fix AutoReg

README.md

@@ -1,4 +1,3 @@
-
 # TODS: Automated Time-series Outlier Detection System
 
 <img width="500" src="./docs/img/tods_logo.png" alt="Logo" />

tods/detection_algorithm/core/MultiAutoRegOD.py

@@ -154,6 +154,12 @@ class MultiAutoRegOD(CollectiveBaseDetector):
         self.decision_scores_ = self._score_combination(
             self._decison_mat_scalaled)
 
+        # print(self.decision_scores_.shape, self.left_inds_.shape, self.right_inds_.shape)
+        self.decision_scores_ = np.concatenate((np.zeros((self.window_size,)), self.decision_scores_))
+        self.left_inds_ = np.concatenate(((-self.window_size) * np.ones((self.window_size,)).astype(np.int), self.left_inds_))
+        self.right_inds_ = np.concatenate((np.zeros((self.window_size,)).astype(np.int), self.right_inds_))
+        # print(self.decision_scores_.shape, self.left_inds_.shape, self.right_inds_.shape)
+
         self._process_decision_scores()
         return self
 

tods/tests/detection_algorithm/test_AutoRegODetect.py

@@ -28,10 +28,10 @@ class AutoRegODetectTestCase(unittest.TestCase):
 
         self.X_train = d3m_dataframe({'data': [3., 4., 8., 16, 18, 13., 22., 36., 59., 128, 62, 67, 78, 100]},
                                       columns=['data'], generate_metadata=True)
-        self.y_train = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
+        self.y_train = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
         self.X_test = d3m_dataframe({'data': [3., 4., 8.6, 13.4, 22.5, 17, 19.2, 36.1, 127, -23, 59.2]},
                                      columns=['data'], generate_metadata=True)
-        self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])
+        self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0])
 
 
 
@@ -46,6 +46,8 @@ class AutoRegODetectTestCase(unittest.TestCase):
         self.prediction_labels = self.primitive.produce(inputs=self.X_test).value
         self.prediction_score = self.primitive.produce_score(inputs=self.X_test).value
 
+        # print(self.prediction_labels)
+
         self.collective_common_test = CollectiveCommonTest(model=self.primitive._clf,
                                                             X_train=self.X_train,
                                                             y_train=self.y_train,