benda/nonlinearbaseline2025
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added data for example cells

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Jan Benda
2025-05-16 09:04:04 +02:00
parent 923982d43f
commit 5c2ee9f7b2
141 changed files with 425 additions and 40 deletions
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29
ampullaryexamplecell.py
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@@ -1,5 +1,3 @@
import sys
sys.path.insert(0, 'ephys') # for analysing data
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
@@ -13,9 +11,14 @@ cell_name = '2012-05-15-ac'
run1 = 3 # 4
run2 = 1
base_path = Path('ephys')
data_path = base_path / 'data'
results_path = base_path / 'results'
example_cells = [
['2010-11-26-an', 0],
['2011-10-25-ac', 0],
['2011-02-18-ab', 1],
['2014-01-16-aj', 5],
]
data_path = Path('data')
def plot_isih(ax, s, rate, cv, isis, pdf):
@@ -152,13 +155,13 @@ if __name__ == '__main__':
"""
print('Example Ampullary cell:', cell_name)
eodf, rate, cv, isis, pdf, freqs, prr = load_baseline(results_path, cell_name)
eodf, rate, cv, isis, pdf, freqs, prr = load_baseline(data_path, cell_name)
print(f' baseline firing rate: {rate:.0f}Hz')
print(f' baseline firing CV : {cv:.2f}')
contrast1, time1, stimulus1, spikes1 = load_noise(data_path, cell_name, run1)
contrast2, time2, stimulus2, spikes2 = load_noise(data_path, cell_name, run2)
fcutoff1, contrast1, freqs1, gain1, chi21 = load_spectra(results_path, cell_name, run1)
fcutoff2, contrast2, freqs2, gain2, chi22 = load_spectra(results_path, cell_name, run2)
fcutoff1, contrast1, freqs1, gain1, chi21 = load_spectra(data_path, cell_name, run1)
fcutoff2, contrast2, freqs2, gain2, chi22 = load_spectra(data_path, cell_name, run2)
s = plot_style()
s.cell_color1 = s.ampul_color1
@@ -201,15 +204,9 @@ if __name__ == '__main__':
fig.tag([axg, axc1, axc2, axd], xoffs=-3, yoffs=2)
print('Additional example cells:')
example_cells = [
['2010-11-26-an', 0],
['2011-10-25-ac', 0],
['2011-02-18-ab', 1],
['2014-01-16-aj', 5],
]
for k, (cell, run) in enumerate(example_cells):
eodf, rate, cv, _, _, _, _ = load_baseline(results_path, cell)
fcutoff, contrast, freqs, gain, chi2 = load_spectra(results_path, cell, run)
eodf, rate, cv, _, _, _, _ = load_baseline(data_path, cell)
fcutoff, contrast, freqs, gain, chi2 = load_spectra(data_path, cell, run)
dfreqs, diag = diag_projection(freqs, chi2, 2*fcutoff)
nli, nlif = peakedness(dfreqs, diag, rate, median=False)
print(f' {cell:<22s}: run={run:2d}, fbase={rate:3.0f}Hz, CV={cv:.2f}, SI={nli:3.1f}')