Allow n-dimensional input for func API. Some maintenance for tests.

tests/test_sklearn_api_classification_binary.py

@@ -67,6 +67,11 @@ def roc_auc_score_universal(y_true, y_pred):
     """
     ohe = OneHotEncoder(sparse=False)
     y_true = ohe.fit_transform(y_true.reshape(-1, 1))
+    #@@@@
+    if len(y_pred.shape) == 1:
+        y_pred = np.c_[y_pred, y_pred]
+        y_pred[:, 0] = 1 - y_pred[:, 1]
+    #@@@@
     auc_score = roc_auc_score(y_true, y_pred)
     return auc_score
 

vecstack/core.py

@@ -413,11 +413,13 @@ def your_metric(y_true, y_pred):
                                  accept_sparse=['csr'], # allow csr and cast all other sparse types to csr
                                  force_all_finite=False, # allow nan and inf because 
                                                          # some models (xgboost) can handle
+                                 allow_nd=True,
                                  multi_output=False) # do not allow several columns in y_train
 
     if X_test is not None: # allow X_test to be None for mode='oof'
         X_test = check_array(X_test,
                              accept_sparse=['csr'], # allow csr and cast all other sparse types to csr
+                             allow_nd=True,
                              force_all_finite=False) # allow nan and inf because 
                                                      # some models (xgboost) can handle
     if sample_weight is not None: