text: # Copyright 2020 - 2021 MONAI Consortium
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #     http://www.apache.org/licenses/LICENSE-2.0
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import unittest
  
  import numpy as np
  from parameterized import parameterized
  
  from monai.transforms import RandGaussianSmoothd
  
  TEST_CASE_1 = [
      {"keys": "img", "sigma_x": (0.5, 1.5), "prob": 1.0},
      {"img": np.array([[[1, 1, 1], [2, 2, 2], [3, 3, 3]], [[4, 4, 4], [5, 5, 5], [6, 6, 6]]])},
      np.array(
          [
              [[0.71806467, 0.9074683, 0.71806467], [1.0718315, 1.3545481, 1.0718315], [1.0337002, 1.306359, 1.0337002]],
              [[2.0318885, 2.5678391, 2.0318885], [2.6795788, 3.3863702, 2.6795788], [2.3475242, 2.9667296, 2.3475242]],
          ]
      ),
  ]
  
  TEST_CASE_2 = [
      {"keys": "img", "sigma_x": (0.5, 1.5), "sigma_y": (0.5, 1.0), "prob": 1.0},
      {"img": np.array([[[1, 1, 1], [2, 2, 2], [3, 3, 3]], [[4, 4, 4], [5, 5, 5], [6, 6, 6]]])},
      np.array(
          [
              [[0.7686928, 0.9848021, 0.7686928], [1.1474025, 1.4699818, 1.1474024], [1.1065826, 1.4176859, 1.1065826]],
              [[2.1751494, 2.7866683, 2.1751497], [2.8685062, 3.6749542, 2.8685062], [2.5130394, 3.219552, 2.5130394]],
          ]
      ),
  ]
  
  TEST_CASE_3 = [
      {"keys": "img", "sigma_x": (0.5, 1.5), "sigma_y": (0.5, 1.0), "approx": "scalespace", "prob": 1.0},
      {"img": np.array([[[1, 1, 1], [2, 2, 2], [3, 3, 3]], [[4, 4, 4], [5, 5, 5], [6, 6, 6]]])},
      np.array(
          [
              [[0.8128456, 0.96736777, 0.8128456], [1.2742369, 1.5164697, 1.2742369], [1.2800367, 1.5233722, 1.2800368]],
              [[2.3825073, 2.8354228, 2.3825073], [3.1855922, 3.7911744, 3.1855922], [2.8496985, 3.391427, 2.8496985]],
          ]
      ),
  ]
  
  
  class TestRandGaussianSmoothd(unittest.TestCase):
      @parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
      def test_value(self, argments, image, expected_data):
          converter = RandGaussianSmoothd(**argments)
          converter.set_random_state(seed=0)
          result = converter(image)
          np.testing.assert_allclose(result["img"], expected_data, rtol=1e-4)
  
  
  if __name__ == "__main__":
      unittest.main()
  