code: def test_downsample(shape, affine_eye, rng):
      """Test resampling with a 1/2 down-sampling affine."""
      data = rng.random(shape)
  
      rot_img = resample_img(
          Nifti1Image(data, affine_eye),
          target_affine=2 * affine_eye,
          interpolation="nearest",
      )
  
      downsampled = data[::2, ::2, ::2, ...]
      x, y, z = downsampled.shape[:3]
  
      assert_almost_equal(
          downsampled, get_data(rot_img)[:x, :y, :z, ...]
      )
  
      rot_img_2 = resample_img(
          Nifti1Image(data, affine_eye),
          target_affine=2 * affine_eye,
          interpolation="nearest",
          force_resample=True,
      )
  
      assert_almost_equal(get_data(rot_img_2), get_data(rot_img))
  
imports: import copy
  import math
  import os
  from pathlib import Path
  import numpy
  import pytest
  from nibabel import Nifti1Header, Nifti1Image
  from nibabel.freesurfer import MGHImage
  from numpy.testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal, assert_equal
  from nilearn import _utils
  from nilearn._utils import testing
  from nilearn.conftest import _affine_eye, _rng
  from nilearn.image import get_data
  from nilearn.image.image import _pad_array, crop_img
  from nilearn.image.resampling import BoundingBoxError, coord_transform, from_matrix_vector, get_bounds, reorder_img, resample_img, resample_to_img
label_desc: Use image node_id 6 for calling a global function with example usage: test_downsample(shape, affine_eye, rng) without return types