def test_dead_end():
transitions = RailEnvTransitions()
straight_vertical = int('1000000000100000', 2) # Case 1 - straight
straight_horizontal = transitions.rotate_transition(straight_vertical,
90)
dead_end_from_south = int('0010000000000000', 2) # Case 7 - dead end
# We instantiate the following railway
# O->-- where > is the train and O the target. After 6 steps,
# the train should be done.
rail_map = np.array(
[[transitions.rotate_transition(dead_end_from_south, 270)] +
[straight_horizontal] * 3 +
[transitions.rotate_transition(dead_end_from_south, 90)]],
dtype=np.uint16)
rail = GridTransitionMap(width=rail_map.shape[1],
height=rail_map.shape[0],
transitions=transitions)
rail.grid = rail_map
rail_env = RailEnv(width=rail_map.shape[1], height=rail_map.shape[0],
rail_generator=rail_from_grid_transition_map(rail),
schedule_generator=random_schedule_generator(), number_of_agents=1,
obs_builder_object=GlobalObsForRailEnv())
# We try the configuration in the 4 directions:
rail_env.reset()
rail_env.agents = [EnvAgent(initial_position=(0, 2), initial_direction=1, direction=1, target=(0, 0), moving=False)]
rail_env.reset()
rail_env.agents = [EnvAgent(initial_position=(0, 2), initial_direction=3, direction=3, target=(0, 4), moving=False)]
# In the vertical configuration:
rail_map = np.array(
[[dead_end_from_south]] + [[straight_vertical]] * 3 +
[[transitions.rotate_transition(dead_end_from_south, 180)]],
dtype=np.uint16)
rail = GridTransitionMap(width=rail_map.shape[1],
height=rail_map.shape[0],
transitions=transitions)
rail.grid = rail_map
rail_env = RailEnv(width=rail_map.shape[1], height=rail_map.shape[0],
rail_generator=rail_from_grid_transition_map(rail),
schedule_generator=random_schedule_generator(), number_of_agents=1,
obs_builder_object=GlobalObsForRailEnv())
rail_env.reset()
rail_env.agents = [EnvAgent(initial_position=(2, 0), initial_direction=2, direction=2, target=(0, 0), moving=False)]
rail_env.reset()
rail_env.agents = [EnvAgent(initial_position=(2, 0), initial_direction=0, direction=0, target=(4, 0), moving=False)]
def make_simple_rail2() -> Tuple[GridTransitionMap, np.array]:
# We instantiate a very simple rail network on a 7x10 grid:
# |
# |
# |
# _ _ _ _\ _ _ _ _ _ _
# \
# |
# |
# |
transitions = RailEnvTransitions()
cells = transitions.transition_list
empty = cells[0]
dead_end_from_south = cells[7]
dead_end_from_west = transitions.rotate_transition(dead_end_from_south, 90)
dead_end_from_north = transitions.rotate_transition(dead_end_from_south, 180)
dead_end_from_east = transitions.rotate_transition(dead_end_from_south, 270)
vertical_straight = cells[1]
horizontal_straight = transitions.rotate_transition(vertical_straight, 90)
simple_switch_north_right = cells[10]
simple_switch_east_west_north = transitions.rotate_transition(simple_switch_north_right, 270)
simple_switch_west_east_south = transitions.rotate_transition(simple_switch_north_right, 90)
rail_map = np.array(
[[empty] * 3 + [dead_end_from_south] + [empty] * 6] +
[[empty] * 3 + [vertical_straight] + [empty] * 6] * 2 +
[[dead_end_from_east] + [horizontal_straight] * 2 +
[simple_switch_east_west_north] +
[horizontal_straight] * 2 + [simple_switch_west_east_south] +
[horizontal_straight] * 2 + [dead_end_from_west]] +
[[empty] * 6 + [vertical_straight] + [empty] * 3] * 2 +
[[empty] * 6 + [dead_end_from_north] + [empty] * 3], dtype=np.uint16)
rail = GridTransitionMap(width=rail_map.shape[1],
height=rail_map.shape[0], transitions=transitions)
rail.grid = rail_map
return rail, rail_map
def make_simple_rail_with_alternatives() -> Tuple[GridTransitionMap, np.array]:
# We instantiate a very simple rail network on a 7x10 grid:
# 0 1 2 3 4 5 6 7 8 9 10
# 0 /-------------\
# 1 | |
# 2 | |
# 3 _ _ _ /_ _ _ |
# 4 \ ___ /
# 5 |/
# 6 |
# 7 |
transitions = RailEnvTransitions()
cells = transitions.transition_list
empty = cells[0]
dead_end_from_south = cells[7]
right_turn_from_south = cells[8]
right_turn_from_west = transitions.rotate_transition(
right_turn_from_south, 90)
right_turn_from_north = transitions.rotate_transition(
right_turn_from_south, 180)
dead_end_from_west = transitions.rotate_transition(dead_end_from_south, 90)
dead_end_from_north = transitions.rotate_transition(
dead_end_from_south, 180)
dead_end_from_east = transitions.rotate_transition(dead_end_from_south,
270)
vertical_straight = cells[1]
simple_switch_north_left = cells[2]
simple_switch_north_right = cells[10]
simple_switch_left_east = transitions.rotate_transition(
simple_switch_north_left, 90)
horizontal_straight = transitions.rotate_transition(vertical_straight, 90)
double_switch_south_horizontal_straight = horizontal_straight + cells[6]
double_switch_north_horizontal_straight = transitions.rotate_transition(
double_switch_south_horizontal_straight, 180)
rail_map = np.array(
[[empty] * 3 + [right_turn_from_south] + [horizontal_straight] * 5 +
[right_turn_from_west]] +
[[empty] * 3 + [vertical_straight] + [empty] * 5 + [vertical_straight]
] * 2 + [[dead_end_from_east] + [horizontal_straight] * 2 +
[simple_switch_left_east] + [horizontal_straight] * 2 +
[right_turn_from_west] + [empty] * 2 + [vertical_straight]] +
[[empty] * 6 + [simple_switch_north_right] +
[horizontal_straight] * 2 + [right_turn_from_north]] +
[[empty] * 6 + [vertical_straight] + [empty] * 3] +
[[empty] * 6 + [dead_end_from_north] + [empty] * 3],
dtype=np.uint16)
rail = GridTransitionMap(width=rail_map.shape[1],
height=rail_map.shape[0],
transitions=transitions)
rail.grid = rail_map
return rail, rail_map
def test_walker():
# _ _ _
transitions = RailEnvTransitions()
cells = transitions.transition_list
dead_end_from_south = cells[7]
dead_end_from_west = transitions.rotate_transition(dead_end_from_south, 90)
dead_end_from_east = transitions.rotate_transition(dead_end_from_south,
270)
vertical_straight = cells[1]
horizontal_straight = transitions.rotate_transition(vertical_straight, 90)
rail_map = np.array(
[[dead_end_from_east] + [horizontal_straight] + [dead_end_from_west]],
dtype=np.uint16)
rail = GridTransitionMap(width=rail_map.shape[1],
height=rail_map.shape[0],
transitions=transitions)
rail.grid = rail_map
env = RailEnv(
width=rail_map.shape[1],
height=rail_map.shape[0],
rail_generator=rail_from_grid_transition_map(rail),
schedule_generator=random_schedule_generator(),
number_of_agents=1,
obs_builder_object=TreeObsForRailEnv(
max_depth=2,
predictor=ShortestPathPredictorForRailEnv(max_depth=10)),
)
env.reset()
# set initial position and direction for testing...
env.agents[0].position = (0, 1)
env.agents[0].direction = 1
env.agents[0].target = (0, 0)
# reset to set agents from agents_static
env.reset(False, False)
print(env.distance_map.get()[(0, *[0, 1], 1)])
assert env.distance_map.get()[(0, *[0, 1], 1)] == 3
print(env.distance_map.get()[(0, *[0, 2], 3)])
assert env.distance_map.get()[(0, *[0, 2], 1)] == 2
def generator(width: int,
height: int,
num_agents: int,
num_resets: int = 0,
np_random: RandomState = None) -> List:
env_dict = persistence.RailEnvPersister.load_env_dict(
filename, load_from_package=load_from_package)
rail_env_transitions = RailEnvTransitions()
grid = np.array(env_dict["grid"])
rail = GridTransitionMap(width=np.shape(grid)[1],
height=np.shape(grid)[0],
transitions=rail_env_transitions)
rail.grid = grid
if "distance_map" in env_dict:
distance_map = env_dict["distance_map"]
if len(distance_map) > 0:
return rail, {'distance_map': distance_map}
return [rail, None]
def test_rail_environment_single_agent():
# We instantiate the following map on a 3x3 grid
# _ _
# / \/ \
# | | |
# \_/\_/
transitions = RailEnvTransitions()
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())
for _ in range(200):
_ = 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.
assert (transitions.get_transitions(rail_map[agent.position],
agent.direction) != (0, 0, 0, 0))
initial_pos = agent.position
valid_active_actions_done = 0
pos = initial_pos
while valid_active_actions_done < 6:
# We randomly select an action
action = np.random.randint(4)
_, _, _, _ = rail_env.step({0: action})
prev_pos = pos
pos = agent.position # rail_env.agents_position[0]
if prev_pos != pos:
valid_active_actions_done += 1
# 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()
done = False
while not done:
# We randomly select an action
action = np.random.randint(4)
_, _, dones, _ = rail_env.step({0: action})
done = dones['__all__']
def generator(width: int,
height: int,
num_agents: int,
num_resets: int = 0,
np_random: RandomState = None) -> RailGenerator:
t_utils = RailEnvTransitions()
transition_probability = cell_type_relative_proportion
transitions_templates_ = []
transition_probabilities = []
for i in range(len(t_utils.transitions)): # don't include dead-ends
if t_utils.transitions[i] == int('0010000000000000', 2):
continue
all_transitions = 0
for dir_ in range(4):
trans = t_utils.get_transitions(t_utils.transitions[i], dir_)
all_transitions |= (trans[0] << 3) | \
(trans[1] << 2) | \
(trans[2] << 1) | \
(trans[3])
template = [int(x) for x in bin(all_transitions)[2:]]
template = [0] * (4 - len(template)) + template
# add all rotations
for rot in [0, 90, 180, 270]:
transitions_templates_.append(
(template,
t_utils.rotate_transition(t_utils.transitions[i], rot)))
transition_probabilities.append(transition_probability[i])
template = [template[-1]] + template[:-1]
def get_matching_templates(template):
"""
Returns a list of possible transition maps for a given template
Parameters:
------
template:List[int]
Returns:
------
List[int]
"""
ret = []
for i in range(len(transitions_templates_)):
is_match = True
for j in range(4):
if template[j] >= 0 and template[
j] != transitions_templates_[i][0][j]:
is_match = False
break
if is_match:
ret.append((transitions_templates_[i][1],
transition_probabilities[i]))
return ret
MAX_INSERTIONS = (width - 2) * (height - 2) * 10
MAX_ATTEMPTS_FROM_SCRATCH = 10
attempt_number = 0
while attempt_number < MAX_ATTEMPTS_FROM_SCRATCH:
cells_to_fill = []
rail = []
for r in range(height):
rail.append([None] * width)
if r > 0 and r < height - 1:
cells_to_fill = cells_to_fill + [
(r, c) for c in range(1, width - 1)
]
num_insertions = 0
while num_insertions < MAX_INSERTIONS and len(cells_to_fill) > 0:
cell = cells_to_fill[np_random.choice(len(cells_to_fill),
1)[0]]
cells_to_fill.remove(cell)
row = cell[0]
col = cell[1]
# look at its neighbors and see what are the possible transitions
# that can be chosen from, if any.
valid_template = [-1, -1, -1, -1]
for el in [(0, 2, (-1, 0)), (1, 3, (0, 1)), (2, 0, (1, 0)),
(3, 1, (0, -1))]: # N, E, S, W
neigh_trans = rail[row + el[2][0]][col + el[2][1]]
if neigh_trans is not None:
# select transition coming from facing direction el[1] and
# moving to direction el[1]
max_bit = 0
for k in range(4):
max_bit |= t_utils.get_transition(
neigh_trans, k, el[1])
if max_bit:
valid_template[el[0]] = 1
else:
valid_template[el[0]] = 0
possible_cell_transitions = get_matching_templates(
valid_template)
if len(possible_cell_transitions) == 0: # NO VALID TRANSITIONS
# no cell can be filled in without violating some transitions
# can a dead-end solve the problem?
if valid_template.count(1) == 1:
for k in range(4):
if valid_template[k] == 1:
rot = 0
if k == 0:
rot = 180
elif k == 1:
rot = 270
elif k == 2:
rot = 0
elif k == 3:
rot = 90
rail[row][col] = t_utils.rotate_transition(
int('0010000000000000', 2), rot)
num_insertions += 1
break
else:
# can I get valid transitions by removing a single
# neighboring cell?
bestk = -1
besttrans = []
for k in range(4):
tmp_template = valid_template[:]
tmp_template[k] = -1
possible_cell_transitions = get_matching_templates(
tmp_template)
if len(possible_cell_transitions) > len(besttrans):
besttrans = possible_cell_transitions
bestk = k
if bestk >= 0:
# Replace the corresponding cell with None, append it
# to cells to fill, fill in a transition in the current
# cell.
replace_row = row - 1
replace_col = col
if bestk == 1:
replace_row = row
replace_col = col + 1
elif bestk == 2:
replace_row = row + 1
replace_col = col
elif bestk == 3:
replace_row = row
replace_col = col - 1
cells_to_fill.append((replace_row, replace_col))
rail[replace_row][replace_col] = None
possible_transitions, possible_probabilities = zip(
*besttrans)
possible_probabilities = [
p / sum(possible_probabilities)
for p in possible_probabilities
]
rail[row][col] = np_random.choice(
possible_transitions, p=possible_probabilities)
num_insertions += 1
else:
print('WARNING: still nothing!')
rail[row][col] = int('0000000000000000', 2)
num_insertions += 1
pass
else:
possible_transitions, possible_probabilities = zip(
*possible_cell_transitions)
possible_probabilities = [
p / sum(possible_probabilities)
for p in possible_probabilities
]
rail[row][col] = np_random.choice(possible_transitions,
p=possible_probabilities)
num_insertions += 1
if num_insertions == MAX_INSERTIONS:
# Failed to generate a valid level; try again for a number of times
attempt_number += 1
else:
break
if attempt_number == MAX_ATTEMPTS_FROM_SCRATCH:
print('ERROR: failed to generate level')
# Finally pad the border of the map with dead-ends to avoid border issues;
# at most 1 transition in the neigh cell
for r in range(height):
# Check for transitions coming from [r][1] to WEST
max_bit = 0
neigh_trans = rail[r][1]
if neigh_trans is not None:
for k in range(4):
neigh_trans_from_direction = (neigh_trans >>
((3 - k) * 4)) & (2**4 - 1)
max_bit = max_bit | (neigh_trans_from_direction & 1)
if max_bit:
rail[r][0] = t_utils.rotate_transition(
int('0010000000000000', 2), 270)
else:
rail[r][0] = int('0000000000000000', 2)
# Check for transitions coming from [r][-2] to EAST
max_bit = 0
neigh_trans = rail[r][-2]
if neigh_trans is not None:
for k in range(4):
neigh_trans_from_direction = (neigh_trans >>
((3 - k) * 4)) & (2**4 - 1)
max_bit = max_bit | (neigh_trans_from_direction & (1 << 2))
if max_bit:
rail[r][-1] = t_utils.rotate_transition(
int('0010000000000000', 2), 90)
else:
rail[r][-1] = int('0000000000000000', 2)
for c in range(width):
# Check for transitions coming from [1][c] to NORTH
max_bit = 0
neigh_trans = rail[1][c]
if neigh_trans is not None:
for k in range(4):
neigh_trans_from_direction = (neigh_trans >>
((3 - k) * 4)) & (2**4 - 1)
max_bit = max_bit | (neigh_trans_from_direction & (1 << 3))
if max_bit:
rail[0][c] = int('0010000000000000', 2)
else:
rail[0][c] = int('0000000000000000', 2)
# Check for transitions coming from [-2][c] to SOUTH
max_bit = 0
neigh_trans = rail[-2][c]
if neigh_trans is not None:
for k in range(4):
neigh_trans_from_direction = (neigh_trans >>
((3 - k) * 4)) & (2**4 - 1)
max_bit = max_bit | (neigh_trans_from_direction & (1 << 1))
if max_bit:
rail[-1][c] = t_utils.rotate_transition(
int('0010000000000000', 2), 180)
else:
rail[-1][c] = int('0000000000000000', 2)
# For display only, wrong levels
for r in range(height):
for c in range(width):
if rail[r][c] is None:
rail[r][c] = int('0000000000000000', 2)
tmp_rail = np.asarray(rail, dtype=np.uint16)
return_rail = GridTransitionMap(width=width,
height=height,
transitions=t_utils)
return_rail.grid = tmp_rail
return return_rail, None
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)