code: def test_gaussian_auto_large():
      """Test the smooth module with Gaussian smoothing in large automatic mode"""
      sigma = 30.0 / 2.35
      image = numpy.random.uniform(size=(3200, 100)).astype(
          numpy.float32
      )
      mask = numpy.ones(image.shape, bool)
      mask[40:60, 45:65] = False
      fn = lambda x: scipy.ndimage.gaussian_filter(
          x, sigma, mode="constant", cval=0.0
      )
      expected = centrosome.smooth.smooth_with_function_and_mask(
          image, fn, mask
      )
      workspace, module = make_workspace(image, mask)
      module.smoothing_method.value = (
          cellprofiler.modules.smooth.GAUSSIAN_FILTER
      )
      module.run(workspace)
      result = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
      assert not (result is None)
      numpy.testing.assert_almost_equal(result.pixel_data, expected)
  
imports: import io
  import centrosome.filter
  import centrosome.smooth
  import numpy
  import scipy.ndimage
  import skimage.restoration
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler.modules.smooth
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 5 for calling a global function with example usage: test_gaussian_auto_large() without return types