def demo(args=None):
"""Demo script to check installation"""
env = RailEnv(width=15,
height=15,
rail_generator=complex_rail_generator(nr_start_goal=10,
nr_extra=1,
min_dist=8,
max_dist=99999),
schedule_generator=complex_schedule_generator(),
number_of_agents=5)
env._max_episode_steps = int(15 * (env.width + env.height))
env_renderer = RenderTool(env)
while True:
obs, info = env.reset()
_done = False
# Run a single episode here
step = 0
while not _done:
# Compute Action
_action = {}
for _idx, _ in enumerate(env.agents):
_action[_idx] = np.random.randint(0, 5)
obs, all_rewards, done, _ = env.step(_action)
_done = done['__all__']
step += 1
env_renderer.render_env(show=True,
frames=False,
show_observations=False,
show_predictions=False)
time.sleep(0.3)
return 0
def test_rail_environment_single_agent(show=False):
# We instantiate the following map on a 3x3 grid
# _ _
# / \/ \
# | | |
# \_/\_/
transitions = RailEnvTransitions()
if False:
# This env creation doesn't quite work right.
cells = transitions.transition_list
vertical_line = cells[1]
south_symmetrical_switch = cells[6]
north_symmetrical_switch = transitions.rotate_transition(south_symmetrical_switch, 180)
south_east_turn = int('0100000000000010', 2)
south_west_turn = transitions.rotate_transition(south_east_turn, 90)
north_east_turn = transitions.rotate_transition(south_east_turn, 270)
north_west_turn = transitions.rotate_transition(south_east_turn, 180)
rail_map = np.array([[south_east_turn, south_symmetrical_switch,
south_west_turn],
[vertical_line, vertical_line, vertical_line],
[north_east_turn, north_symmetrical_switch,
north_west_turn]],
dtype=np.uint16)
rail = GridTransitionMap(width=3, height=3, transitions=transitions)
rail.grid = rail_map
rail_env = RailEnv(width=3, height=3, rail_generator=rail_from_grid_transition_map(rail),
schedule_generator=random_schedule_generator(), number_of_agents=1,
obs_builder_object=GlobalObsForRailEnv())
else:
rail_env, env_dict = RailEnvPersister.load_new("test_env_loop.pkl", "env_data.tests")
rail_map = rail_env.rail.grid
rail_env._max_episode_steps = 1000
_ = rail_env.reset(False, False, True)
liActions = [int(a) for a in RailEnvActions]
env_renderer = RenderTool(rail_env)
#RailEnvPersister.save(rail_env, "test_env_figure8.pkl")
for _ in range(5):
#rail_env.agents[0].initial_position = (1,2)
_ = rail_env.reset(False, False, True)
# We do not care about target for the moment
agent = rail_env.agents[0]
agent.target = [-1, -1]
# Check that trains are always initialized at a consistent position
# or direction.
# They should always be able to go somewhere.
if show:
print("After reset - agent pos:", agent.position, "dir: ", agent.direction)
print(transitions.get_transitions(rail_map[agent.position], agent.direction))
#assert (transitions.get_transitions(
# rail_map[agent.position],
# agent.direction) != (0, 0, 0, 0))
# HACK - force the direction to one we know is good.
#agent.initial_position = agent.position = (2,3)
agent.initial_direction = agent.direction = 0
if show:
print ("handle:", agent.handle)
#agent.initial_position = initial_pos = agent.position
valid_active_actions_done = 0
pos = agent.position
if show:
env_renderer.render_env(show=show, show_agents=True)
time.sleep(0.01)
iStep = 0
while valid_active_actions_done < 6:
# We randomly select an action
action = np.random.choice(liActions)
#action = RailEnvActions.MOVE_FORWARD
_, _, dict_done, _ = rail_env.step({0: action})
prev_pos = pos
pos = agent.position # rail_env.agents_position[0]
print("action:", action, "pos:", agent.position, "prev:", prev_pos, agent.direction)
print(dict_done)
if prev_pos != pos:
valid_active_actions_done += 1
iStep += 1
if show:
env_renderer.render_env(show=show, show_agents=True, step=iStep)
time.sleep(0.01)
assert iStep < 100, "valid actions should have been performed by now - hung agent"
# After 6 movements on this railway network, the train should be back
# to its original height on the map.
#assert (initial_pos[0] == agent.position[0])
# We check that the train always attains its target after some time
for _ in range(10):
_ = rail_env.reset()
rail_env.agents[0].direction = 0
# JW - to avoid problem with random_schedule_generator.
#rail_env.agents[0].position = (1,2)
iStep = 0
while iStep < 100:
# We randomly select an action
action = np.random.choice(liActions)
_, _, dones, _ = rail_env.step({0: action})
done = dones['__all__']
if done:
break
iStep +=1
assert iStep < 100, "agent should have finished by now"
env_renderer.render_env(show=show)