Implement sport-specific logic in small_field_preset for MLB, enhancing lineup management by dynamically adjusting player selection based on 'Weighted Own' values. This update improves the function's ability to handle team-specific constraints and ensures more accurate lineup generation.

global_func/small_field_preset.py

@@ -6,11 +6,29 @@ def small_field_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols
 
     for slack_var in range(1, 20):
         concat_portfolio = pd.DataFrame(columns=portfolio.columns)
+        if sport == 'MLB':
+            for team in portfolio['Stack'].unique():
+                rows_to_drop = []
+                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'])
 
-        for team in portfolio['Stack'].unique():
+                for i in range(1, len(working_portfolio)):
+                    if working_portfolio.loc[i, 'Weighted Own'] > curr_own_type_max:
+                        rows_to_drop.append(i)
+                    else:
+                        curr_own_type_max = working_portfolio.loc[i, 'Weighted Own'] + (slack_var / 20 * working_portfolio.loc[i, 'Weighted Own'])
+
+                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)
+        else:
             rows_to_drop = []
             working_portfolio = portfolio.copy()
-            working_portfolio = working_portfolio[working_portfolio['Stack'] == team].sort_values(by='Own', ascending = False)
+            working_portfolio = working_portfolio.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'])
 
@@ -22,7 +40,7 @@ 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)