code: def test_minimum_mask():
      numpy.random.seed(72)
      images_and_masks = [
          (
              numpy.random.uniform(size=(100, 100)).astype(
                  numpy.float32
              ),
              numpy.random.uniform(size=(100, 100)) > 0.3,
          )
          for i in range(3)
      ]
      expected = numpy.ones((100, 100), numpy.float32)
      expected_mask = numpy.zeros((100, 100), bool)
      for image, mask in images_and_masks:
          expected[mask] = numpy.minimum(expected[mask], image[mask])
          expected_mask = mask | expected_mask
      image = run_image_set(
          cellprofiler.modules.makeprojection.P_MINIMUM,
          images_and_masks,
      )
      assert image.has_mask
      assert numpy.any(image.mask == False)
      assert numpy.all(expected_mask == image.mask)
      assert numpy.all(
          numpy.abs(
              image.pixel_data[image.mask] - expected[expected_mask]
          )
          < numpy.finfo(float).eps
      )
      assert numpy.all(image.pixel_data[~image.mask] == 0)
  
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 14 for calling a global function with example usage: test_minimum_mask() without return types