code: def test_variance():
      numpy.random.seed(41)
      images_and_masks = [
          (
              numpy.random.uniform(size=(20, 10)).astype(numpy.float32),
              None,
          )
          for i in range(10)
      ]
      image = run_image_set(
          cellprofiler.modules.makeprojection.P_VARIANCE,
          images_and_masks,
      )
      images = numpy.array([x[0] for x in images_and_masks])
      x = numpy.sum(images, 0)
      x2 = numpy.sum(images**2, 0)
      expected = x2 / 10.0 - x**2 / 100.0
      numpy.testing.assert_almost_equal(image.pixel_data, expected, 4)
  
imports: import numpy
  import six.moves
  import cellprofiler_core.image
  import cellprofiler_core.measurement
  import cellprofiler.modules.makeprojection
  import cellprofiler_core.object
  import cellprofiler_core.pipeline
  import cellprofiler_core.workspace
  import tests.frontend.modules
label_desc: Use image node_id 10 for calling a global function with example usage: test_variance() without return types