code: def test_object_is_missing():
      # regression test of #1639
      #
      # Object # 2 should match neighbor # 1, but because of
      # an error in masking distances, neighbor #1 is masked out
      #
      olabels = numpy.zeros((20, 10), int)
      olabels[2, 2] = 2
      nlabels = numpy.zeros((20, 10), int)
      nlabels[2, 3] = 1
      nlabels[5, 2] = 2
      workspace, module = make_workspace(
          olabels,
          cellprofiler.modules.measureobjectneighbors.D_EXPAND,
          distance=20,
          neighbors_labels=nlabels,
      )
      assert isinstance(
          module,
          cellprofiler.modules.measureobjectneighbors.MeasureObjectNeighbors,
      )
      module.run(workspace)
      m = workspace.measurements
      assert isinstance(m, cellprofiler_core.measurement.Measurements)
      ftr = module.get_measurement_name(
          cellprofiler.modules.measureobjectneighbors.M_FIRST_CLOSEST_OBJECT_NUMBER
      )
      values = m[OBJECTS_NAME, ftr]
      assert values[1] == 1
  
imports: import numpy
  import six.moves
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import COLTYPE_INTEGER, COLTYPE_FLOAT, NEIGHBORS, R_FIRST_OBJECT_NUMBER, R_SECOND_OBJECT_NUMBER
  from cellprofiler_core.measurement import RelationshipKey
  import cellprofiler.modules.measureobjectneighbors
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 25 for calling a global function with example usage: test_object_is_missing() without return types