From e7e12745d1e11a8d2d02009735a0c1069f655848 Mon Sep 17 00:00:00 2001
From: dmy <dmy@dmy.com>
Date: Thu, 1 Jan 2026 11:55:05 +0800
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---
 main.py | 46 ++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 38 insertions(+), 8 deletions(-)

diff --git a/main.py b/main.py
index 4a49c84..0ac9c25 100644
--- a/main.py
+++ b/main.py
@@ -13,6 +13,10 @@ import argparse
 plt.rcParams['font.sans-serif'] = ['Microsoft YaHei', 'SimHei', 'Arial']
 plt.rcParams['axes.unicode_minus'] = False
 
+# 常量定义
+VOLTAGE_LEVEL = 66000  # 66kV
+POWER_FACTOR = 0.95
+
 # 1. 生成风电场数据（实际应用中替换为真实坐标）
 def generate_wind_farm_data(n_turbines=30, seed=42, layout='random', spacing=800):
     """
@@ -381,10 +385,6 @@ def design_with_capacitated_sweep(turbines, substation, cable_specs=None):
     
     return cluster_connections + substation_connections, turbines
 
-# 常量定义
-VOLTAGE_LEVEL = 66000  # 66kV
-POWER_FACTOR = 0.95
-
 def get_max_cable_capacity_mw(cable_specs=None):
     """
     计算给定电缆规格中能够承载的最大功率 (单位: MW)。
@@ -616,8 +616,8 @@ def export_to_dxf(turbines, substation, connections_details, filename):
         if layer_name not in doc.layers:
             doc.layers.add(layer_name)
             
-        # 绘制直线
-        msp.add_line(p1, p2, dxfattribs={'layer': layer_name})
+        # 绘制二维多段线
+        msp.add_lwpolyline([p1, p2], dxfattribs={'layer': layer_name})
         
         # 添加电缆型号文字（可选，在线的中点）
         # mid_x = (p1[0] + p2[0]) / 2
@@ -824,7 +824,7 @@ def compare_design_methods(excel_path=None, n_clusters_override=None):
     # 这里我们导出Sector Clustering的结果
     export_to_dxf(clustered_turbines, substation, kmeans_evaluation['details'], dxf_filename)
     
-    plt.show() 
+    # plt.show() 
     
     # 打印详细结果
     print(f"\n===== 海上风电场设计方案比较 ({'导入数据' if excel_path else '自动生成'}) =====")
@@ -833,6 +833,36 @@ def compare_design_methods(excel_path=None, n_clusters_override=None):
         print(f"  总成本: ¥{eval_data['total_cost']:,.2f} ({eval_data['total_cost']/10000:.2f}万元)")
         print(f"  预估总损耗: {eval_data['total_loss']:.2f} kW")
         print(f"  连接数量: {eval_data['num_connections']}")
+
+    # Calculate additional metrics for K-means (Capacitated Sweep)
+    print("\n===== K-Means (Capacitated Sweep) 详细统计 =====")
+    
+    # 1. 总回路数
+    # The 'cluster' column in clustered_turbines holds the circuit ID.
+    num_circuits = clustered_turbines['cluster'].nunique()
+    print(f"总回路数: {num_circuits}")
+    
+    # 2. 每种型号电缆长度
+    cable_lengths = defaultdict(float)
+    max_current = 0.0
+    
+    for conn in kmeans_evaluation['details']:
+        # Length
+        section = conn['cable']['cross_section']
+        length = conn['length']
+        cable_lengths[section] += length
+        
+        # Max Current
+        current = conn['cable']['current']
+        if current > max_current:
+            max_current = current
+            
+    print("每种型号电缆的长度:")
+    for section in sorted(cable_lengths.keys()):
+        print(f"  {section}mm²: {cable_lengths[section]:.2f} m")
+        
+    # 3. 最大支路电流
+    print(f"最大支路电流: {max_current:.2f} A")
     
     return results
 
@@ -850,4 +880,4 @@ if __name__ == "__main__":
     
     # 3. 运行比较
     # 如果本地没有excel文件，将自动回退到生成数据模式
-    compare_design_methods(excel_path, n_clusters_override=args.clusters)
+    compare_design_methods(excel_path, n_clusters_override=args.clusters)
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