############################################################################### # Let us import ``mne_bids`` import os.path as op from mne_bids import raw_to_bids from mne_bids.datasets import fetch_faces_data ############################################################################### # And fetch the data. subject_ids = [1] runs = range(1, 7) data_path = op.join(op.expanduser('~'), 'mne_data') repo = 'ds000117' fetch_faces_data(data_path, repo, subject_ids) output_path = op.join(data_path, 'ds000117-bids') ############################################################################### # # .. warning:: This will download 7.9 GB of data for one subject! # Define event_ids. event_id = { 'face/famous/first': 5, 'face/famous/immediate': 6, 'face/famous/long': 7, 'face/unfamiliar/first': 13, 'face/unfamiliar/immediate': 14, 'face/unfamiliar/long': 15,
def test_fetch_faces_data(): """Dry test fetch_faces_data (Will not download anything).""" data_path = fetch_faces_data(subject_ids=[]) assert op.exists(data_path)