code: def test_data_complete_mask(affine_eye, display):
      """Test for a special case due to matplotlib 2.1.0.
      When the data is completely masked, then we have plotting issues
      See similar issue #9280 reported in matplotlib. This function
      tests the patch added for this particular issue.
      """
      # data is completely masked
      data = np.zeros((10, 20, 30))
      img = Nifti1Image(data, affine_eye)
      n_cuts = 3 if display == OrthoSlicer else 4
      display = display(cut_coords=(0,) * n_cuts)
      display.add_overlay(img)
      display.close()
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from nilearn.datasets import load_mni152_template
  from nilearn.plotting.displays import BaseAxes, LProjector, LRProjector, LYRProjector, LYRZProjector, LZRProjector, LZRYProjector, MosaicSlicer, OrthoProjector, OrthoSlicer, RProjector, TiledSlicer, XProjector, XSlicer, XZProjector, XZSlicer, YProjector, YSlicer, YXProjector, YXSlicer, YZProjector, YZSlicer, ZProjector, ZSlicer
label_desc: Use image node_id 19 for calling a global function with example usage: test_data_complete_mask(affine_eye, display) without return types