发布时间：2025-06-24 20:46:44 作者：北方职教升学中心 阅读量：608
代码分享
代码中一共4个.py文件，一个迷宫形状配置文件，如下：
1、走迷宫模拟软件中已实现功能
1、绪论
1、点击迷宫墙壁可编辑迷宫，并且可保存和加载迷宫形状文件；
2、maze.py
import numpy as npfrom tkinter import filedialogclass Maze(object): def __init__(self, cv, windows_h, bd, win, map_size=32): self.map_size = map_size self.cv = cv self.bd = bd self.win = win self.up = 0 self.down = 1 self.left = 2 self.right = 3 self.maze_map = np.ones((map_size, map_size, 4), dtype='int8') # h/y, w/x, wall/up,down,left,right self.cell_len = int((windows_h-2*self.bd)/map_size) self.line_hand = [] self.win_point = None def draw_win_point(self): # clear win point if self.win_point is not None: self.cv.delete(self.win_point) # draw win point w, h = self.win x, y = (w+0.5)*self.cell_len+self.bd, (h+0.5)*self.cell_len+self.bd rate = self.cell_len/3 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.win_point = self.cv.create_oval(x0, y0, x1, y1, fill='red') def draw_maze(self): # clear maze for tag in self.line_hand: self.cv.delete(tag) # draw maze for h in range(self.map_size): for w in range(self.map_size): for index in range(4): # up and down for wall if index in [self.up, self.down]: x0, y0 = w*self.cell_len+self.bd, (h+index)*self.cell_len+self.bd x1, y1 = (w+1)*self.cell_len+self.bd, (h+index)*self.cell_len+self.bd # left and right for wall else: x0, y0 = (w+index-2)*self.cell_len+self.bd, h*self.cell_len+self.bd x1, y1 = (w+index-2)*self.cell_len+self.bd, (h+1)*self.cell_len+self.bd # no line draw white line if self.maze_map[h, w, index] == 1: color = 'black' else: color = 'Gainsboro' # draw line self.line_hand.append(self.cv.create_line(x0, y0, x1, y1, width=2, fill=color)) self.cv.tag_bind(self.line_hand[-1], '<Button-1>', lambda event, c=[h, w, index]: self.change_cell(c)) def change_cell(self, c): # click to hide or show line h, w, index = c # edge wall if h == 0 and index == self.up: return if w == 0 and index == self.left: return # up wall if index == self.up: # deal clicked line if self.maze_map[h, w, self.up] == 1: self.maze_map[h, w, self.up] = 0 else: self.maze_map[h, w, self.up] = 1 # deal adjoin line if h-1 >= 0: if self.maze_map[h, w, self.up] == 0: self.maze_map[h - 1, w, self.down] = 0 else: self.maze_map[h - 1, w, self.down] = 1 # left wall if index == self.left: # deal clicked line if self.maze_map[h, w, self.left] == 1: self.maze_map[h, w, self.left] = 0 else: self.maze_map[h, w, self.left] = 1 # deal adjoin line if w-1 >= 0: if self.maze_map[h, w, self.left] == 0: self.maze_map[h, w - 1, self.right] = 0 else: self.maze_map[h, w - 1, self.right] = 1 self.draw_maze() def save_maze(self): fileSave = filedialog.asksaveasfilename(defaultextension='.txt', filetypes=[("txt files", ".txt")]) np.savetxt(fileSave, self.maze_map.reshape((1, self.map_size*self.map_size*4)), fmt='%d') def load_maze(self): filePath = filedialog.askopenfilename() self.maze_map = np.loadtxt(filePath).reshape((self.map_size, self.map_size, 4)) self.draw_maze() def get_maze_map(self): return self.maze_map.copy()4、
2、自动搜索迷宫，采用回溯算法搜索整个迷宫；
3、考验参赛选手软硬件结合的能力。简介
电脑鼠走迷宫是一种比赛，制作实物电脑鼠小车在迷宫找目标点，用时最短者获胜。软件截图
打开迷宫形状配置文件
点击迷宫墙壁编辑迷宫形状
搜索迷宫
搜索迷宫
搜索迷宫，并且回溯未到过的地方
搜索结束，找到最短距离的路径
三、main.pyimport tkinter as tkimport maze as mazeimport micromouse as micromouseroot = tk.Tk()windows_w = 640*2+100windows_h = 640bd = 10map_size = 32win = [15, 15]root.title("MicroMouse")root.geometry("{}x{}".format(windows_w, windows_h))cv = tk.Canvas(root, width=windows_h*2, height=windows_h, bg='white')cv.place(x=0, y=0)mz = maze.Maze(cv, windows_h, bd, win, map_size)mz.draw_maze()mz.draw_win_point()mouse = micromouse.MicroMouse(cv, mz.cell_len, bd, win, windows_h, map_size)mouse.draw_mouse(0, 0)mouse.draw_win_oval()mouse.draw_search_maze()save = tk.Button(root, text='保存迷宫', command=mz.save_maze, height=1, width=8)save.place(x=windows_h*2+20, y=10)open = tk.Button(root, text='加载迷宫', command=mz.load_maze, height=1, width=8)open.place(x=windows_h*2+20, y=50)search = tk.Button(root, text='探索迷宫', command=lambda mz=mz: mouse.search_maze(mz), height=1, width=8)search.place(x=windows_h*2+20, y=90)setmouse = tk.Button(root, text='重置电脑鼠', command=mouse.reset_mouse, height=1, width=8)setmouse.place(x=windows_h*2+20, y=130)root.mainloop()
2、采用洪水算法查找迷宫的最短路径。tree.py
class Tree(object): def __init__(self): self.last_tree = None self.next_tree = None self.h = None self.w = None
3、一、micromouse.pyimport numpy as npimport tree as treeclass MicroMouse(object): def __init__(self, cv, cell_len, bd, win, offset, map_size=32): self.cv = cv self.map_size = map_size self.cell_len = cell_len self.bd = bd self.win = win self.offset = offset self.after_id = None self.current_h = 0 self.current_w = 0 self.up = 0 self.down = 1 self.left = 2 self.right = 3 self.current_dir = self.right self.search_map = np.zeros((map_size, map_size, 4), dtype='int8') # h/y, w/x, wall/up,down,left,right self.after_cancel = False # hand self.maze_map = None self.mouse_hand = None self.win_oval = None self.line_hand = [] self.shortest_line_hane = [] # search record self.searched_list = [] # [h/y, w/x] self.branch_list = [] # [h, w, dir] def draw_win_oval(self): # clear win point if self.win_oval is not None: self.cv.delete(self.win_oval) # draw win point w, h = self.win x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.win_oval = self.cv.create_oval(x0, y0, x1, y1, fill='red') def draw_shortest_line(self, path): # clear win point for hane in self.shortest_line_hane: self.cv.delete(hane) # draw win point for point in path: h, w = point x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 5 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.shortest_line_hane.append(self.cv.create_oval(x0, y0, x1, y1, fill='red')) def draw_mouse(self, w, h): """画电脑鼠""" if self.mouse_hand is not None: self.cv.delete(self.mouse_hand) x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 # up if self.current_dir == self.up: x0, y0 = x - rate, y + rate x1, y1 = x + rate, y + rate x2, y2 = x, y - rate # down elif self.current_dir == self.down: x0, y0 = x - rate, y - rate x1, y1 = x + rate, y - rate x2, y2 = x, y + rate # left elif self.current_dir == self.left: x0, y0 = x + rate, y - rate x1, y1 = x + rate, y + rate x2, y2 = x - rate, y # right else: x0, y0 = x - rate, y - rate x1, y1 = x - rate, y + rate x2, y2 = x + rate, y self.mouse_hand = self.cv.create_polygon(x0, y0, x1, y1, x2, y2, fill='red') def draw_search_maze(self): # clear maze for tag in self.line_hand: self.cv.delete(tag) # draw maze for h in range(self.map_size): for w in range(self.map_size): for index in range(4): # up and down for wall if index in [self.up, self.down]: x0 = w * self.cell_len + 3 * self.bd + self.offset y0 = (h + index) * self.cell_len + self.bd x1 = (w + 1) * self.cell_len + 3 * self.bd + self.offset y1 = (h + index) * self.cell_len + self.bd # left and right for wall else: x0 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y0 = h * self.cell_len + self.bd x1 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y1 = (h + 1) * self.cell_len + self.bd # no line draw white line if self.search_map[h, w, index] == 1: color = 'black' else: color = 'white' # draw line self.line_hand.append(self.cv.create_line(x0, y0, x1, y1, width=2, fill=color)) def search_maze(self, mz): """search maze, get maze information""" self.maze_map = mz.get_maze_map() self.after_cancel = True self.by_step() def by_step(self): """search maze by step""" if self.after_cancel: # update search map, (maze's forward right left) point_info = self.update_search_map() # redraw search maze and win point self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h) self.cv.update() # check forward and walk a step, do not walk back self.step_search_maze(point_info) # next step self.cv.after(1000, func=self.by_step()) def step_search_maze(self, point_info): # mouse search maze # find exit point # if self.current_h == self.win[0] and self.current_w == self.win[1]: # return # can choise dir # up if self.current_dir == self.up: point_info[self.down] = -1 # down elif self.current_dir == self.down: point_info[self.up] = -1 # left elif self.current_dir == self.left: point_info[self.right] = -1 # right elif self.current_dir == self.right: point_info[self.left] = -1 ccd = np.where(point_info==0)[-1] ccd_len = len(ccd) finded = False # have dir to go if ccd_len > 0: for dir_ in range(ccd_len): dir = ccd[dir_] # up if dir == self.up: # not searched if [self.current_h-1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h-1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # down elif dir == self.down: # not searched if [self.current_h+1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h+1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # left elif dir == self.left: # not searched if [self.current_h, self.current_w-1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w-1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # right elif dir == self.right: # not searched if [self.current_h, self.current_w+1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w+1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # has search dir, but all have searched if not finded: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # at last have one dir have no search else: self.current_h, self.current_w, self.current_dir = h, w, d # not dir to go, back to branch else: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # record searched list self.searched_list.append([self.current_h, self.current_w]) def update_search_map(self): # update search map current position, (maze's forward right left) point_info = np.copy(self.maze_map[self.current_h][self.current_w]) self.search_map[self.current_h][self.current_w] = point_info # update search map adjoin position, border control if self.current_dir in [self.up, self.down]: # up if self.current_dir == self.up and self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] # down elif self.current_dir == self.down and self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] # left and right if self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] if self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] else: # left if self.current_dir == self.left and self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] # right if self.current_dir == self.right and self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] # up and down if self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] if self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] return point_info def find_shortest_path(self, search_map): """find shortest path""" arrived_points = [[0, 0]] # [h, w] edge_trees = [] shortest_path = [] # [h, w] # root tree root = tree.Tree() root.h = 0 root.w = 0 edge_trees.append(root) while len(edge_trees) > 0: append_trees = [] delete_trees = [] # all edge point to next step for edge_tree in edge_trees: # one edge point to next step point_info = search_map[edge_tree.h][edge_tree.w] # current point can go to dirs, have dir(append) or not have dir(delete) dirs = list(np.where(point_info == 0)[-1]) if len(dirs) > 0: for dir in dirs: if dir == self.up: h, w = edge_tree.h-1, edge_tree.w elif dir == self.down: h, w = edge_tree.h+1, edge_tree.w elif dir == self.left: h, w = edge_tree.h, edge_tree.w-1 else: h, w = edge_tree.h, edge_tree.w+1 # not go to this point before if [h, w] not in arrived_points: append_trees.append(tree.Tree()) append_trees[-1].last_tree = edge_tree append_trees[-1].h = h append_trees[-1].w = w arrived_points.append([h, w]) # find win point if h == self.win[0] and w == self.win[1]: edge_tree_ = append_trees[-1] while edge_tree_.last_tree is not None: shortest_path.append([edge_tree_.h, edge_tree_.w]) edge_tree_ = edge_tree_.last_tree self.draw_shortest_line(shortest_path) return shortest_path else: delete_trees.append(edge_tree) # append for edge_tree in append_trees: edge_trees.append(edge_tree) # delete for delete_tree in delete_trees: edge_trees.remove(delete_tree) return shortest_path def reset_mouse(self): # reset mouse self.after_cancel = False self.current_h = 0 self.current_w = 0 self.current_dir = self.right self.searched_list = [] self.searched_list = [] self.branch_list = [] self.search_map = np.zeros((self.map_size, self.map_size, 4), dtype='int8') self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h)
另外附路线配置文件1101_01.txt
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import tkinter as tkimport maze as mazeimport micromouse as micromouseroot = tk.Tk()windows_w = 640*2+100windows_h = 640bd = 10map_size = 32win = [15, 15]root.title("MicroMouse")root.geometry("{}x{}".format(windows_w, windows_h))cv = tk.Canvas(root, width=windows_h*2, height=windows_h, bg='white')cv.place(x=0, y=0)mz = maze.Maze(cv, windows_h, bd, win, map_size)mz.draw_maze()mz.draw_win_point()mouse = micromouse.MicroMouse(cv, mz.cell_len, bd, win, windows_h, map_size)mouse.draw_mouse(0, 0)mouse.draw_win_oval()mouse.draw_search_maze()save = tk.Button(root, text='保存迷宫', command=mz.save_maze, height=1, width=8)save.place(x=windows_h*2+20, y=10)open = tk.Button(root, text='加载迷宫', command=mz.load_maze, height=1, width=8)open.place(x=windows_h*2+20, y=50)search = tk.Button(root, text='探索迷宫', command=lambda mz=mz: mouse.search_maze(mz), height=1, width=8)search.place(x=windows_h*2+20, y=90)setmouse = tk.Button(root, text='重置电脑鼠', command=mouse.reset_mouse, height=1, width=8)setmouse.place(x=windows_h*2+20, y=130)root.mainloop()class Tree(object): def __init__(self): self.last_tree = None self.next_tree = None self.h = None self.w = None一、micromouse.pyimport numpy as npimport tree as treeclass MicroMouse(object): def __init__(self, cv, cell_len, bd, win, offset, map_size=32): self.cv = cv self.map_size = map_size self.cell_len = cell_len self.bd = bd self.win = win self.offset = offset self.after_id = None self.current_h = 0 self.current_w = 0 self.up = 0 self.down = 1 self.left = 2 self.right = 3 self.current_dir = self.right self.search_map = np.zeros((map_size, map_size, 4), dtype='int8') # h/y, w/x, wall/up,down,left,right self.after_cancel = False # hand self.maze_map = None self.mouse_hand = None self.win_oval = None self.line_hand = [] self.shortest_line_hane = [] # search record self.searched_list = [] # [h/y, w/x] self.branch_list = [] # [h, w, dir] def draw_win_oval(self): # clear win point if self.win_oval is not None: self.cv.delete(self.win_oval) # draw win point w, h = self.win x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.win_oval = self.cv.create_oval(x0, y0, x1, y1, fill='red') def draw_shortest_line(self, path): # clear win point for hane in self.shortest_line_hane: self.cv.delete(hane) # draw win point for point in path: h, w = point x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 5 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.shortest_line_hane.append(self.cv.create_oval(x0, y0, x1, y1, fill='red')) def draw_mouse(self, w, h): """画电脑鼠""" if self.mouse_hand is not None: self.cv.delete(self.mouse_hand) x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 # up if self.current_dir == self.up: x0, y0 = x - rate, y + rate x1, y1 = x + rate, y + rate x2, y2 = x, y - rate # down elif self.current_dir == self.down: x0, y0 = x - rate, y - rate x1, y1 = x + rate, y - rate x2, y2 = x, y + rate # left elif self.current_dir == self.left: x0, y0 = x + rate, y - rate x1, y1 = x + rate, y + rate x2, y2 = x - rate, y # right else: x0, y0 = x - rate, y - rate x1, y1 = x - rate, y + rate x2, y2 = x + rate, y self.mouse_hand = self.cv.create_polygon(x0, y0, x1, y1, x2, y2, fill='red') def draw_search_maze(self): # clear maze for tag in self.line_hand: self.cv.delete(tag) # draw maze for h in range(self.map_size): for w in range(self.map_size): for index in range(4): # up and down for wall if index in [self.up, self.down]: x0 = w * self.cell_len + 3 * self.bd + self.offset y0 = (h + index) * self.cell_len + self.bd x1 = (w + 1) * self.cell_len + 3 * self.bd + self.offset y1 = (h + index) * self.cell_len + self.bd # left and right for wall else: x0 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y0 = h * self.cell_len + self.bd x1 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y1 = (h + 1) * self.cell_len + self.bd # no line draw white line if self.search_map[h, w, index] == 1: color = 'black' else: color = 'white' # draw line self.line_hand.append(self.cv.create_line(x0, y0, x1, y1, width=2, fill=color)) def search_maze(self, mz): """search maze, get maze information""" self.maze_map = mz.get_maze_map() self.after_cancel = True self.by_step() def by_step(self): """search maze by step""" if self.after_cancel: # update search map, (maze's forward right left) point_info = self.update_search_map() # redraw search maze and win point self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h) self.cv.update() # check forward and walk a step, do not walk back self.step_search_maze(point_info) # next step self.cv.after(1000, func=self.by_step()) def step_search_maze(self, point_info): # mouse search maze # find exit point # if self.current_h == self.win[0] and self.current_w == self.win[1]: # return # can choise dir # up if self.current_dir == self.up: point_info[self.down] = -1 # down elif self.current_dir == self.down: point_info[self.up] = -1 # left elif self.current_dir == self.left: point_info[self.right] = -1 # right elif self.current_dir == self.right: point_info[self.left] = -1 ccd = np.where(point_info==0)[-1] ccd_len = len(ccd) finded = False # have dir to go if ccd_len > 0: for dir_ in range(ccd_len): dir = ccd[dir_] # up if dir == self.up: # not searched if [self.current_h-1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h-1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # down elif dir == self.down: # not searched if [self.current_h+1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h+1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # left elif dir == self.left: # not searched if [self.current_h, self.current_w-1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w-1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # right elif dir == self.right: # not searched if [self.current_h, self.current_w+1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w+1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # has search dir, but all have searched if not finded: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # at last have one dir have no search else: self.current_h, self.current_w, self.current_dir = h, w, d # not dir to go, back to branch else: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # record searched list self.searched_list.append([self.current_h, self.current_w]) def update_search_map(self): # update search map current position, (maze's forward right left) point_info = np.copy(self.maze_map[self.current_h][self.current_w]) self.search_map[self.current_h][self.current_w] = point_info # update search map adjoin position, border control if self.current_dir in [self.up, self.down]: # up if self.current_dir == self.up and self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] # down elif self.current_dir == self.down and self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] # left and right if self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] if self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] else: # left if self.current_dir == self.left and self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] # right if self.current_dir == self.right and self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] # up and down if self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] if self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] return point_info def find_shortest_path(self, search_map): """find shortest path""" arrived_points = [[0, 0]] # [h, w] edge_trees = [] shortest_path = [] # [h, w] # root tree root = tree.Tree() root.h = 0 root.w = 0 edge_trees.append(root) while len(edge_trees) > 0: append_trees = [] delete_trees = [] # all edge point to next step for edge_tree in edge_trees: # one edge point to next step point_info = search_map[edge_tree.h][edge_tree.w] # current point can go to dirs, have dir(append) or not have dir(delete) dirs = list(np.where(point_info == 0)[-1]) if len(dirs) > 0: for dir in dirs: if dir == self.up: h, w = edge_tree.h-1, edge_tree.w elif dir == self.down: h, w = edge_tree.h+1, edge_tree.w elif dir == self.left: h, w = edge_tree.h, edge_tree.w-1 else: h, w = edge_tree.h, edge_tree.w+1 # not go to this point before if [h, w] not in arrived_points: append_trees.append(tree.Tree()) append_trees[-1].last_tree = edge_tree append_trees[-1].h = h append_trees[-1].w = w arrived_points.append([h, w]) # find win point if h == self.win[0] and w == self.win[1]: edge_tree_ = append_trees[-1] while edge_tree_.last_tree is not None: shortest_path.append([edge_tree_.h, edge_tree_.w]) edge_tree_ = edge_tree_.last_tree self.draw_shortest_line(shortest_path) return shortest_path else: delete_trees.append(edge_tree) # append for edge_tree in append_trees: edge_trees.append(edge_tree) # delete for delete_tree in delete_trees: edge_trees.remove(delete_tree) return shortest_path def reset_mouse(self): # reset mouse self.after_cancel = False self.current_h = 0 self.current_w = 0 self.current_dir = self.right self.searched_list = [] self.searched_list = [] self.branch_list = [] self.search_map = np.zeros((self.map_size, self.map_size, 4), dtype='int8') self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h)
import numpy as npimport tree as treeclass MicroMouse(object): def __init__(self, cv, cell_len, bd, win, offset, map_size=32): self.cv = cv self.map_size = map_size self.cell_len = cell_len self.bd = bd self.win = win self.offset = offset self.after_id = None self.current_h = 0 self.current_w = 0 self.up = 0 self.down = 1 self.left = 2 self.right = 3 self.current_dir = self.right self.search_map = np.zeros((map_size, map_size, 4), dtype='int8') # h/y, w/x, wall/up,down,left,right self.after_cancel = False # hand self.maze_map = None self.mouse_hand = None self.win_oval = None self.line_hand = [] self.shortest_line_hane = [] # search record self.searched_list = [] # [h/y, w/x] self.branch_list = [] # [h, w, dir] def draw_win_oval(self): # clear win point if self.win_oval is not None: self.cv.delete(self.win_oval) # draw win point w, h = self.win x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.win_oval = self.cv.create_oval(x0, y0, x1, y1, fill='red') def draw_shortest_line(self, path): # clear win point for hane in self.shortest_line_hane: self.cv.delete(hane) # draw win point for point in path: h, w = point x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 5 x0, y0 = x - rate, y - rate x1, y1 = x + rate, y + rate self.shortest_line_hane.append(self.cv.create_oval(x0, y0, x1, y1, fill='red')) def draw_mouse(self, w, h): """画电脑鼠""" if self.mouse_hand is not None: self.cv.delete(self.mouse_hand) x, y = (w + 0.5) * self.cell_len + 3 * self.bd + self.offset, (h + 0.5) * self.cell_len + self.bd rate = self.cell_len / 3 # up if self.current_dir == self.up: x0, y0 = x - rate, y + rate x1, y1 = x + rate, y + rate x2, y2 = x, y - rate # down elif self.current_dir == self.down: x0, y0 = x - rate, y - rate x1, y1 = x + rate, y - rate x2, y2 = x, y + rate # left elif self.current_dir == self.left: x0, y0 = x + rate, y - rate x1, y1 = x + rate, y + rate x2, y2 = x - rate, y # right else: x0, y0 = x - rate, y - rate x1, y1 = x - rate, y + rate x2, y2 = x + rate, y self.mouse_hand = self.cv.create_polygon(x0, y0, x1, y1, x2, y2, fill='red') def draw_search_maze(self): # clear maze for tag in self.line_hand: self.cv.delete(tag) # draw maze for h in range(self.map_size): for w in range(self.map_size): for index in range(4): # up and down for wall if index in [self.up, self.down]: x0 = w * self.cell_len + 3 * self.bd + self.offset y0 = (h + index) * self.cell_len + self.bd x1 = (w + 1) * self.cell_len + 3 * self.bd + self.offset y1 = (h + index) * self.cell_len + self.bd # left and right for wall else: x0 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y0 = h * self.cell_len + self.bd x1 = (w + index - 2) * self.cell_len + 3 * self.bd + self.offset y1 = (h + 1) * self.cell_len + self.bd # no line draw white line if self.search_map[h, w, index] == 1: color = 'black' else: color = 'white' # draw line self.line_hand.append(self.cv.create_line(x0, y0, x1, y1, width=2, fill=color)) def search_maze(self, mz): """search maze, get maze information""" self.maze_map = mz.get_maze_map() self.after_cancel = True self.by_step() def by_step(self): """search maze by step""" if self.after_cancel: # update search map, (maze's forward right left) point_info = self.update_search_map() # redraw search maze and win point self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h) self.cv.update() # check forward and walk a step, do not walk back self.step_search_maze(point_info) # next step self.cv.after(1000, func=self.by_step()) def step_search_maze(self, point_info): # mouse search maze # find exit point # if self.current_h == self.win[0] and self.current_w == self.win[1]: # return # can choise dir # up if self.current_dir == self.up: point_info[self.down] = -1 # down elif self.current_dir == self.down: point_info[self.up] = -1 # left elif self.current_dir == self.left: point_info[self.right] = -1 # right elif self.current_dir == self.right: point_info[self.left] = -1 ccd = np.where(point_info==0)[-1] ccd_len = len(ccd) finded = False # have dir to go if ccd_len > 0: for dir_ in range(ccd_len): dir = ccd[dir_] # up if dir == self.up: # not searched if [self.current_h-1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h-1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # down elif dir == self.down: # not searched if [self.current_h+1, self.current_w] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h+1, self.current_w, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # left elif dir == self.left: # not searched if [self.current_h, self.current_w-1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w-1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # right elif dir == self.right: # not searched if [self.current_h, self.current_w+1] not in self.searched_list: # search first dir, other append to branch list if not finded: h, w, d = self.current_h, self.current_w+1, dir finded = True else: self.branch_list.append([self.current_h, self.current_w, dir]) # has search dir, but all have searched if not finded: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # at last have one dir have no search else: self.current_h, self.current_w, self.current_dir = h, w, d # not dir to go, back to branch else: if len(self.branch_list) > 0: self.current_h, self.current_w, self.current_dir = self.branch_list[-1] self.branch_list.pop() else: print('search complete!') self.find_shortest_path(np.copy(self.search_map)) # record searched list self.searched_list.append([self.current_h, self.current_w]) def update_search_map(self): # update search map current position, (maze's forward right left) point_info = np.copy(self.maze_map[self.current_h][self.current_w]) self.search_map[self.current_h][self.current_w] = point_info # update search map adjoin position, border control if self.current_dir in [self.up, self.down]: # up if self.current_dir == self.up and self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] # down elif self.current_dir == self.down and self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] # left and right if self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] if self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] else: # left if self.current_dir == self.left and self.current_w > 0: self.search_map[self.current_h][self.current_w - 1][self.right] = point_info[self.left] # right if self.current_dir == self.right and self.current_w < (self.map_size-1): self.search_map[self.current_h][self.current_w + 1][self.left] = point_info[self.right] # up and down if self.current_h > 0: self.search_map[self.current_h - 1][self.current_w][self.down] = point_info[self.up] if self.current_h < (self.map_size-1): self.search_map[self.current_h + 1][self.current_w][self.up] = point_info[self.down] return point_info def find_shortest_path(self, search_map): """find shortest path""" arrived_points = [[0, 0]] # [h, w] edge_trees = [] shortest_path = [] # [h, w] # root tree root = tree.Tree() root.h = 0 root.w = 0 edge_trees.append(root) while len(edge_trees) > 0: append_trees = [] delete_trees = [] # all edge point to next step for edge_tree in edge_trees: # one edge point to next step point_info = search_map[edge_tree.h][edge_tree.w] # current point can go to dirs, have dir(append) or not have dir(delete) dirs = list(np.where(point_info == 0)[-1]) if len(dirs) > 0: for dir in dirs: if dir == self.up: h, w = edge_tree.h-1, edge_tree.w elif dir == self.down: h, w = edge_tree.h+1, edge_tree.w elif dir == self.left: h, w = edge_tree.h, edge_tree.w-1 else: h, w = edge_tree.h, edge_tree.w+1 # not go to this point before if [h, w] not in arrived_points: append_trees.append(tree.Tree()) append_trees[-1].last_tree = edge_tree append_trees[-1].h = h append_trees[-1].w = w arrived_points.append([h, w]) # find win point if h == self.win[0] and w == self.win[1]: edge_tree_ = append_trees[-1] while edge_tree_.last_tree is not None: shortest_path.append([edge_tree_.h, edge_tree_.w]) edge_tree_ = edge_tree_.last_tree self.draw_shortest_line(shortest_path) return shortest_path else: delete_trees.append(edge_tree) # append for edge_tree in append_trees: edge_trees.append(edge_tree) # delete for delete_tree in delete_trees: edge_trees.remove(delete_tree) return shortest_path def reset_mouse(self): # reset mouse self.after_cancel = False self.current_h = 0 self.current_w = 0 self.current_dir = self.right self.searched_list = [] self.searched_list = [] self.branch_list = [] self.search_map = np.zeros((self.map_size, self.map_size, 4), dtype='int8') self.draw_search_maze() self.draw_mouse(self.current_w, self.current_h)另外附路线配置文件1101_01.txt
1 0 1 0 1 1 0 0 1 0 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 0 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 0 0 0 1 1 0 0 1 1 0 0 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 0 0 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 0 0 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
整体界面
