Update preset options in app.py to improve lineup generation accuracy. Changed 'Large Field (Finish Percentile / Edge)' to 'Large Field (Manage Similarity)' and adjusted corresponding logic in the form submission process.

app.py

@@ -1111,13 +1111,13 @@ with tab2:
             with st.expander('Presets'):
                 st.info("Still heavily in testing here, I'll announce when they are ready for use.")
                 with st.form(key='Small Field Preset'):
-                    preset_choice = st.selectbox("Preset", options=['Small Field (Heavy Own)', 'Large Field (Finish Percentile / Edge)', 'Hedge Chalk (Manage Leverage)'], index=0)
+                    preset_choice = st.selectbox("Preset", options=['Small Field (Heavy Own)', 'Large Field (Manage Similarity)', 'Hedge Chalk (Manage Leverage)'], index=0)
                     lineup_target = st.number_input("Lineups to produce", value=150, min_value=1, step=1)
                     submitted = st.form_submit_button("Submit")
                     if submitted:
                         if preset_choice == 'Small Field (Heavy Own)':
                             parsed_frame = small_field_preset(st.session_state['working_frame'], lineup_target, excluded_cols)
-                        elif preset_choice == 'Large Field (Finish Percentile / Edge)':
+                        elif preset_choice == 'Large Field (Manage Similarity)':
                             parsed_frame = large_field_preset(st.session_state['working_frame'], lineup_target, excluded_cols)
                         elif preset_choice == 'Hedge Chalk (Manage Leverage)':
                             parsed_frame = hedging_preset(st.session_state['working_frame'], lineup_target, st.session_state['projections_df'])

global_func/large_field_preset.py

@@ -7,6 +7,7 @@ def large_field_preset(portfolio: pd.DataFrame, lineup_target: int, exclude_cols
     
     concat_portfolio = portfolio.copy()
     concat_portfolio = concat_portfolio.sort_values(by='Similarity Score', ascending=True).reset_index(drop=True)
+    concat_portfolio = concat_portfolio[concat_portfolio['Lineup Edge'] > 0]
 
     # Calculate target similarity scores for linear progression
     similarity_floor = concat_portfolio['Similarity Score'].min()