change test behavior due to PyOD change

Author: yzhao062

combo/test/test_detector_comb.py

@@ -10,7 +10,6 @@
 
 
 from sklearn.metrics import roc_auc_score
-from scipy.stats import rankdata
 
 from pyod.utils.data import generate_data
 from pyod.models.knn import KNN
@@ -30,8 +29,8 @@ def setUp(self):
         self.n_test = 100
         self.contamination = 0.1
         self.roc_floor = 0.8
-        self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
-            n_train=self.n_train, n_test=self.n_test,
+        self.X_train, self.X_test, self.y_train, self.y_test = generate_data(
+            n_train=self.n_train, n_test=self.n_test, behaviour='new',
             contamination=self.contamination, random_state=42)
 
         detectors = [KNN(), LOF(), OCSVM()]
@@ -98,8 +97,8 @@ def setUp(self):
         self.n_test = 100
         self.contamination = 0.1
         self.roc_floor = 0.8
-        self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
-            n_train=self.n_train, n_test=self.n_test,
+        self.X_train, self.X_test, self.y_train, self.y_test = generate_data(
+            n_train=self.n_train, n_test=self.n_test, behaviour='new',
             contamination=self.contamination, random_state=42)
 
         detectors = [KNN(), LOF(), OCSVM()]
@@ -166,8 +165,8 @@ def setUp(self):
         self.n_test = 100
         self.contamination = 0.1
         self.roc_floor = 0.8
-        self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
-            n_train=self.n_train, n_test=self.n_test,
+        self.X_train, self.X_test, self.y_train, self.y_test = generate_data(
+            n_train=self.n_train, n_test=self.n_test, behaviour='new',
             contamination=self.contamination, random_state=42)
 
         detectors = [KNN(), LOF(), OCSVM()]

examples/detector_comb_example.py

@@ -31,11 +31,12 @@
 n_test = 100  # number of testing points
 
 # Generate sample data
-X_train, y_train, X_test, y_test = \
+X_train, X_test, y_train, y_test = \
     generate_data(n_train=n_train,
                   n_test=n_test,
                   n_features=2,
                   contamination=contamination,
+                  behaviour='new',
                   random_state=42)
 
 detectors = [KNN(), LOF(), OCSVM()]

examples/detector_lscp_example.py

@@ -31,11 +31,12 @@
 n_test = 100  # number of testing points
 
 # Generate sample data
-X_train, y_train, X_test, y_test = \
+X_train, X_test, y_train, y_test = \
     generate_data(n_train=n_train,
                   n_test=n_test,
                   n_features=2,
                   contamination=contamination,
+                  behaviour='new',
                   random_state=42)
 
 detectors = [KNN(), LOF(), OCSVM()]