diff --git a/noisesplit.py b/noisesplit.py index b3fca7e..08472e0 100644 --- a/noisesplit.py +++ b/noisesplit.py @@ -228,7 +228,7 @@ if __name__ == '__main__': cell_name = ['2017-07-18-ai-invivo-1', 1] # Take this! at 3% model, 5% data nsmall = 100 nlarge = 1000000 - contrast = 0.03 + contrast = 0.05 wdt = 0.0001 wnoise = whitenoise(0, 300, wdt, 0.05, rng=np.random.default_rng(51234)) @@ -237,24 +237,26 @@ if __name__ == '__main__': s = plot_style() fig, axs = plt.subplots(3, 4, cmsize=(s.plot_width, 0.7*s.plot_width), width_ratios=[1, 0, 1, 1, 0.15, 1]) - fig.subplots_adjust(leftm=8, rightm=1.5, topm=3, bottomm=4, + fig.subplots_adjust(leftm=8, rightm=1.5, topm=4, bottomm=4, wspace=0.25, hspace=0.8) axs[0, 2].set_visible(False) axs[0, 3].set_visible(False) + xt = -2.2 + yt = 1.3 # data: - axs[0, 1].text(-2.42, 1.2, 'P-unit data', fontsize='large', + axs[0, 1].text(xt, yt, 'P-unit data', fontsize='large', transform=axs[0, 1].transAxes, color=s.punit_color1) data_contrast, ratebase, eodf = plot_chi2_data(axs[0, 1], s, cell_name[0], cell_name[1]) plot_ram(axs[0, 0], data_contrast, eodf, wtime, wnoise) - axs[0, 1].text(-1.5, 1.2, f'$r={ratebase:.0f}$\\,Hz', + axs[0, 1].text(xt + 0.9, yt, f'$r={ratebase:.0f}$\\,Hz', transform=axs[0, 1].transAxes, fontsize='large') # model: data_files = sims_path.glob(f'chi2-noisen-{cell_name[0]}-{1000*contrast:03.0f}-*.npz') files, nums = sort_files(cell_name[0], data_files, 2) - axs[1, 1].text(-2.42, 1.2, 'P-unit model', fontsize='large', + axs[1, 1].text(xt, yt, 'P-unit model', fontsize='large', transform=axs[1, 1].transAxes, color=s.model_color1) plot_chi2_contrast(axs[1, 1], axs[1, 2], s, files, nums, nsmall, nlarge) axr1 = plot_noise_split(axs[1, 0], contrast, 0, 1, wtime, wnoise) @@ -265,9 +267,9 @@ if __name__ == '__main__': # model noise split: data_files = sims_path.glob(f'chi2-split-{cell_name[0]}-*.npz') files, nums = sort_files(cell_name[0], data_files, 1) - axs[2, 1].text(-2.42, 1.2, 'P-unit model', fontsize='large', + axs[2, 1].text(xt, yt, 'P-unit model', fontsize='large', transform=axs[2, 1].transAxes, color=s.model_color1) - axs[2, 1].text(-1.5, 1.2, f'(noise split)', fontsize='large', + axs[2, 1].text(xt + 0.9, yt, f'(noise split)', fontsize='large', transform=axs[2, 1].transAxes) noise_contrast, noise_frac = plot_chi2_split(axs[2, 1], axs[2, 2], s, files, nums, nsmall, nlarge) @@ -283,6 +285,6 @@ if __name__ == '__main__': fig.tag([axs[0, :2], [axr1] + axs[1, 1:].tolist(), [axr2] + axs[2, 1:].tolist()], - xoffs=-4.5, yoffs=2) + xoffs=[-4.5, 1, 1, -4.5], yoffs=2) fig.savefig() print()