code: def test_mahalanobis(rng):
      n = 50
      x = rng.uniform(size=n) / n
      A = rng.uniform(size=(n, n)) / n
      A = np.dot(A.transpose(), A) + np.eye(n)
      mah = np.dot(x, np.dot(spl.inv(A), x))
  
      assert_almost_equal(mah, multiple_mahalanobis(x, A), decimal=1)
  
imports: import numpy
  import pytest
  import scipy.linalg
  import scipy.stats
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy.stats import norm
  from nilearn._utils.data_gen import generate_fake_fmri
  from nilearn.glm._utils import full_rank, multiple_fast_inverse, multiple_mahalanobis, pad_contrast, positive_reciprocal, z_score
  from nilearn.glm.first_level import FirstLevelModel, make_first_level_design_matrix
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 5 for calling a global function with example usage: test_mahalanobis(rng) without return types