p1: fig

p1/pareto_optimization.py

@@ -796,6 +796,60 @@ def plot_combined_range_analysis(
     return fig
 
 
+def plot_marginal_benefit_only(
+    df: pd.DataFrame,
+    knee_analysis: Dict,
+    save_path: str = '/Volumes/Files/code/mm/20260130_b/p1/marginal_benefit.png'
+):
+    """
+    仅绘制边际收益图（右下角图的简化版）
+    - 长宽比 0.618
+    - 中低饱和度色系
+    - 无标题
+    - 无 Elevator share 线
+    - Y轴范围 450-600
+    """
+    # 使用0.618黄金比例，缩小尺寸以放大字体
+    fig_width = 8
+    fig_height = fig_width * 0.618
+    fig, ax = plt.subplots(figsize=(fig_width, fig_height))
+    
+    T = df['years'].values
+    E = df['energy_PJ'].values
+    
+    # 边际节省
+    dE_dT = np.gradient(E, T)
+    marginal_savings = -dE_dT  # 每多1年节省的能量
+    
+    # 中低饱和度色系
+    color_main = '#4A6FA5'  # 灰蓝色
+    color_fill = '#A8C0D8'  # 浅灰蓝
+    color_vline = '#B85450'  # 暗砖红
+    
+    # 边际收益曲线
+    ax.plot(T, marginal_savings, color=color_main, linewidth=2.5, label='Marginal Saving (PJ/year)')
+    ax.fill_between(T, marginal_savings, alpha=0.25, color=color_fill)
+    
+    # 标记推荐点
+    rec = knee_analysis['recommended']
+    ax.axvline(x=rec['years'], color=color_vline, linestyle=':', linewidth=2,
+               label=f'Recommended: {rec["years"]:.0f}y')
+    
+    ax.set_xlabel('Completion Time (years)', fontsize=11)
+    ax.set_ylabel('Marginal Energy Saving (PJ/year)', fontsize=11)
+    ax.legend(loc='upper right', fontsize=9)
+    ax.grid(True, alpha=0.3)
+    
+    # 设置Y轴范围 450-600
+    ax.set_ylim(450, 600)
+    
+    plt.tight_layout()
+    plt.savefig(save_path, dpi=150, bbox_inches='tight')
+    print(f"边际收益图已保存至: {save_path}")
+    
+    return fig
+
+
 def plot_combined_decision(
     df: pd.DataFrame,
     knee_analysis: Dict,