From d0735fd124c137561c66f448f95b5e8152ebad34 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Tue, 12 Oct 2021 18:03:18 +0200
Subject: [PATCH] errors of external competitors are now added too
---
mlair/run_modules/post_processing.py | 14 ++++++++++++--
1 file changed, 12 insertions(+), 2 deletions(-)
diff --git a/mlair/run_modules/post_processing.py b/mlair/run_modules/post_processing.py
index 425b26cf..0ff4afb3 100644
--- a/mlair/run_modules/post_processing.py
+++ b/mlair/run_modules/post_processing.py
@@ -771,10 +771,20 @@ class PostProcessing(RunEnvironment):
*map(lambda x: external_data.sel(**{self.model_type_dim: x}),
[model_type, "obs"]), dim="index")
- # skill score
+ # load competitors
competitor = self.load_competitors(station)
combined = self._combine_forecasts(external_data, competitor, dim=self.model_type_dim)
model_list = remove_items(combined.coords[self.model_type_dim].values.tolist(), "obs") if combined is not None else None
+
+ # test errors of competitors
+ for model_type in remove_items(model_list, errors.keys()):
+ if model_type not in errors.keys():
+ errors[model_type] = {}
+ errors[model_type][station] = statistics.calculate_error_metrics(
+ *map(lambda x: combined.sel(**{self.model_type_dim: x}),
+ [model_type, "obs"]), dim="index")
+
+ # skill score
skill_score = statistics.SkillScores(combined, models=model_list, ahead_dim=self.ahead_dim)
if external_data is not None:
skill_score_competitive[station] = skill_score.skill_scores()
@@ -828,7 +838,7 @@ class PostProcessing(RunEnvironment):
station_errors = {str(i.values): station_errors.sel(**{dim: i}) for i in sel_index}
for metric, vals in station_errors.items():
if metric == "n":
- continue
+ metric = "count"
pd_vals = pd.DataFrame.from_dict({station: vals}).T
pd_vals.columns = [f"{metric}(t+{x})" for x in vals.coords["ahead"].values]
mc = metric_collection.get(metric, pd.DataFrame())
--
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