check fit for aggregate

Author: SvenKlaassen

doubleml/did/did_multi.py

@@ -778,14 +778,15 @@ def sensitivity_benchmark(self, benchmarking_set, fit_args=None):
 
     def aggregate(self, aggregation="simple"):
         if not isinstance(aggregation, str):
-            raise TypeError(
-                "aggregation must be a string. " f"{str(aggregation)} of type {type(aggregation)} was passed."
-            )
+            raise TypeError("aggregation must be a string. " f"{str(aggregation)} of type {type(aggregation)} was passed.")
         valid_aggregations = ["simple"]
         if aggregation not in valid_aggregations:
-            raise ValueError(
-                f"aggregation must be one of {valid_aggregations}. " f"{str(aggregation)} was passed."
-            )
+            raise ValueError(f"aggregation must be one of {valid_aggregations}. " f"{str(aggregation)} was passed.")
+        if self.framework is None:
+            raise ValueError("Apply fit() before aggregate().")
+
+        if aggregation == "simple":
+            pass
         pass
 
     def _fit_model(self, i_gt, n_jobs_cv=None, store_predictions=True, store_models=False, external_predictions_dict=None):
@@ -888,9 +889,7 @@ def _rename_external_predictions(self, external_predictions):
         return ext_pred_dict
 
     def _calc_nuisance_loss(self):
-        nuisance_loss = {
-            learner: np.full((self.n_rep, self.n_gt_atts), np.nan) for learner in self.modellist[0].params_names
-        }
+        nuisance_loss = {learner: np.full((self.n_rep, self.n_gt_atts), np.nan) for learner in self.modellist[0].params_names}
         for i_model, model in enumerate(self.modellist):
             for learner in self.modellist[0].params_names:
                 for i_rep in range(self.n_rep):

doubleml/did/tests/test_did_multi_exceptions.py

@@ -122,3 +122,8 @@ def test_exceptions_aggregate():
     msg = "aggregation must be one of \\['simple'\\]. invalid was passed."
     with pytest.raises(ValueError, match=msg):
         dml_obj.aggregate(aggregation="invalid")
+
+    # test without fit()
+    msg = r"Apply fit\(\) before aggregate\(\)."
+    with pytest.raises(ValueError, match=msg):
+        dml_obj.aggregate()