text: #!/usr/bin/env python
  
  # Copyright (c) 2016 Hewlett Packard Enterprise Development Company, L.P.
  #
  # 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.
  
  from monasca_analytics.ldp.monasca_derivative import MonascaDerivativeLDP
  from pyspark.resultiterable import ResultIterable
  from test.util_for_testing import gen_metric
  from test.util_for_testing import MonanasTestCase
  
  
  class TestMonascaAggregateLDP(MonanasTestCase):
  
      def setUp(self):
          super(TestMonascaAggregateLDP, self).setUp()
          self.all_metrics = [
              gen_metric("memory", 1.5, 0, "h1"),
              gen_metric("memory", 2.0, 1, "h1"),
              gen_metric("memory", 1.0, 0, "h1"),
              gen_metric("memory", 3.0, 1, "h1"),
              gen_metric("memory", 1.5, 4, "h1"),
              gen_metric("memory", 2.0, 2, "h1"),
              gen_metric("memory", 1.0, 3, "h1"),
              gen_metric("memory", 3.0, 5, "h1"),
          ]
  
      def _values(self, values):
          return map(lambda m: m["metric"]["value"], values)
  
      def tearDown(self):
          super(TestMonascaAggregateLDP, self).tearDown()
  
      def test_derivative_should_do_nothing_with_1_value(self):
          self.assertEqual(MonascaDerivativeLDP.derivative(
              ResultIterable(self.all_metrics[0:1])),
              [])
  
      def test_derivative_should_work_on_first_and_last_values(self):
          new_values = MonascaDerivativeLDP.derivative(
              ResultIterable(self.all_metrics[0:2]))
          new_values = self._values(new_values)
          self.assertEqual(new_values,
                           [0.5, 0.5])
  
      def test_derivative_should_remove_duplicate(self):
          new_values = MonascaDerivativeLDP.derivative(
              ResultIterable(self.all_metrics[0:4]))
          new_values = self._values(new_values)
          self.assertEqual(new_values,
                           [0.5, 0.5])
  
      def test_derivative_should_work(self):
          new_values = MonascaDerivativeLDP.derivative(
              ResultIterable(self.all_metrics))
          new_values = self._values(new_values)
          self.assertEqual(new_values,
                           [0.5, 0.25, -0.5, -0.25, 1.0, 1.5])
  