国外做机器人的网站,磁力兔子搜索引擎,企业形象设计和品牌形象设计,企业建设网站的目的是基于之前写的迷宫生成器实现了Djkstra算法搜索路径。
https://blog.csdn.net/ChillingKangaroo/article/details/122800431 Djkstra基于广度优先算法#xff0c;与简单搜索不同的是Djkstra在访问每一个节点的时候会计算到该节点的最短路径以及上一个节点#xff0c;如果有新…基于之前写的迷宫生成器实现了Djkstra算法搜索路径。
https://blog.csdn.net/ChillingKangaroo/article/details/122800431 Djkstra基于广度优先算法与简单搜索不同的是Djkstra在访问每一个节点的时候会计算到该节点的最短路径以及上一个节点如果有新的路径比之前的路径更短储存的上一个路径点则会被替换掉。在完成计算之后只需要取终点的数据然后就可以沿记录找到已搜索范围中最短的路径。 因为我之前迷宫基于深度优先生成另外因为路径没有权重走一格的距离都是相同的所以其实Djkstra不太能发挥出来实现中没有使用优先级序列不过算法还是有效的。 实现用了python的链表动态添加很方便在没有找到终点的时候循环每次循环查找列表中节点的四个方向如果没有访问过则添加到新列表中循环结尾再把新列表值给查找列表在查找到终点时就停止。 实现效果如下绿色表示djkstra查找范围蓝色表示最短路径使用40x40矩阵测试
import pygame as pg
import time
import randomclass Tile(): #Tile is for generating mazedef __init__(self,grid_size,screen_size,x,y):self.x,self.y x,yself.connected [0,0,0,0] # up,right,down,left 0 for not connectedself.grid_size grid_sizeself.tile_size [(screen_size[0]-100)/grid_size[0],(screen_size[1]-100)/grid_size[1]]self.rectangle (self.x*self.tile_size[0]50,self.y*self.tile_size[1]50,self.tile_size[0],self.tile_size[1])self.points [ [self.x*self.tile_size[0]50,self.y*self.tile_size[1]50], #uppper left[self.x*self.tile_size[0]50self.tile_size[0],self.y*self.tile_size[1]50], #upper right[self.x*self.tile_size[0]50self.tile_size[0],self.y*self.tile_size[1]50self.tile_size[1]], #lower right[self.x*self.tile_size[0]50,self.y*self.tile_size[1]50self.tile_size[1]], #lower left] self.visited Falseself.color (255,253,150)def draw(self,color None): #x,y represents the tile coordinates color self.color if not color else colorpg.draw.rect(screen,color,self.rectangle)for i in range(4):if not self.connected[i]:pg.draw.line(screen,(150,175,255),(self.points[i]),(self.points[((i1)%4)]),5)class Node():def __init__(self):self.visited Falseself.last_node Noneself.steps Nonedef maze_gen(path):global tile_coveredx,y path[-1]if x 0 or x grid_size[0] or y 0 or y grid_size[1]:print(findex out of range at {x,y})returnif matrix[y][x].visited:print(fnode already visited at {x,y})returnelif tile_covered grid_size[0]*grid_size[1]:tile_covered 1print(x,y)matrix[y][x].visited Truepath_choice [0,1,2,3]random.shuffle(path_choice)for i in path_choice:x_,y_ xdirections[i][0],ydirections[i][1]path.append([x_,y_])if maze_gen(path): # tile is not visitedmatrix[y][x].connected[i] 1 #walls of current nodematrix[y_][x_].connected[(i2)%4] 1#reverse the vector directionmatrix[y][x].draw()matrix[y_][x_].draw()pg.display.update()path.pop(-1)return Trueelse:print(all node visited)returndef djkstra():end_point (grid_size[0]-1,grid_size[1]-1)x,y start_pointmatrix[y][x].draw((255,0,0))matrix[end_point[0]][end_point[1]].draw((255,0,0))pg.display.update()border [[0,0]]steps 0while True:steps 1new_border []for x,y in border:if (x,y) end_point:print(exit found)return end_pointfor i in range(4):if matrix[y][x].connected[i]: #if there is a waynext_x,next_y directions[i][0]x,directions[i][1]yif found_path[next_y][next_x].visited False:new_border.append([next_x,next_y])matrix[next_y][next_x].draw((0,255,0))pg.display.update()if found_path[next_y][next_x].last_node None:found_path[next_y][next_x].last_node (x,y)elif steps found_path[next_y][next_x].steps:found_path[next_y][next_x].last_node (x,y)print(fsetting {x,y} to visited)found_path[y][x].visited Trueborder new_borderif new_border []:print(No exit point found)returndef draw_path(end_point):if not end_point:returnelse:x,y end_pointwhile [x,y] ! start_point:print(fgoing though node {x,y})matrix[y][x].draw((0,0,255))print(f{(x,y)} {start_point}:)print((x,y) start_point)x,y found_path[y][x].last_nodepg.display.update()screen_size [800,800]
grid_size [40,40]tile_covered 0
run Truescreen pg.display.set_mode(screen_size)matrix []
directions [[0,-1],[1,0],[0,1],[-1,0]] # up,right,down,left 0 for not connected
found_path [[Node() for x in range(grid_size[0])] for y in range(grid_size[1])]for y in range(grid_size[1]):temp []for x in range(grid_size[0]):tile Tile(grid_size,screen_size,x,y)temp.append(tile)matrix.append(temp)pg.init()
path [[0,0]]
start_point [0,0]screen.fill((255,255,255))
maze_gen(path)pg.display.update()print( Generation Finished )end_point djkstra()
draw_path(end_point)while run:for event in pg.event.get():if event.type pg.QUIT:run Falsepg.quit()
