def return_bids_test_dir(tmpdir_factory):
"""Return path to a written test BIDS dir."""
bids_root = str(tmpdir_factory.mktemp('mnebids_utils_test_bids_ds'))
data_path = testing.data_path()
raw_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw.fif')
event_id = {
'Auditory/Left': 1,
'Auditory/Right': 2,
'Visual/Left': 3,
'Visual/Right': 4,
'Smiley': 5,
'Button': 32
}
events_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw-eve.fif')
cal_fname = op.join(data_path, 'SSS', 'sss_cal_mgh.dat')
crosstalk_fname = op.join(data_path, 'SSS', 'ct_sparse.fif')
raw = mne.io.read_raw_fif(raw_fname)
raw.info['line_freq'] = 60
bids_path.update(root=bids_root)
# Write multiple runs for test_purposes
for run_idx in [run, '02']:
name = bids_path.copy().update(run=run_idx)
write_raw_bids(raw,
name,
events_data=events_fname,
event_id=event_id,
overwrite=True)
write_meg_calibration(cal_fname, bids_path=bids_path)
write_meg_crosstalk(crosstalk_fname, bids_path=bids_path)
return bids_root
def _elektas_extras(crosstalk_file, fine_cal_file, bids_path):
"""
Save the crosstalk and fine-calibration files
:param crosstalk_file: str, path to crosstalk file
:param fine_cal_file: str, path to fine_cal file
:param bids_path: mne-bids BIDSPath instance
:return:
"""
write_meg_calibration(fine_cal_file, bids_path)
write_meg_crosstalk(crosstalk_file, bids_path)
def run():
"""Run the crosstalk_to_bids command."""
from mne.commands.utils import get_optparser
parser = get_optparser(__file__,
usage="usage: %prog options args",
prog_prefix='mne_bids',
version=mne_bids.__version__)
parser.add_option('--bids_root',
dest='bids_root',
help='The path of the folder containing the BIDS '
'dataset')
parser.add_option('--subject_id', dest='subject', help=('Subject name'))
parser.add_option('--session_id', dest='session', help='Session name')
parser.add_option('--file',
dest='fname',
help='The path of the crosstalk file')
parser.add_option('--verbose',
dest='verbose',
action='store_true',
help='Whether do generate additional diagnostic output')
opt, args = parser.parse_args()
if args:
parser.print_help()
parser.error(f'Please do not specify arguments without flags. '
f'Got: {args}.\n')
if opt.bids_root is None:
parser.print_help()
parser.error('You must specify bids_root')
if opt.subject is None:
parser.print_help()
parser.error('You must specify a subject')
bids_path = BIDSPath(subject=opt.subject,
session=opt.session,
root=opt.bids_root)
logger.info(f'Writing crosstalk file {bids_path.basename} …')
write_meg_crosstalk(fname=opt.fname,
bids_path=bids_path,
verbose=opt.verbose)
def return_bids_test_dir(tmpdir_factory):
"""Return path to a written test BIDS dir."""
bids_root = str(tmpdir_factory.mktemp('mnebids_utils_test_bids_ds'))
data_path = testing.data_path()
raw_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw.fif')
event_id = {
'Auditory/Left': 1,
'Auditory/Right': 2,
'Visual/Left': 3,
'Visual/Right': 4,
'Smiley': 5,
'Button': 32
}
events_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw-eve.fif')
cal_fname = op.join(data_path, 'SSS', 'sss_cal_mgh.dat')
crosstalk_fname = op.join(data_path, 'SSS', 'ct_sparse.fif')
raw = mne.io.read_raw_fif(raw_fname)
raw.info['line_freq'] = 60
# Drop unknown events.
events = mne.read_events(events_fname)
events = events[events[:, 2] != 0]
bids_path = _bids_path.copy().update(root=bids_root)
write_raw_bids(raw,
bids_path=bids_path,
events_data=events,
event_id=event_id,
overwrite=True)
write_meg_calibration(cal_fname, bids_path=bids_path)
write_meg_crosstalk(crosstalk_fname, bids_path=bids_path)
return bids_root
"""Add calibration and crosstalk files to BIDS data"""
from tqdm import tqdm
from mne_bids import write_meg_calibration, write_meg_crosstalk, BIDSPath
from metacog.config_parser import cfg
from metacog.paths import crosstalk, calibration, dirs
sss_data = BIDSPath(root=dirs.bids_root)
for subj in tqdm(cfg.all_subjects):
sss_data.update(subject=subj)
write_meg_calibration(calibration, sss_data)
write_meg_crosstalk(crosstalk, sss_data)
session=date_record,
task=task_name,
root=data_bids_dir)
# mri_bids_path = mne_bids.BIDSPath(subject=subj_id, session=date_record,
# root=data_bids_dir)
#
mne_bids.write_raw_bids(raw=raw_meg,
bids_path=meg_bids_path,
anonymize={'daysback': 40000},
overwrite=True,
verbose=True)
if subj_id != 'emptyroom':
mne_bids.write_meg_crosstalk(ct_file, meg_bids_path)
if int(date_record[:4]) < 2020:
mne_bids.write_meg_calibration(fc_files['Before_sept2019'],
meg_bids_path)
else:
mne_bids.write_meg_calibration(fc_files['Current'], meg_bids_path)
# mri_presence = mri_subjnames.count(subj_fullname)
# if mri_presence:
# mri_path_i = mri_subjnames.index(subj_fullname)
# mne_bids.write_anat(t1w=mri_paths[mri_path_i], bids_path=mri_bids_path, raw=raw_meg, overwrite=True)
# print(f'{subj_fullname} has MRI file. Path to MRI file: {mri_paths[mri_path_i]}')
# save fullnames and bids_id
df_subj_bids_codes = pd.DataFrame.from_dict(sub_id_name,
orient='index').reset_index()
write_raw_bids(raw,
bids_path,
events_data=events_data,
event_id=event_id,
overwrite=True)
###############################################################################
# The sample MEG dataset comes with fine-calibration and crosstalk files that
# are required when processing Elekta/Neuromag/MEGIN data using MaxFilter®.
# Let's store these data in appropriate places, too.
cal_fname = op.join(data_path, 'SSS', 'sss_cal_mgh.dat')
ct_fname = op.join(data_path, 'SSS', 'ct_sparse_mgh.fif')
write_meg_calibration(cal_fname, bids_path)
write_meg_crosstalk(ct_fname, bids_path)
###############################################################################
# Now let's see the structure of the BIDS folder we created.
print_dir_tree(output_path)
###############################################################################
# Now let's get an overview of the events on the whole dataset
counts = count_events(output_path)
counts
###############################################################################
# A big advantage of having data organized according to BIDS is that software
# packages can automate your workflow. For example, reading the data back
# specify power line frequency as required by BIDS
raw.info['line_freq'] = 60
raw_er.info['line_freq'] = 60
# Write empty-room data
write_raw_bids(raw=raw_er, bids_path=bids_path_er, verbose=False)
# Write experimental MEG data, fine-calibration and crosstalk files
write_raw_bids(raw=raw,
bids_path=bids_path,
events_data=events_path,
event_id=event_id,
empty_room=bids_path_er,
verbose=False)
write_meg_calibration(cal_path, bids_path=bids_path, verbose=False)
write_meg_crosstalk(ct_path, bids_path=bids_path, verbose=False)
# Write anatomical scan
# We pass the MRI landmark coordinates, which will later be required for
# automated defacing
mri_landmarks = mne.channels.make_dig_montage(
lpa=[66.08580, 51.33362, 46.52982],
nasion=[41.87363, 32.24694, 74.55314],
rpa=[17.23812, 53.08294, 47.01789],
coord_frame='mri_voxel')
bids_path.datatype = 'anat'
write_anat(image=t1w_path,
bids_path=bids_path,
landmarks=mri_landmarks,
verbose=False)
event[0] += delay
# Now actually convert to BIDS.
bids_path = BIDSPath(subject=participant,
task=exp,
datatype='meg',
root=output_dir)
write_raw_bids(raw,
bids_path=bids_path,
events_data=events,
event_id=event_name_to_id_mapping,
overwrite=True,
verbose=False)
write_meg_calibration(mf_cal_fname, bids_path)
write_meg_crosstalk(mf_ctc_fname, bids_path)
t1w_bids_path = BIDSPath(subject=participant,
root=output_dir,
acquisition='t1w')
write_anat(t1w=t1w_fname,
bids_path=t1w_bids_path,
trans=trans_fname,
raw=raw,
overwrite=True,
verbose=False)
del bids_path, trans_fname, raw_fname, raw, events
progress_bar.update()
