# RIFT under test: /home/richard.oshaughnessy/rift_O4d_junior_ralph/.claude/worktrees/base-v2/MonteCarloMarginalizeCode/Code/RIFT
# shape_recovery: 32 runs (8 targets x 4 samplers), preset=quick
 - No vegas - 
no multiprocess
 no cupy (mcsamplerGPU)
 no cupy (mcsamplerAV)
 no cupy (mcsamplerPortfolio)
RIFT portfolio plugins: []
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
10000 405.5078325517685 14.041581271706718 - -1.2552660987134865 0.029326396883198342
20010 1508.2830433771187 14.041752629611246 - -1.2555517721906473 0.015363106965444705
30135 2701.8746801371262 14.041887757834852 - -1.2555517721906473 0.011488785722326344
 [AV mc diag] sigma_mc=0.0115 sigma_lnV=0.0158 trunc_p=1.00e-03 khat=-0.897 ESS=5400.4
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.0016255378723144531
integrator iterations:  5
Result  182.97944615464746 95.38897215466109
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 [mc diag] khat=0.381 ESS=8107.9 sigma_block=0.0098 (chunks=5)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f1377c10190> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1376fd1710> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 404.39057734209877, 203.50536261809594], 1: [0.5, 420.15038011607965, 213.53775579716645]}
	 {0: [0.4952815170793957, 1164.499581626134, 579.9782598062495], 1: [0.5047184829206044, 1282.1656052154672, 692.481017893753]}
	 {0: [0.48579915363587445, 1310.4782710549105, 665.8483784650201], 1: [0.5142008463641256, 1540.8733180932725, 837.138598300517]}
	 {0: [0.47302192316955693, 1394.9737424855948, 691.7852004640791], 1: [0.5269780768304431, 1658.083005665521, 906.1465273931137]}
	 {0: [0.4653409818653412, 1433.8822041985184, 722.9093823383027], 1: [0.5346590181346589, 1805.483273660012, 1010.2862759180348]}
  PORTFOLIO support: escaped_mass=[0. 0.] early=[0. 0.] (hard-edged members [0]; max 3.879e-04, early max 0.000e+00)  weight_share=[0.447 0.553]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
10000 171.45924151547894 14.103563175714072 - -2.3025850929940455 0.04440875770272375
20035 1341.3990029588442 14.105092593009411 - -2.3517296157781 0.01573439771090637
30040 2666.80574674158 14.105173959560206 - -2.3517296157781 0.011167215287126598
 [AV mc diag] sigma_mc=0.0112 sigma_lnV=0.0301 trunc_p=1.00e-03 khat=-0.968 ESS=5236.5
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.0037729740142822266
integrator iterations:  10
Result  183.19254618659724 95.36542399037812
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 [mc diag] khat=1.408 ESS=12965.1 sigma_block=0.0084 (chunks=10)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f1376f082d0> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1376749390> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 177.5448987678759, 89.55207612788095], 1: [0.5, 165.17650151336184, 84.84760653916595]}
	 {0: [0.5089397043305469, 1162.8956903739847, 600.9915713603721], 1: [0.49106029566945303, 921.6851992333078, 495.37765253249154]}
	 {0: [0.5329711561745135, 1578.6934963336735, 820.7567435179499], 1: [0.4670288438254865, 1077.8192143794015, 583.6836429823455]}
	 {0: [0.5628714623240679, 1730.2738782744752, 924.6182159088588], 1: [0.437128537675932, 1104.8907639589308, 604.2954201857742]}
	 {0: [0.585639839064502, 1920.15910667202, 1002.7763089856462], 1: [0.41436016093549805, 1038.771847543745, 566.511993263526]}
	 {0: [0.6160134203668732, 2076.440135601993, 1066.0239237213232], 1: [0.3839865796331269, 1069.6298499585373, 593.0061893951683]}
	 {0: [0.6365795373505092, 2175.9748953564144, 1139.5247998702187], 1: [0.36342046264949085, 1068.228521033336, 596.2946025259992]}
	 {0: [0.6520913189732968, 2273.0143296400825, 1193.180983138384], 1: [0.34790868102670325, 995.8856719594488, 554.4918898172995]}
	 {0: [0.6719410866321384, 2401.221817596801, 1242.4273542170629], 1: [0.3280589133678616, 1004.0328828012109, 558.6775171382616]}
	 {0: [0.6866471755804096, 2502.489572987164, 1301.0892388335583], 1: [0.3133528244195905, 1014.886823891199, 577.1080716255299]}
  PORTFOLIO support: escaped_mass=[0.001 0.   ] early=[0. 0.] (hard-edged members [0]; max 5.204e-04, early max 0.000e+00)  weight_share=[0.625 0.375]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
10000 31.819447074032077 14.207972098313473 - -2.3025850929940455 0.08835771400786861
20036 244.2117034656364 14.210078425715949 - -2.7220031005580765 0.031917797533072424
30130 639.375415982063 14.21021726755302 - -2.722263845420707 0.02042000613224233
40247 1067.9896890154914 14.210218357471094 - -2.722263845420707 0.015949291411617203
50291 1499.5155333867363 14.210218357471094 - -2.722263845420707 0.013501237259551241
60396 1942.3478273356657 14.210218357471094 - -2.722263845420707 0.01185664796374099
70476 2380.662791690032 14.210249149610629 - -2.722263845420707 0.010669749554112522
 [AV mc diag] sigma_mc=0.0107 sigma_lnV=0.0312 trunc_p=1.00e-03 khat=-0.897 ESS=7257.3
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.008828401565551758
integrator iterations:  10
Result  184.19700807750687 95.36396115277081
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 [mc diag] khat=0.13 ESS=4371.8 sigma_block=0.0126 (chunks=10)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f1375bf7b90> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1376dc1710> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 51.9723259421829, 14.748448534784451], 1: [0.5, 55.427432218152695, 20.998614742918825]}
	 {0: [0.49192707463236135, 371.8314195271132, 119.36376127158661], 1: [0.5080729253676386, 332.97792324373694, 121.83103241098968]}
	 {0: [0.5095981199902603, 715.2987679579478, 243.24537930735127], 1: [0.49040188000973983, 376.99580634900184, 141.86204388517163]}
	 {0: [0.5811888596830933, 870.7309062246638, 289.44903804658264], 1: [0.4188111403169068, 385.0667030585916, 136.92404015702158]}
	 {0: [0.635785751111682, 982.0434860206842, 334.3832059784413], 1: [0.36421424888831794, 332.55502092514337, 118.10210511881448]}
	 {0: [0.6894115938771643, 1126.5011675775108, 367.30881046158436], 1: [0.31058840612283584, 309.75672733452075, 115.24733726537433]}
	 {0: [0.734473389032334, 1176.3301954909668, 397.90936568218194], 1: [0.26552661096766605, 295.206057259213, 103.69043501081441]}
	 {0: [0.764314471818733, 1306.9061103706952, 411.8514599317506], 1: [0.23568552818126703, 233.86552042573294, 93.27103159271704]}
	 {0: [0.8032316949739701, 1375.211639958176, 451.13782989615083], 1: [0.1967683050260299, 229.99107527807186, 87.11315971680541]}
	 {0: [0.826779361924609, 1447.7486317707805, 470.7680759023719], 1: [0.17322063807539112, 212.722387752275, 72.63656901282289]}
  PORTFOLIO support: escaped_mass=[0. 0.] early=[0. 0.] (hard-edged members [0]; max 4.775e-04, early max 0.000e+00)  weight_share=[0.705 0.295]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
10000 282.90228061878827 14.069983704468804 - -1.606941032235513 0.03391857697232854
20005 1162.8213455983655 14.069983704468804 - -1.606941032235513 0.01645787071884805
30113 2127.8021769238253 14.069983704468804 - -1.606941032235513 0.012202802407077518
 [AV mc diag] sigma_mc=0.0122 sigma_lnV=0.0200 trunc_p=1.00e-03 khat=-0.714 ESS=4692.2
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.0060503482818603516
integrator iterations:  8
Result  183.48538908288538 95.39121872772748
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 [mc diag] khat=-0.17 ESS=9268.4 sigma_block=0.0067 (chunks=8)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f1376763850> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1375c91390> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 296.2610253951537, 139.04537062577708], 1: [0.5, 279.600495815957, 127.87095339115054]}
	 {0: [0.5071497497009275, 990.3307872048276, 414.86868536147415], 1: [0.4928502502990726, 720.909910850529, 301.34537138166445]}
	 {0: [0.5423754473951683, 1295.2587020551941, 554.9477043414095], 1: [0.45762455260483176, 777.0551196109792, 331.57444545226883]}
	 {0: [0.5827238366336385, 1451.8550023157277, 610.4940117862412], 1: [0.41727616336636153, 738.113878870234, 328.4252229978778]}
	 {0: [0.6214918632533081, 1629.7615647227137, 707.6480668029269], 1: [0.3785081367466921, 682.9422643562978, 308.0735997154563]}
	 {0: [0.6613531910827484, 1800.7728976142726, 778.6250560470654], 1: [0.33864680891725163, 618.3285033975036, 270.8751999372255]}
	 {0: [0.7007496821554526, 1940.6756979943145, 836.4344283729793], 1: [0.2992503178445475, 563.1623845668614, 251.22976019545018]}
	 {0: [0.7354711106840421, 2057.0426762093707, 908.114177346755], 1: [0.2645288893159578, 487.33474807656927, 215.93423013433576]}
  PORTFOLIO support: escaped_mass=[0. 0.] early=[0. 0.] (hard-edged members [0]; max 3.778e-04, early max 0.000e+00)  weight_share=[0.677 0.323]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
10000 2.1166036998516646 14.10878870087279 - -2.3025850929940455 0.5587415207624211
20132 3.2645059053429466 14.10878870087279 - -3.641001373869472 0.3851235949100838
30252 9.328002403246321 14.141353307335391 - -4.6731176712492175 0.215323815340953
40431 21.37504601984334 14.14956001586711 - -5.572872434483273 0.1361427727525657
50631 34.358388363239264 14.167645117262165 - -6.247210283085722 0.09054500478058455
60807 67.86369255033544 14.173680089014397 - -6.247653447285308 0.06486358236993159
70835 99.32094617660934 14.173680089014397 - -6.248222923382703 0.051639105049905605
81038 119.57911197277987 14.180351956366422 - -6.248222923382703 0.04458732795102924
91510 155.0990039198797 14.180351956366422 - -6.248222923382703 0.039398087349960906
101875 190.09241163855137 14.180351956366422 - -6.248222923382703 0.036047136109075416
111963 225.76520348463504 14.180351956366422 - -6.248222923382703 0.03324651341128292
122623 259.27198929944046 14.180351956366422 - -6.248222923382703 0.03091841392320598
132991 279.9762144098173 14.183723594101782 - -6.248222923382703 0.029029142917085856
143001 310.3450237022169 14.183723594101782 - -6.248222923382703 0.027424545989686508
153704 347.8415391039465 14.183723594101782 - -6.248222923382703 0.02609891814222508
164114 379.72463439571266 14.183723594101782 - -6.248222923382703 0.025020895626516593
174904 416.8710093163701 14.183723594101782 - -6.248222923382703 0.023964207037525137
185083 455.7068490238235 14.183752169903658 - -6.248222923382703 0.02318405380550132
195478 489.05074998486566 14.183752169903658 - -6.248222923382703 0.022258981314476334
206296 523.5732322490855 14.183752169903658 - -6.248222923382703 0.02149846880610427
 [AV mc diag] sigma_mc=0.0215 sigma_lnV=0.0575 trunc_p=1.00e-03 khat=-0.166 ESS=1965.4
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.010064363479614258
integrator iterations:  20
Result  178.02185556688133 90.81258801139508
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 [mc diag] khat=0.457 ESS=661.3 sigma_block=0.0202 (chunks=20)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f13759d13d0> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f13759d1750> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 1.248295518238638, 1.1254776568671085], 1: [0.5, 2.1816844448208124, 1.5365904502837253]}
	 {0: [0.339253386004392, 2.0863383845343795, 1.5940715258701235], 1: [0.6607466139956081, 53.58090482074, 23.57512119631764]}
	 {0: [0.18372789928558023, 5.409084759820267, 3.393640955341682], 1: [0.8162721007144199, 106.13664576295155, 41.15145548144278]}
	 {0: [0.11620607778951314, 7.9952264673513325, 4.121404135389044], 1: [0.8837939222104869, 132.15944204805925, 48.06684671180827]}
	 {0: [0.08772788187470719, 25.986585268088895, 10.097772503158266], 1: [0.9122721181252927, 157.89875854390195, 60.52029593346723]}
	 {0: [0.11628338350900845, 96.69020360256873, 33.65520682335699], 1: [0.8837166164909915, 152.99977689446433, 57.91204287960293]}
	 {0: [0.2531097596259792, 258.67905895203916, 78.5049828623709], 1: [0.746890240374021, 142.6312475202534, 57.55971235173839]}
	 {0: [0.4487397859401182, 550.1873432839869, 162.9874371422758], 1: [0.5512602140598818, 108.65845435533113, 41.44042464297316]}
	 {0: [0.6400381261044226, 944.9198364331634, 276.2342100560345], 1: [0.35996187389557754, 72.77266782391348, 28.761735878796756]}
	 {0: [0.7811348197272289, 1364.5842051535617, 424.79237492779964], 1: [0.21886518027277116, 45.71722647821901, 14.473663633891162]}
	 {0: [0.8704973878784255, 1723.631603472961, 537.8398990938981], 1: [0.12950261212157457, 28.757678791607454, 13.831076965402488]}
	 {0: [0.9227850570833107, 1922.3878904753471, 595.382446897122], 1: [0.07721494291668916, 19.51980423046243, 10.067061280011234]}
	 {0: [0.9519073529646879, 2217.9695230124858, 682.448378719267], 1: [0.0480926470353122, 16.85241305820879, 10.206703360945713]}
	 {0: [0.9676013079876755, 2349.837363477613, 756.8019080517107], 1: [0.03239869201232444, 10.954550876231199, 6.132793846440526]}
	 {0: [0.9768275221594512, 2573.0829541708786, 859.785502221698], 1: [0.02317247784054883, 14.695371082180486, 7.748935742530275]}
	 {0: [0.9808875946237463, 2678.765514456453, 840.6982380549798], 1: [0.01911240537625367, 10.730006616457821, 6.035851286889501]}
	 {0: [0.9837329978845024, 2653.714501548123, 860.0494712169331], 1: [0.016267002115497666, 7.101239161492894, 3.9972697322682547]}
	 {0: [0.9858016042408616, 2891.55528919115, 940.1978391861014], 1: [0.01419839575913841, 7.277040664870868, 4.805576804570387]}
	 {0: [0.9868937359358537, 3006.085597972147, 1007.846937353592], 1: [0.013106264064146353, 4.857418974428798, 3.1355698104903915]}
	 {0: [0.9878729209263435, 2923.7569929902147, 954.8498635073959], 1: [0.012127079073656427, 4.96209827142928, 2.7734658774577428]}
  PORTFOLIO support: escaped_mass=[0.732 0.   ] early=[0. 0.] (hard-edged members [0]; max 7.321e-01, early max 0.000e+00)  weight_share=[0.115 0.885]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
10000 2.8178328241298303 14.106811134643898 - -2.3025850929940455 0.418250025586683
20044 6.636898307870252 14.106811134643898 - -3.6415257577304656 0.2694494815146293
30244 18.569424515958797 14.106811134643898 - -4.782558762282528 0.1564679285770689
40272 31.39390947753484 14.133217768998176 - -5.8575611853115035 0.0950400613972893
50400 90.75153016851868 14.135386775261454 - -5.874033760938849 0.05430644632152597
60452 148.50633845870107 14.135881649490756 - -5.874033760938849 0.04278003355929685
70704 212.60838557132809 14.135881649490756 - -5.874033760938849 0.035828163495813414
81059 276.7108388335327 14.135881649490756 - -5.874033760938849 0.03122557243214973
91412 340.4338785177663 14.135881649490756 - -5.874033760938849 0.028282600823514373
101642 364.0198165794389 14.142809716495856 - -5.874033760938849 0.02601678783062935
111890 424.8914651771721 14.142809716495856 - -5.874033760938849 0.024176556816571906
122056 484.99681967482445 14.142809716495856 - -5.874033760938849 0.0226003522331087
132846 539.2465888770378 14.14352107566793 - -5.874033760938849 0.02131653037709023
143490 597.0895719339081 14.14352107566793 - -5.874033760938849 0.020273272673902575
154386 666.0059896139865 14.14352107566793 - -5.874033760938849 0.019326677716182527
164781 727.8723848155978 14.14352107566793 - -5.874033760938849 0.018476723369639025
175748 793.8863446881805 14.14352107566793 - -5.874033760938849 0.01772267842643432
186008 851.2112624839925 14.14352107566793 - -5.874033760938849 0.017076297877889834
196628 911.9729823975033 14.14352107566793 - -5.874033760938849 0.016499163685447564
207568 974.5351768847711 14.14352107566793 - -5.874033760938849 0.015937709768956476
 [AV mc diag] sigma_mc=0.0159 sigma_lnV=0.0546 trunc_p=1.00e-03 khat=-0.28 ESS=3553.0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.0076084136962890625
integrator iterations:  20
Result  177.97393602102287 90.83017502558896
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 [mc diag] khat=0.297 ESS=1007.4 sigma_block=0.0436 (chunks=20)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f13760fd910> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1375e5d850> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 3.2229506800456402, 1.9355493777516504], 1: [0.5, 4.929045834021777, 3.2827185845351945]}
	 {0: [0.431703836171015, 5.724915900075073, 3.1299777750167848], 1: [0.5682961638289852, 48.72026864358284, 19.710710626418305]}
	 {0: [0.2641270524992567, 15.203843836619749, 6.616319734180189], 1: [0.7358729475007432, 94.52715481924848, 36.61256976793132]}
	 {0: [0.2013204303019922, 46.27506611028839, 20.11193104504678], 1: [0.7986795696980078, 121.41226001309323, 36.76455191202447]}
	 {0: [0.23972334865111125, 172.43762301138156, 52.32666705208731], 1: [0.7602766513488888, 126.99272259967736, 27.916166559691472]}
	 {0: [0.4081369455614514, 429.1114975766229, 130.42773810903947], 1: [0.5918630544385485, 85.72695630460859, 27.240108860434518]}
	 {0: [0.6191926759012649, 738.5060624995527, 218.11132567553324], 1: [0.3808073240987352, 35.6840682816515, 11.28663701806526]}
	 {0: [0.7834454494391462, 1030.499638541244, 280.2195711612294], 1: [0.21655455056085382, 23.824908985569103, 9.017061012829894]}
	 {0: [0.8766031638161738, 1240.2597705755363, 350.76594557234114], 1: [0.12339683618382631, 13.46033990898554, 4.985243123910596]}
	 {0: [0.928730415919203, 1492.2969487529986, 438.2176649450233], 1: [0.07126958408079706, 21.433633543062328, 11.357468007228611]}
	 {0: [0.9529098839255886, 1628.8652135545544, 478.48110676722155], 1: [0.04709011607441142, 9.284164039696401, 5.735858740927055]}
	 {0: [0.9691031384852762, 1660.7101436048717, 458.0950568820307], 1: [0.030896861514723702, 10.188097385996098, 5.418576348366525]}
	 {0: [0.9769416450072074, 2048.1855767286247, 589.4461131483129], 1: [0.023058354992792712, 5.759946405628074, 3.2041914110916707]}
	 {0: [0.9824105067997392, 1967.740894952566, 577.3534414829284], 1: [0.017589493200260764, 4.000175011007909, 2.5852406530441283]}
	 {0: [0.9855236847978116, 1997.8324407837415, 613.7267064524941], 1: [0.01447631520218847, 5.074231196920942, 2.666087763281335]}
	 {0: [0.9868198279621364, 2095.0999993465853, 609.9328191157805], 1: [0.013180172037863532, 4.366919336088007, 2.8906413813650795]}
	 {0: [0.9876769398385246, 2080.9025960127187, 596.9447376851235], 1: [0.012323060161475562, 5.0751937735607, 3.4704717473540763]}
	 {0: [0.9879308490632657, 2203.0532366966154, 644.3245156773512], 1: [0.012069150936734456, 6.412134299736653, 3.833441151409804]}
	 {0: [0.9878127487811384, 2274.5530690720357, 679.1439191091749], 1: [0.012187251218861479, 3.430703581190969, 2.0941101816490812]}
	 {0: [0.9884355468971764, 2543.8823905320114, 745.8699702669833], 1: [0.011564453102823693, 7.44295995122474, 4.066419772321259]}
  PORTFOLIO support: escaped_mass=[0.389 0.   ] early=[0. 0.] (hard-edged members [0]; max 3.888e-01, early max 0.000e+00)  weight_share=[0.428 0.572]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
10000 4.654321405166974 13.988356785322358 - -2.3025850929940455 0.34580594000190723
20050 9.258681889522418 14.037186958353475 - -3.5579161895951237 0.18493313267509034
30167 7.66463844118878 14.151979705175876 - -4.7344150169203045 0.18035327572325632
40310 20.449456391967576 14.169994578519773 - -4.9101931925237325 0.10289436933352308
50550 28.586966557435268 14.189128986741126 - -4.910614866575943 0.07673452474672303
60570 38.93282909432903 14.196954453698215 - -4.910614866575943 0.06467603212059274
70674 50.911106019982725 14.196954453698215 - -4.910614866575943 0.05818808259943886
81102 64.59066486677915 14.196954453698215 - -4.910614866575943 0.05187536186667367
91462 77.57399075182056 14.196954453698215 - -4.910614866575943 0.047908500713776364
101614 90.03903884897062 14.196954453698215 - -4.910614866575943 0.044319853366687555
111678 100.53867176841253 14.196954453698215 - -4.910614866575943 0.04125462270603144
122062 112.50028777844122 14.197980189533084 - -4.910614866575943 0.03945010405629966
132187 124.37075724935244 14.197980189533084 - -4.910614866575943 0.036660348691862805
142672 137.87634574629726 14.197980189533084 - -4.910614866575943 0.034707721339066154
153046 151.50287371352752 14.197980189533084 - -4.910614866575943 0.03295379633099876
163672 155.88676272372882 14.202439862883038 - -4.910614866575943 0.03168707773711685
173864 156.57154018585163 14.207692401654008 - -4.910614866575943 0.030585608998772416
184459 169.9892470184039 14.207692401654008 - -4.910614866575943 0.029467700415981464
194503 180.83155211926666 14.207692401654008 - -4.910614866575943 0.028051270045501217
204955 193.37144359736385 14.207692401654008 - -4.910614866575943 0.02736405702203732
 [AV mc diag] sigma_mc=0.0274 sigma_lnV=0.0487 trunc_p=1.00e-03 khat=0.781 ESS=1293.4
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.020084857940673828
integrator iterations:  20
Result  178.4055563189518 90.70626477991523
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 [mc diag] khat=0.784 ESS=397.3 sigma_block=0.0605 (chunks=20)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f137607e050> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f13744e9610> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 5.3232353535111985, 2.8318706422294753], 1: [0.5, 7.981691692974874, 4.317471741880317]}
	 {0: [0.4420876871680066, 10.931135166205015, 4.879967388702239], 1: [0.5579123128319935, 13.240803085435248, 3.800406294214491]}
	 {0: [0.4455339080316621, 42.18070089658118, 13.437826808567078], 1: [0.554466091968338, 11.153366133578782, 4.872062681137628]}
	 {0: [0.6217521335541101, 78.60114305246026, 15.74936504846441], 1: [0.37824786644588987, 6.091055331206363, 2.546657942302334]}
	 {0: [0.7765181417778043, 137.50740020760304, 27.272441187136355], 1: [0.2234818582221957, 30.000603602778448, 6.462846998834879]}
	 {0: [0.7975366169598972, 137.72140528730847, 27.343655795578087], 1: [0.20246338304010286, 27.55189607980161, 8.491320160636752]}
	 {0: [0.8141992244922207, 179.5400624989656, 30.024113623611782], 1: [0.18580077550777924, 4.389715517884242, 2.5334914766178187]}
	 {0: [0.893409723915284, 338.02315597536176, 30.05675614163942], 1: [0.10659027608471605, 20.36151057651219, 9.718564888329606]}
	 {0: [0.9152365353843483, 401.962475369205, 52.268678461794096], 1: [0.08476346461565173, 17.077288575492698, 6.477143282402219]}
	 {0: [0.9338662051551552, 340.63599126039986, 41.959998209699286], 1: [0.06613379484484477, 24.627452931685536, 10.028928861794949]}
	 {0: [0.9300867805715395, 317.5759792908852, 45.79134095823356], 1: [0.0699132194284606, 12.715513505250966, 5.4368075590056755]}
	 {0: [0.9426653378501819, 459.97269189264847, 44.3481510420348], 1: [0.057334662149817944, 3.6926355229120817, 1.962575304661153]}
	 {0: [0.9636274735422092, 659.8359866135735, 41.87138188250769], 1: [0.03637252645779068, 19.184071103293938, 9.150233895407297]}
	 {0: [0.9637000393442082, 787.9528114781957, 55.51651334508068], 1: [0.03629996065579181, 17.437972175202052, 8.44415727677497]}
	 {0: [0.9668875144244687, 1049.4604681584365, 59.07188266331073], 1: [0.03311248557553122, 15.85234529919747, 6.603667098423485]}
	 {0: [0.9716712447495561, 883.9505135912624, 49.849359825317], 1: [0.028328755250443798, 17.666173694896628, 7.517762959678945]}
	 {0: [0.9718062897349808, 843.3299515244514, 68.53034907604707], 1: [0.02819371026501918, 33.61279718661753, 17.17612017335167]}
	 {0: [0.9626392162882289, 797.6482639567147, 62.75511900935909], 1: [0.03736078371177119, 30.429226581281146, 13.69747787725144]}
	 {0: [0.9588906504722623, 1131.37125177585, 65.94339287016473], 1: [0.04110934952773771, 36.99935527334983, 17.289483896285308]}
	 {0: [0.9593705831549305, 1380.9077486788628, 102.6535442621201], 1: [0.04062941684506938, 44.223303406917054, 20.903703043292587]}
  PORTFOLIO support: escaped_mass=[0.237 0.   ] early=[0. 0.] (hard-edged members [0]; max 2.368e-01, early max 0.000e+00)  weight_share=[0.577 0.423]
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
10000 4.152611788172848 14.065534562729912 - -2.3025850929940455 0.324217562024852
20074 10.447034945162336 14.065534562729912 - -3.5403794457954922 0.1897914057866351
30139 31.236757414389245 14.072191660606862 - -4.611648258790916 0.10004443754782794
40159 84.65132754220016 14.072191660606862 - -4.612343669111014 0.05694874392687903
50419 112.89993517566796 14.084321798665568 - -4.612552415589175 0.044389586556079046
60517 153.48659901479346 14.084321798665568 - -4.612856505602161 0.037733608694803245
70573 199.8494973376436 14.084321798665568 - -4.612856505602161 0.03267153838280504
80649 240.51857745523438 14.086245092413563 - -4.612856505602161 0.02977148571448821
90876 285.73443800293717 14.086245092413563 - -4.612856505602161 0.027069882498919628
100946 321.3530180388238 14.088182096916443 - -4.612856505602161 0.02517584391507103
111278 369.6931999026329 14.088182096916443 - -4.612856505602161 0.023481141947943117
121733 424.6839113982268 14.088182096916443 - -4.612856505602161 0.022246804145413357
131877 472.24977554020944 14.088182096916443 - -4.612856505602161 0.02100201295018492
142373 522.4622878245692 14.088468146421286 - -4.612856505602161 0.019946775598064726
152648 573.8509752023142 14.088468146421286 - -4.612856505602161 0.01893429222749329
163193 627.3271574368105 14.088468146421286 - -4.612856505602161 0.018155090422616125
173539 674.2436885584109 14.088468146421286 - -4.612856505602161 0.017491889893707497
184263 723.1379554072879 14.088468146421286 - -4.612856505602161 0.016869603453262792
194987 776.6235611299687 14.088468146421286 - -4.612856505602161 0.016221635517802972
205452 831.0850386974821 14.088468146421286 - -4.612856505602161 0.015699312719243415
 [AV mc diag] sigma_mc=0.0157 sigma_lnV=0.0476 trunc_p=1.00e-03 khat=-0.114 ESS=3679.2
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
 ==> input assumed as lnL 
 ==> internal calculations and return values are lnI 
cumulative eval time:  0.020583629608154297
integrator iterations:  20
Result  177.55758789352998 90.80067203364804
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 [mc diag] khat=0.376 ESS=1248.0 sigma_block=0.0198 (chunks=20)
 Adding parameter  x0  with limits  [-5.0, 5.0]
   Adapting  x0
 mcsampler: Adding parameter  x0  with limits  [-5.0, 5.0]
 Adding parameter  x1  with limits  [-5.0, 5.0]
   Adapting  x1
 mcsampler: Adding parameter  x1  with limits  [-5.0, 5.0]
 Adding parameter  x2  with limits  [-5.0, 5.0]
   Adapting  x2
 mcsampler: Adding parameter  x2  with limits  [-5.0, 5.0]
 Adding parameter  x3  with limits  [-5.0, 5.0]
   Adapting  x3
 mcsampler: Adding parameter  x3  with limits  [-5.0, 5.0]
 PORTFOLIO setup  <RIFT.integrators.mcsamplerAdaptiveVolume.MCSampler object at 0x7f1376c4fe10> {}
 PORTFOLIO setup  <RIFT.integrators.mcsamplerEnsemble.MCSampler object at 0x7f1376c07f10> {}
 mcsamplerEnsemble: setup() called without n_comp; defaulting n_comp=1 (n_comp=None previously disabled GMM training silently; pass n_comp=0 to disable adaptation)
	 {0: [0.5, 6.614685526123144, 3.2104056934069845], 1: [0.5, 4.3605001410842235, 2.8372317126992663]}
	 {0: [0.5618522253853325, 20.491602004190412, 6.408057773342241], 1: [0.4381477746146675, 46.91531304958152, 16.646305913041175]}
	 {0: [0.43128228436914007, 49.822878642459045, 18.157017095989794], 1: [0.5687177156308599, 73.73081037414637, 21.238735093054743]}
	 {0: [0.4173744384588678, 176.14375047750522, 41.565777689052396], 1: [0.5826255615411323, 54.10426018917899, 11.416006484834433]}
	 {0: [0.5905675124495153, 440.0785573115516, 102.42180553967029], 1: [0.40943248755048467, 69.7378838673712, 24.722971785568703]}
	 {0: [0.7246574149845203, 681.3868820506339, 169.155304345117], 1: [0.27534258501547976, 27.50836748965617, 8.831514786231121]}
	 {0: [0.8395685080597443, 896.6674838927986, 193.8014469999679], 1: [0.1604314919402558, 19.67915894650428, 6.790913263219432]}
	 {0: [0.9051461836058894, 1086.333959081652, 265.61433912282985], 1: [0.09485381639411058, 5.006964473718641, 2.4287423279953577]}
	 {0: [0.9460222033129541, 1170.497251012354, 262.5516161912825], 1: [0.0539777966870461, 5.2773286896865645, 2.9364114131677104]}
	 {0: [0.9663754049393039, 1303.092442412304, 287.3181120567953], 1: [0.03362459506069605, 3.853490289686548, 2.450773048081185]}
	 {0: [0.9772192032228765, 1416.7167754830296, 336.64512298842783], 1: [0.02278079677712362, 7.047518512200104, 4.952298782287762]}
	 {0: [0.9815961231461817, 1469.1136627394724, 337.8351815472668], 1: [0.018403876853818182, 5.866944859055205, 3.918816917465496]}
	 {0: [0.9842413021617183, 1586.8128109366335, 405.2503880239854], 1: [0.015758697838281707, 2.5480435600958535, 1.9956201909777809]}
	 {0: [0.9867043897724639, 1625.1972862369262, 378.9465246045593], 1: [0.013295610227536137, 3.475678289130355, 2.5682353128420434]}
	 {0: [0.987660538092123, 1778.7187561638418, 416.9417683769747], 1: [0.012339461907877028, 5.47583229156436, 3.130497622139025]}
	 {0: [0.9876488736779572, 1805.283981990615, 400.28342434168457], 1: [0.01235112632204294, 1.7934259618352553, 1.4008066291680346]}
	 {0: [0.9886635407370604, 1793.622960997514, 426.7313191854827], 1: [0.01133645926293954, 4.4258270542596305, 2.835231957569954]}
	 {0: [0.988445368510721, 2051.866127278426, 488.71650815502176], 1: [0.011554631489278936, 5.316905703446095, 3.5817894993707897]}
	 {0: [0.9882417296143949, 2039.524149922142, 483.31830713134076], 1: [0.011758270385605044, 5.194717875479852, 2.907788041617261]}
	 {0: [0.9881635657674138, 2062.2691201137536, 451.7688224296245], 1: [0.011836434232586257, 2.8949187368585445, 1.8083690293180652]}
  PORTFOLIO support: escaped_mass=[0.322 0.   ] early=[0. 0.] (hard-edged members [0]; max 3.218e-01, early max 0.000e+00)  weight_share=[0.568 0.432]

sampler    target               n_eff     n_ESS   JSmax  |pull| widthdev lnZbias  verdict
AV         mix_d2_n1_s101        2702      5400  0.0002   0.010    0.002  -0.003  PASS
GMM        mix_d2_n1_s101        2050      9797  0.0005   0.023    0.009  -0.006  PASS
AC         mix_d2_n1_s101        2058      8108  0.0002   0.010    0.006  -0.000  PASS
portfolio  mix_d2_n1_s101        2033      9416  0.0002   0.010    0.004  -0.011  PASS
AV         mix_d2_n1_s202        2667      5237  0.0005   0.024    0.011  +0.021  PASS
GMM        mix_d2_n1_s202        1674     15814  0.0001   0.007    0.004  -0.006  PASS
AC         mix_d2_n1_s202        1657     12965  0.0003   0.010    0.008  +0.006  PASS
portfolio  mix_d2_n1_s202        1673     16170  0.0002   0.004    0.001  -0.003  PASS
AV         mix_d2_n2_s101        2381      7257  0.0002   0.008    0.003  -0.016  PASS
GMM        mix_d2_n2_s101         381      6418  0.0004   0.014    0.009  -0.031  PASS
AC         mix_d2_n2_s101         415      4372  0.0006   0.004    0.004  +0.005  PASS
portfolio  mix_d2_n2_s101         394      6865  0.0002   0.001    0.004  -0.009  PASS
AV         mix_d2_n2_s202        2128      4692  0.0010   0.008    0.003  -0.008  PASS
GMM        mix_d2_n2_s202        2206     10289  0.0003   0.009    0.002  -0.001  PASS
AC         mix_d2_n2_s202        2218      9268  0.0004   0.005    0.001  +0.001  PASS
portfolio  mix_d2_n2_s202        2197     13391  0.0003   0.008    0.002  -0.007  PASS
AV         mix_d4_n1_s101         524      1965  0.0018   0.018    0.007  -0.161  PASS
GMM        mix_d4_n1_s101          33       732  0.0036   0.029    0.020  +0.023  STARVED  [n_eff=33 < 100: shape untestable at this budget]
AC         mix_d4_n1_s101          72       661  0.0047   0.075    0.022  +0.052  STARVED  [n_eff=72 < 100: shape untestable at this budget]
portfolio  mix_d4_n1_s101          39       280  0.0158   0.119    0.037  +0.046  STARVED  [n_eff=39 < 100: shape untestable at this budget]
AV         mix_d4_n1_s202         975      3553  0.0005   0.015    0.011  -0.265  FAIL  [lnZ bias -0.265 > 0.228]
GMM        mix_d4_n1_s202          34       795  0.0015   0.028    0.029  +0.041  STARVED  [n_eff=34 < 100: shape untestable at this budget]
AC         mix_d4_n1_s202          96      1007  0.0025   0.031    0.022  -0.042  STARVED  [n_eff=96 < 100: shape untestable at this budget]
portfolio  mix_d4_n1_s202          33       324  0.0088   0.072    0.062  +0.009  STARVED  [n_eff=33 < 100: shape untestable at this budget]
AV         mix_d4_n2_s101         193      1293  0.0025   0.042    0.016  -0.129  PASS
GMM        mix_d4_n2_s101          42       404  0.0205   0.123    0.099  -0.083  STARVED  [n_eff=42 < 100: shape untestable at this budget]
AC         mix_d4_n2_s101          76       397  0.0107   0.036    0.097  -0.041  STARVED  [n_eff=76 < 100: shape untestable at this budget]
portfolio  mix_d4_n2_s101          76       680  0.0421   0.390    0.275  -0.348  STARVED  [n_eff=76 < 100: shape untestable at this budget]
AV         mix_d4_n2_s202         831      3679  0.0005   0.008    0.005  -0.020  PASS
GMM        mix_d4_n2_s202          60      1134  0.0039   0.020    0.020  +0.012  STARVED  [n_eff=60 < 100: shape untestable at this budget]
AC         mix_d4_n2_s202         121      1248  0.0030   0.061    0.021  -0.025  PASS
portfolio  mix_d4_n2_s202          36       294  0.0105   0.085    0.068  -0.024  STARVED  [n_eff=36 < 100: shape untestable at this budget]
# strict failures: 1   warn-only failures: 0   starved (non-blocking): 11
