fix the bug for assertation in main_meta_postprocess

video_prediction_tools/main_scripts/main_meta_postprocess.py

@@ -62,6 +62,7 @@ class MetaPostprocess(object):
         self.load_analysis_config()
         self.get_metrics_values()
         if self.enable_skill_scores:
+            print("Enable the skill scores")
             self.calculate_skill_scores()
             self.plot_skill_scores()
         else:
@@ -80,7 +81,7 @@ class MetaPostprocess(object):
         Function to create the analysis directory if it does not exist
         """
         if not os.path.exists(self.analysis_dir): os.makedirs(self.analysis_dir)
-        print("1. Create analysis dir successfully: The result will be stored to the folder:", self.analysis_dir)
+        print("Create analysis dir successfully: The result will be stored to the folder:", self.analysis_dir)
 
     def copy_analysis_config(self):
         """
@@ -89,7 +90,7 @@ class MetaPostprocess(object):
         try:
             shutil.copy(self.analysis_config, os.path.join(self.analysis_dir, "meta_config.json"))
             self.analysis_config = os.path.join(self.analysis_dir, "meta_config.json")
-            print("2. Copy analysis config successs ")
+            print("Copy analysis config successs ")
         except Exception as e:
             print("The meta_config.json is not found in the dictory: ", self.analysis_config)
         return None
@@ -104,7 +105,7 @@ class MetaPostprocess(object):
         print("*****The following results will be compared and ploted*****")
         [print(i) for i in self.f["results"].values()]
         print("*******************************************************")
-        print("3. Loading analysis config success")
+        print("Loading analysis config success")
 
         return None
 
@@ -133,7 +134,7 @@ class MetaPostprocess(object):
         for i, result_dir in enumerate(self.f["results"].values()):
             vals = MetaPostprocess.get_one_metric_values(result_dir, self.metric, self.models_type[i],self.enable_skill_scores)
             self.metric_values.append(vals)
-        print("4. Get metrics values success")
+        print(" Get metrics values success")
         return self.metric_values
 
     @staticmethod
@@ -184,7 +185,8 @@ class MetaPostprocess(object):
             return None
 
     def get_lead_time_labels(self):
-        assert len(self.metric_values) == 2
+        assert len(self.metric_values[0]) == 2
+
         leadtimes = np.array(self.metric_values[0][1]).shape[1]
         leadtimelist = ["leadhour" + str(i + 1) for i in range(leadtimes)]
         return leadtimelist
@@ -216,7 +218,7 @@ class MetaPostprocess(object):
         fig = plt.figure(figsize = (8, 6))
         ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
         for i in range(len(self.metric_values)): #loop number of test samples
-            assert len(self.metric_values)==2
+            assert len(self.metric_values[0])==2
             score_plot = np.nanquantile(self.metric_values[i][1], 0.5, axis = 0)
            
             assert len(score_plot) == self.n_leadtime