benda/nonlinearbaseline2025
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removed sqrt from chi2

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Jan Benda 2025-05-24 01:01:52 +02:00
parent 752837f4ec
commit bd50335d53
5 changed files with 20 additions and 15 deletions
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3
modelsusceptcontrasts.py
View File

@ -34,7 +34,8 @@ def plot_chi2(ax, s, data_file, rate):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
chi2 = np.abs(data['prss'])*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
ax.set_visible(True)
ax.set_aspect('equal')
i0 = np.argmin(freqs < -fcutoff)

3
modelsusceptlown.py
View File

@ -31,7 +31,8 @@ def plot_chi2(ax, s, data_file, rate):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
chi2 = np.abs(data['prss'])*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
ax.set_visible(True)
ax.set_aspect('equal')
i0 = np.argmin(freqs < -fcutoff)

14
modelsusceptovern.py
View File

@ -26,8 +26,8 @@ def plot_chi2(ax, s, data_file):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
dt_fix = 1 # 0.0005
prss = np.abs(data['prss'])/dt_fix*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)/0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
ax.set_visible(True)
ax.set_aspect('equal')
i0 = np.argmin(freqs < -300)
@ -36,8 +36,8 @@ def plot_chi2(ax, s, data_file):
if i1 == 0:
i1 = len(freqs)
freqs = freqs[i0:i1]
prss = prss[i0:i1, i0:i1]
vmax = np.quantile(prss, 0.996)
chi2 = chi2[i0:i1, i0:i1]
vmax = np.quantile(chi2, 0.996)
ten = 10**np.floor(np.log10(vmax))
for fac, delta in zip([1, 2, 3, 4, 6, 8, 10],
[0.5, 1, 1, 2, 3, 4, 5]):
@ -45,7 +45,7 @@ def plot_chi2(ax, s, data_file):
vmax = fac*ten
ten *= delta
break
pc = ax.pcolormesh(freqs, freqs, prss, vmin=0, vmax=vmax,
pc = ax.pcolormesh(freqs, freqs, chi2, vmin=0, vmax=vmax,
rasterized=True)
ax.set_title(f'$N=10^{np.log10(n):.0f}$', fontsize='medium')
ax.set_xlim(0, 300)
@ -77,8 +77,8 @@ def plot_overn(ax, s, files, nmax=1e6, title=False):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
dt_fix = 1 # 0.0005
chi2 = np.abs(data['prss'])/dt_fix*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)/0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
ns.append(n)
i0 = np.argmin(freqs < 0)
i1 = np.argmax(freqs > 300)

13
noisesplit.py
View File

@ -83,8 +83,8 @@ def plot_overn(ax, s, files, nmax=1e6):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
dt_fix = 1 # 0.0005
chi2 = np.abs(data['prss'])/dt_fix*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)/0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
ns.append(n)
i0 = np.argmin(freqs < 0)
i1 = np.argmax(freqs > fcutoff)
@ -131,7 +131,8 @@ def plot_chi2_contrast(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
chi2 = np.abs(data['prss'])*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
cax = plot_chi2(ax, s, freqs, chi2, n, 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}')
@ -147,7 +148,8 @@ def plot_chi2_split(ax1, ax2, s, files, nums, nsmall, nlarge, rate):
noise_frac = data['noise_frac']
freqs = data['freqs']
pss = data['pss']
chi2 = np.abs(data['prss'])*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
prss = data['prss']
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
cax = plot_chi2(ax, s, freqs, chi2, n, 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}')
@ -169,7 +171,8 @@ def plot_chi2_data(ax, s, cell_name, run):
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
chi2 = np.abs(data['prss'])*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
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={n}')
print()
plot_chi2(ax, s, freqs, chi2, n, ratebase)

2
punitexamplecell.py
View File

@ -76,7 +76,7 @@ def load_spectra(path, cell_name, run=None):
prss = data['prss']
nsegs = int(data['n'])
gain = np.abs(prs)/pss
chi2 = np.abs(prss)*0.5/np.sqrt(pss.reshape(1, -1)*pss.reshape(-1, 1))
chi2 = np.abs(prss)*0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
return fcutoff, contrast, freqs, gain, chi2