code: def test_01_get_measurement_columns():
      module = (
          cellprofiler.modules.measureobjectintensitydistribution.MeasureObjectIntensityDistribution()
      )
      module.images_list.value = "DNA, Cytoplasm, Actin"
      for i, object_name, center_name in (
          (0, "Nucleii", None),
          (1, "Cells", "Nucleii"),
          (2, "Cytoplasm", "Nucleii"),
      ):
          if i:
              module.add_object()
          module.objects[i].object_name.value = object_name
          if center_name is None:
              module.objects[
                  i
              ].center_choice.value = (
                  cellprofiler.modules.measureobjectintensitydistribution.C_SELF
              )
          else:
              module.objects[
                  i
              ].center_choice.value = (
                  cellprofiler.modules.measureobjectintensitydistribution.C_CENTERS_OF_OTHER
              )
              module.objects[i].center_object_name.value = center_name
      for i, bin_count in enumerate((4, 5, 6)):
          if i:
              module.add_bin_count()
          module.bin_counts[i].bin_count.value = bin_count
      module.bin_counts[2].wants_scaled.value = False
  
      columns = module.get_measurement_columns(None)
      column_dictionary = {}
      for object_name, feature, coltype in columns:
          key = (object_name, feature)
          assert not (key in column_dictionary)
          assert coltype == COLTYPE_FLOAT
          column_dictionary[key] = (object_name, feature, coltype)
  
      for object_name in [x.object_name.value for x in module.objects]:
          for image_name in module.images_list.value:
              for bin_count, wants_scaled in [
                  (x.bin_count.value, x.wants_scaled.value)
                  for x in module.bin_counts
              ]:
                  for bin in range(
                      1, bin_count + (1 if wants_scaled else 2)
                  ):
                      for feature_fn in (
                          feature_frac_at_d,
                          feature_mean_frac,
                          feature_radial_cv,
                      ):
                          measurement = feature_fn(
                              bin, bin_count, image_name
                          )
                          key = (object_name, measurement)
                          assert key in column_dictionary
                          del column_dictionary[key]
      assert len(column_dictionary) == 0
  
imports: import io
  import centrosome.propagate
  import numpy
  import scipy.stats
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler_core.module
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
  import cellprofiler.modules.measureobjectintensitydistribution
  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 9 for calling a global function with example usage: test_01_get_measurement_columns() without return types