def test_lambdad_slicing(self):
for p in TEST_NDARRAYS:
img = p(self.imt)
data = {"img": img}
def slice_func(x):
return x[:, :, :6, ::2]
lambd = Lambdad(keys=data.keys(), func=slice_func)
expected = {}
expected = slice_func(data["img"])
out = lambd(data)
out_img = out["img"]
assert_allclose(expected, out_img, type_test=False)
self.assertIsInstance(out_img, MetaTensor)
self.assertEqual(len(out_img.applied_operations), 1)
inv_img = lambd.inverse(out)["img"]
self.assertIsInstance(inv_img, MetaTensor)
self.assertEqual(len(inv_img.applied_operations), 0)
def test_lambdad_slicing(self):
img = self.imt
data = dict()
data["img"] = img
def slice_func(x):
return x[:, :, :6, ::-2]
lambd = Lambdad(keys=data.keys(), func=slice_func)
expected = dict()
expected["img"] = slice_func(data["img"])
self.assertTrue(np.allclose(expected["img"], lambd(data)["img"]))
def test_lambdad_identity(self):
img = self.imt
data = dict()
data["img"] = img
def identity_func(x):
return x
lambd = Lambdad(keys=data.keys(), func=identity_func)
expected = data
expected["img"] = identity_func(data["img"])
self.assertTrue(np.allclose(expected["img"], lambd(data)["img"]))
def test_lambdad_slicing(self):
for p in TEST_NDARRAYS:
img = p(self.imt)
data = {"img": img}
def slice_func(x):
return x[:, :, :6, ::2]
lambd = Lambdad(keys=data.keys(), func=slice_func)
expected = {}
expected["img"] = slice_func(data["img"])
assert_allclose(expected["img"], lambd(data)["img"])
def test_lambdad_identity(self):
for p in TEST_NDARRAYS:
img = p(self.imt)
data = {"img": img, "prop": 1.0}
def noise_func(x):
return x + 1.0
expected = {"img": noise_func(data["img"]), "prop": 1.0}
ret = Lambdad(keys=["img", "prop"], func=noise_func, overwrite=[True, False])(data)
assert_allclose(expected["img"], ret["img"])
assert_allclose(expected["prop"], ret["prop"])
def test_lambdad_identity(self):
img = self.imt
data = {"img": img, "prop": 1.0}
def noise_func(x):
return x + 1.0
expected = {"img": noise_func(data["img"]), "prop": 1.0}
ret = Lambdad(keys=["img", "prop"],
func=noise_func,
overwrite=[True, False])(data)
self.assertTrue(np.allclose(expected["img"], ret["img"]))
self.assertTrue(np.allclose(expected["prop"], ret["prop"]))