code: def test_standardization(rng):
      data = rng.random((3, 3, 3, 5))
      img = nibabel.Nifti1Image(data, np.eye(4))
  
      # test zscore
      masker = NiftiSpheresMasker(
          [(1, 1, 1)], standardize="zscore_sample"
      )
      # Test the fit
      s = masker.fit_transform(img)
  
      np.testing.assert_almost_equal(s.mean(), 0)
      np.testing.assert_almost_equal(s.std(), 1, decimal=1)
  
      # test psc
      masker = NiftiSpheresMasker([(1, 1, 1)], standardize="psc")
      # Test the fit
      s = masker.fit_transform(img)
  
      np.testing.assert_almost_equal(s.mean(), 0)
      np.testing.assert_almost_equal(
          s.ravel(),
          data[1, 1, 1] / data[1, 1, 1].mean() * 100 - 100,
      )
  
imports: import warnings
  import nibabel
  import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from nilearn._utils import data_gen
  from nilearn.image import get_data, new_img_like
  from nilearn.maskers import NiftiSpheresMasker
label_desc: Use image node_id 8 for calling a global function with example usage: test_standardization(rng) without return types