allow_pickle=True for np.load in tests

Author: vecxoz

tests/test_func_api_classification_binary.py

@@ -145,7 +145,7 @@ def test_oof_pred_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -171,7 +171,7 @@ def test_oof_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -197,7 +197,7 @@ def test_pred_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -236,7 +236,7 @@ def test_oof_pred_bag_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -273,7 +273,7 @@ def test_pred_bag_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -304,7 +304,7 @@ def test_oof_pred_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -330,7 +330,7 @@ def test_oof_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -356,7 +356,7 @@ def test_pred_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -398,7 +398,7 @@ def test_oof_pred_bag_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -447,7 +447,7 @@ def test_pred_bag_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -491,7 +491,7 @@ def test_oof_pred_bag_mode_shuffle(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -609,7 +609,7 @@ def test_oof_pred_mode_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -672,7 +672,7 @@ def test_oof_pred_bag_mode_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -712,7 +712,7 @@ def test_oof_pred_mode_proba_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -784,7 +784,7 @@ def test_oof_pred_bag_mode_proba_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -834,7 +834,7 @@ def test_N_dim_input(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 

tests/test_func_api_classification_multiclass.py

@@ -142,7 +142,7 @@ def test_oof_pred_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -168,7 +168,7 @@ def test_oof_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -194,7 +194,7 @@ def test_pred_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -233,7 +233,7 @@ def test_oof_pred_bag_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -270,7 +270,7 @@ def test_pred_bag_mode(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -301,7 +301,7 @@ def test_oof_pred_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -327,7 +327,7 @@ def test_oof_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -353,7 +353,7 @@ def test_pred_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -395,7 +395,7 @@ def test_oof_pred_bag_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -444,7 +444,7 @@ def test_pred_bag_mode_proba(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -488,7 +488,7 @@ def test_oof_pred_bag_mode_shuffle(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -606,7 +606,7 @@ def test_oof_pred_mode_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -669,7 +669,7 @@ def test_oof_pred_bag_mode_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -709,7 +709,7 @@ def test_oof_pred_mode_proba_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -781,7 +781,7 @@ def test_oof_pred_bag_mode_proba_2_models(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]
 
@@ -832,7 +832,7 @@ def test_N_dim_input(self):
         # Normally if cleaning is performed there is only one .npy file at given moment
         # But if we have no cleaning there may be more then one file so we take the latest
         file_name = sorted(glob.glob(os.path.join(temp_dir, '*.npy')))[-1] # take the latest file
-        S = np.load(file_name)
+        S = np.load(file_name, allow_pickle=True)
         S_train_3 = S[0]
         S_test_3 = S[1]