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")