraction=100.0000%, Lmin=-173.36, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5920, regioncalls=226680, ndraw=40, logz=-176.23, remainder_fraction=100.0000%, Lmin=-162.69, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=5947, regioncalls=227800, ndraw=40, logz=-170.03, remainder_fraction=100.0000%, Lmin=-156.47, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5969, regioncalls=228920, ndraw=40, logz=-165.77, remainder_fraction=100.0000%, Lmin=-152.80, Lmax=84.22 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=6018, regioncalls=230920, ndraw=40, logz=-156.66, remainder_fraction=100.0000%, Lmin=-143.72, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3511, ncalls=6059, regioncalls=232560, ndraw=40, logz=-150.40, remainder_fraction=100.0000%, Lmin=-136.95, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=6071, regioncalls=233040, ndraw=40, logz=-148.90, remainder_fraction=100.0000%, Lmin=-136.08, Lmax=87.91 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=6128, regioncalls=235440, ndraw=40, logz=-141.40, remainder_fraction=100.0000%, Lmin=-128.03, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=6175, regioncalls=237400, ndraw=40, logz=-135.44, remainder_fraction=100.0000%, Lmin=-122.57, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=6234, regioncalls=239920, ndraw=40, logz=-129.28, remainder_fraction=100.0000%, Lmin=-115.62, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=6291, regioncalls=242280, ndraw=40, logz=-121.98, remainder_fraction=100.0000%, Lmin=-108.30, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=6307, regioncalls=243000, ndraw=40, logz=-119.49, remainder_fraction=100.0000%, Lmin=-105.57, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=6341, regioncalls=244600, ndraw=40, logz=-114.52, remainder_fraction=100.0000%, Lmin=-101.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=6392, regioncalls=246680, ndraw=40, logz=-107.63, remainder_fraction=100.0000%, Lmin=-92.93, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=6451, regioncalls=249240, ndraw=40, logz=-99.84, remainder_fraction=100.0000%, Lmin=-86.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=6504, regioncalls=251600, ndraw=40, logz=-93.94, remainder_fraction=100.0000%, Lmin=-79.78, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=6560, regioncalls=253920, ndraw=40, logz=-87.53, remainder_fraction=100.0000%, Lmin=-73.71, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=6611, regioncalls=256040, ndraw=40, logz=-80.84, remainder_fraction=100.0000%, Lmin=-66.10, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=6681, regioncalls=258920, ndraw=40, logz=-72.71, remainder_fraction=100.0000%, Lmin=-58.43, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=6731, regioncalls=261160, ndraw=40, logz=-64.17, remainder_fraction=100.0000%, Lmin=-50.14, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=6794, regioncalls=264040, ndraw=40, logz=-56.55, remainder_fraction=100.0000%, Lmin=-42.25, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=6809, regioncalls=264760, ndraw=40, logz=-54.51, remainder_fraction=100.0000%, Lmin=-40.26, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=6846, regioncalls=266360, ndraw=40, logz=-50.77, remainder_fraction=100.0000%, Lmin=-36.34, Lmax=95.46 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=6898, regioncalls=268640, ndraw=40, logz=-44.92, remainder_fraction=100.0000%, Lmin=-30.73, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=6929, regioncalls=270040, ndraw=40, logz=-42.30, remainder_fraction=100.0000%, Lmin=-27.94, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=6953, regioncalls=271000, ndraw=40, logz=-39.90, remainder_fraction=100.0000%, Lmin=-25.81, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=7000, regioncalls=272920, ndraw=40, logz=-33.76, remainder_fraction=100.0000%, Lmin=-19.11, Lmax=97.52 DEBUG ultranest:integrator.py:2610 iteration=4230, ncalls=7038, regioncalls=274560, ndraw=40, logz=-28.94, remainder_fraction=100.0000%, Lmin=-13.81, Lmax=97.81 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=7052, regioncalls=275160, ndraw=40, logz=-27.24, remainder_fraction=100.0000%, Lmin=-12.10, Lmax=98.13 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=7099, regioncalls=277080, ndraw=40, logz=-21.58, remainder_fraction=100.0000%, Lmin=-6.73, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=7151, regioncalls=279240, ndraw=40, logz=-15.35, remainder_fraction=100.0000%, Lmin=-0.29, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=7203, regioncalls=281360, ndraw=40, logz=-9.28, remainder_fraction=100.0000%, Lmin=5.94, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=7263, regioncalls=283840, ndraw=40, logz=-3.98, remainder_fraction=100.0000%, Lmin=11.18, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4410, ncalls=7274, regioncalls=284360, ndraw=40, logz=-2.04, remainder_fraction=100.0000%, Lmin=13.40, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=7311, regioncalls=285880, ndraw=40, logz=3.00, remainder_fraction=100.0000%, Lmin=18.46, Lmax=98.24 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=7358, regioncalls=287760, ndraw=40, logz=8.96, remainder_fraction=100.0000%, Lmin=24.23, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=7384, regioncalls=288920, ndraw=40, logz=11.95, remainder_fraction=100.0000%, Lmin=27.45, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=7409, regioncalls=290000, ndraw=40, logz=14.74, remainder_fraction=100.0000%, Lmin=30.09, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=7463, regioncalls=292240, ndraw=40, logz=19.80, remainder_fraction=100.0000%, Lmin=35.70, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=7503, regioncalls=293880, ndraw=40, logz=23.43, remainder_fraction=100.0000%, Lmin=38.68, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=7515, regioncalls=294360, ndraw=40, logz=24.45, remainder_fraction=100.0000%, Lmin=39.70, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=7565, regioncalls=296400, ndraw=40, logz=28.05, remainder_fraction=100.0000%, Lmin=43.51, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=7617, regioncalls=298480, ndraw=40, logz=32.49, remainder_fraction=100.0000%, Lmin=47.97, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=7668, regioncalls=300600, ndraw=40, logz=35.71, remainder_fraction=100.0000%, Lmin=51.08, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=7724, regioncalls=302880, ndraw=40, logz=38.70, remainder_fraction=100.0000%, Lmin=54.16, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=7737, regioncalls=303480, ndraw=40, logz=39.50, remainder_fraction=100.0000%, Lmin=54.86, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=7777, regioncalls=305360, ndraw=40, logz=41.88, remainder_fraction=100.0000%, Lmin=57.55, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=7829, regioncalls=307480, ndraw=40, logz=45.28, remainder_fraction=100.0000%, Lmin=60.71, Lmax=98.39 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=7859, regioncalls=308760, ndraw=40, logz=46.79, remainder_fraction=100.0000%, Lmin=62.54, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=7881, regioncalls=309640, ndraw=40, logz=48.27, remainder_fraction=100.0000%, Lmin=63.72, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=7928, regioncalls=311600, ndraw=40, logz=51.04, remainder_fraction=100.0000%, Lmin=66.65, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=7967, regioncalls=313240, ndraw=40, logz=52.87, remainder_fraction=100.0000%, Lmin=68.31, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=7977, regioncalls=313640, ndraw=40, logz=53.45, remainder_fraction=100.0000%, Lmin=69.28, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=8026, regioncalls=315640, ndraw=40, logz=56.08, remainder_fraction=100.0000%, Lmin=71.64, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=8078, regioncalls=317840, ndraw=40, logz=57.95, remainder_fraction=100.0000%, Lmin=73.74, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=8129, regioncalls=319880, ndraw=40, logz=59.93, remainder_fraction=100.0000%, Lmin=75.54, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=8182, regioncalls=322000, ndraw=40, logz=61.74, remainder_fraction=100.0000%, Lmin=77.34, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=8233, regioncalls=324160, ndraw=40, logz=63.47, remainder_fraction=100.0000%, Lmin=79.26, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=8291, regioncalls=326560, ndraw=40, logz=65.13, remainder_fraction=100.0000%, Lmin=80.72, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=8319, regioncalls=327760, ndraw=40, logz=65.73, remainder_fraction=100.0000%, Lmin=81.30, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=8345, regioncalls=328840, ndraw=40, logz=66.46, remainder_fraction=100.0000%, Lmin=82.32, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=8395, regioncalls=330880, ndraw=40, logz=67.94, remainder_fraction=100.0000%, Lmin=83.86, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=8433, regioncalls=332480, ndraw=40, logz=68.97, remainder_fraction=99.9999%, Lmin=84.73, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=8450, regioncalls=333280, ndraw=40, logz=69.28, remainder_fraction=99.9998%, Lmin=85.11, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=8501, regioncalls=335360, ndraw=40, logz=70.49, remainder_fraction=99.9994%, Lmin=86.41, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=8557, regioncalls=337640, ndraw=40, logz=71.52, remainder_fraction=99.9984%, Lmin=87.38, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=8610, regioncalls=339920, ndraw=40, logz=72.47, remainder_fraction=99.9959%, Lmin=88.23, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=8661, regioncalls=342240, ndraw=40, logz=73.31, remainder_fraction=99.9900%, Lmin=89.27, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=8675, regioncalls=342920, ndraw=40, logz=73.54, remainder_fraction=99.9876%, Lmin=89.47, Lmax=98.41 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=8711, regioncalls=344440, ndraw=40, logz=74.18, remainder_fraction=99.9764%, Lmin=90.07, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=8765, regioncalls=346600, ndraw=40, logz=74.98, remainder_fraction=99.9489%, Lmin=90.97, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5594, ncalls=8811, regioncalls=348440, ndraw=40, logz=75.61, remainder_fraction=99.9044%, Lmin=91.55, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=8819, regioncalls=348760, ndraw=40, logz=75.71, remainder_fraction=99.8941%, Lmin=91.67, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=8867, regioncalls=350720, ndraw=40, logz=76.38, remainder_fraction=99.7920%, Lmin=92.30, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=8909, regioncalls=352560, ndraw=40, logz=76.84, remainder_fraction=99.6612%, Lmin=92.77, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=8920, regioncalls=353000, ndraw=40, logz=76.99, remainder_fraction=99.6085%, Lmin=92.95, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=8968, regioncalls=355080, ndraw=40, logz=77.53, remainder_fraction=99.3157%, Lmin=93.47, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=9021, regioncalls=357200, ndraw=40, logz=78.02, remainder_fraction=98.8649%, Lmin=93.92, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=9067, regioncalls=359120, ndraw=40, logz=78.47, remainder_fraction=98.2438%, Lmin=94.42, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=9118, regioncalls=361200, ndraw=40, logz=78.86, remainder_fraction=97.3902%, Lmin=94.80, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5850, ncalls=9130, regioncalls=361720, ndraw=40, logz=78.95, remainder_fraction=97.1280%, Lmin=94.86, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=9170, regioncalls=363320, ndraw=40, logz=79.20, remainder_fraction=96.2870%, Lmin=95.08, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=9221, regioncalls=365400, ndraw=40, logz=79.50, remainder_fraction=95.0289%, Lmin=95.37, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=9247, regioncalls=366480, ndraw=40, logz=79.64, remainder_fraction=94.2645%, Lmin=95.52, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=9270, regioncalls=367400, ndraw=40, logz=79.78, remainder_fraction=93.4054%, Lmin=95.66, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=9317, regioncalls=369280, ndraw=40, logz=80.03, remainder_fraction=91.7288%, Lmin=95.90, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=9376, regioncalls=371640, ndraw=40, logz=80.26, remainder_fraction=89.7527%, Lmin=96.11, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=9423, regioncalls=373560, ndraw=40, logz=80.46, remainder_fraction=87.5220%, Lmin=96.30, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=9479, regioncalls=375840, ndraw=40, logz=80.64, remainder_fraction=84.9630%, Lmin=96.48, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=9527, regioncalls=377840, ndraw=40, logz=80.80, remainder_fraction=82.0315%, Lmin=96.69, Lmax=98.49 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=9586, regioncalls=380280, ndraw=40, logz=80.96, remainder_fraction=79.0690%, Lmin=96.85, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=9596, regioncalls=380720, ndraw=40, logz=80.99, remainder_fraction=78.2190%, Lmin=96.89, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=9636, regioncalls=382520, ndraw=40, logz=81.10, remainder_fraction=75.8492%, Lmin=97.00, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=9694, regioncalls=384880, ndraw=40, logz=81.23, remainder_fraction=72.4337%, Lmin=97.13, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6300, ncalls=9717, regioncalls=385880, ndraw=40, logz=81.29, remainder_fraction=70.6438%, Lmin=97.20, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=9741, regioncalls=386840, ndraw=40, logz=81.35, remainder_fraction=69.0033%, Lmin=97.27, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=9796, regioncalls=389200, ndraw=40, logz=81.45, remainder_fraction=65.3357%, Lmin=97.39, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=9846, regioncalls=391240, ndraw=40, logz=81.53, remainder_fraction=62.6597%, Lmin=97.49, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=9859, regioncalls=391840, ndraw=40, logz=81.55, remainder_fraction=61.7254%, Lmin=97.51, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=9911, regioncalls=393920, ndraw=40, logz=81.64, remainder_fraction=57.9415%, Lmin=97.59, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=9962, regioncalls=396040, ndraw=40, logz=81.73, remainder_fraction=54.2676%, Lmin=97.67, Lmax=98.50 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=10008, regioncalls=397920, ndraw=40, logz=81.80, remainder_fraction=50.9164%, Lmin=97.76, Lmax=98.50 INFO ultranest:integrator.py:2654 Explored until L=1e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 10026 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 82.54 +- 0.1468 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 989.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.43, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.19 bs:0.15 tail:0.41 total:0.43 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_flatnuts.py::test_directjumper

0.04

Passed

tests/test_clustering.py::test_clusteringcase_eggbox

0.01

Passed

tests/test_netiterintegrate.py::test_visualisation

0.00

Passed

tests/test_run.py::test_run

9.90

Passed

tests/test_clustering.py::test_clusteringcase

0.57

Passed

tests/test_ordertest.py::test_diff_expand

0.00

[gw2] linux -- Python 3.10.6 /usr/bin/python3
[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_run.py::test_reactive_run_extraparams

11.26

Passed

tests/test_regionsampling.py::test_region_sampling_affine

0.07

Passed

tests/test_regionsampling.py::test_region_sampling_scaling

0.08

Passed

tests/test_run.py::test_reactive_run_resume_eggbox[hdf5]

6.41

[gw7] linux -- Python 3.10.6 /usr/bin/python3
[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..29.4283] | it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..29.4283] | it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..29.4283] | it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..29.4283] | it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..29.4283] | it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..29.4283] | it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..29.4283] | it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [29.6178..62.1019] | it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [29.6178..62.1019] | it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [29.6178..62.1019] | it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [29.6178..62.1019] | it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [29.6178..62.1019] | it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=43.4(0.00%) | Like=49.11..241.87 [29.6178..62.1019] | it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [29.6178..62.1019] | it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [29.6178..62.1019] | it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [62.2053..112.3934] | it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [62.2053..112.3934] | it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [62.2053..112.3934] | it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [62.2053..112.3934] | it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [62.2053..112.3934] | it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 12.65 │ ▁ ▇ │19.30 18.98 +- 0.35 b : 5.3 │ ▇ ▁ │26.2 6.3 +- 1.1 pointstore: (300, 7) 626 626 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.897580582291928408e+01,3.482687211659772908e-01,1.899594672309787668e+01,1.899594672309787668e+01,1.899594672309787668e+01,6.316415107809904228e+00,1.095459745550366071e+00,6.253063034987970781e+00,6.253063034987970781e+00,6.253063034987970781e+00 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.975806 0.348269 18.995947 ... 6.253063 6.253063 6.253063 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.975805822919284 checking mean of parameter 'b': 6.316415107809904 checking stdev of parameter 'a': 0.3482687211659773 checking stdev of parameter 'b': 1.095459745550366 checking median of parameter 'a': 18.995946723097877 checking median of parameter 'b': 6.253063034987971 checking errlo of parameter 'a': 18.995946723097877 checking errlo of parameter 'b': 6.253063034987971 checking errup of parameter 'a': 18.995946723097877 checking errup of parameter 'b': 6.253063034987971 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} ====== Running Eggbox problem [2] ===== [ultranest] Resuming from 300 stored points Mono-modal Volume: ~exp(-3.06) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..29.4283] | it/evals=0/626 eff=inf% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..29.4283] | it/evals=10/626 eff=inf% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..29.4283] | it/evals=20/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..29.4283] | it/evals=30/626 eff=inf% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..29.4283] | it/evals=40/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..29.4283] | it/evals=50/626 eff=inf% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..29.4283] | it/evals=60/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [29.6178..62.1019] | it/evals=70/626 eff=inf% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [29.6178..62.1019] | it/evals=80/626 eff=inf% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [29.6178..62.1019] | it/evals=90/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [29.6178..62.1019] | it/evals=100/626 eff=inf% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [29.6178..62.1019] | it/evals=110/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) * Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=41.4(0.00%) | Like=46.04..241.87 [29.6178..62.1019] | it/evals=115/626 eff=inf% N=100 Z=43.4(0.00%) | Like=49.11..241.87 [29.6178..62.1019] | it/evals=120/626 eff=inf% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [29.6178..62.1019] | it/evals=130/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [29.6178..62.1019] | it/evals=140/626 eff=inf% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [62.2053..112.3934] | it/evals=150/626 eff=inf% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [62.2053..112.3934] | it/evals=160/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [62.2053..112.3934] | it/evals=170/626 eff=inf% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [62.2053..112.3934] | it/evals=180/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [62.2053..112.3934] | it/evals=190/626 eff=inf% N=100 Z=102.1(0.00%) | Like=108.02..241.87 [62.2053..112.3934] | it/evals=200/635 eff=2222.2222% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.07) Quality: ok a: +0.0| ** ******* ****** ****** ******* ****| +31.4 b: +0.0|**** ******* *** ** ******* ****** ***| +31.4 Z=107.6(0.00%) | Like=113.25..241.87 [112.8373..172.1226] | it/evals=210/686 eff=350.0000% N=100 Z=115.9(0.00%) | Like=122.26..241.87 [112.8373..172.1226] | it/evals=220/773 eff=149.6599% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.30) Quality: ok a: +0.0|*** ***** ******* ****** ****** ***| +31.4 b: +0.0|*** ****** ** ** ****** ****** ***| +31.4 Z=122.3(0.00%) | Like=129.85..241.87 [112.8373..172.1226] | it/evals=230/847 eff=104.0724% N=100 Z=129.8(0.00%) | Like=136.55..241.87 [112.8373..172.1226] | it/evals=240/970 eff=69.7674% N=100 Z=137.3(0.00%) | Like=144.23..241.87 [112.8373..172.1226] | it/evals=250/1051 eff=58.8235% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.53) Quality: ok a: +3.1e-05|*** ***** ***** ***** ***** ***| +3.1e+01 b: +0.0|*** ****** ** ** ***** ****** ***| +31.4 Z=142.6(0.00%) | Like=149.88..241.87 [112.8373..172.1226] | it/evals=260/1113 eff=53.3881% N=100 Z=150.6(0.00%) | Like=158.76..242.08 [112.8373..172.1226] | it/evals=270/1240 eff=43.9739% N=100 Have 17 modes Volume: ~exp(-3.30) * Expected Volume: exp(-2.76) Quality: ok a: +3.1e-05|66 HAFAH 3343 522D5 11191 G77| +3.1e+01 b: +3.1e-05|66E 2H22C 94 44 55A75 31131 DDF| +3.1e+01 Z=155.4(0.00%) | Like=161.77..242.08 [112.8373..172.1226] | it/evals=276/1298 eff=41.0714% N=100 Z=157.4(0.00%) | Like=165.84..242.08 [112.8373..172.1226] | it/evals=280/1339 eff=39.2707% N=100 Z=163.4(0.00%) | Like=169.78..242.08 [112.8373..172.1226] | it/evals=290/1390 eff=37.9581% N=100 Have 11 modes Volume: ~exp(-3.97) * Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05|61 1AB31 33432 22221 1112 87| +3.1e+01 b: +3.1e-05|61 12228 94221 173A1 31131 3B| +3.1e+01 Z=169.2(0.00%) | Like=176.32..242.08 [173.9486..199.8262] | it/evals=299/1456 eff=36.0241% N=100 Z=169.7(0.00%) | Like=176.48..242.08 [173.9486..199.8262] | it/evals=300/1464 eff=35.7995% N=100 Z=177.0(0.00%) | Like=183.98..242.08 [173.9486..199.8262] | it/evals=310/1544 eff=33.7691% N=100 Z=182.0(0.00%) | Like=189.03..242.08 [173.9486..199.8262] | it/evals=320/1653 eff=31.1587% N=100 Have 11 modes Volume: ~exp(-4.06) * Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05|61 1A111 33432 22221 8112 87| +3.1e+01 b: +3.1e-05|61 12288 9421 173A3 1133 3B| +3.1e+01 Z=182.7(0.00%) | Like=189.52..242.08 [173.9486..199.8262] | it/evals=322/1678 eff=30.6084% N=100 Z=185.5(0.00%) | Like=192.14..242.08 [173.9486..199.8262] | it/evals=330/1823 eff=27.5689% N=100 Z=187.8(0.00%) | Like=194.77..242.08 [173.9486..199.8262] | it/evals=340/1954 eff=25.6024% N=100 Have 9 modes Volume: ~exp(-4.40) * Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05|69 1311 3432 22221 1112 27| +3.1e+01 b: +3.1e-05|82 1221 42 17233 1139 9| +3.1e+01 Z=189.3(0.00%) | Like=196.24..242.08 [173.9486..199.8262] | it/evals=345/2018 eff=24.7845% N=100 Z=190.7(0.00%) | Like=197.56..242.08 [173.9486..199.8262] | it/evals=350/2076 eff=24.1379% N=100 Z=193.4(0.00%) | Like=201.00..242.08 [200.0805..218.4468] | it/evals=360/2164 eff=23.4070% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05|69 9391 343 222 1112 27| +3.1e+01 b: +3.1e-05|82 221 420 7233 1133 9| +3.1e+01 Z=197.1(0.00%) | Like=204.14..242.08 [200.0805..218.4468] | it/evals=370/2261 eff=22.6300% N=100 Z=200.0(0.00%) | Like=206.82..242.86 [200.0805..218.4468] | it/evals=380/2354 eff=21.9907% N=100 Z=203.2(0.00%) | Like=210.59..242.86 [200.0805..218.4468] | it/evals=390/2534 eff=20.4403% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05|69 9391 343 222 1111 27| +3.1e+01 b: +3.1e-05|82 221 430 723 113 09| +3.1e+01 Z=204.7(0.00%) | Like=211.79..242.86 [200.0805..218.4468] | it/evals=396/2674 eff=19.3359% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 2692 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.433 +- 0.793 single instance: logZ = 235.433 +- 0.246 bootstrapped : logZ = 235.293 +- 0.385 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 0.0 │▁ ▁ ▇ ▇ ▄ ▃│31.4 18.3 +- 7.5 b : 0 │▄ ▃ ▅ ▁▇ ▃│31 18 +- 11 pointstore: (500, 7) 2066 2692 626 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.830718091502420819e+01,7.461548357996892200e+00,1.886508287133898776e+01,1.252215863233727511e+01,2.522619436377484803e+01,1.764800129533112383e+01,1.076980339796848973e+01,1.894881784854014484e+01,1.822050496151064736e-01,2.510396508290707729e+01 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.307181 7.461548 18.865083 ... 18.948818 0.182205 25.103965 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.307180915024208 checking mean of parameter 'b': 17.648001295331124 checking stdev of parameter 'a': 7.461548357996892 checking stdev of parameter 'b': 10.76980339796849 checking median of parameter 'a': 18.865082871338988 checking median of parameter 'b': 18.948817848540145 checking errlo of parameter 'a': 12.522158632337275 checking errlo of parameter 'b': 0.18220504961510647 checking errup of parameter 'a': 25.226194363774848 checking errup of parameter 'b': 25.103965082907077 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} sampler results: ******************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7927566606506654, 'logz_bs': 235.29290858222754, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.38472081967040594, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22556685337143384, 'posterior': {'mean': [18.307180915024208, 17.648001295331124], 'stdev': [7.461548357996892, 10.76980339796849], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'ncall': 2692, 'paramnames': ['a', 'b'], 'logzerr_single': 0.24562688650372005, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} reader results: ******************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7656270015727977, 'logz_bs': 235.75786154760183, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.32516409952395975, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22000811918063334, 'posterior': {'mean': [18.307180915024208, 17.648001295331113], 'stdev': [7.461548357996893, 10.769803397968483], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () weighted_samples :: upoints (500, 2) weighted_samples :: points (500, 2) weighted_samples :: weights (500,) weighted_samples :: logw (500,) weighted_samples :: logl (500,) maximum_likelihood :: logl () maximum_likelihood :: point (2,) maximum_likelihood :: point_untransformed (2,) insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpgpmiyyvf, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=123, regioncalls=920, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=137, regioncalls=1480, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=149, regioncalls=1960, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=162, regioncalls=2480, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=175, regioncalls=3000, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=188, regioncalls=3520, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=206, regioncalls=4240, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=223, regioncalls=4920, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=244, regioncalls=5760, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=284, regioncalls=7360, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=309, regioncalls=8360, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=341, regioncalls=9640, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=377, regioncalls=11080, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=396, regioncalls=11840, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=441, regioncalls=13640, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=502, regioncalls=16080, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=553, regioncalls=18120, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=584, regioncalls=19360, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 626 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpgpmiyyvf, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [107.94292989 191.2912043 0. 0.57032947 0.98250479 17.91742875 30.86629839]: u=[0.57032947 0.98250479] -> p=[17.91742875 30.86629839] -> L=191.29120430116933 INFO ultranest:integrator.py:2364 Resuming from 300 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=626, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=626, regioncalls=0, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=626, regioncalls=0, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=626, regioncalls=0, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=626, regioncalls=0, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=626, regioncalls=0, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=626, regioncalls=0, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=626, regioncalls=0, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=626, regioncalls=0, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=626, regioncalls=0, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=626, regioncalls=0, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=626, regioncalls=0, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=626, regioncalls=0, ndraw=40, logz=41.41, remainder_fraction=100.0000%, Lmin=46.04, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=626, regioncalls=0, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=626, regioncalls=0, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=626, regioncalls=0, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=626, regioncalls=0, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=626, regioncalls=0, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=626, regioncalls=0, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=626, regioncalls=0, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=626, regioncalls=0, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=635, regioncalls=360, ndraw=40, logz=102.10, remainder_fraction=100.0000%, Lmin=108.02, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=686, regioncalls=2400, ndraw=40, logz=107.58, remainder_fraction=100.0000%, Lmin=113.25, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=773, regioncalls=5880, ndraw=40, logz=115.88, remainder_fraction=100.0000%, Lmin=122.26, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), array([13, 18, 18, 14, 9, 15, 4, 6, 2, 1])) DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=847, regioncalls=8840, ndraw=40, logz=122.33, remainder_fraction=100.0000%, Lmin=129.85, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=970, regioncalls=13760, ndraw=40, logz=129.76, remainder_fraction=100.0000%, Lmin=136.55, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1051, regioncalls=17000, ndraw=40, logz=137.33, remainder_fraction=100.0000%, Lmin=144.23, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]), array([ 8, 13, 5, 6, 8, 3, 8, 5, 8, 6, 9, 5, 5, 4, 6, 1])) DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1113, regioncalls=19480, ndraw=40, logz=142.65, remainder_fraction=100.0000%, Lmin=149.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1240, regioncalls=24560, ndraw=40, logz=150.61, remainder_fraction=100.0000%, Lmin=158.76, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]), array([ 7, 14, 8, 5, 8, 4, 6, 5, 8, 10, 3, 5, 4, 5, 2, 1, 5])) DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=1298, regioncalls=26880, ndraw=40, logz=155.38, remainder_fraction=100.0000%, Lmin=161.77, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1339, regioncalls=28520, ndraw=40, logz=157.41, remainder_fraction=100.0000%, Lmin=165.84, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1390, regioncalls=30560, ndraw=40, logz=163.43, remainder_fraction=100.0000%, Lmin=169.78, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([25, 33, 23, 1, 1, 1, 1, 8, 1, 1, 5])) DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=1456, regioncalls=33200, ndraw=40, logz=169.15, remainder_fraction=100.0000%, Lmin=176.32, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1464, regioncalls=33520, ndraw=40, logz=169.65, remainder_fraction=100.0000%, Lmin=176.48, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1544, regioncalls=36720, ndraw=40, logz=177.02, remainder_fraction=100.0000%, Lmin=183.98, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1653, regioncalls=41080, ndraw=40, logz=182.02, remainder_fraction=100.0000%, Lmin=189.03, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([26, 35, 22, 1, 1, 1, 1, 7, 1, 1, 4])) DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=1678, regioncalls=42080, ndraw=40, logz=182.71, remainder_fraction=100.0000%, Lmin=189.52, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=1823, regioncalls=47880, ndraw=40, logz=185.51, remainder_fraction=100.0000%, Lmin=192.14, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=1954, regioncalls=53120, ndraw=40, logz=187.85, remainder_fraction=100.0000%, Lmin=194.77, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([27, 34, 24, 1, 1, 1, 1, 5, 6])) DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=2018, regioncalls=55680, ndraw=40, logz=189.30, remainder_fraction=100.0000%, Lmin=196.24, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2076, regioncalls=58000, ndraw=40, logz=190.69, remainder_fraction=100.0000%, Lmin=197.56, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2164, regioncalls=61520, ndraw=40, logz=193.38, remainder_fraction=100.0000%, Lmin=201.00, Lmax=242.08 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([29, 28, 28, 1, 1, 1, 1, 6, 5])) DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=2261, regioncalls=65400, ndraw=40, logz=197.14, remainder_fraction=100.0000%, Lmin=204.14, Lmax=242.08 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=2354, regioncalls=69120, ndraw=40, logz=200.04, remainder_fraction=100.0000%, Lmin=206.82, Lmax=242.86 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=2534, regioncalls=76320, ndraw=40, logz=203.21, remainder_fraction=100.0000%, Lmin=210.59, Lmax=242.86 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([35, 23, 27, 1, 1, 1, 1, 6, 5])) DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=2674, regioncalls=81920, ndraw=40, logz=204.73, remainder_fraction=100.0000%, Lmin=211.79, Lmax=242.86 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2692 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_run.py::test_run_resume[0.1]

23.76

[gw5] linux -- Python 3.10.6 /usr/bin/python3
[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.23) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1226.65..3.68 [-1226.6504..-307.9035] | it/evals=0/528 eff=0.0000% N=400 Z=-951.8(0.00%) | Like=-945.36..3.68 [-1226.6504..-307.9035] | it/evals=50/528 eff=39.0625% N=400 Mono-modal Volume: ~exp(-4.49) * Expected Volume: exp(-0.23) Quality: ok a: +0.0| ********************************************** | +1.0 Z=-786.4(0.00%) | Like=-779.24..3.68 [-1226.6504..-307.9035] | it/evals=90/528 eff=70.3125% N=400 Z=-746.9(0.00%) | Like=-740.63..3.68 [-1226.6504..-307.9035] | it/evals=100/528 eff=78.1250% N=400 Z=-725.7(0.00%) | Like=-717.99..3.68 [-1226.6504..-307.9035] | it/evals=107/629 eff=46.7249% N=400 Z=-573.3(0.00%) | Like=-561.83..3.69 [-1226.6504..-307.9035] | it/evals=150/629 eff=65.5022% N=400 Have 2 modes Volume: ~exp(-4.72) * Expected Volume: exp(-0.45) Quality: ok a: +0.0| 222222111111111111111111111111111111 +0.8 | +1.0 Z=-499.7(0.00%) | Like=-493.61..3.69 [-1226.6504..-307.9035] | it/evals=180/629 eff=78.6026% N=400 Z=-463.6(0.00%) | Like=-456.60..3.69 [-1226.6504..-307.9035] | it/evals=200/717 eff=63.0915% N=400 Z=-374.7(0.00%) | Like=-364.11..3.69 [-1226.6504..-307.9035] | it/evals=250/717 eff=78.8644% N=400 Have 2 modes Volume: ~exp(-4.91) * Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.2 222111111111111111111111111111 +0.8 | +1.0 Z=-327.4(0.00%) | Like=-320.54..3.69 [-1226.6504..-307.9035] | it/evals=270/783 eff=70.4961% N=400 Z=-278.7(0.00%) | Like=-269.85..3.69 [-307.6123..-69.3248] | it/evals=300/783 eff=78.3290% N=400 Z=-208.4(0.00%) | Like=-201.38..3.69 [-307.6123..-69.3248] | it/evals=350/842 eff=79.1855% N=400 Mono-modal Volume: ~exp(-5.13) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-201.8(0.00%) | Like=-195.89..3.69 [-307.6123..-69.3248] | it/evals=360/842 eff=81.4480% N=400 Z=-168.6(0.00%) | Like=-162.35..3.69 [-307.6123..-69.3248] | it/evals=400/890 eff=81.6327% N=400 Mono-modal Volume: ~exp(-5.45) * Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 ****************** +0.7 | +1.0 Z=-127.9(0.00%) | Like=-120.12..3.69 [-307.6123..-69.3248] | it/evals=450/938 eff=83.6431% N=400 Z=-102.3(0.00%) | Like=-95.31..3.69 [-307.6123..-69.3248] | it/evals=500/983 eff=85.7633% N=400 Mono-modal Volume: ~exp(-5.45) Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 *************** +0.6 | +1.0 Z=-81.9(0.00%) | Like=-75.87..3.69 [-307.6123..-69.3248] | it/evals=540/1015 eff=87.8049% N=400 Z=-76.3(0.00%) | Like=-67.48..3.69 [-67.4783..-14.2446] | it/evals=550/1045 eff=85.2713% N=400 Z=-61.9(0.00%) | Like=-54.84..3.69 [-67.4783..-14.2446] | it/evals=594/1097 eff=85.2224% N=400 Z=-59.7(0.00%) | Like=-53.11..3.69 [-67.4783..-14.2446] | it/evals=600/1097 eff=86.0832% N=400 Mono-modal Volume: ~exp(-5.73) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-50.8(0.00%) | Like=-44.90..3.69 [-67.4783..-14.2446] | it/evals=630/1119 eff=87.6217% N=400 Z=-46.9(0.00%) | Like=-40.98..3.69 [-67.4783..-14.2446] | it/evals=650/1149 eff=86.7824% N=400 Z=-37.7(0.00%) | Like=-31.30..3.69 [-67.4783..-14.2446] | it/evals=692/1202 eff=86.2843% N=400 Z=-36.3(0.00%) | Like=-30.34..3.69 [-67.4783..-14.2446] | it/evals=700/1202 eff=87.2818% N=400 Have 2 modes Volume: ~exp(-5.93) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 1111111111 +0.6 | +1.0 Z=-33.3(0.00%) | Like=-27.63..3.69 [-67.4783..-14.2446] | it/evals=720/1220 eff=87.8049% N=400 Z=-28.5(0.00%) | Like=-22.72..3.69 [-67.4783..-14.2446] | it/evals=750/1241 eff=89.1795% N=400 Z=-22.7(0.00%) | Like=-17.23..3.69 [-67.4783..-14.2446] | it/evals=800/1304 eff=88.4956% N=400 Mono-modal Volume: ~exp(-5.99) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-21.8(0.00%) | Like=-15.95..3.69 [-67.4783..-14.2446] | it/evals=810/1321 eff=87.9479% N=400 Z=-18.2(0.00%) | Like=-12.48..3.69 [-14.1709..-1.0696] | it/evals=850/1358 eff=88.7265% N=400 Z=-14.8(0.00%) | Like=-9.25..3.69 [-14.1709..-1.0696] | it/evals=899/1408 eff=89.1865% N=400 Mono-modal Volume: ~exp(-6.39) * Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ****** +0.6 | +1.0 Z=-14.7(0.00%) | Like=-9.22..3.69 [-14.1709..-1.0696] | it/evals=900/1408 eff=89.2857% N=400 Z=-12.3(0.00%) | Like=-6.68..3.69 [-14.1709..-1.0696] | it/evals=943/1454 eff=89.4687% N=400 Z=-11.8(0.00%) | Like=-6.10..3.69 [-14.1709..-1.0696] | it/evals=950/1454 eff=90.1328% N=400 Mono-modal Volume: ~exp(-6.42) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-10.0(0.00%) | Like=-4.75..3.69 [-14.1709..-1.0696] | it/evals=990/1495 eff=90.4110% N=400 Z=-9.6(0.01%) | Like=-4.29..3.69 [-14.1709..-1.0696] | it/evals=1000/1510 eff=90.0901% N=400 Z=-7.8(0.04%) | Like=-2.56..3.69 [-14.1709..-1.0696] | it/evals=1050/1560 eff=90.5172% N=400 Mono-modal Volume: ~exp(-6.94) * Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.9(0.10%) | Like=-1.64..3.69 [-14.1709..-1.0696] | it/evals=1080/1589 eff=90.8326% N=400 Z=-6.3(0.18%) | Like=-1.10..3.69 [-14.1709..-1.0696] | it/evals=1100/1608 eff=91.0596% N=400 Z=-5.5(0.41%) | Like=-0.43..3.69 [-1.0251..1.4019] | it/evals=1133/1647 eff=90.8581% N=400 Z=-5.1(0.58%) | Like=-0.12..3.69 [-1.0251..1.4019] | it/evals=1150/1662 eff=91.1252% N=400 Mono-modal Volume: ~exp(-6.94) Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-4.7(0.87%) | Like=0.36..3.69 [-1.0251..1.4019] | it/evals=1170/1688 eff=90.8385% N=400 Z=-4.1(1.56%) | Like=0.95..3.69 [-1.0251..1.4019] | it/evals=1200/1714 eff=91.3242% N=400 Z=-3.4(3.05%) | Like=1.50..3.69 [1.4141..1.7303] | it/evals=1240/1753 eff=91.6482% N=400 Z=-3.3(3.55%) | Like=1.65..3.69 [1.4141..1.7303] | it/evals=1250/1768 eff=91.3743% N=400 Mono-modal Volume: ~exp(-7.60) * Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.1(4.13%) | Like=1.78..3.69 [1.7755..1.7957] | it/evals=1260/1785 eff=90.9747% N=400 Z=-2.7(6.23%) | Like=2.01..3.69 [2.0136..2.0168]*| it/evals=1293/1817 eff=91.2491% N=400 Z=-2.6(6.75%) | Like=2.07..3.69 [2.0671..2.0678]*| it/evals=1300/1820 eff=91.5493% N=400 Z=-2.4(8.84%) | Like=2.21..3.69 [2.1969..2.2100] | it/evals=1328/1851 eff=91.5231% N=400 Mono-modal Volume: ~exp(-7.60) Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.2(10.66%) | Like=2.32..3.69 [2.3213..2.3252]*| it/evals=1350/1878 eff=91.3396% N=400 Z=-2.0(13.43%) | Like=2.52..3.69 [2.5109..2.5211] | it/evals=1382/1910 eff=91.5232% N=400 Z=-1.8(15.17%) | Like=2.60..3.69 [2.5988..2.6022]*| it/evals=1400/1928 eff=91.6230% N=400 Mono-modal Volume: ~exp(-7.81) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.27%) | Like=2.78..3.69 [2.7802..2.7819]*| it/evals=1440/1969 eff=91.7782% N=400 Z=-1.5(20.35%) | Like=2.83..3.69 [2.8275..2.8304]*| it/evals=1450/1978 eff=91.8885% N=400 Z=-1.3(25.82%) | Like=3.03..3.69 [3.0320..3.0340]*| it/evals=1499/2029 eff=92.0196% N=400 Z=-1.3(25.93%) | Like=3.03..3.69 [3.0340..3.0340]*| it/evals=1500/2029 eff=92.0810% N=400 Mono-modal Volume: ~exp(-8.19) * Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(29.56%) | Like=3.15..3.69 [3.1450..3.1456]*| it/evals=1530/2062 eff=92.0578% N=400 Z=-1.1(31.96%) | Like=3.20..3.69 [3.2018..3.2042]*| it/evals=1550/2080 eff=92.2619% N=400 Z=-1.0(35.28%) | Like=3.26..3.69 [3.2569..3.2604]*| it/evals=1577/2219 eff=86.6960% N=400 Z=-0.9(38.04%) | Like=3.31..3.69 [3.3108..3.3130]*| it/evals=1600/2219 eff=87.9604% N=400 Mono-modal Volume: ~exp(-8.23) * Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(40.40%) | Like=3.34..3.69 [3.3439..3.3448]*| it/evals=1620/2219 eff=89.0599% N=400 Z=-0.8(43.85%) | Like=3.40..3.69 [3.3956..3.3965]*| it/evals=1650/2219 eff=90.7092% N=400 Z=-0.7(47.86%) | Like=3.44..3.69 [3.4382..3.4385]*| it/evals=1685/2336 eff=87.0351% N=400 Z=-0.7(49.50%) | Like=3.45..3.69 [3.4511..3.4523]*| it/evals=1700/2336 eff=87.8099% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(50.57%) | Like=3.46..3.69 [3.4593..3.4621]*| it/evals=1710/2336 eff=88.3264% N=400 Z=-0.6(54.69%) | Like=3.50..3.69 [3.5027..3.5030]*| it/evals=1750/2336 eff=90.3926% N=400 Z=-0.5(57.91%) | Like=3.53..3.69 [3.5284..3.5286]*| it/evals=1783/2439 eff=87.4448% N=400 Mono-modal Volume: ~exp(-8.57) * Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.50%) | Like=3.54..3.69 [3.5412..3.5415]*| it/evals=1800/2439 eff=88.2786% N=400 Z=-0.4(63.91%) | Like=3.57..3.69 [3.5739..3.5746]*| it/evals=1850/2439 eff=90.7308% N=400 Mono-modal Volume: ~exp(-8.57) Expected Volume: exp(-4.73) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(67.80%) | Like=3.60..3.69 [3.5966..3.5972]*| it/evals=1899/2479 eff=91.3420% N=400 Z=-0.3(67.87%) | Like=3.60..3.69 [3.5972..3.5973]*| it/evals=1900/2479 eff=91.3901% N=400 Z=-0.3(71.47%) | Like=3.62..3.69 [3.6209..3.6212]*| it/evals=1950/2531 eff=91.5063% N=400 Mono-modal Volume: ~exp(-9.06) * Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(73.46%) | Like=3.63..3.69 [3.6274..3.6276]*| it/evals=1980/2559 eff=91.7091% N=400 Z=-0.2(74.71%) | Like=3.63..3.69 [3.6330..3.6334]*| it/evals=2000/2586 eff=91.4913% N=400 Z=-0.2(77.60%) | Like=3.65..3.69 [3.6475..3.6477]*| it/evals=2050/2641 eff=91.4770% N=400 Mono-modal Volume: ~exp(-9.50) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(78.67%) | Like=3.65..3.69 [3.6506..3.6507]*| it/evals=2070/2655 eff=91.7960% N=400 Z=-0.2(80.17%) | Like=3.66..3.69 [3.6553..3.6553]*| it/evals=2100/2687 eff=91.8233% N=400 Z=-0.2(81.80%) | Like=3.66..3.69 [3.6603..3.6604]*| it/evals=2135/2729 eff=91.6702% N=400 Z=-0.1(82.46%) | Like=3.66..3.69 [3.6619..3.6620]*| it/evals=2150/2739 eff=91.9196% N=400 Mono-modal Volume: ~exp(-9.50) Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(84.49%) | Like=3.67..3.69 [3.6671..3.6671]*| it/evals=2200/2790 eff=92.0502% N=400 Have 2 modes Volume: ~exp(-9.64) * Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 21 +0.502 | +1.000 Z=-0.1(86.30%) | Like=3.67..3.69 [3.6702..3.6703]*| it/evals=2250/2849 eff=91.8742% N=400 Z=-0.1(87.89%) | Like=3.67..3.69 [3.6740..3.6740]*| it/evals=2300/2965 eff=89.6686% N=400 Mono-modal Volume: ~exp(-10.03) * Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.04%) | Like=3.68..3.69 [3.6757..3.6757]*| it/evals=2340/2965 eff=91.2281% N=400 Z=-0.1(89.31%) | Like=3.68..3.69 [3.6761..3.6761]*| it/evals=2350/2965 eff=91.6179% N=400 Z=-0.1(90.56%) | Like=3.68..3.69 [3.6781..3.6781]*| it/evals=2400/3088 eff=89.2857% N=400 Mono-modal Volume: ~exp(-10.26) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.23%) | Like=3.68..3.69 [3.6794..3.6795]*| it/evals=2430/3088 eff=90.4018% N=400 Z=-0.0(91.66%) | Like=3.68..3.69 [3.6800..3.6801]*| it/evals=2450/3088 eff=91.1458% N=400 Z=-0.0(92.64%) | Like=3.68..3.69 [3.6811..3.6812]*| it/evals=2500/3207 eff=89.0631% N=400 Mono-modal Volume: ~exp(-10.26) Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(93.50%) | Like=3.68..3.69 [3.6822..3.6822]*| it/evals=2550/3207 eff=90.8443% N=400 Z=-0.0(94.26%) | Like=3.68..3.69 [3.6832..3.6832]*| it/evals=2600/3311 eff=89.3164% N=400 Mono-modal Volume: ~exp(-10.31) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.40%) | Like=3.68..3.69 [3.6833..3.6833]*| it/evals=2610/3311 eff=89.6599% N=400 Z=-0.0(94.93%) | Like=3.68..3.69 [3.6836..3.6836]*| it/evals=2650/3311 eff=91.0340% N=400 Z=-0.0(95.39%) | Like=3.68..3.69 [3.6841..3.6841]*| it/evals=2688/3359 eff=90.8415% N=400 Mono-modal Volume: ~exp(-10.83) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(95.53%) | Like=3.68..3.69 [3.6842..3.6842]*| it/evals=2700/3372 eff=90.8479% N=400 Z=-0.0(95.61%) | Like=3.68..3.69 [3.6842..3.6842]*| it/evals=2707/3486 eff=87.7187% N=400 Z=0.0(96.05%) | Like=3.68..3.69 [3.6846..3.6846]*| it/evals=2750/3486 eff=89.1121% N=400 Mono-modal Volume: ~exp(-10.98) * Expected Volume: exp(-6.98) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=0.0(96.43%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2790/3486 eff=90.4083% N=400 Z=0.0(96.52%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2800/3486 eff=90.7323% N=400 Z=0.0(96.93%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2850/3537 eff=90.8511% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3551 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.04562 +- 0.06643 [ultranest] Effective samples strategy satisfied (ESS = 1262.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 572 minimum live points (dlogz from 0.05 to 0.16, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 [ultranest] Widening roots to 572 live points (have 400 already) ... [ultranest] Sampling 172 live points from prior ... Mono-modal Volume: ~exp(-4.63) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1233.27..3.69 [-1233.2658..-318.2188] | it/evals=0/3851 eff=0.0000% N=572 Z=-899.8(0.00%) | Like=-891.00..3.69 [-1233.2658..-318.2188] | it/evals=93/3851 eff=25.7812% N=572 Mono-modal Volume: ~exp(-4.66) * Expected Volume: exp(-0.22) Quality: ok a: +0.00| ********************************************** | +1.00 Z=-813.2(0.00%) | Like=-806.92..3.69 [-1233.2658..-318.2188] | it/evals=128/3851 eff=33.5938% N=572 Z=-623.8(0.00%) | Like=-616.62..3.69 [-1233.2658..-318.2188] | it/evals=200/3851 eff=53.1250% N=572 Mono-modal Volume: ~exp(-4.77) * Expected Volume: exp(-0.46) Quality: ok a: +0.0| ************************************ +0.8 | +1.0 Z=-511.7(0.00%) | Like=-503.81..3.69 [-1233.2658..-318.2188] | it/evals=264/3851 eff=67.9688% N=572 Z=-365.3(0.00%) | Like=-354.29..3.69 [-1233.2658..-318.2188] | it/evals=367/3925 eff=55.4455% N=572 Mono-modal Volume: ~exp(-5.12) * Expected Volume: exp(-0.69) Quality: ok a: +0.0| +0.2 ****************************** +0.8 | +1.0 Z=-325.4(0.00%) | Like=-318.31..3.69 [-1233.2658..-318.2188] | it/evals=392/3925 eff=59.4059% N=572 Z=-265.5(0.00%) | Like=-258.66..3.69 [-318.1270..-72.8697] | it/evals=450/3925 eff=69.3069% N=572 Mono-modal Volume: ~exp(-5.23) * Expected Volume: exp(-0.91) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-203.2(0.00%) | Like=-196.97..3.69 [-318.1270..-72.8697] | it/evals=521/3987 eff=62.1212% N=572 Z=-188.1(0.00%) | Like=-181.88..3.69 [-318.1270..-72.8697] | it/evals=550/3987 eff=63.2576% N=572 Mono-modal Volume: ~exp(-5.66) * Expected Volume: exp(-1.14) Quality: ok a: +0.0| +0.3 ****************** +0.7 | +1.0 Z=-126.4(0.00%) | Like=-119.36..3.69 [-318.1270..-72.8697] | it/evals=651/4041 eff=62.5786% N=572 Z=-85.8(0.00%) | Like=-78.37..3.69 [-318.1270..-72.8697] | it/evals=764/4081 eff=65.3631% N=572 Mono-modal Volume: ~exp(-5.90) * Expected Volume: exp(-1.37) Quality: ok a: +0.0| +0.4 *************** +0.6 | +1.0 Z=-81.5(0.00%) | Like=-74.83..3.69 [-318.1270..-72.8697] | it/evals=783/4081 eff=67.3184% N=572 Z=-63.9(0.00%) | Like=-57.76..3.69 [-72.7839..-14.8005] | it/evals=850/4112 eff=67.6093% N=572 Mono-modal Volume: ~exp(-6.11) * Expected Volume: exp(-1.60) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-49.8(0.00%) | Like=-43.68..3.69 [-72.7839..-14.8005] | it/evals=914/4112 eff=71.2082% N=572 Z=-34.6(0.00%) | Like=-28.39..3.69 [-72.7839..-14.8005] | it/evals=1031/4159 eff=72.9358% N=572 Mono-modal Volume: ~exp(-6.17) * Expected Volume: exp(-1.82) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 Z=-33.2(0.00%) | Like=-27.07..3.69 [-72.7839..-14.8005] | it/evals=1043/4159 eff=73.6239% N=572 Z=-27.4(0.00%) | Like=-21.42..3.69 [-72.7839..-14.8005] | it/evals=1100/4189 eff=73.1760% N=572 Mono-modal Volume: ~exp(-6.32) * Expected Volume: exp(-2.05) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-21.6(0.00%) | Like=-15.84..3.69 [-72.7839..-14.8005] | it/evals=1173/4209 eff=74.2798% N=572 Z=-19.8(0.00%) | Like=-13.99..3.69 [-14.7621..-1.1236] | it/evals=1200/4223 eff=73.8000% N=572 Mono-modal Volume: ~exp(-6.95) * Expected Volume: exp(-2.28) Quality: ok a: +0.0| +0.5 ****** +0.6 | +1.0 Z=-14.2(0.00%) | Like=-8.82..3.69 [-14.7621..-1.1236] | it/evals=1302/4238 eff=76.1165% N=572 Z=-9.9(0.00%) | Like=-4.80..3.69 [-14.7621..-1.1236] | it/evals=1419/4282 eff=76.9231% N=572 Mono-modal Volume: ~exp(-6.95) Expected Volume: exp(-2.50) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-8.0(0.03%) | Like=-2.75..3.69 [-14.7621..-1.1236] | it/evals=1500/4317 eff=76.5993% N=572 Mono-modal Volume: ~exp(-7.44) * Expected Volume: exp(-2.73) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.6(0.13%) | Like=-1.36..3.69 [-14.7621..-1.1236] | it/evals=1561/4348 eff=75.6800% N=572 Z=-5.0(0.62%) | Like=0.04..3.69 [-1.1141..1.0398] | it/evals=1650/4367 eff=76.5528% N=572 Mono-modal Volume: ~exp(-7.44) Expected Volume: exp(-2.95) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-4.4(1.12%) | Like=0.60..3.69 [-1.1141..1.0398] | it/evals=1689/4389 eff=75.6757% N=572 Z=-3.7(2.42%) | Like=1.27..3.69 [1.0412..1.3033] | it/evals=1750/4416 eff=75.4690% N=572 Z=-3.1(4.09%) | Like=1.72..3.69 [1.6978..1.7207] | it/evals=1800/4451 eff=75.0000% N=572 Mono-modal Volume: ~exp(-7.44) Expected Volume: exp(-3.18) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-2.8(5.71%) | Like=1.95..3.69 [1.9514..1.9675] | it/evals=1837/4459 eff=75.2717% N=572 Mono-modal Volume: ~exp(-8.13) * Expected Volume: exp(-3.41) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.1(11.75%) | Like=2.39..3.69 [2.3870..2.3880]*| it/evals=1948/4503 eff=74.3590% N=572 Z=-2.1(11.89%) | Like=2.39..3.69 [2.3894..2.3901]*| it/evals=1950/4503 eff=74.6154% N=572 Z=-1.8(15.35%) | Like=2.60..3.69 [2.5990..2.6022]*| it/evals=2003/4524 eff=75.1561% N=572 Mono-modal Volume: ~exp(-8.13) Expected Volume: exp(-3.64) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.5(21.10%) | Like=2.86..3.69 [2.8617..2.8623]*| it/evals=2082/4550 eff=75.2116% N=572 Z=-1.1(30.76%) | Like=3.15..3.69 [3.1517..3.1525]*| it/evals=2201/4618 eff=74.5251% N=572 Mono-modal Volume: ~exp(-8.47) * Expected Volume: exp(-3.86) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.1(31.51%) | Like=3.18..3.69 [3.1755..3.1764]*| it/evals=2210/4618 eff=74.7486% N=572 Z=-1.0(33.58%) | Like=3.21..3.69 [3.2093..3.2105]*| it/evals=2235/4756 eff=65.8277% N=572 Mono-modal Volume: ~exp(-8.47) Expected Volume: exp(-4.09) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.8(42.09%) | Like=3.36..3.69 [3.3631..3.3633]*| it/evals=2338/4756 eff=68.3446% N=572 Z=-0.8(43.08%) | Like=3.38..3.69 [3.3774..3.3790]*| it/evals=2350/4756 eff=68.9255% N=572 Z=-0.6(50.85%) | Like=3.46..3.69 [3.4635..3.4638]*| it/evals=2450/4756 eff=71.4424% N=572 Mono-modal Volume: ~exp(-8.88) * Expected Volume: exp(-4.31) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(52.11%) | Like=3.48..3.69 [3.4765..3.4765]*| it/evals=2467/4756 eff=71.9264% N=572 Z=-0.5(60.59%) | Like=3.55..3.69 [3.5495..3.5499]*| it/evals=2592/4778 eff=74.0284% N=572 Mono-modal Volume: ~exp(-9.09) * Expected Volume: exp(-4.54) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(60.97%) | Like=3.55..3.69 [3.5520..3.5533]*| it/evals=2598/4778 eff=74.1232% N=572 Z=-0.5(61.10%) | Like=3.55..3.69 [3.5539..3.5550]*| it/evals=2600/4778 eff=74.2180% N=572 Z=-0.4(63.84%) | Like=3.57..3.69 [3.5736..3.5736]*| it/evals=2645/4911 eff=67.0034% N=572 Mono-modal Volume: ~exp(-9.41) * Expected Volume: exp(-4.77) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(68.32%) | Like=3.60..3.69 [3.5992..3.5993]*| it/evals=2726/4911 eff=69.1077% N=572 Z=-0.3(74.24%) | Like=3.63..3.69 [3.6292..3.6295]*| it/evals=2850/4911 eff=72.7273% N=572 Mono-modal Volume: ~exp(-9.41) Expected Volume: exp(-4.99) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(76.33%) | Like=3.64..3.69 [3.6408..3.6409]*| it/evals=2900/4911 eff=73.9057% N=572 Z=-0.2(78.26%) | Like=3.65..3.69 [3.6484..3.6485]*| it/evals=2950/4936 eff=73.7840% N=572 Mono-modal Volume: ~exp(-9.50) * Expected Volume: exp(-5.22) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(79.52%) | Like=3.65..3.69 [3.6519..3.6521]*| it/evals=2985/4952 eff=73.3930% N=572 Z=-0.2(80.45%) | Like=3.66..3.69 [3.6554..3.6554]*| it/evals=3012/5079 eff=67.1091% N=572 Mono-modal Volume: ~exp(-9.95) * Expected Volume: exp(-5.44) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(83.59%) | Like=3.66..3.69 [3.6638..3.6638]*| it/evals=3114/5079 eff=69.8378% N=572 Z=-0.1(85.07%) | Like=3.67..3.69 [3.6672..3.6672]*| it/evals=3169/5079 eff=71.2389% N=572 Mono-modal Volume: ~exp(-9.95) Expected Volume: exp(-5.67) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.84%) | Like=3.67..3.69 [3.6704..3.6704]*| it/evals=3242/5079 eff=72.8614% N=572 Z=-0.1(89.09%) | Like=3.68..3.69 [3.6751..3.6751]*| it/evals=3350/5113 eff=73.4532% N=572 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-5.90) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.59%) | Like=3.68..3.69 [3.6759..3.6760]*| it/evals=3377/5124 eff=73.5189% N=572 Z=-0.1(90.83%) | Like=3.68..3.69 [3.6780..3.6781]*| it/evals=3450/5253 eff=68.6275% N=572 Z=-0.0(91.59%) | Like=3.68..3.69 [3.6796..3.6796]*| it/evals=3500/5253 eff=69.8039% N=572 Have 2 modes Volume: ~exp(-10.52) * Expected Volume: exp(-6.13) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=-0.0(91.71%) | Like=3.68..3.69 [3.6798..3.6798]*| it/evals=3508/5253 eff=69.9346% N=572 Z=-0.0(92.94%) | Like=3.68..3.69 [3.6812..3.6812]*| it/evals=3600/5253 eff=71.6340% N=572 Have 2 modes Volume: ~exp(-10.82) * Expected Volume: exp(-6.36) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=-0.0(93.37%) | Like=3.68..3.69 [3.6818..3.6818]*| it/evals=3636/5253 eff=72.6144% N=572 Mono-modal Volume: ~exp(-10.97) * Expected Volume: exp(-6.58) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.69%) | Like=3.68..3.69 [3.6833..3.6834]*| it/evals=3764/5272 eff=73.9832% N=572 Z=-0.0(94.70%) | Like=3.68..3.69 [3.6834..3.6834]*| it/evals=3765/5391 eff=68.7650% N=572 Z=-0.0(95.02%) | Like=3.68..3.69 [3.6836..3.6836]*| it/evals=3800/5391 eff=69.0048% N=572 Z=-0.0(95.43%) | Like=3.68..3.69 [3.6840..3.6840]*| it/evals=3850/5391 eff=69.7242% N=572 Mono-modal Volume: ~exp(-11.17) * Expected Volume: exp(-6.81) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(95.76%) | Like=3.68..3.69 [3.6843..3.6843]*| it/evals=3893/5391 eff=70.5036% N=572 Z=0.0(96.16%) | Like=3.68..3.69 [3.6846..3.6847]*| it/evals=3950/5391 eff=71.5228% N=572 Z=0.0(96.49%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=4000/5391 eff=72.1823% N=572 Mono-modal Volume: ~exp(-11.26) * Expected Volume: exp(-7.05) Quality: ok a: +0.0000| +0.4995 ** +0.5005 | +1.0000 Z=0.0(96.68%) | Like=3.69..3.69 [3.6850..3.6850]*| it/evals=4032/5391 eff=72.6619% N=572 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 5391 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.04684 +- 0.05136 [ultranest] Effective samples strategy satisfied (ESS = 1807.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 570 minimum live points (dlogz from 0.04 to 0.18, need <0.1) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.03 total:0.06 required:<0.10 [ultranest] done iterating. logZ = 0.041 +- 0.181 single instance: logZ = 0.041 +- 0.074 bootstrapped : logZ = 0.047 +- 0.178 tail : logZ = +- 0.030 insert order U test : converged: True correlation: inf iterations a : 0.459 │ ▁ ▁▁▁▁▁▁▁▁▂▃▄▄▅▆▇▇▇▇▇▆▅▅▄▃▃▃▁▁▁▁▁▁▁▁▁ │0.539 0.500 +- 0.010 [ultranest] Resuming from 5048 stored points Mono-modal Volume: ~exp(-4.31) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1226.65..3.68 [-1226.6504..-307.9035] | it/evals=0/5391 eff=inf% N=400 Z=-951.8(0.00%) | Like=-945.36..3.68 [-1226.6504..-307.9035] | it/evals=50/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-4.41) * Expected Volume: exp(-0.23) Quality: ok a: +0.0| ********************************************** | +1.0 Z=-786.4(0.00%) | Like=-779.24..3.68 [-1226.6504..-307.9035] | it/evals=90/5391 eff=inf% N=400 Z=-746.9(0.00%) | Like=-740.63..3.68 [-1226.6504..-307.9035] | it/evals=100/5391 eff=inf% N=400 Z=-573.3(0.00%) | Like=-561.83..3.69 [-1226.6504..-307.9035] | it/evals=150/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-4.64) * Expected Volume: exp(-0.45) Quality: ok a: +0.0| 222222111111111111111111111111111111 +0.8 | +1.0 Z=-499.7(0.00%) | Like=-493.61..3.69 [-1226.6504..-307.9035] | it/evals=180/5391 eff=inf% N=400 Z=-463.6(0.00%) | Like=-456.60..3.69 [-1226.6504..-307.9035] | it/evals=200/5391 eff=inf% N=400 Z=-374.7(0.00%) | Like=-364.11..3.69 [-1226.6504..-307.9035] | it/evals=250/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-4.64) Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.2 222111111111111111111111111111 +0.8 | +1.0 Z=-278.7(0.00%) | Like=-269.85..3.69 [-307.6123..-69.3248] | it/evals=300/5391 eff=inf% N=400 Z=-208.4(0.00%) | Like=-201.38..3.69 [-307.6123..-69.3248] | it/evals=350/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-4.82) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-201.8(0.00%) | Like=-195.89..3.69 [-307.6123..-69.3248] | it/evals=360/5391 eff=inf% N=400 Z=-168.6(0.00%) | Like=-162.35..3.69 [-307.6123..-69.3248] | it/evals=400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.28) * Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 ****************** +0.7 | +1.0 Z=-127.9(0.00%) | Like=-120.12..3.69 [-307.6123..-69.3248] | it/evals=450/5391 eff=inf% N=400 Z=-102.3(0.00%) | Like=-95.31..3.69 [-307.6123..-69.3248] | it/evals=500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.28) Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 *************** +0.6 | +1.0 Z=-76.3(0.00%) | Like=-67.48..3.69 [-67.4783..-14.2446] | it/evals=550/5391 eff=inf% N=400 Z=-59.7(0.00%) | Like=-53.11..3.69 [-67.4783..-14.2446] | it/evals=600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-5.89) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-50.8(0.00%) | Like=-44.90..3.69 [-67.4783..-14.2446] | it/evals=630/5391 eff=inf% N=400 Z=-46.9(0.00%) | Like=-40.98..3.69 [-67.4783..-14.2446] | it/evals=650/5391 eff=inf% N=400 Z=-36.3(0.00%) | Like=-30.34..3.69 [-67.4783..-14.2446] | it/evals=700/5391 eff=inf% N=400 Have 2 modes Volume: ~exp(-6.17) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 1111111111 +0.6 | +1.0 Z=-33.3(0.00%) | Like=-27.63..3.69 [-67.4783..-14.2446] | it/evals=720/5391 eff=inf% N=400 Z=-28.5(0.00%) | Like=-22.72..3.69 [-67.4783..-14.2446] | it/evals=750/5391 eff=inf% N=400 Z=-22.7(0.00%) | Like=-17.23..3.69 [-67.4783..-14.2446] | it/evals=800/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.29) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-21.8(0.00%) | Like=-15.95..3.69 [-67.4783..-14.2446] | it/evals=810/5391 eff=inf% N=400 Z=-18.2(0.00%) | Like=-12.48..3.69 [-14.1709..-1.0696] | it/evals=850/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.40) * Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ****** +0.6 | +1.0 Z=-14.7(0.00%) | Like=-9.22..3.69 [-14.1709..-1.0696] | it/evals=900/5391 eff=inf% N=400 Z=-11.8(0.00%) | Like=-6.10..3.69 [-14.1709..-1.0696] | it/evals=950/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.75) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-10.0(0.00%) | Like=-4.75..3.69 [-14.1709..-1.0696] | it/evals=990/5391 eff=inf% N=400 Z=-9.6(0.01%) | Like=-4.29..3.69 [-14.1709..-1.0696] | it/evals=1000/5391 eff=inf% N=400 Z=-7.8(0.04%) | Like=-2.56..3.69 [-14.1709..-1.0696] | it/evals=1050/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-6.75) Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.3(0.18%) | Like=-1.10..3.69 [-14.1709..-1.0696] | it/evals=1100/5391 eff=inf% N=400 Z=-5.1(0.58%) | Like=-0.12..3.69 [-1.0251..1.4019] | it/evals=1150/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.01) * Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-4.7(0.87%) | Like=0.36..3.69 [-1.0251..1.4019] | it/evals=1170/5391 eff=inf% N=400 Z=-4.1(1.56%) | Like=0.95..3.69 [-1.0251..1.4019] | it/evals=1200/5391 eff=inf% N=400 Z=-3.3(3.55%) | Like=1.65..3.69 [1.4141..1.7303] | it/evals=1250/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.20) * Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.1(4.13%) | Like=1.78..3.69 [1.7755..1.7957] | it/evals=1260/5391 eff=inf% N=400 Z=-2.6(6.75%) | Like=2.07..3.69 [2.0671..2.0678]*| it/evals=1300/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.70) * Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.2(10.66%) | Like=2.32..3.69 [2.3213..2.3252]*| it/evals=1350/5391 eff=inf% N=400 Z=-1.8(15.17%) | Like=2.60..3.69 [2.5988..2.6022]*| it/evals=1400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.72) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.27%) | Like=2.78..3.69 [2.7802..2.7819]*| it/evals=1440/5391 eff=inf% N=400 Z=-1.5(20.35%) | Like=2.83..3.69 [2.8275..2.8304]*| it/evals=1450/5391 eff=inf% N=400 Z=-1.3(25.93%) | Like=3.03..3.69 [3.0340..3.0340]*| it/evals=1500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-7.95) * Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(29.56%) | Like=3.15..3.69 [3.1450..3.1456]*| it/evals=1530/5391 eff=inf% N=400 Z=-1.1(31.96%) | Like=3.20..3.69 [3.2018..3.2042]*| it/evals=1550/5391 eff=inf% N=400 Z=-0.9(38.04%) | Like=3.31..3.69 [3.3108..3.3130]*| it/evals=1600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.34) * Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(40.40%) | Like=3.34..3.69 [3.3439..3.3448]*| it/evals=1620/5391 eff=inf% N=400 Z=-0.8(43.85%) | Like=3.40..3.69 [3.3956..3.3965]*| it/evals=1650/5391 eff=inf% N=400 Z=-0.7(49.50%) | Like=3.45..3.69 [3.4511..3.4523]*| it/evals=1700/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.56) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(50.57%) | Like=3.46..3.69 [3.4593..3.4621]*| it/evals=1710/5391 eff=inf% N=400 Z=-0.6(54.69%) | Like=3.50..3.69 [3.5027..3.5030]*| it/evals=1750/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.56) Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.50%) | Like=3.54..3.69 [3.5412..3.5415]*| it/evals=1800/5391 eff=inf% N=400 Z=-0.4(63.91%) | Like=3.57..3.69 [3.5739..3.5746]*| it/evals=1850/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-8.58) * Expected Volume: exp(-4.73) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.4(67.12%) | Like=3.59..3.69 [3.5915..3.5916]*| it/evals=1890/5391 eff=inf% N=400 Z=-0.3(67.87%) | Like=3.60..3.69 [3.5972..3.5973]*| it/evals=1900/5391 eff=inf% N=400 Z=-0.3(71.47%) | Like=3.62..3.69 [3.6209..3.6212]*| it/evals=1950/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.02) * Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(73.46%) | Like=3.63..3.69 [3.6274..3.6276]*| it/evals=1980/5391 eff=inf% N=400 Z=-0.2(74.71%) | Like=3.63..3.69 [3.6330..3.6334]*| it/evals=2000/5391 eff=inf% N=400 Z=-0.2(77.60%) | Like=3.65..3.69 [3.6475..3.6477]*| it/evals=2050/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.33) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(78.67%) | Like=3.65..3.69 [3.6506..3.6507]*| it/evals=2070/5391 eff=inf% N=400 Z=-0.2(80.17%) | Like=3.66..3.69 [3.6553..3.6553]*| it/evals=2100/5391 eff=inf% N=400 Z=-0.1(82.46%) | Like=3.66..3.69 [3.6619..3.6620]*| it/evals=2150/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.72) * Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(82.89%) | Like=3.66..3.69 [3.6628..3.6632]*| it/evals=2160/5391 eff=inf% N=400 Z=-0.1(84.49%) | Like=3.67..3.69 [3.6671..3.6671]*| it/evals=2200/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-9.72) Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.30%) | Like=3.67..3.69 [3.6702..3.6703]*| it/evals=2250/5391 eff=inf% N=400 Z=-0.1(87.89%) | Like=3.67..3.69 [3.6740..3.6740]*| it/evals=2300/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.05) * Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.04%) | Like=3.68..3.69 [3.6757..3.6757]*| it/evals=2340/5391 eff=inf% N=400 Z=-0.1(89.31%) | Like=3.68..3.69 [3.6761..3.6761]*| it/evals=2350/5391 eff=inf% N=400 Z=-0.1(90.56%) | Like=3.68..3.69 [3.6781..3.6781]*| it/evals=2400/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.19) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.23%) | Like=3.68..3.69 [3.6794..3.6795]*| it/evals=2430/5391 eff=inf% N=400 Z=-0.0(91.66%) | Like=3.68..3.69 [3.6800..3.6801]*| it/evals=2450/5391 eff=inf% N=400 Z=-0.0(92.64%) | Like=3.68..3.69 [3.6811..3.6812]*| it/evals=2500/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.27) * Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(92.99%) | Like=3.68..3.69 [3.6816..3.6817]*| it/evals=2520/5391 eff=inf% N=400 Z=-0.0(93.50%) | Like=3.68..3.69 [3.6822..3.6822]*| it/evals=2550/5391 eff=inf% N=400 Z=-0.0(94.26%) | Like=3.68..3.69 [3.6832..3.6832]*| it/evals=2600/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.64) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.40%) | Like=3.68..3.69 [3.6833..3.6833]*| it/evals=2610/5391 eff=inf% N=400 Z=-0.0(94.93%) | Like=3.68..3.69 [3.6836..3.6836]*| it/evals=2650/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.82) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(95.53%) | Like=3.68..3.69 [3.6842..3.6842]*| it/evals=2700/5391 eff=inf% N=400 Z=0.0(96.05%) | Like=3.68..3.69 [3.6846..3.6846]*| it/evals=2750/5391 eff=inf% N=400 Mono-modal Volume: ~exp(-10.89) * Expected Volume: exp(-6.98) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=0.0(96.43%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2790/5391 eff=inf% N=400 Z=0.0(96.52%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2800/5391 eff=inf% N=400 Z=0.0(96.93%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2850/5391 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 5391 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.05415 +- 0.07355 [ultranest] Effective samples strategy satisfied (ESS = 1262.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 398 minimum live points (dlogz from 0.05 to 0.28, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.10 [ultranest] done iterating. logZ = 0.043 +- 0.277 single instance: logZ = 0.043 +- 0.089 bootstrapped : logZ = 0.054 +- 0.276 tail : logZ = +- 0.029 insert order U test : converged: True correlation: inf iterations a : 0.459 │ ▁ ▁▁▁▁▁▁▁▁▂▂▃▃▅▅▆▇▇▆▇▅▅▆▃▃▃▃▃▁▁▁▁▁▁▁▁ │0.537 0.500 +- 0.010 ran with dlogz: 0.1 first run gave: {'niter': 4663, 'logz': 0.04097491838788085, 'logzerr': 0.18063136711385278, 'logz_bs': 0.046839054946532954, 'logz_single': 0.04097491838788085, 'logzerr_tail': 0.029540945136971863, 'logzerr_bs': 0.1781993921028741, 'ess': 1807.664188236005, 'H': 3.154130512875934, 'Herr': 0.046845066579135605, 'posterior': {'mean': [0.49970846080869835], 'stdev': [0.01004709239352154], 'median': [0.49935731941479294], 'errlo': [0.4895958650446224], 'errup': [0.5098140852032222], 'information_gain_bits': [3.4619440240408434]}, 'maximum_likelihood': {'logl': 3.686231637806363, 'point': [0.4999982692743935], 'point_untransformed': [0.4999982692743935]}, 'ncall': 5391, 'paramnames': ['a'], 'logzerr_single': 0.07425775503844387, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3261, 'logz': 0.043086985075368095, 'logzerr': 0.2772812105360212, 'logz_bs': 0.05414593490827967, 'logz_single': 0.043086985075368095, 'logzerr_tail': 0.029467881253302547, 'logzerr_bs': 0.27571092414114207, 'ess': 1262.1858737131056, 'H': 3.154512692418824, 'Herr': 0.06253777219135659, 'posterior': {'mean': [0.4997429610264432], 'stdev': [0.010025904571764277], 'median': [0.4993018305586789], 'errlo': [0.490008435684678], 'errup': [0.5097540368099296], 'information_gain_bits': [3.4625603733966566]}, 'maximum_likelihood': {'logl': 3.686231637806363, 'point': [0.4999982692743935], 'point_untransformed': [0.4999982692743935]}, 'ncall': 5391, 'paramnames': ['a'], 'logzerr_single': 0.08880473935014425, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpzqf9taua, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=528, regioncalls=128, ndraw=128, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=528, regioncalls=128, ndraw=128, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=107, ncalls=629, regioncalls=256, ndraw=128, logz=-725.74, remainder_fraction=100.0000%, Lmin=-717.99, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=629, regioncalls=256, ndraw=128, logz=-573.25, remainder_fraction=100.0000%, Lmin=-561.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=629, regioncalls=256, ndraw=128, logz=-499.66, remainder_fraction=100.0000%, Lmin=-493.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=717, regioncalls=384, ndraw=128, logz=-463.56, remainder_fraction=100.0000%, Lmin=-456.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=717, regioncalls=384, ndraw=128, logz=-374.71, remainder_fraction=100.0000%, Lmin=-364.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=783, regioncalls=512, ndraw=128, logz=-327.38, remainder_fraction=100.0000%, Lmin=-320.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=783, regioncalls=512, ndraw=128, logz=-278.70, remainder_fraction=100.0000%, Lmin=-269.85, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=842, regioncalls=640, ndraw=128, logz=-208.44, remainder_fraction=100.0000%, Lmin=-201.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=842, regioncalls=640, ndraw=128, logz=-201.75, remainder_fraction=100.0000%, Lmin=-195.89, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=890, regioncalls=768, ndraw=128, logz=-168.63, remainder_fraction=100.0000%, Lmin=-162.35, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=938, regioncalls=896, ndraw=128, logz=-127.89, remainder_fraction=100.0000%, Lmin=-120.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=983, regioncalls=1024, ndraw=128, logz=-102.29, remainder_fraction=100.0000%, Lmin=-95.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1015, regioncalls=1152, ndraw=128, logz=-81.90, remainder_fraction=100.0000%, Lmin=-75.87, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1045, regioncalls=1280, ndraw=128, logz=-76.26, remainder_fraction=100.0000%, Lmin=-67.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=1097, regioncalls=1536, ndraw=128, logz=-61.88, remainder_fraction=100.0000%, Lmin=-54.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1097, regioncalls=1536, ndraw=128, logz=-59.67, remainder_fraction=100.0000%, Lmin=-53.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1119, regioncalls=1664, ndraw=128, logz=-50.83, remainder_fraction=100.0000%, Lmin=-44.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1149, regioncalls=1792, ndraw=128, logz=-46.91, remainder_fraction=100.0000%, Lmin=-40.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=692, ncalls=1202, regioncalls=2048, ndraw=128, logz=-37.74, remainder_fraction=100.0000%, Lmin=-31.30, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1202, regioncalls=2048, ndraw=128, logz=-36.30, remainder_fraction=100.0000%, Lmin=-30.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1220, regioncalls=2176, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-27.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1241, regioncalls=2304, ndraw=128, logz=-28.46, remainder_fraction=100.0000%, Lmin=-22.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1304, regioncalls=2688, ndraw=128, logz=-22.67, remainder_fraction=100.0000%, Lmin=-17.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1321, regioncalls=2816, ndraw=128, logz=-21.80, remainder_fraction=100.0000%, Lmin=-15.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1358, regioncalls=3072, ndraw=128, logz=-18.22, remainder_fraction=100.0000%, Lmin=-12.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=899, ncalls=1408, regioncalls=3584, ndraw=128, logz=-14.76, remainder_fraction=100.0000%, Lmin=-9.25, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1408, regioncalls=3584, ndraw=128, logz=-14.70, remainder_fraction=100.0000%, Lmin=-9.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1454, regioncalls=4096, ndraw=128, logz=-12.31, remainder_fraction=99.9996%, Lmin=-6.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1454, regioncalls=4096, ndraw=128, logz=-11.83, remainder_fraction=99.9993%, Lmin=-6.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1495, regioncalls=4480, ndraw=128, logz=-9.96, remainder_fraction=99.9955%, Lmin=-4.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1510, regioncalls=4608, ndraw=128, logz=-9.56, remainder_fraction=99.9931%, Lmin=-4.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1560, regioncalls=5248, ndraw=128, logz=-7.83, remainder_fraction=99.9619%, Lmin=-2.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1589, regioncalls=5760, ndraw=128, logz=-6.88, remainder_fraction=99.9019%, Lmin=-1.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1608, regioncalls=6016, ndraw=128, logz=-6.28, remainder_fraction=99.8203%, Lmin=-1.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1133, ncalls=1647, regioncalls=6656, ndraw=128, logz=-5.46, remainder_fraction=99.5937%, Lmin=-0.43, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1662, regioncalls=6912, ndraw=128, logz=-5.10, remainder_fraction=99.4200%, Lmin=-0.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1688, regioncalls=7424, ndraw=128, logz=-4.69, remainder_fraction=99.1264%, Lmin=0.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1714, regioncalls=7936, ndraw=128, logz=-4.10, remainder_fraction=98.4353%, Lmin=0.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1753, regioncalls=8704, ndraw=128, logz=-3.43, remainder_fraction=96.9477%, Lmin=1.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1768, regioncalls=9088, ndraw=128, logz=-3.28, remainder_fraction=96.4486%, Lmin=1.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1785, regioncalls=9344, ndraw=128, logz=-3.13, remainder_fraction=95.8667%, Lmin=1.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1293, ncalls=1817, regioncalls=10112, ndraw=128, logz=-2.71, remainder_fraction=93.7658%, Lmin=2.01, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1820, regioncalls=10240, ndraw=128, logz=-2.63, remainder_fraction=93.2522%, Lmin=2.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1328, ncalls=1851, regioncalls=10880, ndraw=128, logz=-2.36, remainder_fraction=91.1578%, Lmin=2.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1878, regioncalls=11776, ndraw=128, logz=-2.18, remainder_fraction=89.3449%, Lmin=2.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1382, ncalls=1910, regioncalls=12800, ndraw=128, logz=-1.95, remainder_fraction=86.5669%, Lmin=2.52, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1928, regioncalls=13312, ndraw=128, logz=-1.83, remainder_fraction=84.8291%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1969, regioncalls=14464, ndraw=128, logz=-1.60, remainder_fraction=80.7292%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1978, regioncalls=14720, ndraw=128, logz=-1.54, remainder_fraction=79.6520%, Lmin=2.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1499, ncalls=2029, regioncalls=16640, ndraw=128, logz=-1.31, remainder_fraction=74.1831%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2029, regioncalls=16640, ndraw=128, logz=-1.30, remainder_fraction=74.0684%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2062, regioncalls=17408, ndraw=128, logz=-1.18, remainder_fraction=70.4449%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2080, regioncalls=18048, ndraw=128, logz=-1.10, remainder_fraction=68.0352%, Lmin=3.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1577, ncalls=2219, regioncalls=19456, ndraw=128, logz=-1.00, remainder_fraction=64.7182%, Lmin=3.26, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.92, remainder_fraction=61.9581%, Lmin=3.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.86, remainder_fraction=59.5960%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2219, regioncalls=19456, ndraw=128, logz=-0.78, remainder_fraction=56.1467%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1685, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.69, remainder_fraction=52.1398%, Lmin=3.44, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.66, remainder_fraction=50.5050%, Lmin=3.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.64, remainder_fraction=49.4302%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2336, regioncalls=20352, ndraw=128, logz=-0.56, remainder_fraction=45.3100%, Lmin=3.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1783, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.50, remainder_fraction=42.0902%, Lmin=3.53, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.48, remainder_fraction=40.5034%, Lmin=3.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2439, regioncalls=20736, ndraw=128, logz=-0.40, remainder_fraction=36.0867%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1899, ncalls=2479, regioncalls=21632, ndraw=128, logz=-0.35, remainder_fraction=32.2019%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2479, regioncalls=21632, ndraw=128, logz=-0.34, remainder_fraction=32.1257%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2531, regioncalls=22528, ndraw=128, logz=-0.29, remainder_fraction=28.5291%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2559, regioncalls=23296, ndraw=128, logz=-0.27, remainder_fraction=26.5391%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2586, regioncalls=24448, ndraw=128, logz=-0.25, remainder_fraction=25.2935%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=2641, regioncalls=25344, ndraw=128, logz=-0.21, remainder_fraction=22.4028%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2655, regioncalls=25600, ndraw=128, logz=-0.20, remainder_fraction=21.3341%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=2687, regioncalls=26112, ndraw=128, logz=-0.18, remainder_fraction=19.8255%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2135, ncalls=2729, regioncalls=26752, ndraw=128, logz=-0.16, remainder_fraction=18.1963%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2739, regioncalls=26880, ndraw=128, logz=-0.15, remainder_fraction=17.5384%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2790, regioncalls=27648, ndraw=128, logz=-0.13, remainder_fraction=15.5068%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=2849, regioncalls=28416, ndraw=128, logz=-0.10, remainder_fraction=13.7044%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.09, remainder_fraction=12.1072%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.07, remainder_fraction=10.9631%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=2965, regioncalls=28672, ndraw=128, logz=-0.07, remainder_fraction=10.6942%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.06, remainder_fraction=9.4447%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.05, remainder_fraction=8.7657%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3088, regioncalls=29056, ndraw=128, logz=-0.04, remainder_fraction=8.3401%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3207, regioncalls=29440, ndraw=128, logz=-0.03, remainder_fraction=7.3634%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3207, regioncalls=29440, ndraw=128, logz=-0.02, remainder_fraction=6.5007%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.02, remainder_fraction=5.7383%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.01, remainder_fraction=5.5969%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3311, regioncalls=29568, ndraw=128, logz=-0.01, remainder_fraction=5.0652%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=3359, regioncalls=30592, ndraw=128, logz=-0.00, remainder_fraction=4.6069%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3372, regioncalls=30848, ndraw=128, logz=-0.00, remainder_fraction=4.4709%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2707, ncalls=3486, regioncalls=31232, ndraw=128, logz=-0.00, remainder_fraction=4.3934%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.00, remainder_fraction=3.9462%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.01, remainder_fraction=3.5710%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3486, regioncalls=31232, ndraw=128, logz=0.01, remainder_fraction=3.4829%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=3537, regioncalls=32128, ndraw=128, logz=0.01, remainder_fraction=3.0740%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 3551 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.04562 +- 0.06643 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1262.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 399 and 399, most (1767/1768 iterations) have 398 INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 572 minimum live points (dlogz from 0.05 to 0.16, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 572 live points (have 400 already) ... INFO ultranest:integrator.py:1433 Sampling 172 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 572.0), (inf, 572.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=3851, regioncalls=32512, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1233.27, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=93, ncalls=3851, regioncalls=32512, ndraw=128, logz=-899.81, remainder_fraction=100.0000%, Lmin=-891.00, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=128, ncalls=3851, regioncalls=32512, ndraw=128, logz=-813.16, remainder_fraction=100.0000%, Lmin=-806.92, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=3851, regioncalls=32512, ndraw=128, logz=-623.76, remainder_fraction=100.0000%, Lmin=-616.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=264, ncalls=3851, regioncalls=32512, ndraw=128, logz=-511.66, remainder_fraction=100.0000%, Lmin=-503.81, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=367, ncalls=3925, regioncalls=32640, ndraw=128, logz=-365.29, remainder_fraction=100.0000%, Lmin=-354.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=392, ncalls=3925, regioncalls=32640, ndraw=128, logz=-325.40, remainder_fraction=100.0000%, Lmin=-318.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3925, regioncalls=32640, ndraw=128, logz=-265.45, remainder_fraction=100.0000%, Lmin=-258.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=521, ncalls=3987, regioncalls=32768, ndraw=128, logz=-203.18, remainder_fraction=100.0000%, Lmin=-196.97, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=3987, regioncalls=32768, ndraw=128, logz=-188.11, remainder_fraction=100.0000%, Lmin=-181.88, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=651, ncalls=4041, regioncalls=32896, ndraw=128, logz=-126.37, remainder_fraction=100.0000%, Lmin=-119.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=764, ncalls=4081, regioncalls=33024, ndraw=128, logz=-85.82, remainder_fraction=100.0000%, Lmin=-78.37, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=783, ncalls=4081, regioncalls=33024, ndraw=128, logz=-81.55, remainder_fraction=100.0000%, Lmin=-74.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=4112, regioncalls=33152, ndraw=128, logz=-63.87, remainder_fraction=100.0000%, Lmin=-57.76, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=914, ncalls=4112, regioncalls=33152, ndraw=128, logz=-49.78, remainder_fraction=100.0000%, Lmin=-43.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1031, ncalls=4159, regioncalls=33408, ndraw=128, logz=-34.62, remainder_fraction=100.0000%, Lmin=-28.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1043, ncalls=4159, regioncalls=33408, ndraw=128, logz=-33.25, remainder_fraction=100.0000%, Lmin=-27.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=4189, regioncalls=33536, ndraw=128, logz=-27.41, remainder_fraction=100.0000%, Lmin=-21.42, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1173, ncalls=4209, regioncalls=33664, ndraw=128, logz=-21.63, remainder_fraction=100.0000%, Lmin=-15.84, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=4223, regioncalls=33792, ndraw=128, logz=-19.81, remainder_fraction=100.0000%, Lmin=-13.99, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1302, ncalls=4238, regioncalls=33920, ndraw=128, logz=-14.21, remainder_fraction=99.9999%, Lmin=-8.82, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1419, ncalls=4282, regioncalls=34432, ndraw=128, logz=-9.94, remainder_fraction=99.9954%, Lmin=-4.80, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=4317, regioncalls=34816, ndraw=128, logz=-7.98, remainder_fraction=99.9670%, Lmin=-2.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1561, ncalls=4348, regioncalls=35072, ndraw=128, logz=-6.64, remainder_fraction=99.8735%, Lmin=-1.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=4367, regioncalls=35456, ndraw=128, logz=-5.03, remainder_fraction=99.3755%, Lmin=0.04, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1689, ncalls=4389, regioncalls=35840, ndraw=128, logz=-4.44, remainder_fraction=98.8825%, Lmin=0.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=4416, regioncalls=36224, ndraw=128, logz=-3.67, remainder_fraction=97.5793%, Lmin=1.27, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=4451, regioncalls=36736, ndraw=128, logz=-3.14, remainder_fraction=95.9120%, Lmin=1.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1837, ncalls=4459, regioncalls=36992, ndraw=128, logz=-2.81, remainder_fraction=94.2897%, Lmin=1.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=4503, regioncalls=37760, ndraw=128, logz=-2.10, remainder_fraction=88.2499%, Lmin=2.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=4503, regioncalls=37760, ndraw=128, logz=-2.09, remainder_fraction=88.1147%, Lmin=2.39, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2003, ncalls=4524, regioncalls=38656, ndraw=128, logz=-1.83, remainder_fraction=84.6478%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2082, ncalls=4550, regioncalls=39424, ndraw=128, logz=-1.51, remainder_fraction=78.8970%, Lmin=2.86, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2201, ncalls=4618, regioncalls=41216, ndraw=128, logz=-1.14, remainder_fraction=69.2387%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2210, ncalls=4618, regioncalls=41216, ndraw=128, logz=-1.11, remainder_fraction=68.4922%, Lmin=3.18, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2235, ncalls=4756, regioncalls=42240, ndraw=128, logz=-1.05, remainder_fraction=66.4217%, Lmin=3.21, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2338, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.82, remainder_fraction=57.9099%, Lmin=3.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.80, remainder_fraction=56.9172%, Lmin=3.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.63, remainder_fraction=49.1470%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2467, ncalls=4756, regioncalls=42240, ndraw=128, logz=-0.61, remainder_fraction=47.8918%, Lmin=3.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2592, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.46, remainder_fraction=39.4142%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2598, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.45, remainder_fraction=39.0289%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=4778, regioncalls=43648, ndraw=128, logz=-0.45, remainder_fraction=38.9029%, Lmin=3.55, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2645, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.41, remainder_fraction=36.1607%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2726, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.34, remainder_fraction=31.6822%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.26, remainder_fraction=25.7564%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=4911, regioncalls=44672, ndraw=128, logz=-0.23, remainder_fraction=23.6731%, Lmin=3.64, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=4936, regioncalls=45184, ndraw=128, logz=-0.20, remainder_fraction=21.7394%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2985, ncalls=4952, regioncalls=45312, ndraw=128, logz=-0.19, remainder_fraction=20.4793%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3012, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.18, remainder_fraction=19.5548%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3114, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.14, remainder_fraction=16.4127%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3169, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.12, remainder_fraction=14.9285%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3242, ncalls=5079, regioncalls=45824, ndraw=128, logz=-0.10, remainder_fraction=13.1587%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=5113, regioncalls=46464, ndraw=128, logz=-0.07, remainder_fraction=10.9120%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3377, ncalls=5124, regioncalls=46592, ndraw=128, logz=-0.07, remainder_fraction=10.4119%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3450, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.06, remainder_fraction=9.1719%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3500, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.05, remainder_fraction=8.4078%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3508, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.05, remainder_fraction=8.2914%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.03, remainder_fraction=7.0639%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3636, ncalls=5253, regioncalls=47360, ndraw=128, logz=-0.03, remainder_fraction=6.6343%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3764, ncalls=5272, regioncalls=48128, ndraw=128, logz=-0.01, remainder_fraction=5.3069%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3765, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=5.2976%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=4.9837%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3850, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.01, remainder_fraction=4.5672%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3893, ncalls=5391, regioncalls=48384, ndraw=128, logz=-0.00, remainder_fraction=4.2369%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=3950, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.00, remainder_fraction=3.8355%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.01, remainder_fraction=3.5148%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=5391, regioncalls=48384, ndraw=128, logz=0.01, remainder_fraction=3.3237%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5391 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.04684 +- 0.05136 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1807.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 683 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 571 and 571, most (3132/3133 iterations) have 570 DEBUG ultranest:integrator.py:1663 at least 570 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 570 minimum live points (dlogz from 0.04 to 0.18, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.03 total:0.06 required:<0.10 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpzqf9taua, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [3.68337942 3.68622715 0. 0.50003002 0.50003002]: u=[0.50003002] -> p=[0.50003002] -> L=3.686227145661632 INFO ultranest:integrator.py:2364 Resuming from 5048 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=5391, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=5391, regioncalls=0, ndraw=128, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=5391, regioncalls=0, ndraw=128, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=5391, regioncalls=0, ndraw=128, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=5391, regioncalls=0, ndraw=128, logz=-573.25, remainder_fraction=100.0000%, Lmin=-561.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=5391, regioncalls=0, ndraw=128, logz=-499.66, remainder_fraction=100.0000%, Lmin=-493.61, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=5391, regioncalls=0, ndraw=128, logz=-463.56, remainder_fraction=100.0000%, Lmin=-456.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=5391, regioncalls=0, ndraw=128, logz=-374.71, remainder_fraction=100.0000%, Lmin=-364.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=5391, regioncalls=0, ndraw=128, logz=-278.70, remainder_fraction=100.0000%, Lmin=-269.85, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=5391, regioncalls=0, ndraw=128, logz=-208.44, remainder_fraction=100.0000%, Lmin=-201.38, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=5391, regioncalls=0, ndraw=128, logz=-201.75, remainder_fraction=100.0000%, Lmin=-195.89, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5391, regioncalls=0, ndraw=128, logz=-168.63, remainder_fraction=100.0000%, Lmin=-162.35, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5391, regioncalls=0, ndraw=128, logz=-127.89, remainder_fraction=100.0000%, Lmin=-120.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=5391, regioncalls=0, ndraw=128, logz=-102.29, remainder_fraction=100.0000%, Lmin=-95.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=5391, regioncalls=0, ndraw=128, logz=-76.26, remainder_fraction=100.0000%, Lmin=-67.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=5391, regioncalls=0, ndraw=128, logz=-59.67, remainder_fraction=100.0000%, Lmin=-53.11, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=5391, regioncalls=0, ndraw=128, logz=-50.83, remainder_fraction=100.0000%, Lmin=-44.90, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5391, regioncalls=0, ndraw=128, logz=-46.91, remainder_fraction=100.0000%, Lmin=-40.98, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5391, regioncalls=0, ndraw=128, logz=-36.30, remainder_fraction=100.0000%, Lmin=-30.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5391, regioncalls=0, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-27.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=5391, regioncalls=0, ndraw=128, logz=-28.46, remainder_fraction=100.0000%, Lmin=-22.72, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=5391, regioncalls=0, ndraw=128, logz=-22.67, remainder_fraction=100.0000%, Lmin=-17.23, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=5391, regioncalls=0, ndraw=128, logz=-21.80, remainder_fraction=100.0000%, Lmin=-15.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=5391, regioncalls=0, ndraw=128, logz=-18.22, remainder_fraction=100.0000%, Lmin=-12.48, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=5391, regioncalls=0, ndraw=128, logz=-14.70, remainder_fraction=100.0000%, Lmin=-9.22, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=5391, regioncalls=0, ndraw=128, logz=-11.83, remainder_fraction=99.9993%, Lmin=-6.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=5391, regioncalls=0, ndraw=128, logz=-9.96, remainder_fraction=99.9955%, Lmin=-4.75, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=5391, regioncalls=0, ndraw=128, logz=-9.56, remainder_fraction=99.9931%, Lmin=-4.29, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=5391, regioncalls=0, ndraw=128, logz=-7.83, remainder_fraction=99.9619%, Lmin=-2.56, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=5391, regioncalls=0, ndraw=128, logz=-6.28, remainder_fraction=99.8203%, Lmin=-1.10, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=5391, regioncalls=0, ndraw=128, logz=-5.10, remainder_fraction=99.4200%, Lmin=-0.12, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=5391, regioncalls=0, ndraw=128, logz=-4.69, remainder_fraction=99.1264%, Lmin=0.36, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=5391, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=98.4353%, Lmin=0.95, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=5391, regioncalls=0, ndraw=128, logz=-3.28, remainder_fraction=96.4486%, Lmin=1.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=5391, regioncalls=0, ndraw=128, logz=-3.13, remainder_fraction=95.8667%, Lmin=1.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=5391, regioncalls=0, ndraw=128, logz=-2.63, remainder_fraction=93.2522%, Lmin=2.07, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=5391, regioncalls=0, ndraw=128, logz=-2.18, remainder_fraction=89.3449%, Lmin=2.32, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.83, remainder_fraction=84.8291%, Lmin=2.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.60, remainder_fraction=80.7292%, Lmin=2.78, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.54, remainder_fraction=79.6520%, Lmin=2.83, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.30, remainder_fraction=74.0684%, Lmin=3.03, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.18, remainder_fraction=70.4449%, Lmin=3.15, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=5391, regioncalls=0, ndraw=128, logz=-1.10, remainder_fraction=68.0352%, Lmin=3.20, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.92, remainder_fraction=61.9581%, Lmin=3.31, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.86, remainder_fraction=59.5960%, Lmin=3.34, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.78, remainder_fraction=56.1467%, Lmin=3.40, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.66, remainder_fraction=50.5050%, Lmin=3.45, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.64, remainder_fraction=49.4302%, Lmin=3.46, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.56, remainder_fraction=45.3100%, Lmin=3.50, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.48, remainder_fraction=40.5034%, Lmin=3.54, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.40, remainder_fraction=36.0867%, Lmin=3.57, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.36, remainder_fraction=32.8840%, Lmin=3.59, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.34, remainder_fraction=32.1257%, Lmin=3.60, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.29, remainder_fraction=28.5291%, Lmin=3.62, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.27, remainder_fraction=26.5391%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.25, remainder_fraction=25.2935%, Lmin=3.63, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.21, remainder_fraction=22.4028%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.20, remainder_fraction=21.3341%, Lmin=3.65, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.18, remainder_fraction=19.8255%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.15, remainder_fraction=17.5384%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.14, remainder_fraction=17.1128%, Lmin=3.66, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.13, remainder_fraction=15.5068%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.10, remainder_fraction=13.7044%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.09, remainder_fraction=12.1072%, Lmin=3.67, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.07, remainder_fraction=10.9631%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.07, remainder_fraction=10.6942%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.06, remainder_fraction=9.4447%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.05, remainder_fraction=8.7657%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.04, remainder_fraction=8.3401%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.03, remainder_fraction=7.3634%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.03, remainder_fraction=7.0055%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.02, remainder_fraction=6.5007%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.02, remainder_fraction=5.7383%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.01, remainder_fraction=5.5969%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.01, remainder_fraction=5.0652%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=5391, regioncalls=0, ndraw=128, logz=-0.00, remainder_fraction=4.4709%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=5391, regioncalls=0, ndraw=128, logz=0.00, remainder_fraction=3.9462%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.5710%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.4829%, Lmin=3.68, Lmax=3.69 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=5391, regioncalls=0, ndraw=128, logz=0.01, remainder_fraction=3.0740%, Lmin=3.69, Lmax=3.69 INFO ultranest:integrator.py:2654 Explored until L=4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5391 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = 0.05415 +- 0.07355 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1262.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.08 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 399 and 399, most (1463/1464 iterations) have 398 DEBUG ultranest:integrator.py:1663 at least 398 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 398 minimum live points (dlogz from 0.05 to 0.28, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.10 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_ordertest.py::test_invalid_order

0.00

[gw1] linux -- Python 3.10.6 /usr/bin/python3
[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_run.py::test_reactive_run

12.19

[gw1] linux -- Python 3.10.6 /usr/bin/python3
[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.28) * Expected Volume: exp(0.00) Quality: ok Hinz: -5.0|*****************************************************| +5.0 Kunz: -5.0|*****************************************************| +5.0 Z=-inf(0.00%) | Like=-110.42..0.28 [-110.4238..-29.8742] | it/evals=0/401 eff=0.0000% N=400 Z=-67.0(0.00%) | Like=-62.58..0.43 [-110.4238..-29.8742] | it/evals=50/452 eff=96.1538% N=400 Mono-modal Volume: ~exp(-4.42) * Expected Volume: exp(-0.23) Quality: ok Hinz: -5.0| ***************************************************| +5.0 Kunz: -5.0| * *************************************************| +5.0 Z=-57.4(0.00%) | Like=-52.63..0.43 [-110.4238..-29.8742] | it/evals=90/494 eff=95.7447% N=400 Z=-54.9(0.00%) | Like=-50.20..0.43 [-110.4238..-29.8742] | it/evals=100/505 eff=95.2381% N=400 Z=-46.9(0.00%) | Like=-42.21..0.43 [-110.4238..-29.8742] | it/evals=150/567 eff=89.8204% N=400 Mono-modal Volume: ~exp(-4.60) * Expected Volume: exp(-0.45) Quality: ok Hinz: -5.0| ***********************************************| +5.0 Kunz: -5.0| ***********************************************| +5.0 Z=-42.2(0.00%) | Like=-37.96..0.43 [-110.4238..-29.8742] | it/evals=180/613 eff=84.5070% N=400 Z=-40.4(0.00%) | Like=-36.05..0.43 [-110.4238..-29.8742] | it/evals=200/634 eff=85.4701% N=400 Z=-36.2(0.00%) | Like=-31.84..0.43 [-110.4238..-29.8742] | it/evals=250/700 eff=83.3333% N=400 Mono-modal Volume: ~exp(-4.98) * Expected Volume: exp(-0.67) Quality: ok Hinz: -5.0| ****************************************** | +5.0 Kunz: -5.0| ****************************************** | +5.0 Z=-34.3(0.00%) | Like=-29.94..0.43 [-110.4238..-29.8742] | it/evals=270/735 eff=80.5970% N=400 Z=-31.7(0.00%) | Like=-27.71..0.43 [-29.8121..-13.5243] | it/evals=300/770 eff=81.0811% N=400 Z=-28.9(0.00%) | Like=-24.89..0.43 [-29.8121..-13.5243] | it/evals=350/834 eff=80.6452% N=400 Mono-modal Volume: ~exp(-4.98) Expected Volume: exp(-0.90) Quality: ok Hinz: -5.0| *************************************** | +5.0 Kunz: -5.0| -2.8 ************************************** | +5.0 Z=-25.6(0.00%) | Like=-21.07..0.49 [-29.8121..-13.5243] | it/evals=397/898 eff=79.7189% N=400 Z=-25.4(0.00%) | Like=-20.82..0.49 [-29.8121..-13.5243] | it/evals=400/907 eff=78.8955% N=400 Mono-modal Volume: ~exp(-5.43) * Expected Volume: exp(-1.12) Quality: ok Hinz: -5.0| -2.5 ********************************** | +5.0 Kunz: -5.0| -2.5 ********************************** | +5.0 Z=-22.6(0.00%) | Like=-18.55..0.49 [-29.8121..-13.5243] | it/evals=450/976 eff=78.1250% N=400 Z=-20.5(0.00%) | Like=-16.26..0.49 [-29.8121..-13.5243] | it/evals=500/1043 eff=77.7605% N=400 Mono-modal Volume: ~exp(-5.80) * Expected Volume: exp(-1.35) Quality: ok Hinz: -5.0| -2.3 ******************************* | +5.0 Kunz: -5.0| -2.1 ****************************** | +5.0 Z=-18.7(0.00%) | Like=-14.60..0.51 [-29.8121..-13.5243] | it/evals=540/1105 eff=76.5957% N=400 Z=-18.3(0.00%) | Like=-14.26..0.55 [-29.8121..-13.5243] | it/evals=550/1118 eff=76.6017% N=400 Z=-16.6(0.00%) | Like=-12.62..0.55 [-13.5092..-7.0346] | it/evals=600/1179 eff=77.0218% N=400 Mono-modal Volume: ~exp(-6.11) * Expected Volume: exp(-1.57) Quality: ok Hinz: -5.0| -2.0 **************************** | +5.0 Kunz: -5.0| -1.9 **************************** | +5.0 Z=-15.7(0.00%) | Like=-11.69..0.55 [-13.5092..-7.0346] | it/evals=630/1225 eff=76.3636% N=400 Z=-15.2(0.00%) | Like=-11.26..0.55 [-13.5092..-7.0346] | it/evals=650/1250 eff=76.4706% N=400 Z=-13.8(0.00%) | Like=-9.78..0.55 [-13.5092..-7.0346] | it/evals=700/1314 eff=76.5864% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-1.80) Quality: ok Hinz: -5.0| -1.7 ************************** +2.9 | +5.0 Kunz: -5.0| -1.6 ************************ +2.9 | +5.0 Z=-12.7(0.01%) | Like=-8.72..0.55 [-13.5092..-7.0346] | it/evals=750/1378 eff=76.6871% N=400 Z=-11.8(0.03%) | Like=-7.66..0.55 [-13.5092..-7.0346] | it/evals=800/1448 eff=76.3359% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-2.02) Quality: ok Hinz: -5.0| -1.4 *********************** +2.6 | +5.0 Kunz: -5.0| -1.4 ********************* +2.5 | +5.0 Z=-10.9(0.06%) | Like=-6.78..0.55 [-7.0343..-2.9827] | it/evals=839/1498 eff=76.4117% N=400 Z=-10.7(0.07%) | Like=-6.56..0.55 [-7.0343..-2.9827] | it/evals=850/1516 eff=76.1649% N=400 Z=-9.9(0.16%) | Like=-5.87..0.56 [-7.0343..-2.9827] | it/evals=894/1582 eff=75.6345% N=400 Mono-modal Volume: ~exp(-6.54) * Expected Volume: exp(-2.25) Quality: ok Hinz: -5.0| -1.2 ******************** +2.5 | +5.0 Kunz: -5.0| -1.1 ******************** +2.5 | +5.0 Z=-9.8(0.18%) | Like=-5.80..0.56 [-7.0343..-2.9827] | it/evals=900/1588 eff=75.7576% N=400 Z=-9.1(0.37%) | Like=-4.92..0.57 [-7.0343..-2.9827] | it/evals=950/1654 eff=75.7576% N=400 Mono-modal Volume: ~exp(-6.86) * Expected Volume: exp(-2.47) Quality: ok Hinz: -5.0| -1.0 ****************** +2.3 | +5.0 Kunz: -5.0| -0.9 ****************** +2.2 | +5.0 Z=-8.5(0.69%) | Like=-4.29..0.57 [-7.0343..-2.9827] | it/evals=990/1707 eff=75.7460% N=400 Z=-8.4(0.80%) | Like=-4.17..0.57 [-7.0343..-2.9827] | it/evals=1000/1719 eff=75.8150% N=400 Z=-7.8(1.42%) | Like=-3.65..0.59 [-7.0343..-2.9827] | it/evals=1050/1787 eff=75.7030% N=400 Mono-modal Volume: ~exp(-7.25) * Expected Volume: exp(-2.70) Quality: ok Hinz: -5.0| -0.8 **************** +2.1 | +5.0 Kunz: -5.0| -0.8 **************** +2.0 | +5.0 Z=-7.4(1.95%) | Like=-3.36..0.59 [-7.0343..-2.9827] | it/evals=1080/1835 eff=75.2613% N=400 Z=-7.3(2.35%) | Like=-3.20..0.59 [-7.0343..-2.9827] | it/evals=1100/1859 eff=75.3941% N=400 Z=-6.8(3.59%) | Like=-2.70..0.59 [-2.9806..-2.0814] | it/evals=1150/1926 eff=75.3604% N=400 Mono-modal Volume: ~exp(-7.32) * Expected Volume: exp(-2.92) Quality: ok Hinz: -5.0| -0.7 **************** +2.0 | +5.0 Kunz: -5.0| -0.7 ************** +1.9 | +5.0 Z=-6.7(4.17%) | Like=-2.58..0.59 [-2.9806..-2.0814] | it/evals=1170/1958 eff=75.0963% N=400 Z=-6.4(5.26%) | Like=-2.40..0.59 [-2.9806..-2.0814] | it/evals=1200/1996 eff=75.1880% N=400 Z=-6.2(6.60%) | Like=-2.15..0.59 [-2.9806..-2.0814] | it/evals=1234/2034 eff=75.5202% N=400 Z=-6.1(7.29%) | Like=-2.06..0.59 [-2.0779..-1.8415] | it/evals=1250/2050 eff=75.7576% N=400 Mono-modal Volume: ~exp(-7.62) * Expected Volume: exp(-3.15) Quality: ok Hinz: -5.0| -0.6 ************** +1.8 | +5.0 Kunz: -5.0| -0.5 ************* +1.7 | +5.0 Z=-6.0(7.81%) | Like=-2.00..0.59 [-2.0779..-1.8415] | it/evals=1260/2061 eff=75.8579% N=400 Z=-5.8(9.88%) | Like=-1.73..0.59 [-1.7370..-1.7261] | it/evals=1300/2108 eff=76.1124% N=400 Mono-modal Volume: ~exp(-7.62) Expected Volume: exp(-3.37) Quality: ok Hinz: -5.0| -0.4 ************ +1.7 | +5.0 Kunz: -5.0| -0.4 ************ +1.7 | +5.0 Z=-5.5(12.75%) | Like=-1.48..0.59 [-1.4844..-1.4839]*| it/evals=1350/2169 eff=76.3143% N=400 Z=-5.3(16.19%) | Like=-1.26..0.59 [-1.2643..-1.2571]*| it/evals=1400/2237 eff=76.2112% N=400 Mono-modal Volume: ~exp(-8.00) * Expected Volume: exp(-3.60) Quality: ok Hinz: -5.0| -0.4 ************ +1.6 | +5.0 Kunz: -5.0| -0.3 ********** +1.6 | +5.0 Z=-5.1(19.40%) | Like=-1.09..0.59 [-1.1004..-1.0902] | it/evals=1440/2295 eff=75.9894% N=400 Z=-5.1(20.14%) | Like=-1.04..0.59 [-1.0447..-1.0442]*| it/evals=1450/2306 eff=76.0756% N=400 Z=-4.9(23.91%) | Like=-0.91..0.59 [-0.9064..-0.9011]*| it/evals=1500/2374 eff=75.9878% N=400 Mono-modal Volume: ~exp(-8.00) Expected Volume: exp(-3.82) Quality: ok Hinz: -5.0| -0.2 ********** +1.5 | +5.0 Kunz: -5.0| -0.2 ********** +1.5 | +5.0 Z=-4.8(28.28%) | Like=-0.70..0.59 [-0.7041..-0.7009]*| it/evals=1550/2436 eff=76.1297% N=400 Z=-4.6(32.78%) | Like=-0.54..0.59 [-0.5372..-0.5353]*| it/evals=1600/2513 eff=75.7217% N=400 Mono-modal Volume: ~exp(-8.11) * Expected Volume: exp(-4.05) Quality: ok Hinz: -5.0| -0.1 ********** +1.4 | +5.0 Kunz: -5.0| -0.1 ********* +1.4 | +5.0 Z=-4.6(34.48%) | Like=-0.49..0.59 [-0.4910..-0.4874]*| it/evals=1620/2546 eff=75.4893% N=400 Z=-4.5(37.16%) | Like=-0.40..0.59 [-0.3961..-0.3956]*| it/evals=1650/2581 eff=75.6534% N=400 Z=-4.4(40.89%) | Like=-0.32..0.59 [-0.3208..-0.3194]*| it/evals=1691/2643 eff=75.3901% N=400 Z=-4.4(41.71%) | Like=-0.30..0.59 [-0.2959..-0.2954]*| it/evals=1700/2654 eff=75.4215% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.27) Quality: ok Hinz: -5.0e+00| -5.7e-02 ******** +1.3e+00 | +5.0e+00 Kunz: -5.0e+00| -4.2e-02 ******** +1.3e+00 | +5.0e+00 Z=-4.4(42.67%) | Like=-0.29..0.59 [-0.2858..-0.2837]*| it/evals=1710/2670 eff=75.3304% N=400 Z=-4.3(46.38%) | Like=-0.20..0.59 [-0.2049..-0.2046]*| it/evals=1750/2723 eff=75.3336% N=400 Mono-modal Volume: ~exp(-9.00) * Expected Volume: exp(-4.50) Quality: ok Hinz: +0.0e+00|************** +1.2e+00 | +5.0e+00 Kunz: +0.0e+00|************** +1.2e+00 | +5.0e+00 Z=-4.2(50.51%) | Like=-0.09..0.59 [-0.0892..-0.0827]*| it/evals=1800/2788 eff=75.3769% N=400 Z=-4.1(53.76%) | Like=-0.03..0.59 [-0.0285..-0.0284]*| it/evals=1838/2833 eff=75.5446% N=400 Z=-4.1(54.67%) | Like=-0.02..0.59 [-0.0215..-0.0205]*| it/evals=1850/2846 eff=75.6337% N=400 Mono-modal Volume: ~exp(-9.00) Expected Volume: exp(-4.73) Quality: ok Hinz: +0.0e+00|************* +1.2e+00 | +5.0e+00 Kunz: +0.0| ************ +1.2 | +5.0 Z=-4.1(57.84%) | Like=0.04..0.59 [0.0405..0.0482]*| it/evals=1890/2897 eff=75.6908% N=400 Z=-4.0(58.61%) | Like=0.06..0.59 [0.0579..0.0582]*| it/evals=1900/2909 eff=75.7274% N=400 Z=-4.0(62.22%) | Like=0.14..0.59 [0.1399..0.1401]*| it/evals=1948/2984 eff=75.3870% N=400 Z=-4.0(62.35%) | Like=0.14..0.59 [0.1411..0.1432]*| it/evals=1950/2986 eff=75.4060% N=400 Mono-modal Volume: ~exp(-9.22) * Expected Volume: exp(-4.95) Quality: ok Hinz: +0.0| *********** +1.1 | +5.0 Kunz: +0.0| *********** +1.1 | +5.0 Z=-4.0(64.48%) | Like=0.17..0.59 [0.1744..0.1747]*| it/evals=1980/3032 eff=75.2280% N=400 Z=-3.9(65.91%) | Like=0.20..0.59 [0.1955..0.1960]*| it/evals=2000/3058 eff=75.2445% N=400 Z=-3.9(69.23%) | Like=0.25..0.59 [0.2514..0.2534]*| it/evals=2050/3130 eff=75.0916% N=400 Mono-modal Volume: ~exp(-9.22) Expected Volume: exp(-5.18) Quality: ok Hinz: +0.0| ********** +1.1 | +5.0 Kunz: +0.0| ********** +1.0 | +5.0 Z=-3.9(71.23%) | Like=0.28..0.59 [0.2809..0.2844]*| it/evals=2082/3175 eff=75.0270% N=400 Z=-3.8(72.35%) | Like=0.30..0.59 [0.3022..0.3037]*| it/evals=2100/3198 eff=75.0536% N=400 Z=-3.8(75.22%) | Like=0.34..0.59 [0.3430..0.3442]*| it/evals=2150/3266 eff=75.0174% N=400 Mono-modal Volume: ~exp(-9.28) * Expected Volume: exp(-5.40) Quality: ok Hinz: +0.0| ********* +1.0 | +5.0 Kunz: +0.0| +0.3 **************************************| +1.0 Z=-3.8(75.76%) | Like=0.35..0.59 [0.3487..0.3489]*| it/evals=2160/3281 eff=74.9740% N=400 Z=-3.8(77.80%) | Like=0.37..0.59 [0.3745..0.3752]*| it/evals=2200/3327 eff=75.1623% N=400 Mono-modal Volume: ~exp(-9.98) * Expected Volume: exp(-5.63) Quality: ok Hinz: +0.0| +0.3 ************************************* | +1.0 Kunz: +0.0| +0.3 *********************************** | +1.0 Z=-3.7(80.20%) | Like=0.40..0.59 [0.3974..0.3977]*| it/evals=2250/3400 eff=75.0000% N=400 Z=-3.7(82.32%) | Like=0.42..0.59 [0.4190..0.4195]*| it/evals=2300/3462 eff=75.1143% N=400 Mono-modal Volume: ~exp(-10.17) * Expected Volume: exp(-5.85) Quality: ok Hinz: +0.0| +0.3 ********************************* | +1.0 Kunz: +0.0| +0.4 ******************************* | +1.0 Z=-3.7(83.88%) | Like=0.43..0.59 [0.4339..0.4339]*| it/evals=2340/3515 eff=75.1204% N=400 Z=-3.7(84.26%) | Like=0.44..0.59 [0.4383..0.4383]*| it/evals=2350/3529 eff=75.1039% N=400 Z=-3.7(85.96%) | Like=0.45..0.59 [0.4526..0.4536]*| it/evals=2399/3592 eff=75.1566% N=400 Z=-3.7(85.99%) | Like=0.45..0.59 [0.4536..0.4538]*| it/evals=2400/3594 eff=75.1409% N=400 Mono-modal Volume: ~exp(-10.48) * Expected Volume: exp(-6.08) Quality: ok Hinz: +0.0| +0.4 ****************************** | +1.0 Kunz: +0.0| +0.4 ***************************** | +1.0 Z=-3.7(86.93%) | Like=0.46..0.59 [0.4626..0.4627]*| it/evals=2430/3634 eff=75.1391% N=400 Z=-3.6(87.52%) | Like=0.47..0.59 [0.4695..0.4695]*| it/evals=2450/3658 eff=75.1995% N=400 Z=-3.6(88.90%) | Like=0.49..0.59 [0.4854..0.4862]*| it/evals=2500/3731 eff=75.0525% N=400 Mono-modal Volume: ~exp(-10.68) * Expected Volume: exp(-6.30) Quality: ok Hinz: +0.0| +0.4 *************************** | +1.0 Kunz: +0.0| +0.4 ************************* | +1.0 Z=-3.6(89.42%) | Like=0.49..0.59 [0.4901..0.4901]*| it/evals=2520/3759 eff=75.0223% N=400 Z=-3.6(90.14%) | Like=0.50..0.59 [0.4964..0.4965]*| it/evals=2550/3792 eff=75.1769% N=400 Z=-3.6(91.25%) | Like=0.51..0.59 [0.5081..0.5085]*| it/evals=2600/3852 eff=75.3187% N=400 Mono-modal Volume: ~exp(-10.69) * Expected Volume: exp(-6.53) Quality: ok Hinz: +0.0| +0.4 ************************ | +1.0 Kunz: +0.0| +0.4 *********************** | +1.0 Z=-3.6(91.46%) | Like=0.51..0.59 [0.5109..0.5110]*| it/evals=2610/3865 eff=75.3247% N=400 Z=-3.6(92.24%) | Like=0.52..0.59 [0.5188..0.5189]*| it/evals=2650/3919 eff=75.3055% N=400 Mono-modal Volume: ~exp(-11.24) * Expected Volume: exp(-6.75) Quality: ok Hinz: +0.0| +0.4 ********************* | +1.0 Kunz: +0.0| +0.5 ********************* | +1.0 Z=-3.6(93.12%) | Like=0.53..0.59 [0.5284..0.5285]*| it/evals=2700/3994 eff=75.1252% N=400 Z=-3.6(93.80%) | Like=0.54..0.59 [0.5357..0.5357]*| it/evals=2743/4052 eff=75.1095% N=400 Z=-3.6(93.91%) | Like=0.54..0.59 [0.5365..0.5367]*| it/evals=2750/4066 eff=75.0136% N=400 Mono-modal Volume: ~exp(-11.24) Expected Volume: exp(-6.98) Quality: ok Hinz: +0.0| +0.5 ******************* +0.8 | +1.0 Kunz: +0.0| +0.5 ****************** +0.8 | +1.0 Z=-3.6(94.61%) | Like=0.54..0.59 [0.5416..0.5417]*| it/evals=2800/4137 eff=74.9264% N=400 Z=-3.6(95.23%) | Like=0.55..0.59 [0.5472..0.5473]*| it/evals=2850/4211 eff=74.7835% N=400 Mono-modal Volume: ~exp(-11.33) * Expected Volume: exp(-7.20) Quality: ok Hinz: +0.0| +0.5 ****************** +0.8 | +1.0 Kunz: +0.0| +0.5 ***************** +0.8 | +1.0 Z=-3.6(95.56%) | Like=0.55..0.59 [0.5497..0.5498]*| it/evals=2880/4259 eff=74.6307% N=400 Z=-3.6(95.78%) | Like=0.55..0.59 [0.5517..0.5518]*| it/evals=2900/4283 eff=74.6845% N=400 Z=-3.6(96.26%) | Like=0.56..0.59 [0.5568..0.5568]*| it/evals=2950/4349 eff=74.7025% N=400 Mono-modal Volume: ~exp(-12.05) * Expected Volume: exp(-7.43) Quality: ok Hinz: +0.0| +0.5 *************** +0.8 | +1.0 Kunz: +0.0| +0.5 *************** +0.8 | +1.0 Z=-3.5(96.44%) | Like=0.56..0.59 [0.5591..0.5592]*| it/evals=2970/4377 eff=74.6794% N=400 Z=-3.5(96.70%) | Like=0.56..0.59 [0.5616..0.5618]*| it/evals=3000/4417 eff=74.6826% N=400 Z=-3.5(97.06%) | Like=0.56..0.59 [0.5650..0.5650]*| it/evals=3047/4479 eff=74.6997% N=400 Z=-3.5(97.08%) | Like=0.57..0.59 [0.5651..0.5652]*| it/evals=3050/4483 eff=74.7000% N=400 Mono-modal Volume: ~exp(-12.05) Expected Volume: exp(-7.65) Quality: ok Hinz: +0.0| +0.5 *************** +0.8 | +1.0 Kunz: +0.0| +0.5 ************* +0.8 | +1.0 Z=-3.5(97.36%) | Like=0.57..0.59 [0.5675..0.5675]*| it/evals=3091/4537 eff=74.7160% N=400 Z=-3.5(97.42%) | Like=0.57..0.59 [0.5679..0.5679]*| it/evals=3100/4552 eff=74.6628% N=400 Mono-modal Volume: ~exp(-12.28) * Expected Volume: exp(-7.88) Quality: ok Hinz: +0.0| +0.5 ************* +0.7 | +1.0 Kunz: +0.0| +0.5 ************ +0.7 | +1.0 Z=-3.5(97.72%) | Like=0.57..0.59 [0.5706..0.5707]*| it/evals=3150/4629 eff=74.4857% N=400 Z=-3.5(97.98%) | Like=0.57..0.59 [0.5730..0.5730]*| it/evals=3200/4692 eff=74.5573% N=400 Mono-modal Volume: ~exp(-12.40) * Expected Volume: exp(-8.10) Quality: ok Hinz: +0.0| +0.5 *********** +0.7 | +1.0 Kunz: +0.0| +0.5 *********** +0.7 | +1.0 Z=-3.5(98.17%) | Like=0.57..0.59 [0.5749..0.5749]*| it/evals=3240/4743 eff=74.6028% N=400 Z=-3.5(98.22%) | Like=0.58..0.59 [0.5752..0.5752]*| it/evals=3250/4757 eff=74.5926% N=400 Z=-3.5(98.43%) | Like=0.58..0.59 [0.5772..0.5772]*| it/evals=3300/4822 eff=74.6269% N=400 Mono-modal Volume: ~exp(-12.82) * Expected Volume: exp(-8.33) Quality: ok Hinz: +0.0| +0.5 *********** +0.7 | +1.0 Kunz: +0.0| +0.5 ********** +0.7 | +1.0 Z=-3.5(98.54%) | Like=0.58..0.59 [0.5788..0.5788]*| it/evals=3330/4858 eff=74.6972% N=400 Z=-3.5(98.61%) | Like=0.58..0.59 [0.5793..0.5793]*| it/evals=3350/4882 eff=74.7434% N=400 Z=-3.5(98.77%) | Like=0.58..0.59 [0.5811..0.5811]*| it/evals=3400/4940 eff=74.8899% N=400 Mono-modal Volume: ~exp(-12.99) * Expected Volume: exp(-8.55) Quality: ok Hinz: +0.0| +0.6 ********* +0.7 | +1.0 Kunz: +0.0| +0.6 ********* +0.7 | +1.0 Z=-3.5(98.83%) | Like=0.58..0.59 [0.5817..0.5817]*| it/evals=3420/4973 eff=74.7868% N=400 Z=-3.5(98.92%) | Like=0.58..0.59 [0.5824..0.5824]*| it/evals=3450/5012 eff=74.8049% N=400 [ultranest] Explored until L=0.6 [ultranest] Likelihood function evaluations: 5053 [ultranest] logZ = -3.495 +- 0.06646 [ultranest] Effective samples strategy satisfied (ESS = 1629.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.07, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 [ultranest] done iterating. ncalls: 5055 nunique: 5055 {'niter': 3883, 'logz': -3.512979739281697, 'logzerr': 0.15019082031188857, 'logz_bs': -3.4946153773041653, 'logz_single': -3.512979739281697, 'logzerr_tail': 0.00993867560773154, 'logzerr_bs': 0.14986162028058514, 'ess': 1629.911652892675, 'H': 3.093626125867617, 'Herr': 0.05327658224759624, 'posterior': {'mean': [0.6528641810663336, 0.6264357937278213], 'stdev': [0.5380843565640636, 0.5207584836042055], 'median': [0.6513496553807023, 0.6346605137507799], 'errlo': [0.11736651751957616, 0.08940050480431339], 'errup': [1.193722161567365, 1.137157590020708], 'information_gain_bits': [0.6859949672653227, 0.7756177953890441]}, 'weighted_samples': {'upoints': array([[0.01988013, 0.02621099], [0.01833264, 0.066725 ], [0.08504421, 0.03905478], ..., [0.56409333, 0.5633068 ], [0.56303122, 0.5635434 ], [0.56347491, 0.56317946]]), 'points': array([[-4.80119866, -4.73789013], [-4.81667357, -4.33275002], [-4.14955789, -4.60945217], ..., [ 0.64093333, 0.63306805], [ 0.63031216, 0.63543397], [ 0.63474906, 0.63179457]]), 'weights': array([9.26018546e-50, 2.47035294e-46, 4.83768179e-43, ..., 2.50932121e-05, 2.50942808e-05, 2.50947339e-05]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -14.69896455, -14.69896455, -14.69896455]), 'bootstrapped_weights': array([[1.40582785e-49, 1.35668842e-49, 0.00000000e+00, ..., 1.36553936e-49, 1.51693786e-49, 1.46025903e-49], [0.00000000e+00, 3.61422607e-46, 4.17988021e-46, ..., 3.63785987e-46, 0.00000000e+00, 3.88958952e-46], [0.00000000e+00, 7.06788512e-43, 8.17277585e-43, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], ..., [0.00000000e+00, 4.11559930e-05, 4.44503916e-05, ..., 0.00000000e+00, 0.00000000e+00, 3.81059410e-05], [4.47343654e-05, 4.11577458e-05, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 4.44530874e-05, ..., 0.00000000e+00, 4.46347506e-05, 0.00000000e+00]]), 'logl': array([-110.42379603, -102.5323187 , -94.94998881, ..., 0.59307162, 0.59311421, 0.59313227])}, 'samples': array([[ 1.29700997, 0.39691822], [-0.25159545, 1.1739252 ], [ 0.49331732, -0.01375432], ..., [ 1.50143774, 0.56239362], [ 0.97385436, 1.10514422], [ 0.65458513, 0.52712821]]), 'maximum_likelihood': {'logl': 0.5931322698047243, 'point': [0.6347490626876349, 0.6317945702385996], 'point_untransformed': [0.5634749062687635, 0.56317945702386]}, 'ncall': 5053, 'paramnames': ['Hinz', 'Kunz'], 'logzerr_single': 0.08794353480881378, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-110.42, Lmax=0.28 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=452, regioncalls=2080, ndraw=40, logz=-66.99, remainder_fraction=100.0000%, Lmin=-62.58, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=494, regioncalls=3760, ndraw=40, logz=-57.38, remainder_fraction=100.0000%, Lmin=-52.63, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=505, regioncalls=4200, ndraw=40, logz=-54.91, remainder_fraction=100.0000%, Lmin=-50.20, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=567, regioncalls=6680, ndraw=40, logz=-46.91, remainder_fraction=100.0000%, Lmin=-42.21, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=613, regioncalls=8520, ndraw=40, logz=-42.21, remainder_fraction=100.0000%, Lmin=-37.96, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=634, regioncalls=9360, ndraw=40, logz=-40.41, remainder_fraction=100.0000%, Lmin=-36.05, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=700, regioncalls=12000, ndraw=40, logz=-36.16, remainder_fraction=100.0000%, Lmin=-31.84, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=735, regioncalls=13400, ndraw=40, logz=-34.25, remainder_fraction=100.0000%, Lmin=-29.94, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=770, regioncalls=14800, ndraw=40, logz=-31.69, remainder_fraction=100.0000%, Lmin=-27.71, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=834, regioncalls=17360, ndraw=40, logz=-28.93, remainder_fraction=100.0000%, Lmin=-24.89, Lmax=0.43 DEBUG ultranest:integrator.py:2610 iteration=397, ncalls=898, regioncalls=19920, ndraw=40, logz=-25.59, remainder_fraction=100.0000%, Lmin=-21.07, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=907, regioncalls=20280, ndraw=40, logz=-25.35, remainder_fraction=100.0000%, Lmin=-20.82, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=976, regioncalls=23040, ndraw=40, logz=-22.62, remainder_fraction=100.0000%, Lmin=-18.55, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=1043, regioncalls=25720, ndraw=40, logz=-20.49, remainder_fraction=100.0000%, Lmin=-16.26, Lmax=0.49 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1105, regioncalls=28200, ndraw=40, logz=-18.69, remainder_fraction=100.0000%, Lmin=-14.60, Lmax=0.51 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1118, regioncalls=28720, ndraw=40, logz=-18.33, remainder_fraction=100.0000%, Lmin=-14.26, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1179, regioncalls=31160, ndraw=40, logz=-16.64, remainder_fraction=99.9998%, Lmin=-12.62, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1225, regioncalls=33000, ndraw=40, logz=-15.74, remainder_fraction=99.9995%, Lmin=-11.69, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1250, regioncalls=34000, ndraw=40, logz=-15.21, remainder_fraction=99.9991%, Lmin=-11.26, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1314, regioncalls=36560, ndraw=40, logz=-13.84, remainder_fraction=99.9968%, Lmin=-9.78, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1378, regioncalls=39120, ndraw=40, logz=-12.73, remainder_fraction=99.9903%, Lmin=-8.72, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1448, regioncalls=41920, ndraw=40, logz=-11.76, remainder_fraction=99.9742%, Lmin=-7.66, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=839, ncalls=1498, regioncalls=43920, ndraw=40, logz=-10.92, remainder_fraction=99.9410%, Lmin=-6.78, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1516, regioncalls=44640, ndraw=40, logz=-10.71, remainder_fraction=99.9267%, Lmin=-6.56, Lmax=0.55 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=1582, regioncalls=47280, ndraw=40, logz=-9.92, remainder_fraction=99.8388%, Lmin=-5.87, Lmax=0.56 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1588, regioncalls=47520, ndraw=40, logz=-9.83, remainder_fraction=99.8233%, Lmin=-5.80, Lmax=0.56 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1654, regioncalls=50160, ndraw=40, logz=-9.11, remainder_fraction=99.6334%, Lmin=-4.92, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1707, regioncalls=52320, ndraw=40, logz=-8.49, remainder_fraction=99.3057%, Lmin=-4.29, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1719, regioncalls=52840, ndraw=40, logz=-8.36, remainder_fraction=99.1963%, Lmin=-4.17, Lmax=0.57 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1787, regioncalls=55560, ndraw=40, logz=-7.76, remainder_fraction=98.5780%, Lmin=-3.65, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1835, regioncalls=57480, ndraw=40, logz=-7.44, remainder_fraction=98.0469%, Lmin=-3.36, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1859, regioncalls=58480, ndraw=40, logz=-7.26, remainder_fraction=97.6487%, Lmin=-3.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1926, regioncalls=61160, ndraw=40, logz=-6.82, remainder_fraction=96.4136%, Lmin=-2.70, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1958, regioncalls=62440, ndraw=40, logz=-6.65, remainder_fraction=95.8254%, Lmin=-2.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1996, regioncalls=64040, ndraw=40, logz=-6.43, remainder_fraction=94.7437%, Lmin=-2.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=2034, regioncalls=65680, ndraw=40, logz=-6.20, remainder_fraction=93.3965%, Lmin=-2.15, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=2050, regioncalls=66360, ndraw=40, logz=-6.10, remainder_fraction=92.7134%, Lmin=-2.06, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2061, regioncalls=66800, ndraw=40, logz=-6.04, remainder_fraction=92.1904%, Lmin=-2.00, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=2108, regioncalls=68720, ndraw=40, logz=-5.80, remainder_fraction=90.1182%, Lmin=-1.73, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2169, regioncalls=71160, ndraw=40, logz=-5.54, remainder_fraction=87.2523%, Lmin=-1.48, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2237, regioncalls=73880, ndraw=40, logz=-5.31, remainder_fraction=83.8089%, Lmin=-1.26, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2295, regioncalls=76200, ndraw=40, logz=-5.14, remainder_fraction=80.6009%, Lmin=-1.09, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=2306, regioncalls=76720, ndraw=40, logz=-5.11, remainder_fraction=79.8571%, Lmin=-1.04, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2374, regioncalls=79440, ndraw=40, logz=-4.93, remainder_fraction=76.0914%, Lmin=-0.91, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2436, regioncalls=81920, ndraw=40, logz=-4.77, remainder_fraction=71.7238%, Lmin=-0.70, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2513, regioncalls=85000, ndraw=40, logz=-4.62, remainder_fraction=67.2236%, Lmin=-0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2546, regioncalls=86360, ndraw=40, logz=-4.57, remainder_fraction=65.5165%, Lmin=-0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=2581, regioncalls=87760, ndraw=40, logz=-4.50, remainder_fraction=62.8444%, Lmin=-0.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1691, ncalls=2643, regioncalls=90240, ndraw=40, logz=-4.40, remainder_fraction=59.1080%, Lmin=-0.32, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=2654, regioncalls=90680, ndraw=40, logz=-4.38, remainder_fraction=58.2874%, Lmin=-0.30, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2670, regioncalls=91360, ndraw=40, logz=-4.36, remainder_fraction=57.3338%, Lmin=-0.29, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=2723, regioncalls=93480, ndraw=40, logz=-4.28, remainder_fraction=53.6176%, Lmin=-0.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2788, regioncalls=96120, ndraw=40, logz=-4.20, remainder_fraction=49.4894%, Lmin=-0.09, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1838, ncalls=2833, regioncalls=97920, ndraw=40, logz=-4.13, remainder_fraction=46.2356%, Lmin=-0.03, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=2846, regioncalls=98440, ndraw=40, logz=-4.12, remainder_fraction=45.3322%, Lmin=-0.02, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2897, regioncalls=100480, ndraw=40, logz=-4.06, remainder_fraction=42.1616%, Lmin=0.04, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=2909, regioncalls=100960, ndraw=40, logz=-4.05, remainder_fraction=41.3899%, Lmin=0.06, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=2984, regioncalls=103960, ndraw=40, logz=-3.99, remainder_fraction=37.7771%, Lmin=0.14, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=2986, regioncalls=104040, ndraw=40, logz=-3.99, remainder_fraction=37.6453%, Lmin=0.14, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3032, regioncalls=105920, ndraw=40, logz=-3.95, remainder_fraction=35.5167%, Lmin=0.17, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3058, regioncalls=107000, ndraw=40, logz=-3.93, remainder_fraction=34.0860%, Lmin=0.20, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=3130, regioncalls=109960, ndraw=40, logz=-3.88, remainder_fraction=30.7692%, Lmin=0.25, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2082, ncalls=3175, regioncalls=111760, ndraw=40, logz=-3.85, remainder_fraction=28.7658%, Lmin=0.28, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=3198, regioncalls=112680, ndraw=40, logz=-3.84, remainder_fraction=27.6476%, Lmin=0.30, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=3266, regioncalls=115400, ndraw=40, logz=-3.80, remainder_fraction=24.7819%, Lmin=0.34, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3281, regioncalls=116040, ndraw=40, logz=-3.79, remainder_fraction=24.2430%, Lmin=0.35, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3327, regioncalls=117960, ndraw=40, logz=-3.76, remainder_fraction=22.1990%, Lmin=0.37, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3400, regioncalls=121000, ndraw=40, logz=-3.73, remainder_fraction=19.8044%, Lmin=0.40, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=3462, regioncalls=123480, ndraw=40, logz=-3.71, remainder_fraction=17.6802%, Lmin=0.42, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3515, regioncalls=125680, ndraw=40, logz=-3.69, remainder_fraction=16.1212%, Lmin=0.43, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=3529, regioncalls=126320, ndraw=40, logz=-3.68, remainder_fraction=15.7410%, Lmin=0.44, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2399, ncalls=3592, regioncalls=128840, ndraw=40, logz=-3.66, remainder_fraction=14.0446%, Lmin=0.45, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3594, regioncalls=128920, ndraw=40, logz=-3.66, remainder_fraction=14.0103%, Lmin=0.45, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3634, regioncalls=130560, ndraw=40, logz=-3.65, remainder_fraction=13.0726%, Lmin=0.46, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=3658, regioncalls=131520, ndraw=40, logz=-3.65, remainder_fraction=12.4782%, Lmin=0.47, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=3731, regioncalls=134440, ndraw=40, logz=-3.63, remainder_fraction=11.0953%, Lmin=0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3759, regioncalls=135600, ndraw=40, logz=-3.62, remainder_fraction=10.5813%, Lmin=0.49, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=3792, regioncalls=136920, ndraw=40, logz=-3.62, remainder_fraction=9.8607%, Lmin=0.50, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3852, regioncalls=139320, ndraw=40, logz=-3.60, remainder_fraction=8.7482%, Lmin=0.51, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3865, regioncalls=139880, ndraw=40, logz=-3.60, remainder_fraction=8.5412%, Lmin=0.51, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=3919, regioncalls=142160, ndraw=40, logz=-3.59, remainder_fraction=7.7618%, Lmin=0.52, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3994, regioncalls=145160, ndraw=40, logz=-3.58, remainder_fraction=6.8783%, Lmin=0.53, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2743, ncalls=4052, regioncalls=147600, ndraw=40, logz=-3.58, remainder_fraction=6.1985%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=4066, regioncalls=148160, ndraw=40, logz=-3.58, remainder_fraction=6.0943%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4137, regioncalls=151000, ndraw=40, logz=-3.57, remainder_fraction=5.3940%, Lmin=0.54, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=4211, regioncalls=153960, ndraw=40, logz=-3.56, remainder_fraction=4.7748%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4259, regioncalls=155960, ndraw=40, logz=-3.56, remainder_fraction=4.4363%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=4283, regioncalls=156920, ndraw=40, logz=-3.56, remainder_fraction=4.2245%, Lmin=0.55, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=4349, regioncalls=159560, ndraw=40, logz=-3.55, remainder_fraction=3.7367%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4377, regioncalls=160720, ndraw=40, logz=-3.55, remainder_fraction=3.5573%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4417, regioncalls=162360, ndraw=40, logz=-3.55, remainder_fraction=3.3040%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3047, ncalls=4479, regioncalls=164840, ndraw=40, logz=-3.54, remainder_fraction=2.9426%, Lmin=0.56, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=4483, regioncalls=165000, ndraw=40, logz=-3.54, remainder_fraction=2.9209%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3091, ncalls=4537, regioncalls=167160, ndraw=40, logz=-3.54, remainder_fraction=2.6401%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=4552, regioncalls=167760, ndraw=40, logz=-3.54, remainder_fraction=2.5820%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4629, regioncalls=170880, ndraw=40, logz=-3.54, remainder_fraction=2.2817%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4692, regioncalls=173400, ndraw=40, logz=-3.53, remainder_fraction=2.0165%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4743, regioncalls=175480, ndraw=40, logz=-3.53, remainder_fraction=1.8265%, Lmin=0.57, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3250, ncalls=4757, regioncalls=176040, ndraw=40, logz=-3.53, remainder_fraction=1.7818%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3300, ncalls=4822, regioncalls=178640, ndraw=40, logz=-3.53, remainder_fraction=1.5739%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=4858, regioncalls=180280, ndraw=40, logz=-3.53, remainder_fraction=1.4610%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=4882, regioncalls=181240, ndraw=40, logz=-3.53, remainder_fraction=1.3902%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4940, regioncalls=183560, ndraw=40, logz=-3.53, remainder_fraction=1.2278%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4973, regioncalls=184960, ndraw=40, logz=-3.52, remainder_fraction=1.1682%, Lmin=0.58, Lmax=0.59 DEBUG ultranest:integrator.py:2610 iteration=3450, ncalls=5012, regioncalls=186560, ndraw=40, logz=-3.52, remainder_fraction=1.0842%, Lmin=0.58, Lmax=0.59 INFO ultranest:integrator.py:2654 Explored until L=0.6 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5053 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.495 +- 0.06646 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1629.9, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.07, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:2894 Making corner plot ... DEBUG ultranest:integrator.py:2940 Making run plot ... DEBUG ultranest:integrator.py:2916 Making trace plot ...

Passed

tests/test_ordertest.py::test_order_correctness

0.26

Passed

tests/test_regionsampling.py::test_region_ellipsoid

0.03

Passed

tests/test_run.py::test_return_summary

11.26

Passed

tests/test_run.py::test_reactive_run_resume_eggbox[tsv]

5.70

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..29.4283] | it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..29.4283] | it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..29.4283] | it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..29.4283] | it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..29.4283] | it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..29.4283] | it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..29.4283] | it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [29.6178..62.1019] | it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [29.6178..62.1019] | it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [29.6178..62.1019] | it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [29.6178..62.1019] | it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [29.6178..62.1019] | it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=43.4(0.00%) | Like=49.11..241.87 [29.6178..62.1019] | it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [29.6178..62.1019] | it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [29.6178..62.1019] | it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [62.2053..112.3934] | it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [62.2053..112.3934] | it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [62.2053..112.3934] | it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [62.2053..112.3934] | it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [62.2053..112.3934] | it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 12.65 │ ▁ ▇ │19.30 18.98 +- 0.35 b : 5.3 │ ▇ ▁ │26.2 6.3 +- 1.1 626 626 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.897580582291928408e+01,3.482687211659772908e-01,1.899594672309787668e+01,1.899594672309787668e+01,1.899594672309787668e+01,6.316415107809904228e+00,1.095459745550366071e+00,6.253063034987970781e+00,6.253063034987970781e+00,6.253063034987970781e+00 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 18.975806 0.348269 18.995947 ... 6.253063 6.253063 6.253063 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 18.975805822919284 checking mean of parameter 'b': 6.316415107809904 checking stdev of parameter 'a': 0.3482687211659773 checking stdev of parameter 'b': 1.095459745550366 checking median of parameter 'a': 18.995946723097877 checking median of parameter 'b': 6.253063034987971 checking errlo of parameter 'a': 18.995946723097877 checking errlo of parameter 'b': 6.253063034987971 checking errup of parameter 'a': 18.995946723097877 checking errup of parameter 'b': 6.253063034987971 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} ====== Running Eggbox problem [2] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.23) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|* **** ************** ************ ****** *** **********| +3.1e+01 b: +3.1e-05|**** ****** ** ***** ********** **** *** **** **********| +3.1e+01 Z=-inf(0.00%) | Like=1.05..221.09 [1.0467..28.5121] | it/evals=0/101 eff=0.0000% N=100 Z=0.1(0.00%) | Like=3.95..221.09 [1.0467..28.5121] | it/evals=10/111 eff=90.9091% N=100 Z=3.5(0.00%) | Like=6.71..221.09 [1.0467..28.5121] | it/evals=20/122 eff=90.9091% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.23) Quality: ok a: +3.1e-05|* ****************** *********** ***** * ********* **| +3.1e+01 b: +3.1e-05|**** ********* ****** ******* *** *** **** * ********| +3.1e+01 Z=6.4(0.00%) | Like=10.30..228.18 [1.0467..28.5121] | it/evals=30/133 eff=90.9091% N=100 Z=10.4(0.00%) | Like=14.59..228.18 [1.0467..28.5121] | it/evals=40/145 eff=88.8889% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.46) Quality: ok a: +3.1e-05|* *********** ****************** ***** ****** *******| +3.1e+01 b: +3.1e-05|**** **** **** ***** * ******* * ** *** **** *** ******| +3.1e+01 Z=14.8(0.00%) | Like=19.71..228.18 [1.0467..28.5121] | it/evals=50/156 eff=89.2857% N=100 Z=22.2(0.00%) | Like=26.91..228.18 [1.0467..28.5121] | it/evals=60/174 eff=81.0811% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.69) Quality: ok a: +3.1e-05|* ** ******* ****************** ************* ** ***| +3.1e+01 b: +3.1e-05|**** **** **** ***** ** ******* * *********** *** ******| +3.1e+01 Z=26.6(0.00%) | Like=31.35..228.18 [29.1828..62.4284] | it/evals=70/189 eff=78.6517% N=100 Z=29.7(0.00%) | Like=34.32..228.18 [29.1828..62.4284] | it/evals=80/213 eff=70.7965% N=100 Z=33.3(0.00%) | Like=38.77..228.18 [29.1828..62.4284] | it/evals=90/240 eff=64.2857% N=100 Mono-modal Volume: ~exp(-3.26) * Expected Volume: exp(-0.92) Quality: ok a: +3.1e-05|* * ******* * **************** ************* * * ***| +3.1e+01 b: +3.1e-05|**** ******** ***** * ******* * *********** *** *****| +3.1e+01 Z=34.5(0.00%) | Like=39.28..228.18 [29.1828..62.4284] | it/evals=92/246 eff=63.0137% N=100 Z=37.8(0.00%) | Like=42.61..228.18 [29.1828..62.4284] | it/evals=100/273 eff=57.8035% N=100 Z=42.8(0.00%) | Like=47.95..228.18 [29.1828..62.4284] | it/evals=110/297 eff=55.8376% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.15) Quality: ok a: +3.1e-05|** * ********* ********** **** *** ********** * ***| +3.1e+01 b: +3.1e-05|**** ******** * *********** ** * ***** ***** *** * ***| +3.1e+01 Z=48.9(0.00%) | Like=54.86..228.18 [29.1828..62.4284] | it/evals=120/326 eff=53.0973% N=100 Z=55.4(0.00%) | Like=61.66..228.18 [29.1828..62.4284] | it/evals=130/368 eff=48.5075% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.38) Quality: ok a: +3.1e-05|** * ********* ******** ***** *** ********* * ***| +3.1e+01 b: +3.1e-05|**** ******* * ********* ** * *** ***** *** *****| +3.1e+01 Z=60.1(0.00%) | Like=68.52..228.18 [62.6017..102.3957] | it/evals=140/402 eff=46.3576% N=100 Z=67.2(0.00%) | Like=72.18..228.18 [62.6017..102.3957] | it/evals=150/452 eff=42.6136% N=100 Z=71.3(0.00%) | Like=76.78..238.35 [62.6017..102.3957] | it/evals=160/496 eff=40.4040% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.61) Quality: ok a: +3.1e-05|** ******* ******* **** *** ********* ***| +3.1e+01 b: +3.1e-05|**** ******* * * ****** **** **** ********* ***| +3.1e+01 Z=71.7(0.00%) | Like=76.83..238.35 [62.6017..102.3957] | it/evals=161/501 eff=40.1496% N=100 Z=77.7(0.00%) | Like=85.32..238.35 [62.6017..102.3957] | it/evals=170/544 eff=38.2883% N=100 Z=83.6(0.00%) | Like=91.87..238.35 [62.6017..102.3957] | it/evals=180/573 eff=38.0550% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.84) Quality: ok a: +3.1e-05|*** ****** ******* ******** ******** ****| +3.1e+01 b: +3.1e-05|**** ******* ******* ********* ******** ***| +3.1e+01 Z=92.1(0.00%) | Like=98.48..238.35 [62.6017..102.3957] | it/evals=190/595 eff=38.3838% N=100 Z=101.4(0.00%) | Like=108.11..240.89 [102.9564..147.0741] | it/evals=200/674 eff=34.8432% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.07) Quality: ok a: +0.0|*** ****** ******* **** ** ******* ****| +31.4 b: +3.1e-05|*** ****** ******* ******* ******** ***| +3.1e+01 Z=108.2(0.00%) | Like=114.20..240.89 [102.9564..147.0741] | it/evals=210/722 eff=33.7621% N=100 Z=114.0(0.00%) | Like=121.27..240.89 [102.9564..147.0741] | it/evals=220/778 eff=32.4484% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.30) Quality: ok a: +0.0|*** ****** ****** *** ** ******* ***| +31.4 b: +3.1e-05|*** ***** ***** ******* ****** ** | +3.1e+01 Z=122.3(0.00%) | Like=128.65..240.89 [102.9564..147.0741] | it/evals=230/849 eff=30.7076% N=100 Z=128.0(0.00%) | Like=134.37..240.89 [102.9564..147.0741] | it/evals=240/950 eff=28.2353% N=100 Z=132.5(0.00%) | Like=139.29..242.00 [102.9564..147.0741] | it/evals=250/1034 eff=26.7666% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.53) Quality: ok a: +0.0|*** ***** ****** *** ** ****** ***| +31.4 b: +3.1e-05|*** ***** ****** ******* ****** ** | +3.1e+01 Z=140.8(0.00%) | Like=147.11..242.37 [147.1142..186.4200] | it/evals=260/1135 eff=25.1208% N=100 Z=148.1(0.00%) | Like=155.97..242.37 [147.1142..186.4200] | it/evals=270/1279 eff=22.9008% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.76) Quality: ok a: +0.0|*** **** ****** *** * ***** **| +31.4 b: +3.1e-05|*** ***** ***** ***** ****** * *| +3.1e+01 Z=153.6(0.00%) | Like=160.75..242.37 [147.1142..186.4200] | it/evals=277/1369 eff=21.8282% N=100 Z=155.6(0.00%) | Like=163.08..242.37 [147.1142..186.4200] | it/evals=280/1411 eff=21.3577% N=100 Z=161.0(0.00%) | Like=168.19..242.37 [147.1142..186.4200] | it/evals=290/1566 eff=19.7817% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05|** **** ***** ***** ***** **| +3.1e+01 b: +3.1e-05|** ***** ***** ***** ***** *| +3.1e+01 Z=166.0(0.00%) | Like=173.84..242.37 [147.1142..186.4200] | it/evals=300/1700 eff=18.7500% N=100 Z=171.7(0.00%) | Like=179.38..242.37 [147.1142..186.4200] | it/evals=310/1793 eff=18.3107% N=100 Z=177.1(0.00%) | Like=184.35..242.37 [147.1142..186.4200] | it/evals=320/1938 eff=17.4102% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05|** **** **** ***** **** **| +3.1e+01 b: +3.1e-05|** ***** ***** **** **** *| +3.1e+01 Z=181.8(0.00%) | Like=189.01..242.37 [186.7319..216.1536] | it/evals=328/2114 eff=16.2860% N=100 Z=182.5(0.00%) | Like=189.50..242.37 [186.7319..216.1536] | it/evals=330/2226 eff=15.5221% N=100 Z=183.6(0.00%) | Like=190.73..242.37 [186.7319..216.1536] | it/evals=334/2506 eff=13.8820% N=100 Z=186.2(0.00%) | Like=193.29..242.37 [186.7319..216.1536] | it/evals=340/2654 eff=13.3125% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05|** **** **** **** **** **| +3.1e+01 b: +3.1e-05|** **** **** **** *** *| +3.1e+01 Z=190.9(0.00%) | Like=197.89..242.37 [186.7319..216.1536] | it/evals=349/2998 eff=12.0428% N=100 Z=191.2(0.00%) | Like=198.42..242.37 [186.7319..216.1536] | it/evals=350/3009 eff=12.0316% N=100 Z=194.7(0.00%) | Like=201.90..242.37 [186.7319..216.1536] | it/evals=357/3238 eff=11.3767% N=100 Z=197.3(0.00%) | Like=205.11..242.37 [186.7319..216.1536] | it/evals=360/3318 eff=11.1871% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05|** **** **** *** **** **| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 Z=199.7(0.00%) | Like=206.32..242.37 [186.7319..216.1536] | it/evals=368/3563 eff=10.6266% N=100 Z=200.0(0.00%) | Like=206.86..242.37 [186.7319..216.1536] | it/evals=370/3667 eff=10.3729% N=100 Z=202.9(0.00%) | Like=210.14..242.51 [186.7319..216.1536] | it/evals=379/4169 eff=9.3143% N=100 Z=203.2(0.00%) | Like=210.98..242.51 [186.7319..216.1536] | it/evals=380/4187 eff=9.2978% N=100 Z=204.0(0.00%) | Like=211.48..242.51 [186.7319..216.1536] | it/evals=382/4358 eff=8.9713% N=100 Z=206.3(0.00%) | Like=213.44..242.60 [186.7319..216.1536] | it/evals=390/4799 eff=8.2996% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05|** **** *** *** *** *| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 Z=206.5(0.00%) | Like=213.58..242.60 [186.7319..216.1536] | it/evals=391/4909 eff=8.1306% N=100 Z=207.4(0.00%) | Like=214.42..242.60 [186.7319..216.1536] | it/evals=396/5127 eff=7.8775% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 5287 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 236.030 +- 0.815 single instance: logZ = 236.030 +- 0.247 bootstrapped : logZ = 236.020 +- 0.429 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a : 0.0 │▁ ▃▁ ▇ ▂ ▁▇ ▁│31.4 16.9 +- 7.9 b : 0 │▆ ▃▁ ▄▁ ▁ ▁▇ ▃│31 14 +- 11 5287 5287 0 CSV content: "a_mean","a_stdev","a_median","a_errlo","a_errup","b_mean","b_stdev","b_median","b_errlo","b_errup" 1.692122856244112938e+01,7.903712302185231131e+00,1.276958378640852310e+01,6.412527886198907900e+00,2.524009418967003171e+01,1.427582766036078255e+01,1.146926462371362021e+01,1.263626942277114829e+01,6.172183764370788722e-02,2.514548034712652225e+01 a_mean a_stdev a_median ... b_median b_errlo b_errup 0 16.921229 7.903712 12.769584 ... 12.636269 0.061722 25.14548 [1 rows x 10 columns] Index(['a_mean', 'a_stdev', 'a_median', 'a_errlo', 'a_errup', 'b_mean', 'b_stdev', 'b_median', 'b_errlo', 'b_errup'], dtype='object') checking results[niter] ... checking results[logz] ... checking results[logzerr] ... checking results[logz_bs] ... checking results[logz_single] ... checking results[logzerr_tail] ... checking results[logzerr_bs] ... checking results[ess] ... checking results[H] ... checking results[Herr] ... checking results[posterior] ... checking results[maximum_likelihood] ... checking results[ncall] ... checking results[paramnames] ... checking results[logzerr_single] ... checking results[insertion_order_MWW_test] ... niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () checking mean of parameter 'a': 16.92122856244113 checking mean of parameter 'b': 14.275827660360783 checking stdev of parameter 'a': 7.903712302185231 checking stdev of parameter 'b': 11.46926462371362 checking median of parameter 'a': 12.769583786408523 checking median of parameter 'b': 12.636269422771148 checking errlo of parameter 'a': 6.412527886198908 checking errlo of parameter 'b': 0.06172183764370789 checking errup of parameter 'a': 25.24009418967003 checking errup of parameter 'b': 25.145480347126522 weighted_samples dict_keys(['upoints', 'points', 'weights', 'logw', 'bootstrapped_weights', 'logl']) maximum_likelihood dict_keys(['logl', 'point', 'point_untransformed']) ncall () skipping logzerr_single () insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpmkz0zrf5, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=123, regioncalls=920, ndraw=40, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=137, regioncalls=1480, ndraw=40, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=149, regioncalls=1960, ndraw=40, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=162, regioncalls=2480, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=175, regioncalls=3000, ndraw=40, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=188, regioncalls=3520, ndraw=40, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=206, regioncalls=4240, ndraw=40, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=223, regioncalls=4920, ndraw=40, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=244, regioncalls=5760, ndraw=40, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=284, regioncalls=7360, ndraw=40, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=309, regioncalls=8360, ndraw=40, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=341, regioncalls=9640, ndraw=40, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=377, regioncalls=11080, ndraw=40, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=396, regioncalls=11840, ndraw=40, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=441, regioncalls=13640, ndraw=40, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=502, regioncalls=16080, ndraw=40, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=553, regioncalls=18120, ndraw=40, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=584, regioncalls=19360, ndraw=40, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 626 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpmkz0zrf5, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=1.05, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=111, regioncalls=440, ndraw=40, logz=0.06, remainder_fraction=100.0000%, Lmin=3.95, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=122, regioncalls=880, ndraw=40, logz=3.55, remainder_fraction=100.0000%, Lmin=6.71, Lmax=221.09 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=133, regioncalls=1320, ndraw=40, logz=6.36, remainder_fraction=100.0000%, Lmin=10.30, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=145, regioncalls=1800, ndraw=40, logz=10.43, remainder_fraction=100.0000%, Lmin=14.59, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=156, regioncalls=2240, ndraw=40, logz=14.85, remainder_fraction=100.0000%, Lmin=19.71, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=174, regioncalls=2960, ndraw=40, logz=22.21, remainder_fraction=100.0000%, Lmin=26.91, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=189, regioncalls=3560, ndraw=40, logz=26.59, remainder_fraction=100.0000%, Lmin=31.35, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=213, regioncalls=4520, ndraw=40, logz=29.74, remainder_fraction=100.0000%, Lmin=34.32, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=240, regioncalls=5600, ndraw=40, logz=33.34, remainder_fraction=100.0000%, Lmin=38.77, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=92, ncalls=246, regioncalls=5840, ndraw=40, logz=34.49, remainder_fraction=100.0000%, Lmin=39.28, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=273, regioncalls=6920, ndraw=40, logz=37.85, remainder_fraction=100.0000%, Lmin=42.61, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=297, regioncalls=7880, ndraw=40, logz=42.78, remainder_fraction=100.0000%, Lmin=47.95, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=326, regioncalls=9040, ndraw=40, logz=48.91, remainder_fraction=100.0000%, Lmin=54.86, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=368, regioncalls=10720, ndraw=40, logz=55.41, remainder_fraction=100.0000%, Lmin=61.66, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=402, regioncalls=12080, ndraw=40, logz=60.12, remainder_fraction=100.0000%, Lmin=68.52, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=452, regioncalls=14080, ndraw=40, logz=67.24, remainder_fraction=100.0000%, Lmin=72.18, Lmax=228.18 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=496, regioncalls=15840, ndraw=40, logz=71.34, remainder_fraction=100.0000%, Lmin=76.78, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=501, regioncalls=16040, ndraw=40, logz=71.72, remainder_fraction=100.0000%, Lmin=76.83, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=544, regioncalls=17760, ndraw=40, logz=77.69, remainder_fraction=100.0000%, Lmin=85.32, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=573, regioncalls=18920, ndraw=40, logz=83.64, remainder_fraction=100.0000%, Lmin=91.87, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=595, regioncalls=19800, ndraw=40, logz=92.13, remainder_fraction=100.0000%, Lmin=98.48, Lmax=238.35 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=674, regioncalls=22960, ndraw=40, logz=101.38, remainder_fraction=100.0000%, Lmin=108.11, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=722, regioncalls=24880, ndraw=40, logz=108.20, remainder_fraction=100.0000%, Lmin=114.20, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=778, regioncalls=27120, ndraw=40, logz=114.04, remainder_fraction=100.0000%, Lmin=121.27, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=849, regioncalls=29960, ndraw=40, logz=122.34, remainder_fraction=100.0000%, Lmin=128.65, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=950, regioncalls=34000, ndraw=40, logz=128.02, remainder_fraction=100.0000%, Lmin=134.37, Lmax=240.89 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1034, regioncalls=37360, ndraw=40, logz=132.48, remainder_fraction=100.0000%, Lmin=139.29, Lmax=242.00 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1135, regioncalls=41400, ndraw=40, logz=140.81, remainder_fraction=100.0000%, Lmin=147.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1279, regioncalls=47160, ndraw=40, logz=148.11, remainder_fraction=100.0000%, Lmin=155.97, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=277, ncalls=1369, regioncalls=50760, ndraw=40, logz=153.60, remainder_fraction=100.0000%, Lmin=160.75, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1411, regioncalls=52440, ndraw=40, logz=155.63, remainder_fraction=100.0000%, Lmin=163.08, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1566, regioncalls=58640, ndraw=40, logz=161.05, remainder_fraction=100.0000%, Lmin=168.19, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1700, regioncalls=64000, ndraw=40, logz=166.03, remainder_fraction=100.0000%, Lmin=173.84, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1793, regioncalls=67720, ndraw=40, logz=171.65, remainder_fraction=100.0000%, Lmin=179.38, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1938, regioncalls=73520, ndraw=40, logz=177.14, remainder_fraction=100.0000%, Lmin=184.35, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=328, ncalls=2114, regioncalls=80560, ndraw=40, logz=181.84, remainder_fraction=100.0000%, Lmin=189.01, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=2226, regioncalls=85040, ndraw=40, logz=182.54, remainder_fraction=100.0000%, Lmin=189.50, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=334, ncalls=2506, regioncalls=96240, ndraw=40, logz=183.64, remainder_fraction=100.0000%, Lmin=190.73, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=2654, regioncalls=102160, ndraw=40, logz=186.24, remainder_fraction=100.0000%, Lmin=193.29, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=349, ncalls=2998, regioncalls=115920, ndraw=40, logz=190.86, remainder_fraction=100.0000%, Lmin=197.89, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=3009, regioncalls=116360, ndraw=40, logz=191.15, remainder_fraction=100.0000%, Lmin=198.42, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=357, ncalls=3238, regioncalls=125520, ndraw=40, logz=194.71, remainder_fraction=100.0000%, Lmin=201.90, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=3318, regioncalls=128720, ndraw=40, logz=197.32, remainder_fraction=100.0000%, Lmin=205.11, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=3563, regioncalls=138520, ndraw=40, logz=199.69, remainder_fraction=100.0000%, Lmin=206.32, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=3667, regioncalls=142680, ndraw=40, logz=200.02, remainder_fraction=100.0000%, Lmin=206.86, Lmax=242.37 DEBUG ultranest:integrator.py:2610 iteration=379, ncalls=4169, regioncalls=162760, ndraw=40, logz=202.87, remainder_fraction=100.0000%, Lmin=210.14, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=4187, regioncalls=163480, ndraw=40, logz=203.15, remainder_fraction=100.0000%, Lmin=210.98, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=382, ncalls=4358, regioncalls=170320, ndraw=40, logz=204.01, remainder_fraction=100.0000%, Lmin=211.48, Lmax=242.51 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=4799, regioncalls=187960, ndraw=40, logz=206.25, remainder_fraction=100.0000%, Lmin=213.44, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=4909, regioncalls=192360, ndraw=40, logz=206.49, remainder_fraction=100.0000%, Lmin=213.58, Lmax=242.60 DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=5127, regioncalls=201080, ndraw=40, logz=207.43, remainder_fraction=100.0000%, Lmin=214.42, Lmax=242.60 INFO ultranest:integrator.py:2654 Explored until L=2e+02 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5287 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_netiterintegrate.py::test_treedump

0.06

Passed

tests/test_run.py::test_dlogz_reactive_run_SLOW

113.80

[gw0] linux -- Python 3.10.6 /usr/bin/python3
[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3[gw0] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
running for ess [ultranest] To achieve the desired logz accuracy, min_num_live_points was increased to 64 [ultranest] Sampling 64 live points from prior ... Z=-inf(0.00%) | Like=-219160.93..-338.64 [-219160.9259..-66928.1126] | it/evals=0/192 eff=0.0000% N=64 Z=-126286.0(0.00%) | Like=-123905.72..-338.64 [-219160.9259..-66928.1126] | it/evals=6/192 eff=4.6875% N=64 Z=-105163.6(0.00%) | Like=-104323.03..-338.64 [-219160.9259..-66928.1126] | it/evals=12/192 eff=9.3750% N=64 Z=-96310.2(0.00%) | Like=-95825.45..-338.64 [-219160.9259..-66928.1126] | it/evals=15/192 eff=11.7188% N=64 Z=-92147.5(0.00%) | Like=-90911.35..-338.64 [-219160.9259..-66928.1126] | it/evals=18/192 eff=14.0625% N=64 Z=-83359.1(0.00%) | Like=-82523.24..-338.64 [-219160.9259..-66928.1126] | it/evals=24/192 eff=18.7500% N=64 Z=-77249.3(0.00%) | Like=-73174.88..-338.64 [-219160.9259..-66928.1126] | it/evals=30/192 eff=23.4375% N=64 Z=-68821.4(0.00%) | Like=-66961.75..-338.64 [-219160.9259..-66928.1126] | it/evals=36/192 eff=28.1250% N=64 Z=-62913.5(0.00%) | Like=-62524.24..-338.64 [-66894.4747..-30968.4623] | it/evals=42/192 eff=32.8125% N=64 Z=-60415.5(0.00%) | Like=-60348.58..-338.64 [-66894.4747..-30968.4623] | it/evals=45/192 eff=35.1562% N=64 Z=-59089.1(0.00%) | Like=-56644.03..-338.64 [-66894.4747..-30968.4623] | it/evals=48/192 eff=37.5000% N=64 Z=-52753.0(0.00%) | Like=-51631.51..-338.64 [-66894.4747..-30968.4623] | it/evals=54/192 eff=42.1875% N=64 Z=-44451.0(0.00%) | Like=-44202.51..-338.64 [-66894.4747..-30968.4623] | it/evals=60/271 eff=28.9855% N=64 Z=-42311.4(0.00%) | Like=-41912.56..-338.64 [-66894.4747..-30968.4623] | it/evals=66/271 eff=31.8841% N=64 Z=-39346.0(0.00%) | Like=-38622.07..-338.64 [-66894.4747..-30968.4623] | it/evals=72/271 eff=34.7826% N=64 Z=-37952.2(0.00%) | Like=-36783.31..-338.64 [-66894.4747..-30968.4623] | it/evals=75/271 eff=36.2319% N=64 Z=-36006.7(0.00%) | Like=-35497.21..-338.64 [-66894.4747..-30968.4623] | it/evals=78/271 eff=37.6812% N=64 Z=-31115.6(0.00%) | Like=-30731.78..-338.64 [-30731.7843..-12967.1842] | it/evals=84/271 eff=40.5797% N=64 Z=-28688.0(0.00%) | Like=-28421.18..-338.64 [-30731.7843..-12967.1842] | it/evals=90/271 eff=43.4783% N=64 Z=-25187.3(0.00%) | Like=-24656.65..-338.64 [-30731.7843..-12967.1842] | it/evals=96/311 eff=38.8664% N=64 Z=-22113.7(0.00%) | Like=-21443.24..-298.85 [-30731.7843..-12967.1842] | it/evals=102/346 eff=36.1702% N=64 Z=-19585.3(0.00%) | Like=-19464.67..-298.85 [-30731.7843..-12967.1842] | it/evals=105/346 eff=37.2340% N=64 Z=-18980.4(0.00%) | Like=-18714.44..-298.85 [-30731.7843..-12967.1842] | it/evals=108/346 eff=38.2979% N=64 Z=-17101.8(0.00%) | Like=-16522.06..-298.85 [-30731.7843..-12967.1842] | it/evals=114/365 eff=37.8738% N=64 Z=-14939.8(0.00%) | Like=-14867.96..-49.47 [-30731.7843..-12967.1842] | it/evals=120/365 eff=39.8671% N=64 Z=-13749.8(0.00%) | Like=-13612.93..-49.47 [-30731.7843..-12967.1842] | it/evals=126/384 eff=39.3750% N=64 Z=-12095.7(0.00%) | Like=-12066.44..-49.47 [-12930.5907..-6761.7113] | it/evals=132/384 eff=41.2500% N=64 Z=-11676.8(0.00%) | Like=-11455.33..-49.47 [-12930.5907..-6761.7113] | it/evals=138/399 eff=41.1940% N=64 Z=-9942.7(0.00%) | Like=-9610.42..-49.47 [-12930.5907..-6761.7113] | it/evals=144/399 eff=42.9851% N=64 Z=-9087.9(0.00%) | Like=-8762.61..-47.04 [-12930.5907..-6761.7113] | it/evals=150/410 eff=43.3526% N=64 Z=-8235.1(0.00%) | Like=-8086.11..-47.04 [-12930.5907..-6761.7113] | it/evals=156/410 eff=45.0867% N=64 Z=-7472.4(0.00%) | Like=-7249.22..-47.04 [-12930.5907..-6761.7113] | it/evals=162/430 eff=44.2623% N=64 Z=-7233.2(0.00%) | Like=-7189.85..-47.04 [-12930.5907..-6761.7113] | it/evals=165/430 eff=45.0820% N=64 Z=-7139.4(0.00%) | Like=-6909.47..-47.04 [-12930.5907..-6761.7113] | it/evals=168/446 eff=43.9791% N=64 Z=-6586.4(0.00%) | Like=-6511.36..-47.04 [-6758.0662..-3869.3843] | it/evals=174/453 eff=44.7301% N=64 Z=-6229.9(0.00%) | Like=-6179.54..-47.04 [-6758.0662..-3869.3843] | it/evals=180/463 eff=45.1128% N=64 Z=-5870.7(0.00%) | Like=-5704.16..-47.04 [-6758.0662..-3869.3843] | it/evals=186/470 eff=45.8128% N=64 Z=-5350.2(0.00%) | Like=-5299.56..-47.04 [-6758.0662..-3869.3843] | it/evals=192/484 eff=45.7143% N=64 Z=-5230.5(0.00%) | Like=-5122.84..-47.04 [-6758.0662..-3869.3843] | it/evals=195/484 eff=46.4286% N=64 Z=-5007.8(0.00%) | Like=-4993.48..-47.04 [-6758.0662..-3869.3843] | it/evals=198/488 eff=46.6981% N=64 Z=-4757.0(0.00%) | Like=-4671.78..-47.04 [-6758.0662..-3869.3843] | it/evals=204/494 eff=47.4419% N=64 Z=-4376.4(0.00%) | Like=-4050.17..-47.04 [-6758.0662..-3869.3843] | it/evals=210/507 eff=47.4041% N=64 Z=-3611.3(0.00%) | Like=-3538.07..-47.04 [-3844.5238..-2006.9345] | it/evals=216/519 eff=47.4725% N=64 Z=-3253.1(0.00%) | Like=-3230.22..-47.04 [-3844.5238..-2006.9345] | it/evals=222/529 eff=47.7419% N=64 Z=-2973.9(0.00%) | Like=-2936.21..-47.04 [-3844.5238..-2006.9345] | it/evals=228/534 eff=48.5106% N=64 Z=-2717.1(0.00%) | Like=-2689.65..-47.04 [-3844.5238..-2006.9345] | it/evals=234/546 eff=48.5477% N=64 Z=-2482.7(0.00%) | Like=-2396.74..-47.04 [-3844.5238..-2006.9345] | it/evals=240/562 eff=48.1928% N=64 Z=-2251.9(0.00%) | Like=-2227.96..-47.04 [-3844.5238..-2006.9345] | it/evals=246/574 eff=48.2353% N=64 Z=-2051.0(0.00%) | Like=-2020.88..-43.53 [-3844.5238..-2006.9345] | it/evals=252/586 eff=48.2759% N=64 Z=-1996.9(0.00%) | Like=-1971.99..-43.53 [-1992.9917..-938.7180] | it/evals=255/591 eff=48.3871% N=64 Z=-1930.6(0.00%) | Like=-1893.32..-43.53 [-1992.9917..-938.7180] | it/evals=258/595 eff=48.5876% N=64 Z=-1661.3(0.00%) | Like=-1630.36..-43.53 [-1992.9917..-938.7180] | it/evals=264/607 eff=48.6188% N=64 Z=-1531.4(0.00%) | Like=-1450.33..-43.53 [-1992.9917..-938.7180] | it/evals=270/623 eff=48.3005% N=64 Z=-1346.6(0.00%) | Like=-1304.59..-29.10 [-1992.9917..-938.7180] | it/evals=276/640 eff=47.9167% N=64 Z=-1210.1(0.00%) | Like=-1193.96..-7.65 [-1992.9917..-938.7180] | it/evals=282/656 eff=47.6351% N=64 Z=-1128.8(0.00%) | Like=-1115.38..-7.65 [-1992.9917..-938.7180] | it/evals=288/656 eff=48.6486% N=64 Z=-1037.0(0.00%) | Like=-1001.43..-6.62 [-1992.9917..-938.7180] | it/evals=294/667 eff=48.7562% N=64 Z=-946.6(0.00%) | Like=-931.46..-6.62 [-938.4822..-420.6857] | it/evals=300/681 eff=48.6224% N=64 Z=-860.8(0.00%) | Like=-851.17..-6.62 [-938.4822..-420.6857] | it/evals=306/704 eff=47.8125% N=64 Z=-799.9(0.00%) | Like=-784.81..-6.62 [-938.4822..-420.6857] | it/evals=312/716 eff=47.8528% N=64 Z=-722.0(0.00%) | Like=-712.81..-6.62 [-938.4822..-420.6857] | it/evals=318/728 eff=47.8916% N=64 Z=-711.2(0.00%) | Like=-681.06..-6.62 [-938.4822..-420.6857] | it/evals=324/744 eff=47.6471% N=64 Z=-648.6(0.00%) | Like=-627.61..-6.62 [-938.4822..-420.6857] | it/evals=330/773 eff=46.5444% N=64 Z=-579.8(0.00%) | Like=-544.60..-6.62 [-938.4822..-420.6857] | it/evals=336/773 eff=47.3907% N=64 Z=-507.9(0.00%) | Like=-491.75..-6.62 [-938.4822..-420.6857] | it/evals=342/785 eff=47.4341% N=64 Z=-448.9(0.00%) | Like=-436.99..-6.62 [-938.4822..-420.6857] | it/evals=345/786 eff=47.7839% N=64 Z=-440.5(0.00%) | Like=-410.44..-6.62 [-410.4366..-212.6066] | it/evals=348/794 eff=47.6712% N=64 Z=-391.5(0.00%) | Like=-381.77..-6.62 [-410.4366..-212.6066] | it/evals=354/814 eff=47.2000% N=64 Z=-353.2(0.00%) | Like=-341.64..-6.62 [-410.4366..-212.6066] | it/evals=360/924 eff=41.8605% N=64 Z=-330.6(0.00%) | Like=-319.63..-6.62 [-410.4366..-212.6066] | it/evals=366/924 eff=42.5581% N=64 Z=-319.4(0.00%) | Like=-308.99..-6.62 [-410.4366..-212.6066] | it/evals=372/924 eff=43.2558% N=64 Z=-294.6(0.00%) | Like=-274.35..-6.62 [-410.4366..-212.6066] | it/evals=378/924 eff=43.9535% N=64 Z=-256.9(0.00%) | Like=-243.84..-6.62 [-410.4366..-212.6066] | it/evals=384/924 eff=44.6512% N=64 Z=-231.4(0.00%) | Like=-216.70..-6.62 [-410.4366..-212.6066] | it/evals=390/924 eff=45.3488% N=64 Z=-208.6(0.00%) | Like=-197.50..-6.62 [-209.4358..-92.5441] | it/evals=396/924 eff=46.0465% N=64 Z=-192.9(0.00%) | Like=-180.36..-6.62 [-209.4358..-92.5441] | it/evals=402/924 eff=46.7442% N=64 Z=-181.5(0.00%) | Like=-170.96..-2.59 [-209.4358..-92.5441] | it/evals=405/924 eff=47.0930% N=64 Z=-174.8(0.00%) | Like=-164.65..-2.59 [-209.4358..-92.5441] | it/evals=408/1052 eff=41.2955% N=64 Z=-162.1(0.00%) | Like=-151.03..-2.59 [-209.4358..-92.5441] | it/evals=414/1052 eff=41.9028% N=64 Z=-150.8(0.00%) | Like=-136.96..-2.59 [-209.4358..-92.5441] | it/evals=420/1052 eff=42.5101% N=64 Z=-140.3(0.00%) | Like=-128.55..-2.59 [-209.4358..-92.5441] | it/evals=426/1052 eff=43.1174% N=64 Z=-126.9(0.00%) | Like=-115.71..-2.59 [-209.4358..-92.5441] | it/evals=432/1052 eff=43.7247% N=64 Z=-123.3(0.00%) | Like=-111.94..-2.59 [-209.4358..-92.5441] | it/evals=435/1052 eff=44.0283% N=64 Z=-119.5(0.00%) | Like=-108.01..-2.59 [-209.4358..-92.5441] | it/evals=438/1052 eff=44.3320% N=64 Z=-110.7(0.00%) | Like=-94.16..-1.48 [-209.4358..-92.5441] | it/evals=444/1052 eff=44.9393% N=64 Z=-100.8(0.00%) | Like=-86.81..-1.48 [-92.3860..-42.0224] | it/evals=450/1052 eff=45.5466% N=64 Z=-90.8(0.00%) | Like=-77.75..-1.48 [-92.3860..-42.0224] | it/evals=456/1052 eff=46.1538% N=64 Z=-82.6(0.00%) | Like=-69.50..-1.48 [-92.3860..-42.0224] | it/evals=462/1074 eff=45.7426% N=64 Z=-79.0(0.00%) | Like=-67.39..-1.48 [-92.3860..-42.0224] | it/evals=465/1074 eff=46.0396% N=64 Z=-75.8(0.00%) | Like=-64.18..-1.48 [-92.3860..-42.0224] | it/evals=468/1074 eff=46.3366% N=64 Z=-70.1(0.00%) | Like=-54.53..-1.48 [-92.3860..-42.0224] | it/evals=474/1202 eff=41.6520% N=64 Z=-61.5(0.00%) | Like=-49.47..-1.48 [-92.3860..-42.0224] | it/evals=480/1202 eff=42.1793% N=64 Z=-57.8(0.00%) | Like=-46.40..-1.48 [-92.3860..-42.0224] | it/evals=486/1202 eff=42.7065% N=64 Z=-54.4(0.00%) | Like=-43.50..-1.39 [-92.3860..-42.0224] | it/evals=492/1202 eff=43.2337% N=64 Z=-48.9(0.00%) | Like=-37.16..-0.90 [-40.5186..-18.1130] | it/evals=498/1202 eff=43.7610% N=64 Z=-45.5(0.00%) | Like=-33.14..-0.90 [-40.5186..-18.1130] | it/evals=504/1202 eff=44.2882% N=64 Z=-41.0(0.00%) | Like=-29.10..-0.90 [-40.5186..-18.1130] | it/evals=510/1202 eff=44.8155% N=64 Z=-37.6(0.00%) | Like=-25.58..-0.90 [-40.5186..-18.1130] | it/evals=516/1202 eff=45.3427% N=64 Z=-33.7(0.00%) | Like=-22.16..-0.15 [-40.5186..-18.1130] | it/evals=522/1202 eff=45.8699% N=64 Z=-32.6(0.00%) | Like=-21.09..-0.10 [-40.5186..-18.1130] | it/evals=525/1202 eff=46.1336% N=64 Z=-31.7(0.00%) | Like=-20.80..-0.10 [-40.5186..-18.1130] | it/evals=528/1217 eff=45.7936% N=64 Z=-29.7(0.00%) | Like=-18.32..-0.10 [-40.5186..-18.1130] | it/evals=534/1217 eff=46.3140% N=64 Z=-28.3(0.00%) | Like=-17.39..-0.10 [-18.0267..-8.1755] | it/evals=540/1226 eff=46.4716% N=64 Z=-27.4(0.00%) | Like=-16.54..-0.10 [-18.0267..-8.1755] | it/evals=546/1235 eff=46.6268% N=64 Z=-26.6(0.00%) | Like=-15.76..-0.10 [-18.0267..-8.1755] | it/evals=552/1249 eff=46.5823% N=64 Z=-26.0(0.00%) | Like=-13.59..-0.10 [-18.0267..-8.1755] | it/evals=555/1249 eff=46.8354% N=64 Z=-24.9(0.00%) | Like=-13.52..-0.10 [-18.0267..-8.1755] | it/evals=558/1264 eff=46.5000% N=64 Z=-23.6(0.00%) | Like=-12.01..-0.10 [-18.0267..-8.1755] | it/evals=564/1264 eff=47.0000% N=64 Z=-22.4(0.00%) | Like=-11.27..-0.10 [-18.0267..-8.1755] | it/evals=570/1373 eff=43.5447% N=64 Z=-21.7(0.00%) | Like=-10.46..-0.00 [-18.0267..-8.1755] | it/evals=576/1373 eff=44.0031% N=64 Z=-20.9(0.01%) | Like=-9.74..-0.00 [-18.0267..-8.1755] | it/evals=582/1373 eff=44.4614% N=64 Z=-20.4(0.01%) | Like=-8.52..-0.00 [-18.0267..-8.1755] | it/evals=585/1373 eff=44.6906% N=64 Z=-19.8(0.02%) | Like=-8.26..-0.00 [-18.0267..-8.1755] | it/evals=588/1373 eff=44.9198% N=64 Z=-18.9(0.06%) | Like=-7.18..-0.00 [-8.1724..-3.9366] | it/evals=594/1373 eff=45.3782% N=64 Z=-18.1(0.14%) | Like=-6.81..-0.00 [-8.1724..-3.9366] | it/evals=600/1373 eff=45.8365% N=64 Z=-17.6(0.24%) | Like=-6.49..-0.00 [-8.1724..-3.9366] | it/evals=606/1373 eff=46.2949% N=64 Z=-17.2(0.38%) | Like=-6.15..-0.00 [-8.1724..-3.9366] | it/evals=612/1373 eff=46.7532% N=64 Z=-17.0(0.45%) | Like=-6.14..-0.00 [-8.1724..-3.9366] | it/evals=615/1373 eff=46.9824% N=64 Z=-16.8(0.51%) | Like=-5.96..-0.00 [-8.1724..-3.9366] | it/evals=618/1373 eff=47.2116% N=64 Z=-16.5(0.66%) | Like=-5.47..-0.00 [-8.1724..-3.9366] | it/evals=624/1389 eff=47.0943% N=64 Z=-16.2(0.95%) | Like=-4.95..-0.00 [-8.1724..-3.9366] | it/evals=630/1401 eff=47.1204% N=64 Z=-15.8(1.27%) | Like=-4.52..-0.00 [-8.1724..-3.9366] | it/evals=636/1510 eff=43.9834% N=64 Z=-15.4(2.01%) | Like=-3.77..-0.00 [-3.8031..-2.2559] | it/evals=642/1510 eff=44.3983% N=64 Z=-15.0(3.08%) | Like=-3.55..-0.00 [-3.8031..-2.2559] | it/evals=648/1510 eff=44.8133% N=64 Z=-14.7(4.12%) | Like=-3.36..-0.00 [-3.8031..-2.2559] | it/evals=654/1510 eff=45.2282% N=64 Z=-14.4(5.69%) | Like=-3.01..-0.00 [-3.8031..-2.2559] | it/evals=660/1510 eff=45.6432% N=64 Z=-14.1(7.42%) | Like=-2.79..-0.00 [-3.8031..-2.2559] | it/evals=666/1510 eff=46.0581% N=64 Z=-13.9(9.21%) | Like=-2.64..-0.00 [-3.8031..-2.2559] | it/evals=672/1510 eff=46.4730% N=64 Z=-13.8(10.26%) | Like=-2.59..-0.00 [-3.8031..-2.2559] | it/evals=675/1510 eff=46.6805% N=64 Z=-13.7(10.91%) | Like=-2.53..-0.00 [-3.8031..-2.2559] | it/evals=678/1510 eff=46.8880% N=64 Z=-13.6(12.43%) | Like=-2.37..-0.00 [-3.8031..-2.2559] | it/evals=684/1510 eff=47.3029% N=64 Z=-13.4(14.76%) | Like=-2.10..-0.00 [-2.2114..-1.1496] | it/evals=690/1605 eff=44.7761% N=64 Z=-13.3(16.68%) | Like=-1.88..-0.00 [-2.2114..-1.1496] | it/evals=696/1605 eff=45.1655% N=64 Z=-13.1(19.32%) | Like=-1.78..-0.00 [-2.2114..-1.1496] | it/evals=702/1605 eff=45.5548% N=64 Z=-13.0(22.22%) | Like=-1.62..-0.00 [-2.2114..-1.1496] | it/evals=708/1605 eff=45.9442% N=64 Z=-12.9(24.61%) | Like=-1.57..-0.00 [-2.2114..-1.1496] | it/evals=714/1605 eff=46.3335% N=64 Z=-12.8(27.65%) | Like=-1.42..-0.00 [-2.2114..-1.1496] | it/evals=720/1605 eff=46.7229% N=64 Z=-12.7(30.64%) | Like=-1.24..-0.00 [-2.2114..-1.1496] | it/evals=726/1605 eff=47.1123% N=64 Z=-12.6(34.09%) | Like=-1.14..-0.00 [-1.1411..-0.5071] | it/evals=732/1733 eff=43.8586% N=64 Z=-12.5(35.79%) | Like=-1.12..-0.00 [-1.1411..-0.5071] | it/evals=735/1733 eff=44.0383% N=64 Z=-12.5(37.55%) | Like=-1.07..-0.00 [-1.1411..-0.5071] | it/evals=738/1733 eff=44.2181% N=64 Z=-12.4(40.90%) | Like=-0.86..-0.00 [-1.1411..-0.5071] | it/evals=744/1733 eff=44.5776% N=64 Z=-12.3(44.16%) | Like=-0.82..-0.00 [-1.1411..-0.5071] | it/evals=750/1733 eff=44.9371% N=64 Z=-12.2(47.44%) | Like=-0.73..-0.00 [-1.1411..-0.5071] | it/evals=756/1733 eff=45.2966% N=64 Z=-12.2(50.70%) | Like=-0.66..-0.00 [-1.1411..-0.5071] | it/evals=762/1733 eff=45.6561% N=64 Z=-12.1(52.58%) | Like=-0.64..-0.00 [-1.1411..-0.5071] | it/evals=765/1733 eff=45.8358% N=64 Z=-12.1(54.15%) | Like=-0.61..-0.00 [-1.1411..-0.5071] | it/evals=768/1733 eff=46.0156% N=64 Z=-12.1(57.35%) | Like=-0.55..-0.00 [-1.1411..-0.5071] | it/evals=774/1733 eff=46.3751% N=64 Z=-12.0(60.43%) | Like=-0.49..-0.00 [-0.4911..-0.2434] | it/evals=780/1750 eff=46.2633% N=64 Z=-12.0(63.00%) | Like=-0.48..-0.00 [-0.4911..-0.2434] | it/evals=786/1862 eff=43.7152% N=64 Z=-11.9(65.72%) | Like=-0.42..-0.00 [-0.4911..-0.2434] | it/evals=792/1862 eff=44.0489% N=64 Z=-11.9(66.89%) | Like=-0.41..-0.00 [-0.4911..-0.2434] | it/evals=795/1862 eff=44.2158% N=64 Z=-11.9(68.13%) | Like=-0.36..-0.00 [-0.4911..-0.2434] | it/evals=798/1862 eff=44.3826% N=64 Z=-11.9(70.44%) | Like=-0.33..-0.00 [-0.4911..-0.2434] | it/evals=804/1862 eff=44.7164% N=64 Z=-11.8(72.73%) | Like=-0.30..-0.00 [-0.4911..-0.2434] | it/evals=810/1873 eff=44.7761% N=64 Z=-11.8(74.96%) | Like=-0.28..-0.00 [-0.4911..-0.2434] | it/evals=816/1873 eff=45.1078% N=64 Z=-11.8(76.96%) | Like=-0.26..-0.00 [-0.4911..-0.2434] | it/evals=822/1892 eff=44.9672% N=64 Z=-11.8(77.90%) | Like=-0.24..-0.00 [-0.2385..-0.1266] | it/evals=825/1905 eff=44.8126% N=64 Z=-11.7(78.74%) | Like=-0.23..-0.00 [-0.2385..-0.1266] | it/evals=828/1914 eff=44.7568% N=64 Z=-11.7(80.46%) | Like=-0.21..-0.00 [-0.2385..-0.1266] | it/evals=834/1927 eff=44.7665% N=64 Z=-11.7(82.11%) | Like=-0.19..-0.00 [-0.2385..-0.1266] | it/evals=840/1940 eff=44.7761% N=64 Z=-11.7(83.59%) | Like=-0.18..-0.00 [-0.2385..-0.1266] | it/evals=846/1958 eff=44.6674% N=64 Z=-11.7(84.89%) | Like=-0.17..-0.00 [-0.2385..-0.1266] | it/evals=852/1976 eff=44.5607% N=64 Z=-11.7(86.13%) | Like=-0.15..-0.00 [-0.2385..-0.1266] | it/evals=858/1976 eff=44.8745% N=64 Z=-11.6(87.27%) | Like=-0.14..-0.00 [-0.2385..-0.1266] | it/evals=864/2001 eff=44.6051% N=64 Z=-11.6(88.33%) | Like=-0.12..-0.00 [-0.1265..-0.0588] | it/evals=870/2001 eff=44.9148% N=64 Z=-11.6(89.31%) | Like=-0.11..-0.00 [-0.1265..-0.0588] | it/evals=876/2014 eff=44.9231% N=64 Z=-11.6(90.21%) | Like=-0.10..-0.00 [-0.1265..-0.0588] | it/evals=882/2027 eff=44.9312% N=64 Z=-11.6(90.65%) | Like=-0.09..-0.00 [-0.1265..-0.0588] | it/evals=885/2027 eff=45.0841% N=64 Z=-11.6(91.07%) | Like=-0.09..-0.00 [-0.1265..-0.0588] | it/evals=888/2040 eff=44.9393% N=64 Z=-11.6(91.82%) | Like=-0.09..-0.00 [-0.1265..-0.0588] | it/evals=894/2050 eff=45.0151% N=64 Z=-11.6(92.53%) | Like=-0.08..-0.00 [-0.1265..-0.0588] | it/evals=900/2063 eff=45.0225% N=64 Z=-11.6(93.18%) | Like=-0.07..-0.00 [-0.1265..-0.0588] | it/evals=906/2174 eff=42.9384% N=64 Z=-11.6(93.77%) | Like=-0.06..-0.00 [-0.1265..-0.0588] | it/evals=912/2174 eff=43.2227% N=64 Z=-11.6(94.05%) | Like=-0.06..-0.00 [-0.0576..-0.0253] | it/evals=915/2174 eff=43.3649% N=64 Z=-11.6(94.31%) | Like=-0.06..-0.00 [-0.0576..-0.0253] | it/evals=918/2174 eff=43.5071% N=64 Z=-11.6(94.80%) | Like=-0.05..-0.00 [-0.0576..-0.0253] | it/evals=924/2174 eff=43.7915% N=64 Z=-11.6(95.26%) | Like=-0.04..-0.00 [-0.0576..-0.0253] | it/evals=930/2174 eff=44.0758% N=64 Z=-11.5(95.68%) | Like=-0.04..-0.00 [-0.0576..-0.0253] | it/evals=936/2174 eff=44.3602% N=64 Z=-11.5(96.06%) | Like=-0.03..-0.00 [-0.0576..-0.0253] | it/evals=942/2174 eff=44.6445% N=64 Z=-11.5(96.24%) | Like=-0.03..-0.00 [-0.0576..-0.0253] | it/evals=945/2174 eff=44.7867% N=64 Z=-11.5(96.41%) | Like=-0.03..-0.00 [-0.0576..-0.0253] | it/evals=948/2174 eff=44.9289% N=64 Z=-11.5(96.72%) | Like=-0.03..-0.00 [-0.0576..-0.0253] | it/evals=954/2191 eff=44.8519% N=64 Z=-11.5(97.01%) | Like=-0.03..-0.00 [-0.0576..-0.0253] | it/evals=960/2209 eff=44.7552% N=64 Z=-11.5(97.28%) | Like=-0.02..-0.00 [-0.0244..-0.0144]*| it/evals=966/2333 eff=42.5738% N=64 Z=-11.5(97.52%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=972/2333 eff=42.8383% N=64 Z=-11.5(97.74%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=978/2333 eff=43.1027% N=64 Z=-11.5(97.94%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=984/2333 eff=43.3671% N=64 Z=-11.5(98.12%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=990/2333 eff=43.6316% N=64 Z=-11.5(98.29%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=996/2333 eff=43.8960% N=64 Z=-11.5(98.44%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=1002/2333 eff=44.1604% N=64 Z=-11.5(98.58%) | Like=-0.02..-0.00 [-0.0242..-0.0140] | it/evals=1008/2333 eff=44.4249% N=64 Z=-11.5(98.71%) | Like=-0.01..-0.00 [-0.0137..-0.0067]*| it/evals=1014/2333 eff=44.6893% N=64 Z=-11.5(98.82%) | Like=-0.01..-0.00 [-0.0129..-0.0062]*| it/evals=1020/2429 eff=43.1290% N=64 Z=-11.5(98.93%) | Like=-0.01..-0.00 [-0.0111..-0.0058]*| it/evals=1026/2429 eff=43.3827% N=64 [ultranest] Explored until L=-8e-05 [ultranest] Likelihood function evaluations: 2429 [ultranest] logZ = -11.5 +- 0.2693 [ultranest] Effective samples strategy wants to improve: -11.13..-0.00 (ESS = 267.4, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.48+-0.26 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 62 minimum live points (dlogz from 0.20 to 0.65, need <0.5) [ultranest] logZ error budget: single: 0.40 bs:0.27 tail:0.01 total:0.27 required:<0.50 [ultranest] Widening from 64 to 128 live points before L=-1e+01... [ultranest] Will add 64 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) | Like=-1213.22..-0.00 [-1213.2190..-0.0011] | it/evals=280/2433 eff=0.0000% N=64 Z=-1037.1(0.00%) | Like=-1001.43..-0.00 [-1213.2190..-0.0011] | it/evals=294/2433 eff=25.0000% N=65 Z=-597.4(0.00%) | Like=-583.16..-0.00 [-1213.2190..-0.0011] | it/evals=333/2434 eff=40.0000% N=66 Z=-284.4(0.00%) | Like=-265.94..-0.00 [-1213.2190..-0.0011] | it/evals=381/2547 eff=3.3898% N=66 Z=-189.7(0.00%) | Like=-177.08..-0.00 [-1213.2190..-0.0011] | it/evals=407/2547 eff=5.0847% N=67 Z=-187.5(0.00%) | Like=-171.06..-0.00 [-1213.2190..-0.0011] | it/evals=408/2547 eff=5.9322% N=67 Z=-150.9(0.00%) | Like=-136.96..-0.00 [-1213.2190..-0.0011] | it/evals=425/2547 eff=7.6271% N=68 Z=-118.6(0.00%) | Like=-107.56..-0.00 [-1213.2190..-0.0011] | it/evals=444/2547 eff=10.1695% N=71 Z=-109.9(0.00%) | Like=-98.44..-0.00 [-1213.2190..-0.0011] | it/evals=450/2547 eff=13.5593% N=74 Z=-102.2(0.00%) | Like=-91.35..-0.00 [-1213.2190..-0.0011] | it/evals=456/2547 eff=16.1017% N=75 Z=-90.9(0.00%) | Like=-78.43..-0.00 [-1213.2190..-0.0011] | it/evals=465/2547 eff=17.7966% N=76 Z=-76.0(0.00%) | Like=-64.44..-0.00 [-1213.2190..-0.0011] | it/evals=480/2669 eff=10.8333% N=78 Z=-74.2(0.00%) | Like=-62.51..-0.00 [-1213.2190..-0.0011] | it/evals=483/2669 eff=11.6667% N=79 Z=-66.7(0.00%) | Like=-55.18..-0.00 [-1213.2190..-0.0011] | it/evals=492/2669 eff=14.1667% N=80 Z=-60.8(0.00%) | Like=-49.28..-0.00 [-1213.2190..-0.0011] | it/evals=502/2669 eff=15.8333% N=81 Z=-59.9(0.00%) | Like=-48.22..-0.00 [-1213.2190..-0.0011] | it/evals=504/2669 eff=16.2500% N=82 Z=-57.2(0.00%) | Like=-45.81..-0.00 [-1213.2190..-0.0011] | it/evals=510/2669 eff=17.5000% N=84 Z=-54.4(0.00%) | Like=-42.31..-0.00 [-1213.2190..-0.0011] | it/evals=516/2669 eff=18.3333% N=85 Z=-51.1(0.00%) | Like=-38.41..-0.00 [-1213.2190..-0.0011] | it/evals=521/2669 eff=19.5833% N=86 Z=-50.2(0.00%) | Like=-37.47..-0.00 [-1213.2190..-0.0011] | it/evals=522/2669 eff=20.0000% N=87 Z=-42.4(0.00%) | Like=-30.47..-0.00 [-1213.2190..-0.0011] | it/evals=540/2669 eff=24.5833% N=91 Z=-42.0(0.00%) | Like=-29.46..-0.00 [-1213.2190..-0.0011] | it/evals=541/2669 eff=25.0000% N=92 Z=-39.9(0.00%) | Like=-28.19..-0.00 [-1213.2190..-0.0011] | it/evals=546/2669 eff=25.8333% N=92 Z=-37.9(0.00%) | Like=-26.55..-0.00 [-1213.2190..-0.0011] | it/evals=552/2669 eff=28.3333% N=95 Z=-36.6(0.00%) | Like=-24.94..-0.00 [-1213.2190..-0.0011] | it/evals=558/2795 eff=20.2186% N=97 Z=-35.3(0.00%) | Like=-23.99..-0.00 [-1213.2190..-0.0011] | it/evals=563/2795 eff=21.5847% N=99 Z=-35.1(0.00%) | Like=-23.59..-0.00 [-1213.2190..-0.0011] | it/evals=564/2795 eff=21.8579% N=99 Z=-31.6(0.00%) | Like=-20.34..-0.00 [-1213.2190..-0.0011] | it/evals=582/2795 eff=25.1366% N=103 Z=-29.6(0.00%) | Like=-18.37..-0.00 [-1213.2190..-0.0011] | it/evals=594/2795 eff=27.0492% N=103 Z=-28.9(0.00%) | Like=-17.65..-0.00 [-1213.2190..-0.0011] | it/evals=600/2795 eff=27.5956% N=103 Z=-27.9(0.00%) | Like=-16.57..-0.00 [-1213.2190..-0.0011] | it/evals=610/2795 eff=29.7814% N=108 Z=-27.1(0.00%) | Like=-15.91..-0.00 [-1213.2190..-0.0011] | it/evals=618/2795 eff=31.4208% N=113 Z=-26.5(0.00%) | Like=-15.14..-0.00 [-1213.2190..-0.0011] | it/evals=624/2923 eff=24.2915% N=114 Z=-25.8(0.00%) | Like=-13.59..-0.00 [-1213.2190..-0.0011] | it/evals=630/2923 eff=25.5061% N=115 Z=-24.7(0.00%) | Like=-12.77..-0.00 [-1213.2190..-0.0011] | it/evals=637/2923 eff=26.1134% N=117 Z=-24.0(0.00%) | Like=-12.37..-0.00 [-1213.2190..-0.0011] | it/evals=642/2923 eff=27.1255% N=118 Z=-23.4(0.00%) | Like=-11.85..-0.00 [-1213.2190..-0.0011] | it/evals=648/2923 eff=28.3401% N=122 Z=-22.8(0.00%) | Like=-11.29..-0.00 [-1213.2190..-0.0011] | it/evals=654/2923 eff=29.5547% N=125 Z=-21.9(0.00%) | Like=-10.40..-0.00 [-1213.2190..-0.0011] | it/evals=666/2923 eff=30.9717% N=128 Z=-21.4(0.00%) | Like=-9.76..-0.00 [-1213.2190..-0.0011] | it/evals=672/2923 eff=31.1741% N=128 Z=-20.3(0.01%) | Like=-8.41..-0.00 [-1213.2190..-0.0011] | it/evals=684/2923 eff=32.5911% N=128 Z=-19.8(0.02%) | Like=-8.05..-0.00 [-1213.2190..-0.0011] | it/evals=690/2923 eff=32.9960% N=128 Z=-19.3(0.04%) | Like=-7.63..-0.00 [-1213.2190..-0.0011] | it/evals=696/2923 eff=34.0081% N=128 Z=-17.9(0.17%) | Like=-6.48..-0.00 [-1213.2190..-0.0011] | it/evals=720/2923 eff=35.8300% N=128 Z=-17.7(0.22%) | Like=-6.24..-0.00 [-1213.2190..-0.0011] | it/evals=725/2923 eff=36.0324% N=128 Z=-17.4(0.30%) | Like=-6.07..-0.00 [-1213.2190..-0.0011] | it/evals=732/2935 eff=35.5731% N=128 Z=-17.0(0.40%) | Like=-5.75..-0.00 [-1213.2190..-0.0011] | it/evals=744/2945 eff=36.4341% N=128 Z=-16.6(0.57%) | Like=-5.43..-0.00 [-1213.2190..-0.0011] | it/evals=755/2945 eff=37.2093% N=128 Z=-16.0(1.04%) | Like=-4.42..-0.00 [-1213.2190..-0.0011] | it/evals=774/3060 eff=31.8542% N=128 Z=-15.8(1.31%) | Like=-4.03..-0.00 [-1213.2190..-0.0011] | it/evals=780/3060 eff=32.4881% N=128 Z=-15.6(1.52%) | Like=-3.85..-0.00 [-1213.2190..-0.0011] | it/evals=784/3060 eff=32.8051% N=128 Z=-15.3(2.07%) | Like=-3.67..-0.00 [-1213.2190..-0.0011] | it/evals=792/3060 eff=33.1220% N=128 Z=-14.9(3.13%) | Like=-3.36..-0.00 [-1213.2190..-0.0011] | it/evals=804/3060 eff=33.9144% N=128 Z=-14.8(3.79%) | Like=-3.08..-0.00 [-1213.2190..-0.0011] | it/evals=810/3060 eff=34.3899% N=128 Z=-14.7(4.08%) | Like=-3.06..-0.00 [-1213.2190..-0.0011] | it/evals=813/3060 eff=34.7068% N=128 Z=-14.0(8.04%) | Like=-2.52..-0.00 [-1213.2190..-0.0011] | it/evals=843/3060 eff=36.1331% N=128 Z=-13.8(9.22%) | Like=-2.35..-0.00 [-1213.2190..-0.0011] | it/evals=852/3060 eff=36.6086% N=128 Z=-13.6(11.56%) | Like=-2.13..-0.00 [-1213.2190..-0.0011] | it/evals=864/3060 eff=37.8764% N=128 Z=-13.5(13.17%) | Like=-2.04..-0.00 [-1213.2190..-0.0011] | it/evals=872/3060 eff=38.5103% N=128 Z=-13.4(14.01%) | Like=-1.95..-0.00 [-1213.2190..-0.0011] | it/evals=876/3060 eff=38.9857% N=128 Z=-13.4(15.19%) | Like=-1.91..-0.00 [-1213.2190..-0.0011] | it/evals=882/3169 eff=33.7838% N=128 Z=-13.3(16.71%) | Like=-1.85..-0.00 [-1213.2190..-0.0011] | it/evals=888/3169 eff=34.1892% N=128 Z=-13.1(19.44%) | Like=-1.70..-0.00 [-1213.2190..-0.0011] | it/evals=900/3169 eff=35.0000% N=128 Z=-13.1(19.73%) | Like=-1.68..-0.00 [-1213.2190..-0.0011] | it/evals=901/3169 eff=35.1351% N=128 Z=-13.0(22.47%) | Like=-1.59..-0.00 [-1213.2190..-0.0011] | it/evals=912/3169 eff=35.6757% N=128 Z=-12.9(23.72%) | Like=-1.54..-0.00 [-1213.2190..-0.0011] | it/evals=918/3169 eff=36.0811% N=128 Z=-12.8(27.35%) | Like=-1.40..-0.00 [-1213.2190..-0.0011] | it/evals=932/3169 eff=37.1622% N=128 Z=-12.8(28.51%) | Like=-1.33..-0.00 [-1213.2190..-0.0011] | it/evals=936/3169 eff=37.4324% N=128 Z=-12.7(30.17%) | Like=-1.24..-0.00 [-1213.2190..-0.0011] | it/evals=942/3169 eff=37.7027% N=128 Z=-12.6(35.63%) | Like=-1.06..-0.00 [-1213.2190..-0.0011] | it/evals=962/3169 eff=38.7838% N=128 Z=-12.5(36.83%) | Like=-0.99..-0.00 [-1213.2190..-0.0011] | it/evals=966/3169 eff=39.1892% N=128 Z=-12.5(38.44%) | Like=-0.95..-0.00 [-1213.2190..-0.0011] | it/evals=972/3169 eff=39.8649% N=128 Z=-12.4(43.45%) | Like=-0.77..-0.00 [-1213.2190..-0.0011] | it/evals=990/3291 eff=35.1508% N=128 Z=-12.4(43.79%) | Like=-0.77..-0.00 [-1213.2190..-0.0011] | it/evals=991/3291 eff=35.2668% N=128 Z=-12.3(46.96%) | Like=-0.73..-0.00 [-1213.2190..-0.0011] | it/evals=1002/3291 eff=35.8469% N=128 Z=-12.3(48.61%) | Like=-0.68..-0.00 [-1213.2190..-0.0011] | it/evals=1008/3291 eff=36.0789% N=128 Z=-12.2(53.70%) | Like=-0.59..-0.00 [-1213.2190..-0.0011] | it/evals=1026/3291 eff=37.1230% N=128 Z=-12.1(55.38%) | Like=-0.56..-0.00 [-1213.2190..-0.0011] | it/evals=1032/3291 eff=37.4710% N=128 Z=-12.0(59.99%) | Like=-0.49..-0.00 [-1213.2190..-0.0011] | it/evals=1050/3291 eff=38.7471% N=128 Z=-12.0(62.73%) | Like=-0.47..-0.00 [-1213.2190..-0.0011] | it/evals=1062/3291 eff=39.2111% N=128 Z=-12.0(64.13%) | Like=-0.44..-0.00 [-1213.2190..-0.0011] | it/evals=1068/3291 eff=39.6752% N=128 Z=-12.0(65.48%) | Like=-0.42..-0.00 [-1213.2190..-0.0011] | it/evals=1074/3419 eff=34.9495% N=128 Z=-11.9(67.53%) | Like=-0.40..-0.00 [-1213.2190..-0.0011] | it/evals=1084/3419 eff=35.3535% N=128 Z=-11.9(67.96%) | Like=-0.39..-0.00 [-1213.2190..-0.0011] | it/evals=1086/3419 eff=35.5556% N=128 Z=-11.9(69.19%) | Like=-0.36..-0.00 [-1213.2190..-0.0011] | it/evals=1092/3419 eff=36.1616% N=128 Z=-11.9(72.66%) | Like=-0.32..-0.00 [-1213.2190..-0.0011] | it/evals=1110/3419 eff=36.9697% N=128 Z=-11.8(74.75%) | Like=-0.29..-0.00 [-1213.2190..-0.0011] | it/evals=1122/3419 eff=37.5758% N=128 Z=-11.8(77.97%) | Like=-0.26..-0.00 [-1213.2190..-0.0011] | it/evals=1142/3419 eff=38.7879% N=128 Z=-11.7(82.11%) | Like=-0.19..-0.00 [-1213.2190..-0.0011] | it/evals=1172/3438 eff=39.4450% N=128 Z=-11.7(82.62%) | Like=-0.19..-0.00 [-1213.2190..-0.0011] | it/evals=1176/3563 eff=35.3616% N=128 Z=-11.7(84.03%) | Like=-0.18..-0.00 [-1213.2190..-0.0011] | it/evals=1188/3563 eff=35.5379% N=128 Z=-11.7(85.35%) | Like=-0.16..-0.00 [-1213.2190..-0.0011] | it/evals=1200/3563 eff=36.2434% N=128 Z=-11.7(85.45%) | Like=-0.16..-0.00 [-1213.2190..-0.0011] | it/evals=1201/3563 eff=36.3316% N=128 Z=-11.7(85.96%) | Like=-0.16..-0.00 [-1213.2190..-0.0011] | it/evals=1206/3563 eff=36.4198% N=128 Z=-11.7(86.55%) | Like=-0.15..-0.00 [-1213.2190..-0.0011] | it/evals=1212/3563 eff=36.5961% N=128 Z=-11.7(88.28%) | Like=-0.12..-0.00 [-1213.2190..-0.0011] | it/evals=1231/3563 eff=37.3016% N=128 Z=-11.7(88.70%) | Like=-0.12..-0.00 [-1213.2190..-0.0011] | it/evals=1236/3563 eff=37.4780% N=128 Z=-11.7(89.19%) | Like=-0.11..-0.00 [-1213.2190..-0.0011] | it/evals=1242/3563 eff=37.9189% N=128 Z=-11.6(90.10%) | Like=-0.10..-0.00 [-1213.2190..-0.0011] | it/evals=1254/3563 eff=38.4480% N=128 Z=-11.6(90.54%) | Like=-0.10..-0.00 [-1213.2190..-0.0011] | it/evals=1260/3563 eff=38.7125% N=128 Z=-11.6(91.73%) | Like=-0.08..-0.00 [-1213.2190..-0.0011] | it/evals=1278/3563 eff=39.3298% N=128 Z=-11.6(93.10%) | Like=-0.07..-0.00 [-1213.2190..-0.0011] | it/evals=1302/3576 eff=39.9303% N=128 Z=-11.6(94.50%) | Like=-0.05..-0.00 [-1213.2190..-0.0011] | it/evals=1332/3622 eff=39.6479% N=128 Z=-11.6(94.98%) | Like=-0.05..-0.00 [-1213.2190..-0.0011] | it/evals=1344/3634 eff=40.0000% N=128 Z=-11.6(95.10%) | Like=-0.04..-0.00 [-1213.2190..-0.0011] | it/evals=1347/3634 eff=40.1660% N=128 Z=-11.6(95.21%) | Like=-0.04..-0.00 [-1213.2190..-0.0011] | it/evals=1350/3750 eff=36.7903% N=128 Z=-11.6(95.63%) | Like=-0.04..-0.00 [-1213.2190..-0.0011] | it/evals=1362/3750 eff=37.3202% N=128 Z=-11.6(96.07%) | Like=-0.03..-0.00 [-1213.2190..-0.0011] | it/evals=1376/3750 eff=37.8501% N=128 Z=-11.6(96.19%) | Like=-0.03..-0.00 [-1213.2190..-0.0011] | it/evals=1380/3750 eff=38.1529% N=128 Z=-11.6(96.83%) | Like=-0.03..-0.00 [-1213.2190..-0.0011] | it/evals=1404/3750 eff=38.8342% N=128 Z=-11.6(96.86%) | Like=-0.03..-0.00 [-1213.2190..-0.0011] | it/evals=1405/3750 eff=38.9099% N=128 Z=-11.6(97.24%) | Like=-0.03..-0.00 [-1213.2190..-0.0011] | it/evals=1422/3750 eff=39.6669% N=128 Z=-11.6(97.53%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1436/3750 eff=40.0454% N=128 Z=-11.6(97.81%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1452/3750 eff=40.4996% N=128 Z=-11.6(97.91%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1458/3750 eff=40.7267% N=128 Z=-11.6(98.18%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1476/3767 eff=40.6577% N=128 Z=-11.6(98.27%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1482/3767 eff=40.8819% N=128 Z=-11.6(98.42%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1494/3786 eff=40.8990% N=128 Z=-11.6(98.49%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1500/3801 eff=40.7434% N=128 Z=-11.6(98.56%) | Like=-0.02..-0.00 [-1213.2190..-0.0011] | it/evals=1506/3816 eff=40.4470% N=128 Z=-11.5(98.75%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1524/3832 eff=40.4847% N=128 Z=-11.5(98.77%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1526/3832 eff=40.5560% N=128 Z=-11.5(98.81%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1530/3958 eff=37.4755% N=128 Z=-11.5(98.91%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1542/3958 eff=37.8679% N=128 Z=-11.5(99.01%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1554/3958 eff=38.3911% N=128 Z=-11.5(99.05%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1560/3958 eff=38.7835% N=128 Z=-11.5(99.10%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1566/3958 eff=39.1759% N=128 Z=-11.5(99.14%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1572/3958 eff=39.5683% N=128 Z=-11.5(99.18%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1578/3958 eff=39.9608% N=128 Z=-11.5(99.21%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1584/3958 eff=40.3532% N=128 Z=-11.5(99.25%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1590/3958 eff=40.7456% N=128 Z=-11.5(99.28%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1596/3958 eff=41.1380% N=128 Z=-11.5(99.32%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1602/3958 eff=41.5304% N=128 Z=-11.5(99.35%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1608/4069 eff=39.0854% N=128 Z=-11.5(99.37%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1613/4069 eff=39.3902% N=128 Z=-11.5(99.38%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1614/4069 eff=39.4512% N=128 Z=-11.5(99.41%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1620/4069 eff=39.8171% N=128 Z=-11.5(99.43%) | Like=-0.01..-0.00 [-1213.2190..-0.0011] | it/evals=1626/4069 eff=40.1829% N=128 Z=-11.5(99.46%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1632/4069 eff=40.5488% N=128 Z=-11.5(99.48%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1638/4069 eff=40.9146% N=128 Z=-11.5(99.51%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1644/4069 eff=41.2805% N=128 Z=-11.5(99.53%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1650/4082 eff=41.3188% N=128 Z=-11.5(99.55%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1656/4082 eff=41.6818% N=128 Z=-11.5(99.57%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1662/4108 eff=41.3937% N=128 Z=-11.5(99.59%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1668/4108 eff=41.7510% N=128 Z=-11.5(99.61%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1674/4125 eff=41.6863% N=128 Z=-11.5(99.63%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1680/4125 eff=42.0401% N=128 Z=-11.5(99.65%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1686/4135 eff=42.1454% N=128 Z=-11.5(99.66%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1692/4146 eff=42.2248% N=128 Z=-11.5(99.68%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1698/4166 eff=42.0841% N=128 Z=-11.5(99.68%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1700/4166 eff=42.1992% N=128 Z=-11.5(99.69%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1704/4166 eff=42.4295% N=128 Z=-11.5(99.71%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1710/4284 eff=40.0539% N=128 Z=-11.5(99.72%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1716/4284 eff=40.3774% N=128 Z=-11.5(99.73%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1722/4284 eff=40.7008% N=128 Z=-11.5(99.74%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1728/4284 eff=41.0243% N=128 Z=-11.5(99.75%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1729/4284 eff=41.0782% N=128 Z=-11.5(99.76%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1734/4284 eff=41.3477% N=128 Z=-11.5(99.77%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1740/4284 eff=41.6712% N=128 Z=-11.5(99.78%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1746/4284 eff=41.9946% N=128 Z=-11.5(99.79%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1752/4284 eff=42.3181% N=128 Z=-11.5(99.80%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1758/4284 eff=42.6415% N=128 Z=-11.5(99.81%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1764/4284 eff=42.9650% N=128 Z=-11.5(99.82%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1770/4284 eff=43.2884% N=128 Z=-11.5(99.82%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1776/4394 eff=41.1705% N=128 Z=-11.5(99.83%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1782/4394 eff=41.4758% N=128 Z=-11.5(99.84%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1788/4394 eff=41.7812% N=128 Z=-11.5(99.85%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1794/4394 eff=42.0865% N=128 Z=-11.5(99.85%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1800/4394 eff=42.3919% N=128 Z=-11.5(99.86%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1806/4394 eff=42.6972% N=128 Z=-11.5(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1812/4394 eff=43.0025% N=128 Z=-11.5(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1816/4394 eff=43.2061% N=128 Z=-11.5(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1818/4394 eff=43.3079% N=128 Z=-11.5(99.88%) | Like=-0.00..-0.00 [-1213.2190..-0.0011] | it/evals=1824/4394 eff=43.6132% N=128 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 4505 [ultranest] logZ = -11.56 +- 0.3516 [ultranest] Effective samples strategy wants to improve: -10.40..-0.00 (ESS = 519.9, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.17 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 31 minimum live points (dlogz from 0.29 to 0.78, need <0.5) [ultranest] logZ error budget: single: 0.29 bs:0.35 tail:0.00 total:0.35 required:<0.50 [ultranest] Widening from 67 to 256 live points before L=-1e+01... [ultranest] Will add 189 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) | Like=-1213.22..-0.00 [-1213.2190..-0.0010] | it/evals=280/4506 eff=0.0000% N=64 Z=-1037.1(0.00%) | Like=-1001.43..-0.00 [-1213.2190..-0.0010] | it/evals=295/4509 eff=50.0000% N=66 Z=-682.4(0.00%) | Like=-672.78..-0.00 [-1213.2190..-0.0010] | it/evals=328/4512 eff=57.1429% N=68 Z=-238.0(0.00%) | Like=-222.58..-0.00 [-1213.2190..-0.0010] | it/evals=395/4611 eff=5.6604% N=68 Z=-187.5(0.00%) | Like=-171.06..-0.00 [-1213.2190..-0.0010] | it/evals=413/4611 eff=7.5472% N=70 Z=-150.9(0.00%) | Like=-136.96..-0.00 [-1213.2190..-0.0010] | it/evals=430/4611 eff=8.4906% N=72 Z=-119.7(0.00%) | Like=-108.42..-0.00 [-1213.2190..-0.0010] | it/evals=448/4611 eff=10.3774% N=77 Z=-118.4(0.00%) | Like=-107.56..-0.00 [-1213.2190..-0.0010] | it/evals=450/4611 eff=11.3208% N=77 Z=-81.6(0.00%) | Like=-69.50..-0.00 [-1213.2190..-0.0010] | it/evals=480/4611 eff=14.1509% N=84 Z=-66.2(0.00%) | Like=-55.02..-0.00 [-1213.2190..-0.0010] | it/evals=501/4611 eff=18.8679% N=92 Z=-51.9(0.00%) | Like=-40.14..-0.00 [-1213.2190..-0.0010] | it/evals=530/4739 eff=11.5385% N=102 Z=-50.0(0.00%) | Like=-37.47..-0.00 [-1213.2190..-0.0010] | it/evals=534/4739 eff=13.2479% N=106 Z=-43.1(0.00%) | Like=-31.83..-0.00 [-1213.2190..-0.0010] | it/evals=552/4739 eff=15.3846% N=114 Z=-42.0(0.00%) | Like=-30.01..-0.00 [-1213.2190..-0.0010] | it/evals=555/4739 eff=16.2393% N=116 Z=-39.5(0.00%) | Like=-27.98..-0.00 [-1213.2190..-0.0010] | it/evals=564/4739 eff=17.5214% N=116 Z=-36.8(0.00%) | Like=-25.42..-0.00 [-1213.2190..-0.0010] | it/evals=576/4739 eff=19.6581% N=125 Z=-35.4(0.00%) | Like=-23.99..-0.00 [-1213.2190..-0.0010] | it/evals=583/4739 eff=21.3675% N=129 Z=-29.0(0.00%) | Like=-17.70..-0.00 [-1213.2190..-0.0010] | it/evals=624/4855 eff=17.1429% N=139 Z=-28.4(0.00%) | Like=-17.39..-0.00 [-1213.2190..-0.0010] | it/evals=630/4855 eff=17.7143% N=141 Z=-27.9(0.00%) | Like=-16.57..-0.00 [-1213.2190..-0.0010] | it/evals=636/4855 eff=19.1429% N=149 Z=-27.4(0.00%) | Like=-16.19..-0.00 [-1213.2190..-0.0010] | it/evals=642/4855 eff=20.0000% N=153 Z=-26.9(0.00%) | Like=-15.65..-0.00 [-1213.2190..-0.0010] | it/evals=648/4855 eff=20.8571% N=160 Z=-26.5(0.00%) | Like=-15.25..-0.00 [-1213.2190..-0.0010] | it/evals=653/4855 eff=21.4286% N=160 Z=-26.4(0.00%) | Like=-15.15..-0.00 [-1213.2190..-0.0010] | it/evals=654/4855 eff=21.7143% N=160 Z=-25.3(0.00%) | Like=-13.59..-0.00 [-1213.2190..-0.0010] | it/evals=666/4855 eff=23.7143% N=162 Z=-24.2(0.00%) | Like=-12.64..-0.00 [-1213.2190..-0.0010] | it/evals=678/4855 eff=25.1429% N=168 Z=-23.2(0.00%) | Like=-11.68..-0.00 [-1213.2190..-0.0010] | it/evals=690/4855 eff=27.1429% N=176 Z=-22.4(0.00%) | Like=-11.13..-0.00 [-1213.2190..-0.0010] | it/evals=702/4855 eff=30.0000% N=188 Z=-22.1(0.00%) | Like=-10.81..-0.00 [-1213.2190..-0.0010] | it/evals=708/4855 eff=30.5714% N=190 Z=-21.5(0.00%) | Like=-10.06..-0.00 [-1213.2190..-0.0010] | it/evals=720/4983 eff=23.8494% N=191 Z=-21.2(0.00%) | Like=-9.76..-0.00 [-1213.2190..-0.0010] | it/evals=726/4983 eff=24.6862% N=191 Z=-20.9(0.01%) | Like=-9.54..-0.00 [-1213.2190..-0.0010] | it/evals=732/4983 eff=25.1046% N=191 Z=-20.6(0.01%) | Like=-9.07..-0.00 [-1213.2190..-0.0010] | it/evals=738/4983 eff=25.5230% N=191 Z=-19.6(0.02%) | Like=-8.07..-0.00 [-1213.2190..-0.0010] | it/evals=756/4983 eff=26.9874% N=191 Z=-19.0(0.05%) | Like=-7.51..-0.00 [-1213.2190..-0.0010] | it/evals=768/4983 eff=27.6151% N=191 Z=-18.7(0.06%) | Like=-7.26..-0.00 [-1213.2190..-0.0010] | it/evals=774/4983 eff=28.2427% N=191 Z=-18.7(0.06%) | Like=-7.21..-0.00 [-1213.2190..-0.0010] | it/evals=775/4983 eff=28.4519% N=191 Z=-18.3(0.10%) | Like=-6.83..-0.00 [-1213.2190..-0.0010] | it/evals=786/4983 eff=29.0795% N=191 Z=-17.6(0.19%) | Like=-6.27..-0.00 [-1213.2190..-0.0010] | it/evals=804/4983 eff=29.9163% N=191 Z=-17.2(0.29%) | Like=-6.01..-0.00 [-1213.2190..-0.0010] | it/evals=820/4983 eff=30.5439% N=191 Z=-16.7(0.45%) | Like=-5.53..-0.00 [-1213.2190..-0.0010] | it/evals=840/4983 eff=31.7992% N=191 Z=-16.1(0.88%) | Like=-4.59..-0.00 [-1213.2190..-0.0010] | it/evals=867/4983 eff=33.0544% N=191 Z=-14.9(2.72%) | Like=-3.49..-0.00 [-1213.2190..-0.0010] | it/evals=913/5013 eff=35.0394% N=191 Z=-14.4(4.69%) | Like=-2.99..-0.00 [-1213.2190..-0.0010] | it/evals=942/5029 eff=35.6870% N=191 Z=-14.3(5.16%) | Like=-2.89..-0.00 [-1213.2190..-0.0010] | it/evals=948/5029 eff=35.8779% N=191 Z=-14.1(6.50%) | Like=-2.69..-0.00 [-1213.2190..-0.0010] | it/evals=963/5150 eff=29.7674% N=191 Z=-13.9(7.41%) | Like=-2.58..-0.00 [-1213.2190..-0.0010] | it/evals=972/5150 eff=30.2326% N=191 Z=-13.5(11.77%) | Like=-2.11..-0.00 [-1213.2190..-0.0010] | it/evals=1009/5150 eff=31.9380% N=191 Z=-13.4(12.46%) | Like=-2.07..-0.00 [-1213.2190..-0.0010] | it/evals=1014/5150 eff=32.4031% N=191 Z=-13.3(14.16%) | Like=-2.01..-0.00 [-1213.2190..-0.0010] | it/evals=1026/5150 eff=33.3333% N=191 Z=-13.2(15.72%) | Like=-1.91..-0.00 [-1213.2190..-0.0010] | it/evals=1038/5150 eff=33.7984% N=191 Z=-13.0(18.17%) | Like=-1.79..-0.00 [-1213.2190..-0.0010] | it/evals=1054/5150 eff=34.4186% N=191 Z=-13.0(18.46%) | Like=-1.78..-0.00 [-1213.2190..-0.0010] | it/evals=1056/5150 eff=34.5736% N=191 Z=-13.0(19.39%) | Like=-1.72..-0.00 [-1213.2190..-0.0010] | it/evals=1062/5150 eff=35.0388% N=191 Z=-12.8(23.35%) | Like=-1.52..-0.00 [-1213.2190..-0.0010] | it/evals=1086/5150 eff=35.6589% N=191 Z=-12.7(25.38%) | Like=-1.45..-0.00 [-1213.2190..-0.0010] | it/evals=1098/5150 eff=36.4341% N=191 Z=-12.6(29.78%) | Like=-1.26..-0.00 [-1213.2190..-0.0010] | it/evals=1122/5261 eff=32.4074% N=191 Z=-12.5(33.56%) | Like=-1.14..-0.00 [-1213.2190..-0.0010] | it/evals=1142/5261 eff=33.2011% N=191 Z=-12.4(34.30%) | Like=-1.13..-0.00 [-1213.2190..-0.0010] | it/evals=1146/5261 eff=33.3333% N=191 Z=-12.3(37.68%) | Like=-1.00..-0.00 [-1213.2190..-0.0010] | it/evals=1164/5261 eff=34.6561% N=191 Z=-12.3(39.87%) | Like=-0.91..-0.00 [-1213.2190..-0.0010] | it/evals=1176/5261 eff=35.0529% N=191 Z=-12.2(41.78%) | Like=-0.86..-0.00 [-1213.2190..-0.0010] | it/evals=1187/5261 eff=35.5820% N=191 Z=-12.2(43.05%) | Like=-0.83..-0.00 [-1213.2190..-0.0010] | it/evals=1194/5261 eff=35.8466% N=191 Z=-12.2(45.37%) | Like=-0.77..-0.00 [-1213.2190..-0.0010] | it/evals=1206/5261 eff=36.3757% N=191 Z=-12.1(46.54%) | Like=-0.75..-0.00 [-1213.2190..-0.0010] | it/evals=1212/5261 eff=36.5079% N=191 Z=-12.1(49.85%) | Like=-0.68..-0.00 [-1213.2190..-0.0010] | it/evals=1230/5261 eff=37.4339% N=191 Z=-12.0(53.23%) | Like=-0.61..-0.00 [-1213.2190..-0.0010] | it/evals=1248/5370 eff=33.4104% N=191 Z=-12.0(54.28%) | Like=-0.59..-0.00 [-1213.2190..-0.0010] | it/evals=1254/5370 eff=33.6416% N=191 Z=-12.0(55.37%) | Like=-0.58..-0.00 [-1213.2190..-0.0010] | it/evals=1260/5370 eff=34.1040% N=191 Z=-11.9(58.39%) | Like=-0.53..-0.00 [-1213.2190..-0.0010] | it/evals=1277/5370 eff=34.3353% N=191 Z=-11.9(60.58%) | Like=-0.49..-0.00 [-1213.2190..-0.0010] | it/evals=1290/5370 eff=34.7977% N=191 Z=-11.8(65.27%) | Like=-0.42..-0.00 [-1213.2190..-0.0010] | it/evals=1321/5370 eff=36.0694% N=191 Z=-11.8(68.53%) | Like=-0.37..-0.00 [-1213.2190..-0.0010] | it/evals=1344/5370 eff=36.6474% N=191 Z=-11.7(70.88%) | Like=-0.34..-0.00 [-1213.2190..-0.0010] | it/evals=1362/5370 eff=37.4566% N=191 Z=-11.7(71.66%) | Like=-0.33..-0.00 [-1213.2190..-0.0010] | it/evals=1368/5370 eff=37.5723% N=191 Z=-11.6(78.96%) | Like=-0.24..-0.00 [-1213.2190..-0.0010] | it/evals=1434/5406 eff=38.5128% N=191 Z=-11.6(79.51%) | Like=-0.23..-0.00 [-1213.2190..-0.0010] | it/evals=1440/5406 eff=38.7347% N=191 Z=-11.6(81.08%) | Like=-0.21..-0.00 [-1213.2190..-0.0010] | it/evals=1457/5416 eff=38.8584% N=191 Z=-11.6(81.70%) | Like=-0.20..-0.00 [-1213.2190..-0.0010] | it/evals=1464/5544 eff=34.1675% N=191 Z=-11.6(82.71%) | Like=-0.19..-0.00 [-1213.2190..-0.0010] | it/evals=1476/5544 eff=34.5525% N=191 Z=-11.5(84.12%) | Like=-0.18..-0.00 [-1213.2190..-0.0010] | it/evals=1494/5544 eff=35.0337% N=191 Z=-11.5(84.64%) | Like=-0.17..-0.00 [-1213.2190..-0.0010] | it/evals=1501/5544 eff=35.2262% N=191 Z=-11.5(86.68%) | Like=-0.15..-0.00 [-1213.2190..-0.0010] | it/evals=1530/5544 eff=36.4774% N=191 Z=-11.5(87.06%) | Like=-0.14..-0.00 [-1213.2190..-0.0010] | it/evals=1536/5544 eff=36.7661% N=191 Z=-11.5(87.54%) | Like=-0.13..-0.00 [-1213.2190..-0.0010] | it/evals=1544/5544 eff=37.1511% N=191 Z=-11.5(87.79%) | Like=-0.13..-0.00 [-1213.2190..-0.0010] | it/evals=1548/5544 eff=37.3436% N=191 Z=-11.5(88.48%) | Like=-0.12..-0.00 [-1213.2190..-0.0010] | it/evals=1560/5544 eff=37.6323% N=191 Z=-11.5(89.14%) | Like=-0.11..-0.00 [-1213.2190..-0.0010] | it/evals=1572/5544 eff=37.9211% N=191 Z=-11.5(91.18%) | Like=-0.09..-0.00 [-1213.2190..-0.0010] | it/evals=1614/5544 eff=39.3648% N=191 Z=-11.5(91.69%) | Like=-0.09..-0.00 [-1213.2190..-0.0010] | it/evals=1626/5544 eff=39.9423% N=191 Z=-11.5(91.90%) | Like=-0.09..-0.00 [-1213.2190..-0.0010] | it/evals=1631/5554 eff=39.8475% N=191 Z=-11.4(92.86%) | Like=-0.08..-0.00 [-1213.2190..-0.0010] | it/evals=1656/5663 eff=36.8739% N=191 Z=-11.4(93.07%) | Like=-0.07..-0.00 [-1213.2190..-0.0010] | it/evals=1662/5663 eff=37.0466% N=191 Z=-11.4(93.68%) | Like=-0.07..-0.00 [-1213.2190..-0.0010] | it/evals=1680/5663 eff=37.6511% N=191 Z=-11.4(94.05%) | Like=-0.06..-0.00 [-1213.2190..-0.0010] | it/evals=1692/5663 eff=37.9965% N=191 Z=-11.4(94.73%) | Like=-0.05..-0.00 [-1213.2190..-0.0010] | it/evals=1716/5663 eff=38.6874% N=191 Z=-11.4(94.79%) | Like=-0.05..-0.00 [-1213.2190..-0.0010] | it/evals=1718/5663 eff=38.7737% N=191 Z=-11.4(95.34%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=1740/5663 eff=39.3782% N=191 Z=-11.4(95.84%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=1762/5663 eff=39.9827% N=191 Z=-11.4(96.01%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=1770/5663 eff=40.2418% N=191 Z=-11.4(96.25%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1782/5663 eff=40.5009% N=191 Z=-11.4(96.36%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1788/5663 eff=40.6736% N=191 Z=-11.4(96.47%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1794/5663 eff=40.8463% N=191 Z=-11.4(96.78%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1812/5675 eff=41.0256% N=191 Z=-11.4(96.98%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1824/5689 eff=40.8784% N=191 Z=-11.4(97.07%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1830/5689 eff=41.0473% N=191 Z=-11.4(97.42%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=1855/5703 eff=40.9850% N=191 Z=-11.4(97.71%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=1878/5820 eff=38.1749% N=191 Z=-11.4(97.78%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=1884/5820 eff=38.3270% N=191 Z=-11.4(97.95%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=1899/5820 eff=38.4791% N=191 Z=-11.4(98.36%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=1942/5820 eff=39.3916% N=191 Z=-11.4(98.52%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=1962/5820 eff=39.8479% N=191 Z=-11.4(98.65%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=1980/5820 eff=40.3042% N=191 Z=-11.4(98.73%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=1992/5820 eff=40.4563% N=191 Z=-11.4(98.88%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2016/5820 eff=40.9125% N=191 Z=-11.4(98.97%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2031/5820 eff=41.5209% N=191 Z=-11.4(99.01%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2040/5832 eff=41.3715% N=191 Z=-11.4(99.07%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2052/5832 eff=41.7483% N=191 Z=-11.4(99.10%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2058/5845 eff=41.7910% N=191 Z=-11.4(99.13%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2064/5858 eff=41.6851% N=191 Z=-11.4(99.16%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2070/5858 eff=41.9069% N=191 Z=-11.4(99.19%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2078/5858 eff=41.9808% N=191 Z=-11.4(99.28%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2100/5973 eff=39.1689% N=191 Z=-11.4(99.36%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2122/5973 eff=39.9183% N=191 Z=-11.4(99.40%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2136/5973 eff=40.3270% N=191 Z=-11.4(99.46%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2154/5973 eff=40.8719% N=191 Z=-11.4(99.56%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2196/5973 eff=41.8256% N=191 Z=-11.4(99.61%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2216/5973 eff=42.0981% N=191 Z=-11.4(99.63%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2226/5973 eff=42.2343% N=191 Z=-11.4(99.64%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2232/5973 eff=42.3025% N=191 Z=-11.4(99.69%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2260/5973 eff=42.7112% N=191 Z=-11.4(99.69%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2262/5973 eff=42.7793% N=191 Z=-11.4(99.70%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2268/6096 eff=39.6606% N=191 Z=-11.4(99.72%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2280/6096 eff=39.9120% N=191 Z=-11.4(99.74%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2292/6096 eff=40.3520% N=191 Z=-11.4(99.75%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2303/6096 eff=40.4777% N=191 Z=-11.4(99.80%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2346/6096 eff=41.3576% N=191 Z=-11.4(99.83%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2382/6096 eff=42.1119% N=191 Z=-11.4(99.84%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2388/6096 eff=42.3633% N=191 Z=-11.4(99.86%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2412/6096 eff=42.6776% N=191 Z=-11.4(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2424/6111 eff=42.4035% N=191 Z=-11.4(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2430/6111 eff=42.4658% N=191 Z=-11.4(99.89%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2452/6111 eff=42.7148% N=191 Z=-11.4(99.89%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2454/6111 eff=42.8394% N=191 Z=-11.4(99.89%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2460/6234 eff=40.1388% N=191 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 6234 [ultranest] logZ = -11.38 +- 0.3175 [ultranest] Effective samples strategy wants to improve: -8.83..-0.00 (ESS = 776.0, need >10000) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.16 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 20 minimum live points (dlogz from 0.24 to 0.82, need <0.5) [ultranest] logZ error budget: single: 0.23 bs:0.32 tail:0.00 total:0.32 required:<0.50 [ultranest] Widening from 72 to 382 live points before L=-9... [ultranest] Will add 310 live points (x1) at L=-1e+03 ... [ultranest] Exploring (in particular: L=-1213.22..-0.00) ... Z=-1264.4(0.00%) | Like=-1213.22..-0.00 [-1213.2190..-0.0010] | it/evals=280/6361 eff=0.0000% N=64 Z=-1037.1(0.00%) | Like=-1001.43..-0.00 [-1213.2190..-0.0010] | it/evals=295/6361 eff=0.7874% N=67 Z=-237.9(0.00%) | Like=-222.58..-0.00 [-1213.2190..-0.0010] | it/evals=395/6361 eff=1.5748% N=70 Z=-187.5(0.00%) | Like=-171.06..-0.00 [-1213.2190..-0.0010] | it/evals=413/6361 eff=2.3622% N=73 Z=-150.9(0.00%) | Like=-136.96..-0.00 [-1213.2190..-0.0010] | it/evals=430/6361 eff=3.1496% N=76 Z=-122.5(0.00%) | Like=-110.24..-0.00 [-1213.2190..-0.0010] | it/evals=448/6372 eff=5.7971% N=83 Z=-107.6(0.00%) | Like=-94.16..-0.00 [-1213.2190..-0.0010] | it/evals=462/6372 eff=9.4203% N=91 Z=-82.9(0.00%) | Like=-70.89..-0.00 [-1213.2190..-0.0010] | it/evals=483/6503 eff=5.5762% N=95 Z=-74.2(0.00%) | Like=-62.51..-0.00 [-1213.2190..-0.0010] | it/evals=498/6503 eff=8.1784% N=104 Z=-66.9(0.00%) | Like=-55.18..-0.00 [-1213.2190..-0.0010] | it/evals=508/6503 eff=8.5502% N=107 Z=-58.1(0.00%) | Like=-46.40..-0.00 [-1213.2190..-0.0010] | it/evals=528/6503 eff=10.7807% N=117 Z=-56.3(0.00%) | Like=-44.86..-0.00 [-1213.2190..-0.0010] | it/evals=534/6503 eff=11.8959% N=123 Z=-50.4(0.00%) | Like=-38.41..-0.00 [-1213.2190..-0.0010] | it/evals=546/6503 eff=13.0112% N=126 Z=-45.4(0.00%) | Like=-34.07..-0.00 [-1213.2190..-0.0010] | it/evals=563/6503 eff=15.9851% N=135 Z=-41.9(0.00%) | Like=-30.33..-0.00 [-1213.2190..-0.0010] | it/evals=576/6503 eff=18.2156% N=144 Z=-38.5(0.00%) | Like=-26.96..-0.00 [-1213.2190..-0.0010] | it/evals=594/6503 eff=21.1896% N=150 Z=-37.5(0.00%) | Like=-26.06..-0.00 [-1213.2190..-0.0010] | it/evals=600/6503 eff=21.5613% N=152 Z=-36.3(0.00%) | Like=-24.83..-0.00 [-1213.2190..-0.0010] | it/evals=606/6503 eff=22.6766% N=161 Z=-35.4(0.00%) | Like=-23.99..-0.00 [-1213.2190..-0.0010] | it/evals=612/6503 eff=23.7918% N=164 Z=-32.0(0.00%) | Like=-20.84..-0.00 [-1213.2190..-0.0010] | it/evals=636/6519 eff=25.9649% N=175 Z=-31.8(0.00%) | Like=-20.77..-0.00 [-1213.2190..-0.0010] | it/evals=638/6646 eff=18.2039% N=178 Z=-31.5(0.00%) | Like=-20.72..-0.00 [-1213.2190..-0.0010] | it/evals=642/6646 eff=18.6893% N=178 Z=-31.0(0.00%) | Like=-19.78..-0.00 [-1213.2190..-0.0010] | it/evals=648/6646 eff=19.4175% N=178 Z=-30.4(0.00%) | Like=-19.34..-0.00 [-1213.2190..-0.0010] | it/evals=654/6646 eff=20.1456% N=178 Z=-29.2(0.00%) | Like=-18.09..-0.00 [-1213.2190..-0.0010] | it/evals=666/6646 eff=20.6311% N=180 Z=-28.7(0.00%) | Like=-17.60..-0.00 [-1213.2190..-0.0010] | it/evals=672/6646 eff=20.8738% N=180 Z=-28.3(0.00%) | Like=-17.22..-0.00 [-1213.2190..-0.0010] | it/evals=679/6646 eff=21.8447% N=186 Z=-28.0(0.00%) | Like=-16.98..-0.00 [-1213.2190..-0.0010] | it/evals=684/6646 eff=23.0583% N=195 Z=-27.3(0.00%) | Like=-16.08..-0.00 [-1213.2190..-0.0010] | it/evals=696/6646 eff=24.7573% N=204 Z=-25.1(0.00%) | Like=-13.57..-0.00 [-1213.2190..-0.0010] | it/evals=732/6646 eff=28.8835% N=218 Z=-24.7(0.00%) | Like=-13.38..-0.00 [-1213.2190..-0.0010] | it/evals=738/6646 eff=29.3689% N=221 Z=-23.9(0.00%) | Like=-12.43..-0.00 [-1213.2190..-0.0010] | it/evals=750/6646 eff=30.5825% N=224 Z=-23.6(0.00%) | Like=-12.27..-0.00 [-1213.2190..-0.0010] | it/evals=756/6646 eff=31.3107% N=230 Z=-23.0(0.00%) | Like=-11.55..-0.00 [-1213.2190..-0.0010] | it/evals=768/6646 eff=32.7670% N=236 Z=-22.7(0.00%) | Like=-11.30..-0.00 [-1213.2190..-0.0010] | it/evals=774/6646 eff=33.7379% N=242 Z=-22.6(0.00%) | Like=-11.27..-0.00 [-1213.2190..-0.0010] | it/evals=776/6657 eff=33.3333% N=248 Z=-22.0(0.00%) | Like=-10.67..-0.00 [-1213.2190..-0.0010] | it/evals=792/6666 eff=34.4907% N=260 Z=-21.5(0.00%) | Like=-10.14..-0.00 [-1213.2190..-0.0010] | it/evals=804/6674 eff=35.6818% N=263 Z=-20.9(0.01%) | Like=-9.43..-0.00 [-1213.2190..-0.0010] | it/evals=822/6683 eff=35.8575% N=264 Z=-20.7(0.01%) | Like=-9.25..-0.00 [-1213.2190..-0.0010] | it/evals=828/6683 eff=36.5256% N=264 Z=-20.4(0.01%) | Like=-8.80..-0.00 [-1213.2190..-0.0010] | it/evals=835/6695 eff=36.6594% N=265 Z=-19.7(0.02%) | Like=-8.19..-0.00 [-1213.2190..-0.0010] | it/evals=852/6695 eff=37.5271% N=265 Z=-19.3(0.03%) | Like=-7.87..-0.00 [-1213.2190..-0.0010] | it/evals=864/6706 eff=37.5000% N=265 Z=-18.8(0.06%) | Like=-7.34..-0.00 [-1213.2190..-0.0010] | it/evals=882/6706 eff=38.9831% N=265 Z=-18.4(0.09%) | Like=-7.05..-0.00 [-1213.2190..-0.0010] | it/evals=894/6718 eff=38.4298% N=265 Z=-18.4(0.09%) | Like=-7.02..-0.00 [-1213.2190..-0.0010] | it/evals=896/6718 eff=38.6364% N=265 Z=-17.8(0.17%) | Like=-6.49..-0.00 [-1213.2190..-0.0010] | it/evals=918/6839 eff=32.0661% N=265 Z=-17.6(0.22%) | Like=-6.24..-0.00 [-1213.2190..-0.0010] | it/evals=930/6839 eff=32.7273% N=265 Z=-17.1(0.35%) | Like=-5.94..-0.00 [-1213.2190..-0.0010] | it/evals=956/6839 eff=33.7190% N=265 Z=-16.9(0.40%) | Like=-5.82..-0.00 [-1213.2190..-0.0010] | it/evals=966/6839 eff=34.3802% N=265 Z=-16.5(0.60%) | Like=-5.27..-0.00 [-1213.2190..-0.0010] | it/evals=990/6839 eff=35.2066% N=265 Z=-16.4(0.66%) | Like=-5.08..-0.00 [-1213.2190..-0.0010] | it/evals=996/6839 eff=35.8678% N=265 Z=-16.2(0.80%) | Like=-4.77..-0.00 [-1213.2190..-0.0010] | it/evals=1008/6839 eff=36.6942% N=265 Z=-16.1(0.87%) | Like=-4.66..-0.00 [-1213.2190..-0.0010] | it/evals=1014/6839 eff=36.8595% N=265 Z=-16.1(0.90%) | Like=-4.65..-0.00 [-1213.2190..-0.0010] | it/evals=1016/6839 eff=37.1901% N=265 Z=-16.0(0.96%) | Like=-4.57..-0.00 [-1213.2190..-0.0010] | it/evals=1020/6839 eff=37.3554% N=265 Z=-15.7(1.34%) | Like=-4.15..-0.00 [-1213.2190..-0.0010] | it/evals=1038/6839 eff=38.5124% N=265 Z=-15.5(1.62%) | Like=-3.99..-0.00 [-1213.2190..-0.0010] | it/evals=1050/6839 eff=39.3388% N=265 Z=-15.4(1.78%) | Like=-3.89..-0.00 [-1213.2190..-0.0010] | it/evals=1056/6839 eff=40.0000% N=265 Z=-15.1(2.40%) | Like=-3.66..-0.00 [-1213.2190..-0.0010] | it/evals=1076/6839 eff=40.8264% N=265 Z=-14.8(3.26%) | Like=-3.36..-0.00 [-1213.2190..-0.0010] | it/evals=1098/6839 eff=41.3223% N=265 Z=-14.6(3.84%) | Like=-3.19..-0.00 [-1213.2190..-0.0010] | it/evals=1110/6839 eff=41.9835% N=265 Z=-14.3(5.12%) | Like=-2.90..-0.00 [-1213.2190..-0.0010] | it/evals=1134/6953 eff=36.4395% N=265 Z=-14.3(5.41%) | Like=-2.85..-0.00 [-1213.2190..-0.0010] | it/evals=1139/6953 eff=36.5786% N=265 Z=-14.1(6.61%) | Like=-2.68..-0.00 [-1213.2190..-0.0010] | it/evals=1158/6953 eff=37.2740% N=265 Z=-13.7(9.82%) | Like=-2.23..-0.00 [-1213.2190..-0.0010] | it/evals=1201/6953 eff=38.5257% N=265 Z=-13.4(13.72%) | Like=-1.98..-0.00 [-1213.2190..-0.0010] | it/evals=1242/6953 eff=39.7775% N=265 Z=-13.2(16.30%) | Like=-1.81..-0.00 [-1213.2190..-0.0010] | it/evals=1266/6953 eff=40.4729% N=265 Z=-13.1(18.13%) | Like=-1.74..-0.00 [-1213.2190..-0.0010] | it/evals=1284/6953 eff=41.3074% N=265 Z=-12.9(20.82%) | Like=-1.58..-0.00 [-1213.2190..-0.0010] | it/evals=1308/6953 eff=42.0028% N=265 Z=-12.9(21.53%) | Like=-1.55..-0.00 [-1213.2190..-0.0010] | it/evals=1314/6953 eff=42.1419% N=265 Z=-12.8(25.46%) | Like=-1.39..-0.00 [-1213.2190..-0.0010] | it/evals=1344/6953 eff=42.9764% N=265 Z=-12.6(28.66%) | Like=-1.24..-0.00 [-1213.2190..-0.0010] | it/evals=1368/6959 eff=43.3103% N=265 Z=-12.5(32.47%) | Like=-1.10..-0.00 [-1213.2190..-0.0010] | it/evals=1396/7064 eff=38.3133% N=265 Z=-12.5(33.66%) | Like=-1.07..-0.00 [-1213.2190..-0.0010] | it/evals=1404/7064 eff=38.7952% N=265 Z=-12.5(34.46%) | Like=-1.04..-0.00 [-1213.2190..-0.0010] | it/evals=1410/7064 eff=39.1566% N=265 Z=-12.4(35.32%) | Like=-1.01..-0.00 [-1213.2190..-0.0010] | it/evals=1416/7064 eff=39.3976% N=265 Z=-12.4(37.79%) | Like=-0.93..-0.00 [-1213.2190..-0.0010] | it/evals=1434/7064 eff=40.1205% N=265 Z=-12.3(40.87%) | Like=-0.83..-0.00 [-1213.2190..-0.0010] | it/evals=1458/7064 eff=40.8434% N=265 Z=-12.2(44.28%) | Like=-0.75..-0.00 [-1213.2190..-0.0010] | it/evals=1482/7064 eff=41.4458% N=265 Z=-12.1(49.36%) | Like=-0.64..-0.00 [-1213.2190..-0.0010] | it/evals=1518/7064 eff=42.1687% N=265 Z=-12.1(50.12%) | Like=-0.63..-0.00 [-1213.2190..-0.0010] | it/evals=1524/7064 eff=42.5301% N=265 Z=-12.1(51.75%) | Like=-0.60..-0.00 [-1213.2190..-0.0010] | it/evals=1536/7064 eff=43.0120% N=265 Z=-12.0(52.52%) | Like=-0.59..-0.00 [-1213.2190..-0.0010] | it/evals=1542/7064 eff=43.3735% N=265 Z=-11.9(58.70%) | Like=-0.49..-0.00 [-1213.2190..-0.0010] | it/evals=1590/7064 eff=44.9398% N=265 Z=-11.9(60.82%) | Like=-0.46..-0.00 [-1213.2190..-0.0010] | it/evals=1608/7064 eff=45.0602% N=265 Z=-11.9(61.54%) | Like=-0.44..-0.00 [-1213.2190..-0.0010] | it/evals=1614/7177 eff=39.8727% N=265 Z=-11.8(64.39%) | Like=-0.40..-0.00 [-1213.2190..-0.0010] | it/evals=1640/7177 eff=40.1909% N=265 Z=-11.7(72.06%) | Like=-0.29..-0.00 [-1213.2190..-0.0010] | it/evals=1716/7177 eff=42.0997% N=265 Z=-11.7(72.61%) | Like=-0.29..-0.00 [-1213.2190..-0.0010] | it/evals=1722/7177 eff=42.3118% N=265 Z=-11.7(73.15%) | Like=-0.28..-0.00 [-1213.2190..-0.0010] | it/evals=1728/7177 eff=42.5239% N=265 Z=-11.7(74.69%) | Like=-0.27..-0.00 [-1213.2190..-0.0010] | it/evals=1746/7177 eff=42.9480% N=265 Z=-11.7(75.66%) | Like=-0.26..-0.00 [-1213.2190..-0.0010] | it/evals=1758/7177 eff=43.2662% N=265 Z=-11.7(75.91%) | Like=-0.25..-0.00 [-1213.2190..-0.0010] | it/evals=1761/7177 eff=43.3722% N=265 Z=-11.7(76.14%) | Like=-0.25..-0.00 [-1213.2190..-0.0010] | it/evals=1764/7177 eff=43.5843% N=265 Z=-11.7(76.60%) | Like=-0.24..-0.00 [-1213.2190..-0.0010] | it/evals=1770/7177 eff=43.7964% N=265 Z=-11.7(77.50%) | Like=-0.23..-0.00 [-1213.2190..-0.0010] | it/evals=1782/7177 eff=44.1145% N=265 Z=-11.6(80.50%) | Like=-0.20..-0.00 [-1213.2190..-0.0010] | it/evals=1824/7289 eff=40.8531% N=265 Z=-11.6(81.68%) | Like=-0.18..-0.00 [-1213.2190..-0.0010] | it/evals=1842/7289 eff=41.3270% N=265 Z=-11.6(82.76%) | Like=-0.18..-0.00 [-1213.2190..-0.0010] | it/evals=1860/7289 eff=41.6114% N=265 Z=-11.6(83.96%) | Like=-0.16..-0.00 [-1213.2190..-0.0010] | it/evals=1881/7289 eff=42.2749% N=265 Z=-11.6(84.79%) | Like=-0.15..-0.00 [-1213.2190..-0.0010] | it/evals=1896/7289 eff=42.5592% N=265 Z=-11.6(85.10%) | Like=-0.15..-0.00 [-1213.2190..-0.0010] | it/evals=1902/7289 eff=42.8436% N=265 Z=-11.6(85.42%) | Like=-0.15..-0.00 [-1213.2190..-0.0010] | it/evals=1908/7289 eff=42.9384% N=265 Z=-11.5(86.02%) | Like=-0.14..-0.00 [-1213.2190..-0.0010] | it/evals=1920/7289 eff=43.4123% N=265 Z=-11.5(87.19%) | Like=-0.12..-0.00 [-1213.2190..-0.0010] | it/evals=1945/7289 eff=43.6967% N=265 Z=-11.5(87.68%) | Like=-0.12..-0.00 [-1213.2190..-0.0010] | it/evals=1956/7289 eff=44.0758% N=265 Z=-11.5(89.16%) | Like=-0.11..-0.00 [-1213.2190..-0.0010] | it/evals=1992/7299 eff=44.6948% N=265 Z=-11.5(89.39%) | Like=-0.10..-0.00 [-1213.2190..-0.0010] | it/evals=1998/7314 eff=44.2593% N=265 Z=-11.5(89.61%) | Like=-0.10..-0.00 [-1213.2190..-0.0010] | it/evals=2004/7314 eff=44.5370% N=265 Z=-11.5(89.76%) | Like=-0.10..-0.00 [-1213.2190..-0.0010] | it/evals=2008/7314 eff=44.6296% N=265 Z=-11.5(90.87%) | Like=-0.09..-0.00 [-1213.2190..-0.0010] | it/evals=2040/7314 eff=45.2778% N=265 Z=-11.5(91.75%) | Like=-0.08..-0.00 [-1213.2190..-0.0010] | it/evals=2068/7331 eff=45.1231% N=265 Z=-11.5(91.81%) | Like=-0.08..-0.00 [-1213.2190..-0.0010] | it/evals=2070/7331 eff=45.2142% N=265 Z=-11.5(91.98%) | Like=-0.08..-0.00 [-1213.2190..-0.0010] | it/evals=2076/7459 eff=40.7347% N=265 Z=-11.5(92.82%) | Like=-0.07..-0.00 [-1213.2190..-0.0010] | it/evals=2106/7459 eff=41.3061% N=265 Z=-11.5(93.27%) | Like=-0.06..-0.00 [-1213.2190..-0.0010] | it/evals=2124/7459 eff=41.9592% N=265 Z=-11.5(93.97%) | Like=-0.06..-0.00 [-1213.2190..-0.0010] | it/evals=2154/7459 eff=42.8571% N=265 Z=-11.5(94.74%) | Like=-0.05..-0.00 [-1213.2190..-0.0010] | it/evals=2191/7459 eff=43.3469% N=265 Z=-11.4(95.27%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=2220/7459 eff=44.0816% N=265 Z=-11.4(95.38%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=2226/7459 eff=44.1633% N=265 Z=-11.4(95.80%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=2252/7459 eff=44.6531% N=265 Z=-11.4(95.86%) | Like=-0.04..-0.00 [-1213.2190..-0.0010] | it/evals=2256/7459 eff=44.8163% N=265 Z=-11.4(95.95%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=2262/7471 eff=44.6241% N=265 Z=-11.4(96.61%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=2310/7471 eff=45.3517% N=265 Z=-11.4(96.83%) | Like=-0.03..-0.00 [-1213.2190..-0.0010] | it/evals=2328/7484 eff=45.3600% N=265 Z=-11.4(97.38%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2379/7503 eff=45.4689% N=265 Z=-11.4(97.52%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2394/7515 eff=45.2771% N=265 Z=-11.4(97.58%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2400/7515 eff=45.4333% N=265 Z=-11.4(97.63%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2406/7515 eff=45.7455% N=265 Z=-11.4(97.74%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2418/7519 eff=45.8366% N=265 Z=-11.4(97.79%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2424/7525 eff=45.9334% N=265 Z=-11.4(97.84%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2430/7534 eff=45.7692% N=265 Z=-11.4(97.93%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2442/7534 eff=46.0769% N=265 Z=-11.4(98.06%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2460/7551 eff=45.7859% N=265 Z=-11.4(98.15%) | Like=-0.02..-0.00 [-1213.2190..-0.0010] | it/evals=2472/7551 eff=45.8618% N=265 Z=-11.4(98.42%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2514/7565 eff=45.8302% N=265 Z=-11.4(98.49%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2526/7573 eff=45.9298% N=265 Z=-11.4(98.55%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2538/7573 eff=46.0792% N=265 Z=-11.4(98.59%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2544/7585 eff=45.8919% N=265 Z=-11.4(98.74%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2575/7600 eff=45.9736% N=265 Z=-11.4(98.79%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2586/7707 eff=42.8377% N=265 Z=-11.4(98.97%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2628/7707 eff=43.6524% N=265 Z=-11.4(99.01%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2640/7707 eff=44.1276% N=265 Z=-11.4(99.06%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2652/7707 eff=44.2634% N=265 Z=-11.4(99.10%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2664/7707 eff=44.5350% N=265 Z=-11.4(99.12%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2670/7707 eff=44.8065% N=265 Z=-11.4(99.18%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2688/7707 eff=45.2817% N=265 Z=-11.4(99.20%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2697/7707 eff=45.3496% N=265 Z=-11.4(99.23%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2706/7707 eff=45.5533% N=265 Z=-11.4(99.25%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2712/7707 eff=45.6212% N=265 Z=-11.4(99.28%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2724/7707 eff=45.8927% N=265 Z=-11.4(99.43%) | Like=-0.01..-0.00 [-1213.2190..-0.0010] | it/evals=2784/7815 eff=43.5800% N=265 Z=-11.4(99.53%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2836/7815 eff=44.4655% N=265 Z=-11.4(99.56%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2856/7815 eff=44.8450% N=265 Z=-11.4(99.58%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2868/7815 eff=45.1613% N=265 Z=-11.4(99.61%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2886/7815 eff=45.6673% N=265 Z=-11.4(99.63%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2900/7815 eff=46.1101% N=265 Z=-11.4(99.64%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2904/7815 eff=46.1733% N=265 Z=-11.4(99.68%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2940/7915 eff=44.0214% N=265 Z=-11.4(99.70%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2958/7915 eff=44.4378% N=265 Z=-11.4(99.70%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2960/7915 eff=44.4973% N=265 Z=-11.4(99.72%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2970/7915 eff=44.6758% N=265 Z=-11.4(99.74%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=2994/7915 eff=44.9137% N=265 Z=-11.4(99.76%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3020/7915 eff=45.0922% N=265 Z=-11.4(99.77%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3024/7915 eff=45.2112% N=265 Z=-11.4(99.77%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3030/7915 eff=45.3302% N=265 Z=-11.4(99.78%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3036/7915 eff=45.4491% N=265 Z=-11.4(99.81%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3082/7915 eff=46.2225% N=265 Z=-11.4(99.81%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3084/7915 eff=46.3415% N=265 Z=-11.4(99.82%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3096/7915 eff=46.5794% N=265 Z=-11.4(99.83%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3102/8043 eff=43.5047% N=265 Z=-11.4(99.83%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3114/8043 eff=43.6153% N=265 Z=-11.4(99.85%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3132/8043 eff=44.0575% N=265 Z=-11.4(99.85%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3142/8043 eff=44.2233% N=265 Z=-11.4(99.85%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3144/8043 eff=44.2786% N=265 Z=-11.4(99.86%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3156/8043 eff=44.3892% N=265 Z=-11.4(99.86%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3162/8043 eff=44.5550% N=265 Z=-11.4(99.87%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3186/8043 eff=44.7761% N=265 Z=-11.4(99.88%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3192/8043 eff=44.9420% N=265 Z=-11.4(99.88%) | Like=-0.00..-0.00 [-1213.2190..-0.0010] | it/evals=3203/8043 eff=45.1078% N=265 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 8043 [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. {'logzerr': 0.9374094861051898, 'logzerr_tail': 0.0011725337660379864, 'logzerr_bs': 0.9374087527885386, 'logzerr_single': 0.40351303854783166} running again for logz [ultranest] To achieve the desired logz accuracy, min_num_live_points was increased to 317 [ultranest] Widening roots to 317 live points (have 64 already) ... [ultranest] Sampling 253 live points from prior ... Z=-inf(0.00%) | Like=-241488.71..-3.82 [-241488.7072..-82400.8396] | it/evals=0/8424 eff=0.0000% N=317 Z=-162015.1(0.00%) | Like=-161448.65..-3.82 [-241488.7072..-82400.8396] | it/evals=32/8424 eff=23.4375% N=317 Z=-131996.6(0.00%) | Like=-131605.67..-3.82 [-241488.7072..-82400.8396] | it/evals=64/8424 eff=47.6562% N=317 Z=-128725.2(0.00%) | Like=-128075.71..-3.82 [-241488.7072..-82400.8396] | it/evals=71/8424 eff=51.5625% N=317 Z=-116039.8(0.00%) | Like=-114669.88..-3.82 [-241488.7072..-82400.8396] | it/evals=96/8424 eff=67.1875% N=317 Z=-99426.6(0.00%) | Like=-98932.41..-3.82 [-241488.7072..-82400.8396] | it/evals=142/8532 eff=54.6610% N=317 Z=-94469.9(0.00%) | Like=-94083.98..-3.82 [-241488.7072..-82400.8396] | it/evals=160/8532 eff=61.0169% N=317 Z=-87325.6(0.00%) | Like=-86803.89..-3.82 [-241488.7072..-82400.8396] | it/evals=192/8532 eff=72.0339% N=317 Z=-82682.4(0.00%) | Like=-82549.78..-3.82 [-241488.7072..-82400.8396] | it/evals=213/8532 eff=80.0847% N=317 Z=-80003.6(0.00%) | Like=-79785.50..-3.82 [-82217.8876..-39297.2246] | it/evals=224/8618 eff=61.1801% N=317 Z=-70498.5(0.00%) | Like=-70003.16..-3.82 [-82217.8876..-39297.2246] | it/evals=256/8618 eff=68.9441% N=317 Z=-64668.8(0.00%) | Like=-64418.55..-3.82 [-82217.8876..-39297.2246] | it/evals=284/8618 eff=75.7764% N=317 Z=-63638.8(0.00%) | Like=-63331.41..-3.82 [-82217.8876..-39297.2246] | it/evals=288/8690 eff=62.9442% N=317 Z=-58374.9(0.00%) | Like=-58204.04..-3.82 [-82217.8876..-39297.2246] | it/evals=320/8690 eff=69.0355% N=317 Z=-53117.7(0.00%) | Like=-53020.86..-3.82 [-82217.8876..-39297.2246] | it/evals=352/8751 eff=65.7143% N=317 Z=-52754.9(0.00%) | Like=-52549.25..-3.82 [-82217.8876..-39297.2246] | it/evals=356/8751 eff=66.3736% N=317 Z=-46729.1(0.00%) | Like=-46556.06..-3.82 [-82217.8876..-39297.2246] | it/evals=384/8795 eff=65.9319% N=317 Z=-41641.5(0.00%) | Like=-41619.23..-3.82 [-82217.8876..-39297.2246] | it/evals=416/8795 eff=69.9399% N=317 Z=-40285.8(0.00%) | Like=-40055.45..-3.82 [-82217.8876..-39297.2246] | it/evals=427/8847 eff=64.9728% N=317 Z=-33470.5(0.00%) | Like=-33458.45..-3.82 [-39226.8744..-18825.6538] | it/evals=480/8888 eff=67.5676% N=317 Z=-31546.8(0.00%) | Like=-31396.11..-3.82 [-39226.8744..-18825.6538] | it/evals=498/8888 eff=70.4392% N=317 Z=-27877.5(0.00%) | Like=-27864.29..-3.82 [-39226.8744..-18825.6538] | it/evals=544/8959 eff=68.0241% N=317 Z=-25189.2(0.00%) | Like=-25077.39..-3.82 [-39226.8744..-18825.6538] | it/evals=569/8997 eff=67.4750% N=317 Z=-22115.6(0.00%) | Like=-22086.43..-3.82 [-39226.8744..-18825.6538] | it/evals=608/9022 eff=69.6970% N=317 Z=-20053.1(0.00%) | Like=-20041.42..-3.82 [-39226.8744..-18825.6538] | it/evals=641/9077 eff=68.7580% N=317 Z=-18174.9(0.00%) | Like=-18074.66..-3.82 [-18818.8699..-8802.8925] | it/evals=672/9117 eff=68.5749% N=317 Z=-16363.8(0.00%) | Like=-16329.53..-3.82 [-18818.8699..-8802.8925] | it/evals=704/9134 eff=70.2864% N=317 Z=-15518.8(0.00%) | Like=-15470.57..-3.82 [-18818.8699..-8802.8925] | it/evals=713/9161 eff=68.9017% N=317 Z=-14427.6(0.00%) | Like=-14415.73..-3.82 [-18818.8699..-8802.8925] | it/evals=736/9170 eff=70.0229% N=317 Z=-12734.3(0.00%) | Like=-12708.83..-3.82 [-18818.8699..-8802.8925] | it/evals=768/9213 eff=69.4656% N=317 Z=-12142.6(0.00%) | Like=-12106.51..-3.82 [-18818.8699..-8802.8925] | it/evals=784/9229 eff=69.9893% N=317 Z=-10709.4(0.00%) | Like=-10695.44..-3.82 [-18818.8699..-8802.8925] | it/evals=832/9277 eff=70.2345% N=317 Z=-9925.9(0.00%) | Like=-9864.47..-3.82 [-18818.8699..-8802.8925] | it/evals=855/9313 eff=69.9115% N=317 Z=-7688.6(0.00%) | Like=-7673.33..-3.82 [-8762.6068..-4923.2104] | it/evals=926/9382 eff=70.5341% N=317 Z=-7668.8(0.00%) | Like=-7628.51..-3.82 [-8762.6068..-4923.2104] | it/evals=928/9388 eff=70.3297% N=317 Z=-7017.7(0.00%) | Like=-6989.00..-3.82 [-8762.6068..-4923.2104] | it/evals=960/9419 eff=70.5254% N=317 Z=-6547.7(0.00%) | Like=-6517.63..-3.82 [-8762.6068..-4923.2104] | it/evals=992/9448 eff=71.0069% N=317 Z=-6493.6(0.00%) | Like=-6475.15..-3.82 [-8762.6068..-4923.2104] | it/evals=997/9452 eff=71.0208% N=317 Z=-5491.7(0.00%) | Like=-5474.86..-3.82 [-8762.6068..-4923.2104] | it/evals=1056/9527 eff=70.4305% N=317 Z=-5276.7(0.00%) | Like=-5247.51..-3.82 [-8762.6068..-4923.2104] | it/evals=1068/9541 eff=70.2811% N=317 Z=-5002.7(0.00%) | Like=-4977.41..-3.82 [-8762.6068..-4923.2104] | it/evals=1088/9551 eff=70.8367% N=317 Z=-4662.2(0.00%) | Like=-4631.19..-3.82 [-4921.7374..-2418.6487] | it/evals=1120/9589 eff=70.7657% N=317 Z=-4455.0(0.00%) | Like=-4442.88..-3.82 [-4921.7374..-2418.6487] | it/evals=1139/9614 eff=70.6373% N=317 Z=-4252.7(0.00%) | Like=-4222.67..-3.82 [-4921.7374..-2418.6487] | it/evals=1152/9630 eff=70.6147% N=317 Z=-3824.9(0.00%) | Like=-3815.29..-3.82 [-4921.7374..-2418.6487] | it/evals=1184/9667 eff=70.6783% N=317 Z=-3493.1(0.00%) | Like=-3476.58..-3.82 [-4921.7374..-2418.6487] | it/evals=1210/9705 eff=70.3336% N=317 Z=-3443.5(0.00%) | Like=-3429.82..-3.82 [-4921.7374..-2418.6487] | it/evals=1216/9714 eff=70.2398% N=317 Z=-3058.7(0.00%) | Like=-3048.73..-3.82 [-4921.7374..-2418.6487] | it/evals=1248/9747 eff=70.5031% N=317 Z=-2809.0(0.00%) | Like=-2784.85..-3.82 [-4921.7374..-2418.6487] | it/evals=1280/9785 eff=70.3156% N=317 Z=-2794.6(0.00%) | Like=-2783.83..-3.82 [-4921.7374..-2418.6487] | it/evals=1281/9785 eff=70.3828% N=317 Z=-2506.5(0.00%) | Like=-2479.05..-3.82 [-4921.7374..-2418.6487] | it/evals=1312/9816 eff=70.5921% N=317 Z=-2237.6(0.00%) | Like=-2220.11..-3.82 [-2396.7422..-1225.8972] | it/evals=1344/9850 eff=70.5920% N=317 Z=-2146.6(0.00%) | Like=-2126.85..-3.82 [-2396.7422..-1225.8972] | it/evals=1352/9860 eff=70.5882% N=317 Z=-2008.7(0.00%) | Like=-1994.21..-3.82 [-2396.7422..-1225.8972] | it/evals=1376/9995 eff=66.0977% N=317 Z=-1742.5(0.00%) | Like=-1725.08..-3.82 [-2396.7422..-1225.8972] | it/evals=1423/9995 eff=68.3343% N=317 Z=-1655.1(0.00%) | Like=-1637.97..-3.82 [-2396.7422..-1225.8972] | it/evals=1440/9995 eff=69.2172% N=317 Z=-1484.1(0.00%) | Like=-1470.82..-3.82 [-2396.7422..-1225.8972] | it/evals=1472/10127 eff=65.6472% N=317 Z=-1400.3(0.00%) | Like=-1388.39..-3.82 [-2396.7422..-1225.8972] | it/evals=1494/10127 eff=66.5756% N=317 Z=-1345.5(0.00%) | Like=-1329.96..-3.82 [-2396.7422..-1225.8972] | it/evals=1504/10127 eff=67.0672% N=317 Z=-1202.1(0.00%) | Like=-1190.79..-3.82 [-1218.4285..-623.5609] | it/evals=1541/10127 eff=68.5418% N=317 Z=-1105.5(0.00%) | Like=-1094.12..-3.82 [-1218.4285..-623.5609] | it/evals=1568/10127 eff=69.6341% N=317 Z=-1002.7(0.00%) | Like=-991.38..-3.82 [-1218.4285..-623.5609] | it/evals=1600/10271 eff=65.6709% N=317 Z=-912.7(0.00%) | Like=-897.72..-1.26 [-1218.4285..-623.5609] | it/evals=1632/10271 eff=66.8354% N=317 Z=-807.7(0.00%) | Like=-795.37..-1.26 [-1218.4285..-623.5609] | it/evals=1671/10271 eff=68.4557% N=317 Z=-749.5(0.00%) | Like=-730.32..-1.26 [-1218.4285..-623.5609] | it/evals=1696/10399 eff=65.2877% N=317 Z=-697.8(0.00%) | Like=-683.69..-1.26 [-1218.4285..-623.5609] | it/evals=1728/10399 eff=66.3814% N=317 Z=-673.3(0.00%) | Like=-661.52..-1.26 [-1218.4285..-623.5609] | it/evals=1742/10399 eff=66.9044% N=317 Z=-627.0(0.00%) | Like=-609.67..-1.26 [-622.7094..-322.7858] | it/evals=1760/10399 eff=67.5226% N=317 Z=-581.5(0.00%) | Like=-564.18..-1.26 [-622.7094..-322.7858] | it/evals=1792/10399 eff=68.7589% N=317 Z=-540.4(0.00%) | Like=-527.04..-1.26 [-622.7094..-322.7858] | it/evals=1813/10527 eff=65.7104% N=317 Z=-517.1(0.00%) | Like=-505.17..-1.26 [-622.7094..-322.7858] | it/evals=1824/10527 eff=66.0690% N=317 Z=-465.7(0.00%) | Like=-452.56..-1.26 [-622.7094..-322.7858] | it/evals=1856/10527 eff=67.2792% N=317 Z=-427.8(0.00%) | Like=-414.10..-1.26 [-622.7094..-322.7858] | it/evals=1884/10529 eff=68.2490% N=317 Z=-414.8(0.00%) | Like=-401.25..-1.26 [-622.7094..-322.7858] | it/evals=1888/10532 eff=68.2469% N=317 Z=-381.3(0.00%) | Like=-368.88..-1.26 [-622.7094..-322.7858] | it/evals=1920/10663 eff=65.5260% N=317 Z=-348.6(0.00%) | Like=-336.76..-1.26 [-622.7094..-322.7858] | it/evals=1955/10663 eff=66.7089% N=317 Z=-318.9(0.00%) | Like=-306.73..-1.26 [-321.7020..-141.7603] | it/evals=1984/10663 eff=67.5539% N=317 Z=-288.9(0.00%) | Like=-277.25..-1.26 [-321.7020..-141.7603] | it/evals=2016/10791 eff=65.1703% N=317 Z=-277.6(0.00%) | Like=-264.93..-1.26 [-321.7020..-141.7603] | it/evals=2026/10791 eff=65.4910% N=317 Z=-261.1(0.00%) | Like=-248.44..-1.26 [-321.7020..-141.7603] | it/evals=2048/10791 eff=66.2124% N=317 Z=-230.3(0.00%) | Like=-217.48..-1.26 [-321.7020..-141.7603] | it/evals=2080/10791 eff=67.0541% N=317 Z=-205.0(0.00%) | Like=-193.36..-1.26 [-321.7020..-141.7603] | it/evals=2112/10919 eff=64.6969% N=317 Z=-181.2(0.00%) | Like=-169.41..-1.26 [-321.7020..-141.7603] | it/evals=2155/10919 eff=65.8788% N=317 Z=-167.4(0.00%) | Like=-155.64..-1.26 [-321.7020..-141.7603] | it/evals=2176/10919 eff=66.4506% N=317 Z=-146.5(0.00%) | Like=-134.15..-1.26 [-141.7043..-68.9141] | it/evals=2224/11047 eff=64.5947% N=317 Z=-142.0(0.00%) | Like=-129.80..-1.26 [-141.7043..-68.9141] | it/evals=2240/11047 eff=65.0309% N=317 Z=-127.8(0.00%) | Like=-115.79..-0.15 [-141.7043..-68.9141] | it/evals=2270/11047 eff=65.7943% N=317 Z=-127.2(0.00%) | Like=-115.56..-0.15 [-141.7043..-68.9141] | it/evals=2272/11047 eff=65.8306% N=317 Z=-122.3(0.00%) | Like=-110.14..-0.15 [-141.7043..-68.9141] | it/evals=2286/11047 eff=66.0851% N=317 Z=-117.7(0.00%) | Like=-105.62..-0.15 [-141.7043..-68.9141] | it/evals=2306/11047 eff=66.4122% N=317 Z=-110.3(0.00%) | Like=-97.73..-0.15 [-141.7043..-68.9141] | it/evals=2324/11047 eff=66.7394% N=317 Z=-105.2(0.00%) | Like=-93.15..-0.15 [-141.7043..-68.9141] | it/evals=2336/11047 eff=66.9575% N=317 Z=-101.7(0.00%) | Like=-89.63..-0.15 [-141.7043..-68.9141] | it/evals=2345/11047 eff=67.0302% N=317 Z=-93.6(0.00%) | Like=-81.94..-0.15 [-141.7043..-68.9141] | it/evals=2368/11175 eff=64.7100% N=317 Z=-85.0(0.00%) | Like=-72.89..-0.15 [-141.7043..-68.9141] | it/evals=2400/11175 eff=65.5783% N=317 Z=-81.8(0.00%) | Like=-70.23..-0.15 [-141.7043..-68.9141] | it/evals=2416/11175 eff=65.9951% N=317 Z=-80.3(0.00%) | Like=-68.43..-0.15 [-68.4891..-30.7962] | it/evals=2424/11175 eff=66.0993% N=317 Z=-78.2(0.00%) | Like=-66.18..-0.15 [-68.4891..-30.7962] | it/evals=2436/11175 eff=66.2730% N=317 Z=-75.3(0.00%) | Like=-63.38..-0.15 [-68.4891..-30.7962] | it/evals=2451/11175 eff=66.4814% N=317 Z=-73.4(0.00%) | Like=-61.04..-0.15 [-68.4891..-30.7962] | it/evals=2458/11175 eff=66.5162% N=317 Z=-72.1(0.00%) | Like=-60.41..-0.15 [-68.4891..-30.7962] | it/evals=2464/11175 eff=66.7246% N=317 Z=-66.7(0.00%) | Like=-54.78..-0.15 [-68.4891..-30.7962] | it/evals=2498/11303 eff=64.6492% N=317 Z=-62.5(0.00%) | Like=-50.15..-0.15 [-68.4891..-30.7962] | it/evals=2515/11303 eff=64.8154% N=317 Z=-60.5(0.00%) | Like=-48.80..-0.15 [-68.4891..-30.7962] | it/evals=2525/11303 eff=64.9152% N=317 Z=-60.1(0.00%) | Like=-48.34..-0.15 [-68.4891..-30.7962] | it/evals=2528/11303 eff=64.9817% N=317 Z=-56.5(0.00%) | Like=-44.54..-0.15 [-68.4891..-30.7962] | it/evals=2553/11303 eff=65.1480% N=317 Z=-47.1(0.00%) | Like=-35.03..-0.15 [-68.4891..-30.7962] | it/evals=2609/11303 eff=65.8464% N=317 Z=-45.3(0.00%) | Like=-33.25..-0.15 [-68.4891..-30.7962] | it/evals=2626/11303 eff=66.1124% N=317 Z=-43.2(0.00%) | Like=-30.78..-0.15 [-30.7776..-15.7338] | it/evals=2643/11303 eff=66.2787% N=317 Z=-41.6(0.00%) | Like=-29.57..-0.15 [-30.7776..-15.7338] | it/evals=2655/11303 eff=66.3452% N=317 Z=-41.5(0.00%) | Like=-29.50..-0.15 [-30.7776..-15.7338] | it/evals=2656/11303 eff=66.3785% N=317 Z=-38.4(0.00%) | Like=-26.58..-0.15 [-30.7776..-15.7338] | it/evals=2688/11431 eff=63.8915% N=317 Z=-37.1(0.00%) | Like=-25.20..-0.15 [-30.7776..-15.7338] | it/evals=2704/11431 eff=63.9872% N=317 Z=-35.3(0.00%) | Like=-23.47..-0.15 [-30.7776..-15.7338] | it/evals=2725/11431 eff=64.0510% N=317 Z=-34.4(0.00%) | Like=-22.42..-0.15 [-30.7776..-15.7338] | it/evals=2734/11431 eff=64.0829% N=317 Z=-33.3(0.00%) | Like=-21.69..-0.15 [-30.7776..-15.7338] | it/evals=2749/11431 eff=64.2105% N=317 Z=-33.2(0.00%) | Like=-21.59..-0.15 [-30.7776..-15.7338] | it/evals=2752/11431 eff=64.3062% N=317 Z=-31.8(0.00%) | Like=-20.13..-0.15 [-30.7776..-15.7338] | it/evals=2776/11431 eff=64.3381% N=317 Z=-31.3(0.00%) | Like=-19.57..-0.15 [-30.7776..-15.7338] | it/evals=2784/11431 eff=64.4657% N=317 Z=-29.6(0.00%) | Like=-17.93..-0.15 [-30.7776..-15.7338] | it/evals=2814/11431 eff=64.7528% N=317 Z=-29.5(0.00%) | Like=-17.84..-0.15 [-30.7776..-15.7338] | it/evals=2816/11431 eff=64.8166% N=317 Z=-25.4(0.00%) | Like=-13.64..-0.15 [-15.6805..-7.9399] | it/evals=2919/11431 eff=65.0080% N=317 Z=-24.9(0.00%) | Like=-13.20..-0.15 [-15.6805..-7.9399] | it/evals=2935/11431 eff=65.0399% N=317 Z=-18.8(0.10%) | Like=-6.95..-0.15 [-7.9116..-3.8309] | it/evals=3143/11431 eff=65.1994% N=317 Z=-17.4(0.37%) | Like=-5.92..-0.15 [-7.9116..-3.8309] | it/evals=3217/11431 eff=65.4864% N=317 Z=-17.2(0.44%) | Like=-5.61..-0.15 [-7.9116..-3.8309] | it/evals=3232/11559 eff=63.0401% N=317 Z=-16.3(1.05%) | Like=-4.48..-0.15 [-7.9116..-3.8309] | it/evals=3292/11559 eff=63.2240% N=317 Z=-15.4(2.77%) | Like=-3.48..-0.15 [-3.8177..-2.4714] | it/evals=3363/11559 eff=63.4998% N=317 Z=-15.0(3.92%) | Like=-3.14..-0.15 [-3.8177..-2.4714] | it/evals=3392/11559 eff=63.7144% N=317 Z=-14.5(7.07%) | Like=-2.61..-0.15 [-3.8177..-2.4714] | it/evals=3453/11559 eff=63.8983% N=317 Z=-14.2(9.23%) | Like=-2.31..-0.15 [-2.4600..-2.1293] | it/evals=3488/11559 eff=64.1434% N=317 Z=-13.9(11.80%) | Like=-2.11..-0.15 [-2.1230..-2.0268] | it/evals=3520/11559 eff=64.4805% N=317 Z=-13.9(12.26%) | Like=-2.10..-0.15 [-2.1230..-2.0268] | it/evals=3525/11687 eff=62.1056% N=317 Z=-13.7(14.47%) | Like=-2.00..-0.15 [-2.0266..-1.9746] | it/evals=3552/11687 eff=62.2235% N=317 Z=-13.6(17.27%) | Like=-1.81..-0.15 [-1.8111..-1.8053]*| it/evals=3584/11687 eff=62.4300% N=317 Z=-13.5(18.57%) | Like=-1.76..-0.15 [-1.7615..-1.7597]*| it/evals=3600/11687 eff=62.4595% N=317 Z=-13.2(25.71%) | Like=-1.42..-0.02 [-1.4249..-1.4230]*| it/evals=3672/11687 eff=62.8723% N=317 Z=-12.9(34.00%) | Like=-1.08..-0.02 [-1.0809..-1.0800]*| it/evals=3745/11687 eff=63.1672% N=317 Z=-12.7(43.03%) | Like=-0.81..-0.02 [-0.8056..-0.7950] | it/evals=3825/11687 eff=63.5506% N=317 Z=-12.6(44.75%) | Like=-0.75..-0.02 [-0.7524..-0.7519]*| it/evals=3840/11815 eff=61.3242% N=317 Z=-12.6(48.49%) | Like=-0.68..-0.02 [-0.6754..-0.6735]*| it/evals=3872/11815 eff=61.5516% N=317 Z=-12.5(51.50%) | Like=-0.62..-0.02 [-0.6219..-0.6213]*| it/evals=3898/11815 eff=61.6937% N=317 Z=-12.4(59.23%) | Like=-0.49..-0.02 [-0.4913..-0.4911]*| it/evals=3971/11815 eff=62.0063% N=317 Z=-12.3(64.94%) | Like=-0.40..-0.01 [-0.4028..-0.4027]*| it/evals=4032/11815 eff=62.3757% N=317 Z=-12.2(66.31%) | Like=-0.39..-0.01 [-0.3886..-0.3884]*| it/evals=4047/11815 eff=62.4041% N=317 Z=-12.2(72.11%) | Like=-0.31..-0.00 [-0.3051..-0.3033]*| it/evals=4119/11815 eff=62.8303% N=317 Z=-12.1(77.02%) | Like=-0.25..-0.00 [-0.2471..-0.2470]*| it/evals=4190/11943 eff=60.8994% N=317 Z=-12.1(79.08%) | Like=-0.22..-0.00 [-0.2192..-0.2183]*| it/evals=4224/11943 eff=61.0639% N=317 Z=-12.0(81.72%) | Like=-0.19..-0.00 [-0.1877..-0.1873]*| it/evals=4271/11943 eff=61.2558% N=317 Z=-12.0(85.49%) | Like=-0.15..-0.00 [-0.1473..-0.1470]*| it/evals=4351/11943 eff=61.5574% N=317 Z=-12.0(88.74%) | Like=-0.11..-0.00 [-0.1102..-0.1092]*| it/evals=4437/11943 eff=61.8316% N=317 Z=-11.9(91.00%) | Like=-0.09..-0.00 [-0.0883..-0.0882]*| it/evals=4512/12071 eff=60.0795% N=317 Z=-11.9(92.79%) | Like=-0.07..-0.00 [-0.0703..-0.0698]*| it/evals=4585/12071 eff=60.3974% N=317 Z=-11.9(94.25%) | Like=-0.05..-0.00 [-0.0538..-0.0534]*| it/evals=4659/12071 eff=60.7417% N=317 Z=-11.9(95.41%) | Like=-0.04..-0.00 [-0.0407..-0.0405]*| it/evals=4732/12071 eff=61.1391% N=317 Z=-11.9(96.44%) | Like=-0.03..-0.00 [-0.0317..-0.0317]*| it/evals=4814/12199 eff=59.4158% N=317 Z=-11.9(96.95%) | Like=-0.03..-0.00 [-0.0274..-0.0273]*| it/evals=4864/12199 eff=59.6977% N=317 Z=-11.9(97.15%) | Like=-0.03..-0.00 [-0.0252..-0.0252]*| it/evals=4886/12199 eff=59.8002% N=317 Z=-11.9(97.77%) | Like=-0.02..-0.00 [-0.0197..-0.0196]*| it/evals=4965/12199 eff=59.9283% N=317 Z=-11.9(98.24%) | Like=-0.02..-0.00 [-0.0157..-0.0155]*| it/evals=5041/12199 eff=60.1076% N=317 Z=-11.8(98.48%) | Like=-0.01..-0.00 [-0.0132..-0.0132]*| it/evals=5088/12199 eff=60.3382% N=317 Z=-11.8(98.62%) | Like=-0.01..-0.00 [-0.0116..-0.0116]*| it/evals=5118/12199 eff=60.4151% N=317 Z=-11.8(98.91%) | Like=-0.01..-0.00 [-0.0096..-0.0095]*| it/evals=5193/12327 eff=58.7447% N=317 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 12327 logzerr in iteration 0 0.2196993183606724 [ultranest] logZ = -11.91 +- 0.1636 [ultranest] Effective samples strategy satisfied (ESS = 1275.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.33 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 684 minimum live points (dlogz from 0.14 to 0.39, need <0.1) [ultranest] logZ error budget: single: 0.20 bs:0.16 tail:0.00 total:0.16 required:<0.10 [ultranest] Widening roots to 684 live points (have 317 already) ... [ultranest] Sampling 367 live points from prior ... Z=-inf(0.00%) | Like=-245997.63..-0.00 [-245997.6291..-81232.4708] | it/evals=0/12822 eff=0.0000% N=684 Z=-187609.4(0.00%) | Like=-186405.10..-0.00 [-245997.6291..-81232.4708] | it/evals=32/12822 eff=12.5000% N=684 Z=-161455.3(0.00%) | Like=-161381.59..-0.00 [-245997.6291..-81232.4708] | it/evals=64/12822 eff=24.2188% N=684 Z=-126861.1(0.00%) | Like=-126691.41..-0.00 [-245997.6291..-81232.4708] | it/evals=153/12822 eff=60.1562% N=684 Z=-124993.8(0.00%) | Like=-124623.45..-0.00 [-245997.6291..-81232.4708] | it/evals=160/12822 eff=64.0625% N=684 Z=-117214.0(0.00%) | Like=-116938.49..-0.00 [-245997.6291..-81232.4708] | it/evals=192/12822 eff=75.7812% N=684 Z=-97355.7(0.00%) | Like=-97219.05..-0.00 [-245997.6291..-81232.4708] | it/evals=306/12936 eff=65.7025% N=684 Z=-95807.3(0.00%) | Like=-95734.25..-0.00 [-245997.6291..-81232.4708] | it/evals=320/12936 eff=68.1818% N=684 Z=-91971.2(0.00%) | Like=-91886.49..-0.00 [-245997.6291..-81232.4708] | it/evals=352/12936 eff=76.0331% N=684 Z=-82305.9(0.00%) | Like=-82247.48..-0.00 [-245997.6291..-81232.4708] | it/evals=448/13021 eff=70.6422% N=684 Z=-81427.2(0.00%) | Like=-81363.91..-0.00 [-245997.6291..-81232.4708] | it/evals=459/13021 eff=73.0887% N=684 Z=-64179.3(0.00%) | Like=-64076.33..-0.00 [-81125.3031..-39471.8305] | it/evals=613/13109 eff=78.7952% N=684 Z=-62083.5(0.00%) | Like=-62055.51..-0.00 [-81125.3031..-39471.8305] | it/evals=640/13167 eff=71.6702% N=684 Z=-55598.4(0.00%) | Like=-55501.50..-0.00 [-81125.3031..-39471.8305] | it/evals=704/13167 eff=77.8013% N=684 Z=-53118.4(0.00%) | Like=-53083.22..-0.00 [-81125.3031..-39471.8305] | it/evals=736/13227 eff=72.0450% N=684 Z=-51060.5(0.00%) | Like=-50944.30..-0.00 [-81125.3031..-39471.8305] | it/evals=766/13227 eff=75.4221% N=684 Z=-50898.5(0.00%) | Like=-50831.91..-0.00 [-81125.3031..-39471.8305] | it/evals=768/13227 eff=75.7974% N=684 Z=-46496.9(0.00%) | Like=-46183.72..-0.00 [-81125.3031..-39471.8305] | it/evals=832/13279 eff=76.4103% N=684 Z=-40286.5(0.00%) | Like=-40211.90..-0.00 [-81125.3031..-39471.8305] | it/evals=920/13362 eff=73.8024% N=684 Z=-39698.9(0.00%) | Like=-39683.11..-0.00 [-81125.3031..-39471.8305] | it/evals=928/13362 eff=74.4012% N=684 Z=-36753.0(0.00%) | Like=-36476.24..-0.00 [-39431.9524..-20053.8866] | it/evals=992/13401 eff=75.3890% N=684 Z=-32856.3(0.00%) | Like=-32828.11..-0.00 [-39431.9524..-20053.8866] | it/evals=1056/13440 eff=76.1394% N=684 Z=-32044.0(0.00%) | Like=-32010.20..-0.00 [-39431.9524..-20053.8866] | it/evals=1073/13481 eff=73.8247% N=684 Z=-31324.1(0.00%) | Like=-31219.37..-0.00 [-39431.9524..-20053.8866] | it/evals=1088/13481 eff=74.3329% N=684 Z=-28767.8(0.00%) | Like=-28745.22..-0.00 [-39431.9524..-20053.8866] | it/evals=1152/13510 eff=75.4902% N=684 Z=-27662.9(0.00%) | Like=-27410.93..-0.00 [-39431.9524..-20053.8866] | it/evals=1184/13538 eff=75.4739% N=684 Z=-26376.7(0.00%) | Like=-26340.93..-0.00 [-39431.9524..-20053.8866] | it/evals=1216/13571 eff=75.0285% N=684 Z=-25891.9(0.00%) | Like=-25883.36..-0.00 [-39431.9524..-20053.8866] | it/evals=1226/13571 eff=75.8267% N=684 Z=-23501.0(0.00%) | Like=-23478.71..-0.00 [-39431.9524..-20053.8866] | it/evals=1280/13599 eff=76.4641% N=684 Z=-20787.7(0.00%) | Like=-20770.24..-0.00 [-39431.9524..-20053.8866] | it/evals=1376/13676 eff=75.6619% N=684 Z=-20721.9(0.00%) | Like=-20701.67..-0.00 [-39431.9524..-20053.8866] | it/evals=1379/13676 eff=75.9674% N=684 Z=-17968.4(0.00%) | Like=-17940.01..-0.00 [-20045.2935..-9311.7228] | it/evals=1472/13748 eff=75.7116% N=684 Z=-17203.8(0.00%) | Like=-17165.16..-0.00 [-20045.2935..-9311.7228] | it/evals=1504/13774 eff=75.3704% N=684 Z=-16506.9(0.00%) | Like=-16495.21..-0.00 [-20045.2935..-9311.7228] | it/evals=1532/13787 eff=76.0293% N=684 Z=-16431.1(0.00%) | Like=-16396.53..-0.00 [-20045.2935..-9311.7228] | it/evals=1536/13801 eff=75.2484% N=684 Z=-15454.6(0.00%) | Like=-15437.84..-0.00 [-20045.2935..-9311.7228] | it/evals=1568/13824 eff=75.4867% N=684 Z=-14760.1(0.00%) | Like=-14716.26..-0.00 [-20045.2935..-9311.7228] | it/evals=1600/13839 eff=76.0699% N=684 Z=-13227.5(0.00%) | Like=-13205.51..-0.00 [-20045.2935..-9311.7228] | it/evals=1664/13896 eff=75.5408% N=684 Z=-12861.1(0.00%) | Like=-12832.47..-0.00 [-20045.2935..-9311.7228] | it/evals=1685/13913 eff=75.4717% N=684 Z=-12709.2(0.00%) | Like=-12690.15..-0.00 [-20045.2935..-9311.7228] | it/evals=1696/13921 eff=75.5501% N=684 Z=-12143.4(0.00%) | Like=-12109.35..-0.00 [-20045.2935..-9311.7228] | it/evals=1728/13946 eff=75.3994% N=684 Z=-11044.1(0.00%) | Like=-11032.09..-0.00 [-20045.2935..-9311.7228] | it/evals=1792/13986 eff=75.4644% N=684 Z=-10425.2(0.00%) | Like=-10391.11..-0.00 [-20045.2935..-9311.7228] | it/evals=1838/14017 eff=75.4346% N=684 Z=-9665.2(0.00%) | Like=-9652.87..-0.00 [-20045.2935..-9311.7228] | it/evals=1888/14056 eff=75.3304% N=684 Z=-9171.3(0.00%) | Like=-9130.80..-0.00 [-9305.2933..-4646.4641] | it/evals=1920/14074 eff=75.5797% N=684 Z=-8182.8(0.00%) | Like=-8144.74..-0.00 [-9305.2933..-4646.4641] | it/evals=1984/14128 eff=74.8257% N=684 Z=-8087.4(0.00%) | Like=-8076.70..-0.00 [-9305.2933..-4646.4641] | it/evals=1991/14128 eff=75.0349% N=684 Z=-7663.8(0.00%) | Like=-7631.84..-0.00 [-9305.2933..-4646.4641] | it/evals=2016/14143 eff=75.0863% N=684 Z=-7040.2(0.00%) | Like=-7029.29..-0.00 [-9305.2933..-4646.4641] | it/evals=2080/14182 eff=75.4032% N=684 Z=-6723.6(0.00%) | Like=-6709.37..-0.00 [-9305.2933..-4646.4641] | it/evals=2112/14197 eff=75.2495% N=684 Z=-6516.9(0.00%) | Like=-6501.72..-0.00 [-9305.2933..-4646.4641] | it/evals=2145/14227 eff=74.9511% N=684 Z=-5352.9(0.00%) | Like=-5336.39..-0.00 [-9305.2933..-4646.4641] | it/evals=2272/14299 eff=75.2648% N=684 Z=-5178.1(0.00%) | Like=-5164.18..-0.00 [-9305.2933..-4646.4641] | it/evals=2298/14310 eff=75.4950% N=684 Z=-4253.4(0.00%) | Like=-4241.59..-0.00 [-4634.1264..-2467.0091] | it/evals=2436/14398 eff=75.3521% N=684 Z=-4182.7(0.00%) | Like=-4170.30..-0.00 [-4634.1264..-2467.0091] | it/evals=2451/14407 eff=75.4816% N=684 Z=-4081.7(0.00%) | Like=-4069.29..-0.00 [-4634.1264..-2467.0091] | it/evals=2464/14416 eff=75.4355% N=684 Z=-3733.5(0.00%) | Like=-3721.18..-0.00 [-4634.1264..-2467.0091] | it/evals=2528/14459 eff=75.8074% N=684 Z=-3555.6(0.00%) | Like=-3543.84..-0.00 [-4634.1264..-2467.0091] | it/evals=2560/14483 eff=75.9083% N=684 Z=-3408.8(0.00%) | Like=-3397.38..-0.00 [-4634.1264..-2467.0091] | it/evals=2592/14504 eff=75.9116% N=684 Z=-3362.3(0.00%) | Like=-3351.36..-0.00 [-4634.1264..-2467.0091] | it/evals=2605/14516 eff=75.8507% N=684 Z=-3255.8(0.00%) | Like=-3242.69..-0.00 [-4634.1264..-2467.0091] | it/evals=2624/14527 eff=75.9411% N=684 Z=-3054.5(0.00%) | Like=-3036.35..-0.00 [-4634.1264..-2467.0091] | it/evals=2656/14546 eff=75.9179% N=684 Z=-2945.7(0.00%) | Like=-2931.48..-0.00 [-4634.1264..-2467.0091] | it/evals=2688/14577 eff=75.6240% N=684 Z=-2673.9(0.00%) | Like=-2660.40..-0.00 [-4634.1264..-2467.0091] | it/evals=2758/14631 eff=75.5292% N=684 Z=-2579.0(0.00%) | Like=-2561.40..-0.00 [-4634.1264..-2467.0091] | it/evals=2784/14652 eff=75.4341% N=684 Z=-2462.3(0.00%) | Like=-2444.29..-0.00 [-2466.9117..-1268.6170] | it/evals=2816/14675 eff=75.6689% N=684 Z=-2117.6(0.00%) | Like=-2106.38..-0.00 [-2466.9117..-1268.6170] | it/evals=2912/14851 eff=72.0445% N=684 Z=-2035.8(0.00%) | Like=-2022.74..-0.00 [-2466.9117..-1268.6170] | it/evals=2944/14851 eff=72.8790% N=684 Z=-1984.8(0.00%) | Like=-1972.57..-0.00 [-2466.9117..-1268.6170] | it/evals=2976/14851 eff=73.7135% N=684 Z=-1878.9(0.00%) | Like=-1863.53..-0.00 [-2466.9117..-1268.6170] | it/evals=3008/14851 eff=74.4553% N=684 Z=-1806.3(0.00%) | Like=-1792.98..-0.00 [-2466.9117..-1268.6170] | it/evals=3040/14863 eff=75.1037% N=684 Z=-1743.3(0.00%) | Like=-1730.24..-0.00 [-2466.9117..-1268.6170] | it/evals=3065/14997 eff=71.2983% N=684 Z=-1718.4(0.00%) | Like=-1702.34..-0.00 [-2466.9117..-1268.6170] | it/evals=3072/14997 eff=71.4720% N=684 Z=-1484.8(0.00%) | Like=-1471.64..-0.00 [-2466.9117..-1268.6170] | it/evals=3168/14997 eff=73.6431% N=684 Z=-1399.2(0.00%) | Like=-1381.92..-0.00 [-2466.9117..-1268.6170] | it/evals=3218/15000 eff=74.7181% N=684 Z=-1369.5(0.00%) | Like=-1356.96..-0.00 [-2466.9117..-1268.6170] | it/evals=3232/15138 eff=70.9902% N=684 Z=-1269.3(0.00%) | Like=-1257.57..-0.00 [-1267.9975..-643.9316] | it/evals=3296/15138 eff=72.3404% N=684 Z=-1218.7(0.00%) | Like=-1207.31..-0.00 [-1267.9975..-643.9316] | it/evals=3320/15138 eff=72.8723% N=684 Z=-1211.0(0.00%) | Like=-1198.20..-0.00 [-1267.9975..-643.9316] | it/evals=3328/15138 eff=73.1588% N=684 Z=-1108.0(0.00%) | Like=-1095.95..-0.00 [-1267.9975..-643.9316] | it/evals=3392/15138 eff=74.6727% N=684 Z=-1053.3(0.00%) | Like=-1039.44..-0.00 [-1267.9975..-643.9316] | it/evals=3424/15277 eff=71.3124% N=684 Z=-1009.7(0.00%) | Like=-997.35..-0.00 [-1267.9975..-643.9316] | it/evals=3453/15277 eff=71.7770% N=684 Z=-910.8(0.00%) | Like=-899.90..-0.00 [-1267.9975..-643.9316] | it/evals=3520/15277 eff=73.0933% N=684 Z=-868.7(0.00%) | Like=-855.04..-0.00 [-1267.9975..-643.9316] | it/evals=3552/15277 eff=73.6353% N=684 Z=-830.2(0.00%) | Like=-818.44..-0.00 [-1267.9975..-643.9316] | it/evals=3584/15405 eff=70.8963% N=684 Z=-795.5(0.00%) | Like=-784.17..-0.00 [-1267.9975..-643.9316] | it/evals=3608/15405 eff=71.2283% N=684 Z=-756.4(0.00%) | Like=-744.32..-0.00 [-1267.9975..-643.9316] | it/evals=3648/15405 eff=72.0767% N=684 Z=-725.7(0.00%) | Like=-713.19..-0.00 [-1267.9975..-643.9316] | it/evals=3680/15405 eff=72.8882% N=684 Z=-701.4(0.00%) | Like=-689.19..-0.00 [-1267.9975..-643.9316] | it/evals=3712/15405 eff=73.2571% N=684 Z=-673.6(0.00%) | Like=-662.07..-0.00 [-1267.9975..-643.9316] | it/evals=3744/15535 eff=70.4681% N=684 Z=-655.8(0.00%) | Like=-643.74..-0.00 [-643.7386..-332.5924] | it/evals=3761/15535 eff=70.8201% N=684 Z=-614.3(0.00%) | Like=-602.28..-0.00 [-643.7386..-332.5924] | it/evals=3808/15535 eff=71.9113% N=684 Z=-592.7(0.00%) | Like=-582.26..-0.00 [-643.7386..-332.5924] | it/evals=3840/15535 eff=72.4393% N=684 Z=-531.7(0.00%) | Like=-519.27..-0.00 [-643.7386..-332.5924] | it/evals=3915/15666 eff=70.6258% N=684 Z=-430.1(0.00%) | Like=-418.12..-0.00 [-643.7386..-332.5924] | it/evals=4054/15794 eff=70.0645% N=684 Z=-425.6(0.00%) | Like=-413.07..-0.00 [-643.7386..-332.5924] | it/evals=4064/15794 eff=70.2903% N=684 Z=-421.9(0.00%) | Like=-409.43..-0.00 [-643.7386..-332.5924] | it/evals=4069/15794 eff=70.3871% N=684 Z=-389.6(0.00%) | Like=-376.91..-0.00 [-643.7386..-332.5924] | it/evals=4128/15794 eff=71.4516% N=684 Z=-372.9(0.00%) | Like=-361.35..-0.00 [-643.7386..-332.5924] | it/evals=4160/15794 eff=72.0000% N=684 Z=-337.8(0.00%) | Like=-324.36..-0.00 [-331.8152..-159.3144] | it/evals=4226/15922 eff=70.1053% N=684 Z=-296.1(0.00%) | Like=-284.28..-0.00 [-331.8152..-159.3144] | it/evals=4320/15922 eff=71.4994% N=684 Z=-279.9(0.00%) | Like=-267.68..-0.00 [-331.8152..-159.3144] | it/evals=4352/16050 eff=69.3683% N=684 Z=-268.9(0.00%) | Like=-257.11..-0.00 [-331.8152..-159.3144] | it/evals=4379/16050 eff=69.7259% N=684 Z=-267.0(0.00%) | Like=-254.70..-0.00 [-331.8152..-159.3144] | it/evals=4384/16050 eff=69.8451% N=684 Z=-255.4(0.00%) | Like=-242.85..-0.00 [-331.8152..-159.3144] | it/evals=4416/16050 eff=70.3218% N=684 Z=-243.9(0.00%) | Like=-232.03..-0.00 [-331.8152..-159.3144] | it/evals=4448/16050 eff=70.9774% N=684 Z=-233.1(0.00%) | Like=-221.16..-0.00 [-331.8152..-159.3144] | it/evals=4473/16050 eff=71.3349% N=684 Z=-230.1(0.00%) | Like=-217.50..-0.00 [-331.8152..-159.3144] | it/evals=4480/16050 eff=71.5137% N=684 Z=-218.9(0.00%) | Like=-207.04..-0.00 [-331.8152..-159.3144] | it/evals=4512/16178 eff=69.4030% N=684 Z=-209.1(0.00%) | Like=-196.76..-0.00 [-331.8152..-159.3144] | it/evals=4544/16178 eff=69.9483% N=684 Z=-186.3(0.00%) | Like=-174.58..-0.00 [-331.8152..-159.3144] | it/evals=4626/16178 eff=71.1825% N=684 Z=-181.9(0.00%) | Like=-170.09..-0.00 [-331.8152..-159.3144] | it/evals=4643/16178 eff=71.4122% N=684 Z=-175.4(0.00%) | Like=-163.13..-0.00 [-331.8152..-159.3144] | it/evals=4672/16306 eff=69.4075% N=684 Z=-148.0(0.00%) | Like=-135.88..-0.00 [-159.0852..-76.9488] | it/evals=4804/16306 eff=71.4563% N=684 Z=-143.0(0.00%) | Like=-131.19..-0.00 [-159.0852..-76.9488] | it/evals=4832/16306 eff=71.8162% N=684 Z=-130.6(0.00%) | Like=-118.67..-0.00 [-159.0852..-76.9488] | it/evals=4896/16434 eff=70.3743% N=684 Z=-128.3(0.00%) | Like=-115.92..-0.00 [-159.0852..-76.9488] | it/evals=4907/16434 eff=70.5080% N=684 Z=-124.4(0.00%) | Like=-112.47..-0.00 [-159.0852..-76.9488] | it/evals=4928/16434 eff=70.8021% N=684 Z=-123.4(0.00%) | Like=-111.74..-0.00 [-159.0852..-76.9488] | it/evals=4934/16434 eff=70.8289% N=684 Z=-118.9(0.00%) | Like=-107.33..-0.00 [-159.0852..-76.9488] | it/evals=4965/16434 eff=71.1765% N=684 Z=-118.5(0.00%) | Like=-106.72..-0.00 [-159.0852..-76.9488] | it/evals=4969/16434 eff=71.2032% N=684 Z=-115.0(0.00%) | Like=-103.05..-0.00 [-159.0852..-76.9488] | it/evals=4992/16434 eff=71.6845% N=684 Z=-111.8(0.00%) | Like=-99.74..-0.00 [-159.0852..-76.9488] | it/evals=5006/16562 eff=69.4416% N=684 Z=-111.4(0.00%) | Like=-99.54..-0.00 [-159.0852..-76.9488] | it/evals=5009/16562 eff=69.4674% N=684 Z=-105.5(0.00%) | Like=-93.70..-0.00 [-159.0852..-76.9488] | it/evals=5048/16562 eff=70.1138% N=684 Z=-102.8(0.00%) | Like=-90.95..-0.00 [-159.0852..-76.9488] | it/evals=5070/16562 eff=70.5016% N=684 Z=-99.8(0.00%) | Like=-87.49..-0.00 [-159.0852..-76.9488] | it/evals=5088/16562 eff=70.8376% N=684 Z=-90.4(0.00%) | Like=-78.23..-0.00 [-159.0852..-76.9488] | it/evals=5152/16562 eff=71.7166% N=684 Z=-86.6(0.00%) | Like=-74.52..-0.00 [-76.9377..-37.2756] | it/evals=5184/16691 eff=69.8274% N=684 Z=-83.5(0.00%) | Like=-71.83..-0.00 [-76.9377..-37.2756] | it/evals=5216/16691 eff=70.2777% N=684 Z=-82.7(0.00%) | Like=-70.96..-0.00 [-76.9377..-37.2756] | it/evals=5225/16691 eff=70.4028% N=684 Z=-81.1(0.00%) | Like=-68.97..-0.00 [-76.9377..-37.2756] | it/evals=5242/16691 eff=70.5279% N=684 Z=-80.4(0.00%) | Like=-68.49..-0.00 [-76.9377..-37.2756] | it/evals=5248/16691 eff=70.6530% N=684 Z=-78.6(0.00%) | Like=-66.57..-0.00 [-76.9377..-37.2756] | it/evals=5268/16691 eff=70.8531% N=684 Z=-77.3(0.00%) | Like=-65.21..-0.00 [-76.9377..-37.2756] | it/evals=5280/16691 eff=71.0033% N=684 Z=-75.7(0.00%) | Like=-63.94..-0.00 [-76.9377..-37.2756] | it/evals=5299/16691 eff=71.2534% N=684 Z=-74.7(0.00%) | Like=-62.61..-0.00 [-76.9377..-37.2756] | it/evals=5312/16691 eff=71.5286% N=684 Z=-74.2(0.00%) | Like=-62.03..-0.00 [-76.9377..-37.2756] | it/evals=5317/16691 eff=71.5537% N=684 Z=-69.5(0.00%) | Like=-57.77..-0.00 [-76.9377..-37.2756] | it/evals=5376/16819 eff=70.1333% N=684 Z=-67.1(0.00%) | Like=-55.15..-0.00 [-76.9377..-37.2756] | it/evals=5409/16819 eff=70.5939% N=684 Z=-62.8(0.00%) | Like=-50.80..-0.00 [-76.9377..-37.2756] | it/evals=5454/16819 eff=71.2485% N=684 Z=-61.5(0.00%) | Like=-49.57..-0.00 [-76.9377..-37.2756] | it/evals=5472/16819 eff=71.6121% N=684 Z=-60.9(0.00%) | Like=-48.98..-0.00 [-76.9377..-37.2756] | it/evals=5480/16819 eff=71.6606% N=684 Z=-58.8(0.00%) | Like=-46.82..-0.00 [-76.9377..-37.2756] | it/evals=5510/16947 eff=69.8331% N=684 Z=-58.2(0.00%) | Like=-46.15..-0.00 [-76.9377..-37.2756] | it/evals=5518/16947 eff=69.9036% N=684 Z=-57.5(0.00%) | Like=-45.58..-0.00 [-76.9377..-37.2756] | it/evals=5527/16947 eff=69.9741% N=684 Z=-54.8(0.00%) | Like=-42.92..-0.00 [-76.9377..-37.2756] | it/evals=5568/16947 eff=70.6325% N=684 Z=-51.4(0.00%) | Like=-39.32..-0.00 [-76.9377..-37.2756] | it/evals=5617/16947 eff=71.2438% N=684 Z=-50.2(0.00%) | Like=-38.13..-0.00 [-76.9377..-37.2756] | it/evals=5634/16947 eff=71.5025% N=684 Z=-49.6(0.00%) | Like=-37.22..-0.00 [-37.2169..-17.5865] | it/evals=5641/16947 eff=71.5730% N=684 Z=-48.9(0.00%) | Like=-36.77..-0.00 [-37.2169..-17.5865] | it/evals=5650/16947 eff=71.6200% N=684 Z=-47.9(0.00%) | Like=-35.90..-0.00 [-37.2169..-17.5865] | it/evals=5664/17075 eff=69.7786% N=684 Z=-46.3(0.00%) | Like=-34.58..-0.00 [-37.2169..-17.5865] | it/evals=5696/17075 eff=70.3036% N=684 Z=-45.6(0.00%) | Like=-33.92..-0.00 [-37.2169..-17.5865] | it/evals=5713/17075 eff=70.4634% N=684 Z=-44.8(0.00%) | Like=-32.89..-0.00 [-37.2169..-17.5865] | it/evals=5728/17075 eff=70.7373% N=684 Z=-43.7(0.00%) | Like=-31.70..-0.00 [-37.2169..-17.5865] | it/evals=5754/17075 eff=71.0112% N=684 Z=-43.3(0.00%) | Like=-31.11..-0.00 [-37.2169..-17.5865] | it/evals=5760/17075 eff=71.1481% N=684 Z=-42.3(0.00%) | Like=-30.08..-0.00 [-37.2169..-17.5865] | it/evals=5779/17075 eff=71.3764% N=684 Z=-39.8(0.00%) | Like=-27.65..-0.00 [-37.2169..-17.5865] | it/evals=5826/17075 eff=71.8557% N=684 Z=-39.3(0.00%) | Like=-27.15..-0.00 [-37.2169..-17.5865] | it/evals=5836/17075 eff=71.9699% N=684 Z=-38.9(0.00%) | Like=-26.83..-0.00 [-37.2169..-17.5865] | it/evals=5843/17204 eff=69.9778% N=684 Z=-38.3(0.00%) | Like=-26.46..-0.00 [-37.2169..-17.5865] | it/evals=5856/17204 eff=70.1552% N=684 Z=-38.0(0.00%) | Like=-25.95..-0.00 [-37.2169..-17.5865] | it/evals=5864/17204 eff=70.1996% N=684 Z=-37.4(0.00%) | Like=-25.29..-0.00 [-37.2169..-17.5865] | it/evals=5875/17204 eff=70.3104% N=684 Z=-36.7(0.00%) | Like=-24.68..-0.00 [-37.2169..-17.5865] | it/evals=5891/17204 eff=70.4656% N=684 Z=-36.4(0.00%) | Like=-24.51..-0.00 [-37.2169..-17.5865] | it/evals=5898/17204 eff=70.5100% N=684 Z=-35.7(0.00%) | Like=-23.79..-0.00 [-37.2169..-17.5865] | it/evals=5917/17204 eff=70.8204% N=684 Z=-35.6(0.00%) | Like=-23.68..-0.00 [-37.2169..-17.5865] | it/evals=5920/17204 eff=70.8647% N=684 Z=-35.1(0.00%) | Like=-23.33..-0.00 [-37.2169..-17.5865] | it/evals=5933/17204 eff=71.0200% N=684 Z=-33.4(0.00%) | Like=-21.69..-0.00 [-37.2169..-17.5865] | it/evals=5982/17204 eff=71.6630% N=684 Z=-33.4(0.00%) | Like=-21.67..-0.00 [-37.2169..-17.5865] | it/evals=5984/17204 eff=71.6851% N=684 Z=-33.0(0.00%) | Like=-21.37..-0.00 [-37.2169..-17.5865] | it/evals=5997/17204 eff=71.7960% N=684 Z=-32.4(0.00%) | Like=-20.57..-0.00 [-37.2169..-17.5865] | it/evals=6016/17204 eff=71.8847% N=684 Z=-31.4(0.00%) | Like=-19.55..-0.00 [-37.2169..-17.5865] | it/evals=6048/17332 eff=70.3320% N=684 Z=-30.5(0.00%) | Like=-18.65..-0.00 [-37.2169..-17.5865] | it/evals=6080/17332 eff=70.7201% N=684 Z=-29.8(0.00%) | Like=-18.06..-0.00 [-37.2169..-17.5865] | it/evals=6106/17332 eff=71.0004% N=684 Z=-28.6(0.00%) | Like=-16.94..-0.00 [-17.5830..-8.7075] | it/evals=6156/17332 eff=71.1945% N=684 Z=-28.1(0.00%) | Like=-16.29..-0.00 [-17.5830..-8.7075] | it/evals=6180/17332 eff=71.3670% N=684 Z=-27.9(0.00%) | Like=-16.05..-0.00 [-17.5830..-8.7075] | it/evals=6189/17332 eff=71.4317% N=684 Z=-27.7(0.00%) | Like=-15.90..-0.00 [-17.5830..-8.7075] | it/evals=6198/17332 eff=71.4532% N=684 Z=-27.5(0.00%) | Like=-15.72..-0.00 [-17.5830..-8.7075] | it/evals=6207/17332 eff=71.5395% N=684 Z=-27.4(0.00%) | Like=-15.68..-0.00 [-17.5830..-8.7075] | it/evals=6208/17332 eff=71.5610% N=684 Z=-26.5(0.00%) | Like=-14.74..-0.00 [-17.5830..-8.7075] | it/evals=6247/17332 eff=72.0569% N=684 Z=-26.3(0.00%) | Like=-14.43..-0.00 [-17.5830..-8.7075] | it/evals=6261/17332 eff=72.2078% N=684 Z=-25.2(0.00%) | Like=-13.47..-0.00 [-17.5830..-8.7075] | it/evals=6317/17460 eff=70.9820% N=684 Z=-24.8(0.00%) | Like=-13.02..-0.00 [-17.5830..-8.7075] | it/evals=6336/17460 eff=71.3386% N=684 Z=-24.4(0.00%) | Like=-12.55..-0.00 [-17.5830..-8.7075] | it/evals=6364/17460 eff=71.5695% N=684 Z=-24.0(0.00%) | Like=-12.13..-0.00 [-17.5830..-8.7075] | it/evals=6382/17460 eff=71.6534% N=684 Z=-23.6(0.00%) | Like=-11.79..-0.00 [-17.5830..-8.7075] | it/evals=6404/17460 eff=71.8422% N=684 Z=-22.6(0.00%) | Like=-10.83..-0.00 [-17.5830..-8.7075] | it/evals=6465/17460 eff=72.1569% N=684 Z=-22.5(0.00%) | Like=-10.78..-0.00 [-17.5830..-8.7075] | it/evals=6473/17460 eff=72.2199% N=684 Z=-22.3(0.00%) | Like=-10.46..-0.00 [-17.5830..-8.7075] | it/evals=6489/17588 eff=70.5149% N=684 Z=-22.2(0.00%) | Like=-10.36..-0.00 [-17.5830..-8.7075] | it/evals=6496/17588 eff=70.6171% N=684 Z=-22.0(0.00%) | Like=-10.14..-0.00 [-17.5830..-8.7075] | it/evals=6508/17588 eff=70.6988% N=684 Z=-21.8(0.00%) | Like=-10.02..-0.00 [-17.5830..-8.7075] | it/evals=6518/17588 eff=70.8214% N=684 Z=-21.2(0.01%) | Like=-9.40..-0.00 [-17.5830..-8.7075] | it/evals=6560/17588 eff=71.3527% N=684 Z=-21.0(0.01%) | Like=-9.07..-0.00 [-17.5830..-8.7075] | it/evals=6579/17588 eff=71.5774% N=684 Z=-20.8(0.01%) | Like=-8.88..-0.00 [-17.5830..-8.7075] | it/evals=6592/17588 eff=71.8022% N=684 Z=-20.4(0.02%) | Like=-8.43..-0.00 [-8.6784..-4.4277] | it/evals=6624/17588 eff=72.2517% N=684 Z=-19.6(0.04%) | Like=-7.67..-0.00 [-8.6784..-4.4277] | it/evals=6688/17716 eff=71.1868% N=684 Z=-19.2(0.07%) | Like=-7.33..-0.00 [-8.6784..-4.4277] | it/evals=6720/17716 eff=71.5253% N=684 Z=-19.1(0.08%) | Like=-7.25..-0.00 [-8.6784..-4.4277] | it/evals=6732/17716 eff=71.7045% N=684 Z=-18.9(0.09%) | Like=-7.05..-0.00 [-8.6784..-4.4277] | it/evals=6752/17716 eff=71.9434% N=684 Z=-18.5(0.13%) | Like=-6.74..-0.00 [-8.6784..-4.4277] | it/evals=6784/17844 eff=70.5437% N=684 Z=-18.0(0.23%) | Like=-6.25..-0.00 [-8.6784..-4.4277] | it/evals=6848/17844 eff=71.2233% N=684 Z=-17.7(0.30%) | Like=-6.04..-0.00 [-8.6784..-4.4277] | it/evals=6885/17844 eff=71.6117% N=684 Z=-17.5(0.37%) | Like=-5.90..-0.00 [-8.6784..-4.4277] | it/evals=6912/17844 eff=71.7087% N=684 Z=-17.1(0.56%) | Like=-5.31..-0.00 [-8.6784..-4.4277] | it/evals=6976/17972 eff=70.6518% N=684 Z=-16.9(0.70%) | Like=-5.08..-0.00 [-8.6784..-4.4277] | it/evals=7008/17972 eff=71.0496% N=684 Z=-16.7(0.86%) | Like=-4.85..-0.00 [-8.6784..-4.4277] | it/evals=7038/17972 eff=71.4475% N=684 Z=-16.6(0.87%) | Like=-4.83..-0.00 [-8.6784..-4.4277] | it/evals=7040/17972 eff=71.4854% N=684 Z=-16.2(1.30%) | Like=-4.37..-0.00 [-4.4214..-3.4531] | it/evals=7104/17972 eff=72.1485% N=684 Z=-16.0(1.57%) | Like=-4.13..-0.00 [-4.4214..-3.4531] | it/evals=7136/18100 eff=70.7917% N=684 Z=-15.8(1.88%) | Like=-3.95..-0.00 [-4.4214..-3.4531] | it/evals=7168/18100 eff=71.1062% N=684 Z=-15.7(2.18%) | Like=-3.79..-0.00 [-4.4214..-3.4531] | it/evals=7193/18100 eff=71.3097% N=684 Z=-15.6(2.28%) | Like=-3.76..-0.00 [-4.4214..-3.4531] | it/evals=7200/18100 eff=71.3836% N=684 Z=-15.5(2.71%) | Like=-3.56..-0.00 [-4.4214..-3.4531] | it/evals=7232/18100 eff=71.7536% N=684 Z=-15.1(3.76%) | Like=-3.25..-0.00 [-3.4370..-3.1979] | it/evals=7296/18228 eff=70.6903% N=684 Z=-14.9(4.84%) | Like=-3.00..-0.00 [-2.9955..-2.9920]*| it/evals=7346/18228 eff=71.1059% N=684 Z=-14.7(5.85%) | Like=-2.81..-0.00 [-2.8127..-2.8054]*| it/evals=7392/18228 eff=71.6299% N=684 Z=-14.6(6.67%) | Like=-2.67..-0.00 [-2.6700..-2.6691]*| it/evals=7424/18228 eff=71.8829% N=684 Z=-14.4(7.58%) | Like=-2.54..-0.00 [-2.5444..-2.5429]*| it/evals=7456/18356 eff=70.5758% N=684 Z=-14.3(8.46%) | Like=-2.42..-0.00 [-2.4244..-2.4222]*| it/evals=7488/18356 eff=70.8937% N=684 Z=-14.3(8.78%) | Like=-2.37..-0.00 [-2.3749..-2.3739]*| it/evals=7499/18356 eff=71.0173% N=684 Z=-14.2(9.54%) | Like=-2.30..-0.00 [-2.3035..-2.3032]*| it/evals=7520/18356 eff=71.1939% N=684 Z=-13.9(13.11%) | Like=-2.04..-0.00 [-2.0395..-2.0384]*| it/evals=7616/18356 eff=71.9887% N=684 Z=-13.8(14.40%) | Like=-1.95..-0.00 [-1.9533..-1.9525]*| it/evals=7648/18484 eff=70.6736% N=684 Z=-13.8(14.62%) | Like=-1.94..-0.00 [-1.9440..-1.9426]*| it/evals=7655/18484 eff=70.7081% N=684 Z=-13.4(20.12%) | Like=-1.61..-0.00 [-1.6148..-1.6144]*| it/evals=7782/18484 eff=71.7617% N=684 Z=-13.4(21.32%) | Like=-1.56..-0.00 [-1.5592..-1.5584]*| it/evals=7809/18612 eff=70.4123% N=684 Z=-13.2(26.31%) | Like=-1.36..-0.00 [-1.3566..-1.3508]*| it/evals=7904/18612 eff=71.3079% N=684 Z=-13.1(27.90%) | Like=-1.28..-0.00 [-1.2802..-1.2800]*| it/evals=7936/18612 eff=71.6627% N=684 Z=-13.1(29.34%) | Like=-1.24..-0.00 [-1.2413..-1.2369]*| it/evals=7963/18740 eff=70.3936% N=684 Z=-13.0(31.31%) | Like=-1.18..-0.00 [-1.1764..-1.1723]*| it/evals=8000/18740 eff=70.8071% N=684 Z=-13.0(33.05%) | Like=-1.12..-0.00 [-1.1213..-1.1202]*| it/evals=8032/18740 eff=71.0883% N=684 Z=-12.8(37.69%) | Like=-1.00..-0.00 [-0.9998..-0.9996]*| it/evals=8118/18868 eff=70.4730% N=684 Z=-12.8(38.20%) | Like=-0.99..-0.00 [-0.9875..-0.9875]*| it/evals=8128/18868 eff=70.6025% N=684 Z=-12.7(43.08%) | Like=-0.84..-0.00 [-0.8379..-0.8373]*| it/evals=8224/18996 eff=70.0413% N=684 Z=-12.7(44.83%) | Like=-0.80..-0.00 [-0.8004..-0.7995]*| it/evals=8256/18996 eff=70.2951% N=684 Z=-12.6(45.57%) | Like=-0.78..-0.00 [-0.7846..-0.7799]*| it/evals=8271/18996 eff=70.5173% N=684 Z=-12.6(48.06%) | Like=-0.73..-0.00 [-0.7335..-0.7326]*| it/evals=8320/18996 eff=70.9457% N=684 Z=-12.5(51.33%) | Like=-0.67..-0.00 [-0.6661..-0.6653]*| it/evals=8384/19124 eff=70.1244% N=684 Z=-12.5(52.90%) | Like=-0.64..-0.00 [-0.6429..-0.6428]*| it/evals=8416/19124 eff=70.4355% N=684 Z=-12.5(53.31%) | Like=-0.63..-0.00 [-0.6325..-0.6316]*| it/evals=8425/19124 eff=70.4821% N=684 Z=-12.4(55.98%) | Like=-0.59..-0.00 [-0.5858..-0.5855]*| it/evals=8480/19124 eff=70.9331% N=684 Z=-12.4(58.96%) | Like=-0.54..-0.00 [-0.5387..-0.5380]*| it/evals=8544/19252 eff=70.0976% N=684 Z=-12.4(60.42%) | Like=-0.52..-0.00 [-0.5153..-0.5150]*| it/evals=8576/19252 eff=70.3111% N=684 Z=-12.4(60.51%) | Like=-0.51..-0.00 [-0.5131..-0.5114]*| it/evals=8578/19252 eff=70.3416% N=684 Z=-12.3(61.79%) | Like=-0.49..-0.00 [-0.4851..-0.4848]*| it/evals=8608/19252 eff=70.5855% N=684 Z=-12.3(63.15%) | Like=-0.46..-0.00 [-0.4571..-0.4570]*| it/evals=8640/19252 eff=70.8600% N=684 Z=-12.2(66.94%) | Like=-0.40..-0.00 [-0.4014..-0.4010]*| it/evals=8734/19380 eff=70.2812% N=684 Z=-12.2(67.02%) | Like=-0.40..-0.00 [-0.4009..-0.4007]*| it/evals=8736/19380 eff=70.2961% N=684 Z=-12.2(68.27%) | Like=-0.38..-0.00 [-0.3804..-0.3793]*| it/evals=8768/19380 eff=70.5354% N=684 Z=-12.2(72.52%) | Like=-0.32..-0.00 [-0.3151..-0.3129]*| it/evals=8887/19508 eff=70.1497% N=684 Z=-12.2(73.90%) | Like=-0.29..-0.00 [-0.2917..-0.2915]*| it/evals=8928/19508 eff=70.3698% N=684 Z=-12.1(74.92%) | Like=-0.28..-0.00 [-0.2754..-0.2753]*| it/evals=8960/19508 eff=70.5753% N=684 Z=-12.1(76.89%) | Like=-0.25..-0.00 [-0.2547..-0.2546]*| it/evals=9024/19636 eff=69.7638% N=684 Z=-12.1(77.42%) | Like=-0.25..-0.00 [-0.2465..-0.2458]*| it/evals=9042/19636 eff=69.8646% N=684 Z=-12.1(77.82%) | Like=-0.24..-0.00 [-0.2401..-0.2400]*| it/evals=9056/19636 eff=70.0375% N=684 Z=-12.1(78.71%) | Like=-0.23..-0.00 [-0.2305..-0.2303]*| it/evals=9088/19636 eff=70.3111% N=684 Z=-12.1(80.41%) | Like=-0.21..-0.00 [-0.2074..-0.2064]*| it/evals=9152/19636 eff=70.7433% N=684 Z=-12.1(81.22%) | Like=-0.20..-0.00 [-0.1960..-0.1953]*| it/evals=9184/19764 eff=69.6888% N=684 Z=-12.1(81.50%) | Like=-0.19..-0.00 [-0.1922..-0.1920]*| it/evals=9195/19764 eff=69.7595% N=684 Z=-12.0(83.47%) | Like=-0.17..-0.00 [-0.1711..-0.1708]*| it/evals=9280/19764 eff=70.2829% N=684 Z=-12.0(84.83%) | Like=-0.15..-0.00 [-0.1532..-0.1531]*| it/evals=9344/19892 eff=69.5749% N=684 Z=-12.0(84.94%) | Like=-0.15..-0.00 [-0.1515..-0.1513]*| it/evals=9349/19892 eff=69.6166% N=684 Z=-12.0(86.10%) | Like=-0.14..-0.00 [-0.1421..-0.1416]*| it/evals=9408/19892 eff=70.0194% N=684 Z=-12.0(87.26%) | Like=-0.13..-0.00 [-0.1263..-0.1261]*| it/evals=9472/20020 eff=69.3557% N=684 Z=-12.0(87.79%) | Like=-0.12..-0.00 [-0.1216..-0.1214]*| it/evals=9503/20020 eff=69.6151% N=684 Z=-12.0(87.81%) | Like=-0.12..-0.00 [-0.1214..-0.1214]*| it/evals=9504/20020 eff=69.6287% N=684 Z=-12.0(88.33%) | Like=-0.12..-0.00 [-0.1157..-0.1157]*| it/evals=9536/20020 eff=69.8608% N=684 Z=-12.0(88.84%) | Like=-0.11..-0.00 [-0.1109..-0.1108]*| it/evals=9568/20020 eff=70.0928% N=684 Z=-12.0(89.32%) | Like=-0.11..-0.00 [-0.1071..-0.1071]*| it/evals=9600/20020 eff=70.3249% N=684 Z=-12.0(90.12%) | Like=-0.10..-0.00 [-0.0973..-0.0973]*| it/evals=9656/20148 eff=69.4795% N=684 Z=-11.9(91.45%) | Like=-0.08..-0.00 [-0.0828..-0.0827]*| it/evals=9760/20148 eff=70.1905% N=684 Z=-11.9(92.06%) | Like=-0.08..-0.00 [-0.0785..-0.0785]*| it/evals=9812/20276 eff=69.3748% N=684 Z=-11.9(92.19%) | Like=-0.08..-0.00 [-0.0778..-0.0777]*| it/evals=9824/20276 eff=69.4408% N=684 Z=-11.9(92.53%) | Like=-0.07..-0.00 [-0.0735..-0.0734]*| it/evals=9856/20276 eff=69.6914% N=684 Z=-11.9(92.86%) | Like=-0.07..-0.00 [-0.0691..-0.0690]*| it/evals=9888/20276 eff=69.8628% N=684 Z=-11.9(93.60%) | Like=-0.06..-0.00 [-0.0610..-0.0609]*| it/evals=9965/20404 eff=69.2607% N=684 Z=-11.9(94.04%) | Like=-0.06..-0.00 [-0.0568..-0.0566]*| it/evals=10016/20404 eff=69.6368% N=684 Z=-11.9(94.56%) | Like=-0.05..-0.00 [-0.0504..-0.0503]*| it/evals=10080/20404 eff=70.2205% N=684 Z=-11.9(94.81%) | Like=-0.05..-0.00 [-0.0482..-0.0481]*| it/evals=10112/20532 eff=69.3162% N=684 Z=-11.9(94.86%) | Like=-0.05..-0.00 [-0.0478..-0.0477]*| it/evals=10119/20532 eff=69.3672% N=684 Z=-11.9(95.04%) | Like=-0.05..-0.00 [-0.0460..-0.0460]*| it/evals=10144/20532 eff=69.5203% N=684 Z=-11.9(95.26%) | Like=-0.04..-0.00 [-0.0438..-0.0438]*| it/evals=10176/20532 eff=69.7372% N=684 Z=-11.9(95.47%) | Like=-0.04..-0.00 [-0.0422..-0.0422]*| it/evals=10208/20532 eff=69.9796% N=684 Z=-11.9(95.87%) | Like=-0.04..-0.00 [-0.0381..-0.0380]*| it/evals=10272/20660 eff=69.3196% N=684 Z=-11.9(96.05%) | Like=-0.04..-0.00 [-0.0365..-0.0365]*| it/evals=10304/20660 eff=69.5581% N=684 Z=-11.9(96.23%) | Like=-0.03..-0.00 [-0.0347..-0.0346]*| it/evals=10336/20660 eff=69.7841% N=684 Z=-11.9(96.69%) | Like=-0.03..-0.00 [-0.0305..-0.0305]*| it/evals=10426/20788 eff=69.1871% N=684 Z=-11.9(97.01%) | Like=-0.03..-0.00 [-0.0279..-0.0279]*| it/evals=10496/20788 eff=69.6318% N=684 Z=-11.9(97.14%) | Like=-0.03..-0.00 [-0.0262..-0.0262]*| it/evals=10528/20788 eff=69.8542% N=684 Z=-11.9(97.34%) | Like=-0.02..-0.00 [-0.0245..-0.0244]*| it/evals=10579/20916 eff=69.0708% N=684 Z=-11.9(97.51%) | Like=-0.02..-0.00 [-0.0229..-0.0228]*| it/evals=10624/20916 eff=69.3140% N=684 Z=-11.9(97.62%) | Like=-0.02..-0.00 [-0.0218..-0.0218]*| it/evals=10656/20916 eff=69.5451% N=684 Z=-11.9(97.73%) | Like=-0.02..-0.00 [-0.0208..-0.0207]*| it/evals=10688/20916 eff=69.7762% N=684 Z=-11.9(97.88%) | Like=-0.02..-0.00 [-0.0192..-0.0192]*| it/evals=10734/21044 eff=68.9940% N=684 Z=-11.9(97.93%) | Like=-0.02..-0.00 [-0.0188..-0.0188]*| it/evals=10752/21044 eff=69.1018% N=684 Z=-11.9(98.03%) | Like=-0.02..-0.00 [-0.0179..-0.0179]*| it/evals=10784/21044 eff=69.2216% N=684 Z=-11.9(98.12%) | Like=-0.02..-0.00 [-0.0172..-0.0172]*| it/evals=10816/21044 eff=69.4371% N=684 Z=-11.9(98.30%) | Like=-0.02..-0.00 [-0.0153..-0.0152]*| it/evals=10888/21172 eff=68.8606% N=684 Z=-11.9(98.36%) | Like=-0.01..-0.00 [-0.0147..-0.0147]*| it/evals=10912/21172 eff=69.0375% N=684 Z=-11.9(98.43%) | Like=-0.01..-0.00 [-0.0140..-0.0139]*| it/evals=10944/21172 eff=69.2498% N=684 Z=-11.9(98.51%) | Like=-0.01..-0.00 [-0.0132..-0.0132]*| it/evals=10976/21172 eff=69.4503% N=684 Z=-11.9(98.64%) | Like=-0.01..-0.00 [-0.0120..-0.0119]*| it/evals=11040/21300 eff=68.8706% N=684 Z=-11.9(98.64%) | Like=-0.01..-0.00 [-0.0119..-0.0119]*| it/evals=11042/21300 eff=68.8822% N=684 Z=-11.9(98.76%) | Like=-0.01..-0.00 [-0.0109..-0.0109]*| it/evals=11104/21300 eff=69.3121% N=684 Z=-11.9(98.91%) | Like=-0.01..-0.00 [-0.0097..-0.0097]*| it/evals=11196/21428 eff=68.7886% N=684 Z=-11.9(98.97%) | Like=-0.01..-0.00 [-0.0092..-0.0091]*| it/evals=11232/21428 eff=69.0176% N=684 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 21428 logzerr in iteration 1 0.18154709950658637 [ultranest] logZ = -11.85 +- 0.1011 [ultranest] Effective samples strategy satisfied (ESS = 2747.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 1367 minimum live points (dlogz from 0.08 to 0.21, need <0.1) [ultranest] logZ error budget: single: 0.18 bs:0.10 tail:0.01 total:0.10 required:<0.10 [ultranest] Widening roots to 1367 live points (have 684 already) ... [ultranest] Sampling 683 live points from prior ... Z=-233003.0(0.00%) | Like=-230589.81..-0.00 [-245997.6291..-81000.4327] | it/evals=5/22239 eff=0.0000% N=1367 Z=-199426.0(0.00%) | Like=-198726.43..-0.00 [-245997.6291..-81000.4327] | it/evals=32/22239 eff=9.3750% N=1367 Z=-149600.3(0.00%) | Like=-148811.73..-0.00 [-245997.6291..-81000.4327] | it/evals=157/22239 eff=57.0312% N=1367 Z=-147913.4(0.00%) | Like=-147895.18..-0.00 [-245997.6291..-81000.4327] | it/evals=160/22239 eff=58.5938% N=1367 Z=-141385.4(0.00%) | Like=-141373.63..-0.00 [-245997.6291..-81000.4327] | it/evals=192/22239 eff=71.0938% N=1367 Z=-124821.4(0.00%) | Like=-124722.98..-0.00 [-245997.6291..-81000.4327] | it/evals=311/22367 eff=58.9844% N=1367 Z=-119354.7(0.00%) | Like=-119332.76..-0.00 [-245997.6291..-81000.4327] | it/evals=352/22367 eff=68.3594% N=1367 Z=-116564.9(0.00%) | Like=-116552.15..-0.00 [-245997.6291..-81000.4327] | it/evals=384/22367 eff=74.2188% N=1367 Z=-105894.0(0.00%) | Like=-105771.48..-0.00 [-245997.6291..-81000.4327] | it/evals=509/22475 eff=70.6044% N=1367 Z=-105522.6(0.00%) | Like=-105358.10..-0.00 [-245997.6291..-81000.4327] | it/evals=512/22475 eff=71.1538% N=1367 Z=-103558.9(0.00%) | Like=-103464.97..-0.00 [-245997.6291..-81000.4327] | it/evals=544/22475 eff=76.0989% N=1367 Z=-98572.9(0.00%) | Like=-98514.71..-0.00 [-245997.6291..-81000.4327] | it/evals=608/22583 eff=66.3136% N=1367 Z=-97795.0(0.00%) | Like=-97702.37..-0.00 [-245997.6291..-81000.4327] | it/evals=618/22583 eff=67.5847% N=1367 Z=-94853.2(0.00%) | Like=-94828.90..-0.00 [-245997.6291..-81000.4327] | it/evals=672/22583 eff=73.3051% N=1367 Z=-93006.2(0.00%) | Like=-92954.38..-0.00 [-245997.6291..-81000.4327] | it/evals=704/22583 eff=76.6949% N=1367 Z=-85411.0(0.00%) | Like=-85395.38..-0.00 [-245997.6291..-81000.4327] | it/evals=832/22667 eff=75.0000% N=1367 Z=-82306.6(0.00%) | Like=-82251.50..-0.00 [-245997.6291..-81000.4327] | it/evals=896/22667 eff=80.5755% N=1367 Z=-81023.2(0.00%) | Like=-81000.43..-0.00 [-245997.6291..-81000.4327] | it/evals=926/22743 eff=72.7848% N=1367 Z=-80948.6(0.00%) | Like=-80888.75..-0.00 [-80940.7496..-40866.8558] | it/evals=928/22743 eff=72.9430% N=1367 Z=-77582.3(0.00%) | Like=-77565.22..-0.00 [-80940.7496..-40866.8558] | it/evals=992/22743 eff=78.3228% N=1367 Z=-73503.6(0.00%) | Like=-73423.93..-0.00 [-80940.7496..-40866.8558] | it/evals=1056/22817 eff=75.2125% N=1367 Z=-71606.1(0.00%) | Like=-71595.62..-0.00 [-80940.7496..-40866.8558] | it/evals=1088/22817 eff=77.9037% N=1367 Z=-69564.8(0.00%) | Like=-69507.85..-0.00 [-80940.7496..-40866.8558] | it/evals=1120/22892 eff=72.3431% N=1367 Z=-68137.5(0.00%) | Like=-68006.23..-0.00 [-80940.7496..-40866.8558] | it/evals=1152/22892 eff=74.3918% N=1367 Z=-66557.8(0.00%) | Like=-66520.87..-0.00 [-80940.7496..-40866.8558] | it/evals=1184/22892 eff=76.3124% N=1367 Z=-65303.2(0.00%) | Like=-65261.64..-0.00 [-80940.7496..-40866.8558] | it/evals=1216/22892 eff=78.7452% N=1367 Z=-64655.7(0.00%) | Like=-64592.02..-0.00 [-80940.7496..-40866.8558] | it/evals=1232/22942 eff=75.0903% N=1367 Z=-63771.6(0.00%) | Like=-63760.11..-0.00 [-80940.7496..-40866.8558] | it/evals=1248/22942 eff=75.9326% N=1367 Z=-60798.7(0.00%) | Like=-60781.74..-0.00 [-80940.7496..-40866.8558] | it/evals=1312/22942 eff=79.7834% N=1367 Z=-55667.6(0.00%) | Like=-55649.92..-0.00 [-80940.7496..-40866.8558] | it/evals=1434/23048 eff=78.1217% N=1367 Z=-54246.3(0.00%) | Like=-54207.42..-0.00 [-80940.7496..-40866.8558] | it/evals=1472/23111 eff=75.2000% N=1367 Z=-51934.6(0.00%) | Like=-51913.09..-0.00 [-80940.7496..-40866.8558] | it/evals=1536/23111 eff=78.4000% N=1367 Z=-51908.7(0.00%) | Like=-51840.55..-0.00 [-80940.7496..-40866.8558] | it/evals=1539/23111 eff=78.6000% N=1367 Z=-50702.1(0.00%) | Like=-50615.28..-0.00 [-80940.7496..-40866.8558] | it/evals=1568/23111 eff=79.8000% N=1367 Z=-49341.2(0.00%) | Like=-49307.18..-0.00 [-80940.7496..-40866.8558] | it/evals=1600/23165 eff=77.2296% N=1367 Z=-45151.9(0.00%) | Like=-45133.65..-0.00 [-80940.7496..-40866.8558] | it/evals=1718/23223 eff=78.3273% N=1367 Z=-41409.7(0.00%) | Like=-41382.37..-0.00 [-80940.7496..-40866.8558] | it/evals=1843/23302 eff=78.8413% N=1367 Z=-41321.7(0.00%) | Like=-41294.39..-0.00 [-80940.7496..-40866.8558] | it/evals=1845/23302 eff=78.9253% N=1367 Z=-40908.4(0.00%) | Like=-40870.94..-0.00 [-80940.7496..-40866.8558] | it/evals=1856/23302 eff=79.5130% N=1367 Z=-39979.4(0.00%) | Like=-39965.82..-0.00 [-40839.0816..-20283.7951] | it/evals=1888/23344 eff=78.1833% N=1367 Z=-39214.6(0.00%) | Like=-39202.45..-0.00 [-40839.0816..-20283.7951] | it/evals=1920/23344 eff=79.3187% N=1367 Z=-38457.5(0.00%) | Like=-38445.21..-0.00 [-40839.0816..-20283.7951] | it/evals=1952/23379 eff=78.6278% N=1367 Z=-35102.7(0.00%) | Like=-35093.29..-0.00 [-40839.0816..-20283.7951] | it/evals=2075/23442 eff=79.5642% N=1367 Z=-34982.2(0.00%) | Like=-34917.81..-0.00 [-40839.0816..-20283.7951] | it/evals=2080/23442 eff=79.8648% N=1367 Z=-33126.3(0.00%) | Like=-33087.46..-0.00 [-40839.0816..-20283.7951] | it/evals=2151/23516 eff=78.0783% N=1367 Z=-30972.5(0.00%) | Like=-30958.08..-0.00 [-40839.0816..-20283.7951] | it/evals=2240/23568 eff=78.3802% N=1367 Z=-30472.5(0.00%) | Like=-30381.09..-0.00 [-40839.0816..-20283.7951] | it/evals=2272/23568 eff=79.3411% N=1367 Z=-27663.6(0.00%) | Like=-27619.70..-0.00 [-40839.0816..-20283.7951] | it/evals=2404/23652 eff=79.1694% N=1367 Z=-27023.9(0.00%) | Like=-26954.52..-0.00 [-40839.0816..-20283.7951] | it/evals=2432/23652 eff=79.8832% N=1367 Z=-26425.7(0.00%) | Like=-26407.73..-0.00 [-40839.0816..-20283.7951] | it/evals=2458/23692 eff=78.6211% N=1367 Z=-26287.4(0.00%) | Like=-26248.78..-0.00 [-40839.0816..-20283.7951] | it/evals=2464/23692 eff=78.8741% N=1367 Z=-25544.6(0.00%) | Like=-25534.48..-0.00 [-40839.0816..-20283.7951] | it/evals=2496/23692 eff=79.8229% N=1367 Z=-24292.2(0.00%) | Like=-24270.10..-0.00 [-40839.0816..-20283.7951] | it/evals=2560/23757 eff=78.8578% N=1367 Z=-23053.4(0.00%) | Like=-23035.53..-0.00 [-40839.0816..-20283.7951] | it/evals=2624/23817 eff=78.0188% N=1367 Z=-21981.5(0.00%) | Like=-21961.22..-0.00 [-40839.0816..-20283.7951] | it/evals=2688/23817 eff=79.2497% N=1367 Z=-21026.3(0.00%) | Like=-21006.52..-0.00 [-40839.0816..-20283.7951] | it/evals=2752/23879 eff=78.2805% N=1367 Z=-20797.4(0.00%) | Like=-20779.19..-0.00 [-40839.0816..-20283.7951] | it/evals=2764/23879 eff=78.5633% N=1367 Z=-20576.0(0.00%) | Like=-20539.90..-0.00 [-40839.0816..-20283.7951] | it/evals=2784/23898 eff=78.2876% N=1367 Z=-19135.0(0.00%) | Like=-19112.44..-0.00 [-20246.2291..-10136.9334] | it/evals=2880/23948 eff=78.6609% N=1367 Z=-18084.0(0.00%) | Like=-18032.94..-0.00 [-20246.2291..-10136.9334] | it/evals=2944/23998 eff=78.1664% N=1367 Z=-17224.2(0.00%) | Like=-17206.57..-0.00 [-20246.2291..-10136.9334] | it/evals=3008/24037 eff=78.1412% N=1367 Z=-16624.7(0.00%) | Like=-16607.32..-0.00 [-20246.2291..-10136.9334] | it/evals=3071/24091 eff=78.0808% N=1367 Z=-15375.4(0.00%) | Like=-15354.26..-0.00 [-20246.2291..-10136.9334] | it/evals=3168/24154 eff=78.1204% N=1367 Z=-15007.6(0.00%) | Like=-14988.86..-0.00 [-20246.2291..-10136.9334] | it/evals=3200/24170 eff=78.4361% N=1367 Z=-14683.6(0.00%) | Like=-14655.76..-0.00 [-20246.2291..-10136.9334] | it/evals=3232/24195 eff=78.2150% N=1367 Z=-13582.1(0.00%) | Like=-13564.64..-0.00 [-20246.2291..-10136.9334] | it/evals=3328/24258 eff=78.1090% N=1367 Z=-13277.7(0.00%) | Like=-13247.86..-0.00 [-20246.2291..-10136.9334] | it/evals=3360/24286 eff=78.0230% N=1367 Z=-13008.2(0.00%) | Like=-12998.38..-0.00 [-20246.2291..-10136.9334] | it/evals=3379/24296 eff=78.1693% N=1367 Z=-12913.2(0.00%) | Like=-12897.91..-0.00 [-20246.2291..-10136.9334] | it/evals=3392/24308 eff=77.9700% N=1367 Z=-12664.1(0.00%) | Like=-12652.44..-0.00 [-20246.2291..-10136.9334] | it/evals=3424/24320 eff=78.0896% N=1367 Z=-12409.4(0.00%) | Like=-12388.48..-0.00 [-20246.2291..-10136.9334] | it/evals=3456/24335 eff=78.5522% N=1367 Z=-11620.5(0.00%) | Like=-11582.93..-0.00 [-20246.2291..-10136.9334] | it/evals=3552/24385 eff=78.4960% N=1367 Z=-11082.9(0.00%) | Like=-11065.76..-0.00 [-20246.2291..-10136.9334] | it/evals=3616/24441 eff=78.4549% N=1367 Z=-10850.9(0.00%) | Like=-10838.93..-0.00 [-20246.2291..-10136.9334] | it/evals=3648/24470 eff=78.1263% N=1367 Z=-10650.6(0.00%) | Like=-10639.10..-0.00 [-20246.2291..-10136.9334] | it/evals=3680/24478 eff=78.4115% N=1367 Z=-10628.7(0.00%) | Like=-10617.44..-0.00 [-20246.2291..-10136.9334] | it/evals=3685/24488 eff=78.1658% N=1367 Z=-10178.9(0.00%) | Like=-10167.27..-0.00 [-20246.2291..-10136.9334] | it/evals=3744/24527 eff=78.5182% N=1367 Z=-9708.3(0.00%) | Like=-9696.46..-0.00 [-10134.5674..-5086.2764] | it/evals=3808/24566 eff=78.3707% N=1367 Z=-9465.1(0.00%) | Like=-9447.09..-0.00 [-10134.5674..-5086.2764] | it/evals=3840/24579 eff=78.5656% N=1367 Z=-9298.3(0.00%) | Like=-9287.10..-0.00 [-10134.5674..-5086.2764] | it/evals=3872/24599 eff=78.7379% N=1367 Z=-8460.0(0.00%) | Like=-8441.72..-0.00 [-10134.5674..-5086.2764] | it/evals=3991/24689 eff=78.5881% N=1367 Z=-8430.8(0.00%) | Like=-8400.14..-0.00 [-10134.5674..-5086.2764] | it/evals=4000/24698 eff=78.5852% N=1367 Z=-8247.5(0.00%) | Like=-8236.69..-0.00 [-10134.5674..-5086.2764] | it/evals=4032/24719 eff=78.7193% N=1367 Z=-7456.4(0.00%) | Like=-7441.33..-0.00 [-10134.5674..-5086.2764] | it/evals=4154/24798 eff=78.7868% N=1367 Z=-7421.5(0.00%) | Like=-7410.18..-0.00 [-10134.5674..-5086.2764] | it/evals=4160/24798 eff=78.8612% N=1367 Z=-6754.4(0.00%) | Like=-6731.95..-0.00 [-10134.5674..-5086.2764] | it/evals=4290/24874 eff=78.9359% N=1367 Z=-6715.0(0.00%) | Like=-6688.55..-0.00 [-10134.5674..-5086.2764] | it/evals=4298/24874 eff=79.0445% N=1367 Z=-6632.3(0.00%) | Like=-6621.66..-0.00 [-10134.5674..-5086.2764] | it/evals=4320/24888 eff=78.9341% N=1367 Z=-6265.4(0.00%) | Like=-6249.26..-0.00 [-10134.5674..-5086.2764] | it/evals=4416/24931 eff=79.1135% N=1367 Z=-5663.0(0.00%) | Like=-5646.45..-0.00 [-10134.5674..-5086.2764] | it/evals=4542/25014 eff=79.0561% N=1367 Z=-5475.1(0.00%) | Like=-5463.30..-0.00 [-10134.5674..-5086.2764] | it/evals=4576/25038 eff=79.0229% N=1367 Z=-5332.7(0.00%) | Like=-5311.10..-0.00 [-10134.5674..-5086.2764] | it/evals=4604/25065 eff=78.8761% N=1367 Z=-5312.4(0.00%) | Like=-5301.13..-0.00 [-10134.5674..-5086.2764] | it/evals=4608/25065 eff=78.9100% N=1367 Z=-4957.4(0.00%) | Like=-4946.54..-0.00 [-5072.1175..-2642.5397] | it/evals=4713/25220 eff=76.9379% N=1367 Z=-4906.8(0.00%) | Like=-4894.92..-0.00 [-5072.1175..-2642.5397] | it/evals=4736/25220 eff=77.2917% N=1367 Z=-4813.7(0.00%) | Like=-4801.97..-0.00 [-5072.1175..-2642.5397] | it/evals=4768/25220 eff=77.7420% N=1367 Z=-4682.5(0.00%) | Like=-4668.12..-0.00 [-5072.1175..-2642.5397] | it/evals=4800/25220 eff=78.2567% N=1367 Z=-4366.9(0.00%) | Like=-4356.02..-0.00 [-5072.1175..-2642.5397] | it/evals=4896/25348 eff=76.5215% N=1367 Z=-4337.6(0.00%) | Like=-4324.16..-0.00 [-5072.1175..-2642.5397] | it/evals=4910/25348 eff=76.7995% N=1367 Z=-4181.1(0.00%) | Like=-4163.43..-0.00 [-5072.1175..-2642.5397] | it/evals=4960/25348 eff=77.4791% N=1367 Z=-4081.6(0.00%) | Like=-4070.76..-0.00 [-5072.1175..-2642.5397] | it/evals=4992/25348 eff=78.0970% N=1367 Z=-3998.4(0.00%) | Like=-3985.59..-0.00 [-5072.1175..-2642.5397] | it/evals=5024/25348 eff=78.5604% N=1367 Z=-3720.7(0.00%) | Like=-3703.78..-0.00 [-5072.1175..-2642.5397] | it/evals=5120/25414 eff=78.4136% N=1367 Z=-3487.6(0.00%) | Like=-3475.45..-0.00 [-5072.1175..-2642.5397] | it/evals=5219/25477 eff=78.4611% N=1367 Z=-3358.5(0.00%) | Like=-3343.71..-0.00 [-5072.1175..-2642.5397] | it/evals=5280/25513 eff=78.5714% N=1367 Z=-3286.7(0.00%) | Like=-3273.52..-0.00 [-5072.1175..-2642.5397] | it/evals=5312/25540 eff=78.5360% N=1367 Z=-3147.1(0.00%) | Like=-3132.22..-0.00 [-5072.1175..-2642.5397] | it/evals=5376/25678 eff=76.6470% N=1367 Z=-3047.1(0.00%) | Like=-3036.11..-0.00 [-5072.1175..-2642.5397] | it/evals=5408/25678 eff=77.1236% N=1367 Z=-2823.7(0.00%) | Like=-2808.69..-0.00 [-5072.1175..-2642.5397] | it/evals=5525/25806 eff=75.9405% N=1367 Z=-2792.1(0.00%) | Like=-2777.92..-0.00 [-5072.1175..-2642.5397] | it/evals=5536/25806 eff=76.0758% N=1367 Z=-2615.9(0.00%) | Like=-2600.48..-0.00 [-2638.0754..-1326.0440] | it/evals=5632/25806 eff=77.2395% N=1367 Z=-2461.1(0.00%) | Like=-2449.05..-0.00 [-2638.0754..-1326.0440] | it/evals=5696/25806 eff=77.9432% N=1367 Z=-2243.1(0.00%) | Like=-2231.89..-0.00 [-2638.0754..-1326.0440] | it/evals=5817/25892 eff=77.8101% N=1367 Z=-2236.1(0.00%) | Like=-2221.79..-0.00 [-2638.0754..-1326.0440] | it/evals=5824/25897 eff=77.8394% N=1367 Z=-2225.4(0.00%) | Like=-2213.82..-0.00 [-2638.0754..-1326.0440] | it/evals=5832/25900 eff=77.8042% N=1367 Z=-2139.1(0.00%) | Like=-2127.89..-0.00 [-2638.0754..-1326.0440] | it/evals=5888/25943 eff=77.8706% N=1367 Z=-2099.1(0.00%) | Like=-2086.76..-0.00 [-2638.0754..-1326.0440] | it/evals=5920/26078 eff=75.5231% N=1367 Z=-2050.8(0.00%) | Like=-2034.23..-0.00 [-2638.0754..-1326.0440] | it/evals=5952/26078 eff=75.9012% N=1367 Z=-1909.6(0.00%) | Like=-1897.66..-0.00 [-2638.0754..-1326.0440] | it/evals=6048/26078 eff=76.9095% N=1367 Z=-1862.7(0.00%) | Like=-1850.29..-0.00 [-2638.0754..-1326.0440] | it/evals=6080/26078 eff=77.2372% N=1367 Z=-1816.0(0.00%) | Like=-1804.71..-0.00 [-2638.0754..-1326.0440] | it/evals=6112/26078 eff=77.5649% N=1367 Z=-1781.3(0.00%) | Like=-1768.12..-0.00 [-2638.0754..-1326.0440] | it/evals=6138/26078 eff=77.9430% N=1367 Z=-1734.1(0.00%) | Like=-1722.11..-0.00 [-2638.0754..-1326.0440] | it/evals=6176/26209 eff=75.8175% N=1367 Z=-1701.8(0.00%) | Like=-1690.14..-0.00 [-2638.0754..-1326.0440] | it/evals=6208/26209 eff=76.3543% N=1367 Z=-1614.1(0.00%) | Like=-1601.53..-0.00 [-2638.0754..-1326.0440] | it/evals=6272/26209 eff=77.0620% N=1367 Z=-1570.6(0.00%) | Like=-1558.80..-0.00 [-2638.0754..-1326.0440] | it/evals=6304/26209 eff=77.4524% N=1367 Z=-1536.5(0.00%) | Like=-1524.46..-0.00 [-2638.0754..-1326.0440] | it/evals=6336/26209 eff=77.8184% N=1367 Z=-1508.9(0.00%) | Like=-1496.65..-0.00 [-2638.0754..-1326.0440] | it/evals=6368/26337 eff=75.9110% N=1367 Z=-1430.0(0.00%) | Like=-1417.67..-0.00 [-2638.0754..-1326.0440] | it/evals=6444/26337 eff=76.7156% N=1367 Z=-1299.7(0.00%) | Like=-1287.21..-0.00 [-1324.5454..-687.8940] | it/evals=6575/26465 eff=75.9072% N=1367 Z=-1266.1(0.00%) | Like=-1254.76..-0.00 [-1324.5454..-687.8940] | it/evals=6624/26465 eff=76.3436% N=1367 Z=-1239.6(0.00%) | Like=-1226.95..-0.00 [-1324.5454..-687.8940] | it/evals=6656/26465 eff=76.8718% N=1367 Z=-1221.3(0.00%) | Like=-1208.32..-0.00 [-1324.5454..-687.8940] | it/evals=6674/26465 eff=77.0326% N=1367 Z=-1160.7(0.00%) | Like=-1148.74..-0.00 [-1324.5454..-687.8940] | it/evals=6752/26465 eff=77.9054% N=1367 Z=-1131.3(0.00%) | Like=-1120.09..-0.00 [-1324.5454..-687.8940] | it/evals=6784/26598 eff=75.9305% N=1367 Z=-1110.9(0.00%) | Like=-1099.55..-0.00 [-1324.5454..-687.8940] | it/evals=6816/26598 eff=76.3316% N=1367 Z=-1058.7(0.00%) | Like=-1046.28..-0.00 [-1324.5454..-687.8940] | it/evals=6880/26598 eff=77.1117% N=1367 Z=-1013.5(0.00%) | Like=-1001.90..-0.00 [-1324.5454..-687.8940] | it/evals=6944/26598 eff=77.8917% N=1367 Z=-1011.4(0.00%) | Like=-999.47..-0.00 [-1324.5454..-687.8940] | it/evals=6949/26598 eff=77.9140% N=1367 Z=-994.7(0.00%) | Like=-982.66..-0.00 [-1324.5454..-687.8940] | it/evals=6976/26729 eff=76.0286% N=1367 Z=-968.5(0.00%) | Like=-956.23..-0.00 [-1324.5454..-687.8940] | it/evals=7008/26729 eff=76.5266% N=1367 Z=-947.9(0.00%) | Like=-935.89..-0.00 [-1324.5454..-687.8940] | it/evals=7040/26729 eff=76.8298% N=1367 Z=-885.1(0.00%) | Like=-872.75..-0.00 [-1324.5454..-687.8940] | it/evals=7136/26729 eff=77.9558% N=1367 Z=-827.5(0.00%) | Like=-814.60..-0.00 [-1324.5454..-687.8940] | it/evals=7232/26857 eff=76.8226% N=1367 Z=-811.3(0.00%) | Like=-799.15..-0.00 [-1324.5454..-687.8940] | it/evals=7255/26857 eff=77.1176% N=1367 Z=-777.6(0.00%) | Like=-765.80..-0.00 [-1324.5454..-687.8940] | it/evals=7328/26857 eff=77.9182% N=1367 Z=-758.4(0.00%) | Like=-746.72..-0.00 [-1324.5454..-687.8940] | it/evals=7360/26988 eff=76.1739% N=1367 Z=-715.7(0.00%) | Like=-703.92..-0.00 [-1324.5454..-687.8940] | it/evals=7456/26988 eff=77.1171% N=1367 Z=-699.5(0.00%) | Like=-687.85..-0.00 [-687.8545..-350.2747] | it/evals=7488/26988 eff=77.3631% N=1367 Z=-671.8(0.00%) | Like=-658.11..-0.00 [-687.8545..-350.2747] | it/evals=7552/26988 eff=78.0193% N=1367 Z=-664.6(0.00%) | Like=-652.30..-0.00 [-687.8545..-350.2747] | it/evals=7562/27116 eff=76.1239% N=1367 Z=-622.8(0.00%) | Like=-610.91..-0.00 [-687.8545..-350.2747] | it/evals=7648/27116 eff=76.9830% N=1367 Z=-596.9(0.00%) | Like=-584.46..-0.00 [-687.8545..-350.2747] | it/evals=7712/27116 eff=77.5624% N=1367 Z=-560.6(0.00%) | Like=-548.04..-0.00 [-687.8545..-350.2747] | it/evals=7808/27245 eff=76.5095% N=1367 Z=-549.5(0.00%) | Like=-537.70..-0.00 [-687.8545..-350.2747] | it/evals=7840/27245 eff=76.8017% N=1367 Z=-534.7(0.00%) | Like=-522.74..-0.00 [-687.8545..-350.2747] | it/evals=7873/27245 eff=77.1718% N=1367 Z=-518.8(0.00%) | Like=-505.87..-0.00 [-687.8545..-350.2747] | it/evals=7904/27245 eff=77.4640% N=1367 Z=-501.1(0.00%) | Like=-489.30..-0.00 [-687.8545..-350.2747] | it/evals=7968/27373 eff=76.2638% N=1367 Z=-488.2(0.00%) | Like=-475.66..-0.00 [-687.8545..-350.2747] | it/evals=8000/27373 eff=76.6819% N=1367 Z=-462.8(0.00%) | Like=-450.94..-0.00 [-687.8545..-350.2747] | it/evals=8064/27373 eff=77.2140% N=1367 Z=-451.7(0.00%) | Like=-439.45..-0.00 [-687.8545..-350.2747] | it/evals=8096/27373 eff=77.5371% N=1367 Z=-432.0(0.00%) | Like=-419.86..-0.00 [-687.8545..-350.2747] | it/evals=8160/27501 eff=76.2338% N=1367 Z=-428.2(0.00%) | Like=-415.99..-0.00 [-687.8545..-350.2747] | it/evals=8179/27501 eff=76.4378% N=1367 Z=-386.0(0.00%) | Like=-373.03..-0.00 [-687.8545..-350.2747] | it/evals=8320/27501 eff=77.6438% N=1367 Z=-369.9(0.00%) | Like=-358.44..-0.00 [-687.8545..-350.2747] | it/evals=8384/27629 eff=76.4226% N=1367 Z=-343.9(0.00%) | Like=-331.86..-0.00 [-350.2058..-170.9640] | it/evals=8485/27629 eff=77.4012% N=1367 Z=-331.8(0.00%) | Like=-320.00..-0.00 [-350.2058..-170.9640] | it/evals=8544/27760 eff=76.2259% N=1367 Z=-325.8(0.00%) | Like=-313.38..-0.00 [-350.2058..-170.9640] | it/evals=8576/27760 eff=76.4914% N=1367 Z=-310.3(0.00%) | Like=-298.21..-0.00 [-350.2058..-170.9640] | it/evals=8640/27760 eff=77.0579% N=1367 Z=-303.0(0.00%) | Like=-291.71..-0.00 [-350.2058..-170.9640] | it/evals=8672/27760 eff=77.3234% N=1367 Z=-276.0(0.00%) | Like=-264.15..-0.00 [-350.2058..-170.9640] | it/evals=8791/27888 eff=76.7007% N=1367 Z=-268.2(0.00%) | Like=-255.71..-0.00 [-350.2058..-170.9640] | it/evals=8832/27888 eff=77.0296% N=1367 Z=-261.8(0.00%) | Like=-249.61..-0.00 [-350.2058..-170.9640] | it/evals=8864/27888 eff=77.2719% N=1367 Z=-256.1(0.00%) | Like=-243.29..-0.00 [-350.2058..-170.9640] | it/evals=8896/27888 eff=77.5662% N=1367 Z=-249.1(0.00%) | Like=-237.18..-0.00 [-350.2058..-170.9640] | it/evals=8928/28020 eff=76.0535% N=1367 Z=-237.3(0.00%) | Like=-225.33..-0.00 [-350.2058..-170.9640] | it/evals=8992/28020 eff=76.6796% N=1367 Z=-233.9(0.00%) | Like=-222.09..-0.00 [-350.2058..-170.9640] | it/evals=9012/28020 eff=76.8320% N=1367 Z=-232.0(0.00%) | Like=-219.92..-0.00 [-350.2058..-170.9640] | it/evals=9024/28020 eff=76.9673% N=1367 Z=-219.9(0.00%) | Like=-208.09..-0.00 [-350.2058..-170.9640] | it/evals=9088/28020 eff=77.4920% N=1367 Z=-214.9(0.00%) | Like=-203.30..-0.00 [-350.2058..-170.9640] | it/evals=9120/28149 eff=76.1179% N=1367 Z=-210.5(0.00%) | Like=-198.78..-0.00 [-350.2058..-170.9640] | it/evals=9152/28149 eff=76.3995% N=1367 Z=-192.5(0.00%) | Like=-180.40..-0.00 [-350.2058..-170.9640] | it/evals=9288/28149 eff=77.5091% N=1367 Z=-188.6(0.00%) | Like=-175.97..-0.00 [-350.2058..-170.9640] | it/evals=9318/28277 eff=76.2082% N=1367 Z=-185.3(0.00%) | Like=-173.61..-0.00 [-350.2058..-170.9640] | it/evals=9344/28277 eff=76.4677% N=1367 Z=-182.3(0.00%) | Like=-170.56..-0.00 [-170.9432..-86.0482] | it/evals=9374/28277 eff=76.7272% N=1367 Z=-182.1(0.00%) | Like=-170.15..-0.00 [-170.9432..-86.0482] | it/evals=9376/28277 eff=76.7596% N=1367 Z=-178.6(0.00%) | Like=-166.48..-0.00 [-170.9432..-86.0482] | it/evals=9408/28277 eff=77.0029% N=1367 Z=-167.1(0.00%) | Like=-155.21..-0.00 [-170.9432..-86.0482] | it/evals=9504/28405 eff=76.1678% N=1367 Z=-164.3(0.00%) | Like=-152.60..-0.00 [-170.9432..-86.0482] | it/evals=9536/28405 eff=76.4697% N=1367 Z=-161.5(0.00%) | Like=-149.99..-0.00 [-170.9432..-86.0482] | it/evals=9568/28405 eff=76.6444% N=1367 Z=-154.8(0.00%) | Like=-142.39..-0.00 [-170.9432..-86.0482] | it/evals=9632/28405 eff=77.2005% N=1367 Z=-150.8(0.00%) | Like=-138.99..-0.00 [-170.9432..-86.0482] | it/evals=9664/28405 eff=77.4071% N=1367 Z=-149.1(0.00%) | Like=-137.07..-0.00 [-170.9432..-86.0482] | it/evals=9683/28533 eff=76.0355% N=1367 Z=-148.6(0.00%) | Like=-136.77..-0.00 [-170.9432..-86.0482] | it/evals=9689/28533 eff=76.0666% N=1367 Z=-147.9(0.00%) | Like=-135.85..-0.00 [-170.9432..-86.0482] | it/evals=9696/28533 eff=76.1601% N=1367 Z=-141.8(0.00%) | Like=-129.59..-0.00 [-170.9432..-86.0482] | it/evals=9760/28533 eff=76.6116% N=1367 Z=-135.5(0.00%) | Like=-123.71..-0.00 [-170.9432..-86.0482] | it/evals=9824/28533 eff=77.1878% N=1367 Z=-132.8(0.00%) | Like=-121.11..-0.00 [-170.9432..-86.0482] | it/evals=9856/28661 eff=75.9389% N=1367 Z=-128.0(0.00%) | Like=-115.94..-0.00 [-170.9432..-86.0482] | it/evals=9914/28661 eff=76.4427% N=1367 Z=-123.8(0.00%) | Like=-111.79..-0.00 [-170.9432..-86.0482] | it/evals=9962/28661 eff=76.7634% N=1367 Z=-119.8(0.00%) | Like=-107.76..-0.00 [-170.9432..-86.0482] | it/evals=10016/28661 eff=77.1908% N=1367 Z=-119.0(0.00%) | Like=-107.07..-0.00 [-170.9432..-86.0482] | it/evals=10027/28661 eff=77.2214% N=1367 Z=-114.3(0.00%) | Like=-101.54..-0.00 [-170.9432..-86.0482] | it/evals=10080/28789 eff=76.1605% N=1367 Z=-112.1(0.00%) | Like=-99.94..-0.00 [-170.9432..-86.0482] | it/evals=10100/28789 eff=76.2803% N=1367 Z=-111.4(0.00%) | Like=-99.38..-0.00 [-170.9432..-86.0482] | it/evals=10109/28789 eff=76.3252% N=1367 Z=-111.2(0.00%) | Like=-99.21..-0.00 [-170.9432..-86.0482] | it/evals=10112/28789 eff=76.3552% N=1367 Z=-108.7(0.00%) | Like=-96.63..-0.00 [-170.9432..-86.0482] | it/evals=10144/28789 eff=76.6397% N=1367 Z=-106.4(0.00%) | Like=-94.45..-0.00 [-170.9432..-86.0482] | it/evals=10176/28789 eff=76.8943% N=1367 Z=-105.9(0.00%) | Like=-94.08..-0.00 [-170.9432..-86.0482] | it/evals=10184/28789 eff=76.9093% N=1367 Z=-104.5(0.00%) | Like=-92.57..-0.00 [-170.9432..-86.0482] | it/evals=10208/28789 eff=77.1638% N=1367 Z=-103.1(0.00%) | Like=-91.10..-0.00 [-170.9432..-86.0482] | it/evals=10234/28917 eff=75.8742% N=1367 Z=-100.8(0.00%) | Like=-88.97..-0.00 [-170.9432..-86.0482] | it/evals=10272/28917 eff=76.2562% N=1367 Z=-93.8(0.00%) | Like=-81.88..-0.00 [-86.0274..-42.3187] | it/evals=10394/28917 eff=77.3435% N=1367 Z=-93.4(0.00%) | Like=-81.44..-0.00 [-86.0274..-42.3187] | it/evals=10400/28917 eff=77.3729% N=1367 Z=-91.5(0.00%) | Like=-79.34..-0.00 [-86.0274..-42.3187] | it/evals=10432/29045 eff=76.2475% N=1367 Z=-89.6(0.00%) | Like=-77.69..-0.00 [-86.0274..-42.3187] | it/evals=10464/29045 eff=76.5215% N=1367 Z=-85.8(0.00%) | Like=-73.89..-0.00 [-86.0274..-42.3187] | it/evals=10528/29045 eff=76.9253% N=1367 Z=-85.2(0.00%) | Like=-73.29..-0.00 [-86.0274..-42.3187] | it/evals=10540/29045 eff=77.0118% N=1367 Z=-84.3(0.00%) | Like=-72.34..-0.00 [-86.0274..-42.3187] | it/evals=10560/29045 eff=77.1705% N=1367 Z=-82.8(0.00%) | Like=-71.10..-0.00 [-86.0274..-42.3187] | it/evals=10592/29173 eff=76.0125% N=1367 Z=-81.3(0.00%) | Like=-69.12..-0.00 [-86.0274..-42.3187] | it/evals=10626/29173 eff=76.2390% N=1367 Z=-79.9(0.00%) | Like=-67.82..-0.00 [-86.0274..-42.3187] | it/evals=10656/29173 eff=76.4514% N=1367 Z=-79.1(0.00%) | Like=-66.91..-0.00 [-86.0274..-42.3187] | it/evals=10673/29173 eff=76.5364% N=1367 Z=-78.3(0.00%) | Like=-66.26..-0.00 [-86.0274..-42.3187] | it/evals=10688/29173 eff=76.7063% N=1367 Z=-75.9(0.00%) | Like=-63.97..-0.00 [-86.0274..-42.3187] | it/evals=10747/29173 eff=77.1453% N=1367 Z=-75.7(0.00%) | Like=-63.71..-0.00 [-86.0274..-42.3187] | it/evals=10752/29173 eff=77.1878% N=1367 Z=-74.3(0.00%) | Like=-62.42..-0.00 [-86.0274..-42.3187] | it/evals=10787/29301 eff=76.0779% N=1367 Z=-73.0(0.00%) | Like=-60.94..-0.00 [-86.0274..-42.3187] | it/evals=10816/29301 eff=76.3143% N=1367 Z=-71.5(0.00%) | Like=-59.38..-0.00 [-86.0274..-42.3187] | it/evals=10848/29301 eff=76.4812% N=1367 Z=-68.0(0.00%) | Like=-55.95..-0.00 [-86.0274..-42.3187] | it/evals=10944/29301 eff=77.0932% N=1367 Z=-67.2(0.00%) | Like=-55.09..-0.00 [-86.0274..-42.3187] | it/evals=10962/29301 eff=77.1905% N=1367 Z=-66.6(0.00%) | Like=-54.48..-0.00 [-86.0274..-42.3187] | it/evals=10976/29301 eff=77.2879% N=1367 Z=-65.3(0.00%) | Like=-53.20..-0.00 [-86.0274..-42.3187] | it/evals=11008/29429 eff=76.2230% N=1367 Z=-64.0(0.00%) | Like=-51.86..-0.00 [-86.0274..-42.3187] | it/evals=11040/29429 eff=76.5236% N=1367 Z=-63.1(0.00%) | Like=-50.92..-0.00 [-86.0274..-42.3187] | it/evals=11060/29429 eff=76.6193% N=1367 Z=-61.4(0.00%) | Like=-49.10..-0.00 [-86.0274..-42.3187] | it/evals=11100/29429 eff=76.8106% N=1367 Z=-61.2(0.00%) | Like=-48.98..-0.00 [-86.0274..-42.3187] | it/evals=11104/29429 eff=76.8516% N=1367 Z=-60.0(0.00%) | Like=-47.75..-0.00 [-86.0274..-42.3187] | it/evals=11136/29429 eff=77.0292% N=1367 Z=-59.1(0.00%) | Like=-46.92..-0.00 [-86.0274..-42.3187] | it/evals=11156/29429 eff=77.1522% N=1367 Z=-58.7(0.00%) | Like=-46.58..-0.00 [-86.0274..-42.3187] | it/evals=11168/29429 eff=77.3025% N=1367 Z=-58.4(0.00%) | Like=-46.33..-0.00 [-86.0274..-42.3187] | it/evals=11176/29429 eff=77.3299% N=1367 Z=-57.7(0.00%) | Like=-45.78..-0.00 [-86.0274..-42.3187] | it/evals=11196/29429 eff=77.4665% N=1367 Z=-57.6(0.00%) | Like=-45.65..-0.00 [-86.0274..-42.3187] | it/evals=11200/29429 eff=77.5212% N=1367 Z=-55.4(0.00%) | Like=-43.42..-0.00 [-86.0274..-42.3187] | it/evals=11264/29557 eff=76.5915% N=1367 Z=-53.4(0.00%) | Like=-41.25..-0.00 [-42.3073..-20.4432] | it/evals=11328/29557 eff=77.0346% N=1367 Z=-51.6(0.00%) | Like=-39.42..-0.00 [-42.3073..-20.4432] | it/evals=11383/29557 eff=77.4376% N=1367 Z=-50.4(0.00%) | Like=-38.29..-0.00 [-42.3073..-20.4432] | it/evals=11422/29685 eff=76.4193% N=1367 Z=-50.3(0.00%) | Like=-38.25..-0.00 [-42.3073..-20.4432] | it/evals=11424/29685 eff=76.4457% N=1367 Z=-49.6(0.00%) | Like=-37.35..-0.00 [-42.3073..-20.4432] | it/evals=11447/29685 eff=76.6570% N=1367 Z=-49.2(0.00%) | Like=-37.13..-0.00 [-42.3073..-20.4432] | it/evals=11459/29685 eff=76.7230% N=1367 Z=-48.3(0.00%) | Like=-36.21..-0.00 [-42.3073..-20.4432] | it/evals=11488/29685 eff=76.9739% N=1367 Z=-46.6(0.00%) | Like=-34.81..-0.00 [-42.3073..-20.4432] | it/evals=11552/29685 eff=77.3964% N=1367 Z=-45.9(0.00%) | Like=-34.04..-0.00 [-42.3073..-20.4432] | it/evals=11588/29685 eff=77.5680% N=1367 Z=-45.2(0.00%) | Like=-33.16..-0.00 [-42.3073..-20.4432] | it/evals=11616/29813 eff=76.5256% N=1367 Z=-44.4(0.00%) | Like=-32.56..-0.00 [-42.3073..-20.4432] | it/evals=11648/29813 eff=76.7333% N=1367 Z=-43.8(0.00%) | Like=-31.99..-0.00 [-42.3073..-20.4432] | it/evals=11677/29813 eff=76.9151% N=1367 Z=-43.8(0.00%) | Like=-31.96..-0.00 [-42.3073..-20.4432] | it/evals=11680/29813 eff=76.9540% N=1367 Z=-42.4(0.00%) | Like=-30.29..-0.00 [-42.3073..-20.4432] | it/evals=11744/29813 eff=77.4474% N=1367 Z=-40.0(0.00%) | Like=-27.87..-0.00 [-42.3073..-20.4432] | it/evals=11843/29941 eff=76.8582% N=1367 Z=-39.5(0.00%) | Like=-27.31..-0.00 [-42.3073..-20.4432] | it/evals=11866/29941 eff=77.0115% N=1367 Z=-39.3(0.00%) | Like=-27.23..-0.00 [-42.3073..-20.4432] | it/evals=11872/29941 eff=77.0881% N=1367 Z=-39.0(0.00%) | Like=-26.83..-0.00 [-42.3073..-20.4432] | it/evals=11886/29941 eff=77.1775% N=1367 Z=-38.1(0.00%) | Like=-26.00..-0.00 [-42.3073..-20.4432] | it/evals=11927/29941 eff=77.4330% N=1367 Z=-37.9(0.00%) | Like=-25.87..-0.00 [-42.3073..-20.4432] | it/evals=11936/29941 eff=77.5096% N=1367 Z=-37.6(0.00%) | Like=-25.52..-0.00 [-42.3073..-20.4432] | it/evals=11952/29941 eff=77.6373% N=1367 Z=-36.8(0.00%) | Like=-24.75..-0.00 [-42.3073..-20.4432] | it/evals=11995/30069 eff=76.7027% N=1367 Z=-36.7(0.00%) | Like=-24.61..-0.00 [-42.3073..-20.4432] | it/evals=12000/30069 eff=76.7404% N=1367 Z=-36.6(0.00%) | Like=-24.53..-0.00 [-42.3073..-20.4432] | it/evals=12007/30069 eff=76.7655% N=1367 Z=-35.8(0.00%) | Like=-23.92..-0.00 [-42.3073..-20.4432] | it/evals=12051/30069 eff=77.0797% N=1367 Z=-35.3(0.00%) | Like=-23.37..-0.00 [-42.3073..-20.4432] | it/evals=12086/30069 eff=77.3184% N=1367 Z=-35.1(0.00%) | Like=-23.14..-0.00 [-42.3073..-20.4432] | it/evals=12096/30069 eff=77.3938% N=1367 Z=-34.6(0.00%) | Like=-22.38..-0.00 [-42.3073..-20.4432] | it/evals=12128/30069 eff=77.5823% N=1367 Z=-33.8(0.00%) | Like=-21.81..-0.00 [-42.3073..-20.4432] | it/evals=12169/30069 eff=77.7708% N=1367 Z=-33.5(0.00%) | Like=-21.57..-0.00 [-42.3073..-20.4432] | it/evals=12192/30069 eff=77.9467% N=1367 Z=-33.3(0.00%) | Like=-21.41..-0.00 [-42.3073..-20.4432] | it/evals=12203/30197 eff=76.7499% N=1367 Z=-32.7(0.00%) | Like=-20.68..-0.00 [-42.3073..-20.4432] | it/evals=12240/30197 eff=76.9725% N=1367 Z=-32.0(0.00%) | Like=-20.00..-0.00 [-20.4335..-10.0318] | it/evals=12288/30197 eff=77.3312% N=1367 Z=-31.5(0.00%) | Like=-19.47..-0.00 [-20.4335..-10.0318] | it/evals=12320/30197 eff=77.5291% N=1367 Z=-31.1(0.00%) | Like=-19.01..-0.00 [-20.4335..-10.0318] | it/evals=12352/30197 eff=77.7393% N=1367 Z=-30.6(0.00%) | Like=-18.56..-0.00 [-20.4335..-10.0318] | it/evals=12384/30197 eff=77.9372% N=1367 Z=-30.1(0.00%) | Like=-18.09..-0.00 [-20.4335..-10.0318] | it/evals=12418/30325 eff=76.8566% N=1367 Z=-29.7(0.00%) | Like=-17.74..-0.00 [-20.4335..-10.0318] | it/evals=12448/30325 eff=77.0757% N=1367 Z=-29.3(0.00%) | Like=-17.36..-0.00 [-20.4335..-10.0318] | it/evals=12482/30325 eff=77.2096% N=1367 Z=-29.1(0.00%) | Like=-17.16..-0.00 [-20.4335..-10.0318] | it/evals=12502/30325 eff=77.3314% N=1367 Z=-28.9(0.00%) | Like=-17.04..-0.00 [-20.4335..-10.0318] | it/evals=12514/30325 eff=77.4288% N=1367 Z=-28.3(0.00%) | Like=-16.45..-0.00 [-20.4335..-10.0318] | it/evals=12569/30325 eff=77.7940% N=1367 Z=-28.2(0.00%) | Like=-16.39..-0.00 [-20.4335..-10.0318] | it/evals=12576/30325 eff=77.8792% N=1367 Z=-28.1(0.00%) | Like=-16.12..-0.00 [-20.4335..-10.0318] | it/evals=12593/30325 eff=77.9888% N=1367 Z=-27.9(0.00%) | Like=-15.99..-0.00 [-20.4335..-10.0318] | it/evals=12604/30453 eff=76.8521% N=1367 Z=-27.8(0.00%) | Like=-15.89..-0.00 [-20.4335..-10.0318] | it/evals=12613/30453 eff=76.8880% N=1367 Z=-27.7(0.00%) | Like=-15.73..-0.00 [-20.4335..-10.0318] | it/evals=12628/30453 eff=76.9719% N=1367 Z=-26.8(0.00%) | Like=-14.77..-0.00 [-20.4335..-10.0318] | it/evals=12703/30453 eff=77.4275% N=1367 Z=-26.5(0.00%) | Like=-14.53..-0.00 [-20.4335..-10.0318] | it/evals=12729/30453 eff=77.5354% N=1367 Z=-26.5(0.00%) | Like=-14.45..-0.00 [-20.4335..-10.0318] | it/evals=12736/30453 eff=77.6193% N=1367 Z=-26.1(0.00%) | Like=-14.13..-0.00 [-20.4335..-10.0318] | it/evals=12768/30453 eff=77.8351% N=1367 Z=-25.8(0.00%) | Like=-13.86..-0.00 [-20.4335..-10.0318] | it/evals=12800/30453 eff=78.0269% N=1367 Z=-25.5(0.00%) | Like=-13.56..-0.00 [-20.4335..-10.0318] | it/evals=12833/30581 eff=77.0130% N=1367 Z=-25.4(0.00%) | Like=-13.51..-0.00 [-20.4335..-10.0318] | it/evals=12842/30581 eff=77.0484% N=1367 Z=-24.9(0.00%) | Like=-12.95..-0.00 [-20.4335..-10.0318] | it/evals=12896/30581 eff=77.3554% N=1367 Z=-24.7(0.00%) | Like=-12.66..-0.00 [-20.4335..-10.0318] | it/evals=12920/30581 eff=77.4380% N=1367 Z=-24.6(0.00%) | Like=-12.57..-0.00 [-20.4335..-10.0318] | it/evals=12928/30581 eff=77.4970% N=1367 Z=-24.4(0.00%) | Like=-12.28..-0.00 [-20.4335..-10.0318] | it/evals=12953/30581 eff=77.6033% N=1367 Z=-24.3(0.00%) | Like=-12.20..-0.00 [-20.4335..-10.0318] | it/evals=12960/30581 eff=77.6623% N=1367 Z=-24.1(0.00%) | Like=-11.98..-0.00 [-20.4335..-10.0318] | it/evals=12985/30581 eff=77.7804% N=1367 Z=-24.0(0.00%) | Like=-11.92..-0.00 [-20.4335..-10.0318] | it/evals=12992/30581 eff=77.8040% N=1367 Z=-23.7(0.00%) | Like=-11.63..-0.00 [-20.4335..-10.0318] | it/evals=13024/30581 eff=78.0519% N=1367 Z=-23.4(0.00%) | Like=-11.37..-0.00 [-20.4335..-10.0318] | it/evals=13058/30709 eff=77.0993% N=1367 Z=-23.3(0.00%) | Like=-11.30..-0.00 [-20.4335..-10.0318] | it/evals=13066/30709 eff=77.1226% N=1367 Z=-23.2(0.00%) | Like=-11.22..-0.00 [-20.4335..-10.0318] | it/evals=13079/30709 eff=77.1342% N=1367 Z=-23.1(0.00%) | Like=-11.13..-0.00 [-20.4335..-10.0318] | it/evals=13088/30709 eff=77.1807% N=1367 Z=-23.1(0.00%) | Like=-11.12..-0.00 [-20.4335..-10.0318] | it/evals=13092/30709 eff=77.1924% N=1367 Z=-23.0(0.00%) | Like=-11.06..-0.00 [-20.4335..-10.0318] | it/evals=13099/30709 eff=77.2156% N=1367 Z=-22.9(0.00%) | Like=-10.93..-0.00 [-20.4335..-10.0318] | it/evals=13120/30709 eff=77.4250% N=1367 Z=-22.7(0.00%) | Like=-10.77..-0.00 [-20.4335..-10.0318] | it/evals=13144/30709 eff=77.5762% N=1367 Z=-22.4(0.00%) | Like=-10.45..-0.00 [-20.4335..-10.0318] | it/evals=13179/30709 eff=77.7855% N=1367 Z=-22.4(0.00%) | Like=-10.41..-0.00 [-20.4335..-10.0318] | it/evals=13184/30709 eff=77.8204% N=1367 Z=-22.2(0.00%) | Like=-10.16..-0.00 [-20.4335..-10.0318] | it/evals=13209/30709 eff=77.9600% N=1367 Z=-22.1(0.00%) | Like=-10.11..-0.00 [-20.4335..-10.0318] | it/evals=13216/30709 eff=77.9833% N=1367 Z=-22.1(0.00%) | Like=-10.03..-0.00 [-20.4335..-10.0318] | it/evals=13226/30709 eff=78.0181% N=1367 Z=-21.2(0.01%) | Like=-9.20..-0.00 [-10.0214..-5.1716] | it/evals=13344/30837 eff=77.5957% N=1367 Z=-21.1(0.01%) | Like=-9.10..-0.00 [-10.0214..-5.1716] | it/evals=13353/30837 eff=77.6415% N=1367 Z=-20.3(0.03%) | Like=-8.27..-0.00 [-10.0214..-5.1716] | it/evals=13481/30965 eff=77.2758% N=1367 Z=-19.9(0.04%) | Like=-7.99..-0.00 [-10.0214..-5.1716] | it/evals=13536/30965 eff=77.5695% N=1367 Z=-19.6(0.05%) | Like=-7.51..-0.00 [-10.0214..-5.1716] | it/evals=13600/30965 eff=77.9309% N=1367 Z=-19.4(0.06%) | Like=-7.35..-0.00 [-10.0214..-5.1716] | it/evals=13632/30965 eff=78.1003% N=1367 Z=-19.2(0.08%) | Like=-7.25..-0.00 [-10.0214..-5.1716] | it/evals=13662/31093 eff=77.1543% N=1367 Z=-18.9(0.11%) | Like=-6.96..-0.00 [-10.0214..-5.1716] | it/evals=13728/31093 eff=77.5328% N=1367 Z=-18.7(0.12%) | Like=-6.79..-0.00 [-10.0214..-5.1716] | it/evals=13760/31093 eff=77.7221% N=1367 Z=-18.3(0.19%) | Like=-6.35..-0.00 [-10.0214..-5.1716] | it/evals=13856/31221 eff=77.0692% N=1367 Z=-18.2(0.22%) | Like=-6.21..-0.00 [-10.0214..-5.1716] | it/evals=13888/31221 eff=77.2119% N=1367 Z=-17.9(0.28%) | Like=-6.04..-0.00 [-10.0214..-5.1716] | it/evals=13952/31221 eff=77.5741% N=1367 Z=-17.8(0.30%) | Like=-5.99..-0.00 [-10.0214..-5.1716] | it/evals=13970/31221 eff=77.6619% N=1367 Z=-17.6(0.40%) | Like=-5.72..-0.00 [-10.0214..-5.1716] | it/evals=14048/31349 eff=76.9972% N=1367 Z=-17.4(0.45%) | Like=-5.58..-0.00 [-10.0214..-5.1716] | it/evals=14080/31349 eff=77.1812% N=1367 Z=-17.3(0.51%) | Like=-5.43..-0.00 [-10.0214..-5.1716] | it/evals=14112/31349 eff=77.3219% N=1367 Z=-17.2(0.57%) | Like=-5.27..-0.00 [-10.0214..-5.1716] | it/evals=14144/31349 eff=77.4843% N=1367 Z=-17.1(0.64%) | Like=-5.17..-0.00 [-10.0214..-5.1716] | it/evals=14176/31349 eff=77.7225% N=1367 Z=-17.0(0.71%) | Like=-5.03..-0.00 [-5.1687..-4.2961] | it/evals=14208/31349 eff=77.8848% N=1367 Z=-16.9(0.79%) | Like=-4.92..-0.00 [-5.1687..-4.2961] | it/evals=14240/31349 eff=78.0797% N=1367 Z=-16.8(0.89%) | Like=-4.81..-0.00 [-5.1687..-4.2961] | it/evals=14272/31477 eff=77.1514% N=1367 Z=-16.8(0.90%) | Like=-4.80..-0.00 [-5.1687..-4.2961] | it/evals=14276/31477 eff=77.1941% N=1367 Z=-16.7(0.98%) | Like=-4.72..-0.00 [-5.1687..-4.2961] | it/evals=14304/31477 eff=77.3863% N=1367 Z=-16.5(1.19%) | Like=-4.50..-0.00 [-5.1687..-4.2961] | it/evals=14368/31477 eff=77.7386% N=1367 Z=-16.3(1.43%) | Like=-4.28..-0.00 [-4.2957..-4.0989] | it/evals=14432/31605 eff=77.0487% N=1367 Z=-16.1(1.71%) | Like=-4.08..-0.00 [-4.0966..-4.0439] | it/evals=14496/31605 eff=77.4384% N=1367 Z=-15.9(2.06%) | Like=-3.90..-0.00 [-3.8990..-3.8887] | it/evals=14560/31605 eff=77.8070% N=1367 Z=-15.8(2.24%) | Like=-3.81..-0.00 [-3.8053..-3.8045]*| it/evals=14588/31605 eff=77.9334% N=1367 Z=-15.5(3.07%) | Like=-3.49..-0.00 [-3.4913..-3.4904]*| it/evals=14705/31733 eff=77.4787% N=1367 Z=-15.4(3.46%) | Like=-3.36..-0.00 [-3.3600..-3.3593]*| it/evals=14752/31733 eff=77.7593% N=1367 Z=-15.2(4.04%) | Like=-3.21..-0.00 [-3.2122..-3.2120]*| it/evals=14816/31861 eff=77.0769% N=1367 Z=-15.2(4.35%) | Like=-3.13..-0.00 [-3.1265..-3.1251]*| it/evals=14848/31861 eff=77.2308% N=1367 Z=-15.0(4.87%) | Like=-3.01..-0.00 [-3.0075..-3.0072]*| it/evals=14896/31861 eff=77.4564% N=1367 Z=-15.0(5.05%) | Like=-2.98..-0.00 [-2.9836..-2.9828]*| it/evals=14912/31861 eff=77.5590% N=1367 Z=-14.8(6.35%) | Like=-2.73..-0.00 [-2.7287..-2.7268]*| it/evals=15024/31989 eff=77.0905% N=1367 Z=-14.7(6.57%) | Like=-2.70..-0.00 [-2.6955..-2.6910]*| it/evals=15040/31989 eff=77.1614% N=1367 Z=-14.7(7.02%) | Like=-2.64..-0.00 [-2.6362..-2.6362]*| it/evals=15072/31989 eff=77.3335% N=1367 Z=-14.5(8.41%) | Like=-2.45..-0.00 [-2.4462..-2.4446]*| it/evals=15168/31989 eff=77.7890% N=1367 Z=-14.4(8.88%) | Like=-2.38..-0.00 [-2.3771..-2.3767]*| it/evals=15200/31989 eff=77.9712% N=1367 Z=-14.4(8.92%) | Like=-2.38..-0.00 [-2.3760..-2.3749]*| it/evals=15202/32117 eff=76.9838% N=1367 Z=-14.4(9.45%) | Like=-2.33..-0.00 [-2.3337..-2.3234] | it/evals=15232/32117 eff=77.1037% N=1367 Z=-14.3(10.59%) | Like=-2.22..-0.00 [-2.2167..-2.2136]*| it/evals=15296/32117 eff=77.4835% N=1367 Z=-14.2(11.17%) | Like=-2.17..-0.00 [-2.1710..-2.1693]*| it/evals=15328/32117 eff=77.6334% N=1367 Z=-14.1(12.37%) | Like=-2.06..-0.00 [-2.0636..-2.0621]*| it/evals=15392/32117 eff=77.8033% N=1367 Z=-14.0(13.02%) | Like=-2.03..-0.00 [-2.0268..-2.0267]*| it/evals=15424/32117 eff=77.9832% N=1367 Z=-13.9(14.26%) | Like=-1.93..-0.00 [-1.9311..-1.9295]*| it/evals=15488/32245 eff=77.2548% N=1367 Z=-13.9(14.70%) | Like=-1.91..-0.00 [-1.9062..-1.9062]*| it/evals=15509/32245 eff=77.3535% N=1367 Z=-13.9(15.64%) | Like=-1.83..-0.00 [-1.8308..-1.8308]*| it/evals=15552/32245 eff=77.5607% N=1367 Z=-13.8(17.05%) | Like=-1.76..-0.00 [-1.7573..-1.7568]*| it/evals=15616/32373 eff=76.8953% N=1367 Z=-13.7(17.72%) | Like=-1.71..-0.00 [-1.7137..-1.7131]*| it/evals=15648/32373 eff=77.0025% N=1367 Z=-13.7(18.47%) | Like=-1.68..-0.00 [-1.6798..-1.6797]*| it/evals=15680/32373 eff=77.1974% N=1367 Z=-13.6(20.01%) | Like=-1.61..-0.00 [-1.6112..-1.6105]*| it/evals=15744/32373 eff=77.5385% N=1367 Z=-13.6(20.75%) | Like=-1.57..-0.00 [-1.5747..-1.5746]*| it/evals=15776/32373 eff=77.7139% N=1367 Z=-13.5(21.56%) | Like=-1.53..-0.00 [-1.5321..-1.5277]*| it/evals=15808/32373 eff=77.8406% N=1367 Z=-13.5(21.74%) | Like=-1.52..-0.00 [-1.5214..-1.5192]*| it/evals=15815/32501 eff=76.9297% N=1367 Z=-13.5(22.37%) | Like=-1.49..-0.00 [-1.4905..-1.4904]*| it/evals=15840/32501 eff=77.0645% N=1367 Z=-13.4(25.47%) | Like=-1.38..-0.00 [-1.3774..-1.3766]*| it/evals=15961/32501 eff=77.6131% N=1367 Z=-13.4(25.65%) | Like=-1.37..-0.00 [-1.3715..-1.3695]*| it/evals=15968/32501 eff=77.6516% N=1367 Z=-13.3(26.51%) | Like=-1.33..-0.00 [-1.3344..-1.3343]*| it/evals=16000/32501 eff=77.8633% N=1367 Z=-13.3(27.35%) | Like=-1.31..-0.00 [-1.3112..-1.3110]*| it/evals=16032/32629 eff=77.1439% N=1367 Z=-13.3(28.18%) | Like=-1.29..-0.00 [-1.2906..-1.2905]*| it/evals=16064/32629 eff=77.3246% N=1367 Z=-13.2(29.77%) | Like=-1.24..-0.00 [-1.2400..-1.2369]*| it/evals=16125/32629 eff=77.5908% N=1367 Z=-13.2(30.71%) | Like=-1.21..-0.00 [-1.2051..-1.2047]*| it/evals=16160/32629 eff=77.7809% N=1367 Z=-13.2(31.57%) | Like=-1.18..-0.00 [-1.1828..-1.1817]*| it/evals=16192/32757 eff=77.0148% N=1367 Z=-13.1(32.42%) | Like=-1.15..-0.00 [-1.1483..-1.1481]*| it/evals=16224/32757 eff=77.1370% N=1367 Z=-13.1(34.20%) | Like=-1.11..-0.00 [-1.1053..-1.1044]*| it/evals=16288/32757 eff=77.4281% N=1367 Z=-13.1(35.05%) | Like=-1.09..-0.00 [-1.0864..-1.0854]*| it/evals=16320/32757 eff=77.5784% N=1367 Z=-13.0(37.58%) | Like=-1.01..-0.00 [-1.0103..-1.0094]*| it/evals=16416/32885 eff=77.0652% N=1367 Z=-13.0(37.98%) | Like=-1.00..-0.00 [-0.9999..-0.9998]*| it/evals=16432/32885 eff=77.1673% N=1367 Z=-13.0(38.38%) | Like=-0.99..-0.00 [-0.9941..-0.9940]*| it/evals=16448/32885 eff=77.2601% N=1367 Z=-12.9(39.23%) | Like=-0.97..-0.00 [-0.9690..-0.9686]*| it/evals=16480/32885 eff=77.3900% N=1367 Z=-12.9(40.88%) | Like=-0.92..-0.00 [-0.9221..-0.9210]*| it/evals=16544/32885 eff=77.7613% N=1367 Z=-12.9(42.50%) | Like=-0.88..-0.00 [-0.8757..-0.8756]*| it/evals=16608/33013 eff=77.1510% N=1367 Z=-12.8(43.29%) | Like=-0.86..-0.00 [-0.8575..-0.8570]*| it/evals=16640/33013 eff=77.2702% N=1367 Z=-12.8(44.97%) | Like=-0.81..-0.00 [-0.8137..-0.8134]*| it/evals=16704/33013 eff=77.5729% N=1367 Z=-12.8(45.81%) | Like=-0.79..-0.00 [-0.7941..-0.7933]*| it/evals=16736/33013 eff=77.7197% N=1367 Z=-12.8(45.87%) | Like=-0.79..-0.00 [-0.7933..-0.7930]*| it/evals=16738/33013 eff=77.7289% N=1367 Z=-12.8(46.65%) | Like=-0.78..-0.00 [-0.7759..-0.7747]*| it/evals=16768/33141 eff=77.0082% N=1367 Z=-12.7(49.64%) | Like=-0.72..-0.00 [-0.7225..-0.7220]*| it/evals=16886/33141 eff=77.5431% N=1367 Z=-12.6(52.64%) | Like=-0.66..-0.00 [-0.6617..-0.6608]*| it/evals=17006/33269 eff=77.1913% N=1367 Z=-12.6(53.71%) | Like=-0.64..-0.00 [-0.6412..-0.6412]*| it/evals=17050/33269 eff=77.3526% N=1367 Z=-12.6(53.85%) | Like=-0.64..-0.00 [-0.6369..-0.6368]*| it/evals=17056/33269 eff=77.3974% N=1367 Z=-12.6(54.60%) | Like=-0.62..-0.00 [-0.6248..-0.6242]*| it/evals=17088/33269 eff=77.5408% N=1367 Z=-12.6(55.39%) | Like=-0.61..-0.00 [-0.6094..-0.6089]*| it/evals=17120/33269 eff=77.6842% N=1367 Z=-12.6(56.15%) | Like=-0.60..-0.00 [-0.5951..-0.5950]*| it/evals=17152/33269 eff=77.8455% N=1367 Z=-12.6(56.91%) | Like=-0.58..-0.00 [-0.5823..-0.5822]*| it/evals=17184/33397 eff=77.0955% N=1367 Z=-12.5(59.15%) | Like=-0.54..-0.00 [-0.5411..-0.5410]*| it/evals=17280/33397 eff=77.4677% N=1367 Z=-12.5(59.87%) | Like=-0.53..-0.00 [-0.5307..-0.5304]*| it/evals=17312/33397 eff=77.5828% N=1367 Z=-12.5(60.85%) | Like=-0.52..-0.00 [-0.5161..-0.5156]*| it/evals=17356/33525 eff=76.9406% N=1367 Z=-12.5(61.30%) | Like=-0.51..-0.00 [-0.5099..-0.5097]*| it/evals=17376/33525 eff=77.0370% N=1367 Z=-12.5(62.68%) | Like=-0.48..-0.00 [-0.4834..-0.4828]*| it/evals=17440/33525 eff=77.3524% N=1367 Z=-12.5(63.36%) | Like=-0.47..-0.00 [-0.4740..-0.4738]*| it/evals=17472/33525 eff=77.5276% N=1367 Z=-12.4(65.63%) | Like=-0.44..-0.00 [-0.4375..-0.4373]*| it/evals=17581/33653 eff=77.1877% N=1367 Z=-12.4(67.19%) | Like=-0.41..-0.00 [-0.4137..-0.4135]*| it/evals=17662/33653 eff=77.5342% N=1367 Z=-12.4(67.83%) | Like=-0.40..-0.00 [-0.4034..-0.4033]*| it/evals=17696/33653 eff=77.6815% N=1367 Z=-12.4(68.43%) | Like=-0.39..-0.00 [-0.3937..-0.3937]*| it/evals=17728/33781 eff=76.9580% N=1367 Z=-12.4(69.04%) | Like=-0.38..-0.00 [-0.3841..-0.3832]*| it/evals=17760/33781 eff=77.1037% N=1367 Z=-12.3(71.17%) | Like=-0.35..-0.00 [-0.3516..-0.3513]*| it/evals=17879/33781 eff=77.5664% N=1367 Z=-12.3(71.87%) | Like=-0.34..-0.00 [-0.3414..-0.3412]*| it/evals=17920/33909 eff=76.9029% N=1367 Z=-12.3(72.41%) | Like=-0.33..-0.00 [-0.3301..-0.3301]*| it/evals=17952/33909 eff=77.0978% N=1367 Z=-12.3(72.69%) | Like=-0.33..-0.00 [-0.3264..-0.3262]*| it/evals=17969/33909 eff=77.1402% N=1367 Z=-12.3(73.47%) | Like=-0.31..-0.00 [-0.3129..-0.3129]*| it/evals=18016/33909 eff=77.3606% N=1367 Z=-12.3(74.00%) | Like=-0.31..-0.00 [-0.3065..-0.3063]*| it/evals=18048/33909 eff=77.5216% N=1367 Z=-12.3(75.02%) | Like=-0.29..-0.00 [-0.2909..-0.2908]*| it/evals=18112/34037 eff=76.9914% N=1367 Z=-12.3(76.83%) | Like=-0.27..-0.00 [-0.2680..-0.2680]*| it/evals=18230/34037 eff=77.5029% N=1367 Z=-12.3(77.44%) | Like=-0.26..-0.00 [-0.2613..-0.2611]*| it/evals=18272/34037 eff=77.6371% N=1367 Z=-12.3(77.48%) | Like=-0.26..-0.00 [-0.2610..-0.2610]*| it/evals=18275/34037 eff=77.6539% N=1367 Z=-12.2(78.35%) | Like=-0.25..-0.00 [-0.2479..-0.2479]*| it/evals=18336/34165 eff=77.1362% N=1367 Z=-12.2(78.79%) | Like=-0.24..-0.00 [-0.2424..-0.2423]*| it/evals=18368/34165 eff=77.2938% N=1367 Z=-12.2(79.22%) | Like=-0.24..-0.00 [-0.2372..-0.2370]*| it/evals=18400/34165 eff=77.4266% N=1367 Z=-12.2(80.07%) | Like=-0.23..-0.00 [-0.2271..-0.2269]*| it/evals=18464/34165 eff=77.6672% N=1367 Z=-12.2(80.48%) | Like=-0.22..-0.00 [-0.2219..-0.2219]*| it/evals=18496/34293 eff=76.9824% N=1367 Z=-12.2(80.88%) | Like=-0.22..-0.00 [-0.2162..-0.2161]*| it/evals=18528/34293 eff=77.1548% N=1367 Z=-12.2(81.28%) | Like=-0.21..-0.00 [-0.2117..-0.2116]*| it/evals=18560/34293 eff=77.3108% N=1367 Z=-12.2(81.58%) | Like=-0.21..-0.00 [-0.2073..-0.2064]*| it/evals=18584/34293 eff=77.4175% N=1367 Z=-12.2(82.05%) | Like=-0.20..-0.00 [-0.2013..-0.2011]*| it/evals=18624/34293 eff=77.5981% N=1367 Z=-12.2(82.42%) | Like=-0.20..-0.00 [-0.1969..-0.1968]*| it/evals=18656/34421 eff=76.9618% N=1367 Z=-12.2(82.80%) | Like=-0.19..-0.00 [-0.1930..-0.1929]*| it/evals=18688/34421 eff=77.1243% N=1367 Z=-12.2(83.16%) | Like=-0.19..-0.00 [-0.1881..-0.1881]*| it/evals=18720/34421 eff=77.2543% N=1367 Z=-12.2(84.37%) | Like=-0.18..-0.00 [-0.1750..-0.1748]*| it/evals=18832/34421 eff=77.7092% N=1367 Z=-12.2(84.96%) | Like=-0.17..-0.00 [-0.1663..-0.1662]*| it/evals=18890/34549 eff=77.1507% N=1367 Z=-12.2(85.18%) | Like=-0.16..-0.00 [-0.1635..-0.1635]*| it/evals=18912/34549 eff=77.2552% N=1367 Z=-12.2(85.81%) | Like=-0.16..-0.00 [-0.1566..-0.1566]*| it/evals=18976/34549 eff=77.5446% N=1367 Z=-12.2(86.11%) | Like=-0.15..-0.00 [-0.1527..-0.1525]*| it/evals=19008/34549 eff=77.6733% N=1367 Z=-12.1(86.71%) | Like=-0.15..-0.00 [-0.1463..-0.1462]*| it/evals=19072/34677 eff=77.1208% N=1367 Z=-12.1(87.28%) | Like=-0.14..-0.00 [-0.1404..-0.1402]*| it/evals=19136/34677 eff=77.3755% N=1367 Z=-12.1(87.55%) | Like=-0.14..-0.00 [-0.1379..-0.1379]*| it/evals=19168/34677 eff=77.5028% N=1367 Z=-12.1(87.80%) | Like=-0.13..-0.00 [-0.1342..-0.1342]*| it/evals=19198/34677 eff=77.6381% N=1367 Z=-12.1(87.82%) | Like=-0.13..-0.00 [-0.1341..-0.1338]*| it/evals=19200/34677 eff=77.6540% N=1367 Z=-12.1(88.08%) | Like=-0.13..-0.00 [-0.1301..-0.1301]*| it/evals=19232/34805 eff=77.0128% N=1367 Z=-12.1(88.34%) | Like=-0.13..-0.00 [-0.1278..-0.1278]*| it/evals=19264/34805 eff=77.1782% N=1367 Z=-12.1(89.09%) | Like=-0.12..-0.00 [-0.1196..-0.1196]*| it/evals=19360/34805 eff=77.5406% N=1367 Z=-12.1(89.79%) | Like=-0.11..-0.00 [-0.1103..-0.1102]*| it/evals=19456/34933 eff=77.0941% N=1367 Z=-12.1(90.13%) | Like=-0.11..-0.00 [-0.1075..-0.1074]*| it/evals=19505/34933 eff=77.2890% N=1367 Z=-12.1(90.89%) | Like=-0.10..-0.00 [-0.0986..-0.0985]*| it/evals=19621/34933 eff=77.7648% N=1367 Z=-12.1(91.63%) | Like=-0.09..-0.00 [-0.0895..-0.0894]*| it/evals=19743/35061 eff=77.4286% N=1367 Z=-12.1(91.64%) | Like=-0.09..-0.00 [-0.0894..-0.0893]*| it/evals=19744/35061 eff=77.4363% N=1367 Z=-12.1(92.02%) | Like=-0.08..-0.00 [-0.0844..-0.0844]*| it/evals=19811/35189 eff=76.9307% N=1367 Z=-12.1(92.36%) | Like=-0.08..-0.00 [-0.0807..-0.0806]*| it/evals=19872/35189 eff=77.1295% N=1367 Z=-12.1(92.53%) | Like=-0.08..-0.00 [-0.0792..-0.0791]*| it/evals=19904/35189 eff=77.2289% N=1367 Z=-12.1(92.69%) | Like=-0.08..-0.00 [-0.0779..-0.0779]*| it/evals=19936/35189 eff=77.3207% N=1367 Z=-12.1(92.85%) | Like=-0.08..-0.00 [-0.0760..-0.0760]*| it/evals=19968/35189 eff=77.4430% N=1367 Z=-12.1(93.17%) | Like=-0.07..-0.00 [-0.0717..-0.0716]*| it/evals=20032/35317 eff=76.9347% N=1367 Z=-12.1(93.47%) | Like=-0.07..-0.00 [-0.0680..-0.0680]*| it/evals=20096/35317 eff=77.2679% N=1367 Z=-12.1(93.57%) | Like=-0.07..-0.00 [-0.0667..-0.0667]*| it/evals=20117/35317 eff=77.3512% N=1367 Z=-12.1(93.62%) | Like=-0.07..-0.00 [-0.0663..-0.0663]*| it/evals=20128/35317 eff=77.4042% N=1367 Z=-12.1(94.13%) | Like=-0.06..-0.00 [-0.0610..-0.0610]*| it/evals=20247/35445 eff=77.1111% N=1367 Z=-12.1(94.30%) | Like=-0.06..-0.00 [-0.0598..-0.0598]*| it/evals=20288/35445 eff=77.2911% N=1367 Z=-12.1(94.43%) | Like=-0.06..-0.00 [-0.0583..-0.0582]*| it/evals=20320/35445 eff=77.4336% N=1367 Z=-12.1(94.68%) | Like=-0.06..-0.00 [-0.0556..-0.0555]*| it/evals=20384/35573 eff=76.9276% N=1367 Z=-12.1(94.80%) | Like=-0.05..-0.00 [-0.0543..-0.0542]*| it/evals=20416/35573 eff=77.0614% N=1367 Z=-12.1(94.82%) | Like=-0.05..-0.00 [-0.0539..-0.0539]*| it/evals=20423/35573 eff=77.0911% N=1367 Z=-12.1(95.03%) | Like=-0.05..-0.00 [-0.0515..-0.0515]*| it/evals=20480/35573 eff=77.3213% N=1367 Z=-12.1(95.25%) | Like=-0.05..-0.00 [-0.0491..-0.0490]*| it/evals=20544/35701 eff=76.8433% N=1367 Z=-12.1(95.56%) | Like=-0.05..-0.00 [-0.0454..-0.0454]*| it/evals=20640/35701 eff=77.1891% N=1367 Z=-12.0(95.76%) | Like=-0.04..-0.00 [-0.0434..-0.0433]*| it/evals=20704/35829 eff=76.6730% N=1367 Z=-12.0(95.84%) | Like=-0.04..-0.00 [-0.0426..-0.0426]*| it/evals=20729/35829 eff=76.7532% N=1367 Z=-12.0(95.86%) | Like=-0.04..-0.00 [-0.0425..-0.0424]*| it/evals=20736/35829 eff=76.7750% N=1367 Z=-12.0(95.95%) | Like=-0.04..-0.00 [-0.0416..-0.0416]*| it/evals=20768/35829 eff=76.8917% N=1367 Z=-12.0(96.14%) | Like=-0.04..-0.00 [-0.0399..-0.0399]*| it/evals=20832/35829 eff=77.1395% N=1367 Z=-12.0(96.22%) | Like=-0.04..-0.00 [-0.0391..-0.0391]*| it/evals=20864/35829 eff=77.2780% N=1367 Z=-12.0(96.31%) | Like=-0.04..-0.00 [-0.0379..-0.0379]*| it/evals=20896/35957 eff=76.7153% N=1367 Z=-12.0(96.47%) | Like=-0.04..-0.00 [-0.0361..-0.0361]*| it/evals=20960/35957 eff=76.9103% N=1367 Z=-12.0(96.55%) | Like=-0.04..-0.00 [-0.0352..-0.0352]*| it/evals=20992/35957 eff=77.0331% N=1367 Z=-12.0(96.63%) | Like=-0.03..-0.00 [-0.0345..-0.0345]*| it/evals=21024/35957 eff=77.1486% N=1367 Z=-12.0(96.66%) | Like=-0.03..-0.00 [-0.0343..-0.0343]*| it/evals=21035/35957 eff=77.1775% N=1367 Z=-12.0(96.86%) | Like=-0.03..-0.00 [-0.0321..-0.0320]*| it/evals=21120/36085 eff=76.7354% N=1367 Z=-12.0(96.93%) | Like=-0.03..-0.00 [-0.0312..-0.0312]*| it/evals=21152/36085 eff=76.8427% N=1367 Z=-12.0(97.07%) | Like=-0.03..-0.00 [-0.0299..-0.0298]*| it/evals=21216/36085 eff=77.0216% N=1367 Z=-12.0(97.20%) | Like=-0.03..-0.00 [-0.0286..-0.0285]*| it/evals=21280/36085 eff=77.2864% N=1367 Z=-12.0(97.32%) | Like=-0.03..-0.00 [-0.0271..-0.0271]*| it/evals=21341/36213 eff=76.7763% N=1367 Z=-12.0(97.39%) | Like=-0.03..-0.00 [-0.0265..-0.0265]*| it/evals=21376/36213 eff=76.9465% N=1367 Z=-12.0(97.45%) | Like=-0.03..-0.00 [-0.0258..-0.0258]*| it/evals=21408/36213 eff=77.0600% N=1367 Z=-12.0(97.51%) | Like=-0.03..-0.00 [-0.0252..-0.0252]*| it/evals=21440/36213 eff=77.1593% N=1367 Z=-12.0(97.67%) | Like=-0.02..-0.00 [-0.0235..-0.0235]*| it/evals=21536/36341 eff=76.8236% N=1367 Z=-12.0(97.78%) | Like=-0.02..-0.00 [-0.0224..-0.0224]*| it/evals=21600/36341 eff=77.0204% N=1367 Z=-12.0(97.83%) | Like=-0.02..-0.00 [-0.0218..-0.0218]*| it/evals=21632/36341 eff=77.1188% N=1367 Z=-12.0(97.85%) | Like=-0.02..-0.00 [-0.0215..-0.0215]*| it/evals=21647/36341 eff=77.1820% N=1367 Z=-12.0(97.93%) | Like=-0.02..-0.00 [-0.0207..-0.0206]*| it/evals=21696/36469 eff=76.6472% N=1367 Z=-12.0(98.10%) | Like=-0.02..-0.00 [-0.0190..-0.0190]*| it/evals=21813/36469 eff=77.0790% N=1367 Z=-12.0(98.11%) | Like=-0.02..-0.00 [-0.0189..-0.0189]*| it/evals=21824/36469 eff=77.1277% N=1367 Z=-12.0(98.15%) | Like=-0.02..-0.00 [-0.0185..-0.0185]*| it/evals=21856/36469 eff=77.2252% N=1367 Z=-12.0(98.20%) | Like=-0.02..-0.00 [-0.0181..-0.0181]*| it/evals=21888/36597 eff=76.6947% N=1367 Z=-12.0(98.24%) | Like=-0.02..-0.00 [-0.0178..-0.0177]*| it/evals=21920/36597 eff=76.8259% N=1367 Z=-12.0(98.28%) | Like=-0.02..-0.00 [-0.0173..-0.0173]*| it/evals=21952/36597 eff=76.9225% N=1367 Z=-12.0(98.28%) | Like=-0.02..-0.00 [-0.0173..-0.0173]*| it/evals=21954/36597 eff=76.9294% N=1367 Z=-12.0(98.42%) | Like=-0.02..-0.00 [-0.0157..-0.0157]*| it/evals=22073/36725 eff=76.6731% N=1367 Z=-12.0(98.43%) | Like=-0.02..-0.00 [-0.0156..-0.0156]*| it/evals=22080/36725 eff=76.7141% N=1367 Z=-12.0(98.47%) | Like=-0.02..-0.00 [-0.0153..-0.0153]*| it/evals=22112/36725 eff=76.8099% N=1367 Z=-12.0(98.54%) | Like=-0.01..-0.00 [-0.0147..-0.0147]*| it/evals=22176/36725 eff=77.0836% N=1367 Z=-12.0(98.57%) | Like=-0.01..-0.00 [-0.0143..-0.0143]*| it/evals=22208/36725 eff=77.1931% N=1367 Z=-12.0(98.62%) | Like=-0.01..-0.00 [-0.0137..-0.0137]*| it/evals=22262/36853 eff=76.6992% N=1367 Z=-12.0(98.67%) | Like=-0.01..-0.00 [-0.0133..-0.0133]*| it/evals=22304/36853 eff=76.8688% N=1367 Z=-12.0(98.73%) | Like=-0.01..-0.00 [-0.0127..-0.0127]*| it/evals=22368/36853 eff=77.1062% N=1367 Z=-12.0(98.76%) | Like=-0.01..-0.00 [-0.0123..-0.0123]*| it/evals=22400/36981 eff=76.5501% N=1367 Z=-12.0(98.86%) | Like=-0.01..-0.00 [-0.0113..-0.0113]*| it/evals=22516/36981 eff=76.9065% N=1367 Z=-12.0(98.89%) | Like=-0.01..-0.00 [-0.0109..-0.0109]*| it/evals=22560/36981 eff=77.0814% N=1367 Z=-12.0(98.90%) | Like=-0.01..-0.00 [-0.0109..-0.0109]*| it/evals=22568/36981 eff=77.1083% N=1367 Z=-12.0(98.94%) | Like=-0.01..-0.00 [-0.0105..-0.0105]*| it/evals=22624/37109 eff=76.6235% N=1367 Z=-12.0(98.99%) | Like=-0.01..-0.00 [-0.0101..-0.0101]*| it/evals=22688/37109 eff=76.8169% N=1367 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 37109 logzerr in iteration 2 0.1560823420564488 [ultranest] logZ = -12.01 +- 0.08472 [ultranest] Effective samples strategy satisfied (ESS = 5474.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.04 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 1540 minimum live points (dlogz from 0.07 to 0.16, need <0.1) [ultranest] logZ error budget: single: 0.17 bs:0.08 tail:0.01 total:0.08 required:<0.10 [ultranest] Widening roots to 1540 live points (have 1367 already) ... [ultranest] Sampling 173 live points from prior ... Z=-239552.2(0.00%) | Like=-238281.70..-0.00 [-245997.6291..-79459.9313] | it/evals=3/37410 eff=0.0000% N=1540 Z=-173988.3(0.00%) | Like=-173835.02..-0.00 [-245997.6291..-79459.9313] | it/evals=96/37410 eff=9.3750% N=1540 Z=-133092.2(0.00%) | Like=-133000.93..-0.00 [-245997.6291..-79459.9313] | it/evals=284/37410 eff=24.2188% N=1540 Z=-124631.0(0.00%) | Like=-124520.10..-0.00 [-245997.6291..-79459.9313] | it/evals=351/37410 eff=29.6875% N=1540 Z=-107627.2(0.00%) | Like=-107602.24..-0.00 [-245997.6291..-79459.9313] | it/evals=544/37410 eff=45.3125% N=1540 Z=-96420.1(0.00%) | Like=-96392.28..-0.00 [-245997.6291..-79459.9313] | it/evals=710/37410 eff=56.2500% N=1540 Z=-86398.7(0.00%) | Like=-86298.13..-0.00 [-245997.6291..-79459.9313] | it/evals=901/37489 eff=43.4783% N=1540 Z=-79505.3(0.00%) | Like=-79393.60..-0.00 [-79393.5973..-40497.5965] | it/evals=1060/37489 eff=53.6232% N=1540 Z=-70723.8(0.00%) | Like=-70710.58..-0.00 [-79393.5973..-40497.5965] | it/evals=1234/37489 eff=65.2174% N=1540 Z=-63768.3(0.00%) | Like=-63731.15..-0.00 [-79393.5973..-40497.5965] | it/evals=1405/37555 eff=57.1429% N=1540 Z=-56835.8(0.00%) | Like=-56823.71..-0.00 [-79393.5973..-40497.5965] | it/evals=1585/37555 eff=67.0330% N=1540 Z=-54185.4(0.00%) | Like=-54153.90..-0.00 [-79393.5973..-40497.5965] | it/evals=1664/37555 eff=69.5971% N=1540 Z=-51386.9(0.00%) | Like=-51264.62..-0.00 [-79393.5973..-40497.5965] | it/evals=1750/37608 eff=60.1227% N=1540 Z=-44798.9(0.00%) | Like=-44760.93..-0.00 [-79393.5973..-40497.5965] | it/evals=1948/37608 eff=65.0307% N=1540 Z=-40813.4(0.00%) | Like=-40791.72..-0.00 [-79393.5973..-40497.5965] | it/evals=2100/37648 eff=65.5738% N=1540 Z=-36953.2(0.00%) | Like=-36939.91..-0.00 [-40475.1321..-20327.9432] | it/evals=2272/37690 eff=63.7255% N=1540 Z=-32241.0(0.00%) | Like=-32213.31..-0.00 [-40475.1321..-20327.9432] | it/evals=2470/37690 eff=69.6078% N=1540 Z=-28632.7(0.00%) | Like=-28561.44..-0.00 [-40475.1321..-20327.9432] | it/evals=2661/37715 eff=70.2079% N=1540 Z=-25654.7(0.00%) | Like=-25635.08..-0.00 [-40475.1321..-20327.9432] | it/evals=2814/37740 eff=70.5240% N=1540 Z=-25635.9(0.00%) | Like=-25623.18..-0.00 [-40475.1321..-20327.9432] | it/evals=2816/37740 eff=70.9607% N=1540 Z=-23981.7(0.00%) | Like=-23963.75..-0.00 [-40475.1321..-20327.9432] | it/evals=2912/37759 eff=71.2788% N=1540 Z=-22378.2(0.00%) | Like=-22366.28..-0.00 [-40475.1321..-20327.9432] | it/evals=3008/37783 eff=69.8603% N=1540 Z=-22028.2(0.00%) | Like=-22007.25..-0.00 [-40475.1321..-20327.9432] | it/evals=3040/37783 eff=71.0579% N=1540 Z=-20442.7(0.00%) | Like=-20426.83..-0.00 [-40475.1321..-20327.9432] | it/evals=3168/37808 eff=70.5323% N=1540 Z=-17754.6(0.00%) | Like=-17736.14..-0.00 [-20307.2324..-10019.8323] | it/evals=3360/37829 eff=71.6636% N=1540 Z=-15901.5(0.00%) | Like=-15887.14..-0.00 [-20307.2324..-10019.8323] | it/evals=3529/37847 eff=71.6814% N=1540 Z=-14039.6(0.00%) | Like=-14029.53..-0.00 [-20307.2324..-10019.8323] | it/evals=3715/37862 eff=73.2759% N=1540 Z=-12807.1(0.00%) | Like=-12795.57..-0.00 [-20307.2324..-10019.8323] | it/evals=3840/37877 eff=72.7731% N=1540 Z=-12574.9(0.00%) | Like=-12559.04..-0.00 [-20307.2324..-10019.8323] | it/evals=3876/37885 eff=72.6368% N=1540 Z=-12144.3(0.00%) | Like=-12127.69..-0.00 [-20307.2324..-10019.8323] | it/evals=3936/37893 eff=73.1588% N=1540 Z=-10990.0(0.00%) | Like=-10975.88..-0.00 [-20307.2324..-10019.8323] | it/evals=4096/37914 eff=73.4177% N=1540 Z=-10144.5(0.00%) | Like=-10132.46..-0.00 [-20307.2324..-10019.8323] | it/evals=4231/37929 eff=73.5703% N=1540 Z=-9343.8(0.00%) | Like=-9327.89..-0.00 [-10016.4147..-5038.6055] | it/evals=4352/37957 eff=72.7407% N=1540 Z=-8430.9(0.00%) | Like=-8414.08..-0.00 [-10016.4147..-5038.6055] | it/evals=4512/37981 eff=73.2475% N=1540 Z=-8123.9(0.00%) | Like=-8113.96..-0.00 [-10016.4147..-5038.6055] | it/evals=4576/37993 eff=73.6990% N=1540 Z=-7196.1(0.00%) | Like=-7180.52..-0.00 [-10016.4147..-5038.6055] | it/evals=4756/38028 eff=73.5925% N=1540 Z=-6485.3(0.00%) | Like=-6474.78..-0.00 [-10016.4147..-5038.6055] | it/evals=4922/38045 eff=73.7877% N=1540 Z=-5765.3(0.00%) | Like=-5748.02..-0.00 [-10016.4147..-5038.6055] | it/evals=5103/38067 eff=74.0127% N=1540 Z=-5099.3(0.00%) | Like=-5086.49..-0.00 [-10016.4147..-5038.6055] | it/evals=5269/38085 eff=74.5953% N=1540 Z=-5061.0(0.00%) | Like=-5045.01..-0.00 [-10016.4147..-5038.6055] | it/evals=5280/38085 eff=74.8443% N=1540 Z=-4514.5(0.00%) | Like=-4502.57..-0.00 [-5034.2444..-2565.3637] | it/evals=5466/38106 eff=74.7573% N=1540 Z=-4072.9(0.00%) | Like=-4061.12..-0.00 [-5034.2444..-2565.3637] | it/evals=5634/38129 eff=74.9705% N=1540 Z=-3596.9(0.00%) | Like=-3584.90..-0.00 [-5034.2444..-2565.3637] | it/evals=5819/38146 eff=75.1157% N=1540 Z=-3272.6(0.00%) | Like=-3260.34..-0.00 [-5034.2444..-2565.3637] | it/evals=5983/38165 eff=75.0849% N=1540 Z=-3147.2(0.00%) | Like=-3135.30..-0.00 [-5034.2444..-2565.3637] | it/evals=6048/38177 eff=75.0838% N=1540 Z=-2762.7(0.00%) | Like=-2751.30..-0.00 [-5034.2444..-2565.3637] | it/evals=6241/38203 eff=74.7014% N=1540 Z=-2629.1(0.00%) | Like=-2618.04..-0.00 [-5034.2444..-2565.3637] | it/evals=6327/38220 eff=74.8401% N=1540 Z=-2380.5(0.00%) | Like=-2367.79..-0.00 [-2563.2706..-1292.2424] | it/evals=6464/38359 eff=67.0381% N=1540 Z=-2144.8(0.00%) | Like=-2132.51..-0.00 [-2563.2706..-1292.2424] | it/evals=6624/38359 eff=68.6165% N=1540 Z=-2089.0(0.00%) | Like=-2076.26..-0.00 [-2563.2706..-1292.2424] | it/evals=6676/38359 eff=69.2665% N=1540 Z=-1955.1(0.00%) | Like=-1941.84..-0.00 [-2563.2706..-1292.2424] | it/evals=6784/38359 eff=70.2878% N=1540 Z=-1815.6(0.00%) | Like=-1804.35..-0.00 [-2563.2706..-1292.2424] | it/evals=6880/38359 eff=71.2163% N=1540 Z=-1655.3(0.00%) | Like=-1643.27..-0.00 [-2563.2706..-1292.2424] | it/evals=7020/38359 eff=72.7019% N=1540 Z=-1475.6(0.00%) | Like=-1463.60..-0.00 [-2563.2706..-1292.2424] | it/evals=7201/38490 eff=66.8046% N=1540 Z=-1365.7(0.00%) | Like=-1353.37..-0.00 [-2563.2706..-1292.2424] | it/evals=7328/38490 eff=67.8808% N=1540 Z=-1332.2(0.00%) | Like=-1319.18..-0.00 [-2563.2706..-1292.2424] | it/evals=7366/38490 eff=68.1291% N=1540 Z=-1308.2(0.00%) | Like=-1296.93..-0.00 [-2563.2706..-1292.2424] | it/evals=7392/38490 eff=68.4603% N=1540 Z=-1242.1(0.00%) | Like=-1230.00..-0.00 [-1290.8302..-661.3478] | it/evals=7488/38490 eff=69.1225% N=1540 Z=-1217.3(0.00%) | Like=-1205.97..-0.00 [-1290.8302..-661.3478] | it/evals=7515/38490 eff=69.2053% N=1540 Z=-1080.5(0.00%) | Like=-1067.45..-0.00 [-1290.8302..-661.3478] | it/evals=7706/38490 eff=70.4470% N=1540 Z=-1007.6(0.00%) | Like=-995.29..-0.00 [-1290.8302..-661.3478] | it/evals=7815/38490 eff=71.1921% N=1540 Z=-970.3(0.00%) | Like=-957.73..-0.00 [-1290.8302..-661.3478] | it/evals=7872/38490 eff=71.6887% N=1540 Z=-855.8(0.00%) | Like=-842.85..-0.00 [-1290.8302..-661.3478] | it/evals=8080/38620 eff=66.4425% N=1540 Z=-807.8(0.00%) | Like=-796.55..-0.00 [-1290.8302..-661.3478] | it/evals=8159/38620 eff=67.0404% N=1540 Z=-724.7(0.00%) | Like=-712.92..-0.00 [-1290.8302..-661.3478] | it/evals=8348/38620 eff=68.3857% N=1540 Z=-658.1(0.00%) | Like=-646.04..-0.00 [-661.3393..-332.5205] | it/evals=8503/38620 eff=69.3572% N=1540 Z=-587.0(0.00%) | Like=-575.15..-0.00 [-661.3393..-332.5205] | it/evals=8698/38620 eff=71.0015% N=1540 Z=-537.9(0.00%) | Like=-524.84..-0.00 [-661.3393..-332.5205] | it/evals=8832/38620 eff=72.1973% N=1540 Z=-522.2(0.00%) | Like=-510.37..-0.00 [-661.3393..-332.5205] | it/evals=8865/38620 eff=72.2720% N=1540 Z=-461.9(0.00%) | Like=-449.49..-0.00 [-661.3393..-332.5205] | it/evals=9054/38748 eff=67.3943% N=1540 Z=-414.0(0.00%) | Like=-401.66..-0.00 [-661.3393..-332.5205] | it/evals=9224/38748 eff=68.3492% N=1540 Z=-408.9(0.00%) | Like=-397.38..-0.00 [-661.3393..-332.5205] | it/evals=9248/38748 eff=68.4175% N=1540 Z=-376.3(0.00%) | Like=-364.65..-0.00 [-661.3393..-332.5205] | it/evals=9376/38748 eff=69.8499% N=1540 Z=-334.8(0.00%) | Like=-322.80..-0.00 [-332.3972..-163.5867] | it/evals=9572/38748 eff=71.2824% N=1540 Z=-298.8(0.00%) | Like=-286.87..-0.00 [-332.3972..-163.5867] | it/evals=9758/38876 eff=66.8130% N=1540 Z=-267.8(0.00%) | Like=-255.40..-0.00 [-332.3972..-163.5867] | it/evals=9919/38876 eff=68.0678% N=1540 Z=-256.5(0.00%) | Like=-244.28..-0.00 [-332.3972..-163.5867] | it/evals=9984/38876 eff=68.3187% N=1540 Z=-239.7(0.00%) | Like=-227.95..-0.00 [-332.3972..-163.5867] | it/evals=10080/38876 eff=69.1970% N=1540 Z=-233.3(0.00%) | Like=-221.25..-0.00 [-332.3972..-163.5867] | it/evals=10125/38876 eff=69.5107% N=1540 Z=-220.0(0.00%) | Like=-208.20..-0.00 [-332.3972..-163.5867] | it/evals=10208/38876 eff=70.2635% N=1540 Z=-196.4(0.00%) | Like=-184.30..-0.00 [-332.3972..-163.5867] | it/evals=10401/39004 eff=66.3763% N=1540 Z=-188.7(0.00%) | Like=-176.92..-0.00 [-332.3972..-163.5867] | it/evals=10471/39004 eff=67.0151% N=1540 Z=-182.4(0.00%) | Like=-170.58..-0.00 [-332.3972..-163.5867] | it/evals=10536/39004 eff=67.4797% N=1540 Z=-163.8(0.00%) | Like=-151.73..-0.00 [-163.5613..-83.2797] | it/evals=10725/39004 eff=68.6992% N=1540 Z=-161.6(0.00%) | Like=-150.13..-0.00 [-163.5613..-83.2797] | it/evals=10752/39004 eff=68.8153% N=1540 Z=-148.4(0.00%) | Like=-136.39..-0.00 [-163.5613..-83.2797] | it/evals=10898/39004 eff=70.0348% N=1540 Z=-132.8(0.00%) | Like=-121.11..-0.00 [-163.5613..-83.2797] | it/evals=11089/39132 eff=66.6486% N=1540 Z=-127.1(0.00%) | Like=-115.24..-0.00 [-163.5613..-83.2797] | it/evals=11169/39132 eff=67.1351% N=1540 Z=-123.8(0.00%) | Like=-111.82..-0.00 [-163.5613..-83.2797] | it/evals=11209/39132 eff=67.4054% N=1540 Z=-119.2(0.00%) | Like=-107.32..-0.00 [-163.5613..-83.2797] | it/evals=11279/39132 eff=67.8378% N=1540 Z=-118.6(0.00%) | Like=-106.33..-0.00 [-163.5613..-83.2797] | it/evals=11288/39132 eff=67.9459% N=1540 Z=-112.2(0.00%) | Like=-100.21..-0.00 [-163.5613..-83.2797] | it/evals=11364/39132 eff=68.3243% N=1540 Z=-107.9(0.00%) | Like=-95.79..-0.00 [-163.5613..-83.2797] | it/evals=11423/39132 eff=68.4865% N=1540 Z=-105.9(0.00%) | Like=-93.92..-0.00 [-163.5613..-83.2797] | it/evals=11455/39132 eff=68.5946% N=1540 Z=-102.5(0.00%) | Like=-90.59..-0.00 [-163.5613..-83.2797] | it/evals=11518/39132 eff=68.8108% N=1540 Z=-95.4(0.00%) | Like=-83.49..-0.00 [-163.5613..-83.2797] | it/evals=11648/39132 eff=69.4595% N=1540 Z=-93.9(0.00%) | Like=-82.04..-0.00 [-83.2491..-41.3037] | it/evals=11680/39132 eff=69.6757% N=1540 Z=-84.7(0.00%) | Like=-72.75..-0.00 [-83.2491..-41.3037] | it/evals=11865/39260 eff=66.3802% N=1540 Z=-81.3(0.00%) | Like=-69.14..-0.00 [-83.2491..-41.3037] | it/evals=11950/39260 eff=66.9363% N=1540 Z=-79.2(0.00%) | Like=-67.07..-0.00 [-83.2491..-41.3037] | it/evals=11999/39260 eff=67.0880% N=1540 Z=-75.6(0.00%) | Like=-63.71..-0.00 [-83.2491..-41.3037] | it/evals=12094/39260 eff=67.7958% N=1540 Z=-74.3(0.00%) | Like=-62.28..-0.00 [-83.2491..-41.3037] | it/evals=12133/39260 eff=67.9474% N=1540 Z=-67.3(0.00%) | Like=-55.14..-0.00 [-83.2491..-41.3037] | it/evals=12321/39260 eff=68.8069% N=1540 Z=-64.9(0.00%) | Like=-52.79..-0.00 [-83.2491..-41.3037] | it/evals=12384/39260 eff=69.1608% N=1540 Z=-63.0(0.00%) | Like=-50.92..-0.00 [-83.2491..-41.3037] | it/evals=12437/39260 eff=69.5652% N=1540 Z=-61.6(0.00%) | Like=-49.40..-0.00 [-83.2491..-41.3037] | it/evals=12480/39388 eff=65.7645% N=1540 Z=-61.3(0.00%) | Like=-49.14..-0.00 [-83.2491..-41.3037] | it/evals=12488/39388 eff=65.9069% N=1540 Z=-60.5(0.00%) | Like=-48.37..-0.00 [-83.2491..-41.3037] | it/evals=12512/39388 eff=66.0019% N=1540 Z=-59.0(0.00%) | Like=-46.89..-0.00 [-83.2491..-41.3037] | it/evals=12554/39388 eff=66.3343% N=1540 Z=-58.3(0.00%) | Like=-46.18..-0.00 [-83.2491..-41.3037] | it/evals=12578/39388 eff=66.4767% N=1540 Z=-57.4(0.00%) | Like=-45.37..-0.00 [-83.2491..-41.3037] | it/evals=12606/39388 eff=66.5242% N=1540 Z=-56.4(0.00%) | Like=-44.49..-0.00 [-83.2491..-41.3037] | it/evals=12640/39388 eff=66.7616% N=1540 Z=-55.5(0.00%) | Like=-43.53..-0.00 [-83.2491..-41.3037] | it/evals=12672/39388 eff=66.9516% N=1540 Z=-51.1(0.00%) | Like=-38.96..-0.00 [-41.2950..-19.8452] | it/evals=12828/39388 eff=67.8538% N=1540 Z=-50.4(0.00%) | Like=-38.30..-0.00 [-41.2950..-19.8452] | it/evals=12852/39388 eff=67.9012% N=1540 Z=-49.1(0.00%) | Like=-37.07..-0.00 [-41.2950..-19.8452] | it/evals=12897/39388 eff=68.0912% N=1540 Z=-46.0(0.00%) | Like=-34.12..-0.00 [-41.2950..-19.8452] | it/evals=13024/39388 eff=68.3761% N=1540 Z=-45.6(0.00%) | Like=-33.54..-0.00 [-41.2950..-19.8452] | it/evals=13042/39388 eff=68.4710% N=1540 Z=-43.8(0.00%) | Like=-32.05..-0.00 [-41.2950..-19.8452] | it/evals=13128/39388 eff=68.8984% N=1540 Z=-43.4(0.00%) | Like=-31.59..-0.00 [-41.2950..-19.8452] | it/evals=13152/39388 eff=69.1358% N=1540 Z=-42.3(0.00%) | Like=-30.21..-0.00 [-41.2950..-19.8452] | it/evals=13209/39388 eff=69.5157% N=1540 Z=-40.8(0.00%) | Like=-28.77..-0.00 [-41.2950..-19.8452] | it/evals=13280/39388 eff=69.9905% N=1540 Z=-39.8(0.00%) | Like=-27.61..-0.00 [-41.2950..-19.8452] | it/evals=13333/39516 eff=66.2936% N=1540 Z=-39.4(0.00%) | Like=-27.29..-0.00 [-41.2950..-19.8452] | it/evals=13354/39516 eff=66.4727% N=1540 Z=-38.9(0.00%) | Like=-26.84..-0.00 [-41.2950..-19.8452] | it/evals=13375/39516 eff=66.6517% N=1540 Z=-38.1(0.00%) | Like=-25.96..-0.00 [-41.2950..-19.8452] | it/evals=13421/39516 eff=66.7860% N=1540 Z=-37.2(0.00%) | Like=-25.11..-0.00 [-41.2950..-19.8452] | it/evals=13471/39516 eff=66.8756% N=1540 Z=-36.6(0.00%) | Like=-24.53..-0.00 [-41.2950..-19.8452] | it/evals=13504/39516 eff=67.0098% N=1540 Z=-35.7(0.00%) | Like=-23.85..-0.00 [-41.2950..-19.8452] | it/evals=13562/39516 eff=67.2337% N=1540 Z=-35.3(0.00%) | Like=-23.36..-0.00 [-41.2950..-19.8452] | it/evals=13594/39516 eff=67.4575% N=1540 Z=-33.5(0.00%) | Like=-21.52..-0.00 [-41.2950..-19.8452] | it/evals=13711/39516 eff=67.8603% N=1540 Z=-33.2(0.00%) | Like=-21.29..-0.00 [-41.2950..-19.8452] | it/evals=13730/39516 eff=67.9051% N=1540 Z=-32.8(0.00%) | Like=-20.75..-0.00 [-41.2950..-19.8452] | it/evals=13757/39516 eff=68.0394% N=1540 Z=-32.8(0.00%) | Like=-20.74..-0.00 [-41.2950..-19.8452] | it/evals=13760/39516 eff=68.0842% N=1540 Z=-31.1(0.00%) | Like=-19.04..-0.00 [-19.8317..-9.6469] | it/evals=13888/39516 eff=68.8004% N=1540 Z=-30.0(0.00%) | Like=-18.02..-0.00 [-19.8317..-9.6469] | it/evals=13973/39516 eff=69.1585% N=1540 Z=-29.9(0.00%) | Like=-17.90..-0.00 [-19.8317..-9.6469] | it/evals=13984/39516 eff=69.2032% N=1540 Z=-29.5(0.00%) | Like=-17.56..-0.00 [-19.8317..-9.6469] | it/evals=14016/39516 eff=69.3823% N=1540 Z=-29.2(0.00%) | Like=-17.29..-0.00 [-19.8317..-9.6469] | it/evals=14040/39516 eff=69.4270% N=1540 Z=-29.1(0.00%) | Like=-17.18..-0.00 [-19.8317..-9.6469] | it/evals=14054/39516 eff=69.4718% N=1540 Z=-28.8(0.00%) | Like=-16.94..-0.00 [-19.8317..-9.6469] | it/evals=14080/39516 eff=69.6061% N=1540 Z=-28.2(0.00%) | Like=-16.29..-0.00 [-19.8317..-9.6469] | it/evals=14142/39516 eff=69.7404% N=1540 Z=-28.1(0.00%) | Like=-16.15..-0.00 [-19.8317..-9.6469] | it/evals=14153/39516 eff=69.8299% N=1540 Z=-27.9(0.00%) | Like=-15.97..-0.00 [-19.8317..-9.6469] | it/evals=14168/39516 eff=69.9194% N=1540 Z=-27.9(0.00%) | Like=-15.91..-0.00 [-19.8317..-9.6469] | it/evals=14175/39516 eff=69.9642% N=1540 Z=-27.7(0.00%) | Like=-15.71..-0.00 [-19.8317..-9.6469] | it/evals=14196/39644 eff=66.2997% N=1540 Z=-27.5(0.00%) | Like=-15.53..-0.00 [-19.8317..-9.6469] | it/evals=14208/39644 eff=66.3844% N=1540 Z=-26.6(0.00%) | Like=-14.59..-0.00 [-19.8317..-9.6469] | it/evals=14301/39644 eff=66.7655% N=1540 Z=-26.5(0.00%) | Like=-14.54..-0.00 [-19.8317..-9.6469] | it/evals=14307/39644 eff=66.8078% N=1540 Z=-25.7(0.00%) | Like=-13.81..-0.00 [-19.8317..-9.6469] | it/evals=14400/39644 eff=67.3582% N=1540 Z=-25.3(0.00%) | Like=-13.43..-0.00 [-19.8317..-9.6469] | it/evals=14449/39644 eff=67.5275% N=1540 Z=-24.7(0.00%) | Like=-12.68..-0.00 [-19.8317..-9.6469] | it/evals=14522/39644 eff=67.8239% N=1540 Z=-24.6(0.00%) | Like=-12.64..-0.00 [-19.8317..-9.6469] | it/evals=14528/39644 eff=67.8662% N=1540 Z=-24.3(0.00%) | Like=-12.26..-0.00 [-19.8317..-9.6469] | it/evals=14568/39644 eff=68.1626% N=1540 Z=-24.0(0.00%) | Like=-11.99..-0.00 [-19.8317..-9.6469] | it/evals=14597/39644 eff=68.2472% N=1540 Z=-24.0(0.00%) | Like=-11.90..-0.00 [-19.8317..-9.6469] | it/evals=14607/39644 eff=68.2896% N=1540 Z=-23.3(0.00%) | Like=-11.36..-0.00 [-19.8317..-9.6469] | it/evals=14683/39644 eff=68.7130% N=1540 Z=-23.3(0.00%) | Like=-11.31..-0.00 [-19.8317..-9.6469] | it/evals=14689/39644 eff=68.7553% N=1540 Z=-23.2(0.00%) | Like=-11.23..-0.00 [-19.8317..-9.6469] | it/evals=14704/39644 eff=68.7976% N=1540 Z=-23.1(0.00%) | Like=-11.11..-0.00 [-19.8317..-9.6469] | it/evals=14722/39644 eff=68.9670% N=1540 Z=-22.9(0.00%) | Like=-10.96..-0.00 [-19.8317..-9.6469] | it/evals=14745/39644 eff=69.0093% N=1540 Z=-22.7(0.00%) | Like=-10.78..-0.00 [-19.8317..-9.6469] | it/evals=14777/39644 eff=69.1787% N=1540 Z=-22.3(0.00%) | Like=-10.37..-0.00 [-19.8317..-9.6469] | it/evals=14829/39644 eff=69.3903% N=1540 Z=-22.2(0.00%) | Like=-10.17..-0.00 [-19.8317..-9.6469] | it/evals=14850/39644 eff=69.4750% N=1540 Z=-22.0(0.00%) | Like=-10.04..-0.00 [-19.8317..-9.6469] | it/evals=14871/39644 eff=69.6444% N=1540 Z=-21.0(0.01%) | Like=-9.04..-0.00 [-9.6392..-5.0468] | it/evals=15031/39772 eff=66.9880% N=1540 Z=-19.9(0.04%) | Like=-7.92..-0.00 [-9.6392..-5.0468] | it/evals=15225/39772 eff=67.4699% N=1540 Z=-19.2(0.08%) | Like=-7.25..-0.00 [-9.6392..-5.0468] | it/evals=15360/39772 eff=68.1124% N=1540 Z=-19.1(0.08%) | Like=-7.15..-0.00 [-9.6392..-5.0468] | it/evals=15382/39772 eff=68.2329% N=1540 Z=-18.8(0.12%) | Like=-6.86..-0.00 [-9.6392..-5.0468] | it/evals=15456/39772 eff=68.6747% N=1540 Z=-18.5(0.15%) | Like=-6.60..-0.00 [-9.6392..-5.0468] | it/evals=15520/39772 eff=68.9157% N=1540 Z=-17.7(0.34%) | Like=-5.88..-0.00 [-9.6392..-5.0468] | it/evals=15741/39772 eff=69.5984% N=1540 Z=-17.1(0.63%) | Like=-5.16..-0.00 [-9.6392..-5.0468] | it/evals=15934/39900 eff=67.0359% N=1540 Z=-17.1(0.63%) | Like=-5.16..-0.00 [-9.6392..-5.0468] | it/evals=15936/39900 eff=67.0741% N=1540 Z=-16.6(0.99%) | Like=-4.70..-0.00 [-5.0411..-4.3847] | it/evals=16086/39900 eff=67.7617% N=1540 Z=-16.0(1.70%) | Like=-4.07..-0.00 [-4.0750..-4.0730]*| it/evals=16295/39900 eff=68.6402% N=1540 Z=-15.9(1.97%) | Like=-3.94..-0.00 [-3.9356..-3.9334]*| it/evals=16352/39900 eff=68.7548% N=1540 Z=-15.7(2.50%) | Like=-3.71..-0.00 [-3.7088..-3.7066]*| it/evals=16447/39900 eff=69.4041% N=1540 Z=-15.6(2.69%) | Like=-3.64..-0.00 [-3.6363..-3.6359]*| it/evals=16480/39900 eff=69.5569% N=1540 Z=-15.4(3.36%) | Like=-3.39..-0.00 [-3.3903..-3.3876]*| it/evals=16576/40028 eff=66.9337% N=1540 Z=-15.1(4.39%) | Like=-3.13..-0.00 [-3.1276..-3.1265]*| it/evals=16704/40028 eff=67.5892% N=1540 Z=-14.9(5.33%) | Like=-2.93..-0.00 [-2.9337..-2.9326]*| it/evals=16801/40028 eff=67.8077% N=1540 Z=-14.6(7.04%) | Like=-2.63..-0.00 [-2.6333..-2.6329]*| it/evals=16954/40028 eff=68.3176% N=1540 Z=-14.4(9.11%) | Like=-2.36..-0.00 [-2.3587..-2.3586]*| it/evals=17109/40028 eff=69.0459% N=1540 Z=-14.3(9.77%) | Like=-2.29..-0.00 [-2.2916..-2.2901]*| it/evals=17152/40028 eff=69.2280% N=1540 Z=-14.1(12.29%) | Like=-2.07..-0.00 [-2.0740..-2.0711]*| it/evals=17308/40156 eff=66.7711% N=1540 Z=-14.0(13.49%) | Like=-1.98..-0.00 [-1.9787..-1.9783]*| it/evals=17376/40156 eff=67.0146% N=1540 Z=-13.8(15.70%) | Like=-1.83..-0.00 [-1.8263..-1.8261]*| it/evals=17496/40156 eff=67.4322% N=1540 Z=-13.8(15.86%) | Like=-1.82..-0.00 [-1.8215..-1.8209]*| it/evals=17504/40156 eff=67.4669% N=1540 Z=-13.7(17.07%) | Like=-1.74..-0.00 [-1.7443..-1.7434]*| it/evals=17568/40156 eff=67.6409% N=1540 Z=-13.6(20.69%) | Like=-1.56..-0.00 [-1.5648..-1.5646]*| it/evals=17743/40156 eff=68.1280% N=1540 Z=-13.4(23.75%) | Like=-1.43..-0.00 [-1.4332..-1.4330]*| it/evals=17880/40156 eff=68.7543% N=1540 Z=-13.4(23.91%) | Like=-1.42..-0.00 [-1.4241..-1.4231]*| it/evals=17888/40156 eff=68.7891% N=1540 Z=-13.4(25.38%) | Like=-1.37..-0.00 [-1.3731..-1.3715]*| it/evals=17952/40156 eff=69.0327% N=1540 Z=-13.3(26.14%) | Like=-1.34..-0.00 [-1.3355..-1.3349]*| it/evals=17984/40156 eff=69.0675% N=1540 Z=-13.2(29.97%) | Like=-1.21..-0.00 [-1.2102..-1.2101]*| it/evals=18148/40284 eff=66.4890% N=1540 Z=-13.1(32.23%) | Like=-1.14..-0.00 [-1.1351..-1.1348]*| it/evals=18243/40284 eff=66.6889% N=1540 Z=-13.0(34.51%) | Like=-1.08..-0.00 [-1.0822..-1.0814]*| it/evals=18336/40284 eff=66.9887% N=1540 Z=-12.9(38.24%) | Like=-0.98..-0.00 [-0.9835..-0.9821]*| it/evals=18494/40284 eff=67.5217% N=1540 Z=-12.9(40.51%) | Like=-0.92..-0.00 [-0.9163..-0.9160]*| it/evals=18591/40284 eff=67.8881% N=1540 Z=-12.9(41.27%) | Like=-0.90..-0.00 [-0.9010..-0.9008]*| it/evals=18624/40284 eff=68.1213% N=1540 Z=-12.8(44.62%) | Like=-0.81..-0.00 [-0.8123..-0.8112]*| it/evals=18771/40284 eff=68.7542% N=1540 Z=-12.7(48.71%) | Like=-0.73..-0.00 [-0.7278..-0.7277]*| it/evals=18950/40412 eff=66.3898% N=1540 Z=-12.6(52.21%) | Like=-0.66..-0.00 [-0.6562..-0.6561]*| it/evals=19107/40412 eff=66.7732% N=1540 Z=-12.6(55.60%) | Like=-0.59..-0.00 [-0.5919..-0.5918]*| it/evals=19264/40412 eff=67.1565% N=1540 Z=-12.6(56.31%) | Like=-0.58..-0.00 [-0.5792..-0.5785]*| it/evals=19297/40412 eff=67.2843% N=1540 Z=-12.5(56.97%) | Like=-0.57..-0.00 [-0.5664..-0.5661]*| it/evals=19328/40412 eff=67.3482% N=1540 Z=-12.5(59.99%) | Like=-0.52..-0.00 [-0.5202..-0.5202]*| it/evals=19474/40412 eff=68.0192% N=1540 Z=-12.4(62.98%) | Like=-0.47..-0.00 [-0.4722..-0.4719]*| it/evals=19628/40540 eff=65.9914% N=1540 Z=-12.4(63.43%) | Like=-0.46..-0.00 [-0.4638..-0.4630]*| it/evals=19651/40540 eff=66.1449% N=1540 Z=-12.4(65.70%) | Like=-0.43..-0.00 [-0.4292..-0.4291]*| it/evals=19776/40540 eff=66.6974% N=1540 Z=-12.4(66.26%) | Like=-0.42..-0.00 [-0.4222..-0.4222]*| it/evals=19808/40540 eff=66.7894% N=1540 Z=-12.4(66.80%) | Like=-0.41..-0.00 [-0.4149..-0.4145]*| it/evals=19840/40540 eff=66.8815% N=1540 Z=-12.3(69.64%) | Like=-0.37..-0.00 [-0.3676..-0.3675]*| it/evals=20009/40540 eff=67.2805% N=1540 Z=-12.3(72.08%) | Like=-0.33..-0.00 [-0.3285..-0.3284]*| it/evals=20166/40540 eff=67.8023% N=1540 Z=-12.3(72.94%) | Like=-0.32..-0.00 [-0.3182..-0.3179]*| it/evals=20224/40540 eff=68.1707% N=1540 Z=-12.3(74.98%) | Like=-0.29..-0.00 [-0.2861..-0.2859]*| it/evals=20366/40668 eff=65.9480% N=1540 Z=-12.2(77.23%) | Like=-0.26..-0.00 [-0.2589..-0.2588]*| it/evals=20531/40668 eff=66.3320% N=1540 Z=-12.2(77.39%) | Like=-0.26..-0.00 [-0.2572..-0.2571]*| it/evals=20544/40668 eff=66.3615% N=1540 Z=-12.2(77.80%) | Like=-0.25..-0.00 [-0.2497..-0.2497]*| it/evals=20576/40668 eff=66.4206% N=1540 Z=-12.2(78.60%) | Like=-0.24..-0.00 [-0.2398..-0.2398]*| it/evals=20640/40668 eff=66.5682% N=1540 Z=-12.2(79.59%) | Like=-0.23..-0.00 [-0.2272..-0.2271]*| it/evals=20722/40668 eff=66.6864% N=1540 Z=-12.2(80.48%) | Like=-0.22..-0.00 [-0.2159..-0.2157]*| it/evals=20800/40668 eff=67.0112% N=1540 Z=-12.2(82.36%) | Like=-0.19..-0.00 [-0.1936..-0.1932]*| it/evals=20973/40668 eff=67.6905% N=1540 Z=-12.2(83.40%) | Like=-0.18..-0.00 [-0.1817..-0.1817]*| it/evals=21076/40796 eff=65.5094% N=1540 Z=-12.2(84.13%) | Like=-0.17..-0.00 [-0.1729..-0.1728]*| it/evals=21152/40796 eff=65.5948% N=1540 Z=-12.1(84.43%) | Like=-0.17..-0.00 [-0.1692..-0.1692]*| it/evals=21184/40796 eff=65.7371% N=1540 Z=-12.1(85.84%) | Like=-0.15..-0.00 [-0.1518..-0.1515]*| it/evals=21342/40796 eff=66.1924% N=1540 Z=-12.1(86.50%) | Like=-0.15..-0.00 [-0.1452..-0.1451]*| it/evals=21421/40796 eff=66.5339% N=1540 Z=-12.1(87.73%) | Like=-0.13..-0.00 [-0.1306..-0.1306]*| it/evals=21579/40796 eff=66.9607% N=1540 Z=-12.1(87.89%) | Like=-0.13..-0.00 [-0.1294..-0.1294]*| it/evals=21600/40796 eff=67.0176% N=1540 Z=-12.1(88.97%) | Like=-0.12..-0.00 [-0.1179..-0.1177]*| it/evals=21753/40924 eff=65.1290% N=1540 Z=-12.1(89.21%) | Like=-0.11..-0.00 [-0.1144..-0.1143]*| it/evals=21789/40924 eff=65.2114% N=1540 Z=-12.1(89.64%) | Like=-0.11..-0.00 [-0.1097..-0.1095]*| it/evals=21856/40924 eff=65.4860% N=1540 Z=-12.1(90.54%) | Like=-0.10..-0.00 [-0.1007..-0.1007]*| it/evals=22003/40924 eff=66.0901% N=1540 Z=-12.1(90.79%) | Like=-0.10..-0.00 [-0.0974..-0.0974]*| it/evals=22048/40924 eff=66.1999% N=1540 Z=-12.1(90.98%) | Like=-0.10..-0.00 [-0.0952..-0.0952]*| it/evals=22080/40924 eff=66.3372% N=1540 Z=-12.1(91.34%) | Like=-0.09..-0.00 [-0.0909..-0.0909]*| it/evals=22148/40924 eff=66.5294% N=1540 Z=-12.1(92.42%) | Like=-0.08..-0.00 [-0.0786..-0.0786]*| it/evals=22360/40924 eff=67.0511% N=1540 Z=-12.1(92.60%) | Like=-0.08..-0.00 [-0.0771..-0.0771]*| it/evals=22400/40924 eff=67.1609% N=1540 Z=-12.1(93.03%) | Like=-0.07..-0.00 [-0.0716..-0.0714]*| it/evals=22495/41052 eff=65.1989% N=1540 Z=-12.0(93.68%) | Like=-0.06..-0.00 [-0.0642..-0.0639]*| it/evals=22652/41052 eff=65.5968% N=1540 Z=-12.0(94.27%) | Like=-0.06..-0.00 [-0.0586..-0.0586]*| it/evals=22807/41052 eff=66.1538% N=1540 Z=-12.0(94.30%) | Like=-0.06..-0.00 [-0.0584..-0.0583]*| it/evals=22816/41052 eff=66.2069% N=1540 Z=-12.0(94.40%) | Like=-0.06..-0.00 [-0.0571..-0.0571]*| it/evals=22844/41052 eff=66.3130% N=1540 Z=-12.0(94.75%) | Like=-0.05..-0.00 [-0.0534..-0.0534]*| it/evals=22944/41052 eff=66.5782% N=1540 Z=-12.0(95.23%) | Like=-0.05..-0.00 [-0.0482..-0.0481]*| it/evals=23097/41180 eff=64.9051% N=1540 Z=-12.0(95.25%) | Like=-0.05..-0.00 [-0.0479..-0.0479]*| it/evals=23104/41180 eff=64.9307% N=1540 Z=-12.0(95.53%) | Like=-0.04..-0.00 [-0.0449..-0.0449]*| it/evals=23198/41180 eff=65.1103% N=1540 Z=-12.0(95.99%) | Like=-0.04..-0.00 [-0.0403..-0.0403]*| it/evals=23371/41180 eff=65.6234% N=1540 Z=-12.0(96.28%) | Like=-0.04..-0.00 [-0.0374..-0.0373]*| it/evals=23488/41180 eff=66.0339% N=1540 Z=-12.0(96.41%) | Like=-0.04..-0.00 [-0.0360..-0.0360]*| it/evals=23545/41180 eff=66.1621% N=1540 Z=-12.0(96.57%) | Like=-0.03..-0.00 [-0.0345..-0.0345]*| it/evals=23616/41180 eff=66.4700% N=1540 Z=-12.0(96.93%) | Like=-0.03..-0.00 [-0.0306..-0.0305]*| it/evals=23787/41308 eff=64.7541% N=1540 Z=-12.0(97.12%) | Like=-0.03..-0.00 [-0.0287..-0.0287]*| it/evals=23889/41308 eff=64.9528% N=1540 Z=-12.0(97.15%) | Like=-0.03..-0.00 [-0.0284..-0.0284]*| it/evals=23904/41308 eff=65.0522% N=1540 Z=-12.0(97.43%) | Like=-0.03..-0.00 [-0.0254..-0.0254]*| it/evals=24069/41308 eff=65.4496% N=1540 Z=-12.0(97.68%) | Like=-0.02..-0.00 [-0.0229..-0.0229]*| it/evals=24223/41308 eff=65.8470% N=1540 Z=-12.0(97.69%) | Like=-0.02..-0.00 [-0.0227..-0.0227]*| it/evals=24234/41308 eff=65.8718% N=1540 Z=-12.0(97.72%) | Like=-0.02..-0.00 [-0.0224..-0.0224]*| it/evals=24256/41308 eff=65.9215% N=1540 Z=-12.0(97.82%) | Like=-0.02..-0.00 [-0.0214..-0.0214]*| it/evals=24320/41308 eff=66.1947% N=1540 Z=-12.0(98.02%) | Like=-0.02..-0.00 [-0.0193..-0.0193]*| it/evals=24474/41436 eff=64.6124% N=1540 Z=-12.0(98.15%) | Like=-0.02..-0.00 [-0.0181..-0.0181]*| it/evals=24581/41436 eff=64.8772% N=1540 Z=-12.0(98.34%) | Like=-0.02..-0.00 [-0.0162..-0.0162]*| it/evals=24746/41436 eff=65.2865% N=1540 Z=-12.0(98.36%) | Like=-0.02..-0.00 [-0.0159..-0.0159]*| it/evals=24768/41436 eff=65.3587% N=1540 Z=-12.0(98.53%) | Like=-0.01..-0.00 [-0.0144..-0.0143]*| it/evals=24931/41436 eff=65.7198% N=1540 Z=-12.0(98.67%) | Like=-0.01..-0.00 [-0.0129..-0.0129]*| it/evals=25090/41436 eff=66.0327% N=1540 Z=-12.0(98.77%) | Like=-0.01..-0.00 [-0.0118..-0.0118]*| it/evals=25216/41564 eff=64.4325% N=1540 Z=-12.0(98.83%) | Like=-0.01..-0.00 [-0.0112..-0.0111]*| it/evals=25290/41564 eff=64.5493% N=1540 Z=-12.0(98.94%) | Like=-0.01..-0.00 [-0.0103..-0.0103]*| it/evals=25440/41564 eff=64.8529% N=1540 Z=-12.0(98.96%) | Like=-0.01..-0.00 [-0.0101..-0.0101]*| it/evals=25472/41564 eff=65.0163% N=1540 Z=-12.0(98.98%) | Like=-0.01..-0.00 [-0.0098..-0.0098]*| it/evals=25504/41564 eff=65.2732% N=1540 [ultranest] Explored until L=-5e-06 [ultranest] Likelihood function evaluations: 41564 logzerr in iteration 3 0.1717176539312442 [ultranest] logZ = -11.97 +- 0.06439 [ultranest] Effective samples strategy satisfied (ESS = 6150.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy wants 384 minimum live points (dlogz from 0.05 to 0.17, need <0.1) [ultranest] logZ error budget: single: 0.16 bs:0.06 tail:0.01 total:0.06 required:<0.10 {'logzerr': 0.1717176539312442, 'logzerr_tail': 0.007007473961262889, 'logzerr_bs': 0.17157461344946334, 'logzerr_single': 0.08443177925682374}
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:2359 To achieve the desired logz accuracy, min_num_live_points was increased to 64 INFO ultranest:integrator.py:1433 Sampling 64 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=10000 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=3, min_num_live_points=64, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=192, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-219160.93, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=6, ncalls=192, regioncalls=128, ndraw=128, logz=-126286.02, remainder_fraction=100.0000%, Lmin=-123905.72, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=12, ncalls=192, regioncalls=128, ndraw=128, logz=-105163.62, remainder_fraction=100.0000%, Lmin=-104323.03, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=15, ncalls=192, regioncalls=128, ndraw=128, logz=-96310.17, remainder_fraction=100.0000%, Lmin=-95825.45, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=18, ncalls=192, regioncalls=128, ndraw=128, logz=-92147.54, remainder_fraction=100.0000%, Lmin=-90911.35, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=24, ncalls=192, regioncalls=128, ndraw=128, logz=-83359.12, remainder_fraction=100.0000%, Lmin=-82523.24, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=192, regioncalls=128, ndraw=128, logz=-77249.29, remainder_fraction=100.0000%, Lmin=-73174.88, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=192, regioncalls=128, ndraw=128, logz=-68821.43, remainder_fraction=100.0000%, Lmin=-66961.75, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=42, ncalls=192, regioncalls=128, ndraw=128, logz=-62913.50, remainder_fraction=100.0000%, Lmin=-62524.24, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=45, ncalls=192, regioncalls=128, ndraw=128, logz=-60415.46, remainder_fraction=100.0000%, Lmin=-60348.58, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=48, ncalls=192, regioncalls=128, ndraw=128, logz=-59089.10, remainder_fraction=100.0000%, Lmin=-56644.03, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=54, ncalls=192, regioncalls=128, ndraw=128, logz=-52753.02, remainder_fraction=100.0000%, Lmin=-51631.51, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=271, regioncalls=256, ndraw=128, logz=-44451.02, remainder_fraction=100.0000%, Lmin=-44202.51, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=66, ncalls=271, regioncalls=256, ndraw=128, logz=-42311.41, remainder_fraction=100.0000%, Lmin=-41912.56, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=72, ncalls=271, regioncalls=256, ndraw=128, logz=-39345.96, remainder_fraction=100.0000%, Lmin=-38622.07, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=75, ncalls=271, regioncalls=256, ndraw=128, logz=-37952.21, remainder_fraction=100.0000%, Lmin=-36783.31, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=78, ncalls=271, regioncalls=256, ndraw=128, logz=-36006.69, remainder_fraction=100.0000%, Lmin=-35497.21, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=84, ncalls=271, regioncalls=256, ndraw=128, logz=-31115.59, remainder_fraction=100.0000%, Lmin=-30731.78, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=271, regioncalls=256, ndraw=128, logz=-28687.96, remainder_fraction=100.0000%, Lmin=-28421.18, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=311, regioncalls=384, ndraw=128, logz=-25187.31, remainder_fraction=100.0000%, Lmin=-24656.65, Lmax=-338.64 DEBUG ultranest:integrator.py:2610 iteration=102, ncalls=346, regioncalls=512, ndraw=128, logz=-22113.68, remainder_fraction=100.0000%, Lmin=-21443.24, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=105, ncalls=346, regioncalls=512, ndraw=128, logz=-19585.34, remainder_fraction=100.0000%, Lmin=-19464.67, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=108, ncalls=346, regioncalls=512, ndraw=128, logz=-18980.38, remainder_fraction=100.0000%, Lmin=-18714.44, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=114, ncalls=365, regioncalls=640, ndraw=128, logz=-17101.81, remainder_fraction=100.0000%, Lmin=-16522.06, Lmax=-298.85 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=365, regioncalls=640, ndraw=128, logz=-14939.80, remainder_fraction=100.0000%, Lmin=-14867.96, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=126, ncalls=384, regioncalls=768, ndraw=128, logz=-13749.80, remainder_fraction=100.0000%, Lmin=-13612.93, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=132, ncalls=384, regioncalls=768, ndraw=128, logz=-12095.75, remainder_fraction=100.0000%, Lmin=-12066.44, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=138, ncalls=399, regioncalls=896, ndraw=128, logz=-11676.84, remainder_fraction=100.0000%, Lmin=-11455.33, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=144, ncalls=399, regioncalls=896, ndraw=128, logz=-9942.74, remainder_fraction=100.0000%, Lmin=-9610.42, Lmax=-49.47 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=410, regioncalls=1024, ndraw=128, logz=-9087.85, remainder_fraction=100.0000%, Lmin=-8762.61, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=156, ncalls=410, regioncalls=1024, ndraw=128, logz=-8235.12, remainder_fraction=100.0000%, Lmin=-8086.11, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=162, ncalls=430, regioncalls=1280, ndraw=128, logz=-7472.39, remainder_fraction=100.0000%, Lmin=-7249.22, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=165, ncalls=430, regioncalls=1280, ndraw=128, logz=-7233.15, remainder_fraction=100.0000%, Lmin=-7189.85, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=168, ncalls=446, regioncalls=1408, ndraw=128, logz=-7139.44, remainder_fraction=100.0000%, Lmin=-6909.47, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=174, ncalls=453, regioncalls=1536, ndraw=128, logz=-6586.35, remainder_fraction=100.0000%, Lmin=-6511.36, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=463, regioncalls=1664, ndraw=128, logz=-6229.86, remainder_fraction=100.0000%, Lmin=-6179.54, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=186, ncalls=470, regioncalls=1792, ndraw=128, logz=-5870.68, remainder_fraction=100.0000%, Lmin=-5704.16, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=484, regioncalls=2048, ndraw=128, logz=-5350.22, remainder_fraction=100.0000%, Lmin=-5299.56, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=195, ncalls=484, regioncalls=2048, ndraw=128, logz=-5230.51, remainder_fraction=100.0000%, Lmin=-5122.84, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=198, ncalls=488, regioncalls=2176, ndraw=128, logz=-5007.77, remainder_fraction=100.0000%, Lmin=-4993.48, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=204, ncalls=494, regioncalls=2304, ndraw=128, logz=-4757.04, remainder_fraction=100.0000%, Lmin=-4671.78, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=507, regioncalls=2560, ndraw=128, logz=-4376.39, remainder_fraction=100.0000%, Lmin=-4050.17, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=216, ncalls=519, regioncalls=2816, ndraw=128, logz=-3611.32, remainder_fraction=100.0000%, Lmin=-3538.07, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=222, ncalls=529, regioncalls=2944, ndraw=128, logz=-3253.14, remainder_fraction=100.0000%, Lmin=-3230.22, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=228, ncalls=534, regioncalls=3072, ndraw=128, logz=-2973.87, remainder_fraction=100.0000%, Lmin=-2936.21, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=234, ncalls=546, regioncalls=3584, ndraw=128, logz=-2717.11, remainder_fraction=100.0000%, Lmin=-2689.65, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=562, regioncalls=4096, ndraw=128, logz=-2482.73, remainder_fraction=100.0000%, Lmin=-2396.74, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=246, ncalls=574, regioncalls=4608, ndraw=128, logz=-2251.88, remainder_fraction=100.0000%, Lmin=-2227.96, Lmax=-47.04 DEBUG ultranest:integrator.py:2610 iteration=252, ncalls=586, regioncalls=5120, ndraw=128, logz=-2050.99, remainder_fraction=100.0000%, Lmin=-2020.88, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=255, ncalls=591, regioncalls=5248, ndraw=128, logz=-1996.88, remainder_fraction=100.0000%, Lmin=-1971.99, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=258, ncalls=595, regioncalls=5376, ndraw=128, logz=-1930.62, remainder_fraction=100.0000%, Lmin=-1893.32, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=264, ncalls=607, regioncalls=5760, ndraw=128, logz=-1661.25, remainder_fraction=100.0000%, Lmin=-1630.36, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=623, regioncalls=6400, ndraw=128, logz=-1531.39, remainder_fraction=100.0000%, Lmin=-1450.33, Lmax=-43.53 DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=640, regioncalls=6784, ndraw=128, logz=-1346.58, remainder_fraction=100.0000%, Lmin=-1304.59, Lmax=-29.10 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=656, regioncalls=6912, ndraw=128, logz=-1210.10, remainder_fraction=100.0000%, Lmin=-1193.96, Lmax=-7.65 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([63, 1])) DEBUG ultranest:integrator.py:2610 iteration=288, ncalls=656, regioncalls=6912, ndraw=128, logz=-1128.82, remainder_fraction=100.0000%, Lmin=-1115.38, Lmax=-7.65 DEBUG ultranest:integrator.py:2610 iteration=294, ncalls=667, regioncalls=7040, ndraw=128, logz=-1037.04, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=681, regioncalls=7168, ndraw=128, logz=-946.58, remainder_fraction=100.0000%, Lmin=-931.46, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=306, ncalls=704, regioncalls=7424, ndraw=128, logz=-860.81, remainder_fraction=100.0000%, Lmin=-851.17, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=312, ncalls=716, regioncalls=7552, ndraw=128, logz=-799.86, remainder_fraction=100.0000%, Lmin=-784.81, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=318, ncalls=728, regioncalls=7680, ndraw=128, logz=-721.99, remainder_fraction=100.0000%, Lmin=-712.81, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=324, ncalls=744, regioncalls=7808, ndraw=128, logz=-711.19, remainder_fraction=100.0000%, Lmin=-681.06, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=773, regioncalls=8064, ndraw=128, logz=-648.60, remainder_fraction=100.0000%, Lmin=-627.61, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=336, ncalls=773, regioncalls=8064, ndraw=128, logz=-579.77, remainder_fraction=100.0000%, Lmin=-544.60, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=342, ncalls=785, regioncalls=8320, ndraw=128, logz=-507.89, remainder_fraction=100.0000%, Lmin=-491.75, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=786, regioncalls=8448, ndraw=128, logz=-448.87, remainder_fraction=100.0000%, Lmin=-436.99, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=348, ncalls=794, regioncalls=8960, ndraw=128, logz=-440.47, remainder_fraction=100.0000%, Lmin=-410.44, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=354, ncalls=814, regioncalls=9216, ndraw=128, logz=-391.49, remainder_fraction=100.0000%, Lmin=-381.77, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=924, regioncalls=9472, ndraw=128, logz=-353.16, remainder_fraction=100.0000%, Lmin=-341.64, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=366, ncalls=924, regioncalls=9472, ndraw=128, logz=-330.60, remainder_fraction=100.0000%, Lmin=-319.63, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=372, ncalls=924, regioncalls=9472, ndraw=128, logz=-319.39, remainder_fraction=100.0000%, Lmin=-308.99, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=378, ncalls=924, regioncalls=9472, ndraw=128, logz=-294.62, remainder_fraction=100.0000%, Lmin=-274.35, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=924, regioncalls=9472, ndraw=128, logz=-256.92, remainder_fraction=100.0000%, Lmin=-243.84, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=924, regioncalls=9472, ndraw=128, logz=-231.44, remainder_fraction=100.0000%, Lmin=-216.70, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=396, ncalls=924, regioncalls=9472, ndraw=128, logz=-208.63, remainder_fraction=100.0000%, Lmin=-197.50, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=402, ncalls=924, regioncalls=9472, ndraw=128, logz=-192.88, remainder_fraction=100.0000%, Lmin=-180.36, Lmax=-6.62 DEBUG ultranest:integrator.py:2610 iteration=405, ncalls=924, regioncalls=9472, ndraw=128, logz=-181.54, remainder_fraction=100.0000%, Lmin=-170.96, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=408, ncalls=1052, regioncalls=9728, ndraw=128, logz=-174.82, remainder_fraction=100.0000%, Lmin=-164.65, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=414, ncalls=1052, regioncalls=9728, ndraw=128, logz=-162.11, remainder_fraction=100.0000%, Lmin=-151.03, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=1052, regioncalls=9728, ndraw=128, logz=-150.81, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=426, ncalls=1052, regioncalls=9728, ndraw=128, logz=-140.27, remainder_fraction=100.0000%, Lmin=-128.55, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=432, ncalls=1052, regioncalls=9728, ndraw=128, logz=-126.93, remainder_fraction=100.0000%, Lmin=-115.71, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=435, ncalls=1052, regioncalls=9728, ndraw=128, logz=-123.34, remainder_fraction=100.0000%, Lmin=-111.94, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=438, ncalls=1052, regioncalls=9728, ndraw=128, logz=-119.55, remainder_fraction=100.0000%, Lmin=-108.01, Lmax=-2.59 DEBUG ultranest:integrator.py:2610 iteration=444, ncalls=1052, regioncalls=9728, ndraw=128, logz=-110.70, remainder_fraction=100.0000%, Lmin=-94.16, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=1052, regioncalls=9728, ndraw=128, logz=-100.78, remainder_fraction=100.0000%, Lmin=-86.81, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=456, ncalls=1052, regioncalls=9728, ndraw=128, logz=-90.78, remainder_fraction=100.0000%, Lmin=-77.75, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=462, ncalls=1074, regioncalls=9984, ndraw=128, logz=-82.64, remainder_fraction=100.0000%, Lmin=-69.50, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=465, ncalls=1074, regioncalls=9984, ndraw=128, logz=-79.02, remainder_fraction=100.0000%, Lmin=-67.39, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=468, ncalls=1074, regioncalls=9984, ndraw=128, logz=-75.79, remainder_fraction=100.0000%, Lmin=-64.18, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=474, ncalls=1202, regioncalls=10368, ndraw=128, logz=-70.13, remainder_fraction=100.0000%, Lmin=-54.53, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1202, regioncalls=10368, ndraw=128, logz=-61.46, remainder_fraction=100.0000%, Lmin=-49.47, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=486, ncalls=1202, regioncalls=10368, ndraw=128, logz=-57.80, remainder_fraction=100.0000%, Lmin=-46.40, Lmax=-1.48 DEBUG ultranest:integrator.py:2610 iteration=492, ncalls=1202, regioncalls=10368, ndraw=128, logz=-54.45, remainder_fraction=100.0000%, Lmin=-43.50, Lmax=-1.39 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=1202, regioncalls=10368, ndraw=128, logz=-48.90, remainder_fraction=100.0000%, Lmin=-37.16, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=504, ncalls=1202, regioncalls=10368, ndraw=128, logz=-45.53, remainder_fraction=100.0000%, Lmin=-33.14, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=1202, regioncalls=10368, ndraw=128, logz=-40.98, remainder_fraction=100.0000%, Lmin=-29.10, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=516, ncalls=1202, regioncalls=10368, ndraw=128, logz=-37.56, remainder_fraction=100.0000%, Lmin=-25.58, Lmax=-0.90 DEBUG ultranest:integrator.py:2610 iteration=522, ncalls=1202, regioncalls=10368, ndraw=128, logz=-33.72, remainder_fraction=100.0000%, Lmin=-22.16, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=525, ncalls=1202, regioncalls=10368, ndraw=128, logz=-32.64, remainder_fraction=100.0000%, Lmin=-21.09, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=528, ncalls=1217, regioncalls=11008, ndraw=128, logz=-31.71, remainder_fraction=100.0000%, Lmin=-20.80, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=1217, regioncalls=11008, ndraw=128, logz=-29.73, remainder_fraction=100.0000%, Lmin=-18.32, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1226, regioncalls=11136, ndraw=128, logz=-28.30, remainder_fraction=100.0000%, Lmin=-17.39, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=1235, regioncalls=11392, ndraw=128, logz=-27.41, remainder_fraction=100.0000%, Lmin=-16.54, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=1249, regioncalls=11520, ndraw=128, logz=-26.61, remainder_fraction=100.0000%, Lmin=-15.76, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=555, ncalls=1249, regioncalls=11520, ndraw=128, logz=-26.03, remainder_fraction=100.0000%, Lmin=-13.59, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=558, ncalls=1264, regioncalls=11904, ndraw=128, logz=-24.91, remainder_fraction=99.9999%, Lmin=-13.52, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=1264, regioncalls=11904, ndraw=128, logz=-23.57, remainder_fraction=99.9995%, Lmin=-12.01, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=1373, regioncalls=12416, ndraw=128, logz=-22.38, remainder_fraction=99.9981%, Lmin=-11.27, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=1373, regioncalls=12416, ndraw=128, logz=-21.67, remainder_fraction=99.9965%, Lmin=-10.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=582, ncalls=1373, regioncalls=12416, ndraw=128, logz=-20.89, remainder_fraction=99.9929%, Lmin=-9.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=585, ncalls=1373, regioncalls=12416, ndraw=128, logz=-20.38, remainder_fraction=99.9876%, Lmin=-8.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=588, ncalls=1373, regioncalls=12416, ndraw=128, logz=-19.82, remainder_fraction=99.9777%, Lmin=-8.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=1373, regioncalls=12416, ndraw=128, logz=-18.90, remainder_fraction=99.9408%, Lmin=-7.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1373, regioncalls=12416, ndraw=128, logz=-18.12, remainder_fraction=99.8597%, Lmin=-6.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=1373, regioncalls=12416, ndraw=128, logz=-17.58, remainder_fraction=99.7583%, Lmin=-6.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=612, ncalls=1373, regioncalls=12416, ndraw=128, logz=-17.16, remainder_fraction=99.6238%, Lmin=-6.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=615, ncalls=1373, regioncalls=12416, ndraw=128, logz=-16.98, remainder_fraction=99.5543%, Lmin=-6.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=1373, regioncalls=12416, ndraw=128, logz=-16.83, remainder_fraction=99.4874%, Lmin=-5.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=1389, regioncalls=12672, ndraw=128, logz=-16.49, remainder_fraction=99.3352%, Lmin=-5.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1401, regioncalls=12800, ndraw=128, logz=-16.17, remainder_fraction=99.0488%, Lmin=-4.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.81, remainder_fraction=98.7259%, Lmin=-4.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.38, remainder_fraction=97.9879%, Lmin=-3.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=1510, regioncalls=13184, ndraw=128, logz=-15.00, remainder_fraction=96.9220%, Lmin=-3.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.68, remainder_fraction=95.8763%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.39, remainder_fraction=94.3145%, Lmin=-3.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=1510, regioncalls=13184, ndraw=128, logz=-14.14, remainder_fraction=92.5810%, Lmin=-2.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.92, remainder_fraction=90.7918%, Lmin=-2.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=675, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.82, remainder_fraction=89.7384%, Lmin=-2.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=678, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.73, remainder_fraction=89.0900%, Lmin=-2.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=1510, regioncalls=13184, ndraw=128, logz=-13.57, remainder_fraction=87.5680%, Lmin=-2.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.41, remainder_fraction=85.2447%, Lmin=-2.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.26, remainder_fraction=83.3174%, Lmin=-1.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=702, ncalls=1605, regioncalls=13440, ndraw=128, logz=-13.11, remainder_fraction=80.6842%, Lmin=-1.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=708, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.98, remainder_fraction=77.7833%, Lmin=-1.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=714, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.87, remainder_fraction=75.3946%, Lmin=-1.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.76, remainder_fraction=72.3463%, Lmin=-1.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=1605, regioncalls=13440, ndraw=128, logz=-12.66, remainder_fraction=69.3637%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.56, remainder_fraction=65.9054%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=735, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.52, remainder_fraction=64.2087%, Lmin=-1.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.48, remainder_fraction=62.4469%, Lmin=-1.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=744, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.39, remainder_fraction=59.0976%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.31, remainder_fraction=55.8394%, Lmin=-0.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.24, remainder_fraction=52.5648%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=762, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.17, remainder_fraction=49.2967%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=765, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.14, remainder_fraction=47.4215%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.11, remainder_fraction=45.8487%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=1733, regioncalls=13696, ndraw=128, logz=-12.06, remainder_fraction=42.6540%, Lmin=-0.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=1750, regioncalls=14336, ndraw=128, logz=-12.01, remainder_fraction=39.5737%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=786, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.96, remainder_fraction=36.9990%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.92, remainder_fraction=34.2785%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=795, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.90, remainder_fraction=33.1147%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=798, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.89, remainder_fraction=31.8738%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=1862, regioncalls=14592, ndraw=128, logz=-11.85, remainder_fraction=29.5577%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1873, regioncalls=14848, ndraw=128, logz=-11.82, remainder_fraction=27.2722%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=816, ncalls=1873, regioncalls=14848, ndraw=128, logz=-11.79, remainder_fraction=25.0354%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=822, ncalls=1892, regioncalls=14976, ndraw=128, logz=-11.77, remainder_fraction=23.0405%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=825, ncalls=1905, regioncalls=15104, ndraw=128, logz=-11.75, remainder_fraction=22.1022%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=1914, regioncalls=15360, ndraw=128, logz=-11.74, remainder_fraction=21.2642%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=834, ncalls=1927, regioncalls=15488, ndraw=128, logz=-11.72, remainder_fraction=19.5390%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1940, regioncalls=15616, ndraw=128, logz=-11.70, remainder_fraction=17.8927%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=846, ncalls=1958, regioncalls=16128, ndraw=128, logz=-11.68, remainder_fraction=16.4115%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=1976, regioncalls=16256, ndraw=128, logz=-11.67, remainder_fraction=15.1147%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=858, ncalls=1976, regioncalls=16256, ndraw=128, logz=-11.65, remainder_fraction=13.8663%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=2001, regioncalls=16512, ndraw=128, logz=-11.64, remainder_fraction=12.7256%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=2001, regioncalls=16512, ndraw=128, logz=-11.63, remainder_fraction=11.6749%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=876, ncalls=2014, regioncalls=16640, ndraw=128, logz=-11.62, remainder_fraction=10.6866%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=2027, regioncalls=16768, ndraw=128, logz=-11.61, remainder_fraction=9.7877%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=885, ncalls=2027, regioncalls=16768, ndraw=128, logz=-11.60, remainder_fraction=9.3465%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=888, ncalls=2040, regioncalls=17152, ndraw=128, logz=-11.60, remainder_fraction=8.9345%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=2050, regioncalls=17280, ndraw=128, logz=-11.59, remainder_fraction=8.1799%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=2063, regioncalls=17408, ndraw=128, logz=-11.58, remainder_fraction=7.4685%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=906, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=6.8186%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=912, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=6.2315%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=915, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.57, remainder_fraction=5.9547%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.56, remainder_fraction=5.6925%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=924, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.56, remainder_fraction=5.1954%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.55, remainder_fraction=4.7380%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=936, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.55, remainder_fraction=4.3215%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.9403%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=945, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.7642%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=2174, regioncalls=17664, ndraw=128, logz=-11.54, remainder_fraction=3.5937%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=954, ncalls=2191, regioncalls=17920, ndraw=128, logz=-11.54, remainder_fraction=3.2766%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=2209, regioncalls=18048, ndraw=128, logz=-11.53, remainder_fraction=2.9865%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.7226%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.4809%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=978, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.53, remainder_fraction=2.2605%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=984, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=2.0604%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.8777%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=996, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.7113%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1002, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.5594%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.4209%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=2333, regioncalls=18304, ndraw=128, logz=-11.52, remainder_fraction=1.2947%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=2429, regioncalls=18560, ndraw=128, logz=-11.52, remainder_fraction=1.1797%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=2429, regioncalls=18560, ndraw=128, logz=-11.51, remainder_fraction=1.0750%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-8e-05 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2429 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.5 +- 0.2693 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -11.13..-0.00 (ESS = 267.4, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.48+-0.26 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 67 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 63 and 63, most (776/777 iterations) have 62 DEBUG ultranest:integrator.py:1663 at least 62 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 62 minimum live points (dlogz from 0.20 to 0.65, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.40 bs:0.27 tail:0.01 total:0.27 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 64 to 128 live points before L=-1e+01... INFO ultranest:integrator.py:1377 Will add 64 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 128.0), (-0.0010811997487929388, 128.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=2433, regioncalls=18688, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=294, ncalls=2433, regioncalls=18688, ndraw=128, logz=-1037.06, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=333, ncalls=2434, regioncalls=18944, ndraw=128, logz=-597.37, remainder_fraction=100.0000%, Lmin=-583.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=381, ncalls=2547, regioncalls=19200, ndraw=128, logz=-284.44, remainder_fraction=100.0000%, Lmin=-265.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=407, ncalls=2547, regioncalls=19200, ndraw=128, logz=-189.66, remainder_fraction=100.0000%, Lmin=-177.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=408, ncalls=2547, regioncalls=19200, ndraw=128, logz=-187.47, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=425, ncalls=2547, regioncalls=19200, ndraw=128, logz=-150.88, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=444, ncalls=2547, regioncalls=19200, ndraw=128, logz=-118.64, remainder_fraction=100.0000%, Lmin=-107.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=2547, regioncalls=19200, ndraw=128, logz=-109.91, remainder_fraction=100.0000%, Lmin=-98.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=456, ncalls=2547, regioncalls=19200, ndraw=128, logz=-102.22, remainder_fraction=100.0000%, Lmin=-91.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=465, ncalls=2547, regioncalls=19200, ndraw=128, logz=-90.95, remainder_fraction=100.0000%, Lmin=-78.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=2669, regioncalls=19456, ndraw=128, logz=-75.95, remainder_fraction=100.0000%, Lmin=-64.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=2669, regioncalls=19456, ndraw=128, logz=-74.17, remainder_fraction=100.0000%, Lmin=-62.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=492, ncalls=2669, regioncalls=19456, ndraw=128, logz=-66.69, remainder_fraction=100.0000%, Lmin=-55.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=502, ncalls=2669, regioncalls=19456, ndraw=128, logz=-60.82, remainder_fraction=100.0000%, Lmin=-49.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=504, ncalls=2669, regioncalls=19456, ndraw=128, logz=-59.92, remainder_fraction=100.0000%, Lmin=-48.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=2669, regioncalls=19456, ndraw=128, logz=-57.17, remainder_fraction=100.0000%, Lmin=-45.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=516, ncalls=2669, regioncalls=19456, ndraw=128, logz=-54.42, remainder_fraction=100.0000%, Lmin=-42.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=521, ncalls=2669, regioncalls=19456, ndraw=128, logz=-51.05, remainder_fraction=100.0000%, Lmin=-38.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=522, ncalls=2669, regioncalls=19456, ndraw=128, logz=-50.16, remainder_fraction=100.0000%, Lmin=-37.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=2669, regioncalls=19456, ndraw=128, logz=-42.42, remainder_fraction=100.0000%, Lmin=-30.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=541, ncalls=2669, regioncalls=19456, ndraw=128, logz=-41.98, remainder_fraction=100.0000%, Lmin=-29.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=2669, regioncalls=19456, ndraw=128, logz=-39.90, remainder_fraction=100.0000%, Lmin=-28.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=2669, regioncalls=19456, ndraw=128, logz=-37.92, remainder_fraction=100.0000%, Lmin=-26.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=558, ncalls=2795, regioncalls=19840, ndraw=128, logz=-36.63, remainder_fraction=100.0000%, Lmin=-24.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=563, ncalls=2795, regioncalls=19840, ndraw=128, logz=-35.35, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=2795, regioncalls=19840, ndraw=128, logz=-35.15, remainder_fraction=100.0000%, Lmin=-23.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=582, ncalls=2795, regioncalls=19840, ndraw=128, logz=-31.58, remainder_fraction=100.0000%, Lmin=-20.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=2795, regioncalls=19840, ndraw=128, logz=-29.59, remainder_fraction=100.0000%, Lmin=-18.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=2795, regioncalls=19840, ndraw=128, logz=-28.89, remainder_fraction=100.0000%, Lmin=-17.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=2795, regioncalls=19840, ndraw=128, logz=-27.92, remainder_fraction=100.0000%, Lmin=-16.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=2795, regioncalls=19840, ndraw=128, logz=-27.11, remainder_fraction=100.0000%, Lmin=-15.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=2923, regioncalls=20096, ndraw=128, logz=-26.54, remainder_fraction=100.0000%, Lmin=-15.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=2923, regioncalls=20096, ndraw=128, logz=-25.80, remainder_fraction=99.9999%, Lmin=-13.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=637, ncalls=2923, regioncalls=20096, ndraw=128, logz=-24.70, remainder_fraction=99.9998%, Lmin=-12.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=2923, regioncalls=20096, ndraw=128, logz=-24.03, remainder_fraction=99.9996%, Lmin=-12.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=2923, regioncalls=20096, ndraw=128, logz=-23.40, remainder_fraction=99.9993%, Lmin=-11.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=2923, regioncalls=20096, ndraw=128, logz=-22.78, remainder_fraction=99.9987%, Lmin=-11.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=2923, regioncalls=20096, ndraw=128, logz=-21.93, remainder_fraction=99.9972%, Lmin=-10.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=2923, regioncalls=20096, ndraw=128, logz=-21.43, remainder_fraction=99.9955%, Lmin=-9.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=2923, regioncalls=20096, ndraw=128, logz=-20.29, remainder_fraction=99.9855%, Lmin=-8.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=2923, regioncalls=20096, ndraw=128, logz=-19.79, remainder_fraction=99.9762%, Lmin=-8.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=2923, regioncalls=20096, ndraw=128, logz=-19.33, remainder_fraction=99.9610%, Lmin=-7.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=2923, regioncalls=20096, ndraw=128, logz=-17.89, remainder_fraction=99.8279%, Lmin=-6.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=725, ncalls=2923, regioncalls=20096, ndraw=128, logz=-17.67, remainder_fraction=99.7839%, Lmin=-6.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=2935, regioncalls=20352, ndraw=128, logz=-17.38, remainder_fraction=99.7043%, Lmin=-6.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=744, ncalls=2945, regioncalls=20480, ndraw=128, logz=-16.99, remainder_fraction=99.5964%, Lmin=-5.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=755, ncalls=2945, regioncalls=20480, ndraw=128, logz=-16.65, remainder_fraction=99.4267%, Lmin=-5.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=3060, regioncalls=20736, ndraw=128, logz=-16.01, remainder_fraction=98.9550%, Lmin=-4.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.78, remainder_fraction=98.6883%, Lmin=-4.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=784, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.63, remainder_fraction=98.4813%, Lmin=-3.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=3060, regioncalls=20736, ndraw=128, logz=-15.33, remainder_fraction=97.9290%, Lmin=-3.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.94, remainder_fraction=96.8743%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.77, remainder_fraction=96.2143%, Lmin=-3.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=813, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.69, remainder_fraction=95.9153%, Lmin=-3.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=843, ncalls=3060, regioncalls=20736, ndraw=128, logz=-14.00, remainder_fraction=91.9626%, Lmin=-2.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.84, remainder_fraction=90.7842%, Lmin=-2.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.63, remainder_fraction=88.4445%, Lmin=-2.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=872, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.50, remainder_fraction=86.8348%, Lmin=-2.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=876, ncalls=3060, regioncalls=20736, ndraw=128, logz=-13.45, remainder_fraction=85.9885%, Lmin=-1.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.36, remainder_fraction=84.8095%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=888, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.28, remainder_fraction=83.2903%, Lmin=-1.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.14, remainder_fraction=80.5574%, Lmin=-1.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=901, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.13, remainder_fraction=80.2663%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=912, ncalls=3169, regioncalls=20992, ndraw=128, logz=-13.00, remainder_fraction=77.5329%, Lmin=-1.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.94, remainder_fraction=76.2756%, Lmin=-1.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=932, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.81, remainder_fraction=72.6547%, Lmin=-1.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=936, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.78, remainder_fraction=71.4900%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.72, remainder_fraction=69.8277%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=962, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.56, remainder_fraction=64.3652%, Lmin=-1.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.53, remainder_fraction=63.1678%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=3169, regioncalls=20992, ndraw=128, logz=-12.49, remainder_fraction=61.5615%, Lmin=-0.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.36, remainder_fraction=56.5519%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=991, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.35, remainder_fraction=56.2055%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1002, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.28, remainder_fraction=53.0360%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.25, remainder_fraction=51.3933%, Lmin=-0.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.15, remainder_fraction=46.2975%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1032, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.13, remainder_fraction=44.6211%, Lmin=-0.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.05, remainder_fraction=40.0149%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1062, ncalls=3291, regioncalls=21248, ndraw=128, logz=-12.00, remainder_fraction=37.2727%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=3291, regioncalls=21248, ndraw=128, logz=-11.98, remainder_fraction=35.8703%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1074, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.96, remainder_fraction=34.5188%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1084, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.93, remainder_fraction=32.4748%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1086, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.92, remainder_fraction=32.0399%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1092, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.90, remainder_fraction=30.8065%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.86, remainder_fraction=27.3363%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1122, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.83, remainder_fraction=25.2494%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=3419, regioncalls=21504, ndraw=128, logz=-11.79, remainder_fraction=22.0287%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1172, ncalls=3438, regioncalls=21888, ndraw=128, logz=-11.73, remainder_fraction=17.8873%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.73, remainder_fraction=17.3835%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1188, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.71, remainder_fraction=15.9739%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.70, remainder_fraction=14.6487%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1201, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.69, remainder_fraction=14.5499%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1206, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.69, remainder_fraction=14.0427%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1212, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.68, remainder_fraction=13.4495%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1231, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.66, remainder_fraction=11.7219%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1236, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.66, remainder_fraction=11.2963%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.65, remainder_fraction=10.8058%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1254, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.64, remainder_fraction=9.8969%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.64, remainder_fraction=9.4586%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1278, ncalls=3563, regioncalls=22272, ndraw=128, logz=-11.62, remainder_fraction=8.2689%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1302, ncalls=3576, regioncalls=22656, ndraw=128, logz=-11.61, remainder_fraction=6.9033%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1332, ncalls=3622, regioncalls=23040, ndraw=128, logz=-11.59, remainder_fraction=5.4995%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=3634, regioncalls=23168, ndraw=128, logz=-11.59, remainder_fraction=5.0179%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1347, ncalls=3634, regioncalls=23168, ndraw=128, logz=-11.59, remainder_fraction=4.9040%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.59, remainder_fraction=4.7925%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1362, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=4.3724%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=3.9261%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.58, remainder_fraction=3.8070%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1404, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.57, remainder_fraction=3.1659%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1405, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.57, remainder_fraction=3.1418%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1422, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.7558%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1436, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.4740%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1452, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.1859%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1458, ncalls=3750, regioncalls=23424, ndraw=128, logz=-11.56, remainder_fraction=2.0868%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1476, ncalls=3767, regioncalls=23808, ndraw=128, logz=-11.55, remainder_fraction=1.8154%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1482, ncalls=3767, regioncalls=23808, ndraw=128, logz=-11.55, remainder_fraction=1.7332%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=3786, regioncalls=23936, ndraw=128, logz=-11.55, remainder_fraction=1.5793%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=3801, regioncalls=24064, ndraw=128, logz=-11.55, remainder_fraction=1.5079%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1506, ncalls=3816, regioncalls=24192, ndraw=128, logz=-11.55, remainder_fraction=1.4394%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1524, ncalls=3832, regioncalls=24320, ndraw=128, logz=-11.55, remainder_fraction=1.2519%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1526, ncalls=3832, regioncalls=24320, ndraw=128, logz=-11.55, remainder_fraction=1.2326%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=1.1948%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1542, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=1.0886%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1554, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9918%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9466%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1566, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.9034%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1572, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.55, remainder_fraction=0.8622%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1578, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.8229%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1584, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7853%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7495%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1596, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.7153%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1602, ncalls=3958, regioncalls=24576, ndraw=128, logz=-11.54, remainder_fraction=0.6827%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1608, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6515%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1613, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6266%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.6217%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5933%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5663%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1632, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5404%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1638, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.5157%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1644, ncalls=4069, regioncalls=24704, ndraw=128, logz=-11.54, remainder_fraction=0.4921%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=4082, regioncalls=25088, ndraw=128, logz=-11.54, remainder_fraction=0.4696%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=4082, regioncalls=25088, ndraw=128, logz=-11.54, remainder_fraction=0.4482%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1662, ncalls=4108, regioncalls=25344, ndraw=128, logz=-11.54, remainder_fraction=0.4277%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1668, ncalls=4108, regioncalls=25344, ndraw=128, logz=-11.54, remainder_fraction=0.4082%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1674, ncalls=4125, regioncalls=25472, ndraw=128, logz=-11.54, remainder_fraction=0.3895%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=4125, regioncalls=25472, ndraw=128, logz=-11.54, remainder_fraction=0.3717%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1686, ncalls=4135, regioncalls=25600, ndraw=128, logz=-11.54, remainder_fraction=0.3547%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1692, ncalls=4146, regioncalls=25728, ndraw=128, logz=-11.54, remainder_fraction=0.3385%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1698, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3230%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3180%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1704, ncalls=4166, regioncalls=25984, ndraw=128, logz=-11.54, remainder_fraction=0.3082%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2941%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2807%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1722, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2679%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2556%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1729, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2536%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1734, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2439%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1740, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2328%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2221%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1752, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2119%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1758, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.2022%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1764, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.1930%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=4284, regioncalls=26240, ndraw=128, logz=-11.54, remainder_fraction=0.1842%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1776, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1757%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1677%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1600%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1794, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1527%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1457%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1806, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1390%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1812, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1327%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1816, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1286%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1818, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1266%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=4394, regioncalls=26496, ndraw=128, logz=-11.54, remainder_fraction=0.1208%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 4505 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.56 +- 0.3516 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -10.40..-0.00 (ESS = 519.9, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.17 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 89 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 31 and 127, most (304/962 iterations) have 126 DEBUG ultranest:integrator.py:1663 at least 31 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 31 minimum live points (dlogz from 0.29 to 0.78, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.29 bs:0.35 tail:0.00 total:0.35 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 67 to 256 live points before L=-1e+01... INFO ultranest:integrator.py:1377 Will add 189 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 256.0), (-0.0010811997487929388, 256.0), (-0.001004869805783571, 256.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=4506, regioncalls=27008, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=4509, regioncalls=27264, ndraw=128, logz=-1037.08, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=328, ncalls=4512, regioncalls=27520, ndraw=128, logz=-682.35, remainder_fraction=100.0000%, Lmin=-672.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=395, ncalls=4611, regioncalls=27776, ndraw=128, logz=-237.95, remainder_fraction=100.0000%, Lmin=-222.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=413, ncalls=4611, regioncalls=27776, ndraw=128, logz=-187.53, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=4611, regioncalls=27776, ndraw=128, logz=-150.94, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=4611, regioncalls=27776, ndraw=128, logz=-119.70, remainder_fraction=100.0000%, Lmin=-108.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=4611, regioncalls=27776, ndraw=128, logz=-118.36, remainder_fraction=100.0000%, Lmin=-107.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=4611, regioncalls=27776, ndraw=128, logz=-81.57, remainder_fraction=100.0000%, Lmin=-69.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=501, ncalls=4611, regioncalls=27776, ndraw=128, logz=-66.24, remainder_fraction=100.0000%, Lmin=-55.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=4739, regioncalls=28032, ndraw=128, logz=-51.86, remainder_fraction=100.0000%, Lmin=-40.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=4739, regioncalls=28032, ndraw=128, logz=-49.97, remainder_fraction=100.0000%, Lmin=-37.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=4739, regioncalls=28032, ndraw=128, logz=-43.13, remainder_fraction=100.0000%, Lmin=-31.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=555, ncalls=4739, regioncalls=28032, ndraw=128, logz=-42.04, remainder_fraction=100.0000%, Lmin=-30.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=564, ncalls=4739, regioncalls=28032, ndraw=128, logz=-39.46, remainder_fraction=100.0000%, Lmin=-27.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=4739, regioncalls=28032, ndraw=128, logz=-36.75, remainder_fraction=100.0000%, Lmin=-25.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=583, ncalls=4739, regioncalls=28032, ndraw=128, logz=-35.38, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=624, ncalls=4855, regioncalls=28288, ndraw=128, logz=-28.98, remainder_fraction=100.0000%, Lmin=-17.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=4855, regioncalls=28288, ndraw=128, logz=-28.39, remainder_fraction=100.0000%, Lmin=-17.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=4855, regioncalls=28288, ndraw=128, logz=-27.90, remainder_fraction=100.0000%, Lmin=-16.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=4855, regioncalls=28288, ndraw=128, logz=-27.40, remainder_fraction=100.0000%, Lmin=-16.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.90, remainder_fraction=100.0000%, Lmin=-15.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=653, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.49, remainder_fraction=100.0000%, Lmin=-15.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=4855, regioncalls=28288, ndraw=128, logz=-26.42, remainder_fraction=100.0000%, Lmin=-15.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=4855, regioncalls=28288, ndraw=128, logz=-25.35, remainder_fraction=99.9999%, Lmin=-13.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=678, ncalls=4855, regioncalls=28288, ndraw=128, logz=-24.18, remainder_fraction=99.9997%, Lmin=-12.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=4855, regioncalls=28288, ndraw=128, logz=-23.23, remainder_fraction=99.9992%, Lmin=-11.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=702, ncalls=4855, regioncalls=28288, ndraw=128, logz=-22.44, remainder_fraction=99.9983%, Lmin=-11.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=708, ncalls=4855, regioncalls=28288, ndraw=128, logz=-22.13, remainder_fraction=99.9979%, Lmin=-10.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=4983, regioncalls=28544, ndraw=128, logz=-21.52, remainder_fraction=99.9965%, Lmin=-10.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=4983, regioncalls=28544, ndraw=128, logz=-21.19, remainder_fraction=99.9950%, Lmin=-9.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=4983, regioncalls=28544, ndraw=128, logz=-20.91, remainder_fraction=99.9933%, Lmin=-9.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=4983, regioncalls=28544, ndraw=128, logz=-20.61, remainder_fraction=99.9915%, Lmin=-9.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=4983, regioncalls=28544, ndraw=128, logz=-19.57, remainder_fraction=99.9752%, Lmin=-8.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=4983, regioncalls=28544, ndraw=128, logz=-19.00, remainder_fraction=99.9539%, Lmin=-7.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.74, remainder_fraction=99.9394%, Lmin=-7.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=775, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.70, remainder_fraction=99.9364%, Lmin=-7.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=786, ncalls=4983, regioncalls=28544, ndraw=128, logz=-18.27, remainder_fraction=99.9021%, Lmin=-6.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=4983, regioncalls=28544, ndraw=128, logz=-17.64, remainder_fraction=99.8105%, Lmin=-6.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=4983, regioncalls=28544, ndraw=128, logz=-17.18, remainder_fraction=99.7066%, Lmin=-6.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=4983, regioncalls=28544, ndraw=128, logz=-16.72, remainder_fraction=99.5474%, Lmin=-5.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=867, ncalls=4983, regioncalls=28544, ndraw=128, logz=-16.05, remainder_fraction=99.1215%, Lmin=-4.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=913, ncalls=5013, regioncalls=29696, ndraw=128, logz=-14.91, remainder_fraction=97.2821%, Lmin=-3.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=5029, regioncalls=30080, ndraw=128, logz=-14.38, remainder_fraction=95.3083%, Lmin=-2.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=5029, regioncalls=30080, ndraw=128, logz=-14.28, remainder_fraction=94.8380%, Lmin=-2.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=963, ncalls=5150, regioncalls=30336, ndraw=128, logz=-14.05, remainder_fraction=93.5025%, Lmin=-2.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=972, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.93, remainder_fraction=92.5870%, Lmin=-2.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1009, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.47, remainder_fraction=88.2266%, Lmin=-2.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.41, remainder_fraction=87.5361%, Lmin=-2.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1026, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.29, remainder_fraction=85.8432%, Lmin=-2.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1038, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.18, remainder_fraction=84.2791%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1054, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.04, remainder_fraction=81.8261%, Lmin=-1.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=5150, regioncalls=30336, ndraw=128, logz=-13.03, remainder_fraction=81.5433%, Lmin=-1.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1062, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.98, remainder_fraction=80.6121%, Lmin=-1.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1086, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.80, remainder_fraction=76.6455%, Lmin=-1.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1098, ncalls=5150, regioncalls=30336, ndraw=128, logz=-12.72, remainder_fraction=74.6206%, Lmin=-1.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1122, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.57, remainder_fraction=70.2203%, Lmin=-1.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.46, remainder_fraction=66.4358%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1146, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.44, remainder_fraction=65.6969%, Lmin=-1.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1164, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.35, remainder_fraction=62.3245%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.29, remainder_fraction=60.1290%, Lmin=-0.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1187, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.24, remainder_fraction=58.2223%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.21, remainder_fraction=56.9507%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1206, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.16, remainder_fraction=54.6266%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1212, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.13, remainder_fraction=53.4593%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=5261, regioncalls=30592, ndraw=128, logz=-12.06, remainder_fraction=50.1470%, Lmin=-0.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=5370, regioncalls=30848, ndraw=128, logz=-12.00, remainder_fraction=46.7688%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1254, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.98, remainder_fraction=45.7204%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.96, remainder_fraction=44.6320%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1277, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.91, remainder_fraction=41.6147%, Lmin=-0.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.88, remainder_fraction=39.4202%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1321, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.80, remainder_fraction=34.7283%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.75, remainder_fraction=31.4702%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1362, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.72, remainder_fraction=29.1227%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1368, ncalls=5370, regioncalls=30848, ndraw=128, logz=-11.71, remainder_fraction=28.3381%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=5406, regioncalls=31488, ndraw=128, logz=-11.61, remainder_fraction=21.0434%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=5406, regioncalls=31488, ndraw=128, logz=-11.60, remainder_fraction=20.4862%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1457, ncalls=5416, regioncalls=31616, ndraw=128, logz=-11.58, remainder_fraction=18.9227%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1464, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.57, remainder_fraction=18.2990%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1476, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.56, remainder_fraction=17.2881%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.55, remainder_fraction=15.8845%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1501, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.54, remainder_fraction=15.3600%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.52, remainder_fraction=13.3208%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.51, remainder_fraction=12.9431%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1544, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.51, remainder_fraction=12.4551%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1548, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.50, remainder_fraction=12.2101%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.49, remainder_fraction=11.5199%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1572, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.49, remainder_fraction=10.8593%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.46, remainder_fraction=8.8170%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=5544, regioncalls=32000, ndraw=128, logz=-11.46, remainder_fraction=8.3070%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1631, ncalls=5554, regioncalls=32256, ndraw=128, logz=-11.46, remainder_fraction=8.0995%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.45, remainder_fraction=7.1425%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1662, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.44, remainder_fraction=6.9287%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.44, remainder_fraction=6.3244%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1692, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.9508%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.2679%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1718, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.43, remainder_fraction=5.2140%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1740, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.42, remainder_fraction=4.6584%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1762, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=4.1613%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.9946%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.7549%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.6402%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1794, ncalls=5663, regioncalls=32512, ndraw=128, logz=-11.41, remainder_fraction=3.5303%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1812, ncalls=5675, regioncalls=32768, ndraw=128, logz=-11.40, remainder_fraction=3.2177%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=5689, regioncalls=32896, ndraw=128, logz=-11.40, remainder_fraction=3.0243%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1830, ncalls=5689, regioncalls=32896, ndraw=128, logz=-11.40, remainder_fraction=2.9321%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1855, ncalls=5703, regioncalls=33024, ndraw=128, logz=-11.40, remainder_fraction=2.5769%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1878, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.40, remainder_fraction=2.2880%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1884, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=2.2179%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1899, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=2.0519%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1942, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.6417%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1962, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.4800%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.39, remainder_fraction=1.3478%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1992, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.2663%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.1177%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2031, ncalls=5820, regioncalls=33280, ndraw=128, logz=-11.38, remainder_fraction=1.0338%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=5832, regioncalls=33664, ndraw=128, logz=-11.38, remainder_fraction=0.9865%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2052, ncalls=5832, regioncalls=33664, ndraw=128, logz=-11.38, remainder_fraction=0.9266%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2058, ncalls=5845, regioncalls=33792, ndraw=128, logz=-11.38, remainder_fraction=0.8981%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2064, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8705%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8437%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2078, ncalls=5858, regioncalls=33920, ndraw=128, logz=-11.38, remainder_fraction=0.8092%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.7214%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2122, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.6432%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2136, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.5979%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2154, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.5443%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2196, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.4371%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2216, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3937%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3737%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2232, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3622%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2260, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3129%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2262, ncalls=5973, regioncalls=34304, ndraw=128, logz=-11.38, remainder_fraction=0.3096%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2268, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.38, remainder_fraction=0.3001%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.38, remainder_fraction=0.2818%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2292, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.2647%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2303, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.2499%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2346, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1995%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2382, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1653%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2388, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1602%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2412, ncalls=6096, regioncalls=34560, ndraw=128, logz=-11.37, remainder_fraction=0.1413%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1327%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1286%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2452, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1146%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2454, ncalls=6111, regioncalls=34816, ndraw=128, logz=-11.37, remainder_fraction=0.1134%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2460, ncalls=6234, regioncalls=35072, ndraw=128, logz=-11.37, remainder_fraction=0.1099%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 6234 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -11.38 +- 0.3175 INFO ultranest:integrator.py:1582 Effective samples strategy wants to improve: -8.83..-0.00 (ESS = 776.0, need >10000) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.16 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 104 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 21 and 190, most (637/1347 iterations) have 189 DEBUG ultranest:integrator.py:1663 at least 20 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 20 minimum live points (dlogz from 0.24 to 0.82, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.23 bs:0.32 tail:0.00 total:0.32 required:<0.50 INFO ultranest:integrator.py:2733 Widening from 72 to 382 live points before L=-9... INFO ultranest:integrator.py:1377 Will add 310 live points (x1) at L=-1e+03 ... INFO ultranest:integrator.py:2454 Exploring (in particular: L=-1213.22..-0.00) ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 64.0), (-1213.2189925079801, 382.0), (-0.0010811997487929388, 382.0), (-0.001004869805783571, 382.0), (inf, 64.0)] DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=6361, regioncalls=35456, ndraw=128, logz=-1264.38, remainder_fraction=100.0000%, Lmin=-1213.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=6361, regioncalls=35456, ndraw=138, logz=-1037.10, remainder_fraction=100.0000%, Lmin=-1001.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=395, ncalls=6361, regioncalls=35456, ndraw=140, logz=-237.94, remainder_fraction=100.0000%, Lmin=-222.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=413, ncalls=6361, regioncalls=35456, ndraw=140, logz=-187.52, remainder_fraction=100.0000%, Lmin=-171.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=6361, regioncalls=35456, ndraw=138, logz=-150.93, remainder_fraction=100.0000%, Lmin=-136.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=6372, regioncalls=35864, ndraw=136, logz=-122.55, remainder_fraction=100.0000%, Lmin=-110.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=462, ncalls=6372, regioncalls=35864, ndraw=134, logz=-107.59, remainder_fraction=100.0000%, Lmin=-94.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=6503, regioncalls=36126, ndraw=131, logz=-82.94, remainder_fraction=100.0000%, Lmin=-70.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=6503, regioncalls=36126, ndraw=128, logz=-74.24, remainder_fraction=100.0000%, Lmin=-62.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=508, ncalls=6503, regioncalls=36126, ndraw=128, logz=-66.86, remainder_fraction=100.0000%, Lmin=-55.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=528, ncalls=6503, regioncalls=36126, ndraw=128, logz=-58.10, remainder_fraction=100.0000%, Lmin=-46.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=534, ncalls=6503, regioncalls=36126, ndraw=128, logz=-56.27, remainder_fraction=100.0000%, Lmin=-44.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=546, ncalls=6503, regioncalls=36126, ndraw=128, logz=-50.43, remainder_fraction=100.0000%, Lmin=-38.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=563, ncalls=6503, regioncalls=36126, ndraw=128, logz=-45.44, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=6503, regioncalls=36126, ndraw=128, logz=-41.88, remainder_fraction=100.0000%, Lmin=-30.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=594, ncalls=6503, regioncalls=36126, ndraw=128, logz=-38.49, remainder_fraction=100.0000%, Lmin=-26.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=6503, regioncalls=36126, ndraw=128, logz=-37.46, remainder_fraction=100.0000%, Lmin=-26.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=6503, regioncalls=36126, ndraw=128, logz=-36.31, remainder_fraction=100.0000%, Lmin=-24.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=612, ncalls=6503, regioncalls=36126, ndraw=128, logz=-35.38, remainder_fraction=100.0000%, Lmin=-23.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=6519, regioncalls=36510, ndraw=128, logz=-32.03, remainder_fraction=100.0000%, Lmin=-20.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=638, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.84, remainder_fraction=100.0000%, Lmin=-20.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.53, remainder_fraction=100.0000%, Lmin=-20.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=648, ncalls=6646, regioncalls=36894, ndraw=128, logz=-31.00, remainder_fraction=100.0000%, Lmin=-19.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=654, ncalls=6646, regioncalls=36894, ndraw=128, logz=-30.41, remainder_fraction=100.0000%, Lmin=-19.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=6646, regioncalls=36894, ndraw=128, logz=-29.25, remainder_fraction=100.0000%, Lmin=-18.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=6646, regioncalls=36894, ndraw=128, logz=-28.75, remainder_fraction=100.0000%, Lmin=-17.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=679, ncalls=6646, regioncalls=36894, ndraw=128, logz=-28.25, remainder_fraction=100.0000%, Lmin=-17.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=684, ncalls=6646, regioncalls=36894, ndraw=128, logz=-27.96, remainder_fraction=100.0000%, Lmin=-16.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=6646, regioncalls=36894, ndraw=128, logz=-27.25, remainder_fraction=100.0000%, Lmin=-16.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=732, ncalls=6646, regioncalls=36894, ndraw=128, logz=-25.07, remainder_fraction=99.9999%, Lmin=-13.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=738, ncalls=6646, regioncalls=36894, ndraw=128, logz=-24.72, remainder_fraction=99.9998%, Lmin=-13.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6646, regioncalls=36894, ndraw=128, logz=-23.95, remainder_fraction=99.9996%, Lmin=-12.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=6646, regioncalls=36894, ndraw=128, logz=-23.61, remainder_fraction=99.9995%, Lmin=-12.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=6646, regioncalls=36894, ndraw=128, logz=-22.98, remainder_fraction=99.9990%, Lmin=-11.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=774, ncalls=6646, regioncalls=36894, ndraw=128, logz=-22.68, remainder_fraction=99.9988%, Lmin=-11.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=776, ncalls=6657, regioncalls=37150, ndraw=128, logz=-22.59, remainder_fraction=99.9987%, Lmin=-11.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=792, ncalls=6666, regioncalls=37278, ndraw=128, logz=-21.98, remainder_fraction=99.9976%, Lmin=-10.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=804, ncalls=6674, regioncalls=37406, ndraw=128, logz=-21.53, remainder_fraction=99.9963%, Lmin=-10.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=822, ncalls=6683, regioncalls=37534, ndraw=128, logz=-20.89, remainder_fraction=99.9928%, Lmin=-9.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=6683, regioncalls=37534, ndraw=128, logz=-20.68, remainder_fraction=99.9912%, Lmin=-9.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=835, ncalls=6695, regioncalls=37662, ndraw=128, logz=-20.40, remainder_fraction=99.9887%, Lmin=-8.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=852, ncalls=6695, regioncalls=37662, ndraw=128, logz=-19.75, remainder_fraction=99.9780%, Lmin=-8.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=6706, regioncalls=37918, ndraw=128, logz=-19.34, remainder_fraction=99.9658%, Lmin=-7.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=882, ncalls=6706, regioncalls=37918, ndraw=128, logz=-18.77, remainder_fraction=99.9369%, Lmin=-7.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=6718, regioncalls=38046, ndraw=128, logz=-18.44, remainder_fraction=99.9116%, Lmin=-7.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=896, ncalls=6718, regioncalls=38046, ndraw=128, logz=-18.38, remainder_fraction=99.9065%, Lmin=-7.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=918, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.82, remainder_fraction=99.8296%, Lmin=-6.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.55, remainder_fraction=99.7768%, Lmin=-6.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=956, ncalls=6839, regioncalls=38302, ndraw=128, logz=-17.07, remainder_fraction=99.6489%, Lmin=-5.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.91, remainder_fraction=99.5984%, Lmin=-5.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.53, remainder_fraction=99.4020%, Lmin=-5.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=996, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.43, remainder_fraction=99.3359%, Lmin=-5.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1008, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.21, remainder_fraction=99.2037%, Lmin=-4.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.11, remainder_fraction=99.1287%, Lmin=-4.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1016, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.07, remainder_fraction=99.1029%, Lmin=-4.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=6839, regioncalls=38302, ndraw=128, logz=-16.00, remainder_fraction=99.0398%, Lmin=-4.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1038, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.69, remainder_fraction=98.6639%, Lmin=-4.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.49, remainder_fraction=98.3777%, Lmin=-3.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.39, remainder_fraction=98.2236%, Lmin=-3.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1076, ncalls=6839, regioncalls=38302, ndraw=128, logz=-15.09, remainder_fraction=97.6003%, Lmin=-3.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1098, ncalls=6839, regioncalls=38302, ndraw=128, logz=-14.79, remainder_fraction=96.7437%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=6839, regioncalls=38302, ndraw=128, logz=-14.64, remainder_fraction=96.1617%, Lmin=-3.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1134, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.35, remainder_fraction=94.8765%, Lmin=-2.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1139, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.29, remainder_fraction=94.5864%, Lmin=-2.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1158, ncalls=6953, regioncalls=38686, ndraw=128, logz=-14.09, remainder_fraction=93.3880%, Lmin=-2.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1201, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.68, remainder_fraction=90.1803%, Lmin=-2.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.35, remainder_fraction=86.2793%, Lmin=-1.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1266, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.19, remainder_fraction=83.6994%, Lmin=-1.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1284, ncalls=6953, regioncalls=38686, ndraw=128, logz=-13.08, remainder_fraction=81.8688%, Lmin=-1.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1308, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.94, remainder_fraction=79.1812%, Lmin=-1.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1314, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.91, remainder_fraction=78.4698%, Lmin=-1.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=6953, regioncalls=38686, ndraw=128, logz=-12.76, remainder_fraction=74.5431%, Lmin=-1.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1368, ncalls=6959, regioncalls=39070, ndraw=128, logz=-12.64, remainder_fraction=71.3420%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1396, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.52, remainder_fraction=67.5284%, Lmin=-1.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1404, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.49, remainder_fraction=66.3431%, Lmin=-1.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.46, remainder_fraction=65.5363%, Lmin=-1.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1416, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.44, remainder_fraction=64.6824%, Lmin=-1.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.37, remainder_fraction=62.2065%, Lmin=-0.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1458, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.29, remainder_fraction=59.1336%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1482, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.21, remainder_fraction=55.7232%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.10, remainder_fraction=50.6385%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1524, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.09, remainder_fraction=49.8769%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.06, remainder_fraction=48.2513%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1542, ncalls=7064, regioncalls=39326, ndraw=128, logz=-12.04, remainder_fraction=47.4784%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=7064, regioncalls=39326, ndraw=128, logz=-11.93, remainder_fraction=41.2959%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1608, ncalls=7064, regioncalls=39326, ndraw=128, logz=-11.90, remainder_fraction=39.1822%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.89, remainder_fraction=38.4617%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.84, remainder_fraction=35.6138%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1716, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.73, remainder_fraction=27.9367%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1722, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.72, remainder_fraction=27.3930%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.71, remainder_fraction=26.8532%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.69, remainder_fraction=25.3058%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1758, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.68, remainder_fraction=24.3436%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1761, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.68, remainder_fraction=24.0906%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1764, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.67, remainder_fraction=23.8601%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1770, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.67, remainder_fraction=23.4015%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1782, ncalls=7177, regioncalls=39582, ndraw=128, logz=-11.65, remainder_fraction=22.5009%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.62, remainder_fraction=19.5045%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1842, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.60, remainder_fraction=18.3242%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1860, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.59, remainder_fraction=17.2409%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1881, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.57, remainder_fraction=16.0354%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1896, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=15.2150%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1902, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=14.8963%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1908, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.56, remainder_fraction=14.5770%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.55, remainder_fraction=13.9809%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1945, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.54, remainder_fraction=12.8134%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1956, ncalls=7289, regioncalls=39838, ndraw=128, logz=-11.53, remainder_fraction=12.3213%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1992, ncalls=7299, regioncalls=40094, ndraw=128, logz=-11.51, remainder_fraction=10.8408%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1998, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.6135%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2004, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.3875%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2008, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.51, remainder_fraction=10.2385%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=7314, regioncalls=40222, ndraw=128, logz=-11.49, remainder_fraction=9.1279%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2068, ncalls=7331, regioncalls=40606, ndraw=128, logz=-11.49, remainder_fraction=8.2488%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=7331, regioncalls=40606, ndraw=128, logz=-11.48, remainder_fraction=8.1912%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2076, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.48, remainder_fraction=8.0155%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2106, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.47, remainder_fraction=7.1843%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2124, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.47, remainder_fraction=6.7270%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2154, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.46, remainder_fraction=6.0304%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2191, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=5.2636%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2220, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=4.7287%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.45, remainder_fraction=4.6249%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2252, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.44, remainder_fraction=4.1999%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2256, ncalls=7459, regioncalls=40862, ndraw=128, logz=-11.44, remainder_fraction=4.1379%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2262, ncalls=7471, regioncalls=41246, ndraw=128, logz=-11.44, remainder_fraction=4.0465%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2310, ncalls=7471, regioncalls=41246, ndraw=128, logz=-11.43, remainder_fraction=3.3857%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2328, ncalls=7484, regioncalls=41374, ndraw=128, logz=-11.43, remainder_fraction=3.1667%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2379, ncalls=7503, regioncalls=41630, ndraw=128, logz=-11.43, remainder_fraction=2.6188%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2394, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.4757%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.4208%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2406, ncalls=7515, regioncalls=41886, ndraw=128, logz=-11.42, remainder_fraction=2.3674%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2418, ncalls=7519, regioncalls=42014, ndraw=128, logz=-11.42, remainder_fraction=2.2637%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=7525, regioncalls=42142, ndraw=128, logz=-11.42, remainder_fraction=2.2136%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=7534, regioncalls=42270, ndraw=128, logz=-11.42, remainder_fraction=2.1647%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2442, ncalls=7534, regioncalls=42270, ndraw=128, logz=-11.42, remainder_fraction=2.0696%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2460, ncalls=7551, regioncalls=42526, ndraw=128, logz=-11.42, remainder_fraction=1.9351%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2472, ncalls=7551, regioncalls=42526, ndraw=128, logz=-11.42, remainder_fraction=1.8500%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2514, ncalls=7565, regioncalls=42654, ndraw=128, logz=-11.42, remainder_fraction=1.5810%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2526, ncalls=7573, regioncalls=42782, ndraw=128, logz=-11.41, remainder_fraction=1.5116%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2538, ncalls=7573, regioncalls=42782, ndraw=128, logz=-11.41, remainder_fraction=1.4451%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2544, ncalls=7585, regioncalls=42910, ndraw=128, logz=-11.41, remainder_fraction=1.4130%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2575, ncalls=7600, regioncalls=43038, ndraw=128, logz=-11.41, remainder_fraction=1.2579%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2586, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=1.2070%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2628, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=1.0309%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9854%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2652, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9420%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2664, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.9004%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2670, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.8803%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.8227%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2697, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7953%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2706, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7689%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2712, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7517%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2724, ncalls=7707, regioncalls=43294, ndraw=128, logz=-11.41, remainder_fraction=0.7186%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.5734%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2836, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4714%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2856, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4372%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2868, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.4179%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2886, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3905%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3705%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2904, ncalls=7815, regioncalls=43550, ndraw=128, logz=-11.40, remainder_fraction=0.3649%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2940, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.3186%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2958, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2977%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2955%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2846%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2994, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2600%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3020, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2357%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3024, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2322%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3030, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2270%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3036, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.2219%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3082, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1866%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3084, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1852%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3096, ncalls=7915, regioncalls=43806, ndraw=128, logz=-11.40, remainder_fraction=0.1770%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3102, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1730%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3114, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1654%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3132, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1545%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3142, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1488%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3144, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1477%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3156, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1411%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3162, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1380%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3186, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1260%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3192, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1232%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3203, ncalls=8043, regioncalls=44062, ndraw=128, logz=-11.40, remainder_fraction=0.1182%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 8043 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. INFO ultranest:integrator.py:2359 To achieve the desired logz accuracy, min_num_live_points was increased to 317 INFO ultranest:integrator.py:1393 Widening roots to 317 live points (have 64 already) ... INFO ultranest:integrator.py:1433 Sampling 253 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=10, min_num_live_points=317, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 317.0), (inf, 317.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=8424, regioncalls=44190, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-241488.71, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=8424, regioncalls=44190, ndraw=128, logz=-162015.11, remainder_fraction=100.0000%, Lmin=-161448.65, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=8424, regioncalls=44190, ndraw=128, logz=-131996.59, remainder_fraction=100.0000%, Lmin=-131605.67, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=71, ncalls=8424, regioncalls=44190, ndraw=128, logz=-128725.16, remainder_fraction=100.0000%, Lmin=-128075.71, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=8424, regioncalls=44190, ndraw=128, logz=-116039.81, remainder_fraction=100.0000%, Lmin=-114669.88, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=142, ncalls=8532, regioncalls=44318, ndraw=128, logz=-99426.57, remainder_fraction=100.0000%, Lmin=-98932.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=8532, regioncalls=44318, ndraw=128, logz=-94469.85, remainder_fraction=100.0000%, Lmin=-94083.98, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=8532, regioncalls=44318, ndraw=128, logz=-87325.59, remainder_fraction=100.0000%, Lmin=-86803.89, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=213, ncalls=8532, regioncalls=44318, ndraw=128, logz=-82682.38, remainder_fraction=100.0000%, Lmin=-82549.78, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=224, ncalls=8618, regioncalls=44446, ndraw=128, logz=-80003.59, remainder_fraction=100.0000%, Lmin=-79785.50, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=256, ncalls=8618, regioncalls=44446, ndraw=128, logz=-70498.54, remainder_fraction=100.0000%, Lmin=-70003.16, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=284, ncalls=8618, regioncalls=44446, ndraw=128, logz=-64668.85, remainder_fraction=100.0000%, Lmin=-64418.55, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=288, ncalls=8690, regioncalls=44574, ndraw=128, logz=-63638.76, remainder_fraction=100.0000%, Lmin=-63331.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=8690, regioncalls=44574, ndraw=128, logz=-58374.89, remainder_fraction=100.0000%, Lmin=-58204.04, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=8751, regioncalls=44702, ndraw=128, logz=-53117.67, remainder_fraction=100.0000%, Lmin=-53020.86, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=356, ncalls=8751, regioncalls=44702, ndraw=128, logz=-52754.91, remainder_fraction=100.0000%, Lmin=-52549.25, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=8795, regioncalls=44830, ndraw=128, logz=-46729.14, remainder_fraction=100.0000%, Lmin=-46556.06, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=416, ncalls=8795, regioncalls=44830, ndraw=128, logz=-41641.47, remainder_fraction=100.0000%, Lmin=-41619.23, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=427, ncalls=8847, regioncalls=44958, ndraw=128, logz=-40285.78, remainder_fraction=100.0000%, Lmin=-40055.45, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=8888, regioncalls=45086, ndraw=128, logz=-33470.46, remainder_fraction=100.0000%, Lmin=-33458.45, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=8888, regioncalls=45086, ndraw=128, logz=-31546.84, remainder_fraction=100.0000%, Lmin=-31396.11, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=8959, regioncalls=45342, ndraw=128, logz=-27877.51, remainder_fraction=100.0000%, Lmin=-27864.29, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=569, ncalls=8997, regioncalls=45470, ndraw=128, logz=-25189.21, remainder_fraction=100.0000%, Lmin=-25077.39, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=608, ncalls=9022, regioncalls=45598, ndraw=128, logz=-22115.61, remainder_fraction=100.0000%, Lmin=-22086.43, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=641, ncalls=9077, regioncalls=45854, ndraw=128, logz=-20053.07, remainder_fraction=100.0000%, Lmin=-20041.42, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=9117, regioncalls=46110, ndraw=128, logz=-18174.90, remainder_fraction=100.0000%, Lmin=-18074.66, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=9134, regioncalls=46238, ndraw=128, logz=-16363.81, remainder_fraction=100.0000%, Lmin=-16329.53, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=9161, regioncalls=46366, ndraw=128, logz=-15518.76, remainder_fraction=100.0000%, Lmin=-15470.57, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=736, ncalls=9170, regioncalls=46494, ndraw=128, logz=-14427.59, remainder_fraction=100.0000%, Lmin=-14415.73, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=9213, regioncalls=46878, ndraw=128, logz=-12734.27, remainder_fraction=100.0000%, Lmin=-12708.83, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=784, ncalls=9229, regioncalls=47006, ndraw=128, logz=-12142.61, remainder_fraction=100.0000%, Lmin=-12106.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=9277, regioncalls=47646, ndraw=128, logz=-10709.40, remainder_fraction=100.0000%, Lmin=-10695.44, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=855, ncalls=9313, regioncalls=48030, ndraw=128, logz=-9925.89, remainder_fraction=100.0000%, Lmin=-9864.47, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=926, ncalls=9382, regioncalls=48926, ndraw=128, logz=-7688.58, remainder_fraction=100.0000%, Lmin=-7673.33, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=9388, regioncalls=49054, ndraw=128, logz=-7668.77, remainder_fraction=100.0000%, Lmin=-7628.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=9419, regioncalls=49822, ndraw=128, logz=-7017.74, remainder_fraction=100.0000%, Lmin=-6989.00, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=9448, regioncalls=50334, ndraw=128, logz=-6547.73, remainder_fraction=100.0000%, Lmin=-6517.63, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=997, ncalls=9452, regioncalls=50462, ndraw=128, logz=-6493.60, remainder_fraction=100.0000%, Lmin=-6475.15, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=9527, regioncalls=51742, ndraw=128, logz=-5491.72, remainder_fraction=100.0000%, Lmin=-5474.86, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=9541, regioncalls=52126, ndraw=128, logz=-5276.69, remainder_fraction=100.0000%, Lmin=-5247.51, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=9551, regioncalls=52382, ndraw=128, logz=-5002.67, remainder_fraction=100.0000%, Lmin=-4977.41, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=9589, regioncalls=53278, ndraw=128, logz=-4662.24, remainder_fraction=100.0000%, Lmin=-4631.19, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1139, ncalls=9614, regioncalls=53662, ndraw=128, logz=-4455.00, remainder_fraction=100.0000%, Lmin=-4442.88, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=9630, regioncalls=54174, ndraw=128, logz=-4252.66, remainder_fraction=100.0000%, Lmin=-4222.67, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=9667, regioncalls=55198, ndraw=128, logz=-3824.87, remainder_fraction=100.0000%, Lmin=-3815.29, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=9705, regioncalls=56478, ndraw=128, logz=-3493.08, remainder_fraction=100.0000%, Lmin=-3476.58, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=9714, regioncalls=56734, ndraw=128, logz=-3443.49, remainder_fraction=100.0000%, Lmin=-3429.82, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=9747, regioncalls=57758, ndraw=128, logz=-3058.70, remainder_fraction=100.0000%, Lmin=-3048.73, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=9785, regioncalls=59166, ndraw=128, logz=-2808.99, remainder_fraction=100.0000%, Lmin=-2784.85, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1281, ncalls=9785, regioncalls=59166, ndraw=128, logz=-2794.65, remainder_fraction=100.0000%, Lmin=-2783.83, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1312, ncalls=9816, regioncalls=60446, ndraw=128, logz=-2506.47, remainder_fraction=100.0000%, Lmin=-2479.05, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1344, ncalls=9850, regioncalls=62110, ndraw=128, logz=-2237.57, remainder_fraction=100.0000%, Lmin=-2220.11, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1352, ncalls=9860, regioncalls=62750, ndraw=128, logz=-2146.63, remainder_fraction=100.0000%, Lmin=-2126.85, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=9995, regioncalls=63262, ndraw=128, logz=-2008.67, remainder_fraction=100.0000%, Lmin=-1994.21, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1423, ncalls=9995, regioncalls=63262, ndraw=128, logz=-1742.50, remainder_fraction=100.0000%, Lmin=-1725.08, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=9995, regioncalls=63262, ndraw=128, logz=-1655.08, remainder_fraction=100.0000%, Lmin=-1637.97, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1484.09, remainder_fraction=100.0000%, Lmin=-1470.82, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1400.33, remainder_fraction=100.0000%, Lmin=-1388.39, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1504, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1345.46, remainder_fraction=100.0000%, Lmin=-1329.96, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1202.13, remainder_fraction=100.0000%, Lmin=-1190.79, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=10127, regioncalls=63774, ndraw=128, logz=-1105.47, remainder_fraction=100.0000%, Lmin=-1094.12, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=10271, regioncalls=65694, ndraw=128, logz=-1002.65, remainder_fraction=100.0000%, Lmin=-991.38, Lmax=-3.82 DEBUG ultranest:integrator.py:2610 iteration=1632, ncalls=10271, regioncalls=65694, ndraw=128, logz=-912.72, remainder_fraction=100.0000%, Lmin=-897.72, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1671, ncalls=10271, regioncalls=65694, ndraw=128, logz=-807.73, remainder_fraction=100.0000%, Lmin=-795.37, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1696, ncalls=10399, regioncalls=65950, ndraw=128, logz=-749.54, remainder_fraction=100.0000%, Lmin=-730.32, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=10399, regioncalls=65950, ndraw=128, logz=-697.79, remainder_fraction=100.0000%, Lmin=-683.69, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1742, ncalls=10399, regioncalls=65950, ndraw=128, logz=-673.31, remainder_fraction=100.0000%, Lmin=-661.52, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=10399, regioncalls=65950, ndraw=128, logz=-627.00, remainder_fraction=100.0000%, Lmin=-609.67, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1792, ncalls=10399, regioncalls=65950, ndraw=128, logz=-581.50, remainder_fraction=100.0000%, Lmin=-564.18, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1813, ncalls=10527, regioncalls=66206, ndraw=128, logz=-540.40, remainder_fraction=100.0000%, Lmin=-527.04, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1824, ncalls=10527, regioncalls=66206, ndraw=128, logz=-517.13, remainder_fraction=100.0000%, Lmin=-505.17, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1856, ncalls=10527, regioncalls=66206, ndraw=128, logz=-465.68, remainder_fraction=100.0000%, Lmin=-452.56, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1884, ncalls=10529, regioncalls=66334, ndraw=128, logz=-427.82, remainder_fraction=100.0000%, Lmin=-414.10, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=10532, regioncalls=66718, ndraw=128, logz=-414.81, remainder_fraction=100.0000%, Lmin=-401.25, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=10663, regioncalls=67614, ndraw=128, logz=-381.28, remainder_fraction=100.0000%, Lmin=-368.88, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1955, ncalls=10663, regioncalls=67614, ndraw=128, logz=-348.65, remainder_fraction=100.0000%, Lmin=-336.76, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=1984, ncalls=10663, regioncalls=67614, ndraw=128, logz=-318.88, remainder_fraction=100.0000%, Lmin=-306.73, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=10791, regioncalls=67998, ndraw=128, logz=-288.88, remainder_fraction=100.0000%, Lmin=-277.25, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2026, ncalls=10791, regioncalls=67998, ndraw=128, logz=-277.58, remainder_fraction=100.0000%, Lmin=-264.93, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2048, ncalls=10791, regioncalls=67998, ndraw=128, logz=-261.11, remainder_fraction=100.0000%, Lmin=-248.44, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=10791, regioncalls=67998, ndraw=128, logz=-230.34, remainder_fraction=100.0000%, Lmin=-217.48, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2112, ncalls=10919, regioncalls=68510, ndraw=128, logz=-204.99, remainder_fraction=100.0000%, Lmin=-193.36, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2155, ncalls=10919, regioncalls=68510, ndraw=128, logz=-181.19, remainder_fraction=100.0000%, Lmin=-169.41, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2176, ncalls=10919, regioncalls=68510, ndraw=128, logz=-167.36, remainder_fraction=100.0000%, Lmin=-155.64, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2224, ncalls=11047, regioncalls=68766, ndraw=128, logz=-146.53, remainder_fraction=100.0000%, Lmin=-134.15, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=11047, regioncalls=68766, ndraw=128, logz=-142.00, remainder_fraction=100.0000%, Lmin=-129.80, Lmax=-1.26 DEBUG ultranest:integrator.py:2610 iteration=2270, ncalls=11047, regioncalls=68766, ndraw=128, logz=-127.80, remainder_fraction=100.0000%, Lmin=-115.79, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=11047, regioncalls=68766, ndraw=128, logz=-127.19, remainder_fraction=100.0000%, Lmin=-115.56, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2286, ncalls=11047, regioncalls=68766, ndraw=128, logz=-122.30, remainder_fraction=100.0000%, Lmin=-110.14, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2306, ncalls=11047, regioncalls=68766, ndraw=128, logz=-117.68, remainder_fraction=100.0000%, Lmin=-105.62, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2324, ncalls=11047, regioncalls=68766, ndraw=128, logz=-110.32, remainder_fraction=100.0000%, Lmin=-97.73, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2336, ncalls=11047, regioncalls=68766, ndraw=128, logz=-105.22, remainder_fraction=100.0000%, Lmin=-93.15, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2345, ncalls=11047, regioncalls=68766, ndraw=128, logz=-101.69, remainder_fraction=100.0000%, Lmin=-89.63, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2368, ncalls=11175, regioncalls=69022, ndraw=128, logz=-93.56, remainder_fraction=100.0000%, Lmin=-81.94, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=11175, regioncalls=69022, ndraw=128, logz=-84.98, remainder_fraction=100.0000%, Lmin=-72.89, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2416, ncalls=11175, regioncalls=69022, ndraw=128, logz=-81.78, remainder_fraction=100.0000%, Lmin=-70.23, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2424, ncalls=11175, regioncalls=69022, ndraw=128, logz=-80.30, remainder_fraction=100.0000%, Lmin=-68.43, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2436, ncalls=11175, regioncalls=69022, ndraw=128, logz=-78.17, remainder_fraction=100.0000%, Lmin=-66.18, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2451, ncalls=11175, regioncalls=69022, ndraw=128, logz=-75.34, remainder_fraction=100.0000%, Lmin=-63.38, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2458, ncalls=11175, regioncalls=69022, ndraw=128, logz=-73.35, remainder_fraction=100.0000%, Lmin=-61.04, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=11175, regioncalls=69022, ndraw=128, logz=-72.13, remainder_fraction=100.0000%, Lmin=-60.41, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2498, ncalls=11303, regioncalls=69278, ndraw=128, logz=-66.69, remainder_fraction=100.0000%, Lmin=-54.78, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2515, ncalls=11303, regioncalls=69278, ndraw=128, logz=-62.46, remainder_fraction=100.0000%, Lmin=-50.15, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2525, ncalls=11303, regioncalls=69278, ndraw=128, logz=-60.51, remainder_fraction=100.0000%, Lmin=-48.80, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2528, ncalls=11303, regioncalls=69278, ndraw=128, logz=-60.12, remainder_fraction=100.0000%, Lmin=-48.34, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2553, ncalls=11303, regioncalls=69278, ndraw=128, logz=-56.54, remainder_fraction=100.0000%, Lmin=-44.54, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2609, ncalls=11303, regioncalls=69278, ndraw=128, logz=-47.08, remainder_fraction=100.0000%, Lmin=-35.03, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2626, ncalls=11303, regioncalls=69278, ndraw=128, logz=-45.29, remainder_fraction=100.0000%, Lmin=-33.25, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2643, ncalls=11303, regioncalls=69278, ndraw=128, logz=-43.23, remainder_fraction=100.0000%, Lmin=-30.78, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2655, ncalls=11303, regioncalls=69278, ndraw=128, logz=-41.63, remainder_fraction=100.0000%, Lmin=-29.57, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2656, ncalls=11303, regioncalls=69278, ndraw=128, logz=-41.51, remainder_fraction=100.0000%, Lmin=-29.50, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=11431, regioncalls=69662, ndraw=128, logz=-38.38, remainder_fraction=100.0000%, Lmin=-26.58, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2704, ncalls=11431, regioncalls=69662, ndraw=128, logz=-37.05, remainder_fraction=100.0000%, Lmin=-25.20, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2725, ncalls=11431, regioncalls=69662, ndraw=128, logz=-35.33, remainder_fraction=100.0000%, Lmin=-23.47, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2734, ncalls=11431, regioncalls=69662, ndraw=128, logz=-34.44, remainder_fraction=100.0000%, Lmin=-22.42, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2749, ncalls=11431, regioncalls=69662, ndraw=128, logz=-33.33, remainder_fraction=100.0000%, Lmin=-21.69, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2752, ncalls=11431, regioncalls=69662, ndraw=128, logz=-33.16, remainder_fraction=100.0000%, Lmin=-21.59, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2776, ncalls=11431, regioncalls=69662, ndraw=128, logz=-31.77, remainder_fraction=100.0000%, Lmin=-20.13, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=11431, regioncalls=69662, ndraw=128, logz=-31.32, remainder_fraction=100.0000%, Lmin=-19.57, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2814, ncalls=11431, regioncalls=69662, ndraw=128, logz=-29.62, remainder_fraction=100.0000%, Lmin=-17.93, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=11431, regioncalls=69662, ndraw=128, logz=-29.52, remainder_fraction=100.0000%, Lmin=-17.84, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2919, ncalls=11431, regioncalls=69662, ndraw=128, logz=-25.44, remainder_fraction=99.9999%, Lmin=-13.64, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=2935, ncalls=11431, regioncalls=69662, ndraw=128, logz=-24.86, remainder_fraction=99.9998%, Lmin=-13.20, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3143, ncalls=11431, regioncalls=69662, ndraw=128, logz=-18.76, remainder_fraction=99.9040%, Lmin=-6.95, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3217, ncalls=11431, regioncalls=69662, ndraw=128, logz=-17.43, remainder_fraction=99.6278%, Lmin=-5.92, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=11559, regioncalls=70046, ndraw=128, logz=-17.23, remainder_fraction=99.5565%, Lmin=-5.61, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3292, ncalls=11559, regioncalls=70046, ndraw=128, logz=-16.35, remainder_fraction=98.9485%, Lmin=-4.48, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3363, ncalls=11559, regioncalls=70046, ndraw=128, logz=-15.37, remainder_fraction=97.2338%, Lmin=-3.48, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=11559, regioncalls=70046, ndraw=128, logz=-15.05, remainder_fraction=96.0776%, Lmin=-3.14, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3453, ncalls=11559, regioncalls=70046, ndraw=128, logz=-14.46, remainder_fraction=92.9309%, Lmin=-2.61, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3488, ncalls=11559, regioncalls=70046, ndraw=128, logz=-14.18, remainder_fraction=90.7736%, Lmin=-2.31, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=11559, regioncalls=70046, ndraw=128, logz=-13.95, remainder_fraction=88.1955%, Lmin=-2.11, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3525, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.91, remainder_fraction=87.7358%, Lmin=-2.10, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.75, remainder_fraction=85.5337%, Lmin=-2.00, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3584, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.58, remainder_fraction=82.7298%, Lmin=-1.81, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.50, remainder_fraction=81.4265%, Lmin=-1.76, Lmax=-0.15 DEBUG ultranest:integrator.py:2610 iteration=3672, ncalls=11687, regioncalls=70430, ndraw=128, logz=-13.18, remainder_fraction=74.2901%, Lmin=-1.42, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3745, ncalls=11687, regioncalls=70430, ndraw=128, logz=-12.92, remainder_fraction=66.0021%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3825, ncalls=11687, regioncalls=70430, ndraw=128, logz=-12.67, remainder_fraction=56.9671%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.63, remainder_fraction=55.2492%, Lmin=-0.75, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3872, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.56, remainder_fraction=51.5108%, Lmin=-0.68, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3898, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.50, remainder_fraction=48.5045%, Lmin=-0.62, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=3971, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.36, remainder_fraction=40.7717%, Lmin=-0.49, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.27, remainder_fraction=35.0644%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=4047, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.25, remainder_fraction=33.6862%, Lmin=-0.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=4119, ncalls=11815, regioncalls=70814, ndraw=128, logz=-12.16, remainder_fraction=27.8867%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4190, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.09, remainder_fraction=22.9791%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4224, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.07, remainder_fraction=20.9237%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4271, ncalls=11943, regioncalls=71070, ndraw=128, logz=-12.03, remainder_fraction=18.2849%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4351, ncalls=11943, regioncalls=71070, ndraw=128, logz=-11.99, remainder_fraction=14.5101%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4437, ncalls=11943, regioncalls=71070, ndraw=128, logz=-11.95, remainder_fraction=11.2584%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.93, remainder_fraction=9.0028%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4585, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.91, remainder_fraction=7.2134%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4659, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.89, remainder_fraction=5.7531%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4732, ncalls=12071, regioncalls=71326, ndraw=128, logz=-11.88, remainder_fraction=4.5945%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4814, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.87, remainder_fraction=3.5639%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4864, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.86, remainder_fraction=3.0504%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4886, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.86, remainder_fraction=2.8487%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4965, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=2.2266%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5041, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.7558%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5088, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.5156%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5118, ncalls=12199, regioncalls=71838, ndraw=128, logz=-11.85, remainder_fraction=1.3796%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5193, ncalls=12327, regioncalls=72094, ndraw=128, logz=-11.84, remainder_fraction=1.0903%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 12327 INFO ultranest:integrator.py:2697 logZ = -11.91 +- 0.1636 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1275.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.33 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 781 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (4156/4672 iterations) have 315 DEBUG ultranest:integrator.py:1663 at least 684 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 684 minimum live points (dlogz from 0.14 to 0.39, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.20 bs:0.16 tail:0.00 total:0.16 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 684 live points (have 317 already) ... INFO ultranest:integrator.py:1433 Sampling 367 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 684.0), (inf, 684.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=12822, regioncalls=72222, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-245997.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=12822, regioncalls=72222, ndraw=128, logz=-187609.44, remainder_fraction=100.0000%, Lmin=-186405.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=12822, regioncalls=72222, ndraw=128, logz=-161455.27, remainder_fraction=100.0000%, Lmin=-161381.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=153, ncalls=12822, regioncalls=72222, ndraw=128, logz=-126861.12, remainder_fraction=100.0000%, Lmin=-126691.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=12822, regioncalls=72222, ndraw=128, logz=-124993.76, remainder_fraction=100.0000%, Lmin=-124623.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=12822, regioncalls=72222, ndraw=128, logz=-117214.00, remainder_fraction=100.0000%, Lmin=-116938.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=306, ncalls=12936, regioncalls=72350, ndraw=128, logz=-97355.70, remainder_fraction=100.0000%, Lmin=-97219.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=12936, regioncalls=72350, ndraw=128, logz=-95807.34, remainder_fraction=100.0000%, Lmin=-95734.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=12936, regioncalls=72350, ndraw=128, logz=-91971.18, remainder_fraction=100.0000%, Lmin=-91886.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=448, ncalls=13021, regioncalls=72478, ndraw=128, logz=-82305.88, remainder_fraction=100.0000%, Lmin=-82247.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=459, ncalls=13021, regioncalls=72478, ndraw=128, logz=-81427.25, remainder_fraction=100.0000%, Lmin=-81363.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=613, ncalls=13109, regioncalls=72606, ndraw=128, logz=-64179.31, remainder_fraction=100.0000%, Lmin=-64076.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=13167, regioncalls=72734, ndraw=128, logz=-62083.49, remainder_fraction=100.0000%, Lmin=-62055.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=13167, regioncalls=72734, ndraw=128, logz=-55598.35, remainder_fraction=100.0000%, Lmin=-55501.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=736, ncalls=13227, regioncalls=72862, ndraw=128, logz=-53118.40, remainder_fraction=100.0000%, Lmin=-53083.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=766, ncalls=13227, regioncalls=72862, ndraw=128, logz=-51060.51, remainder_fraction=100.0000%, Lmin=-50944.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=768, ncalls=13227, regioncalls=72862, ndraw=128, logz=-50898.46, remainder_fraction=100.0000%, Lmin=-50831.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=13279, regioncalls=72990, ndraw=128, logz=-46496.86, remainder_fraction=100.0000%, Lmin=-46183.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=13362, regioncalls=73246, ndraw=128, logz=-40286.55, remainder_fraction=100.0000%, Lmin=-40211.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=13362, regioncalls=73246, ndraw=128, logz=-39698.95, remainder_fraction=100.0000%, Lmin=-39683.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=13401, regioncalls=73374, ndraw=128, logz=-36752.96, remainder_fraction=100.0000%, Lmin=-36476.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=13440, regioncalls=73502, ndraw=128, logz=-32856.27, remainder_fraction=100.0000%, Lmin=-32828.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1073, ncalls=13481, regioncalls=73630, ndraw=128, logz=-32044.04, remainder_fraction=100.0000%, Lmin=-32010.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=13481, regioncalls=73630, ndraw=128, logz=-31324.08, remainder_fraction=100.0000%, Lmin=-31219.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=13510, regioncalls=73758, ndraw=128, logz=-28767.77, remainder_fraction=100.0000%, Lmin=-28745.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=13538, regioncalls=73886, ndraw=128, logz=-27662.85, remainder_fraction=100.0000%, Lmin=-27410.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=13571, regioncalls=74014, ndraw=128, logz=-26376.74, remainder_fraction=100.0000%, Lmin=-26340.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1226, ncalls=13571, regioncalls=74014, ndraw=128, logz=-25891.91, remainder_fraction=100.0000%, Lmin=-25883.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=13599, regioncalls=74142, ndraw=128, logz=-23501.00, remainder_fraction=100.0000%, Lmin=-23478.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1376, ncalls=13676, regioncalls=74526, ndraw=128, logz=-20787.70, remainder_fraction=100.0000%, Lmin=-20770.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1379, ncalls=13676, regioncalls=74526, ndraw=128, logz=-20721.92, remainder_fraction=100.0000%, Lmin=-20701.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=13748, regioncalls=75038, ndraw=128, logz=-17968.42, remainder_fraction=100.0000%, Lmin=-17940.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1504, ncalls=13774, regioncalls=75166, ndraw=128, logz=-17203.78, remainder_fraction=100.0000%, Lmin=-17165.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1532, ncalls=13787, regioncalls=75294, ndraw=128, logz=-16506.90, remainder_fraction=100.0000%, Lmin=-16495.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=13801, regioncalls=75422, ndraw=128, logz=-16431.14, remainder_fraction=100.0000%, Lmin=-16396.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=13824, regioncalls=75678, ndraw=128, logz=-15454.63, remainder_fraction=100.0000%, Lmin=-15437.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=13839, regioncalls=75806, ndraw=128, logz=-14760.11, remainder_fraction=100.0000%, Lmin=-14716.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1664, ncalls=13896, regioncalls=76318, ndraw=128, logz=-13227.51, remainder_fraction=100.0000%, Lmin=-13205.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1685, ncalls=13913, regioncalls=76446, ndraw=128, logz=-12861.14, remainder_fraction=100.0000%, Lmin=-12832.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1696, ncalls=13921, regioncalls=76574, ndraw=128, logz=-12709.17, remainder_fraction=100.0000%, Lmin=-12690.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=13946, regioncalls=76830, ndraw=128, logz=-12143.44, remainder_fraction=100.0000%, Lmin=-12109.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1792, ncalls=13986, regioncalls=77214, ndraw=128, logz=-11044.06, remainder_fraction=100.0000%, Lmin=-11032.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1838, ncalls=14017, regioncalls=77598, ndraw=128, logz=-10425.17, remainder_fraction=100.0000%, Lmin=-10391.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=14056, regioncalls=78110, ndraw=128, logz=-9665.21, remainder_fraction=100.0000%, Lmin=-9652.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=14074, regioncalls=78366, ndraw=128, logz=-9171.28, remainder_fraction=100.0000%, Lmin=-9130.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1984, ncalls=14128, regioncalls=79006, ndraw=128, logz=-8182.76, remainder_fraction=100.0000%, Lmin=-8144.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1991, ncalls=14128, regioncalls=79006, ndraw=128, logz=-8087.38, remainder_fraction=100.0000%, Lmin=-8076.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2016, ncalls=14143, regioncalls=79262, ndraw=128, logz=-7663.77, remainder_fraction=100.0000%, Lmin=-7631.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=14182, regioncalls=79902, ndraw=128, logz=-7040.15, remainder_fraction=100.0000%, Lmin=-7029.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2112, ncalls=14197, regioncalls=80158, ndraw=128, logz=-6723.57, remainder_fraction=100.0000%, Lmin=-6709.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2145, ncalls=14227, regioncalls=80670, ndraw=128, logz=-6516.93, remainder_fraction=100.0000%, Lmin=-6501.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=14299, regioncalls=82206, ndraw=128, logz=-5352.92, remainder_fraction=100.0000%, Lmin=-5336.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2298, ncalls=14310, regioncalls=82334, ndraw=128, logz=-5178.13, remainder_fraction=100.0000%, Lmin=-5164.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2436, ncalls=14398, regioncalls=84510, ndraw=128, logz=-4253.36, remainder_fraction=100.0000%, Lmin=-4241.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2451, ncalls=14407, regioncalls=84766, ndraw=128, logz=-4182.70, remainder_fraction=100.0000%, Lmin=-4170.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=14416, regioncalls=85022, ndraw=128, logz=-4081.69, remainder_fraction=100.0000%, Lmin=-4069.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2528, ncalls=14459, regioncalls=86174, ndraw=128, logz=-3733.52, remainder_fraction=100.0000%, Lmin=-3721.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=14483, regioncalls=87198, ndraw=128, logz=-3555.56, remainder_fraction=100.0000%, Lmin=-3543.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2592, ncalls=14504, regioncalls=88094, ndraw=128, logz=-3408.79, remainder_fraction=100.0000%, Lmin=-3397.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2605, ncalls=14516, regioncalls=88350, ndraw=128, logz=-3362.34, remainder_fraction=100.0000%, Lmin=-3351.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2624, ncalls=14527, regioncalls=88990, ndraw=128, logz=-3255.79, remainder_fraction=100.0000%, Lmin=-3242.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2656, ncalls=14546, regioncalls=89630, ndraw=128, logz=-3054.50, remainder_fraction=100.0000%, Lmin=-3036.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=14577, regioncalls=91166, ndraw=128, logz=-2945.71, remainder_fraction=100.0000%, Lmin=-2931.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2758, ncalls=14631, regioncalls=93086, ndraw=128, logz=-2673.88, remainder_fraction=100.0000%, Lmin=-2660.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=14652, regioncalls=94110, ndraw=128, logz=-2578.97, remainder_fraction=100.0000%, Lmin=-2561.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=14675, regioncalls=95134, ndraw=128, logz=-2462.28, remainder_fraction=100.0000%, Lmin=-2444.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2912, ncalls=14851, regioncalls=97950, ndraw=128, logz=-2117.65, remainder_fraction=100.0000%, Lmin=-2106.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=14851, regioncalls=97950, ndraw=128, logz=-2035.83, remainder_fraction=100.0000%, Lmin=-2022.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2976, ncalls=14851, regioncalls=97950, ndraw=128, logz=-1984.77, remainder_fraction=100.0000%, Lmin=-1972.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=14851, regioncalls=97950, ndraw=128, logz=-1878.87, remainder_fraction=100.0000%, Lmin=-1863.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=14863, regioncalls=98590, ndraw=128, logz=-1806.25, remainder_fraction=100.0000%, Lmin=-1792.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3065, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1743.26, remainder_fraction=100.0000%, Lmin=-1730.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3072, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1718.37, remainder_fraction=100.0000%, Lmin=-1702.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=14997, regioncalls=99230, ndraw=128, logz=-1484.81, remainder_fraction=100.0000%, Lmin=-1471.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3218, ncalls=15000, regioncalls=99486, ndraw=128, logz=-1399.21, remainder_fraction=100.0000%, Lmin=-1381.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1369.52, remainder_fraction=100.0000%, Lmin=-1356.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3296, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1269.28, remainder_fraction=100.0000%, Lmin=-1257.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1218.67, remainder_fraction=100.0000%, Lmin=-1207.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3328, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1211.04, remainder_fraction=100.0000%, Lmin=-1198.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=15138, regioncalls=100638, ndraw=128, logz=-1108.00, remainder_fraction=100.0000%, Lmin=-1095.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3424, ncalls=15277, regioncalls=102174, ndraw=128, logz=-1053.34, remainder_fraction=100.0000%, Lmin=-1039.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3453, ncalls=15277, regioncalls=102174, ndraw=128, logz=-1009.67, remainder_fraction=100.0000%, Lmin=-997.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=15277, regioncalls=102174, ndraw=128, logz=-910.78, remainder_fraction=100.0000%, Lmin=-899.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=15277, regioncalls=102174, ndraw=128, logz=-868.72, remainder_fraction=100.0000%, Lmin=-855.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3584, ncalls=15405, regioncalls=102558, ndraw=128, logz=-830.22, remainder_fraction=100.0000%, Lmin=-818.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3608, ncalls=15405, regioncalls=102558, ndraw=128, logz=-795.53, remainder_fraction=100.0000%, Lmin=-784.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3648, ncalls=15405, regioncalls=102558, ndraw=128, logz=-756.39, remainder_fraction=100.0000%, Lmin=-744.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=15405, regioncalls=102558, ndraw=128, logz=-725.68, remainder_fraction=100.0000%, Lmin=-713.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3712, ncalls=15405, regioncalls=102558, ndraw=128, logz=-701.43, remainder_fraction=100.0000%, Lmin=-689.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3744, ncalls=15535, regioncalls=103070, ndraw=128, logz=-673.57, remainder_fraction=100.0000%, Lmin=-662.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3761, ncalls=15535, regioncalls=103070, ndraw=128, logz=-655.76, remainder_fraction=100.0000%, Lmin=-643.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3808, ncalls=15535, regioncalls=103070, ndraw=128, logz=-614.33, remainder_fraction=100.0000%, Lmin=-602.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=15535, regioncalls=103070, ndraw=128, logz=-592.72, remainder_fraction=100.0000%, Lmin=-582.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3915, ncalls=15666, regioncalls=103966, ndraw=128, logz=-531.69, remainder_fraction=100.0000%, Lmin=-519.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4054, ncalls=15794, regioncalls=104222, ndraw=128, logz=-430.06, remainder_fraction=100.0000%, Lmin=-418.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4064, ncalls=15794, regioncalls=104222, ndraw=128, logz=-425.59, remainder_fraction=100.0000%, Lmin=-413.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4069, ncalls=15794, regioncalls=104222, ndraw=128, logz=-421.91, remainder_fraction=100.0000%, Lmin=-409.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4128, ncalls=15794, regioncalls=104222, ndraw=128, logz=-389.61, remainder_fraction=100.0000%, Lmin=-376.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=15794, regioncalls=104222, ndraw=128, logz=-372.86, remainder_fraction=100.0000%, Lmin=-361.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4226, ncalls=15922, regioncalls=104478, ndraw=128, logz=-337.78, remainder_fraction=100.0000%, Lmin=-324.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=15922, regioncalls=104478, ndraw=128, logz=-296.12, remainder_fraction=100.0000%, Lmin=-284.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4352, ncalls=16050, regioncalls=104734, ndraw=128, logz=-279.88, remainder_fraction=100.0000%, Lmin=-267.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4379, ncalls=16050, regioncalls=104734, ndraw=128, logz=-268.89, remainder_fraction=100.0000%, Lmin=-257.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4384, ncalls=16050, regioncalls=104734, ndraw=128, logz=-267.00, remainder_fraction=100.0000%, Lmin=-254.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4416, ncalls=16050, regioncalls=104734, ndraw=128, logz=-255.39, remainder_fraction=100.0000%, Lmin=-242.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4448, ncalls=16050, regioncalls=104734, ndraw=128, logz=-243.89, remainder_fraction=100.0000%, Lmin=-232.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4473, ncalls=16050, regioncalls=104734, ndraw=128, logz=-233.10, remainder_fraction=100.0000%, Lmin=-221.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=16050, regioncalls=104734, ndraw=128, logz=-230.08, remainder_fraction=100.0000%, Lmin=-217.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=16178, regioncalls=105118, ndraw=128, logz=-218.91, remainder_fraction=100.0000%, Lmin=-207.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4544, ncalls=16178, regioncalls=105118, ndraw=128, logz=-209.11, remainder_fraction=100.0000%, Lmin=-196.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4626, ncalls=16178, regioncalls=105118, ndraw=128, logz=-186.28, remainder_fraction=100.0000%, Lmin=-174.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4643, ncalls=16178, regioncalls=105118, ndraw=128, logz=-181.94, remainder_fraction=100.0000%, Lmin=-170.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4672, ncalls=16306, regioncalls=105374, ndraw=128, logz=-175.41, remainder_fraction=100.0000%, Lmin=-163.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4804, ncalls=16306, regioncalls=105374, ndraw=128, logz=-148.00, remainder_fraction=100.0000%, Lmin=-135.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4832, ncalls=16306, regioncalls=105374, ndraw=128, logz=-143.04, remainder_fraction=100.0000%, Lmin=-131.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4896, ncalls=16434, regioncalls=105630, ndraw=128, logz=-130.59, remainder_fraction=100.0000%, Lmin=-118.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4907, ncalls=16434, regioncalls=105630, ndraw=128, logz=-128.26, remainder_fraction=100.0000%, Lmin=-115.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4928, ncalls=16434, regioncalls=105630, ndraw=128, logz=-124.41, remainder_fraction=100.0000%, Lmin=-112.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4934, ncalls=16434, regioncalls=105630, ndraw=128, logz=-123.43, remainder_fraction=100.0000%, Lmin=-111.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4965, ncalls=16434, regioncalls=105630, ndraw=128, logz=-118.86, remainder_fraction=100.0000%, Lmin=-107.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4969, ncalls=16434, regioncalls=105630, ndraw=128, logz=-118.47, remainder_fraction=100.0000%, Lmin=-106.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4992, ncalls=16434, regioncalls=105630, ndraw=128, logz=-115.01, remainder_fraction=100.0000%, Lmin=-103.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5006, ncalls=16562, regioncalls=105886, ndraw=128, logz=-111.80, remainder_fraction=100.0000%, Lmin=-99.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5009, ncalls=16562, regioncalls=105886, ndraw=128, logz=-111.38, remainder_fraction=100.0000%, Lmin=-99.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5048, ncalls=16562, regioncalls=105886, ndraw=128, logz=-105.52, remainder_fraction=100.0000%, Lmin=-93.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5070, ncalls=16562, regioncalls=105886, ndraw=128, logz=-102.79, remainder_fraction=100.0000%, Lmin=-90.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5088, ncalls=16562, regioncalls=105886, ndraw=128, logz=-99.80, remainder_fraction=100.0000%, Lmin=-87.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5152, ncalls=16562, regioncalls=105886, ndraw=128, logz=-90.35, remainder_fraction=100.0000%, Lmin=-78.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5184, ncalls=16691, regioncalls=106398, ndraw=128, logz=-86.58, remainder_fraction=100.0000%, Lmin=-74.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5216, ncalls=16691, regioncalls=106398, ndraw=128, logz=-83.51, remainder_fraction=100.0000%, Lmin=-71.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5225, ncalls=16691, regioncalls=106398, ndraw=128, logz=-82.71, remainder_fraction=100.0000%, Lmin=-70.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5242, ncalls=16691, regioncalls=106398, ndraw=128, logz=-81.06, remainder_fraction=100.0000%, Lmin=-68.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5248, ncalls=16691, regioncalls=106398, ndraw=128, logz=-80.41, remainder_fraction=100.0000%, Lmin=-68.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5268, ncalls=16691, regioncalls=106398, ndraw=128, logz=-78.58, remainder_fraction=100.0000%, Lmin=-66.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=16691, regioncalls=106398, ndraw=128, logz=-77.28, remainder_fraction=100.0000%, Lmin=-65.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5299, ncalls=16691, regioncalls=106398, ndraw=128, logz=-75.68, remainder_fraction=100.0000%, Lmin=-63.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5312, ncalls=16691, regioncalls=106398, ndraw=128, logz=-74.69, remainder_fraction=100.0000%, Lmin=-62.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5317, ncalls=16691, regioncalls=106398, ndraw=128, logz=-74.16, remainder_fraction=100.0000%, Lmin=-62.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5376, ncalls=16819, regioncalls=106654, ndraw=128, logz=-69.46, remainder_fraction=100.0000%, Lmin=-57.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5409, ncalls=16819, regioncalls=106654, ndraw=128, logz=-67.06, remainder_fraction=100.0000%, Lmin=-55.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5454, ncalls=16819, regioncalls=106654, ndraw=128, logz=-62.82, remainder_fraction=100.0000%, Lmin=-50.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5472, ncalls=16819, regioncalls=106654, ndraw=128, logz=-61.53, remainder_fraction=100.0000%, Lmin=-49.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=16819, regioncalls=106654, ndraw=128, logz=-60.92, remainder_fraction=100.0000%, Lmin=-48.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5510, ncalls=16947, regioncalls=106910, ndraw=128, logz=-58.82, remainder_fraction=100.0000%, Lmin=-46.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5518, ncalls=16947, regioncalls=106910, ndraw=128, logz=-58.19, remainder_fraction=100.0000%, Lmin=-46.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5527, ncalls=16947, regioncalls=106910, ndraw=128, logz=-57.54, remainder_fraction=100.0000%, Lmin=-45.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5568, ncalls=16947, regioncalls=106910, ndraw=128, logz=-54.79, remainder_fraction=100.0000%, Lmin=-42.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5617, ncalls=16947, regioncalls=106910, ndraw=128, logz=-51.43, remainder_fraction=100.0000%, Lmin=-39.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5634, ncalls=16947, regioncalls=106910, ndraw=128, logz=-50.19, remainder_fraction=100.0000%, Lmin=-38.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5641, ncalls=16947, regioncalls=106910, ndraw=128, logz=-49.58, remainder_fraction=100.0000%, Lmin=-37.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5650, ncalls=16947, regioncalls=106910, ndraw=128, logz=-48.93, remainder_fraction=100.0000%, Lmin=-36.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5664, ncalls=17075, regioncalls=107422, ndraw=128, logz=-47.94, remainder_fraction=100.0000%, Lmin=-35.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5696, ncalls=17075, regioncalls=107422, ndraw=128, logz=-46.29, remainder_fraction=100.0000%, Lmin=-34.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5713, ncalls=17075, regioncalls=107422, ndraw=128, logz=-45.59, remainder_fraction=100.0000%, Lmin=-33.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5728, ncalls=17075, regioncalls=107422, ndraw=128, logz=-44.83, remainder_fraction=100.0000%, Lmin=-32.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5754, ncalls=17075, regioncalls=107422, ndraw=128, logz=-43.65, remainder_fraction=100.0000%, Lmin=-31.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=17075, regioncalls=107422, ndraw=128, logz=-43.32, remainder_fraction=100.0000%, Lmin=-31.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5779, ncalls=17075, regioncalls=107422, ndraw=128, logz=-42.25, remainder_fraction=100.0000%, Lmin=-30.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5826, ncalls=17075, regioncalls=107422, ndraw=128, logz=-39.81, remainder_fraction=100.0000%, Lmin=-27.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5836, ncalls=17075, regioncalls=107422, ndraw=128, logz=-39.29, remainder_fraction=100.0000%, Lmin=-27.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5843, ncalls=17204, regioncalls=108062, ndraw=128, logz=-38.92, remainder_fraction=100.0000%, Lmin=-26.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5856, ncalls=17204, regioncalls=108062, ndraw=128, logz=-38.33, remainder_fraction=100.0000%, Lmin=-26.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5864, ncalls=17204, regioncalls=108062, ndraw=128, logz=-37.97, remainder_fraction=100.0000%, Lmin=-25.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5875, ncalls=17204, regioncalls=108062, ndraw=128, logz=-37.44, remainder_fraction=100.0000%, Lmin=-25.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5891, ncalls=17204, regioncalls=108062, ndraw=128, logz=-36.70, remainder_fraction=100.0000%, Lmin=-24.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5898, ncalls=17204, regioncalls=108062, ndraw=128, logz=-36.41, remainder_fraction=100.0000%, Lmin=-24.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5917, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.71, remainder_fraction=100.0000%, Lmin=-23.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.60, remainder_fraction=100.0000%, Lmin=-23.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5933, ncalls=17204, regioncalls=108062, ndraw=128, logz=-35.14, remainder_fraction=100.0000%, Lmin=-23.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5982, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.45, remainder_fraction=100.0000%, Lmin=-21.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5984, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.39, remainder_fraction=100.0000%, Lmin=-21.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5997, ncalls=17204, regioncalls=108062, ndraw=128, logz=-33.03, remainder_fraction=100.0000%, Lmin=-21.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6016, ncalls=17204, regioncalls=108062, ndraw=128, logz=-32.44, remainder_fraction=100.0000%, Lmin=-20.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=17332, regioncalls=108318, ndraw=128, logz=-31.44, remainder_fraction=100.0000%, Lmin=-19.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=17332, regioncalls=108318, ndraw=128, logz=-30.50, remainder_fraction=100.0000%, Lmin=-18.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6106, ncalls=17332, regioncalls=108318, ndraw=128, logz=-29.81, remainder_fraction=100.0000%, Lmin=-18.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6156, ncalls=17332, regioncalls=108318, ndraw=128, logz=-28.62, remainder_fraction=100.0000%, Lmin=-16.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6180, ncalls=17332, regioncalls=108318, ndraw=128, logz=-28.08, remainder_fraction=100.0000%, Lmin=-16.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6189, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.87, remainder_fraction=100.0000%, Lmin=-16.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6198, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.66, remainder_fraction=100.0000%, Lmin=-15.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6207, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.47, remainder_fraction=100.0000%, Lmin=-15.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6208, ncalls=17332, regioncalls=108318, ndraw=128, logz=-27.45, remainder_fraction=100.0000%, Lmin=-15.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6247, ncalls=17332, regioncalls=108318, ndraw=128, logz=-26.55, remainder_fraction=100.0000%, Lmin=-14.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6261, ncalls=17332, regioncalls=108318, ndraw=128, logz=-26.26, remainder_fraction=99.9999%, Lmin=-14.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6317, ncalls=17460, regioncalls=108574, ndraw=128, logz=-25.16, remainder_fraction=99.9998%, Lmin=-13.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6336, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.84, remainder_fraction=99.9998%, Lmin=-13.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6364, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.35, remainder_fraction=99.9996%, Lmin=-12.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6382, ncalls=17460, regioncalls=108574, ndraw=128, logz=-24.02, remainder_fraction=99.9995%, Lmin=-12.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6404, ncalls=17460, regioncalls=108574, ndraw=128, logz=-23.63, remainder_fraction=99.9992%, Lmin=-11.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6465, ncalls=17460, regioncalls=108574, ndraw=128, logz=-22.64, remainder_fraction=99.9979%, Lmin=-10.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6473, ncalls=17460, regioncalls=108574, ndraw=128, logz=-22.52, remainder_fraction=99.9976%, Lmin=-10.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6489, ncalls=17588, regioncalls=109086, ndraw=128, logz=-22.28, remainder_fraction=99.9970%, Lmin=-10.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6496, ncalls=17588, regioncalls=109086, ndraw=128, logz=-22.18, remainder_fraction=99.9967%, Lmin=-10.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6508, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.99, remainder_fraction=99.9960%, Lmin=-10.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6518, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.85, remainder_fraction=99.9953%, Lmin=-10.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=17588, regioncalls=109086, ndraw=128, logz=-21.23, remainder_fraction=99.9912%, Lmin=-9.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6579, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.97, remainder_fraction=99.9888%, Lmin=-9.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6592, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.79, remainder_fraction=99.9866%, Lmin=-8.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=17588, regioncalls=109086, ndraw=128, logz=-20.35, remainder_fraction=99.9792%, Lmin=-8.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6688, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.57, remainder_fraction=99.9553%, Lmin=-7.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.19, remainder_fraction=99.9329%, Lmin=-7.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6732, ncalls=17716, regioncalls=109342, ndraw=128, logz=-19.06, remainder_fraction=99.9228%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6752, ncalls=17716, regioncalls=109342, ndraw=128, logz=-18.86, remainder_fraction=99.9055%, Lmin=-7.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=17844, regioncalls=109598, ndraw=128, logz=-18.55, remainder_fraction=99.8702%, Lmin=-6.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6848, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.98, remainder_fraction=99.7729%, Lmin=-6.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6885, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.70, remainder_fraction=99.6976%, Lmin=-6.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6912, ncalls=17844, regioncalls=109598, ndraw=128, logz=-17.51, remainder_fraction=99.6343%, Lmin=-5.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6976, ncalls=17972, regioncalls=109854, ndraw=128, logz=-17.08, remainder_fraction=99.4375%, Lmin=-5.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7008, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.86, remainder_fraction=99.2979%, Lmin=-5.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7038, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.66, remainder_fraction=99.1449%, Lmin=-4.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.65, remainder_fraction=99.1322%, Lmin=-4.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7104, ncalls=17972, regioncalls=109854, ndraw=128, logz=-16.23, remainder_fraction=98.7000%, Lmin=-4.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7136, ncalls=18100, regioncalls=110110, ndraw=128, logz=-16.03, remainder_fraction=98.4281%, Lmin=-4.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7168, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.83, remainder_fraction=98.1164%, Lmin=-3.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7193, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.68, remainder_fraction=97.8153%, Lmin=-3.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.64, remainder_fraction=97.7212%, Lmin=-3.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7232, ncalls=18100, regioncalls=110110, ndraw=128, logz=-15.46, remainder_fraction=97.2928%, Lmin=-3.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7296, ncalls=18228, regioncalls=110366, ndraw=128, logz=-15.13, remainder_fraction=96.2357%, Lmin=-3.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7346, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.89, remainder_fraction=95.1607%, Lmin=-3.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7392, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.69, remainder_fraction=94.1522%, Lmin=-2.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7424, ncalls=18228, regioncalls=110366, ndraw=128, logz=-14.55, remainder_fraction=93.3329%, Lmin=-2.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7456, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.43, remainder_fraction=92.4218%, Lmin=-2.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.30, remainder_fraction=91.5439%, Lmin=-2.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7499, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.26, remainder_fraction=91.2163%, Lmin=-2.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=18356, regioncalls=110878, ndraw=128, logz=-14.19, remainder_fraction=90.4641%, Lmin=-2.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7616, ncalls=18356, regioncalls=110878, ndraw=128, logz=-13.87, remainder_fraction=86.8875%, Lmin=-2.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7648, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.78, remainder_fraction=85.6003%, Lmin=-1.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7655, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.76, remainder_fraction=85.3763%, Lmin=-1.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7782, ncalls=18484, regioncalls=111134, ndraw=128, logz=-13.44, remainder_fraction=79.8800%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7809, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.38, remainder_fraction=78.6786%, Lmin=-1.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7904, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.19, remainder_fraction=73.6927%, Lmin=-1.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7936, ncalls=18612, regioncalls=111390, ndraw=128, logz=-13.13, remainder_fraction=72.0994%, Lmin=-1.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7963, ncalls=18740, regioncalls=111646, ndraw=128, logz=-13.08, remainder_fraction=70.6569%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8000, ncalls=18740, regioncalls=111646, ndraw=128, logz=-13.01, remainder_fraction=68.6910%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8032, ncalls=18740, regioncalls=111646, ndraw=128, logz=-12.96, remainder_fraction=66.9543%, Lmin=-1.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8118, ncalls=18868, regioncalls=112030, ndraw=128, logz=-12.83, remainder_fraction=62.3127%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8128, ncalls=18868, regioncalls=112030, ndraw=128, logz=-12.82, remainder_fraction=61.8006%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8224, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.69, remainder_fraction=56.9226%, Lmin=-0.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8256, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.65, remainder_fraction=55.1686%, Lmin=-0.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8271, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.63, remainder_fraction=54.4333%, Lmin=-0.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8320, ncalls=18996, regioncalls=112414, ndraw=128, logz=-12.58, remainder_fraction=51.9435%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8384, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.52, remainder_fraction=48.6747%, Lmin=-0.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8416, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.49, remainder_fraction=47.1015%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8425, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.48, remainder_fraction=46.6891%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8480, ncalls=19124, regioncalls=113054, ndraw=128, logz=-12.43, remainder_fraction=44.0215%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8544, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.38, remainder_fraction=41.0352%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8576, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.35, remainder_fraction=39.5759%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8578, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.35, remainder_fraction=39.4897%, Lmin=-0.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8608, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.33, remainder_fraction=38.2056%, Lmin=-0.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8640, ncalls=19252, regioncalls=114078, ndraw=128, logz=-12.31, remainder_fraction=36.8536%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8734, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.25, remainder_fraction=33.0614%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8736, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.25, remainder_fraction=32.9849%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8768, ncalls=19380, regioncalls=114462, ndraw=128, logz=-12.23, remainder_fraction=31.7334%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8887, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.17, remainder_fraction=27.4835%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8928, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.15, remainder_fraction=26.1010%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8960, ncalls=19508, regioncalls=114846, ndraw=128, logz=-12.14, remainder_fraction=25.0771%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9024, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.11, remainder_fraction=23.1124%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9042, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.10, remainder_fraction=22.5832%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9056, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.10, remainder_fraction=22.1827%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9088, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.09, remainder_fraction=21.2880%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9152, ncalls=19636, regioncalls=115102, ndraw=128, logz=-12.07, remainder_fraction=19.5886%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9184, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.06, remainder_fraction=18.7827%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9195, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.05, remainder_fraction=18.5036%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9280, ncalls=19764, regioncalls=115358, ndraw=128, logz=-12.03, remainder_fraction=16.5262%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9344, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.01, remainder_fraction=15.1651%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9349, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.01, remainder_fraction=15.0616%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9408, ncalls=19892, regioncalls=115614, ndraw=128, logz=-12.00, remainder_fraction=13.8965%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9472, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.7397%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9503, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.2075%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9504, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.98, remainder_fraction=12.1910%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9536, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.97, remainder_fraction=11.6663%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9568, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.97, remainder_fraction=11.1622%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9600, ncalls=20020, regioncalls=115870, ndraw=128, logz=-11.96, remainder_fraction=10.6812%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9656, ncalls=20148, regioncalls=116638, ndraw=128, logz=-11.95, remainder_fraction=9.8847%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9760, ncalls=20148, regioncalls=116638, ndraw=128, logz=-11.94, remainder_fraction=8.5460%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9812, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.9438%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9824, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.8115%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9856, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.93, remainder_fraction=7.4677%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9888, ncalls=20276, regioncalls=117022, ndraw=128, logz=-11.92, remainder_fraction=7.1387%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9965, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.91, remainder_fraction=6.4020%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10016, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.91, remainder_fraction=5.9550%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=20404, regioncalls=117406, ndraw=128, logz=-11.90, remainder_fraction=5.4369%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10112, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=5.1939%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10119, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=5.1429%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10144, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=4.9628%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10176, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.90, remainder_fraction=4.7402%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=20532, regioncalls=118046, ndraw=128, logz=-11.89, remainder_fraction=4.5281%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10272, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=4.1317%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10304, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=3.9463%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10336, ncalls=20660, regioncalls=118686, ndraw=128, logz=-11.89, remainder_fraction=3.7692%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10426, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=3.3117%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10496, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=2.9939%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10528, ncalls=20788, regioncalls=119326, ndraw=128, logz=-11.88, remainder_fraction=2.8586%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10579, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.88, remainder_fraction=2.6559%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10624, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.4885%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10656, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.3759%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10688, ncalls=20916, regioncalls=119710, ndraw=128, logz=-11.87, remainder_fraction=2.2686%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10734, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=2.1225%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=2.0679%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10784, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=1.9742%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10816, ncalls=21044, regioncalls=119966, ndraw=128, logz=-11.87, remainder_fraction=1.8847%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10888, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.87, remainder_fraction=1.6979%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10912, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.87, remainder_fraction=1.6399%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10944, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.86, remainder_fraction=1.5655%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10976, ncalls=21172, regioncalls=120222, ndraw=128, logz=-11.86, remainder_fraction=1.4945%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11040, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.3617%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11042, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.3577%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11104, ncalls=21300, regioncalls=120478, ndraw=128, logz=-11.86, remainder_fraction=1.2408%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11196, ncalls=21428, regioncalls=120990, ndraw=128, logz=-11.86, remainder_fraction=1.0854%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11232, ncalls=21428, regioncalls=120990, ndraw=128, logz=-11.86, remainder_fraction=1.0300%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 21428 INFO ultranest:integrator.py:2697 logZ = -11.85 +- 0.1011 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2747.9, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1119 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (9088/9428 iterations) have 682 DEBUG ultranest:integrator.py:1663 at least 1367 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 1367 minimum live points (dlogz from 0.08 to 0.21, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.18 bs:0.10 tail:0.01 total:0.10 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 1367 live points (have 684 already) ... INFO ultranest:integrator.py:1433 Sampling 683 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 1367.0), (inf, 1367.0)] DEBUG ultranest:integrator.py:2610 iteration=5, ncalls=22239, regioncalls=121118, ndraw=128, logz=-233003.00, remainder_fraction=100.0000%, Lmin=-230589.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=32, ncalls=22239, regioncalls=121118, ndraw=128, logz=-199426.05, remainder_fraction=100.0000%, Lmin=-198726.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=157, ncalls=22239, regioncalls=121118, ndraw=128, logz=-149600.33, remainder_fraction=100.0000%, Lmin=-148811.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=22239, regioncalls=121118, ndraw=128, logz=-147913.41, remainder_fraction=100.0000%, Lmin=-147895.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=192, ncalls=22239, regioncalls=121118, ndraw=128, logz=-141385.44, remainder_fraction=100.0000%, Lmin=-141373.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=311, ncalls=22367, regioncalls=121246, ndraw=128, logz=-124821.42, remainder_fraction=100.0000%, Lmin=-124722.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=352, ncalls=22367, regioncalls=121246, ndraw=128, logz=-119354.68, remainder_fraction=100.0000%, Lmin=-119332.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=22367, regioncalls=121246, ndraw=128, logz=-116564.88, remainder_fraction=100.0000%, Lmin=-116552.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=509, ncalls=22475, regioncalls=121374, ndraw=128, logz=-105894.01, remainder_fraction=100.0000%, Lmin=-105771.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=512, ncalls=22475, regioncalls=121374, ndraw=128, logz=-105522.63, remainder_fraction=100.0000%, Lmin=-105358.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=22475, regioncalls=121374, ndraw=128, logz=-103558.95, remainder_fraction=100.0000%, Lmin=-103464.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=608, ncalls=22583, regioncalls=121502, ndraw=128, logz=-98572.93, remainder_fraction=100.0000%, Lmin=-98514.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=618, ncalls=22583, regioncalls=121502, ndraw=128, logz=-97795.04, remainder_fraction=100.0000%, Lmin=-97702.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=672, ncalls=22583, regioncalls=121502, ndraw=128, logz=-94853.19, remainder_fraction=100.0000%, Lmin=-94828.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=704, ncalls=22583, regioncalls=121502, ndraw=128, logz=-93006.22, remainder_fraction=100.0000%, Lmin=-92954.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=832, ncalls=22667, regioncalls=121630, ndraw=128, logz=-85410.96, remainder_fraction=100.0000%, Lmin=-85395.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=896, ncalls=22667, regioncalls=121630, ndraw=128, logz=-82306.57, remainder_fraction=100.0000%, Lmin=-82251.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=926, ncalls=22743, regioncalls=121758, ndraw=128, logz=-81023.20, remainder_fraction=100.0000%, Lmin=-81000.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=928, ncalls=22743, regioncalls=121758, ndraw=128, logz=-80948.65, remainder_fraction=100.0000%, Lmin=-80888.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=992, ncalls=22743, regioncalls=121758, ndraw=128, logz=-77582.27, remainder_fraction=100.0000%, Lmin=-77565.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1056, ncalls=22817, regioncalls=121886, ndraw=128, logz=-73503.58, remainder_fraction=100.0000%, Lmin=-73423.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1088, ncalls=22817, regioncalls=121886, ndraw=128, logz=-71606.05, remainder_fraction=100.0000%, Lmin=-71595.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=22892, regioncalls=122014, ndraw=128, logz=-69564.78, remainder_fraction=100.0000%, Lmin=-69507.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1152, ncalls=22892, regioncalls=122014, ndraw=128, logz=-68137.54, remainder_fraction=100.0000%, Lmin=-68006.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1184, ncalls=22892, regioncalls=122014, ndraw=128, logz=-66557.80, remainder_fraction=100.0000%, Lmin=-66520.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=22892, regioncalls=122014, ndraw=128, logz=-65303.22, remainder_fraction=100.0000%, Lmin=-65261.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1232, ncalls=22942, regioncalls=122142, ndraw=128, logz=-64655.71, remainder_fraction=100.0000%, Lmin=-64592.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1248, ncalls=22942, regioncalls=122142, ndraw=128, logz=-63771.59, remainder_fraction=100.0000%, Lmin=-63760.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1312, ncalls=22942, regioncalls=122142, ndraw=128, logz=-60798.74, remainder_fraction=100.0000%, Lmin=-60781.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1434, ncalls=23048, regioncalls=122398, ndraw=128, logz=-55667.63, remainder_fraction=100.0000%, Lmin=-55649.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=23111, regioncalls=122526, ndraw=128, logz=-54246.26, remainder_fraction=100.0000%, Lmin=-54207.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1536, ncalls=23111, regioncalls=122526, ndraw=128, logz=-51934.62, remainder_fraction=100.0000%, Lmin=-51913.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1539, ncalls=23111, regioncalls=122526, ndraw=128, logz=-51908.73, remainder_fraction=100.0000%, Lmin=-51840.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1568, ncalls=23111, regioncalls=122526, ndraw=128, logz=-50702.13, remainder_fraction=100.0000%, Lmin=-50615.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=23165, regioncalls=122654, ndraw=128, logz=-49341.16, remainder_fraction=100.0000%, Lmin=-49307.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1718, ncalls=23223, regioncalls=122782, ndraw=128, logz=-45151.88, remainder_fraction=100.0000%, Lmin=-45133.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1843, ncalls=23302, regioncalls=123038, ndraw=128, logz=-41409.71, remainder_fraction=100.0000%, Lmin=-41382.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1845, ncalls=23302, regioncalls=123038, ndraw=128, logz=-41321.71, remainder_fraction=100.0000%, Lmin=-41294.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1856, ncalls=23302, regioncalls=123038, ndraw=128, logz=-40908.42, remainder_fraction=100.0000%, Lmin=-40870.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1888, ncalls=23344, regioncalls=123166, ndraw=128, logz=-39979.36, remainder_fraction=100.0000%, Lmin=-39965.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=23344, regioncalls=123166, ndraw=128, logz=-39214.58, remainder_fraction=100.0000%, Lmin=-39202.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1952, ncalls=23379, regioncalls=123294, ndraw=128, logz=-38457.53, remainder_fraction=100.0000%, Lmin=-38445.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2075, ncalls=23442, regioncalls=123550, ndraw=128, logz=-35102.65, remainder_fraction=100.0000%, Lmin=-35093.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=23442, regioncalls=123550, ndraw=128, logz=-34982.19, remainder_fraction=100.0000%, Lmin=-34917.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2151, ncalls=23516, regioncalls=123806, ndraw=128, logz=-33126.27, remainder_fraction=100.0000%, Lmin=-33087.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=23568, regioncalls=124062, ndraw=128, logz=-30972.50, remainder_fraction=100.0000%, Lmin=-30958.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=23568, regioncalls=124062, ndraw=128, logz=-30472.51, remainder_fraction=100.0000%, Lmin=-30381.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2404, ncalls=23652, regioncalls=124446, ndraw=128, logz=-27663.57, remainder_fraction=100.0000%, Lmin=-27619.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2432, ncalls=23652, regioncalls=124446, ndraw=128, logz=-27023.92, remainder_fraction=100.0000%, Lmin=-26954.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2458, ncalls=23692, regioncalls=124574, ndraw=128, logz=-26425.68, remainder_fraction=100.0000%, Lmin=-26407.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=23692, regioncalls=124574, ndraw=128, logz=-26287.45, remainder_fraction=100.0000%, Lmin=-26248.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2496, ncalls=23692, regioncalls=124574, ndraw=128, logz=-25544.59, remainder_fraction=100.0000%, Lmin=-25534.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=23757, regioncalls=124958, ndraw=128, logz=-24292.17, remainder_fraction=100.0000%, Lmin=-24270.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2624, ncalls=23817, regioncalls=125214, ndraw=128, logz=-23053.44, remainder_fraction=100.0000%, Lmin=-23035.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2688, ncalls=23817, regioncalls=125214, ndraw=128, logz=-21981.47, remainder_fraction=100.0000%, Lmin=-21961.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2752, ncalls=23879, regioncalls=125598, ndraw=128, logz=-21026.27, remainder_fraction=100.0000%, Lmin=-21006.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2764, ncalls=23879, regioncalls=125598, ndraw=128, logz=-20797.43, remainder_fraction=100.0000%, Lmin=-20779.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2784, ncalls=23898, regioncalls=125726, ndraw=128, logz=-20575.98, remainder_fraction=100.0000%, Lmin=-20539.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=23948, regioncalls=126110, ndraw=128, logz=-19134.96, remainder_fraction=100.0000%, Lmin=-19112.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=23998, regioncalls=126494, ndraw=128, logz=-18084.03, remainder_fraction=100.0000%, Lmin=-18032.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=24037, regioncalls=126750, ndraw=128, logz=-17224.20, remainder_fraction=100.0000%, Lmin=-17206.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3071, ncalls=24091, regioncalls=127134, ndraw=128, logz=-16624.71, remainder_fraction=100.0000%, Lmin=-16607.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=24154, regioncalls=127646, ndraw=128, logz=-15375.38, remainder_fraction=100.0000%, Lmin=-15354.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=24170, regioncalls=127774, ndraw=128, logz=-15007.61, remainder_fraction=100.0000%, Lmin=-14988.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3232, ncalls=24195, regioncalls=127902, ndraw=128, logz=-14683.63, remainder_fraction=100.0000%, Lmin=-14655.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3328, ncalls=24258, regioncalls=128414, ndraw=128, logz=-13582.10, remainder_fraction=100.0000%, Lmin=-13564.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=24286, regioncalls=128670, ndraw=128, logz=-13277.66, remainder_fraction=100.0000%, Lmin=-13247.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3379, ncalls=24296, regioncalls=128798, ndraw=128, logz=-13008.15, remainder_fraction=100.0000%, Lmin=-12998.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3392, ncalls=24308, regioncalls=128926, ndraw=128, logz=-12913.20, remainder_fraction=100.0000%, Lmin=-12897.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3424, ncalls=24320, regioncalls=129054, ndraw=128, logz=-12664.07, remainder_fraction=100.0000%, Lmin=-12652.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3456, ncalls=24335, regioncalls=129182, ndraw=128, logz=-12409.39, remainder_fraction=100.0000%, Lmin=-12388.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3552, ncalls=24385, regioncalls=129694, ndraw=128, logz=-11620.47, remainder_fraction=100.0000%, Lmin=-11582.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3616, ncalls=24441, regioncalls=130334, ndraw=128, logz=-11082.91, remainder_fraction=100.0000%, Lmin=-11065.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3648, ncalls=24470, regioncalls=130590, ndraw=128, logz=-10850.90, remainder_fraction=100.0000%, Lmin=-10838.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=24478, regioncalls=130718, ndraw=128, logz=-10650.65, remainder_fraction=100.0000%, Lmin=-10639.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3685, ncalls=24488, regioncalls=130846, ndraw=128, logz=-10628.72, remainder_fraction=100.0000%, Lmin=-10617.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3744, ncalls=24527, regioncalls=131358, ndraw=128, logz=-10178.86, remainder_fraction=100.0000%, Lmin=-10167.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3808, ncalls=24566, regioncalls=131870, ndraw=128, logz=-9708.26, remainder_fraction=100.0000%, Lmin=-9696.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=24579, regioncalls=131998, ndraw=128, logz=-9465.14, remainder_fraction=100.0000%, Lmin=-9447.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3872, ncalls=24599, regioncalls=132382, ndraw=128, logz=-9298.28, remainder_fraction=100.0000%, Lmin=-9287.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3991, ncalls=24689, regioncalls=133662, ndraw=128, logz=-8459.96, remainder_fraction=100.0000%, Lmin=-8441.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=24698, regioncalls=133790, ndraw=128, logz=-8430.80, remainder_fraction=100.0000%, Lmin=-8400.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4032, ncalls=24719, regioncalls=134174, ndraw=128, logz=-8247.54, remainder_fraction=100.0000%, Lmin=-8236.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4154, ncalls=24798, regioncalls=135582, ndraw=128, logz=-7456.39, remainder_fraction=100.0000%, Lmin=-7441.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=24798, regioncalls=135582, ndraw=128, logz=-7421.50, remainder_fraction=100.0000%, Lmin=-7410.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4290, ncalls=24874, regioncalls=136734, ndraw=128, logz=-6754.42, remainder_fraction=100.0000%, Lmin=-6731.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4298, ncalls=24874, regioncalls=136734, ndraw=128, logz=-6715.01, remainder_fraction=100.0000%, Lmin=-6688.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=24888, regioncalls=137118, ndraw=128, logz=-6632.30, remainder_fraction=100.0000%, Lmin=-6621.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4416, ncalls=24931, regioncalls=138142, ndraw=128, logz=-6265.39, remainder_fraction=100.0000%, Lmin=-6249.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4542, ncalls=25014, regioncalls=139806, ndraw=128, logz=-5663.02, remainder_fraction=100.0000%, Lmin=-5646.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4576, ncalls=25038, regioncalls=140190, ndraw=128, logz=-5475.07, remainder_fraction=100.0000%, Lmin=-5463.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4604, ncalls=25065, regioncalls=140830, ndraw=128, logz=-5332.69, remainder_fraction=100.0000%, Lmin=-5311.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4608, ncalls=25065, regioncalls=140830, ndraw=128, logz=-5312.35, remainder_fraction=100.0000%, Lmin=-5301.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4713, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4957.43, remainder_fraction=100.0000%, Lmin=-4946.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4736, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4906.82, remainder_fraction=100.0000%, Lmin=-4894.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4768, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4813.69, remainder_fraction=100.0000%, Lmin=-4801.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=25220, regioncalls=141726, ndraw=128, logz=-4682.49, remainder_fraction=100.0000%, Lmin=-4668.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4896, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4366.94, remainder_fraction=100.0000%, Lmin=-4356.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4910, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4337.55, remainder_fraction=100.0000%, Lmin=-4324.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4181.06, remainder_fraction=100.0000%, Lmin=-4163.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4992, ncalls=25348, regioncalls=141854, ndraw=128, logz=-4081.59, remainder_fraction=100.0000%, Lmin=-4070.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5024, ncalls=25348, regioncalls=141854, ndraw=128, logz=-3998.37, remainder_fraction=100.0000%, Lmin=-3985.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=25414, regioncalls=143774, ndraw=128, logz=-3720.66, remainder_fraction=100.0000%, Lmin=-3703.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5219, ncalls=25477, regioncalls=145694, ndraw=128, logz=-3487.62, remainder_fraction=100.0000%, Lmin=-3475.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=25513, regioncalls=147230, ndraw=128, logz=-3358.46, remainder_fraction=100.0000%, Lmin=-3343.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5312, ncalls=25540, regioncalls=148382, ndraw=128, logz=-3286.69, remainder_fraction=100.0000%, Lmin=-3273.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5376, ncalls=25678, regioncalls=149022, ndraw=128, logz=-3147.08, remainder_fraction=100.0000%, Lmin=-3132.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5408, ncalls=25678, regioncalls=149022, ndraw=128, logz=-3047.07, remainder_fraction=100.0000%, Lmin=-3036.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5525, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2823.69, remainder_fraction=100.0000%, Lmin=-2808.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5536, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2792.09, remainder_fraction=100.0000%, Lmin=-2777.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5632, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2615.93, remainder_fraction=100.0000%, Lmin=-2600.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5696, ncalls=25806, regioncalls=149150, ndraw=128, logz=-2461.13, remainder_fraction=100.0000%, Lmin=-2449.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5817, ncalls=25892, regioncalls=152862, ndraw=128, logz=-2243.06, remainder_fraction=100.0000%, Lmin=-2231.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5824, ncalls=25897, regioncalls=153118, ndraw=128, logz=-2236.10, remainder_fraction=100.0000%, Lmin=-2221.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5832, ncalls=25900, regioncalls=153246, ndraw=128, logz=-2225.37, remainder_fraction=100.0000%, Lmin=-2213.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5888, ncalls=25943, regioncalls=155934, ndraw=128, logz=-2139.12, remainder_fraction=100.0000%, Lmin=-2127.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=26078, regioncalls=156702, ndraw=128, logz=-2099.07, remainder_fraction=100.0000%, Lmin=-2086.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5952, ncalls=26078, regioncalls=156702, ndraw=128, logz=-2050.81, remainder_fraction=100.0000%, Lmin=-2034.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1909.60, remainder_fraction=100.0000%, Lmin=-1897.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1862.70, remainder_fraction=100.0000%, Lmin=-1850.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6112, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1815.98, remainder_fraction=100.0000%, Lmin=-1804.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6138, ncalls=26078, regioncalls=156702, ndraw=128, logz=-1781.34, remainder_fraction=100.0000%, Lmin=-1768.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6176, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1734.14, remainder_fraction=100.0000%, Lmin=-1722.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6208, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1701.84, remainder_fraction=100.0000%, Lmin=-1690.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6272, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1614.13, remainder_fraction=100.0000%, Lmin=-1601.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6304, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1570.62, remainder_fraction=100.0000%, Lmin=-1558.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6336, ncalls=26209, regioncalls=157214, ndraw=128, logz=-1536.50, remainder_fraction=100.0000%, Lmin=-1524.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6368, ncalls=26337, regioncalls=157342, ndraw=128, logz=-1508.89, remainder_fraction=100.0000%, Lmin=-1496.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6444, ncalls=26337, regioncalls=157342, ndraw=128, logz=-1430.05, remainder_fraction=100.0000%, Lmin=-1417.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6575, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1299.75, remainder_fraction=100.0000%, Lmin=-1287.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1266.10, remainder_fraction=100.0000%, Lmin=-1254.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6656, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1239.64, remainder_fraction=100.0000%, Lmin=-1226.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6674, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1221.34, remainder_fraction=100.0000%, Lmin=-1208.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6752, ncalls=26465, regioncalls=157854, ndraw=128, logz=-1160.70, remainder_fraction=100.0000%, Lmin=-1148.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1131.34, remainder_fraction=100.0000%, Lmin=-1120.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6816, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1110.89, remainder_fraction=100.0000%, Lmin=-1099.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1058.73, remainder_fraction=100.0000%, Lmin=-1046.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6944, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1013.50, remainder_fraction=100.0000%, Lmin=-1001.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6949, ncalls=26598, regioncalls=158750, ndraw=128, logz=-1011.38, remainder_fraction=100.0000%, Lmin=-999.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6976, ncalls=26729, regioncalls=159262, ndraw=128, logz=-994.70, remainder_fraction=100.0000%, Lmin=-982.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7008, ncalls=26729, regioncalls=159262, ndraw=128, logz=-968.55, remainder_fraction=100.0000%, Lmin=-956.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=26729, regioncalls=159262, ndraw=128, logz=-947.90, remainder_fraction=100.0000%, Lmin=-935.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7136, ncalls=26729, regioncalls=159262, ndraw=128, logz=-885.07, remainder_fraction=100.0000%, Lmin=-872.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7232, ncalls=26857, regioncalls=159390, ndraw=128, logz=-827.46, remainder_fraction=100.0000%, Lmin=-814.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7255, ncalls=26857, regioncalls=159390, ndraw=128, logz=-811.29, remainder_fraction=100.0000%, Lmin=-799.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7328, ncalls=26857, regioncalls=159390, ndraw=128, logz=-777.63, remainder_fraction=100.0000%, Lmin=-765.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=26988, regioncalls=160414, ndraw=128, logz=-758.38, remainder_fraction=100.0000%, Lmin=-746.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7456, ncalls=26988, regioncalls=160414, ndraw=128, logz=-715.72, remainder_fraction=100.0000%, Lmin=-703.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=26988, regioncalls=160414, ndraw=128, logz=-699.47, remainder_fraction=100.0000%, Lmin=-687.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7552, ncalls=26988, regioncalls=160414, ndraw=128, logz=-671.79, remainder_fraction=100.0000%, Lmin=-658.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7562, ncalls=27116, regioncalls=160542, ndraw=128, logz=-664.60, remainder_fraction=100.0000%, Lmin=-652.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7648, ncalls=27116, regioncalls=160542, ndraw=128, logz=-622.81, remainder_fraction=100.0000%, Lmin=-610.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7712, ncalls=27116, regioncalls=160542, ndraw=128, logz=-596.90, remainder_fraction=100.0000%, Lmin=-584.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7808, ncalls=27245, regioncalls=160926, ndraw=128, logz=-560.57, remainder_fraction=100.0000%, Lmin=-548.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7840, ncalls=27245, regioncalls=160926, ndraw=128, logz=-549.54, remainder_fraction=100.0000%, Lmin=-537.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7873, ncalls=27245, regioncalls=160926, ndraw=128, logz=-534.69, remainder_fraction=100.0000%, Lmin=-522.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7904, ncalls=27245, regioncalls=160926, ndraw=128, logz=-518.81, remainder_fraction=100.0000%, Lmin=-505.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7968, ncalls=27373, regioncalls=161182, ndraw=128, logz=-501.05, remainder_fraction=100.0000%, Lmin=-489.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8000, ncalls=27373, regioncalls=161182, ndraw=128, logz=-488.23, remainder_fraction=100.0000%, Lmin=-475.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8064, ncalls=27373, regioncalls=161182, ndraw=128, logz=-462.78, remainder_fraction=100.0000%, Lmin=-450.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8096, ncalls=27373, regioncalls=161182, ndraw=128, logz=-451.71, remainder_fraction=100.0000%, Lmin=-439.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8160, ncalls=27501, regioncalls=161310, ndraw=128, logz=-432.03, remainder_fraction=100.0000%, Lmin=-419.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8179, ncalls=27501, regioncalls=161310, ndraw=128, logz=-428.19, remainder_fraction=100.0000%, Lmin=-415.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8320, ncalls=27501, regioncalls=161310, ndraw=128, logz=-386.01, remainder_fraction=100.0000%, Lmin=-373.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8384, ncalls=27629, regioncalls=161566, ndraw=128, logz=-369.92, remainder_fraction=100.0000%, Lmin=-358.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8485, ncalls=27629, regioncalls=161566, ndraw=128, logz=-343.91, remainder_fraction=100.0000%, Lmin=-331.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8544, ncalls=27760, regioncalls=162590, ndraw=128, logz=-331.85, remainder_fraction=100.0000%, Lmin=-320.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8576, ncalls=27760, regioncalls=162590, ndraw=128, logz=-325.77, remainder_fraction=100.0000%, Lmin=-313.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8640, ncalls=27760, regioncalls=162590, ndraw=128, logz=-310.34, remainder_fraction=100.0000%, Lmin=-298.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8672, ncalls=27760, regioncalls=162590, ndraw=128, logz=-303.00, remainder_fraction=100.0000%, Lmin=-291.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8791, ncalls=27888, regioncalls=162718, ndraw=128, logz=-276.04, remainder_fraction=100.0000%, Lmin=-264.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8832, ncalls=27888, regioncalls=162718, ndraw=128, logz=-268.24, remainder_fraction=100.0000%, Lmin=-255.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8864, ncalls=27888, regioncalls=162718, ndraw=128, logz=-261.85, remainder_fraction=100.0000%, Lmin=-249.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8896, ncalls=27888, regioncalls=162718, ndraw=128, logz=-256.10, remainder_fraction=100.0000%, Lmin=-243.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8928, ncalls=28020, regioncalls=163870, ndraw=128, logz=-249.09, remainder_fraction=100.0000%, Lmin=-237.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8992, ncalls=28020, regioncalls=163870, ndraw=128, logz=-237.30, remainder_fraction=100.0000%, Lmin=-225.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9012, ncalls=28020, regioncalls=163870, ndraw=128, logz=-233.88, remainder_fraction=100.0000%, Lmin=-222.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9024, ncalls=28020, regioncalls=163870, ndraw=128, logz=-232.03, remainder_fraction=100.0000%, Lmin=-219.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9088, ncalls=28020, regioncalls=163870, ndraw=128, logz=-219.93, remainder_fraction=100.0000%, Lmin=-208.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9120, ncalls=28149, regioncalls=164254, ndraw=128, logz=-214.94, remainder_fraction=100.0000%, Lmin=-203.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9152, ncalls=28149, regioncalls=164254, ndraw=128, logz=-210.52, remainder_fraction=100.0000%, Lmin=-198.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9288, ncalls=28149, regioncalls=164254, ndraw=128, logz=-192.50, remainder_fraction=100.0000%, Lmin=-180.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9318, ncalls=28277, regioncalls=164382, ndraw=128, logz=-188.56, remainder_fraction=100.0000%, Lmin=-175.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9344, ncalls=28277, regioncalls=164382, ndraw=128, logz=-185.27, remainder_fraction=100.0000%, Lmin=-173.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9374, ncalls=28277, regioncalls=164382, ndraw=128, logz=-182.35, remainder_fraction=100.0000%, Lmin=-170.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9376, ncalls=28277, regioncalls=164382, ndraw=128, logz=-182.12, remainder_fraction=100.0000%, Lmin=-170.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9408, ncalls=28277, regioncalls=164382, ndraw=128, logz=-178.57, remainder_fraction=100.0000%, Lmin=-166.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9504, ncalls=28405, regioncalls=164638, ndraw=128, logz=-167.11, remainder_fraction=100.0000%, Lmin=-155.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9536, ncalls=28405, regioncalls=164638, ndraw=128, logz=-164.30, remainder_fraction=100.0000%, Lmin=-152.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9568, ncalls=28405, regioncalls=164638, ndraw=128, logz=-161.45, remainder_fraction=100.0000%, Lmin=-149.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9632, ncalls=28405, regioncalls=164638, ndraw=128, logz=-154.84, remainder_fraction=100.0000%, Lmin=-142.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9664, ncalls=28405, regioncalls=164638, ndraw=128, logz=-150.83, remainder_fraction=100.0000%, Lmin=-138.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9683, ncalls=28533, regioncalls=164766, ndraw=128, logz=-149.12, remainder_fraction=100.0000%, Lmin=-137.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9689, ncalls=28533, regioncalls=164766, ndraw=128, logz=-148.58, remainder_fraction=100.0000%, Lmin=-136.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9696, ncalls=28533, regioncalls=164766, ndraw=128, logz=-147.87, remainder_fraction=100.0000%, Lmin=-135.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9760, ncalls=28533, regioncalls=164766, ndraw=128, logz=-141.77, remainder_fraction=100.0000%, Lmin=-129.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9824, ncalls=28533, regioncalls=164766, ndraw=128, logz=-135.50, remainder_fraction=100.0000%, Lmin=-123.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9856, ncalls=28661, regioncalls=165150, ndraw=128, logz=-132.77, remainder_fraction=100.0000%, Lmin=-121.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9914, ncalls=28661, regioncalls=165150, ndraw=128, logz=-128.01, remainder_fraction=100.0000%, Lmin=-115.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9962, ncalls=28661, regioncalls=165150, ndraw=128, logz=-123.77, remainder_fraction=100.0000%, Lmin=-111.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10016, ncalls=28661, regioncalls=165150, ndraw=128, logz=-119.81, remainder_fraction=100.0000%, Lmin=-107.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10027, ncalls=28661, regioncalls=165150, ndraw=128, logz=-118.98, remainder_fraction=100.0000%, Lmin=-107.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=28789, regioncalls=165406, ndraw=128, logz=-114.34, remainder_fraction=100.0000%, Lmin=-101.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10100, ncalls=28789, regioncalls=165406, ndraw=128, logz=-112.10, remainder_fraction=100.0000%, Lmin=-99.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10109, ncalls=28789, regioncalls=165406, ndraw=128, logz=-111.40, remainder_fraction=100.0000%, Lmin=-99.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10112, ncalls=28789, regioncalls=165406, ndraw=128, logz=-111.19, remainder_fraction=100.0000%, Lmin=-99.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10144, ncalls=28789, regioncalls=165406, ndraw=128, logz=-108.74, remainder_fraction=100.0000%, Lmin=-96.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10176, ncalls=28789, regioncalls=165406, ndraw=128, logz=-106.42, remainder_fraction=100.0000%, Lmin=-94.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10184, ncalls=28789, regioncalls=165406, ndraw=128, logz=-105.91, remainder_fraction=100.0000%, Lmin=-94.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=28789, regioncalls=165406, ndraw=128, logz=-104.53, remainder_fraction=100.0000%, Lmin=-92.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10234, ncalls=28917, regioncalls=165662, ndraw=128, logz=-103.06, remainder_fraction=100.0000%, Lmin=-91.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10272, ncalls=28917, regioncalls=165662, ndraw=128, logz=-100.84, remainder_fraction=100.0000%, Lmin=-88.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10394, ncalls=28917, regioncalls=165662, ndraw=128, logz=-93.77, remainder_fraction=100.0000%, Lmin=-81.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10400, ncalls=28917, regioncalls=165662, ndraw=128, logz=-93.44, remainder_fraction=100.0000%, Lmin=-81.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10432, ncalls=29045, regioncalls=165790, ndraw=128, logz=-91.47, remainder_fraction=100.0000%, Lmin=-79.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10464, ncalls=29045, regioncalls=165790, ndraw=128, logz=-89.60, remainder_fraction=100.0000%, Lmin=-77.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10528, ncalls=29045, regioncalls=165790, ndraw=128, logz=-85.83, remainder_fraction=100.0000%, Lmin=-73.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10540, ncalls=29045, regioncalls=165790, ndraw=128, logz=-85.25, remainder_fraction=100.0000%, Lmin=-73.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10560, ncalls=29045, regioncalls=165790, ndraw=128, logz=-84.28, remainder_fraction=100.0000%, Lmin=-72.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10592, ncalls=29173, regioncalls=166046, ndraw=128, logz=-82.82, remainder_fraction=100.0000%, Lmin=-71.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10626, ncalls=29173, regioncalls=166046, ndraw=128, logz=-81.34, remainder_fraction=100.0000%, Lmin=-69.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10656, ncalls=29173, regioncalls=166046, ndraw=128, logz=-79.88, remainder_fraction=100.0000%, Lmin=-67.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10673, ncalls=29173, regioncalls=166046, ndraw=128, logz=-79.07, remainder_fraction=100.0000%, Lmin=-66.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10688, ncalls=29173, regioncalls=166046, ndraw=128, logz=-78.31, remainder_fraction=100.0000%, Lmin=-66.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10747, ncalls=29173, regioncalls=166046, ndraw=128, logz=-75.88, remainder_fraction=100.0000%, Lmin=-63.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=29173, regioncalls=166046, ndraw=128, logz=-75.66, remainder_fraction=100.0000%, Lmin=-63.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10787, ncalls=29301, regioncalls=166302, ndraw=128, logz=-74.31, remainder_fraction=100.0000%, Lmin=-62.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10816, ncalls=29301, regioncalls=166302, ndraw=128, logz=-72.98, remainder_fraction=100.0000%, Lmin=-60.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10848, ncalls=29301, regioncalls=166302, ndraw=128, logz=-71.50, remainder_fraction=100.0000%, Lmin=-59.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10944, ncalls=29301, regioncalls=166302, ndraw=128, logz=-68.01, remainder_fraction=100.0000%, Lmin=-55.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10962, ncalls=29301, regioncalls=166302, ndraw=128, logz=-67.19, remainder_fraction=100.0000%, Lmin=-55.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10976, ncalls=29301, regioncalls=166302, ndraw=128, logz=-66.60, remainder_fraction=100.0000%, Lmin=-54.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11008, ncalls=29429, regioncalls=166558, ndraw=128, logz=-65.27, remainder_fraction=100.0000%, Lmin=-53.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11040, ncalls=29429, regioncalls=166558, ndraw=128, logz=-63.96, remainder_fraction=100.0000%, Lmin=-51.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11060, ncalls=29429, regioncalls=166558, ndraw=128, logz=-63.12, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11100, ncalls=29429, regioncalls=166558, ndraw=128, logz=-61.42, remainder_fraction=100.0000%, Lmin=-49.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11104, ncalls=29429, regioncalls=166558, ndraw=128, logz=-61.24, remainder_fraction=100.0000%, Lmin=-48.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11136, ncalls=29429, regioncalls=166558, ndraw=128, logz=-59.96, remainder_fraction=100.0000%, Lmin=-47.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11156, ncalls=29429, regioncalls=166558, ndraw=128, logz=-59.09, remainder_fraction=100.0000%, Lmin=-46.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11168, ncalls=29429, regioncalls=166558, ndraw=128, logz=-58.66, remainder_fraction=100.0000%, Lmin=-46.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11176, ncalls=29429, regioncalls=166558, ndraw=128, logz=-58.37, remainder_fraction=100.0000%, Lmin=-46.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11196, ncalls=29429, regioncalls=166558, ndraw=128, logz=-57.68, remainder_fraction=100.0000%, Lmin=-45.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11200, ncalls=29429, regioncalls=166558, ndraw=128, logz=-57.56, remainder_fraction=100.0000%, Lmin=-45.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11264, ncalls=29557, regioncalls=166814, ndraw=128, logz=-55.42, remainder_fraction=100.0000%, Lmin=-43.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11328, ncalls=29557, regioncalls=166814, ndraw=128, logz=-53.39, remainder_fraction=100.0000%, Lmin=-41.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11383, ncalls=29557, regioncalls=166814, ndraw=128, logz=-51.59, remainder_fraction=100.0000%, Lmin=-39.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11422, ncalls=29685, regioncalls=167454, ndraw=128, logz=-50.36, remainder_fraction=100.0000%, Lmin=-38.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11424, ncalls=29685, regioncalls=167454, ndraw=128, logz=-50.30, remainder_fraction=100.0000%, Lmin=-38.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11447, ncalls=29685, regioncalls=167454, ndraw=128, logz=-49.59, remainder_fraction=100.0000%, Lmin=-37.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11459, ncalls=29685, regioncalls=167454, ndraw=128, logz=-49.20, remainder_fraction=100.0000%, Lmin=-37.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11488, ncalls=29685, regioncalls=167454, ndraw=128, logz=-48.34, remainder_fraction=100.0000%, Lmin=-36.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11552, ncalls=29685, regioncalls=167454, ndraw=128, logz=-46.64, remainder_fraction=100.0000%, Lmin=-34.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11588, ncalls=29685, regioncalls=167454, ndraw=128, logz=-45.87, remainder_fraction=100.0000%, Lmin=-34.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11616, ncalls=29813, regioncalls=167838, ndraw=128, logz=-45.17, remainder_fraction=100.0000%, Lmin=-33.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11648, ncalls=29813, regioncalls=167838, ndraw=128, logz=-44.43, remainder_fraction=100.0000%, Lmin=-32.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11677, ncalls=29813, regioncalls=167838, ndraw=128, logz=-43.83, remainder_fraction=100.0000%, Lmin=-31.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11680, ncalls=29813, regioncalls=167838, ndraw=128, logz=-43.77, remainder_fraction=100.0000%, Lmin=-31.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11744, ncalls=29813, regioncalls=167838, ndraw=128, logz=-42.38, remainder_fraction=100.0000%, Lmin=-30.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11843, ncalls=29941, regioncalls=168094, ndraw=128, logz=-40.02, remainder_fraction=100.0000%, Lmin=-27.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11866, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.46, remainder_fraction=100.0000%, Lmin=-27.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11872, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.32, remainder_fraction=100.0000%, Lmin=-27.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11886, ncalls=29941, regioncalls=168094, ndraw=128, logz=-39.01, remainder_fraction=100.0000%, Lmin=-26.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11927, ncalls=29941, regioncalls=168094, ndraw=128, logz=-38.11, remainder_fraction=100.0000%, Lmin=-26.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11936, ncalls=29941, regioncalls=168094, ndraw=128, logz=-37.92, remainder_fraction=100.0000%, Lmin=-25.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11952, ncalls=29941, regioncalls=168094, ndraw=128, logz=-37.60, remainder_fraction=100.0000%, Lmin=-25.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11995, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.79, remainder_fraction=100.0000%, Lmin=-24.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12000, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.70, remainder_fraction=100.0000%, Lmin=-24.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12007, ncalls=30069, regioncalls=168350, ndraw=128, logz=-36.56, remainder_fraction=100.0000%, Lmin=-24.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12051, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.82, remainder_fraction=100.0000%, Lmin=-23.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12086, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.28, remainder_fraction=100.0000%, Lmin=-23.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12096, ncalls=30069, regioncalls=168350, ndraw=128, logz=-35.12, remainder_fraction=100.0000%, Lmin=-23.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12128, ncalls=30069, regioncalls=168350, ndraw=128, logz=-34.55, remainder_fraction=100.0000%, Lmin=-22.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12169, ncalls=30069, regioncalls=168350, ndraw=128, logz=-33.82, remainder_fraction=100.0000%, Lmin=-21.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12192, ncalls=30069, regioncalls=168350, ndraw=128, logz=-33.46, remainder_fraction=100.0000%, Lmin=-21.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12203, ncalls=30197, regioncalls=168734, ndraw=128, logz=-33.31, remainder_fraction=100.0000%, Lmin=-21.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12240, ncalls=30197, regioncalls=168734, ndraw=128, logz=-32.75, remainder_fraction=100.0000%, Lmin=-20.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12288, ncalls=30197, regioncalls=168734, ndraw=128, logz=-32.03, remainder_fraction=100.0000%, Lmin=-20.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12320, ncalls=30197, regioncalls=168734, ndraw=128, logz=-31.54, remainder_fraction=100.0000%, Lmin=-19.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12352, ncalls=30197, regioncalls=168734, ndraw=128, logz=-31.06, remainder_fraction=100.0000%, Lmin=-19.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12384, ncalls=30197, regioncalls=168734, ndraw=128, logz=-30.60, remainder_fraction=100.0000%, Lmin=-18.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12418, ncalls=30325, regioncalls=169118, ndraw=128, logz=-30.13, remainder_fraction=100.0000%, Lmin=-18.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12448, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.74, remainder_fraction=100.0000%, Lmin=-17.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12482, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.30, remainder_fraction=100.0000%, Lmin=-17.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12502, ncalls=30325, regioncalls=169118, ndraw=128, logz=-29.06, remainder_fraction=100.0000%, Lmin=-17.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12514, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.93, remainder_fraction=100.0000%, Lmin=-17.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12569, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.32, remainder_fraction=100.0000%, Lmin=-16.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12576, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.25, remainder_fraction=100.0000%, Lmin=-16.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12593, ncalls=30325, regioncalls=169118, ndraw=128, logz=-28.07, remainder_fraction=100.0000%, Lmin=-16.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12604, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.94, remainder_fraction=100.0000%, Lmin=-15.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12613, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.84, remainder_fraction=100.0000%, Lmin=-15.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12628, ncalls=30453, regioncalls=169374, ndraw=128, logz=-27.68, remainder_fraction=100.0000%, Lmin=-15.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12703, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.81, remainder_fraction=100.0000%, Lmin=-14.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12729, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.53, remainder_fraction=99.9999%, Lmin=-14.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12736, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.46, remainder_fraction=99.9999%, Lmin=-14.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12768, ncalls=30453, regioncalls=169374, ndraw=128, logz=-26.12, remainder_fraction=99.9999%, Lmin=-14.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12800, ncalls=30453, regioncalls=169374, ndraw=128, logz=-25.79, remainder_fraction=99.9999%, Lmin=-13.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12833, ncalls=30581, regioncalls=169630, ndraw=128, logz=-25.48, remainder_fraction=99.9999%, Lmin=-13.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12842, ncalls=30581, regioncalls=169630, ndraw=128, logz=-25.40, remainder_fraction=99.9998%, Lmin=-13.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12896, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.92, remainder_fraction=99.9997%, Lmin=-12.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12920, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.69, remainder_fraction=99.9997%, Lmin=-12.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12928, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.62, remainder_fraction=99.9997%, Lmin=-12.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12953, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.37, remainder_fraction=99.9996%, Lmin=-12.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12960, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.30, remainder_fraction=99.9995%, Lmin=-12.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12985, ncalls=30581, regioncalls=169630, ndraw=128, logz=-24.05, remainder_fraction=99.9994%, Lmin=-11.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12992, ncalls=30581, regioncalls=169630, ndraw=128, logz=-23.98, remainder_fraction=99.9994%, Lmin=-11.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13024, ncalls=30581, regioncalls=169630, ndraw=128, logz=-23.68, remainder_fraction=99.9991%, Lmin=-11.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13058, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.38, remainder_fraction=99.9988%, Lmin=-11.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13066, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.31, remainder_fraction=99.9988%, Lmin=-11.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13079, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.21, remainder_fraction=99.9986%, Lmin=-11.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13088, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.13, remainder_fraction=99.9985%, Lmin=-11.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13092, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.10, remainder_fraction=99.9985%, Lmin=-11.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13099, ncalls=30709, regioncalls=170014, ndraw=128, logz=-23.04, remainder_fraction=99.9984%, Lmin=-11.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13120, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.88, remainder_fraction=99.9981%, Lmin=-10.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13144, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.70, remainder_fraction=99.9977%, Lmin=-10.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13179, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.43, remainder_fraction=99.9970%, Lmin=-10.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13184, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.39, remainder_fraction=99.9969%, Lmin=-10.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13209, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.20, remainder_fraction=99.9962%, Lmin=-10.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13216, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.15, remainder_fraction=99.9960%, Lmin=-10.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13226, ncalls=30709, regioncalls=170014, ndraw=128, logz=-22.07, remainder_fraction=99.9957%, Lmin=-10.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13344, ncalls=30837, regioncalls=170654, ndraw=128, logz=-21.19, remainder_fraction=99.9894%, Lmin=-9.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13353, ncalls=30837, regioncalls=170654, ndraw=128, logz=-21.13, remainder_fraction=99.9888%, Lmin=-9.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13481, ncalls=30965, regioncalls=171166, ndraw=128, logz=-20.27, remainder_fraction=99.9738%, Lmin=-8.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13536, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.95, remainder_fraction=99.9640%, Lmin=-7.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13600, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.57, remainder_fraction=99.9469%, Lmin=-7.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13632, ncalls=30965, regioncalls=171166, ndraw=128, logz=-19.39, remainder_fraction=99.9355%, Lmin=-7.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13662, ncalls=31093, regioncalls=171294, ndraw=128, logz=-19.22, remainder_fraction=99.9236%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13728, ncalls=31093, regioncalls=171294, ndraw=128, logz=-18.89, remainder_fraction=99.8927%, Lmin=-6.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13760, ncalls=31093, regioncalls=171294, ndraw=128, logz=-18.74, remainder_fraction=99.8758%, Lmin=-6.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13856, ncalls=31221, regioncalls=171550, ndraw=128, logz=-18.30, remainder_fraction=99.8078%, Lmin=-6.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13888, ncalls=31221, regioncalls=171550, ndraw=128, logz=-18.16, remainder_fraction=99.7779%, Lmin=-6.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13952, ncalls=31221, regioncalls=171550, ndraw=128, logz=-17.90, remainder_fraction=99.7167%, Lmin=-6.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13970, ncalls=31221, regioncalls=171550, ndraw=128, logz=-17.83, remainder_fraction=99.6980%, Lmin=-5.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14048, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.55, remainder_fraction=99.5963%, Lmin=-5.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14080, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.44, remainder_fraction=99.5485%, Lmin=-5.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14112, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.33, remainder_fraction=99.4927%, Lmin=-5.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14144, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.21, remainder_fraction=99.4301%, Lmin=-5.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14176, ncalls=31349, regioncalls=171806, ndraw=128, logz=-17.10, remainder_fraction=99.3623%, Lmin=-5.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14208, ncalls=31349, regioncalls=171806, ndraw=128, logz=-16.99, remainder_fraction=99.2870%, Lmin=-5.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14240, ncalls=31349, regioncalls=171806, ndraw=128, logz=-16.88, remainder_fraction=99.2082%, Lmin=-4.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14272, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.77, remainder_fraction=99.1149%, Lmin=-4.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14276, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.76, remainder_fraction=99.1039%, Lmin=-4.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14304, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.66, remainder_fraction=99.0229%, Lmin=-4.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14368, ncalls=31477, regioncalls=171934, ndraw=128, logz=-16.46, remainder_fraction=98.8110%, Lmin=-4.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14432, ncalls=31605, regioncalls=172190, ndraw=128, logz=-16.26, remainder_fraction=98.5695%, Lmin=-4.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14496, ncalls=31605, regioncalls=172190, ndraw=128, logz=-16.07, remainder_fraction=98.2861%, Lmin=-4.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14560, ncalls=31605, regioncalls=172190, ndraw=128, logz=-15.89, remainder_fraction=97.9366%, Lmin=-3.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14588, ncalls=31605, regioncalls=172190, ndraw=128, logz=-15.81, remainder_fraction=97.7613%, Lmin=-3.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14705, ncalls=31733, regioncalls=172446, ndraw=128, logz=-15.50, remainder_fraction=96.9303%, Lmin=-3.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14752, ncalls=31733, regioncalls=172446, ndraw=128, logz=-15.38, remainder_fraction=96.5398%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14816, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.23, remainder_fraction=95.9618%, Lmin=-3.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14848, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.15, remainder_fraction=95.6535%, Lmin=-3.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14896, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.04, remainder_fraction=95.1340%, Lmin=-3.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14912, ncalls=31861, regioncalls=172574, ndraw=128, logz=-15.00, remainder_fraction=94.9467%, Lmin=-2.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15024, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.77, remainder_fraction=93.6492%, Lmin=-2.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15040, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.73, remainder_fraction=93.4331%, Lmin=-2.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15072, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.67, remainder_fraction=92.9778%, Lmin=-2.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15168, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.48, remainder_fraction=91.5894%, Lmin=-2.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15200, ncalls=31989, regioncalls=172830, ndraw=128, logz=-14.42, remainder_fraction=91.1171%, Lmin=-2.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15202, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.42, remainder_fraction=91.0756%, Lmin=-2.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15232, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.36, remainder_fraction=90.5477%, Lmin=-2.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15296, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.25, remainder_fraction=89.4125%, Lmin=-2.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15328, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.20, remainder_fraction=88.8292%, Lmin=-2.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15392, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.10, remainder_fraction=87.6337%, Lmin=-2.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15424, ncalls=32117, regioncalls=173342, ndraw=128, logz=-14.05, remainder_fraction=86.9769%, Lmin=-2.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15488, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.95, remainder_fraction=85.7444%, Lmin=-1.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15509, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.92, remainder_fraction=85.3009%, Lmin=-1.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15552, ncalls=32245, regioncalls=173470, ndraw=128, logz=-13.86, remainder_fraction=84.3630%, Lmin=-1.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15616, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.77, remainder_fraction=82.9456%, Lmin=-1.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15648, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.73, remainder_fraction=82.2809%, Lmin=-1.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15680, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.69, remainder_fraction=81.5293%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15744, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.61, remainder_fraction=79.9864%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15776, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.57, remainder_fraction=79.2454%, Lmin=-1.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15808, ncalls=32373, regioncalls=173854, ndraw=128, logz=-13.54, remainder_fraction=78.4365%, Lmin=-1.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15815, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.53, remainder_fraction=78.2577%, Lmin=-1.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15840, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.50, remainder_fraction=77.6266%, Lmin=-1.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15961, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.37, remainder_fraction=74.5275%, Lmin=-1.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15968, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.37, remainder_fraction=74.3480%, Lmin=-1.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16000, ncalls=32501, regioncalls=174110, ndraw=128, logz=-13.33, remainder_fraction=73.4918%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16032, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.30, remainder_fraction=72.6490%, Lmin=-1.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16064, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.27, remainder_fraction=71.8195%, Lmin=-1.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16125, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.22, remainder_fraction=70.2286%, Lmin=-1.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16160, ncalls=32629, regioncalls=174238, ndraw=128, logz=-13.19, remainder_fraction=69.2902%, Lmin=-1.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16192, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.16, remainder_fraction=68.4339%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16224, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.13, remainder_fraction=67.5848%, Lmin=-1.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16288, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.08, remainder_fraction=65.8040%, Lmin=-1.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16320, ncalls=32757, regioncalls=174750, ndraw=128, logz=-13.06, remainder_fraction=64.9519%, Lmin=-1.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16416, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.99, remainder_fraction=62.4237%, Lmin=-1.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16432, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.98, remainder_fraction=62.0156%, Lmin=-1.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16448, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.97, remainder_fraction=61.6200%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16480, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.94, remainder_fraction=60.7711%, Lmin=-0.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16544, ncalls=32885, regioncalls=174878, ndraw=128, logz=-12.90, remainder_fraction=59.1170%, Lmin=-0.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16608, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.86, remainder_fraction=57.5043%, Lmin=-0.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16640, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.84, remainder_fraction=56.7107%, Lmin=-0.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16704, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.80, remainder_fraction=55.0321%, Lmin=-0.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16736, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.79, remainder_fraction=54.1889%, Lmin=-0.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16738, ncalls=33013, regioncalls=175134, ndraw=128, logz=-12.78, remainder_fraction=54.1322%, Lmin=-0.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16768, ncalls=33141, regioncalls=175902, ndraw=128, logz=-12.77, remainder_fraction=53.3550%, Lmin=-0.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16886, ncalls=33141, regioncalls=175902, ndraw=128, logz=-12.70, remainder_fraction=50.3625%, Lmin=-0.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17006, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.65, remainder_fraction=47.3600%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17050, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.63, remainder_fraction=46.2865%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17056, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.62, remainder_fraction=46.1478%, Lmin=-0.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17088, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.61, remainder_fraction=45.4016%, Lmin=-0.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17120, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.60, remainder_fraction=44.6083%, Lmin=-0.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17152, ncalls=33269, regioncalls=176030, ndraw=128, logz=-12.58, remainder_fraction=43.8488%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17184, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.57, remainder_fraction=43.0946%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17280, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.53, remainder_fraction=40.8473%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17312, ncalls=33397, regioncalls=176286, ndraw=128, logz=-12.52, remainder_fraction=40.1255%, Lmin=-0.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17356, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.50, remainder_fraction=39.1477%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17376, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.50, remainder_fraction=38.7014%, Lmin=-0.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17440, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.47, remainder_fraction=37.3232%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17472, ncalls=33525, regioncalls=176414, ndraw=128, logz=-12.46, remainder_fraction=36.6385%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17581, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.43, remainder_fraction=34.3693%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17662, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.40, remainder_fraction=32.8077%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17696, ncalls=33653, regioncalls=176670, ndraw=128, logz=-12.39, remainder_fraction=32.1684%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17728, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.39, remainder_fraction=31.5693%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17760, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.38, remainder_fraction=30.9612%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17879, ncalls=33781, regioncalls=176926, ndraw=128, logz=-12.35, remainder_fraction=28.8293%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17920, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.34, remainder_fraction=28.1267%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17952, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.33, remainder_fraction=27.5866%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17969, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.32, remainder_fraction=27.3085%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18016, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.31, remainder_fraction=26.5279%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18048, ncalls=33909, regioncalls=177054, ndraw=128, logz=-12.31, remainder_fraction=26.0012%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18112, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.29, remainder_fraction=24.9766%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18230, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.27, remainder_fraction=23.1682%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18272, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.26, remainder_fraction=22.5599%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18275, ncalls=34037, regioncalls=177438, ndraw=128, logz=-12.26, remainder_fraction=22.5161%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18336, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.25, remainder_fraction=21.6519%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18368, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.24, remainder_fraction=21.2109%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18400, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.24, remainder_fraction=20.7765%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18464, ncalls=34165, regioncalls=177694, ndraw=128, logz=-12.23, remainder_fraction=19.9299%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18496, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.22, remainder_fraction=19.5189%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18528, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.22, remainder_fraction=19.1186%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18560, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.21, remainder_fraction=18.7184%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18584, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.21, remainder_fraction=18.4228%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18624, ncalls=34293, regioncalls=177822, ndraw=128, logz=-12.20, remainder_fraction=17.9469%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18656, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.20, remainder_fraction=17.5753%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18688, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.19, remainder_fraction=17.2030%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18720, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.19, remainder_fraction=16.8438%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18832, ncalls=34421, regioncalls=178334, ndraw=128, logz=-12.18, remainder_fraction=15.6344%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18890, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.17, remainder_fraction=15.0390%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18912, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.17, remainder_fraction=14.8187%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18976, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.16, remainder_fraction=14.1902%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19008, ncalls=34549, regioncalls=178462, ndraw=128, logz=-12.15, remainder_fraction=13.8858%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19072, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.15, remainder_fraction=13.2906%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19136, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.7235%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19168, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.4516%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19198, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.1981%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19200, ncalls=34677, regioncalls=178718, ndraw=128, logz=-12.14, remainder_fraction=12.1819%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19232, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.13, remainder_fraction=11.9162%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19264, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.13, remainder_fraction=11.6587%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19360, ncalls=34805, regioncalls=178974, ndraw=128, logz=-12.12, remainder_fraction=10.9125%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19456, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.11, remainder_fraction=10.2129%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19505, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.11, remainder_fraction=9.8736%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19621, ncalls=34933, regioncalls=179102, ndraw=128, logz=-12.10, remainder_fraction=9.1127%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19743, ncalls=35061, regioncalls=179486, ndraw=128, logz=-12.09, remainder_fraction=8.3702%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19744, ncalls=35061, regioncalls=179486, ndraw=128, logz=-12.09, remainder_fraction=8.3643%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19811, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.09, remainder_fraction=7.9789%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19872, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.6438%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19904, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.4733%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19936, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.3070%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19968, ncalls=35189, regioncalls=179614, ndraw=128, logz=-12.08, remainder_fraction=7.1451%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20032, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.08, remainder_fraction=6.8310%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20096, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.5276%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20117, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.4312%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20128, ncalls=35317, regioncalls=179998, ndraw=128, logz=-12.07, remainder_fraction=6.3814%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20247, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.07, remainder_fraction=5.8657%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20288, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.06, remainder_fraction=5.6980%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20320, ncalls=35445, regioncalls=180382, ndraw=128, logz=-12.06, remainder_fraction=5.5698%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20384, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.3221%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20416, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.2017%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20423, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=5.1758%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20480, ncalls=35573, regioncalls=180510, ndraw=128, logz=-12.06, remainder_fraction=4.9705%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20544, ncalls=35701, regioncalls=180766, ndraw=128, logz=-12.05, remainder_fraction=4.7491%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20640, ncalls=35701, regioncalls=180766, ndraw=128, logz=-12.05, remainder_fraction=4.4352%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20704, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.2361%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20729, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.1609%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20736, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.1401%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20768, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.05, remainder_fraction=4.0464%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20832, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.04, remainder_fraction=3.8647%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20864, ncalls=35829, regioncalls=180894, ndraw=128, logz=-12.04, remainder_fraction=3.7770%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20896, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.6915%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20960, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.5256%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20992, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.4453%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21024, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.3671%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21035, ncalls=35957, regioncalls=181150, ndraw=128, logz=-12.04, remainder_fraction=3.3406%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21120, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=3.1425%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21152, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=3.0710%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21216, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.04, remainder_fraction=2.9326%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21280, ncalls=36085, regioncalls=181662, ndraw=128, logz=-12.03, remainder_fraction=2.8003%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21341, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.6795%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21376, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.6127%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21408, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.5530%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21440, ncalls=36213, regioncalls=181790, ndraw=128, logz=-12.03, remainder_fraction=2.4947%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21536, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.3277%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21600, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.2224%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21632, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.1715%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21647, ncalls=36341, regioncalls=182046, ndraw=128, logz=-12.03, remainder_fraction=2.1481%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21696, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.03, remainder_fraction=2.0733%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21813, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.9049%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21824, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.8897%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21856, ncalls=36469, regioncalls=182430, ndraw=128, logz=-12.02, remainder_fraction=1.8464%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21888, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.8040%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21920, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7627%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21952, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7222%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21954, ncalls=36597, regioncalls=182558, ndraw=128, logz=-12.02, remainder_fraction=1.7197%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22073, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5775%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22080, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5695%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22112, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.5335%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22176, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.4639%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22208, ncalls=36725, regioncalls=183454, ndraw=128, logz=-12.02, remainder_fraction=1.4302%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22262, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.3753%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22304, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.3339%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22368, ncalls=36853, regioncalls=183582, ndraw=128, logz=-12.02, remainder_fraction=1.2733%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22400, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.2440%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22516, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1433%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22560, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1073%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22568, ncalls=36981, regioncalls=183838, ndraw=128, logz=-12.02, remainder_fraction=1.1009%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22624, ncalls=37109, regioncalls=184094, ndraw=128, logz=-12.02, remainder_fraction=1.0569%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22688, ncalls=37109, regioncalls=184094, ndraw=128, logz=-12.02, remainder_fraction=1.0089%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 37109 INFO ultranest:integrator.py:2697 logZ = -12.01 +- 0.08472 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 5474.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.04 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1572 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (22399/23859 iterations) have 1365 DEBUG ultranest:integrator.py:1663 at least 1540 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 1540 minimum live points (dlogz from 0.07 to 0.16, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.17 bs:0.08 tail:0.01 total:0.08 required:<0.10 INFO ultranest:integrator.py:1393 Widening roots to 1540 live points (have 1367 already) ... INFO ultranest:integrator.py:1433 Sampling 173 live points from prior ... DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 1540.0), (inf, 1540.0)] DEBUG ultranest:integrator.py:2610 iteration=3, ncalls=37410, regioncalls=184222, ndraw=128, logz=-239552.19, remainder_fraction=100.0000%, Lmin=-238281.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=96, ncalls=37410, regioncalls=184222, ndraw=128, logz=-173988.29, remainder_fraction=100.0000%, Lmin=-173835.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=284, ncalls=37410, regioncalls=184222, ndraw=128, logz=-133092.16, remainder_fraction=100.0000%, Lmin=-133000.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=351, ncalls=37410, regioncalls=184222, ndraw=128, logz=-124631.01, remainder_fraction=100.0000%, Lmin=-124520.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=37410, regioncalls=184222, ndraw=128, logz=-107627.17, remainder_fraction=100.0000%, Lmin=-107602.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=37410, regioncalls=184222, ndraw=128, logz=-96420.06, remainder_fraction=100.0000%, Lmin=-96392.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=901, ncalls=37489, regioncalls=184350, ndraw=128, logz=-86398.70, remainder_fraction=100.0000%, Lmin=-86298.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=37489, regioncalls=184350, ndraw=128, logz=-79505.33, remainder_fraction=100.0000%, Lmin=-79393.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=37489, regioncalls=184350, ndraw=128, logz=-70723.83, remainder_fraction=100.0000%, Lmin=-70710.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1405, ncalls=37555, regioncalls=184478, ndraw=128, logz=-63768.33, remainder_fraction=100.0000%, Lmin=-63731.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1585, ncalls=37555, regioncalls=184478, ndraw=128, logz=-56835.78, remainder_fraction=100.0000%, Lmin=-56823.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1664, ncalls=37555, regioncalls=184478, ndraw=128, logz=-54185.44, remainder_fraction=100.0000%, Lmin=-54153.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=37608, regioncalls=184606, ndraw=128, logz=-51386.89, remainder_fraction=100.0000%, Lmin=-51264.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=37608, regioncalls=184606, ndraw=128, logz=-44798.94, remainder_fraction=100.0000%, Lmin=-44760.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=37648, regioncalls=184734, ndraw=128, logz=-40813.38, remainder_fraction=100.0000%, Lmin=-40791.72, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=37690, regioncalls=184862, ndraw=128, logz=-36953.24, remainder_fraction=100.0000%, Lmin=-36939.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2470, ncalls=37690, regioncalls=184862, ndraw=128, logz=-32240.95, remainder_fraction=100.0000%, Lmin=-32213.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2661, ncalls=37715, regioncalls=184990, ndraw=128, logz=-28632.75, remainder_fraction=100.0000%, Lmin=-28561.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2814, ncalls=37740, regioncalls=185118, ndraw=128, logz=-25654.65, remainder_fraction=100.0000%, Lmin=-25635.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=37740, regioncalls=185118, ndraw=128, logz=-25635.91, remainder_fraction=100.0000%, Lmin=-25623.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2912, ncalls=37759, regioncalls=185246, ndraw=128, logz=-23981.67, remainder_fraction=100.0000%, Lmin=-23963.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3008, ncalls=37783, regioncalls=185374, ndraw=128, logz=-22378.23, remainder_fraction=100.0000%, Lmin=-22366.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=37783, regioncalls=185374, ndraw=128, logz=-22028.21, remainder_fraction=100.0000%, Lmin=-22007.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=37808, regioncalls=185502, ndraw=128, logz=-20442.70, remainder_fraction=100.0000%, Lmin=-20426.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=37829, regioncalls=185630, ndraw=128, logz=-17754.62, remainder_fraction=100.0000%, Lmin=-17736.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3529, ncalls=37847, regioncalls=185758, ndraw=128, logz=-15901.51, remainder_fraction=100.0000%, Lmin=-15887.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3715, ncalls=37862, regioncalls=185886, ndraw=128, logz=-14039.63, remainder_fraction=100.0000%, Lmin=-14029.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=37877, regioncalls=186014, ndraw=128, logz=-12807.13, remainder_fraction=100.0000%, Lmin=-12795.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3876, ncalls=37885, regioncalls=186142, ndraw=128, logz=-12574.92, remainder_fraction=100.0000%, Lmin=-12559.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3936, ncalls=37893, regioncalls=186270, ndraw=128, logz=-12144.28, remainder_fraction=100.0000%, Lmin=-12127.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4096, ncalls=37914, regioncalls=186398, ndraw=128, logz=-10989.99, remainder_fraction=100.0000%, Lmin=-10975.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4231, ncalls=37929, regioncalls=186526, ndraw=128, logz=-10144.50, remainder_fraction=100.0000%, Lmin=-10132.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4352, ncalls=37957, regioncalls=186910, ndraw=128, logz=-9343.82, remainder_fraction=100.0000%, Lmin=-9327.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4512, ncalls=37981, regioncalls=187294, ndraw=128, logz=-8430.92, remainder_fraction=100.0000%, Lmin=-8414.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4576, ncalls=37993, regioncalls=187422, ndraw=128, logz=-8123.95, remainder_fraction=100.0000%, Lmin=-8113.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4756, ncalls=38028, regioncalls=187934, ndraw=128, logz=-7196.05, remainder_fraction=100.0000%, Lmin=-7180.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4922, ncalls=38045, regioncalls=188318, ndraw=128, logz=-6485.35, remainder_fraction=100.0000%, Lmin=-6474.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5103, ncalls=38067, regioncalls=188702, ndraw=128, logz=-5765.25, remainder_fraction=100.0000%, Lmin=-5748.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5269, ncalls=38085, regioncalls=189342, ndraw=128, logz=-5099.27, remainder_fraction=100.0000%, Lmin=-5086.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=38085, regioncalls=189342, ndraw=128, logz=-5060.95, remainder_fraction=100.0000%, Lmin=-5045.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5466, ncalls=38106, regioncalls=189854, ndraw=128, logz=-4514.48, remainder_fraction=100.0000%, Lmin=-4502.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5634, ncalls=38129, regioncalls=190622, ndraw=128, logz=-4072.94, remainder_fraction=100.0000%, Lmin=-4061.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5819, ncalls=38146, regioncalls=191262, ndraw=128, logz=-3596.91, remainder_fraction=100.0000%, Lmin=-3584.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5983, ncalls=38165, regioncalls=192030, ndraw=128, logz=-3272.55, remainder_fraction=100.0000%, Lmin=-3260.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6048, ncalls=38177, regioncalls=192414, ndraw=128, logz=-3147.20, remainder_fraction=100.0000%, Lmin=-3135.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6241, ncalls=38203, regioncalls=193310, ndraw=128, logz=-2762.69, remainder_fraction=100.0000%, Lmin=-2751.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6327, ncalls=38220, regioncalls=193694, ndraw=128, logz=-2629.08, remainder_fraction=100.0000%, Lmin=-2618.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6464, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2380.46, remainder_fraction=100.0000%, Lmin=-2367.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6624, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2144.78, remainder_fraction=100.0000%, Lmin=-2132.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6676, ncalls=38359, regioncalls=194846, ndraw=128, logz=-2088.96, remainder_fraction=100.0000%, Lmin=-2076.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6784, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1955.11, remainder_fraction=100.0000%, Lmin=-1941.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1815.59, remainder_fraction=100.0000%, Lmin=-1804.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7020, ncalls=38359, regioncalls=194846, ndraw=128, logz=-1655.30, remainder_fraction=100.0000%, Lmin=-1643.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7201, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1475.64, remainder_fraction=100.0000%, Lmin=-1463.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7328, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1365.72, remainder_fraction=100.0000%, Lmin=-1353.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7366, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1332.19, remainder_fraction=100.0000%, Lmin=-1319.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7392, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1308.19, remainder_fraction=100.0000%, Lmin=-1296.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7488, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1242.10, remainder_fraction=100.0000%, Lmin=-1230.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7515, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1217.30, remainder_fraction=100.0000%, Lmin=-1205.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7706, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1080.47, remainder_fraction=100.0000%, Lmin=-1067.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7815, ncalls=38490, regioncalls=195230, ndraw=128, logz=-1007.59, remainder_fraction=100.0000%, Lmin=-995.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7872, ncalls=38490, regioncalls=195230, ndraw=128, logz=-970.25, remainder_fraction=100.0000%, Lmin=-957.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8080, ncalls=38620, regioncalls=195742, ndraw=128, logz=-855.79, remainder_fraction=100.0000%, Lmin=-842.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8159, ncalls=38620, regioncalls=195742, ndraw=128, logz=-807.82, remainder_fraction=100.0000%, Lmin=-796.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8348, ncalls=38620, regioncalls=195742, ndraw=128, logz=-724.70, remainder_fraction=100.0000%, Lmin=-712.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8503, ncalls=38620, regioncalls=195742, ndraw=128, logz=-658.07, remainder_fraction=100.0000%, Lmin=-646.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8698, ncalls=38620, regioncalls=195742, ndraw=128, logz=-586.95, remainder_fraction=100.0000%, Lmin=-575.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8832, ncalls=38620, regioncalls=195742, ndraw=128, logz=-537.89, remainder_fraction=100.0000%, Lmin=-524.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=8865, ncalls=38620, regioncalls=195742, ndraw=128, logz=-522.17, remainder_fraction=100.0000%, Lmin=-510.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9054, ncalls=38748, regioncalls=196126, ndraw=128, logz=-461.89, remainder_fraction=100.0000%, Lmin=-449.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9224, ncalls=38748, regioncalls=196126, ndraw=128, logz=-413.98, remainder_fraction=100.0000%, Lmin=-401.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9248, ncalls=38748, regioncalls=196126, ndraw=128, logz=-408.92, remainder_fraction=100.0000%, Lmin=-397.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9376, ncalls=38748, regioncalls=196126, ndraw=128, logz=-376.26, remainder_fraction=100.0000%, Lmin=-364.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9572, ncalls=38748, regioncalls=196126, ndraw=128, logz=-334.76, remainder_fraction=100.0000%, Lmin=-322.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9758, ncalls=38876, regioncalls=196382, ndraw=128, logz=-298.76, remainder_fraction=100.0000%, Lmin=-286.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9919, ncalls=38876, regioncalls=196382, ndraw=128, logz=-267.78, remainder_fraction=100.0000%, Lmin=-255.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=9984, ncalls=38876, regioncalls=196382, ndraw=128, logz=-256.46, remainder_fraction=100.0000%, Lmin=-244.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10080, ncalls=38876, regioncalls=196382, ndraw=128, logz=-239.70, remainder_fraction=100.0000%, Lmin=-227.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10125, ncalls=38876, regioncalls=196382, ndraw=128, logz=-233.28, remainder_fraction=100.0000%, Lmin=-221.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10208, ncalls=38876, regioncalls=196382, ndraw=128, logz=-220.01, remainder_fraction=100.0000%, Lmin=-208.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10401, ncalls=39004, regioncalls=196766, ndraw=128, logz=-196.41, remainder_fraction=100.0000%, Lmin=-184.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10471, ncalls=39004, regioncalls=196766, ndraw=128, logz=-188.68, remainder_fraction=100.0000%, Lmin=-176.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10536, ncalls=39004, regioncalls=196766, ndraw=128, logz=-182.37, remainder_fraction=100.0000%, Lmin=-170.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10725, ncalls=39004, regioncalls=196766, ndraw=128, logz=-163.77, remainder_fraction=100.0000%, Lmin=-151.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10752, ncalls=39004, regioncalls=196766, ndraw=128, logz=-161.56, remainder_fraction=100.0000%, Lmin=-150.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=10898, ncalls=39004, regioncalls=196766, ndraw=128, logz=-148.42, remainder_fraction=100.0000%, Lmin=-136.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11089, ncalls=39132, regioncalls=197022, ndraw=128, logz=-132.84, remainder_fraction=100.0000%, Lmin=-121.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11169, ncalls=39132, regioncalls=197022, ndraw=128, logz=-127.12, remainder_fraction=100.0000%, Lmin=-115.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11209, ncalls=39132, regioncalls=197022, ndraw=128, logz=-123.83, remainder_fraction=100.0000%, Lmin=-111.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11279, ncalls=39132, regioncalls=197022, ndraw=128, logz=-119.24, remainder_fraction=100.0000%, Lmin=-107.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11288, ncalls=39132, regioncalls=197022, ndraw=128, logz=-118.64, remainder_fraction=100.0000%, Lmin=-106.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11364, ncalls=39132, regioncalls=197022, ndraw=128, logz=-112.19, remainder_fraction=100.0000%, Lmin=-100.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11423, ncalls=39132, regioncalls=197022, ndraw=128, logz=-107.95, remainder_fraction=100.0000%, Lmin=-95.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11455, ncalls=39132, regioncalls=197022, ndraw=128, logz=-105.87, remainder_fraction=100.0000%, Lmin=-93.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11518, ncalls=39132, regioncalls=197022, ndraw=128, logz=-102.53, remainder_fraction=100.0000%, Lmin=-90.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11648, ncalls=39132, regioncalls=197022, ndraw=128, logz=-95.45, remainder_fraction=100.0000%, Lmin=-83.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11680, ncalls=39132, regioncalls=197022, ndraw=128, logz=-93.92, remainder_fraction=100.0000%, Lmin=-82.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11865, ncalls=39260, regioncalls=197278, ndraw=128, logz=-84.74, remainder_fraction=100.0000%, Lmin=-72.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11950, ncalls=39260, regioncalls=197278, ndraw=128, logz=-81.31, remainder_fraction=100.0000%, Lmin=-69.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=11999, ncalls=39260, regioncalls=197278, ndraw=128, logz=-79.19, remainder_fraction=100.0000%, Lmin=-67.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12094, ncalls=39260, regioncalls=197278, ndraw=128, logz=-75.61, remainder_fraction=100.0000%, Lmin=-63.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12133, ncalls=39260, regioncalls=197278, ndraw=128, logz=-74.26, remainder_fraction=100.0000%, Lmin=-62.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12321, ncalls=39260, regioncalls=197278, ndraw=128, logz=-67.29, remainder_fraction=100.0000%, Lmin=-55.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12384, ncalls=39260, regioncalls=197278, ndraw=128, logz=-64.95, remainder_fraction=100.0000%, Lmin=-52.79, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12437, ncalls=39260, regioncalls=197278, ndraw=128, logz=-63.04, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12480, ncalls=39388, regioncalls=197790, ndraw=128, logz=-61.55, remainder_fraction=100.0000%, Lmin=-49.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12488, ncalls=39388, regioncalls=197790, ndraw=128, logz=-61.26, remainder_fraction=100.0000%, Lmin=-49.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12512, ncalls=39388, regioncalls=197790, ndraw=128, logz=-60.46, remainder_fraction=100.0000%, Lmin=-48.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12554, ncalls=39388, regioncalls=197790, ndraw=128, logz=-59.03, remainder_fraction=100.0000%, Lmin=-46.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12578, ncalls=39388, regioncalls=197790, ndraw=128, logz=-58.29, remainder_fraction=100.0000%, Lmin=-46.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12606, ncalls=39388, regioncalls=197790, ndraw=128, logz=-57.44, remainder_fraction=100.0000%, Lmin=-45.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12640, ncalls=39388, regioncalls=197790, ndraw=128, logz=-56.44, remainder_fraction=100.0000%, Lmin=-44.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12672, ncalls=39388, regioncalls=197790, ndraw=128, logz=-55.48, remainder_fraction=100.0000%, Lmin=-43.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12828, ncalls=39388, regioncalls=197790, ndraw=128, logz=-51.09, remainder_fraction=100.0000%, Lmin=-38.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12852, ncalls=39388, regioncalls=197790, ndraw=128, logz=-50.41, remainder_fraction=100.0000%, Lmin=-38.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=12897, ncalls=39388, regioncalls=197790, ndraw=128, logz=-49.13, remainder_fraction=100.0000%, Lmin=-37.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13024, ncalls=39388, regioncalls=197790, ndraw=128, logz=-46.02, remainder_fraction=100.0000%, Lmin=-34.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13042, ncalls=39388, regioncalls=197790, ndraw=128, logz=-45.63, remainder_fraction=100.0000%, Lmin=-33.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13128, ncalls=39388, regioncalls=197790, ndraw=128, logz=-43.84, remainder_fraction=100.0000%, Lmin=-32.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13152, ncalls=39388, regioncalls=197790, ndraw=128, logz=-43.42, remainder_fraction=100.0000%, Lmin=-31.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13209, ncalls=39388, regioncalls=197790, ndraw=128, logz=-42.34, remainder_fraction=100.0000%, Lmin=-30.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13280, ncalls=39388, regioncalls=197790, ndraw=128, logz=-40.85, remainder_fraction=100.0000%, Lmin=-28.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13333, ncalls=39516, regioncalls=198046, ndraw=128, logz=-39.79, remainder_fraction=100.0000%, Lmin=-27.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13354, ncalls=39516, regioncalls=198046, ndraw=128, logz=-39.35, remainder_fraction=100.0000%, Lmin=-27.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13375, ncalls=39516, regioncalls=198046, ndraw=128, logz=-38.95, remainder_fraction=100.0000%, Lmin=-26.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13421, ncalls=39516, regioncalls=198046, ndraw=128, logz=-38.08, remainder_fraction=100.0000%, Lmin=-25.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13471, ncalls=39516, regioncalls=198046, ndraw=128, logz=-37.17, remainder_fraction=100.0000%, Lmin=-25.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13504, ncalls=39516, regioncalls=198046, ndraw=128, logz=-36.60, remainder_fraction=100.0000%, Lmin=-24.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13562, ncalls=39516, regioncalls=198046, ndraw=128, logz=-35.71, remainder_fraction=100.0000%, Lmin=-23.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13594, ncalls=39516, regioncalls=198046, ndraw=128, logz=-35.26, remainder_fraction=100.0000%, Lmin=-23.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13711, ncalls=39516, regioncalls=198046, ndraw=128, logz=-33.45, remainder_fraction=100.0000%, Lmin=-21.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13730, ncalls=39516, regioncalls=198046, ndraw=128, logz=-33.20, remainder_fraction=100.0000%, Lmin=-21.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13757, ncalls=39516, regioncalls=198046, ndraw=128, logz=-32.83, remainder_fraction=100.0000%, Lmin=-20.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13760, ncalls=39516, regioncalls=198046, ndraw=128, logz=-32.78, remainder_fraction=100.0000%, Lmin=-20.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13888, ncalls=39516, regioncalls=198046, ndraw=128, logz=-31.06, remainder_fraction=100.0000%, Lmin=-19.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13973, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.99, remainder_fraction=100.0000%, Lmin=-18.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=13984, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.86, remainder_fraction=100.0000%, Lmin=-17.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14016, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.50, remainder_fraction=100.0000%, Lmin=-17.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14040, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.23, remainder_fraction=100.0000%, Lmin=-17.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14054, ncalls=39516, regioncalls=198046, ndraw=128, logz=-29.08, remainder_fraction=100.0000%, Lmin=-17.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14080, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.81, remainder_fraction=100.0000%, Lmin=-16.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14142, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.19, remainder_fraction=100.0000%, Lmin=-16.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14153, ncalls=39516, regioncalls=198046, ndraw=128, logz=-28.08, remainder_fraction=100.0000%, Lmin=-16.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14168, ncalls=39516, regioncalls=198046, ndraw=128, logz=-27.93, remainder_fraction=100.0000%, Lmin=-15.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14175, ncalls=39516, regioncalls=198046, ndraw=128, logz=-27.86, remainder_fraction=100.0000%, Lmin=-15.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14196, ncalls=39644, regioncalls=198302, ndraw=128, logz=-27.65, remainder_fraction=100.0000%, Lmin=-15.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14208, ncalls=39644, regioncalls=198302, ndraw=128, logz=-27.53, remainder_fraction=100.0000%, Lmin=-15.53, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14301, ncalls=39644, regioncalls=198302, ndraw=128, logz=-26.59, remainder_fraction=100.0000%, Lmin=-14.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14307, ncalls=39644, regioncalls=198302, ndraw=128, logz=-26.53, remainder_fraction=100.0000%, Lmin=-14.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14400, ncalls=39644, regioncalls=198302, ndraw=128, logz=-25.69, remainder_fraction=99.9999%, Lmin=-13.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14449, ncalls=39644, regioncalls=198302, ndraw=128, logz=-25.29, remainder_fraction=99.9998%, Lmin=-13.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14522, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.69, remainder_fraction=99.9997%, Lmin=-12.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14528, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.64, remainder_fraction=99.9997%, Lmin=-12.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14568, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.29, remainder_fraction=99.9995%, Lmin=-12.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14597, ncalls=39644, regioncalls=198302, ndraw=128, logz=-24.04, remainder_fraction=99.9994%, Lmin=-11.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14607, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.95, remainder_fraction=99.9994%, Lmin=-11.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14683, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.34, remainder_fraction=99.9988%, Lmin=-11.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14689, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.30, remainder_fraction=99.9988%, Lmin=-11.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14704, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.19, remainder_fraction=99.9986%, Lmin=-11.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14722, ncalls=39644, regioncalls=198302, ndraw=128, logz=-23.06, remainder_fraction=99.9985%, Lmin=-11.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14745, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.90, remainder_fraction=99.9982%, Lmin=-10.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14777, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.68, remainder_fraction=99.9977%, Lmin=-10.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14829, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.33, remainder_fraction=99.9968%, Lmin=-10.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14850, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.19, remainder_fraction=99.9963%, Lmin=-10.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=14871, ncalls=39644, regioncalls=198302, ndraw=128, logz=-22.05, remainder_fraction=99.9957%, Lmin=-10.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15031, ncalls=39772, regioncalls=198558, ndraw=128, logz=-21.02, remainder_fraction=99.9878%, Lmin=-9.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15225, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.91, remainder_fraction=99.9632%, Lmin=-7.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15360, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.20, remainder_fraction=99.9237%, Lmin=-7.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15382, ncalls=39772, regioncalls=198558, ndraw=128, logz=-19.10, remainder_fraction=99.9159%, Lmin=-7.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15456, ncalls=39772, regioncalls=198558, ndraw=128, logz=-18.78, remainder_fraction=99.8843%, Lmin=-6.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15520, ncalls=39772, regioncalls=198558, ndraw=128, logz=-18.51, remainder_fraction=99.8491%, Lmin=-6.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15741, ncalls=39772, regioncalls=198558, ndraw=128, logz=-17.70, remainder_fraction=99.6623%, Lmin=-5.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15934, ncalls=39900, regioncalls=198942, ndraw=128, logz=-17.08, remainder_fraction=99.3713%, Lmin=-5.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=15936, ncalls=39900, regioncalls=198942, ndraw=128, logz=-17.07, remainder_fraction=99.3675%, Lmin=-5.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16086, ncalls=39900, regioncalls=198942, ndraw=128, logz=-16.62, remainder_fraction=99.0149%, Lmin=-4.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16295, ncalls=39900, regioncalls=198942, ndraw=128, logz=-16.05, remainder_fraction=98.3041%, Lmin=-4.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16352, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.90, remainder_fraction=98.0299%, Lmin=-3.94, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16447, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.67, remainder_fraction=97.5041%, Lmin=-3.71, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16480, ncalls=39900, regioncalls=198942, ndraw=128, logz=-15.59, remainder_fraction=97.3108%, Lmin=-3.64, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16576, ncalls=40028, regioncalls=199582, ndraw=128, logz=-15.38, remainder_fraction=96.6421%, Lmin=-3.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16704, ncalls=40028, regioncalls=199582, ndraw=128, logz=-15.11, remainder_fraction=95.6073%, Lmin=-3.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16801, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.92, remainder_fraction=94.6685%, Lmin=-2.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=16954, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.64, remainder_fraction=92.9563%, Lmin=-2.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17109, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.37, remainder_fraction=90.8881%, Lmin=-2.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17152, ncalls=40028, regioncalls=199582, ndraw=128, logz=-14.31, remainder_fraction=90.2332%, Lmin=-2.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17308, ncalls=40156, regioncalls=200094, ndraw=128, logz=-14.08, remainder_fraction=87.7145%, Lmin=-2.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17376, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.98, remainder_fraction=86.5056%, Lmin=-1.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17496, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.83, remainder_fraction=84.3049%, Lmin=-1.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17504, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.82, remainder_fraction=84.1424%, Lmin=-1.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17568, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.75, remainder_fraction=82.9257%, Lmin=-1.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17743, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.55, remainder_fraction=79.3073%, Lmin=-1.56, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17880, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.42, remainder_fraction=76.2527%, Lmin=-1.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17888, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.41, remainder_fraction=76.0863%, Lmin=-1.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17952, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.35, remainder_fraction=74.6161%, Lmin=-1.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=17984, ncalls=40156, regioncalls=200094, ndraw=128, logz=-13.32, remainder_fraction=73.8593%, Lmin=-1.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18148, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.19, remainder_fraction=70.0275%, Lmin=-1.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18243, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.11, remainder_fraction=67.7670%, Lmin=-1.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18336, ncalls=40284, regioncalls=200350, ndraw=128, logz=-13.05, remainder_fraction=65.4918%, Lmin=-1.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18494, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.94, remainder_fraction=61.7598%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18591, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.89, remainder_fraction=59.4928%, Lmin=-0.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18624, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.87, remainder_fraction=58.7285%, Lmin=-0.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18771, ncalls=40284, regioncalls=200350, ndraw=128, logz=-12.79, remainder_fraction=55.3808%, Lmin=-0.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=18950, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.70, remainder_fraction=51.2947%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19107, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.63, remainder_fraction=47.7864%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19264, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.57, remainder_fraction=44.3957%, Lmin=-0.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19297, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.55, remainder_fraction=43.6924%, Lmin=-0.58, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19328, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.54, remainder_fraction=43.0323%, Lmin=-0.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19474, ncalls=40412, regioncalls=200606, ndraw=128, logz=-12.49, remainder_fraction=40.0065%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19628, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.44, remainder_fraction=37.0154%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19651, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.44, remainder_fraction=36.5739%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19776, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.40, remainder_fraction=34.3001%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19808, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.39, remainder_fraction=33.7389%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=19840, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.38, remainder_fraction=33.1966%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20009, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.34, remainder_fraction=30.3599%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20166, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.31, remainder_fraction=27.9244%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20224, ncalls=40540, regioncalls=200862, ndraw=128, logz=-12.29, remainder_fraction=27.0625%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20366, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.27, remainder_fraction=25.0157%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20531, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.24, remainder_fraction=22.7737%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20544, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.24, remainder_fraction=22.6061%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20576, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.23, remainder_fraction=22.2002%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20640, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.22, remainder_fraction=21.3984%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20722, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.21, remainder_fraction=20.4114%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20800, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.20, remainder_fraction=19.5170%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=20973, ncalls=40668, regioncalls=201118, ndraw=128, logz=-12.17, remainder_fraction=17.6382%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21076, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.16, remainder_fraction=16.5963%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21152, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.15, remainder_fraction=15.8720%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21184, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.15, remainder_fraction=15.5739%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21342, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.13, remainder_fraction=14.1631%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21421, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.12, remainder_fraction=13.5018%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21579, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.11, remainder_fraction=12.2687%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21600, ncalls=40796, regioncalls=201374, ndraw=128, logz=-12.11, remainder_fraction=12.1134%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21753, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.10, remainder_fraction=11.0325%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21789, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.09, remainder_fraction=10.7911%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=21856, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.09, remainder_fraction=10.3564%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22003, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.08, remainder_fraction=9.4650%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22048, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.08, remainder_fraction=9.2068%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22080, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.07, remainder_fraction=9.0250%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22148, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.07, remainder_fraction=8.6553%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22360, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.06, remainder_fraction=7.5826%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22400, ncalls=40924, regioncalls=201630, ndraw=128, logz=-12.06, remainder_fraction=7.3958%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22495, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.05, remainder_fraction=6.9702%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22652, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=6.3151%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22807, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.7283%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22816, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.6958%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22844, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.04, remainder_fraction=5.5962%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=22944, ncalls=41052, regioncalls=201886, ndraw=128, logz=-12.03, remainder_fraction=5.2532%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23097, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.03, remainder_fraction=4.7695%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23104, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.03, remainder_fraction=4.7486%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23198, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=4.4739%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23371, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=4.0074%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23488, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=3.7199%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23545, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.02, remainder_fraction=3.5870%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23616, ncalls=41180, regioncalls=202142, ndraw=128, logz=-12.01, remainder_fraction=3.4284%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23787, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=3.0737%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23889, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=2.8795%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=23904, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.01, remainder_fraction=2.8520%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24069, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.5657%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24223, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.3245%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24234, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.3081%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24256, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.2758%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24320, ncalls=41308, regioncalls=202526, ndraw=128, logz=-12.00, remainder_fraction=2.1842%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24474, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.9784%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24581, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.8467%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24746, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.6606%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24768, ncalls=41436, regioncalls=203038, ndraw=128, logz=-12.00, remainder_fraction=1.6372%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=24931, ncalls=41436, regioncalls=203038, ndraw=128, logz=-11.99, remainder_fraction=1.4741%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25090, ncalls=41436, regioncalls=203038, ndraw=128, logz=-11.99, remainder_fraction=1.3304%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25216, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.2265%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25290, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.1693%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25440, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0613%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25472, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0396%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=25504, ncalls=41564, regioncalls=203422, ndraw=128, logz=-11.99, remainder_fraction=1.0183%, Lmin=-0.01, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-5e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 41564 INFO ultranest:integrator.py:2697 logZ = -11.97 +- 0.06439 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 6150.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) DEBUG ultranest:integrator.py:1636 conservative estimate says at least 1665 live points are needed to reach dlogz goal DEBUG ultranest:integrator.py:1652 number of live points vary between 1 and inf, most (20029/20329 iterations) have 1538 DEBUG ultranest:integrator.py:1663 at least 384 live points are needed to reach dlogz goal INFO ultranest:integrator.py:1667 Evidency uncertainty strategy wants 384 minimum live points (dlogz from 0.05 to 0.17, need <0.1) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.16 bs:0.06 tail:0.01 total:0.06 required:<0.10

Passed

tests/test_popstepsampling.py::test_direction_proposals

0.64

Passed

tests/test_run.py::test_run_resume[0.5]

12.77

Passed

tests/test_regionsampling.py::test_ellipsoids

0.28

Passed

tests/test_samplingpath.py::test_wrap

0.01

[gw7] linux -- Python 3.10.6 /usr/bin/python3
[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_samplingpath.py::test_random

0.74

[gw7] linux -- Python 3.10.6 /usr/bin/python3
[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_stepsampling.py::test_stepsampler

0.15

Passed

tests/test_stepsampling.py::test_stepsampler_adapt_when_stuck

0.27

Passed

tests/test_run.py::test_reactive_run_warmstart_gauss

10.30

[gw10] linux -- Python 3.10.6 /usr/bin/python3
[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
====== Running Gauss problem [1] ===== [ultranest] Sampling 100 live points from prior ... Z=-inf(0.00%) | Like=-5e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=0/101 eff=0.0000% N=100 Z=-4e+13(0.00%) | Like=-4.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=10/112 eff=83.3333% N=100 Z=-3e+13(0.00%) | Like=-3.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=20/122 eff=90.9091% N=100 Z=-3e+13(0.00%) | Like=-3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=30/132 eff=93.7500% N=100 Z=-3e+13(0.00%) | Like=-2.6e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=40/143 eff=93.0233% N=100 Z=-2e+13(0.00%) | Like=-2.2e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=46/151 eff=90.1961% N=100 Z=-2e+13(0.00%) | Like=-2.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=50/155 eff=90.9091% N=100 Z=-2e+13(0.00%) | Like=-1.7e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=60/165 eff=92.3077% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=69/174 eff=93.2432% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=70/176 eff=92.1053% N=100 Z=-1e+13(0.00%) | Like=-1.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=80/186 eff=93.0233% N=100 Z=-1e+13(0.00%) | Like=-9.6e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=90/197 eff=92.7835% N=100 Z=-8e+12(0.00%) | Like=-8.1e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=100/208 eff=92.5926% N=100 Z=-7e+12(0.00%) | Like=-7e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=110/220 eff=91.6667% N=100 Z=-7e+12(0.00%) | Like=-6.8e+12..-2.1e+09 [-1.232e+13..-4.452e+12] | it/evals=115/225 eff=92.0000% N=100 Z=-6e+12(0.00%) | Like=-6.2e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=120/230 eff=92.3077% N=100 Z=-5e+12(0.00%) | Like=-5e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=130/243 eff=90.9091% N=100 Z=-5e+12(0.00%) | Like=-4.5e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=140/257 eff=89.1720% N=100 Z=-3e+12(0.00%) | Like=-3.4e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=150/268 eff=89.2857% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=160/278 eff=89.8876% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=161/279 eff=89.9441% N=100 Z=-2e+12(0.00%) | Like=-2.1e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=170/289 eff=89.9471% N=100 Z=-2e+12(0.00%) | Like=-1.8e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=180/299 eff=90.4523% N=100 Z=-1e+12(0.00%) | Like=-1.5e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=190/309 eff=90.9091% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=200/319 eff=91.3242% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=207/326 eff=91.5929% N=100 Z=-1e+12(0.00%) | Like=-1e+12..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=210/329 eff=91.7031% N=100 Z=-9e+11(0.00%) | Like=-8.4e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=220/342 eff=90.9091% N=100 Z=-7e+11(0.00%) | Like=-7.1e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=230/352 eff=91.2698% N=100 Z=-6e+11(0.00%) | Like=-5.8e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=240/364 eff=90.9091% N=100 Z=-5e+11(0.00%) | Like=-5e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=250/376 eff=90.5797% N=100 Z=-5e+11(0.00%) | Like=-4.6e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=253/379 eff=90.6810% N=100 Z=-4e+11(0.00%) | Like=-4.2e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=260/387 eff=90.5923% N=100 Z=-3e+11(0.00%) | Like=-3.3e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=270/401 eff=89.7010% N=100 Z=-3e+11(0.00%) | Like=-3e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=276/408 eff=89.6104% N=100 Z=-3e+11(0.00%) | Like=-2.7e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=280/412 eff=89.7436% N=100 Z=-2e+11(0.00%) | Like=-2.2e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=290/422 eff=90.0621% N=100 Z=-2e+11(0.00%) | Like=-1.9e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=299/431 eff=90.3323% N=100 Z=-2e+11(0.00%) | Like=-1.8e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=300/432 eff=90.3614% N=100 Z=-1e+11(0.00%) | Like=-1.3e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=310/446 eff=89.5954% N=100 Z=-1e+11(0.00%) | Like=-1.1e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=320/458 eff=89.3855% N=100 Z=-1e+11(0.00%) | Like=-1e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=322/460 eff=89.4444% N=100 Z=-9e+10(0.00%) | Like=-8.4e+10..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=330/468 eff=89.6739% N=100 Z=-8e+10(0.00%) | Like=-7.8e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=340/478 eff=89.9471% N=100 Z=-7e+10(0.00%) | Like=-6.5e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=350/488 eff=90.2062% N=100 Z=-5e+10(0.00%) | Like=-5.2e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=360/498 eff=90.4523% N=100 Z=-4e+10(0.00%) | Like=-4.5e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=368/506 eff=90.6404% N=100 Z=-4e+10(0.00%) | Like=-4.4e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=370/508 eff=90.6863% N=100 Z=-4e+10(0.00%) | Like=-3.8e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=380/518 eff=90.9091% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=390/528 eff=91.1215% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=391/529 eff=91.1422% N=100 Z=-3e+10(0.00%) | Like=-2.5e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=400/539 eff=91.1162% N=100 Z=-2e+10(0.00%) | Like=-2.2e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=410/549 eff=91.3140% N=100 Z=-2e+10(0.00%) | Like=-2e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=414/553 eff=91.3907% N=100 Z=-2e+10(0.00%) | Like=-1.7e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=420/559 eff=91.5033% N=100 Z=-1e+10(0.00%) | Like=-1.3e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=430/569 eff=91.6844% N=100 Z=-1e+10(0.00%) | Like=-1.1e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=440/581 eff=91.4761% N=100 Z=-9e+09(0.00%) | Like=-8.8e+09..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=450/591 eff=91.6497% N=100 Z=-7e+09(0.00%) | Like=-7.3e+09..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=460/603 eff=91.4513% N=100 Z=-6e+09(0.00%) | Like=-5.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=470/615 eff=91.2621% N=100 Z=-5e+09(0.00%) | Like=-4.5e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=480/625 eff=91.4286% N=100 Z=-4e+09(0.00%) | Like=-4.3e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=483/628 eff=91.4773% N=100 Z=-4e+09(0.00%) | Like=-3.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=490/635 eff=91.5888% N=100 Z=-3e+09(0.00%) | Like=-3.1e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=500/648 eff=91.2409% N=100 Z=-3e+09(0.00%) | Like=-2.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=506/656 eff=91.0072% N=100 Z=-2e+09(0.00%) | Like=-2.5e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=510/660 eff=91.0714% N=100 Z=-2e+09(0.00%) | Like=-2e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=520/671 eff=91.0683% N=100 Z=-2e+09(0.00%) | Like=-1.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=529/682 eff=90.8935% N=100 Z=-2e+09(0.00%) | Like=-1.6e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=530/685 eff=90.5983% N=100 Z=-1e+09(0.00%) | Like=-1.3e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=540/697 eff=90.4523% N=100 Z=-8e+08(0.00%) | Like=-8.4e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=550/710 eff=90.1639% N=100 Z=-8e+08(0.00%) | Like=-8.2e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=552/712 eff=90.1961% N=100 Z=-8e+08(0.00%) | Like=-7.4e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=560/721 eff=90.1771% N=100 Z=-6e+08(0.00%) | Like=-5.9e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=570/731 eff=90.3328% N=100 Z=-5e+08(0.00%) | Like=-5.2e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=580/741 eff=90.4836% N=100 Z=-4e+08(0.00%) | Like=-3.8e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=590/755 eff=90.0763% N=100 Z=-3e+08(0.00%) | Like=-3.1e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=598/763 eff=90.1961% N=100 Z=-3e+08(0.00%) | Like=-2.8e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=600/765 eff=90.2256% N=100 Z=-2e+08(0.00%) | Like=-2.4e+08..-2e+04 [-2.461e+08..-7.777e+07] | it/evals=610/775 eff=90.3704% N=100 Z=-2e+08(0.00%) | Like=-2.2e+08..-2e+04 [-2.461e+08..-7.777e+07] | it/evals=620/786 eff=90.3790% N=100 Z=-2e+08(0.00%) | Like=-1.8e+08..-2e+04 [-2.461e+08..-7.777e+07] | it/evals=630/796 eff=90.5172% N=100 Z=-1e+08(0.00%) | Like=-1.5e+08..-2e+04 [-2.461e+08..-7.777e+07] | it/evals=640/806 eff=90.6516% N=100 Z=-1e+08(0.00%) | Like=-1.4e+08..-6e+03 [-2.461e+08..-7.777e+07] | it/evals=644/810 eff=90.7042% N=100 Z=-1e+08(0.00%) | Like=-1.3e+08..-6e+03 [-2.461e+08..-7.777e+07] | it/evals=650/816 eff=90.7821% N=100 Z=-1e+08(0.00%) | Like=-1.1e+08..-6e+03 [-2.461e+08..-7.777e+07] | it/evals=660/827 eff=90.7840% N=100 Z=-99584971.5(0.00%) | Like=-99056746.97..-6022.96 [-2.461e+08..-7.777e+07] | it/evals=667/835 eff=90.7483% N=100 Z=-95148616.1(0.00%) | Like=-93692477.41..-6022.96 [-2.461e+08..-7.777e+07] | it/evals=670/838 eff=90.7859% N=100 Z=-78681625.8(0.00%) | Like=-76849640.99..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=680/849 eff=90.7877% N=100 Z=-67129640.5(0.00%) | Like=-66446442.40..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=690/860 eff=90.7895% N=100 Z=-52437072.4(0.00%) | Like=-52098992.93..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=700/872 eff=90.6736% N=100 Z=-42467034.5(0.00%) | Like=-40947576.24..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=710/883 eff=90.6769% N=100 Z=-40875016.2(0.00%) | Like=-40682265.05..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=713/886 eff=90.7125% N=100 Z=-34273953.3(0.00%) | Like=-34009302.56..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=720/893 eff=90.7945% N=100 Z=-28150952.9(0.00%) | Like=-27577294.66..-6022.96 [-76849640.9883..-21157237.0757] | it/evals=730/904 eff=90.7960% N=100 Z=-24903284.6(0.00%) | Like=-24585788.12..-26.00 [-76849640.9883..-21157237.0757] | it/evals=740/917 eff=90.5753% N=100 Z=-18109608.4(0.00%) | Like=-17736757.48..-26.00 [-19938210.0363..-4653930.8201] | it/evals=750/927 eff=90.6892% N=100 Z=-15169525.4(0.00%) | Like=-14227274.47..-26.00 [-19938210.0363..-4653930.8201] | it/evals=760/937 eff=90.8005% N=100 Z=-11387981.3(0.00%) | Like=-11171106.07..-26.00 [-19938210.0363..-4653930.8201] | it/evals=770/949 eff=90.6949% N=100 Z=-9540359.8(0.00%) | Like=-9254160.55..-26.00 [-19938210.0363..-4653930.8201] | it/evals=780/959 eff=90.8033% N=100 Z=-9246880.2(0.00%) | Like=-9220004.55..-26.00 [-19938210.0363..-4653930.8201] | it/evals=782/961 eff=90.8246% N=100 Z=-8202857.7(0.00%) | Like=-7968261.52..-26.00 [-19938210.0363..-4653930.8201] | it/evals=790/969 eff=90.9091% N=100 Z=-6151494.4(0.00%) | Like=-6110210.34..-26.00 [-19938210.0363..-4653930.8201] | it/evals=800/980 eff=90.9091% N=100 Z=-5595023.2(0.00%) | Like=-5544084.40..-26.00 [-19938210.0363..-4653930.8201] | it/evals=805/986 eff=90.8578% N=100 Z=-5168753.7(0.00%) | Like=-5104017.56..-26.00 [-19938210.0363..-4653930.8201] | it/evals=810/991 eff=90.9091% N=100 Z=-4348450.3(0.00%) | Like=-4124983.59..-26.00 [-4571171.0738..-801360.3533] | it/evals=820/1001 eff=91.0100% N=100 Z=-3288211.8(0.00%) | Like=-3052967.15..-26.00 [-4571171.0738..-801360.3533] | it/evals=828/1010 eff=90.9890% N=100 Z=-2816901.9(0.00%) | Like=-2813964.84..-26.00 [-4571171.0738..-801360.3533] | it/evals=830/1012 eff=91.0088% N=100 Z=-2391242.8(0.00%) | Like=-2352037.02..-26.00 [-4571171.0738..-801360.3533] | it/evals=840/1022 eff=91.1063% N=100 Z=-1694476.5(0.00%) | Like=-1688714.15..-26.00 [-4571171.0738..-801360.3533] | it/evals=850/1033 eff=91.1040% N=100 Z=-1688727.3(0.00%) | Like=-1641589.55..-26.00 [-4571171.0738..-801360.3533] | it/evals=851/1034 eff=91.1135% N=100 Z=-1391311.1(0.00%) | Like=-1378714.97..-26.00 [-4571171.0738..-801360.3533] | it/evals=860/1044 eff=91.1017% N=100 Z=-1016207.0(0.00%) | Like=-1005805.90..-26.00 [-4571171.0738..-801360.3533] | it/evals=870/1056 eff=91.0042% N=100 Z=-921148.4(0.00%) | Like=-899817.07..-26.00 [-4571171.0738..-801360.3533] | it/evals=874/1061 eff=90.9469% N=100 Z=-823593.3(0.00%) | Like=-820443.05..-26.00 [-4571171.0738..-801360.3533] | it/evals=880/1067 eff=91.0031% N=100 Z=-718128.1(0.00%) | Like=-716385.20..-26.00 [-793371.7270..-221963.8669] | it/evals=890/1078 eff=91.0020% N=100 Z=-596455.2(0.00%) | Like=-575764.61..-26.00 [-793371.7270..-221963.8669] | it/evals=900/1090 eff=90.9091% N=100 Z=-491331.9(0.00%) | Like=-490644.03..-26.00 [-793371.7270..-221963.8669] | it/evals=910/1101 eff=90.9091% N=100 Z=-403815.9(0.00%) | Like=-396540.01..-26.00 [-793371.7270..-221963.8669] | it/evals=920/1112 eff=90.9091% N=100 Z=-335464.4(0.00%) | Like=-335428.11..-4.83 [-793371.7270..-221963.8669] | it/evals=930/1122 eff=90.9980% N=100 Z=-281288.1(0.00%) | Like=-269279.55..-4.83 [-793371.7270..-221963.8669] | it/evals=940/1133 eff=90.9971% N=100 Z=-267112.8(0.00%) | Like=-259247.40..-4.83 [-793371.7270..-221963.8669] | it/evals=943/1137 eff=90.9354% N=100 Z=-232361.2(0.00%) | Like=-227851.27..-4.83 [-793371.7270..-221963.8669] | it/evals=950/1144 eff=90.9962% N=100 Z=-195082.6(0.00%) | Like=-192338.76..-4.83 [-221393.3591..-50063.0867] | it/evals=960/1154 eff=91.0816% N=100 Z=-158846.7(0.00%) | Like=-156838.84..-4.83 [-221393.3591..-50063.0867] | it/evals=970/1165 eff=91.0798% N=100 Z=-123015.8(0.00%) | Like=-122093.92..-4.83 [-221393.3591..-50063.0867] | it/evals=980/1176 eff=91.0781% N=100 Z=-98769.3(0.00%) | Like=-94308.81..-4.83 [-221393.3591..-50063.0867] | it/evals=989/1186 eff=91.0681% N=100 Z=-94323.3(0.00%) | Like=-93705.11..-4.83 [-221393.3591..-50063.0867] | it/evals=990/1187 eff=91.0764% N=100 Z=-75793.0(0.00%) | Like=-75159.71..-4.83 [-221393.3591..-50063.0867] | it/evals=1000/1198 eff=91.0747% N=100 Z=-69193.8(0.00%) | Like=-69178.34..-4.43 [-221393.3591..-50063.0867] | it/evals=1010/1209 eff=91.0730% N=100 Z=-68151.1(0.00%) | Like=-67031.91..-4.43 [-221393.3591..-50063.0867] | it/evals=1012/1212 eff=91.0072% N=100 Z=-59478.1(0.00%) | Like=-56316.63..-4.43 [-221393.3591..-50063.0867] | it/evals=1020/1221 eff=90.9902% N=100 Z=-49166.7(0.00%) | Like=-46314.73..-4.43 [-49739.3666..-12576.5127] | it/evals=1030/1232 eff=90.9894% N=100 Z=-42809.3(0.00%) | Like=-40722.23..-4.43 [-49739.3666..-12576.5127] | it/evals=1035/1238 eff=90.9490% N=100 Z=-38197.5(0.00%) | Like=-36533.18..-4.43 [-49739.3666..-12576.5127] | it/evals=1040/1243 eff=90.9886% N=100 Z=-33560.9(0.00%) | Like=-32411.75..-4.43 [-49739.3666..-12576.5127] | it/evals=1050/1253 eff=91.0668% N=100 Z=-28364.5(0.00%) | Like=-28235.71..-4.43 [-49739.3666..-12576.5127] | it/evals=1060/1263 eff=91.1436% N=100 Z=-23735.6(0.00%) | Like=-21704.04..-4.43 [-49739.3666..-12576.5127] | it/evals=1070/1273 eff=91.2191% N=100 Z=-17722.4(0.00%) | Like=-17494.12..-0.07 [-49739.3666..-12576.5127] | it/evals=1080/1283 eff=91.2933% N=100 Z=-17509.5(0.00%) | Like=-17033.55..-0.07 [-49739.3666..-12576.5127] | it/evals=1081/1284 eff=91.3007% N=100 Z=-13805.2(0.00%) | Like=-13616.77..-0.07 [-49739.3666..-12576.5127] | it/evals=1090/1293 eff=91.3663% N=100 Z=-11448.5(0.00%) | Like=-11430.06..-0.07 [-12572.1941..-3639.3566] | it/evals=1100/1304 eff=91.3621% N=100 Z=-10886.1(0.00%) | Like=-10406.01..-0.07 [-12572.1941..-3639.3566] | it/evals=1104/1308 eff=91.3907% N=100 Z=-9677.3(0.00%) | Like=-9405.45..-0.07 [-12572.1941..-3639.3566] | it/evals=1110/1314 eff=91.4333% N=100 Z=-7396.0(0.00%) | Like=-7330.88..-0.07 [-12572.1941..-3639.3566] | it/evals=1120/1325 eff=91.4286% N=100 Z=-6557.4(0.00%) | Like=-6502.58..-0.07 [-12572.1941..-3639.3566] | it/evals=1130/1337 eff=91.3500% N=100 Z=-4918.0(0.00%) | Like=-4673.62..-0.07 [-12572.1941..-3639.3566] | it/evals=1140/1348 eff=91.3462% N=100 Z=-4140.2(0.00%) | Like=-4068.57..-0.07 [-12572.1941..-3639.3566] | it/evals=1150/1358 eff=91.4149% N=100 Z=-3620.6(0.00%) | Like=-3375.59..-0.07 [-3604.3797..-802.6300] | it/evals=1160/1368 eff=91.4826% N=100 Z=-2712.2(0.00%) | Like=-2672.37..-0.00 [-3604.3797..-802.6300] | it/evals=1170/1380 eff=91.4062% N=100 Z=-2576.7(0.00%) | Like=-2536.55..-0.00 [-3604.3797..-802.6300] | it/evals=1173/1383 eff=91.4263% N=100 Z=-2224.7(0.00%) | Like=-2201.36..-0.00 [-3604.3797..-802.6300] | it/evals=1180/1391 eff=91.4020% N=100 Z=-1915.5(0.00%) | Like=-1898.60..-0.00 [-3604.3797..-802.6300] | it/evals=1190/1404 eff=91.2577% N=100 Z=-1600.7(0.00%) | Like=-1576.13..-0.00 [-3604.3797..-802.6300] | it/evals=1200/1417 eff=91.1162% N=100 Z=-1273.5(0.00%) | Like=-1210.46..-0.00 [-3604.3797..-802.6300] | it/evals=1210/1429 eff=91.0459% N=100 Z=-1035.2(0.00%) | Like=-936.01..-0.00 [-3604.3797..-802.6300] | it/evals=1220/1440 eff=91.0448% N=100 Z=-747.3(0.00%) | Like=-722.16..-0.00 [-753.4608..-154.1297] | it/evals=1230/1454 eff=90.8419% N=100 Z=-637.3(0.00%) | Like=-618.44..-0.00 [-753.4608..-154.1297] | it/evals=1240/1466 eff=90.7760% N=100 Z=-622.1(0.00%) | Like=-567.65..-0.00 [-753.4608..-154.1297] | it/evals=1242/1468 eff=90.7895% N=100 Z=-453.1(0.00%) | Like=-420.93..-0.00 [-753.4608..-154.1297] | it/evals=1250/1476 eff=90.8430% N=100 Z=-343.4(0.00%) | Like=-321.96..-0.00 [-753.4608..-154.1297] | it/evals=1260/1487 eff=90.8435% N=100 Z=-324.7(0.00%) | Like=-304.81..-0.00 [-753.4608..-154.1297] | it/evals=1265/1493 eff=90.8112% N=100 Z=-293.1(0.00%) | Like=-269.15..-0.00 [-753.4608..-154.1297] | it/evals=1270/1498 eff=90.8441% N=100 Z=-245.0(0.00%) | Like=-220.24..-0.00 [-753.4608..-154.1297] | it/evals=1280/1508 eff=90.9091% N=100 Z=-198.7(0.00%) | Like=-179.69..-0.00 [-753.4608..-154.1297] | it/evals=1288/1517 eff=90.8963% N=100 Z=-190.1(0.00%) | Like=-163.20..-0.00 [-753.4608..-154.1297] | it/evals=1290/1519 eff=90.9091% N=100 Z=-156.7(0.00%) | Like=-138.36..-0.00 [-153.8288..-33.2230] | it/evals=1300/1532 eff=90.7821% N=100 Z=-144.3(0.00%) | Like=-124.32..-0.00 [-153.8288..-33.2230] | it/evals=1310/1544 eff=90.7202% N=100 Z=-107.5(0.00%) | Like=-88.54..-0.00 [-153.8288..-33.2230] | it/evals=1320/1555 eff=90.7216% N=100 Z=-94.0(0.00%) | Like=-70.34..-0.00 [-153.8288..-33.2230] | it/evals=1330/1566 eff=90.7231% N=100 Z=-84.4(0.00%) | Like=-66.66..-0.00 [-153.8288..-33.2230] | it/evals=1334/1572 eff=90.6250% N=100 Z=-78.0(0.00%) | Like=-59.63..-0.00 [-153.8288..-33.2230] | it/evals=1340/1578 eff=90.6631% N=100 Z=-68.1(0.00%) | Like=-47.59..-0.00 [-153.8288..-33.2230] | it/evals=1350/1591 eff=90.5433% N=100 Z=-55.9(0.00%) | Like=-36.04..-0.00 [-153.8288..-33.2230] | it/evals=1357/1598 eff=90.5874% N=100 Z=-51.8(0.00%) | Like=-34.07..-0.00 [-153.8288..-33.2230] | it/evals=1360/1601 eff=90.6063% N=100 Z=-46.7(0.00%) | Like=-28.87..-0.00 [-32.3716..-7.9890] | it/evals=1370/1613 eff=90.5486% N=100 Z=-42.4(0.00%) | Like=-24.81..-0.00 [-32.3716..-7.9890] | it/evals=1380/1626 eff=90.4325% N=100 Z=-38.6(0.00%) | Like=-21.44..-0.00 [-32.3716..-7.9890] | it/evals=1390/1637 eff=90.4359% N=100 Z=-35.5(0.00%) | Like=-18.34..-0.00 [-32.3716..-7.9890] | it/evals=1400/1648 eff=90.4393% N=100 Z=-34.9(0.00%) | Like=-17.38..-0.00 [-32.3716..-7.9890] | it/evals=1403/1652 eff=90.3995% N=100 Z=-32.8(0.00%) | Like=-15.23..-0.00 [-32.3716..-7.9890] | it/evals=1410/1662 eff=90.2689% N=100 Z=-30.7(0.00%) | Like=-13.76..-0.00 [-32.3716..-7.9890] | it/evals=1420/1673 eff=90.2734% N=100 Z=-29.5(0.00%) | Like=-12.25..-0.00 [-32.3716..-7.9890] | it/evals=1426/1680 eff=90.2532% N=100 Z=-28.1(0.00%) | Like=-10.30..-0.00 [-32.3716..-7.9890] | it/evals=1430/1684 eff=90.2778% N=100 Z=-26.1(0.00%) | Like=-8.61..-0.00 [-32.3716..-7.9890] | it/evals=1440/1697 eff=90.1691% N=100 Z=-24.3(0.01%) | Like=-7.41..-0.00 [-7.8443..-4.9205] | it/evals=1450/1710 eff=90.0621% N=100 Z=-23.0(0.05%) | Like=-5.44..-0.00 [-7.8443..-4.9205] | it/evals=1460/1720 eff=90.1235% N=100 Z=-21.5(0.26%) | Like=-4.30..-0.00 [-4.3008..-4.1557] | it/evals=1470/1731 eff=90.1288% N=100 Z=-21.3(0.32%) | Like=-3.97..-0.00 [-3.9720..-3.8905] | it/evals=1472/1733 eff=90.1408% N=100 Z=-20.4(0.80%) | Like=-3.18..-0.00 [-3.1789..-3.0107] | it/evals=1480/1741 eff=90.1889% N=100 Z=-19.4(2.05%) | Like=-2.57..-0.00 [-2.6399..-2.5714] | it/evals=1490/1751 eff=90.2483% N=100 Z=-19.1(2.82%) | Like=-2.45..-0.00 [-2.4464..-2.3119] | it/evals=1495/1756 eff=90.2778% N=100 Z=-18.9(3.62%) | Like=-2.25..-0.00 [-2.2673..-2.2510] | it/evals=1500/1761 eff=90.3070% N=100 Z=-18.4(5.61%) | Like=-1.86..-0.00 [-1.8649..-1.8110] | it/evals=1510/1774 eff=90.2031% N=100 Z=-18.1(7.76%) | Like=-1.50..-0.00 [-1.4996..-1.4776] | it/evals=1518/1782 eff=90.2497% N=100 Z=-18.0(8.38%) | Like=-1.41..-0.00 [-1.4062..-1.3954] | it/evals=1520/1784 eff=90.2613% N=100 Z=-17.7(11.75%) | Like=-1.25..-0.00 [-1.2661..-1.2467] | it/evals=1530/1795 eff=90.2655% N=100 Z=-17.4(15.70%) | Like=-0.99..-0.00 [-1.0017..-0.9891] | it/evals=1540/1806 eff=90.2696% N=100 Z=-17.3(16.14%) | Like=-0.98..-0.00 [-0.9819..-0.9559] | it/evals=1541/1807 eff=90.2753% N=100 Z=-17.1(20.25%) | Like=-0.83..-0.00 [-0.8264..-0.8118] | it/evals=1550/1816 eff=90.3263% N=100 Z=-16.9(24.79%) | Like=-0.67..-0.00 [-0.6822..-0.6720] | it/evals=1560/1826 eff=90.3824% N=100 Z=-16.8(26.54%) | Like=-0.63..-0.00 [-0.6420..-0.6278] | it/evals=1564/1830 eff=90.4046% N=100 Z=-16.7(29.30%) | Like=-0.55..-0.00 [-0.5506..-0.5464]*| it/evals=1570/1837 eff=90.3857% N=100 Z=-16.6(33.97%) | Like=-0.42..-0.00 [-0.4191..-0.4065] | it/evals=1580/1849 eff=90.3373% N=100 Z=-16.5(37.23%) | Like=-0.38..-0.00 [-0.3823..-0.3738]*| it/evals=1587/1858 eff=90.2730% N=100 Z=-16.5(38.67%) | Like=-0.35..-0.00 [-0.3479..-0.3376] | it/evals=1590/1861 eff=90.2896% N=100 Z=-16.3(43.36%) | Like=-0.28..-0.00 [-0.2759..-0.2674]*| it/evals=1600/1872 eff=90.2935% N=100 Z=-16.2(47.93%) | Like=-0.20..-0.00 [-0.2117..-0.1995] | it/evals=1610/1883 eff=90.2973% N=100 [ultranest] Explored until L=-4e-06 [ultranest] Likelihood function evaluations: 1887 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -15.512 +- 0.959 single instance: logZ = -15.512 +- 0.391 bootstrapped : logZ = -15.438 +- 0.869 tail : logZ = +- 0.404 insert order U test : converged: True correlation: inf iterations a : -0.00365│ ▁ ▁▁▁▁▁▂▁▂▃▃▃▄▆▄▇▅▇▇▇▆▆▃▃▄▄▂▂▁▁▁▁▁ ▁▁ │0.00350 0.00005 +- 0.00098 pointstore: (1715, 5) 1887 1887 0 ====== Running Gauss problem [2] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.004417743572744871 Exception as expected: Cannot resume because loglikelihood function changed, unless resume=resume-similar. To start from scratch, delete '/tmp/tmpmtve497_'. ====== Running Gauss problem [3] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.018817470773834135 [ultranest] trying to salvage points from previous, different run ... [ultranest] Resuming from 1344 stored points Z=-inf(0.00%) | Like=-5e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=0/1887 eff=inf% N=100 Z=-4e+13(0.00%) | Like=-4.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=10/1887 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=20/1887 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3.2e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=23/1887 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=30/1887 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-2.6e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=40/1887 eff=inf% N=100 Z=-2e+13(0.00%) | Like=-2.1e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=50/1887 eff=inf% N=100 Z=-2e+13(0.00%) | Like=-1.7e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=60/1887 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=69/1887 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=70/1887 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.3e+13..-1.4e+10 [-4.998e+13..-1.242e+13] | it/evals=80/1887 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-9.6e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=90/1887 eff=inf% N=100 Z=-8e+12(0.00%) | Like=-8.1e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=100/1887 eff=inf% N=100 Z=-7e+12(0.00%) | Like=-7e+12..-1.4e+10 [-1.232e+13..-4.452e+12] | it/evals=110/1887 eff=inf% N=100 Z=-7e+12(0.00%) | Like=-6.8e+12..-2.1e+09 [-1.232e+13..-4.452e+12] | it/evals=115/1887 eff=inf% N=100 Z=-6e+12(0.00%) | Like=-6.2e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=120/1887 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-5e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=130/1887 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-4.6e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=138/1887 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-4.5e+12..-2e+04 [-1.232e+13..-4.452e+12] | it/evals=140/1887 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-3.4e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=150/1887 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=160/1887 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=161/1887 eff=inf% N=100 Z=-2e+12(0.00%) | Like=-2.1e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=170/1887 eff=inf% N=100 Z=-2e+12(0.00%) | Like=-1.8e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=180/1887 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.5e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=190/1887 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.394e+12..-1.143e+12] | it/evals=200/1887 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=207/1887 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1e+12..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=210/1887 eff=inf% N=100 Z=-9e+11(0.00%) | Like=-8.4e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=220/1887 eff=inf% N=100 Z=-7e+11(0.00%) | Like=-7.1e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=230/1887 eff=inf% N=100 Z=-6e+11(0.00%) | Like=-5.8e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=240/1887 eff=inf% N=100 Z=-5e+11(0.00%) | Like=-5e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=250/1887 eff=inf% N=100 Z=-5e+11(0.00%) | Like=-4.6e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=253/1887 eff=inf% N=100 Z=-4e+11(0.00%) | Like=-4.2e+11..-2e+04 [-1.142e+12..-3.697e+11] | it/evals=260/1887 eff=inf% N=100 Z=-3e+11(0.00%) | Like=-3.3e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=270/1887 eff=inf% N=100 Z=-3e+11(0.00%) | Like=-2.7e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=280/1887 eff=inf% N=100 Z=-2e+11(0.00%) | Like=-2.2e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=290/1887 eff=inf% N=100 Z=-2e+11(0.00%) | Like=-1.9e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=299/1887 eff=inf% N=100 Z=-2e+11(0.00%) | Like=-1.8e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=300/1887 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1.3e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=310/1887 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1.1e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=320/1887 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1e+11..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=322/1887 eff=inf% N=100 Z=-9e+10(0.00%) | Like=-8.4e+10..-2e+04 [-3.628e+11..-8.168e+10] | it/evals=330/1887 eff=inf% N=100 Z=-8e+10(0.00%) | Like=-7.8e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=340/1887 eff=inf% N=100 Z=-7e+10(0.00%) | Like=-7.1e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=345/1887 eff=inf% N=100 Z=-7e+10(0.00%) | Like=-6.5e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=350/1887 eff=inf% N=100 Z=-5e+10(0.00%) | Like=-5.2e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=360/1887 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-4.5e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=368/1887 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-4.4e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=370/1887 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-3.8e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=380/1887 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=390/1887 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-8.065e+10..-2.652e+10] | it/evals=391/1887 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.5e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=400/1887 eff=inf% N=100 Z=-2e+10(0.00%) | Like=-2.2e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=410/1887 eff=inf% N=100 Z=-2e+10(0.00%) | Like=-1.7e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=420/1887 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.3e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=430/1887 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.2e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=437/1887 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.1e+10..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=440/1887 eff=inf% N=100 Z=-9e+09(0.00%) | Like=-8.8e+09..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=450/1887 eff=inf% N=100 Z=-7e+09(0.00%) | Like=-7.3e+09..-2e+04 [-2.652e+10..-7.121e+09] | it/evals=460/1887 eff=inf% N=100 Z=-6e+09(0.00%) | Like=-5.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=470/1887 eff=inf% N=100 Z=-5e+09(0.00%) | Like=-4.5e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=480/1887 eff=inf% N=100 Z=-4e+09(0.00%) | Like=-4.3e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=483/1887 eff=inf% N=100 Z=-4e+09(0.00%) | Like=-3.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=490/1887 eff=inf% N=100 Z=-3e+09(0.00%) | Like=-3.1e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=500/1887 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-2.5e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=510/1887 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-2e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=520/1887 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-1.7e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=529/1887 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-1.6e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=530/1887 eff=inf% N=100 Z=-1e+09(0.00%) | Like=-1.3e+09..-2e+04 [-6.93e+09..-1.231e+09] | it/evals=540/1887 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-8.4e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=550/1887 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-8.2e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=552/1887 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-7.4e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=560/1887 eff=inf% N=100 Z=-6e+08(0.00%) | Like=-5.9e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=570/1887 eff=inf% N=100 Z=-6e+08(0.00%) | Like=-5.4e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=575/1887 eff=inf% N=100 Z=-5e+08(0.00%) | Like=-5.2e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=580/1887 eff=inf% N=100 Z=-4e+08(0.00%) | Like=-3.8e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=590/1887 eff=inf% N=100 Z=-3e+08(0.00%) | Like=-3.1e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=598/1887 eff=inf% N=100 Z=-3e+08(0.00%) | Like=-2.8e+08..-2e+04 [-1.215e+09..-2.487e+08] | it/evals=600/1887 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-2.4e+08..-2e+04 [-2.462e+08..-7.776e+07] | it/evals=610/1887 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-2.2e+08..-2e+04 [-2.462e+08..-7.776e+07] | it/evals=620/1887 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-2.2e+08..-2e+04 [-2.462e+08..-7.776e+07] | it/evals=621/1887 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-1.8e+08..-2e+04 [-2.462e+08..-7.776e+07] | it/evals=630/1887 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.5e+08..-2e+04 [-2.462e+08..-7.776e+07] | it/evals=640/1887 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.4e+08..-6e+03 [-2.462e+08..-7.776e+07] | it/evals=644/1887 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.3e+08..-6e+03 [-2.462e+08..-7.776e+07] | it/evals=650/1887 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.1e+08..-6e+03 [-2.462e+08..-7.776e+07] | it/evals=660/1887 eff=inf% N=100 Z=-99582148.9(0.00%) | Like=-99059562.04..-6001.03 [-2.462e+08..-7.776e+07] | it/evals=667/1887 eff=inf% N=100 Z=-95151375.1(0.00%) | Like=-93695215.20..-6001.03 [-2.462e+08..-7.776e+07] | it/evals=670/1887 eff=inf% N=100 Z=-78679116.9(0.00%) | Like=-76847161.50..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=680/1887 eff=inf% N=100 Z=-67131957.9(0.00%) | Like=-66448748.01..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=690/1887 eff=inf% N=100 Z=-52435024.3(0.00%) | Like=-52096951.40..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=700/1887 eff=inf% N=100 Z=-42465191.4(0.00%) | Like=-40949386.18..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=710/1887 eff=inf% N=100 Z=-40873207.9(0.00%) | Like=-40680461.02..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=713/1887 eff=inf% N=100 Z=-34272297.5(0.00%) | Like=-34010952.05..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=720/1887 eff=inf% N=100 Z=-28152453.6(0.00%) | Like=-27575809.36..-6001.03 [-76847161.4980..-21155936.6446] | it/evals=730/1887 eff=inf% N=100 Z=-24901873.1(0.00%) | Like=-24584385.70..-24.58 [-76847161.4980..-21155936.6446] | it/evals=740/1887 eff=inf% N=100 Z=-18110812.1(0.00%) | Like=-17737948.70..-24.58 [-19936947.1007..-4653936.2656] | it/evals=750/1887 eff=inf% N=100 Z=-15302856.8(0.00%) | Like=-15168411.63..-24.58 [-19936947.1007..-4653936.2656] | it/evals=759/1887 eff=inf% N=100 Z=-15168423.8(0.00%) | Like=-14226207.64..-24.58 [-19936947.1007..-4653936.2656] | it/evals=760/1887 eff=inf% N=100 Z=-11388935.8(0.00%) | Like=-11170160.74..-24.58 [-19936947.1007..-4653936.2656] | it/evals=770/1887 eff=inf% N=100 Z=-9539486.2(0.00%) | Like=-9255020.99..-24.58 [-19936947.1007..-4653936.2656] | it/evals=780/1887 eff=inf% N=100 Z=-9247740.3(0.00%) | Like=-9220863.41..-24.58 [-19936947.1007..-4653936.2656] | it/evals=782/1887 eff=inf% N=100 Z=-8203667.8(0.00%) | Like=-7969059.95..-24.58 [-19936947.1007..-4653936.2656] | it/evals=790/1887 eff=inf% N=100 Z=-6152195.9(0.00%) | Like=-6110909.52..-24.58 [-19936947.1007..-4653936.2656] | it/evals=800/1887 eff=inf% N=100 Z=-5168110.7(0.00%) | Like=-5104656.58..-24.58 [-19936947.1007..-4653936.2656] | it/evals=810/1887 eff=inf% N=100 Z=-4349040.1(0.00%) | Like=-4125558.07..-24.58 [-4570566.3677..-801613.5660] | it/evals=820/1887 eff=inf% N=100 Z=-2816427.2(0.00%) | Like=-2814439.32..-24.58 [-4570566.3677..-801613.5660] | it/evals=830/1887 eff=inf% N=100 Z=-2391680.2(0.00%) | Like=-2352470.82..-24.58 [-4570566.3677..-801613.5660] | it/evals=840/1887 eff=inf% N=100 Z=-1694108.3(0.00%) | Like=-1689081.73..-24.58 [-4570566.3677..-801613.5660] | it/evals=850/1887 eff=inf% N=100 Z=-1689094.8(0.00%) | Like=-1641951.96..-24.58 [-4570566.3677..-801613.5660] | it/evals=851/1887 eff=inf% N=100 Z=-1391644.8(0.00%) | Like=-1379047.10..-24.58 [-4570566.3677..-801613.5660] | it/evals=860/1887 eff=inf% N=100 Z=-1016250.7(0.00%) | Like=-1006089.59..-24.58 [-4570566.3677..-801613.5660] | it/evals=870/1887 eff=inf% N=100 Z=-920877.0(0.00%) | Like=-900085.39..-24.58 [-4570566.3677..-801613.5660] | it/evals=874/1887 eff=inf% N=100 Z=-823336.7(0.00%) | Like=-820186.88..-24.58 [-4570566.3677..-801613.5660] | it/evals=880/1887 eff=inf% N=100 Z=-718367.8(0.00%) | Like=-716624.62..-24.58 [-793119.8150..-221964.0581] | it/evals=890/1887 eff=inf% N=100 Z=-639630.0(0.00%) | Like=-639396.18..-24.58 [-793119.8150..-221964.0581] | it/evals=897/1887 eff=inf% N=100 Z=-596673.7(0.00%) | Like=-575979.25..-24.58 [-793119.8150..-221964.0581] | it/evals=900/1887 eff=inf% N=100 Z=-491530.1(0.00%) | Like=-490445.93..-24.58 [-793119.8150..-221964.0581] | it/evals=910/1887 eff=inf% N=100 Z=-403995.7(0.00%) | Like=-396361.92..-24.58 [-793119.8150..-221964.0581] | it/evals=920/1887 eff=inf% N=100 Z=-335628.3(0.00%) | Like=-335591.94..-4.23 [-793119.8150..-221964.0581] | it/evals=930/1887 eff=inf% N=100 Z=-281138.1(0.00%) | Like=-269426.35..-4.23 [-793119.8150..-221964.0581] | it/evals=940/1887 eff=inf% N=100 Z=-266966.7(0.00%) | Like=-259391.44..-4.23 [-793119.8150..-221964.0581] | it/evals=943/1887 eff=inf% N=100 Z=-232224.9(0.00%) | Like=-227986.30..-4.23 [-793119.8150..-221964.0581] | it/evals=950/1887 eff=inf% N=100 Z=-195207.5(0.00%) | Like=-192214.74..-4.23 [-221260.2947..-49999.8216] | it/evals=960/1887 eff=inf% N=100 Z=-172769.0(0.00%) | Like=-171647.55..-4.23 [-221260.2947..-49999.8216] | it/evals=966/1887 eff=inf% N=100 Z=-158733.9(0.00%) | Like=-156726.85..-4.23 [-221260.2947..-49999.8216] | it/evals=970/1887 eff=inf% N=100 Z=-123115.0(0.00%) | Like=-122192.77..-4.23 [-221260.2947..-49999.8216] | it/evals=980/1887 eff=inf% N=100 Z=-98858.2(0.00%) | Like=-94395.69..-4.23 [-221260.2947..-49999.8216] | it/evals=989/1887 eff=inf% N=100 Z=-94410.2(0.00%) | Like=-93791.71..-4.23 [-221260.2947..-49999.8216] | it/evals=990/1887 eff=inf% N=100 Z=-75715.2(0.00%) | Like=-75082.19..-4.23 [-221260.2947..-49999.8216] | it/evals=1000/1887 eff=inf% N=100 Z=-69119.4(0.00%) | Like=-69103.96..-3.86 [-221260.2947..-49999.8216] | it/evals=1010/1887 eff=inf% N=100 Z=-68077.3(0.00%) | Like=-66958.70..-3.86 [-221260.2947..-49999.8216] | it/evals=1012/1887 eff=inf% N=100 Z=-59547.1(0.00%) | Like=-56249.53..-3.86 [-221260.2947..-49999.8216] | it/evals=1020/1887 eff=inf% N=100 Z=-49104.0(0.00%) | Like=-46375.62..-3.86 [-49676.3061..-12608.2519] | it/evals=1030/1887 eff=inf% N=100 Z=-42750.8(0.00%) | Like=-40665.18..-3.86 [-49676.3061..-12608.2519] | it/evals=1035/1887 eff=inf% N=100 Z=-38252.8(0.00%) | Like=-36587.26..-3.86 [-49676.3061..-12608.2519] | it/evals=1040/1887 eff=inf% N=100 Z=-33612.8(0.00%) | Like=-32462.69..-3.86 [-49676.3061..-12608.2519] | it/evals=1050/1887 eff=inf% N=100 Z=-28541.5(0.00%) | Like=-28487.57..-3.86 [-49676.3061..-12608.2519] | it/evals=1058/1887 eff=inf% N=100 Z=-28412.2(0.00%) | Like=-28188.21..-3.86 [-49676.3061..-12608.2519] | it/evals=1060/1887 eff=inf% N=100 Z=-23692.0(0.00%) | Like=-21662.39..-3.86 [-49676.3061..-12608.2519] | it/evals=1070/1887 eff=inf% N=100 Z=-17760.0(0.00%) | Like=-17456.73..-0.01 [-49676.3061..-12608.2519] | it/evals=1080/1887 eff=inf% N=100 Z=-13838.4(0.00%) | Like=-13583.79..-0.01 [-49676.3061..-12608.2519] | it/evals=1090/1887 eff=inf% N=100 Z=-11478.8(0.00%) | Like=-11399.84..-0.01 [-12603.9281..-3639.2946] | it/evals=1100/1887 eff=inf% N=100 Z=-10856.6(0.00%) | Like=-10434.89..-0.01 [-12603.9281..-3639.2946] | it/evals=1104/1887 eff=inf% N=100 Z=-9705.1(0.00%) | Like=-9378.04..-0.01 [-12603.9281..-3639.2946] | it/evals=1110/1887 eff=inf% N=100 Z=-7371.7(0.00%) | Like=-7306.69..-0.01 [-12603.9281..-3639.2946] | it/evals=1120/1887 eff=inf% N=100 Z=-6854.9(0.00%) | Like=-6766.39..-0.01 [-12603.9281..-3639.2946] | it/evals=1127/1887 eff=inf% N=100 Z=-6580.3(0.00%) | Like=-6479.79..-0.01 [-12603.9281..-3639.2946] | it/evals=1130/1887 eff=inf% N=100 Z=-4937.8(0.00%) | Like=-4692.98..-0.01 [-12603.9281..-3639.2946] | it/evals=1140/1887 eff=inf% N=100 Z=-4122.1(0.00%) | Like=-4067.70..-0.01 [-12603.9281..-3639.2946] | it/evals=1150/1887 eff=inf% N=100 Z=-3637.6(0.00%) | Like=-3359.18..-0.01 [-3621.3806..-807.4065] | it/evals=1160/1887 eff=inf% N=100 Z=-2706.4(0.00%) | Like=-2657.76..-0.01 [-3621.3806..-807.4065] | it/evals=1170/1887 eff=inf% N=100 Z=-2238.0(0.00%) | Like=-2188.11..-0.01 [-3621.3806..-807.4065] | it/evals=1180/1887 eff=inf% N=100 Z=-1903.2(0.00%) | Like=-1886.29..-0.01 [-3621.3806..-807.4065] | it/evals=1190/1887 eff=inf% N=100 Z=-1581.5(0.00%) | Like=-1542.77..-0.01 [-3621.3806..-807.4065] | it/evals=1200/1887 eff=inf% N=100 Z=-1237.0(0.00%) | Like=-1202.19..-0.01 [-3621.3806..-807.4065] | it/evals=1210/1887 eff=inf% N=100 Z=-1026.2(0.00%) | Like=-935.24..-0.01 [-3621.3806..-807.4065] | it/evals=1219/1887 eff=inf% N=100 Z=-952.0(0.00%) | Like=-931.89..-0.01 [-3621.3806..-807.4065] | it/evals=1220/1887 eff=inf% N=100 Z=-743.4(0.00%) | Like=-707.99..-0.01 [-749.1139..-155.2214] | it/evals=1230/1887 eff=inf% N=100 Z=-629.1(0.00%) | Like=-611.43..-0.00 [-749.1139..-155.2214] | it/evals=1240/1887 eff=inf% N=100 Z=-591.4(0.00%) | Like=-540.26..-0.00 [-749.1139..-155.2214] | it/evals=1242/1887 eff=inf% N=100 Z=-443.8(0.00%) | Like=-423.44..-0.00 [-749.1139..-155.2214] | it/evals=1250/1894 eff=17857.1429% N=100 Z=-338.3(0.00%) | Like=-319.03..-0.00 [-749.1139..-155.2214] | it/evals=1260/1906 eff=6631.5789% N=100 Z=-320.4(0.00%) | Like=-299.89..-0.00 [-749.1139..-155.2214] | it/evals=1265/1911 eff=5270.8333% N=100 Z=-309.0(0.00%) | Like=-274.96..-0.00 [-749.1139..-155.2214] | it/evals=1270/1916 eff=4379.3103% N=100 Z=-258.4(0.00%) | Like=-236.24..-0.00 [-749.1139..-155.2214] | it/evals=1280/1927 eff=3200.0000% N=100 Z=-201.0(0.00%) | Like=-179.77..-0.00 [-749.1139..-155.2214] | it/evals=1288/1936 eff=2628.5714% N=100 Z=-193.8(0.00%) | Like=-169.63..-0.00 [-749.1139..-155.2214] | it/evals=1290/1938 eff=2529.4118% N=100 Z=-161.9(0.00%) | Like=-130.03..-0.00 [-154.4051..-26.4873] | it/evals=1300/1949 eff=2096.7742% N=100 Z=-122.9(0.00%) | Like=-100.59..-0.00 [-154.4051..-26.4873] | it/evals=1310/1962 eff=1746.6667% N=100 Z=-102.1(0.00%) | Like=-82.16..-0.00 [-154.4051..-26.4873] | it/evals=1320/1972 eff=1552.9412% N=100 Z=-84.0(0.00%) | Like=-65.28..-0.00 [-154.4051..-26.4873] | it/evals=1330/1982 eff=1400.0000% N=100 Z=-77.8(0.00%) | Like=-60.49..-0.00 [-154.4051..-26.4873] | it/evals=1334/1987 eff=1334.0000% N=100 Z=-74.6(0.00%) | Like=-54.73..-0.00 [-154.4051..-26.4873] | it/evals=1340/1993 eff=1264.1509% N=100 Z=-66.2(0.00%) | Like=-43.45..-0.00 [-154.4051..-26.4873] | it/evals=1350/2004 eff=1153.8462% N=100 Z=-50.5(0.00%) | Like=-31.91..-0.00 [-154.4051..-26.4873] | it/evals=1357/2012 eff=1085.6000% N=100 Z=-48.7(0.00%) | Like=-31.07..-0.00 [-154.4051..-26.4873] | it/evals=1360/2015 eff=1062.5000% N=100 Z=-43.6(0.00%) | Like=-26.08..-0.00 [-26.2958..-5.4409] | it/evals=1370/2027 eff=978.5714% N=100 Z=-39.1(0.00%) | Like=-21.30..-0.00 [-26.2958..-5.4409] | it/evals=1380/2037 eff=920.0000% N=100 Z=-35.6(0.00%) | Like=-18.42..-0.00 [-26.2958..-5.4409] | it/evals=1390/2049 eff=858.0247% N=100 Z=-32.6(0.00%) | Like=-14.44..-0.00 [-26.2958..-5.4409] | it/evals=1400/2059 eff=813.9535% N=100 Z=-28.9(0.00%) | Like=-11.08..-0.00 [-26.2958..-5.4409] | it/evals=1410/2070 eff=770.4918% N=100 Z=-26.6(0.00%) | Like=-9.33..-0.00 [-26.2958..-5.4409] | it/evals=1420/2082 eff=728.2051% N=100 Z=-25.7(0.00%) | Like=-8.50..-0.00 [-26.2958..-5.4409] | it/evals=1426/2089 eff=705.9406% N=100 Z=-24.9(0.01%) | Like=-7.55..-0.00 [-26.2958..-5.4409] | it/evals=1430/2094 eff=690.8213% N=100 Z=-23.4(0.03%) | Like=-6.42..-0.00 [-26.2958..-5.4409] | it/evals=1440/2104 eff=663.5945% N=100 Z=-22.1(0.12%) | Like=-4.83..-0.00 [-4.8274..-4.7523] | it/evals=1450/2114 eff=638.7665% N=100 Z=-20.9(0.43%) | Like=-3.80..-0.00 [-3.7974..-3.7761] | it/evals=1460/2124 eff=616.0338% N=100 Z=-20.0(1.03%) | Like=-3.40..-0.00 [-3.4030..-3.3651] | it/evals=1470/2134 eff=595.1417% N=100 Z=-19.9(1.19%) | Like=-3.36..-0.00 [-3.3576..-3.3270] | it/evals=1472/2136 eff=591.1647% N=100 Z=-19.5(1.79%) | Like=-2.90..-0.00 [-2.8996..-2.8747] | it/evals=1480/2144 eff=575.8755% N=100 Z=-19.0(2.98%) | Like=-2.28..-0.00 [-2.2828..-2.1849] | it/evals=1490/2155 eff=555.9701% N=100 Z=-18.4(5.21%) | Like=-1.61..-0.00 [-1.7463..-1.6139] | it/evals=1500/2167 eff=535.7143% N=100 Z=-17.9(8.23%) | Like=-1.33..-0.00 [-1.3875..-1.3339] | it/evals=1510/2178 eff=518.9003% N=100 Z=-17.6(11.17%) | Like=-1.18..-0.00 [-1.1805..-1.1732]*| it/evals=1518/2188 eff=504.3189% N=100 Z=-17.5(12.00%) | Like=-1.17..-0.00 [-1.1726..-1.1180] | it/evals=1520/2190 eff=501.6502% N=100 Z=-17.2(16.09%) | Like=-0.89..-0.00 [-0.8888..-0.8881]*| it/evals=1530/2201 eff=487.2611% N=100 Z=-17.0(20.67%) | Like=-0.77..-0.00 [-0.7738..-0.7474] | it/evals=1540/2211 eff=475.3086% N=100 Z=-17.0(21.17%) | Like=-0.75..-0.00 [-0.7738..-0.7474] | it/evals=1541/2212 eff=474.1538% N=100 Z=-16.8(25.27%) | Like=-0.66..-0.00 [-0.6833..-0.6582] | it/evals=1550/2222 eff=462.6866% N=100 Z=-16.6(29.85%) | Like=-0.54..-0.00 [-0.5355..-0.5234] | it/evals=1560/2236 eff=446.9914% N=100 Z=-16.5(34.80%) | Like=-0.41..-0.00 [-0.4471..-0.4112] | it/evals=1570/2246 eff=437.3259% N=100 Z=-16.3(39.66%) | Like=-0.35..-0.00 [-0.3542..-0.3495]*| it/evals=1580/2258 eff=425.8760% N=100 Z=-16.3(42.87%) | Like=-0.28..-0.00 [-0.2820..-0.2808]*| it/evals=1587/2267 eff=417.6316% N=100 Z=-16.2(44.25%) | Like=-0.26..-0.00 [-0.2561..-0.2521]*| it/evals=1590/2270 eff=415.1436% N=100 Z=-16.1(48.74%) | Like=-0.23..-0.00 [-0.2337..-0.2135] | it/evals=1600/2282 eff=405.0633% N=100 [ultranest] Explored until L=-2e-05 [ultranest] Likelihood function evaluations: 2284 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -15.401 +- 0.741 single instance: logZ = -15.401 +- 0.390 bootstrapped : logZ = -15.459 +- 0.620 tail : logZ = +- 0.405 insert order U test : converged: True correlation: inf iterations a : -0.00331│ ▁▁▁▁▁▁▁▁▂▂▃▅▄▃▇▇▇▇▇▄▆▄▃▄▂▃▁▁ ▁▁▁ ▁ │0.00440 0.00025 +- 0.00098 pointstore: (1703, 5) 397 2284 1887
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=False, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 100 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=101, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977128652622.04, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=112, regioncalls=480, ndraw=40, logz=-41932563448515.12, remainder_fraction=100.0000%, Lmin=-40508378723011.33, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=122, regioncalls=880, ndraw=40, logz=-33237565078343.30, remainder_fraction=100.0000%, Lmin=-33004788076548.36, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=132, regioncalls=1280, ndraw=40, logz=-29684133841641.27, remainder_fraction=100.0000%, Lmin=-29654731646156.86, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=143, regioncalls=1720, ndraw=40, logz=-26024311452003.38, remainder_fraction=100.0000%, Lmin=-25864311505807.76, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=46, ncalls=151, regioncalls=2040, ndraw=40, logz=-22394867389307.37, remainder_fraction=100.0000%, Lmin=-22267402908949.62, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=155, regioncalls=2200, ndraw=40, logz=-21618903469091.73, remainder_fraction=100.0000%, Lmin=-20657643852261.66, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=165, regioncalls=2600, ndraw=40, logz=-16736505395315.38, remainder_fraction=100.0000%, Lmin=-16631669273078.86, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=69, ncalls=174, regioncalls=2960, ndraw=40, logz=-14754875235796.48, remainder_fraction=100.0000%, Lmin=-13974010155653.97, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=176, regioncalls=3040, ndraw=40, logz=-13974010155659.27, remainder_fraction=100.0000%, Lmin=-13902692147308.39, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=186, regioncalls=3440, ndraw=40, logz=-12514435159574.19, remainder_fraction=100.0000%, Lmin=-12508279160474.38, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=197, regioncalls=3880, ndraw=40, logz=-10193267488313.77, remainder_fraction=100.0000%, Lmin=-9640968563235.02, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=208, regioncalls=4320, ndraw=40, logz=-8200640852030.98, remainder_fraction=100.0000%, Lmin=-8082128050878.53, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=220, regioncalls=4800, ndraw=40, logz=-7173863638817.49, remainder_fraction=100.0000%, Lmin=-6962107832262.44, Lmax=-14202345756.60 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=225, regioncalls=5000, ndraw=40, logz=-6806896849592.72, remainder_fraction=100.0000%, Lmin=-6798572125612.82, Lmax=-2101560050.10 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=230, regioncalls=5200, ndraw=40, logz=-6322457704122.88, remainder_fraction=100.0000%, Lmin=-6247007877914.18, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=243, regioncalls=5720, ndraw=40, logz=-5036135578185.74, remainder_fraction=100.0000%, Lmin=-5013134155411.33, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=257, regioncalls=6280, ndraw=40, logz=-4566342513618.33, remainder_fraction=100.0000%, Lmin=-4489051812244.98, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=268, regioncalls=6720, ndraw=40, logz=-3426886969738.49, remainder_fraction=100.0000%, Lmin=-3417861015794.89, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=278, regioncalls=7120, ndraw=40, logz=-2961969420058.14, remainder_fraction=100.0000%, Lmin=-2922089236302.01, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=279, regioncalls=7160, ndraw=40, logz=-2922089236308.22, remainder_fraction=100.0000%, Lmin=-2889249507418.14, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=289, regioncalls=7560, ndraw=40, logz=-2133520045718.24, remainder_fraction=100.0000%, Lmin=-2131391081808.14, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=299, regioncalls=7960, ndraw=40, logz=-1843764249986.19, remainder_fraction=100.0000%, Lmin=-1836388311150.23, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=309, regioncalls=8360, ndraw=40, logz=-1479338126812.93, remainder_fraction=100.0000%, Lmin=-1477274817822.07, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=319, regioncalls=8760, ndraw=40, logz=-1162164164059.82, remainder_fraction=100.0000%, Lmin=-1149513369148.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=326, regioncalls=9040, ndraw=40, logz=-1098683740545.40, remainder_fraction=100.0000%, Lmin=-1085733203899.34, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=329, regioncalls=9160, ndraw=40, logz=-1062199650048.03, remainder_fraction=100.0000%, Lmin=-1036687340045.72, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=342, regioncalls=9680, ndraw=40, logz=-871674334253.59, remainder_fraction=100.0000%, Lmin=-839966514038.46, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=352, regioncalls=10080, ndraw=40, logz=-715976483973.56, remainder_fraction=100.0000%, Lmin=-706773276409.40, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=364, regioncalls=10560, ndraw=40, logz=-593422182128.55, remainder_fraction=100.0000%, Lmin=-576444441337.76, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=376, regioncalls=11080, ndraw=40, logz=-511876960333.87, remainder_fraction=100.0000%, Lmin=-501758974682.00, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=253, ncalls=379, regioncalls=11200, ndraw=40, logz=-478675075304.45, remainder_fraction=100.0000%, Lmin=-455241053559.73, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=387, regioncalls=11520, ndraw=40, logz=-423629485137.20, remainder_fraction=100.0000%, Lmin=-418959245625.39, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=401, regioncalls=12120, ndraw=40, logz=-337456305895.85, remainder_fraction=100.0000%, Lmin=-332415073979.82, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=276, ncalls=408, regioncalls=12400, ndraw=40, logz=-298475456646.05, remainder_fraction=100.0000%, Lmin=-298119333065.73, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=412, regioncalls=12600, ndraw=40, logz=-280041079556.47, remainder_fraction=100.0000%, Lmin=-266139199581.03, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=422, regioncalls=13040, ndraw=40, logz=-219987159145.22, remainder_fraction=100.0000%, Lmin=-217170277506.50, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=431, regioncalls=13400, ndraw=40, logz=-186287571926.49, remainder_fraction=100.0000%, Lmin=-186217150611.38, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=432, regioncalls=13440, ndraw=40, logz=-186217150618.98, remainder_fraction=100.0000%, Lmin=-176257223101.81, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=446, regioncalls=14040, ndraw=40, logz=-136032296082.24, remainder_fraction=100.0000%, Lmin=-134941926834.72, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=458, regioncalls=14520, ndraw=40, logz=-106028758932.65, remainder_fraction=100.0000%, Lmin=-105574617114.81, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=460, regioncalls=14600, ndraw=40, logz=-102631626890.59, remainder_fraction=100.0000%, Lmin=-101211365642.63, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=468, regioncalls=14960, ndraw=40, logz=-85746886310.20, remainder_fraction=100.0000%, Lmin=-84170564177.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=478, regioncalls=15360, ndraw=40, logz=-78454705852.75, remainder_fraction=100.0000%, Lmin=-77856855358.69, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=488, regioncalls=15760, ndraw=40, logz=-65217978077.06, remainder_fraction=100.0000%, Lmin=-65071379682.57, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=498, regioncalls=16160, ndraw=40, logz=-52784301112.17, remainder_fraction=100.0000%, Lmin=-52465515313.79, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=506, regioncalls=16480, ndraw=40, logz=-44886006297.10, remainder_fraction=100.0000%, Lmin=-44881183821.51, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=508, regioncalls=16600, ndraw=40, logz=-44337101807.05, remainder_fraction=100.0000%, Lmin=-43924418108.48, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=518, regioncalls=17080, ndraw=40, logz=-38174116980.61, remainder_fraction=100.0000%, Lmin=-38166134224.94, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=528, regioncalls=17480, ndraw=40, logz=-30564921897.35, remainder_fraction=100.0000%, Lmin=-29014402527.49, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=529, regioncalls=17520, ndraw=40, logz=-29014402536.00, remainder_fraction=100.0000%, Lmin=-28739121812.84, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=539, regioncalls=17960, ndraw=40, logz=-25254381195.53, remainder_fraction=100.0000%, Lmin=-25189070092.02, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=410, ncalls=549, regioncalls=18360, ndraw=40, logz=-21660404181.26, remainder_fraction=100.0000%, Lmin=-21548375173.69, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=414, ncalls=553, regioncalls=18560, ndraw=40, logz=-20472052660.36, remainder_fraction=100.0000%, Lmin=-20078668592.97, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=559, regioncalls=18840, ndraw=40, logz=-17503276366.73, remainder_fraction=100.0000%, Lmin=-16696410598.10, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=569, regioncalls=19240, ndraw=40, logz=-13957975006.86, remainder_fraction=100.0000%, Lmin=-13215545136.09, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=581, regioncalls=19720, ndraw=40, logz=-11354970506.81, remainder_fraction=100.0000%, Lmin=-11308593818.41, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=591, regioncalls=20120, ndraw=40, logz=-8954739289.76, remainder_fraction=100.0000%, Lmin=-8802399549.13, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=460, ncalls=603, regioncalls=20640, ndraw=40, logz=-7358620740.27, remainder_fraction=100.0000%, Lmin=-7312924005.82, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=470, ncalls=615, regioncalls=21120, ndraw=40, logz=-5913717188.92, remainder_fraction=100.0000%, Lmin=-5686842852.59, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=625, regioncalls=21520, ndraw=40, logz=-4561851573.73, remainder_fraction=100.0000%, Lmin=-4534652974.21, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=628, regioncalls=21680, ndraw=40, logz=-4341443065.59, remainder_fraction=100.0000%, Lmin=-4317184186.04, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=490, ncalls=635, regioncalls=21960, ndraw=40, logz=-3683655620.41, remainder_fraction=100.0000%, Lmin=-3668713486.10, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=648, regioncalls=22520, ndraw=40, logz=-3119287299.14, remainder_fraction=100.0000%, Lmin=-3077114603.52, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=506, ncalls=656, regioncalls=22880, ndraw=40, logz=-2711784349.67, remainder_fraction=100.0000%, Lmin=-2672326802.74, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=660, regioncalls=23040, ndraw=40, logz=-2471295503.35, remainder_fraction=100.0000%, Lmin=-2451644303.44, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=671, regioncalls=23480, ndraw=40, logz=-2046833928.20, remainder_fraction=100.0000%, Lmin=-1963025685.85, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=529, ncalls=682, regioncalls=23960, ndraw=40, logz=-1683061127.53, remainder_fraction=100.0000%, Lmin=-1655504010.18, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=685, regioncalls=24080, ndraw=40, logz=-1655504020.08, remainder_fraction=100.0000%, Lmin=-1587929042.93, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=697, regioncalls=24560, ndraw=40, logz=-1345672698.85, remainder_fraction=100.0000%, Lmin=-1324107214.64, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=710, regioncalls=25080, ndraw=40, logz=-842704557.04, remainder_fraction=100.0000%, Lmin=-842098627.35, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=712, regioncalls=25200, ndraw=40, logz=-829471104.02, remainder_fraction=100.0000%, Lmin=-821755543.39, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=721, regioncalls=25560, ndraw=40, logz=-768681282.57, remainder_fraction=100.0000%, Lmin=-741055451.88, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=731, regioncalls=25960, ndraw=40, logz=-598461526.63, remainder_fraction=100.0000%, Lmin=-588030061.40, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=580, ncalls=741, regioncalls=26360, ndraw=40, logz=-523313989.11, remainder_fraction=100.0000%, Lmin=-520429923.57, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=590, ncalls=755, regioncalls=26920, ndraw=40, logz=-389302279.60, remainder_fraction=100.0000%, Lmin=-384227190.96, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=763, regioncalls=27280, ndraw=40, logz=-330216148.35, remainder_fraction=100.0000%, Lmin=-310871070.23, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=765, regioncalls=27360, ndraw=40, logz=-291718407.06, remainder_fraction=100.0000%, Lmin=-277171076.01, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=775, regioncalls=27760, ndraw=40, logz=-245515440.47, remainder_fraction=100.0000%, Lmin=-244117200.51, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=620, ncalls=786, regioncalls=28200, ndraw=40, logz=-222411923.28, remainder_fraction=100.0000%, Lmin=-218434467.04, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=796, regioncalls=28600, ndraw=40, logz=-179666648.72, remainder_fraction=100.0000%, Lmin=-179079251.49, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=806, regioncalls=29000, ndraw=40, logz=-147157505.55, remainder_fraction=100.0000%, Lmin=-146182858.52, Lmax=-19941.74 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=810, regioncalls=29160, ndraw=40, logz=-139592730.12, remainder_fraction=100.0000%, Lmin=-139232509.33, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=816, regioncalls=29520, ndraw=40, logz=-128990960.00, remainder_fraction=100.0000%, Lmin=-127079723.98, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=827, regioncalls=29960, ndraw=40, logz=-108091218.09, remainder_fraction=100.0000%, Lmin=-105743831.21, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=667, ncalls=835, regioncalls=30360, ndraw=40, logz=-99584971.45, remainder_fraction=100.0000%, Lmin=-99056746.97, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=670, ncalls=838, regioncalls=30480, ndraw=40, logz=-95148616.12, remainder_fraction=100.0000%, Lmin=-93692477.41, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=849, regioncalls=30920, ndraw=40, logz=-78681625.77, remainder_fraction=100.0000%, Lmin=-76849640.99, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=860, regioncalls=31360, ndraw=40, logz=-67129640.49, remainder_fraction=100.0000%, Lmin=-66446442.40, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=872, regioncalls=31840, ndraw=40, logz=-52437072.43, remainder_fraction=100.0000%, Lmin=-52098992.93, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=883, regioncalls=32280, ndraw=40, logz=-42467034.54, remainder_fraction=100.0000%, Lmin=-40947576.24, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=886, regioncalls=32520, ndraw=40, logz=-40875016.23, remainder_fraction=100.0000%, Lmin=-40682265.05, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=893, regioncalls=32800, ndraw=40, logz=-34273953.31, remainder_fraction=100.0000%, Lmin=-34009302.56, Lmax=-6022.96 DEBUG ultranest:integrator.py:2610 iteration=730, ncalls=904, regioncalls=33240, ndraw=40, logz=-28150952.86, remainder_fraction=100.0000%, Lmin=-27577294.66, Lmax=-6022.96 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=917, regioncalls=33760, ndraw=40, logz=-24903284.59, remainder_fraction=100.0000%, Lmin=-24585788.12, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=927, regioncalls=34160, ndraw=40, logz=-18109608.41, remainder_fraction=100.0000%, Lmin=-17736757.48, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=937, regioncalls=34640, ndraw=40, logz=-15169525.42, remainder_fraction=100.0000%, Lmin=-14227274.47, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=770, ncalls=949, regioncalls=35120, ndraw=40, logz=-11387981.32, remainder_fraction=100.0000%, Lmin=-11171106.07, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=959, regioncalls=35520, ndraw=40, logz=-9540359.81, remainder_fraction=100.0000%, Lmin=-9254160.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=782, ncalls=961, regioncalls=35640, ndraw=40, logz=-9246880.24, remainder_fraction=100.0000%, Lmin=-9220004.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=790, ncalls=969, regioncalls=35960, ndraw=40, logz=-8202857.71, remainder_fraction=100.0000%, Lmin=-7968261.52, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=980, regioncalls=36440, ndraw=40, logz=-6151494.36, remainder_fraction=100.0000%, Lmin=-6110210.34, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=805, ncalls=986, regioncalls=36760, ndraw=40, logz=-5595023.23, remainder_fraction=100.0000%, Lmin=-5544084.40, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=991, regioncalls=36960, ndraw=40, logz=-5168753.73, remainder_fraction=100.0000%, Lmin=-5104017.56, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=1001, regioncalls=37360, ndraw=40, logz=-4348450.29, remainder_fraction=100.0000%, Lmin=-4124983.59, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=828, ncalls=1010, regioncalls=37800, ndraw=40, logz=-3288211.79, remainder_fraction=100.0000%, Lmin=-3052967.15, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=830, ncalls=1012, regioncalls=37880, ndraw=40, logz=-2816901.87, remainder_fraction=100.0000%, Lmin=-2813964.84, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1022, regioncalls=38280, ndraw=40, logz=-2391242.81, remainder_fraction=100.0000%, Lmin=-2352037.02, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1033, regioncalls=38720, ndraw=40, logz=-1694476.49, remainder_fraction=100.0000%, Lmin=-1688714.15, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=851, ncalls=1034, regioncalls=38960, ndraw=40, logz=-1688727.26, remainder_fraction=100.0000%, Lmin=-1641589.55, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=860, ncalls=1044, regioncalls=39360, ndraw=40, logz=-1391311.12, remainder_fraction=100.0000%, Lmin=-1378714.97, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=1056, regioncalls=39840, ndraw=40, logz=-1016206.97, remainder_fraction=100.0000%, Lmin=-1005805.90, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=874, ncalls=1061, regioncalls=40080, ndraw=40, logz=-921148.44, remainder_fraction=100.0000%, Lmin=-899817.07, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1067, regioncalls=40320, ndraw=40, logz=-823593.32, remainder_fraction=100.0000%, Lmin=-820443.05, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=890, ncalls=1078, regioncalls=40760, ndraw=40, logz=-718128.13, remainder_fraction=100.0000%, Lmin=-716385.20, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1090, regioncalls=41240, ndraw=40, logz=-596455.20, remainder_fraction=100.0000%, Lmin=-575764.61, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=910, ncalls=1101, regioncalls=41680, ndraw=40, logz=-491331.87, remainder_fraction=100.0000%, Lmin=-490644.03, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1112, regioncalls=42200, ndraw=40, logz=-403815.91, remainder_fraction=100.0000%, Lmin=-396540.01, Lmax=-26.00 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=1122, regioncalls=42600, ndraw=40, logz=-335464.44, remainder_fraction=100.0000%, Lmin=-335428.11, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=940, ncalls=1133, regioncalls=43080, ndraw=40, logz=-281288.10, remainder_fraction=100.0000%, Lmin=-269279.55, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1137, regioncalls=43280, ndraw=40, logz=-267112.83, remainder_fraction=100.0000%, Lmin=-259247.40, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1144, regioncalls=43560, ndraw=40, logz=-232361.23, remainder_fraction=100.0000%, Lmin=-227851.27, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1154, regioncalls=43960, ndraw=40, logz=-195082.59, remainder_fraction=100.0000%, Lmin=-192338.76, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=970, ncalls=1165, regioncalls=44400, ndraw=40, logz=-158846.65, remainder_fraction=100.0000%, Lmin=-156838.84, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=980, ncalls=1176, regioncalls=44840, ndraw=40, logz=-123015.80, remainder_fraction=100.0000%, Lmin=-122093.92, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=1186, regioncalls=45280, ndraw=40, logz=-98769.27, remainder_fraction=100.0000%, Lmin=-94308.81, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1187, regioncalls=45320, ndraw=40, logz=-94323.31, remainder_fraction=100.0000%, Lmin=-93705.11, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1198, regioncalls=45760, ndraw=40, logz=-75793.03, remainder_fraction=100.0000%, Lmin=-75159.71, Lmax=-4.83 DEBUG ultranest:integrator.py:2610 iteration=1010, ncalls=1209, regioncalls=46200, ndraw=40, logz=-69193.78, remainder_fraction=100.0000%, Lmin=-69178.34, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1012, ncalls=1212, regioncalls=46360, ndraw=40, logz=-68151.14, remainder_fraction=100.0000%, Lmin=-67031.91, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=1221, regioncalls=46720, ndraw=40, logz=-59478.14, remainder_fraction=100.0000%, Lmin=-56316.63, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1030, ncalls=1232, regioncalls=47160, ndraw=40, logz=-49166.66, remainder_fraction=100.0000%, Lmin=-46314.73, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1035, ncalls=1238, regioncalls=47480, ndraw=40, logz=-42809.28, remainder_fraction=100.0000%, Lmin=-40722.23, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1243, regioncalls=47680, ndraw=40, logz=-38197.53, remainder_fraction=100.0000%, Lmin=-36533.18, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1253, regioncalls=48080, ndraw=40, logz=-33560.94, remainder_fraction=100.0000%, Lmin=-32411.75, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=1263, regioncalls=48480, ndraw=40, logz=-28364.53, remainder_fraction=100.0000%, Lmin=-28235.71, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1070, ncalls=1273, regioncalls=48880, ndraw=40, logz=-23735.59, remainder_fraction=100.0000%, Lmin=-21704.04, Lmax=-4.43 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1283, regioncalls=49280, ndraw=40, logz=-17722.35, remainder_fraction=100.0000%, Lmin=-17494.12, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1081, ncalls=1284, regioncalls=49400, ndraw=40, logz=-17509.53, remainder_fraction=100.0000%, Lmin=-17033.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1090, ncalls=1293, regioncalls=49760, ndraw=40, logz=-13805.21, remainder_fraction=100.0000%, Lmin=-13616.77, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1304, regioncalls=50200, ndraw=40, logz=-11448.52, remainder_fraction=100.0000%, Lmin=-11430.06, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1104, ncalls=1308, regioncalls=50400, ndraw=40, logz=-10886.12, remainder_fraction=100.0000%, Lmin=-10406.01, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=1314, regioncalls=50640, ndraw=40, logz=-9677.28, remainder_fraction=100.0000%, Lmin=-9405.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1325, regioncalls=51080, ndraw=40, logz=-7395.99, remainder_fraction=100.0000%, Lmin=-7330.88, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1130, ncalls=1337, regioncalls=51560, ndraw=40, logz=-6557.37, remainder_fraction=100.0000%, Lmin=-6502.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1140, ncalls=1348, regioncalls=52000, ndraw=40, logz=-4917.95, remainder_fraction=100.0000%, Lmin=-4673.62, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1358, regioncalls=52480, ndraw=40, logz=-4140.24, remainder_fraction=100.0000%, Lmin=-4068.57, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1368, regioncalls=52880, ndraw=40, logz=-3620.58, remainder_fraction=100.0000%, Lmin=-3375.59, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1380, regioncalls=53360, ndraw=40, logz=-2712.22, remainder_fraction=100.0000%, Lmin=-2672.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1173, ncalls=1383, regioncalls=53520, ndraw=40, logz=-2576.74, remainder_fraction=100.0000%, Lmin=-2536.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1180, ncalls=1391, regioncalls=53840, ndraw=40, logz=-2224.70, remainder_fraction=100.0000%, Lmin=-2201.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1190, ncalls=1404, regioncalls=54360, ndraw=40, logz=-1915.51, remainder_fraction=100.0000%, Lmin=-1898.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1417, regioncalls=54880, ndraw=40, logz=-1600.73, remainder_fraction=100.0000%, Lmin=-1576.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=1429, regioncalls=55360, ndraw=40, logz=-1273.46, remainder_fraction=100.0000%, Lmin=-1210.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1220, ncalls=1440, regioncalls=55800, ndraw=40, logz=-1035.19, remainder_fraction=100.0000%, Lmin=-936.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=1454, regioncalls=56360, ndraw=40, logz=-747.28, remainder_fraction=100.0000%, Lmin=-722.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1466, regioncalls=56840, ndraw=40, logz=-637.32, remainder_fraction=100.0000%, Lmin=-618.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=1468, regioncalls=56960, ndraw=40, logz=-622.12, remainder_fraction=100.0000%, Lmin=-567.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1476, regioncalls=57280, ndraw=40, logz=-453.14, remainder_fraction=100.0000%, Lmin=-420.93, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1487, regioncalls=57720, ndraw=40, logz=-343.36, remainder_fraction=100.0000%, Lmin=-321.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1265, ncalls=1493, regioncalls=58000, ndraw=40, logz=-324.71, remainder_fraction=100.0000%, Lmin=-304.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1270, ncalls=1498, regioncalls=58200, ndraw=40, logz=-293.07, remainder_fraction=100.0000%, Lmin=-269.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1508, regioncalls=58600, ndraw=40, logz=-244.96, remainder_fraction=100.0000%, Lmin=-220.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1288, ncalls=1517, regioncalls=59040, ndraw=40, logz=-198.68, remainder_fraction=100.0000%, Lmin=-179.69, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=1519, regioncalls=59120, ndraw=40, logz=-190.06, remainder_fraction=100.0000%, Lmin=-163.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1532, regioncalls=59640, ndraw=40, logz=-156.72, remainder_fraction=100.0000%, Lmin=-138.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1310, ncalls=1544, regioncalls=60160, ndraw=40, logz=-144.27, remainder_fraction=100.0000%, Lmin=-124.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1555, regioncalls=60600, ndraw=40, logz=-107.47, remainder_fraction=100.0000%, Lmin=-88.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=1566, regioncalls=61040, ndraw=40, logz=-93.99, remainder_fraction=100.0000%, Lmin=-70.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1334, ncalls=1572, regioncalls=61320, ndraw=40, logz=-84.38, remainder_fraction=100.0000%, Lmin=-66.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1340, ncalls=1578, regioncalls=61560, ndraw=40, logz=-78.05, remainder_fraction=100.0000%, Lmin=-59.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1591, regioncalls=62080, ndraw=40, logz=-68.06, remainder_fraction=100.0000%, Lmin=-47.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=1598, regioncalls=62400, ndraw=40, logz=-55.87, remainder_fraction=100.0000%, Lmin=-36.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=1601, regioncalls=62520, ndraw=40, logz=-51.83, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1370, ncalls=1613, regioncalls=63000, ndraw=40, logz=-46.66, remainder_fraction=100.0000%, Lmin=-28.87, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=1626, regioncalls=63560, ndraw=40, logz=-42.36, remainder_fraction=100.0000%, Lmin=-24.81, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1390, ncalls=1637, regioncalls=64000, ndraw=40, logz=-38.60, remainder_fraction=100.0000%, Lmin=-21.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1648, regioncalls=64440, ndraw=40, logz=-35.49, remainder_fraction=100.0000%, Lmin=-18.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1403, ncalls=1652, regioncalls=64640, ndraw=40, logz=-34.86, remainder_fraction=100.0000%, Lmin=-17.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=1662, regioncalls=65040, ndraw=40, logz=-32.76, remainder_fraction=100.0000%, Lmin=-15.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1420, ncalls=1673, regioncalls=65480, ndraw=40, logz=-30.69, remainder_fraction=100.0000%, Lmin=-13.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1426, ncalls=1680, regioncalls=65840, ndraw=40, logz=-29.49, remainder_fraction=99.9999%, Lmin=-12.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1430, ncalls=1684, regioncalls=66000, ndraw=40, logz=-28.14, remainder_fraction=99.9997%, Lmin=-10.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1697, regioncalls=66520, ndraw=40, logz=-26.12, remainder_fraction=99.9977%, Lmin=-8.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=1710, regioncalls=67040, ndraw=40, logz=-24.32, remainder_fraction=99.9859%, Lmin=-7.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1460, ncalls=1720, regioncalls=67440, ndraw=40, logz=-23.03, remainder_fraction=99.9451%, Lmin=-5.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1470, ncalls=1731, regioncalls=67880, ndraw=40, logz=-21.49, remainder_fraction=99.7426%, Lmin=-4.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=1733, regioncalls=68040, ndraw=40, logz=-21.26, remainder_fraction=99.6811%, Lmin=-3.97, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=1741, regioncalls=68360, ndraw=40, logz=-20.36, remainder_fraction=99.1955%, Lmin=-3.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1490, ncalls=1751, regioncalls=68760, ndraw=40, logz=-19.45, remainder_fraction=97.9467%, Lmin=-2.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1495, ncalls=1756, regioncalls=69000, ndraw=40, logz=-19.13, remainder_fraction=97.1779%, Lmin=-2.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=1761, regioncalls=69200, ndraw=40, logz=-18.86, remainder_fraction=96.3847%, Lmin=-2.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1510, ncalls=1774, regioncalls=69720, ndraw=40, logz=-18.41, remainder_fraction=94.3893%, Lmin=-1.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=1782, regioncalls=70080, ndraw=40, logz=-18.08, remainder_fraction=92.2357%, Lmin=-1.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=1784, regioncalls=70160, ndraw=40, logz=-18.01, remainder_fraction=91.6178%, Lmin=-1.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=1795, regioncalls=70600, ndraw=40, logz=-17.66, remainder_fraction=88.2455%, Lmin=-1.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1540, ncalls=1806, regioncalls=71040, ndraw=40, logz=-17.37, remainder_fraction=84.3049%, Lmin=-0.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=1807, regioncalls=71160, ndraw=40, logz=-17.34, remainder_fraction=83.8617%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=1816, regioncalls=71520, ndraw=40, logz=-17.13, remainder_fraction=79.7528%, Lmin=-0.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=1826, regioncalls=71920, ndraw=40, logz=-16.92, remainder_fraction=75.2117%, Lmin=-0.67, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1564, ncalls=1830, regioncalls=72120, ndraw=40, logz=-16.85, remainder_fraction=73.4569%, Lmin=-0.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1570, ncalls=1837, regioncalls=72400, ndraw=40, logz=-16.75, remainder_fraction=70.7038%, Lmin=-0.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1580, ncalls=1849, regioncalls=72880, ndraw=40, logz=-16.59, remainder_fraction=66.0335%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1587, ncalls=1858, regioncalls=73280, ndraw=40, logz=-16.50, remainder_fraction=62.7706%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=1861, regioncalls=73400, ndraw=40, logz=-16.46, remainder_fraction=61.3265%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=1872, regioncalls=73840, ndraw=40, logz=-16.35, remainder_fraction=56.6426%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1610, ncalls=1883, regioncalls=74400, ndraw=40, logz=-16.25, remainder_fraction=52.0720%, Lmin=-0.20, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-4e-06 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 1887 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [-1.94762221e-01 -1.80163717e-05 0.00000000e+00 5.00000005e-01 1.06002728e-04]: u=[0.50000001] -> p=[0.000106] -> L=-1.801637165560648e-05 WARNING ultranest:integrator.py:1282 Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.004417743572744871 DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpmtve497_, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 DEBUG ultranest:integrator.py:1271 Testing resume consistency: [-1.94762221e-01 -1.80163717e-05 0.00000000e+00 5.00000005e-01 1.06002728e-04]: u=[0.50000001] -> p=[0.000106] -> L=-1.801637165560648e-05 WARNING ultranest:integrator.py:1282 Trying to resume from previous run, but likelihood function gives different result: [0.50000001] gave -1.801637165560648e-05, now -0.018817470773834135 INFO ultranest:integrator.py:1200 trying to salvage points from previous, different run ... INFO ultranest:integrator.py:2364 Resuming from 1344 stored points DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=1887, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977130652164.57, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=10, ncalls=1887, regioncalls=0, ndraw=40, logz=-41932561616957.05, remainder_fraction=100.0000%, Lmin=-40508380523197.54, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=20, ncalls=1887, regioncalls=0, ndraw=40, logz=-33237566708988.97, remainder_fraction=100.0000%, Lmin=-33004789701473.93, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=23, ncalls=1887, regioncalls=0, ndraw=40, logz=-32543005101534.51, remainder_fraction=100.0000%, Lmin=-32265055588306.13, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=30, ncalls=1887, regioncalls=0, ndraw=40, logz=-29684135382657.41, remainder_fraction=100.0000%, Lmin=-29654730105904.14, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=1887, regioncalls=0, ndraw=40, logz=-26024312894898.02, remainder_fraction=100.0000%, Lmin=-25864312944260.04, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1887, regioncalls=0, ndraw=40, logz=-21618902153982.53, remainder_fraction=100.0000%, Lmin=-20657642566722.29, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=60, ncalls=1887, regioncalls=0, ndraw=40, logz=-16736504238198.11, remainder_fraction=100.0000%, Lmin=-16631670426566.43, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=69, ncalls=1887, regioncalls=0, ndraw=40, logz=-14754876322254.05, remainder_fraction=100.0000%, Lmin=-13974009098336.24, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=70, ncalls=1887, regioncalls=0, ndraw=40, logz=-13974009098341.54, remainder_fraction=100.0000%, Lmin=-13902691092692.20, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=1887, regioncalls=0, ndraw=40, logz=-12514434158996.97, remainder_fraction=100.0000%, Lmin=-12508280160805.51, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1887, regioncalls=0, ndraw=40, logz=-10193266585284.78, remainder_fraction=100.0000%, Lmin=-9640969441459.09, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1887, regioncalls=0, ndraw=40, logz=-8200640042061.08, remainder_fraction=100.0000%, Lmin=-8082128854974.46, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=110, ncalls=1887, regioncalls=0, ndraw=40, logz=-7173864396385.38, remainder_fraction=100.0000%, Lmin=-6962108578565.77, Lmax=-14202379464.00 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=1887, regioncalls=0, ndraw=40, logz=-6806897587530.23, remainder_fraction=100.0000%, Lmin=-6798571388126.72, Lmax=-2101547083.83 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=1887, regioncalls=0, ndraw=40, logz=-6322458415316.69, remainder_fraction=100.0000%, Lmin=-6247007170976.70, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=130, ncalls=1887, regioncalls=0, ndraw=40, logz=-5036134943448.93, remainder_fraction=100.0000%, Lmin=-5013134788697.02, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=138, ncalls=1887, regioncalls=0, ndraw=40, logz=-4680998274552.75, remainder_fraction=100.0000%, Lmin=-4635047605209.84, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=140, ncalls=1887, regioncalls=0, ndraw=40, logz=-4566343118025.00, remainder_fraction=100.0000%, Lmin=-4489051212975.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1887, regioncalls=0, ndraw=40, logz=-3426887493332.78, remainder_fraction=100.0000%, Lmin=-3417861538699.18, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=1887, regioncalls=0, ndraw=40, logz=-2961968933275.30, remainder_fraction=100.0000%, Lmin=-2922088752807.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=161, ncalls=1887, regioncalls=0, ndraw=40, logz=-2922088752813.53, remainder_fraction=100.0000%, Lmin=-2889249026647.98, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=170, ncalls=1887, regioncalls=0, ndraw=40, logz=-2133520458854.56, remainder_fraction=100.0000%, Lmin=-2131391494738.28, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=1887, regioncalls=0, ndraw=40, logz=-1843763865927.44, remainder_fraction=100.0000%, Lmin=-1836388694440.05, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=190, ncalls=1887, regioncalls=0, ndraw=40, logz=-1479337782796.89, remainder_fraction=100.0000%, Lmin=-1477275161598.16, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1887, regioncalls=0, ndraw=40, logz=-1162163859144.88, remainder_fraction=100.0000%, Lmin=-1149513065897.32, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=1887, regioncalls=0, ndraw=40, logz=-1098683444075.02, remainder_fraction=100.0000%, Lmin=-1085732909181.43, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=210, ncalls=1887, regioncalls=0, ndraw=40, logz=-1062199358541.67, remainder_fraction=100.0000%, Lmin=-1036687628030.10, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=220, ncalls=1887, regioncalls=0, ndraw=40, logz=-871674598325.47, remainder_fraction=100.0000%, Lmin=-839966254814.02, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=230, ncalls=1887, regioncalls=0, ndraw=40, logz=-715976244645.11, remainder_fraction=100.0000%, Lmin=-706773038624.09, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=1887, regioncalls=0, ndraw=40, logz=-593422400013.35, remainder_fraction=100.0000%, Lmin=-576444226592.45, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1887, regioncalls=0, ndraw=40, logz=-511877162695.34, remainder_fraction=100.0000%, Lmin=-501759175033.50, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=253, ncalls=1887, regioncalls=0, ndraw=40, logz=-478675270993.01, remainder_fraction=100.0000%, Lmin=-455241244398.12, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=260, ncalls=1887, regioncalls=0, ndraw=40, logz=-423629301043.88, remainder_fraction=100.0000%, Lmin=-418959428701.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1887, regioncalls=0, ndraw=40, logz=-337456141589.74, remainder_fraction=100.0000%, Lmin=-332414910905.61, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=1887, regioncalls=0, ndraw=40, logz=-280040929879.21, remainder_fraction=100.0000%, Lmin=-266139053666.23, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=1887, regioncalls=0, ndraw=40, logz=-219987026484.12, remainder_fraction=100.0000%, Lmin=-217170145697.48, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=299, ncalls=1887, regioncalls=0, ndraw=40, logz=-186287694004.38, remainder_fraction=100.0000%, Lmin=-186217028556.61, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=1887, regioncalls=0, ndraw=40, logz=-186217028564.21, remainder_fraction=100.0000%, Lmin=-176257104355.97, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=310, ncalls=1887, regioncalls=0, ndraw=40, logz=-136032191762.64, remainder_fraction=100.0000%, Lmin=-134941822934.04, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=1887, regioncalls=0, ndraw=40, logz=-106028851032.08, remainder_fraction=100.0000%, Lmin=-105574709016.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=322, ncalls=1887, regioncalls=0, ndraw=40, logz=-102631536278.64, remainder_fraction=100.0000%, Lmin=-101211275659.83, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=330, ncalls=1887, regioncalls=0, ndraw=40, logz=-85746803486.61, remainder_fraction=100.0000%, Lmin=-84170482118.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=1887, regioncalls=0, ndraw=40, logz=-78454626629.19, remainder_fraction=100.0000%, Lmin=-77856776437.56, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=345, ncalls=1887, regioncalls=0, ndraw=40, logz=-73766873722.80, remainder_fraction=100.0000%, Lmin=-70940842137.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=1887, regioncalls=0, ndraw=40, logz=-65217905845.25, remainder_fraction=100.0000%, Lmin=-65071451833.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=1887, regioncalls=0, ndraw=40, logz=-52784236129.54, remainder_fraction=100.0000%, Lmin=-52465580099.93, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=368, ncalls=1887, regioncalls=0, ndraw=40, logz=-44886066221.08, remainder_fraction=100.0000%, Lmin=-44881243742.26, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=370, ncalls=1887, regioncalls=0, ndraw=40, logz=-44337042250.65, remainder_fraction=100.0000%, Lmin=-43924358829.89, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=380, ncalls=1887, regioncalls=0, ndraw=40, logz=-38174061718.26, remainder_fraction=100.0000%, Lmin=-38166189481.55, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=390, ncalls=1887, regioncalls=0, ndraw=40, logz=-30564872448.47, remainder_fraction=100.0000%, Lmin=-29014354349.17, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=391, ncalls=1887, regioncalls=0, ndraw=40, logz=-29014354357.68, remainder_fraction=100.0000%, Lmin=-28739169762.10, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=1887, regioncalls=0, ndraw=40, logz=-25254336247.24, remainder_fraction=100.0000%, Lmin=-25189114982.19, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=410, ncalls=1887, regioncalls=0, ndraw=40, logz=-21660445808.58, remainder_fraction=100.0000%, Lmin=-21548416693.23, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=420, ncalls=1887, regioncalls=0, ndraw=40, logz=-17503238946.67, remainder_fraction=100.0000%, Lmin=-16696447145.52, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=430, ncalls=1887, regioncalls=0, ndraw=40, logz=-13958008423.01, remainder_fraction=100.0000%, Lmin=-13215512620.83, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=437, ncalls=1887, regioncalls=0, ndraw=40, logz=-11682652172.69, remainder_fraction=100.0000%, Lmin=-11587026393.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=1887, regioncalls=0, ndraw=40, logz=-11355000646.46, remainder_fraction=100.0000%, Lmin=-11308563740.41, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=1887, regioncalls=0, ndraw=40, logz=-8954712524.52, remainder_fraction=100.0000%, Lmin=-8802373012.54, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=460, ncalls=1887, regioncalls=0, ndraw=40, logz=-7358645003.22, remainder_fraction=100.0000%, Lmin=-7312899818.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=470, ncalls=1887, regioncalls=0, ndraw=40, logz=-5913695438.14, remainder_fraction=100.0000%, Lmin=-5686821523.11, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1887, regioncalls=0, ndraw=40, logz=-4561832470.13, remainder_fraction=100.0000%, Lmin=-4534672020.81, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=483, ncalls=1887, regioncalls=0, ndraw=40, logz=-4341461702.01, remainder_fraction=100.0000%, Lmin=-4317165601.80, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=490, ncalls=1887, regioncalls=0, ndraw=40, logz=-3683672787.04, remainder_fraction=100.0000%, Lmin=-3668730617.87, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=1887, regioncalls=0, ndraw=40, logz=-3119303096.09, remainder_fraction=100.0000%, Lmin=-3077098913.76, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=510, ncalls=1887, regioncalls=0, ndraw=40, logz=-2471309564.08, remainder_fraction=100.0000%, Lmin=-2451630298.77, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1887, regioncalls=0, ndraw=40, logz=-2046821131.87, remainder_fraction=100.0000%, Lmin=-1963038217.51, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=529, ncalls=1887, regioncalls=0, ndraw=40, logz=-1683072731.21, remainder_fraction=100.0000%, Lmin=-1655492501.92, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=530, ncalls=1887, regioncalls=0, ndraw=40, logz=-1655492511.82, remainder_fraction=100.0000%, Lmin=-1587917772.00, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1887, regioncalls=0, ndraw=40, logz=-1345683074.51, remainder_fraction=100.0000%, Lmin=-1324117506.82, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=1887, regioncalls=0, ndraw=40, logz=-842696346.31, remainder_fraction=100.0000%, Lmin=-842106835.16, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=1887, regioncalls=0, ndraw=40, logz=-829479250.06, remainder_fraction=100.0000%, Lmin=-821747435.36, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1887, regioncalls=0, ndraw=40, logz=-768673440.75, remainder_fraction=100.0000%, Lmin=-741047752.26, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=570, ncalls=1887, regioncalls=0, ndraw=40, logz=-598454607.33, remainder_fraction=100.0000%, Lmin=-588036920.17, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=575, ncalls=1887, regioncalls=0, ndraw=40, logz=-561645953.60, remainder_fraction=100.0000%, Lmin=-542758608.59, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=580, ncalls=1887, regioncalls=0, ndraw=40, logz=-523320459.46, remainder_fraction=100.0000%, Lmin=-520436376.06, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=590, ncalls=1887, regioncalls=0, ndraw=40, logz=-389296698.92, remainder_fraction=100.0000%, Lmin=-384221646.77, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=1887, regioncalls=0, ndraw=40, logz=-330211008.59, remainder_fraction=100.0000%, Lmin=-310876057.20, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1887, regioncalls=0, ndraw=40, logz=-291723237.97, remainder_fraction=100.0000%, Lmin=-277166367.13, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=610, ncalls=1887, regioncalls=0, ndraw=40, logz=-245519872.33, remainder_fraction=100.0000%, Lmin=-244121619.74, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=620, ncalls=1887, regioncalls=0, ndraw=40, logz=-222407705.13, remainder_fraction=100.0000%, Lmin=-218430286.78, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=621, ncalls=1887, regioncalls=0, ndraw=40, logz=-218430297.59, remainder_fraction=100.0000%, Lmin=-215262149.04, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1887, regioncalls=0, ndraw=40, logz=-179662857.52, remainder_fraction=100.0000%, Lmin=-179075466.49, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1887, regioncalls=0, ndraw=40, logz=-147160936.70, remainder_fraction=100.0000%, Lmin=-146186278.28, Lmax=-19901.81 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=1887, regioncalls=0, ndraw=40, logz=-139596071.91, remainder_fraction=100.0000%, Lmin=-139229171.90, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=1887, regioncalls=0, ndraw=40, logz=-128987747.66, remainder_fraction=100.0000%, Lmin=-127082912.47, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=660, ncalls=1887, regioncalls=0, ndraw=40, logz=-108094158.74, remainder_fraction=100.0000%, Lmin=-105746739.75, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=667, ncalls=1887, regioncalls=0, ndraw=40, logz=-99582148.92, remainder_fraction=100.0000%, Lmin=-99059562.04, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=670, ncalls=1887, regioncalls=0, ndraw=40, logz=-95151375.11, remainder_fraction=100.0000%, Lmin=-93695215.20, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1887, regioncalls=0, ndraw=40, logz=-78679116.90, remainder_fraction=100.0000%, Lmin=-76847161.50, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=690, ncalls=1887, regioncalls=0, ndraw=40, logz=-67131957.92, remainder_fraction=100.0000%, Lmin=-66448748.01, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=1887, regioncalls=0, ndraw=40, logz=-52435024.29, remainder_fraction=100.0000%, Lmin=-52096951.40, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=710, ncalls=1887, regioncalls=0, ndraw=40, logz=-42465191.36, remainder_fraction=100.0000%, Lmin=-40949386.18, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=713, ncalls=1887, regioncalls=0, ndraw=40, logz=-40873207.94, remainder_fraction=100.0000%, Lmin=-40680461.02, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1887, regioncalls=0, ndraw=40, logz=-34272297.45, remainder_fraction=100.0000%, Lmin=-34010952.05, Lmax=-6001.03 DEBUG ultranest:integrator.py:2610 iteration=730, ncalls=1887, regioncalls=0, ndraw=40, logz=-28152453.57, remainder_fraction=100.0000%, Lmin=-27575809.36, Lmax=-6001.03 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=1887, regioncalls=0, ndraw=40, logz=-24901873.14, remainder_fraction=100.0000%, Lmin=-24584385.70, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=1887, regioncalls=0, ndraw=40, logz=-18110812.08, remainder_fraction=100.0000%, Lmin=-17737948.70, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=759, ncalls=1887, regioncalls=0, ndraw=40, logz=-15302856.79, remainder_fraction=100.0000%, Lmin=-15168411.63, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1887, regioncalls=0, ndraw=40, logz=-15168423.83, remainder_fraction=100.0000%, Lmin=-14226207.64, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=770, ncalls=1887, regioncalls=0, ndraw=40, logz=-11388935.83, remainder_fraction=100.0000%, Lmin=-11170160.74, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=780, ncalls=1887, regioncalls=0, ndraw=40, logz=-9539486.20, remainder_fraction=100.0000%, Lmin=-9255020.99, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=782, ncalls=1887, regioncalls=0, ndraw=40, logz=-9247740.34, remainder_fraction=100.0000%, Lmin=-9220863.41, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=790, ncalls=1887, regioncalls=0, ndraw=40, logz=-8203667.81, remainder_fraction=100.0000%, Lmin=-7969059.95, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1887, regioncalls=0, ndraw=40, logz=-6152195.90, remainder_fraction=100.0000%, Lmin=-6110909.52, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1887, regioncalls=0, ndraw=40, logz=-5168110.71, remainder_fraction=100.0000%, Lmin=-5104656.58, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=820, ncalls=1887, regioncalls=0, ndraw=40, logz=-4349040.12, remainder_fraction=100.0000%, Lmin=-4125558.07, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=830, ncalls=1887, regioncalls=0, ndraw=40, logz=-2816427.18, remainder_fraction=100.0000%, Lmin=-2814439.32, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1887, regioncalls=0, ndraw=40, logz=-2391680.21, remainder_fraction=100.0000%, Lmin=-2352470.82, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=1887, regioncalls=0, ndraw=40, logz=-1694108.33, remainder_fraction=100.0000%, Lmin=-1689081.73, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=851, ncalls=1887, regioncalls=0, ndraw=40, logz=-1689094.84, remainder_fraction=100.0000%, Lmin=-1641951.96, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=860, ncalls=1887, regioncalls=0, ndraw=40, logz=-1391644.76, remainder_fraction=100.0000%, Lmin=-1379047.10, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=870, ncalls=1887, regioncalls=0, ndraw=40, logz=-1016250.69, remainder_fraction=100.0000%, Lmin=-1006089.59, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=874, ncalls=1887, regioncalls=0, ndraw=40, logz=-920877.00, remainder_fraction=100.0000%, Lmin=-900085.39, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1887, regioncalls=0, ndraw=40, logz=-823336.66, remainder_fraction=100.0000%, Lmin=-820186.88, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=890, ncalls=1887, regioncalls=0, ndraw=40, logz=-718367.84, remainder_fraction=100.0000%, Lmin=-716624.62, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=897, ncalls=1887, regioncalls=0, ndraw=40, logz=-639629.99, remainder_fraction=100.0000%, Lmin=-639396.18, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1887, regioncalls=0, ndraw=40, logz=-596673.66, remainder_fraction=100.0000%, Lmin=-575979.25, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=910, ncalls=1887, regioncalls=0, ndraw=40, logz=-491530.15, remainder_fraction=100.0000%, Lmin=-490445.93, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1887, regioncalls=0, ndraw=40, logz=-403995.67, remainder_fraction=100.0000%, Lmin=-396361.92, Lmax=-24.58 DEBUG ultranest:integrator.py:2610 iteration=930, ncalls=1887, regioncalls=0, ndraw=40, logz=-335628.28, remainder_fraction=100.0000%, Lmin=-335591.94, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=940, ncalls=1887, regioncalls=0, ndraw=40, logz=-281138.11, remainder_fraction=100.0000%, Lmin=-269426.35, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=943, ncalls=1887, regioncalls=0, ndraw=40, logz=-266966.68, remainder_fraction=100.0000%, Lmin=-259391.44, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=1887, regioncalls=0, ndraw=40, logz=-232224.92, remainder_fraction=100.0000%, Lmin=-227986.30, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1887, regioncalls=0, ndraw=40, logz=-195207.53, remainder_fraction=100.0000%, Lmin=-192214.74, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=966, ncalls=1887, regioncalls=0, ndraw=40, logz=-172769.03, remainder_fraction=100.0000%, Lmin=-171647.55, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=970, ncalls=1887, regioncalls=0, ndraw=40, logz=-158733.95, remainder_fraction=100.0000%, Lmin=-156726.85, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=980, ncalls=1887, regioncalls=0, ndraw=40, logz=-123115.01, remainder_fraction=100.0000%, Lmin=-122192.77, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=1887, regioncalls=0, ndraw=40, logz=-98858.17, remainder_fraction=100.0000%, Lmin=-94395.69, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1887, regioncalls=0, ndraw=40, logz=-94410.19, remainder_fraction=100.0000%, Lmin=-93791.71, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1887, regioncalls=0, ndraw=40, logz=-75715.19, remainder_fraction=100.0000%, Lmin=-75082.19, Lmax=-4.23 DEBUG ultranest:integrator.py:2610 iteration=1010, ncalls=1887, regioncalls=0, ndraw=40, logz=-69119.40, remainder_fraction=100.0000%, Lmin=-69103.96, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1012, ncalls=1887, regioncalls=0, ndraw=40, logz=-68077.33, remainder_fraction=100.0000%, Lmin=-66958.70, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1020, ncalls=1887, regioncalls=0, ndraw=40, logz=-59547.14, remainder_fraction=100.0000%, Lmin=-56249.53, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1030, ncalls=1887, regioncalls=0, ndraw=40, logz=-49103.98, remainder_fraction=100.0000%, Lmin=-46375.62, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1035, ncalls=1887, regioncalls=0, ndraw=40, logz=-42750.79, remainder_fraction=100.0000%, Lmin=-40665.18, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1887, regioncalls=0, ndraw=40, logz=-38252.82, remainder_fraction=100.0000%, Lmin=-36587.26, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=1887, regioncalls=0, ndraw=40, logz=-33612.77, remainder_fraction=100.0000%, Lmin=-32462.69, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1058, ncalls=1887, regioncalls=0, ndraw=40, logz=-28541.51, remainder_fraction=100.0000%, Lmin=-28487.57, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=1887, regioncalls=0, ndraw=40, logz=-28412.18, remainder_fraction=100.0000%, Lmin=-28188.21, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1070, ncalls=1887, regioncalls=0, ndraw=40, logz=-23692.05, remainder_fraction=100.0000%, Lmin=-21662.39, Lmax=-3.86 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1887, regioncalls=0, ndraw=40, logz=-17760.01, remainder_fraction=100.0000%, Lmin=-17456.73, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1090, ncalls=1887, regioncalls=0, ndraw=40, logz=-13838.44, remainder_fraction=100.0000%, Lmin=-13583.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=1887, regioncalls=0, ndraw=40, logz=-11478.78, remainder_fraction=100.0000%, Lmin=-11399.84, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1104, ncalls=1887, regioncalls=0, ndraw=40, logz=-10856.65, remainder_fraction=100.0000%, Lmin=-10434.89, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1110, ncalls=1887, regioncalls=0, ndraw=40, logz=-9705.10, remainder_fraction=100.0000%, Lmin=-9378.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1887, regioncalls=0, ndraw=40, logz=-7371.71, remainder_fraction=100.0000%, Lmin=-7306.69, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1127, ncalls=1887, regioncalls=0, ndraw=40, logz=-6854.87, remainder_fraction=100.0000%, Lmin=-6766.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1130, ncalls=1887, regioncalls=0, ndraw=40, logz=-6580.27, remainder_fraction=100.0000%, Lmin=-6479.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1140, ncalls=1887, regioncalls=0, ndraw=40, logz=-4937.77, remainder_fraction=100.0000%, Lmin=-4692.98, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=1887, regioncalls=0, ndraw=40, logz=-4122.10, remainder_fraction=100.0000%, Lmin=-4067.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1887, regioncalls=0, ndraw=40, logz=-3637.58, remainder_fraction=100.0000%, Lmin=-3359.18, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1887, regioncalls=0, ndraw=40, logz=-2706.36, remainder_fraction=100.0000%, Lmin=-2657.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1180, ncalls=1887, regioncalls=0, ndraw=40, logz=-2238.02, remainder_fraction=100.0000%, Lmin=-2188.11, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1190, ncalls=1887, regioncalls=0, ndraw=40, logz=-1903.20, remainder_fraction=100.0000%, Lmin=-1886.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1887, regioncalls=0, ndraw=40, logz=-1581.52, remainder_fraction=100.0000%, Lmin=-1542.77, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1210, ncalls=1887, regioncalls=0, ndraw=40, logz=-1237.02, remainder_fraction=100.0000%, Lmin=-1202.19, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1219, ncalls=1887, regioncalls=0, ndraw=40, logz=-1026.17, remainder_fraction=100.0000%, Lmin=-935.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1220, ncalls=1887, regioncalls=0, ndraw=40, logz=-952.04, remainder_fraction=100.0000%, Lmin=-931.89, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1230, ncalls=1887, regioncalls=0, ndraw=40, logz=-743.38, remainder_fraction=100.0000%, Lmin=-707.99, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1887, regioncalls=0, ndraw=40, logz=-629.08, remainder_fraction=100.0000%, Lmin=-611.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1242, ncalls=1887, regioncalls=0, ndraw=40, logz=-591.43, remainder_fraction=100.0000%, Lmin=-540.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=1894, regioncalls=320, ndraw=40, logz=-443.82, remainder_fraction=100.0000%, Lmin=-423.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1906, regioncalls=840, ndraw=40, logz=-338.27, remainder_fraction=100.0000%, Lmin=-319.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1265, ncalls=1911, regioncalls=1080, ndraw=40, logz=-320.42, remainder_fraction=100.0000%, Lmin=-299.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1270, ncalls=1916, regioncalls=1280, ndraw=40, logz=-308.97, remainder_fraction=100.0000%, Lmin=-274.96, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1927, regioncalls=1720, ndraw=40, logz=-258.39, remainder_fraction=100.0000%, Lmin=-236.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1288, ncalls=1936, regioncalls=2160, ndraw=40, logz=-200.98, remainder_fraction=100.0000%, Lmin=-179.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1290, ncalls=1938, regioncalls=2240, ndraw=40, logz=-193.77, remainder_fraction=100.0000%, Lmin=-169.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=1949, regioncalls=2680, ndraw=40, logz=-161.93, remainder_fraction=100.0000%, Lmin=-130.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1310, ncalls=1962, regioncalls=3200, ndraw=40, logz=-122.86, remainder_fraction=100.0000%, Lmin=-100.59, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1972, regioncalls=3600, ndraw=40, logz=-102.14, remainder_fraction=100.0000%, Lmin=-82.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=1982, regioncalls=4000, ndraw=40, logz=-83.98, remainder_fraction=100.0000%, Lmin=-65.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1334, ncalls=1987, regioncalls=4280, ndraw=40, logz=-77.82, remainder_fraction=100.0000%, Lmin=-60.49, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1340, ncalls=1993, regioncalls=4520, ndraw=40, logz=-74.57, remainder_fraction=100.0000%, Lmin=-54.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2004, regioncalls=4960, ndraw=40, logz=-66.17, remainder_fraction=100.0000%, Lmin=-43.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=2012, regioncalls=5360, ndraw=40, logz=-50.51, remainder_fraction=100.0000%, Lmin=-31.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2015, regioncalls=5480, ndraw=40, logz=-48.69, remainder_fraction=100.0000%, Lmin=-31.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1370, ncalls=2027, regioncalls=5960, ndraw=40, logz=-43.60, remainder_fraction=100.0000%, Lmin=-26.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1380, ncalls=2037, regioncalls=6400, ndraw=40, logz=-39.07, remainder_fraction=100.0000%, Lmin=-21.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1390, ncalls=2049, regioncalls=6880, ndraw=40, logz=-35.61, remainder_fraction=100.0000%, Lmin=-18.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2059, regioncalls=7320, ndraw=40, logz=-32.64, remainder_fraction=100.0000%, Lmin=-14.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1410, ncalls=2070, regioncalls=7760, ndraw=40, logz=-28.95, remainder_fraction=99.9999%, Lmin=-11.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1420, ncalls=2082, regioncalls=8240, ndraw=40, logz=-26.64, remainder_fraction=99.9987%, Lmin=-9.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1426, ncalls=2089, regioncalls=8560, ndraw=40, logz=-25.66, remainder_fraction=99.9964%, Lmin=-8.50, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1430, ncalls=2094, regioncalls=8760, ndraw=40, logz=-24.86, remainder_fraction=99.9918%, Lmin=-7.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2104, regioncalls=9160, ndraw=40, logz=-23.41, remainder_fraction=99.9664%, Lmin=-6.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=2114, regioncalls=9560, ndraw=40, logz=-22.13, remainder_fraction=99.8781%, Lmin=-4.83, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1460, ncalls=2124, regioncalls=9960, ndraw=40, logz=-20.87, remainder_fraction=99.5678%, Lmin=-3.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1470, ncalls=2134, regioncalls=10360, ndraw=40, logz=-20.02, remainder_fraction=98.9715%, Lmin=-3.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=2136, regioncalls=10480, ndraw=40, logz=-19.89, remainder_fraction=98.8134%, Lmin=-3.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2144, regioncalls=10800, ndraw=40, logz=-19.47, remainder_fraction=98.2117%, Lmin=-2.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1490, ncalls=2155, regioncalls=11240, ndraw=40, logz=-18.95, remainder_fraction=97.0160%, Lmin=-2.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=2167, regioncalls=11720, ndraw=40, logz=-18.37, remainder_fraction=94.7928%, Lmin=-1.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1510, ncalls=2178, regioncalls=12160, ndraw=40, logz=-17.91, remainder_fraction=91.7658%, Lmin=-1.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1518, ncalls=2188, regioncalls=12640, ndraw=40, logz=-17.60, remainder_fraction=88.8301%, Lmin=-1.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2190, regioncalls=12720, ndraw=40, logz=-17.53, remainder_fraction=87.9963%, Lmin=-1.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2201, regioncalls=13160, ndraw=40, logz=-17.23, remainder_fraction=83.9101%, Lmin=-0.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1540, ncalls=2211, regioncalls=13560, ndraw=40, logz=-16.98, remainder_fraction=79.3301%, Lmin=-0.77, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1541, ncalls=2212, regioncalls=13640, ndraw=40, logz=-16.96, remainder_fraction=78.8284%, Lmin=-0.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=2222, regioncalls=14040, ndraw=40, logz=-16.78, remainder_fraction=74.7285%, Lmin=-0.66, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2236, regioncalls=14600, ndraw=40, logz=-16.61, remainder_fraction=70.1478%, Lmin=-0.54, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1570, ncalls=2246, regioncalls=15000, ndraw=40, logz=-16.46, remainder_fraction=65.2006%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1580, ncalls=2258, regioncalls=15480, ndraw=40, logz=-16.33, remainder_fraction=60.3402%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1587, ncalls=2267, regioncalls=15880, ndraw=40, logz=-16.25, remainder_fraction=57.1348%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1590, ncalls=2270, regioncalls=16000, ndraw=40, logz=-16.22, remainder_fraction=55.7549%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2282, regioncalls=16480, ndraw=40, logz=-16.12, remainder_fraction=51.2608%, Lmin=-0.23, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-2e-05 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 2284 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2671 Reached maximum number of improvement loops. INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_store.py::test_hdf5_store

0.11

Passed

tests/test_store.py::test_nullstore

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_transforms.py::test_affine_transform

0.09

Passed

tests/test_transforms.py::test_wrap

0.03

Passed

tests/test_samplingpath.py::test_forward

2.39

[gw7] linux -- Python 3.10.6 /usr/bin/python3
[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_vectorize

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_is_affine_transform

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[0-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[4-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[10-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[17-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[31-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[100-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[1000-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-1]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-4]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-10]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-37]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-53]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-100]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-1000]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_distributed_work_chunk_size[513-513]

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_viz.py::test_rounding_pos

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_viz.py::test_rounding_u

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_viz.py::test_rounding_negpos

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_viz.py::test_rounding_withguess

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_viz.py::test_fmt

0.00

[gw8] linux -- Python 3.10.6 /usr/bin/python3
[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3[gw8] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_popstepsampling.py::test_stepsampler_cubeslice

53.12

[gw4] linux -- Python 3.10.6 /usr/bin/python3
[gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3[gw4] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-29.02..-0.12 [-29.0187..-8.0090] | it/evals=0/536 eff=0.0000% N=400 Z=-31.3(0.00%) | Like=-26.51..-0.12 [-29.0187..-8.0090] | it/evals=7/693 eff=2.3891% N=400 Z=-30.7(0.00%) | Like=-24.76..-0.12 [-29.0187..-8.0090] | it/evals=9/954 eff=1.6245% N=400 Z=-28.7(0.00%) | Like=-24.10..-0.12 [-29.0187..-8.0090] | it/evals=14/1183 eff=1.7880% N=400 Z=-27.2(0.00%) | Like=-22.74..-0.12 [-29.0187..-8.0090] | it/evals=21/1672 eff=1.6509% N=400 Z=-26.2(0.00%) | Like=-22.14..-0.12 [-29.0187..-8.0090] | it/evals=28/2101 eff=1.6461% N=400 Z=-25.2(0.00%) | Like=-21.02..-0.12 [-29.0187..-8.0090] | it/evals=36/2686 eff=1.5748% N=400 Z=-24.3(0.00%) | Like=-20.71..-0.12 [-29.0187..-8.0090] | it/evals=44/3319 eff=1.5074% N=400 Z=-23.8(0.00%) | Like=-19.89..-0.12 [-29.0187..-8.0090] | it/evals=50/3720 eff=1.5060% N=400 Z=-23.1(0.00%) | Like=-18.80..-0.12 [-29.0187..-8.0090] | it/evals=56/4373 eff=1.4095% N=400 Z=-22.0(0.00%) | Like=-18.12..-0.12 [-29.0187..-8.0090] | it/evals=64/5028 eff=1.3829% N=400 Z=-21.2(0.00%) | Like=-17.32..-0.12 [-29.0187..-8.0090] | it/evals=72/5864 eff=1.3177% N=400 Z=-20.7(0.00%) | Like=-16.60..-0.12 [-29.0187..-8.0090] | it/evals=78/6490 eff=1.2808% N=400 Z=-19.8(0.00%) | Like=-15.90..-0.12 [-29.0187..-8.0090] | it/evals=86/7143 eff=1.2754% N=400 Z=-19.5(0.00%) | Like=-15.75..-0.12 [-29.0187..-8.0090] | it/evals=90/7541 eff=1.2603% N=400 Z=-18.9(0.00%) | Like=-15.14..-0.12 [-29.0187..-8.0090] | it/evals=98/8287 eff=1.2426% N=400 Z=-18.7(0.00%) | Like=-15.08..-0.12 [-29.0187..-8.0090] | it/evals=100/8459 eff=1.2408% N=400 Z=-18.3(0.00%) | Like=-14.69..-0.12 [-29.0187..-8.0090] | it/evals=107/9217 eff=1.2136% N=400 Z=-17.8(0.00%) | Like=-14.13..-0.12 [-29.0187..-8.0090] | it/evals=115/9951 eff=1.2041% N=400 Z=-17.3(0.00%) | Like=-13.68..-0.07 [-29.0187..-8.0090] | it/evals=123/10701 eff=1.1941% N=400 Z=-16.9(0.00%) | Like=-13.17..-0.07 [-29.0187..-8.0090] | it/evals=129/11262 eff=1.1876% N=400 Z=-16.6(0.00%) | Like=-12.89..-0.07 [-29.0187..-8.0090] | it/evals=133/11977 eff=1.1488% N=400 Z=-16.1(0.00%) | Like=-12.62..-0.07 [-29.0187..-8.0090] | it/evals=141/12747 eff=1.1420% N=400 Z=-15.7(0.00%) | Like=-12.35..-0.07 [-29.0187..-8.0090] | it/evals=148/13404 eff=1.1381% N=400 Z=-15.6(0.00%) | Like=-12.14..-0.07 [-29.0187..-8.0090] | it/evals=150/13647 eff=1.1323% N=400 Z=-15.2(0.00%) | Like=-11.58..-0.07 [-29.0187..-8.0090] | it/evals=157/14399 eff=1.1215% N=400 Z=-14.8(0.00%) | Like=-11.33..-0.07 [-29.0187..-8.0090] | it/evals=164/15197 eff=1.1083% N=400 Z=-14.4(0.00%) | Like=-10.99..-0.07 [-29.0187..-8.0090] | it/evals=172/16003 eff=1.1024% N=400 Z=-14.2(0.00%) | Like=-10.72..-0.07 [-29.0187..-8.0090] | it/evals=177/16565 eff=1.0950% N=400 Z=-13.9(0.00%) | Like=-10.55..-0.07 [-29.0187..-8.0090] | it/evals=183/17159 eff=1.0920% N=400 Z=-13.5(0.00%) | Like=-10.22..-0.07 [-29.0187..-8.0090] | it/evals=191/18165 eff=1.0751% N=400 Z=-13.3(0.00%) | Like=-10.14..-0.07 [-29.0187..-8.0090] | it/evals=197/18639 eff=1.0801% N=400 Z=-13.2(0.00%) | Like=-9.97..-0.07 [-29.0187..-8.0090] | it/evals=200/19033 eff=1.0734% N=400 Z=-12.9(0.01%) | Like=-9.77..-0.07 [-29.0187..-8.0090] | it/evals=207/19834 eff=1.0651% N=400 Z=-12.7(0.01%) | Like=-9.45..-0.07 [-29.0187..-8.0090] | it/evals=215/20615 eff=1.0636% N=400 Z=-12.4(0.01%) | Like=-9.24..-0.07 [-29.0187..-8.0090] | it/evals=223/21453 eff=1.0592% N=400 Z=-12.1(0.01%) | Like=-8.93..-0.07 [-29.0187..-8.0090] | it/evals=231/22294 eff=1.0551% N=400 Z=-11.9(0.02%) | Like=-8.73..-0.07 [-29.0187..-8.0090] | it/evals=239/23143 eff=1.0509% N=400 Z=-11.6(0.02%) | Like=-8.58..-0.07 [-29.0187..-8.0090] | it/evals=246/24075 eff=1.0391% N=400 Z=-11.5(0.02%) | Like=-8.53..-0.07 [-29.0187..-8.0090] | it/evals=250/24541 eff=1.0356% N=400 Z=-11.3(0.03%) | Like=-8.41..-0.07 [-29.0187..-8.0090] | it/evals=258/25455 eff=1.0297% N=400 Z=-11.2(0.03%) | Like=-8.29..-0.07 [-29.0187..-8.0090] | it/evals=263/26214 eff=1.0188% N=400 Z=-11.1(0.04%) | Like=-8.16..-0.07 [-29.0187..-8.0090] | it/evals=269/26672 eff=1.0239% N=400 Z=-11.0(0.04%) | Like=-8.12..-0.07 [-29.0187..-8.0090] | it/evals=270/26673 eff=1.0277% N=400 Z=-10.9(0.04%) | Like=-8.02..-0.07 [-29.0187..-8.0090] | it/evals=275/27576 eff=1.0119% N=400 Z=-10.8(0.05%) | Like=-7.86..-0.07 [-8.0021..-4.4217] | it/evals=282/28416 eff=1.0066% N=400 Z=-10.6(0.06%) | Like=-7.71..-0.07 [-8.0021..-4.4217] | it/evals=290/29359 eff=1.0014% N=400 Z=-10.4(0.08%) | Like=-7.58..-0.07 [-8.0021..-4.4217] | it/evals=298/30265 eff=0.9978% N=400 Z=-10.4(0.08%) | Like=-7.55..-0.07 [-8.0021..-4.4217] | it/evals=300/30355 eff=1.0015% N=400 Z=-10.3(0.09%) | Like=-7.43..-0.07 [-8.0021..-4.4217] | it/evals=307/31184 eff=0.9973% N=400 Z=-10.2(0.10%) | Like=-7.31..-0.07 [-8.0021..-4.4217] | it/evals=312/31933 eff=0.9894% N=400 Z=-10.1(0.11%) | Like=-7.14..-0.07 [-8.0021..-4.4217] | it/evals=317/32546 eff=0.9861% N=400 Z=-9.9(0.13%) | Like=-6.99..-0.07 [-8.0021..-4.4217] | it/evals=323/33284 eff=0.9822% N=400 Z=-9.8(0.14%) | Like=-6.90..-0.07 [-8.0021..-4.4217] | it/evals=327/33982 eff=0.9737% N=400 Z=-9.7(0.15%) | Like=-6.78..-0.07 [-8.0021..-4.4217] | it/evals=333/34837 eff=0.9670% N=400 Z=-9.6(0.18%) | Like=-6.70..-0.07 [-8.0021..-4.4217] | it/evals=340/35660 eff=0.9643% N=400 Z=-9.5(0.20%) | Like=-6.60..-0.07 [-8.0021..-4.4217] | it/evals=346/36402 eff=0.9611% N=400 Z=-9.4(0.22%) | Like=-6.55..-0.07 [-8.0021..-4.4217] | it/evals=350/36856 eff=0.9601% N=400 Z=-9.3(0.25%) | Like=-6.45..-0.07 [-8.0021..-4.4217] | it/evals=358/37810 eff=0.9570% N=400 Z=-9.2(0.26%) | Like=-6.43..-0.07 [-8.0021..-4.4217] | it/evals=360/38137 eff=0.9540% N=400 Z=-9.2(0.27%) | Like=-6.37..-0.07 [-8.0021..-4.4217] | it/evals=363/38593 eff=0.9504% N=400 Z=-9.1(0.31%) | Like=-6.29..-0.07 [-8.0021..-4.4217] | it/evals=371/39451 eff=0.9500% N=400 Z=-8.9(0.35%) | Like=-6.21..-0.07 [-8.0021..-4.4217] | it/evals=379/40337 eff=0.9490% N=400 Z=-8.8(0.39%) | Like=-6.14..-0.07 [-8.0021..-4.4217] | it/evals=387/41243 eff=0.9475% N=400 Z=-8.7(0.41%) | Like=-6.09..-0.07 [-8.0021..-4.4217] | it/evals=393/42174 eff=0.9408% N=400 Z=-8.6(0.45%) | Like=-6.04..-0.07 [-8.0021..-4.4217] | it/evals=400/42784 eff=0.9438% N=400 Z=-8.6(0.50%) | Like=-5.97..-0.07 [-8.0021..-4.4217] | it/evals=406/43671 eff=0.9383% N=400 Z=-8.5(0.54%) | Like=-5.93..-0.07 [-8.0021..-4.4217] | it/evals=412/44560 eff=0.9330% N=400 Z=-8.4(0.58%) | Like=-5.84..-0.07 [-8.0021..-4.4217] | it/evals=418/45405 eff=0.9288% N=400 Z=-8.3(0.63%) | Like=-5.79..-0.07 [-8.0021..-4.4217] | it/evals=426/46327 eff=0.9276% N=400 Z=-8.3(0.68%) | Like=-5.71..-0.07 [-8.0021..-4.4217] | it/evals=433/47200 eff=0.9252% N=400 Z=-8.2(0.75%) | Like=-5.65..-0.07 [-8.0021..-4.4217] | it/evals=441/48250 eff=0.9216% N=400 Z=-8.1(0.79%) | Like=-5.61..-0.07 [-8.0021..-4.4217] | it/evals=445/48752 eff=0.9203% N=400 Z=-8.1(0.84%) | Like=-5.56..-0.07 [-8.0021..-4.4217] | it/evals=450/49284 eff=0.9205% N=400 Z=-8.1(0.87%) | Like=-5.48..-0.07 [-8.0021..-4.4217] | it/evals=453/49769 eff=0.9176% N=400 Z=-8.0(0.92%) | Like=-5.45..-0.07 [-8.0021..-4.4217] | it/evals=459/50563 eff=0.9150% N=400 Z=-7.9(0.98%) | Like=-5.31..-0.07 [-8.0021..-4.4217] | it/evals=467/51611 eff=0.9119% N=400 Z=-7.8(1.04%) | Like=-5.24..-0.07 [-8.0021..-4.4217] | it/evals=473/52558 eff=0.9069% N=400 Z=-7.8(1.13%) | Like=-5.10..-0.07 [-8.0021..-4.4217] | it/evals=481/53684 eff=0.9027% N=400 Z=-7.7(1.19%) | Like=-5.06..-0.07 [-8.0021..-4.4217] | it/evals=487/54410 eff=0.9017% N=400 Z=-7.6(1.28%) | Like=-4.95..-0.07 [-8.0021..-4.4217] | it/evals=493/55309 eff=0.8978% N=400 Z=-7.6(1.32%) | Like=-4.92..-0.07 [-8.0021..-4.4217] | it/evals=496/55944 eff=0.8930% N=400 Z=-7.6(1.35%) | Like=-4.90..-0.07 [-8.0021..-4.4217] | it/evals=498/56321 eff=0.8905% N=400 Z=-7.6(1.38%) | Like=-4.88..-0.07 [-8.0021..-4.4217] | it/evals=500/56392 eff=0.8930% N=400 Z=-7.5(1.47%) | Like=-4.84..-0.07 [-8.0021..-4.4217] | it/evals=505/57435 eff=0.8854% N=400 Z=-7.4(1.57%) | Like=-4.75..-0.04 [-8.0021..-4.4217] | it/evals=513/58513 eff=0.8828% N=400 Z=-7.4(1.67%) | Like=-4.68..-0.04 [-8.0021..-4.4217] | it/evals=519/59253 eff=0.8819% N=400 Z=-7.3(1.76%) | Like=-4.60..-0.04 [-8.0021..-4.4217] | it/evals=525/60254 eff=0.8771% N=400 Z=-7.2(1.91%) | Like=-4.53..-0.04 [-8.0021..-4.4217] | it/evals=532/61187 eff=0.8752% N=400 Z=-7.2(2.04%) | Like=-4.47..-0.04 [-8.0021..-4.4217] | it/evals=539/62196 eff=0.8722% N=400 Z=-7.1(2.16%) | Like=-4.43..-0.04 [-8.0021..-4.4217] | it/evals=544/62917 eff=0.8702% N=400 Z=-7.1(2.27%) | Like=-4.42..-0.04 [-4.4216..-3.3233] | it/evals=550/63774 eff=0.8679% N=400 Z=-7.1(2.32%) | Like=-4.38..-0.04 [-4.4216..-3.3233] | it/evals=552/64225 eff=0.8649% N=400 Z=-7.0(2.47%) | Like=-4.34..-0.04 [-4.4216..-3.3233] | it/evals=560/65355 eff=0.8621% N=400 Z=-6.9(2.68%) | Like=-4.30..-0.04 [-4.4216..-3.3233] | it/evals=568/66384 eff=0.8608% N=400 Z=-6.9(2.88%) | Like=-4.24..-0.04 [-4.4216..-3.3233] | it/evals=576/67504 eff=0.8584% N=400 Z=-6.8(3.02%) | Like=-4.17..-0.04 [-4.4216..-3.3233] | it/evals=584/68662 eff=0.8555% N=400 Z=-6.7(3.21%) | Like=-4.13..-0.04 [-4.4216..-3.3233] | it/evals=591/69706 eff=0.8527% N=400 Z=-6.7(3.38%) | Like=-4.10..-0.04 [-4.4216..-3.3233] | it/evals=598/70919 eff=0.8480% N=400 Z=-6.7(3.44%) | Like=-4.09..-0.04 [-4.4216..-3.3233] | it/evals=600/71025 eff=0.8496% N=400 Z=-6.6(3.60%) | Like=-4.07..-0.04 [-4.4216..-3.3233] | it/evals=606/72196 eff=0.8441% N=400 Z=-6.6(3.81%) | Like=-4.00..-0.04 [-4.4216..-3.3233] | it/evals=613/73252 eff=0.8414% N=400 Z=-6.5(4.06%) | Like=-3.94..-0.04 [-4.4216..-3.3233] | it/evals=621/74253 eff=0.8409% N=400 Z=-6.5(4.22%) | Like=-3.89..-0.04 [-4.4216..-3.3233] | it/evals=627/75009 eff=0.8404% N=400 Z=-6.5(4.31%) | Like=-3.88..-0.04 [-4.4216..-3.3233] | it/evals=630/75437 eff=0.8396% N=400 Z=-6.4(4.44%) | Like=-3.86..-0.04 [-4.4216..-3.3233] | it/evals=636/76382 eff=0.8370% N=400 Z=-6.4(4.65%) | Like=-3.79..-0.04 [-4.4216..-3.3233] | it/evals=642/77350 eff=0.8343% N=400 Z=-6.3(4.94%) | Like=-3.75..-0.04 [-4.4216..-3.3233] | it/evals=650/78496 eff=0.8323% N=400 Z=-6.3(5.23%) | Like=-3.70..-0.04 [-4.4216..-3.3233] | it/evals=658/79613 eff=0.8307% N=400 Z=-6.2(5.51%) | Like=-3.66..-0.04 [-4.4216..-3.3233] | it/evals=666/80634 eff=0.8301% N=400 Z=-6.2(5.72%) | Like=-3.62..-0.04 [-4.4216..-3.3233] | it/evals=673/81568 eff=0.8291% N=400 Z=-6.1(5.96%) | Like=-3.59..-0.04 [-4.4216..-3.3233] | it/evals=680/82576 eff=0.8275% N=400 Z=-6.1(6.23%) | Like=-3.54..-0.04 [-4.4216..-3.3233] | it/evals=688/83669 eff=0.8262% N=400 Z=-6.0(6.54%) | Like=-3.48..-0.04 [-4.4216..-3.3233] | it/evals=696/84584 eff=0.8268% N=400 Z=-6.0(6.64%) | Like=-3.45..-0.04 [-4.4216..-3.3233] | it/evals=700/85135 eff=0.8261% N=400 Z=-6.0(6.89%) | Like=-3.41..-0.04 [-4.4216..-3.3233] | it/evals=705/86108 eff=0.8226% N=400 Z=-6.0(7.13%) | Like=-3.37..-0.04 [-4.4216..-3.3233] | it/evals=712/87277 eff=0.8195% N=400 Z=-5.9(7.36%) | Like=-3.32..-0.04 [-3.3224..-2.9811] | it/evals=718/88239 eff=0.8174% N=400 Z=-5.9(7.46%) | Like=-3.31..-0.04 [-3.3224..-2.9811] | it/evals=720/88371 eff=0.8185% N=400 Z=-5.9(7.77%) | Like=-3.27..-0.04 [-3.3224..-2.9811] | it/evals=726/89374 eff=0.8160% N=400 Z=-5.8(8.08%) | Like=-3.23..-0.04 [-3.3224..-2.9811] | it/evals=733/90293 eff=0.8154% N=400 Z=-5.8(8.23%) | Like=-3.20..-0.04 [-3.3224..-2.9811] | it/evals=740/91297 eff=0.8141% N=400 Z=-5.8(8.48%) | Like=-3.14..-0.04 [-3.3224..-2.9811] | it/evals=746/92331 eff=0.8115% N=400 Z=-5.7(8.70%) | Like=-3.13..-0.04 [-3.3224..-2.9811] | it/evals=750/92915 eff=0.8107% N=400 Z=-5.7(8.89%) | Like=-3.11..-0.04 [-3.3224..-2.9811] | it/evals=756/94000 eff=0.8077% N=400 Z=-5.7(9.29%) | Like=-3.06..-0.04 [-3.3224..-2.9811] | it/evals=764/95164 eff=0.8062% N=400 Z=-5.6(9.72%) | Like=-3.02..-0.04 [-3.3224..-2.9811] | it/evals=772/96298 eff=0.8050% N=400 Z=-5.6(10.08%) | Like=-2.97..-0.04 [-2.9692..-2.8625] | it/evals=778/97206 eff=0.8037% N=400 Z=-5.6(10.44%) | Like=-2.94..-0.04 [-2.9692..-2.8625] | it/evals=785/98334 eff=0.8016% N=400 Z=-5.5(10.85%) | Like=-2.87..-0.04 [-2.9692..-2.8625] | it/evals=793/99477 eff=0.8004% N=400 Z=-5.5(11.09%) | Like=-2.85..-0.04 [-2.8574..-2.8235] | it/evals=799/100468 eff=0.7985% N=400 Z=-5.5(11.16%) | Like=-2.85..-0.04 [-2.8574..-2.8235] | it/evals=800/100506 eff=0.7992% N=400 Z=-5.5(11.42%) | Like=-2.81..-0.04 [-2.8234..-2.7987] | it/evals=806/101434 eff=0.7978% N=400 Z=-5.5(11.68%) | Like=-2.80..-0.04 [-2.7975..-2.7923]*| it/evals=810/102038 eff=0.7969% N=400 Z=-5.4(11.83%) | Like=-2.78..-0.04 [-2.7782..-2.7749]*| it/evals=814/102776 eff=0.7951% N=400 Z=-5.4(12.25%) | Like=-2.76..-0.04 [-2.7568..-2.7543]*| it/evals=821/103984 eff=0.7926% N=400 Z=-5.4(12.62%) | Like=-2.74..-0.04 [-2.7421..-2.7343]*| it/evals=829/105283 eff=0.7904% N=400 Z=-5.3(13.09%) | Like=-2.71..-0.04 [-2.7101..-2.7091]*| it/evals=836/106162 eff=0.7905% N=400 Z=-5.3(13.38%) | Like=-2.70..-0.04 [-2.7010..-2.6973]*| it/evals=842/107262 eff=0.7879% N=400 Z=-5.3(13.80%) | Like=-2.68..-0.04 [-2.6849..-2.6631] | it/evals=849/108432 eff=0.7859% N=400 Z=-5.3(13.85%) | Like=-2.66..-0.04 [-2.6849..-2.6631] | it/evals=850/108444 eff=0.7867% N=400 Z=-5.3(14.28%) | Like=-2.64..-0.04 [-2.6406..-2.6382]*| it/evals=856/109634 eff=0.7836% N=400 Z=-5.2(14.79%) | Like=-2.63..-0.04 [-2.6259..-2.6247]*| it/evals=864/110880 eff=0.7820% N=400 Z=-5.2(15.07%) | Like=-2.60..-0.04 [-2.5996..-2.5972]*| it/evals=869/111876 eff=0.7795% N=400 Z=-5.2(15.53%) | Like=-2.57..-0.04 [-2.5669..-2.5655]*| it/evals=877/113071 eff=0.7784% N=400 Z=-5.1(16.12%) | Like=-2.53..-0.04 [-2.5327..-2.5295]*| it/evals=886/114293 eff=0.7779% N=400 Z=-5.1(16.65%) | Like=-2.49..-0.04 [-2.4943..-2.4929]*| it/evals=894/115521 eff=0.7766% N=400 Z=-5.1(17.09%) | Like=-2.48..-0.04 [-2.4828..-2.4795]*| it/evals=900/116779 eff=0.7733% N=400 Z=-5.1(17.52%) | Like=-2.47..-0.04 [-2.4686..-2.4683]*| it/evals=907/117816 eff=0.7725% N=400 Z=-5.0(17.81%) | Like=-2.45..-0.03 [-2.4528..-2.4519]*| it/evals=915/119020 eff=0.7714% N=400 Z=-5.0(18.29%) | Like=-2.42..-0.03 [-2.4219..-2.4207]*| it/evals=923/120345 eff=0.7695% N=400 Z=-5.0(18.85%) | Like=-2.38..-0.03 [-2.3821..-2.3816]*| it/evals=931/121552 eff=0.7685% N=400 Z=-5.0(19.36%) | Like=-2.34..-0.03 [-2.3443..-2.3378]*| it/evals=939/122806 eff=0.7671% N=400 Z=-4.9(19.97%) | Like=-2.31..-0.03 [-2.3133..-2.3082]*| it/evals=948/124131 eff=0.7662% N=400 Z=-4.9(20.07%) | Like=-2.31..-0.03 [-2.3067..-2.3053]*| it/evals=950/124525 eff=0.7654% N=400 Z=-4.9(20.76%) | Like=-2.28..-0.03 [-2.2752..-2.2715]*| it/evals=959/125834 eff=0.7645% N=400 Z=-4.9(21.47%) | Like=-2.24..-0.03 [-2.2407..-2.2397]*| it/evals=968/127106 eff=0.7640% N=400 Z=-4.8(21.91%) | Like=-2.22..-0.03 [-2.2248..-2.2178]*| it/evals=975/128335 eff=0.7621% N=400 Z=-4.8(22.45%) | Like=-2.20..-0.03 [-2.1973..-2.1911]*| it/evals=982/129796 eff=0.7589% N=400 Z=-4.8(22.88%) | Like=-2.16..-0.03 [-2.1561..-2.1559]*| it/evals=989/131025 eff=0.7571% N=400 Z=-4.8(22.90%) | Like=-2.16..-0.03 [-2.1559..-2.1421] | it/evals=990/131028 eff=0.7579% N=400 Z=-4.8(23.42%) | Like=-2.13..-0.03 [-2.1280..-2.1250]*| it/evals=997/132268 eff=0.7561% N=400 Z=-4.8(23.67%) | Like=-2.12..-0.03 [-2.1239..-2.1174]*| it/evals=1000/132303 eff=0.7581% N=400 Z=-4.8(24.09%) | Like=-2.09..-0.03 [-2.0875..-2.0860]*| it/evals=1005/133447 eff=0.7554% N=400 Z=-4.7(24.82%) | Like=-2.06..-0.03 [-2.0643..-2.0582]*| it/evals=1014/134816 eff=0.7544% N=400 Z=-4.7(25.35%) | Like=-2.04..-0.03 [-2.0414..-2.0388]*| it/evals=1021/135885 eff=0.7536% N=400 Z=-4.7(25.71%) | Like=-2.02..-0.03 [-2.0203..-2.0155]*| it/evals=1028/137173 eff=0.7516% N=400 Z=-4.7(26.30%) | Like=-2.00..-0.03 [-1.9990..-1.9960]*| it/evals=1036/138360 eff=0.7509% N=400 Z=-4.7(26.77%) | Like=-1.98..-0.03 [-1.9766..-1.9623] | it/evals=1043/139538 eff=0.7496% N=400 Z=-4.6(27.21%) | Like=-1.94..-0.03 [-1.9436..-1.9429]*| it/evals=1048/140562 eff=0.7477% N=400 Z=-4.6(27.38%) | Like=-1.94..-0.03 [-1.9375..-1.9336]*| it/evals=1050/140682 eff=0.7485% N=400 Z=-4.6(27.77%) | Like=-1.93..-0.03 [-1.9272..-1.9231]*| it/evals=1055/141823 eff=0.7460% N=400 Z=-4.6(28.07%) | Like=-1.90..-0.03 [-1.9010..-1.8971]*| it/evals=1060/142697 eff=0.7449% N=400 Z=-4.6(28.68%) | Like=-1.88..-0.03 [-1.8769..-1.8698]*| it/evals=1068/143907 eff=0.7442% N=400 Z=-4.6(29.11%) | Like=-1.86..-0.03 [-1.8600..-1.8557]*| it/evals=1073/144733 eff=0.7434% N=400 Z=-4.6(29.60%) | Like=-1.83..-0.03 [-1.8289..-1.8246]*| it/evals=1079/145847 eff=0.7419% N=400 Z=-4.5(29.87%) | Like=-1.81..-0.03 [-1.8077..-1.8053]*| it/evals=1083/146495 eff=0.7413% N=400 Z=-4.5(30.53%) | Like=-1.79..-0.03 [-1.7927..-1.7916]*| it/evals=1091/148031 eff=0.7390% N=400 Z=-4.5(31.06%) | Like=-1.78..-0.03 [-1.7772..-1.7753]*| it/evals=1099/149288 eff=0.7381% N=400 Z=-4.5(31.15%) | Like=-1.78..-0.03 [-1.7753..-1.7745]*| it/evals=1100/149295 eff=0.7388% N=400 Z=-4.5(31.59%) | Like=-1.76..-0.03 [-1.7586..-1.7517]*| it/evals=1106/150295 eff=0.7378% N=400 Z=-4.5(31.92%) | Like=-1.75..-0.03 [-1.7461..-1.7415]*| it/evals=1111/151105 eff=0.7372% N=400 Z=-4.5(32.32%) | Like=-1.73..-0.03 [-1.7346..-1.7313]*| it/evals=1116/152390 eff=0.7343% N=400 Z=-4.4(32.75%) | Like=-1.71..-0.03 [-1.7080..-1.7060]*| it/evals=1123/153502 eff=0.7335% N=400 Z=-4.4(33.46%) | Like=-1.69..-0.03 [-1.6872..-1.6855]*| it/evals=1131/154756 eff=0.7327% N=400 Z=-4.4(33.89%) | Like=-1.67..-0.03 [-1.6693..-1.6684]*| it/evals=1136/155670 eff=0.7316% N=400 Z=-4.4(34.37%) | Like=-1.65..-0.03 [-1.6460..-1.6448]*| it/evals=1142/156840 eff=0.7300% N=400 Z=-4.4(34.70%) | Like=-1.62..-0.03 [-1.6231..-1.6221]*| it/evals=1147/157659 eff=0.7294% N=400 Z=-4.4(34.85%) | Like=-1.62..-0.03 [-1.6204..-1.6127]*| it/evals=1150/158021 eff=0.7296% N=400 Z=-4.4(35.43%) | Like=-1.60..-0.03 [-1.5980..-1.5940]*| it/evals=1158/159283 eff=0.7288% N=400 Z=-4.4(35.82%) | Like=-1.59..-0.03 [-1.5901..-1.5884]*| it/evals=1163/160304 eff=0.7273% N=400 Z=-4.3(36.36%) | Like=-1.57..-0.03 [-1.5687..-1.5677]*| it/evals=1170/161116 eff=0.7280% N=400 Z=-4.3(36.87%) | Like=-1.55..-0.03 [-1.5518..-1.5517]*| it/evals=1176/162144 eff=0.7271% N=400 Z=-4.3(37.46%) | Like=-1.54..-0.03 [-1.5449..-1.5443]*| it/evals=1183/163297 eff=0.7262% N=400 Z=-4.3(37.88%) | Like=-1.53..-0.03 [-1.5265..-1.5214]*| it/evals=1189/164331 eff=0.7253% N=400 Z=-4.3(38.17%) | Like=-1.52..-0.03 [-1.5152..-1.5138]*| it/evals=1194/165292 eff=0.7241% N=400 Z=-4.3(38.68%) | Like=-1.50..-0.03 [-1.5038..-1.5029]*| it/evals=1200/166312 eff=0.7233% N=400 Z=-4.3(39.44%) | Like=-1.49..-0.03 [-1.4892..-1.4880]*| it/evals=1208/167575 eff=0.7226% N=400 Z=-4.2(40.03%) | Like=-1.47..-0.03 [-1.4707..-1.4687]*| it/evals=1216/168949 eff=0.7215% N=400 Z=-4.2(40.34%) | Like=-1.46..-0.03 [-1.4630..-1.4610]*| it/evals=1221/169986 eff=0.7200% N=400 Z=-4.2(40.76%) | Like=-1.44..-0.03 [-1.4358..-1.4332]*| it/evals=1229/171180 eff=0.7196% N=400 Z=-4.2(41.14%) | Like=-1.41..-0.03 [-1.4145..-1.4128]*| it/evals=1234/172349 eff=0.7177% N=400 Z=-4.2(41.54%) | Like=-1.39..-0.03 [-1.3878..-1.3791]*| it/evals=1239/173329 eff=0.7165% N=400 Z=-4.2(42.23%) | Like=-1.36..-0.03 [-1.3627..-1.3601]*| it/evals=1247/174627 eff=0.7157% N=400 Z=-4.2(42.48%) | Like=-1.36..-0.03 [-1.3573..-1.3572]*| it/evals=1250/174686 eff=0.7172% N=400 Z=-4.2(42.67%) | Like=-1.35..-0.03 [-1.3506..-1.3490]*| it/evals=1252/175596 eff=0.7146% N=400 Z=-4.2(43.21%) | Like=-1.33..-0.03 [-1.3322..-1.3305]*| it/evals=1259/176652 eff=0.7143% N=400 Z=-4.2(43.31%) | Like=-1.33..-0.03 [-1.3305..-1.3289]*| it/evals=1260/176886 eff=0.7139% N=400 Z=-4.2(43.89%) | Like=-1.32..-0.03 [-1.3185..-1.3156]*| it/evals=1267/177902 eff=0.7138% N=400 Z=-4.1(44.33%) | Like=-1.31..-0.03 [-1.3069..-1.3062]*| it/evals=1273/178998 eff=0.7128% N=400 Z=-4.1(44.96%) | Like=-1.29..-0.03 [-1.2851..-1.2840]*| it/evals=1282/180274 eff=0.7127% N=400 Z=-4.1(45.42%) | Like=-1.27..-0.03 [-1.2719..-1.2719]*| it/evals=1289/181554 eff=0.7115% N=400 Z=-4.1(46.03%) | Like=-1.26..-0.03 [-1.2645..-1.2623]*| it/evals=1298/182819 eff=0.7115% N=400 Z=-4.1(46.21%) | Like=-1.26..-0.03 [-1.2611..-1.2610]*| it/evals=1300/183109 eff=0.7115% N=400 Z=-4.1(46.69%) | Like=-1.24..-0.03 [-1.2438..-1.2438]*| it/evals=1306/184349 eff=0.7100% N=400 Z=-4.1(47.27%) | Like=-1.24..-0.03 [-1.2368..-1.2340]*| it/evals=1315/185624 eff=0.7100% N=400 Z=-4.1(47.87%) | Like=-1.21..-0.03 [-1.2213..-1.2071] | it/evals=1322/186767 eff=0.7094% N=400 Z=-4.0(48.59%) | Like=-1.20..-0.03 [-1.1960..-1.1909]*| it/evals=1330/187985 eff=0.7090% N=400 Z=-4.0(48.87%) | Like=-1.19..-0.03 [-1.1869..-1.1853]*| it/evals=1335/188900 eff=0.7082% N=400 Z=-4.0(49.26%) | Like=-1.17..-0.03 [-1.1729..-1.1723]*| it/evals=1341/189874 eff=0.7077% N=400 Z=-4.0(49.95%) | Like=-1.15..-0.03 [-1.1467..-1.1466]*| it/evals=1349/191131 eff=0.7073% N=400 Z=-4.0(50.01%) | Like=-1.15..-0.03 [-1.1466..-1.1435]*| it/evals=1350/191558 eff=0.7062% N=400 Z=-4.0(50.55%) | Like=-1.13..-0.03 [-1.1343..-1.1332]*| it/evals=1357/192760 eff=0.7054% N=400 Z=-4.0(51.18%) | Like=-1.12..-0.03 [-1.1184..-1.1181]*| it/evals=1365/194107 eff=0.7047% N=400 Z=-4.0(51.83%) | Like=-1.10..-0.03 [-1.1031..-1.0998]*| it/evals=1373/195417 eff=0.7040% N=400 Z=-4.0(52.30%) | Like=-1.09..-0.03 [-1.0898..-1.0887]*| it/evals=1381/196696 eff=0.7035% N=400 Z=-4.0(52.94%) | Like=-1.08..-0.03 [-1.0811..-1.0800]*| it/evals=1389/197982 eff=0.7030% N=400 Z=-4.0(53.43%) | Like=-1.07..-0.03 [-1.0683..-1.0609]*| it/evals=1395/199016 eff=0.7024% N=400 Z=-3.9(53.81%) | Like=-1.05..-0.03 [-1.0548..-1.0535]*| it/evals=1400/200002 eff=0.7014% N=400 Z=-3.9(54.37%) | Like=-1.05..-0.03 [-1.0462..-1.0455]*| it/evals=1408/201398 eff=0.7005% N=400 Z=-3.9(54.91%) | Like=-1.04..-0.03 [-1.0397..-1.0395]*| it/evals=1416/202794 eff=0.6996% N=400 Z=-3.9(55.48%) | Like=-1.03..-0.03 [-1.0303..-1.0266]*| it/evals=1424/204211 eff=0.6987% N=400 Z=-3.9(56.10%) | Like=-1.02..-0.03 [-1.0217..-1.0210]*| it/evals=1432/205426 eff=0.6984% N=400 Z=-3.9(56.68%) | Like=-1.01..-0.03 [-1.0070..-1.0039]*| it/evals=1440/206860 eff=0.6975% N=400 Z=-3.9(57.15%) | Like=-0.99..-0.03 [-0.9869..-0.9866]*| it/evals=1446/207891 eff=0.6969% N=400 Z=-3.9(57.44%) | Like=-0.98..-0.03 [-0.9832..-0.9830]*| it/evals=1450/208561 eff=0.6966% N=400 Z=-3.9(57.95%) | Like=-0.98..-0.03 [-0.9787..-0.9783]*| it/evals=1457/209885 eff=0.6955% N=400 Z=-3.9(58.48%) | Like=-0.97..-0.03 [-0.9731..-0.9717]*| it/evals=1464/211060 eff=0.6950% N=400 Z=-3.9(59.01%) | Like=-0.97..-0.03 [-0.9661..-0.9654]*| it/evals=1472/212368 eff=0.6944% N=400 Z=-3.8(59.48%) | Like=-0.96..-0.03 [-0.9569..-0.9553]*| it/evals=1480/213760 eff=0.6937% N=400 Z=-3.8(59.89%) | Like=-0.95..-0.03 [-0.9487..-0.9483]*| it/evals=1487/214932 eff=0.6931% N=400 Z=-3.8(60.27%) | Like=-0.94..-0.03 [-0.9397..-0.9391]*| it/evals=1492/215921 eff=0.6923% N=400 Z=-3.8(60.61%) | Like=-0.93..-0.03 [-0.9297..-0.9294]*| it/evals=1498/216880 eff=0.6920% N=400 Z=-3.8(60.77%) | Like=-0.93..-0.03 [-0.9288..-0.9253]*| it/evals=1500/217236 eff=0.6918% N=400 Z=-3.8(61.38%) | Like=-0.91..-0.02 [-0.9142..-0.9136]*| it/evals=1508/218630 eff=0.6910% N=400 Z=-3.8(61.93%) | Like=-0.89..-0.02 [-0.8911..-0.8876]*| it/evals=1516/219890 eff=0.6907% N=400 Z=-3.8(62.26%) | Like=-0.88..-0.02 [-0.8785..-0.8783]*| it/evals=1522/221352 eff=0.6888% N=400 Z=-3.8(62.68%) | Like=-0.87..-0.02 [-0.8723..-0.8714]*| it/evals=1529/222535 eff=0.6883% N=400 Z=-3.8(62.74%) | Like=-0.87..-0.02 [-0.8714..-0.8709]*| it/evals=1530/222727 eff=0.6882% N=400 Z=-3.8(63.17%) | Like=-0.86..-0.02 [-0.8620..-0.8601]*| it/evals=1537/223922 eff=0.6876% N=400 Z=-3.8(63.61%) | Like=-0.85..-0.02 [-0.8460..-0.8460]*| it/evals=1545/225297 eff=0.6870% N=400 Z=-3.8(63.94%) | Like=-0.84..-0.02 [-0.8410..-0.8380]*| it/evals=1550/226001 eff=0.6871% N=400 Z=-3.8(64.37%) | Like=-0.83..-0.02 [-0.8271..-0.8264]*| it/evals=1557/227211 eff=0.6865% N=400 Z=-3.8(64.82%) | Like=-0.81..-0.02 [-0.8135..-0.8135]*| it/evals=1565/228491 eff=0.6861% N=400 Z=-3.8(65.30%) | Like=-0.81..-0.02 [-0.8085..-0.8078]*| it/evals=1573/229851 eff=0.6855% N=400 Z=-3.7(65.81%) | Like=-0.80..-0.02 [-0.7971..-0.7912]*| it/evals=1582/231405 eff=0.6848% N=400 Z=-3.7(66.14%) | Like=-0.79..-0.01 [-0.7878..-0.7859]*| it/evals=1588/232425 eff=0.6844% N=400 Z=-3.7(66.49%) | Like=-0.78..-0.01 [-0.7784..-0.7762]*| it/evals=1594/234014 eff=0.6823% N=400 Z=-3.7(66.87%) | Like=-0.77..-0.01 [-0.7704..-0.7694]*| it/evals=1600/234722 eff=0.6828% N=400 Z=-3.7(67.24%) | Like=-0.76..-0.01 [-0.7624..-0.7612]*| it/evals=1606/235930 eff=0.6819% N=400 Z=-3.7(67.74%) | Like=-0.76..-0.01 [-0.7569..-0.7543]*| it/evals=1614/237299 eff=0.6813% N=400 Z=-3.7(68.06%) | Like=-0.75..-0.01 [-0.7488..-0.7482]*| it/evals=1620/238351 eff=0.6808% N=400 Z=-3.7(68.40%) | Like=-0.74..-0.01 [-0.7431..-0.7415]*| it/evals=1626/239603 eff=0.6798% N=400 Z=-3.7(68.86%) | Like=-0.74..-0.01 [-0.7364..-0.7359]*| it/evals=1634/240903 eff=0.6794% N=400 Z=-3.7(69.23%) | Like=-0.73..-0.01 [-0.7284..-0.7256]*| it/evals=1641/242354 eff=0.6782% N=400 Z=-3.7(69.63%) | Like=-0.72..-0.01 [-0.7220..-0.7206]*| it/evals=1648/243473 eff=0.6780% N=400 Z=-3.7(69.73%) | Like=-0.72..-0.01 [-0.7195..-0.7148]*| it/evals=1650/243713 eff=0.6781% N=400 Z=-3.7(70.06%) | Like=-0.71..-0.01 [-0.7096..-0.7094]*| it/evals=1656/244993 eff=0.6770% N=400 Z=-3.7(70.48%) | Like=-0.70..-0.01 [-0.7035..-0.7019]*| it/evals=1663/246209 eff=0.6765% N=400 Z=-3.7(70.74%) | Like=-0.70..-0.01 [-0.6991..-0.6988]*| it/evals=1668/247247 eff=0.6757% N=400 Z=-3.7(71.18%) | Like=-0.69..-0.01 [-0.6852..-0.6840]*| it/evals=1676/248747 eff=0.6749% N=400 Z=-3.7(71.62%) | Like=-0.68..-0.01 [-0.6781..-0.6776]*| it/evals=1684/249958 eff=0.6748% N=400 Z=-3.7(71.98%) | Like=-0.67..-0.01 [-0.6719..-0.6718]*| it/evals=1691/251223 eff=0.6742% N=400 Z=-3.7(72.41%) | Like=-0.66..-0.01 [-0.6648..-0.6648]*| it/evals=1699/252454 eff=0.6741% N=400 Z=-3.7(72.45%) | Like=-0.66..-0.01 [-0.6648..-0.6643]*| it/evals=1700/252456 eff=0.6745% N=400 Z=-3.6(72.83%) | Like=-0.66..-0.01 [-0.6552..-0.6548]*| it/evals=1708/253741 eff=0.6742% N=400 Z=-3.6(72.93%) | Like=-0.65..-0.01 [-0.6541..-0.6538]*| it/evals=1710/253762 eff=0.6749% N=400 Z=-3.6(73.20%) | Like=-0.65..-0.01 [-0.6517..-0.6495]*| it/evals=1715/254976 eff=0.6737% N=400 Z=-3.6(73.51%) | Like=-0.64..-0.01 [-0.6420..-0.6343]*| it/evals=1721/256099 eff=0.6731% N=400 Z=-3.6(73.95%) | Like=-0.62..-0.01 [-0.6205..-0.6195]*| it/evals=1729/257675 eff=0.6720% N=400 Z=-3.6(74.36%) | Like=-0.61..-0.01 [-0.6089..-0.6087]*| it/evals=1737/259026 eff=0.6716% N=400 Z=-3.6(74.83%) | Like=-0.60..-0.01 [-0.6015..-0.6013]*| it/evals=1746/260451 eff=0.6714% N=400 Z=-3.6(75.02%) | Like=-0.60..-0.01 [-0.5980..-0.5966]*| it/evals=1750/261074 eff=0.6713% N=400 Z=-3.6(75.38%) | Like=-0.59..-0.01 [-0.5934..-0.5918]*| it/evals=1757/262618 eff=0.6701% N=400 Z=-3.6(75.72%) | Like=-0.59..-0.01 [-0.5866..-0.5866]*| it/evals=1765/263914 eff=0.6698% N=400 Z=-3.6(76.13%) | Like=-0.58..-0.01 [-0.5832..-0.5821]*| it/evals=1773/265169 eff=0.6696% N=400 Z=-3.6(76.51%) | Like=-0.57..-0.01 [-0.5735..-0.5729]*| it/evals=1781/266465 eff=0.6694% N=400 Z=-3.6(76.84%) | Like=-0.57..-0.01 [-0.5652..-0.5647]*| it/evals=1788/267765 eff=0.6687% N=400 Z=-3.6(77.17%) | Like=-0.56..-0.01 [-0.5567..-0.5554]*| it/evals=1795/269142 eff=0.6679% N=400 Z=-3.6(77.40%) | Like=-0.55..-0.01 [-0.5526..-0.5525]*| it/evals=1800/269863 eff=0.6680% N=400 Z=-3.6(77.58%) | Like=-0.55..-0.01 [-0.5508..-0.5507]*| it/evals=1804/270731 eff=0.6673% N=400 Z=-3.6(77.88%) | Like=-0.54..-0.01 [-0.5398..-0.5398]*| it/evals=1811/272311 eff=0.6660% N=400 Z=-3.6(78.23%) | Like=-0.54..-0.01 [-0.5357..-0.5339]*| it/evals=1819/273696 eff=0.6656% N=400 Z=-3.6(78.53%) | Like=-0.53..-0.01 [-0.5307..-0.5300]*| it/evals=1826/274507 eff=0.6662% N=400 Z=-3.6(78.71%) | Like=-0.52..-0.01 [-0.5249..-0.5247]*| it/evals=1830/275651 eff=0.6648% N=400 Z=-3.6(79.00%) | Like=-0.52..-0.01 [-0.5185..-0.5183]*| it/evals=1837/276935 eff=0.6643% N=400 Z=-3.6(79.30%) | Like=-0.51..-0.01 [-0.5105..-0.5101]*| it/evals=1845/278293 eff=0.6639% N=400 Z=-3.6(79.49%) | Like=-0.51..-0.01 [-0.5060..-0.5058]*| it/evals=1850/279113 eff=0.6638% N=400 Z=-3.6(79.79%) | Like=-0.50..-0.01 [-0.4984..-0.4958]*| it/evals=1857/280450 eff=0.6631% N=400 Z=-3.6(80.13%) | Like=-0.49..-0.01 [-0.4920..-0.4918]*| it/evals=1865/281972 eff=0.6624% N=400 Z=-3.5(80.56%) | Like=-0.48..-0.00 [-0.4798..-0.4788]*| it/evals=1876/283256 eff=0.6632% N=400 Z=-3.5(80.92%) | Like=-0.47..-0.00 [-0.4732..-0.4720]*| it/evals=1885/285070 eff=0.6622% N=400 Z=-3.5(81.11%) | Like=-0.47..-0.00 [-0.4693..-0.4681]*| it/evals=1890/285727 eff=0.6624% N=400 Z=-3.5(81.34%) | Like=-0.46..-0.00 [-0.4626..-0.4623]*| it/evals=1896/287050 eff=0.6614% N=400 Z=-3.5(81.48%) | Like=-0.46..-0.00 [-0.4558..-0.4558]*| it/evals=1900/287684 eff=0.6614% N=400 Z=-3.5(81.84%) | Like=-0.45..-0.00 [-0.4501..-0.4493]*| it/evals=1910/288941 eff=0.6620% N=400 Z=-3.5(82.09%) | Like=-0.44..-0.00 [-0.4446..-0.4423]*| it/evals=1917/290248 eff=0.6614% N=400 Z=-3.5(82.38%) | Like=-0.44..-0.00 [-0.4369..-0.4365]*| it/evals=1925/291586 eff=0.6611% N=400 Z=-3.5(82.69%) | Like=-0.43..-0.00 [-0.4309..-0.4308]*| it/evals=1933/292876 eff=0.6609% N=400 Z=-3.5(82.94%) | Like=-0.43..-0.00 [-0.4281..-0.4273]*| it/evals=1940/294179 eff=0.6604% N=400 Z=-3.5(83.21%) | Like=-0.42..-0.00 [-0.4232..-0.4228]*| it/evals=1948/295516 eff=0.6601% N=400 Z=-3.5(83.28%) | Like=-0.42..-0.00 [-0.4222..-0.4221]*| it/evals=1950/295613 eff=0.6605% N=400 Z=-3.5(83.56%) | Like=-0.42..-0.00 [-0.4171..-0.4166]*| it/evals=1958/296901 eff=0.6604% N=400 Z=-3.5(83.83%) | Like=-0.41..-0.00 [-0.4129..-0.4120]*| it/evals=1966/298201 eff=0.6602% N=400 Z=-3.5(84.13%) | Like=-0.41..-0.00 [-0.4051..-0.4046]*| it/evals=1975/299993 eff=0.6592% N=400 Z=-3.5(84.30%) | Like=-0.40..-0.00 [-0.4029..-0.4023]*| it/evals=1980/300651 eff=0.6594% N=400 Z=-3.5(84.53%) | Like=-0.40..-0.00 [-0.3979..-0.3962]*| it/evals=1987/301913 eff=0.6590% N=400 Z=-3.5(84.82%) | Like=-0.39..-0.00 [-0.3932..-0.3932]*| it/evals=1995/303133 eff=0.6590% N=400 Z=-3.5(84.98%) | Like=-0.39..-0.00 [-0.3917..-0.3901]*| it/evals=2000/303776 eff=0.6592% N=400 Z=-3.5(85.19%) | Like=-0.39..-0.00 [-0.3867..-0.3862]*| it/evals=2007/305031 eff=0.6588% N=400 Z=-3.5(85.36%) | Like=-0.38..-0.00 [-0.3844..-0.3843]*| it/evals=2012/306273 eff=0.6578% N=400 Z=-3.5(85.61%) | Like=-0.38..-0.00 [-0.3786..-0.3776]*| it/evals=2020/307636 eff=0.6575% N=400 Z=-3.5(85.84%) | Like=-0.37..-0.00 [-0.3744..-0.3742]*| it/evals=2028/308755 eff=0.6577% N=400 Z=-3.5(85.99%) | Like=-0.37..-0.00 [-0.3711..-0.3707]*| it/evals=2033/309871 eff=0.6569% N=400 Z=-3.5(86.24%) | Like=-0.37..-0.00 [-0.3674..-0.3667]*| it/evals=2041/311163 eff=0.6568% N=400 Z=-3.5(86.44%) | Like=-0.36..-0.00 [-0.3595..-0.3593]*| it/evals=2047/312307 eff=0.6563% N=400 Z=-3.5(86.52%) | Like=-0.36..-0.00 [-0.3582..-0.3582]*| it/evals=2050/312313 eff=0.6572% N=400 Z=-3.5(86.67%) | Like=-0.36..-0.00 [-0.3553..-0.3531]*| it/evals=2055/313463 eff=0.6564% N=400 Z=-3.5(86.81%) | Like=-0.35..-0.00 [-0.3494..-0.3488]*| it/evals=2060/314447 eff=0.6560% N=400 Z=-3.5(87.02%) | Like=-0.35..-0.00 [-0.3457..-0.3451]*| it/evals=2068/315751 eff=0.6558% N=400 Z=-3.5(87.08%) | Like=-0.34..-0.00 [-0.3448..-0.3448]*| it/evals=2070/315963 eff=0.6560% N=400 Z=-3.5(87.28%) | Like=-0.34..-0.00 [-0.3404..-0.3400]*| it/evals=2077/317183 eff=0.6557% N=400 Z=-3.5(87.46%) | Like=-0.34..-0.00 [-0.3376..-0.3371]*| it/evals=2084/318371 eff=0.6554% N=400 Z=-3.5(87.60%) | Like=-0.33..-0.00 [-0.3336..-0.3334]*| it/evals=2089/319341 eff=0.6550% N=400 Z=-3.5(87.78%) | Like=-0.33..-0.00 [-0.3311..-0.3308]*| it/evals=2096/320561 eff=0.6547% N=400 Z=-3.5(87.89%) | Like=-0.33..-0.00 [-0.3291..-0.3290]*| it/evals=2100/321161 eff=0.6547% N=400 Z=-3.5(88.07%) | Like=-0.33..-0.00 [-0.3255..-0.3253]*| it/evals=2107/322344 eff=0.6545% N=400 Z=-3.5(88.23%) | Like=-0.32..-0.00 [-0.3219..-0.3216]*| it/evals=2113/323486 eff=0.6540% N=400 Z=-3.5(88.38%) | Like=-0.32..-0.00 [-0.3190..-0.3189]*| it/evals=2119/324648 eff=0.6535% N=400 Z=-3.5(88.56%) | Like=-0.32..-0.00 [-0.3160..-0.3159]*| it/evals=2126/325819 eff=0.6533% N=400 Z=-3.4(88.67%) | Like=-0.31..-0.00 [-0.3147..-0.3144]*| it/evals=2130/326780 eff=0.6526% N=400 Z=-3.4(88.84%) | Like=-0.31..-0.00 [-0.3090..-0.3088]*| it/evals=2137/327927 eff=0.6525% N=400 Z=-3.4(88.96%) | Like=-0.31..-0.00 [-0.3080..-0.3076]*| it/evals=2142/328771 eff=0.6523% N=400 Z=-3.4(89.14%) | Like=-0.31..-0.00 [-0.3054..-0.3053]*| it/evals=2149/330050 eff=0.6519% N=400 Z=-3.4(89.16%) | Like=-0.31..-0.00 [-0.3053..-0.3053]*| it/evals=2150/330154 eff=0.6520% N=400 Z=-3.4(89.31%) | Like=-0.30..-0.00 [-0.2999..-0.2999]*| it/evals=2156/331014 eff=0.6521% N=400 Z=-3.4(89.40%) | Like=-0.30..-0.00 [-0.2991..-0.2986]*| it/evals=2160/331682 eff=0.6520% N=400 Z=-3.4(89.51%) | Like=-0.30..-0.00 [-0.2973..-0.2969]*| it/evals=2165/332818 eff=0.6513% N=400 Z=-3.4(89.66%) | Like=-0.29..-0.00 [-0.2917..-0.2915]*| it/evals=2172/334125 eff=0.6508% N=400 Z=-3.4(89.84%) | Like=-0.29..-0.00 [-0.2883..-0.2872]*| it/evals=2180/335600 eff=0.6504% N=400 Z=-3.4(90.01%) | Like=-0.29..-0.00 [-0.2860..-0.2850]*| it/evals=2188/336929 eff=0.6502% N=400 Z=-3.4(90.19%) | Like=-0.28..-0.00 [-0.2823..-0.2819]*| it/evals=2196/338257 eff=0.6500% N=400 Z=-3.4(90.28%) | Like=-0.28..-0.00 [-0.2794..-0.2786]*| it/evals=2200/338933 eff=0.6499% N=400 Z=-3.4(90.40%) | Like=-0.28..-0.00 [-0.2763..-0.2760]*| it/evals=2206/340016 eff=0.6496% N=400 Z=-3.4(90.49%) | Like=-0.27..-0.00 [-0.2738..-0.2736]*| it/evals=2210/340940 eff=0.6490% N=400 Z=-3.4(90.66%) | Like=-0.27..-0.00 [-0.2690..-0.2689]*| it/evals=2218/342183 eff=0.6489% N=400 Z=-3.4(90.83%) | Like=-0.26..-0.00 [-0.2639..-0.2639]*| it/evals=2226/343509 eff=0.6488% N=400 Z=-3.4(91.00%) | Like=-0.26..-0.00 [-0.2604..-0.2591]*| it/evals=2234/344612 eff=0.6490% N=400 Z=-3.4(91.13%) | Like=-0.26..-0.00 [-0.2551..-0.2545]*| it/evals=2241/345805 eff=0.6488% N=400 Z=-3.4(91.25%) | Like=-0.25..-0.00 [-0.2527..-0.2522]*| it/evals=2247/347049 eff=0.6482% N=400 Z=-3.4(91.31%) | Like=-0.25..-0.00 [-0.2514..-0.2509]*| it/evals=2250/347629 eff=0.6480% N=400 Z=-3.4(91.42%) | Like=-0.25..-0.00 [-0.2479..-0.2478]*| it/evals=2256/348869 eff=0.6474% N=400 Z=-3.4(91.58%) | Like=-0.25..-0.00 [-0.2462..-0.2459]*| it/evals=2264/350130 eff=0.6474% N=400 Z=-3.4(91.73%) | Like=-0.24..-0.00 [-0.2439..-0.2439]*| it/evals=2272/351422 eff=0.6473% N=400 Z=-3.4(91.86%) | Like=-0.24..-0.00 [-0.2416..-0.2416]*| it/evals=2279/352749 eff=0.6468% N=400 Z=-3.4(92.00%) | Like=-0.24..-0.00 [-0.2401..-0.2398]*| it/evals=2287/354025 eff=0.6467% N=400 Z=-3.4(92.17%) | Like=-0.24..-0.00 [-0.2356..-0.2356]*| it/evals=2296/355385 eff=0.6468% N=400 Z=-3.4(92.24%) | Like=-0.23..-0.00 [-0.2347..-0.2344]*| it/evals=2300/356045 eff=0.6467% N=400 Z=-3.4(92.38%) | Like=-0.23..-0.00 [-0.2325..-0.2324]*| it/evals=2308/357389 eff=0.6465% N=400 Z=-3.4(92.50%) | Like=-0.23..-0.00 [-0.2307..-0.2306]*| it/evals=2315/358620 eff=0.6463% N=400 Z=-3.4(92.63%) | Like=-0.23..-0.00 [-0.2289..-0.2283]*| it/evals=2323/359956 eff=0.6461% N=400 Z=-3.4(92.75%) | Like=-0.23..-0.00 [-0.2266..-0.2263]*| it/evals=2330/360972 eff=0.6462% N=400 Z=-3.4(92.83%) | Like=-0.22..-0.00 [-0.2244..-0.2226]*| it/evals=2335/361933 eff=0.6459% N=400 Z=-3.4(92.91%) | Like=-0.22..-0.00 [-0.2212..-0.2211]*| it/evals=2340/362725 eff=0.6458% N=400 Z=-3.4(93.01%) | Like=-0.22..-0.00 [-0.2190..-0.2173]*| it/evals=2346/363977 eff=0.6453% N=400 Z=-3.4(93.07%) | Like=-0.22..-0.00 [-0.2165..-0.2164]*| it/evals=2350/364638 eff=0.6452% N=400 Z=-3.4(93.20%) | Like=-0.21..-0.00 [-0.2136..-0.2126]*| it/evals=2358/365992 eff=0.6450% N=400 Z=-3.4(93.31%) | Like=-0.21..-0.00 [-0.2087..-0.2082]*| it/evals=2365/367191 eff=0.6448% N=400 Z=-3.4(93.46%) | Like=-0.21..-0.00 [-0.2055..-0.2050]*| it/evals=2375/368621 eff=0.6450% N=400 Z=-3.4(93.58%) | Like=-0.20..-0.00 [-0.2007..-0.2007]*| it/evals=2383/370241 eff=0.6443% N=400 Z=-3.4(93.72%) | Like=-0.20..-0.00 [-0.1976..-0.1975]*| it/evals=2393/371563 eff=0.6447% N=400 Z=-3.4(93.82%) | Like=-0.20..-0.00 [-0.1950..-0.1943]*| it/evals=2400/372823 eff=0.6444% N=400 Z=-3.4(93.93%) | Like=-0.19..-0.00 [-0.1927..-0.1925]*| it/evals=2408/374076 eff=0.6444% N=400 Z=-3.4(94.05%) | Like=-0.19..-0.00 [-0.1874..-0.1870]*| it/evals=2416/375751 eff=0.6437% N=400 Z=-3.4(94.19%) | Like=-0.18..-0.00 [-0.1844..-0.1844]*| it/evals=2427/377177 eff=0.6441% N=400 Z=-3.4(94.23%) | Like=-0.18..-0.00 [-0.1842..-0.1840]*| it/evals=2430/377883 eff=0.6437% N=400 Z=-3.4(94.34%) | Like=-0.18..-0.00 [-0.1818..-0.1813]*| it/evals=2438/379251 eff=0.6435% N=400 Z=-3.4(94.41%) | Like=-0.18..-0.00 [-0.1795..-0.1795]*| it/evals=2444/380555 eff=0.6429% N=400 Z=-3.4(94.49%) | Like=-0.18..-0.00 [-0.1782..-0.1781]*| it/evals=2450/381211 eff=0.6434% N=400 Z=-3.4(94.57%) | Like=-0.18..-0.00 [-0.1758..-0.1746]*| it/evals=2456/382575 eff=0.6426% N=400 Z=-3.4(94.67%) | Like=-0.17..-0.00 [-0.1724..-0.1719]*| it/evals=2464/383831 eff=0.6426% N=400 Z=-3.4(94.75%) | Like=-0.17..-0.00 [-0.1707..-0.1707]*| it/evals=2471/385167 eff=0.6422% N=400 Z=-3.4(94.85%) | Like=-0.17..-0.00 [-0.1692..-0.1682]*| it/evals=2479/386483 eff=0.6421% N=400 Z=-3.4(94.96%) | Like=-0.17..-0.00 [-0.1663..-0.1662]*| it/evals=2488/388095 eff=0.6417% N=400 Z=-3.4(95.06%) | Like=-0.17..-0.00 [-0.1651..-0.1650]*| it/evals=2497/389615 eff=0.6415% N=400 Z=-3.4(95.09%) | Like=-0.16..-0.00 [-0.1642..-0.1641]*| it/evals=2500/389953 eff=0.6418% N=400 Z=-3.4(95.18%) | Like=-0.16..-0.00 [-0.1612..-0.1610]*| it/evals=2508/391758 eff=0.6408% N=400 Z=-3.4(95.28%) | Like=-0.16..-0.00 [-0.1595..-0.1594]*| it/evals=2517/392934 eff=0.6412% N=400 Z=-3.4(95.34%) | Like=-0.16..-0.00 [-0.1590..-0.1572]*| it/evals=2522/394145 eff=0.6405% N=400 Z=-3.4(95.43%) | Like=-0.16..-0.00 [-0.1551..-0.1550]*| it/evals=2530/395380 eff=0.6405% N=400 Z=-3.4(95.50%) | Like=-0.15..-0.00 [-0.1535..-0.1534]*| it/evals=2537/396686 eff=0.6402% N=400 Z=-3.4(95.59%) | Like=-0.15..-0.00 [-0.1524..-0.1522]*| it/evals=2546/398301 eff=0.6399% N=400 Z=-3.4(95.64%) | Like=-0.15..-0.00 [-0.1505..-0.1502]*| it/evals=2550/398948 eff=0.6398% N=400 Z=-3.4(95.72%) | Like=-0.15..-0.00 [-0.1493..-0.1490]*| it/evals=2558/400259 eff=0.6397% N=400 Z=-3.4(95.79%) | Like=-0.15..-0.00 [-0.1472..-0.1472]*| it/evals=2565/401596 eff=0.6393% N=400 Z=-3.4(95.86%) | Like=-0.15..-0.00 [-0.1455..-0.1453]*| it/evals=2573/402884 eff=0.6393% N=400 Z=-3.4(95.94%) | Like=-0.14..-0.00 [-0.1412..-0.1408]*| it/evals=2581/404180 eff=0.6392% N=400 Z=-3.4(96.02%) | Like=-0.14..-0.00 [-0.1395..-0.1391]*| it/evals=2589/405476 eff=0.6391% N=400 Z=-3.4(96.07%) | Like=-0.14..-0.00 [-0.1367..-0.1364]*| it/evals=2595/406855 eff=0.6384% N=400 Z=-3.4(96.12%) | Like=-0.13..-0.00 [-0.1350..-0.1348]*| it/evals=2600/407511 eff=0.6386% N=400 Z=-3.4(96.18%) | Like=-0.13..-0.00 [-0.1343..-0.1340]*| it/evals=2607/408762 eff=0.6384% N=400 Z=-3.4(96.21%) | Like=-0.13..-0.00 [-0.1337..-0.1337]*| it/evals=2610/409074 eff=0.6387% N=400 Z=-3.4(96.27%) | Like=-0.13..-0.00 [-0.1325..-0.1323]*| it/evals=2617/410438 eff=0.6382% N=400 Z=-3.4(96.34%) | Like=-0.13..-0.00 [-0.1308..-0.1307]*| it/evals=2625/411842 eff=0.6380% N=400 Z=-3.4(96.42%) | Like=-0.13..-0.00 [-0.1279..-0.1275]*| it/evals=2634/413543 eff=0.6376% N=400 Z=-3.4(96.49%) | Like=-0.13..-0.00 [-0.1259..-0.1258]*| it/evals=2642/414800 eff=0.6375% N=400 Z=-3.4(96.55%) | Like=-0.12..-0.00 [-0.1240..-0.1238]*| it/evals=2650/416076 eff=0.6375% N=400 Z=-3.4(96.62%) | Like=-0.12..-0.00 [-0.1227..-0.1226]*| it/evals=2658/417597 eff=0.6371% N=400 Z=-3.4(96.68%) | Like=-0.12..-0.00 [-0.1211..-0.1211]*| it/evals=2666/418866 eff=0.6371% N=400 Z=-3.4(96.74%) | Like=-0.12..-0.00 [-0.1200..-0.1199]*| it/evals=2674/420228 eff=0.6369% N=400 Z=-3.4(96.81%) | Like=-0.12..-0.00 [-0.1184..-0.1183]*| it/evals=2682/421691 eff=0.6366% N=400 Z=-3.4(96.84%) | Like=-0.12..-0.00 [-0.1175..-0.1171]*| it/evals=2687/422859 eff=0.6360% N=400 Z=-3.4(96.90%) | Like=-0.12..-0.00 [-0.1154..-0.1154]*| it/evals=2695/424153 eff=0.6360% N=400 Z=-3.4(96.94%) | Like=-0.11..-0.00 [-0.1140..-0.1137]*| it/evals=2700/424853 eff=0.6361% N=400 Z=-3.4(96.99%) | Like=-0.11..-0.00 [-0.1129..-0.1128]*| it/evals=2707/426081 eff=0.6359% N=400 Z=-3.4(97.05%) | Like=-0.11..-0.00 [-0.1113..-0.1112]*| it/evals=2716/427783 eff=0.6355% N=400 Z=-3.4(97.12%) | Like=-0.11..-0.00 [-0.1094..-0.1092]*| it/evals=2725/429087 eff=0.6357% N=400 Z=-3.4(97.18%) | Like=-0.11..-0.00 [-0.1075..-0.1074]*| it/evals=2734/430734 eff=0.6353% N=400 Z=-3.4(97.24%) | Like=-0.11..-0.00 [-0.1060..-0.1058]*| it/evals=2743/432084 eff=0.6354% N=400 Z=-3.4(97.28%) | Like=-0.10..-0.00 [-0.1038..-0.1036]*| it/evals=2750/433209 eff=0.6354% N=400 Z=-3.4(97.34%) | Like=-0.10..-0.00 [-0.1018..-0.1017]*| it/evals=2759/434541 eff=0.6355% N=400 Z=-3.4(97.39%) | Like=-0.10..-0.00 [-0.1002..-0.1000]*| it/evals=2767/435865 eff=0.6354% N=400 Z=-3.4(97.42%) | Like=-0.10..-0.00 [-0.0987..-0.0985]*| it/evals=2772/437051 eff=0.6348% N=400 Z=-3.4(97.48%) | Like=-0.10..-0.00 [-0.0981..-0.0978]*| it/evals=2781/438375 eff=0.6350% N=400 Z=-3.4(97.53%) | Like=-0.10..-0.00 [-0.0957..-0.0956]*| it/evals=2790/439611 eff=0.6352% N=400 Z=-3.4(97.57%) | Like=-0.10..-0.00 [-0.0951..-0.0950]*| it/evals=2797/441134 eff=0.6346% N=400 Z=-3.4(97.59%) | Like=-0.09..-0.00 [-0.0947..-0.0944]*| it/evals=2800/441273 eff=0.6351% N=400 Z=-3.4(97.64%) | Like=-0.09..-0.00 [-0.0935..-0.0934]*| it/evals=2808/442474 eff=0.6352% N=400 Z=-3.4(97.68%) | Like=-0.09..-0.00 [-0.0925..-0.0925]*| it/evals=2816/444228 eff=0.6345% N=400 Z=-3.4(97.72%) | Like=-0.09..-0.00 [-0.0915..-0.0908]*| it/evals=2822/445500 eff=0.6340% N=400 Z=-3.4(97.75%) | Like=-0.09..-0.00 [-0.0896..-0.0896]*| it/evals=2829/446603 eff=0.6340% N=400 Z=-3.4(97.78%) | Like=-0.09..-0.00 [-0.0889..-0.0887]*| it/evals=2834/447455 eff=0.6339% N=400 Z=-3.4(97.82%) | Like=-0.09..-0.00 [-0.0873..-0.0873]*| it/evals=2842/448706 eff=0.6339% N=400 Z=-3.4(97.86%) | Like=-0.09..-0.00 [-0.0862..-0.0860]*| it/evals=2849/449926 eff=0.6338% N=400 Z=-3.4(97.87%) | Like=-0.09..-0.00 [-0.0860..-0.0860]*| it/evals=2850/449954 eff=0.6340% N=400 Z=-3.4(97.90%) | Like=-0.08..-0.00 [-0.0842..-0.0840]*| it/evals=2857/451220 eff=0.6337% N=400 Z=-3.4(97.94%) | Like=-0.08..-0.00 [-0.0827..-0.0825]*| it/evals=2865/452703 eff=0.6334% N=400 Z=-3.3(97.98%) | Like=-0.08..-0.00 [-0.0816..-0.0809]*| it/evals=2873/453977 eff=0.6334% N=400 Z=-3.3(98.02%) | Like=-0.08..-0.00 [-0.0804..-0.0803]*| it/evals=2880/455237 eff=0.6332% N=400 Z=-3.3(98.05%) | Like=-0.08..-0.00 [-0.0800..-0.0799]*| it/evals=2888/456550 eff=0.6331% N=400 Z=-3.3(98.09%) | Like=-0.08..-0.00 [-0.0792..-0.0791]*| it/evals=2896/457846 eff=0.6331% N=400 Z=-3.3(98.11%) | Like=-0.08..-0.00 [-0.0790..-0.0788]*| it/evals=2900/458521 eff=0.6330% N=400 Z=-3.3(98.14%) | Like=-0.08..-0.00 [-0.0782..-0.0779]*| it/evals=2907/459673 eff=0.6330% N=400 Z=-3.3(98.15%) | Like=-0.08..-0.00 [-0.0775..-0.0774]*| it/evals=2910/460517 eff=0.6324% N=400 Z=-3.3(98.19%) | Like=-0.08..-0.00 [-0.0763..-0.0763]*| it/evals=2919/461802 eff=0.6326% N=400 Z=-3.3(98.22%) | Like=-0.08..-0.00 [-0.0753..-0.0753]*| it/evals=2926/463176 eff=0.6323% N=400 Z=-3.3(98.26%) | Like=-0.07..-0.00 [-0.0741..-0.0740]*| it/evals=2934/464523 eff=0.6322% N=400 Z=-3.3(98.29%) | Like=-0.07..-0.00 [-0.0729..-0.0728]*| it/evals=2942/465875 eff=0.6320% N=400 Z=-3.3(98.33%) | Like=-0.07..-0.00 [-0.0716..-0.0715]*| it/evals=2950/467204 eff=0.6320% N=400 Z=-3.3(98.37%) | Like=-0.07..-0.00 [-0.0700..-0.0699]*| it/evals=2960/468947 eff=0.6317% N=400 Z=-3.3(98.40%) | Like=-0.07..-0.00 [-0.0690..-0.0690]*| it/evals=2969/470091 eff=0.6321% N=400 Z=-3.3(98.40%) | Like=-0.07..-0.00 [-0.0690..-0.0690]*| it/evals=2970/470696 eff=0.6315% N=400 Z=-3.3(98.44%) | Like=-0.07..-0.00 [-0.0685..-0.0684]*| it/evals=2978/471947 eff=0.6315% N=400 Z=-3.3(98.47%) | Like=-0.07..-0.00 [-0.0674..-0.0673]*| it/evals=2986/473395 eff=0.6313% N=400 Z=-3.3(98.50%) | Like=-0.07..-0.00 [-0.0665..-0.0664]*| it/evals=2994/474732 eff=0.6312% N=400 Z=-3.3(98.52%) | Like=-0.07..-0.00 [-0.0659..-0.0658]*| it/evals=3000/475462 eff=0.6315% N=400 Z=-3.3(98.54%) | Like=-0.07..-0.00 [-0.0652..-0.0652]*| it/evals=3006/476748 eff=0.6311% N=400 Z=-3.3(98.57%) | Like=-0.06..-0.00 [-0.0647..-0.0646]*| it/evals=3014/478046 eff=0.6310% N=400 Z=-3.3(98.60%) | Like=-0.06..-0.00 [-0.0642..-0.0641]*| it/evals=3022/479427 eff=0.6309% N=400 Z=-3.3(98.63%) | Like=-0.06..-0.00 [-0.0635..-0.0635]*| it/evals=3031/480765 eff=0.6310% N=400 Z=-3.3(98.65%) | Like=-0.06..-0.00 [-0.0632..-0.0632]*| it/evals=3038/481985 eff=0.6308% N=400 Z=-3.3(98.68%) | Like=-0.06..-0.00 [-0.0626..-0.0625]*| it/evals=3046/483313 eff=0.6308% N=400 Z=-3.3(98.69%) | Like=-0.06..-0.00 [-0.0619..-0.0618]*| it/evals=3050/484209 eff=0.6304% N=400 Z=-3.3(98.71%) | Like=-0.06..-0.00 [-0.0614..-0.0614]*| it/evals=3058/485486 eff=0.6304% N=400 Z=-3.3(98.72%) | Like=-0.06..-0.00 [-0.0614..-0.0613]*| it/evals=3060/485700 eff=0.6305% N=400 Z=-3.3(98.73%) | Like=-0.06..-0.00 [-0.0612..-0.0611]*| it/evals=3064/486716 eff=0.6300% N=400 Z=-3.3(98.75%) | Like=-0.06..-0.00 [-0.0607..-0.0607]*| it/evals=3071/488011 eff=0.6298% N=400 Z=-3.3(98.78%) | Like=-0.06..-0.00 [-0.0600..-0.0600]*| it/evals=3079/489356 eff=0.6297% N=400 Z=-3.3(98.80%) | Like=-0.06..-0.00 [-0.0597..-0.0597]*| it/evals=3087/490653 eff=0.6297% N=400 Z=-3.3(98.82%) | Like=-0.06..-0.00 [-0.0588..-0.0587]*| it/evals=3094/491929 eff=0.6295% N=400 Z=-3.3(98.84%) | Like=-0.06..-0.00 [-0.0579..-0.0578]*| it/evals=3100/492690 eff=0.6297% N=400 Z=-3.3(98.86%) | Like=-0.06..-0.00 [-0.0575..-0.0575]*| it/evals=3107/493971 eff=0.6295% N=400 Z=-3.3(98.89%) | Like=-0.06..-0.00 [-0.0563..-0.0563]*| it/evals=3117/495411 eff=0.6297% N=400 Z=-3.3(98.91%) | Like=-0.06..-0.00 [-0.0560..-0.0560]*| it/evals=3125/496783 eff=0.6296% N=400 Z=-3.3(98.93%) | Like=-0.06..-0.00 [-0.0556..-0.0556]*| it/evals=3132/498266 eff=0.6291% N=400 Z=-3.3(98.95%) | Like=-0.05..-0.00 [-0.0549..-0.0549]*| it/evals=3142/499798 eff=0.6292% N=400 Z=-3.3(98.97%) | Like=-0.05..-0.00 [-0.0541..-0.0541]*| it/evals=3150/501237 eff=0.6289% N=400 Z=-3.3(98.99%) | Like=-0.05..-0.00 [-0.0535..-0.0535]*| it/evals=3158/502625 eff=0.6288% N=400 [ultranest] Explored until L=-0.002 [ultranest] Likelihood function evaluations: 502865 [ultranest] logZ = -3.322 +- 0.04713 [ultranest] Effective samples strategy satisfied (ESS = 1862.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.330 +- 0.087 single instance: logZ = -3.330 +- 0.068 bootstrapped : logZ = -3.322 +- 0.087 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▂▂▃▃▄▅▄▆▅▅▄▃▃▃▂▂▂▃▃▅▆▇▇▇▆▇▆▄▃▃▂▁▁▁▁│1.00 0.53 +- 0.22 param1 : 0.00 │▁▁▁▁▂▂▃▂▄▃▅▅▆▄▄▄▃▂▂▂▂▃▄▃▆▇▇▆▆▆▅▃▃▃▁▁▁▁▁│1.00 0.53 +- 0.22 param2 : 0.00 │▁▁▁▁▁▂▃▃▄▅▅▆▆▅▅▄▃▂▂▂▂▂▄▆▇▇▇▇▇▇▅▄▃▃▁▁▁▁▁│1.00 0.53 +- 0.22
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=536, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-29.02, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=7, ncalls=693, regioncalls=0, ndraw=128, logz=-31.35, remainder_fraction=100.0000%, Lmin=-26.51, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=9, ncalls=954, regioncalls=0, ndraw=128, logz=-30.71, remainder_fraction=100.0000%, Lmin=-24.76, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=14, ncalls=1183, regioncalls=0, ndraw=128, logz=-28.70, remainder_fraction=100.0000%, Lmin=-24.10, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=21, ncalls=1672, regioncalls=0, ndraw=128, logz=-27.16, remainder_fraction=100.0000%, Lmin=-22.74, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=28, ncalls=2101, regioncalls=0, ndraw=128, logz=-26.18, remainder_fraction=100.0000%, Lmin=-22.14, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=2686, regioncalls=0, ndraw=128, logz=-25.18, remainder_fraction=100.0000%, Lmin=-21.02, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=44, ncalls=3319, regioncalls=0, ndraw=128, logz=-24.33, remainder_fraction=100.0000%, Lmin=-20.71, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=3720, regioncalls=0, ndraw=128, logz=-23.83, remainder_fraction=100.0000%, Lmin=-19.89, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=56, ncalls=4373, regioncalls=0, ndraw=128, logz=-23.11, remainder_fraction=100.0000%, Lmin=-18.80, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=64, ncalls=5028, regioncalls=0, ndraw=128, logz=-22.01, remainder_fraction=100.0000%, Lmin=-18.12, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=72, ncalls=5864, regioncalls=0, ndraw=128, logz=-21.23, remainder_fraction=100.0000%, Lmin=-17.32, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=78, ncalls=6490, regioncalls=0, ndraw=128, logz=-20.66, remainder_fraction=100.0000%, Lmin=-16.60, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=86, ncalls=7143, regioncalls=0, ndraw=128, logz=-19.84, remainder_fraction=100.0000%, Lmin=-15.90, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=7541, regioncalls=0, ndraw=128, logz=-19.48, remainder_fraction=100.0000%, Lmin=-15.75, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=98, ncalls=8287, regioncalls=0, ndraw=128, logz=-18.89, remainder_fraction=100.0000%, Lmin=-15.14, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=8459, regioncalls=0, ndraw=128, logz=-18.73, remainder_fraction=100.0000%, Lmin=-15.08, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=107, ncalls=9217, regioncalls=0, ndraw=128, logz=-18.25, remainder_fraction=100.0000%, Lmin=-14.69, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=115, ncalls=9951, regioncalls=0, ndraw=128, logz=-17.76, remainder_fraction=100.0000%, Lmin=-14.13, Lmax=-0.12 DEBUG ultranest:integrator.py:2610 iteration=123, ncalls=10701, regioncalls=0, ndraw=128, logz=-17.27, remainder_fraction=99.9999%, Lmin=-13.68, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=129, ncalls=11262, regioncalls=0, ndraw=128, logz=-16.86, remainder_fraction=99.9999%, Lmin=-13.17, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=133, ncalls=11977, regioncalls=0, ndraw=128, logz=-16.57, remainder_fraction=99.9999%, Lmin=-12.89, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=141, ncalls=12747, regioncalls=0, ndraw=128, logz=-16.08, remainder_fraction=99.9998%, Lmin=-12.62, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=148, ncalls=13404, regioncalls=0, ndraw=128, logz=-15.71, remainder_fraction=99.9996%, Lmin=-12.35, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=13647, regioncalls=0, ndraw=128, logz=-15.61, remainder_fraction=99.9996%, Lmin=-12.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=157, ncalls=14399, regioncalls=0, ndraw=128, logz=-15.20, remainder_fraction=99.9994%, Lmin=-11.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=164, ncalls=15197, regioncalls=0, ndraw=128, logz=-14.79, remainder_fraction=99.9991%, Lmin=-11.33, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=172, ncalls=16003, regioncalls=0, ndraw=128, logz=-14.41, remainder_fraction=99.9987%, Lmin=-10.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=177, ncalls=16565, regioncalls=0, ndraw=128, logz=-14.17, remainder_fraction=99.9983%, Lmin=-10.72, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=183, ncalls=17159, regioncalls=0, ndraw=128, logz=-13.89, remainder_fraction=99.9977%, Lmin=-10.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=191, ncalls=18165, regioncalls=0, ndraw=128, logz=-13.54, remainder_fraction=99.9968%, Lmin=-10.22, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=197, ncalls=18639, regioncalls=0, ndraw=128, logz=-13.31, remainder_fraction=99.9959%, Lmin=-10.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=19033, regioncalls=0, ndraw=128, logz=-13.20, remainder_fraction=99.9955%, Lmin=-9.97, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=207, ncalls=19834, regioncalls=0, ndraw=128, logz=-12.95, remainder_fraction=99.9942%, Lmin=-9.77, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=215, ncalls=20615, regioncalls=0, ndraw=128, logz=-12.66, remainder_fraction=99.9924%, Lmin=-9.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=223, ncalls=21453, regioncalls=0, ndraw=128, logz=-12.39, remainder_fraction=99.9899%, Lmin=-9.24, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=231, ncalls=22294, regioncalls=0, ndraw=128, logz=-12.12, remainder_fraction=99.9865%, Lmin=-8.93, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=239, ncalls=23143, regioncalls=0, ndraw=128, logz=-11.86, remainder_fraction=99.9830%, Lmin=-8.73, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=246, ncalls=24075, regioncalls=0, ndraw=128, logz=-11.64, remainder_fraction=99.9786%, Lmin=-8.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=24541, regioncalls=0, ndraw=128, logz=-11.53, remainder_fraction=99.9759%, Lmin=-8.53, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=258, ncalls=25455, regioncalls=0, ndraw=128, logz=-11.33, remainder_fraction=99.9700%, Lmin=-8.41, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=263, ncalls=26214, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9657%, Lmin=-8.29, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=269, ncalls=26672, regioncalls=0, ndraw=128, logz=-11.07, remainder_fraction=99.9610%, Lmin=-8.16, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=26673, regioncalls=0, ndraw=128, logz=-11.05, remainder_fraction=99.9600%, Lmin=-8.12, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=275, ncalls=27576, regioncalls=0, ndraw=128, logz=-10.93, remainder_fraction=99.9550%, Lmin=-8.02, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=28416, regioncalls=0, ndraw=128, logz=-10.78, remainder_fraction=99.9469%, Lmin=-7.86, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=290, ncalls=29359, regioncalls=0, ndraw=128, logz=-10.60, remainder_fraction=99.9371%, Lmin=-7.71, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=298, ncalls=30265, regioncalls=0, ndraw=128, logz=-10.43, remainder_fraction=99.9249%, Lmin=-7.58, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=30355, regioncalls=0, ndraw=128, logz=-10.39, remainder_fraction=99.9214%, Lmin=-7.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=307, ncalls=31184, regioncalls=0, ndraw=128, logz=-10.25, remainder_fraction=99.9102%, Lmin=-7.43, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=312, ncalls=31933, regioncalls=0, ndraw=128, logz=-10.16, remainder_fraction=99.9012%, Lmin=-7.31, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=317, ncalls=32546, regioncalls=0, ndraw=128, logz=-10.06, remainder_fraction=99.8897%, Lmin=-7.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=323, ncalls=33284, regioncalls=0, ndraw=128, logz=-9.93, remainder_fraction=99.8738%, Lmin=-6.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=327, ncalls=33982, regioncalls=0, ndraw=128, logz=-9.85, remainder_fraction=99.8631%, Lmin=-6.90, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=333, ncalls=34837, regioncalls=0, ndraw=128, logz=-9.73, remainder_fraction=99.8454%, Lmin=-6.78, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=340, ncalls=35660, regioncalls=0, ndraw=128, logz=-9.59, remainder_fraction=99.8221%, Lmin=-6.70, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=346, ncalls=36402, regioncalls=0, ndraw=128, logz=-9.47, remainder_fraction=99.7992%, Lmin=-6.60, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=36856, regioncalls=0, ndraw=128, logz=-9.40, remainder_fraction=99.7829%, Lmin=-6.55, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=358, ncalls=37810, regioncalls=0, ndraw=128, logz=-9.26, remainder_fraction=99.7516%, Lmin=-6.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=38137, regioncalls=0, ndraw=128, logz=-9.23, remainder_fraction=99.7420%, Lmin=-6.43, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=363, ncalls=38593, regioncalls=0, ndraw=128, logz=-9.18, remainder_fraction=99.7311%, Lmin=-6.37, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=371, ncalls=39451, regioncalls=0, ndraw=128, logz=-9.05, remainder_fraction=99.6917%, Lmin=-6.29, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=379, ncalls=40337, regioncalls=0, ndraw=128, logz=-8.93, remainder_fraction=99.6519%, Lmin=-6.21, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=387, ncalls=41243, regioncalls=0, ndraw=128, logz=-8.82, remainder_fraction=99.6097%, Lmin=-6.14, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=393, ncalls=42174, regioncalls=0, ndraw=128, logz=-8.74, remainder_fraction=99.5853%, Lmin=-6.09, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=42784, regioncalls=0, ndraw=128, logz=-8.65, remainder_fraction=99.5452%, Lmin=-6.04, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=406, ncalls=43671, regioncalls=0, ndraw=128, logz=-8.57, remainder_fraction=99.5042%, Lmin=-5.97, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=412, ncalls=44560, regioncalls=0, ndraw=128, logz=-8.50, remainder_fraction=99.4619%, Lmin=-5.93, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=418, ncalls=45405, regioncalls=0, ndraw=128, logz=-8.43, remainder_fraction=99.4174%, Lmin=-5.84, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=426, ncalls=46327, regioncalls=0, ndraw=128, logz=-8.34, remainder_fraction=99.3676%, Lmin=-5.79, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=433, ncalls=47200, regioncalls=0, ndraw=128, logz=-8.26, remainder_fraction=99.3206%, Lmin=-5.71, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=441, ncalls=48250, regioncalls=0, ndraw=128, logz=-8.18, remainder_fraction=99.2511%, Lmin=-5.65, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=445, ncalls=48752, regioncalls=0, ndraw=128, logz=-8.14, remainder_fraction=99.2125%, Lmin=-5.61, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=49284, regioncalls=0, ndraw=128, logz=-8.09, remainder_fraction=99.1649%, Lmin=-5.56, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=453, ncalls=49769, regioncalls=0, ndraw=128, logz=-8.06, remainder_fraction=99.1345%, Lmin=-5.48, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=459, ncalls=50563, regioncalls=0, ndraw=128, logz=-7.99, remainder_fraction=99.0789%, Lmin=-5.45, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=467, ncalls=51611, regioncalls=0, ndraw=128, logz=-7.91, remainder_fraction=99.0193%, Lmin=-5.31, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=473, ncalls=52558, regioncalls=0, ndraw=128, logz=-7.85, remainder_fraction=98.9621%, Lmin=-5.24, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=481, ncalls=53684, regioncalls=0, ndraw=128, logz=-7.77, remainder_fraction=98.8714%, Lmin=-5.10, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=487, ncalls=54410, regioncalls=0, ndraw=128, logz=-7.70, remainder_fraction=98.8055%, Lmin=-5.06, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=493, ncalls=55309, regioncalls=0, ndraw=128, logz=-7.64, remainder_fraction=98.7227%, Lmin=-4.95, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=496, ncalls=55944, regioncalls=0, ndraw=128, logz=-7.61, remainder_fraction=98.6757%, Lmin=-4.92, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=56321, regioncalls=0, ndraw=128, logz=-7.59, remainder_fraction=98.6515%, Lmin=-4.90, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=56392, regioncalls=0, ndraw=128, logz=-7.57, remainder_fraction=98.6210%, Lmin=-4.88, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=505, ncalls=57435, regioncalls=0, ndraw=128, logz=-7.51, remainder_fraction=98.5343%, Lmin=-4.84, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=513, ncalls=58513, regioncalls=0, ndraw=128, logz=-7.43, remainder_fraction=98.4325%, Lmin=-4.75, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=519, ncalls=59253, regioncalls=0, ndraw=128, logz=-7.37, remainder_fraction=98.3328%, Lmin=-4.68, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=525, ncalls=60254, regioncalls=0, ndraw=128, logz=-7.31, remainder_fraction=98.2373%, Lmin=-4.60, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=532, ncalls=61187, regioncalls=0, ndraw=128, logz=-7.24, remainder_fraction=98.0928%, Lmin=-4.53, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=539, ncalls=62196, regioncalls=0, ndraw=128, logz=-7.18, remainder_fraction=97.9580%, Lmin=-4.47, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=544, ncalls=62917, regioncalls=0, ndraw=128, logz=-7.13, remainder_fraction=97.8407%, Lmin=-4.43, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=63774, regioncalls=0, ndraw=128, logz=-7.07, remainder_fraction=97.7294%, Lmin=-4.42, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=552, ncalls=64225, regioncalls=0, ndraw=128, logz=-7.05, remainder_fraction=97.6804%, Lmin=-4.38, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=65355, regioncalls=0, ndraw=128, logz=-6.98, remainder_fraction=97.5271%, Lmin=-4.34, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=568, ncalls=66384, regioncalls=0, ndraw=128, logz=-6.92, remainder_fraction=97.3223%, Lmin=-4.30, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=576, ncalls=67504, regioncalls=0, ndraw=128, logz=-6.85, remainder_fraction=97.1236%, Lmin=-4.24, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=584, ncalls=68662, regioncalls=0, ndraw=128, logz=-6.79, remainder_fraction=96.9797%, Lmin=-4.17, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=591, ncalls=69706, regioncalls=0, ndraw=128, logz=-6.73, remainder_fraction=96.7874%, Lmin=-4.13, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=598, ncalls=70919, regioncalls=0, ndraw=128, logz=-6.68, remainder_fraction=96.6162%, Lmin=-4.10, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=71025, regioncalls=0, ndraw=128, logz=-6.67, remainder_fraction=96.5634%, Lmin=-4.09, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=606, ncalls=72196, regioncalls=0, ndraw=128, logz=-6.62, remainder_fraction=96.3981%, Lmin=-4.07, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=613, ncalls=73252, regioncalls=0, ndraw=128, logz=-6.57, remainder_fraction=96.1906%, Lmin=-4.00, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=621, ncalls=74253, regioncalls=0, ndraw=128, logz=-6.52, remainder_fraction=95.9411%, Lmin=-3.94, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=627, ncalls=75009, regioncalls=0, ndraw=128, logz=-6.48, remainder_fraction=95.7792%, Lmin=-3.89, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=75437, regioncalls=0, ndraw=128, logz=-6.46, remainder_fraction=95.6901%, Lmin=-3.88, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=636, ncalls=76382, regioncalls=0, ndraw=128, logz=-6.42, remainder_fraction=95.5628%, Lmin=-3.86, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=642, ncalls=77350, regioncalls=0, ndraw=128, logz=-6.38, remainder_fraction=95.3460%, Lmin=-3.79, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=78496, regioncalls=0, ndraw=128, logz=-6.32, remainder_fraction=95.0645%, Lmin=-3.75, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=658, ncalls=79613, regioncalls=0, ndraw=128, logz=-6.27, remainder_fraction=94.7749%, Lmin=-3.70, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=666, ncalls=80634, regioncalls=0, ndraw=128, logz=-6.22, remainder_fraction=94.4915%, Lmin=-3.66, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=673, ncalls=81568, regioncalls=0, ndraw=128, logz=-6.18, remainder_fraction=94.2776%, Lmin=-3.62, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=82576, regioncalls=0, ndraw=128, logz=-6.14, remainder_fraction=94.0417%, Lmin=-3.59, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=688, ncalls=83669, regioncalls=0, ndraw=128, logz=-6.09, remainder_fraction=93.7668%, Lmin=-3.54, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=696, ncalls=84584, regioncalls=0, ndraw=128, logz=-6.05, remainder_fraction=93.4628%, Lmin=-3.48, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=85135, regioncalls=0, ndraw=128, logz=-6.02, remainder_fraction=93.3556%, Lmin=-3.45, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=705, ncalls=86108, regioncalls=0, ndraw=128, logz=-6.00, remainder_fraction=93.1139%, Lmin=-3.41, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=712, ncalls=87277, regioncalls=0, ndraw=128, logz=-5.96, remainder_fraction=92.8651%, Lmin=-3.37, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=718, ncalls=88239, regioncalls=0, ndraw=128, logz=-5.92, remainder_fraction=92.6439%, Lmin=-3.32, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=88371, regioncalls=0, ndraw=128, logz=-5.91, remainder_fraction=92.5366%, Lmin=-3.31, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=726, ncalls=89374, regioncalls=0, ndraw=128, logz=-5.88, remainder_fraction=92.2251%, Lmin=-3.27, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=733, ncalls=90293, regioncalls=0, ndraw=128, logz=-5.84, remainder_fraction=91.9199%, Lmin=-3.23, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=740, ncalls=91297, regioncalls=0, ndraw=128, logz=-5.80, remainder_fraction=91.7701%, Lmin=-3.20, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=746, ncalls=92331, regioncalls=0, ndraw=128, logz=-5.77, remainder_fraction=91.5238%, Lmin=-3.14, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=92915, regioncalls=0, ndraw=128, logz=-5.75, remainder_fraction=91.3032%, Lmin=-3.13, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=756, ncalls=94000, regioncalls=0, ndraw=128, logz=-5.72, remainder_fraction=91.1140%, Lmin=-3.11, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=764, ncalls=95164, regioncalls=0, ndraw=128, logz=-5.68, remainder_fraction=90.7148%, Lmin=-3.06, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=772, ncalls=96298, regioncalls=0, ndraw=128, logz=-5.64, remainder_fraction=90.2795%, Lmin=-3.02, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=778, ncalls=97206, regioncalls=0, ndraw=128, logz=-5.61, remainder_fraction=89.9240%, Lmin=-2.97, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=785, ncalls=98334, regioncalls=0, ndraw=128, logz=-5.57, remainder_fraction=89.5642%, Lmin=-2.94, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=793, ncalls=99477, regioncalls=0, ndraw=128, logz=-5.54, remainder_fraction=89.1546%, Lmin=-2.87, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=799, ncalls=100468, regioncalls=0, ndraw=128, logz=-5.51, remainder_fraction=88.9093%, Lmin=-2.85, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=100506, regioncalls=0, ndraw=128, logz=-5.50, remainder_fraction=88.8449%, Lmin=-2.85, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=806, ncalls=101434, regioncalls=0, ndraw=128, logz=-5.47, remainder_fraction=88.5772%, Lmin=-2.81, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=102038, regioncalls=0, ndraw=128, logz=-5.45, remainder_fraction=88.3182%, Lmin=-2.80, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=814, ncalls=102776, regioncalls=0, ndraw=128, logz=-5.44, remainder_fraction=88.1672%, Lmin=-2.78, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=821, ncalls=103984, regioncalls=0, ndraw=128, logz=-5.40, remainder_fraction=87.7522%, Lmin=-2.76, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=829, ncalls=105283, regioncalls=0, ndraw=128, logz=-5.37, remainder_fraction=87.3842%, Lmin=-2.74, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=836, ncalls=106162, regioncalls=0, ndraw=128, logz=-5.34, remainder_fraction=86.9149%, Lmin=-2.71, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=842, ncalls=107262, regioncalls=0, ndraw=128, logz=-5.31, remainder_fraction=86.6220%, Lmin=-2.70, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=849, ncalls=108432, regioncalls=0, ndraw=128, logz=-5.28, remainder_fraction=86.1965%, Lmin=-2.68, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=108444, regioncalls=0, ndraw=128, logz=-5.28, remainder_fraction=86.1534%, Lmin=-2.66, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=856, ncalls=109634, regioncalls=0, ndraw=128, logz=-5.26, remainder_fraction=85.7233%, Lmin=-2.64, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=864, ncalls=110880, regioncalls=0, ndraw=128, logz=-5.22, remainder_fraction=85.2140%, Lmin=-2.63, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=869, ncalls=111876, regioncalls=0, ndraw=128, logz=-5.20, remainder_fraction=84.9304%, Lmin=-2.60, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=877, ncalls=113071, regioncalls=0, ndraw=128, logz=-5.17, remainder_fraction=84.4730%, Lmin=-2.57, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=886, ncalls=114293, regioncalls=0, ndraw=128, logz=-5.14, remainder_fraction=83.8845%, Lmin=-2.53, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=894, ncalls=115521, regioncalls=0, ndraw=128, logz=-5.11, remainder_fraction=83.3476%, Lmin=-2.49, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=116779, regioncalls=0, ndraw=128, logz=-5.09, remainder_fraction=82.9070%, Lmin=-2.48, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=907, ncalls=117816, regioncalls=0, ndraw=128, logz=-5.06, remainder_fraction=82.4805%, Lmin=-2.47, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=915, ncalls=119020, regioncalls=0, ndraw=128, logz=-5.04, remainder_fraction=82.1871%, Lmin=-2.45, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=923, ncalls=120345, regioncalls=0, ndraw=128, logz=-5.01, remainder_fraction=81.7142%, Lmin=-2.42, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=931, ncalls=121552, regioncalls=0, ndraw=128, logz=-4.98, remainder_fraction=81.1462%, Lmin=-2.38, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=939, ncalls=122806, regioncalls=0, ndraw=128, logz=-4.96, remainder_fraction=80.6354%, Lmin=-2.34, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=948, ncalls=124131, regioncalls=0, ndraw=128, logz=-4.93, remainder_fraction=80.0308%, Lmin=-2.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=124525, regioncalls=0, ndraw=128, logz=-4.92, remainder_fraction=79.9262%, Lmin=-2.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=959, ncalls=125834, regioncalls=0, ndraw=128, logz=-4.89, remainder_fraction=79.2442%, Lmin=-2.28, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=968, ncalls=127106, regioncalls=0, ndraw=128, logz=-4.87, remainder_fraction=78.5322%, Lmin=-2.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=975, ncalls=128335, regioncalls=0, ndraw=128, logz=-4.85, remainder_fraction=78.0921%, Lmin=-2.22, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=982, ncalls=129796, regioncalls=0, ndraw=128, logz=-4.82, remainder_fraction=77.5509%, Lmin=-2.20, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=989, ncalls=131025, regioncalls=0, ndraw=128, logz=-4.80, remainder_fraction=77.1161%, Lmin=-2.16, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=131028, regioncalls=0, ndraw=128, logz=-4.80, remainder_fraction=77.0999%, Lmin=-2.16, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=997, ncalls=132268, regioncalls=0, ndraw=128, logz=-4.78, remainder_fraction=76.5821%, Lmin=-2.13, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=132303, regioncalls=0, ndraw=128, logz=-4.77, remainder_fraction=76.3325%, Lmin=-2.12, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1005, ncalls=133447, regioncalls=0, ndraw=128, logz=-4.76, remainder_fraction=75.9134%, Lmin=-2.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1014, ncalls=134816, regioncalls=0, ndraw=128, logz=-4.73, remainder_fraction=75.1846%, Lmin=-2.06, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1021, ncalls=135885, regioncalls=0, ndraw=128, logz=-4.71, remainder_fraction=74.6452%, Lmin=-2.04, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1028, ncalls=137173, regioncalls=0, ndraw=128, logz=-4.69, remainder_fraction=74.2930%, Lmin=-2.02, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1036, ncalls=138360, regioncalls=0, ndraw=128, logz=-4.67, remainder_fraction=73.7034%, Lmin=-2.00, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1043, ncalls=139538, regioncalls=0, ndraw=128, logz=-4.65, remainder_fraction=73.2286%, Lmin=-1.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1048, ncalls=140562, regioncalls=0, ndraw=128, logz=-4.64, remainder_fraction=72.7853%, Lmin=-1.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=140682, regioncalls=0, ndraw=128, logz=-4.63, remainder_fraction=72.6208%, Lmin=-1.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1055, ncalls=141823, regioncalls=0, ndraw=128, logz=-4.62, remainder_fraction=72.2291%, Lmin=-1.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1060, ncalls=142697, regioncalls=0, ndraw=128, logz=-4.61, remainder_fraction=71.9285%, Lmin=-1.90, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1068, ncalls=143907, regioncalls=0, ndraw=128, logz=-4.58, remainder_fraction=71.3196%, Lmin=-1.88, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1073, ncalls=144733, regioncalls=0, ndraw=128, logz=-4.57, remainder_fraction=70.8905%, Lmin=-1.86, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1079, ncalls=145847, regioncalls=0, ndraw=128, logz=-4.56, remainder_fraction=70.3962%, Lmin=-1.83, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1083, ncalls=146495, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=70.1319%, Lmin=-1.81, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1091, ncalls=148031, regioncalls=0, ndraw=128, logz=-4.53, remainder_fraction=69.4710%, Lmin=-1.79, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1099, ncalls=149288, regioncalls=0, ndraw=128, logz=-4.51, remainder_fraction=68.9367%, Lmin=-1.78, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=149295, regioncalls=0, ndraw=128, logz=-4.50, remainder_fraction=68.8495%, Lmin=-1.78, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1106, ncalls=150295, regioncalls=0, ndraw=128, logz=-4.49, remainder_fraction=68.4076%, Lmin=-1.76, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1111, ncalls=151105, regioncalls=0, ndraw=128, logz=-4.48, remainder_fraction=68.0835%, Lmin=-1.75, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1116, ncalls=152390, regioncalls=0, ndraw=128, logz=-4.47, remainder_fraction=67.6795%, Lmin=-1.73, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1123, ncalls=153502, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=67.2453%, Lmin=-1.71, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1131, ncalls=154756, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=66.5362%, Lmin=-1.69, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1136, ncalls=155670, regioncalls=0, ndraw=128, logz=-4.42, remainder_fraction=66.1125%, Lmin=-1.67, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1142, ncalls=156840, regioncalls=0, ndraw=128, logz=-4.41, remainder_fraction=65.6280%, Lmin=-1.65, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1147, ncalls=157659, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=65.2970%, Lmin=-1.62, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=158021, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=65.1511%, Lmin=-1.62, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1158, ncalls=159283, regioncalls=0, ndraw=128, logz=-4.37, remainder_fraction=64.5717%, Lmin=-1.60, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1163, ncalls=160304, regioncalls=0, ndraw=128, logz=-4.36, remainder_fraction=64.1816%, Lmin=-1.59, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=161116, regioncalls=0, ndraw=128, logz=-4.34, remainder_fraction=63.6428%, Lmin=-1.57, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1176, ncalls=162144, regioncalls=0, ndraw=128, logz=-4.33, remainder_fraction=63.1316%, Lmin=-1.55, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1183, ncalls=163297, regioncalls=0, ndraw=128, logz=-4.32, remainder_fraction=62.5427%, Lmin=-1.54, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1189, ncalls=164331, regioncalls=0, ndraw=128, logz=-4.30, remainder_fraction=62.1219%, Lmin=-1.53, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=165292, regioncalls=0, ndraw=128, logz=-4.29, remainder_fraction=61.8306%, Lmin=-1.52, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=166312, regioncalls=0, ndraw=128, logz=-4.28, remainder_fraction=61.3152%, Lmin=-1.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1208, ncalls=167575, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=60.5636%, Lmin=-1.49, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1216, ncalls=168949, regioncalls=0, ndraw=128, logz=-4.25, remainder_fraction=59.9707%, Lmin=-1.47, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1221, ncalls=169986, regioncalls=0, ndraw=128, logz=-4.24, remainder_fraction=59.6611%, Lmin=-1.46, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1229, ncalls=171180, regioncalls=0, ndraw=128, logz=-4.23, remainder_fraction=59.2401%, Lmin=-1.44, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1234, ncalls=172349, regioncalls=0, ndraw=128, logz=-4.22, remainder_fraction=58.8625%, Lmin=-1.41, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1239, ncalls=173329, regioncalls=0, ndraw=128, logz=-4.21, remainder_fraction=58.4573%, Lmin=-1.39, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1247, ncalls=174627, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=57.7728%, Lmin=-1.36, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=174686, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=57.5210%, Lmin=-1.36, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1252, ncalls=175596, regioncalls=0, ndraw=128, logz=-4.18, remainder_fraction=57.3282%, Lmin=-1.35, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1259, ncalls=176652, regioncalls=0, ndraw=128, logz=-4.17, remainder_fraction=56.7873%, Lmin=-1.33, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=176886, regioncalls=0, ndraw=128, logz=-4.17, remainder_fraction=56.6865%, Lmin=-1.33, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1267, ncalls=177902, regioncalls=0, ndraw=128, logz=-4.15, remainder_fraction=56.1055%, Lmin=-1.32, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1273, ncalls=178998, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=55.6734%, Lmin=-1.31, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1282, ncalls=180274, regioncalls=0, ndraw=128, logz=-4.13, remainder_fraction=55.0354%, Lmin=-1.29, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1289, ncalls=181554, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=54.5799%, Lmin=-1.27, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1298, ncalls=182819, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=53.9707%, Lmin=-1.26, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=183109, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=53.7885%, Lmin=-1.26, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1306, ncalls=184349, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=53.3077%, Lmin=-1.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1315, ncalls=185624, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=52.7342%, Lmin=-1.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1322, ncalls=186767, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=52.1344%, Lmin=-1.21, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1330, ncalls=187985, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=51.4118%, Lmin=-1.20, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1335, ncalls=188900, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=51.1255%, Lmin=-1.19, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1341, ncalls=189874, regioncalls=0, ndraw=128, logz=-4.03, remainder_fraction=50.7369%, Lmin=-1.17, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1349, ncalls=191131, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=50.0458%, Lmin=-1.15, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=191558, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=49.9925%, Lmin=-1.15, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1357, ncalls=192760, regioncalls=0, ndraw=128, logz=-4.01, remainder_fraction=49.4501%, Lmin=-1.13, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1365, ncalls=194107, regioncalls=0, ndraw=128, logz=-4.00, remainder_fraction=48.8177%, Lmin=-1.12, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1373, ncalls=195417, regioncalls=0, ndraw=128, logz=-3.99, remainder_fraction=48.1704%, Lmin=-1.10, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1381, ncalls=196696, regioncalls=0, ndraw=128, logz=-3.97, remainder_fraction=47.7005%, Lmin=-1.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1389, ncalls=197982, regioncalls=0, ndraw=128, logz=-3.96, remainder_fraction=47.0590%, Lmin=-1.08, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1395, ncalls=199016, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=46.5733%, Lmin=-1.07, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=200002, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=46.1871%, Lmin=-1.05, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1408, ncalls=201398, regioncalls=0, ndraw=128, logz=-3.94, remainder_fraction=45.6260%, Lmin=-1.05, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1416, ncalls=202794, regioncalls=0, ndraw=128, logz=-3.93, remainder_fraction=45.0946%, Lmin=-1.04, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1424, ncalls=204211, regioncalls=0, ndraw=128, logz=-3.92, remainder_fraction=44.5176%, Lmin=-1.03, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1432, ncalls=205426, regioncalls=0, ndraw=128, logz=-3.91, remainder_fraction=43.8979%, Lmin=-1.02, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=206860, regioncalls=0, ndraw=128, logz=-3.90, remainder_fraction=43.3227%, Lmin=-1.01, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1446, ncalls=207891, regioncalls=0, ndraw=128, logz=-3.89, remainder_fraction=42.8518%, Lmin=-0.99, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=208561, regioncalls=0, ndraw=128, logz=-3.88, remainder_fraction=42.5588%, Lmin=-0.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1457, ncalls=209885, regioncalls=0, ndraw=128, logz=-3.88, remainder_fraction=42.0478%, Lmin=-0.98, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1464, ncalls=211060, regioncalls=0, ndraw=128, logz=-3.87, remainder_fraction=41.5226%, Lmin=-0.97, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1472, ncalls=212368, regioncalls=0, ndraw=128, logz=-3.86, remainder_fraction=40.9935%, Lmin=-0.97, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=213760, regioncalls=0, ndraw=128, logz=-3.85, remainder_fraction=40.5184%, Lmin=-0.96, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1487, ncalls=214932, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=40.1063%, Lmin=-0.95, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1492, ncalls=215921, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=39.7295%, Lmin=-0.94, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1498, ncalls=216880, regioncalls=0, ndraw=128, logz=-3.83, remainder_fraction=39.3938%, Lmin=-0.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=217236, regioncalls=0, ndraw=128, logz=-3.83, remainder_fraction=39.2266%, Lmin=-0.93, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1508, ncalls=218630, regioncalls=0, ndraw=128, logz=-3.82, remainder_fraction=38.6220%, Lmin=-0.91, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1516, ncalls=219890, regioncalls=0, ndraw=128, logz=-3.81, remainder_fraction=38.0736%, Lmin=-0.89, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1522, ncalls=221352, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.7437%, Lmin=-0.88, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1529, ncalls=222535, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.3219%, Lmin=-0.87, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=222727, regioncalls=0, ndraw=128, logz=-3.80, remainder_fraction=37.2575%, Lmin=-0.87, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1537, ncalls=223922, regioncalls=0, ndraw=128, logz=-3.79, remainder_fraction=36.8316%, Lmin=-0.86, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1545, ncalls=225297, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=36.3914%, Lmin=-0.85, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=226001, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=36.0648%, Lmin=-0.84, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1557, ncalls=227211, regioncalls=0, ndraw=128, logz=-3.77, remainder_fraction=35.6278%, Lmin=-0.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1565, ncalls=228491, regioncalls=0, ndraw=128, logz=-3.76, remainder_fraction=35.1825%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1573, ncalls=229851, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=34.6997%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1582, ncalls=231405, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=34.1898%, Lmin=-0.80, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1588, ncalls=232425, regioncalls=0, ndraw=128, logz=-3.74, remainder_fraction=33.8591%, Lmin=-0.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1594, ncalls=234014, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=33.5123%, Lmin=-0.78, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=234722, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=33.1344%, Lmin=-0.77, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1606, ncalls=235930, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=32.7584%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1614, ncalls=237299, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=32.2649%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=238351, regioncalls=0, ndraw=128, logz=-3.71, remainder_fraction=31.9350%, Lmin=-0.75, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1626, ncalls=239603, regioncalls=0, ndraw=128, logz=-3.71, remainder_fraction=31.6011%, Lmin=-0.74, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1634, ncalls=240903, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=31.1443%, Lmin=-0.74, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1641, ncalls=242354, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.7713%, Lmin=-0.73, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1648, ncalls=243473, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.3679%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=243713, regioncalls=0, ndraw=128, logz=-3.69, remainder_fraction=30.2673%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1656, ncalls=244993, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=29.9417%, Lmin=-0.71, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1663, ncalls=246209, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=29.5216%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1668, ncalls=247247, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=29.2560%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1676, ncalls=248747, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=28.8177%, Lmin=-0.69, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1684, ncalls=249958, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=28.3780%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1691, ncalls=251223, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=28.0201%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1699, ncalls=252454, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=27.5889%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=252456, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=27.5537%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1708, ncalls=253741, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=27.1738%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=253762, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=27.0691%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1715, ncalls=254976, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=26.8026%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1721, ncalls=256099, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=26.4894%, Lmin=-0.64, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1729, ncalls=257675, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=26.0502%, Lmin=-0.62, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1737, ncalls=259026, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=25.6381%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1746, ncalls=260451, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=25.1702%, Lmin=-0.60, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=261074, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=24.9783%, Lmin=-0.60, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1757, ncalls=262618, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=24.6173%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1765, ncalls=263914, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=24.2783%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1773, ncalls=265169, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=23.8709%, Lmin=-0.58, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1781, ncalls=266465, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=23.4919%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1788, ncalls=267765, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=23.1560%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1795, ncalls=269142, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=22.8337%, Lmin=-0.56, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=269863, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=22.5989%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1804, ncalls=270731, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=22.4159%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1811, ncalls=272311, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=22.1180%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1819, ncalls=273696, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=21.7683%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1826, ncalls=274507, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.4689%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1830, ncalls=275651, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.2920%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1837, ncalls=276935, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=21.0046%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1845, ncalls=278293, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.6981%, Lmin=-0.51, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=279113, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.5062%, Lmin=-0.51, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1857, ncalls=280450, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=20.2144%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1865, ncalls=281972, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=19.8721%, Lmin=-0.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1876, ncalls=283256, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=19.4363%, Lmin=-0.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1885, ncalls=285070, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=19.0849%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=285727, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=18.8919%, Lmin=-0.47, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1896, ncalls=287050, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=18.6619%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=287684, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=18.5192%, Lmin=-0.46, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1910, ncalls=288941, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=18.1599%, Lmin=-0.45, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1917, ncalls=290248, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=17.9067%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1925, ncalls=291586, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.6214%, Lmin=-0.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1933, ncalls=292876, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.3105%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1940, ncalls=294179, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=17.0645%, Lmin=-0.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1948, ncalls=295516, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.7943%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=295613, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.7164%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1958, ncalls=296901, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.4389%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1966, ncalls=298201, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=16.1662%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1975, ncalls=299993, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.8691%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=300651, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.7044%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1987, ncalls=301913, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=15.4675%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=1995, ncalls=303133, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=15.1802%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=303776, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=15.0240%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2007, ncalls=305031, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=14.8057%, Lmin=-0.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2012, ncalls=306273, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=14.6436%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2020, ncalls=307636, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.3950%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2028, ncalls=308755, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.1553%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2033, ncalls=309871, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=14.0060%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2041, ncalls=311163, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=13.7559%, Lmin=-0.37, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2047, ncalls=312307, regioncalls=0, ndraw=128, logz=-3.48, remainder_fraction=13.5648%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=312313, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.4757%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2055, ncalls=313463, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.3297%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2060, ncalls=314447, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=13.1879%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2068, ncalls=315751, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.9770%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=315963, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.9210%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2077, ncalls=317183, regioncalls=0, ndraw=128, logz=-3.47, remainder_fraction=12.7220%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2084, ncalls=318371, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.5351%, Lmin=-0.34, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2089, ncalls=319341, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.3974%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2096, ncalls=320561, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.2152%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=321161, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=12.1107%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2107, ncalls=322344, regioncalls=0, ndraw=128, logz=-3.46, remainder_fraction=11.9295%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2113, ncalls=323486, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.7690%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2119, ncalls=324648, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.6167%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2126, ncalls=325819, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.4403%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2130, ncalls=326780, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.3350%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2137, ncalls=327927, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.1650%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2142, ncalls=328771, regioncalls=0, ndraw=128, logz=-3.45, remainder_fraction=11.0415%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2149, ncalls=330050, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.8644%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=330154, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.8411%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2156, ncalls=331014, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.6940%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=331682, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.6029%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2165, ncalls=332818, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.4874%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2172, ncalls=334125, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.3389%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2180, ncalls=335600, regioncalls=0, ndraw=128, logz=-3.44, remainder_fraction=10.1603%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2188, ncalls=336929, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.9863%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2196, ncalls=338257, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.8082%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=338933, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.7195%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2206, ncalls=340016, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.5972%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2210, ncalls=340940, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.5115%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2218, ncalls=342183, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.3382%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2226, ncalls=343509, regioncalls=0, ndraw=128, logz=-3.43, remainder_fraction=9.1733%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2234, ncalls=344612, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=9.0049%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2241, ncalls=345805, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.8679%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2247, ncalls=347049, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.7529%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=347629, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.6917%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2256, ncalls=348869, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.5758%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2264, ncalls=350130, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.4240%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2272, ncalls=351422, regioncalls=0, ndraw=128, logz=-3.42, remainder_fraction=8.2731%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2279, ncalls=352749, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=8.1448%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2287, ncalls=354025, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=8.0024%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2296, ncalls=355385, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.8321%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=356045, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.7606%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2308, ncalls=357389, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.6169%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2315, ncalls=358620, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.4990%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2323, ncalls=359956, regioncalls=0, ndraw=128, logz=-3.41, remainder_fraction=7.3681%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2330, ncalls=360972, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.2513%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2335, ncalls=361933, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.1699%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=362725, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=7.0919%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2346, ncalls=363977, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.9940%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=364638, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.9298%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2358, ncalls=365992, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.8025%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2365, ncalls=367191, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.6928%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2375, ncalls=368621, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.5371%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2383, ncalls=370241, regioncalls=0, ndraw=128, logz=-3.40, remainder_fraction=6.4196%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2393, ncalls=371563, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.2776%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=372823, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.1795%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2408, ncalls=374076, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=6.0650%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2416, ncalls=375751, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.9542%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2427, ncalls=377177, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.8079%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=377883, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.7682%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2438, ncalls=379251, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.6650%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2444, ncalls=380555, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.5852%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=381211, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.5106%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2456, ncalls=382575, regioncalls=0, ndraw=128, logz=-3.39, remainder_fraction=5.4331%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2464, ncalls=383831, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.3338%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2471, ncalls=385167, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.2486%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2479, ncalls=386483, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.1495%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2488, ncalls=388095, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=5.0446%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2497, ncalls=389615, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.9410%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=389953, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.9061%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2508, ncalls=391758, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.8152%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2517, ncalls=392934, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.7156%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2522, ncalls=394145, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.6598%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2530, ncalls=395380, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.5719%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2537, ncalls=396686, regioncalls=0, ndraw=128, logz=-3.38, remainder_fraction=4.4993%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2546, ncalls=398301, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.4054%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=398948, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.3647%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2558, ncalls=400259, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.2835%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2565, ncalls=401596, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.2146%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2573, ncalls=402884, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.1356%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2581, ncalls=404180, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=4.0578%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2589, ncalls=405476, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.9809%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2595, ncalls=406855, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.9256%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=407511, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.8796%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2607, ncalls=408762, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.8162%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=409074, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.7895%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2617, ncalls=410438, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.7267%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2625, ncalls=411842, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.6574%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2634, ncalls=413543, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.5795%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2642, ncalls=414800, regioncalls=0, ndraw=128, logz=-3.37, remainder_fraction=3.5123%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=416076, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.4464%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2658, ncalls=417597, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.3812%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2666, ncalls=418866, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.3186%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2674, ncalls=420228, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.2552%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2682, ncalls=421691, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.1934%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2687, ncalls=422859, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.1555%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2695, ncalls=424153, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0957%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=424853, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0593%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2707, ncalls=426081, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=3.0093%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2716, ncalls=427783, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.9460%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2725, ncalls=429087, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.8832%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2734, ncalls=430734, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.8225%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2743, ncalls=432084, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.7615%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=433209, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.7156%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2759, ncalls=434541, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.6579%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2767, ncalls=435865, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.6072%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2772, ncalls=437051, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.5765%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2781, ncalls=438375, regioncalls=0, ndraw=128, logz=-3.36, remainder_fraction=2.5208%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=439611, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4670%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2797, ncalls=441134, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4257%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=441273, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.4084%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2808, ncalls=442474, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.3627%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2816, ncalls=444228, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.3181%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2822, ncalls=445500, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2847%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2829, ncalls=446603, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2460%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2834, ncalls=447455, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.2188%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2842, ncalls=448706, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1764%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2849, ncalls=449926, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1400%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=449954, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.1349%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2857, ncalls=451220, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0988%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2865, ncalls=452703, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0584%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2873, ncalls=453977, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=2.0191%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=455237, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9850%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2888, ncalls=456550, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9471%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2896, ncalls=457846, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.9099%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=458521, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8913%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2907, ncalls=459673, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8592%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2910, ncalls=460517, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8457%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2919, ncalls=461802, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.8059%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2926, ncalls=463176, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7757%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2934, ncalls=464523, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7415%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2942, ncalls=465875, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.7078%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=467204, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.6746%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=468947, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.6342%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2969, ncalls=470091, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5992%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=470696, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5954%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2978, ncalls=471947, regioncalls=0, ndraw=128, logz=-3.35, remainder_fraction=1.5644%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2986, ncalls=473395, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.5339%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2994, ncalls=474732, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.5040%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=475462, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4822%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3006, ncalls=476748, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4606%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3014, ncalls=478046, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4323%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3022, ncalls=479427, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.4048%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3031, ncalls=480765, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3746%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3038, ncalls=481985, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3512%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3046, ncalls=483313, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3250%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=484209, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.3121%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3058, ncalls=485486, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2867%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=485700, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2804%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3064, ncalls=486716, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2679%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3071, ncalls=488011, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2465%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3079, ncalls=489356, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.2224%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3087, ncalls=490653, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1986%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3094, ncalls=491929, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1783%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=492690, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1611%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3107, ncalls=493971, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1413%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3117, ncalls=495411, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.1138%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3125, ncalls=496783, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0923%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3132, ncalls=498266, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0737%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3142, ncalls=499798, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0475%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=501237, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0273%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3158, ncalls=502625, regioncalls=0, ndraw=128, logz=-3.34, remainder_fraction=1.0072%, Lmin=-0.05, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 502865 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.322 +- 0.04713 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1862.2, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_utils.py::test_tau

0.18

[gw7] linux -- Python 3.10.6 /usr/bin/python3
[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3[gw7] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_utils.py::test_make_log_dirs

0.00

Passed

tests/test_run.py::test_run_compat

14.37

[gw11] linux -- Python 3.10.6 /usr/bin/python3
[gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3[gw11] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-3.81) * Expected Volume: exp(0.00) Quality: ok a: -5.0|********************************************************| +5.0 b: +0.1|*************************************** ********* ******| +1.0 Z=-inf(0.00%) | Like=-150059.97..-44.75 [-150059.9655..-29270.9321] | it/evals=0/401 eff=0.0000% N=400 Z=-104734.3(0.00%) | Like=-100947.38..-44.75 [-150059.9655..-29270.9321] | it/evals=40/444 eff=90.9091% N=400 Z=-86037.1(0.00%) | Like=-85924.59..-44.75 [-150059.9655..-29270.9321] | it/evals=80/489 eff=89.8876% N=400 Mono-modal Volume: ~exp(-4.45) * Expected Volume: exp(-0.23) Quality: ok a: -5.0| ********************************************** | +5.0 b: +0.1|********************** *********************************| +1.0 Z=-80369.4(0.00%) | Like=-80185.87..-44.75 [-150059.9655..-29270.9321] | it/evals=90/501 eff=89.1089% N=400 Z=-71475.7(0.00%) | Like=-69443.05..-21.05 [-150059.9655..-29270.9321] | it/evals=120/534 eff=89.5522% N=400 Z=-58131.3(0.00%) | Like=-57488.58..-21.05 [-150059.9655..-29270.9321] | it/evals=160/580 eff=88.8889% N=400 Mono-modal Volume: ~exp(-4.56) * Expected Volume: exp(-0.45) Quality: ok a: -5.0| -2.7 ************************************* | +5.0 b: +0.1|********************************************************| +1.0 Z=-52991.0(0.00%) | Like=-52852.75..-21.05 [-150059.9655..-29270.9321] | it/evals=180/605 eff=87.8049% N=400 Z=-48345.7(0.00%) | Like=-47845.05..-21.05 [-150059.9655..-29270.9321] | it/evals=200/626 eff=88.4956% N=400 Z=-37590.2(0.00%) | Like=-37078.25..-21.05 [-150059.9655..-29270.9321] | it/evals=240/673 eff=87.9121% N=400 Mono-modal Volume: ~exp(-4.99) * Expected Volume: exp(-0.67) Quality: ok a: -5.0| -2.0 **************************** +2.9 | +5.0 b: +0.1|***************************************************** **| +1.0 Z=-30372.3(0.00%) | Like=-30322.16..-21.05 [-150059.9655..-29270.9321] | it/evals=270/715 eff=85.7143% N=400 Z=-29298.9(0.00%) | Like=-29249.63..-21.05 [-29249.6268..-7497.7425] | it/evals=280/726 eff=85.8896% N=400 Z=-23091.8(0.00%) | Like=-22946.67..-21.05 [-29249.6268..-7497.7425] | it/evals=320/783 eff=83.5509% N=400 Mono-modal Volume: ~exp(-4.99) Expected Volume: exp(-0.90) Quality: ok a: -5.0| -1.4 *********************** +2.5 | +5.0 b: +0.1|********************************************** *********| +1.0 Z=-19145.8(0.00%) | Like=-19121.63..-21.05 [-29249.6268..-7497.7425] | it/evals=360/836 eff=82.5688% N=400 Z=-15862.1(0.00%) | Like=-15678.57..-12.03 [-29249.6268..-7497.7425] | it/evals=400/887 eff=82.1355% N=400 Z=-12827.1(0.00%) | Like=-12796.21..-12.03 [-29249.6268..-7497.7425] | it/evals=440/939 eff=81.6327% N=400 Mono-modal Volume: ~exp(-5.56) * Expected Volume: exp(-1.12) Quality: ok a: -5.0| -1.0 ****************** +2.0 | +5.0 b: +0.1|********************************************** *********| +1.0 Z=-12184.6(0.00%) | Like=-12146.12..-12.03 [-29249.6268..-7497.7425] | it/evals=450/952 eff=81.5217% N=400 Z=-10323.6(0.00%) | Like=-10274.28..-12.03 [-29249.6268..-7497.7425] | it/evals=480/985 eff=82.0513% N=400 Z=-8902.1(0.00%) | Like=-8890.74..-12.03 [-29249.6268..-7497.7425] | it/evals=520/1035 eff=81.8898% N=400 Mono-modal Volume: ~exp(-5.92) * Expected Volume: exp(-1.35) Quality: ok a: -5.0| -0.8 *************** +1.7 | +5.0 b: +0.1|********************************************** *********| +1.0 Z=-8189.9(0.00%) | Like=-8169.35..-12.03 [-29249.6268..-7497.7425] | it/evals=540/1061 eff=81.6944% N=400 Z=-7413.0(0.00%) | Like=-7382.62..6.94 [-7486.8234..-2586.6868] | it/evals=560/1088 eff=81.3953% N=400 Z=-6344.0(0.00%) | Like=-6266.53..6.94 [-7486.8234..-2586.6868] | it/evals=600/1141 eff=80.9717% N=400 Mono-modal Volume: ~exp(-5.92) Expected Volume: exp(-1.57) Quality: ok a: -5.0| -0.5 ************ +1.6 | +5.0 b: +0.1|********************************************** **** * **| +1.0 Z=-5508.5(0.00%) | Like=-5472.47..6.94 [-7486.8234..-2586.6868] | it/evals=640/1194 eff=80.6045% N=400 Z=-4780.2(0.00%) | Like=-4683.80..6.94 [-7486.8234..-2586.6868] | it/evals=680/1248 eff=80.1887% N=400 Mono-modal Volume: ~exp(-5.92) Expected Volume: exp(-1.80) Quality: ok a: -5.0| -0.4 *********** +1.3 | +5.0 b: +0.1|********************************************** *** ****| +1.0 Z=-4018.6(0.00%) | Like=-4000.38..6.94 [-7486.8234..-2586.6868] | it/evals=720/1298 eff=80.1782% N=400 Z=-3394.1(0.00%) | Like=-3362.26..6.94 [-7486.8234..-2586.6868] | it/evals=760/1345 eff=80.4233% N=400 Z=-2872.6(0.00%) | Like=-2864.26..6.94 [-7486.8234..-2586.6868] | it/evals=800/1395 eff=80.4020% N=400 Mono-modal Volume: ~exp(-6.21) * Expected Volume: exp(-2.02) Quality: ok a: -5.0| -0.2 ********* +1.2 | +5.0 b: +0.1|************************************** ******* *** ****| +1.0 Z=-2789.6(0.00%) | Like=-2774.48..6.94 [-7486.8234..-2586.6868] | it/evals=810/1410 eff=80.1980% N=400 Z=-2445.5(0.00%) | Like=-2411.76..6.94 [-2585.0265..-977.3647] | it/evals=840/1448 eff=80.1527% N=400 Z=-2007.6(0.00%) | Like=-1991.57..6.94 [-2585.0265..-977.3647] | it/evals=880/1497 eff=80.2188% N=400 Mono-modal Volume: ~exp(-6.32) * Expected Volume: exp(-2.25) Quality: ok a: -5.0| -0.1 ******** +1.1 | +5.0 b: +0.1|************************************** ******** *** ****| +1.0 Z=-1899.4(0.00%) | Like=-1886.20..6.94 [-2585.0265..-977.3647] | it/evals=900/1519 eff=80.4290% N=400 Z=-1803.2(0.00%) | Like=-1779.20..6.94 [-2585.0265..-977.3647] | it/evals=920/1543 eff=80.4899% N=400 Z=-1572.2(0.00%) | Like=-1555.01..6.94 [-2585.0265..-977.3647] | it/evals=960/1596 eff=80.2676% N=400 Mono-modal Volume: ~exp(-6.76) * Expected Volume: exp(-2.47) Quality: ok a: -5.0e+00| -6.7e-03 ******* +1.0e+00 | +5.0e+00 b: +0.1|************************************** ************ * * | +1.0 Z=-1474.5(0.00%) | Like=-1458.46..6.94 [-2585.0265..-977.3647] | it/evals=990/1632 eff=80.3571% N=400 Z=-1383.0(0.00%) | Like=-1374.21..6.94 [-2585.0265..-977.3647] | it/evals=1000/1644 eff=80.3859% N=400 Z=-1226.8(0.00%) | Like=-1216.61..6.94 [-2585.0265..-977.3647] | it/evals=1040/1691 eff=80.5577% N=400 Mono-modal Volume: ~exp(-6.76) Expected Volume: exp(-2.70) Quality: ok a: +0.00| *** * ******************************************* * | +1.00 b: +0.1|*************************************************** | +1.0 Z=-1084.4(0.00%) | Like=-1075.73..6.94 [-2585.0265..-977.3647] | it/evals=1080/1748 eff=80.1187% N=400 Z=-963.0(0.00%) | Like=-953.68..6.94 [-975.7270..-498.6373] | it/evals=1120/1798 eff=80.1144% N=400 Z=-855.4(0.00%) | Like=-844.78..6.94 [-975.7270..-498.6373] | it/evals=1160/1850 eff=80.0000% N=400 Mono-modal Volume: ~exp(-7.18) * Expected Volume: exp(-2.92) Quality: ok a: +0.0| * ******************************************* | +1.0 b: +0.1|************************************************* | +1.0 Z=-824.7(0.00%) | Like=-814.00..6.94 [-975.7270..-498.6373] | it/evals=1170/1861 eff=80.0821% N=400 Z=-763.2(0.00%) | Like=-753.01..6.94 [-975.7270..-498.6373] | it/evals=1200/1902 eff=79.8935% N=400 Z=-692.3(0.00%) | Like=-682.98..6.94 [-975.7270..-498.6373] | it/evals=1240/1952 eff=79.8969% N=400 Mono-modal Volume: ~exp(-7.18) Expected Volume: exp(-3.15) Quality: ok a: +0.0| **************************************** | +1.0 b: +0.1| ********************************************* | +1.0 Z=-644.0(0.00%) | Like=-634.74..6.94 [-975.7270..-498.6373] | it/evals=1274/2000 eff=79.6250% N=400 Z=-638.6(0.00%) | Like=-629.70..6.94 [-975.7270..-498.6373] | it/evals=1280/2006 eff=79.7011% N=400 Z=-586.3(0.00%) | Like=-575.50..6.94 [-975.7270..-498.6373] | it/evals=1320/2052 eff=79.9031% N=400 Mono-modal Volume: ~exp(-7.54) * Expected Volume: exp(-3.37) Quality: ok a: +0.0| ************************************** | +1.0 b: +0.1| ****************************************** +0.8 | +1.0 Z=-555.6(0.00%) | Like=-546.02..6.94 [-975.7270..-498.6373] | it/evals=1350/2097 eff=79.5522% N=400 Z=-550.8(0.00%) | Like=-539.31..6.94 [-975.7270..-498.6373] | it/evals=1360/2108 eff=79.6253% N=400 Z=-511.1(0.00%) | Like=-502.53..6.94 [-975.7270..-498.6373] | it/evals=1400/2161 eff=79.5003% N=400 Mono-modal Volume: ~exp(-7.99) * Expected Volume: exp(-3.60) Quality: ok a: +0.0| +0.2 ********************************** +0.8 | +1.0 b: +0.1| ************************************** +0.8 | +1.0 Z=-460.0(0.00%) | Like=-448.24..6.94 [-497.7545..-255.3082] | it/evals=1440/2211 eff=79.5141% N=400 Z=-415.4(0.00%) | Like=-405.19..6.94 [-497.7545..-255.3082] | it/evals=1480/2261 eff=79.5271% N=400 Z=-377.3(0.00%) | Like=-367.12..6.94 [-497.7545..-255.3082] | it/evals=1520/2315 eff=79.3734% N=400 Mono-modal Volume: ~exp(-8.08) * Expected Volume: exp(-3.82) Quality: ok a: +0.0| +0.2 ****************************** +0.8 | +1.0 b: +0.1| ********************************** +0.8 | +1.0 Z=-362.2(0.00%) | Like=-352.36..6.94 [-497.7545..-255.3082] | it/evals=1530/2335 eff=79.0698% N=400 Z=-333.8(0.00%) | Like=-324.76..6.94 [-497.7545..-255.3082] | it/evals=1560/2371 eff=79.1476% N=400 Z=-308.7(0.00%) | Like=-299.15..6.94 [-497.7545..-255.3082] | it/evals=1600/2424 eff=79.0514% N=400 Mono-modal Volume: ~exp(-8.18) * Expected Volume: exp(-4.05) Quality: ok a: +0.0| +0.3 **************************** +0.7 | +1.0 b: +0.1| ******************************* +0.7 | +1.0 Z=-293.7(0.00%) | Like=-284.49..6.94 [-497.7545..-255.3082] | it/evals=1620/2448 eff=79.1016% N=400 Z=-284.0(0.00%) | Like=-274.78..6.94 [-497.7545..-255.3082] | it/evals=1640/2470 eff=79.2271% N=400 Z=-263.4(0.00%) | Like=-253.48..6.94 [-254.8939..-131.7677] | it/evals=1680/2519 eff=79.2827% N=400 Mono-modal Volume: ~exp(-8.73) * Expected Volume: exp(-4.27) Quality: ok a: +0.0| +0.3 ************************** +0.7 | +1.0 b: +0.1| +0.3 **************************** +0.7 | +1.0 Z=-247.2(0.00%) | Like=-237.91..6.98 [-254.8939..-131.7677] | it/evals=1710/2562 eff=79.0934% N=400 Z=-241.6(0.00%) | Like=-231.36..6.98 [-254.8939..-131.7677] | it/evals=1720/2574 eff=79.1168% N=400 Z=-223.9(0.00%) | Like=-213.84..6.98 [-254.8939..-131.7677] | it/evals=1760/2625 eff=79.1011% N=400 Mono-modal Volume: ~exp(-8.73) Expected Volume: exp(-4.50) Quality: ok a: +0.0| +0.3 ********************** +0.7 | +1.0 b: +0.1| +0.3 ************************** +0.7 | +1.0 Z=-200.6(0.00%) | Like=-189.89..7.11 [-254.8939..-131.7677] | it/evals=1800/2682 eff=78.8782% N=400 Z=-181.7(0.00%) | Like=-172.17..7.11 [-254.8939..-131.7677] | it/evals=1840/2741 eff=78.5989% N=400 Z=-170.2(0.00%) | Like=-160.77..7.11 [-254.8939..-131.7677] | it/evals=1880/2794 eff=78.5297% N=400 Mono-modal Volume: ~exp(-9.04) * Expected Volume: exp(-4.73) Quality: ok a: +0.0| +0.3 ******************** +0.7 | +1.0 b: +0.1| +0.3 ********************** +0.7 | +1.0 Z=-166.2(0.00%) | Like=-154.79..7.11 [-254.8939..-131.7677] | it/evals=1890/2806 eff=78.5536% N=400 Z=-151.6(0.00%) | Like=-141.60..7.11 [-254.8939..-131.7677] | it/evals=1920/2841 eff=78.6563% N=400 Z=-140.7(0.00%) | Like=-130.92..7.11 [-131.5175..-70.4115] | it/evals=1960/2898 eff=78.4628% N=400 Mono-modal Volume: ~exp(-9.19) * Expected Volume: exp(-4.95) Quality: ok a: +0.0| +0.3 ****************** +0.7 | +1.0 b: +0.1| +0.3 ********************* +0.7 | +1.0 Z=-134.7(0.00%) | Like=-124.27..7.11 [-131.5175..-70.4115] | it/evals=1980/2925 eff=78.4158% N=400 Z=-129.5(0.00%) | Like=-119.73..7.11 [-131.5175..-70.4115] | it/evals=2000/2948 eff=78.4929% N=400 Z=-118.0(0.00%) | Like=-108.43..7.11 [-131.5175..-70.4115] | it/evals=2040/3003 eff=78.3711% N=400 Mono-modal Volume: ~exp(-9.19) Expected Volume: exp(-5.18) Quality: ok a: +0.0| +0.4 ****************** +0.6 | +1.0 b: +0.1| +0.4 ******************* +0.6 | +1.0 Z=-108.7(0.00%) | Like=-99.45..7.11 [-131.5175..-70.4115] | it/evals=2080/3054 eff=78.3723% N=400 Z=-100.6(0.00%) | Like=-90.81..7.11 [-131.5175..-70.4115] | it/evals=2120/3108 eff=78.2866% N=400 Mono-modal Volume: ~exp(-9.82) * Expected Volume: exp(-5.40) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 b: +0.1| +0.4 ****************** +0.6 | +1.0 Z=-94.2(0.00%) | Like=-84.22..7.11 [-131.5175..-70.4115] | it/evals=2160/3168 eff=78.0347% N=400 Z=-85.7(0.00%) | Like=-75.78..7.11 [-131.5175..-70.4115] | it/evals=2200/3216 eff=78.1250% N=400 Z=-77.7(0.00%) | Like=-67.57..7.11 [-70.3405..-32.6129] | it/evals=2240/3271 eff=78.0216% N=400 Mono-modal Volume: ~exp(-9.82) Expected Volume: exp(-5.63) Quality: ok a: +0.0| +0.4 ************** +0.6 | +1.0 b: +0.1| +0.4 **************** +0.6 | +1.0 Z=-69.7(0.00%) | Like=-59.45..7.11 [-70.3405..-32.6129] | it/evals=2280/3322 eff=78.0287% N=400 Z=-63.5(0.00%) | Like=-53.27..7.14 [-70.3405..-32.6129] | it/evals=2320/3370 eff=78.1145% N=400 Mono-modal Volume: ~exp(-10.21) * Expected Volume: exp(-5.85) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.1| +0.4 ************** +0.6 | +1.0 Z=-59.4(0.00%) | Like=-49.34..7.14 [-70.3405..-32.6129] | it/evals=2340/3397 eff=78.0781% N=400 Z=-57.0(0.00%) | Like=-47.23..7.14 [-70.3405..-32.6129] | it/evals=2360/3423 eff=78.0681% N=400 Z=-52.4(0.00%) | Like=-42.72..7.14 [-70.3405..-32.6129] | it/evals=2400/3476 eff=78.0234% N=400 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-6.08) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.1| +0.4 ************* +0.6 | +1.0 Z=-49.6(0.00%) | Like=-40.08..7.33 [-70.3405..-32.6129] | it/evals=2430/3513 eff=78.0597% N=400 Z=-48.7(0.00%) | Like=-38.96..7.33 [-70.3405..-32.6129] | it/evals=2440/3523 eff=78.1300% N=400 Z=-44.2(0.00%) | Like=-34.02..7.33 [-70.3405..-32.6129] | it/evals=2480/3569 eff=78.2581% N=400 Mono-modal Volume: ~exp(-10.38) * Expected Volume: exp(-6.30) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.1| +0.4 ************ +0.6 | +1.0 Z=-40.5(0.00%) | Like=-30.69..7.37 [-32.6004..-14.3802] | it/evals=2520/3623 eff=78.1880% N=400 Z=-37.6(0.00%) | Like=-28.06..7.37 [-32.6004..-14.3802] | it/evals=2560/3669 eff=78.3114% N=400 Z=-34.6(0.00%) | Like=-24.34..7.37 [-32.6004..-14.3802] | it/evals=2600/3717 eff=78.3841% N=400 Mono-modal Volume: ~exp(-10.38) Expected Volume: exp(-6.53) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.1| +0.4 ********** +0.6 | +1.0 Z=-31.2(0.00%) | Like=-21.05..7.37 [-32.6004..-14.3802] | it/evals=2640/3765 eff=78.4547% N=400 Z=-28.7(0.00%) | Like=-18.82..7.37 [-32.6004..-14.3802] | it/evals=2680/3819 eff=78.3855% N=400 Mono-modal Volume: ~exp(-11.02) * Expected Volume: exp(-6.75) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.1| +0.4 ********** +0.6 | +1.0 Z=-27.5(0.00%) | Like=-17.74..7.37 [-32.6004..-14.3802] | it/evals=2700/3846 eff=78.3517% N=400 Z=-26.4(0.00%) | Like=-16.46..7.37 [-32.6004..-14.3802] | it/evals=2720/3868 eff=78.4314% N=400 Z=-24.1(0.00%) | Like=-14.05..7.37 [-14.3780..-3.9396] | it/evals=2760/3915 eff=78.5206% N=400 Mono-modal Volume: ~exp(-11.24) * Expected Volume: exp(-6.98) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.1| +0.4 ******** +0.6 | +1.0 Z=-22.4(0.00%) | Like=-12.21..7.37 [-14.3780..-3.9396] | it/evals=2790/3959 eff=78.3928% N=400 Z=-21.8(0.00%) | Like=-11.95..7.37 [-14.3780..-3.9396] | it/evals=2800/3970 eff=78.4314% N=400 Z=-20.2(0.00%) | Like=-10.28..7.37 [-14.3780..-3.9396] | it/evals=2840/4021 eff=78.4314% N=400 Mono-modal Volume: ~exp(-11.40) * Expected Volume: exp(-7.20) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.1| +0.4 ******** +0.6 | +1.0 Z=-18.6(0.00%) | Like=-8.69..7.37 [-14.3780..-3.9396] | it/evals=2880/4075 eff=78.3673% N=400 Z=-17.0(0.00%) | Like=-6.99..7.37 [-14.3780..-3.9396] | it/evals=2920/4120 eff=78.4946% N=400 Z=-15.7(0.00%) | Like=-5.68..7.37 [-14.3780..-3.9396] | it/evals=2960/4178 eff=78.3483% N=400 Mono-modal Volume: ~exp(-11.64) * Expected Volume: exp(-7.43) Quality: ok a: +0.00| +0.45 ****** +0.55 | +1.00 b: +0.1| +0.4 ******* +0.5 | +1.0 Z=-15.4(0.00%) | Like=-5.42..7.37 [-14.3780..-3.9396] | it/evals=2970/4189 eff=78.3848% N=400 Z=-14.4(0.00%) | Like=-4.50..7.37 [-14.3780..-3.9396] | it/evals=3000/4223 eff=78.4724% N=400 Z=-13.3(0.00%) | Like=-3.36..7.37 [-3.9354..1.6850] | it/evals=3040/4277 eff=78.4111% N=400 Mono-modal Volume: ~exp(-11.64) Expected Volume: exp(-7.65) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.10| +0.46 ****** +0.54 | +1.00 Z=-12.3(0.01%) | Like=-2.41..7.37 [-3.9354..1.6850] | it/evals=3080/4327 eff=78.4314% N=400 Z=-11.4(0.02%) | Like=-1.42..7.37 [-3.9354..1.6850] | it/evals=3120/4378 eff=78.4314% N=400 Mono-modal Volume: ~exp(-12.23) * Expected Volume: exp(-7.88) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.10| +0.46 ****** +0.54 | +1.00 Z=-10.8(0.03%) | Like=-0.86..7.37 [-3.9354..1.6850] | it/evals=3150/4421 eff=78.3387% N=400 Z=-10.6(0.03%) | Like=-0.62..7.37 [-3.9354..1.6850] | it/evals=3160/4431 eff=78.3925% N=400 Z=-9.9(0.07%) | Like=-0.01..7.37 [-3.9354..1.6850] | it/evals=3200/4485 eff=78.3354% N=400 Mono-modal Volume: ~exp(-12.23) Expected Volume: exp(-8.10) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.10| +0.47 ****** +0.54 | +1.00 Z=-9.2(0.14%) | Like=0.70..7.37 [-3.9354..1.6850] | it/evals=3240/4535 eff=78.3555% N=400 Z=-8.6(0.26%) | Like=1.42..7.37 [-3.9354..1.6850] | it/evals=3278/4579 eff=78.4398% N=400 Z=-8.6(0.27%) | Like=1.50..7.37 [-3.9354..1.6850] | it/evals=3280/4582 eff=78.4314% N=400 Z=-8.0(0.49%) | Like=2.05..7.37 [1.6923..4.1587] | it/evals=3320/4639 eff=78.3204% N=400 Mono-modal Volume: ~exp(-12.39) * Expected Volume: exp(-8.33) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.10| +0.47 ***** +0.53 | +1.00 Z=-7.9(0.57%) | Like=2.15..7.37 [1.6923..4.1587] | it/evals=3330/4653 eff=78.2977% N=400 Z=-7.5(0.84%) | Like=2.45..7.37 [1.6923..4.1587] | it/evals=3360/4691 eff=78.3034% N=400 Z=-7.0(1.26%) | Like=2.91..7.37 [1.6923..4.1587] | it/evals=3400/4741 eff=78.3230% N=400 Mono-modal Volume: ~exp(-12.71) * Expected Volume: exp(-8.55) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.10| +0.47 **** +0.53 | +1.00 Z=-6.8(1.56%) | Like=3.16..7.37 [1.6923..4.1587] | it/evals=3420/4773 eff=78.2072% N=400 Z=-6.6(1.90%) | Like=3.31..7.37 [1.6923..4.1587] | it/evals=3440/4798 eff=78.2174% N=400 Z=-6.3(2.69%) | Like=3.70..7.37 [1.6923..4.1587] | it/evals=3480/4851 eff=78.1847% N=400 Mono-modal Volume: ~exp(-13.21) * Expected Volume: exp(-8.78) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.10| +0.47 **** +0.53 | +1.00 Z=-6.0(3.47%) | Like=4.07..7.37 [1.6923..4.1587] | it/evals=3510/4883 eff=78.2958% N=400 Z=-5.9(3.75%) | Like=4.14..7.37 [1.6923..4.1587] | it/evals=3520/4896 eff=78.2918% N=400 Z=-5.6(5.21%) | Like=4.39..7.37 [4.1659..4.7607] | it/evals=3560/4944 eff=78.3451% N=400 Mono-modal Volume: ~exp(-13.36) * Expected Volume: exp(-9.00) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.10| +0.48 **** +0.52 | +1.00 Z=-5.3(6.88%) | Like=4.68..7.37 [4.1659..4.7607] | it/evals=3600/4993 eff=78.3801% N=400 Z=-5.0(8.83%) | Like=4.93..7.37 [4.7746..4.9545] | it/evals=3640/5041 eff=78.4314% N=400 Z=-4.8(10.87%) | Like=5.12..7.37 [5.1236..5.1240]*| it/evals=3680/5093 eff=78.4147% N=400 Mono-modal Volume: ~exp(-13.36) Expected Volume: exp(-9.23) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.10| +0.48 **** +0.52 | +1.00 Z=-4.7(12.70%) | Like=5.28..7.37 [5.2759..5.2786]*| it/evals=3713/5137 eff=78.3829% N=400 Z=-4.6(13.10%) | Like=5.33..7.37 [5.3304..5.3354]*| it/evals=3720/5148 eff=78.3488% N=400 Z=-4.4(15.78%) | Like=5.50..7.37 [5.5014..5.5038]*| it/evals=3760/5199 eff=78.3497% N=400 Mono-modal Volume: ~exp(-13.36) Expected Volume: exp(-9.45) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.10| +0.48 **** +0.52 | +1.00 Z=-4.3(18.69%) | Like=5.68..7.37 [5.6814..5.6889]*| it/evals=3800/5245 eff=78.4314% N=400 Z=-4.1(21.95%) | Like=5.88..7.37 [5.8831..5.8902]*| it/evals=3840/5295 eff=78.4474% N=400 Mono-modal Volume: ~exp(-13.85) * Expected Volume: exp(-9.68) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 b: +0.10| +0.48 *** +0.52 | +1.00 Z=-4.0(24.55%) | Like=5.99..7.37 [5.9942..5.9960]*| it/evals=3870/5342 eff=78.3084% N=400 Z=-4.0(25.43%) | Like=6.02..7.37 [6.0202..6.0249]*| it/evals=3880/5354 eff=78.3205% N=400 Z=-3.8(28.82%) | Like=6.16..7.37 [6.1617..6.1641]*| it/evals=3920/5409 eff=78.2591% N=400 Mono-modal Volume: ~exp(-14.32) * Expected Volume: exp(-9.90) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 *** +0.51 | +1.00 Z=-3.7(32.49%) | Like=6.28..7.37 [6.2842..6.2846]*| it/evals=3960/5460 eff=78.2609% N=400 Z=-3.6(36.14%) | Like=6.41..7.37 [6.4106..6.4118]*| it/evals=4000/5516 eff=78.1861% N=400 Z=-3.5(39.90%) | Like=6.49..7.37 [6.4926..6.4949]*| it/evals=4040/5566 eff=78.2036% N=400 Mono-modal Volume: ~exp(-14.32) Expected Volume: exp(-10.13) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-3.5(42.07%) | Like=6.56..7.37 [6.5609..6.5625]*| it/evals=4064/5593 eff=78.2592% N=400 Z=-3.4(43.53%) | Like=6.58..7.37 [6.5825..6.5828]*| it/evals=4080/5610 eff=78.3109% N=400 Z=-3.4(47.11%) | Like=6.66..7.37 [6.6583..6.6593]*| it/evals=4120/5660 eff=78.3270% N=400 Mono-modal Volume: ~exp(-14.58) * Expected Volume: exp(-10.35) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-3.3(48.91%) | Like=6.70..7.37 [6.6999..6.7039]*| it/evals=4140/5685 eff=78.3349% N=400 Z=-3.3(50.57%) | Like=6.73..7.37 [6.7254..6.7256]*| it/evals=4160/5710 eff=78.3427% N=400 Z=-3.2(54.07%) | Like=6.79..7.37 [6.7935..6.7968]*| it/evals=4200/5759 eff=78.3728% N=400 Mono-modal Volume: ~exp(-14.58) Expected Volume: exp(-10.58) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-3.2(57.44%) | Like=6.87..7.37 [6.8738..6.8752]*| it/evals=4240/5814 eff=78.3155% N=400 Z=-3.1(60.63%) | Like=6.93..7.37 [6.9326..6.9344]*| it/evals=4280/5863 eff=78.3452% N=400 Mono-modal Volume: ~exp(-14.58) Expected Volume: exp(-10.80) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-3.1(63.70%) | Like=6.96..7.37 [6.9634..6.9638]*| it/evals=4320/5927 eff=78.1618% N=400 Z=-3.0(66.60%) | Like=7.01..7.37 [7.0058..7.0065]*| it/evals=4360/5973 eff=78.2343% N=400 Z=-3.0(69.25%) | Like=7.05..7.37 [7.0472..7.0492]*| it/evals=4400/6026 eff=78.2083% N=400 Mono-modal Volume: ~exp(-15.49) * Expected Volume: exp(-11.02) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-3.0(69.90%) | Like=7.06..7.37 [7.0585..7.0592]*| it/evals=4410/6039 eff=78.2054% N=400 Z=-2.9(71.75%) | Like=7.09..7.37 [7.0875..7.0885]*| it/evals=4440/6073 eff=78.2655% N=400 Z=-2.9(74.08%) | Like=7.11..7.37 [7.1143..7.1150]*| it/evals=4480/6124 eff=78.2669% N=400 Mono-modal Volume: ~exp(-15.49) Expected Volume: exp(-11.25) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-2.9(76.27%) | Like=7.13..7.37 [7.1346..7.1370]*| it/evals=4520/6175 eff=78.2684% N=400 Z=-2.9(78.30%) | Like=7.16..7.37 [7.1624..7.1628]*| it/evals=4560/6226 eff=78.2698% N=400 Mono-modal Volume: ~exp(-15.68) * Expected Volume: exp(-11.47) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-2.8(79.73%) | Like=7.18..7.37 [7.1780..7.1784]*| it/evals=4590/6271 eff=78.1809% N=400 Z=-2.8(80.19%) | Like=7.18..7.37 [7.1828..7.1828]*| it/evals=4600/6283 eff=78.1914% N=400 Z=-2.8(81.92%) | Like=7.20..7.37 [7.2017..7.2018]*| it/evals=4640/6331 eff=78.2330% N=400 Mono-modal Volume: ~exp(-16.06) * Expected Volume: exp(-11.70) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.10| +0.49 ** +0.51 | +1.00 Z=-2.8(83.50%) | Like=7.22..7.37 [7.2158..7.2163]*| it/evals=4680/6376 eff=78.3133% N=400 Z=-2.8(84.96%) | Like=7.23..7.37 [7.2290..7.2296]*| it/evals=4720/6422 eff=78.3793% N=400 Z=-2.8(86.30%) | Like=7.24..7.37 [7.2418..7.2425]*| it/evals=4760/6472 eff=78.3926% N=400 Mono-modal Volume: ~exp(-16.27) * Expected Volume: exp(-11.92) Quality: ok a: +0.000| +0.495 ** +0.505 | +1.000 b: +0.10| +0.50 ** +0.51 | +1.00 Z=-2.8(86.62%) | Like=7.24..7.37 [7.2443..7.2449]*| it/evals=4770/6486 eff=78.3766% N=400 Z=-2.7(87.54%) | Like=7.25..7.37 [7.2528..7.2531]*| it/evals=4800/6521 eff=78.4186% N=400 Z=-2.7(88.65%) | Like=7.26..7.37 [7.2621..7.2623]*| it/evals=4840/6579 eff=78.3298% N=400 Mono-modal Volume: ~exp(-16.38) * Expected Volume: exp(-12.15) Quality: ok a: +0.000| +0.495 ** +0.504 | +1.000 b: +0.100| +0.496 ** +0.504 | +1.000 Z=-2.7(89.18%) | Like=7.27..7.37 [7.2671..7.2675]*| it/evals=4860/6605 eff=78.3239% N=400 Z=-2.7(89.68%) | Like=7.27..7.37 [7.2729..7.2730]*| it/evals=4880/6628 eff=78.3558% N=400 Z=-2.7(90.61%) | Like=7.28..7.37 [7.2809..7.2811]*| it/evals=4920/6675 eff=78.4064% N=400 Mono-modal Volume: ~exp(-16.38) Expected Volume: exp(-12.37) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 b: +0.100| +0.496 ** +0.504 | +1.000 Z=-2.7(91.37%) | Like=7.29..7.37 [7.2879..7.2882]*| it/evals=4955/6724 eff=78.3523% N=400 Z=-2.7(91.47%) | Like=7.29..7.37 [7.2895..7.2899]*| it/evals=4960/6729 eff=78.3694% N=400 Z=-2.7(92.25%) | Like=7.30..7.37 [7.2977..7.2981]*| it/evals=5000/6783 eff=78.3331% N=400 Mono-modal Volume: ~exp(-16.56) * Expected Volume: exp(-12.60) Quality: ok a: +0.000| +0.497 ** +0.504 | +1.000 b: +0.100| +0.496 ** +0.504 | +1.000 Z=-2.7(92.96%) | Like=7.30..7.37 [7.3042..7.3043]*| it/evals=5040/6838 eff=78.2852% N=400 Z=-2.7(93.52%) | Like=7.31..7.37 [7.3103..7.3103]*| it/evals=5074/6882 eff=78.2783% N=400 Z=-2.7(93.61%) | Like=7.31..7.37 [7.3111..7.3111]*| it/evals=5080/6891 eff=78.2622% N=400 Z=-2.7(94.21%) | Like=7.32..7.37 [7.3152..7.3153]*| it/evals=5120/6948 eff=78.1918% N=400 Mono-modal Volume: ~exp(-17.02) * Expected Volume: exp(-12.82) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.100| +0.497 ** +0.503 | +1.000 Z=-2.7(94.35%) | Like=7.32..7.37 [7.3162..7.3164]*| it/evals=5130/6960 eff=78.2012% N=400 Z=-2.7(94.74%) | Like=7.32..7.37 [7.3203..7.3204]*| it/evals=5160/6997 eff=78.2174% N=400 Z=-2.7(95.23%) | Like=7.33..7.37 [7.3258..7.3259]*| it/evals=5200/7048 eff=78.2190% N=400 Mono-modal Volume: ~exp(-17.46) * Expected Volume: exp(-13.05) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.100| +0.497 ** +0.503 | +1.000 Z=-2.7(95.46%) | Like=7.33..7.37 [7.3290..7.3290]*| it/evals=5220/7073 eff=78.2257% N=400 Z=-2.7(95.67%) | Like=7.33..7.37 [7.3307..7.3310]*| it/evals=5240/7096 eff=78.2557% N=400 Z=-2.6(96.08%) | Like=7.33..7.37 [7.3350..7.3350]*| it/evals=5280/7145 eff=78.2802% N=400 Mono-modal Volume: ~exp(-17.46) Expected Volume: exp(-13.27) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.100| +0.497 ** +0.503 | +1.000 Z=-2.6(96.45%) | Like=7.34..7.37 [7.3383..7.3385]*| it/evals=5320/7199 eff=78.2468% N=400 Z=-2.6(96.78%) | Like=7.34..7.37 [7.3419..7.3419]*| it/evals=5360/7253 eff=78.2139% N=400 Mono-modal Volume: ~exp(-17.90) * Expected Volume: exp(-13.50) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.100| +0.498 ** +0.502 | +1.000 Z=-2.6(97.08%) | Like=7.35..7.37 [7.3454..7.3454]*| it/evals=5400/7305 eff=78.2042% N=400 Z=-2.6(97.35%) | Like=7.35..7.37 [7.3478..7.3479]*| it/evals=5440/7352 eff=78.2509% N=400 Z=-2.6(97.60%) | Like=7.35..7.37 [7.3500..7.3500]*| it/evals=5480/7409 eff=78.1852% N=400 Mono-modal Volume: ~exp(-17.98) * Expected Volume: exp(-13.72) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.100| +0.498 ** +0.502 | +1.000 Z=-2.6(97.66%) | Like=7.35..7.37 [7.3507..7.3507]*| it/evals=5490/7422 eff=78.1829% N=400 Z=-2.6(97.83%) | Like=7.35..7.37 [7.3524..7.3524]*| it/evals=5520/7462 eff=78.1648% N=400 Z=-2.6(98.03%) | Like=7.35..7.37 [7.3541..7.3541]*| it/evals=5560/7518 eff=78.1118% N=400 Mono-modal Volume: ~exp(-18.06) * Expected Volume: exp(-13.95) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.100| +0.498 ** +0.502 | +1.000 Z=-2.6(98.13%) | Like=7.35..7.37 [7.3548..7.3549]*| it/evals=5580/7547 eff=78.0747% N=400 Z=-2.6(98.22%) | Like=7.36..7.37 [7.3555..7.3555]*| it/evals=5600/7571 eff=78.0923% N=400 Z=-2.6(98.39%) | Like=7.36..7.37 [7.3573..7.3573]*| it/evals=5640/7620 eff=78.1163% N=400 Mono-modal Volume: ~exp(-18.68) * Expected Volume: exp(-14.17) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.100| +0.498 * +0.502 | +1.000 Z=-2.6(98.50%) | Like=7.36..7.37 [7.3586..7.3587]*| it/evals=5670/7663 eff=78.0669% N=400 Z=-2.6(98.54%) | Like=7.36..7.37 [7.3589..7.3589]*| it/evals=5680/7674 eff=78.0863% N=400 Z=-2.6(98.68%) | Like=7.36..7.37 [7.3603..7.3603]*| it/evals=5720/7724 eff=78.0994% N=400 Mono-modal Volume: ~exp(-18.68) Expected Volume: exp(-14.40) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 b: +0.100| +0.499 * +0.501 | +1.000 Z=-2.6(98.80%) | Like=7.36..7.37 [7.3612..7.3613]*| it/evals=5760/7779 eff=78.0594% N=400 Z=-2.6(98.92%) | Like=7.36..7.37 [7.3622..7.3622]*| it/evals=5800/7830 eff=78.0619% N=400 [ultranest] Explored until L=7 [ultranest] Likelihood function evaluations: 7875 [ultranest] logZ = -2.61 +- 0.1019 [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.10 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [ultranest] logZ error budget: single: 0.15 bs:0.10 tail:0.01 total:0.10 required:<0.50 [ultranest] done iterating. logZ = -2.607 +- 0.217 single instance: logZ = -2.607 +- 0.150 bootstrapped : logZ = -2.610 +- 0.217 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : 0.4543│ ▁ ▁▁▁▁▁▁▁▁▂▂▂▃▄▄▄▆▇▇▆▆▅▄▄▃▂▂▁▁▁▁▁▁▁ ▁ │0.5399 0.4997 +- 0.0100 b : 0.4567│ ▁ ▁▁▁▁▁▁▁▂▂▃▄▄▅▇▇▇▇▆▆▆▄▄▃▂▂▁▁▁▁▁▁▁▁▁ │0.5410 0.4998 +- 0.0098 evidence: -2.6 +- 0.2 parameter values: a : 0.500 +- 0.010 b : 0.500 +- 0.010
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=0 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=401, regioncalls=40, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-150059.97, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=444, regioncalls=1760, ndraw=40, logz=-104734.27, remainder_fraction=100.0000%, Lmin=-100947.38, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=489, regioncalls=3560, ndraw=40, logz=-86037.10, remainder_fraction=100.0000%, Lmin=-85924.59, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=501, regioncalls=4040, ndraw=40, logz=-80369.36, remainder_fraction=100.0000%, Lmin=-80185.87, Lmax=-44.75 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=534, regioncalls=5360, ndraw=40, logz=-71475.71, remainder_fraction=100.0000%, Lmin=-69443.05, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=580, regioncalls=7200, ndraw=40, logz=-58131.26, remainder_fraction=100.0000%, Lmin=-57488.58, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=605, regioncalls=8200, ndraw=40, logz=-52990.96, remainder_fraction=100.0000%, Lmin=-52852.75, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=626, regioncalls=9040, ndraw=40, logz=-48345.67, remainder_fraction=100.0000%, Lmin=-47845.05, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=673, regioncalls=10920, ndraw=40, logz=-37590.25, remainder_fraction=100.0000%, Lmin=-37078.25, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=715, regioncalls=12600, ndraw=40, logz=-30372.34, remainder_fraction=100.0000%, Lmin=-30322.16, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=726, regioncalls=13040, ndraw=40, logz=-29298.93, remainder_fraction=100.0000%, Lmin=-29249.63, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=783, regioncalls=15320, ndraw=40, logz=-23091.82, remainder_fraction=100.0000%, Lmin=-22946.67, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=836, regioncalls=17440, ndraw=40, logz=-19145.77, remainder_fraction=100.0000%, Lmin=-19121.63, Lmax=-21.05 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=887, regioncalls=19480, ndraw=40, logz=-15862.07, remainder_fraction=100.0000%, Lmin=-15678.57, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=939, regioncalls=21560, ndraw=40, logz=-12827.12, remainder_fraction=100.0000%, Lmin=-12796.21, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=952, regioncalls=22080, ndraw=40, logz=-12184.58, remainder_fraction=100.0000%, Lmin=-12146.12, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=985, regioncalls=23400, ndraw=40, logz=-10323.61, remainder_fraction=100.0000%, Lmin=-10274.28, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1035, regioncalls=25400, ndraw=40, logz=-8902.07, remainder_fraction=100.0000%, Lmin=-8890.74, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1061, regioncalls=26440, ndraw=40, logz=-8189.90, remainder_fraction=100.0000%, Lmin=-8169.35, Lmax=-12.03 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1088, regioncalls=27520, ndraw=40, logz=-7412.95, remainder_fraction=100.0000%, Lmin=-7382.62, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1141, regioncalls=29640, ndraw=40, logz=-6343.98, remainder_fraction=100.0000%, Lmin=-6266.53, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1194, regioncalls=31760, ndraw=40, logz=-5508.53, remainder_fraction=100.0000%, Lmin=-5472.47, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1248, regioncalls=33920, ndraw=40, logz=-4780.23, remainder_fraction=100.0000%, Lmin=-4683.80, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1298, regioncalls=35920, ndraw=40, logz=-4018.64, remainder_fraction=100.0000%, Lmin=-4000.38, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1345, regioncalls=37800, ndraw=40, logz=-3394.13, remainder_fraction=100.0000%, Lmin=-3362.26, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1395, regioncalls=39800, ndraw=40, logz=-2872.61, remainder_fraction=100.0000%, Lmin=-2864.26, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1410, regioncalls=40400, ndraw=40, logz=-2789.64, remainder_fraction=100.0000%, Lmin=-2774.48, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1448, regioncalls=41920, ndraw=40, logz=-2445.48, remainder_fraction=100.0000%, Lmin=-2411.76, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1497, regioncalls=43880, ndraw=40, logz=-2007.65, remainder_fraction=100.0000%, Lmin=-1991.57, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1519, regioncalls=44760, ndraw=40, logz=-1899.35, remainder_fraction=100.0000%, Lmin=-1886.20, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1543, regioncalls=45720, ndraw=40, logz=-1803.23, remainder_fraction=100.0000%, Lmin=-1779.20, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1596, regioncalls=47840, ndraw=40, logz=-1572.18, remainder_fraction=100.0000%, Lmin=-1555.01, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1632, regioncalls=49280, ndraw=40, logz=-1474.50, remainder_fraction=100.0000%, Lmin=-1458.46, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1644, regioncalls=49760, ndraw=40, logz=-1382.97, remainder_fraction=100.0000%, Lmin=-1374.21, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1691, regioncalls=51680, ndraw=40, logz=-1226.78, remainder_fraction=100.0000%, Lmin=-1216.61, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1748, regioncalls=53960, ndraw=40, logz=-1084.45, remainder_fraction=100.0000%, Lmin=-1075.73, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1798, regioncalls=56040, ndraw=40, logz=-963.03, remainder_fraction=100.0000%, Lmin=-953.68, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1850, regioncalls=58200, ndraw=40, logz=-855.36, remainder_fraction=100.0000%, Lmin=-844.78, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1861, regioncalls=58640, ndraw=40, logz=-824.69, remainder_fraction=100.0000%, Lmin=-814.00, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1902, regioncalls=60360, ndraw=40, logz=-763.19, remainder_fraction=100.0000%, Lmin=-753.01, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1952, regioncalls=62360, ndraw=40, logz=-692.35, remainder_fraction=100.0000%, Lmin=-682.98, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1274, ncalls=2000, regioncalls=64280, ndraw=40, logz=-644.03, remainder_fraction=100.0000%, Lmin=-634.74, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2006, regioncalls=64520, ndraw=40, logz=-638.58, remainder_fraction=100.0000%, Lmin=-629.70, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2052, regioncalls=66400, ndraw=40, logz=-586.31, remainder_fraction=100.0000%, Lmin=-575.50, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2097, regioncalls=68200, ndraw=40, logz=-555.60, remainder_fraction=100.0000%, Lmin=-546.02, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2108, regioncalls=68720, ndraw=40, logz=-550.77, remainder_fraction=100.0000%, Lmin=-539.31, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2161, regioncalls=70920, ndraw=40, logz=-511.11, remainder_fraction=100.0000%, Lmin=-502.53, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2211, regioncalls=72960, ndraw=40, logz=-460.01, remainder_fraction=100.0000%, Lmin=-448.24, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2261, regioncalls=75200, ndraw=40, logz=-415.38, remainder_fraction=100.0000%, Lmin=-405.19, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2315, regioncalls=77520, ndraw=40, logz=-377.25, remainder_fraction=100.0000%, Lmin=-367.12, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2335, regioncalls=78360, ndraw=40, logz=-362.18, remainder_fraction=100.0000%, Lmin=-352.36, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2371, regioncalls=79800, ndraw=40, logz=-333.83, remainder_fraction=100.0000%, Lmin=-324.76, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2424, regioncalls=81960, ndraw=40, logz=-308.69, remainder_fraction=100.0000%, Lmin=-299.15, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2448, regioncalls=83000, ndraw=40, logz=-293.74, remainder_fraction=100.0000%, Lmin=-284.49, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2470, regioncalls=83880, ndraw=40, logz=-283.97, remainder_fraction=100.0000%, Lmin=-274.78, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2519, regioncalls=85880, ndraw=40, logz=-263.38, remainder_fraction=100.0000%, Lmin=-253.48, Lmax=6.94 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2562, regioncalls=87600, ndraw=40, logz=-247.25, remainder_fraction=100.0000%, Lmin=-237.91, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2574, regioncalls=88120, ndraw=40, logz=-241.56, remainder_fraction=100.0000%, Lmin=-231.36, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2625, regioncalls=90320, ndraw=40, logz=-223.90, remainder_fraction=100.0000%, Lmin=-213.84, Lmax=6.98 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2682, regioncalls=92640, ndraw=40, logz=-200.63, remainder_fraction=100.0000%, Lmin=-189.89, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2741, regioncalls=95200, ndraw=40, logz=-181.65, remainder_fraction=100.0000%, Lmin=-172.17, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2794, regioncalls=97360, ndraw=40, logz=-170.22, remainder_fraction=100.0000%, Lmin=-160.77, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2806, regioncalls=97840, ndraw=40, logz=-166.23, remainder_fraction=100.0000%, Lmin=-154.79, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=2841, regioncalls=99320, ndraw=40, logz=-151.55, remainder_fraction=100.0000%, Lmin=-141.60, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=2898, regioncalls=101600, ndraw=40, logz=-140.72, remainder_fraction=100.0000%, Lmin=-130.92, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2925, regioncalls=102720, ndraw=40, logz=-134.73, remainder_fraction=100.0000%, Lmin=-124.27, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2948, regioncalls=103640, ndraw=40, logz=-129.51, remainder_fraction=100.0000%, Lmin=-119.73, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3003, regioncalls=105840, ndraw=40, logz=-118.04, remainder_fraction=100.0000%, Lmin=-108.43, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3054, regioncalls=107960, ndraw=40, logz=-108.75, remainder_fraction=100.0000%, Lmin=-99.45, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3108, regioncalls=110160, ndraw=40, logz=-100.55, remainder_fraction=100.0000%, Lmin=-90.81, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3168, regioncalls=112760, ndraw=40, logz=-94.24, remainder_fraction=100.0000%, Lmin=-84.22, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3216, regioncalls=114680, ndraw=40, logz=-85.72, remainder_fraction=100.0000%, Lmin=-75.78, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3271, regioncalls=116880, ndraw=40, logz=-77.65, remainder_fraction=100.0000%, Lmin=-67.57, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3322, regioncalls=119080, ndraw=40, logz=-69.66, remainder_fraction=100.0000%, Lmin=-59.45, Lmax=7.11 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3370, regioncalls=121040, ndraw=40, logz=-63.49, remainder_fraction=100.0000%, Lmin=-53.27, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3397, regioncalls=122200, ndraw=40, logz=-59.38, remainder_fraction=100.0000%, Lmin=-49.34, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3423, regioncalls=123240, ndraw=40, logz=-56.99, remainder_fraction=100.0000%, Lmin=-47.23, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3476, regioncalls=125440, ndraw=40, logz=-52.43, remainder_fraction=100.0000%, Lmin=-42.72, Lmax=7.14 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3513, regioncalls=127000, ndraw=40, logz=-49.58, remainder_fraction=100.0000%, Lmin=-40.08, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3523, regioncalls=127400, ndraw=40, logz=-48.72, remainder_fraction=100.0000%, Lmin=-38.96, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3569, regioncalls=129360, ndraw=40, logz=-44.19, remainder_fraction=100.0000%, Lmin=-34.02, Lmax=7.33 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3623, regioncalls=131600, ndraw=40, logz=-40.55, remainder_fraction=100.0000%, Lmin=-30.69, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3669, regioncalls=133440, ndraw=40, logz=-37.57, remainder_fraction=100.0000%, Lmin=-28.06, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3717, regioncalls=135360, ndraw=40, logz=-34.64, remainder_fraction=100.0000%, Lmin=-24.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=3765, regioncalls=137440, ndraw=40, logz=-31.18, remainder_fraction=100.0000%, Lmin=-21.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=3819, regioncalls=139840, ndraw=40, logz=-28.69, remainder_fraction=100.0000%, Lmin=-18.82, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3846, regioncalls=141080, ndraw=40, logz=-27.51, remainder_fraction=100.0000%, Lmin=-17.74, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=3868, regioncalls=142000, ndraw=40, logz=-26.35, remainder_fraction=100.0000%, Lmin=-16.46, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=3915, regioncalls=143920, ndraw=40, logz=-24.06, remainder_fraction=100.0000%, Lmin=-14.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=3959, regioncalls=145720, ndraw=40, logz=-22.35, remainder_fraction=100.0000%, Lmin=-12.21, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3970, regioncalls=146160, ndraw=40, logz=-21.84, remainder_fraction=100.0000%, Lmin=-11.95, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4021, regioncalls=148280, ndraw=40, logz=-20.19, remainder_fraction=100.0000%, Lmin=-10.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4075, regioncalls=150520, ndraw=40, logz=-18.57, remainder_fraction=100.0000%, Lmin=-8.69, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4120, regioncalls=152320, ndraw=40, logz=-17.00, remainder_fraction=99.9999%, Lmin=-6.99, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4178, regioncalls=154720, ndraw=40, logz=-15.70, remainder_fraction=99.9998%, Lmin=-5.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4189, regioncalls=155240, ndraw=40, logz=-15.38, remainder_fraction=99.9997%, Lmin=-5.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4223, regioncalls=156600, ndraw=40, logz=-14.41, remainder_fraction=99.9993%, Lmin=-4.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4277, regioncalls=158800, ndraw=40, logz=-13.32, remainder_fraction=99.9978%, Lmin=-3.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4327, regioncalls=160840, ndraw=40, logz=-12.33, remainder_fraction=99.9941%, Lmin=-2.41, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4378, regioncalls=162960, ndraw=40, logz=-11.38, remainder_fraction=99.9840%, Lmin=-1.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4421, regioncalls=164920, ndraw=40, logz=-10.79, remainder_fraction=99.9719%, Lmin=-0.86, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4431, regioncalls=165320, ndraw=40, logz=-10.59, remainder_fraction=99.9658%, Lmin=-0.62, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4485, regioncalls=167480, ndraw=40, logz=-9.87, remainder_fraction=99.9273%, Lmin=-0.01, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4535, regioncalls=169480, ndraw=40, logz=-9.23, remainder_fraction=99.8568%, Lmin=0.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3278, ncalls=4579, regioncalls=171240, ndraw=40, logz=-8.63, remainder_fraction=99.7381%, Lmin=1.42, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4582, regioncalls=171360, ndraw=40, logz=-8.60, remainder_fraction=99.7283%, Lmin=1.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4639, regioncalls=173640, ndraw=40, logz=-8.00, remainder_fraction=99.5053%, Lmin=2.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=4653, regioncalls=174240, ndraw=40, logz=-7.87, remainder_fraction=99.4304%, Lmin=2.15, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=4691, regioncalls=175760, ndraw=40, logz=-7.49, remainder_fraction=99.1633%, Lmin=2.45, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4741, regioncalls=177760, ndraw=40, logz=-7.05, remainder_fraction=98.7439%, Lmin=2.91, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4773, regioncalls=179120, ndraw=40, logz=-6.83, remainder_fraction=98.4381%, Lmin=3.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=4798, regioncalls=180120, ndraw=40, logz=-6.63, remainder_fraction=98.0980%, Lmin=3.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=4851, regioncalls=182240, ndraw=40, logz=-6.25, remainder_fraction=97.3054%, Lmin=3.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=4883, regioncalls=183560, ndraw=40, logz=-5.99, remainder_fraction=96.5291%, Lmin=4.07, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=4896, regioncalls=184080, ndraw=40, logz=-5.90, remainder_fraction=96.2471%, Lmin=4.14, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=4944, regioncalls=186000, ndraw=40, logz=-5.58, remainder_fraction=94.7862%, Lmin=4.39, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=4993, regioncalls=188040, ndraw=40, logz=-5.30, remainder_fraction=93.1211%, Lmin=4.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=5041, regioncalls=189960, ndraw=40, logz=-5.05, remainder_fraction=91.1694%, Lmin=4.93, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=5093, regioncalls=192040, ndraw=40, logz=-4.82, remainder_fraction=89.1330%, Lmin=5.12, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3713, ncalls=5137, regioncalls=193960, ndraw=40, logz=-4.66, remainder_fraction=87.3015%, Lmin=5.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=5148, regioncalls=194400, ndraw=40, logz=-4.62, remainder_fraction=86.8964%, Lmin=5.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=5199, regioncalls=196600, ndraw=40, logz=-4.44, remainder_fraction=84.2154%, Lmin=5.50, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5245, regioncalls=198760, ndraw=40, logz=-4.27, remainder_fraction=81.3149%, Lmin=5.68, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=5295, regioncalls=200800, ndraw=40, logz=-4.12, remainder_fraction=78.0537%, Lmin=5.88, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3870, ncalls=5342, regioncalls=202720, ndraw=40, logz=-4.01, remainder_fraction=75.4451%, Lmin=5.99, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=5354, regioncalls=203200, ndraw=40, logz=-3.98, remainder_fraction=74.5652%, Lmin=6.02, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=5409, regioncalls=205440, ndraw=40, logz=-3.85, remainder_fraction=71.1762%, Lmin=6.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=5460, regioncalls=207560, ndraw=40, logz=-3.73, remainder_fraction=67.5136%, Lmin=6.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=5516, regioncalls=209800, ndraw=40, logz=-3.62, remainder_fraction=63.8559%, Lmin=6.41, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=5566, regioncalls=211800, ndraw=40, logz=-3.53, remainder_fraction=60.1034%, Lmin=6.49, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4064, ncalls=5593, regioncalls=212920, ndraw=40, logz=-3.47, remainder_fraction=57.9275%, Lmin=6.56, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=5610, regioncalls=213680, ndraw=40, logz=-3.44, remainder_fraction=56.4701%, Lmin=6.58, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=5660, regioncalls=215800, ndraw=40, logz=-3.36, remainder_fraction=52.8938%, Lmin=6.66, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=5685, regioncalls=216840, ndraw=40, logz=-3.32, remainder_fraction=51.0927%, Lmin=6.70, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=5710, regioncalls=217840, ndraw=40, logz=-3.29, remainder_fraction=49.4302%, Lmin=6.73, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=5759, regioncalls=219800, ndraw=40, logz=-3.22, remainder_fraction=45.9272%, Lmin=6.79, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=5814, regioncalls=222080, ndraw=40, logz=-3.16, remainder_fraction=42.5649%, Lmin=6.87, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=5863, regioncalls=224320, ndraw=40, logz=-3.11, remainder_fraction=39.3748%, Lmin=6.93, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=5927, regioncalls=226960, ndraw=40, logz=-3.06, remainder_fraction=36.2988%, Lmin=6.96, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=5973, regioncalls=229280, ndraw=40, logz=-3.02, remainder_fraction=33.3961%, Lmin=7.01, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=6026, regioncalls=231640, ndraw=40, logz=-2.98, remainder_fraction=30.7454%, Lmin=7.05, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4410, ncalls=6039, regioncalls=232280, ndraw=40, logz=-2.97, remainder_fraction=30.0950%, Lmin=7.06, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=6073, regioncalls=233640, ndraw=40, logz=-2.94, remainder_fraction=28.2514%, Lmin=7.09, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=6124, regioncalls=235680, ndraw=40, logz=-2.91, remainder_fraction=25.9230%, Lmin=7.11, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=6175, regioncalls=237800, ndraw=40, logz=-2.88, remainder_fraction=23.7342%, Lmin=7.13, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=6226, regioncalls=239920, ndraw=40, logz=-2.85, remainder_fraction=21.6995%, Lmin=7.16, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=6271, regioncalls=241760, ndraw=40, logz=-2.83, remainder_fraction=20.2731%, Lmin=7.18, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=6283, regioncalls=242240, ndraw=40, logz=-2.83, remainder_fraction=19.8052%, Lmin=7.18, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=6331, regioncalls=244160, ndraw=40, logz=-2.81, remainder_fraction=18.0759%, Lmin=7.20, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=6376, regioncalls=246000, ndraw=40, logz=-2.79, remainder_fraction=16.5029%, Lmin=7.22, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=6422, regioncalls=247880, ndraw=40, logz=-2.77, remainder_fraction=15.0420%, Lmin=7.23, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=6472, regioncalls=249880, ndraw=40, logz=-2.75, remainder_fraction=13.6991%, Lmin=7.24, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=6486, regioncalls=250520, ndraw=40, logz=-2.75, remainder_fraction=13.3817%, Lmin=7.24, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=6521, regioncalls=251960, ndraw=40, logz=-2.74, remainder_fraction=12.4589%, Lmin=7.25, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=6579, regioncalls=254280, ndraw=40, logz=-2.73, remainder_fraction=11.3485%, Lmin=7.26, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=6605, regioncalls=255400, ndraw=40, logz=-2.72, remainder_fraction=10.8204%, Lmin=7.27, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=6628, regioncalls=256320, ndraw=40, logz=-2.72, remainder_fraction=10.3187%, Lmin=7.27, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=6675, regioncalls=258200, ndraw=40, logz=-2.71, remainder_fraction=9.3888%, Lmin=7.28, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4955, ncalls=6724, regioncalls=260240, ndraw=40, logz=-2.70, remainder_fraction=8.6349%, Lmin=7.29, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=6729, regioncalls=260440, ndraw=40, logz=-2.70, remainder_fraction=8.5328%, Lmin=7.29, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=6783, regioncalls=262760, ndraw=40, logz=-2.69, remainder_fraction=7.7468%, Lmin=7.30, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=6838, regioncalls=265080, ndraw=40, logz=-2.68, remainder_fraction=7.0364%, Lmin=7.30, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5074, ncalls=6882, regioncalls=266840, ndraw=40, logz=-2.67, remainder_fraction=6.4801%, Lmin=7.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=6891, regioncalls=267200, ndraw=40, logz=-2.67, remainder_fraction=6.3868%, Lmin=7.31, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=6948, regioncalls=269520, ndraw=40, logz=-2.67, remainder_fraction=5.7946%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=6960, regioncalls=270040, ndraw=40, logz=-2.67, remainder_fraction=5.6548%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=6997, regioncalls=271560, ndraw=40, logz=-2.66, remainder_fraction=5.2573%, Lmin=7.32, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=7048, regioncalls=273600, ndraw=40, logz=-2.66, remainder_fraction=4.7704%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=7073, regioncalls=274640, ndraw=40, logz=-2.65, remainder_fraction=4.5435%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=7096, regioncalls=275560, ndraw=40, logz=-2.65, remainder_fraction=4.3270%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=7145, regioncalls=277520, ndraw=40, logz=-2.65, remainder_fraction=3.9223%, Lmin=7.33, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=7199, regioncalls=279720, ndraw=40, logz=-2.64, remainder_fraction=3.5549%, Lmin=7.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=7253, regioncalls=282160, ndraw=40, logz=-2.64, remainder_fraction=3.2218%, Lmin=7.34, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=7305, regioncalls=284320, ndraw=40, logz=-2.64, remainder_fraction=2.9192%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=7352, regioncalls=286240, ndraw=40, logz=-2.63, remainder_fraction=2.6453%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=7409, regioncalls=288520, ndraw=40, logz=-2.63, remainder_fraction=2.3966%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=7422, regioncalls=289080, ndraw=40, logz=-2.63, remainder_fraction=2.3382%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=7462, regioncalls=290720, ndraw=40, logz=-2.63, remainder_fraction=2.1709%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=7518, regioncalls=292960, ndraw=40, logz=-2.63, remainder_fraction=1.9659%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5580, ncalls=7547, regioncalls=294160, ndraw=40, logz=-2.63, remainder_fraction=1.8707%, Lmin=7.35, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=7571, regioncalls=295120, ndraw=40, logz=-2.63, remainder_fraction=1.7802%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=7620, regioncalls=297080, ndraw=40, logz=-2.62, remainder_fraction=1.6120%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=7663, regioncalls=298880, ndraw=40, logz=-2.62, remainder_fraction=1.4964%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=7674, regioncalls=299360, ndraw=40, logz=-2.62, remainder_fraction=1.4598%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=7724, regioncalls=301440, ndraw=40, logz=-2.62, remainder_fraction=1.3217%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=7779, regioncalls=303760, ndraw=40, logz=-2.62, remainder_fraction=1.1966%, Lmin=7.36, Lmax=7.37 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=7830, regioncalls=306040, ndraw=40, logz=-2.62, remainder_fraction=1.0835%, Lmin=7.36, Lmax=7.37 INFO ultranest:integrator.py:2654 Explored until L=7 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 7875 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -2.61 +- 0.1019 INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.10 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.15 bs:0.10 tail:0.01 total:0.10 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:2894 Making corner plot ... DEBUG ultranest:integrator.py:2940 Making run plot ... DEBUG ultranest:integrator.py:2916 Making trace plot ...

Passed

tests/test_run.py::test_run_warmstart_gauss_SLOW

63.51

[gw2] linux -- Python 3.10.6 /usr/bin/python3
[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3[gw2] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
====== Running Gauss problem [1] ===== center: 0 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-5e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=0/528 eff=0.0000% N=400 Z=-4e+13(0.00%) | Like=-4.2e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=40/528 eff=31.2500% N=400 Z=-4e+13(0.00%) | Like=-3.5e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=80/528 eff=62.5000% N=400 Z=-3e+13(0.00%) | Like=-3.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=90/528 eff=70.3125% N=400 Z=-3e+13(0.00%) | Like=-2.9e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=120/635 eff=51.0638% N=400 Z=-2e+13(0.00%) | Like=-2.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=160/635 eff=68.0851% N=400 Z=-2e+13(0.00%) | Like=-2.2e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=180/635 eff=76.5957% N=400 Z=-2e+13(0.00%) | Like=-1.9e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=200/635 eff=85.1064% N=400 Z=-2e+13(0.00%) | Like=-1.6e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=240/722 eff=74.5342% N=400 Z=-1e+13(0.00%) | Like=-1.4e+13..-3.5e+07 [-4.998e+13..-1.283e+13] | it/evals=270/722 eff=83.8509% N=400 Z=-1e+13(0.00%) | Like=-1.3e+13..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=280/789 eff=71.9794% N=400 Z=-1e+13(0.00%) | Like=-1.1e+13..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=320/789 eff=82.2622% N=400 Z=-8e+12(0.00%) | Like=-8.2e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=360/844 eff=81.0811% N=400 Z=-7e+12(0.00%) | Like=-6.9e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=400/888 eff=81.9672% N=400 Z=-6e+12(0.00%) | Like=-5.7e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=440/935 eff=82.2430% N=400 Z=-5e+12(0.00%) | Like=-4.6e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=480/978 eff=83.0450% N=400 Z=-4e+12(0.00%) | Like=-3.7e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=520/1016 eff=84.4156% N=400 Z=-3e+12(0.00%) | Like=-3.4e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=540/1016 eff=87.6623% N=400 Z=-3e+12(0.00%) | Like=-3.1e+12..-3.5e+07 [-1.278e+13..-2.92e+12] | it/evals=560/1041 eff=87.3635% N=400 Z=-3e+12(0.00%) | Like=-2.6e+12..-3.5e+07 [-2.896e+12..-8.337e+11] | it/evals=600/1075 eff=88.8889% N=400 Z=-2e+12(0.00%) | Like=-2.2e+12..-3.5e+07 [-2.896e+12..-8.337e+11] | it/evals=630/1104 eff=89.4886% N=400 Z=-2e+12(0.00%) | Like=-2.1e+12..-3.5e+07 [-2.896e+12..-8.337e+11] | it/evals=640/1132 eff=87.4317% N=400 Z=-2e+12(0.00%) | Like=-1.8e+12..-3.3e+07 [-2.896e+12..-8.337e+11] | it/evals=680/1156 eff=89.9471% N=400 Z=-1e+12(0.00%) | Like=-1.5e+12..-3.3e+07 [-2.896e+12..-8.337e+11] | it/evals=720/1205 eff=89.4410% N=400 Z=-1e+12(0.00%) | Like=-1.2e+12..-3.3e+07 [-2.896e+12..-8.337e+11] | it/evals=760/1241 eff=90.3686% N=400 Z=-1e+12(0.00%) | Like=-1e+12..-3.3e+07 [-2.896e+12..-8.337e+11] | it/evals=800/1284 eff=90.4977% N=400 Z=-1e+12(0.00%) | Like=-9.7e+11..-3.3e+07 [-2.896e+12..-8.337e+11] | it/evals=810/1284 eff=91.6290% N=400 Z=-9e+11(0.00%) | Like=-8.6e+11..-7.6e+06 [-2.896e+12..-8.337e+11] | it/evals=840/1323 eff=91.0076% N=400 Z=-7e+11(0.00%) | Like=-6.7e+11..-7.6e+06 [-8.3e+11..-1.89e+11] | it/evals=880/1367 eff=91.0031% N=400 Z=-6e+11(0.00%) | Like=-5.9e+11..-7.6e+06 [-8.3e+11..-1.89e+11] | it/evals=900/1381 eff=91.7431% N=400 Z=-5e+11(0.00%) | Like=-5.4e+11..-7.6e+06 [-8.3e+11..-1.89e+11] | it/evals=920/1413 eff=90.8193% N=400 Z=-4e+11(0.00%) | Like=-4.2e+11..-3.1e+05 [-8.3e+11..-1.89e+11] | it/evals=960/1455 eff=90.9953% N=400 Z=-3e+11(0.00%) | Like=-3.5e+11..-3.1e+05 [-8.3e+11..-1.89e+11] | it/evals=1000/1487 eff=91.9963% N=400 Z=-3e+11(0.00%) | Like=-3e+11..-3.6e+02 [-8.3e+11..-1.89e+11] | it/evals=1040/1536 eff=91.5493% N=400 Z=-2e+11(0.00%) | Like=-2.5e+11..-3.6e+02 [-8.3e+11..-1.89e+11] | it/evals=1080/1574 eff=91.9932% N=400 Z=-2e+11(0.00%) | Like=-2e+11..-3.6e+02 [-8.3e+11..-1.89e+11] | it/evals=1120/1614 eff=92.2570% N=400 Z=-2e+11(0.00%) | Like=-1.7e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1160/1652 eff=92.6518% N=400 Z=-2e+11(0.00%) | Like=-1.6e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1170/1664 eff=92.5633% N=400 Z=-1e+11(0.00%) | Like=-1.4e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1200/1698 eff=92.4499% N=400 Z=-1e+11(0.00%) | Like=-1.2e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1240/1740 eff=92.5373% N=400 Z=-1e+11(0.00%) | Like=-1.1e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1260/1762 eff=92.5110% N=400 Z=-1e+11(0.00%) | Like=-1e+11..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1280/1776 eff=93.0233% N=400 Z=-8e+10(0.00%) | Like=-8e+10..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1320/1817 eff=93.1546% N=400 Z=-7e+10(0.00%) | Like=-6.6e+10..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1350/1851 eff=93.0393% N=400 Z=-6e+10(0.00%) | Like=-6.3e+10..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1360/1859 eff=93.2145% N=400 Z=-5e+10(0.00%) | Like=-5.1e+10..-3.6e+02 [-1.878e+11..-4.372e+10] | it/evals=1400/1907 eff=92.8998% N=400 Z=-4e+10(0.00%) | Like=-4.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1440/1948 eff=93.0233% N=400 Z=-3e+10(0.00%) | Like=-3.3e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1480/1988 eff=93.1990% N=400 Z=-3e+10(0.00%) | Like=-2.7e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1520/2029 eff=93.3088% N=400 Z=-2e+10(0.00%) | Like=-2.5e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1530/2037 eff=93.4637% N=400 Z=-2e+10(0.00%) | Like=-2.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1560/2075 eff=93.1343% N=400 Z=-2e+10(0.00%) | Like=-1.7e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1600/2116 eff=93.2401% N=400 Z=-1e+10(0.00%) | Like=-1.4e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1640/2153 eff=93.5539% N=400 Z=-1e+10(0.00%) | Like=-1.2e+10..-3.6e+02 [-4.368e+10..-1.077e+10] | it/evals=1680/2195 eff=93.5933% N=400 Z=-1e+10(0.00%) | Like=-1e+10..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1710/2235 eff=93.1880% N=400 Z=-1e+10(0.00%) | Like=-9.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1720/2238 eff=93.5800% N=400 Z=-8e+09(0.00%) | Like=-8.1e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1760/2279 eff=93.6668% N=400 Z=-7e+09(0.00%) | Like=-6.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1800/2319 eff=93.7989% N=400 Z=-6e+09(0.00%) | Like=-5.8e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1840/2362 eff=93.7819% N=400 Z=-5e+09(0.00%) | Like=-4.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1880/2403 eff=93.8592% N=400 Z=-5e+09(0.00%) | Like=-4.6e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1892/2422 eff=93.5707% N=400 Z=-4e+09(0.00%) | Like=-3.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1919/2451 eff=93.5641% N=400 Z=-4e+09(0.00%) | Like=-3.9e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1920/2451 eff=93.6129% N=400 Z=-3e+09(0.00%) | Like=-3.2e+09..-3.6e+02 [-1.076e+10..-3.166e+09] | it/evals=1949/2485 eff=93.4772% N=400 Z=-3e+09(0.00%) | Like=-3.1e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=1960/2490 eff=93.7799% N=400 Z=-3e+09(0.00%) | Like=-2.8e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=1980/2623 eff=89.0688% N=400 Z=-3e+09(0.00%) | Like=-2.5e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2000/2623 eff=89.9685% N=400 Z=-2e+09(0.00%) | Like=-2.2e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2040/2623 eff=91.7679% N=400 Z=-2e+09(0.00%) | Like=-1.9e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2070/2623 eff=93.1174% N=400 Z=-2e+09(0.00%) | Like=-1.8e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2080/2624 eff=93.5252% N=400 Z=-2e+09(0.00%) | Like=-1.6e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2119/2671 eff=93.3069% N=400 Z=-2e+09(0.00%) | Like=-1.5e+09..-3.6e+02 [-3.164e+09..-8.557e+08] | it/evals=2120/2671 eff=93.3509% N=400 Z=-1e+09(0.00%) | Like=-1.3e+09..-3.1e+02 [-3.164e+09..-8.557e+08] | it/evals=2150/2707 eff=93.1946% N=400 Z=-1e+09(0.00%) | Like=-1.2e+09..-3.1e+02 [-3.164e+09..-8.557e+08] | it/evals=2160/2707 eff=93.6281% N=400 Z=-1e+09(0.00%) | Like=-1.2e+09..-3.1e+02 [-3.164e+09..-8.557e+08] | it/evals=2162/2835 eff=88.7885% N=400 Z=-1e+09(0.00%) | Like=-9.8e+08..-3.1e+02 [-3.164e+09..-8.557e+08] | it/evals=2200/2835 eff=90.3491% N=400 Z=-8e+08(0.00%) | Like=-8.1e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2240/2835 eff=91.9918% N=400 Z=-7e+08(0.00%) | Like=-7e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2275/2934 eff=89.7790% N=400 Z=-7e+08(0.00%) | Like=-6.9e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2280/2934 eff=89.9763% N=400 Z=-6e+08(0.00%) | Like=-5.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2320/2934 eff=91.5549% N=400 Z=-5e+08(0.00%) | Like=-5.2e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2340/2934 eff=92.3441% N=400 Z=-5e+08(0.00%) | Like=-4.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2360/2934 eff=93.1334% N=400 Z=-4e+08(0.00%) | Like=-3.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2400/3050 eff=90.5660% N=400 Z=-3e+08(0.00%) | Like=-3.1e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2430/3050 eff=91.6981% N=400 Z=-3e+08(0.00%) | Like=-3e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2440/3050 eff=92.0755% N=400 Z=-3e+08(0.00%) | Like=-2.6e+08..-3.1e+02 [-8.538e+08..-2.413e+08] | it/evals=2480/3068 eff=92.9535% N=400 Z=-2e+08(0.00%) | Like=-2.3e+08..-3.1e+02 [-2.41e+08..-5.562e+07] | it/evals=2520/3121 eff=92.6130% N=400 Z=-2e+08(0.00%) | Like=-1.9e+08..-3.1e+02 [-2.41e+08..-5.562e+07] | it/evals=2560/3154 eff=92.9557% N=400 Z=-2e+08(0.00%) | Like=-1.5e+08..-3.1e+02 [-2.41e+08..-5.562e+07] | it/evals=2600/3199 eff=92.8903% N=400 Z=-1e+08(0.00%) | Like=-1.4e+08..-3.1e+02 [-2.41e+08..-5.562e+07] | it/evals=2610/3208 eff=92.9487% N=400 Z=-1e+08(0.00%) | Like=-1.2e+08..-3.1e+02 [-2.41e+08..-5.562e+07] | it/evals=2640/3327 eff=90.1947% N=400 Z=-96060458.7(0.00%) | Like=-96033237.17..-310.03 [-2.41e+08..-5.562e+07] | it/evals=2680/3327 eff=91.5613% N=400 Z=-83875005.8(0.00%) | Like=-83141993.83..-310.03 [-2.41e+08..-5.562e+07] | it/evals=2700/3327 eff=92.2446% N=400 Z=-76588171.4(0.00%) | Like=-76540182.09..-310.03 [-2.41e+08..-5.562e+07] | it/evals=2720/3327 eff=92.9279% N=400 Z=-59897794.8(0.00%) | Like=-59677779.22..-310.03 [-2.41e+08..-5.562e+07] | it/evals=2760/3444 eff=90.6702% N=400 Z=-49760498.3(0.00%) | Like=-49599851.63..-310.03 [-55543211.0406..-12665864.2124] | it/evals=2800/3444 eff=91.9842% N=400 Z=-38489542.9(0.00%) | Like=-38441431.28..-310.03 [-55543211.0406..-12665864.2124] | it/evals=2840/3535 eff=90.5901% N=400 Z=-32469743.9(0.00%) | Like=-32313765.59..-135.66 [-55543211.0406..-12665864.2124] | it/evals=2880/3535 eff=91.8660% N=400 Z=-26172602.5(0.00%) | Like=-25938804.52..-135.66 [-55543211.0406..-12665864.2124] | it/evals=2920/3658 eff=89.6255% N=400 Z=-19538332.5(0.00%) | Like=-19450366.38..-135.66 [-55543211.0406..-12665864.2124] | it/evals=2960/3658 eff=90.8533% N=400 Z=-18348100.4(0.00%) | Like=-18344493.62..-135.66 [-55543211.0406..-12665864.2124] | it/evals=2970/3658 eff=91.1602% N=400 Z=-15340466.4(0.00%) | Like=-14985637.97..-135.66 [-55543211.0406..-12665864.2124] | it/evals=3000/3677 eff=91.5471% N=400 Z=-12719911.3(0.00%) | Like=-12647299.74..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3040/3718 eff=91.6215% N=400 Z=-11831095.0(0.00%) | Like=-11787664.15..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3060/3736 eff=91.7266% N=400 Z=-11141633.0(0.00%) | Like=-11121830.90..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3080/3864 eff=88.9145% N=400 Z=-8877250.8(0.00%) | Like=-8874484.68..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3120/3864 eff=90.0693% N=400 Z=-7615450.3(0.00%) | Like=-7615312.38..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3150/3864 eff=90.9353% N=400 Z=-7380434.6(0.00%) | Like=-7356864.48..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3160/3864 eff=91.2240% N=400 Z=-7157825.5(0.00%) | Like=-7156384.89..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3168/3992 eff=88.1960% N=400 Z=-6113566.7(0.00%) | Like=-6050922.96..-135.66 [-12647299.7429..-3318556.2028] | it/evals=3200/3992 eff=89.0869% N=400 Z=-4573067.9(0.00%) | Like=-4566133.63..-3.90 [-12647299.7429..-3318556.2028] | it/evals=3240/3992 eff=90.2004% N=400 Z=-3863486.2(0.00%) | Like=-3829448.55..-3.90 [-12647299.7429..-3318556.2028] | it/evals=3275/4100 eff=88.5135% N=400 Z=-3808107.7(0.00%) | Like=-3795971.02..-3.90 [-12647299.7429..-3318556.2028] | it/evals=3280/4100 eff=88.6486% N=400 Z=-3110640.6(0.00%) | Like=-3107239.98..-3.90 [-3317418.8544..-855043.6863] | it/evals=3320/4100 eff=89.7297% N=400 Z=-2675252.3(0.00%) | Like=-2668849.17..-3.90 [-3317418.8544..-855043.6863] | it/evals=3360/4100 eff=90.8108% N=400 Z=-2564767.2(0.00%) | Like=-2551402.90..-3.90 [-3317418.8544..-855043.6863] | it/evals=3370/4195 eff=88.8011% N=400 Z=-2198473.6(0.00%) | Like=-2196576.76..-3.90 [-3317418.8544..-855043.6863] | it/evals=3400/4195 eff=89.5916% N=400 Z=-2012812.8(0.00%) | Like=-2009485.22..-3.90 [-3317418.8544..-855043.6863] | it/evals=3420/4195 eff=90.1186% N=400 Z=-1847415.7(0.00%) | Like=-1829858.31..-3.90 [-3317418.8544..-855043.6863] | it/evals=3440/4195 eff=90.6456% N=400 Z=-1451906.3(0.00%) | Like=-1442627.27..-0.09 [-3317418.8544..-855043.6863] | it/evals=3480/4227 eff=90.9328% N=400 Z=-1216639.3(0.00%) | Like=-1212596.34..-0.09 [-3317418.8544..-855043.6863] | it/evals=3510/4262 eff=90.8856% N=400 Z=-1180207.6(0.00%) | Like=-1175032.69..-0.09 [-3317418.8544..-855043.6863] | it/evals=3520/4385 eff=88.3312% N=400 Z=-946994.7(0.00%) | Like=-940999.45..-0.09 [-3317418.8544..-855043.6863] | it/evals=3560/4385 eff=89.3350% N=400 Z=-778747.5(0.00%) | Like=-771170.46..-0.09 [-851045.7409..-213305.0473] | it/evals=3600/4385 eff=90.3388% N=400 Z=-635147.0(0.00%) | Like=-634663.92..-0.09 [-851045.7409..-213305.0473] | it/evals=3636/4475 eff=89.2270% N=400 Z=-612791.6(0.00%) | Like=-608833.23..-0.09 [-851045.7409..-213305.0473] | it/evals=3640/4475 eff=89.3252% N=400 Z=-508846.5(0.00%) | Like=-506165.20..-0.09 [-851045.7409..-213305.0473] | it/evals=3680/4475 eff=90.3067% N=400 Z=-490388.8(0.00%) | Like=-485575.72..-0.09 [-851045.7409..-213305.0473] | it/evals=3690/4475 eff=90.5521% N=400 Z=-429946.8(0.00%) | Like=-428595.78..-0.09 [-851045.7409..-213305.0473] | it/evals=3720/4500 eff=90.7317% N=400 Z=-346384.6(0.00%) | Like=-346198.97..-0.09 [-851045.7409..-213305.0473] | it/evals=3760/4542 eff=90.7774% N=400 Z=-313687.0(0.00%) | Like=-313029.66..-0.09 [-851045.7409..-213305.0473] | it/evals=3780/4561 eff=90.8435% N=400 Z=-282186.4(0.00%) | Like=-281568.56..-0.09 [-851045.7409..-213305.0473] | it/evals=3800/4689 eff=88.5987% N=400 Z=-227408.1(0.00%) | Like=-227371.78..-0.09 [-851045.7409..-213305.0473] | it/evals=3840/4689 eff=89.5314% N=400 Z=-194507.7(0.00%) | Like=-194017.43..-0.09 [-213262.9865..-46727.2354] | it/evals=3880/4689 eff=90.4640% N=400 Z=-160420.8(0.00%) | Like=-159571.94..-0.09 [-213262.9865..-46727.2354] | it/evals=3920/4790 eff=89.2938% N=400 Z=-125606.0(0.00%) | Like=-124767.18..-0.09 [-213262.9865..-46727.2354] | it/evals=3960/4790 eff=90.2050% N=400 Z=-111728.7(0.00%) | Like=-109892.50..-0.09 [-213262.9865..-46727.2354] | it/evals=3983/4914 eff=88.2366% N=400 Z=-99628.7(0.00%) | Like=-98796.75..-0.09 [-213262.9865..-46727.2354] | it/evals=4000/4914 eff=88.6132% N=400 Z=-79563.3(0.00%) | Like=-79495.58..-0.09 [-213262.9865..-46727.2354] | it/evals=4040/4914 eff=89.4993% N=400 Z=-77992.0(0.00%) | Like=-77957.02..-0.09 [-213262.9865..-46727.2354] | it/evals=4050/4914 eff=89.7209% N=400 Z=-67526.6(0.00%) | Like=-67417.47..-0.09 [-213262.9865..-46727.2354] | it/evals=4080/4925 eff=90.1657% N=400 Z=-55235.3(0.00%) | Like=-55056.05..-0.09 [-213262.9865..-46727.2354] | it/evals=4120/4955 eff=90.4501% N=400 Z=-48939.9(0.00%) | Like=-48543.38..-0.09 [-213262.9865..-46727.2354] | it/evals=4140/4979 eff=90.4128% N=400 Z=-43455.7(0.00%) | Like=-43364.58..-0.09 [-46275.4307..-11188.2679] | it/evals=4160/5102 eff=88.4730% N=400 Z=-36008.2(0.00%) | Like=-35757.46..-0.09 [-46275.4307..-11188.2679] | it/evals=4200/5102 eff=89.3237% N=400 Z=-30396.8(0.00%) | Like=-30282.97..-0.09 [-46275.4307..-11188.2679] | it/evals=4230/5102 eff=89.9617% N=400 Z=-29056.5(0.00%) | Like=-28855.17..-0.09 [-46275.4307..-11188.2679] | it/evals=4240/5102 eff=90.1744% N=400 Z=-24102.7(0.00%) | Like=-23927.05..-0.09 [-46275.4307..-11188.2679] | it/evals=4280/5138 eff=90.3335% N=400 Z=-19450.2(0.00%) | Like=-19344.73..-0.09 [-46275.4307..-11188.2679] | it/evals=4320/5174 eff=90.4902% N=400 Z=-16094.6(0.00%) | Like=-15916.99..-0.07 [-46275.4307..-11188.2679] | it/evals=4360/5219 eff=90.4752% N=400 Z=-12625.4(0.00%) | Like=-12576.55..-0.00 [-46275.4307..-11188.2679] | it/evals=4400/5261 eff=90.5164% N=400 Z=-10993.4(0.00%) | Like=-10899.62..-0.00 [-11181.5477..-3229.8137] | it/evals=4440/5301 eff=90.5938% N=400 Z=-8992.4(0.00%) | Like=-8974.20..-0.00 [-11181.5477..-3229.8137] | it/evals=4480/5337 eff=90.7434% N=400 Z=-8243.3(0.00%) | Like=-8189.63..-0.00 [-11181.5477..-3229.8137] | it/evals=4500/5485 eff=88.4956% N=400 Z=-7716.0(0.00%) | Like=-7682.92..-0.00 [-11181.5477..-3229.8137] | it/evals=4520/5485 eff=88.8889% N=400 Z=-6371.8(0.00%) | Like=-6328.55..-0.00 [-11181.5477..-3229.8137] | it/evals=4560/5485 eff=89.6755% N=400 Z=-5676.5(0.00%) | Like=-5634.43..-0.00 [-11181.5477..-3229.8137] | it/evals=4590/5485 eff=90.2655% N=400 Z=-5463.7(0.00%) | Like=-5444.29..-0.00 [-11181.5477..-3229.8137] | it/evals=4600/5485 eff=90.4621% N=400 Z=-4563.9(0.00%) | Like=-4536.39..-0.00 [-11181.5477..-3229.8137] | it/evals=4640/5524 eff=90.5543% N=400 Z=-3732.2(0.00%) | Like=-3678.91..-0.00 [-11181.5477..-3229.8137] | it/evals=4680/5568 eff=90.5573% N=400 Z=-2979.6(0.00%) | Like=-2953.36..-0.00 [-3184.0781..-809.5316] | it/evals=4720/5685 eff=89.3094% N=400 Z=-2401.3(0.00%) | Like=-2380.68..-0.00 [-3184.0781..-809.5316] | it/evals=4760/5685 eff=90.0662% N=400 Z=-2354.8(0.00%) | Like=-2328.48..-0.00 [-3184.0781..-809.5316] | it/evals=4770/5685 eff=90.2554% N=400 Z=-2084.0(0.00%) | Like=-2062.99..-0.00 [-3184.0781..-809.5316] | it/evals=4800/5813 eff=88.6754% N=400 Z=-1671.7(0.00%) | Like=-1641.27..-0.00 [-3184.0781..-809.5316] | it/evals=4840/5813 eff=89.4144% N=400 Z=-1525.2(0.00%) | Like=-1482.31..-0.00 [-3184.0781..-809.5316] | it/evals=4860/5813 eff=89.7839% N=400 Z=-1305.5(0.00%) | Like=-1279.17..-0.00 [-3184.0781..-809.5316] | it/evals=4880/5813 eff=90.1533% N=400 Z=-1056.9(0.00%) | Like=-1031.76..-0.00 [-3184.0781..-809.5316] | it/evals=4920/5843 eff=90.3913% N=400 Z=-900.7(0.00%) | Like=-869.80..-0.00 [-3184.0781..-809.5316] | it/evals=4950/5872 eff=90.4605% N=400 Z=-863.9(0.00%) | Like=-843.51..-0.00 [-3184.0781..-809.5316] | it/evals=4960/5995 eff=88.6506% N=400 Z=-739.9(0.00%) | Like=-720.07..-0.00 [-808.6368..-200.7839] | it/evals=5000/5995 eff=89.3655% N=400 Z=-590.5(0.00%) | Like=-571.07..-0.00 [-808.6368..-200.7839] | it/evals=5040/5995 eff=90.0804% N=400 Z=-461.2(0.00%) | Like=-440.89..-0.00 [-808.6368..-200.7839] | it/evals=5080/6087 eff=89.3265% N=400 Z=-379.9(0.00%) | Like=-357.65..-0.00 [-808.6368..-200.7839] | it/evals=5120/6087 eff=90.0299% N=400 Z=-362.9(0.00%) | Like=-337.70..-0.00 [-808.6368..-200.7839] | it/evals=5130/6087 eff=90.2057% N=400 Z=-313.5(0.00%) | Like=-293.65..-0.00 [-808.6368..-200.7839] | it/evals=5160/6215 eff=88.7360% N=400 Z=-262.5(0.00%) | Like=-244.16..-0.00 [-808.6368..-200.7839] | it/evals=5200/6215 eff=89.4239% N=400 Z=-235.8(0.00%) | Like=-218.07..-0.00 [-808.6368..-200.7839] | it/evals=5220/6215 eff=89.7678% N=400 Z=-218.7(0.00%) | Like=-199.82..-0.00 [-200.5435..-50.2258] | it/evals=5240/6215 eff=90.1118% N=400 Z=-186.1(0.00%) | Like=-166.86..-0.00 [-200.5435..-50.2258] | it/evals=5280/6254 eff=90.1947% N=400 Z=-163.8(0.00%) | Like=-144.80..-0.00 [-200.5435..-50.2258] | it/evals=5310/6410 eff=88.3527% N=400 Z=-157.3(0.00%) | Like=-137.86..-0.00 [-200.5435..-50.2258] | it/evals=5320/6410 eff=88.5191% N=400 Z=-130.3(0.00%) | Like=-110.84..-0.00 [-200.5435..-50.2258] | it/evals=5360/6410 eff=89.1847% N=400 Z=-108.3(0.00%) | Like=-88.95..-0.00 [-200.5435..-50.2258] | it/evals=5400/6410 eff=89.8502% N=400 Z=-91.7(0.00%) | Like=-73.04..-0.00 [-200.5435..-50.2258] | it/evals=5440/6528 eff=88.7728% N=400 Z=-78.2(0.00%) | Like=-58.61..-0.00 [-200.5435..-50.2258] | it/evals=5480/6528 eff=89.4256% N=400 Z=-74.9(0.00%) | Like=-56.74..-0.00 [-200.5435..-50.2258] | it/evals=5490/6528 eff=89.5888% N=400 Z=-67.8(0.00%) | Like=-48.78..-0.00 [-50.0590..-13.4702] | it/evals=5520/6528 eff=90.0783% N=400 Z=-59.7(0.00%) | Like=-41.06..-0.00 [-50.0590..-13.4702] | it/evals=5560/6640 eff=89.1026% N=400 Z=-56.2(0.00%) | Like=-38.29..-0.00 [-50.0590..-13.4702] | it/evals=5580/6640 eff=89.4231% N=400 Z=-53.2(0.00%) | Like=-34.68..-0.00 [-50.0590..-13.4702] | it/evals=5600/6640 eff=89.7436% N=400 Z=-47.0(0.00%) | Like=-28.44..-0.00 [-50.0590..-13.4702] | it/evals=5640/6755 eff=88.7490% N=400 Z=-41.5(0.00%) | Like=-23.57..-0.00 [-50.0590..-13.4702] | it/evals=5680/6755 eff=89.3784% N=400 Z=-37.9(0.00%) | Like=-20.01..-0.00 [-50.0590..-13.4702] | it/evals=5720/6852 eff=88.6547% N=400 Z=-34.1(0.00%) | Like=-15.85..-0.00 [-50.0590..-13.4702] | it/evals=5760/6852 eff=89.2746% N=400 Z=-30.9(0.00%) | Like=-13.28..-0.00 [-13.4688..-3.1923] | it/evals=5800/6977 eff=88.1861% N=400 Z=-28.8(0.00%) | Like=-11.09..-0.00 [-13.4688..-3.1923] | it/evals=5840/6977 eff=88.7943% N=400 Z=-26.9(0.00%) | Like=-9.15..-0.00 [-13.4688..-3.1923] | it/evals=5880/6977 eff=89.4025% N=400 Z=-24.9(0.01%) | Like=-7.23..-0.00 [-13.4688..-3.1923] | it/evals=5920/7073 eff=88.7157% N=400 Z=-24.2(0.03%) | Like=-6.80..-0.00 [-13.4688..-3.1923] | it/evals=5940/7073 eff=89.0154% N=400 Z=-23.5(0.05%) | Like=-6.03..-0.00 [-13.4688..-3.1923] | it/evals=5960/7073 eff=89.3152% N=400 Z=-22.4(0.15%) | Like=-4.86..-0.00 [-13.4688..-3.1923] | it/evals=6000/7184 eff=88.4434% N=400 Z=-21.5(0.36%) | Like=-4.13..-0.00 [-13.4688..-3.1923] | it/evals=6030/7184 eff=88.8856% N=400 Z=-21.3(0.46%) | Like=-3.90..-0.00 [-13.4688..-3.1923] | it/evals=6040/7184 eff=89.0330% N=400 Z=-20.4(1.09%) | Like=-3.17..-0.00 [-3.1816..-2.1117] | it/evals=6080/7299 eff=88.1287% N=400 Z=-19.7(2.17%) | Like=-2.60..-0.00 [-3.1816..-2.1117] | it/evals=6120/7299 eff=88.7085% N=400 Z=-19.2(3.76%) | Like=-2.15..-0.00 [-3.1816..-2.1117] | it/evals=6160/7299 eff=89.2883% N=400 Z=-18.7(6.01%) | Like=-1.75..-0.00 [-1.7610..-1.7500] | it/evals=6200/7380 eff=88.8252% N=400 Z=-18.6(6.67%) | Like=-1.68..-0.00 [-1.6793..-1.6740]*| it/evals=6210/7380 eff=88.9685% N=400 Z=-18.3(8.94%) | Like=-1.44..-0.00 [-1.4423..-1.4353]*| it/evals=6240/7380 eff=89.3983% N=400 Z=-18.0(12.51%) | Like=-1.10..-0.00 [-1.0978..-1.0911]*| it/evals=6280/7422 eff=89.4332% N=400 Z=-17.8(14.60%) | Like=-0.98..-0.00 [-0.9788..-0.9589] | it/evals=6300/7556 eff=88.0380% N=400 Z=-17.7(16.90%) | Like=-0.88..-0.00 [-0.8820..-0.8818]*| it/evals=6320/7556 eff=88.3175% N=400 Z=-17.4(21.49%) | Like=-0.73..-0.00 [-0.7336..-0.7293]*| it/evals=6360/7556 eff=88.8765% N=400 Z=-17.3(25.14%) | Like=-0.62..-0.00 [-0.6150..-0.6139]*| it/evals=6390/7556 eff=89.2957% N=400 Z=-17.2(26.34%) | Like=-0.60..-0.00 [-0.6036..-0.5966]*| it/evals=6400/7556 eff=89.4354% N=400 Z=-17.1(31.18%) | Like=-0.52..-0.00 [-0.5169..-0.5159]*| it/evals=6440/7684 eff=88.4130% N=400 Z=-16.9(35.88%) | Like=-0.41..-0.00 [-0.4129..-0.4080]*| it/evals=6480/7684 eff=88.9621% N=400 Z=-16.8(40.68%) | Like=-0.35..-0.00 [-0.3522..-0.3507]*| it/evals=6520/7789 eff=88.2393% N=400 Z=-16.7(45.25%) | Like=-0.28..-0.00 [-0.2764..-0.2754]*| it/evals=6560/7789 eff=88.7806% N=400 Z=-16.7(46.40%) | Like=-0.27..-0.00 [-0.2675..-0.2657]*| it/evals=6570/7789 eff=88.9160% N=400 Z=-16.6(49.71%) | Like=-0.23..-0.00 [-0.2340..-0.2338]*| it/evals=6600/7789 eff=89.3220% N=400 Z=-16.5(53.87%) | Like=-0.20..-0.00 [-0.1973..-0.1961]*| it/evals=6640/7899 eff=88.5451% N=400 Z=-16.5(55.88%) | Like=-0.18..-0.00 [-0.1796..-0.1778]*| it/evals=6660/7899 eff=88.8118% N=400 Z=-16.4(57.81%) | Like=-0.16..-0.00 [-0.1601..-0.1601]*| it/evals=6680/7899 eff=89.0785% N=400 Z=-16.4(61.48%) | Like=-0.13..-0.00 [-0.1326..-0.1321]*| it/evals=6720/7918 eff=89.3855% N=400 Z=-16.3(64.05%) | Like=-0.12..-0.00 [-0.1170..-0.1168]*| it/evals=6750/7951 eff=89.3921% N=400 Z=-16.3(64.86%) | Like=-0.11..-0.00 [-0.1117..-0.1115]*| it/evals=6760/7963 eff=89.3825% N=400 Z=-16.3(67.99%) | Like=-0.09..-0.00 [-0.0907..-0.0904]*| it/evals=6800/7999 eff=89.4855% N=400 Z=-16.2(70.89%) | Like=-0.08..-0.00 [-0.0757..-0.0752]*| it/evals=6840/8045 eff=89.4702% N=400 Z=-16.2(73.55%) | Like=-0.06..-0.00 [-0.0598..-0.0597]*| it/evals=6880/8085 eff=89.5250% N=400 Z=-16.2(75.99%) | Like=-0.05..-0.00 [-0.0483..-0.0483]*| it/evals=6920/8131 eff=89.5098% N=400 Z=-16.2(76.56%) | Like=-0.05..-0.00 [-0.0454..-0.0452]*| it/evals=6930/8138 eff=89.5580% N=400 Z=-16.1(78.21%) | Like=-0.04..-0.00 [-0.0389..-0.0389]*| it/evals=6960/8266 eff=88.4821% N=400 Z=-16.1(80.24%) | Like=-0.03..-0.00 [-0.0330..-0.0330]*| it/evals=7000/8266 eff=88.9906% N=400 Z=-16.1(81.18%) | Like=-0.03..-0.00 [-0.0297..-0.0297]*| it/evals=7020/8266 eff=89.2449% N=400 Z=-16.1(82.08%) | Like=-0.03..-0.00 [-0.0270..-0.0269]*| it/evals=7040/8266 eff=89.4991% N=400 Z=-16.1(83.76%) | Like=-0.02..-0.00 [-0.0229..-0.0229]*| it/evals=7080/8313 eff=89.4730% N=400 Z=-16.1(84.92%) | Like=-0.02..-0.00 [-0.0205..-0.0204]*| it/evals=7110/8337 eff=89.5804% N=400 Z=-16.0(85.28%) | Like=-0.02..-0.00 [-0.0197..-0.0196]*| it/evals=7120/8465 eff=88.2827% N=400 Z=-16.0(86.67%) | Like=-0.02..-0.00 [-0.0157..-0.0157]*| it/evals=7160/8465 eff=88.7787% N=400 Z=-16.0(87.93%) | Like=-0.01..-0.00 [-0.0133..-0.0132]*| it/evals=7200/8465 eff=89.2746% N=400 Z=-16.0(89.07%) | Like=-0.01..-0.00 [-0.0110..-0.0110]*| it/evals=7240/8580 eff=88.5086% N=400 Z=-16.0(90.10%) | Like=-0.01..-0.00 [-0.0093..-0.0093]*| it/evals=7280/8580 eff=88.9976% N=400 Z=-16.0(90.34%) | Like=-0.01..-0.00 [-0.0088..-0.0088]*| it/evals=7290/8580 eff=89.1198% N=400 Z=-16.0(91.04%) | Like=-0.01..-0.00 [-0.0077..-0.0077]*| it/evals=7320/8580 eff=89.4866% N=400 Z=-16.0(91.89%) | Like=-0.01..-0.00 [-0.0060..-0.0060]*| it/evals=7360/8703 eff=88.6427% N=400 Z=-16.0(92.66%) | Like=-0.00..-0.00 [-0.0048..-0.0047]*| it/evals=7400/8703 eff=89.1244% N=400 Z=-16.0(93.35%) | Like=-0.00..-0.00 [-0.0037..-0.0037]*| it/evals=7440/8703 eff=89.6062% N=400 Z=-16.0(93.83%) | Like=-0.00..-0.00 [-0.0031..-0.0031]*| it/evals=7470/8786 eff=89.0770% N=400 Z=-16.0(93.98%) | Like=-0.00..-0.00 [-0.0030..-0.0030]*| it/evals=7480/8786 eff=89.1963% N=400 Z=-15.9(94.56%) | Like=-0.00..-0.00 [-0.0024..-0.0024]*| it/evals=7520/8802 eff=89.5025% N=400 Z=-15.9(95.07%) | Like=-0.00..-0.00 [-0.0020..-0.0020]*| it/evals=7560/8853 eff=89.4357% N=400 Z=-15.9(95.54%) | Like=-0.00..-0.00 [-0.0016..-0.0016]*| it/evals=7600/8981 eff=88.5678% N=400 Z=-15.9(95.97%) | Like=-0.00..-0.00 [-0.0014..-0.0014]*| it/evals=7640/8981 eff=89.0339% N=400 Z=-15.9(96.06%) | Like=-0.00..-0.00 [-0.0013..-0.0013]*| it/evals=7650/8981 eff=89.1504% N=400 Z=-15.9(96.35%) | Like=-0.00..-0.00 [-0.0012..-0.0012]*| it/evals=7680/8981 eff=89.5001% N=400 [ultranest] Explored until L=-2e-07 [ultranest] Likelihood function evaluations: 9102 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -15.87 +- 0.1519 [ultranest] Effective samples strategy satisfied (ESS = 1239.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.5) [ultranest] logZ error budget: single: 0.20 bs:0.15 tail:0.03 total:0.16 required:<0.50 [ultranest] done iterating. logZ = -15.890 +- 0.249 single instance: logZ = -15.890 +- 0.196 bootstrapped : logZ = -15.868 +- 0.246 tail : logZ = +- 0.033 insert order U test : converged: True correlation: inf iterations a : -0.00381│ ▁▁▁▁▁▁▁▁▂▁▃▅▅▆▆▇▇▇▇▇▇▆▅▃▂▃▂▁▁▁▁▁▁▁▁▁▁ │0.00422 -0.00002 +- 0.00099 expected posterior: 0 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [-2.2975248259440545e-05] [0.0009885788563336665] [[1.14374817e-04] [4.02024891e-04] [9.97322850e-01] ... [5.00000000e-01] [5.00000000e-01] [5.00000000e-01]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 8.32523583e-05 8.32523694e-05 8.32523752e-05] ====== Running Gauss problem [2] ===== center: 0 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-2.6e+13..-14 [-2.637e+13..-16.51] | it/evals=0/528 eff=0.0000% N=400 Z=-1027058.7(0.00%) | Like=-367803.47..-13.70 [-2.637e+13..-16.51] | it/evals=40/528 eff=31.2500% N=400 Z=-60.4(0.00%) | Like=-50.38..-13.70 [-2.637e+13..-16.51] | it/evals=80/528 eff=62.5000% N=400 Z=-29.3(0.00%) | Like=-21.93..-13.70 [-2.637e+13..-16.51] | it/evals=90/528 eff=70.3125% N=400 Z=-22.5(0.18%) | Like=-19.03..-13.70 [-2.637e+13..-16.51] | it/evals=120/631 eff=51.9481% N=400 Z=-20.7(1.07%) | Like=-17.74..-13.70 [-2.637e+13..-16.51] | it/evals=160/631 eff=69.2641% N=400 Z=-20.1(1.99%) | Like=-17.26..-13.70 [-2.637e+13..-16.51] | it/evals=180/631 eff=77.9221% N=400 Z=-19.6(3.12%) | Like=-17.08..-13.70 [-2.637e+13..-16.51] | it/evals=200/719 eff=62.6959% N=400 Z=-18.9(6.18%) | Like=-16.60..-13.70 [-2.637e+13..-16.51] | it/evals=240/719 eff=75.2351% N=400 Z=-18.5(9.73%) | Like=-16.43..-13.70 [-16.4311..-16.4298]*| it/evals=280/796 eff=70.7071% N=400 Z=-18.1(13.67%) | Like=-16.28..-13.70 [-16.2781..-16.2756]*| it/evals=320/867 eff=68.5225% N=400 Z=-17.9(17.63%) | Like=-16.18..-13.70 [-16.1754..-16.1748]*| it/evals=360/867 eff=77.0878% N=400 Z=-17.7(21.60%) | Like=-16.05..-13.70 [-16.0474..-16.0417]*| it/evals=400/936 eff=74.6269% N=400 Z=-17.5(25.56%) | Like=-15.95..-13.70 [-15.9463..-15.9461]*| it/evals=440/992 eff=74.3243% N=400 Z=-17.5(26.64%) | Like=-15.93..-13.70 [-15.9250..-15.9249]*| it/evals=450/992 eff=76.0135% N=400 Z=-17.4(29.58%) | Like=-15.86..-13.70 [-15.8649..-15.8597]*| it/evals=480/1054 eff=73.3945% N=400 Z=-17.2(33.49%) | Like=-15.76..-13.62 [-15.7628..-15.7623]*| it/evals=520/1144 eff=69.8925% N=400 Z=-17.2(35.58%) | Like=-15.73..-13.62 [-15.7282..-15.7241]*| it/evals=540/1144 eff=72.5806% N=400 Z=-17.1(37.48%) | Like=-15.69..-13.62 [-15.6919..-15.6890]*| it/evals=560/1180 eff=71.7949% N=400 Z=-17.0(41.12%) | Like=-15.63..-13.49 [-15.6301..-15.6282]*| it/evals=600/1222 eff=72.9927% N=400 Z=-17.0(43.89%) | Like=-15.58..-13.49 [-15.5796..-15.5769]*| it/evals=630/1266 eff=72.7483% N=400 Z=-16.9(44.89%) | Like=-15.56..-13.49 [-15.5584..-15.5526]*| it/evals=640/1266 eff=73.9030% N=400 Z=-16.9(48.56%) | Like=-15.48..-13.49 [-15.4782..-15.4778]*| it/evals=680/1325 eff=73.5135% N=400 Z=-16.8(52.03%) | Like=-15.43..-13.49 [-15.4259..-15.4258]*| it/evals=720/1399 eff=72.0721% N=400 Z=-16.7(55.28%) | Like=-15.38..-13.49 [-15.3840..-15.3834]*| it/evals=760/1418 eff=74.6562% N=400 Z=-16.7(58.33%) | Like=-15.34..-13.49 [-15.3392..-15.3376]*| it/evals=800/1489 eff=73.4619% N=400 Z=-16.7(58.94%) | Like=-15.33..-13.49 [-15.3305..-15.3287]*| it/evals=810/1489 eff=74.3802% N=400 Z=-16.6(61.15%) | Like=-15.30..-13.49 [-15.2987..-15.2985]*| it/evals=840/1522 eff=74.8663% N=400 Z=-16.6(63.99%) | Like=-15.26..-13.49 [-15.2561..-15.2551]*| it/evals=880/1580 eff=74.5763% N=400 Z=-16.6(65.11%) | Like=-15.24..-13.21 [-15.2369..-15.2337]*| it/evals=900/1617 eff=73.9523% N=400 Z=-16.5(66.43%) | Like=-15.22..-13.21 [-15.2153..-15.2151]*| it/evals=920/1636 eff=74.4337% N=400 Z=-16.5(69.03%) | Like=-15.18..-13.21 [-15.1819..-15.1808]*| it/evals=960/1692 eff=74.3034% N=400 Z=-16.5(70.66%) | Like=-15.16..-13.21 [-15.1630..-15.1630]*| it/evals=990/1740 eff=73.8806% N=400 Z=-16.5(71.06%) | Like=-15.16..-13.21 [-15.1554..-15.1554]*| it/evals=1000/1750 eff=74.0741% N=400 Z=-16.5(73.36%) | Like=-15.13..-13.21 [-15.1262..-15.1248]*| it/evals=1040/1797 eff=74.4452% N=400 Z=-16.4(75.42%) | Like=-15.10..-13.21 [-15.1019..-15.1009]*| it/evals=1080/1852 eff=74.3802% N=400 Z=-16.4(77.32%) | Like=-15.08..-13.21 [-15.0804..-15.0802]*| it/evals=1120/1910 eff=74.1722% N=400 Z=-16.4(79.16%) | Like=-15.06..-13.21 [-15.0589..-15.0587]*| it/evals=1160/1959 eff=74.4067% N=400 Z=-16.4(79.61%) | Like=-15.05..-13.21 [-15.0540..-15.0538]*| it/evals=1170/1981 eff=74.0038% N=400 Z=-16.4(80.72%) | Like=-15.04..-13.05 [-15.0409..-15.0408]*| it/evals=1200/2011 eff=74.4879% N=400 Z=-16.3(82.07%) | Like=-15.02..-13.05 [-15.0242..-15.0231]*| it/evals=1240/2058 eff=74.7889% N=400 Z=-16.3(82.29%) | Like=-15.01..-12.00 [-15.0125..-15.0123]*| it/evals=1260/2084 eff=74.8219% N=400 Z=-16.3(82.29%) | Like=-15.00..-12.00 [-15.0040..-15.0038]*| it/evals=1280/2099 eff=75.3384% N=400 Z=-16.3(83.14%) | Like=-14.99..-11.86 [-14.9866..-14.9853]*| it/evals=1320/2153 eff=75.2995% N=400 Z=-16.3(84.11%) | Like=-14.97..-11.86 [-14.9730..-14.9727]*| it/evals=1350/2188 eff=75.5034% N=400 Z=-16.3(84.28%) | Like=-14.97..-11.86 [-14.9662..-14.9659]*| it/evals=1360/2197 eff=75.6817% N=400 Z=-16.3(84.96%) | Like=-14.95..-11.85 [-14.9525..-14.9522]*| it/evals=1400/2252 eff=75.5940% N=400 Z=-16.3(86.04%) | Like=-14.94..-11.85 [-14.9381..-14.9380]*| it/evals=1440/2300 eff=75.7895% N=400 Z=-16.3(86.97%) | Like=-14.93..-11.85 [-14.9272..-14.9268]*| it/evals=1480/2347 eff=76.0144% N=400 Z=-16.3(88.01%) | Like=-14.91..-11.85 [-14.9131..-14.9129]*| it/evals=1520/2393 eff=76.2669% N=400 Z=-16.2(88.82%) | Like=-14.90..-11.85 [-14.9011..-14.9005]*| it/evals=1560/2447 eff=76.2091% N=400 Z=-16.2(89.49%) | Like=-14.89..-11.85 [-14.8877..-14.8876]*| it/evals=1600/2519 eff=75.5073% N=400 Z=-16.2(89.78%) | Like=-14.88..-11.85 [-14.8836..-14.8832]*| it/evals=1620/2585 eff=74.1419% N=400 Z=-16.2(90.17%) | Like=-14.88..-11.85 [-14.8797..-14.8789]*| it/evals=1640/2585 eff=75.0572% N=400 Z=-16.2(90.86%) | Like=-14.87..-11.85 [-14.8688..-14.8685]*| it/evals=1680/2679 eff=73.7165% N=400 Z=-16.2(91.24%) | Like=-14.86..-11.85 [-14.8606..-14.8605]*| it/evals=1710/2679 eff=75.0329% N=400 Z=-16.2(91.39%) | Like=-14.86..-11.85 [-14.8570..-14.8565]*| it/evals=1720/2679 eff=75.4717% N=400 Z=-16.2(91.88%) | Like=-14.84..-11.85 [-14.8446..-14.8434]*| it/evals=1760/2793 eff=73.5478% N=400 Z=-16.2(91.63%) | Like=-14.83..-11.54 [-14.8334..-14.8332]*| it/evals=1800/2862 eff=73.1113% N=400 Z=-16.2(92.02%) | Like=-14.82..-11.54 [-14.8180..-14.8179]*| it/evals=1840/2862 eff=74.7360% N=400 Z=-16.2(92.39%) | Like=-14.78..-11.54 [-14.7823..-14.7809]*| it/evals=1880/2936 eff=74.1325% N=400 Z=-16.2(92.53%) | Like=-14.77..-11.54 [-14.7750..-14.7732]*| it/evals=1890/2936 eff=74.5268% N=400 Z=-16.2(92.77%) | Like=-14.75..-11.54 [-14.7478..-14.7478]*| it/evals=1920/3010 eff=73.5632% N=400 Z=-16.2(92.99%) | Like=-14.72..-11.54 [-14.7162..-14.7158]*| it/evals=1960/3075 eff=73.2710% N=400 Z=-16.2(93.09%) | Like=-14.69..-11.54 [-14.6910..-14.6876]*| it/evals=1980/3075 eff=74.0187% N=400 Z=-16.2(93.34%) | Like=-14.67..-11.54 [-14.6694..-14.6690]*| it/evals=2000/3075 eff=74.7664% N=400 Z=-16.2(93.47%) | Like=-14.64..-11.54 [-14.6373..-14.6357]*| it/evals=2040/3142 eff=74.3982% N=400 Z=-16.2(93.64%) | Like=-14.61..-11.54 [-14.6082..-14.6081]*| it/evals=2070/3201 eff=73.9022% N=400 Z=-16.2(93.66%) | Like=-14.59..-11.54 [-14.5872..-14.5872]*| it/evals=2080/3201 eff=74.2592% N=400 Z=-16.2(93.89%) | Like=-14.50..-11.54 [-14.5049..-14.5020]*| it/evals=2120/3301 eff=73.0782% N=400 Z=-16.2(94.09%) | Like=-14.43..-11.54 [-14.4330..-14.4327]*| it/evals=2160/3301 eff=74.4571% N=400 Z=-16.2(94.22%) | Like=-14.37..-11.54 [-14.3805..-14.3662] | it/evals=2200/3363 eff=74.2491% N=400 Z=-16.2(94.52%) | Like=-14.28..-11.54 [-14.2802..-14.2797]*| it/evals=2240/3430 eff=73.9274% N=400 Z=-16.2(94.55%) | Like=-14.27..-11.54 [-14.2663..-14.2647]*| it/evals=2250/3430 eff=74.2574% N=400 Z=-16.2(94.64%) | Like=-14.20..-11.50 [-14.1976..-14.1882]*| it/evals=2280/3504 eff=73.4536% N=400 Z=-16.2(94.92%) | Like=-14.12..-11.50 [-14.1185..-14.1133]*| it/evals=2320/3572 eff=73.1400% N=400 Z=-16.2(94.89%) | Like=-14.09..-11.30 [-14.0926..-14.0919]*| it/evals=2340/3572 eff=73.7705% N=400 Z=-16.2(94.89%) | Like=-14.06..-11.30 [-14.0608..-14.0605]*| it/evals=2360/3572 eff=74.4010% N=400 Z=-16.2(95.09%) | Like=-14.00..-11.20 [-14.0034..-14.0033]*| it/evals=2400/3679 eff=73.1930% N=400 Z=-16.2(95.15%) | Like=-13.97..-11.20 [-13.9725..-13.9714]*| it/evals=2430/3679 eff=74.1080% N=400 Z=-16.2(95.16%) | Like=-13.96..-11.20 [-13.9593..-13.9586]*| it/evals=2440/3766 eff=72.4896% N=400 Z=-16.2(95.35%) | Like=-13.91..-11.20 [-13.9065..-13.9053]*| it/evals=2480/3766 eff=73.6780% N=400 Z=-16.2(95.50%) | Like=-13.85..-11.20 [-13.8539..-13.8502]*| it/evals=2520/3857 eff=72.8956% N=400 Z=-16.2(95.68%) | Like=-13.80..-11.20 [-13.8021..-13.7979]*| it/evals=2560/3857 eff=74.0526% N=400 Z=-16.2(95.83%) | Like=-13.75..-11.20 [-13.7492..-13.7448]*| it/evals=2600/3935 eff=73.5502% N=400 Z=-16.2(95.89%) | Like=-13.73..-11.20 [-13.7291..-13.7285]*| it/evals=2610/3935 eff=73.8331% N=400 Z=-16.2(96.01%) | Like=-13.70..-11.20 [-13.6977..-13.6974]*| it/evals=2640/4033 eff=72.6672% N=400 Z=-16.2(96.19%) | Like=-13.66..-11.20 [-13.6557..-13.6556]*| it/evals=2680/4033 eff=73.7682% N=400 Z=-16.2(96.25%) | Like=-13.63..-11.20 [-13.6340..-13.6333]*| it/evals=2700/4123 eff=72.5222% N=400 Z=-16.2(96.30%) | Like=-13.61..-11.20 [-13.6100..-13.6069]*| it/evals=2720/4123 eff=73.0594% N=400 Z=-16.2(96.42%) | Like=-13.54..-11.20 [-13.5417..-13.5403]*| it/evals=2760/4227 eff=72.1192% N=400 Z=-16.2(96.53%) | Like=-13.45..-11.20 [-13.4463..-13.4462]*| it/evals=2790/4227 eff=72.9031% N=400 Z=-16.2(96.55%) | Like=-13.42..-11.20 [-13.4240..-13.4220]*| it/evals=2800/4227 eff=73.1644% N=400 Z=-16.2(96.67%) | Like=-13.29..-11.20 [-13.2876..-13.2869]*| it/evals=2840/4264 eff=73.4990% N=400 Z=-16.1(96.76%) | Like=-13.17..-11.16 [-13.1669..-13.1666]*| it/evals=2880/4319 eff=73.4881% N=400 Z=-16.1(96.91%) | Like=-13.05..-10.83 [-13.0540..-13.0520]*| it/evals=2920/4395 eff=73.0914% N=400 Z=-16.1(97.01%) | Like=-12.98..-10.78 [-12.9820..-12.9807]*| it/evals=2960/4448 eff=73.1225% N=400 Z=-16.1(97.04%) | Like=-12.96..-10.78 [-12.9597..-12.9573]*| it/evals=2970/4461 eff=73.1347% N=400 Z=-16.1(97.16%) | Like=-12.90..-10.78 [-12.9001..-12.8960]*| it/evals=3000/4573 eff=71.8907% N=400 Z=-16.1(97.28%) | Like=-12.81..-10.71 [-12.8120..-12.8075]*| it/evals=3040/4573 eff=72.8493% N=400 Z=-16.1(97.33%) | Like=-12.76..-10.71 [-12.7593..-12.7593]*| it/evals=3060/4677 eff=71.5455% N=400 Z=-16.1(97.40%) | Like=-12.71..-10.71 [-12.7227..-12.7119] | it/evals=3080/4677 eff=72.0131% N=400 Z=-16.1(97.51%) | Like=-12.62..-10.71 [-12.6216..-12.6187]*| it/evals=3120/4677 eff=72.9483% N=400 Z=-16.1(97.61%) | Like=-12.56..-10.71 [-12.5573..-12.5570]*| it/evals=3150/4783 eff=71.8686% N=400 Z=-16.1(97.65%) | Like=-12.53..-10.71 [-12.5334..-12.5307]*| it/evals=3160/4783 eff=72.0967% N=400 Z=-16.1(97.79%) | Like=-12.47..-10.67 [-12.4663..-12.4660]*| it/evals=3200/4807 eff=72.6118% N=400 Z=-16.1(97.90%) | Like=-12.40..-10.67 [-12.4004..-12.3983]*| it/evals=3240/4864 eff=72.5806% N=400 Z=-16.1(98.03%) | Like=-12.34..-10.67 [-12.3382..-12.3369]*| it/evals=3280/4963 eff=71.8825% N=400 Z=-16.1(98.16%) | Like=-12.28..-10.67 [-12.2780..-12.2776]*| it/evals=3320/4963 eff=72.7591% N=400 Z=-16.1(98.19%) | Like=-12.26..-10.67 [-12.2599..-12.2526]*| it/evals=3330/5070 eff=71.3062% N=400 Z=-16.1(98.27%) | Like=-12.19..-10.41 [-12.1911..-12.1903]*| it/evals=3360/5070 eff=71.9486% N=400 Z=-16.1(98.40%) | Like=-12.11..-10.41 [-12.1122..-12.1102]*| it/evals=3400/5082 eff=72.6185% N=400 Z=-16.1(98.50%) | Like=-12.06..-10.41 [-12.0599..-12.0591]*| it/evals=3440/5139 eff=72.5892% N=400 Z=-16.1(98.57%) | Like=-12.02..-10.27 [-12.0160..-12.0145]*| it/evals=3480/5205 eff=72.4246% N=400 Z=-16.1(98.63%) | Like=-11.98..-10.27 [-11.9758..-11.9748]*| it/evals=3520/5258 eff=72.4578% N=400 Z=-16.1(98.71%) | Like=-11.94..-10.27 [-11.9392..-11.9390]*| it/evals=3560/5320 eff=72.3577% N=400 Z=-16.1(98.79%) | Like=-11.90..-10.27 [-11.9040..-11.9036]*| it/evals=3600/5373 eff=72.3909% N=400 Z=-16.1(98.83%) | Like=-11.87..-10.07 [-11.8686..-11.8648]*| it/evals=3640/5436 eff=72.2796% N=400 Z=-16.1(98.88%) | Like=-11.83..-10.04 [-11.8315..-11.8309]*| it/evals=3680/5487 eff=72.3413% N=400 Z=-16.1(98.88%) | Like=-11.83..-10.04 [-11.8277..-11.8275]*| it/evals=3690/5600 eff=70.9615% N=400 Z=-16.1(98.90%) | Like=-11.81..-10.04 [-11.8122..-11.8104]*| it/evals=3720/5600 eff=71.5385% N=400 Z=-16.1(98.95%) | Like=-11.78..-10.04 [-11.7838..-11.7833]*| it/evals=3760/5600 eff=72.3077% N=400 Z=-16.1(98.97%) | Like=-11.77..-9.95 [-11.7704..-11.7691]*| it/evals=3780/5700 eff=71.3208% N=400 Z=-16.1(98.99%) | Like=-11.75..-9.95 [-11.7459..-11.7457]*| it/evals=3800/5700 eff=71.6981% N=400 [ultranest] Explored until L=-1e+01 [ultranest] Likelihood function evaluations: 5700 [ultranest] logZ = -16.1 +- 0.031 [ultranest] Effective samples strategy satisfied (ESS = 1540.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) [ultranest] logZ error budget: single: 0.04 bs:0.03 tail:0.01 total:0.03 required:<0.50 [ultranest] done iterating. logZ = -16.113 +- 0.081 single instance: logZ = -16.113 +- 0.040 bootstrapped : logZ = -16.104 +- 0.081 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : -0.00320│▁▁▁▁▁▁▁▁▁▃▂▃▄▅▅▆▆▇▇▇▆▆▅▆▅▄▃▄▂▂▁▁▁▁▁▁▁▁ │0.00332 0.00000 +- 0.00094 aux_logweight : -16.20│▁▂▂▂▃▅▆▇▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ │-9.65 -15.00 +- 0.81 expected posterior: 0 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [3.103301183435752e-07, -15.00417091567436] [0.0009388036712996759, 0.8058161277233461] [[0.12036642 0.99849055] [0.99526706 0.98967293] [0.14897278 0.99923711] ... [0.49959749 0.8562253 ] [0.49994909 0.85537463] [0.50001132 0.85666616]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 7.76359460e-05 7.98804246e-05 8.69500660e-05] ====== Running Gauss problem [3] ===== center: 0.001 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-1.5e+13..-14 [-1.485e+13..-16.89] | it/evals=0/528 eff=0.0000% N=400 Z=-12164310.7(0.00%) | Like=-12150372.90..-13.67 [-1.485e+13..-16.89] | it/evals=40/528 eff=31.2500% N=400 Z=-652.1(0.00%) | Like=-620.56..-13.67 [-1.485e+13..-16.89] | it/evals=80/528 eff=62.5000% N=400 Z=-56.8(0.00%) | Like=-49.94..-13.67 [-1.485e+13..-16.89] | it/evals=90/528 eff=70.3125% N=400 Z=-26.1(0.00%) | Like=-21.82..-13.67 [-1.485e+13..-16.89] | it/evals=120/632 eff=51.7241% N=400 Z=-22.1(0.27%) | Like=-18.83..-13.67 [-1.485e+13..-16.89] | it/evals=160/632 eff=68.9655% N=400 Z=-21.4(0.56%) | Like=-18.34..-13.67 [-1.485e+13..-16.89] | it/evals=180/632 eff=77.5862% N=400 Z=-20.8(1.00%) | Like=-17.96..-13.67 [-1.485e+13..-16.89] | it/evals=200/715 eff=63.4921% N=400 Z=-20.0(2.31%) | Like=-17.37..-13.67 [-1.485e+13..-16.89] | it/evals=240/715 eff=76.1905% N=400 Z=-19.3(4.39%) | Like=-16.92..-13.67 [-1.485e+13..-16.89] | it/evals=280/791 eff=71.6113% N=400 Z=-18.8(7.19%) | Like=-16.54..-13.67 [-16.5401..-16.5393]*| it/evals=320/791 eff=81.8414% N=400 Z=-18.5(10.63%) | Like=-16.31..-13.67 [-16.3150..-16.3083]*| it/evals=360/856 eff=78.9474% N=400 Z=-18.1(14.46%) | Like=-16.13..-13.67 [-16.1344..-16.1344]*| it/evals=400/918 eff=77.2201% N=400 Z=-17.9(18.72%) | Like=-16.00..-13.67 [-15.9980..-15.9956]*| it/evals=440/979 eff=75.9931% N=400 Z=-17.7(23.05%) | Like=-15.83..-13.67 [-15.8259..-15.8212]*| it/evals=480/1031 eff=76.0697% N=400 Z=-17.5(27.56%) | Like=-15.73..-13.67 [-15.7350..-15.7345]*| it/evals=520/1076 eff=76.9231% N=400 Z=-17.4(29.55%) | Like=-15.69..-13.67 [-15.6855..-15.6849]*| it/evals=540/1076 eff=79.8817% N=400 Z=-17.4(31.40%) | Like=-15.65..-13.49 [-15.6502..-15.6481]*| it/evals=560/1112 eff=78.6517% N=400 Z=-17.2(35.65%) | Like=-15.59..-13.49 [-15.5913..-15.5908]*| it/evals=600/1186 eff=76.3359% N=400 Z=-17.1(39.90%) | Like=-15.54..-13.49 [-15.5399..-15.5364]*| it/evals=640/1227 eff=77.3881% N=400 Z=-17.0(43.82%) | Like=-15.48..-13.49 [-15.4766..-15.4740]*| it/evals=680/1287 eff=76.6629% N=400 Z=-17.0(47.61%) | Like=-15.42..-13.49 [-15.4168..-15.4144]*| it/evals=720/1339 eff=76.6773% N=400 Z=-16.9(51.42%) | Like=-15.35..-13.49 [-15.3493..-15.3493]*| it/evals=760/1416 eff=74.8031% N=400 Z=-16.8(54.77%) | Like=-15.31..-13.49 [-15.3112..-15.3108]*| it/evals=800/1471 eff=74.6965% N=400 Z=-16.8(55.65%) | Like=-15.30..-13.49 [-15.3001..-15.2999]*| it/evals=810/1493 eff=74.1080% N=400 Z=-16.8(57.99%) | Like=-15.28..-13.49 [-15.2763..-15.2737]*| it/evals=840/1556 eff=72.6644% N=400 Z=-16.7(61.13%) | Like=-15.23..-13.49 [-15.2320..-15.2308]*| it/evals=880/1606 eff=72.9685% N=400 Z=-16.7(62.67%) | Like=-15.21..-13.49 [-15.2117..-15.2116]*| it/evals=900/1619 eff=73.8310% N=400 Z=-16.7(64.06%) | Like=-15.20..-13.49 [-15.1985..-15.1978]*| it/evals=920/1643 eff=74.0145% N=400 Z=-16.6(66.71%) | Like=-15.17..-13.49 [-15.1695..-15.1685]*| it/evals=960/1708 eff=73.3945% N=400 Z=-16.6(69.19%) | Like=-15.14..-13.49 [-15.1418..-15.1407]*| it/evals=1000/1762 eff=73.4214% N=400 Z=-16.6(71.62%) | Like=-15.11..-13.49 [-15.1081..-15.1027]*| it/evals=1040/1807 eff=73.9161% N=400 Z=-16.5(73.92%) | Like=-15.08..-13.49 [-15.0822..-15.0813]*| it/evals=1080/1868 eff=73.5695% N=400 Z=-16.5(76.00%) | Like=-15.06..-13.49 [-15.0588..-15.0579]*| it/evals=1120/1916 eff=73.8786% N=400 Z=-16.5(77.87%) | Like=-15.03..-13.49 [-15.0345..-15.0342]*| it/evals=1160/1974 eff=73.6976% N=400 Z=-16.5(78.37%) | Like=-15.03..-13.49 [-15.0299..-15.0296]*| it/evals=1170/1984 eff=73.8636% N=400 Z=-16.4(79.57%) | Like=-15.02..-13.49 [-15.0170..-15.0166]*| it/evals=1200/2027 eff=73.7554% N=400 Z=-16.4(81.16%) | Like=-15.00..-13.49 [-14.9982..-14.9982]*| it/evals=1240/2080 eff=73.8095% N=400 Z=-16.4(81.91%) | Like=-14.99..-13.49 [-14.9908..-14.9906]*| it/evals=1260/2108 eff=73.7705% N=400 Z=-16.4(82.58%) | Like=-14.98..-13.49 [-14.9839..-14.9838]*| it/evals=1280/2137 eff=73.6903% N=400 Z=-16.4(83.85%) | Like=-14.97..-13.49 [-14.9659..-14.9636]*| it/evals=1320/2184 eff=73.9910% N=400 Z=-16.4(84.64%) | Like=-14.96..-13.49 [-14.9561..-14.9558]*| it/evals=1350/2232 eff=73.6900% N=400 Z=-16.4(84.98%) | Like=-14.95..-13.49 [-14.9540..-14.9539]*| it/evals=1360/2249 eff=73.5533% N=400 Z=-16.4(86.09%) | Like=-14.94..-13.49 [-14.9422..-14.9417]*| it/evals=1400/2300 eff=73.6842% N=400 Z=-16.4(87.08%) | Like=-14.93..-13.36 [-14.9321..-14.9321]*| it/evals=1440/2361 eff=73.4319% N=400 Z=-16.3(87.89%) | Like=-14.92..-12.53 [-14.9195..-14.9193]*| it/evals=1480/2412 eff=73.5586% N=400 Z=-16.3(88.89%) | Like=-14.91..-12.53 [-14.9066..-14.9063]*| it/evals=1520/2476 eff=73.2177% N=400 Z=-16.3(89.09%) | Like=-14.90..-12.53 [-14.9042..-14.9039]*| it/evals=1530/2490 eff=73.2057% N=400 Z=-16.3(89.66%) | Like=-14.90..-12.53 [-14.8975..-14.8973]*| it/evals=1560/2532 eff=73.1707% N=400 Z=-16.3(90.44%) | Like=-14.89..-12.53 [-14.8867..-14.8867]*| it/evals=1600/2618 eff=72.1371% N=400 Z=-16.3(90.60%) | Like=-14.88..-12.49 [-14.8831..-14.8825]*| it/evals=1620/2618 eff=73.0388% N=400 Z=-16.3(90.61%) | Like=-14.88..-12.49 [-14.8789..-14.8786]*| it/evals=1640/2644 eff=73.0838% N=400 Z=-16.3(91.28%) | Like=-14.87..-12.49 [-14.8701..-14.8699]*| it/evals=1680/2748 eff=71.5503% N=400 Z=-16.3(91.74%) | Like=-14.86..-12.49 [-14.8616..-14.8612]*| it/evals=1710/2748 eff=72.8279% N=400 Z=-16.3(91.91%) | Like=-14.86..-12.49 [-14.8592..-14.8590]*| it/evals=1720/2759 eff=72.9123% N=400 Z=-16.3(92.22%) | Like=-14.85..-12.28 [-14.8486..-14.8480]*| it/evals=1760/2832 eff=72.3684% N=400 Z=-16.3(92.64%) | Like=-14.84..-12.28 [-14.8378..-14.8377]*| it/evals=1800/2881 eff=72.5514% N=400 Z=-16.3(93.08%) | Like=-14.83..-12.28 [-14.8283..-14.8279]*| it/evals=1840/2932 eff=72.6698% N=400 Z=-16.3(93.27%) | Like=-14.80..-12.28 [-14.8025..-14.8020]*| it/evals=1880/2986 eff=72.6991% N=400 Z=-16.3(93.38%) | Like=-14.79..-12.28 [-14.7927..-14.7927]*| it/evals=1890/3026 eff=71.9726% N=400 Z=-16.3(93.57%) | Like=-14.77..-12.28 [-14.7664..-14.7651]*| it/evals=1920/3035 eff=72.8653% N=400 Z=-16.3(93.80%) | Like=-14.74..-12.28 [-14.7364..-14.7358]*| it/evals=1960/3089 eff=72.8896% N=400 Z=-16.3(93.98%) | Like=-14.70..-12.11 [-14.6990..-14.6985]*| it/evals=2000/3138 eff=73.0460% N=400 Z=-16.3(94.11%) | Like=-14.66..-12.01 [-14.6634..-14.6633]*| it/evals=2040/3198 eff=72.9092% N=400 Z=-16.3(94.17%) | Like=-14.64..-12.01 [-14.6356..-14.6354]*| it/evals=2070/3238 eff=72.9387% N=400 Z=-16.3(94.07%) | Like=-14.63..-11.86 [-14.6296..-14.6283]*| it/evals=2080/3332 eff=70.9413% N=400 Z=-16.3(94.32%) | Like=-14.58..-11.86 [-14.5820..-14.5819]*| it/evals=2120/3332 eff=72.3056% N=400 Z=-16.3(94.49%) | Like=-14.50..-11.86 [-14.5002..-14.4999]*| it/evals=2160/3418 eff=71.5706% N=400 Z=-16.3(94.68%) | Like=-14.43..-11.86 [-14.4343..-14.4339]*| it/evals=2200/3418 eff=72.8960% N=400 Z=-16.3(94.87%) | Like=-14.37..-11.82 [-14.3699..-14.3699]*| it/evals=2240/3505 eff=72.1417% N=400 Z=-16.3(94.95%) | Like=-14.35..-11.82 [-14.3475..-14.3475]*| it/evals=2250/3505 eff=72.4638% N=400 Z=-16.2(95.05%) | Like=-14.29..-11.82 [-14.2882..-14.2796]*| it/evals=2280/3534 eff=72.7505% N=400 Z=-16.2(95.34%) | Like=-14.20..-11.82 [-14.2023..-14.2019]*| it/evals=2320/3587 eff=72.7957% N=400 Z=-16.2(95.47%) | Like=-14.18..-11.82 [-14.1756..-14.1742]*| it/evals=2340/3618 eff=72.7160% N=400 Z=-16.2(95.52%) | Like=-14.16..-11.82 [-14.1554..-14.1547]*| it/evals=2360/3638 eff=72.8845% N=400 Z=-16.2(95.68%) | Like=-14.09..-11.82 [-14.0896..-14.0883]*| it/evals=2400/3687 eff=73.0149% N=400 Z=-16.2(95.78%) | Like=-14.05..-11.72 [-14.0463..-14.0459]*| it/evals=2430/3810 eff=71.2610% N=400 Z=-16.2(95.81%) | Like=-14.02..-11.72 [-14.0151..-14.0133]*| it/evals=2440/3810 eff=71.5543% N=400 Z=-16.2(96.00%) | Like=-13.96..-11.72 [-13.9564..-13.9536]*| it/evals=2480/3810 eff=72.7273% N=400 Z=-16.2(96.14%) | Like=-13.91..-11.71 [-13.9094..-13.9084]*| it/evals=2520/3877 eff=72.4763% N=400 Z=-16.2(96.29%) | Like=-13.86..-11.69 [-13.8607..-13.8603]*| it/evals=2560/3898 eff=73.1847% N=400 Z=-16.2(96.46%) | Like=-13.82..-11.69 [-13.8167..-13.8162]*| it/evals=2600/3950 eff=73.2394% N=400 Z=-16.2(96.63%) | Like=-13.77..-11.69 [-13.7720..-13.7715]*| it/evals=2640/4004 eff=73.2519% N=400 Z=-16.2(96.82%) | Like=-13.73..-11.69 [-13.7302..-13.7288]*| it/evals=2680/4063 eff=73.1641% N=400 Z=-16.2(96.95%) | Like=-13.68..-11.69 [-13.6837..-13.6824]*| it/evals=2720/4127 eff=72.9809% N=400 Z=-16.2(97.02%) | Like=-13.65..-11.61 [-13.6456..-13.6413]*| it/evals=2760/4182 eff=72.9773% N=400 Z=-16.2(97.13%) | Like=-13.61..-11.61 [-13.6132..-13.6118]*| it/evals=2790/4235 eff=72.7510% N=400 Z=-16.2(97.16%) | Like=-13.60..-11.61 [-13.6000..-13.5998]*| it/evals=2800/4307 eff=71.6662% N=400 Z=-16.2(97.28%) | Like=-13.56..-11.61 [-13.5605..-13.5599]*| it/evals=2840/4307 eff=72.6900% N=400 Z=-16.2(97.32%) | Like=-13.49..-11.54 [-13.4916..-13.4903]*| it/evals=2880/4374 eff=72.4711% N=400 Z=-16.2(97.41%) | Like=-13.38..-11.54 [-13.3842..-13.3841]*| it/evals=2920/4432 eff=72.4206% N=400 Z=-16.2(97.51%) | Like=-13.27..-11.54 [-13.2720..-13.2686]*| it/evals=2960/4486 eff=72.4425% N=400 Z=-16.2(97.54%) | Like=-13.24..-11.54 [-13.2353..-13.2338]*| it/evals=2970/4486 eff=72.6872% N=400 Z=-16.2(97.61%) | Like=-13.16..-11.54 [-13.1555..-13.1539]*| it/evals=3000/4523 eff=72.7626% N=400 Z=-16.2(97.72%) | Like=-13.06..-11.49 [-13.0552..-13.0470]*| it/evals=3040/4574 eff=72.8318% N=400 Z=-16.2(97.77%) | Like=-13.01..-11.49 [-13.0056..-13.0028]*| it/evals=3060/4600 eff=72.8571% N=400 Z=-16.2(97.84%) | Like=-12.97..-11.49 [-12.9655..-12.9602]*| it/evals=3080/4698 eff=71.6612% N=400 Z=-16.2(97.95%) | Like=-12.87..-11.49 [-12.8714..-12.8701]*| it/evals=3120/4698 eff=72.5919% N=400 Z=-16.2(98.01%) | Like=-12.80..-11.22 [-12.8027..-12.8020]*| it/evals=3150/4780 eff=71.9178% N=400 Z=-16.2(98.04%) | Like=-12.78..-11.22 [-12.7811..-12.7780]*| it/evals=3160/4780 eff=72.1461% N=400 Z=-16.2(98.14%) | Like=-12.70..-11.22 [-12.6983..-12.6942]*| it/evals=3200/4869 eff=71.6044% N=400 Z=-16.2(98.24%) | Like=-12.62..-10.99 [-12.6225..-12.6224]*| it/evals=3240/4869 eff=72.4994% N=400 Z=-16.2(98.33%) | Like=-12.54..-10.99 [-12.5409..-12.5381]*| it/evals=3280/4948 eff=72.1196% N=400 Z=-16.2(98.41%) | Like=-12.49..-10.99 [-12.4924..-12.4903]*| it/evals=3320/5013 eff=71.9705% N=400 Z=-16.2(98.44%) | Like=-12.48..-10.99 [-12.4779..-12.4775]*| it/evals=3330/5013 eff=72.1873% N=400 Z=-16.2(98.50%) | Like=-12.43..-10.94 [-12.4298..-12.4296]*| it/evals=3360/5129 eff=71.0510% N=400 Z=-16.2(98.59%) | Like=-12.37..-10.94 [-12.3703..-12.3693]*| it/evals=3400/5129 eff=71.8968% N=400 Z=-16.2(98.64%) | Like=-12.35..-10.94 [-12.3461..-12.3410]*| it/evals=3420/5129 eff=72.3197% N=400 Z=-16.2(98.69%) | Like=-12.32..-10.94 [-12.3181..-12.3150]*| it/evals=3440/5235 eff=71.1479% N=400 Z=-16.2(98.78%) | Like=-12.27..-10.94 [-12.2675..-12.2673]*| it/evals=3480/5235 eff=71.9752% N=400 Z=-16.2(98.84%) | Like=-12.22..-10.94 [-12.2200..-12.2193]*| it/evals=3510/5341 eff=71.0383% N=400 Z=-16.2(98.85%) | Like=-12.21..-10.94 [-12.2086..-12.2078]*| it/evals=3520/5341 eff=71.2406% N=400 Z=-16.2(98.92%) | Like=-12.17..-10.94 [-12.1669..-12.1656]*| it/evals=3560/5341 eff=72.0502% N=400 Z=-16.2(98.99%) | Like=-12.12..-10.94 [-12.1237..-12.1213]*| it/evals=3600/5456 eff=71.2025% N=400 [ultranest] Explored until L=-1e+01 [ultranest] Likelihood function evaluations: 5456 [ultranest] logZ = -16.18 +- 0.03606 [ultranest] Effective samples strategy satisfied (ESS = 1474.1, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.04, need <0.5) [ultranest] logZ error budget: single: 0.04 bs:0.04 tail:0.01 total:0.04 required:<0.50 [ultranest] done iterating. logZ = -16.194 +- 0.092 single instance: logZ = -16.194 +- 0.043 bootstrapped : logZ = -16.183 +- 0.091 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a : -0.00229│▁▁▁▁▁▁▁▂▂▂▃▃▄▅▆▅▇▇▇▆▇▅▅▄▃▂▂▂▂▁▁▁▁ ▁ │0.00454 0.00084 +- 0.00089 aux_logweight : -16.20│▁▁▁▁▂▃▄▅▇▇▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ │-10.68 -15.01 +- 0.67 expected posterior: 0.001 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [0.0008448999199092131, -15.012361700518356] [0.0008942846449051315, 0.6690517874129255] [[0.12340181 0.99040087] [0.88659057 0.98849281] [0.86872833 0.98900429] ... [0.50254808 0.84611492] [0.50338149 0.84606757] [0.50301997 0.84628771]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 5.56604570e-05 5.56804178e-05 5.80766537e-05] ====== Running Gauss problem [4] ===== center: 1 folder: /tmp/tmpo5ypz9wy [ultranest] Sampling 400 live points from prior ... Z=-inf(0.00%) | Like=-2.7e+13..-8.5e+02 [-2.707e+13..-5.001e+05] | it/evals=0/528 eff=0.0000% N=400 Z=-3316105.2(0.00%) | Like=-2597981.55..-846.67 [-2.707e+13..-5.001e+05] | it/evals=40/528 eff=31.2500% N=400 Z=-502427.0(0.00%) | Like=-502376.73..-846.67 [-2.707e+13..-5.001e+05] | it/evals=80/528 eff=62.5000% N=400 Z=-502236.7(0.00%) | Like=-502117.19..-846.67 [-2.707e+13..-5.001e+05] | it/evals=90/528 eff=70.3125% N=400 Z=-501645.2(0.00%) | Like=-501629.49..-846.67 [-2.707e+13..-5.001e+05] | it/evals=120/638 eff=50.4202% N=400 Z=-501135.8(0.00%) | Like=-501121.91..-846.67 [-2.707e+13..-5.001e+05] | it/evals=160/638 eff=67.2269% N=400 Z=-500731.1(0.00%) | Like=-500719.78..-846.67 [-2.707e+13..-5.001e+05] | it/evals=200/732 eff=60.2410% N=400 Z=-500421.0(0.00%) | Like=-500412.11..-846.67 [-2.707e+13..-5.001e+05] | it/evals=240/732 eff=72.2892% N=400 Z=-500230.3(0.00%) | Like=-500222.16..-846.67 [-2.707e+13..-5.001e+05] | it/evals=270/813 eff=65.3753% N=400 Z=-500174.1(0.00%) | Like=-500165.75..-846.67 [-2.707e+13..-5.001e+05] | it/evals=280/813 eff=67.7966% N=400 Z=-499905.4(0.00%) | Like=-499898.07..-846.67 [-500135.1572..-498820.1386] | it/evals=320/873 eff=67.6533% N=400 Z=-499684.3(0.00%) | Like=-499674.47..-846.67 [-500135.1572..-498820.1386] | it/evals=360/873 eff=76.1099% N=400 Z=-499526.8(0.00%) | Like=-499518.11..-846.67 [-500135.1572..-498820.1386] | it/evals=400/933 eff=75.0469% N=400 Z=-499362.7(0.00%) | Like=-499354.40..-846.67 [-500135.1572..-498820.1386] | it/evals=440/990 eff=74.5763% N=400 Z=-499346.1(0.00%) | Like=-499339.33..-846.67 [-500135.1572..-498820.1386] | it/evals=450/990 eff=76.2712% N=400 Z=-499217.2(0.00%) | Like=-499205.12..-846.67 [-500135.1572..-498820.1386] | it/evals=480/1045 eff=74.4186% N=400 Z=-499029.7(0.00%) | Like=-499014.37..-846.67 [-500135.1572..-498820.1386] | it/evals=520/1088 eff=75.5814% N=400 Z=-498940.9(0.00%) | Like=-498931.16..-846.67 [-500135.1572..-498820.1386] | it/evals=540/1088 eff=78.4884% N=400 Z=-498843.8(0.00%) | Like=-498836.53..-846.67 [-500135.1572..-498820.1386] | it/evals=560/1123 eff=77.4550% N=400 Z=-498726.9(0.00%) | Like=-498713.18..-846.67 [-498819.3616..-497827.6601] | it/evals=600/1196 eff=75.3769% N=400 Z=-498594.3(0.00%) | Like=-498580.76..-846.67 [-498819.3616..-497827.6601] | it/evals=630/1226 eff=76.2712% N=400 Z=-498550.8(0.00%) | Like=-498542.58..-846.67 [-498819.3616..-497827.6601] | it/evals=640/1251 eff=75.2056% N=400 Z=-498370.7(0.00%) | Like=-498363.17..-846.67 [-498819.3616..-497827.6601] | it/evals=680/1287 eff=76.6629% N=400 Z=-498250.2(0.00%) | Like=-498237.06..-846.67 [-498819.3616..-497827.6601] | it/evals=720/1337 eff=76.8410% N=400 Z=-498145.1(0.00%) | Like=-498133.69..-846.67 [-498819.3616..-497827.6601] | it/evals=760/1401 eff=75.9241% N=400 Z=-497991.5(0.00%) | Like=-497972.61..-846.67 [-498819.3616..-497827.6601] | it/evals=800/1437 eff=77.1456% N=400 Z=-497947.4(0.00%) | Like=-497935.76..-846.67 [-498819.3616..-497827.6601] | it/evals=810/1455 eff=76.7773% N=400 Z=-497859.3(0.00%) | Like=-497841.61..-846.67 [-498819.3616..-497827.6601] | it/evals=840/1494 eff=76.7824% N=400 Z=-497720.1(0.00%) | Like=-497704.25..-846.67 [-497827.6061..-496894.2389] | it/evals=880/1527 eff=78.0834% N=400 Z=-497633.2(0.00%) | Like=-497620.88..-846.67 [-497827.6061..-496894.2389] | it/evals=900/1559 eff=77.6531% N=400 Z=-497569.3(0.00%) | Like=-497559.10..-846.67 [-497827.6061..-496894.2389] | it/evals=920/1591 eff=77.2460% N=400 Z=-497435.4(0.00%) | Like=-497425.78..-846.67 [-497827.6061..-496894.2389] | it/evals=960/1641 eff=77.3570% N=400 Z=-497308.0(0.00%) | Like=-497298.81..-846.67 [-497827.6061..-496894.2389] | it/evals=990/1693 eff=76.5661% N=400 Z=-497281.0(0.00%) | Like=-497265.98..-846.67 [-497827.6061..-496894.2389] | it/evals=1000/1704 eff=76.6871% N=400 Z=-497120.5(0.00%) | Like=-497110.05..-846.67 [-497827.6061..-496894.2389] | it/evals=1040/1752 eff=76.9231% N=400 Z=-496991.5(0.00%) | Like=-496980.01..-846.67 [-497827.6061..-496894.2389] | it/evals=1080/1809 eff=76.6501% N=400 Z=-496828.4(0.00%) | Like=-496818.80..-229.19 [-496893.1801..-476193.7693] | it/evals=1120/1860 eff=76.7123% N=400 Z=-496597.7(0.00%) | Like=-496588.52..-229.19 [-496893.1801..-476193.7693] | it/evals=1160/1906 eff=77.0252% N=400 Z=-495915.3(0.00%) | Like=-495883.80..-229.19 [-496893.1801..-476193.7693] | it/evals=1200/1959 eff=76.9724% N=400 Z=-493922.8(0.00%) | Like=-493845.25..-229.19 [-496893.1801..-476193.7693] | it/evals=1240/2018 eff=76.6378% N=400 Z=-492888.7(0.00%) | Like=-492837.70..-229.19 [-496893.1801..-476193.7693] | it/evals=1260/2050 eff=76.3636% N=400 Z=-491534.0(0.00%) | Like=-491486.25..-229.19 [-496893.1801..-476193.7693] | it/evals=1280/2080 eff=76.1905% N=400 Z=-487814.6(0.00%) | Like=-487578.52..-229.19 [-496893.1801..-476193.7693] | it/evals=1320/2130 eff=76.3006% N=400 Z=-479048.0(0.00%) | Like=-478730.51..-137.91 [-496893.1801..-476193.7693] | it/evals=1360/2180 eff=76.4045% N=400 Z=-467590.3(0.00%) | Like=-467197.20..-137.91 [-475937.5598..-338262.0948] | it/evals=1400/2236 eff=76.2527% N=400 Z=-458117.6(0.00%) | Like=-458097.65..-137.91 [-475937.5598..-338262.0948] | it/evals=1440/2304 eff=75.6303% N=400 Z=-446788.8(0.00%) | Like=-446452.99..-137.91 [-475937.5598..-338262.0948] | it/evals=1480/2347 eff=76.0144% N=400 Z=-430727.4(0.00%) | Like=-430448.72..-17.03 [-475937.5598..-338262.0948] | it/evals=1520/2408 eff=75.6972% N=400 Z=-413498.2(0.00%) | Like=-413026.67..-17.03 [-475937.5598..-338262.0948] | it/evals=1560/2458 eff=75.8017% N=400 Z=-379384.8(0.00%) | Like=-378797.67..-17.03 [-475937.5598..-338262.0948] | it/evals=1600/2521 eff=75.4361% N=400 Z=-367175.3(0.00%) | Like=-366497.90..-17.03 [-475937.5598..-338262.0948] | it/evals=1620/2555 eff=75.1740% N=400 Z=-347124.3(0.00%) | Like=-346275.59..-13.22 [-475937.5598..-338262.0948] | it/evals=1640/2592 eff=74.8175% N=400 Z=-315360.1(0.00%) | Like=-315266.06..-13.22 [-337913.5634..-149146.4481] | it/evals=1680/2660 eff=74.3363% N=400 Z=-288095.7(0.00%) | Like=-287308.57..-13.22 [-337913.5634..-149146.4481] | it/evals=1710/2712 eff=73.9619% N=400 Z=-283381.3(0.00%) | Like=-279597.31..-13.22 [-337913.5634..-149146.4481] | it/evals=1720/2726 eff=73.9467% N=400 Z=-251538.8(0.00%) | Like=-249847.19..-13.22 [-337913.5634..-149146.4481] | it/evals=1760/2834 eff=72.3090% N=400 Z=-224651.3(0.00%) | Like=-224588.99..-13.22 [-337913.5634..-149146.4481] | it/evals=1800/2906 eff=71.8276% N=400 Z=-198168.4(0.00%) | Like=-197940.18..-13.22 [-337913.5634..-149146.4481] | it/evals=1840/2971 eff=71.5675% N=400 Z=-178248.9(0.00%) | Like=-178172.53..-13.22 [-337913.5634..-149146.4481] | it/evals=1880/3030 eff=71.4829% N=400 Z=-154606.9(0.00%) | Like=-154562.77..-10.13 [-337913.5634..-149146.4481] | it/evals=1920/3088 eff=71.4286% N=400 Z=-134803.4(0.00%) | Like=-134078.66..-10.13 [-148753.5759..-54819.0147] | it/evals=1960/3197 eff=70.0751% N=400 Z=-118050.8(0.00%) | Like=-117828.10..-10.13 [-148753.5759..-54819.0147] | it/evals=2000/3248 eff=70.2247% N=400 Z=-106216.8(0.00%) | Like=-105342.65..-10.13 [-148753.5759..-54819.0147] | it/evals=2040/3366 eff=68.7795% N=400 Z=-92006.1(0.00%) | Like=-91832.14..-10.13 [-148753.5759..-54819.0147] | it/evals=2080/3485 eff=67.4230% N=400 Z=-77698.2(0.00%) | Like=-77294.92..-10.13 [-148753.5759..-54819.0147] | it/evals=2120/3572 eff=66.8348% N=400 Z=-66119.0(0.00%) | Like=-65995.65..-10.13 [-148753.5759..-54819.0147] | it/evals=2160/3683 eff=65.7935% N=400 Z=-56368.3(0.00%) | Like=-56336.47..-10.13 [-148753.5759..-54819.0147] | it/evals=2200/3758 eff=65.5152% N=400 Z=-48186.8(0.00%) | Like=-47662.68..-10.13 [-54662.7058..-18363.2862] | it/evals=2240/3888 eff=64.2202% N=400 Z=-41627.8(0.00%) | Like=-41542.91..-8.41 [-54662.7058..-18363.2862] | it/evals=2280/4025 eff=62.8966% N=400 Z=-34854.9(0.00%) | Like=-34438.03..-8.41 [-54662.7058..-18363.2862] | it/evals=2320/4158 eff=61.7350% N=400 Z=-32311.4(0.00%) | Like=-32244.02..-7.88 [-54662.7058..-18363.2862] | it/evals=2340/4212 eff=61.3851% N=400 Z=-29883.3(0.00%) | Like=-29757.69..-7.88 [-54662.7058..-18363.2862] | it/evals=2360/4275 eff=60.9032% N=400 Z=-25256.6(0.00%) | Like=-25242.32..-7.50 [-54662.7058..-18363.2862] | it/evals=2400/4378 eff=60.3318% N=400 Z=-20762.8(0.00%) | Like=-20722.55..-7.50 [-54662.7058..-18363.2862] | it/evals=2440/4463 eff=60.0541% N=400 Z=-17778.1(0.00%) | Like=-17743.47..-7.50 [-18300.1333..-4927.9682] | it/evals=2480/4621 eff=58.7538% N=400 Z=-15116.3(0.00%) | Like=-15054.41..-7.50 [-18300.1333..-4927.9682] | it/evals=2520/4763 eff=57.7584% N=400 Z=-12610.8(0.00%) | Like=-12579.89..-7.30 [-18300.1333..-4927.9682] | it/evals=2560/4903 eff=56.8510% N=400 Z=-10184.2(0.00%) | Like=-10150.09..-7.30 [-18300.1333..-4927.9682] | it/evals=2600/5035 eff=56.0949% N=400 Z=-8631.7(0.00%) | Like=-8602.91..-7.30 [-18300.1333..-4927.9682] | it/evals=2640/5178 eff=55.2532% N=400 Z=-7251.3(0.00%) | Like=-7217.86..-7.30 [-18300.1333..-4927.9682] | it/evals=2680/5384 eff=53.7721% N=400 Z=-5986.2(0.00%) | Like=-5967.35..-7.30 [-18300.1333..-4927.9682] | it/evals=2720/5503 eff=53.3020% N=400 Z=-4915.3(0.00%) | Like=-4874.76..-7.30 [-4912.3727..-1318.0866] | it/evals=2760/5644 eff=52.6316% N=400 Z=-3981.6(0.00%) | Like=-3924.82..-7.30 [-4912.3727..-1318.0866] | it/evals=2800/5795 eff=51.8999% N=400 Z=-3159.5(0.00%) | Like=-3140.75..-5.20 [-4912.3727..-1318.0866] | it/evals=2840/5921 eff=51.4400% N=400 Z=-2626.7(0.00%) | Like=-2605.14..-5.20 [-4912.3727..-1318.0866] | it/evals=2880/6090 eff=50.6151% N=400 Z=-2250.5(0.00%) | Like=-2196.70..-5.20 [-4912.3727..-1318.0866] | it/evals=2920/6213 eff=50.2322% N=400 Z=-1854.9(0.00%) | Like=-1817.78..-5.20 [-4912.3727..-1318.0866] | it/evals=2960/6341 eff=49.8233% N=400 Z=-1554.1(0.00%) | Like=-1539.31..-5.20 [-4912.3727..-1318.0866] | it/evals=3000/6475 eff=49.3827% N=400 Z=-1353.4(0.00%) | Like=-1332.34..-5.20 [-4912.3727..-1318.0866] | it/evals=3040/6598 eff=49.0481% N=400 Z=-1194.8(0.00%) | Like=-1163.63..-5.20 [-1310.7086..-300.6940] | it/evals=3060/6663 eff=48.8584% N=400 Z=-1066.7(0.00%) | Like=-1041.75..-5.20 [-1310.7086..-300.6940] | it/evals=3080/6717 eff=48.7573% N=400 Z=-876.0(0.00%) | Like=-855.57..-5.20 [-1310.7086..-300.6940] | it/evals=3120/6850 eff=48.3721% N=400 Z=-732.0(0.00%) | Like=-712.71..-5.20 [-1310.7086..-300.6940] | it/evals=3150/6928 eff=48.2537% N=400 Z=-689.5(0.00%) | Like=-670.52..-5.20 [-1310.7086..-300.6940] | it/evals=3160/6952 eff=48.2295% N=400 Z=-563.9(0.00%) | Like=-541.75..-5.20 [-1310.7086..-300.6940] | it/evals=3200/7038 eff=48.2073% N=400 Z=-459.2(0.00%) | Like=-445.06..-5.20 [-1310.7086..-300.6940] | it/evals=3240/7131 eff=48.1355% N=400 Z=-367.0(0.00%) | Like=-350.86..-5.20 [-1310.7086..-300.6940] | it/evals=3280/7228 eff=48.0375% N=400 Z=-320.3(0.00%) | Like=-306.59..-5.20 [-1310.7086..-300.6940] | it/evals=3320/7336 eff=47.8662% N=400 Z=-274.4(0.00%) | Like=-259.98..-5.20 [-298.9220..-89.8731] | it/evals=3358/7426 eff=47.7939% N=400 Z=-272.4(0.00%) | Like=-257.69..-5.20 [-298.9220..-89.8731] | it/evals=3360/7432 eff=47.7816% N=400 Z=-233.7(0.00%) | Like=-219.11..-5.20 [-298.9220..-89.8731] | it/evals=3400/7539 eff=47.6257% N=400 Z=-204.4(0.00%) | Like=-189.73..-5.20 [-298.9220..-89.8731] | it/evals=3434/7631 eff=47.4900% N=400 Z=-201.3(0.00%) | Like=-186.33..-5.20 [-298.9220..-89.8731] | it/evals=3440/7647 eff=47.4679% N=400 Z=-167.9(0.00%) | Like=-152.98..-5.11 [-298.9220..-89.8731] | it/evals=3480/7725 eff=47.5085% N=400 Z=-147.8(0.00%) | Like=-134.01..-5.11 [-298.9220..-89.8731] | it/evals=3510/7807 eff=47.3876% N=400 Z=-142.2(0.00%) | Like=-128.00..-5.11 [-298.9220..-89.8731] | it/evals=3520/7826 eff=47.4010% N=400 Z=-125.1(0.00%) | Like=-108.54..-5.11 [-298.9220..-89.8731] | it/evals=3555/7898 eff=47.4126% N=400 Z=-118.7(0.00%) | Like=-104.54..-5.11 [-298.9220..-89.8731] | it/evals=3560/7908 eff=47.4161% N=400 Z=-100.4(0.00%) | Like=-86.29..-5.11 [-89.6320..-30.8567] | it/evals=3599/8022 eff=47.2186% N=400 Z=-100.1(0.00%) | Like=-85.86..-5.11 [-89.6320..-30.8567] | it/evals=3600/8025 eff=47.2131% N=400 Z=-89.6(0.00%) | Like=-74.63..-5.11 [-89.6320..-30.8567] | it/evals=3632/8103 eff=47.1505% N=400 Z=-86.5(0.00%) | Like=-72.54..-5.11 [-89.6320..-30.8567] | it/evals=3640/8122 eff=47.1380% N=400 Z=-76.9(0.00%) | Like=-63.03..-5.11 [-89.6320..-30.8567] | it/evals=3666/8218 eff=46.8918% N=400 Z=-73.2(0.00%) | Like=-59.46..-5.11 [-89.6320..-30.8567] | it/evals=3680/8257 eff=46.8372% N=400 Z=-68.1(0.00%) | Like=-54.31..-5.11 [-89.6320..-30.8567] | it/evals=3700/8304 eff=46.8117% N=400 Z=-62.7(0.00%) | Like=-48.99..-5.11 [-89.6320..-30.8567] | it/evals=3720/8358 eff=46.7454% N=400 Z=-57.1(0.00%) | Like=-43.96..-5.11 [-89.6320..-30.8567] | it/evals=3753/8449 eff=46.6269% N=400 Z=-55.8(0.00%) | Like=-41.79..-5.11 [-89.6320..-30.8567] | it/evals=3760/8483 eff=46.5174% N=400 Z=-52.0(0.00%) | Like=-38.43..-5.11 [-89.6320..-30.8567] | it/evals=3779/8551 eff=46.3624% N=400 Z=-50.4(0.00%) | Like=-36.85..-5.11 [-89.6320..-30.8567] | it/evals=3792/8591 eff=46.2947% N=400 Z=-49.3(0.00%) | Like=-35.57..-5.11 [-89.6320..-30.8567] | it/evals=3800/8616 eff=46.2512% N=400 Z=-46.0(0.00%) | Like=-32.64..-5.11 [-89.6320..-30.8567] | it/evals=3824/8676 eff=46.2059% N=400 Z=-44.7(0.00%) | Like=-31.53..-5.11 [-89.6320..-30.8567] | it/evals=3840/8713 eff=46.1927% N=400 Z=-42.6(0.00%) | Like=-29.40..-5.11 [-30.3328..-14.1145] | it/evals=3859/8771 eff=46.0996% N=400 Z=-41.2(0.00%) | Like=-27.33..-5.11 [-30.3328..-14.1145] | it/evals=3874/8818 eff=46.0204% N=400 Z=-40.4(0.00%) | Like=-26.67..-5.11 [-30.3328..-14.1145] | it/evals=3880/8836 eff=45.9934% N=400 Z=-37.8(0.00%) | Like=-24.16..-5.11 [-30.3328..-14.1145] | it/evals=3904/8880 eff=46.0377% N=400 Z=-36.5(0.00%) | Like=-23.19..-5.11 [-30.3328..-14.1145] | it/evals=3917/8927 eff=45.9364% N=400 Z=-36.3(0.00%) | Like=-22.90..-5.11 [-30.3328..-14.1145] | it/evals=3920/8941 eff=45.8963% N=400 Z=-34.6(0.00%) | Like=-21.59..-5.11 [-30.3328..-14.1145] | it/evals=3943/8999 eff=45.8542% N=400 Z=-33.7(0.00%) | Like=-20.53..-5.11 [-30.3328..-14.1145] | it/evals=3960/9039 eff=45.8386% N=400 Z=-32.5(0.00%) | Like=-19.42..-5.11 [-30.3328..-14.1145] | it/evals=3982/9077 eff=45.8914% N=400 Z=-31.5(0.00%) | Like=-18.39..-5.11 [-30.3328..-14.1145] | it/evals=4000/9113 eff=45.9084% N=400 Z=-30.5(0.00%) | Like=-17.38..-5.11 [-30.3328..-14.1145] | it/evals=4019/9161 eff=45.8738% N=400 Z=-29.7(0.00%) | Like=-16.67..-5.11 [-30.3328..-14.1145] | it/evals=4037/9215 eff=45.7969% N=400 Z=-29.5(0.00%) | Like=-16.62..-5.11 [-30.3328..-14.1145] | it/evals=4040/9232 eff=45.7428% N=400 Z=-29.0(0.00%) | Like=-15.87..-5.11 [-30.3328..-14.1145] | it/evals=4050/9263 eff=45.6956% N=400 Z=-28.4(0.01%) | Like=-15.45..-5.11 [-30.3328..-14.1145] | it/evals=4063/9294 eff=45.6825% N=400 Z=-27.9(0.01%) | Like=-15.04..-5.11 [-30.3328..-14.1145] | it/evals=4078/9329 eff=45.6714% N=400 Z=-27.8(0.01%) | Like=-14.93..-5.11 [-30.3328..-14.1145] | it/evals=4080/9332 eff=45.6785% N=400 Z=-27.2(0.02%) | Like=-14.31..-5.11 [-30.3328..-14.1145] | it/evals=4098/9377 eff=45.6500% N=400 Z=-26.7(0.03%) | Like=-14.02..-5.11 [-14.0632..-9.8588] | it/evals=4112/9414 eff=45.6179% N=400 Z=-26.5(0.04%) | Like=-13.69..-5.11 [-14.0632..-9.8588] | it/evals=4120/9453 eff=45.5098% N=400 Z=-26.1(0.06%) | Like=-13.23..-5.11 [-14.0632..-9.8588] | it/evals=4134/9488 eff=45.4886% N=400 Z=-25.9(0.08%) | Like=-13.08..-5.11 [-14.0632..-9.8588] | it/evals=4141/9507 eff=45.4705% N=400 Z=-25.5(0.12%) | Like=-12.74..-5.11 [-14.0632..-9.8588] | it/evals=4155/9532 eff=45.4993% N=400 Z=-25.4(0.14%) | Like=-12.59..-5.11 [-14.0632..-9.8588] | it/evals=4160/9541 eff=45.5092% N=400 Z=-24.9(0.22%) | Like=-12.17..-5.11 [-14.0632..-9.8588] | it/evals=4180/9584 eff=45.5139% N=400 Z=-24.7(0.27%) | Like=-12.04..-5.11 [-14.0632..-9.8588] | it/evals=4190/9620 eff=45.4447% N=400 Z=-24.5(0.34%) | Like=-11.89..-5.11 [-14.0632..-9.8588] | it/evals=4200/9641 eff=45.4496% N=400 Z=-24.2(0.45%) | Like=-11.56..-5.11 [-14.0632..-9.8588] | it/evals=4213/9674 eff=45.4281% N=400 Z=-23.9(0.58%) | Like=-11.33..-5.11 [-14.0632..-9.8588] | it/evals=4227/9708 eff=45.4125% N=400 Z=-23.8(0.67%) | Like=-11.21..-5.11 [-14.0632..-9.8588] | it/evals=4234/9723 eff=45.4146% N=400 Z=-23.7(0.75%) | Like=-11.07..-5.11 [-14.0632..-9.8588] | it/evals=4240/9742 eff=45.3864% N=400 Z=-23.5(0.92%) | Like=-10.85..-5.11 [-14.0632..-9.8588] | it/evals=4252/9768 eff=45.3886% N=400 Z=-23.2(1.18%) | Like=-10.64..-5.11 [-14.0632..-9.8588] | it/evals=4265/9803 eff=45.3579% N=400 Z=-23.1(1.39%) | Like=-10.55..-5.11 [-14.0632..-9.8588] | it/evals=4275/9835 eff=45.3100% N=400 Z=-23.0(1.49%) | Like=-10.51..-5.11 [-14.0632..-9.8588] | it/evals=4280/9856 eff=45.2623% N=400 Z=-22.7(1.91%) | Like=-10.30..-5.11 [-14.0632..-9.8588] | it/evals=4298/9888 eff=45.2993% N=400 Z=-22.7(2.08%) | Like=-10.22..-5.11 [-14.0632..-9.8588] | it/evals=4304/9921 eff=45.2053% N=400 Z=-22.5(2.41%) | Like=-10.13..-5.11 [-14.0632..-9.8588] | it/evals=4316/9955 eff=45.1701% N=400 Z=-22.5(2.53%) | Like=-10.10..-5.11 [-14.0632..-9.8588] | it/evals=4320/9973 eff=45.1269% N=400 Z=-22.3(2.83%) | Like=-9.97..-5.11 [-14.0632..-9.8588] | it/evals=4331/9993 eff=45.1475% N=400 Z=-22.2(3.41%) | Like=-9.83..-5.11 [-9.8567..-9.3412] | it/evals=4347/10027 eff=45.1543% N=400 Z=-22.1(3.63%) | Like=-9.78..-5.11 [-9.8567..-9.3412] | it/evals=4355/10042 eff=45.1670% N=400 Z=-22.0(3.82%) | Like=-9.71..-5.11 [-9.8567..-9.3412] | it/evals=4360/10062 eff=45.1252% N=400 Z=-21.9(4.23%) | Like=-9.64..-5.11 [-9.8567..-9.3412] | it/evals=4370/10086 eff=45.1167% N=400 Z=-21.8(4.53%) | Like=-9.57..-5.11 [-9.8567..-9.3412] | it/evals=4379/10116 eff=45.0700% N=400 Z=-21.8(4.78%) | Like=-9.50..-5.11 [-9.8567..-9.3412] | it/evals=4386/10145 eff=45.0077% N=400 Z=-21.7(5.16%) | Like=-9.44..-5.11 [-9.8567..-9.3412] | it/evals=4394/10169 eff=44.9790% N=400 Z=-21.6(5.45%) | Like=-9.36..-5.11 [-9.8567..-9.3412] | it/evals=4400/10185 eff=44.9668% N=400 Z=-21.6(5.75%) | Like=-9.29..-5.11 [-9.3145..-9.1773] | it/evals=4406/10212 eff=44.9042% N=400 Z=-21.5(5.89%) | Like=-9.25..-5.11 [-9.3145..-9.1773] | it/evals=4412/10227 eff=44.8967% N=400 Z=-21.5(6.24%) | Like=-9.20..-5.05 [-9.3145..-9.1773] | it/evals=4421/10253 eff=44.8696% N=400 Z=-21.3(6.81%) | Like=-9.16..-5.05 [-9.1770..-9.0766] | it/evals=4435/10279 eff=44.8932% N=400 Z=-21.3(7.06%) | Like=-9.15..-5.05 [-9.1770..-9.0766] | it/evals=4440/10292 eff=44.8848% N=400 Z=-21.3(7.30%) | Like=-9.11..-5.05 [-9.1770..-9.0766] | it/evals=4448/10316 eff=44.8568% N=400 Z=-21.2(7.77%) | Like=-9.08..-5.05 [-9.1770..-9.0766] | it/evals=4456/10337 eff=44.8425% N=400 Z=-21.1(8.29%) | Like=-9.04..-5.05 [-9.0765..-8.9720] | it/evals=4465/10366 eff=44.8023% N=400 Z=-21.1(8.69%) | Like=-9.01..-5.05 [-9.0765..-8.9720] | it/evals=4472/10387 eff=44.7782% N=400 Z=-21.1(9.15%) | Like=-8.97..-5.05 [-9.0765..-8.9720] | it/evals=4480/10401 eff=44.7955% N=400 Z=-21.0(9.46%) | Like=-8.93..-4.93 [-8.9377..-8.9033] | it/evals=4489/10435 eff=44.7334% N=400 Z=-20.9(10.19%) | Like=-8.89..-4.93 [-8.8865..-8.8784]*| it/evals=4500/10460 eff=44.7316% N=400 Z=-20.9(10.51%) | Like=-8.86..-4.93 [-8.8556..-8.8493]*| it/evals=4509/10487 eff=44.7011% N=400 Z=-20.8(11.01%) | Like=-8.82..-4.93 [-8.8202..-8.8174]*| it/evals=4517/10523 eff=44.6212% N=400 Z=-20.8(11.22%) | Like=-8.80..-4.93 [-8.8032..-8.8027]*| it/evals=4520/10535 eff=44.5979% N=400 Z=-20.8(11.45%) | Like=-8.79..-4.93 [-8.7851..-8.7834]*| it/evals=4527/10556 eff=44.5746% N=400 Z=-20.8(11.55%) | Like=-8.77..-4.93 [-8.7681..-8.7566] | it/evals=4535/10584 eff=44.5306% N=400 Z=-20.7(11.73%) | Like=-8.72..-4.93 [-8.7376..-8.7031] | it/evals=4547/10615 eff=44.5130% N=400 Z=-20.7(12.30%) | Like=-8.70..-4.93 [-8.7022..-8.6953]*| it/evals=4555/10643 eff=44.4694% N=400 Z=-20.6(12.57%) | Like=-8.69..-4.93 [-8.6887..-8.6866]*| it/evals=4560/10649 eff=44.4921% N=400 Z=-20.6(13.11%) | Like=-8.65..-4.93 [-8.6483..-8.6446]*| it/evals=4568/10674 eff=44.4617% N=400 Z=-20.6(13.50%) | Like=-8.62..-4.93 [-8.6164..-8.6085]*| it/evals=4574/10697 eff=44.4207% N=400 Z=-20.5(14.01%) | Like=-8.59..-4.93 [-8.5888..-8.5886]*| it/evals=4582/10731 eff=44.3520% N=400 Z=-20.5(14.66%) | Like=-8.57..-4.93 [-8.5655..-8.5630]*| it/evals=4591/10752 eff=44.3489% N=400 Z=-20.5(15.00%) | Like=-8.53..-4.93 [-8.5338..-8.5277]*| it/evals=4597/10769 eff=44.3341% N=400 Z=-20.5(15.15%) | Like=-8.52..-4.93 [-8.5247..-8.5234]*| it/evals=4599/10789 eff=44.2680% N=400 Z=-20.5(15.22%) | Like=-8.52..-4.93 [-8.5234..-8.5136]*| it/evals=4600/10794 eff=44.2563% N=400 Z=-20.4(15.72%) | Like=-8.49..-4.93 [-8.4869..-8.4828]*| it/evals=4610/10822 eff=44.2334% N=400 Z=-20.4(16.23%) | Like=-8.47..-4.93 [-8.4681..-8.4662]*| it/evals=4617/10843 eff=44.2114% N=400 Z=-20.4(16.61%) | Like=-8.44..-4.93 [-8.4407..-8.4344]*| it/evals=4626/10868 eff=44.1918% N=400 Z=-20.4(16.76%) | Like=-8.41..-4.93 [-8.4249..-8.4139] | it/evals=4632/10889 eff=44.1605% N=400 Z=-20.3(17.06%) | Like=-8.40..-4.93 [-8.4036..-8.4020]*| it/evals=4636/10906 eff=44.1272% N=400 Z=-20.3(17.31%) | Like=-8.40..-4.93 [-8.3973..-8.3949]*| it/evals=4639/10922 eff=44.0886% N=400 Z=-20.3(17.38%) | Like=-8.39..-4.93 [-8.3949..-8.3946]*| it/evals=4640/10925 eff=44.0855% N=400 Z=-20.3(17.58%) | Like=-8.37..-4.93 [-8.3691..-8.3658]*| it/evals=4648/10955 eff=44.0360% N=400 Z=-20.3(18.15%) | Like=-8.35..-4.93 [-8.3498..-8.3482]*| it/evals=4656/10978 eff=44.0159% N=400 Z=-20.3(18.21%) | Like=-8.33..-4.93 [-8.3329..-8.3323]*| it/evals=4661/10996 eff=43.9883% N=400 Z=-20.2(18.66%) | Like=-8.31..-4.93 [-8.3149..-8.3142]*| it/evals=4667/11027 eff=43.9164% N=400 Z=-20.2(18.96%) | Like=-8.30..-4.93 [-8.3000..-8.2992]*| it/evals=4671/11045 eff=43.8798% N=400 Z=-20.2(19.44%) | Like=-8.28..-4.93 [-8.2790..-8.2648] | it/evals=4679/11062 eff=43.8848% N=400 Z=-20.2(19.52%) | Like=-8.26..-4.93 [-8.2790..-8.2648] | it/evals=4680/11065 eff=43.8819% N=400 Z=-20.2(20.00%) | Like=-8.25..-4.93 [-8.2504..-8.2467]*| it/evals=4688/11088 eff=43.8623% N=400 Z=-20.2(20.46%) | Like=-8.24..-4.93 [-8.2378..-8.2357]*| it/evals=4694/11106 eff=43.8446% N=400 Z=-20.1(20.91%) | Like=-8.22..-4.93 [-8.2223..-8.2201]*| it/evals=4700/11122 eff=43.8351% N=400 Z=-20.1(21.15%) | Like=-8.20..-4.93 [-8.2016..-8.2008]*| it/evals=4703/11145 eff=43.7692% N=400 Z=-20.1(21.43%) | Like=-8.19..-4.93 [-8.1937..-8.1930]*| it/evals=4707/11165 eff=43.7250% N=400 Z=-20.1(21.47%) | Like=-8.19..-4.87 [-8.1930..-8.1819] | it/evals=4708/11179 eff=43.6775% N=400 Z=-20.1(21.75%) | Like=-8.16..-4.87 [-8.1627..-8.1582]*| it/evals=4718/11199 eff=43.6892% N=400 Z=-20.1(21.90%) | Like=-8.16..-4.87 [-8.1579..-8.1571]*| it/evals=4720/11211 eff=43.6592% N=400 Z=-20.1(22.13%) | Like=-8.15..-4.87 [-8.1507..-8.1482]*| it/evals=4723/11223 eff=43.6385% N=400 Z=-20.1(22.30%) | Like=-8.14..-4.87 [-8.1438..-8.1418]*| it/evals=4725/11238 eff=43.5966% N=400 Z=-20.1(22.55%) | Like=-8.14..-4.87 [-8.1382..-8.1349]*| it/evals=4728/11262 eff=43.5279% N=400 Z=-20.0(22.97%) | Like=-8.13..-4.87 [-8.1293..-8.1278]*| it/evals=4734/11275 eff=43.5310% N=400 Z=-20.0(23.42%) | Like=-8.11..-4.87 [-8.1061..-8.1041]*| it/evals=4743/11303 eff=43.5018% N=400 Z=-20.0(23.76%) | Like=-8.09..-4.87 [-8.0926..-8.0907]*| it/evals=4747/11326 eff=43.4468% N=400 Z=-20.0(24.18%) | Like=-8.08..-4.87 [-8.0789..-8.0734]*| it/evals=4753/11347 eff=43.4183% N=400 Z=-20.0(24.43%) | Like=-8.06..-4.87 [-8.0570..-8.0551]*| it/evals=4757/11369 eff=43.3677% N=400 Z=-20.0(24.52%) | Like=-8.05..-4.87 [-8.0535..-8.0531]*| it/evals=4760/11384 eff=43.3358% N=400 Z=-20.0(24.92%) | Like=-8.04..-4.87 [-8.0416..-8.0404]*| it/evals=4767/11407 eff=43.3088% N=400 Z=-19.9(25.16%) | Like=-8.04..-4.87 [-8.0351..-8.0347]*| it/evals=4770/11417 eff=43.2967% N=400 Z=-19.9(27.33%) | Like=-7.98..-4.87 [-7.9760..-7.9742]*| it/evals=4800/11523 eff=43.1538% N=400 Z=-19.8(29.56%) | Like=-7.89..-4.87 [-7.8912..-7.8909]*| it/evals=4840/11637 eff=43.0720% N=400 Z=-19.7(31.82%) | Like=-7.80..-4.87 [-7.7984..-7.7983]*| it/evals=4880/11749 eff=42.9994% N=400 Z=-19.6(34.42%) | Like=-7.70..-4.87 [-7.6970..-7.6952]*| it/evals=4920/11872 eff=42.8870% N=400 Z=-19.6(36.69%) | Like=-7.65..-4.87 [-7.6510..-7.6487]*| it/evals=4950/11971 eff=42.7794% N=400 Z=-19.6(37.38%) | Like=-7.63..-4.87 [-7.6306..-7.6254]*| it/evals=4960/12011 eff=42.7181% N=400 Z=-19.5(39.11%) | Like=-7.56..-4.87 [-7.5590..-7.5564]*| it/evals=5000/12149 eff=42.5568% N=400 Z=-19.5(41.35%) | Like=-7.52..-4.79 [-7.5208..-7.5185]*| it/evals=5037/12261 eff=42.4669% N=400 Z=-19.5(41.62%) | Like=-7.52..-4.79 [-7.5166..-7.5158]*| it/evals=5040/12269 eff=42.4636% N=400 Z=-19.4(43.18%) | Like=-7.46..-4.79 [-7.4638..-7.4628]*| it/evals=5071/12384 eff=42.3148% N=400 Z=-19.4(43.90%) | Like=-7.45..-4.79 [-7.4532..-7.4528]*| it/evals=5080/12421 eff=42.2594% N=400 Z=-19.4(45.94%) | Like=-7.42..-4.79 [-7.4201..-7.4190]*| it/evals=5109/12541 eff=42.0806% N=400 Z=-19.4(46.53%) | Like=-7.40..-4.79 [-7.4006..-7.4002]*| it/evals=5120/12582 eff=42.0292% N=400 Z=-19.4(46.89%) | Like=-7.39..-4.79 [-7.3903..-7.3821]*| it/evals=5130/12615 eff=41.9975% N=400 Z=-19.3(47.97%) | Like=-7.34..-4.79 [-7.3401..-7.3391]*| it/evals=5160/12717 eff=41.8933% N=400 Z=-19.3(49.00%) | Like=-7.29..-4.79 [-7.2895..-7.2876]*| it/evals=5193/12831 eff=41.7746% N=400 Z=-19.3(49.30%) | Like=-7.28..-4.79 [-7.2800..-7.2798]*| it/evals=5200/12855 eff=41.7503% N=400 Z=-19.3(50.31%) | Like=-7.25..-4.79 [-7.2476..-7.2457]*| it/evals=5224/12928 eff=41.6986% N=400 Z=-19.2(51.04%) | Like=-7.22..-4.79 [-7.2249..-7.2200]*| it/evals=5240/12971 eff=41.6832% N=400 Z=-19.2(52.13%) | Like=-7.18..-4.79 [-7.1810..-7.1805]*| it/evals=5274/13076 eff=41.6062% N=400 Z=-19.2(52.37%) | Like=-7.17..-4.79 [-7.1682..-7.1681]*| it/evals=5280/13091 eff=41.6043% N=400 Z=-19.2(52.68%) | Like=-7.14..-4.77 [-7.1416..-7.1416]*| it/evals=5297/13156 eff=41.5256% N=400 Z=-19.2(52.85%) | Like=-7.12..-4.77 [-7.1162..-7.1161]*| it/evals=5310/13200 eff=41.4844% N=400 Z=-19.2(53.47%) | Like=-7.10..-4.77 [-7.0977..-7.0973]*| it/evals=5320/13224 eff=41.4847% N=400 Z=-19.2(54.94%) | Like=-7.05..-4.77 [-7.0507..-7.0502]*| it/evals=5360/13334 eff=41.4412% N=400 Z=-19.1(56.57%) | Like=-6.99..-4.77 [-6.9914..-6.9893]*| it/evals=5400/13412 eff=41.5002% N=400 Z=-19.1(58.15%) | Like=-6.92..-4.77 [-6.9184..-6.9182]*| it/evals=5440/13478 eff=41.5966% N=400 Z=-19.1(59.46%) | Like=-6.81..-4.77 [-6.8070..-6.8051]*| it/evals=5480/13552 eff=41.6667% N=400 Z=-19.1(61.24%) | Like=-6.61..-4.77 [-6.6105..-6.6076]*| it/evals=5520/13608 eff=41.7929% N=400 Z=-19.0(62.75%) | Like=-6.47..-4.77 [-6.4671..-6.4663]*| it/evals=5560/13669 eff=41.9022% N=400 Z=-19.0(64.14%) | Like=-6.37..-4.77 [-6.3693..-6.3689]*| it/evals=5595/13733 eff=41.9635% N=400 Z=-19.0(64.35%) | Like=-6.34..-4.77 [-6.3407..-6.3406]*| it/evals=5600/13742 eff=41.9727% N=400 Z=-19.0(66.11%) | Like=-6.25..-4.77 [-6.2545..-6.2519]*| it/evals=5640/13815 eff=42.0425% N=400 Z=-19.0(67.14%) | Like=-6.16..-4.77 [-6.1605..-6.1596]*| it/evals=5670/13868 eff=42.0998% N=400 Z=-19.0(67.62%) | Like=-6.14..-4.77 [-6.1350..-6.1325]*| it/evals=5680/13884 eff=42.1240% N=400 Z=-18.9(69.13%) | Like=-6.06..-4.73 [-6.0565..-6.0563]*| it/evals=5716/13950 eff=42.1845% N=400 Z=-18.9(69.34%) | Like=-6.05..-4.73 [-6.0545..-6.0502]*| it/evals=5720/13956 eff=42.1953% N=400 Z=-18.9(70.56%) | Like=-6.00..-4.73 [-5.9976..-5.9969]*| it/evals=5750/14020 eff=42.2173% N=400 Z=-18.9(70.94%) | Like=-5.98..-4.73 [-5.9797..-5.9792]*| it/evals=5760/14045 eff=42.2133% N=400 Z=-18.9(72.06%) | Like=-5.93..-4.73 [-5.9330..-5.9289]*| it/evals=5787/14091 eff=42.2686% N=400 Z=-18.9(72.61%) | Like=-5.91..-4.73 [-5.9085..-5.9069]*| it/evals=5800/14112 eff=42.2987% N=400 Z=-18.9(73.29%) | Like=-5.87..-4.73 [-5.8673..-5.8669]*| it/evals=5819/14145 eff=42.3354% N=400 Z=-18.9(74.05%) | Like=-5.83..-4.73 [-5.8273..-5.8166] | it/evals=5840/14178 eff=42.3864% N=400 Z=-18.9(74.64%) | Like=-5.80..-4.73 [-5.7956..-5.7947]*| it/evals=5852/14199 eff=42.4089% N=400 Z=-18.8(75.34%) | Like=-5.75..-4.68 [-5.7469..-5.7457]*| it/evals=5874/14229 eff=42.4760% N=400 Z=-18.8(75.54%) | Like=-5.74..-4.68 [-5.7368..-5.7337]*| it/evals=5880/14243 eff=42.4763% N=400 Z=-18.8(76.33%) | Like=-5.70..-4.64 [-5.7037..-5.7023]*| it/evals=5903/14282 eff=42.5227% N=400 Z=-18.8(76.93%) | Like=-5.67..-4.64 [-5.6662..-5.6660]*| it/evals=5919/14317 eff=42.5307% N=400 Z=-18.8(76.98%) | Like=-5.67..-4.64 [-5.6660..-5.6653]*| it/evals=5920/14319 eff=42.5318% N=400 Z=-18.8(77.69%) | Like=-5.64..-4.64 [-5.6392..-5.6369]*| it/evals=5940/14346 eff=42.5929% N=400 Z=-18.8(78.30%) | Like=-5.60..-4.64 [-5.5965..-5.5936]*| it/evals=5960/14374 eff=42.6506% N=400 Z=-18.8(78.68%) | Like=-5.58..-4.64 [-5.5807..-5.5787]*| it/evals=5969/14398 eff=42.6418% N=400 Z=-18.8(79.19%) | Like=-5.56..-4.64 [-5.5582..-5.5544]*| it/evals=5982/14428 eff=42.6433% N=400 Z=-18.8(79.89%) | Like=-5.53..-4.64 [-5.5265..-5.5265]*| it/evals=6000/14456 eff=42.6864% N=400 Z=-18.8(80.51%) | Like=-5.51..-4.62 [-5.5070..-5.5069]*| it/evals=6021/14493 eff=42.7233% N=400 Z=-18.8(80.91%) | Like=-5.49..-4.62 [-5.4948..-5.4896]*| it/evals=6034/14519 eff=42.7367% N=400 Z=-18.8(81.10%) | Like=-5.48..-4.62 [-5.4849..-5.4844]*| it/evals=6040/14529 eff=42.7490% N=400 Z=-18.8(81.51%) | Like=-5.46..-4.62 [-5.4624..-5.4588]*| it/evals=6054/14552 eff=42.7784% N=400 Z=-18.8(82.12%) | Like=-5.43..-4.62 [-5.4316..-5.4312]*| it/evals=6072/14584 eff=42.8088% N=400 Z=-18.8(82.30%) | Like=-5.41..-4.62 [-5.4122..-5.4080]*| it/evals=6080/14600 eff=42.8169% N=400 Z=-18.7(82.68%) | Like=-5.39..-4.50 [-5.3909..-5.3902]*| it/evals=6097/14629 eff=42.8491% N=400 Z=-18.7(83.04%) | Like=-5.37..-4.50 [-5.3695..-5.3663]*| it/evals=6109/14653 eff=42.8612% N=400 Z=-18.7(83.36%) | Like=-5.36..-4.50 [-5.3558..-5.3558]*| it/evals=6120/14671 eff=42.8842% N=400 Z=-18.7(83.65%) | Like=-5.34..-4.50 [-5.3398..-5.3389]*| it/evals=6131/14697 eff=42.8831% N=400 Z=-18.7(84.02%) | Like=-5.33..-4.47 [-5.3278..-5.3274]*| it/evals=6144/14713 eff=42.9260% N=400 Z=-18.7(84.32%) | Like=-5.32..-4.47 [-5.3196..-5.3193]*| it/evals=6153/14729 eff=42.9409% N=400 Z=-18.7(84.54%) | Like=-5.30..-4.47 [-5.3031..-5.3025]*| it/evals=6160/14741 eff=42.9538% N=400 Z=-18.7(84.93%) | Like=-5.28..-4.47 [-5.2837..-5.2828]*| it/evals=6174/14762 eff=42.9884% N=400 Z=-18.7(85.25%) | Like=-5.28..-4.47 [-5.2758..-5.2748]*| it/evals=6185/14779 eff=43.0141% N=400 Z=-18.7(85.64%) | Like=-5.26..-4.47 [-5.2589..-5.2586]*| it/evals=6200/14806 eff=43.0376% N=400 Z=-18.7(85.90%) | Like=-5.24..-4.47 [-5.2428..-5.2427]*| it/evals=6210/14822 eff=43.0592% N=400 Z=-18.7(86.19%) | Like=-5.24..-4.47 [-5.2354..-5.2347]*| it/evals=6220/14848 eff=43.0509% N=400 Z=-18.7(86.55%) | Like=-5.22..-4.47 [-5.2204..-5.2198]*| it/evals=6235/14880 eff=43.0594% N=400 Z=-18.7(86.66%) | Like=-5.22..-4.47 [-5.2177..-5.2162]*| it/evals=6240/14900 eff=43.0345% N=400 Z=-18.7(87.04%) | Like=-5.21..-4.47 [-5.2057..-5.2054]*| it/evals=6256/14929 eff=43.0587% N=400 Z=-18.7(87.33%) | Like=-5.19..-4.47 [-5.1896..-5.1895]*| it/evals=6269/14953 eff=43.0770% N=400 Z=-18.7(87.53%) | Like=-5.18..-4.47 [-5.1776..-5.1775]*| it/evals=6278/14971 eff=43.0856% N=400 Z=-18.7(87.58%) | Like=-5.18..-4.47 [-5.1758..-5.1754]*| it/evals=6280/14974 eff=43.0904% N=400 Z=-18.7(87.82%) | Like=-5.17..-4.47 [-5.1684..-5.1679]*| it/evals=6290/14995 eff=43.0970% N=400 Z=-18.7(87.97%) | Like=-5.17..-4.47 [-5.1651..-5.1649]*| it/evals=6297/15010 eff=43.1006% N=400 Z=-18.7(88.24%) | Like=-5.16..-4.47 [-5.1572..-5.1553]*| it/evals=6308/15030 eff=43.1169% N=400 Z=-18.7(88.52%) | Like=-5.15..-4.47 [-5.1456..-5.1440]*| it/evals=6320/15050 eff=43.1399% N=400 Z=-18.7(88.70%) | Like=-5.13..-4.29 [-5.1340..-5.1329]*| it/evals=6329/15078 eff=43.1190% N=400 Z=-18.7(88.88%) | Like=-5.13..-4.29 [-5.1293..-5.1288]*| it/evals=6337/15101 eff=43.1059% N=400 Z=-18.7(89.07%) | Like=-5.12..-4.29 [-5.1226..-5.1226]*| it/evals=6346/15124 eff=43.0997% N=400 Z=-18.7(89.27%) | Like=-5.11..-4.29 [-5.1145..-5.1122]*| it/evals=6356/15146 eff=43.1032% N=400 Z=-18.7(89.33%) | Like=-5.11..-4.28 [-5.1088..-5.1070]*| it/evals=6360/15154 eff=43.1070% N=400 Z=-18.7(89.49%) | Like=-5.10..-4.28 [-5.1034..-5.1025]*| it/evals=6368/15172 eff=43.1086% N=400 Z=-18.7(89.66%) | Like=-5.09..-4.28 [-5.0939..-5.0938]*| it/evals=6376/15188 eff=43.1160% N=400 Z=-18.7(89.79%) | Like=-5.09..-4.28 [-5.0913..-5.0901]*| it/evals=6383/15204 eff=43.1167% N=400 Z=-18.7(89.93%) | Like=-5.09..-4.28 [-5.0874..-5.0869]*| it/evals=6390/15221 eff=43.1145% N=400 Z=-18.7(90.07%) | Like=-5.08..-4.28 [-5.0808..-5.0802]*| it/evals=6397/15240 eff=43.1065% N=400 Z=-18.7(90.13%) | Like=-5.08..-4.28 [-5.0798..-5.0794]*| it/evals=6400/15261 eff=43.0657% N=400 Z=-18.7(90.40%) | Like=-5.07..-4.28 [-5.0698..-5.0690]*| it/evals=6415/15286 eff=43.0942% N=400 Z=-18.7(90.51%) | Like=-5.06..-4.28 [-5.0640..-5.0639]*| it/evals=6421/15312 eff=43.0593% N=400 Z=-18.6(90.76%) | Like=-5.05..-4.28 [-5.0480..-5.0478]*| it/evals=6434/15334 eff=43.0829% N=400 Z=-18.6(90.87%) | Like=-5.04..-4.28 [-5.0440..-5.0438]*| it/evals=6440/15343 eff=43.0971% N=400 Z=-18.6(90.91%) | Like=-5.04..-4.28 [-5.0437..-5.0428]*| it/evals=6442/15361 eff=43.0586% N=400 Z=-18.6(91.04%) | Like=-5.04..-4.28 [-5.0386..-5.0377]*| it/evals=6449/15381 eff=43.0479% N=400 Z=-18.6(91.15%) | Like=-5.04..-4.28 [-5.0361..-5.0360]*| it/evals=6455/15401 eff=43.0305% N=400 Z=-18.6(91.29%) | Like=-5.03..-4.28 [-5.0292..-5.0269]*| it/evals=6463/15414 eff=43.0465% N=400 Z=-18.6(91.43%) | Like=-5.02..-4.28 [-5.0213..-5.0209]*| it/evals=6471/15431 eff=43.0510% N=400 Z=-18.6(91.55%) | Like=-5.02..-4.28 [-5.0174..-5.0170]*| it/evals=6478/15446 eff=43.0546% N=400 Z=-18.6(91.58%) | Like=-5.02..-4.18 [-5.0161..-5.0153]*| it/evals=6480/15450 eff=43.0565% N=400 Z=-18.6(91.72%) | Like=-5.01..-4.18 [-5.0096..-5.0089]*| it/evals=6491/15479 eff=43.0466% N=400 Z=-18.6(91.76%) | Like=-5.01..-4.18 [-5.0088..-5.0085]*| it/evals=6494/15496 eff=43.0180% N=400 Z=-18.6(91.81%) | Like=-5.01..-4.18 [-5.0082..-5.0070]*| it/evals=6497/15521 eff=42.9667% N=400 Z=-18.6(91.89%) | Like=-5.01..-4.18 [-5.0060..-5.0036]*| it/evals=6502/15545 eff=42.9317% N=400 Z=-18.6(92.01%) | Like=-4.99..-4.18 [-4.9911..-4.9885]*| it/evals=6511/15564 eff=42.9372% N=400 Z=-18.6(92.09%) | Like=-4.98..-4.13 [-4.9850..-4.9843]*| it/evals=6516/15585 eff=42.9108% N=400 Z=-18.6(92.13%) | Like=-4.98..-4.13 [-4.9835..-4.9829]*| it/evals=6520/15595 eff=42.9089% N=400 Z=-18.6(92.22%) | Like=-4.98..-4.13 [-4.9807..-4.9790]*| it/evals=6525/15609 eff=42.9022% N=400 Z=-18.6(92.27%) | Like=-4.98..-4.13 [-4.9770..-4.9766]*| it/evals=6528/15625 eff=42.8768% N=400 Z=-18.6(92.41%) | Like=-4.97..-4.13 [-4.9726..-4.9710]*| it/evals=6537/15646 eff=42.8768% N=400 Z=-18.6(92.51%) | Like=-4.97..-4.13 [-4.9674..-4.9673]*| it/evals=6544/15665 eff=42.8693% N=400 Z=-18.6(92.56%) | Like=-4.96..-4.13 [-4.9646..-4.9644]*| it/evals=6548/15686 eff=42.8366% N=400 Z=-18.6(92.65%) | Like=-4.96..-4.13 [-4.9619..-4.9615]*| it/evals=6554/15698 eff=42.8422% N=400 Z=-18.6(92.72%) | Like=-4.96..-4.13 [-4.9598..-4.9597]*| it/evals=6559/15716 eff=42.8245% N=400 Z=-18.6(92.73%) | Like=-4.96..-4.13 [-4.9597..-4.9596]*| it/evals=6560/15723 eff=42.8115% N=400 Z=-18.6(92.76%) | Like=-4.96..-4.13 [-4.9591..-4.9590]*| it/evals=6562/15734 eff=42.7938% N=400 Z=-18.6(92.87%) | Like=-4.96..-4.13 [-4.9562..-4.9561]*| it/evals=6569/15750 eff=42.7948% N=400 Z=-18.6(92.88%) | Like=-4.96..-4.13 [-4.9561..-4.9559]*| it/evals=6570/15755 eff=42.7874% N=400 Z=-18.6(93.29%) | Like=-4.94..-4.13 [-4.9402..-4.9400]*| it/evals=6600/15832 eff=42.7683% N=400 Z=-18.6(93.82%) | Like=-4.92..-4.13 [-4.9163..-4.9160]*| it/evals=6640/15949 eff=42.7037% N=400 Z=-18.6(94.30%) | Like=-4.89..-4.13 [-4.8867..-4.8863]*| it/evals=6680/16038 eff=42.7165% N=400 Z=-18.6(94.75%) | Like=-4.87..-4.13 [-4.8681..-4.8661]*| it/evals=6720/16183 eff=42.5775% N=400 Z=-18.6(95.15%) | Like=-4.85..-4.13 [-4.8456..-4.8451]*| it/evals=6758/16309 eff=42.4791% N=400 Z=-18.6(95.16%) | Like=-4.84..-4.13 [-4.8444..-4.8444]*| it/evals=6760/16309 eff=42.4917% N=400 Z=-18.6(95.53%) | Like=-4.82..-4.10 [-4.8229..-4.8226]*| it/evals=6800/16412 eff=42.4681% N=400 Z=-18.6(95.67%) | Like=-4.82..-4.07 [-4.8155..-4.8146]*| it/evals=6815/16472 eff=42.4029% N=400 Z=-18.6(95.87%) | Like=-4.81..-4.07 [-4.8060..-4.8060]*| it/evals=6840/16535 eff=42.3923% N=400 Z=-18.6(96.18%) | Like=-4.79..-3.94 [-4.7871..-4.7868]*| it/evals=6880/16635 eff=42.3776% N=400 Z=-18.6(96.42%) | Like=-4.77..-3.94 [-4.7714..-4.7713]*| it/evals=6920/16752 eff=42.3190% N=400 Z=-18.6(96.48%) | Like=-4.77..-3.89 [-4.7682..-4.7680]*| it/evals=6930/16776 eff=42.3180% N=400 Z=-18.6(96.65%) | Like=-4.76..-3.89 [-4.7575..-4.7572]*| it/evals=6960/16850 eff=42.3100% N=400 Z=-18.6(96.88%) | Like=-4.74..-3.84 [-4.7432..-4.7429]*| it/evals=7000/16951 eff=42.2935% N=400 Z=-18.6(97.07%) | Like=-4.73..-3.81 [-4.7303..-4.7302]*| it/evals=7040/17039 eff=42.3102% N=400 Z=-18.6(97.30%) | Like=-4.71..-3.81 [-4.7142..-4.7141]*| it/evals=7080/17121 eff=42.3420% N=400 Z=-18.6(97.49%) | Like=-4.70..-3.81 [-4.7022..-4.7015]*| it/evals=7120/17229 eff=42.3079% N=400 Z=-18.6(97.65%) | Like=-4.68..-3.80 [-4.6829..-4.6828]*| it/evals=7160/17321 eff=42.3143% N=400 Z=-18.6(97.78%) | Like=-4.66..-3.72 [-4.6614..-4.6612]*| it/evals=7200/17401 eff=42.3504% N=400 Z=-18.6(97.91%) | Like=-4.64..-3.72 [-4.6406..-4.6403]*| it/evals=7240/17478 eff=42.3937% N=400 Z=-18.6(98.02%) | Like=-4.62..-3.67 [-4.6169..-4.6160]*| it/evals=7280/17550 eff=42.4490% N=400 Z=-18.6(98.13%) | Like=-4.58..-3.65 [-4.5783..-4.5781]*| it/evals=7317/17609 eff=42.5184% N=400 Z=-18.6(98.14%) | Like=-4.57..-3.65 [-4.5747..-4.5746]*| it/evals=7320/17620 eff=42.5087% N=400 Z=-18.6(98.26%) | Like=-4.53..-3.65 [-4.5280..-4.5253]*| it/evals=7360/17688 eff=42.5729% N=400 Z=-18.6(98.37%) | Like=-4.48..-3.64 [-4.4780..-4.4749]*| it/evals=7400/17753 eff=42.6439% N=400 Z=-18.6(98.48%) | Like=-4.43..-3.64 [-4.4267..-4.4263]*| it/evals=7440/17834 eff=42.6752% N=400 Z=-18.6(98.58%) | Like=-4.39..-3.64 [-4.3906..-4.3900]*| it/evals=7480/17895 eff=42.7551% N=400 Z=-18.6(98.67%) | Like=-4.35..-3.57 [-4.3458..-4.3446]*| it/evals=7520/17985 eff=42.7637% N=400 Z=-18.6(98.76%) | Like=-4.31..-3.53 [-4.3055..-4.3052]*| it/evals=7560/18055 eff=42.8207% N=400 Z=-18.6(98.84%) | Like=-4.27..-3.51 [-4.2667..-4.2665]*| it/evals=7600/18127 eff=42.8725% N=400 Z=-18.6(98.90%) | Like=-4.23..-3.51 [-4.2323..-4.2322]*| it/evals=7629/18196 eff=42.8692% N=400 Z=-18.6(98.92%) | Like=-4.22..-3.51 [-4.2205..-4.2173]*| it/evals=7640/18220 eff=42.8732% N=400 Z=-18.6(98.94%) | Like=-4.21..-3.51 [-4.2076..-4.2065]*| it/evals=7650/18242 eff=42.8764% N=400 Z=-18.6(98.99%) | Like=-4.18..-3.51 [-4.1829..-4.1826]*| it/evals=7680/18285 eff=42.9410% N=400 [ultranest] Explored until L=-4 [ultranest] Likelihood function evaluations: 18296 [ultranest] logZ = -18.54 +- 0.1012 [ultranest] Effective samples strategy satisfied (ESS = 2455.4, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [ultranest] logZ error budget: single: 0.17 bs:0.10 tail:0.01 total:0.10 required:<0.50 [ultranest] done iterating. logZ = -18.543 +- 0.242 single instance: logZ = -18.543 +- 0.170 bootstrapped : logZ = -18.537 +- 0.242 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 133 iterations a : 0.99616│ ▁▁▁▁▁▁▁▁▂▂▃▄▄▆▆▆▇▇▇▇▅▅▄▂▂▁▁▁▁▁▁▁▁▁▁ ▁ │1.00448 1.00001 +- 0.00096 aux_logweight : -9.5 │ ▁▁▂▂▂▂▃▃▄▃▅▅▅▅▇▂▁▁▂▂▂▂▃▄▃▅▅▅▆▂▁▁▁▁▁▁▁ │-3.2 -6.6 +- 1.3 expected posterior: 1 +- 0.001 dict_keys(['niter', 'logz', 'logzerr', 'logz_bs', 'logz_single', 'logzerr_tail', 'logzerr_bs', 'ess', 'H', 'Herr', 'posterior', 'weighted_samples', 'samples', 'maximum_likelihood', 'ncall', 'paramnames', 'logzerr_single', 'insertion_order_MWW_test']) dict_keys(['mean', 'stdev', 'median', 'errlo', 'errup', 'information_gain_bits']) [1.0000129282162666, -6.550121410221049] [0.0009588598232977235, 1.3204149055392533] [[0.8883395 0.99817529] [0.13034117 0.99142363] [0.78474881 0.99736353] ... [0.50172998 0.944065 ] [0.50169013 0.94429909] [0.50165847 0.94449494]] [0.00000000e+00 0.00000000e+00 0.00000000e+00 ... 3.65990988e-05 3.76571984e-05 3.82909311e-05] [9102, 5700, 5456, 18296]
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=1+0, resume=False, log_dir=/tmp/tmpo5ypz9wy, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977127652850.78, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-42494098572103.11, remainder_fraction=100.0000%, Lmin=-42215979073894.67, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-35539577109063.16, remainder_fraction=100.0000%, Lmin=-35342846910271.16, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-33613237485632.04, remainder_fraction=100.0000%, Lmin=-33560252660467.55, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=635, regioncalls=256, ndraw=128, logz=-29384711911101.59, remainder_fraction=100.0000%, Lmin=-29244181297237.11, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=635, regioncalls=256, ndraw=128, logz=-24734621524258.34, remainder_fraction=100.0000%, Lmin=-24432486117944.29, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=635, regioncalls=256, ndraw=128, logz=-21802390368988.16, remainder_fraction=100.0000%, Lmin=-21645686453768.96, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=635, regioncalls=256, ndraw=128, logz=-18894098943280.38, remainder_fraction=100.0000%, Lmin=-18862720235209.72, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=722, regioncalls=384, ndraw=128, logz=-16143856057425.05, remainder_fraction=100.0000%, Lmin=-15989446312158.34, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=722, regioncalls=384, ndraw=128, logz=-13535837684113.13, remainder_fraction=100.0000%, Lmin=-13504682847649.48, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=789, regioncalls=512, ndraw=128, logz=-12727737770655.03, remainder_fraction=100.0000%, Lmin=-12717546885535.99, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=789, regioncalls=512, ndraw=128, logz=-10598883623681.07, remainder_fraction=100.0000%, Lmin=-10586634997537.11, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=844, regioncalls=640, ndraw=128, logz=-8214913784357.06, remainder_fraction=100.0000%, Lmin=-8210097848813.22, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=888, regioncalls=768, ndraw=128, logz=-6956519205225.25, remainder_fraction=100.0000%, Lmin=-6861252665445.04, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=935, regioncalls=896, ndraw=128, logz=-5701116414373.90, remainder_fraction=100.0000%, Lmin=-5697064810248.16, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=978, regioncalls=1024, ndraw=128, logz=-4635046691812.15, remainder_fraction=100.0000%, Lmin=-4589605457636.64, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1016, regioncalls=1152, ndraw=128, logz=-3732152419982.96, remainder_fraction=100.0000%, Lmin=-3694550010663.56, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1016, regioncalls=1152, ndraw=128, logz=-3434353117102.53, remainder_fraction=100.0000%, Lmin=-3416276968141.32, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1041, regioncalls=1280, ndraw=128, logz=-3127794898135.65, remainder_fraction=100.0000%, Lmin=-3125426459492.65, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1075, regioncalls=1408, ndraw=128, logz=-2641292819157.70, remainder_fraction=100.0000%, Lmin=-2628326533692.18, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1104, regioncalls=1536, ndraw=128, logz=-2261190883104.97, remainder_fraction=100.0000%, Lmin=-2248263800080.57, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1132, regioncalls=1664, ndraw=128, logz=-2137661409200.45, remainder_fraction=100.0000%, Lmin=-2132854392978.04, Lmax=-34582804.86 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1156, regioncalls=1792, ndraw=128, logz=-1777309068832.62, remainder_fraction=100.0000%, Lmin=-1776189008324.79, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1205, regioncalls=2048, ndraw=128, logz=-1477274645941.83, remainder_fraction=100.0000%, Lmin=-1473039555787.20, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1241, regioncalls=2304, ndraw=128, logz=-1228986328760.53, remainder_fraction=100.0000%, Lmin=-1220530275369.51, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1284, regioncalls=2560, ndraw=128, logz=-1008068513965.31, remainder_fraction=100.0000%, Lmin=-1006791737458.03, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1284, regioncalls=2560, ndraw=128, logz=-967911594539.75, remainder_fraction=100.0000%, Lmin=-965894680564.93, Lmax=-32607075.17 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1323, regioncalls=2816, ndraw=128, logz=-866464949430.24, remainder_fraction=100.0000%, Lmin=-863727290145.78, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1367, regioncalls=3072, ndraw=128, logz=-674755956448.05, remainder_fraction=100.0000%, Lmin=-672288777919.19, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1381, regioncalls=3200, ndraw=128, logz=-590520231360.32, remainder_fraction=100.0000%, Lmin=-590264632476.69, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1413, regioncalls=3456, ndraw=128, logz=-545547274549.16, remainder_fraction=100.0000%, Lmin=-543016922876.22, Lmax=-7556171.89 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1455, regioncalls=3840, ndraw=128, logz=-424503798884.03, remainder_fraction=100.0000%, Lmin=-423311078212.85, Lmax=-306369.44 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1487, regioncalls=4224, ndraw=128, logz=-348540245203.58, remainder_fraction=100.0000%, Lmin=-348466153072.81, Lmax=-306369.44 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1536, regioncalls=4736, ndraw=128, logz=-301347767746.06, remainder_fraction=100.0000%, Lmin=-295535831803.94, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1574, regioncalls=5248, ndraw=128, logz=-249139009684.09, remainder_fraction=100.0000%, Lmin=-248826262015.12, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1614, regioncalls=5760, ndraw=128, logz=-204174473489.88, remainder_fraction=100.0000%, Lmin=-203548030042.37, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1652, regioncalls=6400, ndraw=128, logz=-168277592220.41, remainder_fraction=100.0000%, Lmin=-166951449494.73, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1664, regioncalls=6656, ndraw=128, logz=-161350123311.64, remainder_fraction=100.0000%, Lmin=-161016494392.26, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1698, regioncalls=7168, ndraw=128, logz=-139757817034.57, remainder_fraction=100.0000%, Lmin=-139665996555.80, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=1740, regioncalls=8192, ndraw=128, logz=-121163576609.50, remainder_fraction=100.0000%, Lmin=-120962215020.88, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=1762, regioncalls=8576, ndraw=128, logz=-113404243129.32, remainder_fraction=100.0000%, Lmin=-113256039153.14, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=1776, regioncalls=8960, ndraw=128, logz=-102435191408.59, remainder_fraction=100.0000%, Lmin=-102117171296.36, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=1817, regioncalls=10112, ndraw=128, logz=-80561498365.26, remainder_fraction=100.0000%, Lmin=-79890825764.41, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=1851, regioncalls=11008, ndraw=128, logz=-65980578546.46, remainder_fraction=100.0000%, Lmin=-65934086414.84, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=1859, regioncalls=11264, ndraw=128, logz=-62736742728.29, remainder_fraction=100.0000%, Lmin=-62725499591.66, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=1907, regioncalls=12544, ndraw=128, logz=-51120575825.01, remainder_fraction=100.0000%, Lmin=-51101692631.95, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=1948, regioncalls=13952, ndraw=128, logz=-42406526059.95, remainder_fraction=100.0000%, Lmin=-41727505290.80, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=1988, regioncalls=15488, ndraw=128, logz=-33363659562.70, remainder_fraction=100.0000%, Lmin=-32924159572.88, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2029, regioncalls=17024, ndraw=128, logz=-26893053278.43, remainder_fraction=100.0000%, Lmin=-26868052278.66, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2037, regioncalls=17408, ndraw=128, logz=-24932869629.00, remainder_fraction=100.0000%, Lmin=-24826507729.08, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2075, regioncalls=18304, ndraw=128, logz=-21544043932.64, remainder_fraction=100.0000%, Lmin=-21517268972.40, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2116, regioncalls=18816, ndraw=128, logz=-16937433908.05, remainder_fraction=100.0000%, Lmin=-16876272169.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2153, regioncalls=19328, ndraw=128, logz=-14363707315.45, remainder_fraction=100.0000%, Lmin=-14361596834.87, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2195, regioncalls=20096, ndraw=128, logz=-11693905440.60, remainder_fraction=100.0000%, Lmin=-11691023694.63, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2235, regioncalls=20608, ndraw=128, logz=-10340175552.09, remainder_fraction=100.0000%, Lmin=-10317453753.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2238, regioncalls=20864, ndraw=128, logz=-9842053945.87, remainder_fraction=100.0000%, Lmin=-9818062632.12, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2279, regioncalls=22144, ndraw=128, logz=-8152308889.97, remainder_fraction=100.0000%, Lmin=-8104310734.91, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2319, regioncalls=22912, ndraw=128, logz=-6835430799.19, remainder_fraction=100.0000%, Lmin=-6811739139.58, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2362, regioncalls=24320, ndraw=128, logz=-5819912443.41, remainder_fraction=100.0000%, Lmin=-5787984622.54, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2403, regioncalls=24832, ndraw=128, logz=-4884810311.13, remainder_fraction=100.0000%, Lmin=-4858215343.46, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1892, ncalls=2422, regioncalls=25216, ndraw=128, logz=-4636067942.28, remainder_fraction=100.0000%, Lmin=-4621133708.26, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1919, ncalls=2451, regioncalls=25984, ndraw=128, logz=-3858382892.65, remainder_fraction=100.0000%, Lmin=-3854669333.61, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=2451, regioncalls=25984, ndraw=128, logz=-3854669344.40, remainder_fraction=100.0000%, Lmin=-3852626167.06, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1949, ncalls=2485, regioncalls=26752, ndraw=128, logz=-3256231187.70, remainder_fraction=100.0000%, Lmin=-3248632067.55, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=2490, regioncalls=26880, ndraw=128, logz=-3111636724.41, remainder_fraction=100.0000%, Lmin=-3098574454.19, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2768588523.53, remainder_fraction=100.0000%, Lmin=-2751589624.20, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2501023164.86, remainder_fraction=100.0000%, Lmin=-2499560475.77, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=2623, regioncalls=27520, ndraw=128, logz=-2174481162.42, remainder_fraction=100.0000%, Lmin=-2152077450.73, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=2623, regioncalls=27520, ndraw=128, logz=-1895190042.95, remainder_fraction=100.0000%, Lmin=-1893014663.83, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=2624, regioncalls=27648, ndraw=128, logz=-1850397210.79, remainder_fraction=100.0000%, Lmin=-1846179058.70, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2119, ncalls=2671, regioncalls=29696, ndraw=128, logz=-1559142759.67, remainder_fraction=100.0000%, Lmin=-1556767683.82, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=2671, regioncalls=29696, ndraw=128, logz=-1556767695.11, remainder_fraction=100.0000%, Lmin=-1546248420.17, Lmax=-363.28 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=2707, regioncalls=30208, ndraw=128, logz=-1265681926.79, remainder_fraction=100.0000%, Lmin=-1263138337.35, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=2707, regioncalls=30208, ndraw=128, logz=-1218919277.48, remainder_fraction=100.0000%, Lmin=-1216729629.78, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2162, ncalls=2835, regioncalls=30464, ndraw=128, logz=-1215700445.06, remainder_fraction=100.0000%, Lmin=-1215469460.95, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=2835, regioncalls=30464, ndraw=128, logz=-987935092.69, remainder_fraction=100.0000%, Lmin=-983795398.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=2835, regioncalls=30464, ndraw=128, logz=-811811706.41, remainder_fraction=100.0000%, Lmin=-809071566.79, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2275, ncalls=2934, regioncalls=30592, ndraw=128, logz=-705861567.39, remainder_fraction=100.0000%, Lmin=-704698526.64, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=2934, regioncalls=30592, ndraw=128, logz=-694647234.99, remainder_fraction=100.0000%, Lmin=-693426148.12, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=2934, regioncalls=30592, ndraw=128, logz=-567705826.45, remainder_fraction=100.0000%, Lmin=-563342394.87, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=2934, regioncalls=30592, ndraw=128, logz=-521635225.62, remainder_fraction=100.0000%, Lmin=-520267088.69, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=2934, regioncalls=30592, ndraw=128, logz=-459117643.74, remainder_fraction=100.0000%, Lmin=-455164296.21, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3050, regioncalls=30848, ndraw=128, logz=-364531808.48, remainder_fraction=100.0000%, Lmin=-363659580.69, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3050, regioncalls=30848, ndraw=128, logz=-314130669.64, remainder_fraction=100.0000%, Lmin=-312456213.72, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3050, regioncalls=30848, ndraw=128, logz=-305067137.67, remainder_fraction=100.0000%, Lmin=-302035358.51, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3068, regioncalls=31232, ndraw=128, logz=-268203743.10, remainder_fraction=100.0000%, Lmin=-264563106.06, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3121, regioncalls=31872, ndraw=128, logz=-227680306.46, remainder_fraction=100.0000%, Lmin=-226720712.29, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3154, regioncalls=32256, ndraw=128, logz=-192282494.48, remainder_fraction=100.0000%, Lmin=-191862767.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3199, regioncalls=32768, ndraw=128, logz=-152481573.93, remainder_fraction=100.0000%, Lmin=-150064687.00, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3208, regioncalls=32896, ndraw=128, logz=-141786985.67, remainder_fraction=100.0000%, Lmin=-141208770.10, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=3327, regioncalls=33280, ndraw=128, logz=-123715293.16, remainder_fraction=100.0000%, Lmin=-123273647.93, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=3327, regioncalls=33280, ndraw=128, logz=-96060458.65, remainder_fraction=100.0000%, Lmin=-96033237.17, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=3327, regioncalls=33280, ndraw=128, logz=-83875005.77, remainder_fraction=100.0000%, Lmin=-83141993.83, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=3327, regioncalls=33280, ndraw=128, logz=-76588171.43, remainder_fraction=100.0000%, Lmin=-76540182.09, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=3444, regioncalls=33536, ndraw=128, logz=-59897794.76, remainder_fraction=100.0000%, Lmin=-59677779.22, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=3444, regioncalls=33536, ndraw=128, logz=-49760498.26, remainder_fraction=100.0000%, Lmin=-49599851.63, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=3535, regioncalls=33664, ndraw=128, logz=-38489542.92, remainder_fraction=100.0000%, Lmin=-38441431.28, Lmax=-310.03 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=3535, regioncalls=33664, ndraw=128, logz=-32469743.87, remainder_fraction=100.0000%, Lmin=-32313765.59, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=3658, regioncalls=33920, ndraw=128, logz=-26172602.52, remainder_fraction=100.0000%, Lmin=-25938804.52, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=3658, regioncalls=33920, ndraw=128, logz=-19538332.47, remainder_fraction=100.0000%, Lmin=-19450366.38, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=3658, regioncalls=33920, ndraw=128, logz=-18348100.45, remainder_fraction=100.0000%, Lmin=-18344493.62, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=3677, regioncalls=34688, ndraw=128, logz=-15340466.36, remainder_fraction=100.0000%, Lmin=-14985637.97, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=3718, regioncalls=35456, ndraw=128, logz=-12719911.28, remainder_fraction=100.0000%, Lmin=-12647299.74, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=3736, regioncalls=35712, ndraw=128, logz=-11831094.99, remainder_fraction=100.0000%, Lmin=-11787664.15, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=3864, regioncalls=35968, ndraw=128, logz=-11141632.98, remainder_fraction=100.0000%, Lmin=-11121830.90, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=3864, regioncalls=35968, ndraw=128, logz=-8877250.79, remainder_fraction=100.0000%, Lmin=-8874484.68, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=3864, regioncalls=35968, ndraw=128, logz=-7615450.32, remainder_fraction=100.0000%, Lmin=-7615312.38, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=3864, regioncalls=35968, ndraw=128, logz=-7380434.58, remainder_fraction=100.0000%, Lmin=-7356864.48, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3168, ncalls=3992, regioncalls=36480, ndraw=128, logz=-7157825.53, remainder_fraction=100.0000%, Lmin=-7156384.89, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=3992, regioncalls=36480, ndraw=128, logz=-6113566.67, remainder_fraction=100.0000%, Lmin=-6050922.96, Lmax=-135.66 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=3992, regioncalls=36480, ndraw=128, logz=-4573067.94, remainder_fraction=100.0000%, Lmin=-4566133.63, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3275, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3863486.20, remainder_fraction=100.0000%, Lmin=-3829448.55, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3808107.67, remainder_fraction=100.0000%, Lmin=-3795971.02, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4100, regioncalls=36864, ndraw=128, logz=-3110640.62, remainder_fraction=100.0000%, Lmin=-3107239.98, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=4100, regioncalls=36864, ndraw=128, logz=-2675252.29, remainder_fraction=100.0000%, Lmin=-2668849.17, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3370, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2564767.22, remainder_fraction=100.0000%, Lmin=-2551402.90, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2198473.59, remainder_fraction=100.0000%, Lmin=-2196576.76, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=4195, regioncalls=36992, ndraw=128, logz=-2012812.77, remainder_fraction=100.0000%, Lmin=-2009485.22, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=4195, regioncalls=36992, ndraw=128, logz=-1847415.71, remainder_fraction=100.0000%, Lmin=-1829858.31, Lmax=-3.90 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=4227, regioncalls=37504, ndraw=128, logz=-1451906.35, remainder_fraction=100.0000%, Lmin=-1442627.27, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=4262, regioncalls=37888, ndraw=128, logz=-1216639.27, remainder_fraction=100.0000%, Lmin=-1212596.34, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=4385, regioncalls=38144, ndraw=128, logz=-1180207.61, remainder_fraction=100.0000%, Lmin=-1175032.69, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=4385, regioncalls=38144, ndraw=128, logz=-946994.71, remainder_fraction=100.0000%, Lmin=-940999.45, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=4385, regioncalls=38144, ndraw=128, logz=-778747.47, remainder_fraction=100.0000%, Lmin=-771170.46, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3636, ncalls=4475, regioncalls=38272, ndraw=128, logz=-635147.03, remainder_fraction=100.0000%, Lmin=-634663.92, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=4475, regioncalls=38272, ndraw=128, logz=-612791.63, remainder_fraction=100.0000%, Lmin=-608833.23, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=4475, regioncalls=38272, ndraw=128, logz=-508846.48, remainder_fraction=100.0000%, Lmin=-506165.20, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=4475, regioncalls=38272, ndraw=128, logz=-490388.80, remainder_fraction=100.0000%, Lmin=-485575.72, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=4500, regioncalls=38656, ndraw=128, logz=-429946.80, remainder_fraction=100.0000%, Lmin=-428595.78, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=4542, regioncalls=39168, ndraw=128, logz=-346384.62, remainder_fraction=100.0000%, Lmin=-346198.97, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3780, ncalls=4561, regioncalls=39424, ndraw=128, logz=-313687.01, remainder_fraction=100.0000%, Lmin=-313029.66, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=4689, regioncalls=39680, ndraw=128, logz=-282186.40, remainder_fraction=100.0000%, Lmin=-281568.56, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=4689, regioncalls=39680, ndraw=128, logz=-227408.14, remainder_fraction=100.0000%, Lmin=-227371.78, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=4689, regioncalls=39680, ndraw=128, logz=-194507.74, remainder_fraction=100.0000%, Lmin=-194017.43, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=4790, regioncalls=39808, ndraw=128, logz=-160420.77, remainder_fraction=100.0000%, Lmin=-159571.94, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=4790, regioncalls=39808, ndraw=128, logz=-125605.97, remainder_fraction=100.0000%, Lmin=-124767.18, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=3983, ncalls=4914, regioncalls=40064, ndraw=128, logz=-111728.69, remainder_fraction=100.0000%, Lmin=-109892.50, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=4914, regioncalls=40064, ndraw=128, logz=-99628.65, remainder_fraction=100.0000%, Lmin=-98796.75, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=4914, regioncalls=40064, ndraw=128, logz=-79563.29, remainder_fraction=100.0000%, Lmin=-79495.58, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=4914, regioncalls=40064, ndraw=128, logz=-77991.97, remainder_fraction=100.0000%, Lmin=-77957.02, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=4925, regioncalls=40320, ndraw=128, logz=-67526.58, remainder_fraction=100.0000%, Lmin=-67417.47, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=4955, regioncalls=40576, ndraw=128, logz=-55235.26, remainder_fraction=100.0000%, Lmin=-55056.05, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4140, ncalls=4979, regioncalls=41088, ndraw=128, logz=-48939.88, remainder_fraction=100.0000%, Lmin=-48543.38, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=5102, regioncalls=41344, ndraw=128, logz=-43455.66, remainder_fraction=100.0000%, Lmin=-43364.58, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=5102, regioncalls=41344, ndraw=128, logz=-36008.24, remainder_fraction=100.0000%, Lmin=-35757.46, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4230, ncalls=5102, regioncalls=41344, ndraw=128, logz=-30396.80, remainder_fraction=100.0000%, Lmin=-30282.97, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=5102, regioncalls=41344, ndraw=128, logz=-29056.51, remainder_fraction=100.0000%, Lmin=-28855.17, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=5138, regioncalls=41856, ndraw=128, logz=-24102.75, remainder_fraction=100.0000%, Lmin=-23927.05, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=5174, regioncalls=42368, ndraw=128, logz=-19450.22, remainder_fraction=100.0000%, Lmin=-19344.73, Lmax=-0.09 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=5219, regioncalls=43136, ndraw=128, logz=-16094.58, remainder_fraction=100.0000%, Lmin=-15916.99, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=5261, regioncalls=43648, ndraw=128, logz=-12625.39, remainder_fraction=100.0000%, Lmin=-12576.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=5301, regioncalls=44160, ndraw=128, logz=-10993.45, remainder_fraction=100.0000%, Lmin=-10899.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=5337, regioncalls=44800, ndraw=128, logz=-8992.37, remainder_fraction=100.0000%, Lmin=-8974.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=5485, regioncalls=45440, ndraw=128, logz=-8243.26, remainder_fraction=100.0000%, Lmin=-8189.63, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=5485, regioncalls=45440, ndraw=128, logz=-7716.04, remainder_fraction=100.0000%, Lmin=-7682.92, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=5485, regioncalls=45440, ndraw=128, logz=-6371.79, remainder_fraction=100.0000%, Lmin=-6328.55, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4590, ncalls=5485, regioncalls=45440, ndraw=128, logz=-5676.53, remainder_fraction=100.0000%, Lmin=-5634.43, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=5485, regioncalls=45440, ndraw=128, logz=-5463.72, remainder_fraction=100.0000%, Lmin=-5444.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=5524, regioncalls=45952, ndraw=128, logz=-4563.87, remainder_fraction=100.0000%, Lmin=-4536.39, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=5568, regioncalls=46464, ndraw=128, logz=-3732.19, remainder_fraction=100.0000%, Lmin=-3678.91, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2979.60, remainder_fraction=100.0000%, Lmin=-2953.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2401.32, remainder_fraction=100.0000%, Lmin=-2380.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=5685, regioncalls=46720, ndraw=128, logz=-2354.75, remainder_fraction=100.0000%, Lmin=-2328.48, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=5813, regioncalls=47104, ndraw=128, logz=-2084.03, remainder_fraction=100.0000%, Lmin=-2062.99, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1671.66, remainder_fraction=100.0000%, Lmin=-1641.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4860, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1525.16, remainder_fraction=100.0000%, Lmin=-1482.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=5813, regioncalls=47104, ndraw=128, logz=-1305.51, remainder_fraction=100.0000%, Lmin=-1279.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=5843, regioncalls=47616, ndraw=128, logz=-1056.91, remainder_fraction=100.0000%, Lmin=-1031.76, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=5872, regioncalls=48128, ndraw=128, logz=-900.70, remainder_fraction=100.0000%, Lmin=-869.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=5995, regioncalls=48384, ndraw=128, logz=-863.90, remainder_fraction=100.0000%, Lmin=-843.51, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=5995, regioncalls=48384, ndraw=128, logz=-739.95, remainder_fraction=100.0000%, Lmin=-720.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=5995, regioncalls=48384, ndraw=128, logz=-590.48, remainder_fraction=100.0000%, Lmin=-571.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=6087, regioncalls=48512, ndraw=128, logz=-461.16, remainder_fraction=100.0000%, Lmin=-440.89, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=6087, regioncalls=48512, ndraw=128, logz=-379.85, remainder_fraction=100.0000%, Lmin=-357.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=6087, regioncalls=48512, ndraw=128, logz=-362.86, remainder_fraction=100.0000%, Lmin=-337.70, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=6215, regioncalls=48896, ndraw=128, logz=-313.48, remainder_fraction=100.0000%, Lmin=-293.65, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=6215, regioncalls=48896, ndraw=128, logz=-262.54, remainder_fraction=100.0000%, Lmin=-244.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5220, ncalls=6215, regioncalls=48896, ndraw=128, logz=-235.82, remainder_fraction=100.0000%, Lmin=-218.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=6215, regioncalls=48896, ndraw=128, logz=-218.72, remainder_fraction=100.0000%, Lmin=-199.82, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=6254, regioncalls=49536, ndraw=128, logz=-186.07, remainder_fraction=100.0000%, Lmin=-166.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=6410, regioncalls=50304, ndraw=128, logz=-163.79, remainder_fraction=100.0000%, Lmin=-144.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=6410, regioncalls=50304, ndraw=128, logz=-157.35, remainder_fraction=100.0000%, Lmin=-137.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=6410, regioncalls=50304, ndraw=128, logz=-130.32, remainder_fraction=100.0000%, Lmin=-110.84, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=6410, regioncalls=50304, ndraw=128, logz=-108.33, remainder_fraction=100.0000%, Lmin=-88.95, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=6528, regioncalls=50560, ndraw=128, logz=-91.69, remainder_fraction=100.0000%, Lmin=-73.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=6528, regioncalls=50560, ndraw=128, logz=-78.22, remainder_fraction=100.0000%, Lmin=-58.61, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5490, ncalls=6528, regioncalls=50560, ndraw=128, logz=-74.92, remainder_fraction=100.0000%, Lmin=-56.74, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=6528, regioncalls=50560, ndraw=128, logz=-67.83, remainder_fraction=100.0000%, Lmin=-48.78, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=6640, regioncalls=50816, ndraw=128, logz=-59.68, remainder_fraction=100.0000%, Lmin=-41.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5580, ncalls=6640, regioncalls=50816, ndraw=128, logz=-56.20, remainder_fraction=100.0000%, Lmin=-38.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=6640, regioncalls=50816, ndraw=128, logz=-53.16, remainder_fraction=100.0000%, Lmin=-34.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=6755, regioncalls=51200, ndraw=128, logz=-47.03, remainder_fraction=100.0000%, Lmin=-28.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=6755, regioncalls=51200, ndraw=128, logz=-41.54, remainder_fraction=100.0000%, Lmin=-23.57, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=6852, regioncalls=51328, ndraw=128, logz=-37.89, remainder_fraction=100.0000%, Lmin=-20.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=6852, regioncalls=51328, ndraw=128, logz=-34.08, remainder_fraction=100.0000%, Lmin=-15.85, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=6977, regioncalls=51584, ndraw=128, logz=-30.92, remainder_fraction=100.0000%, Lmin=-13.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=6977, regioncalls=51584, ndraw=128, logz=-28.76, remainder_fraction=99.9997%, Lmin=-11.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=6977, regioncalls=51584, ndraw=128, logz=-26.91, remainder_fraction=99.9983%, Lmin=-9.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=7073, regioncalls=51712, ndraw=128, logz=-24.90, remainder_fraction=99.9876%, Lmin=-7.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=7073, regioncalls=51712, ndraw=128, logz=-24.18, remainder_fraction=99.9749%, Lmin=-6.80, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=7073, regioncalls=51712, ndraw=128, logz=-23.55, remainder_fraction=99.9526%, Lmin=-6.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=7184, regioncalls=52096, ndraw=128, logz=-22.37, remainder_fraction=99.8453%, Lmin=-4.86, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6030, ncalls=7184, regioncalls=52096, ndraw=128, logz=-21.55, remainder_fraction=99.6444%, Lmin=-4.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=7184, regioncalls=52096, ndraw=128, logz=-21.29, remainder_fraction=99.5447%, Lmin=-3.90, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=7299, regioncalls=52352, ndraw=128, logz=-20.42, remainder_fraction=98.9077%, Lmin=-3.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=7299, regioncalls=52352, ndraw=128, logz=-19.74, remainder_fraction=97.8310%, Lmin=-2.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=7299, regioncalls=52352, ndraw=128, logz=-19.19, remainder_fraction=96.2426%, Lmin=-2.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.71, remainder_fraction=93.9944%, Lmin=-1.75, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.61, remainder_fraction=93.3324%, Lmin=-1.68, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=7380, regioncalls=52480, ndraw=128, logz=-18.32, remainder_fraction=91.0625%, Lmin=-1.44, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=7422, regioncalls=53248, ndraw=128, logz=-17.98, remainder_fraction=87.4935%, Lmin=-1.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6300, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.82, remainder_fraction=85.3959%, Lmin=-0.98, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.68, remainder_fraction=83.0994%, Lmin=-0.88, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.43, remainder_fraction=78.5133%, Lmin=-0.73, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.28, remainder_fraction=74.8625%, Lmin=-0.62, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=7556, regioncalls=53760, ndraw=128, logz=-17.23, remainder_fraction=73.6584%, Lmin=-0.60, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=7684, regioncalls=54016, ndraw=128, logz=-17.06, remainder_fraction=68.8212%, Lmin=-0.52, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=7684, regioncalls=54016, ndraw=128, logz=-16.91, remainder_fraction=64.1156%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.79, remainder_fraction=59.3193%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.68, remainder_fraction=54.7469%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6570, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.66, remainder_fraction=53.6018%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6600, ncalls=7789, regioncalls=54144, ndraw=128, logz=-16.59, remainder_fraction=50.2886%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6640, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.51, remainder_fraction=46.1265%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6660, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.47, remainder_fraction=44.1182%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6680, ncalls=7899, regioncalls=54400, ndraw=128, logz=-16.44, remainder_fraction=42.1888%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=7918, regioncalls=54784, ndraw=128, logz=-16.38, remainder_fraction=38.5249%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6750, ncalls=7951, regioncalls=55168, ndraw=128, logz=-16.34, remainder_fraction=35.9534%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6760, ncalls=7963, regioncalls=55424, ndraw=128, logz=-16.32, remainder_fraction=35.1382%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6800, ncalls=7999, regioncalls=55808, ndraw=128, logz=-16.28, remainder_fraction=32.0091%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6840, ncalls=8045, regioncalls=56448, ndraw=128, logz=-16.23, remainder_fraction=29.1078%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=8085, regioncalls=56960, ndraw=128, logz=-16.20, remainder_fraction=26.4548%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6920, ncalls=8131, regioncalls=57600, ndraw=128, logz=-16.17, remainder_fraction=24.0141%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6930, ncalls=8138, regioncalls=57728, ndraw=128, logz=-16.16, remainder_fraction=23.4390%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=6960, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.14, remainder_fraction=21.7938%, Lmin=-0.04, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7000, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.11, remainder_fraction=19.7631%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7020, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.10, remainder_fraction=18.8221%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=8266, regioncalls=57984, ndraw=128, logz=-16.09, remainder_fraction=17.9210%, Lmin=-0.03, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7080, ncalls=8313, regioncalls=58496, ndraw=128, logz=-16.07, remainder_fraction=16.2402%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7110, ncalls=8337, regioncalls=58880, ndraw=128, logz=-16.05, remainder_fraction=15.0830%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7120, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.05, remainder_fraction=14.7162%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7160, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.03, remainder_fraction=13.3321%, Lmin=-0.02, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=8465, regioncalls=59136, ndraw=128, logz=-16.02, remainder_fraction=12.0743%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7240, ncalls=8580, regioncalls=59520, ndraw=128, logz=-16.01, remainder_fraction=10.9343%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7280, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.99, remainder_fraction=9.8999%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7290, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.99, remainder_fraction=9.6570%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7320, ncalls=8580, regioncalls=59520, ndraw=128, logz=-15.98, remainder_fraction=8.9628%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.97, remainder_fraction=8.1140%, Lmin=-0.01, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7400, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.97, remainder_fraction=7.3446%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7440, ncalls=8703, regioncalls=59776, ndraw=128, logz=-15.96, remainder_fraction=6.6475%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7470, ncalls=8786, regioncalls=59904, ndraw=128, logz=-15.95, remainder_fraction=6.1683%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7480, ncalls=8786, regioncalls=59904, ndraw=128, logz=-15.95, remainder_fraction=6.0163%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=8802, regioncalls=60288, ndraw=128, logz=-15.95, remainder_fraction=5.4447%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7560, ncalls=8853, regioncalls=60928, ndraw=128, logz=-15.94, remainder_fraction=4.9272%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7600, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.94, remainder_fraction=4.4589%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7640, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=4.0350%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7650, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=3.9354%, Lmin=-0.00, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=7680, ncalls=8981, regioncalls=61184, ndraw=128, logz=-15.93, remainder_fraction=3.6513%, Lmin=-0.00, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-2e-07 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 9102 INFO ultranest:integrator.py:2774 Writing samples and results to disk ... INFO ultranest:integrator.py:2806 Writing samples and results to disk ... done DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -15.87 +- 0.1519 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1239.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.20 bs:0.15 tail:0.03 total:0.16 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-26372698294787.03, Lmax=-13.90 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-1027058.68, remainder_fraction=100.0000%, Lmin=-367803.47, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-60.45, remainder_fraction=100.0000%, Lmin=-50.38, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-29.28, remainder_fraction=99.9998%, Lmin=-21.93, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=631, regioncalls=256, ndraw=128, logz=-22.50, remainder_fraction=99.8222%, Lmin=-19.03, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=631, regioncalls=256, ndraw=128, logz=-20.69, remainder_fraction=98.9330%, Lmin=-17.74, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=631, regioncalls=256, ndraw=128, logz=-20.07, remainder_fraction=98.0088%, Lmin=-17.26, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=719, regioncalls=384, ndraw=128, logz=-19.63, remainder_fraction=96.8814%, Lmin=-17.08, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=719, regioncalls=384, ndraw=128, logz=-18.94, remainder_fraction=93.8205%, Lmin=-16.60, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=796, regioncalls=512, ndraw=128, logz=-18.48, remainder_fraction=90.2741%, Lmin=-16.43, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=867, regioncalls=640, ndraw=128, logz=-18.15, remainder_fraction=86.3264%, Lmin=-16.28, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=867, regioncalls=640, ndraw=128, logz=-17.89, remainder_fraction=82.3716%, Lmin=-16.18, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=936, regioncalls=768, ndraw=128, logz=-17.69, remainder_fraction=78.3963%, Lmin=-16.05, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=992, regioncalls=896, ndraw=128, logz=-17.51, remainder_fraction=74.4446%, Lmin=-15.95, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=992, regioncalls=896, ndraw=128, logz=-17.47, remainder_fraction=73.3637%, Lmin=-15.93, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1054, regioncalls=1024, ndraw=128, logz=-17.36, remainder_fraction=70.4213%, Lmin=-15.86, Lmax=-13.70 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1144, regioncalls=1280, ndraw=128, logz=-17.24, remainder_fraction=66.5149%, Lmin=-15.76, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1144, regioncalls=1280, ndraw=128, logz=-17.18, remainder_fraction=64.4159%, Lmin=-15.73, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1180, regioncalls=1408, ndraw=128, logz=-17.13, remainder_fraction=62.5174%, Lmin=-15.69, Lmax=-13.62 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1222, regioncalls=1536, ndraw=128, logz=-17.03, remainder_fraction=58.8842%, Lmin=-15.63, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1266, regioncalls=1664, ndraw=128, logz=-16.97, remainder_fraction=56.1143%, Lmin=-15.58, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1266, regioncalls=1664, ndraw=128, logz=-16.94, remainder_fraction=55.1073%, Lmin=-15.56, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1325, regioncalls=1920, ndraw=128, logz=-16.87, remainder_fraction=51.4374%, Lmin=-15.48, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1399, regioncalls=2176, ndraw=128, logz=-16.80, remainder_fraction=47.9747%, Lmin=-15.43, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1418, regioncalls=2304, ndraw=128, logz=-16.74, remainder_fraction=44.7173%, Lmin=-15.38, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1489, regioncalls=2688, ndraw=128, logz=-16.68, remainder_fraction=41.6710%, Lmin=-15.34, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1489, regioncalls=2688, ndraw=128, logz=-16.67, remainder_fraction=41.0579%, Lmin=-15.33, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1522, regioncalls=2944, ndraw=128, logz=-16.63, remainder_fraction=38.8517%, Lmin=-15.30, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1580, regioncalls=3328, ndraw=128, logz=-16.59, remainder_fraction=36.0139%, Lmin=-15.26, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1617, regioncalls=3584, ndraw=128, logz=-16.57, remainder_fraction=34.8946%, Lmin=-15.24, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1636, regioncalls=3712, ndraw=128, logz=-16.55, remainder_fraction=33.5674%, Lmin=-15.22, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1692, regioncalls=4096, ndraw=128, logz=-16.51, remainder_fraction=30.9724%, Lmin=-15.18, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1740, regioncalls=4480, ndraw=128, logz=-16.49, remainder_fraction=29.3425%, Lmin=-15.16, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1750, regioncalls=4608, ndraw=128, logz=-16.48, remainder_fraction=28.9446%, Lmin=-15.16, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1797, regioncalls=5248, ndraw=128, logz=-16.45, remainder_fraction=26.6418%, Lmin=-15.13, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1852, regioncalls=5888, ndraw=128, logz=-16.42, remainder_fraction=24.5757%, Lmin=-15.10, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1910, regioncalls=6656, ndraw=128, logz=-16.40, remainder_fraction=22.6763%, Lmin=-15.08, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1959, regioncalls=7424, ndraw=128, logz=-16.38, remainder_fraction=20.8360%, Lmin=-15.06, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1981, regioncalls=7680, ndraw=128, logz=-16.37, remainder_fraction=20.3949%, Lmin=-15.05, Lmax=-13.21 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2011, regioncalls=7936, ndraw=128, logz=-16.36, remainder_fraction=19.2763%, Lmin=-15.04, Lmax=-13.05 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2058, regioncalls=8704, ndraw=128, logz=-16.34, remainder_fraction=17.9343%, Lmin=-15.02, Lmax=-13.05 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2084, regioncalls=9088, ndraw=128, logz=-16.33, remainder_fraction=17.7076%, Lmin=-15.01, Lmax=-12.00 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2099, regioncalls=9472, ndraw=128, logz=-16.33, remainder_fraction=17.7135%, Lmin=-15.00, Lmax=-12.00 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2153, regioncalls=10624, ndraw=128, logz=-16.31, remainder_fraction=16.8556%, Lmin=-14.99, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2188, regioncalls=11392, ndraw=128, logz=-16.30, remainder_fraction=15.8899%, Lmin=-14.97, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2197, regioncalls=11648, ndraw=128, logz=-16.30, remainder_fraction=15.7189%, Lmin=-14.97, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2252, regioncalls=13056, ndraw=128, logz=-16.29, remainder_fraction=15.0393%, Lmin=-14.95, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2300, regioncalls=14208, ndraw=128, logz=-16.27, remainder_fraction=13.9593%, Lmin=-14.94, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2347, regioncalls=15872, ndraw=128, logz=-16.26, remainder_fraction=13.0329%, Lmin=-14.93, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2393, regioncalls=17280, ndraw=128, logz=-16.26, remainder_fraction=11.9868%, Lmin=-14.91, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2447, regioncalls=19328, ndraw=128, logz=-16.25, remainder_fraction=11.1844%, Lmin=-14.90, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2519, regioncalls=19840, ndraw=128, logz=-16.24, remainder_fraction=10.5107%, Lmin=-14.89, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2585, regioncalls=19968, ndraw=128, logz=-16.24, remainder_fraction=10.2179%, Lmin=-14.88, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2585, regioncalls=19968, ndraw=128, logz=-16.23, remainder_fraction=9.8265%, Lmin=-14.88, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.23, remainder_fraction=9.1364%, Lmin=-14.87, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.22, remainder_fraction=8.7569%, Lmin=-14.86, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2679, regioncalls=20224, ndraw=128, logz=-16.22, remainder_fraction=8.6061%, Lmin=-14.86, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2793, regioncalls=22272, ndraw=128, logz=-16.22, remainder_fraction=8.1162%, Lmin=-14.84, Lmax=-11.85 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2862, regioncalls=22400, ndraw=128, logz=-16.21, remainder_fraction=8.3709%, Lmin=-14.83, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2862, regioncalls=22400, ndraw=128, logz=-16.21, remainder_fraction=7.9819%, Lmin=-14.82, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2936, regioncalls=22528, ndraw=128, logz=-16.20, remainder_fraction=7.6070%, Lmin=-14.78, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=2936, regioncalls=22528, ndraw=128, logz=-16.20, remainder_fraction=7.4659%, Lmin=-14.77, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3010, regioncalls=23168, ndraw=128, logz=-16.20, remainder_fraction=7.2276%, Lmin=-14.75, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.20, remainder_fraction=7.0091%, Lmin=-14.72, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.20, remainder_fraction=6.9076%, Lmin=-14.69, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3075, regioncalls=23296, ndraw=128, logz=-16.19, remainder_fraction=6.6638%, Lmin=-14.67, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3142, regioncalls=23552, ndraw=128, logz=-16.19, remainder_fraction=6.5265%, Lmin=-14.64, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3201, regioncalls=23680, ndraw=128, logz=-16.19, remainder_fraction=6.3636%, Lmin=-14.61, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3201, regioncalls=23680, ndraw=128, logz=-16.19, remainder_fraction=6.3383%, Lmin=-14.59, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3301, regioncalls=25216, ndraw=128, logz=-16.19, remainder_fraction=6.1060%, Lmin=-14.50, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3301, regioncalls=25216, ndraw=128, logz=-16.18, remainder_fraction=5.9113%, Lmin=-14.43, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3363, regioncalls=25472, ndraw=128, logz=-16.18, remainder_fraction=5.7821%, Lmin=-14.37, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3430, regioncalls=25600, ndraw=128, logz=-16.18, remainder_fraction=5.4850%, Lmin=-14.28, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3430, regioncalls=25600, ndraw=128, logz=-16.18, remainder_fraction=5.4465%, Lmin=-14.27, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3504, regioncalls=25856, ndraw=128, logz=-16.18, remainder_fraction=5.3598%, Lmin=-14.20, Lmax=-11.50 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.0849%, Lmin=-14.12, Lmax=-11.50 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.1115%, Lmin=-14.09, Lmax=-11.30 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3572, regioncalls=25984, ndraw=128, logz=-16.17, remainder_fraction=5.1050%, Lmin=-14.06, Lmax=-11.30 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3679, regioncalls=26624, ndraw=128, logz=-16.17, remainder_fraction=4.9120%, Lmin=-14.00, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3679, regioncalls=26624, ndraw=128, logz=-16.17, remainder_fraction=4.8491%, Lmin=-13.97, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3766, regioncalls=27264, ndraw=128, logz=-16.17, remainder_fraction=4.8425%, Lmin=-13.96, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3766, regioncalls=27264, ndraw=128, logz=-16.16, remainder_fraction=4.6542%, Lmin=-13.91, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3857, regioncalls=27392, ndraw=128, logz=-16.16, remainder_fraction=4.4993%, Lmin=-13.85, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3857, regioncalls=27392, ndraw=128, logz=-16.16, remainder_fraction=4.3184%, Lmin=-13.80, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3935, regioncalls=27520, ndraw=128, logz=-16.16, remainder_fraction=4.1650%, Lmin=-13.75, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=3935, regioncalls=27520, ndraw=128, logz=-16.16, remainder_fraction=4.1110%, Lmin=-13.73, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4033, regioncalls=27904, ndraw=128, logz=-16.16, remainder_fraction=3.9877%, Lmin=-13.70, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4033, regioncalls=27904, ndraw=128, logz=-16.16, remainder_fraction=3.8082%, Lmin=-13.66, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=4123, regioncalls=28032, ndraw=128, logz=-16.16, remainder_fraction=3.7535%, Lmin=-13.63, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4123, regioncalls=28032, ndraw=128, logz=-16.15, remainder_fraction=3.6973%, Lmin=-13.61, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.5760%, Lmin=-13.54, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.4688%, Lmin=-13.45, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4227, regioncalls=28416, ndraw=128, logz=-16.15, remainder_fraction=3.4510%, Lmin=-13.42, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4264, regioncalls=29312, ndraw=128, logz=-16.15, remainder_fraction=3.3256%, Lmin=-13.29, Lmax=-11.20 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4319, regioncalls=30336, ndraw=128, logz=-16.15, remainder_fraction=3.2426%, Lmin=-13.17, Lmax=-11.16 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4395, regioncalls=31616, ndraw=128, logz=-16.15, remainder_fraction=3.0915%, Lmin=-13.05, Lmax=-10.83 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4448, regioncalls=32768, ndraw=128, logz=-16.15, remainder_fraction=2.9927%, Lmin=-12.98, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4461, regioncalls=33024, ndraw=128, logz=-16.15, remainder_fraction=2.9557%, Lmin=-12.96, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4573, regioncalls=33280, ndraw=128, logz=-16.14, remainder_fraction=2.8380%, Lmin=-12.90, Lmax=-10.78 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4573, regioncalls=33280, ndraw=128, logz=-16.14, remainder_fraction=2.7163%, Lmin=-12.81, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.6739%, Lmin=-12.76, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.6039%, Lmin=-12.71, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4677, regioncalls=33408, ndraw=128, logz=-16.14, remainder_fraction=2.4925%, Lmin=-12.62, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4783, regioncalls=33664, ndraw=128, logz=-16.14, remainder_fraction=2.3941%, Lmin=-12.56, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4783, regioncalls=33664, ndraw=128, logz=-16.14, remainder_fraction=2.3535%, Lmin=-12.53, Lmax=-10.71 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4807, regioncalls=34176, ndraw=128, logz=-16.14, remainder_fraction=2.2115%, Lmin=-12.47, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4864, regioncalls=35200, ndraw=128, logz=-16.14, remainder_fraction=2.1043%, Lmin=-12.40, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4963, regioncalls=35584, ndraw=128, logz=-16.13, remainder_fraction=1.9696%, Lmin=-12.34, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=4963, regioncalls=35584, ndraw=128, logz=-16.13, remainder_fraction=1.8382%, Lmin=-12.28, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5070, regioncalls=35712, ndraw=128, logz=-16.13, remainder_fraction=1.8081%, Lmin=-12.26, Lmax=-10.67 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5070, regioncalls=35712, ndraw=128, logz=-16.13, remainder_fraction=1.7309%, Lmin=-12.19, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5082, regioncalls=36096, ndraw=128, logz=-16.13, remainder_fraction=1.6023%, Lmin=-12.11, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5139, regioncalls=37248, ndraw=128, logz=-16.13, remainder_fraction=1.5003%, Lmin=-12.06, Lmax=-10.41 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=5205, regioncalls=38272, ndraw=128, logz=-16.13, remainder_fraction=1.4310%, Lmin=-12.02, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=5258, regioncalls=39168, ndraw=128, logz=-16.13, remainder_fraction=1.3744%, Lmin=-11.98, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=5320, regioncalls=40448, ndraw=128, logz=-16.13, remainder_fraction=1.2919%, Lmin=-11.94, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5373, regioncalls=41728, ndraw=128, logz=-16.13, remainder_fraction=1.2086%, Lmin=-11.90, Lmax=-10.27 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=5436, regioncalls=43264, ndraw=128, logz=-16.13, remainder_fraction=1.1708%, Lmin=-11.87, Lmax=-10.07 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=5487, regioncalls=44416, ndraw=128, logz=-16.12, remainder_fraction=1.1240%, Lmin=-11.83, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3690, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.1193%, Lmin=-11.83, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.0971%, Lmin=-11.81, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=5600, regioncalls=45056, ndraw=128, logz=-16.12, remainder_fraction=1.0474%, Lmin=-11.78, Lmax=-10.04 DEBUG ultranest:integrator.py:2610 iteration=3780, ncalls=5700, regioncalls=45184, ndraw=128, logz=-16.12, remainder_fraction=1.0309%, Lmin=-11.77, Lmax=-9.95 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=5700, regioncalls=45184, ndraw=128, logz=-16.12, remainder_fraction=1.0082%, Lmin=-11.75, Lmax=-9.95 INFO ultranest:integrator.py:2654 Explored until L=-1e+01 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5700 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -16.1 +- 0.031 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1540.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.03, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.04 bs:0.03 tail:0.01 total:0.03 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-14849705163238.41, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-12164310.70, remainder_fraction=100.0000%, Lmin=-12150372.90, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-652.11, remainder_fraction=100.0000%, Lmin=-620.56, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-56.81, remainder_fraction=100.0000%, Lmin=-49.94, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=632, regioncalls=256, ndraw=128, logz=-26.15, remainder_fraction=99.9952%, Lmin=-21.82, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=632, regioncalls=256, ndraw=128, logz=-22.12, remainder_fraction=99.7343%, Lmin=-18.83, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=632, regioncalls=256, ndraw=128, logz=-21.38, remainder_fraction=99.4416%, Lmin=-18.34, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=715, regioncalls=384, ndraw=128, logz=-20.80, remainder_fraction=98.9965%, Lmin=-17.96, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=715, regioncalls=384, ndraw=128, logz=-19.97, remainder_fraction=97.6888%, Lmin=-17.37, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=791, regioncalls=512, ndraw=128, logz=-19.34, remainder_fraction=95.6112%, Lmin=-16.92, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=791, regioncalls=512, ndraw=128, logz=-18.84, remainder_fraction=92.8123%, Lmin=-16.54, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=856, regioncalls=640, ndraw=128, logz=-18.45, remainder_fraction=89.3711%, Lmin=-16.31, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=918, regioncalls=768, ndraw=128, logz=-18.14, remainder_fraction=85.5446%, Lmin=-16.13, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=979, regioncalls=896, ndraw=128, logz=-17.90, remainder_fraction=81.2828%, Lmin=-16.00, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1031, regioncalls=1024, ndraw=128, logz=-17.69, remainder_fraction=76.9481%, Lmin=-15.83, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1076, regioncalls=1152, ndraw=128, logz=-17.51, remainder_fraction=72.4432%, Lmin=-15.73, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1076, regioncalls=1152, ndraw=128, logz=-17.44, remainder_fraction=70.4491%, Lmin=-15.69, Lmax=-13.67 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1112, regioncalls=1280, ndraw=128, logz=-17.36, remainder_fraction=68.6035%, Lmin=-15.65, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1186, regioncalls=1536, ndraw=128, logz=-17.24, remainder_fraction=64.3482%, Lmin=-15.59, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1227, regioncalls=1664, ndraw=128, logz=-17.13, remainder_fraction=60.1018%, Lmin=-15.54, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1287, regioncalls=1920, ndraw=128, logz=-17.04, remainder_fraction=56.1766%, Lmin=-15.48, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1339, regioncalls=2176, ndraw=128, logz=-16.96, remainder_fraction=52.3925%, Lmin=-15.42, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1416, regioncalls=2560, ndraw=128, logz=-16.88, remainder_fraction=48.5818%, Lmin=-15.35, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1471, regioncalls=2816, ndraw=128, logz=-16.82, remainder_fraction=45.2266%, Lmin=-15.31, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1493, regioncalls=2944, ndraw=128, logz=-16.80, remainder_fraction=44.3521%, Lmin=-15.30, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1556, regioncalls=3328, ndraw=128, logz=-16.76, remainder_fraction=42.0094%, Lmin=-15.28, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1606, regioncalls=3712, ndraw=128, logz=-16.71, remainder_fraction=38.8738%, Lmin=-15.23, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1619, regioncalls=3840, ndraw=128, logz=-16.68, remainder_fraction=37.3284%, Lmin=-15.21, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1643, regioncalls=4224, ndraw=128, logz=-16.66, remainder_fraction=35.9391%, Lmin=-15.20, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1708, regioncalls=4736, ndraw=128, logz=-16.62, remainder_fraction=33.2899%, Lmin=-15.17, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1762, regioncalls=5248, ndraw=128, logz=-16.58, remainder_fraction=30.8116%, Lmin=-15.14, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1807, regioncalls=5760, ndraw=128, logz=-16.55, remainder_fraction=28.3777%, Lmin=-15.11, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1868, regioncalls=6528, ndraw=128, logz=-16.52, remainder_fraction=26.0772%, Lmin=-15.08, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1916, regioncalls=7168, ndraw=128, logz=-16.49, remainder_fraction=23.9965%, Lmin=-15.06, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1974, regioncalls=8064, ndraw=128, logz=-16.47, remainder_fraction=22.1263%, Lmin=-15.03, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=1984, regioncalls=8192, ndraw=128, logz=-16.46, remainder_fraction=21.6256%, Lmin=-15.03, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=2027, regioncalls=8832, ndraw=128, logz=-16.45, remainder_fraction=20.4266%, Lmin=-15.02, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2080, regioncalls=9728, ndraw=128, logz=-16.43, remainder_fraction=18.8390%, Lmin=-15.00, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2108, regioncalls=10240, ndraw=128, logz=-16.42, remainder_fraction=18.0867%, Lmin=-14.99, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2137, regioncalls=10752, ndraw=128, logz=-16.41, remainder_fraction=17.4153%, Lmin=-14.98, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2184, regioncalls=11776, ndraw=128, logz=-16.39, remainder_fraction=16.1452%, Lmin=-14.97, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=2232, regioncalls=13056, ndraw=128, logz=-16.38, remainder_fraction=15.3566%, Lmin=-14.96, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2249, regioncalls=13440, ndraw=128, logz=-16.38, remainder_fraction=15.0174%, Lmin=-14.95, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2300, regioncalls=14592, ndraw=128, logz=-16.37, remainder_fraction=13.9140%, Lmin=-14.94, Lmax=-13.49 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2361, regioncalls=16000, ndraw=128, logz=-16.35, remainder_fraction=12.9170%, Lmin=-14.93, Lmax=-13.36 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2412, regioncalls=17792, ndraw=128, logz=-16.34, remainder_fraction=12.1141%, Lmin=-14.92, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2476, regioncalls=19840, ndraw=128, logz=-16.33, remainder_fraction=11.1146%, Lmin=-14.91, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=2490, regioncalls=20096, ndraw=128, logz=-16.33, remainder_fraction=10.9083%, Lmin=-14.90, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2532, regioncalls=21888, ndraw=128, logz=-16.33, remainder_fraction=10.3378%, Lmin=-14.90, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2618, regioncalls=22272, ndraw=128, logz=-16.32, remainder_fraction=9.5622%, Lmin=-14.89, Lmax=-12.53 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2618, regioncalls=22272, ndraw=128, logz=-16.31, remainder_fraction=9.3973%, Lmin=-14.88, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2644, regioncalls=23680, ndraw=128, logz=-16.31, remainder_fraction=9.3884%, Lmin=-14.88, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2748, regioncalls=24832, ndraw=128, logz=-16.30, remainder_fraction=8.7230%, Lmin=-14.87, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2748, regioncalls=24832, ndraw=128, logz=-16.30, remainder_fraction=8.2577%, Lmin=-14.86, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2759, regioncalls=25472, ndraw=128, logz=-16.30, remainder_fraction=8.0916%, Lmin=-14.86, Lmax=-12.49 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2832, regioncalls=25984, ndraw=128, logz=-16.29, remainder_fraction=7.7817%, Lmin=-14.85, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2881, regioncalls=26112, ndraw=128, logz=-16.29, remainder_fraction=7.3639%, Lmin=-14.84, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2932, regioncalls=26240, ndraw=128, logz=-16.28, remainder_fraction=6.9211%, Lmin=-14.83, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=2986, regioncalls=26368, ndraw=128, logz=-16.28, remainder_fraction=6.7286%, Lmin=-14.80, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=3026, regioncalls=26496, ndraw=128, logz=-16.28, remainder_fraction=6.6216%, Lmin=-14.79, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3035, regioncalls=27264, ndraw=128, logz=-16.27, remainder_fraction=6.4277%, Lmin=-14.77, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3089, regioncalls=28288, ndraw=128, logz=-16.27, remainder_fraction=6.2005%, Lmin=-14.74, Lmax=-12.28 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3138, regioncalls=29056, ndraw=128, logz=-16.27, remainder_fraction=6.0162%, Lmin=-14.70, Lmax=-12.11 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3198, regioncalls=29952, ndraw=128, logz=-16.26, remainder_fraction=5.8900%, Lmin=-14.66, Lmax=-12.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=3238, regioncalls=30592, ndraw=128, logz=-16.26, remainder_fraction=5.8281%, Lmin=-14.64, Lmax=-12.01 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3332, regioncalls=31104, ndraw=128, logz=-16.26, remainder_fraction=5.9317%, Lmin=-14.63, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3332, regioncalls=31104, ndraw=128, logz=-16.26, remainder_fraction=5.6781%, Lmin=-14.58, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3418, regioncalls=31232, ndraw=128, logz=-16.26, remainder_fraction=5.5063%, Lmin=-14.50, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3418, regioncalls=31232, ndraw=128, logz=-16.25, remainder_fraction=5.3221%, Lmin=-14.43, Lmax=-11.86 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3505, regioncalls=31360, ndraw=128, logz=-16.25, remainder_fraction=5.1279%, Lmin=-14.37, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=3505, regioncalls=31360, ndraw=128, logz=-16.25, remainder_fraction=5.0507%, Lmin=-14.35, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=3534, regioncalls=32256, ndraw=128, logz=-16.25, remainder_fraction=4.9457%, Lmin=-14.29, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=3587, regioncalls=33152, ndraw=128, logz=-16.25, remainder_fraction=4.6605%, Lmin=-14.20, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=3618, regioncalls=33664, ndraw=128, logz=-16.25, remainder_fraction=4.5307%, Lmin=-14.18, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=3638, regioncalls=34176, ndraw=128, logz=-16.24, remainder_fraction=4.4758%, Lmin=-14.16, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=3687, regioncalls=34944, ndraw=128, logz=-16.24, remainder_fraction=4.3247%, Lmin=-14.09, Lmax=-11.82 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.2249%, Lmin=-14.05, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.1912%, Lmin=-14.02, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=3810, regioncalls=35968, ndraw=128, logz=-16.24, remainder_fraction=4.0032%, Lmin=-13.96, Lmax=-11.72 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=3877, regioncalls=36096, ndraw=128, logz=-16.24, remainder_fraction=3.8561%, Lmin=-13.91, Lmax=-11.71 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=3898, regioncalls=36608, ndraw=128, logz=-16.23, remainder_fraction=3.7150%, Lmin=-13.86, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=3950, regioncalls=37632, ndraw=128, logz=-16.23, remainder_fraction=3.5438%, Lmin=-13.82, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=4004, regioncalls=38656, ndraw=128, logz=-16.23, remainder_fraction=3.3672%, Lmin=-13.77, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=4063, regioncalls=39936, ndraw=128, logz=-16.23, remainder_fraction=3.1812%, Lmin=-13.73, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=4127, regioncalls=41216, ndraw=128, logz=-16.23, remainder_fraction=3.0476%, Lmin=-13.68, Lmax=-11.69 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=4182, regioncalls=42368, ndraw=128, logz=-16.23, remainder_fraction=2.9796%, Lmin=-13.65, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=4235, regioncalls=43648, ndraw=128, logz=-16.23, remainder_fraction=2.8709%, Lmin=-13.61, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=4307, regioncalls=43904, ndraw=128, logz=-16.23, remainder_fraction=2.8404%, Lmin=-13.60, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=4307, regioncalls=43904, ndraw=128, logz=-16.22, remainder_fraction=2.7205%, Lmin=-13.56, Lmax=-11.61 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=4374, regioncalls=44032, ndraw=128, logz=-16.22, remainder_fraction=2.6810%, Lmin=-13.49, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=4432, regioncalls=44160, ndraw=128, logz=-16.22, remainder_fraction=2.5938%, Lmin=-13.38, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=4486, regioncalls=44288, ndraw=128, logz=-16.22, remainder_fraction=2.4867%, Lmin=-13.27, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=4486, regioncalls=44288, ndraw=128, logz=-16.22, remainder_fraction=2.4569%, Lmin=-13.24, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=4523, regioncalls=44928, ndraw=128, logz=-16.22, remainder_fraction=2.3929%, Lmin=-13.16, Lmax=-11.54 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=4574, regioncalls=45824, ndraw=128, logz=-16.22, remainder_fraction=2.2842%, Lmin=-13.06, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=4600, regioncalls=46208, ndraw=128, logz=-16.22, remainder_fraction=2.2311%, Lmin=-13.01, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=4698, regioncalls=46464, ndraw=128, logz=-16.22, remainder_fraction=2.1599%, Lmin=-12.97, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=4698, regioncalls=46464, ndraw=128, logz=-16.22, remainder_fraction=2.0496%, Lmin=-12.87, Lmax=-11.49 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=4780, regioncalls=46592, ndraw=128, logz=-16.21, remainder_fraction=1.9867%, Lmin=-12.80, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=4780, regioncalls=46592, ndraw=128, logz=-16.21, remainder_fraction=1.9626%, Lmin=-12.78, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=4869, regioncalls=46976, ndraw=128, logz=-16.21, remainder_fraction=1.8622%, Lmin=-12.70, Lmax=-11.22 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=4869, regioncalls=46976, ndraw=128, logz=-16.21, remainder_fraction=1.7643%, Lmin=-12.62, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=4948, regioncalls=47104, ndraw=128, logz=-16.21, remainder_fraction=1.6724%, Lmin=-12.54, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=5013, regioncalls=47232, ndraw=128, logz=-16.21, remainder_fraction=1.5873%, Lmin=-12.49, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=5013, regioncalls=47232, ndraw=128, logz=-16.21, remainder_fraction=1.5607%, Lmin=-12.48, Lmax=-10.99 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.5019%, Lmin=-12.43, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.4067%, Lmin=-12.37, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3420, ncalls=5129, regioncalls=47488, ndraw=128, logz=-16.21, remainder_fraction=1.3564%, Lmin=-12.35, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=5235, regioncalls=47744, ndraw=128, logz=-16.21, remainder_fraction=1.3057%, Lmin=-12.32, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=5235, regioncalls=47744, ndraw=128, logz=-16.21, remainder_fraction=1.2195%, Lmin=-12.27, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.21, remainder_fraction=1.1632%, Lmin=-12.22, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.21, remainder_fraction=1.1480%, Lmin=-12.21, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=5341, regioncalls=47872, ndraw=128, logz=-16.20, remainder_fraction=1.0796%, Lmin=-12.17, Lmax=-10.94 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=5456, regioncalls=48256, ndraw=128, logz=-16.20, remainder_fraction=1.0066%, Lmin=-12.12, Lmax=-10.94 INFO ultranest:integrator.py:2654 Explored until L=-1e+01 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 5456 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -16.18 +- 0.03606 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1474.1, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.04, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.04 bs:0.04 tail:0.01 total:0.04 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=528, regioncalls=128, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-27067381821958.52, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=40, ncalls=528, regioncalls=128, ndraw=128, logz=-3316105.24, remainder_fraction=100.0000%, Lmin=-2597981.55, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=80, ncalls=528, regioncalls=128, ndraw=128, logz=-502426.97, remainder_fraction=100.0000%, Lmin=-502376.73, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=528, regioncalls=128, ndraw=128, logz=-502236.71, remainder_fraction=100.0000%, Lmin=-502117.19, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=120, ncalls=638, regioncalls=256, ndraw=128, logz=-501645.16, remainder_fraction=100.0000%, Lmin=-501629.49, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=160, ncalls=638, regioncalls=256, ndraw=128, logz=-501135.84, remainder_fraction=100.0000%, Lmin=-501121.91, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=732, regioncalls=384, ndraw=128, logz=-500731.08, remainder_fraction=100.0000%, Lmin=-500719.78, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=240, ncalls=732, regioncalls=384, ndraw=128, logz=-500420.99, remainder_fraction=100.0000%, Lmin=-500412.11, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=813, regioncalls=512, ndraw=128, logz=-500230.25, remainder_fraction=100.0000%, Lmin=-500222.16, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=280, ncalls=813, regioncalls=512, ndraw=128, logz=-500174.08, remainder_fraction=100.0000%, Lmin=-500165.75, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=320, ncalls=873, regioncalls=640, ndraw=128, logz=-499905.42, remainder_fraction=100.0000%, Lmin=-499898.07, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=873, regioncalls=640, ndraw=128, logz=-499684.35, remainder_fraction=100.0000%, Lmin=-499674.47, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=933, regioncalls=768, ndraw=128, logz=-499526.78, remainder_fraction=100.0000%, Lmin=-499518.11, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=440, ncalls=990, regioncalls=896, ndraw=128, logz=-499362.75, remainder_fraction=100.0000%, Lmin=-499354.40, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=990, regioncalls=896, ndraw=128, logz=-499346.06, remainder_fraction=100.0000%, Lmin=-499339.33, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=480, ncalls=1045, regioncalls=1024, ndraw=128, logz=-499217.19, remainder_fraction=100.0000%, Lmin=-499205.12, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=520, ncalls=1088, regioncalls=1152, ndraw=128, logz=-499029.69, remainder_fraction=100.0000%, Lmin=-499014.37, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=1088, regioncalls=1152, ndraw=128, logz=-498940.90, remainder_fraction=100.0000%, Lmin=-498931.16, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=560, ncalls=1123, regioncalls=1280, ndraw=128, logz=-498843.83, remainder_fraction=100.0000%, Lmin=-498836.53, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=1196, regioncalls=1536, ndraw=128, logz=-498726.86, remainder_fraction=100.0000%, Lmin=-498713.18, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=1226, regioncalls=1664, ndraw=128, logz=-498594.27, remainder_fraction=100.0000%, Lmin=-498580.76, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=640, ncalls=1251, regioncalls=1792, ndraw=128, logz=-498550.78, remainder_fraction=100.0000%, Lmin=-498542.58, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=680, ncalls=1287, regioncalls=1920, ndraw=128, logz=-498370.73, remainder_fraction=100.0000%, Lmin=-498363.17, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=1337, regioncalls=2176, ndraw=128, logz=-498250.23, remainder_fraction=100.0000%, Lmin=-498237.06, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=760, ncalls=1401, regioncalls=2432, ndraw=128, logz=-498145.05, remainder_fraction=100.0000%, Lmin=-498133.69, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=1437, regioncalls=2688, ndraw=128, logz=-497991.53, remainder_fraction=100.0000%, Lmin=-497972.61, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=1455, regioncalls=2816, ndraw=128, logz=-497947.39, remainder_fraction=100.0000%, Lmin=-497935.76, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=840, ncalls=1494, regioncalls=3072, ndraw=128, logz=-497859.26, remainder_fraction=100.0000%, Lmin=-497841.61, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=880, ncalls=1527, regioncalls=3328, ndraw=128, logz=-497720.07, remainder_fraction=100.0000%, Lmin=-497704.25, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=1559, regioncalls=3584, ndraw=128, logz=-497633.20, remainder_fraction=100.0000%, Lmin=-497620.88, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=920, ncalls=1591, regioncalls=3840, ndraw=128, logz=-497569.29, remainder_fraction=100.0000%, Lmin=-497559.10, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=960, ncalls=1641, regioncalls=4224, ndraw=128, logz=-497435.38, remainder_fraction=100.0000%, Lmin=-497425.78, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=1693, regioncalls=4736, ndraw=128, logz=-497308.03, remainder_fraction=100.0000%, Lmin=-497298.81, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=1704, regioncalls=4864, ndraw=128, logz=-497280.99, remainder_fraction=100.0000%, Lmin=-497265.98, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1040, ncalls=1752, regioncalls=5376, ndraw=128, logz=-497120.48, remainder_fraction=100.0000%, Lmin=-497110.05, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=1809, regioncalls=6144, ndraw=128, logz=-496991.53, remainder_fraction=100.0000%, Lmin=-496980.01, Lmax=-846.67 DEBUG ultranest:integrator.py:2610 iteration=1120, ncalls=1860, regioncalls=6784, ndraw=128, logz=-496828.38, remainder_fraction=100.0000%, Lmin=-496818.80, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1160, ncalls=1906, regioncalls=7296, ndraw=128, logz=-496597.66, remainder_fraction=100.0000%, Lmin=-496588.52, Lmax=-229.19 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=1959, regioncalls=8064, ndraw=128, logz=-495915.27, remainder_fraction=100.0000%, Lmin=-495883.80, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1240, ncalls=2018, regioncalls=9088, ndraw=128, logz=-493922.82, remainder_fraction=100.0000%, Lmin=-493845.25, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=2050, regioncalls=9472, ndraw=128, logz=-492888.69, remainder_fraction=100.0000%, Lmin=-492837.70, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1280, ncalls=2080, regioncalls=9984, ndraw=128, logz=-491534.02, remainder_fraction=100.0000%, Lmin=-491486.25, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1320, ncalls=2130, regioncalls=10880, ndraw=128, logz=-487814.63, remainder_fraction=100.0000%, Lmin=-487578.52, Lmax=-229.19 DEBUG ultranest:integrator.py:2610 iteration=1360, ncalls=2180, regioncalls=11776, ndraw=128, logz=-479047.95, remainder_fraction=100.0000%, Lmin=-478730.51, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=2236, regioncalls=13568, ndraw=128, logz=-467590.29, remainder_fraction=100.0000%, Lmin=-467197.20, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=2304, regioncalls=14592, ndraw=128, logz=-458117.57, remainder_fraction=100.0000%, Lmin=-458097.65, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1480, ncalls=2347, regioncalls=16000, ndraw=128, logz=-446788.79, remainder_fraction=100.0000%, Lmin=-446452.99, Lmax=-137.91 DEBUG ultranest:integrator.py:2610 iteration=1520, ncalls=2408, regioncalls=17920, ndraw=128, logz=-430727.37, remainder_fraction=100.0000%, Lmin=-430448.72, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1560, ncalls=2458, regioncalls=19968, ndraw=128, logz=-413498.20, remainder_fraction=100.0000%, Lmin=-413026.67, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=2521, regioncalls=22272, ndraw=128, logz=-379384.75, remainder_fraction=100.0000%, Lmin=-378797.67, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=2555, regioncalls=23424, ndraw=128, logz=-367175.35, remainder_fraction=100.0000%, Lmin=-366497.90, Lmax=-17.03 DEBUG ultranest:integrator.py:2610 iteration=1640, ncalls=2592, regioncalls=24832, ndraw=128, logz=-347124.34, remainder_fraction=100.0000%, Lmin=-346275.59, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1680, ncalls=2660, regioncalls=27648, ndraw=128, logz=-315360.05, remainder_fraction=100.0000%, Lmin=-315266.06, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=2712, regioncalls=30080, ndraw=128, logz=-288095.70, remainder_fraction=100.0000%, Lmin=-287308.57, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1720, ncalls=2726, regioncalls=31232, ndraw=128, logz=-283381.27, remainder_fraction=100.0000%, Lmin=-279597.31, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1760, ncalls=2834, regioncalls=33024, ndraw=128, logz=-251538.82, remainder_fraction=100.0000%, Lmin=-249847.19, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=2906, regioncalls=33152, ndraw=128, logz=-224651.30, remainder_fraction=100.0000%, Lmin=-224588.99, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=2971, regioncalls=33280, ndraw=128, logz=-198168.36, remainder_fraction=100.0000%, Lmin=-197940.18, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1880, ncalls=3030, regioncalls=33408, ndraw=128, logz=-178248.87, remainder_fraction=100.0000%, Lmin=-178172.53, Lmax=-13.22 DEBUG ultranest:integrator.py:2610 iteration=1920, ncalls=3088, regioncalls=33536, ndraw=128, logz=-154606.93, remainder_fraction=100.0000%, Lmin=-154562.77, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=1960, ncalls=3197, regioncalls=33792, ndraw=128, logz=-134803.42, remainder_fraction=100.0000%, Lmin=-134078.66, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=3248, regioncalls=33920, ndraw=128, logz=-118050.81, remainder_fraction=100.0000%, Lmin=-117828.10, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2040, ncalls=3366, regioncalls=34304, ndraw=128, logz=-106216.80, remainder_fraction=100.0000%, Lmin=-105342.65, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2080, ncalls=3485, regioncalls=34688, ndraw=128, logz=-92006.08, remainder_fraction=100.0000%, Lmin=-91832.14, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2120, ncalls=3572, regioncalls=34944, ndraw=128, logz=-77698.21, remainder_fraction=100.0000%, Lmin=-77294.92, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=3683, regioncalls=35328, ndraw=128, logz=-66119.00, remainder_fraction=100.0000%, Lmin=-65995.65, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=3758, regioncalls=35584, ndraw=128, logz=-56368.32, remainder_fraction=100.0000%, Lmin=-56336.47, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2240, ncalls=3888, regioncalls=35968, ndraw=128, logz=-48186.79, remainder_fraction=100.0000%, Lmin=-47662.68, Lmax=-10.13 DEBUG ultranest:integrator.py:2610 iteration=2280, ncalls=4025, regioncalls=36480, ndraw=128, logz=-41627.75, remainder_fraction=100.0000%, Lmin=-41542.91, Lmax=-8.41 DEBUG ultranest:integrator.py:2610 iteration=2320, ncalls=4158, regioncalls=36992, ndraw=128, logz=-34854.93, remainder_fraction=100.0000%, Lmin=-34438.03, Lmax=-8.41 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=4212, regioncalls=37376, ndraw=128, logz=-32311.38, remainder_fraction=100.0000%, Lmin=-32244.02, Lmax=-7.88 DEBUG ultranest:integrator.py:2610 iteration=2360, ncalls=4275, regioncalls=39552, ndraw=128, logz=-29883.30, remainder_fraction=100.0000%, Lmin=-29757.69, Lmax=-7.88 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=4378, regioncalls=39936, ndraw=128, logz=-25256.57, remainder_fraction=100.0000%, Lmin=-25242.32, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2440, ncalls=4463, regioncalls=40320, ndraw=128, logz=-20762.80, remainder_fraction=100.0000%, Lmin=-20722.55, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2480, ncalls=4621, regioncalls=40960, ndraw=128, logz=-17778.12, remainder_fraction=100.0000%, Lmin=-17743.47, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=4763, regioncalls=41600, ndraw=128, logz=-15116.35, remainder_fraction=100.0000%, Lmin=-15054.41, Lmax=-7.50 DEBUG ultranest:integrator.py:2610 iteration=2560, ncalls=4903, regioncalls=42368, ndraw=128, logz=-12610.82, remainder_fraction=100.0000%, Lmin=-12579.89, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=5035, regioncalls=43008, ndraw=128, logz=-10184.21, remainder_fraction=100.0000%, Lmin=-10150.09, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=5178, regioncalls=43776, ndraw=128, logz=-8631.74, remainder_fraction=100.0000%, Lmin=-8602.91, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2680, ncalls=5384, regioncalls=45056, ndraw=128, logz=-7251.27, remainder_fraction=100.0000%, Lmin=-7217.86, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2720, ncalls=5503, regioncalls=45952, ndraw=128, logz=-5986.16, remainder_fraction=100.0000%, Lmin=-5967.35, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2760, ncalls=5644, regioncalls=47232, ndraw=128, logz=-4915.26, remainder_fraction=100.0000%, Lmin=-4874.76, Lmax=-7.30 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([389, 10, 1])) DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=5795, regioncalls=48640, ndraw=128, logz=-3981.64, remainder_fraction=100.0000%, Lmin=-3924.82, Lmax=-7.30 DEBUG ultranest:integrator.py:2610 iteration=2840, ncalls=5921, regioncalls=49920, ndraw=128, logz=-3159.55, remainder_fraction=100.0000%, Lmin=-3140.75, Lmax=-5.20 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([388, 11, 1])) DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=6090, regioncalls=51712, ndraw=128, logz=-2626.72, remainder_fraction=100.0000%, Lmin=-2605.14, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=2920, ncalls=6213, regioncalls=53376, ndraw=128, logz=-2250.49, remainder_fraction=100.0000%, Lmin=-2196.70, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=2960, ncalls=6341, regioncalls=55296, ndraw=128, logz=-1854.86, remainder_fraction=100.0000%, Lmin=-1817.78, Lmax=-5.20 DEBUG ultranest:integrator.py:1987 clustering found some stray points [need_accept=False] (array([1, 2]), array([399, 1])) DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=6475, regioncalls=57472, ndraw=128, logz=-1554.06, remainder_fraction=100.0000%, Lmin=-1539.31, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3040, ncalls=6598, regioncalls=59904, ndraw=128, logz=-1353.42, remainder_fraction=100.0000%, Lmin=-1332.34, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=6663, regioncalls=61312, ndraw=128, logz=-1194.80, remainder_fraction=100.0000%, Lmin=-1163.63, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=6717, regioncalls=62592, ndraw=128, logz=-1066.69, remainder_fraction=100.0000%, Lmin=-1041.75, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3120, ncalls=6850, regioncalls=65408, ndraw=128, logz=-875.97, remainder_fraction=100.0000%, Lmin=-855.57, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=6928, regioncalls=67072, ndraw=128, logz=-732.00, remainder_fraction=100.0000%, Lmin=-712.71, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3160, ncalls=6952, regioncalls=70272, ndraw=128, logz=-689.53, remainder_fraction=100.0000%, Lmin=-670.52, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=7038, regioncalls=78976, ndraw=128, logz=-563.92, remainder_fraction=100.0000%, Lmin=-541.75, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=7131, regioncalls=87424, ndraw=128, logz=-459.16, remainder_fraction=100.0000%, Lmin=-445.06, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3280, ncalls=7228, regioncalls=98816, ndraw=128, logz=-367.03, remainder_fraction=100.0000%, Lmin=-350.86, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3320, ncalls=7336, regioncalls=115200, ndraw=128, logz=-320.34, remainder_fraction=100.0000%, Lmin=-306.59, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3358, ncalls=7426, regioncalls=127872, ndraw=128, logz=-274.37, remainder_fraction=100.0000%, Lmin=-259.98, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3360, ncalls=7432, regioncalls=128640, ndraw=128, logz=-272.39, remainder_fraction=100.0000%, Lmin=-257.69, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=7539, regioncalls=146432, ndraw=128, logz=-233.72, remainder_fraction=100.0000%, Lmin=-219.11, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3434, ncalls=7631, regioncalls=160512, ndraw=128, logz=-204.44, remainder_fraction=100.0000%, Lmin=-189.73, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3440, ncalls=7647, regioncalls=162432, ndraw=128, logz=-201.29, remainder_fraction=100.0000%, Lmin=-186.33, Lmax=-5.20 DEBUG ultranest:integrator.py:2610 iteration=3480, ncalls=7725, regioncalls=176512, ndraw=128, logz=-167.95, remainder_fraction=100.0000%, Lmin=-152.98, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3510, ncalls=7807, regioncalls=193152, ndraw=128, logz=-147.78, remainder_fraction=100.0000%, Lmin=-134.01, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3520, ncalls=7826, regioncalls=198144, ndraw=128, logz=-142.17, remainder_fraction=100.0000%, Lmin=-128.00, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3555, ncalls=7898, regioncalls=221568, ndraw=128, logz=-125.08, remainder_fraction=100.0000%, Lmin=-108.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3560, ncalls=7908, regioncalls=224128, ndraw=128, logz=-118.71, remainder_fraction=100.0000%, Lmin=-104.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3599, ncalls=8022, regioncalls=249856, ndraw=128, logz=-100.41, remainder_fraction=100.0000%, Lmin=-86.29, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3600, ncalls=8025, regioncalls=251136, ndraw=128, logz=-100.06, remainder_fraction=100.0000%, Lmin=-85.86, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3632, ncalls=8103, regioncalls=278272, ndraw=128, logz=-89.63, remainder_fraction=100.0000%, Lmin=-74.63, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3640, ncalls=8122, regioncalls=284416, ndraw=128, logz=-86.46, remainder_fraction=100.0000%, Lmin=-72.54, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3666, ncalls=8218, regioncalls=310144, ndraw=128, logz=-76.89, remainder_fraction=100.0000%, Lmin=-63.03, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3680, ncalls=8257, regioncalls=321280, ndraw=128, logz=-73.17, remainder_fraction=100.0000%, Lmin=-59.46, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3700, ncalls=8304, regioncalls=339840, ndraw=128, logz=-68.15, remainder_fraction=100.0000%, Lmin=-54.31, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3720, ncalls=8358, regioncalls=357888, ndraw=128, logz=-62.69, remainder_fraction=100.0000%, Lmin=-48.99, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3753, ncalls=8449, regioncalls=382848, ndraw=128, logz=-57.13, remainder_fraction=100.0000%, Lmin=-43.96, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3760, ncalls=8483, regioncalls=392960, ndraw=128, logz=-55.79, remainder_fraction=100.0000%, Lmin=-41.79, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3779, ncalls=8551, regioncalls=420608, ndraw=128, logz=-52.00, remainder_fraction=100.0000%, Lmin=-38.43, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3792, ncalls=8591, regioncalls=443136, ndraw=128, logz=-50.36, remainder_fraction=100.0000%, Lmin=-36.85, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3800, ncalls=8616, regioncalls=453504, ndraw=128, logz=-49.27, remainder_fraction=100.0000%, Lmin=-35.57, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3824, ncalls=8676, regioncalls=484736, ndraw=128, logz=-45.99, remainder_fraction=100.0000%, Lmin=-32.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3840, ncalls=8713, regioncalls=498432, ndraw=128, logz=-44.66, remainder_fraction=100.0000%, Lmin=-31.53, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3859, ncalls=8771, regioncalls=531328, ndraw=128, logz=-42.60, remainder_fraction=100.0000%, Lmin=-29.40, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3874, ncalls=8818, regioncalls=556160, ndraw=128, logz=-41.20, remainder_fraction=100.0000%, Lmin=-27.33, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3880, ncalls=8836, regioncalls=566351, ndraw=129, logz=-40.37, remainder_fraction=100.0000%, Lmin=-26.67, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3904, ncalls=8880, regioncalls=594821, ndraw=130, logz=-37.79, remainder_fraction=100.0000%, Lmin=-24.16, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3917, ncalls=8927, regioncalls=621938, ndraw=131, logz=-36.51, remainder_fraction=100.0000%, Lmin=-23.19, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3920, ncalls=8941, regioncalls=628802, ndraw=132, logz=-36.26, remainder_fraction=100.0000%, Lmin=-22.90, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3943, ncalls=8999, regioncalls=668569, ndraw=133, logz=-34.63, remainder_fraction=100.0000%, Lmin=-21.59, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3960, ncalls=9039, regioncalls=690545, ndraw=134, logz=-33.69, remainder_fraction=100.0000%, Lmin=-20.53, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=3982, ncalls=9077, regioncalls=721961, ndraw=136, logz=-32.53, remainder_fraction=99.9999%, Lmin=-19.42, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4000, ncalls=9113, regioncalls=748043, ndraw=138, logz=-31.54, remainder_fraction=99.9997%, Lmin=-18.39, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4019, ncalls=9161, regioncalls=783043, ndraw=140, logz=-30.52, remainder_fraction=99.9993%, Lmin=-17.38, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4037, ncalls=9215, regioncalls=817833, ndraw=142, logz=-29.65, remainder_fraction=99.9983%, Lmin=-16.67, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4040, ncalls=9232, regioncalls=828921, ndraw=144, logz=-29.52, remainder_fraction=99.9980%, Lmin=-16.62, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4050, ncalls=9263, regioncalls=861917, ndraw=146, logz=-29.04, remainder_fraction=99.9968%, Lmin=-15.87, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4063, ncalls=9294, regioncalls=901849, ndraw=149, logz=-28.43, remainder_fraction=99.9940%, Lmin=-15.45, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4078, ncalls=9329, regioncalls=939849, ndraw=152, logz=-27.85, remainder_fraction=99.9894%, Lmin=-15.04, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4080, ncalls=9332, regioncalls=945739, ndraw=155, logz=-27.79, remainder_fraction=99.9886%, Lmin=-14.93, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4098, ncalls=9377, regioncalls=985239, ndraw=158, logz=-27.17, remainder_fraction=99.9784%, Lmin=-14.31, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4112, ncalls=9414, regioncalls=1028709, ndraw=161, logz=-26.74, remainder_fraction=99.9667%, Lmin=-14.02, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4120, ncalls=9453, regioncalls=1060389, ndraw=165, logz=-26.50, remainder_fraction=99.9573%, Lmin=-13.69, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4134, ncalls=9488, regioncalls=1097907, ndraw=169, logz=-26.09, remainder_fraction=99.9352%, Lmin=-13.23, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4141, ncalls=9507, regioncalls=1123338, ndraw=173, logz=-25.88, remainder_fraction=99.9201%, Lmin=-13.08, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4155, ncalls=9532, regioncalls=1161924, ndraw=177, logz=-25.50, remainder_fraction=99.8810%, Lmin=-12.74, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4160, ncalls=9541, regioncalls=1170431, ndraw=181, logz=-25.37, remainder_fraction=99.8629%, Lmin=-12.59, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4180, ncalls=9584, regioncalls=1210946, ndraw=185, logz=-24.88, remainder_fraction=99.7773%, Lmin=-12.17, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4190, ncalls=9620, regioncalls=1251014, ndraw=189, logz=-24.66, remainder_fraction=99.7266%, Lmin=-12.04, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4200, ncalls=9641, regioncalls=1277648, ndraw=193, logz=-24.46, remainder_fraction=99.6617%, Lmin=-11.89, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4213, ncalls=9674, regioncalls=1315866, ndraw=197, logz=-24.19, remainder_fraction=99.5512%, Lmin=-11.56, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4227, ncalls=9708, regioncalls=1359498, ndraw=202, logz=-23.92, remainder_fraction=99.4166%, Lmin=-11.33, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4234, ncalls=9723, regioncalls=1389306, ndraw=207, logz=-23.79, remainder_fraction=99.3296%, Lmin=-11.21, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4240, ncalls=9742, regioncalls=1410930, ndraw=212, logz=-23.68, remainder_fraction=99.2541%, Lmin=-11.07, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4252, ncalls=9768, regioncalls=1459321, ndraw=217, logz=-23.47, remainder_fraction=99.0787%, Lmin=-10.85, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4265, ncalls=9803, regioncalls=1501723, ndraw=222, logz=-23.23, remainder_fraction=98.8218%, Lmin=-10.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4275, ncalls=9835, regioncalls=1546669, ndraw=227, logz=-23.07, remainder_fraction=98.6134%, Lmin=-10.55, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4280, ncalls=9856, regioncalls=1571493, ndraw=232, logz=-23.00, remainder_fraction=98.5096%, Lmin=-10.51, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4298, ncalls=9888, regioncalls=1616049, ndraw=237, logz=-22.75, remainder_fraction=98.0947%, Lmin=-10.30, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4304, ncalls=9921, regioncalls=1661004, ndraw=243, logz=-22.67, remainder_fraction=97.9156%, Lmin=-10.22, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4316, ncalls=9955, regioncalls=1708314, ndraw=249, logz=-22.51, remainder_fraction=97.5853%, Lmin=-10.13, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4320, ncalls=9973, regioncalls=1738149, ndraw=255, logz=-22.46, remainder_fraction=97.4659%, Lmin=-10.10, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4331, ncalls=9993, regioncalls=1788000, ndraw=261, logz=-22.33, remainder_fraction=97.1706%, Lmin=-9.97, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4347, ncalls=10027, regioncalls=1836327, ndraw=267, logz=-22.16, remainder_fraction=96.5855%, Lmin=-9.83, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4355, ncalls=10042, regioncalls=1879734, ndraw=273, logz=-22.07, remainder_fraction=96.3666%, Lmin=-9.78, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4360, ncalls=10062, regioncalls=1918236, ndraw=279, logz=-22.02, remainder_fraction=96.1811%, Lmin=-9.71, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4370, ncalls=10086, regioncalls=1971531, ndraw=285, logz=-21.92, remainder_fraction=95.7736%, Lmin=-9.64, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4379, ncalls=10116, regioncalls=2027595, ndraw=292, logz=-21.84, remainder_fraction=95.4674%, Lmin=-9.57, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4386, ncalls=10145, regioncalls=2085302, ndraw=299, logz=-21.77, remainder_fraction=95.2195%, Lmin=-9.50, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4394, ncalls=10169, regioncalls=2121716, ndraw=306, logz=-21.70, remainder_fraction=94.8418%, Lmin=-9.44, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4400, ncalls=10185, regioncalls=2139244, ndraw=313, logz=-21.65, remainder_fraction=94.5458%, Lmin=-9.36, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4406, ncalls=10212, regioncalls=2190764, ndraw=320, logz=-21.59, remainder_fraction=94.2499%, Lmin=-9.29, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4412, ncalls=10227, regioncalls=2228369, ndraw=327, logz=-21.54, remainder_fraction=94.1118%, Lmin=-9.25, Lmax=-5.11 DEBUG ultranest:integrator.py:2610 iteration=4421, ncalls=10253, regioncalls=2286819, ndraw=334, logz=-21.46, remainder_fraction=93.7611%, Lmin=-9.20, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4435, ncalls=10279, regioncalls=2338992, ndraw=341, logz=-21.35, remainder_fraction=93.1867%, Lmin=-9.16, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4440, ncalls=10292, regioncalls=2356740, ndraw=348, logz=-21.31, remainder_fraction=92.9450%, Lmin=-9.15, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4448, ncalls=10316, regioncalls=2412120, ndraw=355, logz=-21.26, remainder_fraction=92.7016%, Lmin=-9.11, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4456, ncalls=10337, regioncalls=2474384, ndraw=362, logz=-21.20, remainder_fraction=92.2318%, Lmin=-9.08, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4465, ncalls=10366, regioncalls=2529884, ndraw=370, logz=-21.14, remainder_fraction=91.7119%, Lmin=-9.04, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4472, ncalls=10387, regioncalls=2586584, ndraw=378, logz=-21.10, remainder_fraction=91.3053%, Lmin=-9.01, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4480, ncalls=10401, regioncalls=2624026, ndraw=386, logz=-21.05, remainder_fraction=90.8454%, Lmin=-8.97, Lmax=-5.05 DEBUG ultranest:integrator.py:2610 iteration=4489, ncalls=10435, regioncalls=2676822, ndraw=394, logz=-21.00, remainder_fraction=90.5391%, Lmin=-8.93, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4500, ncalls=10460, regioncalls=2732298, ndraw=402, logz=-20.93, remainder_fraction=89.8098%, Lmin=-8.89, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4509, ncalls=10487, regioncalls=2785188, ndraw=410, logz=-20.89, remainder_fraction=89.4904%, Lmin=-8.86, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4517, ncalls=10523, regioncalls=2893868, ndraw=418, logz=-20.84, remainder_fraction=88.9873%, Lmin=-8.82, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4520, ncalls=10535, regioncalls=2928882, ndraw=427, logz=-20.83, remainder_fraction=88.7797%, Lmin=-8.80, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4527, ncalls=10556, regioncalls=2989922, ndraw=436, logz=-20.79, remainder_fraction=88.5460%, Lmin=-8.79, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4535, ncalls=10584, regioncalls=3062457, ndraw=445, logz=-20.75, remainder_fraction=88.4498%, Lmin=-8.77, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4547, ncalls=10615, regioncalls=3120115, ndraw=454, logz=-20.70, remainder_fraction=88.2664%, Lmin=-8.72, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4555, ncalls=10643, regioncalls=3184935, ndraw=463, logz=-20.66, remainder_fraction=87.7047%, Lmin=-8.70, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4560, ncalls=10649, regioncalls=3193903, ndraw=472, logz=-20.64, remainder_fraction=87.4259%, Lmin=-8.69, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4568, ncalls=10674, regioncalls=3258838, ndraw=481, logz=-20.61, remainder_fraction=86.8895%, Lmin=-8.65, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4574, ncalls=10697, regioncalls=3318618, ndraw=490, logz=-20.58, remainder_fraction=86.4964%, Lmin=-8.62, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4582, ncalls=10731, regioncalls=3392470, ndraw=499, logz=-20.55, remainder_fraction=85.9932%, Lmin=-8.59, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4591, ncalls=10752, regioncalls=3427082, ndraw=509, logz=-20.51, remainder_fraction=85.3417%, Lmin=-8.57, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4597, ncalls=10769, regioncalls=3480436, ndraw=518, logz=-20.49, remainder_fraction=85.0022%, Lmin=-8.53, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4599, ncalls=10789, regioncalls=3556468, ndraw=528, logz=-20.48, remainder_fraction=84.8535%, Lmin=-8.52, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4600, ncalls=10794, regioncalls=3570456, ndraw=538, logz=-20.47, remainder_fraction=84.7845%, Lmin=-8.52, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4610, ncalls=10822, regioncalls=3637312, ndraw=548, logz=-20.44, remainder_fraction=84.2754%, Lmin=-8.49, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4617, ncalls=10843, regioncalls=3693670, ndraw=558, logz=-20.41, remainder_fraction=83.7745%, Lmin=-8.47, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4626, ncalls=10868, regioncalls=3752174, ndraw=568, logz=-20.38, remainder_fraction=83.3895%, Lmin=-8.44, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4632, ncalls=10889, regioncalls=3816332, ndraw=578, logz=-20.35, remainder_fraction=83.2442%, Lmin=-8.41, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4636, ncalls=10906, regioncalls=3874544, ndraw=588, logz=-20.34, remainder_fraction=82.9396%, Lmin=-8.40, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4639, ncalls=10922, regioncalls=3936736, ndraw=598, logz=-20.33, remainder_fraction=82.6913%, Lmin=-8.40, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4640, ncalls=10925, regioncalls=3946464, ndraw=608, logz=-20.33, remainder_fraction=82.6197%, Lmin=-8.39, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4648, ncalls=10955, regioncalls=4010736, ndraw=618, logz=-20.30, remainder_fraction=82.4187%, Lmin=-8.37, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4656, ncalls=10978, regioncalls=4072908, ndraw=628, logz=-20.27, remainder_fraction=81.8463%, Lmin=-8.35, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4661, ncalls=10996, regioncalls=4135432, ndraw=638, logz=-20.26, remainder_fraction=81.7872%, Lmin=-8.33, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4667, ncalls=11027, regioncalls=4226152, ndraw=648, logz=-20.24, remainder_fraction=81.3443%, Lmin=-8.31, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4671, ncalls=11045, regioncalls=4288004, ndraw=658, logz=-20.22, remainder_fraction=81.0399%, Lmin=-8.30, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4679, ncalls=11062, regioncalls=4352800, ndraw=668, logz=-20.20, remainder_fraction=80.5628%, Lmin=-8.28, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4680, ncalls=11065, regioncalls=4372462, ndraw=678, logz=-20.19, remainder_fraction=80.4832%, Lmin=-8.26, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4688, ncalls=11088, regioncalls=4452958, ndraw=688, logz=-20.17, remainder_fraction=79.9959%, Lmin=-8.25, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4694, ncalls=11106, regioncalls=4516476, ndraw=698, logz=-20.15, remainder_fraction=79.5399%, Lmin=-8.24, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4700, ncalls=11122, regioncalls=4588085, ndraw=709, logz=-20.13, remainder_fraction=79.0910%, Lmin=-8.22, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4703, ncalls=11145, regioncalls=4660805, ndraw=720, logz=-20.13, remainder_fraction=78.8509%, Lmin=-8.20, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4707, ncalls=11165, regioncalls=4731712, ndraw=731, logz=-20.11, remainder_fraction=78.5666%, Lmin=-8.19, Lmax=-4.93 DEBUG ultranest:integrator.py:2610 iteration=4708, ncalls=11179, regioncalls=4799234, ndraw=742, logz=-20.11, remainder_fraction=78.5254%, Lmin=-8.19, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4718, ncalls=11199, regioncalls=4861733, ndraw=753, logz=-20.08, remainder_fraction=78.2526%, Lmin=-8.16, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4720, ncalls=11211, regioncalls=4903753, ndraw=764, logz=-20.08, remainder_fraction=78.1027%, Lmin=-8.16, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4723, ncalls=11223, regioncalls=4981253, ndraw=775, logz=-20.07, remainder_fraction=77.8723%, Lmin=-8.15, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4725, ncalls=11238, regioncalls=5044919, ndraw=786, logz=-20.06, remainder_fraction=77.7045%, Lmin=-8.14, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4728, ncalls=11262, regioncalls=5120634, ndraw=797, logz=-20.05, remainder_fraction=77.4463%, Lmin=-8.14, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4734, ncalls=11275, regioncalls=5186890, ndraw=808, logz=-20.04, remainder_fraction=77.0255%, Lmin=-8.13, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4743, ncalls=11303, regioncalls=5258143, ndraw=819, logz=-20.01, remainder_fraction=76.5814%, Lmin=-8.11, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4747, ncalls=11326, regioncalls=5322961, ndraw=831, logz=-20.00, remainder_fraction=76.2444%, Lmin=-8.09, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4753, ncalls=11347, regioncalls=5414848, ndraw=843, logz=-19.99, remainder_fraction=75.8210%, Lmin=-8.08, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4757, ncalls=11369, regioncalls=5497783, ndraw=855, logz=-19.98, remainder_fraction=75.5731%, Lmin=-8.06, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4760, ncalls=11384, regioncalls=5581015, ndraw=867, logz=-19.97, remainder_fraction=75.4841%, Lmin=-8.05, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4767, ncalls=11407, regioncalls=5647819, ndraw=879, logz=-19.95, remainder_fraction=75.0766%, Lmin=-8.04, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4770, ncalls=11417, regioncalls=5677222, ndraw=891, logz=-19.95, remainder_fraction=74.8395%, Lmin=-8.04, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4800, ncalls=11523, regioncalls=5694379, ndraw=903, logz=-19.87, remainder_fraction=72.6733%, Lmin=-7.98, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4840, ncalls=11637, regioncalls=5714487, ndraw=914, logz=-19.79, remainder_fraction=70.4414%, Lmin=-7.89, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4880, ncalls=11749, regioncalls=5732062, ndraw=925, logz=-19.71, remainder_fraction=68.1763%, Lmin=-7.80, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4920, ncalls=11872, regioncalls=5758242, ndraw=935, logz=-19.64, remainder_fraction=65.5779%, Lmin=-7.70, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4950, ncalls=11971, regioncalls=5774290, ndraw=944, logz=-19.59, remainder_fraction=63.3101%, Lmin=-7.65, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=4960, ncalls=12011, regioncalls=5788585, ndraw=953, logz=-19.57, remainder_fraction=62.6248%, Lmin=-7.63, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=5000, ncalls=12149, regioncalls=5835723, ndraw=962, logz=-19.51, remainder_fraction=60.8928%, Lmin=-7.56, Lmax=-4.87 DEBUG ultranest:integrator.py:2610 iteration=5037, ncalls=12261, regioncalls=5886163, ndraw=970, logz=-19.46, remainder_fraction=58.6482%, Lmin=-7.52, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5040, ncalls=12269, regioncalls=5890075, ndraw=978, logz=-19.46, remainder_fraction=58.3816%, Lmin=-7.52, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5071, ncalls=12384, regioncalls=5934445, ndraw=986, logz=-19.42, remainder_fraction=56.8168%, Lmin=-7.46, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5080, ncalls=12421, regioncalls=5949340, ndraw=993, logz=-19.41, remainder_fraction=56.1009%, Lmin=-7.45, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5109, ncalls=12541, regioncalls=5996340, ndraw=1000, logz=-19.37, remainder_fraction=54.0555%, Lmin=-7.42, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5120, ncalls=12582, regioncalls=6013459, ndraw=1007, logz=-19.36, remainder_fraction=53.4702%, Lmin=-7.40, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5130, ncalls=12615, regioncalls=6029683, ndraw=1014, logz=-19.35, remainder_fraction=53.1077%, Lmin=-7.39, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5160, ncalls=12717, regioncalls=6073543, ndraw=1020, logz=-19.32, remainder_fraction=52.0299%, Lmin=-7.34, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5193, ncalls=12831, regioncalls=6124843, ndraw=1026, logz=-19.29, remainder_fraction=50.9957%, Lmin=-7.29, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5200, ncalls=12855, regioncalls=6133099, ndraw=1032, logz=-19.28, remainder_fraction=50.7015%, Lmin=-7.28, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5224, ncalls=12928, regioncalls=6172543, ndraw=1038, logz=-19.26, remainder_fraction=49.6906%, Lmin=-7.25, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5240, ncalls=12971, regioncalls=6196555, ndraw=1044, logz=-19.25, remainder_fraction=48.9634%, Lmin=-7.22, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5274, ncalls=13076, regioncalls=6251155, ndraw=1050, logz=-19.22, remainder_fraction=47.8735%, Lmin=-7.18, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5280, ncalls=13091, regioncalls=6263815, ndraw=1055, logz=-19.21, remainder_fraction=47.6332%, Lmin=-7.17, Lmax=-4.79 DEBUG ultranest:integrator.py:2610 iteration=5297, ncalls=13156, regioncalls=6313635, ndraw=1060, logz=-19.20, remainder_fraction=47.3198%, Lmin=-7.14, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5310, ncalls=13200, regioncalls=6339195, ndraw=1065, logz=-19.19, remainder_fraction=47.1491%, Lmin=-7.12, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5320, ncalls=13224, regioncalls=6352035, ndraw=1070, logz=-19.18, remainder_fraction=46.5334%, Lmin=-7.10, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5360, ncalls=13334, regioncalls=6382135, ndraw=1075, logz=-19.16, remainder_fraction=45.0622%, Lmin=-7.05, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5400, ncalls=13412, regioncalls=6400495, ndraw=1080, logz=-19.13, remainder_fraction=43.4297%, Lmin=-6.99, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5440, ncalls=13478, regioncalls=6423259, ndraw=1084, logz=-19.10, remainder_fraction=41.8477%, Lmin=-6.92, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5480, ncalls=13552, regioncalls=6467867, ndraw=1088, logz=-19.08, remainder_fraction=40.5377%, Lmin=-6.81, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5520, ncalls=13608, regioncalls=6508271, ndraw=1092, logz=-19.06, remainder_fraction=38.7578%, Lmin=-6.61, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5560, ncalls=13669, regioncalls=6541121, ndraw=1095, logz=-19.03, remainder_fraction=37.2477%, Lmin=-6.47, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5595, ncalls=13733, regioncalls=6583943, ndraw=1098, logz=-19.01, remainder_fraction=35.8584%, Lmin=-6.37, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5600, ncalls=13742, regioncalls=6591650, ndraw=1101, logz=-19.00, remainder_fraction=35.6499%, Lmin=-6.34, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5640, ncalls=13815, regioncalls=6652370, ndraw=1104, logz=-18.98, remainder_fraction=33.8939%, Lmin=-6.25, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5670, ncalls=13868, regioncalls=6701078, ndraw=1107, logz=-18.96, remainder_fraction=32.8648%, Lmin=-6.16, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5680, ncalls=13884, regioncalls=6713288, ndraw=1110, logz=-18.95, remainder_fraction=32.3776%, Lmin=-6.14, Lmax=-4.77 DEBUG ultranest:integrator.py:2610 iteration=5716, ncalls=13950, regioncalls=6763373, ndraw=1113, logz=-18.93, remainder_fraction=30.8652%, Lmin=-6.06, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5720, ncalls=13956, regioncalls=6770069, ndraw=1116, logz=-18.93, remainder_fraction=30.6636%, Lmin=-6.05, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5750, ncalls=14020, regioncalls=6817067, ndraw=1119, logz=-18.91, remainder_fraction=29.4383%, Lmin=-6.00, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5760, ncalls=14045, regioncalls=6832775, ndraw=1122, logz=-18.90, remainder_fraction=29.0635%, Lmin=-5.98, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5787, ncalls=14091, regioncalls=6878900, ndraw=1125, logz=-18.89, remainder_fraction=27.9423%, Lmin=-5.93, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5800, ncalls=14112, regioncalls=6900332, ndraw=1128, logz=-18.88, remainder_fraction=27.3878%, Lmin=-5.91, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5819, ncalls=14145, regioncalls=6945532, ndraw=1130, logz=-18.87, remainder_fraction=26.7142%, Lmin=-5.87, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5840, ncalls=14178, regioncalls=6985187, ndraw=1133, logz=-18.86, remainder_fraction=25.9455%, Lmin=-5.83, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5852, ncalls=14199, regioncalls=7026083, ndraw=1136, logz=-18.85, remainder_fraction=25.3607%, Lmin=-5.80, Lmax=-4.73 DEBUG ultranest:integrator.py:2610 iteration=5874, ncalls=14229, regioncalls=7073921, ndraw=1139, logz=-18.84, remainder_fraction=24.6629%, Lmin=-5.75, Lmax=-4.68 DEBUG ultranest:integrator.py:2610 iteration=5880, ncalls=14243, regioncalls=7088767, ndraw=1142, logz=-18.84, remainder_fraction=24.4625%, Lmin=-5.74, Lmax=-4.68 DEBUG ultranest:integrator.py:2610 iteration=5903, ncalls=14282, regioncalls=7134567, ndraw=1145, logz=-18.83, remainder_fraction=23.6728%, Lmin=-5.70, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5919, ncalls=14317, regioncalls=7189671, ndraw=1148, logz=-18.82, remainder_fraction=23.0676%, Lmin=-5.67, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5920, ncalls=14319, regioncalls=7190822, ndraw=1151, logz=-18.82, remainder_fraction=23.0190%, Lmin=-5.67, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5940, ncalls=14346, regioncalls=7227750, ndraw=1154, logz=-18.81, remainder_fraction=22.3083%, Lmin=-5.64, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5960, ncalls=14374, regioncalls=7260146, ndraw=1157, logz=-18.80, remainder_fraction=21.7002%, Lmin=-5.60, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5969, ncalls=14398, regioncalls=7309983, ndraw=1159, logz=-18.80, remainder_fraction=21.3183%, Lmin=-5.58, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=5982, ncalls=14428, regioncalls=7361111, ndraw=1162, logz=-18.79, remainder_fraction=20.8148%, Lmin=-5.56, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=6000, ncalls=14456, regioncalls=7404216, ndraw=1165, logz=-18.78, remainder_fraction=20.1081%, Lmin=-5.53, Lmax=-4.64 DEBUG ultranest:integrator.py:2610 iteration=6021, ncalls=14493, regioncalls=7449768, ndraw=1168, logz=-18.78, remainder_fraction=19.4889%, Lmin=-5.51, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6034, ncalls=14519, regioncalls=7488411, ndraw=1171, logz=-18.77, remainder_fraction=19.0872%, Lmin=-5.49, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6040, ncalls=14529, regioncalls=7509543, ndraw=1174, logz=-18.77, remainder_fraction=18.9037%, Lmin=-5.48, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6054, ncalls=14552, regioncalls=7560154, ndraw=1177, logz=-18.76, remainder_fraction=18.4863%, Lmin=-5.46, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6072, ncalls=14584, regioncalls=7610894, ndraw=1180, logz=-18.75, remainder_fraction=17.8775%, Lmin=-5.43, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6080, ncalls=14600, regioncalls=7639286, ndraw=1183, logz=-18.75, remainder_fraction=17.6977%, Lmin=-5.41, Lmax=-4.62 DEBUG ultranest:integrator.py:2610 iteration=6097, ncalls=14629, regioncalls=7684354, ndraw=1186, logz=-18.74, remainder_fraction=17.3184%, Lmin=-5.39, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6109, ncalls=14653, regioncalls=7736670, ndraw=1189, logz=-18.74, remainder_fraction=16.9581%, Lmin=-5.37, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6120, ncalls=14671, regioncalls=7761702, ndraw=1192, logz=-18.74, remainder_fraction=16.6429%, Lmin=-5.36, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6131, ncalls=14697, regioncalls=7813087, ndraw=1195, logz=-18.73, remainder_fraction=16.3472%, Lmin=-5.34, Lmax=-4.50 DEBUG ultranest:integrator.py:2610 iteration=6144, ncalls=14713, regioncalls=7866997, ndraw=1198, logz=-18.73, remainder_fraction=15.9765%, Lmin=-5.33, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6153, ncalls=14729, regioncalls=7916238, ndraw=1201, logz=-18.72, remainder_fraction=15.6767%, Lmin=-5.32, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6160, ncalls=14741, regioncalls=7941522, ndraw=1204, logz=-18.72, remainder_fraction=15.4596%, Lmin=-5.30, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6174, ncalls=14762, regioncalls=7987388, ndraw=1207, logz=-18.72, remainder_fraction=15.0667%, Lmin=-5.28, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6185, ncalls=14779, regioncalls=8041838, ndraw=1210, logz=-18.71, remainder_fraction=14.7469%, Lmin=-5.28, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6200, ncalls=14806, regioncalls=8081900, ndraw=1214, logz=-18.71, remainder_fraction=14.3593%, Lmin=-5.26, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6210, ncalls=14822, regioncalls=8144018, ndraw=1218, logz=-18.71, remainder_fraction=14.1013%, Lmin=-5.24, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6220, ncalls=14848, regioncalls=8201452, ndraw=1222, logz=-18.70, remainder_fraction=13.8115%, Lmin=-5.24, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6235, ncalls=14880, regioncalls=8254170, ndraw=1226, logz=-18.70, remainder_fraction=13.4538%, Lmin=-5.22, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6240, ncalls=14900, regioncalls=8289840, ndraw=1230, logz=-18.70, remainder_fraction=13.3422%, Lmin=-5.22, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6256, ncalls=14929, regioncalls=8340434, ndraw=1234, logz=-18.69, remainder_fraction=12.9616%, Lmin=-5.21, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6269, ncalls=14953, regioncalls=8389954, ndraw=1238, logz=-18.69, remainder_fraction=12.6697%, Lmin=-5.19, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6278, ncalls=14971, regioncalls=8443360, ndraw=1242, logz=-18.69, remainder_fraction=12.4724%, Lmin=-5.18, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6280, ncalls=14974, regioncalls=8453328, ndraw=1246, logz=-18.68, remainder_fraction=12.4234%, Lmin=-5.18, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6290, ncalls=14995, regioncalls=8507078, ndraw=1250, logz=-18.68, remainder_fraction=12.1763%, Lmin=-5.17, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6297, ncalls=15010, regioncalls=8558492, ndraw=1254, logz=-18.68, remainder_fraction=12.0339%, Lmin=-5.17, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6308, ncalls=15030, regioncalls=8600006, ndraw=1258, logz=-18.68, remainder_fraction=11.7642%, Lmin=-5.16, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6320, ncalls=15050, regioncalls=8641652, ndraw=1262, logz=-18.67, remainder_fraction=11.4831%, Lmin=-5.15, Lmax=-4.47 DEBUG ultranest:integrator.py:2610 iteration=6329, ncalls=15078, regioncalls=8698622, ndraw=1266, logz=-18.67, remainder_fraction=11.2964%, Lmin=-5.13, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6337, ncalls=15101, regioncalls=8755772, ndraw=1270, logz=-18.67, remainder_fraction=11.1156%, Lmin=-5.13, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6346, ncalls=15124, regioncalls=8813102, ndraw=1274, logz=-18.67, remainder_fraction=10.9322%, Lmin=-5.12, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6356, ncalls=15146, regioncalls=8884726, ndraw=1279, logz=-18.67, remainder_fraction=10.7259%, Lmin=-5.11, Lmax=-4.29 DEBUG ultranest:integrator.py:2610 iteration=6360, ncalls=15154, regioncalls=8905270, ndraw=1284, logz=-18.66, remainder_fraction=10.6661%, Lmin=-5.11, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6368, ncalls=15172, regioncalls=8967142, ndraw=1289, logz=-18.66, remainder_fraction=10.5070%, Lmin=-5.10, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6376, ncalls=15188, regioncalls=9027960, ndraw=1294, logz=-18.66, remainder_fraction=10.3402%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6383, ncalls=15204, regioncalls=9082518, ndraw=1299, logz=-18.66, remainder_fraction=10.2111%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6390, ncalls=15221, regioncalls=9135982, ndraw=1304, logz=-18.66, remainder_fraction=10.0700%, Lmin=-5.09, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6397, ncalls=15240, regioncalls=9204050, ndraw=1309, logz=-18.66, remainder_fraction=9.9304%, Lmin=-5.08, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6400, ncalls=15261, regioncalls=9247412, ndraw=1314, logz=-18.65, remainder_fraction=9.8669%, Lmin=-5.08, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6415, ncalls=15286, regioncalls=9317319, ndraw=1319, logz=-18.65, remainder_fraction=9.5953%, Lmin=-5.07, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6421, ncalls=15312, regioncalls=9370279, ndraw=1324, logz=-18.65, remainder_fraction=9.4904%, Lmin=-5.06, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6434, ncalls=15334, regioncalls=9427426, ndraw=1329, logz=-18.65, remainder_fraction=9.2431%, Lmin=-5.05, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6440, ncalls=15343, regioncalls=9460776, ndraw=1334, logz=-18.65, remainder_fraction=9.1334%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6442, ncalls=15361, regioncalls=9530404, ndraw=1339, logz=-18.65, remainder_fraction=9.0937%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6449, ncalls=15381, regioncalls=9589584, ndraw=1345, logz=-18.64, remainder_fraction=8.9603%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6455, ncalls=15401, regioncalls=9653081, ndraw=1351, logz=-18.64, remainder_fraction=8.8451%, Lmin=-5.04, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6463, ncalls=15414, regioncalls=9703290, ndraw=1357, logz=-18.64, remainder_fraction=8.7111%, Lmin=-5.03, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6471, ncalls=15431, regioncalls=9759173, ndraw=1363, logz=-18.64, remainder_fraction=8.5736%, Lmin=-5.02, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6478, ncalls=15446, regioncalls=9823516, ndraw=1369, logz=-18.64, remainder_fraction=8.4534%, Lmin=-5.02, Lmax=-4.28 DEBUG ultranest:integrator.py:2610 iteration=6480, ncalls=15450, regioncalls=9827641, ndraw=1375, logz=-18.64, remainder_fraction=8.4185%, Lmin=-5.02, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6491, ncalls=15479, regioncalls=9898072, ndraw=1381, logz=-18.64, remainder_fraction=8.2800%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6494, ncalls=15496, regioncalls=9954939, ndraw=1387, logz=-18.64, remainder_fraction=8.2410%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6497, ncalls=15521, regioncalls=10007873, ndraw=1393, logz=-18.64, remainder_fraction=8.1899%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6502, ncalls=15545, regioncalls=10066631, ndraw=1399, logz=-18.63, remainder_fraction=8.1117%, Lmin=-5.01, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6511, ncalls=15564, regioncalls=10121426, ndraw=1405, logz=-18.63, remainder_fraction=7.9896%, Lmin=-4.99, Lmax=-4.18 DEBUG ultranest:integrator.py:2610 iteration=6516, ncalls=15585, regioncalls=10199031, ndraw=1411, logz=-18.63, remainder_fraction=7.9090%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6520, ncalls=15595, regioncalls=10234456, ndraw=1417, logz=-18.63, remainder_fraction=7.8652%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6525, ncalls=15609, regioncalls=10282838, ndraw=1423, logz=-18.63, remainder_fraction=7.7826%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6528, ncalls=15625, regioncalls=10335711, ndraw=1429, logz=-18.63, remainder_fraction=7.7349%, Lmin=-4.98, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6537, ncalls=15646, regioncalls=10387371, ndraw=1435, logz=-18.63, remainder_fraction=7.5932%, Lmin=-4.97, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6544, ncalls=15665, regioncalls=10443570, ndraw=1441, logz=-18.63, remainder_fraction=7.4859%, Lmin=-4.97, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6548, ncalls=15686, regioncalls=10498556, ndraw=1447, logz=-18.63, remainder_fraction=7.4407%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6554, ncalls=15698, regioncalls=10552317, ndraw=1453, logz=-18.63, remainder_fraction=7.3493%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6559, ncalls=15716, regioncalls=10606300, ndraw=1459, logz=-18.62, remainder_fraction=7.2836%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6560, ncalls=15723, regioncalls=10620950, ndraw=1465, logz=-18.62, remainder_fraction=7.2683%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6562, ncalls=15734, regioncalls=10685674, ndraw=1471, logz=-18.62, remainder_fraction=7.2362%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6569, ncalls=15750, regioncalls=10749185, ndraw=1477, logz=-18.62, remainder_fraction=7.1337%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6570, ncalls=15755, regioncalls=10752151, ndraw=1483, logz=-18.62, remainder_fraction=7.1162%, Lmin=-4.96, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6600, ncalls=15832, regioncalls=10768530, ndraw=1489, logz=-18.62, remainder_fraction=6.7089%, Lmin=-4.94, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6640, ncalls=15949, regioncalls=10795440, ndraw=1495, logz=-18.61, remainder_fraction=6.1782%, Lmin=-4.92, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6680, ncalls=16038, regioncalls=10816440, ndraw=1500, logz=-18.61, remainder_fraction=5.7029%, Lmin=-4.89, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6720, ncalls=16183, regioncalls=10860085, ndraw=1505, logz=-18.60, remainder_fraction=5.2518%, Lmin=-4.87, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6758, ncalls=16309, regioncalls=10888756, ndraw=1509, logz=-18.60, remainder_fraction=4.8541%, Lmin=-4.85, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6760, ncalls=16309, regioncalls=10888756, ndraw=1513, logz=-18.60, remainder_fraction=4.8403%, Lmin=-4.84, Lmax=-4.13 DEBUG ultranest:integrator.py:2610 iteration=6800, ncalls=16412, regioncalls=10922130, ndraw=1517, logz=-18.59, remainder_fraction=4.4695%, Lmin=-4.82, Lmax=-4.10 DEBUG ultranest:integrator.py:2610 iteration=6815, ncalls=16472, regioncalls=10944945, ndraw=1521, logz=-18.59, remainder_fraction=4.3337%, Lmin=-4.82, Lmax=-4.07 DEBUG ultranest:integrator.py:2610 iteration=6840, ncalls=16535, regioncalls=10970853, ndraw=1524, logz=-18.59, remainder_fraction=4.1250%, Lmin=-4.81, Lmax=-4.07 DEBUG ultranest:integrator.py:2610 iteration=6880, ncalls=16635, regioncalls=10984596, ndraw=1527, logz=-18.59, remainder_fraction=3.8232%, Lmin=-4.79, Lmax=-3.94 DEBUG ultranest:integrator.py:2610 iteration=6920, ncalls=16752, regioncalls=11006016, ndraw=1530, logz=-18.58, remainder_fraction=3.5781%, Lmin=-4.77, Lmax=-3.94 DEBUG ultranest:integrator.py:2610 iteration=6930, ncalls=16776, regioncalls=11010612, ndraw=1532, logz=-18.58, remainder_fraction=3.5166%, Lmin=-4.77, Lmax=-3.89 DEBUG ultranest:integrator.py:2610 iteration=6960, ncalls=16850, regioncalls=11024418, ndraw=1534, logz=-18.58, remainder_fraction=3.3495%, Lmin=-4.76, Lmax=-3.89 DEBUG ultranest:integrator.py:2610 iteration=7000, ncalls=16951, regioncalls=11042850, ndraw=1536, logz=-18.58, remainder_fraction=3.1207%, Lmin=-4.74, Lmax=-3.84 DEBUG ultranest:integrator.py:2610 iteration=7040, ncalls=17039, regioncalls=11056692, ndraw=1538, logz=-18.58, remainder_fraction=2.9255%, Lmin=-4.73, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7080, ncalls=17121, regioncalls=11070543, ndraw=1539, logz=-18.57, remainder_fraction=2.7041%, Lmin=-4.71, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7120, ncalls=17229, regioncalls=11090563, ndraw=1540, logz=-18.57, remainder_fraction=2.5086%, Lmin=-4.70, Lmax=-3.81 DEBUG ultranest:integrator.py:2610 iteration=7160, ncalls=17321, regioncalls=11110596, ndraw=1541, logz=-18.57, remainder_fraction=2.3511%, Lmin=-4.68, Lmax=-3.80 DEBUG ultranest:integrator.py:2610 iteration=7200, ncalls=17401, regioncalls=11127547, ndraw=1541, logz=-18.57, remainder_fraction=2.2246%, Lmin=-4.66, Lmax=-3.72 DEBUG ultranest:integrator.py:2610 iteration=7240, ncalls=17478, regioncalls=11144498, ndraw=1541, logz=-18.57, remainder_fraction=2.0928%, Lmin=-4.64, Lmax=-3.72 DEBUG ultranest:integrator.py:2610 iteration=7280, ncalls=17550, regioncalls=11166072, ndraw=1541, logz=-18.56, remainder_fraction=1.9776%, Lmin=-4.62, Lmax=-3.67 DEBUG ultranest:integrator.py:2610 iteration=7317, ncalls=17609, regioncalls=11193810, ndraw=1541, logz=-18.56, remainder_fraction=1.8732%, Lmin=-4.58, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7320, ncalls=17620, regioncalls=11196892, ndraw=1541, logz=-18.56, remainder_fraction=1.8629%, Lmin=-4.57, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7360, ncalls=17688, regioncalls=11216925, ndraw=1541, logz=-18.56, remainder_fraction=1.7425%, Lmin=-4.53, Lmax=-3.65 DEBUG ultranest:integrator.py:2610 iteration=7400, ncalls=17753, regioncalls=11243105, ndraw=1540, logz=-18.56, remainder_fraction=1.6284%, Lmin=-4.48, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7440, ncalls=17834, regioncalls=11278502, ndraw=1539, logz=-18.56, remainder_fraction=1.5243%, Lmin=-4.43, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7480, ncalls=17895, regioncalls=11300034, ndraw=1538, logz=-18.56, remainder_fraction=1.4230%, Lmin=-4.39, Lmax=-3.64 DEBUG ultranest:integrator.py:2610 iteration=7520, ncalls=17985, regioncalls=11329237, ndraw=1537, logz=-18.56, remainder_fraction=1.3283%, Lmin=-4.35, Lmax=-3.57 DEBUG ultranest:integrator.py:2610 iteration=7560, ncalls=18055, regioncalls=11353813, ndraw=1536, logz=-18.56, remainder_fraction=1.2420%, Lmin=-4.31, Lmax=-3.53 DEBUG ultranest:integrator.py:2610 iteration=7600, ncalls=18127, regioncalls=11393723, ndraw=1535, logz=-18.56, remainder_fraction=1.1646%, Lmin=-4.27, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7629, ncalls=18196, regioncalls=11439743, ndraw=1534, logz=-18.55, remainder_fraction=1.1037%, Lmin=-4.23, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7640, ncalls=18220, regioncalls=11455073, ndraw=1533, logz=-18.55, remainder_fraction=1.0833%, Lmin=-4.22, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7650, ncalls=18242, regioncalls=11467329, ndraw=1532, logz=-18.55, remainder_fraction=1.0607%, Lmin=-4.21, Lmax=-3.51 DEBUG ultranest:integrator.py:2610 iteration=7680, ncalls=18285, regioncalls=11501011, ndraw=1531, logz=-18.55, remainder_fraction=1.0087%, Lmin=-4.18, Lmax=-3.51 INFO ultranest:integrator.py:2654 Explored until L=-4 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 18296 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -18.54 +- 0.1012 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2455.4, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.17 bs:0.10 tail:0.01 total:0.10 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_stepsampling.py::test_stepsampler_cubeslice

11.34

Passed

tests/test_samplingpath.py::test_reversible_gradient

1.67

[gw1] linux -- Python 3.10.6 /usr/bin/python3
[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 1 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] chose normal [-0.14594849 -0.98929219] 33 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] reflecting with [-0.84015394 -0.54234801] new direction [-0.03645513 0.01646278] re-reflecting gives direction [6.48453852e-06 3.99999995e-02] FORWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] BACKWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] setting seed = 2 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] chose normal [-0.55268598 -0.83338959] 75 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] reflecting with [-0.38762042 -0.92181908] new direction [-0.03999471 0.00065022] re-reflecting gives direction [-0.028441 0.02812667] FORWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] BACKWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] setting seed = 3 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] chose normal [-0.96649142 0.25669891] 45 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] reflecting with [-0.98467624 0.17439239] new direction [-0.02217288 -0.03329209] re-reflecting gives direction [ 0.00939036 -0.03888214] FORWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] BACKWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] setting seed = 4 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] chose normal [-0.97238131 -0.23339792] 0 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] reflecting with [-0.97238131 -0.23339792] new direction [-0.03230892 -0.02358248] re-reflecting gives direction [ 0.03949306 -0.00634806] FORWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] BACKWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] setting seed = 5 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] chose normal [0.31678437 0.94849758] 12 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] reflecting with [-0.33575666 0.94194876] new direction [0.0091709 0.03893449] re-reflecting gives direction [ 0.03173046 -0.02435524] FORWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] BACKWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] setting seed = 6 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] chose normal [0.83159266 0.55538603] 69 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] reflecting with [ 0.43246121 -0.90165254] new direction [-0.03368751 -0.02156737] re-reflecting gives direction [-0.03790637 -0.01277133] FORWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] BACKWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] setting seed = 7 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] chose normal [-0.99882119 0.04854104] 39 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] reflecting with [ 0.77093646 -0.63691206] new direction [0.02773823 0.02881997] re-reflecting gives direction [0.02306847 0.0326779 ] FORWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] BACKWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] setting seed = 8 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] chose normal [0.34627653 0.93813249] 99 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] reflecting with [0.34760793 0.93763998] new direction [ 0.03876506 -0.00986257] re-reflecting gives direction [ 0.03582603 -0.01779032] FORWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] BACKWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] setting seed = 9 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] chose normal [ 0.99593603 -0.09006347] 4 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] reflecting with [0.97389943 0.22697994] new direction [0.02917942 0.02735986] re-reflecting gives direction [-0.03826888 0.01164015] FORWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] BACKWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] setting seed = 10 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] chose normal [ 0.22487937 -0.97438661] 90 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] reflecting with [ 0.22487937 -0.97438661] new direction [0.03996017 0.00178454] re-reflecting gives direction [0.0367006 0.01590805] FORWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] BACKWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] setting seed = 11 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] chose normal [0.54430488 0.83888747] 16 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] reflecting with [0.82811727 0.56055489] new direction [0.0060231 0.03954393] re-reflecting gives direction [-0.03895091 0.0091009 ] FORWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] BACKWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] setting seed = 12 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] chose normal [-0.99011844 0.14023365] 82 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] reflecting with [-0.86634575 0.49944472] new direction [0.00495484 0.03969193] re-reflecting gives direction [0.03186583 0.02417786] FORWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] BACKWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] setting seed = 13 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] chose normal [-0.98685102 0.16163249] 5 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] reflecting with [-0.93229687 0.36169401] new direction [0.00745422 0.0392993 ] re-reflecting gives direction [0.02100007 0.03404404] FORWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] BACKWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] setting seed = 14 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] chose normal [ 0.82456261 -0.56577072] 96 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] reflecting with [0.77339836 0.63392033] new direction [-0.02433225 0.0317481 ] re-reflecting gives direction [-0.02635429 0.03009072] FORWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] BACKWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] setting seed = 15 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] chose normal [ 0.98353428 -0.18072169] 52 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] reflecting with [ 0.95341068 -0.30167545] new direction [ 0.01323002 -0.03774873] re-reflecting gives direction [-0.03253657 -0.0232674 ] FORWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] BACKWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] setting seed = 16 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] chose normal [0.98410666 0.17757839] 28 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] reflecting with [ 0.93475612 -0.35529003] new direction [ 0.01340794 -0.0376859 ] re-reflecting gives direction [-0.03505464 -0.01926583] FORWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] BACKWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] setting seed = 17 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] chose normal [0.77877968 0.62729755] 76 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] reflecting with [ 0.82081006 -0.57120123] new direction [-0.01456347 -0.0372546 ] re-reflecting gives direction [-0.02987327 -0.02660052] FORWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] BACKWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] setting seed = 18 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] chose normal [-0.33803901 -0.9411321 ] 41 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] reflecting with [-0.34524316 0.93851327] new direction [0.03651456 0.01633055] re-reflecting gives direction [0.03839271 0.01122497] FORWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] BACKWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] setting seed = 19 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] chose normal [0.93844564 0.34542696] 79 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] reflecting with [ 0.99641622 -0.08458558] new direction [-0.00263833 -0.0399129 ] re-reflecting gives direction [-0.00412734 -0.03978649] FORWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] BACKWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] setting seed = 20 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] chose normal [ 0.02238176 -0.9997495 ] 63 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] reflecting with [-0.98569607 0.16853264] new direction [-0.0285175 0.02804911] re-reflecting gives direction [0.03621666 0.01698097] FORWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] BACKWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] setting seed = 21 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] chose normal [0.69255841 0.7213618 ] 45 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] reflecting with [0.64446979 0.76462977] new direction [ 0.03965328 -0.00525524] re-reflecting gives direction [ 0.01189335 -0.03819094] FORWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] BACKWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] setting seed = 22 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] chose normal [0.73205365 0.68124698] 97 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] reflecting with [-0.09378428 0.99559254] new direction [-0.03999511 0.00062567] re-reflecting gives direction [-0.03917472 -0.00808342] FORWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] BACKWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] setting seed = 23 reflecting at [0.13591686 0.30336076] with direction [-0.00025999 0.03999916] setting seed = 24 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] chose normal [-0.53400133 0.84548364] 50 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] reflecting with [0.94624486 0.32345119] new direction [ 0.0391631 -0.00813953] re-reflecting gives direction [-0.02598612 -0.03040923] FORWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] BACKWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] setting seed = 25 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] chose normal [-0.97667717 0.21471306] 60 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] reflecting with [-0.63178483 0.77514381] new direction [0.02932087 0.02720821] re-reflecting gives direction [0.03256293 0.02323049] FORWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] BACKWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] setting seed = 26 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] chose normal [-0.50091154 0.86549848] 85 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] reflecting with [-0.85384138 0.52053328] new direction [-0.02180062 0.03353704] re-reflecting gives direction [ 0.03979792 -0.0040157 ] FORWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] BACKWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] setting seed = 27 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] chose normal [ 0.92407929 -0.38220081] 25 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] reflecting with [-0.97547221 -0.22012263] new direction [-0.01602001 0.03665187] re-reflecting gives direction [-0.00127249 0.03997975] FORWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] BACKWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] setting seed = 28 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] chose normal [ 0.25028455 -0.96817232] 53 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] reflecting with [-0.0753835 -0.99715462] new direction [-0.03451679 -0.02021364] re-reflecting gives direction [-0.03108561 0.02517309] FORWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] BACKWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] setting seed = 29 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] chose normal [ 0.93787043 -0.34698568] 15 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] reflecting with [0.8970119 0.44200639] new direction [-0.00691923 0.03939701] re-reflecting gives direction [-0.02702503 0.02948979] FORWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] BACKWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] setting seed = 30 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] chose normal [-0.94320997 -0.33219716] 57 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] reflecting with [-0.53412191 -0.84540746] new direction [-0.03946637 -0.00651194] re-reflecting gives direction [-0.01106701 0.03843854] FORWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] BACKWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] setting seed = 31 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] chose normal [ 0.91849248 -0.39543844] 40 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] reflecting with [-0.99751744 -0.0704199 ] new direction [-0.01171731 0.03824532] re-reflecting gives direction [0.00622801 0.03951217] FORWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] BACKWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] setting seed = 32 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] chose normal [-0.86603501 0.49998337] 44 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] reflecting with [0.78359729 0.6212691 ] new direction [ 0.02794233 -0.02862213] re-reflecting gives direction [ 0.02149569 -0.0337333 ] FORWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] BACKWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] setting seed = 33 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] chose normal [ 0.94116632 -0.33794371] 14 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] reflecting with [ 0.41089806 -0.91168129] new direction [ 0.03504567 -0.01928214] re-reflecting gives direction [0.00876515 0.03902784] FORWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] BACKWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] setting seed = 34 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] chose normal [-0.9662808 -0.2574906] 59 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] reflecting with [-0.99996226 -0.00868732] new direction [-0.02541174 0.03089083] re-reflecting gives direction [0.0248712 0.03132767] FORWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] BACKWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] setting seed = 35 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] chose normal [ 0.81909097 -0.57366365] 13 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] reflecting with [0.99064996 0.13642818] new direction [ 0.03950549 -0.00627028] re-reflecting gives direction [-0.03633999 -0.01671541] FORWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] BACKWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] setting seed = 36 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] chose normal [ 0.99395085 -0.10982581] 7 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] reflecting with [-0.98326229 -0.18219571] new direction [-0.00800478 0.03919086] re-reflecting gives direction [-0.00656845 0.03945701] FORWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] BACKWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] setting seed = 37 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] chose normal [0.24749873 0.96888822] 9 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] reflecting with [0.9968224 0.07965612] new direction [ 0.03964894 -0.00528788] re-reflecting gives direction [-0.03830604 -0.01151726] FORWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] BACKWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] setting seed = 38 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] chose normal [-0.47920534 0.87770282] 91 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] reflecting with [0.07106544 0.99747166] new direction [0.01077519 0.03852136] re-reflecting gives direction [ 0.00520512 -0.03965989] FORWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] BACKWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] setting seed = 39 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] chose normal [-0.96803752 0.25080543] 26 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] reflecting with [ 0.48195217 -0.87619753] new direction [0.03565683 0.01812707] re-reflecting gives direction [0.03440183 0.02040867] FORWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] BACKWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] setting seed = 40 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] chose normal [ 0.99762991 -0.06880816] 34 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] reflecting with [ 0.98422636 -0.17691375] new direction [-0.00574414 -0.03958541] re-reflecting gives direction [-0.0084009 -0.03910786] FORWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] BACKWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] setting seed = 41 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] chose normal [-0.39185582 0.92002664] 4 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] reflecting with [-0.80640044 0.59136988] new direction [-0.03753422 0.01382688] re-reflecting gives direction [ 0.02446896 -0.03164285] FORWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] BACKWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] setting seed = 42 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] chose normal [0.95525297 0.29579006] 28 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] reflecting with [-0.70398882 -0.71021105] new direction [-0.03501649 0.01933508] re-reflecting gives direction [-0.01964246 0.034845 ] FORWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] BACKWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] setting seed = 43 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] chose normal [-0.59139425 0.80638257] 29 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] reflecting with [-0.63872083 0.76943856] new direction [-0.03094035 -0.02535142] re-reflecting gives direction [-0.03061347 -0.0257452 ] FORWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] BACKWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] setting seed = 44 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] chose normal [ 0.99893451 -0.04615032] 29 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] reflecting with [-0.69018106 0.72363672] new direction [-0.03900915 -0.00884794] re-reflecting gives direction [-0.01068318 -0.03854698] FORWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] BACKWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] setting seed = 45 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] chose normal [ 0.06446741 -0.99791981] 84 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] reflecting with [ 0.06446741 -0.99791981] new direction [-0.03980439 -0.00395101] re-reflecting gives direction [-0.0399819 -0.00120333] FORWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] BACKWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] setting seed = 46 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] chose normal [ 0.9478891 -0.31860046] 70 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] reflecting with [0.99984603 0.01754771] new direction [0.02044956 0.03437754] re-reflecting gives direction [-0.02164327 0.0336388 ] FORWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] BACKWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] setting seed = 47 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] chose normal [0.74369889 0.66851474] 81 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] reflecting with [ 0.9436164 -0.33104091] new direction [ 0.0163875 -0.03648904] re-reflecting gives direction [-0.03559232 -0.0182534 ] FORWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] BACKWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] setting seed = 48 reflecting at [0.14141263 0.72381215] with direction [ 0.01008992 -0.03870651] setting seed = 49 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] chose normal [ 0.78315843 -0.62182223] 61 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] reflecting with [0.98231877 0.187216 ] new direction [ 0.0370356 -0.01511173] re-reflecting gives direction [-0.02888115 -0.02767453] FORWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] BACKWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] setting seed = 50 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] chose normal [-0.9091523 -0.4164638] 59 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] reflecting with [-0.95815198 -0.28626 ] new direction [-0.02615101 0.03026755] re-reflecting gives direction [0.00526153 0.03965244] FORWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] BACKWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] setting seed = 51 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] chose normal [-0.99167671 -0.12875285] 11 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] reflecting with [-0.91529383 0.4027868 ] new direction [0.00204569 0.03994765] re-reflecting gives direction [0.02807295 0.02849403] FORWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] BACKWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] setting seed = 52 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] chose normal [0.97430448 0.22523493] 14 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] reflecting with [0.49373504 0.86961239] new direction [-0.00271496 0.03990776] re-reflecting gives direction [-0.03566072 -0.01811941] FORWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] BACKWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] setting seed = 53 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] chose normal [-0.78010783 0.62564509] 68 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] reflecting with [ 0.99116492 -0.13263523] new direction [ 0.00409791 -0.03978954] re-reflecting gives direction [-0.01441546 -0.03731212] FORWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] BACKWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] setting seed = 54 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] chose normal [0.97346802 0.2288231 ] 2 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] reflecting with [ 0.89562093 -0.44481812] new direction [ 0.00894519 -0.03898697] re-reflecting gives direction [-0.03646926 -0.01643148] FORWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] BACKWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] setting seed = 55 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] chose normal [0.7228596 0.69099493] 3 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] reflecting with [-0.98267299 0.18534775] new direction [-0.01147429 -0.03831893] re-reflecting gives direction [-0.00327261 -0.0398659 ] FORWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] BACKWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] setting seed = 56 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] chose normal [0.6437137 0.7652664] 92 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] reflecting with [0.6437137 0.7652664] new direction [ 0.03742321 -0.01412455] re-reflecting gives direction [ 0.02032516 -0.03445124] FORWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] BACKWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] setting seed = 57 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] chose normal [-0.9653418 -0.26098892] 66 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] reflecting with [-0.95158108 -0.30739787] new direction [-0.01673815 -0.03632952] re-reflecting gives direction [ 0.03482865 -0.01967144] FORWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] BACKWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] setting seed = 58 reflecting at [0.00831403 0.22576864] with direction [0.03708157 0.01499858] setting seed = 59 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] chose normal [ 0.96677775 -0.25561844] 29 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] reflecting with [ 0.9754194 -0.22035653] new direction [ 0.02933405 -0.027194 ] re-reflecting gives direction [-0.03817546 -0.01194295] FORWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] BACKWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] setting seed = 60 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] chose normal [-0.99186614 -0.12728533] 21 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] reflecting with [0.11689192 0.99314464] new direction [0.02795024 0.02861441] re-reflecting gives direction [ 0.0205427 -0.03432197] FORWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] BACKWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] setting seed = 61 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] chose normal [-0.96739827 -0.25325991] 26 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] reflecting with [-0.96012904 -0.2795572 ] new direction [-0.00353274 -0.03984369] re-reflecting gives direction [ 0.02436953 -0.03171949] FORWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] BACKWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] setting seed = 62 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] chose normal [0.93863157 0.34492141] 54 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] reflecting with [0.98471485 0.17417424] new direction [0.03829817 0.0115434 ] re-reflecting gives direction [-0.03993416 -0.00229416] FORWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] BACKWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] setting seed = 63 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] chose normal [-0.99656293 0.08283919] 19 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] reflecting with [-0.99966777 -0.02577498] new direction [-0.02770486 -0.02885205] re-reflecting gives direction [ 0.02915488 -0.027386 ] FORWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] BACKWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] setting seed = 64 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] chose normal [0.0269266 0.99963741] 88 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] reflecting with [0.16834631 0.98572791] new direction [0.0379336 0.01269023] re-reflecting gives direction [ 0.03157176 -0.02456061] FORWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] BACKWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] setting seed = 65 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] chose normal [ 0.87714796 -0.48022022] 19 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] reflecting with [ 0.99603093 -0.08900784] new direction [0.03420944 0.02072954] re-reflecting gives direction [-0.02999187 0.02646673] FORWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] BACKWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] setting seed = 66 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] chose normal [ 0.37536664 -0.92687641] 71 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] reflecting with [-0.94506677 0.32687734] new direction [-0.0121731 0.0381027] re-reflecting gives direction [0.03311318 0.02243919] FORWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] BACKWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] setting seed = 67 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] chose normal [0.98377071 0.17943018] 38 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] reflecting with [0.95209698 0.30579625] new direction [ 0.03997674 -0.00136388] re-reflecting gives direction [-0.031706 -0.02438707] FORWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] BACKWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] setting seed = 68 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] chose normal [-0.79459132 0.60714466] 17 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] reflecting with [-0.43881146 0.89857916] new direction [0.0285481 0.02801796] re-reflecting gives direction [0.03964926 0.00528548] FORWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] BACKWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] setting seed = 69 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] chose normal [-0.7961656 -0.60507879] 1 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] reflecting with [-0.86697568 -0.49835046] new direction [-0.02954452 -0.02696519] re-reflecting gives direction [0.0381706 0.01195847] FORWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] BACKWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] setting seed = 70 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] chose normal [ 0.39947727 -0.9167431 ] 42 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] reflecting with [ 0.6826168 -0.73077651] new direction [0.03155141 0.02458676] re-reflecting gives direction [0.0266774 0.02980464] FORWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] BACKWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] setting seed = 71 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] chose normal [-0.97291035 -0.23118274] 69 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] reflecting with [-0.49751035 -0.86745804] new direction [-0.03814895 -0.01202737] re-reflecting gives direction [-0.00888267 0.03900126] FORWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] BACKWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] setting seed = 72 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] chose normal [ 0.99936155 -0.03572801] 44 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] reflecting with [0.20311685 0.97915451] new direction [-0.03319769 0.02231398] re-reflecting gives direction [-0.03933418 -0.00726789] FORWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] BACKWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] setting seed = 73 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] chose normal [ 0.95068267 -0.31016523] 56 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] reflecting with [ 0.98237383 -0.18692688] new direction [ 0.03725902 -0.01455216] re-reflecting gives direction [-0.03999972 0.0001487 ] FORWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] BACKWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] setting seed = 74 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] chose normal [-0.96711996 0.25432065] 26 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] reflecting with [-0.28345858 0.95898448] new direction [0.0376308 0.01356183] re-reflecting gives direction [0.03895671 0.00907606] FORWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] BACKWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] setting seed = 75 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] chose normal [0.96607282 0.25826984] 98 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] reflecting with [0.85293874 0.52201103] new direction [-0.01283057 0.03788636] re-reflecting gives direction [-0.02789929 0.02866409] FORWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] BACKWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] setting seed = 76 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] chose normal [0.99980546 0.01972428] 96 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] reflecting with [ 0.99668345 -0.08137624] new direction [ 0.01928923 -0.03504177] re-reflecting gives direction [-0.02471798 -0.03144871] FORWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] BACKWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] setting seed = 77 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] chose normal [0.99421477 0.10741039] 67 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] reflecting with [ 0.79437479 -0.60742794] new direction [ 0.00021031 -0.03999945] re-reflecting gives direction [-0.03865662 -0.0102794 ] FORWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] BACKWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] setting seed = 78 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] chose normal [-0.00914844 -0.99995815] 42 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] reflecting with [0.81401512 0.58084368] new direction [0.00280365 0.03990162] re-reflecting gives direction [-0.03864408 0.01032644] FORWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] BACKWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] setting seed = 79 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] chose normal [0.11595433 0.99325455] 54 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] reflecting with [-0.11517722 0.99334496] new direction [0.00815767 0.03915932] re-reflecting gives direction [ 0.01690173 -0.03625371] FORWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] BACKWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] setting seed = 80 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] chose normal [-0.99209853 -0.1254612 ] 94 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] reflecting with [-0.97468899 -0.22356515] new direction [ 0.00838404 -0.03911148] re-reflecting gives direction [ 0.00949935 -0.03885566] FORWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] BACKWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] setting seed = 81 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] chose normal [-0.58455495 0.81135412] 52 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] reflecting with [ 0.9366811 -0.35018355] new direction [-0.01353712 -0.03763969] re-reflecting gives direction [-0.01447537 -0.03728892] FORWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] BACKWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] setting seed = 82 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] chose normal [-0.99997753 0.00670296] 37 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] reflecting with [-0.99945421 -0.03303454] new direction [-0.0075057 0.0392895] re-reflecting gives direction [0.00489491 0.03969937] FORWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] BACKWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] setting seed = 83 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] chose normal [-0.83995537 0.54265548] 16 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] reflecting with [-0.94063007 0.33943345] new direction [-0.0399681 -0.00159728] re-reflecting gives direction [ 0.02973828 -0.02675135] FORWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] BACKWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 85 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] chose normal [-0.96043218 0.27851395] 24 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] reflecting with [0.63881082 0.76936385] new direction [ 0.03336656 -0.02206066] re-reflecting gives direction [ 0.02781881 -0.02874219] FORWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] BACKWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] setting seed = 86 reflecting at [0.0772825 0.7321639] with direction [-0.0017544 -0.03996151] setting seed = 87 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] chose normal [-0.12256498 0.99246049] 84 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] reflecting with [-0.96541456 -0.26071962] new direction [-0.02848461 -0.0280825 ] re-reflecting gives direction [ 0.03874902 -0.0099254 ] FORWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] BACKWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] setting seed = 88 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] chose normal [-0.97498227 0.22228264] 41 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] reflecting with [-0.97588769 -0.21827326] new direction [-0.01869452 -0.03536262] re-reflecting gives direction [ 0.03197838 -0.0240288 ] FORWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] BACKWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] setting seed = 89 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] chose normal [-0.73290905 0.68032663] 80 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] reflecting with [-0.99658198 -0.08260969] new direction [-0.03221094 0.02371614] re-reflecting gives direction [0.02786633 0.02869612] FORWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] BACKWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] setting seed = 90 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] chose normal [ 0.8841271 -0.46724648] 74 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] reflecting with [ 0.99881338 -0.04870138] new direction [ 0.02087861 -0.03411867] re-reflecting gives direction [-0.02409888 -0.0319256 ] FORWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] BACKWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] setting seed = 91 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] chose normal [-0.92831744 -0.37178856] 63 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] reflecting with [ 0.50709066 -0.86189272] new direction [ 0.02598594 -0.03040939] re-reflecting gives direction [-0.01395947 0.0374851 ] FORWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] BACKWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] setting seed = 92 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] chose normal [-0.19961852 0.97987369] 68 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] reflecting with [0.80447377 0.59398817] new direction [0.0361881 0.01704175] re-reflecting gives direction [-0.02693892 -0.02956847] FORWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] BACKWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] setting seed = 93 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] chose normal [0.97810947 0.20809099] 55 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] reflecting with [0.99871915 0.05059696] new direction [0.01946991 0.0349417 ] re-reflecting gives direction [-0.02290158 0.03279509] FORWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] BACKWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] setting seed = 94 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] chose normal [-0.99138772 -0.13095947] 38 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] reflecting with [-0.85869194 0.51249211] new direction [-0.01847325 0.03547871] re-reflecting gives direction [0.03999576 0.00058272] FORWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] BACKWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] setting seed = 95 reflecting at [0.1329267 0.27135336] with direction [0.00593512 0.03955723] setting seed = 96 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] chose normal [-0.98828152 0.15264217] 98 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] reflecting with [-0.96810281 0.25055328] new direction [-0.00511631 0.03967144] re-reflecting gives direction [0.02371945 0.0322085 ] FORWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] BACKWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] setting seed = 97 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] chose normal [ 0.97234847 -0.23353469] 26 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] reflecting with [-0.96293126 -0.26974691] new direction [-0.02762979 0.02892395] re-reflecting gives direction [0.00858305 0.03906829] FORWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] BACKWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] setting seed = 98 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] chose normal [0.50785771 0.86144097] 48 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] reflecting with [0.9858335 0.16772692] new direction [ 0.01754476 -0.03594693] re-reflecting gives direction [-0.0046699 -0.03972646] FORWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] BACKWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] setting seed = 99 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] chose normal [0.99595977 0.08980054] 53 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] reflecting with [ 0.8602646 -0.50984784] new direction [ 0.01891779 -0.03524368] re-reflecting gives direction [-0.03999867 -0.00032601] FORWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913] BACKWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913]

Passed

tests/test_stepsampling.py::test_stepsampler_cubemh

11.70

[gw1] linux -- Python 3.10.6 /usr/bin/python3
[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +1.0e-12|******************************* *******************| +1.0e+00 param1: +1.0e-12|***************************************************| +1.0e+00 param2: +1.0e-12|***************************************************| +1.0e+00 Z=-inf(0.00%) | Like=-30.04..-1.06 [-30.0369..-9.7206] | it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.0913). shrinking... ineffective proposal scale (1.01601). shrinking... ineffective proposal scale (1.19093). shrinking... ineffective proposal scale (1.1). shrinking... ineffective proposal scale (1.01601). shrinking... ineffective proposal scale (1.21). shrinking... ineffective proposal scale (1.11761). shrinking... ineffective proposal scale (1.04051). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.961066). shrinking... ineffective proposal scale (0.887686). shrinking... Z=-27.7(0.00%) | Like=-23.65..-1.06 [-30.0369..-9.7206] | it/evals=27/736 eff=8.0357% N=400 ineffective proposal scale (0.826446). shrinking... ineffective proposal scale (0.763345). shrinking... ineffective proposal scale (0.873696). shrinking... ineffective proposal scale (0.813422). shrinking... ineffective proposal scale (0.813422). shrinking... Z=-25.1(0.00%) | Like=-21.40..-1.06 [-30.0369..-9.7206] | it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (0.846375). shrinking... ineffective proposal scale (0.794269). shrinking... ineffective proposal scale (0.800603). shrinking... ineffective proposal scale (0.901899). shrinking... ineffective proposal scale (0.769432). shrinking... ineffective proposal scale (0.710683). shrinking... ineffective proposal scale (0.656421). shrinking... ineffective proposal scale (0.606301). shrinking... ineffective proposal scale (0.560008). shrinking... Mono-modal Volume: ~exp(-4.22) * Expected Volume: exp(-0.23) Quality: ok param0: +0.0000|******************************************* *******| +1.0000 param1: +1.0e-12|*********************************************** ** | +1.0e+00 param2: +1.0e-12|******************************************** **** *| +1.0e+00 Z=-21.0(0.00%) | Like=-16.93..-1.06 [-30.0369..-9.7206] | it/evals=90/1492 eff=8.2418% N=400 Z=-20.0(0.00%) | Like=-16.02..-1.06 [-30.0369..-9.7206] | it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (0.560008). shrinking... ineffective proposal scale (0.51725). shrinking... ineffective proposal scale (0.477757). shrinking... Z=-16.9(0.00%) | Like=-13.39..-0.56 [-30.0369..-9.7206] | it/evals=137/2056 eff=8.2729% N=400 Z=-16.2(0.00%) | Like=-12.90..-0.56 [-30.0369..-9.7206] | it/evals=150/2212 eff=8.2781% N=400 Mono-modal Volume: ~exp(-4.22) Expected Volume: exp(-0.45) Quality: ok param0: +0.0000|******************************************* *******| +1.0000 param1: +1.0e-12|****************************************** **** ** | +1.0e+00 param2: +1.0e-12|************************************** ***** *** | +1.0e+00 Z=-15.0(0.00%) | Like=-11.80..-0.20 [-30.0369..-9.7206] | it/evals=180/2572 eff=8.2873% N=400 ineffective proposal scale (0.217629). shrinking... Z=-14.3(0.00%) | Like=-11.20..-0.20 [-30.0369..-9.7206] | it/evals=200/2812 eff=8.2919% N=400 ineffective proposal scale (0.170132). shrinking... Z=-13.2(0.01%) | Like=-10.26..-0.11 [-30.0369..-9.7206] | it/evals=236/3244 eff=8.2982% N=400 Z=-12.9(0.01%) | Like=-9.98..-0.11 [-30.0369..-9.7206] | it/evals=250/3412 eff=8.3001% N=400 Mono-modal Volume: ~exp(-4.79) * Expected Volume: exp(-0.67) Quality: ok param0: +1.0e-12|*************************************** *** **** **| +1.0e+00 param1: +1.0e-12|****************************************** ** ** | +1.0e+00 param2: +1.0e-12|************************************** ********* | +1.0e+00 Z=-12.4(0.02%) | Like=-9.71..-0.11 [-9.7132..-6.0704] | it/evals=270/3652 eff=8.3026% N=400 Z=-12.0(0.04%) | Like=-9.20..-0.11 [-9.7132..-6.0704] | it/evals=295/3952 eff=8.3052% N=400 Z=-11.9(0.04%) | Like=-9.09..-0.11 [-9.7132..-6.0704] | it/evals=300/4012 eff=8.3056% N=400 Z=-11.2(0.08%) | Like=-8.53..-0.11 [-9.7132..-6.0704] | it/evals=339/4480 eff=8.3088% N=400 Z=-11.0(0.09%) | Like=-8.36..-0.11 [-9.7132..-6.0704] | it/evals=350/4612 eff=8.3096% N=400 Mono-modal Volume: ~exp(-4.83) * Expected Volume: exp(-0.90) Quality: ok param0: +0.0000|******************************************* * ** **| +1.0000 param1: +1.0e-12|****************************************** ** ** | +1.0e+00 param2: +0.0000|************************************** ******** | +1.0000 Z=-10.9(0.11%) | Like=-8.23..-0.11 [-9.7132..-6.0704] | it/evals=360/4732 eff=8.3102% N=400 Z=-10.5(0.15%) | Like=-7.84..-0.11 [-9.7132..-6.0704] | it/evals=384/5020 eff=8.3117% N=400 Z=-10.3(0.20%) | Like=-7.64..-0.11 [-9.7132..-6.0704] | it/evals=400/5212 eff=8.3126% N=400 Z=-9.8(0.29%) | Like=-7.18..-0.11 [-9.7132..-6.0704] | it/evals=442/5716 eff=8.3145% N=400 Mono-modal Volume: ~exp(-4.84) * Expected Volume: exp(-1.12) Quality: ok param0: +0.0000|************************************ ****** * ** *| +1.0000 param1: +1.0e-12|********************************************** ** | +1.0e+00 param2: +1.0e-12|*********************************************** | +1.0e+00 Z=-9.7(0.32%) | Like=-7.09..-0.11 [-9.7132..-6.0704] | it/evals=450/5812 eff=8.3149% N=400 Z=-9.5(0.41%) | Like=-6.83..-0.11 [-9.7132..-6.0704] | it/evals=473/6088 eff=8.3158% N=400 Z=-9.2(0.56%) | Like=-6.57..-0.11 [-9.7132..-6.0704] | it/evals=500/6412 eff=8.3167% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.35) Quality: ok param0: +1.0e-12|************************************ ****** * ** | +1.0e+00 param1: +1.0e-12|************************************************** | +1.0e+00 param2: +1.0e-12|*********************************************** | +1.0e+00 Z=-8.8(0.81%) | Like=-6.14..-0.11 [-9.7132..-6.0704] | it/evals=540/6892 eff=8.3179% N=400 Z=-8.7(0.88%) | Like=-6.02..-0.11 [-6.0299..-4.1927] | it/evals=550/7012 eff=8.3182% N=400 Z=-8.5(1.14%) | Like=-5.73..-0.11 [-6.0299..-4.1927] | it/evals=574/7300 eff=8.3188% N=400 Z=-8.3(1.45%) | Like=-5.49..-0.11 [-6.0299..-4.1927] | it/evals=600/7612 eff=8.3195% N=400 Mono-modal Volume: ~exp(-5.79) * Expected Volume: exp(-1.57) Quality: ok param0: +1.0e-12|******************************************* * ** | +1.0e+00 param1: +0.000|******************************* ***************** | +1.000 param2: +1.0e-12|************************************* ********* | +1.0e+00 Z=-8.0(1.81%) | Like=-5.29..-0.11 [-6.0299..-4.1927] | it/evals=630/7972 eff=8.3201% N=400 Z=-7.9(2.09%) | Like=-5.14..-0.11 [-6.0299..-4.1927] | it/evals=650/8212 eff=8.3205% N=400 Z=-7.6(2.76%) | Like=-4.93..-0.11 [-6.0299..-4.1927] | it/evals=688/8668 eff=8.3212% N=400 Z=-7.5(2.99%) | Like=-4.88..-0.11 [-6.0299..-4.1927] | it/evals=700/8812 eff=8.3214% N=400 Mono-modal Volume: ~exp(-5.79) Expected Volume: exp(-1.80) Quality: ok param0: +0.000|******************************************* * * | +1.000 param1: +0.000|******************************* ***************** | +1.000 param2: +1.0e-12|************************************* ******* * | +1.0e+00 Z=-7.4(3.32%) | Like=-4.76..-0.11 [-6.0299..-4.1927] | it/evals=720/9052 eff=8.3218% N=400 Z=-7.2(3.88%) | Like=-4.57..-0.11 [-6.0299..-4.1927] | it/evals=750/9412 eff=8.3222% N=400 Z=-7.0(5.09%) | Like=-4.31..-0.11 [-6.0299..-4.1927] | it/evals=800/10012 eff=8.3229% N=400 Mono-modal Volume: ~exp(-5.79) Expected Volume: exp(-2.02) Quality: ok param0: +0.000|******************************************* *** | +1.000 param1: +0.00| ******************************* **************** | +1.00 param2: +0.00| ******************************************** | +1.00 Z=-6.8(5.86%) | Like=-4.20..-0.11 [-6.0299..-4.1927] | it/evals=827/10336 eff=8.3233% N=400 Z=-6.7(6.40%) | Like=-4.09..-0.06 [-4.1888..-3.3876] | it/evals=850/10612 eff=8.3235% N=400 Mono-modal Volume: ~exp(-6.66) * Expected Volume: exp(-2.25) Quality: ok param0: +0.00| ***************************************** *** * | +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| ******************************************* * | +1.00 Z=-6.5(7.81%) | Like=-3.82..-0.06 [-4.1888..-3.3876] | it/evals=900/11212 eff=8.3241% N=400 Z=-6.4(9.60%) | Like=-3.56..-0.06 [-4.1888..-3.3876] | it/evals=945/11752 eff=8.3245% N=400 Z=-6.3(9.79%) | Like=-3.54..-0.06 [-4.1888..-3.3876] | it/evals=950/11812 eff=8.3246% N=400 Mono-modal Volume: ~exp(-6.68) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00| ***************************************** *** | +1.00 param1: +0.00| ********************************************** | +1.00 param2: +0.00| ******************************************* * | +1.00 Z=-6.2(11.33%) | Like=-3.29..-0.06 [-3.3856..-3.0945] | it/evals=990/12292 eff=8.3249% N=400 Z=-6.2(11.73%) | Like=-3.22..-0.06 [-3.3856..-3.0945] | it/evals=1000/12412 eff=8.3250% N=400 Z=-6.0(14.31%) | Like=-3.03..-0.06 [-3.0815..-2.9597] | it/evals=1050/13012 eff=8.3254% N=400 Mono-modal Volume: ~exp(-6.68) Expected Volume: exp(-2.70) Quality: ok param0: +0.00| **************************************** * | +1.00 param1: +0.00| ************************* ************ ***** | +1.00 param2: +0.00| * **************************************** * | +1.00 Z=-5.9(16.05%) | Like=-2.90..-0.06 [-2.9039..-2.8993]*| it/evals=1080/13372 eff=8.3256% N=400 Z=-5.8(17.09%) | Like=-2.82..-0.06 [-2.8220..-2.8188]*| it/evals=1100/13612 eff=8.3258% N=400 Z=-5.7(19.97%) | Like=-2.62..-0.06 [-2.6183..-2.6180]*| it/evals=1150/14212 eff=8.3261% N=400 Mono-modal Volume: ~exp(-6.68) Expected Volume: exp(-2.92) Quality: ok param0: +0.00| *************************************** * | +1.00 param1: +0.00| ************************************* ***** | +1.00 param2: +0.00| ***************************************** ** | +1.00 Z=-5.6(22.00%) | Like=-2.50..-0.03 [-2.4972..-2.4851] | it/evals=1186/14644 eff=8.3263% N=400 Z=-5.5(22.87%) | Like=-2.46..-0.03 [-2.4581..-2.4551]*| it/evals=1200/14812 eff=8.3264% N=400 Z=-5.4(25.76%) | Like=-2.28..-0.03 [-2.2759..-2.2634] | it/evals=1250/15412 eff=8.3267% N=400 Have 2 modes Volume: ~exp(-7.56) * Expected Volume: exp(-3.15) Quality: ok param0: +0.0| 11111111111111111111122222222222222222 | +1.0 param1: +0.00| 1111111111111111111111222222 222222222 2222 | +1.00 param2: +0.0| 111111111111111111112222222222222222222 | +1.0 Z=-5.4(26.52%) | Like=-2.24..-0.03 [-2.2375..-2.2365]*| it/evals=1260/15532 eff=8.3267% N=400 Z=-5.3(28.98%) | Like=-2.09..-0.03 [-2.0884..-2.0785]*| it/evals=1300/16012 eff=8.3269% N=400 Have 2 modes Volume: ~exp(-7.76) * Expected Volume: exp(-3.37) Quality: ok param0: +0.0| 11111111111111111111222222222222222222 | +1.0 param1: +0.0| 1111111111111111111 22222222 2222222 2 2 | +1.0 param2: +0.0| 1111111111111111111 222222222222222222 | +1.0 Z=-5.2(32.52%) | Like=-1.90..-0.03 [-1.8971..-1.8900]*| it/evals=1350/16612 eff=8.3272% N=400 Z=-5.1(34.97%) | Like=-1.81..-0.03 [-1.8113..-1.8108]*| it/evals=1379/16960 eff=8.3273% N=400 Z=-5.0(36.57%) | Like=-1.73..-0.03 [-1.7344..-1.7328]*| it/evals=1400/17212 eff=8.3274% N=400 Have 2 modes Volume: ~exp(-7.76) Expected Volume: exp(-3.60) Quality: ok param0: +0.0| 111111111111111111 22222222222222222 | +1.0 param1: +0.0| 111111111111111111 2222222202222222 2 | +1.0 param2: +0.0| 111111111111111111 22222222222222222 | +1.0 Z=-5.0(39.24%) | Like=-1.63..-0.03 [-1.6259..-1.6248]*| it/evals=1440/17692 eff=8.3276% N=400 Z=-4.9(39.95%) | Like=-1.60..-0.03 [-1.6049..-1.5962]*| it/evals=1450/17812 eff=8.3276% N=400 Z=-4.9(43.52%) | Like=-1.48..-0.03 [-1.4784..-1.4782]*| it/evals=1496/18364 eff=8.3278% N=400 Z=-4.9(43.72%) | Like=-1.47..-0.03 [-1.4722..-1.4714]*| it/evals=1500/18412 eff=8.3278% N=400 Have 2 modes Volume: ~exp(-7.76) Expected Volume: exp(-3.82) Quality: ok param0: +0.0| 111111111111111111 2222222222222 22 | +1.0 param1: +0.0| 11111111111111111 22022020222222202 | +1.0 param2: +0.0| 11111111111111111 0 02222222222202 | +1.0 Z=-4.8(46.21%) | Like=-1.41..-0.03 [-1.4149..-1.4132]*| it/evals=1530/18772 eff=8.3279% N=400 Z=-4.8(47.57%) | Like=-1.39..-0.01 [-1.3855..-1.3841]*| it/evals=1550/19012 eff=8.3280% N=400 Z=-4.7(50.20%) | Like=-1.32..-0.01 [-1.3172..-1.3102]*| it/evals=1591/19504 eff=8.3281% N=400 Z=-4.7(50.85%) | Like=-1.29..-0.01 [-1.2927..-1.2916]*| it/evals=1600/19612 eff=8.3281% N=400 Have 2 modes Volume: ~exp(-8.08) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0| 11111111111111111 22222222 22222 +0.8 | +1.0 param1: +0.0| 1111111111111111 222 222222222 | +1.0 param2: +0.0| 11111111111111111 2222222222222 | +1.0 Z=-4.7(52.25%) | Like=-1.25..-0.01 [-1.2530..-1.2526]*| it/evals=1620/19852 eff=8.3282% N=400 Z=-4.6(54.35%) | Like=-1.21..-0.01 [-1.2056..-1.2053]*| it/evals=1650/20214 eff=8.3274% N=400 Z=-4.6(56.82%) | Like=-1.15..-0.01 [-1.1537..-1.1527]*| it/evals=1689/20682 eff=8.3276% N=400 Z=-4.6(57.55%) | Like=-1.14..-0.01 [-1.1414..-1.1366]*| it/evals=1700/20814 eff=8.3276% N=400 Have 2 modes Volume: ~exp(-8.08) Expected Volume: exp(-4.27) Quality: ok param0: +0.0| 111111111111111 2202222 22222 +0.8 | +1.0 param1: +0.0| 111111111111111 2220222222222 | +1.0 param2: +0.0| 111111111111111 02222222222222 | +1.0 Z=-4.5(59.21%) | Like=-1.07..-0.01 [-1.0743..-1.0739]*| it/evals=1726/21126 eff=8.3277% N=400 Z=-4.5(60.73%) | Like=-1.04..-0.01 [-1.0385..-1.0382]*| it/evals=1750/21414 eff=8.3278% N=400 Z=-4.5(63.40%) | Like=-0.95..-0.01 [-0.9492..-0.9480]*| it/evals=1793/21930 eff=8.3279% N=400 Have 2 modes Volume: ~exp(-8.66) * Expected Volume: exp(-4.50) Quality: ok param0: +0.0| 11111111111111 222222222222 +0.8 | +1.0 param1: +0.0| 111111111111111 222222222222 +0.8 | +1.0 param2: +0.0| 111111111111111 2222222222222 | +1.0 Z=-4.5(63.79%) | Like=-0.94..-0.01 [-0.9390..-0.9389]*| it/evals=1800/22014 eff=8.3279% N=400 Z=-4.5(65.27%) | Like=-0.90..-0.01 [-0.9042..-0.9011]*| it/evals=1826/22326 eff=8.3280% N=400 Z=-4.4(66.73%) | Like=-0.88..-0.01 [-0.8812..-0.8805]*| it/evals=1850/22614 eff=8.3281% N=400 Z=-4.4(68.57%) | Like=-0.82..-0.01 [-0.8240..-0.8228]*| it/evals=1883/23010 eff=8.3282% N=400 Have 2 modes Volume: ~exp(-8.79) * Expected Volume: exp(-4.73) Quality: ok param0: +0.0| 1111111111111 222222222222 +0.8 | +1.0 param1: +0.0| 11111111111111 222222222222 +0.8 | +1.0 param2: +0.0| 1111111111111 222222222222 | +1.0 Z=-4.4(68.99%) | Like=-0.81..-0.01 [-0.8129..-0.8128]*| it/evals=1890/23094 eff=8.3282% N=400 Z=-4.4(69.61%) | Like=-0.81..-0.01 [-0.8058..-0.8049]*| it/evals=1900/23214 eff=8.3282% N=400 Z=-4.4(71.90%) | Like=-0.76..-0.01 [-0.7575..-0.7573]*| it/evals=1942/23718 eff=8.3283% N=400 Z=-4.4(72.36%) | Like=-0.75..-0.01 [-0.7484..-0.7480]*| it/evals=1950/23814 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-8.79) Expected Volume: exp(-4.95) Quality: ok param0: +0.0| 111111111111 222222222222 +0.8 | +1.0 param1: +0.0| 1111111111111 22222222222 +0.8 | +1.0 param2: +0.0| 111111111111 2222222222 +0.8 | +1.0 Z=-4.3(74.07%) | Like=-0.70..-0.01 [-0.7006..-0.6990]*| it/evals=1986/24247 eff=8.3281% N=400 Z=-4.3(74.76%) | Like=-0.68..-0.01 [-0.6830..-0.6808]*| it/evals=2000/24415 eff=8.3281% N=400 Z=-4.3(77.04%) | Like=-0.63..-0.01 [-0.6341..-0.6341]*| it/evals=2050/25015 eff=8.3283% N=400 Have 2 modes Volume: ~exp(-9.25) * Expected Volume: exp(-5.18) Quality: ok param0: +0.0| 111111111111 22222222222 +0.8 | +1.0 param1: +0.0| 111111111111 2222222222 +0.8 | +1.0 param2: +0.0| 111111111111 22222222222 +0.8 | +1.0 Z=-4.3(77.92%) | Like=-0.62..-0.01 [-0.6168..-0.6164]*| it/evals=2070/25255 eff=8.3283% N=400 Z=-4.3(79.18%) | Like=-0.59..-0.01 [-0.5915..-0.5908]*| it/evals=2100/25615 eff=8.3284% N=400 Z=-4.2(81.19%) | Like=-0.55..-0.01 [-0.5468..-0.5462]*| it/evals=2150/26215 eff=8.3285% N=400 Have 2 modes Volume: ~exp(-9.25) Expected Volume: exp(-5.40) Quality: ok param0: +0.0| 11111111111 2222222222 +0.8 | +1.0 param1: +0.0| 11111111111 022222222 2 +0.8 | +1.0 param2: +0.0| 11111111111 2222222222 +0.8 | +1.0 Z=-4.2(81.77%) | Like=-0.53..-0.01 [-0.5322..-0.5319]*| it/evals=2166/26407 eff=8.3285% N=400 Z=-4.2(83.00%) | Like=-0.50..-0.01 [-0.5043..-0.5043]*| it/evals=2200/26815 eff=8.3286% N=400 Have 2 modes Volume: ~exp(-9.58) * Expected Volume: exp(-5.63) Quality: ok param0: +0.0| 11111111111 222222222 +0.8 | +1.0 param1: +0.0| 1111111111 22222222 +0.8 | +1.0 param2: +0.0| 11111111111 222222222 +0.8 | +1.0 Z=-4.2(84.68%) | Like=-0.46..-0.01 [-0.4649..-0.4648]*| it/evals=2250/27415 eff=8.3287% N=400 Z=-4.2(86.16%) | Like=-0.43..-0.01 [-0.4325..-0.4324]*| it/evals=2300/28015 eff=8.3288% N=400 Have 2 modes Volume: ~exp(-9.63) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| 1111111111 222222222 +0.8 | +1.0 Z=-4.2(87.28%) | Like=-0.40..-0.01 [-0.4025..-0.4017]*| it/evals=2340/28495 eff=8.3289% N=400 Z=-4.2(87.54%) | Like=-0.40..-0.01 [-0.3971..-0.3969]*| it/evals=2350/28615 eff=8.3289% N=400 Z=-4.1(88.80%) | Like=-0.37..-0.01 [-0.3664..-0.3656]*| it/evals=2400/29215 eff=8.3290% N=400 Have 2 modes Volume: ~exp(-9.67) * Expected Volume: exp(-6.08) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-4.1(89.49%) | Like=-0.35..-0.01 [-0.3506..-0.3505]*| it/evals=2430/29575 eff=8.3290% N=400 Z=-4.1(89.94%) | Like=-0.34..-0.01 [-0.3366..-0.3359]*| it/evals=2450/29815 eff=8.3291% N=400 Z=-4.1(90.98%) | Like=-0.31..-0.01 [-0.3102..-0.3096]*| it/evals=2500/30415 eff=8.3292% N=400 Have 2 modes Volume: ~exp(-10.18) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-4.1(91.36%) | Like=-0.30..-0.01 [-0.2977..-0.2975]*| it/evals=2520/30655 eff=8.3292% N=400 Z=-4.1(91.91%) | Like=-0.28..-0.01 [-0.2806..-0.2805]*| it/evals=2550/31015 eff=8.3293% N=400 Z=-4.1(92.77%) | Like=-0.26..-0.01 [-0.2624..-0.2624]*| it/evals=2600/31615 eff=8.3293% N=400 Have 2 modes Volume: ~exp(-10.18) * Expected Volume: exp(-6.53) Quality: ok param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 2222222 +0.7 | +1.0 param2: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 Z=-4.1(92.94%) | Like=-0.26..-0.01 [-0.2580..-0.2579]*| it/evals=2610/31735 eff=8.3293% N=400 Z=-4.1(93.55%) | Like=-0.24..-0.01 [-0.2415..-0.2406]*| it/evals=2650/32215 eff=8.3294% N=400 Have 2 modes Volume: ~exp(-10.52) * Expected Volume: exp(-6.75) Quality: ok param0: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-4.1(94.24%) | Like=-0.22..-0.01 [-0.2232..-0.2227]*| it/evals=2700/32815 eff=8.3295% N=400 Z=-4.1(94.87%) | Like=-0.20..-0.01 [-0.2014..-0.2007]*| it/evals=2750/33415 eff=8.3295% N=400 Have 2 modes Volume: ~exp(-11.07) * Expected Volume: exp(-6.98) Quality: ok param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-4.1(95.32%) | Like=-0.19..-0.00 [-0.1892..-0.1889]*| it/evals=2790/33895 eff=8.3296% N=400 Z=-4.1(95.43%) | Like=-0.19..-0.00 [-0.1862..-0.1858]*| it/evals=2800/34015 eff=8.3296% N=400 Z=-4.1(95.89%) | Like=-0.17..-0.00 [-0.1721..-0.1719]*| it/evals=2846/34567 eff=8.3297% N=400 Z=-4.1(95.93%) | Like=-0.17..-0.00 [-0.1715..-0.1708]*| it/evals=2850/34615 eff=8.3297% N=400 Have 2 modes Volume: ~exp(-11.66) * Expected Volume: exp(-7.20) Quality: ok param0: +0.0| +0.2 111111 222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 param2: +0.0| +0.2 1111111 22222 +0.7 | +1.0 Z=-4.1(96.20%) | Like=-0.16..-0.00 [-0.1644..-0.1643]*| it/evals=2880/34975 eff=8.3297% N=400 Z=-4.1(96.37%) | Like=-0.16..-0.00 [-0.1583..-0.1583]*| it/evals=2900/35215 eff=8.3297% N=400 Z=-4.1(96.78%) | Like=-0.14..-0.00 [-0.1435..-0.1434]*| it/evals=2950/35815 eff=8.3298% N=400 Have 2 modes Volume: ~exp(-11.66) Expected Volume: exp(-7.43) Quality: ok param0: +0.0| +0.2 111111 222222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.2 111111 22222 +0.7 | +1.0 Z=-4.1(97.05%) | Like=-0.14..-0.00 [-0.1359..-0.1357]*| it/evals=2988/36271 eff=8.3298% N=400 Z=-4.1(97.13%) | Like=-0.13..-0.00 [-0.1339..-0.1332]*| it/evals=3000/36415 eff=8.3299% N=400 Z=-4.1(97.45%) | Like=-0.12..-0.00 [-0.1233..-0.1232]*| it/evals=3050/37015 eff=8.3299% N=400 Have 2 modes Volume: ~exp(-11.73) * Expected Volume: exp(-7.65) Quality: ok param0: +0.0| +0.3 111111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 222222 +0.7 | +1.0 param2: +0.0| +0.3 111111 22222 +0.7 | +1.0 Z=-4.1(97.51%) | Like=-0.12..-0.00 [-0.1212..-0.1211]*| it/evals=3060/37135 eff=8.3299% N=400 Z=-4.1(97.74%) | Like=-0.11..-0.00 [-0.1138..-0.1127]*| it/evals=3100/37615 eff=8.3300% N=400 Have 2 modes Volume: ~exp(-12.08) * Expected Volume: exp(-7.88) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-4.0(97.99%) | Like=-0.10..-0.00 [-0.1045..-0.1044]*| it/evals=3150/38217 eff=8.3296% N=400 Z=-4.0(98.19%) | Like=-0.10..-0.00 [-0.0969..-0.0968]*| it/evals=3192/38721 eff=8.3296% N=400 Z=-4.0(98.22%) | Like=-0.10..-0.00 [-0.0956..-0.0955]*| it/evals=3200/38817 eff=8.3296% N=400 Have 2 modes Volume: ~exp(-12.08) Expected Volume: exp(-8.10) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-4.0(98.38%) | Like=-0.09..-0.00 [-0.0901..-0.0900]*| it/evals=3240/39298 eff=8.3295% N=400 Z=-4.0(98.42%) | Like=-0.09..-0.00 [-0.0888..-0.0883]*| it/evals=3250/39418 eff=8.3295% N=400 Z=-4.0(98.59%) | Like=-0.08..-0.00 [-0.0816..-0.0816]*| it/evals=3296/39970 eff=8.3295% N=400 Z=-4.0(98.60%) | Like=-0.08..-0.00 [-0.0813..-0.0812]*| it/evals=3300/40018 eff=8.3295% N=400 Have 2 modes Volume: ~exp(-12.47) * Expected Volume: exp(-8.33) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-4.0(98.70%) | Like=-0.08..-0.00 [-0.0774..-0.0773]*| it/evals=3330/40378 eff=8.3296% N=400 Z=-4.0(98.76%) | Like=-0.07..-0.00 [-0.0747..-0.0747]*| it/evals=3350/40618 eff=8.3296% N=400 Z=-4.0(98.90%) | Like=-0.07..-0.00 [-0.0675..-0.0675]*| it/evals=3400/41218 eff=8.3297% N=400 Have 2 modes Volume: ~exp(-12.47) Expected Volume: exp(-8.55) Quality: ok param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 2222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-4.0(98.99%) | Like=-0.06..-0.00 [-0.0633..-0.0631]*| it/evals=3433/41615 eff=8.3295% N=400 [ultranest] Explored until L=-0.0002 [ultranest] Likelihood function evaluations: 41675 [ultranest] logZ = -4.031 +- 0.05895 [ultranest] Effective samples strategy satisfied (ESS = 2002.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -4.027 +- 0.106 single instance: logZ = -4.027 +- 0.077 bootstrapped : logZ = -4.031 +- 0.106 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▂▃▃▄▄▅▇▇▇▇▆▆▆▅▃▂▂▁▂▂▂▂▂▂▂▁▁▁▁▁▁▁▁▁▁▁│1.00 0.35 +- 0.17 param1 : 0.00 │▁▁▂▂▂▃▅▅▆▇▇▇▇▇▅▄▃▃▁▂▁▁▁▁▁▂▂▂▁▁▁▁▁▁▁▁▁▁ │1.00 0.34 +- 0.18 param2 : 0.00 │▁▁▁▁▂▃▄▄▇▇▇▇▇▆▅▄▃▃▂▂▁▁▁▁▁▂▁▂▁▂▁▁▁▁▁▁▁▁ │1.00 0.35 +- 0.18
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=412, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.04, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=27, ncalls=736, regioncalls=0, ndraw=128, logz=-27.68, remainder_fraction=100.0000%, Lmin=-23.65, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1012, regioncalls=0, ndraw=128, logz=-25.06, remainder_fraction=100.0000%, Lmin=-21.40, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1492, regioncalls=0, ndraw=128, logz=-21.02, remainder_fraction=100.0000%, Lmin=-16.93, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1612, regioncalls=0, ndraw=128, logz=-20.00, remainder_fraction=100.0000%, Lmin=-16.02, Lmax=-1.06 DEBUG ultranest:integrator.py:2610 iteration=137, ncalls=2056, regioncalls=0, ndraw=128, logz=-16.93, remainder_fraction=99.9997%, Lmin=-13.39, Lmax=-0.56 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=2212, regioncalls=0, ndraw=128, logz=-16.22, remainder_fraction=99.9994%, Lmin=-12.90, Lmax=-0.56 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=2572, regioncalls=0, ndraw=128, logz=-15.05, remainder_fraction=99.9981%, Lmin=-11.80, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=2812, regioncalls=0, ndraw=128, logz=-14.34, remainder_fraction=99.9963%, Lmin=-11.20, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=236, ncalls=3244, regioncalls=0, ndraw=128, logz=-13.22, remainder_fraction=99.9889%, Lmin=-10.26, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3412, regioncalls=0, ndraw=128, logz=-12.87, remainder_fraction=99.9855%, Lmin=-9.98, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=3652, regioncalls=0, ndraw=128, logz=-12.43, remainder_fraction=99.9780%, Lmin=-9.71, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=295, ncalls=3952, regioncalls=0, ndraw=128, logz=-11.96, remainder_fraction=99.9641%, Lmin=-9.20, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=4012, regioncalls=0, ndraw=128, logz=-11.87, remainder_fraction=99.9605%, Lmin=-9.09, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=339, ncalls=4480, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9239%, Lmin=-8.53, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=4612, regioncalls=0, ndraw=128, logz=-11.04, remainder_fraction=99.9084%, Lmin=-8.36, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=4732, regioncalls=0, ndraw=128, logz=-10.89, remainder_fraction=99.8920%, Lmin=-8.23, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=384, ncalls=5020, regioncalls=0, ndraw=128, logz=-10.55, remainder_fraction=99.8460%, Lmin=-7.84, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5212, regioncalls=0, ndraw=128, logz=-10.33, remainder_fraction=99.8031%, Lmin=-7.64, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=442, ncalls=5716, regioncalls=0, ndraw=128, logz=-9.80, remainder_fraction=99.7068%, Lmin=-7.18, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5812, regioncalls=0, ndraw=128, logz=-9.71, remainder_fraction=99.6800%, Lmin=-7.09, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=473, ncalls=6088, regioncalls=0, ndraw=128, logz=-9.46, remainder_fraction=99.5860%, Lmin=-6.83, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=6412, regioncalls=0, ndraw=128, logz=-9.19, remainder_fraction=99.4440%, Lmin=-6.57, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=6892, regioncalls=0, ndraw=128, logz=-8.81, remainder_fraction=99.1854%, Lmin=-6.14, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=7012, regioncalls=0, ndraw=128, logz=-8.71, remainder_fraction=99.1150%, Lmin=-6.02, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=574, ncalls=7300, regioncalls=0, ndraw=128, logz=-8.49, remainder_fraction=98.8630%, Lmin=-5.73, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=7612, regioncalls=0, ndraw=128, logz=-8.25, remainder_fraction=98.5485%, Lmin=-5.49, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=7972, regioncalls=0, ndraw=128, logz=-8.00, remainder_fraction=98.1910%, Lmin=-5.29, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=8212, regioncalls=0, ndraw=128, logz=-7.85, remainder_fraction=97.9083%, Lmin=-5.14, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=688, ncalls=8668, regioncalls=0, ndraw=128, logz=-7.59, remainder_fraction=97.2384%, Lmin=-4.93, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=8812, regioncalls=0, ndraw=128, logz=-7.52, remainder_fraction=97.0112%, Lmin=-4.88, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=9052, regioncalls=0, ndraw=128, logz=-7.40, remainder_fraction=96.6833%, Lmin=-4.76, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=9412, regioncalls=0, ndraw=128, logz=-7.23, remainder_fraction=96.1230%, Lmin=-4.57, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=10012, regioncalls=0, ndraw=128, logz=-6.97, remainder_fraction=94.9092%, Lmin=-4.31, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=827, ncalls=10336, regioncalls=0, ndraw=128, logz=-6.85, remainder_fraction=94.1393%, Lmin=-4.20, Lmax=-0.11 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=10612, regioncalls=0, ndraw=128, logz=-6.75, remainder_fraction=93.6019%, Lmin=-4.09, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=11212, regioncalls=0, ndraw=128, logz=-6.54, remainder_fraction=92.1873%, Lmin=-3.82, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=945, ncalls=11752, regioncalls=0, ndraw=128, logz=-6.36, remainder_fraction=90.4012%, Lmin=-3.56, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=11812, regioncalls=0, ndraw=128, logz=-6.34, remainder_fraction=90.2091%, Lmin=-3.54, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=12292, regioncalls=0, ndraw=128, logz=-6.19, remainder_fraction=88.6691%, Lmin=-3.29, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=12412, regioncalls=0, ndraw=128, logz=-6.15, remainder_fraction=88.2654%, Lmin=-3.22, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=13012, regioncalls=0, ndraw=128, logz=-5.97, remainder_fraction=85.6883%, Lmin=-3.03, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=13372, regioncalls=0, ndraw=128, logz=-5.87, remainder_fraction=83.9463%, Lmin=-2.90, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=13612, regioncalls=0, ndraw=128, logz=-5.81, remainder_fraction=82.9091%, Lmin=-2.82, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=14212, regioncalls=0, ndraw=128, logz=-5.65, remainder_fraction=80.0296%, Lmin=-2.62, Lmax=-0.06 DEBUG ultranest:integrator.py:2610 iteration=1186, ncalls=14644, regioncalls=0, ndraw=128, logz=-5.55, remainder_fraction=78.0026%, Lmin=-2.50, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=14812, regioncalls=0, ndraw=128, logz=-5.52, remainder_fraction=77.1306%, Lmin=-2.46, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=15412, regioncalls=0, ndraw=128, logz=-5.39, remainder_fraction=74.2389%, Lmin=-2.28, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=15532, regioncalls=0, ndraw=128, logz=-5.36, remainder_fraction=73.4801%, Lmin=-2.24, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=16012, regioncalls=0, ndraw=128, logz=-5.27, remainder_fraction=71.0158%, Lmin=-2.09, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=16612, regioncalls=0, ndraw=128, logz=-5.15, remainder_fraction=67.4832%, Lmin=-1.90, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1379, ncalls=16960, regioncalls=0, ndraw=128, logz=-5.09, remainder_fraction=65.0333%, Lmin=-1.81, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=17212, regioncalls=0, ndraw=128, logz=-5.05, remainder_fraction=63.4313%, Lmin=-1.73, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=17692, regioncalls=0, ndraw=128, logz=-4.97, remainder_fraction=60.7556%, Lmin=-1.63, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=17812, regioncalls=0, ndraw=128, logz=-4.95, remainder_fraction=60.0452%, Lmin=-1.60, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1496, ncalls=18364, regioncalls=0, ndraw=128, logz=-4.86, remainder_fraction=56.4823%, Lmin=-1.48, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=18412, regioncalls=0, ndraw=128, logz=-4.86, remainder_fraction=56.2831%, Lmin=-1.47, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=18772, regioncalls=0, ndraw=128, logz=-4.81, remainder_fraction=53.7911%, Lmin=-1.41, Lmax=-0.03 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=19012, regioncalls=0, ndraw=128, logz=-4.77, remainder_fraction=52.4290%, Lmin=-1.39, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1591, ncalls=19504, regioncalls=0, ndraw=128, logz=-4.71, remainder_fraction=49.7954%, Lmin=-1.32, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=19612, regioncalls=0, ndraw=128, logz=-4.70, remainder_fraction=49.1489%, Lmin=-1.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=19852, regioncalls=0, ndraw=128, logz=-4.67, remainder_fraction=47.7467%, Lmin=-1.25, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=20214, regioncalls=0, ndraw=128, logz=-4.64, remainder_fraction=45.6547%, Lmin=-1.21, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1689, ncalls=20682, regioncalls=0, ndraw=128, logz=-4.59, remainder_fraction=43.1841%, Lmin=-1.15, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=20814, regioncalls=0, ndraw=128, logz=-4.58, remainder_fraction=42.4477%, Lmin=-1.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1726, ncalls=21126, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=40.7851%, Lmin=-1.07, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=21414, regioncalls=0, ndraw=128, logz=-4.52, remainder_fraction=39.2742%, Lmin=-1.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1793, ncalls=21930, regioncalls=0, ndraw=128, logz=-4.48, remainder_fraction=36.5956%, Lmin=-0.95, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=22014, regioncalls=0, ndraw=128, logz=-4.47, remainder_fraction=36.2143%, Lmin=-0.94, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1826, ncalls=22326, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=34.7321%, Lmin=-0.90, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=22614, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=33.2721%, Lmin=-0.88, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1883, ncalls=23010, regioncalls=0, ndraw=128, logz=-4.40, remainder_fraction=31.4290%, Lmin=-0.82, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=23094, regioncalls=0, ndraw=128, logz=-4.40, remainder_fraction=31.0105%, Lmin=-0.81, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=23214, regioncalls=0, ndraw=128, logz=-4.39, remainder_fraction=30.3880%, Lmin=-0.81, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1942, ncalls=23718, regioncalls=0, ndraw=128, logz=-4.36, remainder_fraction=28.1000%, Lmin=-0.76, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=23814, regioncalls=0, ndraw=128, logz=-4.35, remainder_fraction=27.6380%, Lmin=-0.75, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1986, ncalls=24247, regioncalls=0, ndraw=128, logz=-4.33, remainder_fraction=25.9258%, Lmin=-0.70, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=24415, regioncalls=0, ndraw=128, logz=-4.32, remainder_fraction=25.2361%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=25015, regioncalls=0, ndraw=128, logz=-4.29, remainder_fraction=22.9561%, Lmin=-0.63, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=25255, regioncalls=0, ndraw=128, logz=-4.28, remainder_fraction=22.0789%, Lmin=-0.62, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=25615, regioncalls=0, ndraw=128, logz=-4.26, remainder_fraction=20.8188%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=26215, regioncalls=0, ndraw=128, logz=-4.24, remainder_fraction=18.8076%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2166, ncalls=26407, regioncalls=0, ndraw=128, logz=-4.23, remainder_fraction=18.2333%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=26815, regioncalls=0, ndraw=128, logz=-4.21, remainder_fraction=16.9984%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=27415, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=15.3219%, Lmin=-0.46, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=28015, regioncalls=0, ndraw=128, logz=-4.18, remainder_fraction=13.8385%, Lmin=-0.43, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=28495, regioncalls=0, ndraw=128, logz=-4.16, remainder_fraction=12.7169%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=28615, regioncalls=0, ndraw=128, logz=-4.16, remainder_fraction=12.4583%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=29215, regioncalls=0, ndraw=128, logz=-4.15, remainder_fraction=11.2007%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=29575, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=10.5052%, Lmin=-0.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=29815, regioncalls=0, ndraw=128, logz=-4.13, remainder_fraction=10.0624%, Lmin=-0.34, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=30415, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=9.0180%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=30655, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=8.6427%, Lmin=-0.30, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=31015, regioncalls=0, ndraw=128, logz=-4.11, remainder_fraction=8.0937%, Lmin=-0.28, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=31615, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=7.2269%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=31735, regioncalls=0, ndraw=128, logz=-4.10, remainder_fraction=7.0617%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=32215, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=6.4500%, Lmin=-0.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32815, regioncalls=0, ndraw=128, logz=-4.09, remainder_fraction=5.7565%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33415, regioncalls=0, ndraw=128, logz=-4.08, remainder_fraction=5.1326%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=33895, regioncalls=0, ndraw=128, logz=-4.08, remainder_fraction=4.6763%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=34015, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.5702%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2846, ncalls=34567, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.1062%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34615, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=4.0697%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34975, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=3.7990%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35215, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=3.6267%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35815, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=3.2241%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2988, ncalls=36271, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=2.9468%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36415, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=2.8655%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37015, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.5458%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37135, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.4872%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37615, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.2610%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38217, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=2.0051%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3192, ncalls=38721, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=1.8122%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=38817, regioncalls=0, ndraw=128, logz=-4.05, remainder_fraction=1.7784%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3240, ncalls=39298, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.6161%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3250, ncalls=39418, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.5776%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3296, ncalls=39970, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.4118%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3300, ncalls=40018, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.3983%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3330, ncalls=40378, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.3003%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3350, ncalls=40618, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.2391%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3400, ncalls=41218, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.0976%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3433, ncalls=41615, regioncalls=0, ndraw=128, logz=-4.04, remainder_fraction=1.0131%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.0002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 41675 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -4.031 +- 0.05895 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 2002.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.08 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_store.py::test_storemany

0.70

[gw10] linux -- Python 3.10.6 /usr/bin/python3
[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3[gw10] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
======== <class 'ultranest.store.TextPointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[1]: [(1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] 0 0.1 reading: [0.0, 1.0, 1.0] stack[2]: [(2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[3]: [(3, [1.0, 1.5, 1.5])] 1 1.1 reading: [1.0, 1.5, 1.5] ======== <class 'ultranest.store.TextPointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[1]: [(2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] stack[2]: [(4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[3]: [(6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] ======== <class 'ultranest.store.TextPointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[1]: [(10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] stack[2]: [(20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[3]: [(30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] ======== <class 'ultranest.store.TextPointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [-inf, 9.9, 9.9]), (11, [-inf, 10.9, 10.9]), (12, [-inf, 11.9, 11.9]), (13, [-inf, 12.9, 12.9]), (14, [-inf, 13.9, 13.9]), (15, [-inf, 14.9, 14.9]), (16, [-inf, 15.9, 15.9]), (17, [-inf, 16.9, 16.9]), (18, [-inf, 17.9, 17.9]), (19, [-inf, 18.9, 18.9]), (20, [-inf, 19.9, 19.9]), (21, [-inf, 20.9, 20.9]), (22, [-inf, 21.9, 21.9]), (23, [-inf, 22.9, 22.9]), (24, [-inf, 23.9, 23.9]), (25, [-inf, 24.9, 24.9]), (26, [-inf, 25.9, 25.9]), (27, [-inf, 26.9, 26.9]), (28, [-inf, 27.9, 27.9]), (29, [-inf, 28.9, 28.9]), (30, [-inf, 29.9, 29.9]), (31, [-inf, 30.9, 30.9]), (32, [-inf, 31.9, 31.9]), (33, [-inf, 32.9, 32.9]), (34, [-inf, 33.9, 33.9]), (35, [-inf, 34.9, 34.9]), (36, [-inf, 35.9, 35.9]), (37, [-inf, 36.9, 36.9]), (38, [-inf, 37.9, 37.9]), (39, [-inf, 38.9, 38.9]), (40, [-inf, 39.9, 39.9]), (41, [-inf, 40.9, 40.9]), (42, [-inf, 41.9, 41.9]), (43, [-inf, 42.9, 42.9]), (44, [-inf, 43.9, 43.9]), (45, [-inf, 44.9, 44.9]), (46, [-inf, 45.9, 45.9]), (47, [-inf, 46.9, 46.9]), (48, [-inf, 47.9, 47.9]), (49, [-inf, 48.9, 48.9]), (50, [-inf, 49.9, 49.9]), (51, [-inf, 50.9, 50.9]), (52, [-inf, 51.9, 51.9]), (53, [-inf, 52.9, 52.9]), (54, [-inf, 53.9, 53.9]), (55, [-inf, 54.9, 54.9]), (56, [-inf, 55.9, 55.9]), (57, [-inf, 56.9, 56.9]), (58, [-inf, 57.9, 57.9]), (59, [-inf, 58.9, 58.9]), (60, [-inf, 59.9, 59.9]), (61, [-inf, 60.9, 60.9]), (62, [-inf, 61.9, 61.9]), (63, [-inf, 62.9, 62.9]), (64, [-inf, 63.9, 63.9]), (65, [-inf, 64.9, 64.9]), (66, [-inf, 65.9, 65.9]), (67, [-inf, 66.9, 66.9]), (68, [-inf, 67.9, 67.9]), (69, [-inf, 68.9, 68.9]), (70, [-inf, 69.9, 69.9]), (71, [-inf, 70.9, 70.9]), (72, [-inf, 71.9, 71.9]), (73, [-inf, 72.9, 72.9]), (74, [-inf, 73.9, 73.9]), (75, [-inf, 74.9, 74.9]), (76, [-inf, 75.9, 75.9]), (77, [-inf, 76.9, 76.9]), (78, [-inf, 77.9, 77.9]), (79, [-inf, 78.9, 78.9]), (80, [-inf, 79.9, 79.9]), (81, [-inf, 80.9, 80.9]), (82, [-inf, 81.9, 81.9]), (83, [-inf, 82.9, 82.9]), (84, [-inf, 83.9, 83.9]), (85, [-inf, 84.9, 84.9]), (86, [-inf, 85.9, 85.9]), (87, [-inf, 86.9, 86.9]), (88, [-inf, 87.9, 87.9]), (89, [-inf, 88.9, 88.9]), (90, [-inf, 89.9, 89.9]), (91, [-inf, 90.9, 90.9]), (92, [-inf, 91.9, 91.9]), (93, [-inf, 92.9, 92.9]), (94, [-inf, 93.9, 93.9]), (95, [-inf, 94.9, 94.9]), (96, [-inf, 95.9, 95.9]), (97, [-inf, 96.9, 96.9]), (98, [-inf, 97.9, 97.9]), (99, [-inf, 98.9, 98.9]), (100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[1]: [(100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] 10 10.1 reading: [10.0, 11.0, 11.0] 11 11.1 reading: [11.0, 12.0, 12.0] 12 12.1 reading: [12.0, 13.0, 13.0] 13 13.1 reading: [13.0, 14.0, 14.0] 14 14.1 reading: [14.0, 15.0, 15.0] 15 15.1 reading: [15.0, 16.0, 16.0] 16 16.1 reading: [16.0, 17.0, 17.0] 17 17.1 reading: [17.0, 18.0, 18.0] 18 18.1 reading: [18.0, 19.0, 19.0] 19 19.1 reading: [19.0, 20.0, 20.0] 20 20.1 reading: [20.0, 21.0, 21.0] 21 21.1 reading: [21.0, 22.0, 22.0] 22 22.1 reading: [22.0, 23.0, 23.0] 23 23.1 reading: [23.0, 24.0, 24.0] 24 24.1 reading: [24.0, 25.0, 25.0] 25 25.1 reading: [25.0, 26.0, 26.0] 26 26.1 reading: [26.0, 27.0, 27.0] 27 27.1 reading: [27.0, 28.0, 28.0] 28 28.1 reading: [28.0, 29.0, 29.0] 29 29.1 reading: [29.0, 30.0, 30.0] 30 30.1 reading: [30.0, 31.0, 31.0] 31 31.1 reading: [31.0, 32.0, 32.0] 32 32.1 reading: [32.0, 33.0, 33.0] 33 33.1 reading: [33.0, 34.0, 34.0] 34 34.1 reading: [34.0, 35.0, 35.0] 35 35.1 reading: [35.0, 36.0, 36.0] 36 36.1 reading: [36.0, 37.0, 37.0] 37 37.1 reading: [37.0, 38.0, 38.0] 38 38.1 reading: [38.0, 39.0, 39.0] 39 39.1 reading: [39.0, 40.0, 40.0] 40 40.1 reading: [40.0, 41.0, 41.0] 41 41.1 reading: [41.0, 42.0, 42.0] 42 42.1 reading: [42.0, 43.0, 43.0] 43 43.1 reading: [43.0, 44.0, 44.0] 44 44.1 reading: [44.0, 45.0, 45.0] 45 45.1 reading: [45.0, 46.0, 46.0] 46 46.1 reading: [46.0, 47.0, 47.0] 47 47.1 reading: [47.0, 48.0, 48.0] 48 48.1 reading: [48.0, 49.0, 49.0] 49 49.1 reading: [49.0, 50.0, 50.0] 50 50.1 reading: [50.0, 51.0, 51.0] 51 51.1 reading: [51.0, 52.0, 52.0] 52 52.1 reading: [52.0, 53.0, 53.0] 53 53.1 reading: [53.0, 54.0, 54.0] 54 54.1 reading: [54.0, 55.0, 55.0] 55 55.1 reading: [55.0, 56.0, 56.0] 56 56.1 reading: [56.0, 57.0, 57.0] 57 57.1 reading: [57.0, 58.0, 58.0] 58 58.1 reading: [58.0, 59.0, 59.0] 59 59.1 reading: [59.0, 60.0, 60.0] 60 60.1 reading: [60.0, 61.0, 61.0] 61 61.1 reading: [61.0, 62.0, 62.0] 62 62.1 reading: [62.0, 63.0, 63.0] 63 63.1 reading: [63.0, 64.0, 64.0] 64 64.1 reading: [64.0, 65.0, 65.0] 65 65.1 reading: [65.0, 66.0, 66.0] 66 66.1 reading: [66.0, 67.0, 67.0] 67 67.1 reading: [67.0, 68.0, 68.0] 68 68.1 reading: [68.0, 69.0, 69.0] 69 69.1 reading: [69.0, 70.0, 70.0] 70 70.1 reading: [70.0, 71.0, 71.0] 71 71.1 reading: [71.0, 72.0, 72.0] 72 72.1 reading: [72.0, 73.0, 73.0] 73 73.1 reading: [73.0, 74.0, 74.0] 74 74.1 reading: [74.0, 75.0, 75.0] 75 75.1 reading: [75.0, 76.0, 76.0] 76 76.1 reading: [76.0, 77.0, 77.0] 77 77.1 reading: [77.0, 78.0, 78.0] 78 78.1 reading: [78.0, 79.0, 79.0] 79 79.1 reading: [79.0, 80.0, 80.0] 80 80.1 reading: [80.0, 81.0, 81.0] 81 81.1 reading: [81.0, 82.0, 82.0] 82 82.1 reading: [82.0, 83.0, 83.0] 83 83.1 reading: [83.0, 84.0, 84.0] 84 84.1 reading: [84.0, 85.0, 85.0] 85 85.1 reading: [85.0, 86.0, 86.0] 86 86.1 reading: [86.0, 87.0, 87.0] 87 87.1 reading: [87.0, 88.0, 88.0] 88 88.1 reading: [88.0, 89.0, 89.0] 89 89.1 reading: [89.0, 90.0, 90.0] 90 90.1 reading: [90.0, 91.0, 91.0] 91 91.1 reading: [91.0, 92.0, 92.0] 92 92.1 reading: [92.0, 93.0, 93.0] 93 93.1 reading: [93.0, 94.0, 94.0] 94 94.1 reading: [94.0, 95.0, 95.0] 95 95.1 reading: [95.0, 96.0, 96.0] 96 96.1 reading: [96.0, 97.0, 97.0] 97 97.1 reading: [97.0, 98.0, 98.0] 98 98.1 reading: [98.0, 99.0, 99.0] 99 99.1 reading: [99.0, 100.0, 100.0] stack[2]: [(200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[3]: [(300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] 11 11.1 reading: [11.0, 11.5, 11.5] 12 12.1 reading: [12.0, 12.5, 12.5] 13 13.1 reading: [13.0, 13.5, 13.5] 14 14.1 reading: [14.0, 14.5, 14.5] 15 15.1 reading: [15.0, 15.5, 15.5] 16 16.1 reading: [16.0, 16.5, 16.5] 17 17.1 reading: [17.0, 17.5, 17.5] 18 18.1 reading: [18.0, 18.5, 18.5] 19 19.1 reading: [19.0, 19.5, 19.5] 20 20.1 reading: [20.0, 20.5, 20.5] 21 21.1 reading: [21.0, 21.5, 21.5] 22 22.1 reading: [22.0, 22.5, 22.5] 23 23.1 reading: [23.0, 23.5, 23.5] 24 24.1 reading: [24.0, 24.5, 24.5] 25 25.1 reading: [25.0, 25.5, 25.5] 26 26.1 reading: [26.0, 26.5, 26.5] 27 27.1 reading: [27.0, 27.5, 27.5] 28 28.1 reading: [28.0, 28.5, 28.5] 29 29.1 reading: [29.0, 29.5, 29.5] 30 30.1 reading: [30.0, 30.5, 30.5] 31 31.1 reading: [31.0, 31.5, 31.5] 32 32.1 reading: [32.0, 32.5, 32.5] 33 33.1 reading: [33.0, 33.5, 33.5] 34 34.1 reading: [34.0, 34.5, 34.5] 35 35.1 reading: [35.0, 35.5, 35.5] 36 36.1 reading: [36.0, 36.5, 36.5] 37 37.1 reading: [37.0, 37.5, 37.5] 38 38.1 reading: [38.0, 38.5, 38.5] 39 39.1 reading: [39.0, 39.5, 39.5] 40 40.1 reading: [40.0, 40.5, 40.5] 41 41.1 reading: [41.0, 41.5, 41.5] 42 42.1 reading: [42.0, 42.5, 42.5] 43 43.1 reading: [43.0, 43.5, 43.5] 44 44.1 reading: [44.0, 44.5, 44.5] 45 45.1 reading: [45.0, 45.5, 45.5] 46 46.1 reading: [46.0, 46.5, 46.5] 47 47.1 reading: [47.0, 47.5, 47.5] 48 48.1 reading: [48.0, 48.5, 48.5] 49 49.1 reading: [49.0, 49.5, 49.5] 50 50.1 reading: [50.0, 50.5, 50.5] 51 51.1 reading: [51.0, 51.5, 51.5] 52 52.1 reading: [52.0, 52.5, 52.5] 53 53.1 reading: [53.0, 53.5, 53.5] 54 54.1 reading: [54.0, 54.5, 54.5] 55 55.1 reading: [55.0, 55.5, 55.5] 56 56.1 reading: [56.0, 56.5, 56.5] 57 57.1 reading: [57.0, 57.5, 57.5] 58 58.1 reading: [58.0, 58.5, 58.5] 59 59.1 reading: [59.0, 59.5, 59.5] 60 60.1 reading: [60.0, 60.5, 60.5] 61 61.1 reading: [61.0, 61.5, 61.5] 62 62.1 reading: [62.0, 62.5, 62.5] 63 63.1 reading: [63.0, 63.5, 63.5] 64 64.1 reading: [64.0, 64.5, 64.5] 65 65.1 reading: [65.0, 65.5, 65.5] 66 66.1 reading: [66.0, 66.5, 66.5] 67 67.1 reading: [67.0, 67.5, 67.5] 68 68.1 reading: [68.0, 68.5, 68.5] 69 69.1 reading: [69.0, 69.5, 69.5] 70 70.1 reading: [70.0, 70.5, 70.5] 71 71.1 reading: [71.0, 71.5, 71.5] 72 72.1 reading: [72.0, 72.5, 72.5] 73 73.1 reading: [73.0, 73.5, 73.5] 74 74.1 reading: [74.0, 74.5, 74.5] 75 75.1 reading: [75.0, 75.5, 75.5] 76 76.1 reading: [76.0, 76.5, 76.5] 77 77.1 reading: [77.0, 77.5, 77.5] 78 78.1 reading: [78.0, 78.5, 78.5] 79 79.1 reading: [79.0, 79.5, 79.5] 80 80.1 reading: [80.0, 80.5, 80.5] 81 81.1 reading: [81.0, 81.5, 81.5] 82 82.1 reading: [82.0, 82.5, 82.5] 83 83.1 reading: [83.0, 83.5, 83.5] 84 84.1 reading: [84.0, 84.5, 84.5] 85 85.1 reading: [85.0, 85.5, 85.5] 86 86.1 reading: [86.0, 86.5, 86.5] 87 87.1 reading: [87.0, 87.5, 87.5] 88 88.1 reading: [88.0, 88.5, 88.5] 89 89.1 reading: [89.0, 89.5, 89.5] 90 90.1 reading: [90.0, 90.5, 90.5] 91 91.1 reading: [91.0, 91.5, 91.5] 92 92.1 reading: [92.0, 92.5, 92.5] 93 93.1 reading: [93.0, 93.5, 93.5] 94 94.1 reading: [94.0, 94.5, 94.5] 95 95.1 reading: [95.0, 95.5, 95.5] 96 96.1 reading: [96.0, 96.5, 96.5] 97 97.1 reading: [97.0, 97.5, 97.5] 98 98.1 reading: [98.0, 98.5, 98.5] 99 99.1 reading: [99.0, 99.5, 99.5] 100 100.1 reading: [100.0, 100.5, 100.5] ======== <class 'ultranest.store.HDF5PointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[1]: [(1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] 0 0.1 reading: [0. 1. 1.] stack[2]: [(2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[3]: [(3, array([1. , 1.5, 1.5]))] 1 1.1 reading: [1. 1.5 1.5] ======== <class 'ultranest.store.HDF5PointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[1]: [(2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] stack[2]: [(4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[3]: [(6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] ======== <class 'ultranest.store.HDF5PointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[1]: [(10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] stack[2]: [(20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[3]: [(30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] ======== <class 'ultranest.store.HDF5PointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([-inf, 9.9, 9.9])), (11, array([-inf, 10.9, 10.9])), (12, array([-inf, 11.9, 11.9])), (13, array([-inf, 12.9, 12.9])), (14, array([-inf, 13.9, 13.9])), (15, array([-inf, 14.9, 14.9])), (16, array([-inf, 15.9, 15.9])), (17, array([-inf, 16.9, 16.9])), (18, array([-inf, 17.9, 17.9])), (19, array([-inf, 18.9, 18.9])), (20, array([-inf, 19.9, 19.9])), (21, array([-inf, 20.9, 20.9])), (22, array([-inf, 21.9, 21.9])), (23, array([-inf, 22.9, 22.9])), (24, array([-inf, 23.9, 23.9])), (25, array([-inf, 24.9, 24.9])), (26, array([-inf, 25.9, 25.9])), (27, array([-inf, 26.9, 26.9])), (28, array([-inf, 27.9, 27.9])), (29, array([-inf, 28.9, 28.9])), (30, array([-inf, 29.9, 29.9])), (31, array([-inf, 30.9, 30.9])), (32, array([-inf, 31.9, 31.9])), (33, array([-inf, 32.9, 32.9])), (34, array([-inf, 33.9, 33.9])), (35, array([-inf, 34.9, 34.9])), (36, array([-inf, 35.9, 35.9])), (37, array([-inf, 36.9, 36.9])), (38, array([-inf, 37.9, 37.9])), (39, array([-inf, 38.9, 38.9])), (40, array([-inf, 39.9, 39.9])), (41, array([-inf, 40.9, 40.9])), (42, array([-inf, 41.9, 41.9])), (43, array([-inf, 42.9, 42.9])), (44, array([-inf, 43.9, 43.9])), (45, array([-inf, 44.9, 44.9])), (46, array([-inf, 45.9, 45.9])), (47, array([-inf, 46.9, 46.9])), (48, array([-inf, 47.9, 47.9])), (49, array([-inf, 48.9, 48.9])), (50, array([-inf, 49.9, 49.9])), (51, array([-inf, 50.9, 50.9])), (52, array([-inf, 51.9, 51.9])), (53, array([-inf, 52.9, 52.9])), (54, array([-inf, 53.9, 53.9])), (55, array([-inf, 54.9, 54.9])), (56, array([-inf, 55.9, 55.9])), (57, array([-inf, 56.9, 56.9])), (58, array([-inf, 57.9, 57.9])), (59, array([-inf, 58.9, 58.9])), (60, array([-inf, 59.9, 59.9])), (61, array([-inf, 60.9, 60.9])), (62, array([-inf, 61.9, 61.9])), (63, array([-inf, 62.9, 62.9])), (64, array([-inf, 63.9, 63.9])), (65, array([-inf, 64.9, 64.9])), (66, array([-inf, 65.9, 65.9])), (67, array([-inf, 66.9, 66.9])), (68, array([-inf, 67.9, 67.9])), (69, array([-inf, 68.9, 68.9])), (70, array([-inf, 69.9, 69.9])), (71, array([-inf, 70.9, 70.9])), (72, array([-inf, 71.9, 71.9])), (73, array([-inf, 72.9, 72.9])), (74, array([-inf, 73.9, 73.9])), (75, array([-inf, 74.9, 74.9])), (76, array([-inf, 75.9, 75.9])), (77, array([-inf, 76.9, 76.9])), (78, array([-inf, 77.9, 77.9])), (79, array([-inf, 78.9, 78.9])), (80, array([-inf, 79.9, 79.9])), (81, array([-inf, 80.9, 80.9])), (82, array([-inf, 81.9, 81.9])), (83, array([-inf, 82.9, 82.9])), (84, array([-inf, 83.9, 83.9])), (85, array([-inf, 84.9, 84.9])), (86, array([-inf, 85.9, 85.9])), (87, array([-inf, 86.9, 86.9])), (88, array([-inf, 87.9, 87.9])), (89, array([-inf, 88.9, 88.9])), (90, array([-inf, 89.9, 89.9])), (91, array([-inf, 90.9, 90.9])), (92, array([-inf, 91.9, 91.9])), (93, array([-inf, 92.9, 92.9])), (94, array([-inf, 93.9, 93.9])), (95, array([-inf, 94.9, 94.9])), (96, array([-inf, 95.9, 95.9])), (97, array([-inf, 96.9, 96.9])), (98, array([-inf, 97.9, 97.9])), (99, array([-inf, 98.9, 98.9])), (100, array([0., 1., 1.])), (101, array([1., 2., 2.])), (102, array([2., 3., 3.])), (103, array([3., 4., 4.])), (104, array([4., 5., 5.])), (105, array([5., 6., 6.])), (106, array([6., 7., 7.])), (107, array([7., 8., 8.])), (108, array([8., 9., 9.])), (109, array([ 9., 10., 10.])), (110, array([10., 11., 11.])), (111, array([11., 12., 12.])), (112, array([12., 13., 13.])), (113, array([13., 14., 14.])), (114, array([14., 15., 15.])), (115, array([15., 16., 16.])), (116, array([16., 17., 17.])), (117, array([17., 18., 18.])), (118, array([18., 19., 19.])), (119, array([19., 20., 20.])), (120, array([20., 21., 21.])), (121, array([21., 22., 22.])), (122, array([22., 23., 23.])), (123, array([23., 24., 24.])), (124, array([24., 25., 25.])), (125, array([25., 26., 26.])), (126, array([26., 27., 27.])), (127, array([27., 28., 28.])), (128, array([28., 29., 29.])), (129, array([29., 30., 30.])), (130, array([30., 31., 31.])), (131, array([31., 32., 32.])), (132, array([32., 33., 33.])), (133, array([33., 34., 34.])), (134, array([34., 35., 35.])), (135, array([35., 36., 36.])), (136, array([36., 37., 37.])), (137, array([37., 38., 38.])), (138, array([38., 39., 39.])), (139, array([39., 40., 40.])), (140, array([40., 41., 41.])), (141, array([41., 42., 42.])), (142, array([42., 43., 43.])), (143, array([43., 44., 44.])), (144, array([44., 45., 45.])), (145, array([45., 46., 46.])), (146, array([46., 47., 47.])), (147, array([47., 48., 48.])), (148, array([48., 49., 49.])), (149, array([49., 50., 50.])), (150, array([50., 51., 51.])), (151, array([51., 52., 52.])), (152, array([52., 53., 53.])), (153, array([53., 54., 54.])), (154, array([54., 55., 55.])), (155, array([55., 56., 56.])), (156, array([56., 57., 57.])), (157, array([57., 58., 58.])), (158, array([58., 59., 59.])), (159, array([59., 60., 60.])), (160, array([60., 61., 61.])), (161, array([61., 62., 62.])), (162, array([62., 63., 63.])), (163, array([63., 64., 64.])), (164, array([64., 65., 65.])), (165, array([65., 66., 66.])), (166, array([66., 67., 67.])), (167, array([67., 68., 68.])), (168, array([68., 69., 69.])), (169, array([69., 70., 70.])), (170, array([70., 71., 71.])), (171, array([71., 72., 72.])), (172, array([72., 73., 73.])), (173, array([73., 74., 74.])), (174, array([74., 75., 75.])), (175, array([75., 76., 76.])), (176, array([76., 77., 77.])), (177, array([77., 78., 78.])), (178, array([78., 79., 79.])), (179, array([79., 80., 80.])), (180, array([80., 81., 81.])), (181, array([81., 82., 82.])), (182, array([82., 83., 83.])), (183, array([83., 84., 84.])), (184, array([84., 85., 85.])), (185, array([85., 86., 86.])), (186, array([86., 87., 87.])), (187, array([87., 88., 88.])), (188, array([88., 89., 89.])), (189, array([89., 90., 90.])), (190, array([90., 91., 91.])), (191, array([91., 92., 92.])), (192, array([92., 93., 93.])), (193, array([93., 94., 94.])), (194, array([94., 95., 95.])), (195, array([95., 96., 96.])), (196, array([96., 97., 97.])), (197, array([97., 98., 98.])), (198, array([98., 99., 99.])), (199, array([ 99., 100., 100.])), (200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] stack[1]: [(100, array([0., 1., 1.])), (101, array([1., 2., 2.])), (102, array([2., 3., 3.])), (103, array([3., 4., 4.])), (104, array([4., 5., 5.])), (105, array([5., 6., 6.])), (106, array([6., 7., 7.])), (107, array([7., 8., 8.])), (108, array([8., 9., 9.])), (109, array([ 9., 10., 10.])), (110, array([10., 11., 11.])), (111, array([11., 12., 12.])), (112, array([12., 13., 13.])), (113, array([13., 14., 14.])), (114, array([14., 15., 15.])), (115, array([15., 16., 16.])), (116, array([16., 17., 17.])), (117, array([17., 18., 18.])), (118, array([18., 19., 19.])), (119, array([19., 20., 20.])), (120, array([20., 21., 21.])), (121, array([21., 22., 22.])), (122, array([22., 23., 23.])), (123, array([23., 24., 24.])), (124, array([24., 25., 25.])), (125, array([25., 26., 26.])), (126, array([26., 27., 27.])), (127, array([27., 28., 28.])), (128, array([28., 29., 29.])), (129, array([29., 30., 30.])), (130, array([30., 31., 31.])), (131, array([31., 32., 32.])), (132, array([32., 33., 33.])), (133, array([33., 34., 34.])), (134, array([34., 35., 35.])), (135, array([35., 36., 36.])), (136, array([36., 37., 37.])), (137, array([37., 38., 38.])), (138, array([38., 39., 39.])), (139, array([39., 40., 40.])), (140, array([40., 41., 41.])), (141, array([41., 42., 42.])), (142, array([42., 43., 43.])), (143, array([43., 44., 44.])), (144, array([44., 45., 45.])), (145, array([45., 46., 46.])), (146, array([46., 47., 47.])), (147, array([47., 48., 48.])), (148, array([48., 49., 49.])), (149, array([49., 50., 50.])), (150, array([50., 51., 51.])), (151, array([51., 52., 52.])), (152, array([52., 53., 53.])), (153, array([53., 54., 54.])), (154, array([54., 55., 55.])), (155, array([55., 56., 56.])), (156, array([56., 57., 57.])), (157, array([57., 58., 58.])), (158, array([58., 59., 59.])), (159, array([59., 60., 60.])), (160, array([60., 61., 61.])), (161, array([61., 62., 62.])), (162, array([62., 63., 63.])), (163, array([63., 64., 64.])), (164, array([64., 65., 65.])), (165, array([65., 66., 66.])), (166, array([66., 67., 67.])), (167, array([67., 68., 68.])), (168, array([68., 69., 69.])), (169, array([69., 70., 70.])), (170, array([70., 71., 71.])), (171, array([71., 72., 72.])), (172, array([72., 73., 73.])), (173, array([73., 74., 74.])), (174, array([74., 75., 75.])), (175, array([75., 76., 76.])), (176, array([76., 77., 77.])), (177, array([77., 78., 78.])), (178, array([78., 79., 79.])), (179, array([79., 80., 80.])), (180, array([80., 81., 81.])), (181, array([81., 82., 82.])), (182, array([82., 83., 83.])), (183, array([83., 84., 84.])), (184, array([84., 85., 85.])), (185, array([85., 86., 86.])), (186, array([86., 87., 87.])), (187, array([87., 88., 88.])), (188, array([88., 89., 89.])), (189, array([89., 90., 90.])), (190, array([90., 91., 91.])), (191, array([91., 92., 92.])), (192, array([92., 93., 93.])), (193, array([93., 94., 94.])), (194, array([94., 95., 95.])), (195, array([95., 96., 96.])), (196, array([96., 97., 97.])), (197, array([97., 98., 98.])), (198, array([98., 99., 99.])), (199, array([ 99., 100., 100.])), (200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] 10 10.1 reading: [10. 11. 11.] 11 11.1 reading: [11. 12. 12.] 12 12.1 reading: [12. 13. 13.] 13 13.1 reading: [13. 14. 14.] 14 14.1 reading: [14. 15. 15.] 15 15.1 reading: [15. 16. 16.] 16 16.1 reading: [16. 17. 17.] 17 17.1 reading: [17. 18. 18.] 18 18.1 reading: [18. 19. 19.] 19 19.1 reading: [19. 20. 20.] 20 20.1 reading: [20. 21. 21.] 21 21.1 reading: [21. 22. 22.] 22 22.1 reading: [22. 23. 23.] 23 23.1 reading: [23. 24. 24.] 24 24.1 reading: [24. 25. 25.] 25 25.1 reading: [25. 26. 26.] 26 26.1 reading: [26. 27. 27.] 27 27.1 reading: [27. 28. 28.] 28 28.1 reading: [28. 29. 29.] 29 29.1 reading: [29. 30. 30.] 30 30.1 reading: [30. 31. 31.] 31 31.1 reading: [31. 32. 32.] 32 32.1 reading: [32. 33. 33.] 33 33.1 reading: [33. 34. 34.] 34 34.1 reading: [34. 35. 35.] 35 35.1 reading: [35. 36. 36.] 36 36.1 reading: [36. 37. 37.] 37 37.1 reading: [37. 38. 38.] 38 38.1 reading: [38. 39. 39.] 39 39.1 reading: [39. 40. 40.] 40 40.1 reading: [40. 41. 41.] 41 41.1 reading: [41. 42. 42.] 42 42.1 reading: [42. 43. 43.] 43 43.1 reading: [43. 44. 44.] 44 44.1 reading: [44. 45. 45.] 45 45.1 reading: [45. 46. 46.] 46 46.1 reading: [46. 47. 47.] 47 47.1 reading: [47. 48. 48.] 48 48.1 reading: [48. 49. 49.] 49 49.1 reading: [49. 50. 50.] 50 50.1 reading: [50. 51. 51.] 51 51.1 reading: [51. 52. 52.] 52 52.1 reading: [52. 53. 53.] 53 53.1 reading: [53. 54. 54.] 54 54.1 reading: [54. 55. 55.] 55 55.1 reading: [55. 56. 56.] 56 56.1 reading: [56. 57. 57.] 57 57.1 reading: [57. 58. 58.] 58 58.1 reading: [58. 59. 59.] 59 59.1 reading: [59. 60. 60.] 60 60.1 reading: [60. 61. 61.] 61 61.1 reading: [61. 62. 62.] 62 62.1 reading: [62. 63. 63.] 63 63.1 reading: [63. 64. 64.] 64 64.1 reading: [64. 65. 65.] 65 65.1 reading: [65. 66. 66.] 66 66.1 reading: [66. 67. 67.] 67 67.1 reading: [67. 68. 68.] 68 68.1 reading: [68. 69. 69.] 69 69.1 reading: [69. 70. 70.] 70 70.1 reading: [70. 71. 71.] 71 71.1 reading: [71. 72. 72.] 72 72.1 reading: [72. 73. 73.] 73 73.1 reading: [73. 74. 74.] 74 74.1 reading: [74. 75. 75.] 75 75.1 reading: [75. 76. 76.] 76 76.1 reading: [76. 77. 77.] 77 77.1 reading: [77. 78. 78.] 78 78.1 reading: [78. 79. 79.] 79 79.1 reading: [79. 80. 80.] 80 80.1 reading: [80. 81. 81.] 81 81.1 reading: [81. 82. 82.] 82 82.1 reading: [82. 83. 83.] 83 83.1 reading: [83. 84. 84.] 84 84.1 reading: [84. 85. 85.] 85 85.1 reading: [85. 86. 86.] 86 86.1 reading: [86. 87. 87.] 87 87.1 reading: [87. 88. 88.] 88 88.1 reading: [88. 89. 89.] 89 89.1 reading: [89. 90. 90.] 90 90.1 reading: [90. 91. 91.] 91 91.1 reading: [91. 92. 92.] 92 92.1 reading: [92. 93. 93.] 93 93.1 reading: [93. 94. 94.] 94 94.1 reading: [94. 95. 95.] 95 95.1 reading: [95. 96. 96.] 96 96.1 reading: [96. 97. 97.] 97 97.1 reading: [97. 98. 98.] 98 98.1 reading: [98. 99. 99.] 99 99.1 reading: [ 99. 100. 100.] stack[2]: [(200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] stack[3]: [(300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] 11 11.1 reading: [11. 11.5 11.5] 12 12.1 reading: [12. 12.5 12.5] 13 13.1 reading: [13. 13.5 13.5] 14 14.1 reading: [14. 14.5 14.5] 15 15.1 reading: [15. 15.5 15.5] 16 16.1 reading: [16. 16.5 16.5] 17 17.1 reading: [17. 17.5 17.5] 18 18.1 reading: [18. 18.5 18.5] 19 19.1 reading: [19. 19.5 19.5] 20 20.1 reading: [20. 20.5 20.5] 21 21.1 reading: [21. 21.5 21.5] 22 22.1 reading: [22. 22.5 22.5] 23 23.1 reading: [23. 23.5 23.5] 24 24.1 reading: [24. 24.5 24.5] 25 25.1 reading: [25. 25.5 25.5] 26 26.1 reading: [26. 26.5 26.5] 27 27.1 reading: [27. 27.5 27.5] 28 28.1 reading: [28. 28.5 28.5] 29 29.1 reading: [29. 29.5 29.5] 30 30.1 reading: [30. 30.5 30.5] 31 31.1 reading: [31. 31.5 31.5] 32 32.1 reading: [32. 32.5 32.5] 33 33.1 reading: [33. 33.5 33.5] 34 34.1 reading: [34. 34.5 34.5] 35 35.1 reading: [35. 35.5 35.5] 36 36.1 reading: [36. 36.5 36.5] 37 37.1 reading: [37. 37.5 37.5] 38 38.1 reading: [38. 38.5 38.5] 39 39.1 reading: [39. 39.5 39.5] 40 40.1 reading: [40. 40.5 40.5] 41 41.1 reading: [41. 41.5 41.5] 42 42.1 reading: [42. 42.5 42.5] 43 43.1 reading: [43. 43.5 43.5] 44 44.1 reading: [44. 44.5 44.5] 45 45.1 reading: [45. 45.5 45.5] 46 46.1 reading: [46. 46.5 46.5] 47 47.1 reading: [47. 47.5 47.5] 48 48.1 reading: [48. 48.5 48.5] 49 49.1 reading: [49. 49.5 49.5] 50 50.1 reading: [50. 50.5 50.5] 51 51.1 reading: [51. 51.5 51.5] 52 52.1 reading: [52. 52.5 52.5] 53 53.1 reading: [53. 53.5 53.5] 54 54.1 reading: [54. 54.5 54.5] 55 55.1 reading: [55. 55.5 55.5] 56 56.1 reading: [56. 56.5 56.5] 57 57.1 reading: [57. 57.5 57.5] 58 58.1 reading: [58. 58.5 58.5] 59 59.1 reading: [59. 59.5 59.5] 60 60.1 reading: [60. 60.5 60.5] 61 61.1 reading: [61. 61.5 61.5] 62 62.1 reading: [62. 62.5 62.5] 63 63.1 reading: [63. 63.5 63.5] 64 64.1 reading: [64. 64.5 64.5] 65 65.1 reading: [65. 65.5 65.5] 66 66.1 reading: [66. 66.5 66.5] 67 67.1 reading: [67. 67.5 67.5] 68 68.1 reading: [68. 68.5 68.5] 69 69.1 reading: [69. 69.5 69.5] 70 70.1 reading: [70. 70.5 70.5] 71 71.1 reading: [71. 71.5 71.5] 72 72.1 reading: [72. 72.5 72.5] 73 73.1 reading: [73. 73.5 73.5] 74 74.1 reading: [74. 74.5 74.5] 75 75.1 reading: [75. 75.5 75.5] 76 76.1 reading: [76. 76.5 76.5] 77 77.1 reading: [77. 77.5 77.5] 78 78.1 reading: [78. 78.5 78.5] 79 79.1 reading: [79. 79.5 79.5] 80 80.1 reading: [80. 80.5 80.5] 81 81.1 reading: [81. 81.5 81.5] 82 82.1 reading: [82. 82.5 82.5] 83 83.1 reading: [83. 83.5 83.5] 84 84.1 reading: [84. 84.5 84.5] 85 85.1 reading: [85. 85.5 85.5] 86 86.1 reading: [86. 86.5 86.5] 87 87.1 reading: [87. 87.5 87.5] 88 88.1 reading: [88. 88.5 88.5] 89 89.1 reading: [89. 89.5 89.5] 90 90.1 reading: [90. 90.5 90.5] 91 91.1 reading: [91. 91.5 91.5] 92 92.1 reading: [92. 92.5 92.5] 93 93.1 reading: [93. 93.5 93.5] 94 94.1 reading: [94. 94.5 94.5] 95 95.1 reading: [95. 95.5 95.5] 96 96.1 reading: [96. 96.5 96.5] 97 97.1 reading: [97. 97.5 97.5] 98 98.1 reading: [98. 98.5 98.5] 99 99.1 reading: [99. 99.5 99.5] 100 100.1 reading: [100. 100.5 100.5]

Passed

tests/test_transforms.py::test_transform

0.04

Passed

tests/test_stepsampling.py::test_crop_bracket

0.00

Passed

tests/test_store.py::test_text_store

0.00

Passed

tests/test_stepsampling.py::test_stepsampler_regionslice

8.32

Passed

tests/test_samplingpath.py::test_samplingpath

0.00

[gw5] linux -- Python 3.10.6 /usr/bin/python3
[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_samplingpath.py::test_samplingpath_cubereflect

0.00

[gw5] linux -- Python 3.10.6 /usr/bin/python3
[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_samplingpath.py::test_samplingpath_oddcase

0.00

[gw5] linux -- Python 3.10.6 /usr/bin/python3
[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3[gw5] linux -- Python 3.10.6 /usr/bin/python3

Passed

tests/test_stepsampling.py::test_stepsampler_regionmh

9.61

[gw1] linux -- Python 3.10.6 /usr/bin/python3
[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3[gw1] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.13) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-inf(0.00%) | Like=-28.44..-0.20 [-28.4416..-8.9505] | it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.17216). shrinking... ineffective proposal scale (1.08266). shrinking... ineffective proposal scale (1.26906). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.74364). shrinking... ineffective proposal scale (1.61051). shrinking... ineffective proposal scale (1.62335). shrinking... ineffective proposal scale (1.64935). shrinking... ineffective proposal scale (1.52341). shrinking... ineffective proposal scale (1.29966). shrinking... ineffective proposal scale (1.29966). shrinking... ineffective proposal scale (1.84333). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.57259). shrinking... ineffective proposal scale (1.99571). shrinking... ineffective proposal scale (1.84333). shrinking... ineffective proposal scale (1.70259). shrinking... Z=-25.5(0.00%) | Like=-21.46..-0.20 [-28.4416..-8.9505] | it/evals=36/844 eff=8.1081% N=400 ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.85803). shrinking... ineffective proposal scale (1.87285). shrinking... ineffective proposal scale (1.72985). shrinking... ineffective proposal scale (1.59777). shrinking... ineffective proposal scale (1.47577). shrinking... ineffective proposal scale (1.3631). shrinking... ineffective proposal scale (1.25902). shrinking... ineffective proposal scale (1.17216). shrinking... Z=-24.0(0.00%) | Like=-20.02..-0.20 [-28.4416..-8.9505] | it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (1.53556). shrinking... ineffective proposal scale (1.44103). shrinking... ineffective proposal scale (1.57259). shrinking... ineffective proposal scale (1.58513). shrinking... ineffective proposal scale (1.35231). shrinking... ineffective proposal scale (1.61051). shrinking... ineffective proposal scale (1.62335). shrinking... ineffective proposal scale (1.4994). shrinking... ineffective proposal scale (1.77156). shrinking... ineffective proposal scale (1.78569). shrinking... ineffective proposal scale (1.82875). shrinking... ineffective proposal scale (1.70259). shrinking... ineffective proposal scale (1.71616). shrinking... ineffective proposal scale (1.59777). shrinking... ineffective proposal scale (1.27918). shrinking... Mono-modal Volume: ~exp(-4.53) * Expected Volume: exp(-0.23) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.2(0.00%) | Like=-16.40..-0.20 [-28.4416..-8.9505] | it/evals=90/1492 eff=8.2418% N=400 ineffective proposal scale (1.41832). shrinking... Z=-19.5(0.00%) | Like=-15.84..-0.20 [-28.4416..-8.9505] | it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (1.22937). shrinking... ineffective proposal scale (0.923647). shrinking... Z=-17.0(0.00%) | Like=-13.62..-0.20 [-28.4416..-8.9505] | it/evals=141/2104 eff=8.2746% N=400 ineffective proposal scale (0.880663). shrinking... Z=-16.5(0.00%) | Like=-12.89..-0.20 [-28.4416..-8.9505] | it/evals=150/2212 eff=8.2781% N=400 ineffective proposal scale (0.819908). shrinking... ineffective proposal scale (0.448344). shrinking... Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.45) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-14.7(0.00%) | Like=-11.19..-0.20 [-28.4416..-8.9505] | it/evals=180/2572 eff=8.2873% N=400 Z=-13.8(0.00%) | Like=-10.66..-0.20 [-28.4416..-8.9505] | it/evals=200/2812 eff=8.2919% N=400 Z=-12.6(0.01%) | Like=-9.61..-0.20 [-28.4416..-8.9505] | it/evals=242/3316 eff=8.2990% N=400 Z=-12.4(0.01%) | Like=-9.44..-0.20 [-28.4416..-8.9505] | it/evals=250/3412 eff=8.3001% N=400 Mono-modal Volume: ~exp(-4.53) Expected Volume: exp(-0.67) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.000|************************************************** | +1.000 param2: +0.000|***************************************************| +1.000 Z=-11.6(0.03%) | Like=-8.73..-0.20 [-8.9485..-4.8498] | it/evals=282/3797 eff=8.3014% N=400 Z=-11.2(0.04%) | Like=-8.20..-0.20 [-8.9485..-4.8498] | it/evals=300/4013 eff=8.3033% N=400 Z=-10.2(0.12%) | Like=-7.29..-0.17 [-8.9485..-4.8498] | it/evals=344/4542 eff=8.3052% N=400 Z=-10.1(0.14%) | Like=-7.23..-0.17 [-8.9485..-4.8498] | it/evals=350/4614 eff=8.3056% N=400 Mono-modal Volume: ~exp(-4.70) * Expected Volume: exp(-0.90) Quality: ok param0: +0.00|************************************************ **| +1.00 param1: +0.000|************************************************** | +1.000 param2: +0.000|***************************************************| +1.000 Z=-9.9(0.16%) | Like=-7.11..-0.17 [-8.9485..-4.8498] | it/evals=360/4734 eff=8.3064% N=400 Z=-9.3(0.29%) | Like=-6.72..-0.17 [-8.9485..-4.8498] | it/evals=400/5214 eff=8.3091% N=400 Z=-8.7(0.54%) | Like=-6.06..-0.17 [-8.9485..-4.8498] | it/evals=449/5802 eff=8.3117% N=400 Mono-modal Volume: ~exp(-5.10) * Expected Volume: exp(-1.12) Quality: ok param0: +0.000|************************************************** | +1.000 param1: +0.000|************************************************** | +1.000 param2: +0.000|************************************************* | +1.000 Z=-8.7(0.55%) | Like=-6.05..-0.17 [-8.9485..-4.8498] | it/evals=450/5814 eff=8.3118% N=400 Z=-8.2(0.92%) | Like=-5.44..-0.10 [-8.9485..-4.8498] | it/evals=498/6390 eff=8.3139% N=400 Z=-8.1(0.95%) | Like=-5.43..-0.10 [-8.9485..-4.8498] | it/evals=500/6414 eff=8.3139% N=400 Mono-modal Volume: ~exp(-5.49) * Expected Volume: exp(-1.35) Quality: ok param0: +0.000|********************************************* **** | +1.000 param1: +0.000|************************************************** | +1.000 param2: +0.000|************************************************* | +1.000 Z=-7.7(1.45%) | Like=-4.92..-0.10 [-8.9485..-4.8498] | it/evals=540/6894 eff=8.3154% N=400 Z=-7.6(1.61%) | Like=-4.85..-0.10 [-4.8456..-3.4991] | it/evals=550/7014 eff=8.3157% N=400 Z=-7.1(2.65%) | Like=-4.40..-0.10 [-4.8456..-3.4991] | it/evals=600/7614 eff=8.3172% N=400 Mono-modal Volume: ~exp(-5.49) Expected Volume: exp(-1.57) Quality: ok param0: +0.00| ******************************************** **** | +1.00 param1: +0.00| *********************************************** * | +1.00 param2: +0.00| *********************************************** | +1.00 Z=-6.8(3.83%) | Like=-4.13..-0.10 [-4.8456..-3.4991] | it/evals=644/8142 eff=8.3183% N=400 Z=-6.8(3.98%) | Like=-4.11..-0.10 [-4.8456..-3.4991] | it/evals=650/8214 eff=8.3184% N=400 Z=-6.4(5.33%) | Like=-3.80..-0.08 [-4.8456..-3.4991] | it/evals=700/8814 eff=8.3195% N=400 Mono-modal Volume: ~exp(-5.51) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00| ********************************************** | +1.00 param1: +0.00| ********************************************* | +1.00 param2: +0.00| *********************************************** | +1.00 Z=-6.3(6.08%) | Like=-3.63..-0.08 [-4.8456..-3.4991] | it/evals=720/9054 eff=8.3199% N=400 Z=-6.1(7.27%) | Like=-3.45..-0.08 [-3.4967..-3.1168] | it/evals=750/9414 eff=8.3204% N=400 Z=-5.9(9.45%) | Like=-3.22..-0.02 [-3.4967..-3.1168] | it/evals=800/10015 eff=8.3203% N=400 Mono-modal Volume: ~exp(-5.89) * Expected Volume: exp(-2.02) Quality: ok param0: +0.00| ********************************************* | +1.00 param1: +0.00| ********************************************* | +1.00 param2: +0.00| ********************************************* | +1.00 Z=-5.8(9.89%) | Like=-3.15..-0.02 [-3.4967..-3.1168] | it/evals=810/10135 eff=8.3205% N=400 Z=-5.6(11.78%) | Like=-2.99..-0.02 [-3.1085..-2.9617] | it/evals=850/10615 eff=8.3211% N=400 Mono-modal Volume: ~exp(-6.00) * Expected Volume: exp(-2.25) Quality: ok positive degeneracy between param2 and param1: rho=0.75 param0: +0.00| ****************************************** | +1.00 param1: +0.00| ******************************************* | +1.00 param2: +0.00| ******************************************* | +1.00 Z=-5.4(14.48%) | Like=-2.74..-0.02 [-2.7355..-2.7280]*| it/evals=900/11215 eff=8.3218% N=400 Z=-5.3(17.63%) | Like=-2.50..-0.02 [-2.4997..-2.4984]*| it/evals=950/11815 eff=8.3224% N=400 Have 2 modes Volume: ~exp(-6.24) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00| 11111111111111111111 222222222222222222222 | +1.00 param1: +0.00| 1111111111111111111112222222222222222222222 | +1.00 param2: +0.00| 111111111111111111111222222222222222222222 | +1.00 Z=-5.1(20.12%) | Like=-2.36..-0.02 [-2.3603..-2.3592]*| it/evals=990/12295 eff=8.3228% N=400 Z=-5.1(20.62%) | Like=-2.33..-0.02 [-2.3273..-2.3250]*| it/evals=1000/12415 eff=8.3229% N=400 Z=-4.9(23.80%) | Like=-2.15..-0.02 [-2.1541..-2.1518]*| it/evals=1050/13015 eff=8.3234% N=400 Have 2 modes Volume: ~exp(-6.64) * Expected Volume: exp(-2.70) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 1111111111111111111 222222222222222222222 | +1.0 param1: +0.0| 11111111111111111111222222222222222222222 | +1.0 param2: +0.0| 11111111111111111111 2222222222222222222 | +1.0 Z=-4.8(25.85%) | Like=-2.07..-0.02 [-2.0652..-2.0598]*| it/evals=1080/13375 eff=8.3237% N=400 Z=-4.8(27.24%) | Like=-1.98..-0.02 [-1.9844..-1.9809]*| it/evals=1100/13615 eff=8.3239% N=400 Z=-4.7(30.95%) | Like=-1.83..-0.02 [-1.8261..-1.8197]*| it/evals=1150/14216 eff=8.3237% N=400 Have 2 modes Volume: ~exp(-6.64) Expected Volume: exp(-2.92) Quality: ok param0: +0.0| 1111111111111111110 22222222222222222222 | +1.0 param1: +0.0| 11111111111111111111 22222222222222222222 | +1.0 param2: +0.0| 1111111111111111111 2222222222222222222 | +1.0 Z=-4.6(33.67%) | Like=-1.72..-0.02 [-1.7225..-1.7194]*| it/evals=1194/14745 eff=8.3235% N=400 Z=-4.6(34.10%) | Like=-1.71..-0.02 [-1.7055..-1.7016]*| it/evals=1200/14817 eff=8.3235% N=400 Z=-4.4(38.12%) | Like=-1.56..-0.02 [-1.5623..-1.5579]*| it/evals=1250/15418 eff=8.3233% N=400 Have 2 modes Volume: ~exp(-7.07) * Expected Volume: exp(-3.15) Quality: ok param0: +0.0| 111111111111111111 222222222222222222 | +1.0 param1: +0.0| 111111111111111111 222222222222222222 | +1.0 param2: +0.0| 111111111111111111 222222222222222222 | +1.0 Z=-4.4(38.86%) | Like=-1.54..-0.02 [-1.5369..-1.5335]*| it/evals=1260/15538 eff=8.3234% N=400 Z=-4.4(41.57%) | Like=-1.45..-0.02 [-1.4458..-1.4450]*| it/evals=1300/16018 eff=8.3237% N=400 Z=-4.3(45.13%) | Like=-1.32..-0.02 [-1.3215..-1.3211]*| it/evals=1349/16606 eff=8.3241% N=400 Have 2 modes Volume: ~exp(-7.39) * Expected Volume: exp(-3.37) Quality: ok param0: +0.0| 11111111111111111 222222222222222 | +1.0 param1: +0.0| 1111111111111111 2222222222222222 | +1.0 param2: +0.0| 1111111111111111 222222222222222 | +1.0 Z=-4.3(45.20%) | Like=-1.32..-0.02 [-1.3211..-1.3210]*| it/evals=1350/16618 eff=8.3241% N=400 Z=-4.2(48.86%) | Like=-1.24..-0.02 [-1.2432..-1.2362]*| it/evals=1399/17206 eff=8.3244% N=400 Z=-4.2(48.91%) | Like=-1.24..-0.02 [-1.2362..-1.2340]*| it/evals=1400/17218 eff=8.3244% N=400 Have 2 modes Volume: ~exp(-7.39) Expected Volume: exp(-3.60) Quality: ok param0: +0.0| 1111111111111111 222222222222222 | +1.0 param1: +0.0| 111111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 22222222222222 | +1.0 Z=-4.1(51.81%) | Like=-1.14..-0.01 [-1.1366..-1.1351]*| it/evals=1440/17698 eff=8.3247% N=400 Z=-4.1(52.50%) | Like=-1.13..-0.01 [-1.1261..-1.1256]*| it/evals=1450/17818 eff=8.3247% N=400 Z=-4.1(55.27%) | Like=-1.05..-0.01 [-1.0456..-1.0449]*| it/evals=1494/18347 eff=8.3245% N=400 Z=-4.1(55.74%) | Like=-1.04..-0.01 [-1.0390..-1.0388]*| it/evals=1500/18419 eff=8.3245% N=400 Have 2 modes Volume: ~exp(-7.84) * Expected Volume: exp(-3.82) Quality: ok param0: +0.0| 111111111111111 222222222222222 | +1.0 param1: +0.0| 11111111111111 22222222222222 | +1.0 param2: +0.0| 11111111111111 22222222222222 | +1.0 Z=-4.0(57.85%) | Like=-0.99..-0.01 [-0.9895..-0.9878]*| it/evals=1530/18779 eff=8.3247% N=400 Z=-4.0(59.20%) | Like=-0.96..-0.01 [-0.9563..-0.9558]*| it/evals=1550/19019 eff=8.3248% N=400 Z=-4.0(62.05%) | Like=-0.87..-0.01 [-0.8714..-0.8694]*| it/evals=1596/19571 eff=8.3251% N=400 Z=-3.9(62.31%) | Like=-0.86..-0.01 [-0.8642..-0.8608]*| it/evals=1600/19619 eff=8.3251% N=400 Have 2 modes Volume: ~exp(-8.48) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0| 11111111111111 22222222222222 | +1.0 param1: +0.0| 111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-3.9(63.51%) | Like=-0.83..-0.01 [-0.8293..-0.8276]*| it/evals=1620/19859 eff=8.3252% N=400 Z=-3.9(65.45%) | Like=-0.79..-0.01 [-0.7910..-0.7892]*| it/evals=1650/20219 eff=8.3253% N=400 Z=-3.9(68.48%) | Like=-0.72..-0.01 [-0.7167..-0.7149]*| it/evals=1700/20819 eff=8.3256% N=400 Have 2 modes Volume: ~exp(-8.48) Expected Volume: exp(-4.27) Quality: ok param0: +0.0| 111111111111 222222222222 | +1.0 param1: +0.0| 111111111111 22222222222 +0.8 | +1.0 param2: +0.0| 111111111111 022222222222 +0.8 | +1.0 Z=-3.8(70.10%) | Like=-0.68..-0.01 [-0.6804..-0.6798]*| it/evals=1728/21155 eff=8.3257% N=400 Z=-3.8(71.29%) | Like=-0.65..-0.01 [-0.6492..-0.6481]*| it/evals=1750/21419 eff=8.3258% N=400 Have 2 modes Volume: ~exp(-8.68) * Expected Volume: exp(-4.50) Quality: ok param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.8(73.94%) | Like=-0.59..-0.01 [-0.5916..-0.5905]*| it/evals=1800/22019 eff=8.3260% N=400 Z=-3.8(75.92%) | Like=-0.55..-0.01 [-0.5516..-0.5513]*| it/evals=1840/22499 eff=8.3262% N=400 Z=-3.8(76.41%) | Like=-0.54..-0.01 [-0.5416..-0.5414]*| it/evals=1850/22619 eff=8.3262% N=400 Have 2 modes Volume: ~exp(-8.80) * Expected Volume: exp(-4.73) Quality: ok param0: +0.0| 1111111111 22222222222 +0.8 | +1.0 param1: +0.0| 1111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.7(78.20%) | Like=-0.50..-0.01 [-0.5016..-0.4995]*| it/evals=1890/23099 eff=8.3264% N=400 Z=-3.7(78.64%) | Like=-0.49..-0.01 [-0.4937..-0.4928]*| it/evals=1900/23219 eff=8.3264% N=400 Z=-3.7(80.50%) | Like=-0.45..-0.01 [-0.4494..-0.4489]*| it/evals=1944/23747 eff=8.3266% N=400 Z=-3.7(80.74%) | Like=-0.44..-0.01 [-0.4427..-0.4397]*| it/evals=1950/23819 eff=8.3266% N=400 Have 2 modes Volume: ~exp(-9.34) * Expected Volume: exp(-4.95) Quality: ok param0: +0.0| 1111111111 2222222222 +0.8 | +1.0 param1: +0.0| 1111111111 222222222 +0.8 | +1.0 param2: +0.0| 1111111111 222222222 +0.8 | +1.0 Z=-3.7(81.89%) | Like=-0.42..-0.01 [-0.4196..-0.4193]*| it/evals=1980/24179 eff=8.3267% N=400 Z=-3.7(82.61%) | Like=-0.41..-0.01 [-0.4054..-0.4050]*| it/evals=2000/24419 eff=8.3267% N=400 Z=-3.7(84.09%) | Like=-0.38..-0.01 [-0.3774..-0.3735]*| it/evals=2042/24923 eff=8.3269% N=400 Z=-3.7(84.36%) | Like=-0.37..-0.01 [-0.3673..-0.3672]*| it/evals=2050/25019 eff=8.3269% N=400 Have 2 modes Volume: ~exp(-9.77) * Expected Volume: exp(-5.18) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.6(85.01%) | Like=-0.35..-0.01 [-0.3542..-0.3535]*| it/evals=2070/25259 eff=8.3270% N=400 Z=-3.6(85.96%) | Like=-0.34..-0.01 [-0.3374..-0.3365]*| it/evals=2100/25619 eff=8.3271% N=400 Z=-3.6(87.42%) | Like=-0.31..-0.01 [-0.3103..-0.3103]*| it/evals=2150/26219 eff=8.3272% N=400 Have 2 modes Volume: ~exp(-9.77) Expected Volume: exp(-5.40) Quality: ok param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 111111110 22222222 +0.8 | +1.0 param2: +0.0| +0.2 111111110 022222220 +0.8 | +1.0 Z=-3.6(88.20%) | Like=-0.29..-0.01 [-0.2948..-0.2947]*| it/evals=2179/26567 eff=8.3273% N=400 Z=-3.6(88.75%) | Like=-0.29..-0.01 [-0.2857..-0.2855]*| it/evals=2200/26819 eff=8.3273% N=400 Have 2 modes Volume: ~exp(-10.02) * Expected Volume: exp(-5.63) Quality: ok param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(89.93%) | Like=-0.26..-0.01 [-0.2637..-0.2637]*| it/evals=2250/27419 eff=8.3275% N=400 Z=-3.6(91.01%) | Like=-0.24..-0.01 [-0.2396..-0.2388]*| it/evals=2300/28019 eff=8.3276% N=400 Have 2 modes Volume: ~exp(-10.24) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(91.79%) | Like=-0.22..-0.01 [-0.2243..-0.2243]*| it/evals=2340/28499 eff=8.3277% N=400 Z=-3.6(91.98%) | Like=-0.22..-0.01 [-0.2186..-0.2184]*| it/evals=2350/28619 eff=8.3277% N=400 Z=-3.6(92.74%) | Like=-0.21..-0.01 [-0.2057..-0.2049]*| it/evals=2393/29135 eff=8.3278% N=400 Z=-3.6(92.85%) | Like=-0.20..-0.01 [-0.2033..-0.2033]*| it/evals=2400/29219 eff=8.3278% N=400 Have 2 modes Volume: ~exp(-10.33) * Expected Volume: exp(-6.08) Quality: ok param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(93.33%) | Like=-0.19..-0.01 [-0.1920..-0.1919]*| it/evals=2430/29579 eff=8.3279% N=400 Z=-3.5(93.64%) | Like=-0.18..-0.01 [-0.1837..-0.1836]*| it/evals=2450/29819 eff=8.3280% N=400 Z=-3.5(94.26%) | Like=-0.17..-0.01 [-0.1734..-0.1731]*| it/evals=2494/30347 eff=8.3280% N=400 Z=-3.5(94.34%) | Like=-0.17..-0.01 [-0.1726..-0.1722]*| it/evals=2500/30419 eff=8.3281% N=400 Have 2 modes Volume: ~exp(-10.75) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0| +0.3 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 Z=-3.5(94.60%) | Like=-0.17..-0.01 [-0.1685..-0.1685]*| it/evals=2520/30659 eff=8.3281% N=400 Z=-3.5(94.97%) | Like=-0.16..-0.00 [-0.1610..-0.1610]*| it/evals=2550/31019 eff=8.3282% N=400 Z=-3.5(95.45%) | Like=-0.15..-0.00 [-0.1481..-0.1480]*| it/evals=2593/31535 eff=8.3282% N=400 Z=-3.5(95.53%) | Like=-0.15..-0.00 [-0.1465..-0.1465]*| it/evals=2600/31619 eff=8.3283% N=400 Have 2 modes Volume: ~exp(-10.75) Expected Volume: exp(-6.53) Quality: ok param0: +0.0| +0.3 1111111 222222 +0.8 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 111111 222222 +0.7 | +1.0 Z=-3.5(95.80%) | Like=-0.14..-0.00 [-0.1411..-0.1409]*| it/evals=2627/31943 eff=8.3283% N=400 Z=-3.5(96.02%) | Like=-0.14..-0.00 [-0.1352..-0.1352]*| it/evals=2650/32219 eff=8.3284% N=400 Z=-3.5(96.46%) | Like=-0.12..-0.00 [-0.1243..-0.1239]*| it/evals=2699/32807 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.05) * Expected Volume: exp(-6.75) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 111111 22222 +0.7 | +1.0 param2: +0.0| +0.3 111111 222222 +0.7 | +1.0 Z=-3.5(96.47%) | Like=-0.12..-0.00 [-0.1239..-0.1239]*| it/evals=2700/32819 eff=8.3284% N=400 Z=-3.5(96.85%) | Like=-0.12..-0.00 [-0.1161..-0.1160]*| it/evals=2749/33408 eff=8.3283% N=400 Z=-3.5(96.86%) | Like=-0.12..-0.00 [-0.1160..-0.1157]*| it/evals=2750/33420 eff=8.3283% N=400 Z=-3.5(97.13%) | Like=-0.11..-0.00 [-0.1111..-0.1110]*| it/evals=2788/33876 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.22) * Expected Volume: exp(-6.98) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.15%) | Like=-0.11..-0.00 [-0.1109..-0.1106]*| it/evals=2790/33900 eff=8.3284% N=400 Z=-3.5(97.21%) | Like=-0.11..-0.00 [-0.1090..-0.1089]*| it/evals=2800/34020 eff=8.3284% N=400 Z=-3.5(97.49%) | Like=-0.10..-0.00 [-0.1003..-0.1001]*| it/evals=2843/34537 eff=8.3282% N=400 Z=-3.5(97.53%) | Like=-0.10..-0.00 [-0.0989..-0.0985]*| it/evals=2850/34621 eff=8.3282% N=400 Have 2 modes Volume: ~exp(-11.71) * Expected Volume: exp(-7.20) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.70%) | Like=-0.09..-0.00 [-0.0918..-0.0918]*| it/evals=2880/34981 eff=8.3283% N=400 Z=-3.5(97.81%) | Like=-0.09..-0.00 [-0.0889..-0.0885]*| it/evals=2900/35221 eff=8.3283% N=400 Z=-3.5(98.03%) | Like=-0.08..-0.00 [-0.0821..-0.0819]*| it/evals=2944/35749 eff=8.3284% N=400 Z=-3.5(98.06%) | Like=-0.08..-0.00 [-0.0809..-0.0806]*| it/evals=2950/35821 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-11.71) Expected Volume: exp(-7.43) Quality: ok param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.21%) | Like=-0.08..-0.00 [-0.0780..-0.0780]*| it/evals=2983/36217 eff=8.3284% N=400 Z=-3.5(98.28%) | Like=-0.08..-0.00 [-0.0757..-0.0757]*| it/evals=3000/36421 eff=8.3285% N=400 Z=-3.5(98.47%) | Like=-0.07..-0.00 [-0.0695..-0.0692]*| it/evals=3050/37021 eff=8.3286% N=400 Have 2 modes Volume: ~exp(-12.23) * Expected Volume: exp(-7.65) Quality: ok param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.51%) | Like=-0.07..-0.00 [-0.0684..-0.0682]*| it/evals=3060/37141 eff=8.3286% N=400 Z=-3.5(98.65%) | Like=-0.06..-0.00 [-0.0642..-0.0640]*| it/evals=3100/37622 eff=8.3284% N=400 Have 2 modes Volume: ~exp(-12.23) Expected Volume: exp(-7.88) Quality: ok positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 2222 +0.7 | +1.0 param2: +0.0| +0.3 11111 2222 +0.7 | +1.0 Z=-3.5(98.80%) | Like=-0.06..-0.00 [-0.0584..-0.0584]*| it/evals=3150/38222 eff=8.3285% N=400 Z=-3.5(98.92%) | Like=-0.05..-0.00 [-0.0531..-0.0529]*| it/evals=3191/38714 eff=8.3285% N=400 Z=-3.5(98.94%) | Like=-0.05..-0.00 [-0.0523..-0.0522]*| it/evals=3200/38822 eff=8.3286% N=400 [ultranest] Explored until L=-0.001 [ultranest] Likelihood function evaluations: 39099 [ultranest] logZ = -3.483 +- 0.05779 [ultranest] Effective samples strategy satisfied (ESS = 1904.7, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.04 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.483 +- 0.142 single instance: logZ = -3.483 +- 0.071 bootstrapped : logZ = -3.483 +- 0.142 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▂▂▄▄▆▆▆▇▇▆▆▄▃▃▂▂▃▃▃▅▅▅▅▅▅▄▄▃▂▁▁▁▁▁▁│1.00 0.46 +- 0.22 param1 : 0.00 │▁▁▁▁▁▂▃▄▅▆▅▇▇▆▅▄▄▃▂▂▂▂▃▃▃▅▅▅▅▄▃▃▃▂▁▁▁▁▁│1.00 0.48 +- 0.22 param2 : 0.00 │▁▁▁▁▂▂▃▄▄▅▇▇▇▆▄▄▃▃▂▂▂▂▃▃▄▅▆▅▅▅▄▃▂▂▁▁▁▁ │1.00 0.47 +- 0.22
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=412, regioncalls=0, ndraw=128, logz=-inf, remainder_fraction=100.0000%, Lmin=-28.44, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=36, ncalls=844, regioncalls=0, ndraw=128, logz=-25.48, remainder_fraction=100.0000%, Lmin=-21.46, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=1012, regioncalls=0, ndraw=128, logz=-23.99, remainder_fraction=100.0000%, Lmin=-20.02, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=1492, regioncalls=0, ndraw=128, logz=-20.23, remainder_fraction=100.0000%, Lmin=-16.40, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=1612, regioncalls=0, ndraw=128, logz=-19.46, remainder_fraction=100.0000%, Lmin=-15.84, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=141, ncalls=2104, regioncalls=0, ndraw=128, logz=-16.95, remainder_fraction=99.9999%, Lmin=-13.62, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=2212, regioncalls=0, ndraw=128, logz=-16.51, remainder_fraction=99.9998%, Lmin=-12.89, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=2572, regioncalls=0, ndraw=128, logz=-14.74, remainder_fraction=99.9987%, Lmin=-11.19, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=2812, regioncalls=0, ndraw=128, logz=-13.79, remainder_fraction=99.9966%, Lmin=-10.66, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=242, ncalls=3316, regioncalls=0, ndraw=128, logz=-12.58, remainder_fraction=99.9887%, Lmin=-9.61, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=3412, regioncalls=0, ndraw=128, logz=-12.38, remainder_fraction=99.9868%, Lmin=-9.44, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=282, ncalls=3797, regioncalls=0, ndraw=128, logz=-11.63, remainder_fraction=99.9729%, Lmin=-8.73, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=4013, regioncalls=0, ndraw=128, logz=-11.21, remainder_fraction=99.9579%, Lmin=-8.20, Lmax=-0.20 DEBUG ultranest:integrator.py:2610 iteration=344, ncalls=4542, regioncalls=0, ndraw=128, logz=-10.20, remainder_fraction=99.8792%, Lmin=-7.29, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=4614, regioncalls=0, ndraw=128, logz=-10.08, remainder_fraction=99.8644%, Lmin=-7.23, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=4734, regioncalls=0, ndraw=128, logz=-9.91, remainder_fraction=99.8406%, Lmin=-7.11, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=5214, regioncalls=0, ndraw=128, logz=-9.32, remainder_fraction=99.7137%, Lmin=-6.72, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=449, ncalls=5802, regioncalls=0, ndraw=128, logz=-8.71, remainder_fraction=99.4554%, Lmin=-6.06, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=5814, regioncalls=0, ndraw=128, logz=-8.70, remainder_fraction=99.4479%, Lmin=-6.05, Lmax=-0.17 DEBUG ultranest:integrator.py:2610 iteration=498, ncalls=6390, regioncalls=0, ndraw=128, logz=-8.15, remainder_fraction=99.0761%, Lmin=-5.44, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=6414, regioncalls=0, ndraw=128, logz=-8.13, remainder_fraction=99.0523%, Lmin=-5.43, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=6894, regioncalls=0, ndraw=128, logz=-7.70, remainder_fraction=98.5505%, Lmin=-4.92, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=7014, regioncalls=0, ndraw=128, logz=-7.60, remainder_fraction=98.3922%, Lmin=-4.85, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=7614, regioncalls=0, ndraw=128, logz=-7.14, remainder_fraction=97.3546%, Lmin=-4.40, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=644, ncalls=8142, regioncalls=0, ndraw=128, logz=-6.80, remainder_fraction=96.1680%, Lmin=-4.13, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=8214, regioncalls=0, ndraw=128, logz=-6.75, remainder_fraction=96.0229%, Lmin=-4.11, Lmax=-0.10 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=8814, regioncalls=0, ndraw=128, logz=-6.43, remainder_fraction=94.6659%, Lmin=-3.80, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=9054, regioncalls=0, ndraw=128, logz=-6.31, remainder_fraction=93.9151%, Lmin=-3.63, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=9414, regioncalls=0, ndraw=128, logz=-6.14, remainder_fraction=92.7343%, Lmin=-3.45, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=10015, regioncalls=0, ndraw=128, logz=-5.88, remainder_fraction=90.5501%, Lmin=-3.22, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=10135, regioncalls=0, ndraw=128, logz=-5.83, remainder_fraction=90.1072%, Lmin=-3.15, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=10615, regioncalls=0, ndraw=128, logz=-5.65, remainder_fraction=88.2198%, Lmin=-2.99, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=11215, regioncalls=0, ndraw=128, logz=-5.44, remainder_fraction=85.5171%, Lmin=-2.74, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=11815, regioncalls=0, ndraw=128, logz=-5.25, remainder_fraction=82.3721%, Lmin=-2.50, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=12295, regioncalls=0, ndraw=128, logz=-5.11, remainder_fraction=79.8787%, Lmin=-2.36, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=12415, regioncalls=0, ndraw=128, logz=-5.08, remainder_fraction=79.3756%, Lmin=-2.33, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=13015, regioncalls=0, ndraw=128, logz=-4.93, remainder_fraction=76.2016%, Lmin=-2.15, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=13375, regioncalls=0, ndraw=128, logz=-4.84, remainder_fraction=74.1510%, Lmin=-2.07, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=13615, regioncalls=0, ndraw=128, logz=-4.79, remainder_fraction=72.7610%, Lmin=-1.98, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=14216, regioncalls=0, ndraw=128, logz=-4.66, remainder_fraction=69.0467%, Lmin=-1.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1194, ncalls=14745, regioncalls=0, ndraw=128, logz=-4.56, remainder_fraction=66.3291%, Lmin=-1.72, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=14817, regioncalls=0, ndraw=128, logz=-4.55, remainder_fraction=65.8998%, Lmin=-1.71, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=15418, regioncalls=0, ndraw=128, logz=-4.45, remainder_fraction=61.8825%, Lmin=-1.56, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=15538, regioncalls=0, ndraw=128, logz=-4.43, remainder_fraction=61.1404%, Lmin=-1.54, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=16018, regioncalls=0, ndraw=128, logz=-4.35, remainder_fraction=58.4255%, Lmin=-1.45, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1349, ncalls=16606, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=54.8657%, Lmin=-1.32, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=16618, regioncalls=0, ndraw=128, logz=-4.27, remainder_fraction=54.8003%, Lmin=-1.32, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1399, ncalls=17206, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=51.1372%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=17218, regioncalls=0, ndraw=128, logz=-4.19, remainder_fraction=51.0867%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=17698, regioncalls=0, ndraw=128, logz=-4.14, remainder_fraction=48.1882%, Lmin=-1.14, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=17818, regioncalls=0, ndraw=128, logz=-4.12, remainder_fraction=47.4966%, Lmin=-1.13, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1494, ncalls=18347, regioncalls=0, ndraw=128, logz=-4.07, remainder_fraction=44.7280%, Lmin=-1.05, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=18419, regioncalls=0, ndraw=128, logz=-4.06, remainder_fraction=44.2614%, Lmin=-1.04, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=18779, regioncalls=0, ndraw=128, logz=-4.02, remainder_fraction=42.1465%, Lmin=-0.99, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=19019, regioncalls=0, ndraw=128, logz=-4.00, remainder_fraction=40.8023%, Lmin=-0.96, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1596, ncalls=19571, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=37.9504%, Lmin=-0.87, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=19619, regioncalls=0, ndraw=128, logz=-3.95, remainder_fraction=37.6924%, Lmin=-0.86, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=19859, regioncalls=0, ndraw=128, logz=-3.93, remainder_fraction=36.4899%, Lmin=-0.83, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=20219, regioncalls=0, ndraw=128, logz=-3.90, remainder_fraction=34.5530%, Lmin=-0.79, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=20819, regioncalls=0, ndraw=128, logz=-3.86, remainder_fraction=31.5163%, Lmin=-0.72, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1728, ncalls=21155, regioncalls=0, ndraw=128, logz=-3.84, remainder_fraction=29.8994%, Lmin=-0.68, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=21419, regioncalls=0, ndraw=128, logz=-3.82, remainder_fraction=28.7098%, Lmin=-0.65, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=22019, regioncalls=0, ndraw=128, logz=-3.78, remainder_fraction=26.0552%, Lmin=-0.59, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1840, ncalls=22499, regioncalls=0, ndraw=128, logz=-3.76, remainder_fraction=24.0787%, Lmin=-0.55, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=22619, regioncalls=0, ndraw=128, logz=-3.75, remainder_fraction=23.5926%, Lmin=-0.54, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=23099, regioncalls=0, ndraw=128, logz=-3.73, remainder_fraction=21.8028%, Lmin=-0.50, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=23219, regioncalls=0, ndraw=128, logz=-3.72, remainder_fraction=21.3594%, Lmin=-0.49, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1944, ncalls=23747, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=19.4957%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=23819, regioncalls=0, ndraw=128, logz=-3.70, remainder_fraction=19.2614%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=24179, regioncalls=0, ndraw=128, logz=-3.68, remainder_fraction=18.1081%, Lmin=-0.42, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=24419, regioncalls=0, ndraw=128, logz=-3.67, remainder_fraction=17.3866%, Lmin=-0.41, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2042, ncalls=24923, regioncalls=0, ndraw=128, logz=-3.66, remainder_fraction=15.9086%, Lmin=-0.38, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=25019, regioncalls=0, ndraw=128, logz=-3.65, remainder_fraction=15.6390%, Lmin=-0.37, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=25259, regioncalls=0, ndraw=128, logz=-3.64, remainder_fraction=14.9864%, Lmin=-0.35, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=25619, regioncalls=0, ndraw=128, logz=-3.63, remainder_fraction=14.0398%, Lmin=-0.34, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=26219, regioncalls=0, ndraw=128, logz=-3.62, remainder_fraction=12.5798%, Lmin=-0.31, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2179, ncalls=26567, regioncalls=0, ndraw=128, logz=-3.61, remainder_fraction=11.8009%, Lmin=-0.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=26819, regioncalls=0, ndraw=128, logz=-3.60, remainder_fraction=11.2539%, Lmin=-0.29, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=27419, regioncalls=0, ndraw=128, logz=-3.59, remainder_fraction=10.0661%, Lmin=-0.26, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=28019, regioncalls=0, ndraw=128, logz=-3.58, remainder_fraction=8.9933%, Lmin=-0.24, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=28499, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=8.2103%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=28619, regioncalls=0, ndraw=128, logz=-3.57, remainder_fraction=8.0236%, Lmin=-0.22, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2393, ncalls=29135, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=7.2645%, Lmin=-0.21, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=29219, regioncalls=0, ndraw=128, logz=-3.56, remainder_fraction=7.1497%, Lmin=-0.20, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=29579, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=6.6677%, Lmin=-0.19, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=29819, regioncalls=0, ndraw=128, logz=-3.55, remainder_fraction=6.3635%, Lmin=-0.18, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2494, ncalls=30347, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.7375%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=30419, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.6567%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=30659, regioncalls=0, ndraw=128, logz=-3.54, remainder_fraction=5.3984%, Lmin=-0.17, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=31019, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=5.0312%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2593, ncalls=31535, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.5486%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=31619, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.4748%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2627, ncalls=31943, regioncalls=0, ndraw=128, logz=-3.53, remainder_fraction=4.1971%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=32219, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.9752%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2699, ncalls=32807, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.5427%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32819, regioncalls=0, ndraw=128, logz=-3.52, remainder_fraction=3.5342%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2749, ncalls=33408, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=3.1458%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33420, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=3.1380%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2788, ncalls=33876, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.8669%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2790, ncalls=33900, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.8535%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=34020, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.7862%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2843, ncalls=34537, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.5142%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34621, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.4729%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34981, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.3022%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35221, regioncalls=0, ndraw=128, logz=-3.51, remainder_fraction=2.1933%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2944, ncalls=35749, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.9723%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35821, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.9440%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2983, ncalls=36217, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.7946%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36421, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.7223%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37021, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.5264%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37141, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.4895%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37622, regioncalls=0, ndraw=128, logz=-3.50, remainder_fraction=1.3513%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38222, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.1963%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3191, ncalls=38714, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.0825%, Lmin=-0.05, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=38822, regioncalls=0, ndraw=128, logz=-3.49, remainder_fraction=1.0589%, Lmin=-0.05, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.001 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39099 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.483 +- 0.05779 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1904.7, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.04 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_regionsampling.py::test_region_mean_distances

0.31

Passed

tests/test_run.py::test_reactive_run_resume_eggbox[csv]

2.17

Passed

tests/test_stepsampling.py::test_stepsampler_variable_speed_SLOW

16.12

[gw3] linux -- Python 3.10.6 /usr/bin/python3
[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3[gw3] linux -- Python 3.10.6 /usr/bin/python3
------------------------------Captured stdout call------------------------------
[ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.34) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-inf(0.00%) | Like=-28.83..-0.16 [-28.8263..-8.7269] | it/evals=0/408 eff=0.0000% N=400 Z=-24.2(0.00%) | Like=-20.35..-0.16 [-28.8263..-8.7269] | it/evals=50/652 eff=19.8413% N=400 Mono-modal Volume: ~exp(-4.53) * Expected Volume: exp(-0.23) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-20.7(0.00%) | Like=-17.02..-0.16 [-28.8263..-8.7269] | it/evals=90/855 eff=19.7802% N=400 Z=-20.0(0.00%) | Like=-16.30..-0.16 [-28.8263..-8.7269] | it/evals=100/917 eff=19.3424% N=400 Z=-16.9(0.00%) | Like=-13.55..-0.16 [-28.8263..-8.7269] | it/evals=150/1204 eff=18.6567% N=400 Mono-modal Volume: ~exp(-4.70) * Expected Volume: exp(-0.45) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-15.3(0.00%) | Like=-11.67..-0.16 [-28.8263..-8.7269] | it/evals=180/1379 eff=18.3861% N=400 Z=-14.3(0.00%) | Like=-10.99..-0.16 [-28.8263..-8.7269] | it/evals=200/1490 eff=18.3486% N=400 Z=-12.6(0.01%) | Like=-9.48..-0.16 [-28.8263..-8.7269] | it/evals=250/1831 eff=17.4703% N=400 Mono-modal Volume: ~exp(-4.89) * Expected Volume: exp(-0.67) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-12.0(0.02%) | Like=-9.05..-0.16 [-28.8263..-8.7269] | it/evals=270/1977 eff=17.1211% N=400 Z=-11.3(0.04%) | Like=-8.32..-0.16 [-8.6993..-4.7523] | it/evals=300/2235 eff=16.3488% N=400 Z=-10.3(0.12%) | Like=-7.39..-0.16 [-8.6993..-4.7523] | it/evals=350/2662 eff=15.4730% N=400 Mono-modal Volume: ~exp(-5.23) * Expected Volume: exp(-0.90) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.000|***************************************************| +1.000 Z=-10.1(0.15%) | Like=-7.24..-0.16 [-8.6993..-4.7523] | it/evals=360/2749 eff=15.3257% N=400 Z=-9.4(0.29%) | Like=-6.61..-0.16 [-8.6993..-4.7523] | it/evals=400/3082 eff=14.9142% N=400 Mono-modal Volume: ~exp(-5.27) * Expected Volume: exp(-1.12) Quality: ok param0: +0.000|** ************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.00|***************************************************| +1.00 Z=-8.8(0.55%) | Like=-6.09..-0.16 [-8.6993..-4.7523] | it/evals=450/3508 eff=14.4788% N=400 Z=-8.2(0.97%) | Like=-5.48..-0.16 [-8.6993..-4.7523] | it/evals=500/3947 eff=14.0964% N=400 Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-1.35) Quality: ok param0: +0.000|* * ***********************************************| +1.000 param1: +0.00| **************************************************| +1.00 param2: +0.00| ************************************************* | +1.00 Z=-7.7(1.64%) | Like=-4.97..-0.16 [-8.6993..-4.7523] | it/evals=550/4377 eff=13.8295% N=400 Z=-7.2(2.54%) | Like=-4.55..-0.16 [-4.7510..-3.5347] | it/evals=600/4902 eff=13.3274% N=400 Mono-modal Volume: ~exp(-5.32) * Expected Volume: exp(-1.57) Quality: ok param0: +0.00| ********************************************** | +1.00 param1: +0.00| ************************************************* | +1.00 param2: +0.00| * *********************************************** | +1.00 Z=-7.0(3.17%) | Like=-4.36..-0.16 [-4.7510..-3.5347] | it/evals=630/5206 eff=13.1086% N=400 Z=-6.9(3.66%) | Like=-4.24..-0.16 [-4.7510..-3.5347] | it/evals=650/5391 eff=13.0234% N=400 Z=-6.5(4.86%) | Like=-3.89..-0.16 [-4.7510..-3.5347] | it/evals=700/5910 eff=12.7042% N=400 Mono-modal Volume: ~exp(-5.82) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00| ******************************************** | +1.00 param1: +0.00| ************************************************ | +1.00 param2: +0.00| * ********************************************** | +1.00 Z=-6.4(5.40%) | Like=-3.77..-0.16 [-4.7510..-3.5347] | it/evals=720/6108 eff=12.6139% N=400 Z=-6.3(6.20%) | Like=-3.64..-0.16 [-4.7510..-3.5347] | it/evals=750/6423 eff=12.4523% N=400 Z=-6.0(8.08%) | Like=-3.22..-0.16 [-3.5248..-3.0127] | it/evals=800/6932 eff=12.2474% N=400 Mono-modal Volume: ~exp(-6.00) * Expected Volume: exp(-2.02) Quality: ok param0: +0.00| ********************************************* | +1.00 param1: +0.00| ********************************************* | +1.00 param2: +0.00| ********************************************* | +1.00 Z=-5.9(8.38%) | Like=-3.18..-0.16 [-3.5248..-3.0127] | it/evals=810/7022 eff=12.2320% N=400 Z=-5.7(10.09%) | Like=-2.95..-0.16 [-3.0064..-2.8253] | it/evals=850/7452 eff=12.0533% N=400 Mono-modal Volume: ~exp(-6.14) * Expected Volume: exp(-2.25) Quality: ok param0: +0.00| ******************************************* | +1.00 param1: +0.00| ******************************************** | +1.00 param2: +0.00| ******************************************* | +1.00 Z=-5.5(13.03%) | Like=-2.71..-0.16 [-2.7099..-2.6926] | it/evals=900/8035 eff=11.7878% N=400 Z=-5.3(15.30%) | Like=-2.53..-0.07 [-2.5312..-2.5204] | it/evals=942/8536 eff=11.5782% N=400 Z=-5.3(15.81%) | Like=-2.49..-0.07 [-2.4875..-2.4820]*| it/evals=950/8630 eff=11.5431% N=400 Have 2 modes Volume: ~exp(-6.44) * Expected Volume: exp(-2.47) Quality: ok param0: +0.00| 1 11111111111111111111222222222222222222222 | +1.00 param1: +0.0| 111111111111111111111222222222222222222222 | +1.0 param2: +0.00| 1111111111111111111112222222222222222222222 | +1.00 Z=-5.2(18.09%) | Like=-2.35..-0.07 [-2.3537..-2.3534]*| it/evals=990/9141 eff=11.3259% N=400 Z=-5.1(18.78%) | Like=-2.32..-0.07 [-2.3178..-2.3145]*| it/evals=1000/9257 eff=11.2905% N=400 Z=-5.0(21.59%) | Like=-2.15..-0.07 [-2.1509..-2.1480]*| it/evals=1042/9763 eff=11.1289% N=400 Z=-5.0(22.21%) | Like=-2.13..-0.07 [-2.1288..-2.1266]*| it/evals=1050/9869 eff=11.0888% N=400 Have 2 modes Volume: ~exp(-6.74) * Expected Volume: exp(-2.70) Quality: ok param0: +0.0| 11111111111111111111122222222222222222222 | +1.0 param1: +0.0| 1111111111111111111122222222222222222222 | +1.0 param2: +0.0| 1 111111111111111111 2222222222222222222 | +1.0 Z=-4.9(24.46%) | Like=-2.04..-0.07 [-2.0359..-2.0335]*| it/evals=1080/10222 eff=10.9957% N=400 Z=-4.8(25.95%) | Like=-1.95..-0.05 [-1.9594..-1.9475] | it/evals=1100/10463 eff=10.9311% N=400 Z=-4.7(29.13%) | Like=-1.80..-0.05 [-1.7997..-1.7967]*| it/evals=1147/11007 eff=10.8136% N=400 Z=-4.7(29.42%) | Like=-1.80..-0.05 [-1.7963..-1.7901]*| it/evals=1150/11037 eff=10.8113% N=400 Have 2 modes Volume: ~exp(-7.25) * Expected Volume: exp(-2.92) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 111111111111111111 222222222222222222 | +1.0 param1: +0.0| 1111111111111111111 2222222222222222222 | +1.0 param2: +0.0| 11111111111111111 222222222222222222 | +1.0 Z=-4.6(31.04%) | Like=-1.74..-0.05 [-1.7399..-1.7393]*| it/evals=1170/11290 eff=10.7438% N=400 Z=-4.6(33.32%) | Like=-1.66..-0.05 [-1.6552..-1.6543]*| it/evals=1200/11649 eff=10.6676% N=400 Z=-4.5(37.58%) | Like=-1.50..-0.05 [-1.4992..-1.4929]*| it/evals=1250/12253 eff=10.5459% N=400 Have 2 modes Volume: ~exp(-7.25) Expected Volume: exp(-3.15) Quality: ok positive degeneracy between param1 and param0: rho=0.75 param0: +0.0| 1111111111111111 222222222222222222 | +1.0 param1: +0.0| 011111111111111111 22222222222222222 | +1.0 param2: +0.0| 11111111111111111 22222222222222222 | +1.0 Z=-4.4(41.19%) | Like=-1.38..-0.02 [-1.3786..-1.3754]*| it/evals=1298/12799 eff=10.4686% N=400 Z=-4.4(41.34%) | Like=-1.37..-0.02 [-1.3736..-1.3729]*| it/evals=1300/12818 eff=10.4687% N=400 Have 2 modes Volume: ~exp(-7.59) * Expected Volume: exp(-3.37) Quality: ok param0: +0.0| 111111111111111 22222222222222222 | +1.0 param1: +0.0| 11111111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 22222222222222222 | +1.0 Z=-4.3(45.17%) | Like=-1.24..-0.02 [-1.2446..-1.2442]*| it/evals=1350/13420 eff=10.3687% N=400 Z=-4.2(48.94%) | Like=-1.17..-0.02 [-1.1729..-1.1720]*| it/evals=1400/14103 eff=10.2167% N=400 Have 2 modes Volume: ~exp(-7.67) * Expected Volume: exp(-3.60) Quality: ok param0: +0.0| 11111111111111 2222222222222222 | +1.0 param1: +0.0| 111111111111111 22222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.1(51.66%) | Like=-1.10..-0.02 [-1.0988..-1.0917]*| it/evals=1440/14656 eff=10.1010% N=400 Z=-4.1(52.34%) | Like=-1.08..-0.02 [-1.0790..-1.0771]*| it/evals=1450/14798 eff=10.0708% N=400 Z=-4.0(56.01%) | Like=-0.97..-0.02 [-0.9728..-0.9710]*| it/evals=1500/15457 eff=9.9621% N=400 Have 2 modes Volume: ~exp(-8.10) * Expected Volume: exp(-3.82) Quality: ok param0: +0.0| 1111111111111 22222222222222 | +1.0 param1: +0.0| 1111111111111 22222222222222 | +1.0 param2: +0.0| 11111111111111 22222222222222 | +1.0 Z=-4.0(58.24%) | Like=-0.91..-0.02 [-0.9133..-0.9124]*| it/evals=1530/15876 eff=9.8863% N=400 Z=-4.0(59.61%) | Like=-0.88..-0.02 [-0.8802..-0.8801]*| it/evals=1550/16146 eff=9.8438% N=400 Z=-3.9(63.06%) | Like=-0.81..-0.02 [-0.8119..-0.8102]*| it/evals=1600/16863 eff=9.7188% N=400 Have 2 modes Volume: ~exp(-8.32) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0| 111111111111 2222222222222 | +1.0 param1: +0.0| 1111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222 | +1.0 Z=-3.9(64.35%) | Like=-0.79..-0.02 [-0.7856..-0.7839]*| it/evals=1620/17112 eff=9.6936% N=400 Z=-3.9(66.11%) | Like=-0.74..-0.02 [-0.7430..-0.7393]*| it/evals=1650/17513 eff=9.6418% N=400 Z=-3.8(69.01%) | Like=-0.67..-0.01 [-0.6732..-0.6726]*| it/evals=1698/18256 eff=9.5094% N=400 Z=-3.8(69.13%) | Like=-0.67..-0.01 [-0.6714..-0.6700]*| it/evals=1700/18286 eff=9.5046% N=400 Have 2 modes Volume: ~exp(-8.58) * Expected Volume: exp(-4.27) Quality: ok param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 111111111111 22222222222 +0.8 | +1.0 param2: +0.0| 111111111111 222222222222 | +1.0 Z=-3.8(69.71%) | Like=-0.66..-0.01 [-0.6579..-0.6573]*| it/evals=1710/18415 eff=9.4921% N=400 Z=-3.8(71.97%) | Like=-0.61..-0.01 [-0.6089..-0.6086]*| it/evals=1750/18982 eff=9.4177% N=400 Have 2 modes Volume: ~exp(-8.80) * Expected Volume: exp(-4.50) Quality: ok param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.8(74.56%) | Like=-0.57..-0.01 [-0.5666..-0.5665]*| it/evals=1800/19686 eff=9.3332% N=400 Z=-3.7(77.00%) | Like=-0.52..-0.01 [-0.5201..-0.5200]*| it/evals=1850/20380 eff=9.2593% N=400 Have 2 modes Volume: ~exp(-8.81) * Expected Volume: exp(-4.73) Quality: ok param0: +0.0| 1111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 2222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.7(78.76%) | Like=-0.48..-0.01 [-0.4809..-0.4805]*| it/evals=1890/20945 eff=9.1993% N=400 Z=-3.7(79.22%) | Like=-0.47..-0.01 [-0.4748..-0.4739]*| it/evals=1900/21094 eff=9.1814% N=400 Z=-3.7(81.23%) | Like=-0.44..-0.01 [-0.4430..-0.4430]*| it/evals=1950/21811 eff=9.1075% N=400 Have 2 modes Volume: ~exp(-9.47) * Expected Volume: exp(-4.95) Quality: ok param0: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param2: +0.0| 1111111111 2222222222 +0.8 | +1.0 Z=-3.7(82.39%) | Like=-0.42..-0.00 [-0.4213..-0.4212]*| it/evals=1980/22248 eff=9.0626% N=400 Z=-3.6(83.11%) | Like=-0.41..-0.00 [-0.4099..-0.4091]*| it/evals=2000/22514 eff=9.0440% N=400 Z=-3.6(84.80%) | Like=-0.38..-0.00 [-0.3805..-0.3804]*| it/evals=2050/23230 eff=8.9794% N=400 Have 2 modes Volume: ~exp(-9.47) Expected Volume: exp(-5.18) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.6(85.93%) | Like=-0.35..-0.00 [-0.3545..-0.3535]*| it/evals=2086/23733 eff=8.9401% N=400 Z=-3.6(86.34%) | Like=-0.35..-0.00 [-0.3465..-0.3464]*| it/evals=2100/23916 eff=8.9301% N=400 Z=-3.6(87.66%) | Like=-0.32..-0.00 [-0.3200..-0.3198]*| it/evals=2146/24579 eff=8.8755% N=400 Z=-3.6(87.77%) | Like=-0.32..-0.00 [-0.3165..-0.3164]*| it/evals=2150/24636 eff=8.8711% N=400 Have 2 modes Volume: ~exp(-9.61) * Expected Volume: exp(-5.40) Quality: ok param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.6(88.03%) | Like=-0.31..-0.00 [-0.3132..-0.3128]*| it/evals=2160/24786 eff=8.8575% N=400 Z=-3.6(89.05%) | Like=-0.29..-0.00 [-0.2923..-0.2917]*| it/evals=2200/25324 eff=8.8268% N=400 Have 2 modes Volume: ~exp(-9.75) * Expected Volume: exp(-5.63) Quality: ok param0: +0.0| +0.2 1111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.6(90.21%) | Like=-0.27..-0.00 [-0.2700..-0.2698]*| it/evals=2250/26022 eff=8.7815% N=400 Z=-3.6(91.25%) | Like=-0.25..-0.00 [-0.2519..-0.2516]*| it/evals=2300/26733 eff=8.7343% N=400 Have 2 modes Volume: ~exp(-10.04) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(92.01%) | Like=-0.24..-0.00 [-0.2357..-0.2355]*| it/evals=2340/27302 eff=8.6982% N=400 Z=-3.5(92.19%) | Like=-0.23..-0.00 [-0.2294..-0.2292]*| it/evals=2350/27437 eff=8.6918% N=400 Z=-3.5(93.02%) | Like=-0.21..-0.00 [-0.2105..-0.2104]*| it/evals=2400/28149 eff=8.6490% N=400 Have 2 modes Volume: ~exp(-10.19) * Expected Volume: exp(-6.08) Quality: ok param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(93.49%) | Like=-0.20..-0.00 [-0.1993..-0.1991]*| it/evals=2430/28569 eff=8.6265% N=400 Z=-3.5(93.78%) | Like=-0.19..-0.00 [-0.1942..-0.1942]*| it/evals=2450/28857 eff=8.6095% N=400 Z=-3.5(94.38%) | Like=-0.18..-0.00 [-0.1843..-0.1840]*| it/evals=2494/29463 eff=8.5814% N=400 Z=-3.5(94.46%) | Like=-0.18..-0.00 [-0.1825..-0.1822]*| it/evals=2500/29561 eff=8.5731% N=400 Have 2 modes Volume: ~exp(-10.24) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0| +0.2 1111111 222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(94.71%) | Like=-0.18..-0.00 [-0.1772..-0.1767]*| it/evals=2520/29853 eff=8.5560% N=400 Z=-3.5(95.07%) | Like=-0.17..-0.00 [-0.1693..-0.1691]*| it/evals=2550/30281 eff=8.5339% N=400 Z=-3.5(95.61%) | Like=-0.16..-0.00 [-0.1558..-0.1558]*| it/evals=2600/30980 eff=8.5023% N=400 Have 2 modes Volume: ~exp(-10.87) * Expected Volume: exp(-6.53) Quality: ok param0: +0.0| +0.3 111111 222222 +0.8 | +1.0 param1: +0.0| +0.3 1111111 222222 +0.8 | +1.0 param2: +0.0| +0.2 111111 222222 +0.7 | +1.0 Z=-3.5(95.72%) | Like=-0.15..-0.00 [-0.1546..-0.1542]*| it/evals=2610/31115 eff=8.4975% N=400 Z=-3.5(96.08%) | Like=-0.14..-0.00 [-0.1445..-0.1443]*| it/evals=2648/31634 eff=8.4779% N=400 Z=-3.5(96.10%) | Like=-0.14..-0.00 [-0.1441..-0.1440]*| it/evals=2650/31661 eff=8.4770% N=400 Z=-3.5(96.52%) | Like=-0.13..-0.00 [-0.1314..-0.1313]*| it/evals=2698/32350 eff=8.4444% N=400 Have 2 modes Volume: ~exp(-11.01) * Expected Volume: exp(-6.75) Quality: ok param0: +0.0| +0.2 111111 22222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 111111 22222 +0.7 | +1.0 Z=-3.5(96.53%) | Like=-0.13..-0.00 [-0.1313..-0.1312]*| it/evals=2700/32376 eff=8.4438% N=400 Z=-3.5(96.92%) | Like=-0.12..-0.00 [-0.1190..-0.1189]*| it/evals=2750/33059 eff=8.4203% N=400 Have 2 modes Volume: ~exp(-11.01) Expected Volume: exp(-6.98) Quality: ok param0: +0.0| +0.3 11111 222220 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.25%) | Like=-0.11..-0.00 [-0.1098..-0.1093]*| it/evals=2796/33719 eff=8.3916% N=400 Z=-3.5(97.27%) | Like=-0.11..-0.00 [-0.1090..-0.1089]*| it/evals=2800/33775 eff=8.3895% N=400 Z=-3.5(97.58%) | Like=-0.10..-0.00 [-0.1009..-0.1008]*| it/evals=2850/34460 eff=8.3676% N=400 Have 2 modes Volume: ~exp(-11.20) * Expected Volume: exp(-7.20) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.75%) | Like=-0.10..-0.00 [-0.0973..-0.0973]*| it/evals=2880/34872 eff=8.3546% N=400 Z=-3.5(97.85%) | Like=-0.09..-0.00 [-0.0936..-0.0934]*| it/evals=2900/35140 eff=8.3477% N=400 Z=-3.5(98.10%) | Like=-0.08..-0.00 [-0.0833..-0.0832]*| it/evals=2950/35853 eff=8.3209% N=400 Have 2 modes Volume: ~exp(-11.50) * Expected Volume: exp(-7.43) Quality: ok positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.19%) | Like=-0.08..-0.00 [-0.0804..-0.0803]*| it/evals=2970/36145 eff=8.3089% N=400 Z=-3.5(98.31%) | Like=-0.08..-0.00 [-0.0768..-0.0767]*| it/evals=3000/36561 eff=8.2962% N=400 Z=-3.5(98.51%) | Like=-0.07..-0.00 [-0.0714..-0.0713]*| it/evals=3050/37263 eff=8.2739% N=400 Have 2 modes Volume: ~exp(-11.85) * Expected Volume: exp(-7.65) Quality: ok param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.54%) | Like=-0.07..-0.00 [-0.0707..-0.0707]*| it/evals=3060/37393 eff=8.2718% N=400 Z=-3.5(98.68%) | Like=-0.07..-0.00 [-0.0663..-0.0661]*| it/evals=3100/37983 eff=8.2484% N=400 Have 2 modes Volume: ~exp(-11.85) Expected Volume: exp(-7.88) Quality: ok param0: +0.0| +0.3 11110 02222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 02222 +0.7 | +1.0 Z=-3.5(98.83%) | Like=-0.06..-0.00 [-0.0607..-0.0606]*| it/evals=3150/38670 eff=8.2310% N=400 Z=-3.5(98.96%) | Like=-0.06..-0.00 [-0.0556..-0.0554]*| it/evals=3200/39390 eff=8.2072% N=400 [ultranest] Explored until L=-0.0009 [ultranest] Likelihood function evaluations: 39576 [ultranest] logZ = -3.454 +- 0.05165 [ultranest] Effective samples strategy satisfied (ESS = 1850.3, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.464 +- 0.118 single instance: logZ = -3.464 +- 0.071 bootstrapped : logZ = -3.454 +- 0.118 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁ ▁▁▁▁▂▃▅▅▆▄▅▅▄▄▃▃▂▃▂▃▃▅▅▇▇▇▇▇▇▄▂▃▂▁▁▁▁│1.00 0.54 +- 0.22 param1 : 0.00 │▁▁▁▁▂▂▂▃▄▄▆▅▅▅▄▄▃▂▂▂▂▃▄▄▅▇▇▇▇▅▇▃▃▂▂▁▁▁▁│1.00 0.53 +- 0.22 param2 : 0.00 │▁▁▁▁▁▂▂▃▄▅▅▆▅▆▃▄▂▃▂▂▃▃▄▄▆▇▇▇▅▇▆▄▃▃▂▂▁▁▁│1.00 0.53 +- 0.22 [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-3.77) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-inf(0.00%) | Like=-30.72..-0.14 [-30.7155..-8.6130] | it/evals=0/408 eff=0.0000% N=400 Z=-23.5(0.00%) | Like=-19.79..-0.14 [-30.7155..-8.6130] | it/evals=50/643 eff=20.5761% N=400 Mono-modal Volume: ~exp(-4.50) * Expected Volume: exp(-0.23) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.3(0.00%) | Like=-16.75..-0.14 [-30.7155..-8.6130] | it/evals=90/842 eff=20.3620% N=400 Z=-19.6(0.00%) | Like=-16.01..-0.14 [-30.7155..-8.6130] | it/evals=100/881 eff=20.7900% N=400 Z=-16.7(0.00%) | Like=-13.30..-0.14 [-30.7155..-8.6130] | it/evals=150/1187 eff=19.0597% N=400 Mono-modal Volume: ~exp(-4.50) Expected Volume: exp(-0.45) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-14.3(0.00%) | Like=-11.07..-0.14 [-30.7155..-8.6130] | it/evals=200/1518 eff=17.8891% N=400 Z=-12.5(0.01%) | Like=-9.36..-0.08 [-30.7155..-8.6130] | it/evals=250/1856 eff=17.1703% N=400 Mono-modal Volume: ~exp(-4.59) * Expected Volume: exp(-0.67) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-11.9(0.02%) | Like=-8.82..-0.08 [-30.7155..-8.6130] | it/evals=270/2017 eff=16.6976% N=400 Z=-11.2(0.04%) | Like=-8.15..-0.08 [-8.5729..-4.8890] | it/evals=300/2241 eff=16.2955% N=400 Z=-10.1(0.12%) | Like=-7.25..-0.08 [-8.5729..-4.8890] | it/evals=350/2597 eff=15.9308% N=400 Mono-modal Volume: ~exp(-4.78) * Expected Volume: exp(-0.90) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|* *************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-9.9(0.14%) | Like=-7.13..-0.08 [-8.5729..-4.8890] | it/evals=360/2686 eff=15.7480% N=400 Z=-9.4(0.26%) | Like=-6.65..-0.08 [-8.5729..-4.8890] | it/evals=400/2991 eff=15.4381% N=400 Mono-modal Volume: ~exp(-5.27) * Expected Volume: exp(-1.12) Quality: ok param0: +0.000|************************************************** | +1.000 param1: +0.000|* *************************************************| +1.000 param2: +0.00|************************************************ **| +1.00 Z=-8.7(0.47%) | Like=-6.15..-0.08 [-8.5729..-4.8890] | it/evals=450/3421 eff=14.8957% N=400 Z=-8.2(0.80%) | Like=-5.58..-0.08 [-8.5729..-4.8890] | it/evals=500/3853 eff=14.4802% N=400 Mono-modal Volume: ~exp(-5.49) * Expected Volume: exp(-1.35) Quality: ok param0: +0.000|************************************************** | +1.000 param1: +0.00| **************************************************| +1.00 param2: +0.000|************************************************** | +1.000 Z=-7.8(1.27%) | Like=-5.11..-0.08 [-8.5729..-4.8890] | it/evals=540/4239 eff=14.0662% N=400 Z=-7.7(1.39%) | Like=-5.07..-0.08 [-8.5729..-4.8890] | it/evals=550/4360 eff=13.8889% N=400 Z=-7.3(2.18%) | Like=-4.63..-0.08 [-4.8759..-3.4495] | it/evals=600/4774 eff=13.7174% N=400 Mono-modal Volume: ~exp(-5.49) Expected Volume: exp(-1.57) Quality: ok param0: +0.00| ***** ******************************************* | +1.00 param1: +0.000|************************************************** | +1.000 param2: +0.00| ************************************************* | +1.00 Z=-6.9(3.19%) | Like=-4.26..-0.08 [-4.8759..-3.4495] | it/evals=650/5228 eff=13.4631% N=400 Z=-6.6(4.42%) | Like=-3.95..-0.08 [-4.8759..-3.4495] | it/evals=700/5694 eff=13.2225% N=400 Mono-modal Volume: ~exp(-5.51) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00| ************************************************ | +1.00 param1: +0.00| ************************************************ | +1.00 param2: +0.00| ********************************************** * | +1.00 Z=-6.5(5.01%) | Like=-3.81..-0.08 [-4.8759..-3.4495] | it/evals=720/5877 eff=13.1459% N=400 Z=-6.3(6.01%) | Like=-3.57..-0.08 [-4.8759..-3.4495] | it/evals=750/6185 eff=12.9646% N=400 Z=-6.0(8.07%) | Like=-3.36..-0.08 [-3.4294..-3.0089] | it/evals=800/6703 eff=12.6924% N=400 Mono-modal Volume: ~exp(-5.75) * Expected Volume: exp(-2.02) Quality: ok positive degeneracy between param1 and param0: rho=0.75 param0: +0.00| ********************************************** | +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| ********************************************* | +1.00 Z=-6.0(8.46%) | Like=-3.31..-0.08 [-3.4294..-3.0089] | it/evals=810/6800 eff=12.6562% N=400 Z=-5.8(10.21%) | Like=-3.02..-0.08 [-3.4294..-3.0089] | it/evals=850/7190 eff=12.5184% N=400 Mono-modal Volume: ~exp(-6.34) * Expected Volume: exp(-2.25) Quality: ok positive degeneracy between param2 and param1: rho=0.77 param0: +0.00| ******************************************* | +1.00 param1: +0.00| ******************************************** | +1.00 param2: +0.00| ******************************************** | +1.00 Z=-5.6(12.57%) | Like=-2.82..-0.04 [-2.8656..-2.7934] | it/evals=900/7734 eff=12.2716% N=400 Z=-5.4(15.40%) | Like=-2.61..-0.04 [-2.6142..-2.6119]*| it/evals=950/8283 eff=12.0512% N=400 Have 2 modes Volume: ~exp(-6.69) * Expected Volume: exp(-2.47) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 111111111111111111112222222222222222222222 | +1.0 param1: +0.00| 1111111111111111111111222222222222222222222 | +1.00 param2: +0.00| 11 1111111111111111111222222222222222222222 | +1.00 Z=-5.2(17.59%) | Like=-2.36..-0.04 [-2.3628..-2.3616]*| it/evals=990/8721 eff=11.8976% N=400 Z=-5.2(18.24%) | Like=-2.31..-0.04 [-2.3115..-2.3053]*| it/evals=1000/8846 eff=11.8399% N=400 Z=-5.0(21.93%) | Like=-2.09..-0.02 [-2.0868..-2.0846]*| it/evals=1050/9438 eff=11.6176% N=400 Have 2 modes Volume: ~exp(-7.11) * Expected Volume: exp(-2.70) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 1111111111111111111 22222222222222222222 | +1.0 param1: +0.0| 11111111111111111111222222222222222222222 | +1.0 param2: +0.0| 111111111111111111 22222222222222222222 | +1.0 Z=-4.9(24.27%) | Like=-2.01..-0.02 [-2.0281..-2.0083] | it/evals=1080/9801 eff=11.4881% N=400 Z=-4.9(25.84%) | Like=-1.93..-0.02 [-1.9348..-1.9280]*| it/evals=1100/10060 eff=11.3872% N=400 Z=-4.7(29.65%) | Like=-1.79..-0.02 [-1.7887..-1.7871]*| it/evals=1150/10677 eff=11.1900% N=400 Have 2 modes Volume: ~exp(-7.11) Expected Volume: exp(-2.92) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 111111111111111111 2222222222222222222 | +1.0 param1: +0.0| 11111111111111111111 2222222222222222222 | +1.0 param2: +0.0| 0111111111111111111 2222222222222222222 | +1.0 Z=-4.6(33.36%) | Like=-1.68..-0.02 [-1.6826..-1.6768]*| it/evals=1200/11350 eff=10.9589% N=400 Z=-4.5(37.03%) | Like=-1.54..-0.02 [-1.5525..-1.5411] | it/evals=1250/12003 eff=10.7731% N=400 Have 2 modes Volume: ~exp(-7.35) * Expected Volume: exp(-3.15) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 11111111111111111 222222222222222222 | +1.0 param1: +0.0| 1 111111111111111 2222222222222222222 | +1.0 param2: +0.0| 111111111111111111 222222222222222222 | +1.0 Z=-4.5(37.74%) | Like=-1.50..-0.02 [-1.5030..-1.5016]*| it/evals=1260/12125 eff=10.7463% N=400 Z=-4.4(40.69%) | Like=-1.38..-0.02 [-1.3932..-1.3832] | it/evals=1300/12647 eff=10.6148% N=400 Have 2 modes Volume: ~exp(-7.35) Expected Volume: exp(-3.37) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 1111111111111111 2222222222222222 | +1.0 param1: +0.0| 111111111111111 22222222222222222 | +1.0 param2: +0.0| 1111111111111111 22222222222222222 | +1.0 Z=-4.3(44.84%) | Like=-1.27..-0.02 [-1.2720..-1.2711]*| it/evals=1350/13312 eff=10.4554% N=400 Z=-4.2(48.70%) | Like=-1.18..-0.02 [-1.1835..-1.1824]*| it/evals=1400/14001 eff=10.2934% N=400 Have 2 modes Volume: ~exp(-7.56) * Expected Volume: exp(-3.60) Quality: ok positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 111111111111111 22222222222222 | +1.0 param1: +0.0| 111111111111111 2222222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.2(51.68%) | Like=-1.11..-0.02 [-1.1101..-1.1077]*| it/evals=1440/14526 eff=10.1940% N=400 Z=-4.1(52.42%) | Like=-1.08..-0.02 [-1.0795..-1.0776]*| it/evals=1450/14675 eff=10.1576% N=400 Z=-4.1(56.27%) | Like=-0.99..-0.02 [-0.9862..-0.9841]*| it/evals=1500/15383 eff=10.0113% N=400 Have 2 modes Volume: ~exp(-8.10) * Expected Volume: exp(-3.82) Quality: ok positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 111111111111111 22222222222222 | +1.0 param1: +0.0| 11111111111111 22222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222222 | +1.0 Z=-4.0(58.31%) | Like=-0.96..-0.02 [-0.9583..-0.9577]*| it/evals=1530/15811 eff=9.9280% N=400 Z=-4.0(59.71%) | Like=-0.93..-0.02 [-0.9327..-0.9319]*| it/evals=1550/16084 eff=9.8827% N=400 Z=-4.0(62.98%) | Like=-0.86..-0.02 [-0.8610..-0.8608]*| it/evals=1600/16777 eff=9.7698% N=400 Have 2 modes Volume: ~exp(-8.40) * Expected Volume: exp(-4.05) Quality: ok param0: +0.0| 11111111111111 2222222222222 | +1.0 param1: +0.0| 1111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-3.9(64.21%) | Like=-0.83..-0.02 [-0.8319..-0.8302]*| it/evals=1620/17068 eff=9.7192% N=400 Z=-3.9(66.02%) | Like=-0.78..-0.02 [-0.7844..-0.7819]*| it/evals=1650/17474 eff=9.6638% N=400 Z=-3.9(68.88%) | Like=-0.72..-0.02 [-0.7185..-0.7171]*| it/evals=1700/18181 eff=9.5608% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.27) Quality: ok param0: +0.0| 011111111111 222222222222 | +1.0 param1: +0.0| 1111111111111 222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222 | +1.0 Z=-3.8(71.69%) | Like=-0.65..-0.02 [-0.6530..-0.6527]*| it/evals=1750/18873 eff=9.4733% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.50) Quality: ok param0: +0.0| 011111111101 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 222222222222 | +1.0 Z=-3.8(74.33%) | Like=-0.61..-0.01 [-0.6079..-0.6078]*| it/evals=1800/19590 eff=9.3799% N=400 Z=-3.8(76.65%) | Like=-0.56..-0.01 [-0.5608..-0.5607]*| it/evals=1850/20308 eff=9.2927% N=400 Have 2 modes Volume: ~exp(-8.40) Expected Volume: exp(-4.73) Quality: ok param0: +0.0| 11111111101 2222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.7(78.46%) | Like=-0.53..-0.01 [-0.5328..-0.5320]*| it/evals=1890/20890 eff=9.2240% N=400 Z=-3.7(78.88%) | Like=-0.52..-0.01 [-0.5217..-0.5216]*| it/evals=1900/21039 eff=9.2059% N=400 Z=-3.7(80.75%) | Like=-0.48..-0.01 [-0.4843..-0.4841]*| it/evals=1946/21688 eff=9.1413% N=400 Z=-3.7(80.91%) | Like=-0.48..-0.01 [-0.4806..-0.4802]*| it/evals=1950/21739 eff=9.1382% N=400 Have 2 modes Volume: ~exp(-9.10) * Expected Volume: exp(-4.95) Quality: ok param0: +0.0| 111111111 2222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 22222222222 +0.8 | +1.0 param2: +0.0| 1111111111 2222222222 +0.8 | +1.0 Z=-3.7(82.04%) | Like=-0.45..-0.01 [-0.4530..-0.4516]*| it/evals=1980/22164 eff=9.0976% N=400 Z=-3.7(82.77%) | Like=-0.44..-0.01 [-0.4359..-0.4357]*| it/evals=2000/22437 eff=9.0756% N=400 Z=-3.7(84.37%) | Like=-0.40..-0.01 [-0.4047..-0.4046]*| it/evals=2047/23121 eff=9.0093% N=400 Z=-3.7(84.46%) | Like=-0.40..-0.00 [-0.4038..-0.4036]*| it/evals=2050/23176 eff=9.0007% N=400 Have 2 modes Volume: ~exp(-9.55) * Expected Volume: exp(-5.18) Quality: ok param0: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 2222222222 +0.8 | +1.0 Z=-3.7(85.08%) | Like=-0.38..-0.00 [-0.3835..-0.3834]*| it/evals=2070/23468 eff=8.9735% N=400 Z=-3.6(86.01%) | Like=-0.36..-0.00 [-0.3626..-0.3625]*| it/evals=2100/23855 eff=8.9533% N=400 Z=-3.6(87.48%) | Like=-0.33..-0.00 [-0.3325..-0.3324]*| it/evals=2150/24513 eff=8.9164% N=400 Have 2 modes Volume: ~exp(-9.55) Expected Volume: exp(-5.40) Quality: ok param0: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 Z=-3.6(88.25%) | Like=-0.31..-0.00 [-0.3127..-0.3123]*| it/evals=2179/24901 eff=8.8935% N=400 Z=-3.6(88.76%) | Like=-0.30..-0.00 [-0.3024..-0.3013]*| it/evals=2200/25200 eff=8.8710% N=400 Have 2 modes Volume: ~exp(-9.86) * Expected Volume: exp(-5.63) Quality: ok param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 Z=-3.6(89.94%) | Like=-0.28..-0.00 [-0.2765..-0.2764]*| it/evals=2250/25854 eff=8.8395% N=400 Z=-3.6(90.99%) | Like=-0.26..-0.00 [-0.2586..-0.2586]*| it/evals=2299/26539 eff=8.7953% N=400 Z=-3.6(91.01%) | Like=-0.26..-0.00 [-0.2586..-0.2575]*| it/evals=2300/26553 eff=8.7944% N=400 Have 2 modes Volume: ~exp(-10.13) * Expected Volume: exp(-5.85) Quality: ok param0: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 Z=-3.6(91.78%) | Like=-0.24..-0.00 [-0.2428..-0.2419]*| it/evals=2340/27133 eff=8.7532% N=400 Z=-3.6(91.97%) | Like=-0.24..-0.00 [-0.2390..-0.2385]*| it/evals=2350/27278 eff=8.7432% N=400 Z=-3.6(92.83%) | Like=-0.22..-0.00 [-0.2196..-0.2195]*| it/evals=2400/27946 eff=8.7127% N=400 Have 2 modes Volume: ~exp(-10.13) Expected Volume: exp(-6.08) Quality: ok param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(93.47%) | Like=-0.20..-0.00 [-0.2011..-0.2010]*| it/evals=2441/28535 eff=8.6760% N=400 Z=-3.6(93.60%) | Like=-0.20..-0.00 [-0.1984..-0.1984]*| it/evals=2450/28675 eff=8.6649% N=400 Z=-3.6(94.30%) | Like=-0.19..-0.00 [-0.1856..-0.1851]*| it/evals=2500/29353 eff=8.6347% N=400 Have 2 modes Volume: ~exp(-10.43) * Expected Volume: exp(-6.30) Quality: ok param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 Z=-3.5(94.56%) | Like=-0.18..-0.00 [-0.1800..-0.1799]*| it/evals=2520/29662 eff=8.6119% N=400 Z=-3.5(94.93%) | Like=-0.17..-0.00 [-0.1693..-0.1687]*| it/evals=2550/30099 eff=8.5861% N=400 Z=-3.5(95.39%) | Like=-0.16..-0.00 [-0.1575..-0.1574]*| it/evals=2591/30671 eff=8.5593% N=400 Z=-3.5(95.49%) | Like=-0.16..-0.00 [-0.1552..-0.1549]*| it/evals=2600/30778 eff=8.5588% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.53) Quality: ok param0: +0.0| +0.2 111111 222222 +0.8 | +1.0 param1: +0.0| +0.2 111111 2222222 +0.7 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 Z=-3.5(95.90%) | Like=-0.15..-0.00 [-0.1482..-0.1482]*| it/evals=2640/31333 eff=8.5346% N=400 Z=-3.5(96.00%) | Like=-0.15..-0.00 [-0.1462..-0.1460]*| it/evals=2650/31473 eff=8.5283% N=400 Z=-3.5(96.42%) | Like=-0.14..-0.00 [-0.1367..-0.1360]*| it/evals=2698/32151 eff=8.4974% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.75) Quality: ok param0: +0.0| +0.3 11111 222222 +0.7 | +1.0 param1: +0.0| +0.3 11111 222222 +0.7 | +1.0 param2: +0.0| +0.3 011111 222222 +0.7 | +1.0 Z=-3.5(96.44%) | Like=-0.14..-0.00 [-0.1360..-0.1359]*| it/evals=2700/32188 eff=8.4938% N=400 Z=-3.5(96.84%) | Like=-0.12..-0.00 [-0.1240..-0.1239]*| it/evals=2750/32861 eff=8.4717% N=400 Have 2 modes Volume: ~exp(-10.43) Expected Volume: exp(-6.98) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 222222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.16%) | Like=-0.12..-0.00 [-0.1170..-0.1167]*| it/evals=2795/33463 eff=8.4536% N=400 Z=-3.5(97.19%) | Like=-0.12..-0.00 [-0.1161..-0.1159]*| it/evals=2800/33526 eff=8.4526% N=400 Z=-3.5(97.47%) | Like=-0.11..-0.00 [-0.1070..-0.1059]*| it/evals=2844/34171 eff=8.4214% N=400 Z=-3.5(97.51%) | Like=-0.11..-0.00 [-0.1053..-0.1051]*| it/evals=2850/34241 eff=8.4217% N=400 Have 2 modes Volume: ~exp(-10.65) * Expected Volume: exp(-7.20) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.68%) | Like=-0.10..-0.00 [-0.1002..-0.0999]*| it/evals=2880/34663 eff=8.4056% N=400 Z=-3.5(97.79%) | Like=-0.10..-0.00 [-0.0955..-0.0954]*| it/evals=2900/34946 eff=8.3946% N=400 Z=-3.5(97.99%) | Like=-0.09..-0.00 [-0.0887..-0.0886]*| it/evals=2939/35496 eff=8.3742% N=400 Z=-3.5(98.04%) | Like=-0.09..-0.00 [-0.0876..-0.0873]*| it/evals=2950/35641 eff=8.3709% N=400 Have 2 modes Volume: ~exp(-11.34) * Expected Volume: exp(-7.43) Quality: ok param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.13%) | Like=-0.08..-0.00 [-0.0850..-0.0839]*| it/evals=2970/35916 eff=8.3624% N=400 Z=-3.5(98.27%) | Like=-0.08..-0.00 [-0.0810..-0.0810]*| it/evals=3000/36340 eff=8.3472% N=400 Z=-3.5(98.44%) | Like=-0.07..-0.00 [-0.0748..-0.0746]*| it/evals=3044/36948 eff=8.3288% N=400 Z=-3.5(98.46%) | Like=-0.07..-0.00 [-0.0740..-0.0738]*| it/evals=3050/37033 eff=8.3258% N=400 Have 2 modes Volume: ~exp(-11.34) Expected Volume: exp(-7.65) Quality: ok param0: +0.0| +0.3 1111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11110 22222 +0.7 | +1.0 Z=-3.5(98.57%) | Like=-0.07..-0.00 [-0.0692..-0.0692]*| it/evals=3080/37466 eff=8.3095% N=400 Z=-3.5(98.64%) | Like=-0.07..-0.00 [-0.0672..-0.0668]*| it/evals=3100/37717 eff=8.3072% N=400 Z=-3.5(98.78%) | Like=-0.06..-0.00 [-0.0622..-0.0622]*| it/evals=3146/38392 eff=8.2807% N=400 Have 2 modes Volume: ~exp(-11.58) * Expected Volume: exp(-7.88) Quality: ok param0: +0.0| +0.3 1111 22222 +0.7 | +1.0 param1: +0.0| +0.3 1111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.80%) | Like=-0.06..-0.00 [-0.0621..-0.0619]*| it/evals=3150/38452 eff=8.2781% N=400 Z=-3.5(98.93%) | Like=-0.06..-0.00 [-0.0580..-0.0580]*| it/evals=3200/39146 eff=8.2589% N=400 [ultranest] Explored until L=-0.002 [ultranest] Likelihood function evaluations: 39507 [ultranest] logZ = -3.501 +- 0.06405 [ultranest] Effective samples strategy satisfied (ESS = 1848.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.493 +- 0.164 single instance: logZ = -3.493 +- 0.071 bootstrapped : logZ = -3.501 +- 0.163 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations param0 : 0.00 │▁▁▁▁▁▁▂▂▄▄▅▅▅▄▄▄▃▃▁▂▂▂▃▃▅▇▇▇▆▆▄▄▃▂▂▁▁▁▁│1.00 0.54 +- 0.22 param1 : 0.00 │▁▁▁▁▁▂▃▂▄▅▄▆▅▄▃▄▃▂▂▁▃▂▃▅▅▇▇▇▅▅▄▅▃▃▂▁▁▁▁│1.00 0.53 +- 0.23 param2 : 0.00 │▁▁▁▁▁▁▃▄▅▄▄▅▅▅▅▃▃▃▂▂▂▃▃▄▅▇▇▆▆▇▅▅▃▂▁▁▁▁▁│1.00 0.53 +- 0.22
-------------------------------Captured log call--------------------------------
DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=408, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-28.83, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=652, regioncalls=0, ndraw=40, logz=-24.15, remainder_fraction=100.0000%, Lmin=-20.35, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=855, regioncalls=0, ndraw=40, logz=-20.66, remainder_fraction=100.0000%, Lmin=-17.02, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=917, regioncalls=0, ndraw=40, logz=-19.96, remainder_fraction=100.0000%, Lmin=-16.30, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1204, regioncalls=0, ndraw=40, logz=-16.87, remainder_fraction=99.9998%, Lmin=-13.55, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=180, ncalls=1379, regioncalls=0, ndraw=40, logz=-15.27, remainder_fraction=99.9992%, Lmin=-11.67, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1490, regioncalls=0, ndraw=40, logz=-14.29, remainder_fraction=99.9978%, Lmin=-10.99, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1831, regioncalls=0, ndraw=40, logz=-12.55, remainder_fraction=99.9876%, Lmin=-9.48, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=1977, regioncalls=0, ndraw=40, logz=-12.03, remainder_fraction=99.9788%, Lmin=-9.05, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=2235, regioncalls=0, ndraw=40, logz=-11.29, remainder_fraction=99.9558%, Lmin=-8.32, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2662, regioncalls=0, ndraw=40, logz=-10.29, remainder_fraction=99.8768%, Lmin=-7.39, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2749, regioncalls=0, ndraw=40, logz=-10.10, remainder_fraction=99.8502%, Lmin=-7.24, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=3082, regioncalls=0, ndraw=40, logz=-9.45, remainder_fraction=99.7066%, Lmin=-6.61, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3508, regioncalls=0, ndraw=40, logz=-8.79, remainder_fraction=99.4495%, Lmin=-6.09, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3947, regioncalls=0, ndraw=40, logz=-8.20, remainder_fraction=99.0254%, Lmin=-5.48, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=4377, regioncalls=0, ndraw=40, logz=-7.67, remainder_fraction=98.3560%, Lmin=-4.97, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=4902, regioncalls=0, ndraw=40, logz=-7.23, remainder_fraction=97.4567%, Lmin=-4.55, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=630, ncalls=5206, regioncalls=0, ndraw=40, logz=-7.00, remainder_fraction=96.8277%, Lmin=-4.36, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5391, regioncalls=0, ndraw=40, logz=-6.86, remainder_fraction=96.3450%, Lmin=-4.24, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5910, regioncalls=0, ndraw=40, logz=-6.55, remainder_fraction=95.1376%, Lmin=-3.89, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=6108, regioncalls=0, ndraw=40, logz=-6.43, remainder_fraction=94.6041%, Lmin=-3.77, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6423, regioncalls=0, ndraw=40, logz=-6.26, remainder_fraction=93.7974%, Lmin=-3.64, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=6932, regioncalls=0, ndraw=40, logz=-6.00, remainder_fraction=91.9152%, Lmin=-3.22, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=7022, regioncalls=0, ndraw=40, logz=-5.94, remainder_fraction=91.6156%, Lmin=-3.18, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=7452, regioncalls=0, ndraw=40, logz=-5.74, remainder_fraction=89.9117%, Lmin=-2.95, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=8035, regioncalls=0, ndraw=40, logz=-5.51, remainder_fraction=86.9683%, Lmin=-2.71, Lmax=-0.16 DEBUG ultranest:integrator.py:2610 iteration=942, ncalls=8536, regioncalls=0, ndraw=40, logz=-5.34, remainder_fraction=84.7024%, Lmin=-2.53, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=8630, regioncalls=0, ndraw=40, logz=-5.31, remainder_fraction=84.1905%, Lmin=-2.49, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=9141, regioncalls=0, ndraw=40, logz=-5.16, remainder_fraction=81.9129%, Lmin=-2.35, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=9257, regioncalls=0, ndraw=40, logz=-5.12, remainder_fraction=81.2186%, Lmin=-2.32, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1042, ncalls=9763, regioncalls=0, ndraw=40, logz=-4.99, remainder_fraction=78.4103%, Lmin=-2.15, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=9869, regioncalls=0, ndraw=40, logz=-4.96, remainder_fraction=77.7926%, Lmin=-2.13, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=10222, regioncalls=0, ndraw=40, logz=-4.87, remainder_fraction=75.5443%, Lmin=-2.04, Lmax=-0.07 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=10463, regioncalls=0, ndraw=40, logz=-4.82, remainder_fraction=74.0501%, Lmin=-1.95, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1147, ncalls=11007, regioncalls=0, ndraw=40, logz=-4.69, remainder_fraction=70.8707%, Lmin=-1.80, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=11037, regioncalls=0, ndraw=40, logz=-4.68, remainder_fraction=70.5823%, Lmin=-1.80, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1170, ncalls=11290, regioncalls=0, ndraw=40, logz=-4.63, remainder_fraction=68.9649%, Lmin=-1.74, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=11649, regioncalls=0, ndraw=40, logz=-4.56, remainder_fraction=66.6778%, Lmin=-1.66, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=12253, regioncalls=0, ndraw=40, logz=-4.45, remainder_fraction=62.4217%, Lmin=-1.50, Lmax=-0.05 DEBUG ultranest:integrator.py:2610 iteration=1298, ncalls=12799, regioncalls=0, ndraw=40, logz=-4.36, remainder_fraction=58.8052%, Lmin=-1.38, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=12818, regioncalls=0, ndraw=40, logz=-4.35, remainder_fraction=58.6619%, Lmin=-1.37, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=13420, regioncalls=0, ndraw=40, logz=-4.26, remainder_fraction=54.8291%, Lmin=-1.24, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=14103, regioncalls=0, ndraw=40, logz=-4.18, remainder_fraction=51.0564%, Lmin=-1.17, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=14656, regioncalls=0, ndraw=40, logz=-4.12, remainder_fraction=48.3362%, Lmin=-1.10, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=14798, regioncalls=0, ndraw=40, logz=-4.11, remainder_fraction=47.6584%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=15457, regioncalls=0, ndraw=40, logz=-4.04, remainder_fraction=43.9916%, Lmin=-0.97, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=15876, regioncalls=0, ndraw=40, logz=-4.00, remainder_fraction=41.7608%, Lmin=-0.91, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=16146, regioncalls=0, ndraw=40, logz=-3.98, remainder_fraction=40.3943%, Lmin=-0.88, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=16863, regioncalls=0, ndraw=40, logz=-3.93, remainder_fraction=36.9419%, Lmin=-0.81, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=17112, regioncalls=0, ndraw=40, logz=-3.91, remainder_fraction=35.6471%, Lmin=-0.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=17513, regioncalls=0, ndraw=40, logz=-3.88, remainder_fraction=33.8851%, Lmin=-0.74, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1698, ncalls=18256, regioncalls=0, ndraw=40, logz=-3.84, remainder_fraction=30.9943%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=18286, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=30.8667%, Lmin=-0.67, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1710, ncalls=18415, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=30.2875%, Lmin=-0.66, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=18982, regioncalls=0, ndraw=40, logz=-3.79, remainder_fraction=28.0333%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=19686, regioncalls=0, ndraw=40, logz=-3.76, remainder_fraction=25.4394%, Lmin=-0.57, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=20380, regioncalls=0, ndraw=40, logz=-3.73, remainder_fraction=22.9973%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=20945, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=21.2394%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=21094, regioncalls=0, ndraw=40, logz=-3.70, remainder_fraction=20.7811%, Lmin=-0.47, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=21811, regioncalls=0, ndraw=40, logz=-3.67, remainder_fraction=18.7682%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=22248, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=17.6122%, Lmin=-0.42, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=22514, regioncalls=0, ndraw=40, logz=-3.65, remainder_fraction=16.8935%, Lmin=-0.41, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=23230, regioncalls=0, ndraw=40, logz=-3.63, remainder_fraction=15.2022%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2086, ncalls=23733, regioncalls=0, ndraw=40, logz=-3.62, remainder_fraction=14.0709%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=23916, regioncalls=0, ndraw=40, logz=-3.61, remainder_fraction=13.6615%, Lmin=-0.35, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2146, ncalls=24579, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=12.3395%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=24636, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=12.2299%, Lmin=-0.32, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2160, ncalls=24786, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=11.9665%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=25324, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=10.9502%, Lmin=-0.29, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=26022, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=9.7880%, Lmin=-0.27, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=26733, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=8.7467%, Lmin=-0.25, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=27302, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=7.9888%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=27437, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=7.8140%, Lmin=-0.23, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=28149, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=6.9763%, Lmin=-0.21, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2430, ncalls=28569, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=6.5113%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=28857, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=6.2211%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2494, ncalls=29463, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.6208%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=29561, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.5427%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=29853, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=5.2866%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=30281, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.9283%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=30980, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.3857%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2610, ncalls=31115, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=4.2832%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2648, ncalls=31634, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.9189%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=31661, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.8998%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2698, ncalls=32350, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.4821%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32376, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=3.4651%, Lmin=-0.13, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=33059, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=3.0753%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2796, ncalls=33719, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.7542%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=33775, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.7283%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34460, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.4214%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34872, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.2520%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=35140, regioncalls=0, ndraw=40, logz=-3.49, remainder_fraction=2.1465%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35853, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.9028%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=36145, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.8127%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36561, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.6855%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37263, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.4927%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3060, ncalls=37393, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.4567%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37983, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.3219%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38670, regioncalls=0, ndraw=40, logz=-3.48, remainder_fraction=1.1704%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=39390, regioncalls=0, ndraw=40, logz=-3.47, remainder_fraction=1.0359%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.0009 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39576 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.454 +- 0.05165 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1850.3, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.07 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.05, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 INFO ultranest:integrator.py:2307 done iterating. DEBUG ultranest:integrator.py:1154 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 INFO ultranest:integrator.py:1433 Sampling 400 live points from prior ... DEBUG ultranest:integrator.py:2395 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 DEBUG ultranest:integrator.py:2399 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 DEBUG ultranest:integrator.py:2458 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] DEBUG ultranest:integrator.py:2610 iteration=0, ncalls=408, regioncalls=0, ndraw=40, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.72, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=50, ncalls=643, regioncalls=0, ndraw=40, logz=-23.52, remainder_fraction=100.0000%, Lmin=-19.79, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=90, ncalls=842, regioncalls=0, ndraw=40, logz=-20.30, remainder_fraction=100.0000%, Lmin=-16.75, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=100, ncalls=881, regioncalls=0, ndraw=40, logz=-19.61, remainder_fraction=100.0000%, Lmin=-16.01, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=150, ncalls=1187, regioncalls=0, ndraw=40, logz=-16.71, remainder_fraction=99.9998%, Lmin=-13.30, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=200, ncalls=1518, regioncalls=0, ndraw=40, logz=-14.31, remainder_fraction=99.9982%, Lmin=-11.07, Lmax=-0.14 DEBUG ultranest:integrator.py:2610 iteration=250, ncalls=1856, regioncalls=0, ndraw=40, logz=-12.50, remainder_fraction=99.9895%, Lmin=-9.36, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=270, ncalls=2017, regioncalls=0, ndraw=40, logz=-11.92, remainder_fraction=99.9811%, Lmin=-8.82, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=300, ncalls=2241, regioncalls=0, ndraw=40, logz=-11.17, remainder_fraction=99.9593%, Lmin=-8.15, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=350, ncalls=2597, regioncalls=0, ndraw=40, logz=-10.12, remainder_fraction=99.8843%, Lmin=-7.25, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=360, ncalls=2686, regioncalls=0, ndraw=40, logz=-9.94, remainder_fraction=99.8597%, Lmin=-7.13, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=400, ncalls=2991, regioncalls=0, ndraw=40, logz=-9.36, remainder_fraction=99.7402%, Lmin=-6.65, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=450, ncalls=3421, regioncalls=0, ndraw=40, logz=-8.74, remainder_fraction=99.5274%, Lmin=-6.15, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=500, ncalls=3853, regioncalls=0, ndraw=40, logz=-8.22, remainder_fraction=99.1959%, Lmin=-5.58, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=540, ncalls=4239, regioncalls=0, ndraw=40, logz=-7.82, remainder_fraction=98.7327%, Lmin=-5.11, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=550, ncalls=4360, regioncalls=0, ndraw=40, logz=-7.72, remainder_fraction=98.6113%, Lmin=-5.07, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=600, ncalls=4774, regioncalls=0, ndraw=40, logz=-7.30, remainder_fraction=97.8227%, Lmin=-4.63, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=650, ncalls=5228, regioncalls=0, ndraw=40, logz=-6.92, remainder_fraction=96.8062%, Lmin=-4.26, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=700, ncalls=5694, regioncalls=0, ndraw=40, logz=-6.60, remainder_fraction=95.5797%, Lmin=-3.95, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=720, ncalls=5877, regioncalls=0, ndraw=40, logz=-6.48, remainder_fraction=94.9944%, Lmin=-3.81, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=750, ncalls=6185, regioncalls=0, ndraw=40, logz=-6.30, remainder_fraction=93.9860%, Lmin=-3.57, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=800, ncalls=6703, regioncalls=0, ndraw=40, logz=-6.03, remainder_fraction=91.9307%, Lmin=-3.36, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=810, ncalls=6800, regioncalls=0, ndraw=40, logz=-5.98, remainder_fraction=91.5442%, Lmin=-3.31, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=850, ncalls=7190, regioncalls=0, ndraw=40, logz=-5.79, remainder_fraction=89.7945%, Lmin=-3.02, Lmax=-0.08 DEBUG ultranest:integrator.py:2610 iteration=900, ncalls=7734, regioncalls=0, ndraw=40, logz=-5.57, remainder_fraction=87.4320%, Lmin=-2.82, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=950, ncalls=8283, regioncalls=0, ndraw=40, logz=-5.38, remainder_fraction=84.5994%, Lmin=-2.61, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=990, ncalls=8721, regioncalls=0, ndraw=40, logz=-5.23, remainder_fraction=82.4132%, Lmin=-2.36, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=1000, ncalls=8846, regioncalls=0, ndraw=40, logz=-5.20, remainder_fraction=81.7602%, Lmin=-2.31, Lmax=-0.04 DEBUG ultranest:integrator.py:2610 iteration=1050, ncalls=9438, regioncalls=0, ndraw=40, logz=-5.02, remainder_fraction=78.0705%, Lmin=-2.09, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1080, ncalls=9801, regioncalls=0, ndraw=40, logz=-4.92, remainder_fraction=75.7277%, Lmin=-2.01, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1100, ncalls=10060, regioncalls=0, ndraw=40, logz=-4.86, remainder_fraction=74.1624%, Lmin=-1.93, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1150, ncalls=10677, regioncalls=0, ndraw=40, logz=-4.72, remainder_fraction=70.3481%, Lmin=-1.79, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1200, ncalls=11350, regioncalls=0, ndraw=40, logz=-4.60, remainder_fraction=66.6382%, Lmin=-1.68, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1250, ncalls=12003, regioncalls=0, ndraw=40, logz=-4.49, remainder_fraction=62.9726%, Lmin=-1.54, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1260, ncalls=12125, regioncalls=0, ndraw=40, logz=-4.47, remainder_fraction=62.2550%, Lmin=-1.50, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1300, ncalls=12647, regioncalls=0, ndraw=40, logz=-4.39, remainder_fraction=59.3069%, Lmin=-1.38, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1350, ncalls=13312, regioncalls=0, ndraw=40, logz=-4.30, remainder_fraction=55.1640%, Lmin=-1.27, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1400, ncalls=14001, regioncalls=0, ndraw=40, logz=-4.21, remainder_fraction=51.3023%, Lmin=-1.18, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1440, ncalls=14526, regioncalls=0, ndraw=40, logz=-4.15, remainder_fraction=48.3174%, Lmin=-1.11, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1450, ncalls=14675, regioncalls=0, ndraw=40, logz=-4.14, remainder_fraction=47.5789%, Lmin=-1.08, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1500, ncalls=15383, regioncalls=0, ndraw=40, logz=-4.07, remainder_fraction=43.7293%, Lmin=-0.99, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1530, ncalls=15811, regioncalls=0, ndraw=40, logz=-4.03, remainder_fraction=41.6883%, Lmin=-0.96, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1550, ncalls=16084, regioncalls=0, ndraw=40, logz=-4.01, remainder_fraction=40.2892%, Lmin=-0.93, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1600, ncalls=16777, regioncalls=0, ndraw=40, logz=-3.96, remainder_fraction=37.0213%, Lmin=-0.86, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1620, ncalls=17068, regioncalls=0, ndraw=40, logz=-3.94, remainder_fraction=35.7910%, Lmin=-0.83, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1650, ncalls=17474, regioncalls=0, ndraw=40, logz=-3.91, remainder_fraction=33.9815%, Lmin=-0.78, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1700, ncalls=18181, regioncalls=0, ndraw=40, logz=-3.87, remainder_fraction=31.1224%, Lmin=-0.72, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1750, ncalls=18873, regioncalls=0, ndraw=40, logz=-3.83, remainder_fraction=28.3121%, Lmin=-0.65, Lmax=-0.02 DEBUG ultranest:integrator.py:2610 iteration=1800, ncalls=19590, regioncalls=0, ndraw=40, logz=-3.79, remainder_fraction=25.6712%, Lmin=-0.61, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1850, ncalls=20308, regioncalls=0, ndraw=40, logz=-3.76, remainder_fraction=23.3453%, Lmin=-0.56, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1890, ncalls=20890, regioncalls=0, ndraw=40, logz=-3.74, remainder_fraction=21.5449%, Lmin=-0.53, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1900, ncalls=21039, regioncalls=0, ndraw=40, logz=-3.73, remainder_fraction=21.1217%, Lmin=-0.52, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1946, ncalls=21688, regioncalls=0, ndraw=40, logz=-3.71, remainder_fraction=19.2455%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1950, ncalls=21739, regioncalls=0, ndraw=40, logz=-3.71, remainder_fraction=19.0872%, Lmin=-0.48, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=1980, ncalls=22164, regioncalls=0, ndraw=40, logz=-3.69, remainder_fraction=17.9575%, Lmin=-0.45, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2000, ncalls=22437, regioncalls=0, ndraw=40, logz=-3.68, remainder_fraction=17.2288%, Lmin=-0.44, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2047, ncalls=23121, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=15.6320%, Lmin=-0.40, Lmax=-0.01 DEBUG ultranest:integrator.py:2610 iteration=2050, ncalls=23176, regioncalls=0, ndraw=40, logz=-3.66, remainder_fraction=15.5371%, Lmin=-0.40, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2070, ncalls=23468, regioncalls=0, ndraw=40, logz=-3.65, remainder_fraction=14.9243%, Lmin=-0.38, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2100, ncalls=23855, regioncalls=0, ndraw=40, logz=-3.64, remainder_fraction=13.9892%, Lmin=-0.36, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2150, ncalls=24513, regioncalls=0, ndraw=40, logz=-3.63, remainder_fraction=12.5203%, Lmin=-0.33, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2179, ncalls=24901, regioncalls=0, ndraw=40, logz=-3.62, remainder_fraction=11.7529%, Lmin=-0.31, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2200, ncalls=25200, regioncalls=0, ndraw=40, logz=-3.61, remainder_fraction=11.2407%, Lmin=-0.30, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2250, ncalls=25854, regioncalls=0, ndraw=40, logz=-3.60, remainder_fraction=10.0608%, Lmin=-0.28, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2299, ncalls=26539, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=9.0080%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2300, ncalls=26553, regioncalls=0, ndraw=40, logz=-3.59, remainder_fraction=8.9903%, Lmin=-0.26, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2340, ncalls=27133, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=8.2171%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2350, ncalls=27278, regioncalls=0, ndraw=40, logz=-3.58, remainder_fraction=8.0294%, Lmin=-0.24, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2400, ncalls=27946, regioncalls=0, ndraw=40, logz=-3.57, remainder_fraction=7.1747%, Lmin=-0.22, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2441, ncalls=28535, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=6.5330%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2450, ncalls=28675, regioncalls=0, ndraw=40, logz=-3.56, remainder_fraction=6.3952%, Lmin=-0.20, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2500, ncalls=29353, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.6963%, Lmin=-0.19, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2520, ncalls=29662, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.4385%, Lmin=-0.18, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2550, ncalls=30099, regioncalls=0, ndraw=40, logz=-3.55, remainder_fraction=5.0740%, Lmin=-0.17, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2591, ncalls=30671, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.6054%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2600, ncalls=30778, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.5081%, Lmin=-0.16, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2640, ncalls=31333, regioncalls=0, ndraw=40, logz=-3.54, remainder_fraction=4.0983%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2650, ncalls=31473, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=4.0025%, Lmin=-0.15, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2698, ncalls=32151, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.5774%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2700, ncalls=32188, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.5598%, Lmin=-0.14, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2750, ncalls=32861, regioncalls=0, ndraw=40, logz=-3.53, remainder_fraction=3.1611%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2795, ncalls=33463, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.8408%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2800, ncalls=33526, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.8080%, Lmin=-0.12, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2844, ncalls=34171, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.5277%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2850, ncalls=34241, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.4920%, Lmin=-0.11, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2880, ncalls=34663, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.3185%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2900, ncalls=34946, regioncalls=0, ndraw=40, logz=-3.52, remainder_fraction=2.2089%, Lmin=-0.10, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2939, ncalls=35496, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=2.0105%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2950, ncalls=35641, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.9576%, Lmin=-0.09, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=2970, ncalls=35916, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.8662%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3000, ncalls=36340, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.7348%, Lmin=-0.08, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3044, ncalls=36948, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.5593%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3050, ncalls=37033, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.5367%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3080, ncalls=37466, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.4286%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3100, ncalls=37717, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.3611%, Lmin=-0.07, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3146, ncalls=38392, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.2164%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3150, ncalls=38452, regioncalls=0, ndraw=40, logz=-3.51, remainder_fraction=1.2047%, Lmin=-0.06, Lmax=-0.00 DEBUG ultranest:integrator.py:2610 iteration=3200, ncalls=39146, regioncalls=0, ndraw=40, logz=-3.50, remainder_fraction=1.0664%, Lmin=-0.06, Lmax=-0.00 INFO ultranest:integrator.py:2654 Explored until L=-0.002 INFO ultranest:integrator.py:2752 Likelihood function evaluations: 39507 DEBUG ultranest:integrator.py:2304 did a run_iter pass! INFO ultranest:integrator.py:2697 logZ = -3.501 +- 0.06405 INFO ultranest:integrator.py:1585 Effective samples strategy satisfied (ESS = 1848.0, need >400) INFO ultranest:integrator.py:1616 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) INFO ultranest:integrator.py:1671 Evidency uncertainty strategy is satisfied (dlogz=0.06, need <0.5) INFO ultranest:integrator.py:1675 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 INFO ultranest:integrator.py:2307 done iterating.

Passed

tests/test_run.py::test_run_resume[2.0]

8.64

Passed

tests/test_samplingpath.py::test_horizontal

0.00

Passed

tests/test_samplingpath.py::test_corner

0.00

Passed

tests/test_stepsampling.py::test_stepsampler_regionmh_adapt

0.25

Passed

tests/test_stepsampling.py::test_ellipsoid_bracket

0.26

Packages	{"pluggy": "0.13.0", "py": "1.10.0", "pytest": "7.1.3"}
Platform	Linux-5.15.0-52-generic-x86_64-with-glibc2.35
Plugins	{"anyio": "3.6.1", "asdf": "2.13.0", "forked": "1.4.0", "html": "3.1.1", "hypothesis": "6.36.0", "metadata": "2.0.2", "typeguard": "2.13.3", "xdist": "2.5.0"}
Python	3.10.6

index.html

Environment

Summary

Results