Merge branch...

Merge branch 'falco_issue313-allow-non-monotonic-window-lead-times-in-helpers-statistics-py-ahead_names-definition-2' into 'develop'

Resolve "allow non-monotonic window lead times in helpers/statistics.py ahead_names definition"

See merge request !310

mlair/helpers/statistics.py

@@ -283,7 +283,7 @@ class SkillScores:
         combination_strings = [f"{first}-{second}" for (first, second) in combinations]
         return combinations, combination_strings
 
-    def skill_scores(self, window_lead_time: int) -> pd.DataFrame:
+    def skill_scores(self, window_lead_time: int, ahead_dim="ahead") -> pd.DataFrame:
         """
         Calculate skill scores for all combinations of model names.
 
@@ -291,7 +291,7 @@ class SkillScores:
 
         :return: skill score for each comparison and forecast step
         """
-        ahead_names = list(range(1, window_lead_time + 1))
+        ahead_names = list(self.external_data[ahead_dim].data)
         combinations, combination_strings = self.get_model_name_combinations()
         skill_score = pd.DataFrame(index=combination_strings)
         for iahead in ahead_names:
@@ -304,7 +304,7 @@ class SkillScores:
         return skill_score
 
     def climatological_skill_scores(self, internal_data: Data, window_lead_time: int,
-                                    forecast_name: str) -> xr.DataArray:
+                                    forecast_name: str, ahead_dim="ahead") -> xr.DataArray:
         """
         Calculate climatological skill scores according to Murphy (1988).
 
@@ -317,7 +317,7 @@ class SkillScores:
 
         :return: all CASES as well as all terms
         """
-        ahead_names = list(range(1, window_lead_time + 1))
+        ahead_names = list(self.external_data[ahead_dim].data)
 
         all_terms = ['AI', 'AII', 'AIII', 'AIV', 'BI', 'BII', 'BIV', 'CI', 'CIV', 'CASE I', 'CASE II', 'CASE III',
                      'CASE IV']