def main(tup, remote_subject_dir, args, flags):
(subject, mri_subject), inverse_method = tup
evoked, epochs = None, None
fname_format, fname_format_cond, conditions = meg.init_main(subject, mri_subject, args)
meg.init_globals_args(subject, mri_subject, fname_format, fname_format_cond, SUBJECTS_EEG_DIR, SUBJECTS_MRI_DIR,
MMVT_DIR, args)
meg.MEG_DIR = SUBJECTS_EEG_DIR
meg.FWD = meg.FWD_EEG
meg.INV = meg.INV_EEG
stat = meg.STAT_AVG if len(conditions) == 1 else meg.STAT_DIFF
if utils.should_run(args, 'read_eeg_sensors_layout'):
flags['read_eeg_sensors_layout'] = read_eeg_sensors_layout(subject, mri_subject, args)
flags = meg.calc_evoked_wrapper(subject, conditions, args, flags)
if utils.should_run(args, 'create_eeg_mesh'):
flags['create_eeg_mesh'] = create_eeg_mesh(mri_subject, args.eeg_electrodes_excluded_from_mesh)
if utils.should_run(args, 'save_evoked_to_blender'):
flags['save_evoked_to_blender'] = save_evoked_to_blender(mri_subject, conditions, args, evoked)
if not op.isfile(meg.COR):
eeg_cor = op.join(meg.SUBJECT_MEG_FOLDER, '{}-cor-trans.fif'.format(subject))
if not op.isfile(eeg_cor):
raise Exception("Can't find head-MRI transformation matrix. Should be in {} or in {}".format(meg.COR, eeg_cor))
meg.COR = eeg_cor
flags = meg.calc_fwd_inv_wrapper(subject, mri_subject, conditions, args, flags)
flags = meg.calc_stc_per_condition_wrapper(subject, conditions, inverse_method, args, flags)
return flags
def init(subject, args, mri_subject='', remote_subject_dir=''):
if mri_subject == '':
mri_subject = subject
fname_format, fname_format_cond, conditions = meg.init_main(subject, mri_subject, remote_subject_dir, args)
meg.init_globals_args(subject, mri_subject, fname_format, fname_format_cond, args=args)
# meg.MEG_DIR = SUBJECTS_EEG_DIR
meg.FWD = meg.FWD_EEG
meg.INV = meg.INV_EEG
stat = meg.STAT_AVG if len(conditions) == 1 else meg.STAT_DIFF
SUBJECT_EEG_DIR = op.join(SUBJECTS_EEG_DIR, subject)
meg.locating_file = partial(utils.locating_file, parent_fol=SUBJECT_EEG_DIR)
return conditions, stat
def init(subject, task):
args = pu.init_args(meg.read_cmd_args(dict(
subject=subject,
atlas='laus125',
task=task,
files_includes_cond=True,
inverse_method='MNE')))
fname_format_cond = '{subject}_hcp_{cond}-{ana_type}.{file_type}'
fname_format = '{subject}_hcp-{ana_type}.{file_type}'
meg.init_globals_args(
subject, '', fname_format, fname_format_cond, args=args)
hcp_params = dict(hcp_path=HCP_DIR, subject=subject, data_type=task)
return args, hcp_params