plot looks nice.
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@ -281,7 +281,9 @@ def main(base_path):
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embed()
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quit()
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fig, ax = plt.subplots()
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fig = plt.figure(figsize=(20/2.54, 12/2.54))
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gs = gridspec.GridSpec(1, 1, left=0.1, bottom=0.1, right=0.95, top=0.95)
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ax = fig.add_subplot(gs[0, 0])
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ax.fill_between(conv_t, perm_p1/np.sum(lose_chirp_count), perm_p99/np.sum(lose_chirp_count), color='cornflowerblue', alpha=.8)
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ax.plot(conv_t, perm_p50/np.sum(lose_chirp_count), color='dodgerblue', alpha=1, lw=3)
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@ -289,13 +291,23 @@ def main(base_path):
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ax.plot(conv_t, jk_p50/np.sum(lose_chirp_count)/jack_pct, color='firebrick', alpha=1, lw=3)
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ax_m = ax.twinx()
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for enu, centered_events in enumerate(lose_chrips_centered_on_ag_off_t):
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Cevents = centered_events[np.abs(centered_events) <= max_dt]
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ax_m.plot(Cevents, np.ones(len(Cevents)) * enu, '|', markersize=8, color='k', alpha=.1)
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ax_m.set_yticks([])
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ax.set_xlabel('time [s]', fontsize=12)
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ax.set_ylabel('event rate [Hz]', fontsize=12)
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ax.set_xlim(-max_dt, max_dt)
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ax.tick_params(labelsize=10)
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# for i in range(len(boot_kde)):
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# ax.plot(conv_t, boot_kde[i] / np.sum(lose_chirp_count), color='tab:blue')
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#
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# for i in range(len(boot_kde)):
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# ax.plot(conv_t, jk_kde[i] / np.sum(lose_chirp_count) / jack_pct, color='tab:red')
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ax.plot(conv_t, kde_array/np.sum(lose_chirp_count), color='k', lw=3)
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# ax.plot(conv_t, kde_array/np.sum(lose_chirp_count), color='k', lw=3)
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plt.show()
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pass
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