From f096e9ba4f642b10d37f68ae2676077ad3becfd3 Mon Sep 17 00:00:00 2001
From: Till Raab <till.raab@uni-tuebingen.de>
Date: Thu, 1 Jun 2023 10:46:13 +0200
Subject: [PATCH] inter event interval analysis done. make function more
universial. relative rate progresion of ecent evaluated
---
complete_analysis.py | 23 -------
event_time_analysis.py | 149 ++++++++++++++++++++++++++++++++---------
2 files changed, 117 insertions(+), 55 deletions(-)
diff --git a/complete_analysis.py b/complete_analysis.py
index c92e432..f4e4db0 100644
--- a/complete_analysis.py
+++ b/complete_analysis.py
@@ -360,29 +360,6 @@ def main(data_folder=None):
# plt.savefig(os.path.join(os.path.join(os.path.split(__file__)[0], 'figures', f'{recording}.png')), dpi=300)
plt.close()
- # fig = plt.figure(figsize=(20/2.54, 20/2.54))
- # gs = gridspec.GridSpec(2, 2, left=0.1, bottom=0.1, right=0.95, top=0.95, height_ratios=[1, 3], width_ratios=[3, 1])
- # ax = fig.add_subplot(gs[1, 0])
- #
- # ax.plot(trial_summary['rises_win'], trial_summary['chirps_win'], 'o', color=Wc, label='winner')
- # ax.plot(trial_summary['rise_lose'], trial_summary['chirps_lose'], 'o', color=Lc, label='loster')
- # ax.set_xlabel('rises [n]', fontsize=12)
- # ax.set_ylabel('chirps [n]', fontsize=12)
- # ax.tick_params(labelsize=10)
- #
- # ax_chirps = fig.add_subplot(gs[1, 1], sharey=ax)
- # ax_chirps.boxplot([trial_summary['chirps_win'], trial_summary['chirps_lose']], widths = .5, positions = [1, 2])
- # ax_chirps.set_xticks([1, 2])
- # ax_chirps.set_xticklabels(['Win', 'Lose'])
- # plt.setp(ax_chirps.get_yticklabels(), visible=False)
- #
- # ax_rises = fig.add_subplot(gs[0, 0], sharex=ax)
- # ax_rises.boxplot([trial_summary['rises_win'], trial_summary['rise_lose']], widths = .5, positions = [1, 2], vert=False)
- # ax_rises.set_yticks([1, 2])
- # ax_rises.set_yticklabels(['Win', 'Lose'])
- # plt.setp(ax_rises.get_xticklabels(), visible=False)
- #
- # plt.show()
for g in pd.unique(trial_summary['group']):
diff --git a/event_time_analysis.py b/event_time_analysis.py
index 4d296f8..8cf5362 100644
--- a/event_time_analysis.py
+++ b/event_time_analysis.py
@@ -7,10 +7,111 @@ import pandas as pd
from IPython import embed
from event_time_correlations import load_and_converete_boris_events, kde, gauss
+female_color, male_color = '#e74c3c', '#3498db'
+
+def iei_analysis(all_chirp_times_lose, all_chirp_times_win, all_rise_times_lose, all_rise_times_win, win_sex, lose_sex):
+ ici_lose = []
+ ici_win = []
+
+ iri_lose = []
+ iri_win = []
+
+ for i in range(len(all_chirp_times_lose)):
+ ici_lose.append(np.diff(all_chirp_times_lose[i]))
+ ici_win.append(np.diff(all_chirp_times_win[i]))
+
+ iri_lose.append(np.diff(all_rise_times_lose[i]))
+ iri_win.append(np.diff(all_rise_times_win[i]))
+
+ for iei, kernal_w in zip([ici_lose, ici_win, iri_lose, iri_win],
+ [1, 1, 5, 50]):
+
+ fig = plt.figure(figsize=(20 / 2.54, 12 / 2.54))
+ gs = gridspec.GridSpec(2, 2, left=0.1, bottom=0.1, right=0.95, top=0.95)
+ ax = []
+ ax.append(fig.add_subplot(gs[0, 0]))
+ ax.append(fig.add_subplot(gs[0, 1], sharey=ax[0], sharex=ax[0]))
+ ax.append(fig.add_subplot(gs[1, 0], sharey=ax[0], sharex=ax[0]))
+ ax.append(fig.add_subplot(gs[1, 1], sharey=ax[0], sharex=ax[0]))
+
+ for i in range(len(iei)):
+ if win_sex[i] == 'm':
+ if lose_sex[i] == 'm':
+ color, linestyle = male_color, '-'
+ sp = 0
+ else:
+ color, linestyle = male_color, '--'
+ sp = 1
+ else:
+ if lose_sex[i] == 'm':
+ color, linestyle = female_color, '--'
+ sp = 2
+ else:
+ color, linestyle = female_color, '-'
+ sp = 3
+
+
+ conv_y_chirp_lose = np.arange(0, np.percentile(np.hstack(iei), 90), .5)
+ kde_array = kde(iei[i], conv_y_chirp_lose, kernal_w=kernal_w, kernal_h=1)
+
+ # kde_array /= np.sum(kde_array)
+ ax[sp].plot(conv_y_chirp_lose, kde_array, zorder=2, color=color, linestyle=linestyle, lw=2)
+
+ plt.setp(ax[1].get_yticklabels(), visible=False)
+ plt.setp(ax[3].get_yticklabels(), visible=False)
+
+
+ plt.setp(ax[0].get_xticklabels(), visible=False)
+ plt.setp(ax[1].get_xticklabels(), visible=False)
+ plt.show()
+
+
+def relative_rate_progression(all_event_t, title=''):
+ stop_t = 3*60*60
+ snippet_len = 15*60
+
+ snippet_starts = np.arange(0, stop_t, snippet_len)
+ all_snippet_ratio = []
+ for event_t in all_event_t:
+ expected_snippet_count = len(event_t[event_t <= stop_t]) / (stop_t / snippet_len)
+
+ snippet_ratio = []
+ for s0 in snippet_starts:
+ snippet_count = len(event_t[(event_t >= s0) & (event_t < s0 + snippet_len)])
+ snippet_ratio.append(snippet_count/expected_snippet_count)
+
+ all_snippet_ratio.append(snippet_ratio)
+ all_snippet_ratio = np.array(all_snippet_ratio)
+
+ fig = plt.figure(figsize=(20/2.54, 12/2.54))
+ gs = gridspec.GridSpec(1, 1, left=.1, bottom=.1, right=0.95, top=0.95)
+ ax = fig.add_subplot(gs[0, 0])
+
+ plot_t = np.repeat(snippet_starts, 2)
+ plot_t[1::2] += snippet_len
+
+ for event_ratios in all_snippet_ratio:
+ plot_ratios = np.repeat(event_ratios, 2)
+ ax.plot(plot_t / 3600, plot_ratios, color='grey', lw=1, alpha=0.5)
+ # ax.plot(snippet_starts + snippet_len/2, event_ratios)
+ mean_ratio = np.median(all_snippet_ratio, axis=0)
+ plot_mean_ratio = np.repeat(mean_ratio, 2)
+ ax.plot(plot_t / 3600, plot_mean_ratio, color='k', lw=3)
+ ax.plot(plot_t / 3600, np.ones_like(plot_t), linestyle='dotted', lw=2, color='k')
+
+ ax.set_xlabel('time [h]', fontsize=12)
+ ax.set_ylabel('norm. event rate', fontsize=12)
+ ax.set_title(title)
+ ax.tick_params(labelsize=10)
+
+ ax.set_xlim(0, 3)
+ ax.set_ylim(0, 5)
+
+ plt.show()
+
def main(base_path):
trial_summary = pd.read_csv('trial_summary.csv', index_col=0)
- female_color, male_color = '#e74c3c', '#3498db'
all_rise_times_lose = []
all_rise_times_win = []
@@ -19,6 +120,9 @@ def main(base_path):
win_sex = []
lose_sex = []
+ all_contact_t = []
+ all_ag_on_t = []
+
for index, trial in trial_summary.iterrows():
print(index, len(trial_summary))
got_boris = False
@@ -42,6 +146,8 @@ def main(base_path):
if got_boris:
contact_t_GRID, ag_on_off_t_GRID, led_idx, led_frames = \
load_and_converete_boris_events(trial_path, trial['recording'], sr=20_000)
+ all_contact_t.append(contact_t_GRID)
+ all_ag_on_t.append(ag_on_off_t_GRID[:, 0])
### communication
if not os.path.exists(os.path.join(trial_path, 'chirp_times_cnn.npy')):
@@ -61,43 +167,22 @@ def main(base_path):
all_chirp_times_lose.append(chirp_times[1])
all_chirp_times_win.append(chirp_times[0])
+
win_sex.append(trial['sex_win'])
lose_sex.append(trial['sex_lose'])
+ iei_analysis(all_chirp_times_lose, all_chirp_times_win, all_rise_times_lose, all_rise_times_win, win_sex, lose_sex)
- embed()
- quit()
- ici_lose = []
- ici_win = []
- for i in range(len(all_chirp_times_lose)):
- ici_lose.append(np.diff(all_chirp_times_lose[i]))
- ici_win.append(np.diff(all_chirp_times_win[i]))
-
- 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])
-
- for i in range(len(ici_lose)):
- if win_sex[i] == 'm':
- if lose_sex[i] == 'm':
- color, linestyle = male_color, '-'
- else:
- color, linestyle = male_color, '--'
- else:
- if lose_sex[i] == 'm':
- color, linestyle = female_color, '--'
- else:
- color, linestyle = female_color, '-'
+ relative_rate_progression(all_chirp_times_lose, title=r'chirp$_{lose}$')
+ relative_rate_progression(all_chirp_times_win, title=r'chirp$_{win}$')
+ relative_rate_progression(all_rise_times_lose, title=r'rise$_{lose}$')
+ relative_rate_progression(all_rise_times_win, title=r'rise$_{win}$')
+ relative_rate_progression(all_contact_t, title=r'contact')
+ relative_rate_progression(all_ag_on_t, title=r'chasing')
- conv_y_chirp_lose = np.arange(0, 30, .5)
- kde_array = kde(ici_lose[i], conv_y_chirp_lose, kernal_w=1, kernal_h=1)
-
- # kde_array /= np.sum(kde_array)
- ax.plot(conv_y_chirp_lose, kde_array, zorder=2, color=color, linestyle=linestyle, lw=2)
-
- plt.show()
-
+ embed()
+ quit()
pass