code: def test_parcellations_transform_multi_nifti_images(
      method, n_parcel, test_image_2
  ):
      fmri_imgs = [test_image_2] * 3
  
      parcellator = Parcellations(
          method=method, n_parcels=n_parcel, verbose=0
      )
      parcellator.fit(fmri_imgs)
  
      # transform multi images to signals.
      # In return, we have length equal to the number of images
      signals = parcellator.transform(fmri_imgs)
  
      assert signals[0].shape == (test_image_2.shape[3], n_parcel)
      assert signals[1].shape == (test_image_2.shape[3], n_parcel)
      assert signals[2].shape == (test_image_2.shape[3], n_parcel)
      assert len(signals) == len(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 11 for calling a global function with example usage: test_parcellations_transform_multi_nifti_images(method, n_parcel, test_image_2) without return types