diff --git a/event_time_analysis.py b/event_time_analysis.py index 2c1070b..cd31178 100644 --- a/event_time_analysis.py +++ b/event_time_analysis.py @@ -91,6 +91,7 @@ def kde(event_dt, max_dt = 60): conv_array += gauss(conv_t, e, kernal_w, kernal_h, norm=True) # plt.plot(conv_t, conv_array) + return conv_array def permulation_kde(event_dt, repetitions = 2000, max_dt = 60, max_mem_use_GB = 4, norm_count = 1): @@ -119,8 +120,6 @@ def permulation_kde(event_dt, repetitions = 2000, max_dt = 60, max_mem_use_GB = del event_dt_perm, gauss_3d return kde_3d - embed() - quit() t0 = time.time() kernal_w = 1 kernal_h = 0.2 @@ -157,11 +156,16 @@ def permulation_kde(event_dt, repetitions = 2000, max_dt = 60, max_mem_use_GB = # del event_dt_perm, gauss_3d, kde_3d chunk_boot_KDE = chunk_permutation(select_event_dt, conv_tt, repetitions % chunk_size, max_jitter, kernal_w, kernal_h) chunk_collector.extend(chunk_boot_KDE) - + chunk_collector = np.array(chunk_collector) + # ToDo: this works but is incorrect i think + chunk_collector /= np.sum(chunk_collector, axis=1).reshape(chunk_collector.shape[0], 1) print(f'bootstrap with {repetitions:.0f} repetitions took {time.time() - t0:.2f}s.') - embed() - quit() + # fig, ax = plt.subplots() + # for i in range(len(chunk_collector)): + # ax.plot(cp.asnumpy(conv_t), chunk_collector[i]) + + return cp.asnumpy(conv_t), chunk_collector def main(base_path): @@ -202,10 +206,15 @@ def main(base_path): lose_chrips_centered_on_ag_off_t.append(event_centered_times(ag_on_off_t_GRID[:, 1], chirp_times[1])) norm_count.append(len(chirp_times[1])) - kde(np.hstack(lose_chrips_centered_on_ag_off_t)) + kde_array = kde(np.hstack(lose_chrips_centered_on_ag_off_t)) + + conv_t, boot_kde = permulation_kde(np.hstack(lose_chrips_centered_on_ag_off_t), norm_count=norm_count) - permulation_kde(np.hstack(lose_chrips_centered_on_ag_off_t), norm_count=norm_count) + fig, ax = plt.subplots() + for i in range(len(boot_kde)): + ax.plot(conv_t, boot_kde[i]) + ax.plot(conv_t, kde_array, color='k', lw=3) pass if __name__ == '__main__':