a9f9c5e31b8e55098e980f2e3fbfd80a43fabfc1,nilearn/datasets/func.py,,fetch_cobre,#Any#Any#Any#Any#,1417

Before Change

    ids = csv_array["subject_type"]
    max_subjects = len(ids)
    if n_subjects is not None:
        if n_subjects < max_subjects:
            // shuffle datasets to have almost equal balance between sch vs ctrl
            ids = shuffle(ids, random_state=0, n_samples=n_subjects)
        elif n_subjects > max_subjects:
            warnings.warn("Warning: there are only %d subjects" % max_subjects)
            n_subjects = max_subjects
    else:
        n_subjects = max_subjects

    func_filenames = [("fmri_" + i.decode().strip(" "\"") +

After Change

    func_files = _fetch_files(data_dir, func_files, verbose=verbose)
    mat_files = _fetch_files(data_dir, mat_files, verbose=verbose)

    if n_subjects < max_subjects:
        first_split = n_subjects/2
        second_split = n_subjects - first_split
        func = func_files[0:71][:first_split]
        func.extend(func_files[72:146][:second_split])
        func_files = func
        mats = mat_files[0:71][:first_split]
        mats.extend(mat_files[72:146][:second_split])
        mat_files = mats

    return Bunch(func=func_files, mat_files=mat_files, phenotypic=csv_array,
                 description=fdescr)

Instances