请帮我生成一段传统A*算法代码,使用python3.9实现
时间: 2024-04-30 08:17:21 浏览: 21
好的,以下是使用Python3.9实现的传统A*算法代码:
```python
import heapq
def astar(start, end, graph):
"""
Apply A* algorithm to find the shortest path from start to end
in the given graph.
Arguments:
start -- the start node
end -- the target node
graph -- a dictionary of nodes and their neighbors with distances
Returns:
A tuple containing the shortest distance and a list of nodes
representing the shortest path from start to end.
"""
# The open set contains nodes to be evaluated
# The closed set contains nodes that have already been evaluated
open_set = []
closed_set = set()
# Create the start node and add it to the open set
start_node = (0, start, [])
heapq.heappush(open_set, start_node)
while open_set:
# Pop the node with the smallest f score from the open set
f, current_node, path = heapq.heappop(open_set)
# If the current node is the target node, return the path
if current_node == end:
return (f, path + [current_node])
# Add the current node to the closed set
closed_set.add(current_node)
# Evaluate the neighbors of the current node
for neighbor, distance in graph[current_node]:
# If the neighbor is in the closed set, skip it
if neighbor in closed_set:
continue
# Calculate the g score for the neighbor
g = f + distance
# If the neighbor is not in the open set, add it
# Otherwise, compare the g score of the new path with the old path
# and choose the shorter path
new_node = (g + heuristic(neighbor, end), neighbor, path + [current_node])
if neighbor not in [node[1] for node in open_set]:
heapq.heappush(open_set, new_node)
else:
index = [node[1] for node in open_set].index(neighbor)
old_node = open_set[index]
if g < old_node[0]:
open_set[index] = new_node
# If the target node is not reachable, return an empty path
return (float('inf'), [])
def heuristic(node, goal):
"""
Calculate the heuristic distance between a node and the goal.
Arguments:
node -- the current node
goal -- the target node
Returns:
The heuristic distance between the node and the goal.
"""
# Euclidean distance
return ((node[0] - goal[0]) ** 2 + (node[1] - goal[1]) ** 2) ** 0.5
```
这是一个基本的A*算法,可以通过传递一个邻接列表或邻接矩阵来确定图形。在这里,我们使用一个包含点和它们的邻居以及它们之间的距离的字典来表示图形。在上面的示例中,我们还定义了一个函数来计算节点和目标之间的启发式距离。
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