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updated model figures to new analysis with the right units

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Jan Benda
2025-05-25 12:29:46 +02:00
parent e785d51b18
commit e87d63c46b
5 changed files with 219 additions and 351 deletions
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101
modelsusceptovern.py
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@@ -3,78 +3,26 @@ from scipy.stats import linregress
import matplotlib.pyplot as plt
from pathlib import Path
from plotstyle import plot_style, labels_params
from plotstyle import noise_files, plot_chi2
from modelsusceptcontrasts import load_chi2
data_path = Path('data')
sims_path = data_path / 'simulations'
def sort_files(cell_name, all_files, n):
files = [fn for fn in all_files if '-'.join(fn.stem.split('-')[2:-n]) == cell_name]
if len(files) == 0:
return None, 0
nums = [int(fn.stem.split('-')[-1]) for fn in files]
idxs = np.argsort(nums)
files = [files[i] for i in idxs]
nums = [nums[i] for i in idxs]
return files, nums
def plot_chi2(ax, s, data_file):
data = np.load(data_file)
n = data['n']
alpha = data['alpha']
freqs = data['freqs']
pss = data['pss']
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)
i0 = np.argmin(freqs < 0)
i1 = np.argmax(freqs > 300)
if i1 == 0:
i1 = len(freqs)
freqs = freqs[i0:i1]
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]):
if fac*ten >= vmax:
vmax = fac*ten
ten *= delta
break
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)
ax.set_ylim(0, 300)
ax.set_xticks_delta(300)
ax.set_minor_xticks(3)
ax.set_yticks_delta(300)
ax.set_minor_yticks(3)
ax.set_xlabel('$f_1$', 'Hz')
ax.set_ylabel('$f_2$', 'Hz')
cax = ax.inset_axes([1.04, 0, 0.05, 1])
cax.set_spines_outward('lrbt', 0)
cb = fig.colorbar(pc, cax=cax)
cb.outline.set_color('none')
cb.outline.set_linewidth(0)
cax.set_yticks_delta(ten)
def plot_overn(ax, s, files, nmax=1e6, title=False):
ns = []
stats = []
for fname in files:
data = np.load(fname)
if not 'n' in data:
if not 'nsegs' in data:
return
n = data['n']
n = data['nsegs']
if nmax is not None and n > nmax:
continue
alpha = data['alpha']
noise_frac = data['noise_frac']
alpha = data['contrast']
freqs = data['freqs']
pss = data['pss']
prss = data['prss']
@@ -84,7 +32,7 @@ def plot_overn(ax, s, files, nmax=1e6, title=False):
i1 = np.argmax(freqs > 300)
if i1 == 0:
i1 = len(freqs)
chi2 = chi2[i0:i1, i0:i1]
chi2 = 1e-4*chi2[i0:i1, i0:i1] # Hz/%^2
stats.append(np.quantile(chi2, [0, 0.001, 0.05, 0.25, 0.5,
0.75, 0.95, 0.998, 1.0]))
ns = np.array(ns)
@@ -94,12 +42,14 @@ def plot_overn(ax, s, files, nmax=1e6, title=False):
stats = stats[indx]
ax.set_visible(True)
ax.plot(ns, stats[:, 7], zorder=50, label='99.8\\%', **s.lsMax)
ax.fill_between(ns, stats[:, 2], stats[:, 6], fc='0.85', zorder=40, label='5--95\\%')
ax.fill_between(ns, stats[:, 3], stats[:, 5], fc='0.5', zorder=45, label='25-75\\%')
ax.fill_between(ns, stats[:, 2], stats[:, 6], fc='0.85',
zorder=40, label='5--95\\%')
ax.fill_between(ns, stats[:, 3], stats[:, 5], fc='0.5',
zorder=45, label='25-75\\%')
ax.plot(ns, stats[:, 4], zorder=50, label='median', **s.lsMedian)
#ax.plot(ns, stats[:, 8], '0.0')
if title:
if 'noise_frac' in data:
if noise_frac < 1:
ax.set_title('$c$=0\\,\\%', fontsize='medium')
else:
ax.set_title(f'$c$={100*alpha:g}\\,\\%', fontsize='medium')
@@ -107,14 +57,12 @@ def plot_overn(ax, s, files, nmax=1e6, title=False):
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_yticks_log(numticks=3)
ax.set_ylim(1e-1, 3e3)
ax.set_minor_yticks_log(numticks=5)
if nmax > 1e6:
ax.set_ylim(3e-1, 5e3)
ax.set_minor_yticks_log(numticks=5)
ax.set_xticks_log(numticks=4)
ax.set_minor_xticks_log(numticks=8)
else:
ax.set_ylim(5e0, 1e4)
ax.set_minor_yticks_log(numticks=5)
ax.set_xticks_log(numticks=3)
ax.set_minor_xticks_log(numticks=6)
ax.set_xlabel('segments')
@@ -126,10 +74,15 @@ def plot_overn(ax, s, files, nmax=1e6, title=False):
def plot_chi2_overn(axs, s, cell_name):
print(cell_name)
files, nums = sort_files(cell_name,
sims_path.glob(f'chi2-split-{cell_name}-*.npz'), 1)
for k, n in enumerate([1e1, 1e2, 1e3, 1e6]):
plot_chi2(axs[k], s, files[nums.index(int(n))])
files, nums = noise_files(sims_path, cell_name)
for k, nsegs in enumerate([1e1, 1e2, 1e3, 1e6]):
freqs, chi2, fcutoff, contrast, n = load_chi2(sims_path, cell_name,
None, nsegs)
ns = f'$N={n}$' if n < 1000 else f'$N=10^{np.log10(n):.0f}$'
cax = plot_chi2(axs[k], s, freqs, chi2, fcutoff)
if k < len(axs) - 2:
cax.set_ylabel('')
axs[k].set_title(ns, fontsize='medium')
plot_overn(axs[-1], s, files)
@@ -149,12 +102,10 @@ if __name__ == '__main__':
for k in range(len(cells)):
plot_chi2_overn(axs[k], s, cells[k])
cell_name = cells[0]
files, nums = sort_files(cell_name,
sims_path.glob(f'chi2-split-{cell_name}-*.npz'), 1)
files, nums = noise_files(sims_path, cell_name)
plot_overn(axs[-1, 0], s, files, 1e7, True)
for k, alphastr in enumerate(['010', '030', '100']):
files, nums = sort_files(cell_name,
sims_path.glob(f'chi2-noisen-{cell_name}-{alphastr}-*.npz'), 2)
for k, alpha in enumerate([0.01, 0.03, 0.1]):
files, nums = noise_files(sims_path, cell_name, alpha)
plot_overn(axs[-1, k + 1], s, files, 1e7, True)
for k in range(4):
fig.common_yticks(axs[k, :4])