How to use the pynets.core.nodemaker.create_parcel_atlas function in pynets

start_time = time.time()
    [WB_coords, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile)
    print("%s%s%s" % ('get_names_and_coords_of_parcels (Masking whole-brain version) --> finished: ',
    str(np.round(time.time() - start_time, 1)), 's'))

    WB_labels = np.arange(len(WB_coords) + 1)[np.arange(len(WB_coords) + 1) != 0].tolist()

    start_time = time.time()
    WB_parcel_list = nodemaker.gen_img_list(parlistfile)
    [_, _, WB_parcel_list_masked] = nodemaker.parcel_masker(roi, WB_coords, WB_parcel_list, WB_labels, dir_path,
                                                            ID, perc_overlap)
    print("%s%s%s" % ('parcel_masker (Masking whole-brain version) --> finished: ',
    np.round(time.time() - start_time, 1), 's'))

    start_time = time.time()
    [WB_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(WB_parcel_list_masked)
    print("%s%s%s" % ('create_parcel_atlas (Masking whole-brain version) --> finished: ',
    np.round(time.time() - start_time, 1), 's'))

    start_time = time.time()
    [WB_net_parcels_map_nifti_unmasked, WB_coords_unmasked, _,
     WB_atlas, WB_uatlas, dir_path] = nodemaker.node_gen(WB_coords, WB_parcel_list, WB_labels,
                                                                        dir_path, ID, parc, atlas, parlistfile)
    print("%s%s%s" % ('node_gen (Masking whole-brain version) --> finished: ',
    np.round(time.time() - start_time, 1), 's'))

    start_time = time.time()
    [WB_net_parcels_map_nifti_masked, WB_coords_masked, WB_labels_masked,
     WB_atlas, WB_uatlas, dir_path] = nodemaker.node_gen_masking(roi, WB_coords, WB_parcel_list,
                                                                                WB_labels, dir_path, ID, parc,
                                                                                atlas, parlistfile)

parcel_list = nodemaker.gen_img_list(parlistfile)
    [net_coords, net_parcel_list, net_labels, network] = nodemaker.get_node_membership(network, func_file, coords,
                                                                                            labels, parc,
                                                                                            parcel_list)
    print("%s%s%s" % ('get_node_membership --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    start_time = time.time()
    [net_coords_masked, net_labels_masked, net_parcel_list_masked] = nodemaker.parcel_masker(roi, net_coords,
                                                                                                  net_parcel_list,
                                                                                                  net_labels,
                                                                                                  dir_path, ID,
                                                                                                  perc_overlap)
    print("%s%s%s" % ('parcel_masker --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    start_time = time.time()
    [net_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(net_parcel_list_masked)
    print("%s%s%s" % ('create_parcel_atlas --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    start_time = time.time()
    out_path = nodemaker.gen_network_parcels(parlistfile, network, net_labels_masked, dir_path)
    print("%s%s%s" % ('gen_network_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    assert coords is not None
    assert net_coords is not None
    assert net_labels is not None
    assert net_parcel_list is not None
    assert net_coords_masked is not None
    assert net_labels_masked is not None
    assert net_parcel_list_masked is not None
    assert out_path is not None
    assert net_parcels_map_nifti is not None
    assert parcel_list_exp is not None

print("%s%s%s" % ('get_names_and_coords_of_parcels --> finished: ',
                      str(np.round(time.time() - start_time, 1)), 's'))

    labels = np.arange(len(coords) + 1)[np.arange(len(coords) + 1) != 0].tolist()

    start_time = time.time()

    parcel_list = nodemaker.gen_img_list(parlistfile)

    [net_coords, net_parcel_list, net_labels, network] = nodemaker.get_node_membership(network, func_file, coords,
                                                                                            labels, parc,
                                                                                            parcel_list)
    print("%s%s%s" % ('get_node_membership --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    start_time = time.time()
    [net_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(net_parcel_list)
    print("%s%s%s" % ('create_parcel_atlas --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    start_time = time.time()
    out_path = nodemaker.gen_network_parcels(parlistfile, network, net_labels, dir_path)
    print("%s%s%s" % ('gen_network_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's'))

    assert coords is not None
    assert net_coords is not None
    assert net_labels is not None
    assert net_parcel_list is not None
    assert out_path is not None
    assert net_parcels_map_nifti is not None
    assert parcel_list_exp is not None
    assert network is not None

"""
    # Set example inputs
    base_dir = str(Path(__file__).parent/"examples")
    parlistfile = base_dir + '/whole_brain_cluster_labels_PCA200.nii.gz'

    start_time = time.time()
    [WB_coords, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile)
    print("%s%s%s" % ('get_names_and_coords_of_parcels (User-atlas whole-brain version) --> finished: ',
                      str(np.round(time.time() - start_time, 1)), 's'))

    WB_labels = np.arange(len(WB_coords) + 1)[np.arange(len(WB_coords) + 1) != 0].tolist()

    start_time = time.time()

    WB_parcel_list = nodemaker.gen_img_list(parlistfile)
    [WB_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(WB_parcel_list)
    print("%s%s%s" % ('create_parcel_atlas (User-atlas whole-brain version) --> finished: ',
                      str(np.round(time.time() - start_time, 1)), 's'))

    assert WB_coords is not None
    assert WB_labels is not None
    assert WB_parcel_list is not None
    assert WB_parcels_map_nifti is not None
    assert parcel_list_exp is not None

labels_adj = list(labels)
    coords_adj = list(tuple(x) for x in coords)
    parcel_list_adj = parcel_list
    try:
        for ix in sorted(indices, reverse=True):
            print("%s%s%s%s" % ('Removing: ', labels_adj[ix], ' at ', coords_adj[ix]))
            labels_adj.pop(ix)
            coords_adj.pop(ix)
            parcel_list_adj.pop(ix)
    except RuntimeError:
        print('ERROR: Restrictive masking. No parcels remain after masking with brain mask/roi...')

    # Create a resampled 3D atlas that can be viewed alongside mask img for QA
    resampled_parcels_nii_path = "%s%s%s%s%s%s" % (dir_path, '/', ID, '_parcels_resampled2roimask_',
                                                   op.basename(roi).split('.')[0], '.nii.gz')
    resampled_parcels_atlas, _ = nodemaker.create_parcel_atlas(parcel_list_adj)
    resampled_parcels_map_nifti = resample_img(resampled_parcels_atlas, target_affine=mask_img.affine,
                                               target_shape=mask_data.shape)
    nib.save(resampled_parcels_map_nifti, resampled_parcels_nii_path)
    mask_img.uncache()
    resampled_parcels_map_nifti.uncache()
    if not coords_adj:
        raise ValueError('\nERROR: ROI mask was likely too restrictive and yielded < 2 remaining parcels')

    return coords_adj, labels_adj, parcel_list_adj

dir_path : str
        Path to directory containing subject derivative data for given run.
    """
    from pynets.core import nodemaker
    import os.path as op
    try:
        import cPickle as pickle
    except ImportError:
        import _pickle as pickle

    # Mask Parcels
    if parc is True:
        # For parcel masking, specify overlap thresh and error cushion in mm voxels
        [coords, labels, parcel_list_masked] = nodemaker.parcel_masker(roi, coords, parcel_list, labels,
                                                                       dir_path, ID, perc_overlap)
        [net_parcels_map_nifti, _] = nodemaker.create_parcel_atlas(parcel_list_masked)
    # Mask Coordinates
    else:
        [coords, labels] = nodemaker.coords_masker(roi, coords, labels, error)
        # Save coords to pickle
        coords_path = "%s%s%s%s" % (dir_path, '/atlas_coords_', op.basename(roi).split('.')[0], '.pkl')
        with open(coords_path, 'wb') as f:
            pickle.dump(coords, f, protocol=2)

        net_parcels_map_nifti = None
    # Save labels to pickle
    labels_path = "%s%s%s%s" % (dir_path, '/atlas_labelnames_', op.basename(roi).split('.')[0], '.pkl')
    with open(labels_path, 'wb') as f:
        pickle.dump(labels, f, protocol=2)

    return net_parcels_map_nifti, coords, labels, atlas, uatlas, dir_path