def test_get_entity_vals(entity, expected_vals, kwargs, return_bids_test_dir):
"""Test getting a list of entities."""
bids_root = return_bids_test_dir
if kwargs is None:
kwargs = dict()
if entity == 'bogus':
with pytest.raises(ValueError, match='`key` must be one of'):
get_entity_vals(bids_root=bids_root, entity_key=entity, **kwargs)
else:
vals = get_entity_vals(bids_root=bids_root, entity_key=entity,
**kwargs)
assert vals == expected_vals
def get_task():
if not task:
tasks = get_entity_vals(bids_root, entity_key='task')
if not tasks:
return None
else:
return tasks[0]
else:
return task
def get_runs():
runs_ = copy.deepcopy(runs) # Avoid clash with global variable.
if runs_ == 'all':
runs_ = get_entity_vals(bids_root, entity_key='run')
if not runs_:
return [None]
else:
return runs_
def get_sessions():
sessions_ = copy.deepcopy(sessions) # Avoid clash with global variable.
if sessions_ == 'all':
sessions_ = get_entity_vals(bids_root, entity_key='ses')
if not sessions_:
return [None]
else:
return sessions_
def get_subjects():
if subjects_list == 'all':
s = get_entity_vals(bids_root, entity_key='sub')
else:
s = subjects_list
subjects = set(s) - set(exclude_subjects)
# Drop empty-room subject.
subjects = subjects - set(['emptyroom'])
return list(subjects)
def test_get_entity_vals(return_bids_test_dir):
"""Test getting a list of entities."""
bids_root = return_bids_test_dir
with pytest.raises(ValueError, match='`key` must be one of'):
get_entity_vals(bids_root, entity_key='bogus')
assert get_entity_vals(bids_root, 'sub') == [subject_id]
assert get_entity_vals(bids_root, 'ses') == [session_id]
assert get_entity_vals(bids_root, 'run') == [run, '02']
assert get_entity_vals(bids_root, 'acq') == []
assert get_entity_vals(bids_root, 'task') == [task]
# If True, the scripts will generate plots. # If running the scripts from a notebook or spyder # run %matplotlib qt in the command line to get the plots in extra windows plot = True # plot = False # ``crop``: tuple or None # If tuple, (tmin, tmax) to crop the raw data # If None (default), do not crop. crop = None # BIDS params # see: bids-specification.rtfd.io/en/latest/99-appendices/04-entity-table.html sessions = get_entity_vals(bids_root, entity_key='ses') sessions = sessions if sessions else [None] # XXX: take only first task for now task = get_entity_vals(bids_root, entity_key='task')[0] runs = get_entity_vals(bids_root, entity_key='run') runs = runs if runs else [None] acq = None proc = None rec = None space = None
from mne_bids import read_raw_bids
from mne_bids.read import _handle_events_reading
from mne_bids.utils import get_entity_vals
layout = mne.channels.read_layout('KIT-AD.lout')
task = 'OcularLDT'
bids_root = op.join('/', 'Volumes', 'teon-backup', 'Experiments', task)
fs_home = op.join('/', 'Applications', 'freesurfer', '7.1.0')
mri_subjects_dir = op.join('/', 'Volumes', 'teon-backup', 'Experiments',
task + '_MRI')
derivative = 'trans'
redo = False
subjects_list = get_entity_vals(bids_root, entity_key='sub')
fname_rep_group = op.join('/', 'Users', 'tbrooks', 'codespace', f'{task}-code',
'output', 'preprocessing',
f'group_{task}_{derivative}-report.html')
rep_group = Report()
# first, copy over fsaverage from FreeSurfer
mne.coreg.create_default_subject(fs_home=fs_home,
update=True,
subjects_dir=mri_subjects_dir)
ss = mne.setup_source_space(subject='fsaverage',
spacing='ico4',
surface='white',
subjects_dir=mri_subjects_dir)
fname_src = op.join(mri_subjects_dir, 'fsaverage', 'bem',
import pathlib
from mne_bids.utils import get_entity_vals
study_name = 'Cam-CAN'
bids_root = pathlib.Path('/storage/store2/work/rhochenb/Data/Cam-CAN/BIDS')
subjects_dir = str(bids_root / 'derivatives' / 'freesurfer')
task = 'task'
# subjects_list = list(set(subjects_list) - set(exclude_subjects))
# subjects_list = 'all'
subjects_list = sorted(get_entity_vals(bids_root, entity_key='sub'))[:50]
ch_types = ['meg']
find_flat_channels_meg = True
find_noisy_channels_meg = True
use_maxwell_filter = True
mf_ctc_fname = pathlib.Path('/storage/store2/work/rhochenb/Data/Cam-CAN/'
'Cam-CAN_ct_sparse.fif')
mf_cal_fname = pathlib.Path('/storage/store2/work/rhochenb/Data/Cam-CAN/'
'Cam-CAN_sss_cal.dat')
tmin = -0.2
tmax = 0.5
baseline = (None, 0)
conditions = [
'audiovis/300Hz', 'audiovis/600Hz', 'audiovis/1200Hz', 'audiovis'
]
N_JOBS = 72
allow_maxshield = True
