Refactor filtering logic in distribute_preset function to improve handling of 'Finish_percentile' thresholds. Introduced a variable for finish threshold to enhance code readability and maintain accurate portfolio selection across all finishing ranges.

global_func/distribute_preset.py

@@ -6,14 +6,16 @@ def distribute_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols:
         concat_portfolio = pd.DataFrame(columns=portfolio.columns)
 
         for finishing_range in range(1, 20):
+            finish_threshold = (finishing_range / 100)
             rows_to_drop = []
             working_portfolio = portfolio.copy()
             if finishing_range == 1:
-                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= (finishing_range / 100)]
+                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= finish_threshold]
             elif finishing_range == 20:
-                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] >= ((finishing_range - 1) / 100)]
+                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] >= (finish_threshold - 1)]
             else:
-                working_portfolio = working_portfolio[(working_portfolio['Finish_percentile'] <= (finishing_range / 100)) & (working_portfolio['Finish_percentile'] >= ((finishing_range - 1) / 100))]
+                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] <= finish_threshold]
+                working_portfolio = working_portfolio[working_portfolio['Finish_percentile'] >= (finish_threshold - 1)]
             working_portfolio = working_portfolio.sort_values(by='median', 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'])