code: def data_for_mask_and_reduce():
      """Create "multi-subject" dataset with fake activation."""
      shape = (6, 8, 10, 5)
  
      imgs = []
      for _ in range(8):
          this_img = _rng().normal(size=shape)
  
          # Add activation
          this_img[2:4, 2:4, 2:4, :] += 10
  
          imgs.append(Nifti1Image(this_img, _affine_eye()))
  
      return imgs
  
file_path: nilearn/nilearn/decomposition/tests/test_base.py
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_array_almost_equal
  from scipy import linalg
  from nilearn.conftest import _affine_eye, _img_3d_ones, _rng
  from nilearn.decomposition._base import _fast_svd, _mask_and_reduce
  from nilearn.maskers import MultiNiftiMasker
label_desc: Use image node_id 1 for calling a global function with example usage: data_for_mask_and_reduce() and returns: imgs