布线问题python
时间: 2023-11-28 09:45:27 浏览: 50
根据提供的引用内容,可以看出这是一个关于无网格线探索算法的问题,而不是布线问题。下面是对该算法的介绍和Python代码实现:
无网格线探索算法是一种基于启发式规则的路径规划算法,它可以在不需要网格化地图的情况下,实现路径规划。该算法的基本思想是,将地图看作一个连续的空间,通过探索线的方式,寻找起点到终点的最短路径。在探索过程中,通过启发式规则来避开障碍物,实现路径规划。
以下是Python代码实现:
```python
import math
# 定义探索线类
class Line:
def __init__(self, start, end):
self.start = start
self.end = end
self.length = math.sqrt((end[0]-start[0])**2 + (end[1]-start[1])**2)
# 定义无网格线探索算法类
class PathPlanning:
def __init__(self, map, start, end):
self.map = map
self.start = start
self.end = end
self.lines = []
self.path = []
# 定义探索线生成函数
def generate_lines(self):
# 生成水平和垂直方向的探索线
for i in range(len(self.map)):
for j in range(len(self.map[0])):
if self.map[i][j] == 0:
if j < len(self.map[0])-1 and self.map[i][j+1] == 0:
self.lines.append(Line((i,j), (i,j+1)))
if i < len(self.map)-1 and self.map[i+1][j] == 0:
self.lines.append(Line((i,j), (i+1,j)))
# 生成斜向的探索线
for i in range(len(self.map)):
for j in range(len(self.map[0])):
if self.map[i][j] == 0:
if i < len(self.map)-1 and j < len(self.map[0])-1 and self.map[i+1][j+1] == 0:
self.lines.append(Line((i,j), (i+1,j+1)))
if i < len(self.map)-1 and j > 0 and self.map[i+1][j-1] == 0:
self.lines.append(Line((i,j), (i+1,j-1)))
# 定义启发式规则函数
def heuristic(self, line):
# 计算探索线的中点
mid = ((line.start[0]+line.end[0])/2, (line.start[1]+line.end[1])/2)
# 计算中点到终点的距离
distance = math.sqrt((self.end[0]-mid[0])**2 + (self.end[1]-mid[1])**2)
# 计算探索线的长度
length = line.length
# 返回启发式值
return distance + length
# 定义路径规划函数
def plan_path(self):
# 生成探索线
self.generate_lines()
# 将起点加入路径
self.path.append(self.start)
# 循环直到找到终点
while self.path[-1] != self.end:
# 初始化最小启发式值和最小启发式值对应的探索线
min_heuristic = float('inf')
min_line = None
# 遍历所有探索线,找到启发式值最小的探索线
for line in self.lines:
if line.start == self.path[-1]:
h = self.heuristic(line)
if h < min_heuristic:
min_heuristic = h
min_line = line
# 将最小启发式值对应的探索线的终点加入路径
self.path.append(min_line.end)
# 输出路径
print('路径为:', self.path)
# 测试
map = [[0,0,1,0,0,0,0],
[0,0,1,1,0,0,0],
[0,0,0,1,0,0,0],
[0,0,0,1,0,0,0],
[0,0,0,1,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0]]
start = (3,2)
end = (4,6)
pp = PathPlanning(map, start, end)
pp.plan_path()
```