code: def test_load_uniform_ball_cloud():
      # Note: computed and shipped point clouds may differ since KMeans results
      # change after
      # https://github.com/scikit-learn/scikit-learn/pull/9288
      # but the exact position of the points does not matter as long as they are
      # well spread inside the unit ball
      for n_points in [10, 20, 40, 80, 160]:
          with warnings.catch_warnings(record=True) as w:
              points = surface._load_uniform_ball_cloud(
                  n_points=n_points
              )
              assert_array_equal(points.shape, (n_points, 3))
              assert len(w) == 0
      with pytest.warns(surface.EfficiencyWarning):
          surface._load_uniform_ball_cloud(n_points=3)
      for n_points in [3, 7]:
          computed = surface._uniform_ball_cloud(n_points)
          loaded = surface._load_uniform_ball_cloud(n_points)
          assert_array_almost_equal(computed, loaded)
          assert (np.std(computed, axis=0) > 0.1).all()
          assert (np.linalg.norm(computed, axis=1) <= 1).all()
  
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 20 for calling a global function with example usage: test_load_uniform_ball_cloud() without return types