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updated captions to new figures

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This commit is contained in:
Jan Benda
2025-05-26 11:36:02 +02:00
parent d043a8c47c
commit 04578fd77e
3 changed files with 97 additions and 86 deletions
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107
noisesplit.py
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@@ -65,56 +65,9 @@ def plot_overn(ax, s, files, nmax=1e6):
ax.set_xlabel('segments')
ax.set_ylabel(r'$|\chi_2|$', r'Hz/\%$^2$')
def plot_chi2_contrast(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
for ax, n in zip([ax1, ax2], [nsmall, nlarge]):
i = nums.index(n)
data = np.load(files[i])
nsegs = data['nsegs']
fcutoff = data['fcutoff']
alpha = data['contrast']
freqs = data['freqs']
pss = data['pss']
prss = data['prss']
if nsegs < 10000:
ax.text(1, 1.1, f'$N={nsegs}$',
ha='right', transform=ax.transAxes)
else:
ax.text(1, 1.1, f'$N=10^{{{np.log10(nsegs):.0f}}}$',
ha='right', transform=ax.transAxes)
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
cax = plot_chi2(ax, s, freqs, chi2, fcutoff, rate)
cax.set_ylabel('')
print(f'Modeled cell {"-".join(files[i].name.split("-")[2:-2])} at {100*alpha:4.1f}% contrast: noise_frac={1:3.1f}, nsegs={n}')
print()
def plot_chi2_split(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
for ax, n in zip([ax1, ax2], [nsmall, nlarge]):
i = nums.index(n)
data = np.load(files[i])
nsegs = data['nsegs']
fcutoff = data['fcutoff']
alpha = data['contrast']
noise_frac = data['noise_frac']
freqs = data['freqs']
pss = data['pss']
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
if nsegs < 10000:
ax.text(1, 1.1, f'$N={nsegs}$',
ha='right', transform=ax.transAxes)
else:
ax.text(1, 1.1, f'$N=10^{{{np.log10(nsegs):.0f}}}$',
ha='right', transform=ax.transAxes)
cax = plot_chi2(ax, s, freqs, chi2, fcutoff, rate)
cax.set_ylabel('')
print(f'Modeled cell {"-".join(files[i].name.split("-")[2:-1])} at {100*alpha:4.1f}% contrast: noise_frac={noise_frac:3.1f}, nsegs={n}')
print()
return alpha, noise_frac
def plot_chi2_data(ax, s, cell_name, run):
vmax = 15
data_file = data_path / f'{cell_name}-baseline.npz'
data = np.load(data_file)
eodf = float(data['eodf'])
@@ -131,13 +84,65 @@ def plot_chi2_data(ax, s, cell_name, run):
pss = data['pss']
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
print(f'Measured cell {"-".join(data_file.name.split("-")[:-2])} at {100*alpha:4.1f}% contrast: r={ratebase:3.0f}Hz, CV={cvbase:4.2f}, dt={1000*deltat:4.2f}ms, nfft={nfft}, win={1000*deltat*nfft:6.1f}ms, nsegs={nsegs}')
print(f'Measured cell {"-".join(data_file.name.split("-")[:-3])} at {100*alpha:4.1f}% contrast:')
print(f' r={ratebase:3.0f}Hz, CV={cvbase:4.2f}, dt={1000*deltat:4.2f}ms, nfft={nfft}, win={1000*deltat*nfft:6.1f}ms, nsegs={nsegs}')
print()
ax.text(1, 1.1, f'$N={nsegs}$',
ha='right', transform=ax.transAxes)
plot_chi2(ax, s, freqs, chi2, fcutoff, ratebase, 15)
plot_chi2(ax, s, freqs, chi2, fcutoff, ratebase, vmax)
return alpha, ratebase, eodf
def plot_chi2_contrast(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
vmax = {0.05: {nsmall: 15, nlarge: 1.2},
0.01: {nsmall: 400, nlarge: 4}}
for ax, n in zip([ax1, ax2], [nsmall, nlarge]):
i = nums.index(n)
data = np.load(files[i])
nsegs = data['nsegs']
fcutoff = float(data['fcutoff'])
alpha = float(data['contrast'])
freqs = data['freqs']
pss = data['pss']
prss = data['prss']
if nsegs < 10000:
ax.text(1, 1.1, f'$N={nsegs}$',
ha='right', transform=ax.transAxes)
else:
ax.text(1, 1.1, f'$N=10^{{{np.log10(nsegs):.0f}}}$',
ha='right', transform=ax.transAxes)
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
cax = plot_chi2(ax, s, freqs, chi2, fcutoff, rate, vmax[alpha][n])
cax.set_ylabel('')
print(f'Modeled cell {"-".join(files[i].name.split("-")[:-4])} at {100*alpha:4.1f}% contrast: noise_frac={1:3.1f}, nsegs={n}')
print()
def plot_chi2_split(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
vmax = {nsmall: 4, nlarge: 1.2}
for ax, n in zip([ax1, ax2], [nsmall, nlarge]):
i = nums.index(n)
data = np.load(files[i])
nsegs = data['nsegs']
fcutoff = float(data['fcutoff'])
alpha = float(data['contrast'])
noise_frac = data['noise_frac']
freqs = data['freqs']
pss = data['pss']
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
if nsegs < 10000:
ax.text(1, 1.1, f'$N={nsegs}$',
ha='right', transform=ax.transAxes)
else:
ax.text(1, 1.1, f'$N=10^{{{np.log10(nsegs):.0f}}}$',
ha='right', transform=ax.transAxes)
cax = plot_chi2(ax, s, freqs, chi2, fcutoff, rate, vmax[n])
cax.set_ylabel('')
print(f'Modeled cell {"-".join(files[i].name.split("-")[:-3])} at {100*alpha:4.1f}% contrast: noise_frac={noise_frac:3.1f}, nsegs={n}')
print()
return alpha, noise_frac
def plot_ram(ax, contrast, eodf, wtime, wnoise):
tmax = 50
@@ -217,7 +222,7 @@ if __name__ == '__main__':
s = plot_style()
fig, axs = plt.subplots(4, 4, cmsize=(s.plot_width, 0.85*s.plot_width),
width_ratios=[1, 0, 1, 1, 0.15, 0.9])
width_ratios=[1, 0, 1, 1, 0.2, 0.85])
fig.subplots_adjust(leftm=8, rightm=1.5, topm=3.5, bottomm=4,
wspace=0.25, hspace=0.6)
axs[0, 2].set_visible(False)