old_contents: #
  #  Copyright 2019 The FATE Authors. All Rights Reserved.
  #
  #  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 uuid
  
  from arch.api import session
  import numpy as np
  
  
  class TestStatistics(unittest.TestCase):
      def setUp(self):
          session.init((str(uuid.uuid1())))
  
      def test_standardized(self):
          from federatedml.statistic.correlation import hetero_pearson
          raw_data = np.random.rand(200, 100)
          expect = (raw_data - np.mean(raw_data, axis=0)) / np.std(raw_data, axis=0)
          data_table = session.parallelize([row for row in raw_data])
          n, standardized = hetero_pearson.HeteroPearson._standardized(data_table)
          standardized_data = np.array([row[1] for row in standardized.collect()])
          self.assertEqual(n, standardized_data.shape[0])
          self.assertEqual(raw_data.shape, standardized_data.shape)
          self.assertAlmostEqual(np.linalg.norm(standardized_data - expect), 0.0)
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: #
  #  Copyright 2019 The FATE Authors. All Rights Reserved.
  #
  #  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 uuid
  
  from arch.api import session
  import numpy as np
  
  
  class TestStatistics(unittest.TestCase):
      def setUp(self):
          session.init((str(uuid.uuid1())))
  
      def test_standardized(self):
          from federatedml.statistic.correlation import hetero_pearson
          raw_data = np.random.rand(200, 100)
          expect = (raw_data - np.mean(raw_data, axis=0)) / np.std(raw_data, axis=0)
          data_table = session.parallelize([row for row in raw_data], partition=10)
          n, standardized = hetero_pearson.HeteroPearson._standardized(data_table)
          standardized_data = np.array([row[1] for row in standardized.collect()])
          self.assertEqual(n, standardized_data.shape[0])
          self.assertEqual(raw_data.shape, standardized_data.shape)
          self.assertAlmostEqual(np.linalg.norm(standardized_data - expect), 0.0)
  
  
  if __name__ == '__main__':
      unittest.main()
  
subject: fix pearson test