code: def test_nan_offset_by_1():
      # Regression test of 1636
      labels = numpy.zeros((10, 15), int)
      labels[3:5, 3:5] = 1
      labels[6:8, 3:5] = 2
  
      m1 = numpy.array((4, numpy.NaN))
      m2 = numpy.array((4, 4))
      workspace, module = make_workspace(
          labels,
          cellprofiler.modules.classifyobjects.BY_TWO_MEASUREMENTS,
          m1,
          m2,
      )
      assert isinstance(
          module, cellprofiler.modules.classifyobjects.ClassifyObjects
      )
      module.first_threshold_method.value = (
          cellprofiler.modules.classifyobjects.TM_MEAN
      )
      module.first_threshold.value = 2
      module.second_threshold_method.value = (
          cellprofiler.modules.classifyobjects.TM_MEAN
      )
      module.second_threshold.value = 2
      module.wants_image.value = True
      module.wants_custom_names.value = False
      module.run(workspace)
      image = workspace.image_set.get_image(IMAGE_NAME).pixel_data
      colors = module.get_colors(4)
      reverse = numpy.zeros(image.shape[:2], int)
      for idx, color in enumerate(colors):
          reverse[
              numpy.all(
                  image == color[numpy.newaxis, numpy.newaxis, :3], 2
              )
          ] = idx
      assert numpy.all(reverse[labels == 1] == 4)
  
imports: import contextlib
  import os
  import pickle
  import tempfile
  import numpy
  import pytest
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, COLTYPE_INTEGER
  import cellprofiler.modules.classifyobjects
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.setting
  import cellprofiler_core.workspace
label_desc: Use image node_id 11 for calling a global function with example usage: test_nan_offset_by_1() without return types