// trials are already non continuous. edge artifact can appears but
// are likely to be present during rest / inter-trial activity
eeg_data = np.hstack([eeg_data_l, eeg_data_r])
log.warning("Trials stacked to create continuous data -- edge effects present")
info = create_info(ch_names=ch_names, ch_types=ch_types,
After Change
ch_names = eeg_ch_names + emg_ch_names + ["Stim"]
ch_types = ["eeg"] * 64 + ["emg"] * 4 + ["stim"]
montage = read_montage("standard_1005")
imagery_left = data.imagery_left - \
data.imagery_left.mean(axis=1, keepdims=True)
imagery_right = data.imagery_right - \
data.imagery_right.mean(axis=1, keepdims=True)
eeg_data_l = np.vstack([imagery_left * 1e-6, data.imagery_event])
eeg_data_r = np.vstack([imagery_right * 1e-6,
data.imagery_event * 2])
// trials are already non continuous. edge artifact can appears but
// are likely to be present during rest / inter-trial activity
eeg_data = np.hstack([eeg_data_l, np.zeros((eeg_data_l.shape[0], 500)),eeg_data_r])
log.warning(
"Trials demeaned and stacked with zero buffer to create continuous data -- edge effects present")
info = create_info(ch_names=ch_names, ch_types=ch_types,
