raab/competition_experiments
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

markov models and iei interval analysis completed

Browse Source
This commit is contained in:
Till Raab 2023-06-19 15:28:53 +02:00
parent 3a4ece9902
commit a038c2f696
1 changed files with 16 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
event_time_analysis.py
View File

@ -13,7 +13,6 @@ from event_time_correlations import load_and_converete_boris_events, kde, gauss
female_color, male_color = '#e74c3c', '#3498db' female_color, male_color = '#e74c3c', '#3498db'
def iei_analysis(event_times, win_sex, lose_sex, kernal_w, title=''): def iei_analysis(event_times, win_sex, lose_sex, kernal_w, title=''):
# ToDo: finish this !!!
iei = [] iei = []
weighted_mean_iei = [] weighted_mean_iei = []
median_iei = [] median_iei = []
@ -32,12 +31,10 @@ def iei_analysis(event_times, win_sex, lose_sex, kernal_w, title=''):
median_iei = np.array(median_iei) median_iei = np.array(median_iei)
fig = plt.figure(figsize=(20 / 2.54, 12 / 2.54)) 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=0.9) gs = gridspec.GridSpec(1, 2, left=0.1, bottom=0.2, right=0.95, top=0.9, width_ratios=[5, 1], wspace=.3)
ax = [] ax = []
ax.append(fig.add_subplot(gs[0, 0])) 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[0, 1]))
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)): for i in range(len(iei)):
if win_sex[i] == 'm': if win_sex[i] == 'm':
@ -59,27 +56,29 @@ def iei_analysis(event_times, win_sex, lose_sex, kernal_w, title=''):
kde_array = kde(iei[i], conv_y, kernal_w=kernal_w, kernal_h=1) kde_array = kde(iei[i], conv_y, kernal_w=kernal_w, kernal_h=1)
# kde_array /= np.sum(kde_array) # kde_array /= np.sum(kde_array)
ax[sp].plot(conv_y, kde_array, zorder=2, color=color, linestyle=linestyle, lw=2) ax[0].plot(conv_y, kde_array, zorder=2, color=color, linestyle=linestyle, lw=2)
# ax_m = ax[0].twinx()
# ax_m.boxplot([weighted_mean_iei[(win_sex == 'm') & (win_sex == 'm') & ~np.isnan(weighted_mean_iei)], ax[1].boxplot([weighted_mean_iei[~np.isnan(weighted_mean_iei)],
# median_iei[(win_sex == 'm') & (win_sex == 'm') & ~np.isnan(median_iei)]], sym='', vert=False) median_iei[~np.isnan(median_iei)]], positions=[0, 1], sym='', widths=0.5)
ax[0].set_xlim(conv_y[0], conv_y[-1]) ax[0].set_xlim(conv_y[0], conv_y[-1])
ax[0].set_ylabel('KDE', fontsize=12) ax[0].set_ylabel('KDE', fontsize=12)
ax[2].set_ylabel('KDE', fontsize=12) ax[0].set_xlabel('inter event interval [s]', fontsize=12)
ax[2].set_xlabel('time [s]', fontsize=12)
ax[3].set_xlabel('time [s]', fontsize=12)
fig.suptitle(title, fontsize=12) fig.suptitle(title, fontsize=12)
for a in ax: for a in ax:
a.tick_params(labelsize=10) a.tick_params(labelsize=10)
plt.setp(ax[1].get_yticklabels(), visible=False) ax[1].set_xticks(np.arange(2))
plt.setp(ax[3].get_yticklabels(), visible=False) ax[1].set_xticklabels([r'weighted$_{time}$', 'median'], rotation=45)
ax[1].set_ylabel('inter event interval [s]', fontsize=12)
plt.setp(ax[0].get_xticklabels(), visible=False) # ax[0]
plt.setp(ax[1].get_xticklabels(), visible=False) # 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.savefig(os.path.join(os.path.split(__file__)[0], 'figures', 'event_meta', f'{title}_iei.png'), dpi=300) plt.savefig(os.path.join(os.path.split(__file__)[0], 'figures', 'event_meta', f'{title}_iei.png'), dpi=300)
plt.close() plt.close()