Avoid dict overrides for entity-level

FairEval.py

@@ -204,38 +204,58 @@ class FairEval(evaluate.Metric):
         assert mode in ['traditional', 'fair', 'weighted'], 'mode must be \'traditional\', \'fair\' or \'weighted\''
         assert error_format in ['count', 'error_ratio', 'entity_ratio'], 'error_format must be \'count\', \'error_ratio\' or \'entity_ratio\''
 
-        # append entity-level errors (always fair)
-        for k, v in results['per_label']['fair'].items():
-            output[k] = {'TP': v['TP'] / fair_divider if error_format == 'entity_ratio' else v['TP'],
-                         'FP': v['FP'] / fair_divider, 'FN': v['FN'] / fair_divider,
-                         'LE': v['LE'] / fair_divider, 'BE': v['BE'] / fair_divider, 'LBE': v['LBE'] / fair_divider,}
-
-        # append entity-level scores (depending on mode)
+        # append entity-level errors and scores
         if mode == 'traditional':
             for k, v in results['per_label'][mode].items():
-                output[k].update({'precision': v['Prec'], 'recall': v['Rec'], 'f1': v['F1'],})
+                output[k] = {# traditional scores
+                             'precision': v['Prec'], 'recall': v['Rec'], 'f1': v['F1'],
+
+                             # traditional errors
+                             'TP': v['TP'] / trad_divider if error_format == 'entity_ratio' else v['TP'],
+                             'FP': v['FP'] / trad_divider, 'FN': v['FN'] / trad_divider}
         elif mode == 'fair' or mode == 'weighted':
             for k, v in results['per_label'][mode].items():
-                output[k].update({'precision': v['Prec'], 'recall': v['Rec'], 'f1': v['F1'],})
+                output[k] = {# fair/weighted scores
+                             'precision': v['Prec'], 'recall': v['Rec'], 'f1': v['F1'],
+
+                             # traditional scores
+                             'trad_prec': results['per_label']['traditional'][k]['Prec'],
+                             'trad_rec': results['per_label']['traditional'][k]['Rec'],
+                             'trad_f1': results['per_label']['traditional'][k]['F1'],
 
-        # append overall scores (depending on mode)
+                             # fair/weighted errors
+                             'TP': v['TP'] / fair_divider if error_format == 'entity_ratio' else v['TP'],
+                             'FP': v['FP'] / fair_divider, 'FN': v['FN'] / fair_divider,
+                             'LE': v['LE'] / fair_divider, 'BE': v['BE'] / fair_divider, 'LBE': v['LBE'] / fair_divider}
+
+        # append overall scores
         output['overall_precision'] = results['overall'][mode]['Prec']
         output['overall_recall'] = results['overall'][mode]['Rec']
         output['overall_f1'] = results['overall'][mode]['F1']
 
-        # append overall error counts (always fair)
-        output['TP'] = results['overall']['fair']['TP'] / fair_divider if error_format == 'entity_ratio' else results['overall'][mode]['TP']
-        output['FP'] = results['overall']['fair']['FP'] / fair_divider
-        output['FN'] = results['overall']['fair']['FN'] / fair_divider
-        output['LE'] = results['overall']['fair']['LE'] / fair_divider
-        output['BE'] = results['overall']['fair']['BE'] / fair_divider
-        output['LBE'] = results['overall']['fair']['LBE'] / fair_divider
+        # append overall error counts (and trad scores if mode is fair)
+        if mode == 'traditional':
+            output['TP'] = results['overall'][mode]['TP'] / trad_divider if error_format == 'entity_ratio' else \
+            results['overall'][mode]['TP']
+            output['FP'] = results['overall'][mode]['FP'] / trad_divider
+            output['FN'] = results['overall'][mode]['FN'] / trad_divider
+        elif mode == 'fair' or 'weighted':
+            output['overall_trad_prec'] = results['overall']['traditional']['Prec']
+            output['overall_trad_rec'] = results['overall']['traditional']['Rec']
+            output['overall_trad_f1'] = results['overall']['traditional']['F1']
+            output['TP'] = results['overall'][mode]['TP'] / fair_divider if error_format == 'entity_ratio' else \
+            results['overall'][mode]['TP']
+            output['FP'] = results['overall'][mode]['FP'] / fair_divider
+            output['FN'] = results['overall'][mode]['FN'] / fair_divider
+            output['LE'] = results['overall'][mode]['LE'] / fair_divider
+            output['BE'] = results['overall'][mode]['BE'] / fair_divider
+            output['LBE'] = results['overall'][mode]['LBE'] / fair_divider
 
         return output
 
 
 def seq_to_fair(seq_sentences):
-    "Transforms input anotated sentences from seqeval span format to FairEval span format"
+    "Transforms input annotated sentences from seqeval span format to FairEval span format"
     out = []
     for seq_sentence in seq_sentences:
         sentence = []