def test_value(self): key = "img" scaler = RandScaleIntensityd(keys=[key], factors=0.5, prob=1.0) scaler.set_random_state(seed=0) result = scaler({key: self.imt}) np.random.seed(0) expected = (self.imt * (1 + np.random.uniform(low=-0.5, high=0.5))).astype(np.float32) np.testing.assert_allclose(result[key], expected)
def test_value(self): key = "img" for p in TEST_NDARRAYS: scaler = RandScaleIntensityd(keys=[key], factors=0.5, prob=1.0) scaler.set_random_state(seed=0) result = scaler({key: p(self.imt)}) np.random.seed(0) # simulate the randomize function of transform np.random.random() expected = (self.imt * (1 + np.random.uniform(low=-0.5, high=0.5))).astype(np.float32) assert_allclose(result[key], p(expected), type_test="tensor")