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class Point:
"""
表示一个点
"""
def __init__(self, x, y):
self.x = x
self.y = y
def __eq__(self, other):
if self.x == other.x and self.y == other.y:
return True
return False
def __str__(self):
return "x:" + str(self.x) + ",y:" + str(self.y)
def __repr__(self):
return "x:" + str(self.x) + ",y:" + str(self.y)
class AStar:
"""
AStar算法的Python3.x实现
"""
class Node: # 描述AStar算法中的节点数据
def __init__(self, point, endPoint, g=0):
self.point = point # 自己的坐标
self.father = None # 父节点
self.g = g # g值g值在用到的时候会重新算
self.h = (abs(endPoint.x - point.x) + abs(endPoint.y - point.y)) * 10 # 计算h值
def __init__(self, map2d, startPoint, endPoint, passTag=0, offset=1):
"""
构造AStar算法的启动条件
:param map2d: Array2D类型的寻路数组
:param startPoint: Point或二元组类型的寻路起点
:param endPoint: Point或二元组类型的寻路终点
:param passTag: int类型的可行走标记若地图数据!=passTag即为障碍
"""
# 开启表
self.openList = []
# 关闭表
self.closeList = []
# 寻路地图
self.map2d = map2d
# 起点终点
if isinstance(startPoint, Point) and isinstance(endPoint, Point):
self.startPoint = startPoint
self.endPoint = endPoint
else:
self.startPoint = Point(*startPoint)
self.endPoint = Point(*endPoint)
# 可行走标记
self.passTag = passTag
# 遍历周围格子的偏移量
self.offset = offset
def getMinNode(self):
"""
获得openlist中F值最小的节点
:return: Node
"""
currentNode = self.openList[0]
for node in self.openList:
if node.g + node.h < currentNode.g + currentNode.h:
currentNode = node
return currentNode
def pointInCloseList(self, point):
for node in self.closeList:
if node.point == point:
return True
return False
def pointInOpenList(self, point):
for node in self.openList:
if node.point == point:
return node
return None
def endPointInCloseList(self):
for node in self.openList:
if node.point == self.endPoint:
return node
return None
def searchNear(self, minF, offsetX, offsetY):
"""
搜索节点周围的点
:param minF:F值最小的节点
:param offsetX:坐标偏移量
:param offsetY:
:return:
"""
# 越界检测
if minF.point.x + offsetX < 0 or minF.point.x + offsetX > self.map2d.w - 1 or minF.point.y + offsetY < 0 or minF.point.y + offsetY > self.map2d.h - 1:
return
# 如果是障碍,就忽略
if self.map2d[minF.point.x + offsetX][minF.point.y + offsetY] != self.passTag:
return
# 如果在关闭表中,就忽略
currentPoint = Point(minF.point.x + offsetX, minF.point.y + offsetY)
if self.pointInCloseList(currentPoint):
return
# 设置单位花费
if offsetX == 0 or offsetY == 0:
step = 10
else:
step = 14
# 如果不再openList中就把它加入openlist
currentNode = self.pointInOpenList(currentPoint)
if not currentNode:
currentNode = AStar.Node(currentPoint, self.endPoint, g=minF.g + step)
currentNode.father = minF
self.openList.append(currentNode)
return
# 如果在openList中判断minF到当前点的G是否更小
if minF.g + step < currentNode.g: # 如果更小就重新计算g值并且改变father
currentNode.g = minF.g + step
currentNode.father = minF
def start(self):
"""
开始寻路
:return: None或Point列表路径
"""
# 判断寻路终点是否是障碍
if self.map2d[self.endPoint.x][self.endPoint.y] != self.passTag:
return None
# 1.将起点放入开启列表
startNode = AStar.Node(self.startPoint, self.endPoint)
self.openList.append(startNode)
# 2.主循环逻辑
count = 0
while True:
count += 1
if count > 400:
return None
# 找到F值最小的点
minF = self.getMinNode()
# 把这个点加入closeList中并且在openList中删除它
self.closeList.append(minF)
self.openList.remove(minF)
# 判断这个节点的上下左右节点,八方寻路
self.searchNear(minF, 0, -self.offset) # 上
self.searchNear(minF, 0, self.offset) # 下
self.searchNear(minF, -self.offset, 0) # 左
self.searchNear(minF, self.offset, 0) # 右
self.searchNear(minF, -self.offset, -self.offset) # 上左
self.searchNear(minF, self.offset, self.offset) # 下右
self.searchNear(minF, -self.offset, self.offset) # 下左
self.searchNear(minF, self.offset, -self.offset) # 上右
# 判断是否终止
point = self.endPointInCloseList()
if point: # 如果终点在关闭表中,就返回结果
# print("关闭表中")
cPoint = point
pathList = []
while True:
if cPoint.father:
pathList.append(cPoint.point)
cPoint = cPoint.father
else:
return list(reversed(pathList))
if len(self.openList) == 0:
return None