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import unittest
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import pandas as pd
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from detectors import pattern_detector, threshold_detector, anomaly_detector
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class TestPatternDetector(unittest.TestCase):
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def test_small_dataframe(self):
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data = [[0,1], [1,2]]
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dataframe = pd.DataFrame(data, columns=['timestamp', 'values'])
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cache = {'windowSize': 10}
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detector = pattern_detector.PatternDetector('GENERAL', 'test_id')
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with self.assertRaises(ValueError):
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detector.detect(dataframe, cache)
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class TestThresholdDetector(unittest.TestCase):
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def test_invalid_cache(self):
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detector = threshold_detector.ThresholdDetector()
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with self.assertRaises(ValueError):
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detector.detect([], None)
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with self.assertRaises(ValueError):
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detector.detect([], {})
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class TestAnomalyDetector(unittest.TestCase):
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def test_dataframe(self):
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data_val = [0, 1, 2, 1, 2, 10, 1, 2, 1]
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data_ind = [1523889000000 + i for i in range(len(data_val))]
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data = {'timestamp': data_ind, 'value': data_val}
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dataframe = pd.DataFrame(data = data)
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dataframe['timestamp'] = pd.to_datetime(dataframe['timestamp'], unit='ms')
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cache = {
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'confidence': 2,
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'alpha': 0.1,
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}
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detector = anomaly_detector.AnomalyDetector()
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detect_result = detector.detect(dataframe, cache)
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result = [(1523889000005.0, 1523889000005.0)]
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self.assertEqual(result, detect_result['segments'])
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