Update app.py

app.py

@@ -2,10 +2,8 @@ import streamlit as st
 import requests
 import pandas as pd
 import pulp
-import plotly.graph_objs as go
 import plotly.express as px
 import numpy as np
-import matplotlib.pyplot as plt
 
 # Renewable energy data fetch function
 def get_renewable_energy_data(city_code):
@@ -205,13 +203,6 @@ if st.button("Run MGA Optimization"):
     alternative_solutions = optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wind_cost, river_cost, battery_cost, yearly_demand, solar_range, wind_range, river_range, offshore_wind_range, [t / 100 for t in thresholds], selected_technologies)
     
     if alternative_solutions:
-        # Cost breakdown visualization
-        cost_data = [{'threshold': sol['threshold'] * 100, 'type': sol['type'], 'technology': sol['technology'], 'total_cost': sol['total_cost']} for sol in alternative_solutions]
-        cost_df = pd.DataFrame(cost_data)
-        fig_cost = px.bar(cost_df, x='threshold', y='total_cost', color='technology', title="Cost Breakdown by Technology and Threshold")
-        fig_cost.update_layout(xaxis_title='Threshold (%)', yaxis_title='Total Cost (¥)')
-        st.plotly_chart(fig_cost, use_container_width=True)
-
         # Display capacity distribution using violin plots
         fig_violin = plot_capacity_distribution(alternative_solutions, selected_technologies)
         st.plotly_chart(fig_violin, use_container_width=True)