Add debug print statements in 'predict_dupes.py' to log key variables during calculation, aiding in the validation of the dupes calculation process.

global_func/predict_dupes.py

@@ -189,6 +189,8 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
         portfolio['dupes_calc'] = (portfolio['own_product'] * portfolio['avg_own_rank']) * Contest_Size + ((portfolio['salary'] - (max_salary - portfolio['Own'])) / 100) - ((max_salary - portfolio['salary']) / 100)
         portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier * (portfolio['Own'] / (120 + (Contest_Size / 1000)))
 
+        
+
         # Round and handle negative values
         portfolio['Dupes'] = np.where(
             portfolio['salary'] == max_salary,
@@ -200,6 +202,13 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
             0, 
             np.round(portfolio['Dupes'], 0) - 1
         )
+
+        print(portfolio['own_product'])
+        print(portfolio['avg_own_rank'])
+        print(portfolio['salary'])
+        print(portfolio['Own'])
+        print(portfolio['dupes_calc'])
+        print(portfolio['Dupes'])
     elif type_var == 'Classic':
         if sport_var == 'CS2':
             dup_count_columns = ['CPT_Own_percent_rank', 'FLEX1_Own_percent_rank', 'FLEX2_Own_percent_rank', 'FLEX3_Own_percent_rank', 'FLEX4_Own_percent_rank', 'FLEX5_Own_percent_rank']