text: # Copyright 2017 The TensorFlow 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.
  # ==============================================================================
  """Tests that the TensorFlow parts of the known anomaly example run."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  from tensorflow.contrib.timeseries.examples import known_anomaly
  
  from tensorflow.python.platform import test
  
  
  class KnownAnomalyExampleTest(test.TestCase):
  
    def test_shapes_and_variance_structural_ar(self):
      (times, observed, all_times, mean, upper_limit, lower_limit,
       anomaly_locations) = known_anomaly.train_and_evaluate_exogenous(
           train_steps=1, estimator_fn=known_anomaly.autoregressive_estimator)
      self.assertAllEqual(
          anomaly_locations,
          [25, 50, 75, 100, 125, 150, 175, 249])
      self.assertAllEqual(all_times.shape, mean.shape)
      self.assertAllEqual(all_times.shape, upper_limit.shape)
      self.assertAllEqual(all_times.shape, lower_limit.shape)
      self.assertAllEqual(times.shape, observed.shape)
  
    def test_shapes_and_variance_structural_ssm(self):
      (times, observed, all_times, mean, upper_limit, lower_limit,
       anomaly_locations) = known_anomaly.train_and_evaluate_exogenous(
           train_steps=50, estimator_fn=known_anomaly.state_space_estimator)
      self.assertAllEqual(
          anomaly_locations,
          [25, 50, 75, 100, 125, 150, 175, 249])
      self.assertAllEqual([200], times.shape)
      self.assertAllEqual([200], observed.shape)
      self.assertAllEqual([300], all_times.shape)
      self.assertAllEqual([300], mean.shape)
      self.assertAllEqual([300], upper_limit.shape)
      self.assertAllEqual([300], lower_limit.shape)
      # Check that initial predictions are relatively confident.
      self.assertLess(upper_limit[210] - lower_limit[210],
                      3.0 * (upper_limit[200] - lower_limit[200]))
      # Check that post-changepoint predictions are less confident
      self.assertGreater(upper_limit[290] - lower_limit[290],
                         3.0 * (upper_limit[240] - lower_limit[240]))
  
  if __name__ == "__main__":
    test.main()
  