code: def test_mask():
      """Test images with two different masks"""
      numpy.random.seed(0)
      image1 = numpy.random.uniform(size=(20, 20))
      mask1 = numpy.ones((20, 20), bool)
      mask1[5:8, 8:12] = False
      mask2 = numpy.ones((20, 20), bool)
      mask2[14:18, 2:5] = False
      mask = mask1 & mask2
      image2 = image1.copy()
      #
      # Try to confound the module by making masked points anti-correlated
      #
      image2[~mask] = 1 - image1[~mask]
      i1 = cellprofiler_core.image.Image(image1, mask=mask1)
      i2 = cellprofiler_core.image.Image(image2, mask=mask2)
      workspace, module = make_workspace(i1, i2)
      module.run(workspace)
      m = workspace.measurements
      mi = module.get_measurement_images(
          None, "Image", "Correlation", "Correlation"
      )
      corr = m.get_current_measurement(
          "Image", "Correlation_Correlation_%s" % mi[0]
      )
      assert round(abs(corr - 1), 7) == 0
  
imports: import numpy
  import six.moves
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
  import cellprofiler.modules.measurecolocalization
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 14 for calling a global function with example usage: test_mask() without return types