code: def _disk_with_spacing(
      radius, dtype=np.uint8, *, strict_radius=True, spacing=None
  ):
      # Identical to morphology.disk, but with a spacing parameter and without decomposition.
      # This is different from morphology.ellipse which produces a slightly different footprint.
      L = np.arange(-radius, radius + 1)
      X, Y = np.meshgrid(L, L)
  
      if spacing is not None:
          X *= spacing[1]
          Y *= spacing[0]
  
      if not strict_radius:
          radius += 0.5
      return np.array((X**2 + Y**2) <= radius**2, dtype=dtype)
  
file_path: scikit-image/skimage/morphology/tests/test_isotropic.py
imports: import numpy
  from numpy.testing import assert_array_equal
  from skimage import color, data, morphology
  from skimage.morphology import binary, isotropic
  from skimage.util import img_as_bool
label_desc: Use image node_id 3 for calling a global function with example usage: _disk_with_spacing(radius, dtype) and returns: np