Update reassess_edge function to include maps_dict parameter for improved player ownership mapping in app.py, enhancing edge reassessment logic.

app.py

@@ -1608,7 +1608,7 @@ with tab2:
                         
                         print(st.session_state['export_base'].head(10))
                         # st.session_state['export_base'] = predict_dupes(st.session_state['export_base'], st.session_state['map_dict'], site_var, type_var, Contest_Size, strength_var, sport_var)
-                        st.session_state['export_base'] = reassess_edge(st.session_state['export_base'], prior_frame, Contest_Size, salary_max)
+                        st.session_state['export_base'] = reassess_edge(st.session_state['export_base'], prior_frame, st.session_state['map_dict'], Contest_Size, salary_max)
                         st.session_state['export_merge'] = st.session_state['export_base'].copy()
                         
         with st.container():

global_func/reassess_edge.py

@@ -65,7 +65,7 @@ def reassess_lineup_edge(row: pd.Series, Contest_Size: int) -> float:
     
     return row['Lineup Edge'] - row['Lineup Edge'].mean()
 
-def reassess_edge(refactored_frame: pd.DataFrame, original_frame: pd.DataFrame, Contest_Size: int, salary_max: int) -> pd.DataFrame:
+def reassess_edge(refactored_frame: pd.DataFrame, original_frame: pd.DataFrame, maps_dict: dict, Contest_Size: int, salary_max: int) -> pd.DataFrame:
     orig_df = original_frame.copy()
     orig_df = orig_df.reset_index(drop=True)
     refactored_df = refactored_frame.copy()
@@ -81,6 +81,9 @@ def reassess_edge(refactored_frame: pd.DataFrame, original_frame: pd.DataFrame,
     num_players = salary_col_index
     own_columns = [f'player_{i}_own' for i in range(1, num_players + 1)]
 
+    for col in range(num_players):
+        refactored_df[f'player_{col}_own'] = refactored_df.iloc[:,col].map(maps_dict['own_map']).astype('float32') / 100
+
     for lineups in change_mask.index:
         refactored_df.loc[lineups, 'Dupes'] = reassess_dupes(refactored_df.loc[lineups, :], salary_max)
         refactored_df.loc[lineups, 'Finish_percentile'] = refactored_df.loc[lineups, 'Finish_percentile']