Change runtimewarning to userwarning

Author: Guillaume Lemaitre

imblearn/combine/tests/test_smote_tomek.py

@@ -78,7 +78,7 @@ def test_smote_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, smote.fit, X, y_single_class)
+    assert_warns(UserWarning, smote.fit, X, y_single_class)
 
 
 def test_smote_fit():

imblearn/ensemble/tests/test_balance_cascade.py

@@ -93,7 +93,7 @@ def test_bc_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, bc.fit, X, y_single_class)
+    assert_warns(UserWarning, bc.fit, X, y_single_class)
 
 
 def test_bc_fit_invalid_ratio():

imblearn/ensemble/tests/test_easy_ensemble.py

@@ -85,7 +85,7 @@ def test_ee_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, ee.fit, X, y_single_class)
+    assert_warns(UserWarning, ee.fit, X, y_single_class)
 
 
 def test_ee_fit_invalid_ratio():

imblearn/over_sampling/tests/test_adasyn.py

@@ -88,7 +88,7 @@ def test_ada_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, ada.fit, X, y_single_class)
+    assert_warns(UserWarning, ada.fit, X, y_single_class)
 
 
 def test_ada_fit_invalid_ratio():

imblearn/over_sampling/tests/test_random_over_sampler.py

@@ -78,7 +78,7 @@ def test_ros_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, ros.fit, X, y_single_class)
+    assert_warns(UserWarning, ros.fit, X, y_single_class)
 
 
 def test_ros_fit_invalid_ratio():

imblearn/over_sampling/tests/test_smote.py

@@ -87,7 +87,7 @@ def test_smote_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, smote.fit, X, y_single_class)
+    assert_warns(UserWarning, smote.fit, X, y_single_class)
 
 
 def test_smote_fit():

imblearn/under_sampling/tests/test_allknn.py

@@ -88,7 +88,7 @@ def test_allknn_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, allknn.fit, X, y_single_class)
+    assert_warns(UserWarning, allknn.fit, X, y_single_class)
 
 
 def test_allknn_fit():

imblearn/under_sampling/tests/test_cluster_centroids.py

@@ -82,7 +82,7 @@ def test_cc_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, cc.fit, X, y_single_class)
+    assert_warns(UserWarning, cc.fit, X, y_single_class)
 
 
 def test_cc_fit_invalid_ratio():

imblearn/under_sampling/tests/test_condensed_nearest_neighbour.py

@@ -64,7 +64,7 @@ def test_cnn_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, cnn.fit, X, y_single_class)
+    assert_warns(UserWarning, cnn.fit, X, y_single_class)
 
 
 def test_cnn_fit():

imblearn/under_sampling/tests/test_edited_nearest_neighbours.py

@@ -65,7 +65,7 @@ def test_enn_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, enn.fit, X, y_single_class)
+    assert_warns(UserWarning, enn.fit, X, y_single_class)
 
 
 def test_enn_fit():

imblearn/under_sampling/tests/test_instance_hardness_threshold.py

@@ -97,7 +97,7 @@ def test_iht_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, iht.fit, X, y_single_class)
+    assert_warns(UserWarning, iht.fit, X, y_single_class)
 
 
 def test_iht_fit_invalid_ratio():

imblearn/under_sampling/tests/test_nearmiss_1.py

@@ -101,7 +101,7 @@ def test_nearmiss_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, nm1.fit, X, y_single_class)
+    assert_warns(UserWarning, nm1.fit, X, y_single_class)
 
 
 def test_nm_fit_invalid_ratio():

imblearn/under_sampling/tests/test_nearmiss_2.py

@@ -101,7 +101,7 @@ def test_nearmiss_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, nm2.fit, X, y_single_class)
+    assert_warns(UserWarning, nm2.fit, X, y_single_class)
 
 
 def test_nm_fit_invalid_ratio():

imblearn/under_sampling/tests/test_nearmiss_3.py

@@ -101,7 +101,7 @@ def test_nearmiss_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, nm3.fit, X, y_single_class)
+    assert_warns(UserWarning, nm3.fit, X, y_single_class)
 
 
 def test_nm_fit_invalid_ratio():

imblearn/under_sampling/tests/test_neighbourhood_cleaning_rule.py

@@ -59,7 +59,7 @@ def test_ncr_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, ncr.fit, X, y_single_class)
+    assert_warns(UserWarning, ncr.fit, X, y_single_class)
 
 
 def test_ncr_fit():

imblearn/under_sampling/tests/test_one_sided_selection.py

@@ -61,7 +61,7 @@ def test_oss_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, oss.fit, X, y_single_class)
+    assert_warns(UserWarning, oss.fit, X, y_single_class)
 
 
 def test_oss_fit():

imblearn/under_sampling/tests/test_random_under_sampler.py

@@ -77,7 +77,7 @@ def test_rus_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, rus.fit, X, y_single_class)
+    assert_warns(UserWarning, rus.fit, X, y_single_class)
 
 
 def test_rus_fit_invalid_ratio():

imblearn/under_sampling/tests/test_repeated_edited_nearest_neighbours.py

@@ -98,7 +98,7 @@ def test_renn_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, renn.fit, X, y_single_class)
+    assert_warns(UserWarning, renn.fit, X, y_single_class)
 
 
 def test_renn_fit():

imblearn/under_sampling/tests/test_tomek_links.py

@@ -62,7 +62,7 @@ def test_tl_fit_single_class():
     # Resample the data
     # Create a wrong y
     y_single_class = np.zeros((X.shape[0], ))
-    assert_warns(RuntimeWarning, tl.fit, X, y_single_class)
+    assert_warns(UserWarning, tl.fit, X, y_single_class)
 
 
 def test_tl_fit():