Update dupes calculation in predict_dupes.py by adjusting salary thresholds from 59700 and 49700 to 60000 and 50000 respectively, enhancing the accuracy of duplicate predictions across different contest sizes.

global_func/predict_dupes.py

@@ -335,7 +335,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
             )
             
             # Calculate dupes formula
-            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (59700 - portfolio['Own'])) / 100) - ((59700 - portfolio['salary']) / 100)
+            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((59700 - portfolio['salary']) / 100)
             portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
             
             # Round and handle negative values
@@ -366,7 +366,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                 lambda row: sum(1 for player in row if player in top_x_ownership_keys), axis=1
             )
             
-            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (59700 - portfolio['Own'])) / 100) - ((59700 - portfolio['salary']) / 100)
+            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((59700 - portfolio['salary']) / 100)
             portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
             # Round and handle negative values
             portfolio['Dupes'] = np.where(
@@ -445,7 +445,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
             )
             
             # Calculate dupes formula
-            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (49700 - portfolio['Own'])) / 100) - ((49700 - portfolio['salary']) / 100)
+            portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 100) - ((49700 - portfolio['salary']) / 100)
             portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
 
             # Round and handle negative values
@@ -496,7 +496,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                 )
                 
                 # Calculate dupes formula
-                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (49700 - portfolio['Own'])) / 50) - ((49700 - portfolio['salary']) / 50)
+                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 50) - ((49700 - portfolio['salary']) / 50)
                 portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
 
                 # Round and handle negative values
@@ -549,7 +549,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                 )
 
                 # Calculate dupes formula
-                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (49700 - portfolio['Own'])) / 50) - ((49700 - portfolio['salary']) / 50)
+                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 50) - ((49700 - portfolio['salary']) / 50)
                 portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
 
                 # Round and handle negative values
@@ -579,7 +579,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
                     lambda row: sum(1 for player in row if player in top_x_ownership_keys), axis=1
                 )
                 
-                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (49700 - portfolio['Own'])) / 100) - ((49700 - portfolio['salary']) / 100)
+                portfolio['dupes_calc'] = (portfolio['avg_own_rank'] / 1000) * (Contest_Size / 100) + ((portfolio['salary'] - (50000 - portfolio['Own'])) / 100) - ((49700 - portfolio['salary']) / 100)
                 portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * portfolio['top_x_presence']
                 # Round and handle negative values
                 portfolio['Dupes'] = np.where(