Reintroduce trimming dictionary in app.py: move the calculation of maximum values for ownership types back into the submission logic, ensuring accurate threshold inputs during portfolio updates and maintaining consistency in the trimming process.

app.py

@@ -881,13 +881,6 @@ with tab2:
                           sum(map_dict['own_map'].get(player, 0) for player in row.iloc[1:]),
                 axis=1
             )
-        trimming_dict_maxes = {
-            'Own': st.session_state['portfolio']['Own'].max(),
-            'Geomean': st.session_state['portfolio']['Geomean'].max(),
-            'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
-            'median': st.session_state['portfolio']['median'].max(),
-            'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
-        }
         col1, col2 = st.columns([2, 8])
         with col1:
             with st.expander('Macro Filter Options'):
@@ -943,6 +936,13 @@ with tab2:
                     if submitted:
                         st.write('initiated')
                         st.session_state['portfolio'] = predict_dupes(st.session_state['portfolio'], map_dict, site_var, type_var, Contest_Size, strength_var, sport_var)
+                        trimming_dict_maxes = {
+                            'Own': st.session_state['portfolio']['Own'].max(),
+                            'Geomean': st.session_state['portfolio']['Geomean'].max(),
+                            'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
+                            'median': st.session_state['portfolio']['median'].max(),
+                            'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
+                        }
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Dupes'] <= max_dupes]
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] >= min_salary]
                         st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= max_salary]
@@ -978,6 +978,13 @@ with tab2:
         with col2:
             st.write('initiated')
             st.session_state['portfolio'] = predict_dupes(st.session_state['portfolio'], map_dict, site_var, type_var, Contest_Size, strength_var, sport_var)
+            trimming_dict_maxes = {
+                            'Own': st.session_state['portfolio']['Own'].max(),
+                            'Geomean': st.session_state['portfolio']['Geomean'].max(),
+                            'Weighted Own': st.session_state['portfolio']['Weighted Own'].max(),
+                            'median': st.session_state['portfolio']['median'].max(),
+                            'Finish_percentile': st.session_state['portfolio']['Finish_percentile'].max()
+                        }
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['Dupes'] <= max_dupes]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] >= min_salary]
             st.session_state['portfolio'] = st.session_state['portfolio'][st.session_state['portfolio']['salary'] <= max_salary]