code: def test_sample_locations_depth(depth, n_points, affine_eye):
      mesh = flat_mesh(5, 7)
      radius = 8.0
      locations = surface._sample_locations(
          mesh, affine_eye, radius, n_points=n_points, depth=depth
      )
      offsets = np.asarray([[0.0, 0.0, -z * radius] for z in depth])
      expected = np.asarray([vertex + offsets for vertex in mesh[0]])
      assert np.allclose(locations, expected)
  
imports: import os
  import tempfile
  import warnings
  import nibabel
  import numpy
  import pytest
  from nibabel import gifti
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from scipy.spatial import Delaunay
  from scipy.stats import pearsonr
  from nilearn import datasets, image
  from nilearn._utils import data_gen
  from nilearn.image import resampling
  from nilearn.surface import Mesh, Surface, load_surf_data, load_surf_mesh, surface
  from nilearn.surface.surface import _gifti_img_to_mesh, _load_surf_files_gifti_gzip
  from nilearn.surface.tests._testing import flat_mesh, generate_surf, z_const_img
label_desc: Use image node_id 22 for calling a global function with example usage: test_sample_locations_depth(depth, n_points, affine_eye) without return types