code: def test_correlated():
      numpy.random.seed(0)
      image = numpy.random.uniform(size=(10, 10))
      i1 = cellprofiler_core.image.Image(image)
      i2 = cellprofiler_core.image.Image(image)
      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
  
      assert len(m.get_object_names()) == 1
      assert m.get_object_names()[0] == "Image"
      columns = module.get_measurement_columns(None)
      features = m.get_feature_names("Image")
      assert len(columns) == len(features)
      for column in columns:
          assert column[1] in features
  
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 10 for calling a global function with example usage: test_correlated() without return types