added hightlights

app.py

@@ -209,16 +209,30 @@ st.write(f"""We evaluate the robustness of the LLM by assessing the variation in
 # st.write(f"ProbTypos: {other_info_dict['ProbTypos_description']}")
 # st.write(f"MaxTypo: {other_info_dict['MaxTypo_description']}")
 
+t_pert_df_global_merged = []
 for t_opt in options:
     st.write('Prompt used : ', t_opt)
     t_pert_df_global = result_processor_obj_dict[t_opt].get_global_perturbers_df()
+    t_pert_df_global['Prompt option'] = processed_t_opt_dict[t_opt]
+    t_pert_df_global['Prompt'] = t_pert_df_global['Perturbation family'] + ' - ' + processed_t_opt_dict[t_opt]
 
     t_pert_fig = px.line(t_pert_df_global, x="Levels", y="Performance", color='Perturbation family')
     t_pert_fig.update_xaxes(tickmode='linear', dtick=1)
-
+    t_pert_df_global_merged += [t_pert_df_global]
 
     st.plotly_chart(t_pert_fig, theme="streamlit", use_container_width=True)
 
+st.write('---')
+st.write('The following plot illustrates the variation in performance across perturbation families and prompts.')
+t_pert_df_global_merged_df = pd.concat(t_pert_df_global_merged, axis=0)
+t_pert_df_global_merged_df_2 = t_pert_df_global_merged_df[['Prompt option', 'Perturbation family','Levels', 'Performance']]
+t_pert_df_global_merged_df_2.set_index(t_pert_df_global_merged_df_2.columns[0])
+# st.dataframe(t_pert_df_global_merged_df_2)
+
+temp_merged_fig = px.line(t_pert_df_global_merged_df, x="Levels", y="Performance", color='Prompt')
+temp_merged_fig.update_xaxes(tickmode='linear', dtick=1)
+st.plotly_chart(temp_merged_fig, theme="streamlit", use_container_width=True)
+
 
 # %%
 st.header("Characteristic results")