code: def test_enhance_circles_masked_volume(image, module, workspace):
      data = numpy.zeros((31, 31, 62))
  
      mask = numpy.ones_like(data, dtype=bool)
  
      k, i, j = numpy.mgrid[-15:16, -15:16, -15:16]
  
      circle = numpy.abs(numpy.sqrt(k * k + i * i + j * j) - 6) <= 1.5
  
      data[:, :, :31] = circle
  
      data[:, :, 31:] = circle
  
      data = data.astype(float)
  
      mask[:, :, 31:][circle] = False
  
      image.pixel_data = data
  
      image.mask = mask
  
      image.dimensions = 3
  
      module.method.value = (
          cellprofiler.modules.enhanceorsuppressfeatures.ENHANCE
      )
  
      module.enhance_method.value = (
          cellprofiler.modules.enhanceorsuppressfeatures.E_CIRCLES
      )
  
      module.object_size.value = 12
  
      module.run(workspace)
  
      actual = workspace.image_set.get_image("output").pixel_data
  
      expected = numpy.zeros_like(data)
  
      data[:, :, 31:] = 0
  
      for index, plane in enumerate(data):
          expected[index] = skimage.transform.hough_circle(plane, 6)[0]
  
      expected[:, :, 31:] = circle
  
      expected = expected.astype(float)
  
      numpy.testing.assert_array_almost_equal(expected, actual)
  
imports: import io
  import os.path
  import centrosome.filter
  import numpy
  import pytest
  import scipy.ndimage
  import skimage.exposure
  import skimage.filters
  import skimage.transform
  import tests.frontend.modules
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.module
  import cellprofiler.modules.enhanceorsuppressfeatures
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
  import tests.frontend
label_desc: Use image node_id 24 for calling a global function with example usage: test_enhance_circles_masked_volume(image, module, workspace) without return types