def test_runtime_mask(self):
mask_data = np.array([[[0, 0, 0], [0, 1, 0], [0, 0, 0]]])
img = np.array([[[1, 1, 1], [2, 2, 2], [3, 3, 3]],
[[4, 4, 4], [5, 5, 5], [6, 6, 6]]])
expected = np.array([[[0, 0, 0], [0, 2, 0], [0, 0, 0]],
[[0, 0, 0], [0, 5, 0], [0, 0, 0]]])
result = MaskIntensity()(img=img, mask_data=mask_data)
assert_allclose(result, expected, type_test="tensor")
def test_value(self, argments, image, expected_data):
for p in TEST_NDARRAYS:
result = MaskIntensity(**argments)(p(image))
assert_allclose(result, p(expected_data), type_test="tensor")
def test_value(self, argments, image, expected_data):
result = MaskIntensity(**argments)(image)
np.testing.assert_allclose(result, expected_data)