p2: fig

p2/plot_completion_time_paper.py

@@ -0,0 +1,89 @@
+"""
+生成论文用的完成时间分布图 - 改进版
+"""
+
+import numpy as np
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from matplotlib import rcParams
+import pandas as pd
+
+# 设置字体
+rcParams['font.sans-serif'] = ['Arial', 'DejaVu Sans', 'Helvetica']
+rcParams['axes.unicode_minus'] = False
+rcParams['font.size'] = 11
+
+# 读取模拟结果数据
+df = pd.read_csv('/Volumes/Files/code/mm/20260130_b/p2/simulation_results.csv')
+
+# 中低饱和度配色方案 - 柔和学术风格
+colors = ['#7BAE7F', '#6A9ECF', '#9B8EC2']  # 柔和的绿、蓝、紫
+
+# 方案名称
+scenario_labels = {
+    'Scenario_A': 'Cost Priority',
+    'Scenario_B': 'Time Priority', 
+    'Scenario_C': 'Balanced'
+}
+
+# 创建图表 - 缩小尺寸以放大字体效果
+fig, axes = plt.subplots(1, 3, figsize=(10, 3.2))
+
+for idx, (scenario_key, label) in enumerate(scenario_labels.items()):
+    ax = axes[idx]
+    
+    # 获取该方案的数据
+    data = df[df['scenario'] == scenario_key]['completion_years']
+    
+    # 计算统计量
+    mean_val = np.mean(data)
+    p5 = np.percentile(data, 5)
+    p95 = np.percentile(data, 95)
+    
+    # 绘制柱状图 - 实心柱状图，增粗柱子
+    ax.hist(data, bins=15, color=colors[idx], alpha=0.9, 
+            edgecolor='white', linewidth=0.8, rwidth=0.9)
+    
+    # 设置子图标题 - 简洁的 (a) (b) (c) 标签
+    ax.set_title(f'({chr(97+idx)}) {label}', fontsize=12, fontweight='normal', pad=8)
+    
+    # 设置坐标轴标签
+    ax.set_xlabel('Completion Years', fontsize=11)
+    if idx == 0:
+        ax.set_ylabel('Frequency', fontsize=11)
+    
+    # 在图内右上角添加纯文本统计信息（无边框）
+    text_str = f'Mean: {mean_val:.1f}\n5%: {p5:.1f}\n95%: {p95:.1f}'
+    ax.text(0.97, 0.97, text_str, transform=ax.transAxes, fontsize=9,
+            verticalalignment='top', horizontalalignment='right',
+            bbox=dict(boxstyle='round,pad=0.3', facecolor='white', 
+                     edgecolor='none', alpha=0.85))
+    
+    # 网格线 - 非常淡
+    ax.grid(True, alpha=0.15, linestyle='-', linewidth=0.5)
+    
+    # 设置刻度字体大小
+    ax.tick_params(axis='both', labelsize=10)
+    
+    # 中间图 (b) 的 x 轴使用整数刻度
+    if idx == 1:
+        from matplotlib.ticker import MaxNLocator
+        ax.xaxis.set_major_locator(MaxNLocator(integer=True))
+    
+    # 简化边框
+    ax.spines['top'].set_visible(False)
+    ax.spines['right'].set_visible(False)
+
+# 调整布局
+plt.tight_layout()
+
+# 保存图片
+plt.savefig('/Volumes/Files/code/mm/20260130_b/p2/completion_time_distribution_paper.png', 
+            dpi=200, bbox_inches='tight', facecolor='white')
+plt.savefig('/Volumes/Files/code/mm/20260130_b/p2/completion_time_distribution_paper.pdf', 
+            dpi=200, bbox_inches='tight', facecolor='white')
+
+print("图表已保存:")
+print("  - completion_time_distribution_paper.png")
+print("  - completion_time_distribution_paper.pdf")

p2/plot_energy_distribution_paper.py

@@ -0,0 +1,85 @@
+"""
+生成论文用的能量分布图 - 改进版
+"""
+
+import numpy as np
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from matplotlib import rcParams
+from matplotlib.ticker import MaxNLocator
+import pandas as pd
+
+# 设置字体
+rcParams['font.sans-serif'] = ['Arial', 'DejaVu Sans', 'Helvetica']
+rcParams['axes.unicode_minus'] = False
+rcParams['font.size'] = 11
+
+# 读取模拟结果数据
+df = pd.read_csv('/Volumes/Files/code/mm/20260130_b/p2/simulation_results.csv')
+
+# 中低饱和度配色方案 - 不同于之前的绿蓝紫，使用暖色调
+colors = ['#D4936A', '#6AACAC', '#C48BB8']  # 柔和的橙、青、玫瑰
+
+# 方案名称
+scenario_labels = {
+    'Scenario_A': 'Cost Priority',
+    'Scenario_B': 'Time Priority', 
+    'Scenario_C': 'Balanced'
+}
+
+# 创建图表 - 缩小尺寸以放大字体效果
+fig, axes = plt.subplots(1, 3, figsize=(10, 3.2))
+
+for idx, (scenario_key, label) in enumerate(scenario_labels.items()):
+    ax = axes[idx]
+    
+    # 获取该方案的数据
+    data = df[df['scenario'] == scenario_key]['total_energy_pj']
+    
+    # 计算统计量
+    mean_val = np.mean(data)
+    p5 = np.percentile(data, 5)
+    p95 = np.percentile(data, 95)
+    
+    # 绘制柱状图 - 实心柱状图，增粗柱子
+    ax.hist(data, bins=15, color=colors[idx], alpha=0.9, 
+            edgecolor='white', linewidth=0.8, rwidth=0.9)
+    
+    # 设置子图标题 - 简洁的 (a) (b) (c) 标签
+    ax.set_title(f'({chr(97+idx)}) {label}', fontsize=12, fontweight='normal', pad=8)
+    
+    # 设置坐标轴标签
+    ax.set_xlabel('Total Energy (PJ)', fontsize=11)
+    if idx == 0:
+        ax.set_ylabel('Frequency', fontsize=11)
+    
+    # 在图内右上角添加纯文本统计信息（无边框）
+    text_str = f'Mean: {mean_val:.0f}\n5%: {p5:.0f}\n95%: {p95:.0f}'
+    ax.text(0.97, 0.97, text_str, transform=ax.transAxes, fontsize=9,
+            verticalalignment='top', horizontalalignment='right',
+            bbox=dict(boxstyle='round,pad=0.3', facecolor='white', 
+                     edgecolor='none', alpha=0.85))
+    
+    # 网格线 - 非常淡
+    ax.grid(True, alpha=0.15, linestyle='-', linewidth=0.5)
+    
+    # 设置刻度字体大小
+    ax.tick_params(axis='both', labelsize=10)
+    
+    # 简化边框
+    ax.spines['top'].set_visible(False)
+    ax.spines['right'].set_visible(False)
+
+# 调整布局
+plt.tight_layout()
+
+# 保存图片
+plt.savefig('/Volumes/Files/code/mm/20260130_b/p2/energy_distribution_paper.png', 
+            dpi=200, bbox_inches='tight', facecolor='white')
+plt.savefig('/Volumes/Files/code/mm/20260130_b/p2/energy_distribution_paper.pdf', 
+            dpi=200, bbox_inches='tight', facecolor='white')
+
+print("图表已保存:")
+print("  - energy_distribution_paper.png")
+print("  - energy_distribution_paper.pdf")