bayesian_listener/__init__.py,sha256=MmaDMRTrreY944RVLZptmcSN_Uvdt3GRCKIaA8YPwvY,568
bayesian_listener/auditory_representation.py,sha256=VKcl_pZcDI8t9G4Fps7RRi5X5F90b0Ji1LOR3KAonFg,7935
bayesian_listener/bayesian_listener.py,sha256=Hyb_hRDIBNJAxdwgFi2UU01sewFpuYMIxB47QnqO_RM,37636
bayesian_listener/fitting.py,sha256=yfY9EmI3ZKwlR0tX32hSpk4ZkuyTs7bVN6uc7LTSzqk,33202
bayesian_listener/metrics.py,sha256=3xrA1dfab7_LbmT4ZdBWiyzZKCvCWaPYkkVUYhyBt8g,26982
bayesian_listener/plotting.py,sha256=4jNISz4hRBdcRfnhZIjlFwnSAVvos8L479cqkEHgN1Y,4791
bayesian_listener/resample.py,sha256=JBo-EUQ5OkPmeI904BB29JWwYpwIrbl_x7cVW4B6Hk0,24053
bayesian_listener/utils.py,sha256=XQPKkuG5HMA4CgiC8c8EuMd7VuXFAypbOF5P52ANyw0,48470
bayesian_listener-0.2.0.dist-info/licenses/LICENSE,sha256=b8nnCcy_4Nd_v_okJ6mDKCvi64jkexzbSfIag7TR5mU,13827
docs/Makefile,sha256=2d6bx554aHY-OPqVivIxeKLNEFelFosu3m5gnkFwt2o,712
docs/background.rst,sha256=g8Flim8E3h3JM22PUdejzJaIdxGOx6FabF8sVqdch2c,10309
docs/conf.py,sha256=f06GzCBkBWjBkgAg_oCUdCH8eNDnLvdCKsTCXnbdM6A,6433
docs/getting_started.rst,sha256=66NDv2-Yvu6-OLaJPQ_TrF9Q0uxRQoRWEfhIUY1IHW8,2737
docs/index.rst,sha256=K7gvAi5XqH_g20PYEifnVynkkhBvJrEf6m-U5lr06U0,4106
docs/make.bat,sha256=6o6A_97Nfwa2i6VkbvGPmtvl6zyLcYLtgGPYquRE8Z4,815
docs/_static/favicon.png,sha256=8nJN1fK00mUAYoe9lEoxIswTVwzJkLtZsXNLs4Ly7NM,211392
docs/api/bayesian_listener.rst,sha256=wuIxfUQn6RteBcwQyRQkFK8ALDTZtRDrnnBzGO1xpTs,581
docs/api/fitting.rst,sha256=Cv8xtgKz-bZx5WTg3LsLfeFFORoDLCvPWYJysVGHLao,1071
docs/api/index.rst,sha256=zNyDWH1ZolkccIUxDXCdajou2TMyk-QcBY-s1wHjX38,578
docs/api/metrics.rst,sha256=pcmxGP1n-3bo3qCH8Es0PQ9yU1dpLRKD-ZJU9OjNexU,1103
docs/api/plotting.rst,sha256=vKDv3baAUPnjLiLuugarFE9U6LVEUf_EP2NUkaRNRLo,215
docs/api/resample.rst,sha256=1iw5zChZeA7yc6zohXhgcUdj1SMS6O9ZE81au-Q0EH0,928
docs/api/utils.rst,sha256=NCdkdj7QdgRO1qiSUWSJdZM8NyS7FConjRwxW42EAz4,1140
docs/guides/compare_interpolation.rst,sha256=UQLNndConajSCokvmC_gIBJKPB1EtcjZ6VD_vBD94wA,2264
docs/guides/fit_model.rst,sha256=9j4JuYmpIvmv-XB5VBUX4HSx4F8ZjI0oq2aZWszdriM,3378
docs/guides/index.rst,sha256=NNbbs8_TjRcBDCMsljKUvvIgi4PSYFO9wdLY0bfRAQk,649
docs/guides/simulate_responses.rst,sha256=KlHUPWpAG2hTfkRsw49hx_I3_LV4IwWLG9NeQJUsETE,2726
docs/guides/understand.rst,sha256=SCEvuHYgHl-YM7BGKwNLFOwKWnhQQQ2I9JCzpymIrUE,8265
tests/__init__.py,sha256=dEx6S6F0JF_fipPU6NKGvwI2ZHokgZ-hV5it5iDZOKY,47
tests/test_bayesian_listener.py,sha256=GHn10oeckCThAQzuu-qm-g0aR9b-t12jGSVXrQqmZYM,17431
tests/test_fitting.py,sha256=n6fLVxgYcpTC9W4ZpXrDtuCn708b1HOYwH8CU5UpZd0,7390
tests/test_guide_compare_interpolation.py,sha256=QvHOfDNnyxNeGfnRFHcQpGbmUYlwIAxMiMKyEVUYIbQ,1901
tests/test_guide_fit_model.py,sha256=OlAKZ8KtIjuhpvm0a_VcI2sVlc8fD0SN7HB-IMEoJ8s,2208
tests/test_guide_simulate.py,sha256=5HeEf37B6VmUUqFpbwBbhrRYycRcdgF7esXBJ8Xl-Js,1373
tests/test_guide_understand.py,sha256=xyl_ndGYaMn3spgKDbvnRVkVN0BhEvRkaz3G5nKN8l4,4403
tests/test_imports.py,sha256=uM9d1YF-d5KD9SnRTRA81SV6xwYjgKfT0CFpEB2_XRQ,1160
tests/test_metrics.py,sha256=3Jwg2pEz1TvustTQwYr3mdy2r-c1Ns3GhqGdQUqAUdc,43471
tests/test_normalisation.py,sha256=zWEQv5DfrDiEiwaH0hmh9z824vui8yvnu0iI8vO17Z0,10325
tests/test_resample.py,sha256=S7T9h6hvuaUgpDNo4ltAPNlNf__DLLwDgjcd6uxGXYY,5203
tests/test_utils.py,sha256=ByTEMAtQ3QYtcOF2QRCcq_VD5GJVB3byVsBMzupWgGI,7179
bayesian_listener-0.2.0.dist-info/METADATA,sha256=5Dor-MdU7nweyWn6TV1fRCKrTj2PV_NZIqUjjVVeJ7w,22461
bayesian_listener-0.2.0.dist-info/WHEEL,sha256=YVMoNqKzERt-wjUZwJ33xBGAwnFl-4cqbYkTtWa4itE,91
bayesian_listener-0.2.0.dist-info/top_level.txt,sha256=ta7umzlMKCeErw4Zm1aOw5ddf_To81zFoAMU535c1Lk,29
bayesian_listener-0.2.0.dist-info/RECORD,,
