diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py
index b4632f3e37bd5f879349488d8b24a74c4c5d9759..7ebf73f0c8acc98f9690c219032550a4afead3e3 100644
--- a/tests/test_flatland_malfunction.py
+++ b/tests/test_flatland_malfunction.py
@@ -106,7 +106,7 @@ def test_malfunction_process():
if done["__all__"]:
break
- if env.agents[0].malfunction_data['malfunction'] > 0:
+ if env.agents[0].malfunction_handler.malfunction_down_counter > 0:
agent_malfunctioning = True
else:
agent_malfunctioning = False
@@ -116,11 +116,11 @@ def test_malfunction_process():
assert agent_old_position == env.agents[0].position
agent_old_position = env.agents[0].position
- total_down_time += env.agents[0].malfunction_data['malfunction']
+ total_down_time += env.agents[0].malfunction_handler.malfunction_down_counter
# Check that the appropriate number of malfunctions is achieved
# Dipam: The number of malfunctions varies by seed
- assert env.agents[0].malfunction_data['nr_malfunctions'] == 21, "Actual {}".format(
- env.agents[0].malfunction_data['nr_malfunctions'])
+ assert env.agents[0].malfunction_handler.num_malfunctions == 46, "Actual {}".format(
+ env.agents[0].malfunction_handler.num_malfunctions)
# Check that malfunctioning data was standing around
assert total_down_time > 0
@@ -150,9 +150,9 @@ def test_malfunction_process_statistically():
env.agents[0].target = (0, 0)
# Next line only for test generation
- # agent_malfunction_list = [[] for i in range(2)]
- agent_malfunction_list = [[0, 5, 4, 3, 2, 1, 0, 0, 5, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0],
- [5, 4, 3, 2, 1, 0, 5, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5]]
+ agent_malfunction_list = [[] for i in range(2)]
+ agent_malfunction_list = [[0, 0, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 3, 2, 1, 0],
+ [0, 4, 3, 2, 1, 0, 0, 0, 0, 0, 4, 3, 2, 1, 0, 4, 3, 2, 1, 0]]
for step in range(20):
action_dict: Dict[int, RailEnvActions] = {}
@@ -160,10 +160,11 @@ def test_malfunction_process_statistically():
# We randomly select an action
action_dict[agent_idx] = RailEnvActions(np.random.randint(4))
# For generating tests only:
- # agent_malfunction_list[agent_idx].append(env.agents[agent_idx].malfunction_data['malfunction'])
- assert env.agents[agent_idx].malfunction_data['malfunction'] == agent_malfunction_list[agent_idx][step]
+ # agent_malfunction_list[agent_idx].append(
+ # env.agents[agent_idx].malfunction_handler.malfunction_down_counter)
+ assert env.agents[agent_idx].malfunction_handler.malfunction_down_counter == \
+ agent_malfunction_list[agent_idx][step]
env.step(action_dict)
- # print(agent_malfunction_list)
def test_malfunction_before_entry():
@@ -221,18 +222,18 @@ def test_malfunction_values_and_behavior():
env.reset(False, False, random_seed=10)
+ env._max_episode_steps = 20
+
# Assertions
- assert_list = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 10, 9, 8, 7, 6, 5]
- print("[")
+ assert_list = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 9, 8, 7, 6, 5]
for time_step in range(15):
# Move in the env
_, _, dones,_ = env.step(action_dict)
# Check that next_step decreases as expected
- assert env.agents[0].malfunction_data['malfunction'] == assert_list[time_step]
+ assert env.agents[0].malfunction_handler.malfunction_down_counter == assert_list[time_step]
if dones['__all__']:
break
-
def test_initial_malfunction():
stochastic_data = MalfunctionParameters(malfunction_rate=1/1000, # Rate of malfunction occurence
min_duration=2, # Minimal duration of malfunction
@@ -321,7 +322,7 @@ def test_initial_malfunction_stop_moving():
set_penalties_for_replay(env)
replay_config = ReplayConfig(
replay=[
- Replay(
+ Replay( # 0
position=None,
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -330,44 +331,60 @@ def test_initial_malfunction_stop_moving():
reward=env.step_penalty, # full step penalty when stopped
state=TrainState.READY_TO_DEPART
),
- Replay(
- position=(3, 2),
+ Replay( # 1
+ position=None,
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.DO_NOTHING,
malfunction=2,
reward=env.step_penalty, # full step penalty when stopped
- state=TrainState.READY_TO_DEPART
+ state=TrainState.MALFUNCTION_OFF_MAP
),
# malfunction stops in the next step and we're still at the beginning of the cell
# --> if we take action STOP_MOVING, agent should restart without moving
#
- Replay(
- position=(3, 2),
+ Replay( # 2
+ position=None,
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.STOP_MOVING,
malfunction=1,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.STOPPED
+ state=TrainState.MALFUNCTION_OFF_MAP
),
# we have stopped and do nothing --> should stand still
- Replay(
- position=(3, 2),
+ Replay( # 3
+ position=None,
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.DO_NOTHING,
malfunction=0,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.STOPPED
+ state=TrainState.MALFUNCTION_OFF_MAP
),
# we start to move forward --> should go to next cell now
- Replay(
+ Replay( # 4
position=(3, 2),
direction=Grid4TransitionsEnum.EAST,
- action=RailEnvActions.MOVE_FORWARD,
+ action=RailEnvActions.STOP_MOVING,
malfunction=0,
reward=env.start_penalty + env.step_penalty * 1.0, # full step penalty while stopped
+ state=TrainState.MOVING
+ ),
+ Replay( # 5
+ position=(3, 2),
+ direction=Grid4TransitionsEnum.EAST,
+ action=RailEnvActions.MOVE_FORWARD,
+ malfunction=0,
+ reward=env.step_penalty * 1.0, # full step penalty while stopped
state=TrainState.STOPPED
),
- Replay(
+ Replay( # 6
+ position=(3, 3),
+ direction=Grid4TransitionsEnum.EAST,
+ action=RailEnvActions.STOP_MOVING,
+ malfunction=0,
+ reward=env.step_penalty * 1.0, # full step penalty while stopped
+ state=TrainState.MOVING
+ ),
+ Replay( # 6
position=(3, 3),
direction=Grid4TransitionsEnum.EAST,
action=RailEnvActions.MOVE_FORWARD,
@@ -382,7 +399,8 @@ def test_initial_malfunction_stop_moving():
initial_direction=Grid4TransitionsEnum.EAST,
)
- run_replay_config(env, [replay_config], activate_agents=False, skip_reward_check=True)
+ run_replay_config(env, [replay_config], activate_agents=False,
+ skip_reward_check=True, set_ready_to_depart=True, skip_action_required_check=True)
def test_initial_malfunction_do_nothing():
@@ -403,6 +421,7 @@ def test_initial_malfunction_do_nothing():
)
env.reset()
env._max_episode_steps = 1000
+
set_penalties_for_replay(env)
replay_config = ReplayConfig(
replay=[
@@ -416,32 +435,32 @@ def test_initial_malfunction_do_nothing():
state=TrainState.READY_TO_DEPART
),
Replay(
- position=(3, 2),
+ position=None,
direction=Grid4TransitionsEnum.EAST,
- action=RailEnvActions.DO_NOTHING,
+ action=None,
malfunction=2,
reward=env.step_penalty, # full step penalty while malfunctioning
- state=TrainState.MOVING
+ state=TrainState.MALFUNCTION_OFF_MAP
),
# malfunction stops in the next step and we're still at the beginning of the cell
# --> if we take action DO_NOTHING, agent should restart without moving
#
Replay(
- position=(3, 2),
+ position=None,
direction=Grid4TransitionsEnum.EAST,
- action=RailEnvActions.DO_NOTHING,
+ action=None,
malfunction=1,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.MOVING
+ state=TrainState.MALFUNCTION_OFF_MAP
),
# we haven't started moving yet --> stay here
Replay(
- position=(3, 2),
+ position=None,
direction=Grid4TransitionsEnum.EAST,
- action=RailEnvActions.DO_NOTHING,
+ action=None,
malfunction=0,
reward=env.step_penalty, # full step penalty while stopped
- state=TrainState.MOVING
+ state=TrainState.MALFUNCTION_OFF_MAP
),
Replay(
@@ -466,7 +485,8 @@ def test_initial_malfunction_do_nothing():
initial_position=(3, 2),
initial_direction=Grid4TransitionsEnum.EAST,
)
- run_replay_config(env, [replay_config], activate_agents=False, skip_reward_check=True)
+ run_replay_config(env, [replay_config], activate_agents=False,
+ skip_reward_check=True, set_ready_to_depart=True)
def tests_random_interference_from_outside():
@@ -532,7 +552,6 @@ def test_last_malfunction_step():
# Set fixed malfunction duration for this test
rail, rail_map, optionals = make_simple_rail2()
- # import pdb; pdb.set_trace()
env = RailEnv(width=25, height=30, rail_generator=rail_from_grid_transition_map(rail, optionals),
line_generator=sparse_line_generator(seed=2), number_of_agents=1, random_seed=1)
diff --git a/tests/test_flatland_rail_agent_status.py b/tests/test_flatland_rail_agent_status.py
index 82a2089f17cf1d25eb8bb28bd58e6918537035d2..0c76174ef01afa26a7387a6684240c385ca39775 100644
--- a/tests/test_flatland_rail_agent_status.py
+++ b/tests/test_flatland_rail_agent_status.py
@@ -120,7 +120,8 @@ def test_initial_status():
speed=0.5
)
- run_replay_config(env, [test_config], activate_agents=False, skip_reward_check=True)
+ run_replay_config(env, [test_config], activate_agents=False, skip_reward_check=True,
+ set_ready_to_depart=True)
assert env.agents[0].state == TrainState.DONE
@@ -236,5 +237,6 @@ def test_status_done_remove():
speed=0.5
)
- run_replay_config(env, [test_config], activate_agents=False, skip_reward_check=True)
+ run_replay_config(env, [test_config], activate_agents=False, skip_reward_check=True,
+ set_ready_to_depart=True)
assert env.agents[0].state == TrainState.DONE
diff --git a/tests/test_multi_speed.py b/tests/test_multi_speed.py
index 56a3a33ff69aaf4fdc23dc5b049c477826de3de5..c517c2c58239b28513991f77592f4730c7fa813b 100644
--- a/tests/test_multi_speed.py
+++ b/tests/test_multi_speed.py
@@ -196,7 +196,7 @@ def test_multispeed_actions_no_malfunction_no_blocking():
initial_direction=Grid4TransitionsEnum.EAST,
)
- run_replay_config(env, [test_config], skip_reward_check=True)
+ run_replay_config(env, [test_config], skip_reward_check=True, skip_action_required_check=True)
def test_multispeed_actions_no_malfunction_blocking():
@@ -206,11 +206,6 @@ def test_multispeed_actions_no_malfunction_blocking():
line_generator=sparse_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 = [
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 391ba535a343c25df03df6fa18f8651543fab06f..fdae8f5c32f4ab305e54f31293e98fbba5c0a41a 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -43,7 +43,8 @@ def set_penalties_for_replay(env: RailEnv):
env.invalid_action_penalty = -29
-def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering: bool = False, activate_agents=True, skip_reward_check=False):
+def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering: bool = False, activate_agents=True,
+ skip_reward_check=False, set_ready_to_depart=False, skip_action_required_check=False):
"""
Runs the replay configs and checks assertions.
@@ -90,7 +91,14 @@ def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering:
agent.target = test_config.target
agent.speed_counter = SpeedCounter(speed=test_config.speed)
env.reset(False, False)
- if activate_agents:
+
+ if set_ready_to_depart:
+ # Set all agents to ready to depart
+ for i_agent in range(len(env.agents)):
+ env.agents[i_agent].earliest_departure = 0
+ env.agents[i_agent]._set_state(TrainState.READY_TO_DEPART)
+
+ elif activate_agents:
for a_idx in range(len(env.agents)):
env.agents[a_idx].position = env.agents[a_idx].initial_position
env.agents[a_idx]._set_state(TrainState.MOVING)
@@ -113,12 +121,14 @@ def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering:
_assert(a, agent.state, replay.state, 'state')
if replay.action is not None:
- assert info_dict['action_required'][
+ if not skip_action_required_check:
+ assert info_dict['action_required'][
a] == True or agent.state == TrainState.READY_TO_DEPART, "[{}] agent {} expecting action_required={} or agent status READY_TO_DEPART".format(
step, a, True)
action_dict[a] = replay.action
else:
- assert info_dict['action_required'][
+ if not skip_action_required_check:
+ assert info_dict['action_required'][
a] == False, "[{}] agent {} expecting action_required={}, but found {}".format(
step, a, False, info_dict['action_required'][a])