code: def test_components_img(canica_data, mask_img):
      n_components = 3
      dict_learning = DictLearning(
          n_components=n_components, mask=mask_img
      )
  
      dict_learning.fit(canica_data)
      components_img = dict_learning.components_img_
  
      assert isinstance(components_img, Nifti1Image)
  
      check_shape = canica_data[0].shape[:3] + (n_components,)
  
      assert components_img.shape, check_shape
  
imports: import numpy
  import pytest
  from nibabel import Nifti1Image
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye
  from nilearn.decomposition.dict_learning import DictLearning
  from nilearn.decomposition.tests.test_canica import _make_canica_test_data
  from nilearn.image import get_data, iter_img
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 10 for calling a global function with example usage: test_components_img(canica_data, mask_img) without return types