code: def test_test_watershed_shape_shape():
      """Identify by local_maxima:shape & intensity:shape
  
      Create an object whose intensity is high near the middle
      but has an hourglass shape, then segment it using shape/shape
      """
      x = (
          cellprofiler.modules.identifyprimaryobjects.IdentifyPrimaryObjects()
      )
      x.use_advanced.value = True
      x.x_name.value = "my_image"
      x.y_name.value = "my_object"
      x.exclude_size.value = False
      x.size_range.value = (2, 10)
      x.fill_holes.value = False
      x.maxima_suppression_size.value = 3
      x.automatic_suppression.value = False
      x.unclump_method.value = (
          cellprofiler.modules.identifyprimaryobjects.UN_SHAPE
      )
      x.watershed_method.value = (
          cellprofiler.modules.identifyprimaryobjects.WA_SHAPE
      )
      x.threshold.threshold_scope.value = TS_GLOBAL
      x.threshold.global_operation.value = centrosome.threshold.TM_OTSU
      x.threshold.threshold_smoothing_scale.value = 0
      img = numpy.array(
          [
              [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
              [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
              [
                  0,
                  0,
                  0,
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0,
                  0,
                  0,
                  0,
              ],
              [0, 0, 0, 0, 0, 0.8, 0.9, 1, 1, 0.9, 0.8, 0, 0, 0, 0, 0],
              [
                  0,
                  0,
                  0,
                  0,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0.7,
                  0,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0.6,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
                  0,
              ],
              [
                  0,
                  0,
                  0,
                  0,
                  0,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0.5,
                  0,
                  0,
                  0,
                  0,
                  0,
              ],
              [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
              [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
          ]
      )
      image = cellprofiler_core.image.Image(img)
      image_set_list = cellprofiler_core.image.ImageSetList()
      image_set = image_set_list.get_image_set(0)
      image_set.providers.append(VanillaImage("my_image", image))
      object_set = cellprofiler_core.object.ObjectSet()
      measurements = cellprofiler_core.measurement.Measurements()
      pipeline = cellprofiler_core.pipeline.Pipeline()
      x.run(
          cellprofiler_core.workspace.Workspace(
              pipeline, x, image_set, object_set, measurements, None
          )
      )
      objects = object_set.get_objects("my_object")
      assert numpy.max(objects.segmented) == 2
  
imports: import io
  import os
  import centrosome.threshold
  import numpy
  import pytest
  import scipy.ndimage
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import FF_COUNT, COLTYPE_INTEGER, FF_FINAL_THRESHOLD, COLTYPE_FLOAT, FF_ORIG_THRESHOLD, M_NUMBER_OBJECT_NUMBER, M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, M_LOCATION_CENTER_Z, FF_SUM_OF_ENTROPIES, FF_WEIGHTED_VARIANCE
  from cellprofiler_core.constants.module._identify import TS_GLOBAL, TS_ADAPTIVE, O_TWO_CLASS, O_FOREGROUND, O_THREE_CLASS, O_BACKGROUND, RB_MODE, RB_SD, RB_MEAN, RB_MEDIAN, RB_MAD, TS_MANUAL, TS_MEASUREMENT
  from cellprofiler_core.image import VanillaImage
  import cellprofiler.modules.identifyprimaryobjects
  import cellprofiler.modules.threshold
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.setting
  import cellprofiler_core.workspace
  import tests.frontend
  import tests.frontend.modules
label_desc: Use image node_id 15 for calling a global function with example usage: test_test_watershed_shape_shape() without return types