Add values for dummy variables and assert mocks called

tests/seer/anomaly_detection/detectors/test_anomaly_detectors.py

@@ -33,33 +33,45 @@ def test_compute_matrix_profile(self, mock_stump):
 
  # Mock to return dummy values
  mock_stump.return_value = np.array([1, 2, 3, 4])
- self.scorer.batch_score = MagicMock(return_value=([], []))
+ self.scorer.batch_score = MagicMock(
+ return_value=(
+ [0.1, 6.5, 4.8, 0.2],
+ ["none", "anomaly_higher_confidence", "anomaly_higher_confidence", "none"],
+ )
+ )
 
  timeseries, mp_dists, window_sizes = convert_synthetic_ts(
  "tests/seer/anomaly_detection/test_data/synthetic_series", as_ts_datatype=False
  )
 
- for ts_values, mp_dist_baseline, window_size in zip(timeseries, mp_dists, window_sizes):
- ts = TimeSeries(timestamps=np.array([]), values=ts_values)
-
- self.ws_selector.optimal_window_size = MagicMock(return_value=window_size)
+ ts_values, mp_dist_baseline, window_size = timeseries[0], mp_dists[0], window_sizes[0]
+ ts = TimeSeries(timestamps=np.array([]), values=ts_values)
 
- self.mp_utils.get_mp_dist_from_mp = MagicMock(return_value=mp_dist_baseline)
+ self.ws_selector.optimal_window_size = MagicMock(return_value=window_size)
+ self.mp_utils.get_mp_dist_from_mp = MagicMock(return_value=mp_dist_baseline)
 
-  result = self.detector._compute_matrix_profile(
-  ts,
-  self.config,
-  ws_selector=self.ws_selector,
-  mp_config=self.mp_config,
-  scorer=self.scorer,
-  mp_utils=self.mp_utils,
-  )
+ result = self.detector._compute_matrix_profile(
+ ts,
+ self.config,
+ ws_selector=self.ws_selector,
+ mp_config=self.mp_config,
+ scorer=self.scorer,
+ mp_utils=self.mp_utils,
+ )
 
- self.assertIsInstance(result, MPTimeSeriesAnomalies)
- self.assertIsInstance(result.flags, list)
- self.assertIsInstance(result.scores, list)
- self.assertIsInstance(result.matrix_profile, np.ndarray)
- self.assertIsInstance(result.window_size, int)
+ self.assertIsInstance(result, MPTimeSeriesAnomalies)
+ self.assertIsInstance(result.flags, list)
+ self.assertEqual(result.scores, [0.1, 6.5, 4.8, 0.2])
+ self.assertIsInstance(result.scores, list)
+ self.assertEqual(
+ result.flags, ["none", "anomaly_higher_confidence", "anomaly_higher_confidence", "none"]
+ )
+ self.assertIsInstance(result.matrix_profile, np.ndarray)
+ self.assertIsInstance(result.window_size, int)
+ mock_stump.assert_called_once()
+ self.scorer.batch_score.assert_called_once()
+ self.ws_selector.optimal_window_size.assert_called_once()
+ self.mp_utils.get_mp_dist_from_mp.assert_called_once()
 
 
 class TestMPStreamAnomalyDetector(unittest.TestCase):
@@ -107,4 +119,5 @@ def test_detect(self, MockMPUtils, MockMPScorer, MockStumpi):
  self.assertEqual(len(anomalies.scores), 3)
  self.assertEqual(len(anomalies.flags), 3)
  self.assertEqual(len(anomalies.matrix_profile), 3)
- mock_scorer.stream_score.assert_called()
+ mock_scorer.stream_score.assert_called_once()
+ mock_stream.assert_called_once()