def test_positive_and_negative_segments(self):
data_val = [
1.0, 1.0, 1.0, 2.0, 3.0, 2.0, 1.0, 1.0, 1.0, 1.0, 5.0, 7.0, 5.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0
]
dataframe = create_dataframe(data_val)
segments = [{
'_id': 'Esl7uetLhx4lCqHa',
'analyticUnitId': 'opnICRJwOmwBELK8',
'from': 1523889000004,
'to': 1523889000006,
'labeled': True,
'deleted': False
}, {
'_id': 'Esl7uetLhx4lCqHa',
'analyticUnitId': 'opnICRJwOmwBELK8',
'from': 1523889000001,
'to': 1523889000003,
'labeled': False,
'deleted': False
}]
segments = [Segment.from_json(segment) for segment in segments]
cache = {}
detector = pattern_detector.PatternDetector('PEAK', 'test_id')
try:
detector.train(dataframe, segments, cache)
except Exception as e:
self.fail('detector.train fail with error {}'.format(e))
def test_segment_generator(self):
detector = anomaly_detector.AnomalyDetector('test_id')
data = [1, 1, 5, 1, -4, 5, 5, 5, -3, 1]
timestamps = create_list_of_timestamps(len(data))
dataframe = create_dataframe(data)
upper_bound = pd.Series([2, 2, 2, 2, 2, 2, 2, 2, 2, 2])
lower_bound = pd.Series([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
segments = list(detector.detections_generator(dataframe, upper_bound, lower_bound, enabled_bounds=Bound.ALL))
segments_borders = list(map(lambda s: [s.from_timestamp, s.to_timestamp], segments))
self.assertEqual(segments_borders, [[timestamps[2], timestamps[2]], [timestamps[4], timestamps[8]]])