code: def test_parcellations_fit_on_multi_nifti_images(
      method, test_image, affine_eye
  ):
      fmri_imgs = [test_image] * 3
  
      parcellator = Parcellations(method=method, n_parcels=5, verbose=0)
      parcellator.fit(fmri_imgs)
  
      assert parcellator.labels_img_ is not None
  
      # Smoke test with explicit mask image
      mask_img = np.ones((10, 11, 12))
      mask_img = Nifti1Image(mask_img, affine_eye)
      parcellator = Parcellations(
          method=method, n_parcels=5, mask=mask_img, verbose=0
      )
      parcellator.fit(fmri_imgs)
  
imports: import warnings
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image
  from nilearn.conftest import _affine_eye
  from nilearn.regions.parcellations import Parcellations, _check_parameters_transform
label_desc: Use image node_id 8 for calling a global function with example usage: test_parcellations_fit_on_multi_nifti_images(method, test_image, affine_eye) without return types