def test_grid4_get_transitions():
grid4_map = GridTransitionMap(2, 2, Grid4Transitions([]))
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.NORTH) == (0, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.EAST) == (0, 0, 0, 0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.SOUTH) == (0, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.WEST) == (0, 0, 0, 0)
assert grid4_map.get_full_transitions(0, 0) == 0
grid4_map.set_transition((0, 0, Grid4TransitionsEnum.NORTH),
Grid4TransitionsEnum.NORTH, 1)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.NORTH) == (1, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.EAST) == (0, 0, 0, 0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.SOUTH) == (0, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.WEST) == (0, 0, 0, 0)
assert grid4_map.get_full_transitions(0, 0) == pow(
2, 15) # the most significant bit is on
grid4_map.set_transition((0, 0, Grid4TransitionsEnum.NORTH),
Grid4TransitionsEnum.WEST, 1)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.NORTH) == (1, 0, 0,
1)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.EAST) == (0, 0, 0, 0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.SOUTH) == (0, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.WEST) == (0, 0, 0, 0)
# the most significant and the fourth most significant bits are on
assert grid4_map.get_full_transitions(0, 0) == pow(2, 15) + pow(2, 12)
grid4_map.set_transition((0, 0, Grid4TransitionsEnum.NORTH),
Grid4TransitionsEnum.NORTH, 0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.NORTH) == (0, 0, 0,
1)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.EAST) == (0, 0, 0, 0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.SOUTH) == (0, 0, 0,
0)
assert grid4_map.get_transitions(0, 0,
Grid4TransitionsEnum.WEST) == (0, 0, 0, 0)
# the fourth most significant bits are on
assert grid4_map.get_full_transitions(0, 0) == pow(2, 12)
def generator(rail: GridTransitionMap, num_agents: int, hints: Any = None, num_resets: int = 0,
np_random: RandomState = None) -> Schedule:
_runtime_seed = seed + num_resets
valid_positions = []
for r in range(rail.height):
for c in range(rail.width):
if rail.get_full_transitions(r, c) > 0:
valid_positions.append((r, c))
if len(valid_positions) == 0:
return Schedule(agent_positions=[], agent_directions=[],
agent_targets=[], agent_speeds=[], agent_malfunction_rates=None, max_episode_steps=0)
if len(valid_positions) < num_agents:
warnings.warn("schedule_generators: len(valid_positions) < num_agents")
return Schedule(agent_positions=[], agent_directions=[],
agent_targets=[], agent_speeds=[], agent_malfunction_rates=None, max_episode_steps=0)
agents_position_idx = [i for i in np_random.choice(len(valid_positions), num_agents, replace=False)]
agents_position = [valid_positions[agents_position_idx[i]] for i in range(num_agents)]
agents_target_idx = [i for i in np_random.choice(len(valid_positions), num_agents, replace=False)]
agents_target = [valid_positions[agents_target_idx[i]] for i in range(num_agents)]
update_agents = np.zeros(num_agents)
re_generate = True
cnt = 0
while re_generate:
cnt += 1
if cnt > 1:
print("re_generate cnt={}".format(cnt))
if cnt > 1000:
raise Exception("After 1000 re_generates still not success, giving up.")
# update position
for i in range(num_agents):
if update_agents[i] == 1:
x = np.setdiff1d(np.arange(len(valid_positions)), agents_position_idx)
agents_position_idx[i] = np_random.choice(x)
agents_position[i] = valid_positions[agents_position_idx[i]]
x = np.setdiff1d(np.arange(len(valid_positions)), agents_target_idx)
agents_target_idx[i] = np_random.choice(x)
agents_target[i] = valid_positions[agents_target_idx[i]]
update_agents = np.zeros(num_agents)
# agents_direction must be a direction for which a solution is
# guaranteed.
agents_direction = [0] * num_agents
re_generate = False
for i in range(num_agents):
valid_movements = []
for direction in range(4):
position = agents_position[i]
moves = rail.get_transitions(position[0], position[1], direction)
for move_index in range(4):
if moves[move_index]:
valid_movements.append((direction, move_index))
valid_starting_directions = []
for m in valid_movements:
new_position = get_new_position(agents_position[i], m[1])
if m[0] not in valid_starting_directions and rail.check_path_exists(new_position, m[1],
agents_target[i]):
valid_starting_directions.append(m[0])
if len(valid_starting_directions) == 0:
update_agents[i] = 1
warnings.warn(
"reset position for agent[{}]: {} -> {}".format(i, agents_position[i], agents_target[i]))
re_generate = True
break
else:
agents_direction[i] = valid_starting_directions[
np_random.choice(len(valid_starting_directions), 1)[0]]
agents_speed = speed_initialization_helper(num_agents, speed_ratio_map, seed=_runtime_seed, np_random=np_random)
# Compute max number of steps with given schedule
extra_time_factor = 1.5 # Factor to allow for more then minimal time
max_episode_steps = int(extra_time_factor * rail.height * rail.width)
return Schedule(agent_positions=agents_position, agent_directions=agents_direction,
agent_targets=agents_target, agent_speeds=agents_speed, agent_malfunction_rates=None,
max_episode_steps=max_episode_steps)