Refactor SE Score calculation in predict_dupes function to adjust the order of operations, ensuring player diversity is factored in after the score computation. This change enhances the accuracy of the SE Score while maintaining code clarity.

global_func/predict_dupes.py

@@ -447,8 +447,8 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
     # Calculate similarity score based on actual player selection
     portfolio['Diversity'] = calculate_player_similarity_score_chunked(portfolio, player_columns)
 
-    portfolio['SE Score'] = ((portfolio['median'] - portfolio['median'].mean()) * (portfolio['Weighted Own'] - portfolio['Weighted Own'].mean())) * (1 - portfolio['Diversity'])
-    portfolio['SE Score'] = (np.tanh(portfolio['SE Score'] / portfolio['SE Score'].std()) + 1) / 2
+    portfolio['SE Score'] = ((portfolio['median'] - portfolio['median'].mean()) * (portfolio['Weighted Own'] - portfolio['Weighted Own'].mean()))
+    portfolio['SE Score'] = ((np.tanh(portfolio['SE Score'] / portfolio['SE Score'].std()) + 1) / 2) * (1 - portfolio['Diversity'])
     # check_portfolio = portfolio.copy()
     portfolio = portfolio.drop(columns=dup_count_columns)
     portfolio = portfolio.drop(columns=own_columns)