def astar(start, end): # 获取起点和终点的经纬度 start_loc = get_location(start) end_loc = get_location(end)
时间: 2023-12-06 17:40:50 浏览: 36
在这段代码中,你定义了一个A*算法函数,该函数接受起点和终点的位置作为参数,并返回一条从起点到终点的最短路径。在这个函数中,你首先使用`get_location()`函数获取起点和终点的经纬度(也就是位置信息)。`get_location()`函数可能是一个自定义的函数,用于从某个地图API或其他来源中获取给定地点的位置信息。获取到起点和终点的位置信息后,你可以使用A*算法来搜索最短路径。
相关问题
import Astar # 定义起点和终点的坐标 start_cor = (19, 0) end_cor = (1, 20) # 定义路径上的路标点 waypoints = [(5, 15), (5, 1), (9, 3), (11, 17), (7, 19), (15, 19), (13, 1), (15, 5)] # 定义计算两个点之间距离的函数 def distance(_from, _to): x1, y1 = _from x2, y2 = _to # 使用 Astar 算法寻路,计算出两个点之间的距离 dist = Astar.get_dist(x1, y1, x2, y2) return dist 其中distance函数返回的是两个坐标之间的距离将以上代码改进以实现从坐标start_cor开始经过waypoint中的所有坐标最后到达终点坐标end_co,要使整个路径最短并打印出经过的每一个坐标
好的,我们可以使用 A* 算法来计算最短路径。以下是改进后的代码:
```python
import Astar
# 定义起点和终点的坐标
start_cor = (19, 0)
end_cor = (1, 20)
# 定义路径上的路标点
waypoints = [(5, 15), (5, 1), (9, 3), (11, 17), (7, 19), (15, 19), (13, 1), (15, 5)]
# 定义计算两个点之间距离的函数
def distance(_from, _to):
x1, y1 = _from
x2, y2 = _to
# 使用 A* 算法寻路,计算出两个点之间的距离
dist = Astar.get_dist(x1, y1, x2, y2)
return dist
# 定义计算整个路径的距离的函数
def get_path_distance(path):
dist = 0
for i in range(len(path)-1):
dist += distance(path[i], path[i+1])
return dist
# 定义寻找最短路径的函数
def find_shortest_path(start, end, waypoints):
# 初始化路径
path = [start]
# 依次加入路标点
for waypoint in waypoints:
# 寻找当前位置到下一个路标点之间的最短路径
sub_path = Astar.find_path(path[-1][0], path[-1][1], waypoint[0], waypoint[1])
# 将最短路径上的所有点加入路径中
path += sub_path[1:]
# 寻找最后一个路标点到终点之间的最短路径
sub_path = Astar.find_path(path[-1][0], path[-1][1], end[0], end[1])
# 将最短路径上的所有点加入路径中
path += sub_path[1:]
# 计算路径长度
dist = get_path_distance(path)
return path, dist
# 寻找最短路径
path, dist = find_shortest_path(start_cor, end_cor, waypoints)
# 打印路径上的所有点
print("路径上的坐标点:")
for point in path:
print(point)
# 打印路径长度
print("路径长度:", dist)
```
这段代码会输出路径上的所有点和路径长度。希望这可以帮助你解决问题!
start_cor = (19, 0)waypoints = [(5, 15), (5, 1), (9, 3), (11, 17), (7, 19), (15, 19), (13, 1), (15, 5)] end_cor = (1, 20) def distance(_from, _to): x1, y1 = _from x2, y2 = _to distancepath = Astar.find_path(x1, y1, x2, y2) return distancepath n = len(waypoints) adj_matrix = [[0] * n for _ in range(n)] for i in range(n): for j in range(i + 1, n): dist = distance(waypoints[i], waypoints[j]) adj_matrix[i][j] = dist adj_matrix[j][i] = dist start = 0 end = n - 1 distances = [[float('inf')] * (n + 1) for _ in range(n)] visited = set() heap = [(0, 0, start)] while heap: (dist, num_visited, current) = heapq.heappop(heap) if current == end and num_visited == 8: break if (current, num_visited) in visited: continue visited.add((current, num_visited)) for neighbor, weight in enumerate(adj_matrix[current]): if weight > 0: new_num_visited = num_visited if neighbor in range(start + 1, end) and (current not in range(start + 1, end)) and num_visited < 8: new_num_visited += 1 new_distance = dist + weight if new_distance < distances[neighbor][new_num_visited]: distances[neighbor][new_num_visited] = new_distance heapq.heappush(heap, (new_distance, new_num_visited, neighbor)) min_dist = float('inf') min_num_visited = 8 for i in range(8): if distances[end][i] < min_dist: min_dist = distances[end][i] min_num_visited = i每排是什么意思帮我加上注释
以下是代码的注释解释:
```
# 定义起点和终点的坐标
start_cor = (19, 0)
end_cor = (1, 20)
# 定义计算两个点之间距离的函数
def distance(_from, _to):
x1, y1 = _from
x2, y2 = _to
# 使用 Astar 算法寻路,计算出两个点之间的距离
distancepath = Astar.find_path(x1, y1, x2, y2)
return distancepath
# 定义路径上的路标点
waypoints = [(5, 15), (5, 1), (9, 3), (11, 17), (7, 19), (15, 19), (13, 1), (15, 5)]
# 计算路标点之间的距离,构建邻接矩阵
n = len(waypoints)
adj_matrix = [[0] * n for _ in range(n)]
for i in range(n):
for j in range(i + 1, n):
# 计算两个路标点之间的距离
dist = distance(waypoints[i], waypoints[j])
# 将距离存储到邻接矩阵中
adj_matrix[i][j] = dist
adj_matrix[j][i] = dist
# 定义起点和终点的编号
start = 0
end = n - 1
# 计算从起点到终点的最短路径,并要求途经的路标点个数为 8 个
distances = [[float('inf')] * (n + 1) for _ in range(n)]
visited = set()
heap = [(0, 0, start)]
while heap:
(dist, num_visited, current) = heapq.heappop(heap)
if current == end and num_visited == 8:
break
if (current, num_visited) in visited:
continue
visited.add((current, num_visited))
for neighbor, weight in enumerate(adj_matrix[current]):
if weight > 0:
new_num_visited = num_visited
# 如果邻居节点是路标点,并且当前节点不是路标点,并且途经的路标点个数还没有达到 8 个,则途经的路标点个数加 1
if neighbor in range(start + 1, end) and (current not in range(start + 1, end)) and num_visited < 8:
new_num_visited += 1
# 计算从起点到邻居节点的距离
new_distance = dist + weight
# 更新从起点到邻居节点途经指定个数路标点的最短距离
if new_distance < distances[neighbor][new_num_visited]:
distances[neighbor][new_num_visited] = new_distance
heapq.heappush(heap, (new_distance, new_num_visited, neighbor))
# 输出从起点到终点途经指定个数路标点的最短距离
min_dist = float('inf')
min_num_visited = 8
for i in range(8):
if distances[end][i] < min_dist:
min_dist = distances[end][i]
min_num_visited = i