chirp distribution in chasing events are not so clear. maybe detect chirp bursts and calculate time correlations with their on/offsets
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@ -585,13 +585,16 @@ def main(base_path):
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[r'chirps$_{lose}$', r'chirps$_{win}$', r'rises$_{lose}$', r'rises$_{win}$']):
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event_category_signal(all_event_t, all_contact_t, all_ag_on_t, all_ag_off_t, win_sex, lose_sex, event_name)
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embed()
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quit()
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#################################
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chase_dur = []
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chase_chirp_count = []
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dt_start_first_chirp = []
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dt_end_first_chirp = []
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dt_start_all_chirp = []
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dt_end_all_chirp = []
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chase_dur_all_chirp = []
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for ag_on_t, ag_off_t, chirp_times_lose in zip(all_ag_on_t, all_ag_off_t, all_chirp_times_lose):
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if len(chirp_times_lose) == 0:
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continue
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@ -602,49 +605,129 @@ def main(base_path):
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if len(chirp_t_oi) >= 1:
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dt_start_first_chirp.append(chirp_t_oi[0] - a_on)
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dt_end_first_chirp.append(a_off - chirp_t_oi[0])
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dt_start_all_chirp.extend(chirp_t_oi - a_on)
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dt_end_all_chirp.extend(a_off - chirp_t_oi)
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chase_dur_all_chirp.extend(np.ones_like(chirp_t_oi) * (a_off - a_on))
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else:
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dt_start_first_chirp.append(np.nan)
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dt_end_first_chirp.append(np.nan)
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fig = plt.figure(figsize=(21/2.54, 19/2.54))
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gs = gridspec.GridSpec(2, 2, left=.15, bottom=0.1, right=0.95, top=0.95)
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dt_start_first_chirp = np.array(dt_start_first_chirp)
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dt_end_first_chirp = np.array(dt_end_first_chirp)
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dt_start_all_chirp = np.array(dt_start_all_chirp)
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dt_end_all_chirp = np.array(dt_end_all_chirp)
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chase_dur_all_chirp = np.array(chase_dur_all_chirp)
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chase_chirp_count = np.array(chase_chirp_count)
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chase_dur = np.array(chase_dur)
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chirp_rate = chase_chirp_count / chase_dur
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chase_dur_per_chirp_count = []
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positions = np.arange(np.max(chase_chirp_count)+1)
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for cc in positions:
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chase_dur_per_chirp_count.append([])
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chase_dur_per_chirp_count[-1].extend(chase_dur[chase_chirp_count == cc])
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################################################
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chase_dur_pct99 = np.percentile(chase_dur, 99)
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chase_dur_bins = np.arange(0, chase_dur_pct99+1, 2.5)
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chase_dur_count_above_th = np.zeros_like(chase_dur_bins[:-1])
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for enu, chase_dur_th in enumerate(chase_dur_bins[:-1]):
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chase_dur_count_above_th[enu] = len(chase_dur[chase_dur >= chase_dur_th])
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################################################
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fig = plt.figure(figsize=(21/2.54, 28/2.54))
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gs = gridspec.GridSpec(3, 2, left=.15, bottom=0.1, right=0.95, top=0.95)
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ax = []
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ax.append(fig.add_subplot(gs[0, 0]))
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ax.append(fig.add_subplot(gs[0, 1], sharex=ax[0]))
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ax.append(fig.add_subplot(gs[1, 0], sharex=ax[0]))
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ax.append(fig.add_subplot(gs[1, 1], sharex=ax[0]))
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ax.append(fig.add_subplot(gs[2, 0], sharex=ax[0]))
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ax.append(fig.add_subplot(gs[2, 1], sharex=ax[0]))
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ax[0].plot(chase_dur, chase_chirp_count, '.')
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ax[0].boxplot(chase_dur_per_chirp_count, positions=positions, vert=False, sym='')
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ax[1].plot(chase_dur, np.array(chase_chirp_count) / np.array(chase_dur), '.')
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ax[2].plot(chase_dur, dt_start_first_chirp, '.')
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ax[3].plot(chase_dur, dt_end_first_chirp, '.')
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ax[2].plot([0, 60], [0, 60], '-k', lw=1)
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ax[3].plot([0, 60], [0, 60], '-k', lw=1)
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ax[2].set_xlabel(r'chase$_{duration}$ [s]', fontsize=12)
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ax[3].set_xlabel(r'chase$_{duration}$ [s]', fontsize=12)
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ax[0].set_ylabel('chirps [n]', fontsize=12)
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ax[1].set_ylabel('chirp rate [Hz]', fontsize=12)
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ax[2].set_ylabel(r'$\Delta$t chase$_{on}$ - chirp$_{0}$', fontsize=12)
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ax[3].set_ylabel(r'$\Delta$t chirp$_{0}$ - chase$_{off}$', fontsize=12)
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n, _ = np.histogram(dt_start_first_chirp, bins=chase_dur_bins)
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n = n / np.sum(n) / (chase_dur_bins[1] - chase_dur_bins[0])
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n = n / chase_dur_count_above_th
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n = n / np.max(n) * chase_dur_pct99
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ax[2].barh(chase_dur_bins[:-1] + (chase_dur_bins[1] - chase_dur_bins[0]) / 2, n,
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height=(chase_dur_bins[1] - chase_dur_bins[0]) * 0.8, color='firebrick', alpha=0.5, zorder=2)
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n, _ = np.histogram(dt_end_first_chirp, bins=chase_dur_bins)
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n = n / np.sum(n) / (chase_dur_bins[1] - chase_dur_bins[0])
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n = n / chase_dur_count_above_th
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n = n / np.max(n) * chase_dur_pct99
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ax[3].barh(chase_dur_bins[:-1] + (chase_dur_bins[1] - chase_dur_bins[0]) / 2, n,
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height=(chase_dur_bins[1] - chase_dur_bins[0]) * 0.8, color='firebrick', alpha=0.5, zorder=2)
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ax[3].invert_yaxis()
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ax[2].set_xlim(right=chase_dur_pct99 + 2)
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ax[2].set_ylim(top=chase_dur_pct99 + 2)
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ax[3].set_xlim(right=chase_dur_pct99 + 2)
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ax[3].set_ylim(bottom=chase_dur_pct99 + 2)
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chase_chirp_count = np.array(chase_chirp_count)
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chase_dur = np.array(chase_dur)
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chirp_rate = chase_chirp_count / chase_dur
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ax[4].plot(chase_dur_all_chirp, dt_start_all_chirp, '.')
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ax[5].plot(chase_dur_all_chirp, dt_end_all_chirp, '.')
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ax[4].plot([0, 60], [0, 60], '-k', lw=1)
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ax[5].plot([0, 60], [0, 60], '-k', lw=1)
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n, _ = np.histogram(dt_start_all_chirp, bins=chase_dur_bins)
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n = n / np.sum(n) / (chase_dur_bins[1] - chase_dur_bins[0])
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n = n / chase_dur_count_above_th
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n = n / np.max(n) * chase_dur_pct99
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ax[4].barh(chase_dur_bins[:-1] + (chase_dur_bins[1] - chase_dur_bins[0])/2, n, height=(chase_dur_bins[1] - chase_dur_bins[0])*0.8, color='firebrick', alpha=0.5, zorder=2)
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n, _ = np.histogram(dt_end_all_chirp, bins=chase_dur_bins)
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n = n / np.sum(n) / (chase_dur_bins[1] - chase_dur_bins[0])
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n = n / chase_dur_count_above_th
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n = n / np.max(n) * chase_dur_pct99
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ax[5].barh(chase_dur_bins[:-1] + (chase_dur_bins[1] - chase_dur_bins[0])/2, n, height=(chase_dur_bins[1] - chase_dur_bins[0])*0.8, color='firebrick', alpha=0.5, zorder=2)
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ax[5].invert_yaxis()
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ax[4].set_xlim(right=chase_dur_pct99+2)
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ax[4].set_ylim(top=chase_dur_pct99+2)
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ax[5].set_xlim(right=chase_dur_pct99+2)
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ax[5].set_ylim(bottom=chase_dur_pct99+2)
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r, p = scp.pearsonr(chase_dur[chase_chirp_count >= 3], chase_chirp_count[chase_chirp_count >= 3])
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ax[0].text(1, 1, f'r= {r:.2f} p={p:.3f}', transform=ax[0].transAxes, ha='right', va='bottom')
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r, p = scp.pearsonr(chase_dur[chase_chirp_count >= 3], chirp_rate[chase_chirp_count >= 3])
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ax[1].text(1, 1, f'r= {r:.2f} p={p:.3f}', transform=ax[1].transAxes, ha='right', va='bottom')
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plt.show()
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fig, ax = plt.subplots()
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ax[4].set_xlabel(r'chase$_{duration}$ [s]', fontsize=12)
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ax[5].set_xlabel(r'chase$_{duration}$ [s]', fontsize=12)
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ax[0].set_ylabel('chirps [n]', fontsize=12)
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ax[1].set_ylabel('chirp rate [Hz]', fontsize=12)
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ax[2].set_ylabel(r'$\Delta$t chase$_{on}$ - chirp$_{0}$', fontsize=12)
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ax[3].set_ylabel(r'$\Delta$t chirp$_{0}$ - chase$_{off}$', fontsize=12)
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ax[4].set_ylabel(r'$\Delta$t chase$_{on}$ - chirps', fontsize=12)
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ax[5].set_ylabel(r'$\Delta$t chirps - chase$_{off}$', fontsize=12)
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# embed()
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# quit()
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plt.show()
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# fig, ax = plt.subplots()
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# n, bin_edges = np.histogram(dt_start_first_chirp[~np.isnan(dt_start_first_chirp)] / chase_dur[~np.isnan(dt_start_first_chirp)], bins = np.arange(0, 1.05, .05))
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# ax.bar(bin_edges[:-1] + (bin_edges[1]-bin_edges[0])/2, n/np.sum(n)/(bin_edges[1] - bin_edges[0]), width=0.8*(bin_edges[1]-bin_edges[0]))
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#
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# n, bin_edges = np.histogram(dt_end_first_chirp[~np.isnan(dt_end_first_chirp)] / chase_dur[~np.isnan(dt_end_first_chirp)], bins = np.arange(0, 1.05, .05))
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# ax.bar(bin_edges[:-1] + (bin_edges[1]-bin_edges[0])/2, n/np.sum(n)/(bin_edges[1] - bin_edges[0]), width=0.8*(bin_edges[1]-bin_edges[0]))
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if __name__ == '__main__':
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main(sys.argv[1])
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@ -257,7 +257,6 @@ def main(base_path):
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lose_chrips_centered_on_win_rises = []
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lose_chrips_centered_on_win_chirp = []
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lose_chirps_centered_on_lose_rises = []
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lose_chirp_count = []
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win_chrips_centered_on_ag_off_t = []
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win_chrips_centered_on_ag_on_t = []
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@ -265,22 +264,25 @@ def main(base_path):
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win_chrips_centered_on_lose_rises = []
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win_chrips_centered_on_lose_chirp = []
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win_chirps_centered_on_win_rises = []
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win_chirp_count = []
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lose_rises_centered_on_ag_off_t = []
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lose_rises_centered_on_ag_on_t = []
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lose_rises_centered_on_contact_t = []
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lose_rises_centered_on_win_chirps = []
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lose_rises_count = []
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win_rises_centered_on_ag_off_t = []
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win_rises_centered_on_ag_on_t = []
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win_rises_centered_on_contact_t = []
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win_rises_centered_on_lose_chirps = []
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win_rises_count = []
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ag_off_centered_on_ag_on = []
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ag_count = []
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lose_chirp_count = []
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win_chirp_count = []
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lose_rises_count = []
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win_rises_count = []
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chase_count = []
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contact_count = []
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sex_win = []
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sex_lose = []
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@ -366,7 +368,8 @@ def main(base_path):
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win_rises_count.append(len(rise_times[0]))
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ag_off_centered_on_ag_on.append(event_centered_times(ag_on_off_t_GRID[:, 0], ag_on_off_t_GRID[:, 1]))
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ag_count.append(len(ag_on_off_t_GRID))
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chase_count.append(len(ag_on_off_t_GRID))
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contact_count.append(len(contact_t_GRID))
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sex_win.append(trial['sex_win'])
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sex_lose.append(trial['sex_lose'])
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@ -381,34 +384,63 @@ def main(base_path):
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conv_t = cp.arange(-max_dt, max_dt+conv_t_dt, conv_t_dt)
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conv_t_numpy = cp.asnumpy(conv_t)
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# kde_array = kde(np.hstack(lose_chrips_centered_on_ag_off_t), conv_t, kernal_w = 1, kernal_h = 1)
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for centered_times, event_counts, title in \
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[[lose_chrips_centered_on_ag_off_t, lose_chirp_count, r'chirp$_{lose}$ on chase$_{off}$'],
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[lose_chrips_centered_on_ag_on_t, lose_chirp_count, r'chirp$_{lose}$ on chase$_{on}$'],
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[lose_chrips_centered_on_contact_t, lose_chirp_count, r'chirp$_{lose}$ on contact'],
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[lose_chrips_centered_on_win_rises, lose_chirp_count, r'chirp$_{lose}$ on rise$_{win}$'],
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[lose_chrips_centered_on_win_chirp, lose_chirp_count, r'chirp$_{lose}$ on chirp$_{win}$'],
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[lose_chirps_centered_on_lose_rises, lose_chirp_count, r'chirp$_{lose}$ on rises$_{lose}$'],
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[win_chrips_centered_on_ag_off_t, win_chirp_count, r'chirp$_{win}$ on chase$_{off}$'],
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[win_chrips_centered_on_ag_on_t, win_chirp_count, r'chirp$_{win}$ on chase$_{on}$'],
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[win_chrips_centered_on_contact_t, win_chirp_count, r'chirp$_{win}$ on contact'],
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[win_chrips_centered_on_lose_rises, win_chirp_count, r'chirp$_{win}$ on rise$_{lose}$'],
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[win_chrips_centered_on_lose_chirp, win_chirp_count, r'chirp$_{win}$ on chirp$_{lose}$'],
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[win_chirps_centered_on_win_rises, win_chirp_count, r'chirp$_{win}$ on rises$_{win}$'],
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[lose_rises_centered_on_ag_off_t, lose_rises_count, r'rise$_{lose}$ on chase$_{off}$'],
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[lose_rises_centered_on_ag_on_t, lose_rises_count, r'rise$_{lose}$ on chase$_{on}$'],
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[lose_rises_centered_on_contact_t, lose_rises_count, r'rise$_{lose}$ on contact'],
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[lose_rises_centered_on_win_chirps, lose_rises_count, r'rise$_{lose}$ on chirp$_{win}$'],
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[win_rises_centered_on_ag_off_t, win_rises_count, r'rise$_{win}$ on chase$_{off}$'],
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[win_rises_centered_on_ag_on_t, win_rises_count, r'rise$_{win}$ on chase$_{on}$'],
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[win_rises_centered_on_contact_t, win_rises_count, r'rise$_{win}$ on contact'],
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[win_rises_centered_on_lose_chirps, win_rises_count, r'rise$_{win}$ on chirp$_{lose}$'],
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[ag_off_centered_on_ag_on, ag_count, r'chase$_{off}$ on chase$_{on}$']]:
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# embed()
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# quit()
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# for centered_times, event_counts, title in \
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# [[lose_chrips_centered_on_ag_off_t, lose_chirp_count, r'chirp$_{lose}$ on chase$_{off}$'],
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# [lose_chrips_centered_on_ag_on_t, lose_chirp_count, r'chirp$_{lose}$ on chase$_{on}$'],
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# [lose_chrips_centered_on_contact_t, lose_chirp_count, r'chirp$_{lose}$ on contact'],
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# [lose_chrips_centered_on_win_rises, lose_chirp_count, r'chirp$_{lose}$ on rise$_{win}$'],
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# [lose_chrips_centered_on_win_chirp, lose_chirp_count, r'chirp$_{lose}$ on chirp$_{win}$'],
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# [lose_chirps_centered_on_lose_rises, lose_chirp_count, r'chirp$_{lose}$ on rises$_{lose}$'],
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#
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# [win_chrips_centered_on_ag_off_t, win_chirp_count, r'chirp$_{win}$ on chase$_{off}$'],
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# [win_chrips_centered_on_ag_on_t, win_chirp_count, r'chirp$_{win}$ on chase$_{on}$'],
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# [win_chrips_centered_on_contact_t, win_chirp_count, r'chirp$_{win}$ on contact'],
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# [win_chrips_centered_on_lose_rises, win_chirp_count, r'chirp$_{win}$ on rise$_{lose}$'],
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# [win_chrips_centered_on_lose_chirp, win_chirp_count, r'chirp$_{win}$ on chirp$_{lose}$'],
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# [win_chirps_centered_on_win_rises, win_chirp_count, r'chirp$_{win}$ on rises$_{win}$'],
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#
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# [lose_rises_centered_on_ag_off_t, lose_rises_count, r'rise$_{lose}$ on chase$_{off}$'],
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# [lose_rises_centered_on_ag_on_t, lose_rises_count, r'rise$_{lose}$ on chase$_{on}$'],
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# [lose_rises_centered_on_contact_t, lose_rises_count, r'rise$_{lose}$ on contact'],
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# [lose_rises_centered_on_win_chirps, lose_rises_count, r'rise$_{lose}$ on chirp$_{win}$'],
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#
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# [win_rises_centered_on_ag_off_t, win_rises_count, r'rise$_{win}$ on chase$_{off}$'],
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# [win_rises_centered_on_ag_on_t, win_rises_count, r'rise$_{win}$ on chase$_{on}$'],
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# [win_rises_centered_on_contact_t, win_rises_count, r'rise$_{win}$ on contact'],
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# [win_rises_centered_on_lose_chirps, win_rises_count, r'rise$_{win}$ on chirp$_{lose}$'],
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#
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# [ag_off_centered_on_ag_on, chase_count, r'chase$_{off}$ on chase$_{on}$']]:
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for centered_times, event_counts, title in \
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[[lose_chrips_centered_on_ag_off_t, chase_count, r'chirp$_{lose}$ on chase$_{off}$'],
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[lose_chrips_centered_on_ag_on_t, chase_count, r'chirp$_{lose}$ on chase$_{on}$'],
|
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[lose_chrips_centered_on_contact_t, contact_count, r'chirp$_{lose}$ on contact'],
|
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[lose_chrips_centered_on_win_rises, win_rises_count, r'chirp$_{lose}$ on rise$_{win}$'],
|
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[lose_chrips_centered_on_win_chirp, win_chirp_count, r'chirp$_{lose}$ on chirp$_{win}$'],
|
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[lose_chirps_centered_on_lose_rises, lose_rises_count, r'chirp$_{lose}$ on rises$_{lose}$'],
|
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|
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[win_chrips_centered_on_ag_off_t, chase_count, r'chirp$_{win}$ on chase$_{off}$'],
|
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[win_chrips_centered_on_ag_on_t, chase_count, r'chirp$_{win}$ on chase$_{on}$'],
|
||||
[win_chrips_centered_on_contact_t, contact_count, r'chirp$_{win}$ on contact'],
|
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[win_chrips_centered_on_lose_rises, lose_rises_count, r'chirp$_{win}$ on rise$_{lose}$'],
|
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[win_chrips_centered_on_lose_chirp, lose_chirp_count, r'chirp$_{win}$ on chirp$_{lose}$'],
|
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[win_chirps_centered_on_win_rises, win_rises_count, r'chirp$_{win}$ on rises$_{win}$'],
|
||||
|
||||
[lose_rises_centered_on_ag_off_t, chase_count, r'rise$_{lose}$ on chase$_{off}$'],
|
||||
[lose_rises_centered_on_ag_on_t, chase_count, r'rise$_{lose}$ on chase$_{on}$'],
|
||||
[lose_rises_centered_on_contact_t, contact_count, r'rise$_{lose}$ on contact'],
|
||||
[lose_rises_centered_on_win_chirps, win_chirp_count, r'rise$_{lose}$ on chirp$_{win}$'],
|
||||
|
||||
[win_rises_centered_on_ag_off_t, chase_count, r'rise$_{win}$ on chase$_{off}$'],
|
||||
[win_rises_centered_on_ag_on_t, chase_count, r'rise$_{win}$ on chase$_{on}$'],
|
||||
[win_rises_centered_on_contact_t, contact_count, r'rise$_{win}$ on contact'],
|
||||
[win_rises_centered_on_lose_chirps, lose_chirp_count, r'rise$_{win}$ on chirp$_{lose}$'],
|
||||
|
||||
[ag_off_centered_on_ag_on, chase_count, r'chase$_{off}$ on chase$_{on}$']]:
|
||||
save_str = title.replace('$', '').replace('{', '').replace('}', '').replace(' ', '_')
|
||||
|
||||
###########################################################################################################
|
||||
@ -491,15 +523,19 @@ def main(base_path):
|
||||
fig = plt.figure(figsize=(20/2.54, 12/2.54))
|
||||
gs = gridspec.GridSpec(1, 1, left=0.1, bottom=0.1, right=0.95, top=0.95)
|
||||
ax = fig.add_subplot(gs[0, 0])
|
||||
# ax.fill_between(conv_t_numpy, perm_p1/np.sum(event_counts), perm_p99/np.sum(event_counts), color='cornflowerblue', alpha=.8)
|
||||
# ax.plot(conv_t_numpy, perm_p50/np.sum(event_counts), color='dodgerblue', alpha=1, lw=3)
|
||||
ax.fill_between(conv_t_numpy, perm_p1/len(np.hstack(centered_times)), perm_p99/len(np.hstack(centered_times)), color='cornflowerblue', alpha=.8)
|
||||
ax.plot(conv_t_numpy, perm_p50/len(np.hstack(centered_times)), color='dodgerblue', alpha=1, lw=3)
|
||||
|
||||
# ax.fill_between(conv_t_numpy, jk_p1/np.sum(event_counts)/jack_pct, jk_p99/np.sum(event_counts)/jack_pct, color='tab:red', alpha=.8)
|
||||
# ax.plot(conv_t_numpy, jk_p50/np.sum(event_counts)/jack_pct, color='firebrick', alpha=1, lw=3)
|
||||
ax.fill_between(conv_t_numpy, jk_p1/len(np.hstack(centered_times))/jack_pct, jk_p99/len(np.hstack(centered_times))/jack_pct, color='tab:red', alpha=.8)
|
||||
ax.plot(conv_t_numpy, jk_p50/len(np.hstack(centered_times))/jack_pct, color='firebrick', alpha=1, lw=3)
|
||||
|
||||
# ax.fill_between(conv_t_numpy, perm_p1/len(np.hstack(centered_times)), perm_p99/len(np.hstack(centered_times)), color='cornflowerblue', alpha=.8)
|
||||
# ax.plot(conv_t_numpy, perm_p50/len(np.hstack(centered_times)), color='dodgerblue', alpha=1, lw=3)
|
||||
#
|
||||
# ax.fill_between(conv_t_numpy, jk_p1/len(np.hstack(centered_times))/jack_pct, jk_p99/len(np.hstack(centered_times))/jack_pct, color='tab:red', alpha=.8)
|
||||
# ax.plot(conv_t_numpy, jk_p50/len(np.hstack(centered_times))/jack_pct, color='firebrick', alpha=1, lw=3)
|
||||
|
||||
ax.fill_between(conv_t_numpy, perm_p1/np.nansum(event_counts), perm_p99/np.nansum(event_counts), color='cornflowerblue', alpha=.8)
|
||||
ax.plot(conv_t_numpy, perm_p50/np.nansum(event_counts), color='dodgerblue', alpha=1, lw=3)
|
||||
|
||||
ax.fill_between(conv_t_numpy, jk_p1/np.nansum(event_counts)/jack_pct, jk_p99/np.nansum(event_counts)/jack_pct, color='tab:red', alpha=.8)
|
||||
ax.plot(conv_t_numpy, jk_p50/np.nansum(event_counts)/jack_pct, color='firebrick', alpha=1, lw=3)
|
||||
|
||||
|
||||
ax_m = ax.twinx()
|
||||
for enu, centered_events in enumerate(centered_times):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user