code: def test_overlapping_outlines():
      params = zlib.decompress(base64.b64decode(PARAMS))
      workspace, module = make_workspace(A02_image, params)
      assert isinstance(
          module, cellprofiler.modules.untangleworms.UntangleWorms
      )
      module.prepare_group(workspace, None, None)
      module.wants_training_set_weights.value = False
      module.override_leftover_weight.value = 6
      module.override_overlap_weight.value = 3
      module.wants_overlapping_outlines.value = True
      module.overlapping_outlines_name.value = OVERLAPPING_OUTLINES_NAME
      module.run(workspace)
      object_set = workspace.object_set
      assert isinstance(object_set, cellprofiler_core.object.ObjectSet)
      worms = object_set.get_objects(OVERLAP_OBJECTS_NAME)
      outlines = workspace.image_set.get_image(
          OVERLAPPING_OUTLINES_NAME
      ).pixel_data
      outlines = numpy.sum(outlines, 2) > 0  # crunch color dimension
      i, j, v = worms.ijv.transpose()
      expected = numpy.zeros(outlines.shape, bool)
      expected[i, j] = True
      # all outlines are in some object...
      assert numpy.all(expected[outlines])
  
imports: import base64
  import io
  import os
  import tempfile
  import zlib
  import imageio
  import centrosome.outline
  import numpy
  import scipy.ndimage
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.modules
  import cellprofiler.modules.untangleworms
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.setting
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 38 for calling a global function with example usage: test_overlapping_outlines() without return types