示例#1
0
def _calc_zvals_parallel(p):
    subject, clip_fname, baseline_fnames, modality, inverse_method, fol, from_index, to_index, use_abs, overwrite = p
    stc_zvals_fname = op.join(
        fol, '{}-epilepsy-{}-{}-{}-amplitude-zvals'.format(
            subject, inverse_method, modality, utils.namebase(clip_fname)))
    if utils.both_hemi_files_exist('{}-{}.stc'.format(
            stc_zvals_fname, '{hemi}')) and not overwrite:
        return True
    stc_fname = op.join(
        MMVT_DIR, subject, meg.modality_fol(modality),
        'ictal-{}-stcs'.format(inverse_method),
        '{}-epilepsy-{}-{}-{}'.format(subject, inverse_method, modality,
                                      utils.namebase(clip_fname)))
    if not utils.both_hemi_files_exist('{}-{}.stc'.format(stc_fname,
                                                          '{hemi}')):
        print('Error finding {}!'.format(stc_fname))
        return False
    return meg.calc_stc_zvals(
        subject,
        '{}-rh.stc'.format(stc_fname),
        baseline_fnames,
        stc_zvals_fname,  # '{}-rh.stc'.format(baseline_fname)
        use_abs,
        from_index,
        to_index,
        True,
        overwrite)
示例#2
0
def main(tup, remote_subject_dir, args, flags):
    (subject, mri_subject), inverse_method = tup
    evoked, epochs = None, None
    conditions, stat = init(subject, args, mri_subject, remote_subject_dir)

    if utils.should_run(args, 'read_sensors_layout'):
        flags['read_sensors_layout'] = read_sensors_layout_args(
            mri_subject, args)

    flags, evoked, epochs = meg.calc_evokes_wrapper(subject,
                                                    conditions,
                                                    args,
                                                    flags,
                                                    mri_subject=mri_subject)

    flags = meg.calc_fwd_inv_wrapper(subject, args, conditions, flags,
                                     mri_subject)

    flags, stcs_conds, stcs_num = meg.calc_stc_per_condition_wrapper(
        subject, conditions, inverse_method, args, flags)

    flags = meg.calc_labels_avg_per_condition_wrapper(subject, conditions,
                                                      args.atlas,
                                                      inverse_method,
                                                      stcs_conds, args, flags,
                                                      stcs_num, None, epochs)

    if 'calc_stc_zvals' in args.function:
        flags['calc_stc_zvals'] = meg.calc_stc_zvals(
            subject, args.stc_name, args.baseline_stc_name, 'eeg',
            args.use_abs, args.from_index, args.to_index, args.stc_zvals_name,
            False, args.overwrite_stc)

    if utils.should_run(args, 'create_helmet_mesh'):
        flags['create_helmet_mesh'] = create_helmet_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 utils.should_run(args, 'calc_minmax'):
        flags['calc_minmax'] = calc_minmax(mri_subject, args)

    if 'plot_evoked' in args.function:
        flags['plot_evoked'], _ = plot_evoked(args.evo_fname, args.evoked_key,
                                              args.pick_meg, args.pick_eeg,
                                              args.pick_eog, args.ssp_proj,
                                              args.spatial_colors,
                                              args.window_title, args.hline,
                                              args.channels_to_exclude)

    if 'snap_sensors_to_outer_skin' in args.function:
        flags['snap_sensors_to_outer_skin'] = snap_sensors_to_outer_skin(
            mri_subject)

    return flags