def run_ica(name, save_dir, lowpass, overwrite):
ica_name = name + filter_string(lowpass) + '-ica.fif'
ica_path = join(save_dir, ica_name)
if overwrite or not isfile(ica_path):
raw = io.read_filtered(name, save_dir, lowpass)
epochs = io.read_epochs(name, save_dir, lowpass)
ica = mne.preprocessing.ICA(n_components=0.95, method='fastica')
ica.fit(epochs)
eog_epochs = mne.preprocessing.create_eog_epochs(raw)
ecg_epochs = mne.preprocessing.create_ecg_epochs(raw)
eog_indices, eog_scores = ica.find_bads_eog(eog_epochs)
ecg_indices, ecg_scores = ica.find_bads_ecg(ecg_epochs)
ica.exclude += eog_indices
ica.exclude += ecg_indices
ica.save(ica_path)
else:
print('ica file: ' + ica_path + ' already exists')
def epoch_raw(name, save_dir, lowpass, event_id, tmin, tmax, baseline, reject,
bad_channels, decim, overwrite):
epochs_name = name + filter_string(lowpass) + '-epo.fif'
epochs_path = join(save_dir, epochs_name)
if overwrite or not isfile(epochs_path):
events = io.read_events(name, save_dir)
raw = io.read_filtered(
name,
save_dir,
lowpass,
)
raw.info['bads'] = bad_channels
picks = mne.pick_types(raw.info,
meg=True,
eog=True,
ecg=True,
exclude='bads')
epochs = mne.Epochs(raw,
events,
event_id,
tmin,
tmax,
baseline,
reject=reject,
preload=True,
picks=picks,
decim=decim)
epochs.save(epochs_path)
else:
print('epochs file: ' + epochs_path + ' already exists')
def plot_power_spectra(name, save_dir, lowpass, subject, save_plots,
figures_path):
raw = io.read_filtered(name, save_dir, lowpass)
psd_figure = raw.plot_psd(fmax=lowpass, n_jobs=1, show=False) # n_jobs=-1)
if save_plots:
save_path = join(figures_path, subject, 'power_spectra_raw', name + \
filter_string(lowpass) + '.jpg')
psd_figure.savefig(save_path, dpi=600)
print 'figure: ' + save_path + ' has been saved'
else:
print 'Not saving plots; set "save_plots" to "True" to save'
def find_events(name, save_dir, stim_channel, min_duration,
adjust_timeline_by_msec, lowpass, overwrite):
events_name = name + '-eve.fif'
events_path = join(save_dir, events_name)
if overwrite or not isfile(events_path):
raw = io.read_filtered(name, save_dir, lowpass)
events = mne.find_events(raw, stim_channel, min_duration=min_duration)
events[:, 0] = [ts + np.round(adjust_timeline_by_msec * 10**-3 * \
raw.info['sfreq']) for ts in events[:, 0]]
mne.event.write_events(events_path, events)
else:
print('event file: ' + events_path + ' already exists')
def plot_filtered(name, save_dir, lowpass):
raw = io.read_filtered(name, save_dir, lowpass)
raw.plot()
