59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
import matplotlib.pyplot as plt
|
||
import matplotlib.patches as patches
|
||
import json
|
||
|
||
def visualize_solution(row_boundaries, col_boundaries, car_paths, W, H):
|
||
plt.rcParams['font.family'] = ['sans-serif']
|
||
plt.rcParams['font.sans-serif'] = ['SimHei']
|
||
fig, ax = plt.subplots()
|
||
ax.set_xlim(0, W)
|
||
ax.set_ylim(H, 0) # 调整y轴方向，原点在左上角
|
||
ax.set_title("区域划分与车-机-巢系统覆盖")
|
||
ax.set_xlabel("区域宽度")
|
||
ax.set_ylabel("区域高度")
|
||
|
||
# 定义若干颜色以区分不同系统（系统编号从0开始）
|
||
colors = ['red', 'blue', 'green', 'orange', 'purple', 'cyan', 'magenta']
|
||
|
||
# 绘制区域中心
|
||
region_center = (H / 2.0, W / 2.0)
|
||
ax.plot(region_center[1], region_center[0],
|
||
'ko', markersize=8, label="区域中心")
|
||
|
||
# 绘制行分割边界
|
||
for row in row_boundaries:
|
||
ax.axhline(y=row * H, color='black', linestyle='--')
|
||
|
||
# 绘制列分割边界
|
||
for col in col_boundaries:
|
||
ax.axvline(x=col * W, color='black', linestyle='--')
|
||
|
||
# 绘制每辆车的轨迹
|
||
for system_id, path in enumerate(car_paths):
|
||
path = [(region_center[0], region_center[1])] + path + [(region_center[0], region_center[1])]
|
||
y, x = zip(*path)
|
||
ax.plot(x, y, marker='o', color=colors[int(system_id) % len(colors)], label=f"系统 {system_id}")
|
||
|
||
# 添加图例
|
||
ax.legend()
|
||
plt.show()
|
||
|
||
if __name__ == "__main__":
|
||
import yaml
|
||
|
||
# 读取参数
|
||
with open('params3.yml', 'r', encoding='utf-8') as file:
|
||
params = yaml.safe_load(file)
|
||
|
||
H = params['H']
|
||
W = params['W']
|
||
|
||
# 读取最佳方案的JSON文件
|
||
with open(r'solutions\trav_ga_params3_parallel.json', 'r', encoding='utf-8') as f:
|
||
best_solution = json.load(f)
|
||
|
||
row_boundaries = best_solution['row_boundaries']
|
||
col_boundaries = best_solution['col_boundaries']
|
||
car_paths = best_solution['car_paths']
|
||
|
||
visualize_solution(row_boundaries, col_boundaries, car_paths, W, H) |