code: def _make_label_data(shape=_shape_3d_default()):
      labels_data = np.zeros(shape, dtype="int32")
      h0, h1, h2 = (s // 2 for s in shape)
      labels_data[:h0, :h1, :h2] = 1
      labels_data[:h0, :h1, h2:] = 2
      labels_data[:h0, h1:, :h2] = 3
      labels_data[:h0, h1:, h2:] = 4
      labels_data[h0:, :h1, :h2] = 5
      labels_data[h0:, :h1, h2:] = 6
      labels_data[h0:, h1:, :h2] = 7
      labels_data[h0:, h1:, h2:] = 8
      return labels_data
  
imports: import warnings
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_almost_equal, assert_equal
  from nilearn._utils.data_gen import generate_fake_fmri, generate_labeled_regions, generate_maps, generate_timeseries
  from nilearn._utils.exceptions import DimensionError
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye, _shape_3d_default
  from nilearn.image import get_data, new_img_like
  from nilearn.maskers import NiftiLabelsMasker
  from nilearn.regions.signal_extraction import _check_shape_and_affine_compatibility, _trim_maps, img_to_signals_labels, img_to_signals_maps, signals_to_img_labels, signals_to_img_maps
label_desc: Use image node_id 1 for calling a global function with example usage: _make_label_data(shape) and returns: labels_data