code: def test_unedited_segmented():
      # Test transferral of unedited segmented segmentation
      # from source to target
  
      unedited = numpy.zeros((10, 10), dtype=int)
      unedited[0:4, 0:4] = 1
      unedited[6:8, 0:4] = 2
      unedited[6:8, 6:8] = 3
      segmented = numpy.zeros((10, 10), dtype=int)
      segmented[6:8, 6:8] = 1
      segmented[6:8, 0:4] = 2
  
      workspace, module = make_workspace({})
      input_objects = cellprofiler_core.object.Objects()
      workspace.object_set.add_objects(input_objects, INPUT_OBJECTS)
      input_objects.segmented = segmented
      input_objects.unedited_segmented = unedited
      module.x_name.value = INPUT_OBJECTS
      module.y_name.value = OUTPUT_OBJECTS
      module.mode.value = (
          cellprofiler.modules.filterobjects.MODE_MEASUREMENTS
      )
      module.measurements[0].measurement.value = TEST_FTR
      module.filter_choice.value = (
          cellprofiler.modules.filterobjects.FI_MINIMAL
      )
      m = workspace.measurements
      m[INPUT_OBJECTS, TEST_FTR] = numpy.array([2, 1])
      module.run(workspace)
      output_objects = workspace.object_set.get_objects(OUTPUT_OBJECTS)
      numpy.testing.assert_equal(
          output_objects.unedited_segmented, unedited
      )
  
imports: import contextlib
  import io
  import os
  import pickle
  import tempfile
  import numpy
  import pytest
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.modules
  from cellprofiler_core.constants.measurement import FF_PARENT, FF_COUNT, FF_CHILDREN_COUNT, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, M_LOCATION_CENTER_Z, M_NUMBER_OBJECT_NUMBER
  import cellprofiler.modules.filterobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 27 for calling a global function with example usage: test_unedited_segmented() without return types