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started to updated example cells to new analysis with the right units

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Jan Benda
2025-05-25 00:47:27 +02:00
parent 223ad8bd4b
commit e785d51b18
4 changed files with 96 additions and 99 deletions
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93
punitexamplecell.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
@@ -13,7 +11,7 @@ example_cell = [['2020-10-27-ag-invivo-1', 0],
example_cells = [
#['2021-06-18-ae-invivo-1', 3], # 98Hz, 1%, ok
['2021-06-18-ae-invivo-1', 2], # 98Hz, 10%, ok
['2012-03-30-ah', 2], # 177Hz, 2.5%, 2.0, nice
['2012-03-30-ah', 5], # 177Hz, 5%, 2.0, nice
##['2012-07-03-ak', 0], # 120Hz, 2.5%, 1.8, broader, the one model cell, nice triangle up to 1%!
##['2012-12-20-ac', 0], # 213Hz, 2.5%, 2.1, ok, model cell, weak triangle up to 1%!
#['2017-07-18-ai-invivo-1', 1], # 78Hz, 5%, 2.3, weak, nice model cell with clear triangle up to 10%!
@@ -51,8 +49,6 @@ def load_noise(path, cell_name, run):
contrast = data['contrast']
time = data['time']
stimulus = data['stimulus']
name = str(data['stimulus_name'])
fcutoff = float(name.lower().replace('blwn', '').replace('inputarr_', '').replace('gwn', '').split('h')[0])
spikes = []
for k in range(1000):
key = f'spikes_{k:03d}'
@@ -62,12 +58,8 @@ def load_noise(path, cell_name, run):
return contrast, time, stimulus, spikes
def load_spectra(path, cell_name, run=None):
if run is None:
data = np.load(cell_name)
else:
d = list(path.glob(f'{cell_name}-spectral*-s{run:02d}.npz'))
data = np.load(d[0])
def load_spectra(path, mode, cell_name, run=None):
data = np.load(path / f'{cell_name}-spectral-{mode}-s{run:02d}.npz')
contrast = float(data['alpha'])
fcutoff = float(data['fcutoff'])
freqs = data['freqs']
@@ -111,18 +103,27 @@ def plot_response_spectrum(ax, s, eodf, rate, freqs, prr):
power_db = 10*np.log10(prr/np.max(prr))
ax.show_spines('b')
mask = freqs < 890
ax.plot(freqs[mask], power_db[mask], **s.lsC1)
ax.plot(freqs[eod_i], power_db[eod_i] + 2, **s.psFEOD)
ax.plot(freqs[rate_i], power_db[rate_i] + 2, **s.psF0)
#ax.plot(freqs[mask], power_db[mask], **s.lsC1)
#ax.plot(freqs[eod_i], power_db[eod_i] + 2, **s.psFEOD)
#ax.plot(freqs[rate_i], power_db[rate_i] + 2, **s.psF0)
#ax.set_ylim(-25, 5)
ax.plot(freqs[mask], 1e-3*prr[mask], **s.lsC1)
ax.plot(freqs[eod_i], 1e-3*prr[eod_i] + 2, **s.psFEOD)
ax.plot(freqs[rate_i], 1e-3*prr[rate_i] + 2, **s.psF0)
ax.set_ylim(0, 30)
ax.set_xlim(0, 900)
ax.set_ylim(-25, 5)
ax.set_xticks_delta(300)
ax.set_xlabel('$f$', 'Hz')
ax.text(freqs[eod_i], power_db[eod_i] + 4, '$f_{\\rm EOD}$',
#ax.text(freqs[eod_i], power_db[eod_i] + 4, '$f_{\\rm EOD}$',
# ha='center')
#ax.text(freqs[rate_i], power_db[rate_i] + 4, '$r$',
# ha='center')
#ax.yscalebar(1.05, 0, 10, 'dB', ha='right')
ax.text(freqs[eod_i], 1e-3*prr[eod_i] + 4, '$f_{\\rm EOD}$',
ha='center')
ax.text(freqs[rate_i], power_db[rate_i] + 4, '$r$',
ax.text(freqs[rate_i], 1e-3*prr[rate_i] + 4, '$r$',
ha='center')
ax.yscalebar(1.05, 0, 10, 'dB', ha='right')
ax.yscalebar(1.05, 0, 5, 'kHz', ha='right')
def plot_response(ax, s, eodf, time1, stimulus1, contrast1, spikes1, contrast2, spikes2):
@@ -150,30 +151,30 @@ def plot_response(ax, s, eodf, time1, stimulus1, contrast1, spikes1, contrast2,
def plot_gain(ax, s, contrast1, freqs1, gain1, contrast2, freqs2, gain2, fcutoff):
ax.plot(freqs2, gain2, label=f'{100*contrast2:.0f}', **s.lsC2)
ax.plot(freqs1, gain1, label=f'{100*contrast1:.0f}', **s.lsC1)
ax.plot(freqs2, 1e-2*gain2, label=f'{100*contrast2:.0f}', **s.lsC2)
ax.plot(freqs1, 1e-2*gain1, label=f'{100*contrast1:.0f}', **s.lsC1)
ax.set_xlim(0, fcutoff)
ax.set_ylim(0, 800)
ax.set_ylim(0, 10)
ax.set_xticks_delta(100)
ax.set_xlabel('$f$', 'Hz')
ax.set_ylabel(r'$|\chi_1|$', 'Hz')
ax.set_ylabel(r'$|\chi_1|$', r'Hz/\%')
def plot_colorbar(ax, pc, dc=None):
cax = ax.inset_axes([1.04, 0, 0.05, 1])
cax.set_spines_outward('lrbt', 0)
cb = cax.get_figure().colorbar(pc, cax=cax, label=r'$|\chi_2|$ [kHz]')
cb = cax.get_figure().colorbar(pc, cax=cax, label=r'$|\chi_2|$ [Hz/\%$^2$]')
cb.outline.set_color('none')
cb.outline.set_linewidth(0)
if dc is not None:
cax.set_yticks_delta(dc)
def plot_chi2(ax, s, contrast, freqs, chi2, fcutoff, vmax):
def plot_chi2(ax, s, contrast, freqs, chi2, fcutoff, vmax=None):
ax.set_aspect('equal')
if vmax is None:
vmax = np.quantile(1e-3*chi2, 0.99)
pc = ax.pcolormesh(freqs, freqs, 1e-3*chi2, vmin=0, vmax=vmax,
vmax = np.quantile(1e-4*chi2, 0.998)
pc = ax.pcolormesh(freqs, freqs, 1e-4*chi2, vmin=0, vmax=vmax,
rasterized=True, zorder=10)
ax.set_xlim(0, fcutoff)
ax.set_ylim(0, fcutoff)
@@ -200,22 +201,22 @@ def plot_diagonals(ax, s, fbase, contrast1, freqs1, chi21, contrast2, freqs2, ch
sifs.append(sif)
print(f' SI at {100*contrast:.1f}% contrast: {sinorm:.2f}')
#ax.axvline(fbase, **s.lsGrid)
ax.plot(diags[1][0], 1e-3*diags[1][1], **s.lsC2)
ax.plot(diags[0][0], 1e-3*diags[0][1], **s.lsC1)
ax.plot(sifs[1], 1e-3*sips[1], **s.psC2)
ax.plot(sifs[0], 1e-3*sips[0], **s.psC1)
ax.plot(diags[1][0], 1e-4*diags[1][1], **s.lsC2)
ax.plot(diags[0][0], 1e-4*diags[0][1], **s.lsC1)
ax.plot(sifs[1], 1e-4*sips[1] + 0.5, clip_on=False, **s.psC2)
ax.plot(sifs[0], 1e-4*sips[0] + 0.5, clip_on=False, **s.psC1)
ax.set_xlim(0, 2*fcutoff)
ax.set_ylim(0, 4.2)
ax.set_ylim(0, 14)
ax.set_xticks_delta(300)
ax.set_yticks_delta(1)
ax.set_yticks_delta(4)
ax.set_xlabel('$f_1 + f_2$', 'Hz')
#ax.set_ylabel(r'$|\chi_2|$', 'kHz')
ax.text(sifs[1] - 50, 1e-3*sips[1], f'{100*contrast2:.0f}\\%',
#ax.set_ylabel(r'$|\chi_2|$', r'Hz/\%$^2$')
ax.text(sifs[1] - 50, 1e-4*sips[1], f'{100*contrast2:.0f}\\%',
ha='right')
ax.text(sifs[1] + 70, 1e-3*sips[1], f'SI={sis[1]:.1f}')
ax.text(sifs[0] - 50, 1e-3*sips[0], f'{100*contrast1:.0f}\\%',
ax.text(sifs[1] + 70, 1e-4*sips[1], f'SI={sis[1]:.1f}')
ax.text(sifs[0] - 50, 1e-4*sips[0] + 2, f'{100*contrast1:.0f}\\%',
ha='right')
ax.text(sifs[0] + 70, 1e-3*sips[0], f'SI={sis[0]:.1f}')
ax.text(sifs[0] + 70, 1e-4*sips[0] + 2, f'SI={sis[0]:.1f}')
#ax.text(fbase, 4.3, '$r$', ha='center')
@@ -237,6 +238,9 @@ if __name__ == '__main__':
#exit()
"""
#mode = 'all'
mode = '100'
cell_name = example_cell[0][0]
print('Example P-unit:', cell_name)
eodf, rate, cv, isis, pdf, freqs, prr = load_baseline(data_path, cell_name)
@@ -246,9 +250,9 @@ if __name__ == '__main__':
*example_cell[0])
contrast2, time2, stimulus2, spikes2 = load_noise(data_path,
*example_cell[1])
fcutoff1, contrast1, freqs1, gain1, chi21 = load_spectra(data_path,
fcutoff1, contrast1, freqs1, gain1, chi21 = load_spectra(data_path, mode,
*example_cell[0])
fcutoff2, contrast2, freqs2, gain2, chi22 = load_spectra(data_path,
fcutoff2, contrast2, freqs2, gain2, chi22 = load_spectra(data_path, mode,
*example_cell[1])
print(f' contrast1: {100*contrast1:4.1f}% contrast2: {100*contrast2:4.1f}%')
print(f' fcutoff1 : {fcutoff1:3.0f}Hz fcutoff2 : {fcutoff2:3.0f}Hz')
@@ -279,11 +283,11 @@ if __name__ == '__main__':
plot_gain(axg, s, contrast1, freqs1, gain1,
contrast2, freqs2, gain2, fcutoff1)
pc = plot_chi2(axc1, s, contrast2, freqs2, chi22, fcutoff2, 4)
pc = plot_chi2(axc1, s, contrast2, freqs2, chi22, fcutoff2, 6)
axc1.plot([0, fcutoff2], [0, fcutoff2], zorder=20, **s.lsDiag)
axc1.set_title(f'$c$={100*contrast2:g}\\,\\%',
fontsize='medium', color=s.cell_color2)
pc = plot_chi2(axc2, s, contrast1, freqs1, chi21, fcutoff1, 4)
pc = plot_chi2(axc2, s, contrast1, freqs1, chi21, fcutoff1, 6)
axc2.set_title(f'$c$={100*contrast1:g}\\,\\%',
fontsize='medium', color=s.cell_color1)
axc2.plot([0, fcutoff1], [0, fcutoff1], zorder=20, **s.lsDiag)
@@ -298,20 +302,19 @@ if __name__ == '__main__':
print('Additional example cells:')
for k, (cell, run) in enumerate(example_cells):
eodf, rate, cv, isis, pdf, _, _ = load_baseline(data_path, cell)
fcutoff, contrast, freqs, gain, chi2 = load_spectra(data_path, cell, run)
fcutoff, contrast, freqs, gain, chi2 = load_spectra(data_path,
mode, cell, run)
dfreqs, diag = diag_projection(freqs, chi2, 2*fcutoff)
sinorm, sirel, sif = peak_size(dfreqs, diag, rate, median=False)
print(f' {cell:<22s}: run={run:2d}, fbase={rate:3.0f}Hz, CV={cv:.2f}, SI={sinorm:3.1f}')
plot_isih2(axs[0, k], s, rate, cv, isis, pdf)
pc = plot_chi2(axs[1, k], s, contrast, freqs, chi2, fcutoff, 1.0)
pc = plot_chi2(axs[1, k], s, contrast, freqs, chi2, fcutoff, 10)
axs[1, k].text(0.95, 0.9, f'SI($r$)={sinorm:.1f}', ha='right', zorder=50,
color='white', fontsize='medium',
transform=axs[1, k].transAxes)
axs[0, 0].text(0, 1.6, 'P-units:', transform=axs[0, 0].transAxes,
color=s.cell_color1,
fontsize='large')
#axs[0, -1].text(0.97, -0.45, '5\\,ms', ha='right',
# transform=axs[0, -1].transAxes)
plot_colorbar(axs[1, -1], pc)
fig.common_yticks(axs[1, :])
fig.tag([axs[0, :]], xoffs=-3, yoffs=1)