benda/nonlinearbaseline2025
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cleaned up for new data

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This commit is contained in:
Jan Benda
2025-05-24 23:23:38 +02:00
parent df3ec149fb
commit 223ad8bd4b
410 changed files with 692 additions and 716 deletions
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32
dataoverview.py
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@@ -248,6 +248,7 @@ if __name__ == '__main__':
punit_model = TableData(data_path /
'Apteronotus_leptorhynchus-Punit-models.csv',
sep=';')
print(punit_model.keys())
punit_model = punit_model[punit_model['contrast'] > 1e-6, :]
punit_data = TableData(data_path /
'Apteronotus_leptorhynchus-Punit-data.csv',
@@ -275,8 +276,8 @@ if __name__ == '__main__':
print(f' response modulation model: min={np.min(rmmodel):3.0f}Hz max={np.max(rmmodel):3.0f}Hz median={np.median(rmmodel):3.0f}Hz')
print(f' response modulation data: min={np.min(rmdata):3.0f}Hz max={np.max(rmdata):3.0f}Hz median={np.median(rmdata):3.0f}Hz')
print()
simodel = punit_model['dnli100']
sidata = punit_data['si' + si]
simodel = punit_model['dsinorm100']
sidata = punit_data['sinorm' + si]
u, p = mannwhitneyu(simodel, sidata)
print('SI does not differ between P-unit models and data:')
print(f' U={u:g}, p={p:.2g}')
@@ -290,36 +291,39 @@ if __name__ == '__main__':
fig.subplots_adjust(leftm=6.5, rightm=13.5, topm=4.5, bottomm=4,
wspace=1.1, hspace=0.6)
si_stats('P-unit model:', punit_model, 'dnli100', si_thresh, 'nsegs100')
si_stats('P-unit model:', punit_model, 'dsinorm100', si_thresh,
'nsegs100')
axs[0, 0].text(0, 1.35, 'P-unit models',
transform=axs[0, 0].transAxes, color=s.model_color1)
plot_cvbase_si_punit(axs[0, 0], punit_model, 'dnli100', si_thresh,
plot_cvbase_si_punit(axs[0, 0], punit_model, 'dsinorm100', si_thresh,
s.model_color2)
plot_rmod_si_punit(axs[0, 1], punit_model, 'dnli100', si_thresh,
plot_rmod_si_punit(axs[0, 1], punit_model, 'dsinorm100', si_thresh,
s.model_color2)
plot_cvstim_si_punit(axs[0, 2], punit_model, 'dnli100', si_thresh,
plot_cvstim_si_punit(axs[0, 2], punit_model, 'dsinorm100', si_thresh,
s.model_color2)
print()
si_stats('P-unit data:', punit_data, 'si' + si, si_thresh, 'nsegs' + si)
si_stats('P-unit data:', punit_data, 'sinorm' + si, si_thresh,
'nsegs' + si)
axs[1, 0].text(0, 1.35, 'P-unit data',
transform=axs[1, 0].transAxes, color=s.punit_color1)
plot_cvbase_si_punit(axs[1, 0], punit_data, 'si' + si, si_thresh,
plot_cvbase_si_punit(axs[1, 0], punit_data, 'sinorm' + si, si_thresh,
s.punit_color2)
plot_rmod_si_punit(axs[1, 1], punit_data, 'si' + si, si_thresh,
plot_rmod_si_punit(axs[1, 1], punit_data, 'sinorm' + si, si_thresh,
s.punit_color2)
plot_cvstim_si_punit(axs[1, 2], punit_data, 'si' + si, si_thresh,
plot_cvstim_si_punit(axs[1, 2], punit_data, 'sinorm' + si, si_thresh,
s.punit_color2)
print()
si_stats('Ampullary data:', ampul_data, 'si' + si, si_thresh, 'nsegs' + si)
si_stats('Ampullary data:', ampul_data, 'sinorm' + si, si_thresh,
'nsegs' + si)
axs[2, 0].text(0, 1.35, 'Ampullary data',
transform=axs[2, 0].transAxes, color=s.ampul_color1)
plot_cvbase_si_ampul(axs[2, 0], ampul_data, 'si' + si, si_thresh,
plot_cvbase_si_ampul(axs[2, 0], ampul_data, 'sinorm' + si, si_thresh,
s.ampul_color2)
plot_rmod_si_ampul(axs[2, 1], ampul_data, 'si' + si, si_thresh,
plot_rmod_si_ampul(axs[2, 1], ampul_data, 'sinorm' + si, si_thresh,
s.ampul_color2)
plot_cvstim_si_ampul(axs[2, 2], ampul_data, 'si' + si, si_thresh,
plot_cvstim_si_ampul(axs[2, 2], ampul_data, 'sinorm' + si, si_thresh,
s.ampul_color2)
print()