if __name__ == "__main__":
IF_EPOCHS = 0
if IF_EPOCHS == 0:
gv.epochs = ['all']
for gv.mouse in [gv.mice[0]]:
data.get_sessions_mouse()
data.get_stimuli_times()
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)
import preprocessing as pre
from plotting import *
from matplotlib.ticker import PercentFormatter
pal = ['r', 'b', 'y']
gv.data_type = 'rates'
for gv.mouse in [gv.mice[2]]:
data.get_sessions_mouse()
data.get_stimuli_times()
data.get_delays_times()
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)