57 lines
1.8 KiB
Python
57 lines
1.8 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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import logging
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import numpy as np
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from sklearn import svm
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from monasca_analytics.sml import svm_one_class
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from test.util_for_testing import MonanasTestCase
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logger = logging.getLogger(__name__)
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class TestSvmOneClass(MonanasTestCase):
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def setUp(self):
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super(TestSvmOneClass, self).setUp()
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self.svm = svm_one_class.SvmOneClass("fakeid", {
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"module": "fake",
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"nb_samples": 1000
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})
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def tearDown(self):
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super(TestSvmOneClass, self).tearDown()
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def get_testing_data(self):
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a = np.random.uniform(size=1000)
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b = np.random.uniform(size=1000)
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c = np.random.uniform(size=1000)
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d = np.random.uniform(size=1000)
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return np.array([a, b, c, d]).T
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def test_generate_train_test_sets(self):
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data = self.get_testing_data()
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train, test = self.svm._generate_train_test_sets(data, 0.6)
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self.assertEqual(600, len(train))
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self.assertEqual(400, len(test))
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def test_learn_structure(self):
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data = self.get_testing_data()
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clf = self.svm.learn_structure(data)
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self.assertIsInstance(clf, svm.OneClassSVM)
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