code: def test_trivial_footprint16(self):
      # check that min, max and mean returns identity if footprint
      # contains only central pixel
  
      image = np.zeros((5, 5), dtype=np.uint16)
      out = np.zeros_like(image)
      mask = np.ones_like(image, dtype=np.uint8)
      image[2, 2] = 255
      image[2, 3] = 128
      image[1, 2] = 16
  
      elem = np.array([[0, 0, 0], [0, 1, 0], [0, 0, 0]], dtype=np.uint8)
      rank.mean(
          image=image,
          footprint=elem,
          out=out,
          mask=mask,
          shift_x=0,
          shift_y=0,
      )
      assert_equal(image, out)
      rank.geometric_mean(
          image=image,
          footprint=elem,
          out=out,
          mask=mask,
          shift_x=0,
          shift_y=0,
      )
      assert_equal(image, out)
      rank.minimum(
          image=image,
          footprint=elem,
          out=out,
          mask=mask,
          shift_x=0,
          shift_y=0,
      )
      assert_equal(image, out)
      rank.maximum(
          image=image,
          footprint=elem,
          out=out,
          mask=mask,
          shift_x=0,
          shift_y=0,
      )
      assert_equal(image, out)
  
imports: import numpy
  import pytest
  from skimage import data, morphology, util
  from skimage._shared._warnings import expected_warnings
  from skimage._shared.testing import assert_allclose, assert_array_almost_equal, assert_equal, fetch, run_in_parallel
  from skimage.filters import rank
  from skimage.filters.rank import __all__
  from skimage.filters.rank import subtract_mean
  from skimage.morphology import ball, disk, gray
  from skimage.util import img_as_float, img_as_ubyte
label_desc: Use image node_id 21 for calling the TestRank obj's underlying member method code with example usage: obj.test_trivial_footprint16() without return types