data.get_delays_times()
for gv.session in [gv.sessions[-1]]:
X_data, y_labels = data.get_fluo_data()
print('mouse', gv.mouse, 'session', gv.session, 'data X',
X_data.shape, 'y', y_labels.shape)
data.get_delays_times()
data.get_frame_rate()
data.get_bins(t_start=0)
gv.duration = X_data.shape[2] / gv.frame_rate
time = np.linspace(0, gv.duration, X_data.shape[2])
for gv.trial in [gv.trials[-1]]:
X_S1_trials, X_S2_trials = data.get_S1_S2_trials(
X_data, y_labels)
X_trials, y_trials = data.get_X_y_epochs(
X_S1_trials, X_S2_trials)
print('trial:', gv.trial, 'X', X_trials.shape, 'y',
y_trials.shape)
X_avg = np.mean(X_trials, axis=1)
fit_values = detrend_data(X_trials[0], poly_fit=1, degree=7)
plt.figure()
plt.plot(X_avg[0])
plt.plot(np.mean(fit_values, axis=0), '--k')
for gv.session in [gv.sessions[-1]]:
X, y = data.get_fluo_data()
print('mouse', gv.mouse, 'session', gv.session, 'data X', X.shape, 'y',
y.shape)
data.get_delays_times()
data.get_frame_rate()
data.get_bins(t_start=.5)
gv.duration = X.shape[2] / gv.frame_rate
gv.time = np.linspace(0, gv.duration, X.shape[2])
trial_averages = []
for i, gv.trial in enumerate(gv.trials):
X_S1, X_S2 = data.get_S1_S2_trials(X, y)
data.get_trial_types(X_S1)
print('X_S1', X_S1.shape, 'X_S2', X_S2.shape)
X_S1 = np.mean(X_S1[:, :, gv.bins_ED], axis=2)
X_S2 = np.mean(X_S2[:, :, gv.bins_ED], axis=2)
X_S1 = np.mean(X_S1, axis=0)
X_S2 = np.mean(X_S2, axis=0)
# idx = np.where(X_S1<.000005)
# X_S1 = np.delete(X_S1, idx)
# X_S2 = np.delete(X_S2, idx)
# idx = np.where(X_S2<.000005)