def test_value(self, input_param, input_data):
for p in TEST_NDARRAYS:
cropper = RandScaleCropd(**input_param)
input_data["img"] = p(input_data["img"])
result = cropper(input_data)
roi = [(2 - i // 2, 2 + i - i // 2) for i in cropper._size]
assert_allclose(result["img"],
input_data["img"][:, roi[0][0]:roi[0][1],
roi[1][0]:roi[1][1]],
type_test=False)
def test_random_shape(self, input_param, input_data, expected_shape):
cropper = RandScaleCropd(**input_param)
cropper.set_random_state(seed=123)
result = cropper(input_data)
self.assertTupleEqual(result["img"].shape, expected_shape)
def test_shape(self, input_param, input_data, expected_shape):
result = RandScaleCropd(**input_param)(input_data)
self.assertTupleEqual(result["img"].shape, expected_shape)
def test_value(self, input_param, input_data):
cropper = RandScaleCropd(**input_param)
result = cropper(input_data)
roi = [(2 - i // 2, 2 + i - i // 2) for i in cropper._size]
np.testing.assert_allclose(result["img"], input_data["img"][:, roi[0][0] : roi[0][1], roi[1][0] : roi[1][1]])