def test_get_anonymization_daysback():
"""Test daysback querying for anonymization."""
data_path = testing.data_path()
raw_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw.fif')
raw = mne.io.read_raw_fif(raw_fname)
daysback_min, daysback_max = _get_anonymization_daysback(raw)
# max_val off by 1 on Windows for some reason
assert abs(daysback_min - 28461) < 2 and abs(daysback_max - 36880) < 2
raw2 = raw.copy()
raw2.info['meas_date'] = (np.int32(1158942080), np.int32(720100))
raw3 = raw.copy()
raw3.info['meas_date'] = (np.int32(914992080), np.int32(720100))
daysback_min, daysback_max = get_anonymization_daysback([raw, raw2, raw3])
assert abs(daysback_min - 29850) < 2 and abs(daysback_max - 35446) < 2
raw4 = raw.copy()
raw4.info['meas_date'] = (np.int32(4992080), np.int32(720100))
raw5 = raw.copy()
raw5.info['meas_date'] = None
daysback_min2, daysback_max2 = get_anonymization_daysback(
[raw, raw2, raw3, raw5])
assert daysback_min2 == daysback_min and daysback_max2 == daysback_max
with pytest.raises(ValueError, match='The dataset spans more time'):
daysback_min, daysback_max = \
get_anonymization_daysback([raw, raw2, raw4])
def test_ctf(_bids_validate):
"""Test functionality of the write_raw_bids conversion for CTF data."""
output_path = _TempDir()
data_path = op.join(testing.data_path(download=False), 'CTF')
raw_fname = op.join(data_path, 'testdata_ctf.ds')
raw = mne.io.read_raw_ctf(raw_fname)
with pytest.warns(UserWarning, match='No line frequency'):
write_raw_bids(raw, bids_basename, output_path=output_path)
_bids_validate(output_path)
with pytest.warns(UserWarning, match='Did not find any events'):
raw = read_raw_bids(bids_basename + '_meg.ds',
output_path,
extra_params=dict(clean_names=False))
# test to check that running again with overwrite == False raises an error
with pytest.raises(FileExistsError, match="already exists"): # noqa: F821
write_raw_bids(raw, bids_basename, output_path=output_path)
assert op.exists(op.join(output_path, 'participants.tsv'))
# test anonymize
raw = mne.io.read_raw_ctf(raw_fname)
with pytest.warns(UserWarning,
match='Converting to FIF for anonymization'):
output_path = _test_anonymize(raw, bids_basename)
_bids_validate(output_path)
# XXX: change the next two lines once raw.set_meas_date() is
# available.
raw.info['meas_date'] = None
raw.anonymize()
with pytest.raises(ValueError, match='All measurement dates are None'):
get_anonymization_daysback(raw)
# BIDS-compatible names that will be used to save the files in BIDS.
raw_list = list()
bids_list = list()
for subject_id in subject_ids:
for run in runs:
raw_fname = eegbci.load_data(subject=subject_id, runs=run)[0]
raw = mne.io.read_raw_edf(raw_fname)
raw.info['line_freq'] = 50 # specify power line frequency
raw_list.append(raw)
bids_path = BIDSPath(subject=f'{subject_id:03}',
session='01', task='MotorImagery',
run=f'{run_map[run]:02}',
root=bids_root)
bids_list.append(bids_path)
daysback_min, daysback_max = get_anonymization_daysback(raw_list)
for raw, bids_path in zip(raw_list, bids_list):
# By using the same anonymization `daysback` number we can
# preserve the longitudinal structure of multiple sessions for a
# single subject and the relation between subjects. Be sure to
# change or delete this number before putting code online, you
# wouldn't want to inadvertently de-anonymize your data.
write_raw_bids(raw, bids_path, event_id=event_id,
anonymize=dict(daysback=daysback_min + 2117),
overwrite=True)
###############################################################################
# Now let's see the structure of the BIDS folder we created.
print_dir_tree(bids_root)
