code: def test_masked_edge(image, module, objects, workspace):
      # Regression test of issue #1115
      labels = numpy.zeros((20, 50), int)
  
      labels[15:25, 15:25] = 1
  
      pixel_data = numpy.random.uniform(size=labels.shape).astype(
          numpy.float32
      )
  
      #
      # Mask the edge of the object
      #
      mask = ~centrosome.outline.outline(labels).astype(bool)
  
      image.pixel_data = pixel_data
  
      image.mask = mask
  
      objects.segmented = labels
  
      module.run(workspace)
  
imports: import math
  import centrosome.outline
  import numpy
  import numpy.testing
  import pytest
  import skimage.measure
  import skimage.segmentation
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import EXPERIMENT, COLTYPE_FLOAT, C_LOCATION
  import cellprofiler.modules.measureobjectintensity
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
label_desc: Use image node_id 25 for calling a global function with example usage: test_masked_edge(image, module, objects, workspace) without return types