Refactor dupes calculation in predict_dupes function to correct ownership ratio adjustments, ensuring accurate predictions based on ownership metrics and Contest_Size. This update enhances the overall accuracy of duplicate predictions.

global_func/predict_dupes.py

@@ -328,7 +328,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
             portfolio['avg_own_rank'] = portfolio[dup_count_columns].mean(axis=1)
             
             # Calculate dupes formula
-            portfolio['dupes_calc'] = ((portfolio['own_product'] * 100) * portfolio['avg_own_rank']) * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * Contest_Size + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((60000 - portfolio['salary']) / 100)
+            portfolio['dupes_calc'] = (portfolio['own_product'] * portfolio['avg_own_rank']) * (portfolio['Own'] / 100) * Contest_Size + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((60000 - portfolio['salary']) / 100)
             portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier
             
             # Round and handle negative values
@@ -527,7 +527,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                 print(portfolio[['Own', 'own_product', 'own_average', 'own_sum', 'avg_own_rank']].head(10))
                 
                 # Calculate dupes formula
-                portfolio['dupes_calc'] = (portfolio['own_product'] * portfolio['avg_own_rank']) * Contest_Size + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 100) - ((50000 - portfolio['salary']) / 100)
+                portfolio['dupes_calc'] = (portfolio['own_product'] * portfolio['avg_own_rank']) * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * Contest_Size + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 100) - ((50000 - portfolio['salary']) / 100)
                 portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier
 
                 # Round and handle negative values