def get_pca_mean_and_pre_whitener_raw(raw, picks, start, stop, decim, reject,
flat, tstep, pre_whitener,
reject_by_annotation):
"""Aux method based on ica._fit_raw from mne v0.15"""
if picks is None: # just use good data channels
picks = _pick_data_channels(raw.info,
exclude='bads',
with_ref_meg=False)
info = pick_info(raw.info, picks)
if info['comps']:
info['comps'] = []
start, stop = _check_start_stop(raw, start, stop)
reject_by_annotation = 'omit' if reject_by_annotation else None
# this will be a copy
data = raw.get_data(picks, start, stop, reject_by_annotation)
# this will be a view
if decim is not None:
data = data[:, ::decim]
# this will make a copy
if (reject is not None) or (flat is not None):
data, drop_inds_ = _reject_data_segments(data, reject, flat, decim,
info, tstep)
# this may operate inplace or make a copy
data, pre_whitener = pre_whiten(data, raw.info, picks, pre_whitener)
pca_mean_ = np.mean(data, axis=1)
return pca_mean_, pre_whitener
def mark_reject_peak2peak(raw, reject={'eeg': 23e-5}, window_length=1.,
label='bad p2p'):
import mne
from mne.utils import _reject_data_segments
_, inds = _reject_data_segments(raw._data, reject, {'eeg': 0.},
window_length, raw.info, 0.5)
# turn inds to time, join
time_segments = np.array(inds) / raw.info['sfreq']
time_segments = join_segments(time_segments)
segment_duration = np.diff(time_segments, axis=-1).ravel()
return mne.Annotations(time_segments[:, 0], segment_duration, label)
def mark_reject_peak2peak(raw, reject={'eeg': 23e-5}, window_length=1.,
label='bad p2p'):
import mne
from mne.utils import _reject_data_segments
_, inds = _reject_data_segments(raw._data, reject, {'eeg': 0.},
window_length, raw.info, 0.5)
# turn inds to time, join
time_segments = np.array(inds) / raw.info['sfreq']
time_segments = join_segments(time_segments)
segment_duration = np.diff(time_segments, axis=-1).ravel()
return mne.Annotations(time_segments[:, 0], segment_duration, label)