def test_fix_stim_artifact():
"""Test fix stim artifact."""
events = read_events(event_fname)
raw = read_raw_fif(raw_fname)
pytest.raises(RuntimeError, fix_stim_artifact, raw)
raw = read_raw_fif(raw_fname, preload=True)
# use window before stimulus in epochs
tmin, tmax, event_id = -0.2, 0.5, 1
picks = pick_types(raw.info,
meg=True,
eeg=True,
eog=True,
stim=False,
exclude='bads')
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
preload=True,
reject=None)
e_start = int(np.ceil(epochs.info['sfreq'] * epochs.tmin))
tmin, tmax = -0.045, -0.015
tmin_samp = int(-0.035 * epochs.info['sfreq']) - e_start
tmax_samp = int(-0.015 * epochs.info['sfreq']) - e_start
epochs = fix_stim_artifact(epochs, tmin=tmin, tmax=tmax, mode='linear')
data = epochs.get_data()[:, :, tmin_samp:tmax_samp]
diff_data0 = np.diff(data[0][0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
epochs = fix_stim_artifact(epochs, tmin=tmin, tmax=tmax, mode='window')
data_from_epochs_fix = epochs.get_data()[:, :, tmin_samp:tmax_samp]
# XXX This is a very weird check...
assert np.all(data_from_epochs_fix) == 0.
# use window before stimulus in raw
event_idx = np.where(events[:, 2] == 1)[0][0]
tmin, tmax = -0.045, -0.015
tmin_samp = int(-0.035 * raw.info['sfreq'])
tmax_samp = int(-0.015 * raw.info['sfreq'])
tidx = int(events[event_idx, 0] - raw.first_samp)
pytest.raises(ValueError, fix_stim_artifact, raw, events=np.array([]))
raw = fix_stim_artifact(raw,
events=None,
event_id=1,
tmin=tmin,
tmax=tmax,
mode='linear',
stim_channel='STI 014')
data, times = raw[:, (tidx + tmin_samp):(tidx + tmax_samp)]
diff_data0 = np.diff(data[0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
raw = fix_stim_artifact(raw,
events,
event_id=1,
tmin=tmin,
tmax=tmax,
mode='window')
data, times = raw[:, (tidx + tmin_samp):(tidx + tmax_samp)]
assert np.all(data) == 0.
# get epochs from raw with fixed data
tmin, tmax, event_id = -0.2, 0.5, 1
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
preload=True,
reject=None,
baseline=None)
e_start = int(np.ceil(epochs.info['sfreq'] * epochs.tmin))
tmin_samp = int(-0.035 * epochs.info['sfreq']) - e_start
tmax_samp = int(-0.015 * epochs.info['sfreq']) - e_start
data_from_raw_fix = epochs.get_data()[:, :, tmin_samp:tmax_samp]
assert np.all(data_from_raw_fix) == 0.
# use window after stimulus
evoked = epochs.average()
tmin, tmax = 0.005, 0.045
tmin_samp = int(0.015 * evoked.info['sfreq']) - evoked.first
tmax_samp = int(0.035 * evoked.info['sfreq']) - evoked.first
evoked = fix_stim_artifact(evoked, tmin=tmin, tmax=tmax, mode='linear')
data = evoked.data[:, tmin_samp:tmax_samp]
diff_data0 = np.diff(data[0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
evoked = fix_stim_artifact(evoked, tmin=tmin, tmax=tmax, mode='window')
data = evoked.data[:, tmin_samp:tmax_samp]
assert np.all(data) == 0.
def test_fix_stim_artifact():
"""Test fix stim artifact."""
events = read_events(event_fname)
raw = read_raw_fif(raw_fname)
assert_raises(RuntimeError, fix_stim_artifact, raw)
raw = read_raw_fif(raw_fname, preload=True)
# use window before stimulus in epochs
tmin, tmax, event_id = -0.2, 0.5, 1
picks = pick_types(raw.info, meg=True, eeg=True,
eog=True, stim=False, exclude='bads')
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
preload=True, reject=None)
e_start = int(np.ceil(epochs.info['sfreq'] * epochs.tmin))
tmin, tmax = -0.045, -0.015
tmin_samp = int(-0.035 * epochs.info['sfreq']) - e_start
tmax_samp = int(-0.015 * epochs.info['sfreq']) - e_start
epochs = fix_stim_artifact(epochs, tmin=tmin, tmax=tmax, mode='linear')
data = epochs.get_data()[:, :, tmin_samp:tmax_samp]
diff_data0 = np.diff(data[0][0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
epochs = fix_stim_artifact(epochs, tmin=tmin, tmax=tmax, mode='window')
data_from_epochs_fix = epochs.get_data()[:, :, tmin_samp:tmax_samp]
assert_true(np.all(data_from_epochs_fix) == 0.)
# use window before stimulus in raw
event_idx = np.where(events[:, 2] == 1)[0][0]
tmin, tmax = -0.045, -0.015
tmin_samp = int(-0.035 * raw.info['sfreq'])
tmax_samp = int(-0.015 * raw.info['sfreq'])
tidx = int(events[event_idx, 0] - raw.first_samp)
assert_raises(ValueError, fix_stim_artifact, raw, events=np.array([]))
raw = fix_stim_artifact(raw, events=None, event_id=1, tmin=tmin,
tmax=tmax, mode='linear', stim_channel='STI 014')
data, times = raw[:, (tidx + tmin_samp):(tidx + tmax_samp)]
diff_data0 = np.diff(data[0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
raw = fix_stim_artifact(raw, events, event_id=1, tmin=tmin,
tmax=tmax, mode='window')
data, times = raw[:, (tidx + tmin_samp):(tidx + tmax_samp)]
assert_true(np.all(data) == 0.)
# get epochs from raw with fixed data
tmin, tmax, event_id = -0.2, 0.5, 1
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
preload=True, reject=None, baseline=None)
e_start = int(np.ceil(epochs.info['sfreq'] * epochs.tmin))
tmin_samp = int(-0.035 * epochs.info['sfreq']) - e_start
tmax_samp = int(-0.015 * epochs.info['sfreq']) - e_start
data_from_raw_fix = epochs.get_data()[:, :, tmin_samp:tmax_samp]
assert_true(np.all(data_from_raw_fix) == 0.)
# use window after stimulus
evoked = epochs.average()
tmin, tmax = 0.005, 0.045
tmin_samp = int(0.015 * evoked.info['sfreq']) - evoked.first
tmax_samp = int(0.035 * evoked.info['sfreq']) - evoked.first
evoked = fix_stim_artifact(evoked, tmin=tmin, tmax=tmax, mode='linear')
data = evoked.data[:, tmin_samp:tmax_samp]
diff_data0 = np.diff(data[0])
diff_data0 -= np.mean(diff_data0)
assert_array_almost_equal(diff_data0, np.zeros(len(diff_data0)))
evoked = fix_stim_artifact(evoked, tmin=tmin, tmax=tmax, mode='window')
data = evoked.data[:, tmin_samp:tmax_samp]
assert_true(np.all(data) == 0.)