Added model_plot_name to postprocessing_plotting.py

mlair/plotting/postprocessing_plotting.py

@@ -32,7 +32,7 @@ logging.getLogger('matplotlib').setLevel(logging.WARNING)
 class PlotContingency(AbstractPlotClass):
 
     def __init__(self, station_names, file_path, comp_path, file_name, plot_folder: str = ".", model_name: str = "nn",
-                 obs_name: str = "obs", comp_names: str = "IntelliO3",
+                 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",
                              "contingency_bias", "contingency_all_scores", "contingency_table"]):
 
@@ -43,6 +43,7 @@ class PlotContingency(AbstractPlotClass):
         self._file_name = file_name
         self._obs_name = obs_name
         self._model_name = model_name
+        self._model_plot_name = model_plot_name
         self._comp_names = to_list(comp_names)
         self._all_names = [self._model_name]
         self._all_names.extend(self._comp_names)
@@ -88,7 +89,11 @@ class PlotContingency(AbstractPlotClass):
                 plt.plot(range(self._min_threshold, self._max_threshold), data.loc[dict(type="nn", scores=score_name)], label=score_name)
         else:
             for type in data.type.values.tolist():
-                plt.plot(range(self._min_threshold, self._max_threshold), data.loc[dict(type=type, scores=score)], label=type)
+                if type in "nn":
+                    plt.plot(range(self._min_threshold, self._max_threshold), data.loc[dict(type=type, scores=score)],
+                             label=self._model_plot_name)
+                else:
+                    plt.plot(range(self._min_threshold, self._max_threshold), data.loc[dict(type=type, scores=score)], label=type)
         plt.title(self._plot_names[self._plot_counter])
         plt.legend()
         self.plot_name = self._plot_names[self._plot_counter]