code: def display(self, workspace, figure):
      dimensions = workspace.display_data.dimensions
      figure.set_subplots((2, 2), dimensions=dimensions)
      figure.subplot_imshow_labels(
          0,
          0,
          workspace.display_data.orig_labels,
          "Original: %s" % self.object_name.value,
      )
  
      object_mask = workspace.display_data.object_mask
      expanded_labels = workspace.display_data.expanded_labels
      neighbor_count_image = workspace.display_data.neighbor_count_image
      neighbor_count_image[~object_mask] = -1
      neighbor_cm = get_colormap(
          workspace.display_data.neighbor_cm_name
      )
      neighbor_cm.set_under((0, 0, 0))
      neighbor_cm = matplotlib.cm.ScalarMappable(cmap=neighbor_cm)
      percent_touching_cm = get_colormap(
          workspace.display_data.percent_touching_cm_name
      )
      percent_touching_cm.set_under((0, 0, 0))
      percent_touching_image = (
          workspace.display_data.percent_touching_image
      )
      percent_touching_image[~object_mask] = -1
      percent_touching_cm = matplotlib.cm.ScalarMappable(
          cmap=percent_touching_cm
      )
      expandplot_position = 0
      if not self.neighbors_are_objects:
          # Display the neighbor object set, move expanded objects plot out of the way
          expandplot_position = 1
          figure.subplot_imshow_labels(
              1,
              0,
              workspace.display_data.neighbor_labels,
              "Neighbors: %s" % self.neighbors_name.value,
          )
      if numpy.any(object_mask):
          figure.subplot_imshow(
              0,
              1,
              neighbor_count_image,
              "%s colored by # of neighbors" % self.object_name.value,
              colormap=neighbor_cm,
              colorbar=True,
              vmin=0,
              vmax=max(neighbor_count_image.max(), 1),
              normalize=False,
              sharexy=figure.subplot(0, 0),
          )
          if self.neighbors_are_objects:
              figure.subplot_imshow(
                  1,
                  1,
                  percent_touching_image,
                  "%s colored by pct touching" % self.object_name.value,
                  colormap=percent_touching_cm,
                  colorbar=True,
                  vmin=0,
                  vmax=max(percent_touching_image.max(), 1),
                  normalize=False,
                  sharexy=figure.subplot(0, 0),
              )
      else:
          # No objects - colorbar blows up.
          figure.subplot_imshow(
              0,
              1,
              neighbor_count_image,
              "%s colored by # of neighbors" % self.object_name.value,
              colormap=neighbor_cm,
              vmin=0,
              vmax=max(neighbor_count_image.max(), 1),
              sharexy=figure.subplot(0, 0),
          )
          if self.neighbors_are_objects:
              figure.subplot_imshow(
                  1,
                  1,
                  percent_touching_image,
                  "%s colored by pct touching" % self.object_name.value,
                  colormap=percent_touching_cm,
                  vmin=0,
                  vmax=max(neighbor_count_image.max(), 1),
                  sharexy=figure.subplot(0, 0),
              )
  
      if self.distance_method == D_EXPAND:
          figure.subplot_imshow_labels(
              1,
              expandplot_position,
              expanded_labels,
              "Expanded %s" % self.object_name.value,
              sharexy=figure.subplot(0, 0),
          )
  
imports: import matplotlib.cm
  import numpy
  import scipy.ndimage
  import scipy.signal
  import skimage.morphology
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
  from cellprofiler_core.constants.measurement import COLTYPE_INTEGER
  from cellprofiler_core.constants.measurement import MCA_AVAILABLE_EACH_CYCLE
  from cellprofiler_core.constants.measurement import NEIGHBORS
  from cellprofiler_core.image import Image
  from cellprofiler_core.measurement import Measurements
  from cellprofiler_core.module import Module
  from cellprofiler_core.object import Objects
  from cellprofiler_core.preferences import get_default_colormap
  from cellprofiler_core.setting import Binary
  from cellprofiler_core.setting.choice import Choice, Colormap
  from cellprofiler_core.setting.subscriber import LabelSubscriber
  from cellprofiler_core.setting.text import ImageName
  from cellprofiler_core.setting.text import Integer
  from cellprofiler_core.workspace import Workspace
  from centrosome.cpmorphology import fixup_scipy_ndimage_result
  from centrosome.cpmorphology import strel_disk, centers_of_labels
  from centrosome.outline import outline
label_desc: Use image node_id 6 for calling the MeasureObjectNeighbors obj's underlying member method code with example usage: obj.display(workspace, figure) without return types