def test_detect_anomalies_fit_pipeine_dict(self):
pipeline = load_pipeline('dummy')
anomalies = functional.detect_anomalies(data=self.anomalous,
pipeline=pipeline,
train_data=self.clean)
pd.testing.assert_frame_equal(self.events, anomalies)
def test_detect_anomalies_fitted_orion(self):
orion = functional.fit_pipeline(self.clean, 'dummy')
anomalies = functional.detect_anomalies(
data=self.anomalous,
pipeline=orion,
)
pd.testing.assert_frame_equal(self.events, anomalies)
def test_detect_anomalies_saved_orion(self, tmpdir):
orion_path = os.path.join(tmpdir, 'orion.pkl')
functional.fit_pipeline(self.clean, 'dummy', save_path=orion_path)
anomalies = functional.detect_anomalies(
data=self.anomalous,
pipeline=orion_path,
)
pd.testing.assert_frame_equal(self.events, anomalies)
def test_detect_anomalies_fit_hyperparams(self):
hyperparams = {
"orion.primitives.detectors.ThresholdDetector#1": {
"ratio": 0.9
}
}
anomalies = functional.detect_anomalies(data=self.anomalous,
hyperparameters=hyperparams,
train_data=self.clean)
pd.testing.assert_frame_equal(self.events, anomalies)
def test_detect_anomalies_fit_pipeline(self):
anomalies = functional.detect_anomalies(data=self.anomalous,
pipeline='dummy',
train_data=self.clean)
pd.testing.assert_frame_equal(self.events, anomalies)
def test_detect_anomalies_fit_default(self):
anomalies = functional.detect_anomalies(data=self.anomalous,
train_data=self.clean)
pd.testing.assert_frame_equal(self.events, anomalies)