Refactor sorting logic in small_field_preset.py to ensure accurate portfolio filtering by utilizing 'Own' for sorting. This change enhances the portfolio distribution process by maintaining consistency in data handling across teams.

global_func/distribute_preset.py

@@ -8,7 +8,7 @@ def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
         for team in portfolio['Stack'].unique():
             rows_to_drop = []
             working_portfolio = portfolio.copy()
-            working_portfolio = working_portfolio[working_portfolio['Stack'] == team].sort_values(by='Similarity Score', ascending = True)
+            working_portfolio = working_portfolio[working_portfolio['Stack'] == team].sort_values(by='median', ascending = False)
             working_portfolio = working_portfolio.reset_index(drop=True)
             curr_own_type_max = working_portfolio.loc[0, 'Similarity Score'] + (slack_var / 20 * working_portfolio.loc[0, 'Similarity Score'])
 

global_func/small_field_preset.py

@@ -7,8 +7,8 @@ def small_field_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols
 
         for team in portfolio['Stack'].unique():
             rows_to_drop = []
-            working_portfolio = portfolio[portfolio['Stack'] == team].sort_values(by='Own', ascending = False).reset_index(drop=True)
-            working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= .10]
+            working_portfolio = portfolio.copy()
+            working_portfolio = working_portfolio[working_portfolio['Stack'] == team].sort_values(by='Own', ascending = False)
             working_portfolio = working_portfolio.reset_index(drop=True)
             curr_own_type_max = working_portfolio.loc[0, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[0, 'Weighted Own'])
 
@@ -20,6 +20,7 @@ def small_field_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols
 
             working_portfolio = working_portfolio.drop(rows_to_drop).reset_index(drop=True)
             concat_portfolio = pd.concat([concat_portfolio, working_portfolio])
+            
         if len(concat_portfolio) >= lineup_target:
             return concat_portfolio.sort_values(by='Own', ascending=False).head(lineup_target)