Add gilbert skill score to PlotContingency

mlair/plotting/postprocessing_plotting.py

@@ -33,7 +33,8 @@ class PlotContingency(AbstractPlotClass):
 
     def __init__(self, station_names, file_path, comp_path, file_name, plot_folder: str = ".", model_name: str = "nn",
                  model_plot_name: str = "nn", obs_name: str = "obs", comp_names: str = "IntelliO3",
-                 plot_names=["contingency_threat_score", "contingency_hit_rate", "contingency_false_alarm_rate",
+                 plot_names=["contingency_gilbert_skill_score", "contingency_threat_score", "contingency_hit_rate",
+                             "contingency_false_alarm_rate",
                              "contingency_bias", "contingency_all_scores", "contingency_table"]):
 
         super().__init__(plot_folder, plot_names[0])
@@ -50,10 +51,12 @@ class PlotContingency(AbstractPlotClass):
         self._plot_names = plot_names
         self._min_threshold, self._max_threshold = self._min_max_threshold()
         contingency_array = self._calculate_contingencies()
-        self._scores = ["ts", "h", "f", "b"]
+        self._scores = ["gss", "ts", "h", "f", "b"]
         score_array = self._calculate_all_scores(contingency_array)
         self._plot_counter = 0
 
+        self._plot(score_array, "gss")
+        self._save()
         self._plot(score_array, "ts")
         self._save()
         self._plot(score_array, "h")
@@ -213,6 +216,14 @@ class PlotContingency(AbstractPlotClass):
         false_above = contingency[1]
         false_below = contingency[2]
         true_below = contingency[3]
+        if score == "gss":
+            frequency_above_threshold = (true_above + false_below)/(true_above + false_above + false_below + true_below)
+            forecasts_above_threshold = true_above + false_above
+            chance_hits = frequency_above_threshold*forecasts_above_threshold
+            if (true_above + false_above + false_below - chance_hits) == 0:
+                score_value = 1
+            else:
+                score_value = (true_above - chance_hits)/(true_above + false_above + false_below - chance_hits)
         if score == "ts":
             if (true_above + false_above + false_below) == 0:
                 score_value = 1