create copies of loss_args

arminwitte · Sep 15, 2023 · 2a92983 · 2a92983
1 parent 99be4c8
commit 2a92983
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Showing 2 changed files with 5 additions and 4 deletions.
diff --git a/binarybeech/attributehandler.py b/binarybeech/attributehandler.py
@@ -79,7 +79,7 @@ def split(self, df):
             n = [len(df_.index) for df_ in split_df]
 
             loss_args = {key: self.algorithm_kwargs[key] for key in ["lambda_l1", "lambda_l2"]}
-            loss_args = [loss_args]*2
+            loss_args = [loss_args.copy(), loss_args.copy()]
             if "__weights__" in df:
                 for i, df_ in enumerate(split_df):
                     loss_args[i]["weights"] = df_["__weights__"].values
@@ -166,7 +166,7 @@ def fun(x):
                 return np.Inf
 
             loss_args = {key: self.algorithm_kwargs[key] for key in ["lambda_l1", "lambda_l2"]}
-            loss_args = [loss_args]*2
+            loss_args = [loss_args.copy(), loss_args.copy()]
             if "__weights__" in df:
                 for i, df_ in enumerate(split_df):
                                 loss_args[i]["weights"] = df_["__weights__"].values
@@ -220,7 +220,7 @@ def split(self, df):
         n = [len(df_.index) for df_ in self.split_df]
 
         loss_args = {key: self.algorithm_kwargs[key] for key in ["lambda_l1", "lambda_l2"]}
-        loss_args = [loss_args]*2
+        loss_args = [loss_args.copy(), loss_args.copy()]
         if "__weights__" in df:
             for i, df_ in enumerate(self.split_df):
                 loss_args[i]["weights"] = df_["__weights__"].values
@@ -305,7 +305,7 @@ def fun(x):
 
 
             loss_args = {key: self.algorithm_kwargs[key] for key in ["lambda_l1", "lambda_l2"]}
-            loss_args = [loss_args]*2
+            loss_args = [loss_args.copy(), loss_args.copy()]
             if "__weights__" in df:
                 for i, df_ in enumerate(split_df):
                     loss_args[i]["weights"] = df_["__weights__"].values

diff --git a/tests/test_datamanager.py b/tests/test_datamanager.py
@@ -11,6 +11,7 @@ def test_datamanager_info():
     assert ah == ["default", "clustering"]
     assert m == [
         "regression",
+        "regression:regularized",
         "classification:gini",
         "classification:entropy",
         "logistic",