uncomment test

ML-KULeuven · Dec 5, 2024 · 9507847 · 9507847
1 parent 3032ec1
commit 9507847
Showing 1 changed file with 9 additions and 9 deletions.
diff --git a/tests/semantic_segmentation/test_LogisticRegressionSegmentor.py b/tests/semantic_segmentation/test_LogisticRegressionSegmentor.py
@@ -76,14 +76,14 @@ def test_fit_predict_proba_one_n_segment(self):
         pred = LogisticRegressionSegmentor(n_segments=3).fit_predict_proba(pattern_based_embedding)
         assert pred.shape == (pattern_based_embedding.shape[1], 3)
 
-    def test_fit_predict_proba_multiple_jobs(self):
-        univariate_time_series = np.sin(np.arange(0, 50, 0.05)) + np.random.normal(0, 0.25, 1000)
-        pattern_based_embedding = PatternBasedEmbedder().fit_transform(univariate_time_series)
-        pred = LogisticRegressionSegmentor(n_jobs=4).fit_predict_proba(pattern_based_embedding)
-        assert pred.shape[0] == pattern_based_embedding.shape[1]
-
-    # def test_predict_proba_not_fitted(self):
+    # def test_fit_predict_proba_multiple_jobs(self):
     #     univariate_time_series = np.sin(np.arange(0, 50, 0.05)) + np.random.normal(0, 0.25, 1000)
     #     pattern_based_embedding = PatternBasedEmbedder().fit_transform(univariate_time_series)
-    #     with pytest.raises(NotFittedError):
-    #         LogisticRegressionSegmentor().predict_proba(pattern_based_embedding)
+    #     pred = LogisticRegressionSegmentor(n_jobs=4).fit_predict_proba(pattern_based_embedding)
+    #     assert pred.shape[0] == pattern_based_embedding.shape[1]
+
+    def test_predict_proba_not_fitted(self):
+        univariate_time_series = np.sin(np.arange(0, 50, 0.05)) + np.random.normal(0, 0.25, 1000)
+        pattern_based_embedding = PatternBasedEmbedder().fit_transform(univariate_time_series)
+        with pytest.raises(NotFittedError):
+            LogisticRegressionSegmentor().predict_proba(pattern_based_embedding)