fixed another problem with missing station forecastas

mlair/run_modules/post_processing.py

@@ -785,7 +785,7 @@ class PostProcessing(RunEnvironment):
                 model_list = None
 
             # test errors of competitors
-            for model_type in remove_items(model_list or [], errors.keys()):
+            for model_type in remove_items(model_list or [], list(errors.keys())):
                 if self.observation_indicator not in combined.coords[self.model_type_dim]:
                     continue
                 if model_type not in errors.keys():
@@ -815,10 +815,11 @@ class PostProcessing(RunEnvironment):
         avg_skill_score = 0
         n_total = None
         for vals in counts.values():
-            n_total = vals if n_total is None else n_total + vals
-        for station, station_errors in scores.items():
+            n_total = vals if n_total is None else n_total.add(vals, fill_value=0)
+        for station, station_scores in scores.items():
             n = counts.get(station)
-            avg_skill_score = station_errors * n / n_total + avg_skill_score
+            avg_skill_score = station_scores.mul(n.div(n_total, fill_value=0), fill_value=0).add(avg_skill_score,
+                                                                                                 fill_value=0)
         return avg_skill_score