def test_04_03_00_manual_input_range_auto_high(self):
numpy.random.seed(0)
expected = numpy.random.uniform(size=(10, 10)).astype(numpy.float32)
expected[0, 0] = 1
workspace, module = self.make_workspace(expected / 2 + .1)
module.rescale_method.value = cellprofiler.modules.rescaleintensity.M_MANUAL_INPUT_RANGE
module.wants_automatic_low.value = cellprofiler.modules.rescaleintensity.CUSTOM_VALUE
module.wants_automatic_high.value = cellprofiler.modules.rescaleintensity.HIGH_EACH_IMAGE
module.source_low.value = .1
self.assertFalse(module.is_aggregation_module())
module.run(workspace)
pixels = workspace.image_set.get_image(OUTPUT_NAME).pixel_data
numpy.testing.assert_almost_equal(pixels, expected)
def test_04_03_00_manual_input_range_auto_high(self):
numpy.random.seed(0)
expected = numpy.random.uniform(size=(10, 10)).astype(numpy.float32)
expected[0, 0] = 1
workspace, module = self.make_workspace(expected / 2 + .1)
module.rescale_method.value = cellprofiler.modules.rescaleintensity.M_MANUAL_INPUT_RANGE
module.wants_automatic_low.value = cellprofiler.modules.rescaleintensity.CUSTOM_VALUE
module.wants_automatic_high.value = cellprofiler.modules.rescaleintensity.HIGH_EACH_IMAGE
module.source_low.value = .1
self.assertFalse(module.is_aggregation_module())
module.run(workspace)
pixels = workspace.image_set.get_image(OUTPUT_NAME).pixel_data
numpy.testing.assert_almost_equal(pixels, expected)
def test_04_02_01_manual_input_range_auto_low_all(self):
numpy.random.seed(421)
image1 = numpy.random.uniform(size=(10, 20)).astype(numpy.float32) * .5 + .5
image2 = numpy.random.uniform(size=(10, 20)).astype(numpy.float32)
expected = (image1 - numpy.min(image2)) / (1 - numpy.min(image2))
workspace, module = self.make_workspace([image1, image2])
self.assertTrue(isinstance(module, cellprofiler.modules.rescaleintensity.RescaleIntensity))
module.rescale_method.value = cellprofiler.modules.rescaleintensity.M_MANUAL_INPUT_RANGE
module.wants_automatic_low.value = cellprofiler.modules.rescaleintensity.LOW_ALL_IMAGES
module.wants_automatic_high.value = cellprofiler.modules.rescaleintensity.CUSTOM_VALUE
module.source_high.value = 1
self.assertTrue(module.is_aggregation_module())
module.prepare_group(workspace, {}, [1, 2])
module.run(workspace)
pixels = workspace.image_set.get_image(OUTPUT_NAME).pixel_data
numpy.testing.assert_almost_equal(pixels, expected)
def test_04_02_01_manual_input_range_auto_low_all(self):
numpy.random.seed(421)
image1 = numpy.random.uniform(size=(10, 20)).astype(
numpy.float32) * .5 + .5
image2 = numpy.random.uniform(size=(10, 20)).astype(numpy.float32)
expected = (image1 - numpy.min(image2)) / (1 - numpy.min(image2))
workspace, module = self.make_workspace([image1, image2])
self.assertTrue(
isinstance(module,
cellprofiler.modules.rescaleintensity.RescaleIntensity))
module.rescale_method.value = cellprofiler.modules.rescaleintensity.M_MANUAL_INPUT_RANGE
module.wants_automatic_low.value = cellprofiler.modules.rescaleintensity.LOW_ALL_IMAGES
module.wants_automatic_high.value = cellprofiler.modules.rescaleintensity.CUSTOM_VALUE
module.source_high.value = 1
self.assertTrue(module.is_aggregation_module())
module.prepare_group(workspace, {}, [1, 2])
module.run(workspace)
pixels = workspace.image_set.get_image(OUTPUT_NAME).pixel_data
numpy.testing.assert_almost_equal(pixels, expected)