def testDungeonRoomsRooms(self):
m = Maze()
m.generator = DungeonRooms(4, 4, rooms=[[(1, 1), (3, 3)]])
m.generate()
self.assertTrue(self.boundary_is_solid(m.grid))
self.assertTrue(self.all_passages_open(m.grid))
def test_dungeon_rooms_serpentine_rooms(self):
m = Maze()
m.generator = DungeonRooms(4,
4,
rooms=[[(1, 1), (3, 3)]],
hunt_order='serpentine')
m.generate()
self.assertTrue(boundary_is_solid(m.grid))
self.assertTrue(all_passages_open(m.grid))
def test_dungeon_rooms_serpentine_rooms(self):
""" test DungeonRooms mazes are reasonably when generating some random rooms in a serpentine fashion """
m = Maze()
m.generator = DungeonRooms(4,
4,
rooms=[[(1, 1), (3, 3)]],
hunt_order='serpentine')
m.generate()
assert boundary_is_solid(m.grid)
assert all_passages_open(m.grid)
def test_dungeon_rooms_random_rooms(self):
""" test Dungeon Rooms maze-creation mazes a reasonably sane maze when generating some random rooms """
m = Maze()
m.generator = DungeonRooms(4,
4,
rooms=[[(1, 1), (3, 3)]],
hunt_order='random')
m.generate()
assert boundary_is_solid(m.grid)
assert all_passages_open(m.grid)
def test_dungeon_rooms_grid(self):
g = np.ones((7, 7), dtype=np.int8)
g[1] = [1, 1, 1, 1, 1, 1, 1]
g[2] = [1, 1, 1, 1, 1, 1, 1]
g[3] = [1, 1, 0, 0, 0, 1, 1]
g[4] = [1, 1, 0, 0, 0, 1, 1]
g[5] = [1, 1, 0, 0, 0, 1, 1]
m = Maze()
m.generator = DungeonRooms(4, 4, grid=g)
m.generate()
self.assertTrue(boundary_is_solid(m.grid))
self.assertTrue(all_passages_open(m.grid))
def test_dungeon_rooms_grid(self):
""" test Dungeon Rooms maze-creation mazes a reasonably sane maze """
g = np.ones((7, 7), dtype=np.int8)
g[1] = [1, 1, 1, 1, 1, 1, 1]
g[2] = [1, 1, 1, 1, 1, 1, 1]
g[3] = [1, 1, 0, 0, 0, 1, 1]
g[4] = [1, 1, 0, 0, 0, 1, 1]
g[5] = [1, 1, 0, 0, 0, 1, 1]
m = Maze()
m.generator = DungeonRooms(4, 4, grid=g)
m.generate()
assert boundary_is_solid(m.grid)
assert all_passages_open(m.grid)
def generate(self,method = ["dungeon"],rooms = None,width = None,height = None):
if width is None: width = self.width
if height is None: width = self.height
width = width // 2
height = height // 2
if method == "dungeon":
self.maze.generator = DungeonRooms(width,height, rooms=rooms)
elif method == "prims":
self.maze.generator = Prims(width,height)
else:
raise Exception(f"Maze generation method must be in {self.options}")
self.maze.generate()
def __init__(self,
n=10,
cycles=3,
seed=np.random.randint(0, 10000),
state_representation='integer'):
'''
Initialize a maze
parameters :
n : (int) Maze has diameter 2n+1
cycles : (int) number of blocks to remove to create cycles
seed : (int) seed for random initialization
state_representation : (str) how state ought to be represented for the agent
'''
Maze.set_seed(seed)
m = Maze()
m.generator = DungeonRooms(n, n)
m.generate()
self.grid = m.grid
# remove some walls to create cycles
walls = np.argwhere(self.grid[1:(2 * n), 1:(2 * n)])
np.random.shuffle(walls)
for i in range(cycles):
row, col = walls[i]
row += 1
col += 1
self.grid[row, col] = 0
corners = [[1, 1], [1, 2 * n - 1], [2 * n - 1, 1],
[2 * n - 1, 2 * n - 1]]
self.start = random.choice(corners)
corners.remove(self.start)
self.end = random.choice(corners)
self.loc = self.start # location of agent
self.action_space = spaces.Discrete(4)
if state_representation == 'integer':
self.gen_state = self.gen_integer_state
self.observation_space = spaces.Discrete(np.prod(self.grid.shape))
elif state_representation == 'one_hot':
self.gen_state = self.gen_one_hot_state
self.observation_space = spaces.Discrete(np.prod(self.grid.shape))
self.observation_space = spaces.Box(low=0,
high=1,
shape=(np.prod(
self.grid.shape), ),
dtype=np.int8)
elif state_representation == 'flat_grid':
self.gen_state = self.gen_flat_grid_state
self.observation_space = spaces.Box(
low=0,
high=5,
shape=(np.prod(self.grid.shape), ),
dtype=np.int8) # not sure if this is right?
else:
raise NotImplementedError # add other ways to represent state here
self.episode_length = 0
self.MAX_LENGTH = 1000 # episodes are cut off at this length