def testCLAClassificationRecord(self):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label"
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.ROWID, record['ROWID'])
self.assertEqual(state.anomalyScore, record['anomalyScore'])
self.assertEqual(state.anomalyVector, record['anomalyVector'])
self.assertEqual(state.anomalyLabel, record['anomalyLabel'])
self.assertEqual(state.setByUser, False)
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label",
"setByUser": True
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.ROWID, record['ROWID'])
self.assertEqual(state.anomalyScore, record['anomalyScore'])
self.assertEqual(state.anomalyVector, record['anomalyVector'])
self.assertEqual(state.anomalyLabel, record['anomalyLabel'])
self.assertEqual(state.setByUser, record['setByUser'])
def testCLAClassificationRecord(self):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label"
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.ROWID, record['ROWID'])
self.assertEqual(state.anomalyScore, record['anomalyScore'])
self.assertEqual(state.anomalyVector, record['anomalyVector'])
self.assertEqual(state.anomalyLabel, record['anomalyLabel'])
self.assertEqual(state.setByUser, False)
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label",
"setByUser": True
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.ROWID, record['ROWID'])
self.assertEqual(state.anomalyScore, record['anomalyScore'])
self.assertEqual(state.anomalyVector, record['anomalyVector'])
self.assertEqual(state.anomalyLabel, record['anomalyLabel'])
self.assertEqual(state.setByUser, record['setByUser'])
def testAddRecordToKNN(self, getAnomalyVector):
getAnomalyVector.return_value = "Vector"
values = {
'categoryRecencyList': [1, 2, 3]
}
classifier = self.helper.clamodel._getAnomalyClassifier().getSelf()
classifier.getParameter.side_effect = values.get
state = {
"ROWID": 5,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
record = _CLAClassificationRecord(**state)
# Test with record not already in KNN
self.helper._addRecordToKNN(record)
classifier._knn.learn.assert_called_once_with("Vector", ANY, rowID=state['ROWID'])
self.assertTrue(not classifier._knn.prototypeSetCategory.called)
classifier._knn.learn.reset_mock()
# Test with record already in KNN
values = {
'categoryRecencyList': [1, 2, 3, 5]
}
classifier.getParameter.side_effect = values.get
self.helper._addRecordToKNN(record)
classifier._knn.prototypeSetCategory.assert_called_once_with(\
state['ROWID'], ANY)
self.assertTrue(not classifier._knn.learn.called)
def testAddRecordToKNN(self, getAnomalyVector):
getAnomalyVector.return_value = "Vector"
values = {'categoryRecencyList': [1, 2, 3]}
classifier = self.helper.clamodel._getAnomalyClassifier().getSelf()
classifier.getParameter.side_effect = values.get
state = {
"ROWID": 5,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
record = _CLAClassificationRecord(**state)
# Test with record not already in KNN
self.helper._addRecordToKNN(record)
classifier._knn.learn.assert_called_once_with("Vector",
ANY,
rowID=state['ROWID'])
self.assertTrue(not classifier._knn.prototypeSetCategory.called)
classifier._knn.learn.reset_mock()
# Test with record already in KNN
values = {'categoryRecencyList': [1, 2, 3, 5]}
classifier.getParameter.side_effect = values.get
self.helper._addRecordToKNN(record)
classifier._knn.prototypeSetCategory.assert_called_once_with(\
state['ROWID'], ANY)
self.assertTrue(not classifier._knn.learn.called)
def testRun(self,compute):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": [1,4,5],
"anomalyLabel": "Label"
}
compute.return_value = _CLAClassificationRecord(**state)
result = self.helper.run()
compute.assert_called_once_with()
self.assertEqual(result, state['anomalyLabel'])
def testRun(self, compute):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": [1, 4, 5],
"anomalyLabel": "Label"
}
compute.return_value = _CLAClassificationRecord(**state)
result = self.helper.run()
compute.assert_called_once_with()
self.assertEqual(result, state['anomalyLabel'])
def testCLAClassificationRecordGetState(self):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label",
"setByUser": False
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.__getstate__(), record)
def testCLAClassificationRecordGetState(self):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label",
"setByUser": False
}
state = _CLAClassificationRecord(**record)
self.assertEqual(state.__getstate__(), record)
def testGetAnomalyVector(self):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": [1,4,5],
"anomalyLabel": "Label"
}
record = _CLAClassificationRecord(**state)
self.helper._anomalyVectorLength = 10
vector = self.helper._getStateAnomalyVector(record)
self.assertEqual(len(vector), self.helper._anomalyVectorLength)
self.assertEqual(vector.nonzero()[0].tolist(), record.anomalyVector)
def testGetAnomalyVector(self):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": [1, 4, 5],
"anomalyLabel": "Label"
}
record = _CLAClassificationRecord(**state)
self.helper._anomalyVectorLength = 10
vector = self.helper._getStateAnomalyVector(record)
self.assertEqual(len(vector), self.helper._anomalyVectorLength)
self.assertEqual(vector.nonzero()[0].tolist(), record.anomalyVector)
def testCompute(self, createRecord, updateState):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label"
}
record = _CLAClassificationRecord(**state)
createRecord.return_value = record
# Test add first record
self.helper._history_length = 10
self.helper._autoDetectWaitRecords = 0
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
updateState.assert_called_once_with(result)
# Test add record before wait records
updateState.reset_mock()
self.helper._history_length = 10
self.helper._autoDetectWaitRecords = 10
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 2)
self.assertTrue(not updateState.called)
# Test exceeded cache length
updateState.reset_mock()
self.helper._history_length = 1
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
self.assertTrue(not updateState.called)
def testCompute(self, createRecord, updateState):
state = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "Vector",
"anomalyLabel": "Label"
}
record = _CLAClassificationRecord(**state)
createRecord.return_value = record
# Test add first record
self.helper._history_length = 10
self.helper._autoDetectWaitRecords = 0
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
updateState.assert_called_once_with(result)
# Test add record before wait records
updateState.reset_mock()
self.helper._history_length = 10
self.helper._autoDetectWaitRecords = 10
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 2)
self.assertTrue(not updateState.called)
# Test exceeded cache length
updateState.reset_mock()
self.helper._history_length = 1
self.helper.saved_states = []
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
result = self.helper.compute()
self.assertEqual(result, record)
self.assertEqual(len(self.helper.saved_states), 1)
self.assertTrue(not updateState.called)
def testRecomputeRecordFromKNN(self, getAnomalyVector):
getAnomalyVector.return_value = "Vector"
values = {
'categoryRecencyList': [1, 2, 3, 5, 6, 7, 8, 9],
'latestDists': numpy.array([0.7, 0.2, 0.5, 1, 0.3, 0.2, 0.1]),
'categories': ['A','B','C','D','E','F','G']
}
classifier = self.helper.clamodel._getAnomalyClassifier().getSelf()
classifier.getLatestDistances.return_value = values['latestDists']
classifier.getCategoryList.return_value = values['categories']
classifier.getParameter.side_effect = values.get
state = {
"ROWID": 5,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
record = _CLAClassificationRecord(**state)
# Test finding best category before record - exists
self.helper._classificationMaxDist = 0.4
self.helper._autoDetectWaitRecords = 0
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, 'B')
# Test finding best category before record - does not exists
self.helper._classificationMaxDist = 0.1
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, None)
# Test finding best category before record - not record before
record.ROWID = 0
self.helper._classificationMaxDist = 0.1
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, None)
def testRecomputeRecordFromKNN(self, getAnomalyVector):
getAnomalyVector.return_value = "Vector"
values = {
'categoryRecencyList': [1, 2, 3, 5, 6, 7, 8, 9],
'latestDists': numpy.array([0.7, 0.2, 0.5, 1, 0.3, 0.2, 0.1]),
'categories': ['A', 'B', 'C', 'D', 'E', 'F', 'G']
}
classifier = self.helper.clamodel._getAnomalyClassifier().getSelf()
classifier.getLatestDistances.return_value = values['latestDists']
classifier.getCategoryList.return_value = values['categories']
classifier.getParameter.side_effect = values.get
state = {
"ROWID": 5,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
record = _CLAClassificationRecord(**state)
# Test finding best category before record - exists
self.helper._classificationMaxDist = 0.4
self.helper._autoDetectWaitRecords = 0
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, 'B')
# Test finding best category before record - does not exists
self.helper._classificationMaxDist = 0.1
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, None)
# Test finding best category before record - not record before
record.ROWID = 0
self.helper._classificationMaxDist = 0.1
result = self.helper._recomputeRecordFromKNN(record)
self.assertEqual(result, None)
def testUpdateState(self, toLabelList, recompute, deleteRecord, addRecord):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
# Test record not labeled and not above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 0
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
deleteRecord.assert_called_once_with([state])
# Test record not labeled and above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 0.5
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL])
addRecord.assert_called_once_with(state)
# Test record not labeled and above threshold during wait period
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 10
self.helper._autoDetectThreshold = 0.5
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
self.assertTrue(not addRecord.called)
# Test record labeled and not above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 0
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = ["Label"]
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, ["Label"])
self.assertTrue(not addRecord.called)
# Test setByUser
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = ["Label 2"]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel,
[recordCopy["anomalyLabel"][0], toLabelList.return_value[0]])
addRecord.assert_called_once_with(state)
# Test removal of above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = []
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL,
CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
# Auto classified threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel,
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG])
addRecord.assert_called_once_with(state)
# Test precedence of threshold label above auto threshold label
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 0.8
toLabelList.return_value = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL,
CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel,
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL])
addRecord.assert_called_once_with(state)
def testUpdateState(self, toLabelList, recompute, deleteRecord, addRecord):
record = {
"ROWID": 0,
"anomalyScore": 1.0,
"anomalyVector": "",
"anomalyLabel": ["Label"],
"setByUser": False
}
# Test record not labeled and not above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 0
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
deleteRecord.assert_called_once_with([state])
# Test record not labeled and above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 0.5
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL])
addRecord.assert_called_once_with(state)
# Test record not labeled and above threshold during wait period
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 10
self.helper._autoDetectThreshold = 0.5
toLabelList.return_value = []
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
self.assertTrue(not addRecord.called)
# Test record labeled and not above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectWaitRecords = 0
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = ["Label"]
state = _CLAClassificationRecord(**record)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, ["Label"])
self.assertTrue(not addRecord.called)
# Test setByUser
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = ["Label 2"]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(
state.anomalyLabel,
[recordCopy["anomalyLabel"][0], toLabelList.return_value[0]])
addRecord.assert_called_once_with(state)
# Test removal of above threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = []
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL,
CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel, [])
# Auto classified threshold
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 1.1
toLabelList.return_value = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(state.anomalyLabel,
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG])
addRecord.assert_called_once_with(state)
# Test precedence of threshold label above auto threshold label
deleteRecord.reset_mock()
addRecord.reset_mock()
self.helper._autoDetectThreshold = 0.8
toLabelList.return_value = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL,
CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL + \
CLAModelClassifierHelper.AUTO_TAG]
recordCopy = copy.deepcopy(record)
recordCopy['setByUser'] = True
recordCopy['anomalyLabel'] = \
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL]
state = _CLAClassificationRecord(**recordCopy)
self.helper._updateState(state)
self.assertEqual(
state.anomalyLabel,
[CLAModelClassifierHelper.AUTO_THRESHOLD_CLASSIFIED_LABEL])
addRecord.assert_called_once_with(state)
