astar.py

class Node:
    def __init__(self, position, parent=None):
        self.position = position
        self.parent = parent
        self.g = 0
        self.h = 0
        self.f = 0

    def __eq__(self, other):
        return self.position == other.position

def heuristic(a, b):
    return abs(a[0] - b[0]) + abs(a[1] - b[1])  # 使用曼哈顿距离

def astar(grid, start, end):
    start_node = Node(start, None)
    end_node = Node(end, None)
    open_list = []
    closed_list = []

    open_list.append(start_node)

    while len(open_list) > 0:
        current_node = open_list[0]
        current_index = 0
        for index, item in enumerate(open_list):
            if item.f < current_node.f:
                current_node = item
                current_index = index

        open_list.pop(current_index)
        closed_list.append(current_node)

        if current_node == end_node:
            path = []
            current = current_node
            while current is not None:
                path.append(current.position)
                current = current.parent
            return path[::-1]  # Return reversed path

        children = []
        for new_position in [(0, -1), (0, 1), (-1, 0), (1, 0)]:  # 相邻方格
            node_position = (current_node.position[0] + new_position[0], current_node.position[1] + new_position[1])

            if node_position[0] > (len(grid) - 1) or node_position[0] < 0 or node_position[1] > (len(grid[len(grid)-1]) -1) or node_position[1] < 0:
                continue

            if grid[node_position[0]][node_position[1]] != 0:
                continue

            new_node = Node(node_position, current_node)
            children.append(new_node)

        for child in children:
            if child in closed_list:
                continue

            child.g = current_node.g + 1
            child.h = heuristic(child.position, end_node.position)
            child.f = child.g + child.h

            if child in open_list:
                continue

            open_list.append(child)