code: def test_multi_pca(multi_pca_data, mask_img):
      """Components are the same if we put twice the same data, \
      and that fit output is deterministic"""
      multi_pca = _MultiPCA(
          mask=mask_img, n_components=3, random_state=0
      )
      multi_pca.fit(multi_pca_data)
  
      components1 = multi_pca.components_
      components2 = multi_pca.fit(multi_pca_data).components_
      components3 = multi_pca.fit(2 * multi_pca_data).components_
  
      np.testing.assert_array_equal(components1, components2)
      np.testing.assert_array_almost_equal(components1, components3)
  
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_almost_equal
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye, _rng
  from nilearn.decomposition._multi_pca import _MultiPCA
  from nilearn.maskers import MultiNiftiMasker, NiftiMasker
label_desc: Use image node_id 6 for calling a global function with example usage: test_multi_pca(multi_pca_data, mask_img) without return types