def handle(self, *args, **options):
m = Maze()
m.generator = Prims(10, 10)
m.generate()
m.generate_entrances()
print()
self.stdout.write(self.style.SUCCESS('Successfully generated'))
def generate_data(self):
results = []
for i in range(self.count):
m = Maze()
m.generator = Prims(20, 20)
m.generate()
m.generate_entrances()
results.append(toHTML(m.grid, m.start, m.end, 25))
self.data = results
return self.data
def _generate(self, w, h, complex):
'''
产生一个特定的迷宫
:param w: int 迷宫宽度
:param h: int 迷宫高度
:param complex: float 算法复杂度，与搜索复杂度不同
:return: Maze 迷宫对象
'''
m = Maze()
m.generator = CellularAutomaton(w, h, complex, default_density)
m.generate()
m.solver = BacktrackingSolver()
#m.start = (1, 1)
#m.end = (w, h)
m.generate_entrances()
m.solve()
return m
def generate_maps(tag: str, dest: str, count: int, xsize: int, ysize: int):
for i in range(count):
# Initialise ith maze.
m = Maze(i)
# Set up generator and generate.
# CellularAutomaton is used as it often gives multiple
# possible solutions for larger map sizes.
m.generator = CellularAutomaton(xsize, ysize)
m.generate()
m.generate_entrances(False, False)
with open(path_join(dest, f"{tag}.{i}.unsolved.map"), "w") as f:
f.write(str(m))
m.solver = ShortestPath()
m.solve()
with open(path_join(dest, f"{tag}.{i}.solved.map"), "w") as f:
f.write(str(m))
import pygame as py
screen_height = 880
screen_width = int(screen_height * 1.0)
mx = 11
my = 11 # width and height of the maze
size = screen_height / mx
colors = [(0, 0, 0), (0, 200, 0), (255, 0, 0),
(255, 255, 0)] # RGB colors of the maze
m = Maze()
m.generator = Prims(5, 5)
m.generate()
m.generate_entrances(True, True)
print(m.tostring(True))
m.grid[m.start[0]][m.start[1]] = 2
m.grid[m.end[0]][m.end[1]] = 3
py.init()
screen = py.display
screen_surf = screen.set_mode((screen_width, screen_height))
class Player(object):
def __init__(self, pos):
self.rect = py.Rect(pos[1] * size, pos[0] * size, size - 1, size - 1)
def move(self, dx, dy):
