120 lines
4.2 KiB
Python
120 lines
4.2 KiB
Python
import numpy as np
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from scipy.stats import linregress
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import matplotlib.pyplot as plt
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from pathlib import Path
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from plotstyle import plot_style, labels_params
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from plotstyle import noise_files, plot_chi2
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from modelsusceptcontrasts import load_chi2
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data_path = Path('data')
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sims_path = data_path / 'simulations'
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def plot_overn(ax, s, files, nmax=1e6, title=False):
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ns = []
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stats = []
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for fname in files:
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data = np.load(fname)
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if not 'nsegs' in data:
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return
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n = data['nsegs']
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if nmax is not None and n > nmax:
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continue
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noise_frac = data['noise_frac']
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alpha = data['contrast']
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freqs = data['freqs']
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pss = data['pss']
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prss = data['prss']
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chi2 = np.abs(prss)/0.5/(pss.reshape(1, -1)*pss.reshape(-1, 1))
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ns.append(n)
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i0 = np.argmin(freqs < 0)
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i1 = np.argmax(freqs > 300)
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if i1 == 0:
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i1 = len(freqs)
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chi2 = 1e-4*chi2[i0:i1, i0:i1] # Hz/%^2
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stats.append(np.quantile(chi2, [0, 0.001, 0.05, 0.25, 0.5,
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0.75, 0.95, 0.998, 1.0]))
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ns = np.array(ns)
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stats = np.array(stats)
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indx = np.argsort(ns)
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ns = ns[indx]
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stats = stats[indx]
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ax.set_visible(True)
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ax.plot(ns, stats[:, 7], zorder=50, label='99.8\\%', **s.lsMax)
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ax.fill_between(ns, stats[:, 2], stats[:, 6], fc='0.85',
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zorder=40, label='5--95\\%')
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ax.fill_between(ns, stats[:, 3], stats[:, 5], fc='0.5',
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zorder=45, label='25-75\\%')
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ax.plot(ns, stats[:, 4], zorder=50, label='median', **s.lsMedian)
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#ax.plot(ns, stats[:, 8], '0.0')
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if title:
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if noise_frac < 1:
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ax.set_title('$c$=0\\,\\%', fontsize='medium')
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else:
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ax.set_title(f'$c$={100*alpha:g}\\,\\%', fontsize='medium')
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ax.set_xlim(1e1, nmax)
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ax.set_xscale('log')
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ax.set_yscale('log')
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ax.set_yticks_log(numticks=3)
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ax.set_ylim(1e-1, 3e3)
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ax.set_minor_yticks_log(numticks=5)
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if nmax > 1e6:
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ax.set_xticks_log(numticks=4)
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ax.set_minor_xticks_log(numticks=8)
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else:
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ax.set_xticks_log(numticks=3)
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ax.set_minor_xticks_log(numticks=6)
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ax.set_xlabel('segments')
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ax.set_ylabel('$|\\chi_2|$ [Hz]')
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if alpha == 0.10:
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ax.legend(loc='upper left', bbox_to_anchor=(1.4, 1.3),
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markerfirst=False, title='$|\\chi_2|$ percentiles')
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def plot_chi2_overn(axs, s, cell_name):
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print(cell_name)
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files, nums = noise_files(sims_path, cell_name)
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for k, nsegs in enumerate([1e2, 1e3, 1e4, 1e6]):
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freqs, chi2, fcutoff, contrast, n = load_chi2(sims_path, cell_name,
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None, nsegs)
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ns = f'$N={n}$' if n < 1000 else f'$N=10^{np.log10(n):.0f}$'
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cax = plot_chi2(axs[k], s, freqs, chi2, fcutoff)
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if k < len(axs) - 2:
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cax.set_ylabel('')
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axs[k].set_title(ns, fontsize='medium')
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plot_overn(axs[-1], s, files)
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if __name__ == '__main__':
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cells = ['2017-07-18-ai-invivo-1', # strong triangle
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'2012-12-13-ao-invivo-1', # triangle
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'2012-12-20-ac-invivo-1', # weak border triangle
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'2013-01-08-ab-invivo-1'] # no triangle
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s = plot_style()
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fig, axs = plt.subplots(6, 6, cmsize=(s.plot_width, 0.9*s.plot_width),
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width_ratios=[1, 1, 1, 1, 0, 1],
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height_ratios=[1, 1, 1, 1, 0, 1])
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fig.subplots_adjust(leftm=8, rightm=0.5, topm=2, bottomm=4,
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wspace=1, hspace=0.8)
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for ax in axs.flat:
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ax.set_visible(False)
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for k in range(len(cells)):
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plot_chi2_overn(axs[k], s, cells[k])
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cell_name = cells[0]
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files, nums = noise_files(sims_path, cell_name)
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plot_overn(axs[-1, 0], s, files, 1e7, True)
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for k, alpha in enumerate([0.01, 0.03, 0.1]):
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files, nums = noise_files(sims_path, cell_name, alpha)
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plot_overn(axs[-1, k + 1], s, files, 1e7, True)
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for k in range(4):
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fig.common_yticks(axs[k, :4])
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fig.common_xticks(axs[:4, k])
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fig.common_xticks(axs[:4, -1])
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fig.align_ylabels(axs[:4, -1], dist=12)
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fig.common_yticks(axs[-1, :4])
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fig.tag(axs, xoffs=-2.5, yoffs=1.8)
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fig.savefig()
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print()
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