fix skitest of KDiscord, PCA, Telemenom

tods/tests/sk_interface/detection_algorithm/test_ski_KDiscordODetector.py

@@ -25,11 +25,13 @@ class KDiscordODetectorSKI_TestCase(unittest.TestCase):
         self.n_test = 100
         self.contamination = 0.1
         self.roc_floor = 0.0
+        self.window_size = 5
         self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
             n_train=self.n_train, n_test=self.n_test,
             contamination=self.contamination, random_state=42)
 
-        self.transformer = KDiscordODetectorSKI(contamination=self.contamination)
+        self.transformer = KDiscordODetectorSKI(contamination=self.contamination, window_size=self.window_size)
+        self.y_test = self.y_test[self.window_size-1:]
         self.transformer.fit(self.X_train)
 
     def test_prediction_labels(self):

tods/tests/sk_interface/detection_algorithm/test_ski_PCAODetector.py

@@ -25,11 +25,13 @@ class PCAODetectorSKI_TestCase(unittest.TestCase):
         self.n_test = 100
         self.contamination = 0.1
         self.roc_floor = 0.0
+        self.window_size = 5
         self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
             n_train=self.n_train, n_test=self.n_test,
             contamination=self.contamination, random_state=42)
 
-        self.transformer = PCAODetectorSKI(contamination=self.contamination)
+        self.transformer = PCAODetectorSKI(contamination=self.contamination, window_size=self.window_size)
+        self.y_test = self.y_test[self.window_size-1:]
         self.transformer.fit(self.X_train)
 
     def test_prediction_labels(self):

tods/tests/sk_interface/detection_algorithm/test_ski_SystemWiseDetection.py

@@ -1,46 +0,0 @@
-import numpy as np
-import pandas as pd
-import os
-from tods.sk_interface.detection_algorithm.SystemWiseDetection_skinterface import SystemWiseDetectionSKI
-
-from pyod.utils.data import generate_data
-import unittest
-from numpy.testing import assert_allclose
-from numpy.testing import assert_array_less
-from unittest import TestCase
-from sklearn.metrics import roc_auc_score
-
-class SystemWiseDetectionSKI_TestCase(unittest.TestCase):
-    def setUp(self):
-
-        _dummy = TestCase('__init__')
-        self.assert_greater_equal = _dummy.assertGreaterEqual
-        self.assert_greater = _dummy.assertGreater
-        self.assert_less_equal = _dummy.assertLessEqual
-        self.assert_less = _dummy.assertLess
-        self.assert_equal = _dummy.assertEqual
-
-        self.maxDiff = None
-        self.n_train = 200
-        self.n_test = 100
-        self.contamination = 0.1
-        self.roc_floor = 0.0
-        self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
-            n_train=self.n_train, n_test=self.n_test,
-            contamination=self.contamination, random_state=42)
-
-        self.transformer = SystemWiseDetectionSKI(contamination=self.contamination)
-        self.transformer.fit(self.X_train)
-
-    def test_prediction_labels(self):
-        pred_labels = self.transformer.predict(self.X_test)
-        self.assert_equal(pred_labels.shape[0], self.y_test.shape[0])
-
-    def test_prediction_score(self):
-        pred_scores = self.transformer.predict_score(self.X_test)
-        self.assert_equal(pred_scores.shape[0], self.y_test.shape[0])
-        self.assert_greater_equal(roc_auc_score(self.y_test, pred_scores), self.roc_floor)
-
-
-if __name__ == '__main__':
-    unittest.main()

tods/tests/sk_interface/detection_algorithm/test_ski_Telemanom.py

@@ -27,10 +27,21 @@ class TelemanomSKI_TestCase(unittest.TestCase):
         self.roc_floor = 0.0
         self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
             n_train=self.n_train, n_test=self.n_test,
-            contamination=self.contamination, random_state=42)
+            contamination=self.contamination, random_state=42, n_features=3)
 
         self.transformer = TelemanomSKI(contamination=self.contamination)
         self.transformer.fit(self.X_train)
+        self.l_s = 5
+        self.n_predictions = 1
+        self.X_train, self.y_train, self.X_test, self.y_test = generate_data(
+                                                n_train=self.n_train, n_test=self.n_test,
+                                                contamination=self.contamination, random_state=42)
+
+        self.transformer = TelemanomSKI(contamination=self.contamination, l_s=self.l_s, n_predictions=self.n_predictions)
+
+        self.y_test = self.y_test[self.l_s:-self.n_predictions]
+        self.y_train = self.y_train[self.l_s:-self.n_predictions]
+        self.transformer.fit(self.X_train)
 
     def test_prediction_labels(self):
         pred_labels = self.transformer.predict(self.X_test)