code: def test_subtract_mean_underflow_correction(dtype):
      # Input: [10, 10, 10]
      footprint = np.ones((1, 3))
      arr = np.array([[10, 10, 10]], dtype=dtype)
      result = subtract_mean(arr, footprint)
  
      if dtype == np.uint8:
          expected_val = 127
      else:
          expected_val = (arr.max() + 1) // 2 - 1
  
      assert np.all(result == expected_val)
  
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 2 for calling a global function with example usage: test_subtract_mean_underflow_correction(dtype) without return types