69 lines
2.6 KiB
Python
69 lines
2.6 KiB
Python
#!/usr/bin/env python
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# Copyright (c) 2016 Hewlett Packard Enterprise Development Company, L.P.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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from monasca_analytics.ldp.monasca_derivative import MonascaDerivativeLDP
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from pyspark.resultiterable import ResultIterable
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from test.util_for_testing import gen_metric
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from test.util_for_testing import MonanasTestCase
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class TestMonascaAggregateLDP(MonanasTestCase):
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def setUp(self):
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super(TestMonascaAggregateLDP, self).setUp()
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self.all_metrics = [
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gen_metric("memory", 1.5, 0, "h1"),
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gen_metric("memory", 2.0, 1, "h1"),
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gen_metric("memory", 1.0, 0, "h1"),
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gen_metric("memory", 3.0, 1, "h1"),
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gen_metric("memory", 1.5, 4, "h1"),
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gen_metric("memory", 2.0, 2, "h1"),
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gen_metric("memory", 1.0, 3, "h1"),
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gen_metric("memory", 3.0, 5, "h1"),
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]
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def _values(self, values):
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return [m["metric"]["value"] for m in values]
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def tearDown(self):
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super(TestMonascaAggregateLDP, self).tearDown()
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def test_derivative_should_do_nothing_with_1_value(self):
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self.assertEqual(MonascaDerivativeLDP.derivative(
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ResultIterable(self.all_metrics[0:1])),
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[])
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def test_derivative_should_work_on_first_and_last_values(self):
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new_values = MonascaDerivativeLDP.derivative(
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ResultIterable(self.all_metrics[0:2]))
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new_values = self._values(new_values)
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self.assertEqual(new_values,
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[0.5, 0.5])
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def test_derivative_should_remove_duplicate(self):
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new_values = MonascaDerivativeLDP.derivative(
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ResultIterable(self.all_metrics[0:4]))
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new_values = self._values(new_values)
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self.assertEqual(new_values,
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[0.5, 0.5])
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def test_derivative_should_work(self):
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new_values = MonascaDerivativeLDP.derivative(
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ResultIterable(self.all_metrics))
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new_values = self._values(new_values)
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self.assertEqual(new_values,
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[0.5, 0.25, -0.5, -0.25, 1.0, 1.5])
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