def test_execute_wrapper_return_is_runnable(self):
"""
Test that the partial returned by execute_wrapper can be executed (kwargs are named correctly)
"""
images = th.generate_images()
roi_mock = mock.Mock()
roi_mock.text.return_value = "0, 0, 5, 5"
RoiNormalisationFilter.execute_wrapper(roi_mock)(images)
roi_mock.text.assert_called_once()
def do_execute(self, images: Images):
original = np.copy(images.data[0])
air = SensibleROI.from_list([3, 3, 4, 4])
result = RoiNormalisationFilter.filter_func(images, air)
th.assert_not_equals(result.data[0], original)
def do_execute(self):
images = th.generate_images()
original = np.copy(images.data[0])
air = [3, 3, 4, 4]
result = RoiNormalisationFilter.filter_func(images, air)
th.assert_not_equals(result.data[0], original)
def test_not_executed_empty_params(self):
images = th.generate_images()
air = None
original = np.copy(images.data[0])
result = RoiNormalisationFilter.filter_func(images, air)
npt.assert_equal(result.data[0], original)
def test_roi_normalisation_performs_rescale(self):
images = th.generate_images()
images_max = images.data.max()
original = np.copy(images.data[0])
air = [3, 3, 4, 4]
result = RoiNormalisationFilter.filter_func(images, air)
th.assert_not_equals(result.data[0], original)
self.assertAlmostEqual(result.data.max(), images_max, places=6)
def test_roi_normalisation_stack_average(self):
air = [3, 3, 6, 8]
images = th.generate_images([10, 20, 30], seed=2021)
images.data[2] *= 2
images.data[3] *= 0.5
air_data_orig = np.copy(images.data[:, air[1]:air[3], air[0]:air[2]])
original = np.copy(images.data[0])
result = RoiNormalisationFilter.filter_func(images, air,
"Stack Average")
air_data_after = np.copy(result.data[:, air[1]:air[3], air[0]:air[2]])
th.assert_not_equals(result.data[0], original)
self.assertAlmostEqual(air_data_orig.mean(),
air_data_after.mean(),
places=6)
self.assertAlmostEqual(air_data_after[0].mean(),
air_data_after[1].mean(),
places=6)
def test_roi_normalisation_to_flat(self):
air = [3, 3, 6, 8]
images = th.generate_images([10, 20, 30], seed=2021)
flat_field = th.generate_images([2, 20, 30], seed=2021)
images.data[::2] *= 0.5
air_data_flat = np.copy(flat_field.data[:, air[1]:air[3],
air[0]:air[2]])
original = np.copy(images.data[0])
result = RoiNormalisationFilter.filter_func(images, air, "Flat Field",
flat_field)
air_data_after = np.copy(result.data[:, air[1]:air[3], air[0]:air[2]])
th.assert_not_equals(result.data[0], original)
self.assertAlmostEqual(air_data_flat.mean(),
air_data_after.mean(),
places=6)
self.assertAlmostEqual(air_data_after[0].mean(),
air_data_after[1].mean(),
places=6)
def test_execute_wrapper_return_is_runnable(self):
"""
Test that the partial returned by execute_wrapper can be executed (kwargs are named correctly)
"""
images = th.generate_images()
RoiNormalisationFilter.execute_wrapper()(images)