diff --git a/flatland/envs/agent_utils.py b/flatland/envs/agent_utils.py
index 00dabd312bb6bc21b7b7fbdd84608df2d8ee1ec7..b90d38a427533846baadb704f5137c90c1044f73 100644
--- a/flatland/envs/agent_utils.py
+++ b/flatland/envs/agent_utils.py
@@ -109,7 +109,11 @@ class EnvAgent:
return get_shortest_paths(distance_map=distance_map, agent_handle=self.handle)[self.handle]
def get_travel_time_on_shortest_path(self, distance_map) -> int:
- distance = len(self.get_shortest_path(distance_map))
+ shortest_path = self.get_shortest_path(distance_map)
+ if shortest_path is not None:
+ distance = len(shortest_path)
+ else:
+ distance = 0
speed = self.speed_data['speed']
return int(np.ceil(distance / speed))
diff --git a/flatland/envs/persistence.py b/flatland/envs/persistence.py
index bc4b169b1aad3893d96d82cb8284b369f13104f2..b8354078f68705e2d3757a61626c03df2ac9dc4c 100644
--- a/flatland/envs/persistence.py
+++ b/flatland/envs/persistence.py
@@ -21,7 +21,7 @@ from flatland.envs.distance_map import DistanceMap
# cannot import objects / classes directly because of circular import
from flatland.envs import malfunction_generators as mal_gen
from flatland.envs import rail_generators as rail_gen
-from flatland.envs import schedule_generators as sched_gen
+from flatland.envs import line_generators as line_gen
msgpack_numpy.patch()
@@ -122,7 +122,7 @@ class RailEnvPersister(object):
width=width, height=height,
rail_generator=rail_gen.rail_from_file(filename,
load_from_package=load_from_package),
- schedule_generator=sched_gen.schedule_from_file(filename,
+ line_generator=line_gen.line_from_file(filename,
load_from_package=load_from_package),
#malfunction_generator_and_process_data=mal_gen.malfunction_from_file(filename,
# load_from_package=load_from_package),
diff --git a/tests/test_action_plan.py b/tests/test_action_plan.py
index 815ecbcd7c1e091681b67d5c095b890ae6ab798a..d5c95408c21bf4f427dbbae929e36cc40ee79065 100644
--- a/tests/test_action_plan.py
+++ b/tests/test_action_plan.py
@@ -34,25 +34,29 @@ def test_action_plan(rendering: bool = False):
for handle, agent in enumerate(env.agents):
print("[{}] {} -> {}".format(handle, agent.initial_position, agent.target))
- chosen_path_dict = {0: [TrainrunWaypoint(lined_at=0, waypoint=Waypoint(position=(3, 0), direction=3)),
- TrainrunWaypoint(lined_at=2, waypoint=Waypoint(position=(3, 1), direction=1)),
- TrainrunWaypoint(lined_at=3, waypoint=Waypoint(position=(3, 2), direction=1)),
- TrainrunWaypoint(lined_at=14, waypoint=Waypoint(position=(3, 3), direction=1)),
- TrainrunWaypoint(lined_at=15, waypoint=Waypoint(position=(3, 4), direction=1)),
- TrainrunWaypoint(lined_at=16, waypoint=Waypoint(position=(3, 5), direction=1)),
- TrainrunWaypoint(lined_at=17, waypoint=Waypoint(position=(3, 6), direction=1)),
- TrainrunWaypoint(lined_at=18, waypoint=Waypoint(position=(3, 7), direction=1)),
- TrainrunWaypoint(lined_at=19, waypoint=Waypoint(position=(3, 8), direction=1)),
- TrainrunWaypoint(lined_at=20, waypoint=Waypoint(position=(3, 8), direction=5))],
- 1: [TrainrunWaypoint(lined_at=0, waypoint=Waypoint(position=(3, 8), direction=3)),
- TrainrunWaypoint(lined_at=3, waypoint=Waypoint(position=(3, 7), direction=3)),
- TrainrunWaypoint(lined_at=5, waypoint=Waypoint(position=(3, 6), direction=3)),
- TrainrunWaypoint(lined_at=7, waypoint=Waypoint(position=(3, 5), direction=3)),
- TrainrunWaypoint(lined_at=9, waypoint=Waypoint(position=(3, 4), direction=3)),
- TrainrunWaypoint(lined_at=11, waypoint=Waypoint(position=(3, 3), direction=3)),
- TrainrunWaypoint(lined_at=13, waypoint=Waypoint(position=(2, 3), direction=0)),
- TrainrunWaypoint(lined_at=15, waypoint=Waypoint(position=(1, 3), direction=0)),
- TrainrunWaypoint(lined_at=17, waypoint=Waypoint(position=(0, 3), direction=0))]}
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
+ chosen_path_dict = {0: [TrainrunWaypoint(scheduled_at=0, waypoint=Waypoint(position=(3, 0), direction=3)),
+ TrainrunWaypoint(scheduled_at=2, waypoint=Waypoint(position=(3, 1), direction=1)),
+ TrainrunWaypoint(scheduled_at=3, waypoint=Waypoint(position=(3, 2), direction=1)),
+ TrainrunWaypoint(scheduled_at=14, waypoint=Waypoint(position=(3, 3), direction=1)),
+ TrainrunWaypoint(scheduled_at=15, waypoint=Waypoint(position=(3, 4), direction=1)),
+ TrainrunWaypoint(scheduled_at=16, waypoint=Waypoint(position=(3, 5), direction=1)),
+ TrainrunWaypoint(scheduled_at=17, waypoint=Waypoint(position=(3, 6), direction=1)),
+ TrainrunWaypoint(scheduled_at=18, waypoint=Waypoint(position=(3, 7), direction=1)),
+ TrainrunWaypoint(scheduled_at=19, waypoint=Waypoint(position=(3, 8), direction=1)),
+ TrainrunWaypoint(scheduled_at=20, waypoint=Waypoint(position=(3, 8), direction=5))],
+ 1: [TrainrunWaypoint(scheduled_at=0, waypoint=Waypoint(position=(3, 8), direction=3)),
+ TrainrunWaypoint(scheduled_at=3, waypoint=Waypoint(position=(3, 7), direction=3)),
+ TrainrunWaypoint(scheduled_at=5, waypoint=Waypoint(position=(3, 6), direction=3)),
+ TrainrunWaypoint(scheduled_at=7, waypoint=Waypoint(position=(3, 5), direction=3)),
+ TrainrunWaypoint(scheduled_at=9, waypoint=Waypoint(position=(3, 4), direction=3)),
+ TrainrunWaypoint(scheduled_at=11, waypoint=Waypoint(position=(3, 3), direction=3)),
+ TrainrunWaypoint(scheduled_at=13, waypoint=Waypoint(position=(2, 3), direction=0)),
+ TrainrunWaypoint(scheduled_at=15, waypoint=Waypoint(position=(1, 3), direction=0)),
+ TrainrunWaypoint(scheduled_at=17, waypoint=Waypoint(position=(0, 3), direction=0))]}
expected_action_plan = [[
# take action to enter the grid
ActionPlanElement(0, RailEnvActions.MOVE_FORWARD),
diff --git a/tests/test_flaltland_rail_agent_status.py b/tests/test_flaltland_rail_agent_status.py
index 4f507415e8acc25a1d931b68f249d568839fd609..87b373051c30e90fb3665a78d8d8e5a46a468d91 100644
--- a/tests/test_flaltland_rail_agent_status.py
+++ b/tests/test_flaltland_rail_agent_status.py
@@ -17,6 +17,11 @@ def test_initial_status():
obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()),
remove_agents_at_target=False)
env.reset()
+
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
set_penalties_for_replay(env)
test_config = ReplayConfig(
replay=[
@@ -126,6 +131,10 @@ def test_status_done_remove():
remove_agents_at_target=True)
env.reset()
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
set_penalties_for_replay(env)
test_config = ReplayConfig(
replay=[
diff --git a/tests/test_flatland_envs_rail_env.py b/tests/test_flatland_envs_rail_env.py
index c531359a2d3d573db32cdec7515155511e5f6d57..53a61c8f755f813d10f892f1a60f17d8650a89e7 100644
--- a/tests/test_flatland_envs_rail_env.py
+++ b/tests/test_flatland_envs_rail_env.py
@@ -9,9 +9,9 @@ from flatland.envs.agent_utils import EnvAgent
from flatland.envs.observations import GlobalObsForRailEnv, TreeObsForRailEnv
from flatland.envs.predictions import ShortestPathPredictorForRailEnv
from flatland.envs.rail_env import RailEnv, RailEnvActions
-from flatland.envs.rail_generators import complex_rail_generator, rail_from_file
+from flatland.envs.rail_generators import sparse_rail_generator, rail_from_file
from flatland.envs.rail_generators import rail_from_grid_transition_map
-from flatland.envs.line_generators import random_line_generator, complex_line_generator, line_from_file
+from flatland.envs.line_generators import random_line_generator, sparse_line_generator, line_from_file
from flatland.utils.simple_rail import make_simple_rail
from flatland.envs.persistence import RailEnvPersister
from flatland.utils.rendertools import RenderTool
@@ -37,9 +37,10 @@ def test_load_env():
def test_save_load():
env = RailEnv(width=10, height=10,
- rail_generator=complex_rail_generator(nr_start_goal=2, nr_extra=5, min_dist=6, seed=1),
- line_generator=complex_line_generator(), number_of_agents=2)
+ rail_generator=sparse_rail_generator(nr_start_goal=2, nr_extra=5, min_dist=6, seed=1),
+ line_generator=sparse_line_generator(), number_of_agents=2)
env.reset()
+
agent_1_pos = env.agents[0].position
agent_1_dir = env.agents[0].direction
agent_1_tar = env.agents[0].target
diff --git a/tests/test_flatland_envs_rail_env_shortest_paths.py b/tests/test_flatland_envs_rail_env_shortest_paths.py
index b2ee9b015c74f74c651aa6396dee3c6ea5a49ce4..ce88aeb81d06875768e903eb63582b2a79160e91 100644
--- a/tests/test_flatland_envs_rail_env_shortest_paths.py
+++ b/tests/test_flatland_envs_rail_env_shortest_paths.py
@@ -23,6 +23,10 @@ def test_get_shortest_paths_unreachable():
obs_builder_object=GlobalObsForRailEnv())
env.reset()
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
# set the initial position
agent = env.agents[0]
agent.position = (3, 1) # west dead-end
@@ -36,7 +40,7 @@ def test_get_shortest_paths_unreachable():
actual = get_shortest_paths(env.distance_map)
expected = {0: None}
- assert actual == expected, "actual={},expected={}".format(actual, expected)
+ assert actual[0] == expected[0], "actual={},expected={}".format(actual[0], expected[0])
# todo file test_002.pkl has to be generated automatically
diff --git a/tests/test_flatland_envs_sparse_rail_generator.py b/tests/test_flatland_envs_sparse_rail_generator.py
index 3e74d720d4276dae588a3989843ada9d1761671d..74e71daced5cde123f7b25054b264ebeee816888 100644
--- a/tests/test_flatland_envs_sparse_rail_generator.py
+++ b/tests/test_flatland_envs_sparse_rail_generator.py
@@ -1512,7 +1512,7 @@ def test_sparse_generator_changes_to_grid_mode():
rail_env = RailEnv(width=10, height=20, rail_generator=sparse_rail_generator(
max_num_cities=100,
max_rails_between_cities=2,
- max_rails_in_city=2,
+ max_rail_pairs_in_city=1,
seed=15,
grid_mode=False
), line_generator=sparse_line_generator(), number_of_agents=10,
diff --git a/tests/test_flatland_schedule_from_file.py b/tests/test_flatland_line_from_file.py
similarity index 79%
rename from tests/test_flatland_schedule_from_file.py
rename to tests/test_flatland_line_from_file.py
index 0b903eae8b56864afc60d0d0d01923e337796479..b324af98a8550a47621be6258d2d559f128f45a5 100644
--- a/tests/test_flatland_schedule_from_file.py
+++ b/tests/test_flatland_line_from_file.py
@@ -25,12 +25,14 @@ def test_line_from_file_sparse():
seed=1,
grid_mode=False,
max_rails_between_cities=3,
- max_rails_in_city=6,
+ max_rail_pairs_in_city=3,
)
line_generator = sparse_line_generator(speed_ration_map)
- create_and_save_env(file_name="./sparse_env_test.pkl", rail_generator=rail_generator,
+ env = create_and_save_env(file_name="./sparse_env_test.pkl", rail_generator=rail_generator,
line_generator=line_generator)
+ old_num_steps = env._max_episode_steps
+ old_num_agents = len(env.agents)
# Sparse generator
@@ -41,10 +43,10 @@ def test_line_from_file_sparse():
sparse_env_from_file.reset(True, True)
# Assert loaded agent number is correct
- assert sparse_env_from_file.get_num_agents() == 10
+ assert sparse_env_from_file.get_num_agents() == old_num_agents
# Assert max steps is correct
- assert sparse_env_from_file._max_episode_steps == 500
+ assert sparse_env_from_file._max_episode_steps == old_num_steps
@@ -65,8 +67,10 @@ def test_line_from_file_random():
rail_generator = random_rail_generator()
line_generator = random_line_generator(speed_ration_map)
- create_and_save_env(file_name="./random_env_test.pkl", rail_generator=rail_generator,
+ env = create_and_save_env(file_name="./random_env_test.pkl", rail_generator=rail_generator,
line_generator=line_generator)
+ old_num_steps = env._max_episode_steps
+ old_num_agents = len(env.agents)
# Random generator
@@ -77,10 +81,10 @@ def test_line_from_file_random():
random_env_from_file.reset(True, True)
# Assert loaded agent number is correct
- assert random_env_from_file.get_num_agents() == 10
+ assert random_env_from_file.get_num_agents() == old_num_agents
# Assert max steps is correct
- assert random_env_from_file._max_episode_steps == 1350
+ assert random_env_from_file._max_episode_steps == old_num_steps
@@ -105,8 +109,10 @@ def test_line_from_file_complex():
max_dist=99999)
line_generator = complex_line_generator(speed_ration_map)
- create_and_save_env(file_name="./complex_env_test.pkl", rail_generator=rail_generator,
+ env = create_and_save_env(file_name="./complex_env_test.pkl", rail_generator=rail_generator,
line_generator=line_generator)
+ old_num_steps = env._max_episode_steps
+ old_num_agents = len(env.agents)
# Load the different envs and check the parameters
@@ -119,7 +125,7 @@ def test_line_from_file_complex():
complex_env_from_file.reset(True, True)
# Assert loaded agent number is correct
- assert complex_env_from_file.get_num_agents() == 10
+ assert complex_env_from_file.get_num_agents() == old_num_agents
# Assert max steps is correct
- assert complex_env_from_file._max_episode_steps == 1350
+ assert complex_env_from_file._max_episode_steps == old_num_steps
diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py
index 53915102c539c8e7703434100634c36fda001049..8675f54fb68bc4203a0a5e3fd9799791fa4ca539 100644
--- a/tests/test_flatland_malfunction.py
+++ b/tests/test_flatland_malfunction.py
@@ -97,6 +97,8 @@ def test_malfunction_process():
actions[i] = np.argmax(obs[i]) + 1
obs, all_rewards, done, _ = env.step(actions)
+ if done["__all__"]:
+ break
if env.agents[0].malfunction_data['malfunction'] > 0:
agent_malfunctioning = True
diff --git a/tests/test_global_observation.py b/tests/test_global_observation.py
index 5b090681813b9976285fe5a726ff9e7dc0226b08..851d849d1246773d7d06b5f38ed0eef820f74a56 100644
--- a/tests/test_global_observation.py
+++ b/tests/test_global_observation.py
@@ -30,6 +30,10 @@ def test_get_global_observation():
obs_builder_object=GlobalObsForRailEnv())
env.reset()
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
obs, all_rewards, done, _ = env.step({i: RailEnvActions.MOVE_FORWARD for i in range(number_of_agents)})
for i in range(len(env.agents)):
agent: EnvAgent = env.agents[i]
diff --git a/tests/test_multi_speed.py b/tests/test_multi_speed.py
index 08b46d00f4a458cfd105d568ca2a045f122cc8bc..2664c5b4f8b18004b4a39095c16acee753832eb7 100644
--- a/tests/test_multi_speed.py
+++ b/tests/test_multi_speed.py
@@ -51,6 +51,7 @@ def test_multi_speed_init():
rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=1, min_dist=8, max_dist=99999,
seed=1), line_generator=complex_line_generator(),
number_of_agents=5)
+
# Initialize the agent with the parameters corresponding to the environment and observation_builder
agent = RandomAgent(218, 4)
@@ -197,6 +198,12 @@ def test_multispeed_actions_no_malfunction_blocking():
line_generator=random_line_generator(), number_of_agents=2,
obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()))
env.reset()
+
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
+
set_penalties_for_replay(env)
test_configs = [
ReplayConfig(
@@ -381,7 +388,11 @@ def test_multispeed_actions_malfunction_no_blocking():
line_generator=random_line_generator(), number_of_agents=1,
obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()))
env.reset()
-
+
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
+
set_penalties_for_replay(env)
test_config = ReplayConfig(
replay=[
@@ -515,6 +526,10 @@ def test_multispeed_actions_no_malfunction_invalid_actions():
line_generator=random_line_generator(), number_of_agents=1,
obs_builder_object=TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv()))
env.reset()
+
+ # Perform DO_NOTHING actions until all trains get to READY_TO_DEPART
+ for _ in range(max([agent.earliest_departure for agent in env.agents])):
+ env.step({}) # DO_NOTHING for all agents
set_penalties_for_replay(env)
test_config = ReplayConfig(
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 4e7c30ca72811b78c564d0c11a011dd4b9e04998..062d56f00dd704960b316e318ee311f5c7a03539 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -152,4 +152,4 @@ def create_and_save_env(file_name: str, line_generator: LineGenerator, rail_gene
env.reset(True, True)
#env.save(file_name)
RailEnvPersister.save(env, file_name)
-
+ return env