Remove debug print statement from calculate_weighted_ownership_single_row and fix geomean calculation in reassess_edge function for improved accuracy in ownership metrics.

global_func/reassess_edge.py

@@ -21,7 +21,6 @@ def calculate_weighted_ownership_single_row(row_ownerships):
     """
 
     ownership_values = pd.to_numeric(row_ownerships.values, errors='coerce')
-    print(ownership_values)
     ownership_values = np.where(np.isnan(ownership_values), 0, ownership_values) / 100
     
     # Calculate mean
@@ -78,6 +77,6 @@ def reassess_edge(refactored_frame: pd.DataFrame, original_frame: pd.DataFrame,
         refactored_df.loc[lineups, 'Win%'] = refactored_df.loc[lineups, 'Win%']
         refactored_df.loc[lineups, 'Edge'] = reassess_lineup_edge(refactored_df.loc[lineups, :], Contest_Size)
         refactored_df.loc[lineups, 'Weighted Own'] = calculate_weighted_ownership_single_row(refactored_df.loc[lineups, own_columns])
-        refactored_df.loc[lineups, 'Geomean'] = np.power((refactored_df.loc[lineups, own_columns] * 100).product(axis=1), 1 / len(own_columns))
+        refactored_df.loc[lineups, 'Geomean'] = np.power((refactored_df.loc[lineups, own_columns] * 100).product(), 1 / len(own_columns))
 
     return refactored_df