Update app.py

app.py

@@ -174,9 +174,32 @@ with st.sidebar:
     thresholds = st.multiselect("Select MGA Cost Deviation Thresholds (%)", [0.5, 1, 2, 3, 5, 7.5, 10], default=[0.5, 1, 5])
 
 if st.button("Run MGA Optimization"):
+    # 実行して alternative_solutions を取得
     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])
+    
     if alternative_solutions:
-        st.write("Alternative Solutions with MGA:")
-        for sol in alternative_solutions:
-            st.write(f"Threshold: {sol['threshold']*100}%, Type: {sol['type']}, Technology: {sol['technology']}")
-            st.json(sol['solution'])
+        # 各しきい値ごとの最小と最大のバッテリー容量を収集
+        epsilon_values = sorted(list(set(sol['threshold'] * 100 for sol in alternative_solutions)))
+        storage_min = []
+        storage_max = []
+        
+        for epsilon in epsilon_values:
+            capacities = [sol['battery_capacity'] for sol in alternative_solutions if sol['threshold'] * 100 == epsilon]
+            storage_min.append(min(capacities))
+            storage_max.append(max(capacities))
+
+        # 可視化
+        fig, ax = plt.subplots()
+        ax.fill_between(epsilon_values, storage_min, storage_max, color='orange', alpha=0.3)  # オレンジ色の塗りつぶし
+        ax.plot(epsilon_values, storage_min, marker='o', color='orange', linestyle='-', linewidth=1.5, label='Min Storage')  # 最小値ライン
+        ax.plot(epsilon_values, storage_max, marker='o', color='orange', linestyle='-', linewidth=1.5, label='Max Storage')  # 最大値ライン
+
+        # ラベルとタイトル
+        ax.set_xlabel(r'$\epsilon$ [%]')
+        ax.set_ylabel('Storage [GW]')
+        ax.set_title('GHG -100%')
+        ax.legend()
+        ax.grid(True, linestyle='--', alpha=0.7)
+
+        # Streamlitにプロットを表示
+        st.pyplot(fig)