def test_union(epoch_a, epoch_b):
expected = np.array([
[0, 50],
[55, 70],
[75, 76],
[77, 77],
[85, 100],
[110, 120],
])
result = epoch_union(epoch_a, epoch_b)
assert np.all(result == expected)
def test_union_float(epoch_a, epoch_b):
expected = np.array([
[0, 50],
[55, 70],
[75, 76],
[77, 77],
[85, 100],
[110, 120],
[140, 150],
]) / 10
result = epoch_union(epoch_a / 10, epoch_b / 10)
assert np.all(result == expected)
def get_est_val_times(recording, balance_phase=False):
rng = np.random.RandomState(0)
epochs = recording.epochs
est_times, val_times = get_est_val_times_by_sequence(recording, rng)
if balance_phase:
target_times = select_balanced_targets(epochs, rng)
m = epochs['name'].str.contains('^repeating$')
repeating_times = epochs.loc[m, ['start', 'end']].values
# Remove the repeating phase from the dataset
est_times = epoch_difference(est_times, repeating_times)
# Now, add back in selected targets from repeating phase
est_times = epoch_union(est_times, target_times)
# Remove the repeating phase from the dataset
val_times = epoch_difference(val_times, repeating_times)
# Now, add back in selected targets from repeating phase
val_times = epoch_union(val_times, target_times)
return est_times, val_times