code: def test_unify_image_closest_point():
      labels = numpy.zeros((10, 20), int)
      labels[2:5, 3:8] = 1
      labels[2:5, 13:18] = 2
      image = numpy.ones((10, 20)) * (labels > 0) * 0.6
      image[2, 8:13] = 0.41
      image[2, 7] = 0.5
      image[2, 13] = 0.5
      labels_out, workspace = rruunn(
          labels,
          cellprofiler.modules.splitormergeobjects.OPTION_MERGE,
          distance_threshold=6,
          image=image,
          minimum_intensity_fraction=0.8,
          where_algorithm=cellprofiler.modules.splitormergeobjects.CA_CLOSEST_POINT,
      )
      assert numpy.all(labels_out[labels != 0] == 1)
      assert numpy.all(labels_out[labels == 0] == 0)
  
imports: import numpy
  import six.moves
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, FF_COUNT, FF_PARENT, COLTYPE_FLOAT, M_NUMBER_OBJECT_NUMBER, COLTYPE_INTEGER, FF_CHILDREN_COUNT
  import cellprofiler.modules.splitormergeobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 13 for calling a global function with example usage: test_unify_image_closest_point() without return types