###############################################################################
# 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)
