code: def test_std_intensity_edge(
      image, measurements, module, objects, workspace
  ):
      numpy.random.seed(39)
  
      labels = numpy.ones((40, 30), int)
  
      labels[:, 15:] = 3
  
      labels[20:, :] += 1
  
      edge_mask = skimage.segmentation.find_boundaries(
          labels, mode="inner"
      )
  
      elabels = labels * edge_mask
  
      pixel_data = numpy.random.uniform(size=(40, 30)).astype(
          numpy.float32
      )
  
      image.pixel_data = pixel_data
  
      objects.segmented = labels
  
      module.run(workspace)
  
      assert isinstance(
          measurements, cellprofiler_core.measurement.Measurements
      )
  
      values = measurements.get_current_measurement(
          OBJECT_NAME,
          "_".join(
              (
                  cellprofiler.modules.measureobjectintensity.INTENSITY,
                  cellprofiler.modules.measureobjectintensity.STD_INTENSITY_EDGE,
                  IMAGE_NAME,
              )
          ),
      )
  
      assert len(values) == 4
  
      for i in range(1, 5):
          numpy.testing.assert_almost_equal(
              values[i - 1], numpy.std(pixel_data[elabels == i])
          )
  
imports: import math
  import centrosome.outline
  import numpy
  import numpy.testing
  import pytest
  import skimage.measure
  import skimage.segmentation
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  from cellprofiler_core.constants.measurement import EXPERIMENT, COLTYPE_FLOAT, C_LOCATION
  import cellprofiler.modules.measureobjectintensity
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.preferences
  import cellprofiler_core.workspace
label_desc: Use image node_id 22 for calling a global function with example usage: test_std_intensity_edge(image, measurements, module, objects, workspace) without return types