Python RandGibbsNoise.set_random_state Examples

Example #1

File: test_rand_gibbs_noise.py Project: Nic-Ma/MONAI

 def test_same_result(self, im_shape, input_type):
     im = self.get_data(im_shape, input_type)
     alpha = [0.5, 0.8]
     t = RandGibbsNoise(1.0, alpha)
     t.set_random_state(42)
     out1 = t(deepcopy(im))
     t.set_random_state(42)
     out2 = t(deepcopy(im))
     assert_allclose(out1, out2, rtol=1e-7, atol=1e-2, type_test="tensor")

Example #2

File: test_rand_gibbs_noise.py Project: ETS-Research-Repositories/MONAI

 def test_same_result(self, im_shape, input_type):
     im = self.get_data(im_shape, input_type)
     alpha = [0.5, 0.8]
     t = RandGibbsNoise(1.0, alpha)
     t.set_random_state(42)
     out1 = t(deepcopy(im))
     t.set_random_state(42)
     out2 = t(deepcopy(im))
     torch.testing.assert_allclose(out1, out2, rtol=1e-7, atol=0)
     self.assertIsInstance(out1, type(im))

Example #3

File: test_rand_gibbs_noise.py Project: gagandaroach/MONAI

 def test_same_result(self, im_shape, as_tensor_output, as_tensor_input):
     im = self.get_data(im_shape, as_tensor_input)
     alpha = [0.5, 0.8]
     t = RandGibbsNoise(1.0, alpha, as_tensor_output)
     t.set_random_state(42)
     out1 = t(deepcopy(im))
     t.set_random_state(42)
     out2 = t(deepcopy(im))
     np.testing.assert_allclose(out1, out2)
     self.assertIsInstance(out1, torch.Tensor if as_tensor_output else np.ndarray)