Merge pull request #7 from shiv3679/patch-2

multiple instances of gss in nwpeval.py
Debasish-Mahapatra · Apr 6, 2024 · dd45376 · dd45376
2 parents deec65b + 42a6a4e
commit dd45376
Showing 1 changed file with 20 additions and 20 deletions.
diff --git a/nwpeval/nwpeval.py b/nwpeval/nwpeval.py
@@ -74,8 +74,8 @@ def compute_metrics(self, metrics, dim=None, thresholds=None):
             elif metric == 'PSS':
                 threshold = thresholds.get('PSS', 0.5)
                 metric_values[metric] = self.compute_pss(threshold, dim)
-            elif metric == 'GS':
-                threshold = thresholds.get('GS', 0.5)
+            # elif metric == 'GS':
+            #     threshold = thresholds.get('GS', 0.5)   # a mirror instance of gilbert skill score already present
                 metric_values[metric] = self.compute_gs(threshold, dim)
             elif metric == 'SEDS':
                 threshold = thresholds.get('SEDS', 0.5)
@@ -454,29 +454,29 @@ def compute_pss(self, threshold, dim=None):
 
         return pss
 
-    def compute_gs(self, threshold, dim=None):
-        """
-        Compute the Gilbert Skill Score (GS) for a given threshold.
+    # def compute_gs(self, threshold, dim=None):
+    #     """
+    #     Compute the Gilbert Skill Score (GS) for a given threshold.
 
-        Args:
-            threshold (float): The threshold value for binary classification.
-            dim (str, list, or None): The dimension(s) along which to compute the GS.
-                                      If None, compute the GS over the entire data.
+    #     Args:
+    #         threshold (float): The threshold value for binary classification.
+    #         dim (str, list, or None): The dimension(s) along which to compute the GS.
+    #                                   If None, compute the GS over the entire data.
 
-        Returns:
-            xarray.DataArray: The computed GS values.
-        """
-        # Convert data to binary based on the threshold
-        obs_binary = (self.obs_data >= threshold).astype(int)
-        model_binary = (self.model_data >= threshold).astype(int)
+    #     Returns:
+    #         xarray.DataArray: The computed GS values.
+    #     """
+    #     # Convert data to binary based on the threshold
+    #     obs_binary = (self.obs_data >= threshold).astype(int)
+    #     model_binary = (self.model_data >= threshold).astype(int)
 
-        # Calculate the confusion matrix
-        tn, fp, fn, tp = self.confusion_matrix(obs_binary, model_binary, dim)
+    #     # Calculate the confusion matrix
+    #     tn, fp, fn, tp = self.confusion_matrix(obs_binary, model_binary, dim)
 
-        # Calculate the GS
-        gs = (tp - ((tp + fp) * (tp + fn) / (tp + fp + fn + tn))) / (tp + fp + fn - ((tp + fp) * (tp + fn) / (tp + fp + fn + tn)))
+    #     # Calculate the GS
+    #     gs = (tp - ((tp + fp) * (tp + fn) / (tp + fp + fn + tn))) / (tp + fp + fn - ((tp + fp) * (tp + fn) / (tp + fp + fn + tn)))
 
-        return gs
+    #     return gs
 
     def compute_seds(self, threshold, dim=None):
         """