diff --git a/flatland/envs/rail_env.py b/flatland/envs/rail_env.py
index 53784a6725a24b65b2d026eaf353f7a72e375619..3139437106861d0f496e6c3e7e840300bd33307c 100644
--- a/flatland/envs/rail_env.py
+++ b/flatland/envs/rail_env.py
@@ -398,8 +398,8 @@ class RailEnv(Environment):
Malfunction generator that breaks agents at a given rate. It does randomly chose agent to break during the run
"""
- if np.random.random() < self._malfunction_prob(rate):
- breaking_agent = random.choice(self.agents)
+ if self.np_random.randn() < self._malfunction_prob(rate):
+ breaking_agent = self.np_random.choice(self.agents)
if breaking_agent.malfunction_data['malfunction'] < 1:
num_broken_steps = self.np_random.randint(self.min_number_of_steps_broken,
self.max_number_of_steps_broken + 1)
diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py
index 7eac117f94ba921b4b0ba406bdc3bcc258ba76c1..2f5ea5f2c4af3ab0e6c912202bdfd234bf0de7a0 100644
--- a/tests/test_flatland_malfunction.py
+++ b/tests/test_flatland_malfunction.py
@@ -120,8 +120,7 @@ def test_malfunction_process():
def test_malfunction_process_statistically():
"""Tests hat malfunctions are produced by stochastic_data!"""
# Set fixed malfunction duration for this test
- stochastic_data = {'prop_malfunction': 1.,
- 'malfunction_rate': 5,
+ stochastic_data = {'malfunction_rate': 5,
'min_duration': 5,
'max_duration': 5}
@@ -142,19 +141,19 @@ def test_malfunction_process_statistically():
env.agents[0].target = (0, 0)
# Next line only for test generation
# agent_malfunction_list = [[] for i in range(20)]
- agent_malfunction_list = [[0, 0, 0, 0, 5, 5, 0, 0, 0, 0], [0, 0, 0, 0, 5, 5, 0, 0, 0, 0],
- [0, 0, 0, 0, 4, 4, 0, 0, 0, 0],
- [0, 0, 0, 0, 3, 3, 0, 0, 0, 0], [0, 0, 0, 0, 2, 2, 0, 0, 0, 5],
- [0, 0, 0, 0, 1, 1, 5, 0, 0, 4],
- [0, 0, 0, 5, 0, 0, 4, 5, 0, 3], [5, 0, 0, 4, 0, 0, 3, 4, 0, 2],
- [4, 5, 0, 3, 5, 5, 2, 3, 5, 1],
- [3, 4, 0, 2, 4, 4, 1, 2, 4, 0], [2, 3, 5, 1, 3, 3, 0, 1, 3, 0],
- [1, 2, 4, 0, 2, 2, 0, 0, 2, 0],
- [0, 1, 3, 0, 1, 1, 5, 0, 1, 0], [0, 0, 2, 0, 0, 0, 4, 0, 0, 0],
- [5, 0, 1, 0, 0, 0, 3, 5, 0, 5],
- [4, 0, 0, 0, 5, 0, 2, 4, 0, 4], [3, 0, 0, 0, 4, 0, 1, 3, 5, 3],
- [2, 0, 0, 0, 3, 0, 0, 2, 4, 2],
- [1, 0, 5, 5, 2, 0, 0, 1, 3, 1], [0, 5, 4, 4, 1, 0, 5, 0, 2, 0]]
+ agent_malfunction_list = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+ [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+ [0, 0, 0, 0, 0, 0, 0, 0, 0, 4], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3],
+ [4, 0, 0, 0, 0, 0, 0, 0, 0, 2],
+ [3, 0, 0, 0, 0, 0, 0, 0, 0, 1], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+ [1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+ [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 4, 0, 0, 0],
+ [0, 0, 0, 0, 0, 0, 3, 0, 0, 0],
+ [0, 0, 0, 0, 0, 0, 2, 4, 0, 0], [0, 0, 0, 0, 0, 0, 1, 3, 0, 0],
+ [0, 0, 0, 0, 0, 0, 0, 2, 0, 0],
+ [0, 0, 0, 0, 0, 0, 0, 1, 0, 4], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3],
+ [0, 0, 0, 0, 0, 0, 0, 0, 0, 2],
+ [0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [4, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
for step in range(20):
action_dict: Dict[int, RailEnvActions] = {}
@@ -170,10 +169,9 @@ def test_malfunction_process_statistically():
def test_malfunction_before_entry():
- """Tests that malfunctions are working properlz for agents before entering the environment!"""
+ """Tests that malfunctions are working properly for agents before entering the environment!"""
# Set fixed malfunction duration for this test
- stochastic_data = {'prop_malfunction': 1.,
- 'malfunction_rate': 5,
+ stochastic_data = {'malfunction_rate': 1,
'min_duration': 10,
'max_duration': 10}
@@ -193,51 +191,15 @@ def test_malfunction_before_entry():
# Test initial malfunction values for all agents
# we want some agents to be malfuncitoning already and some to be working
# we want different next_malfunction values for the agents
- assert env.agents[0].malfunction_data['malfunction'] == 0
assert env.agents[1].malfunction_data['malfunction'] == 0
assert env.agents[2].malfunction_data['malfunction'] == 0
assert env.agents[3].malfunction_data['malfunction'] == 0
- assert env.agents[4].malfunction_data['malfunction'] == 10
- assert env.agents[5].malfunction_data['malfunction'] == 10
+ assert env.agents[4].malfunction_data['malfunction'] == 0
+ assert env.agents[5].malfunction_data['malfunction'] == 0
assert env.agents[6].malfunction_data['malfunction'] == 0
assert env.agents[7].malfunction_data['malfunction'] == 0
assert env.agents[8].malfunction_data['malfunction'] == 0
- assert env.agents[9].malfunction_data['malfunction'] == 0
-
-
-def test_next_malfunction_counter():
- """
- Test that the next malfunction occurs when desired
- Returns
- -------
-
- """
- # Set fixed malfunction duration for this test
-
- rail, rail_map = make_simple_rail2()
- action_dict: Dict[int, RailEnvActions] = {}
-
- env = RailEnv(width=25,
- height=30,
- rail_generator=rail_from_grid_transition_map(rail),
- schedule_generator=random_schedule_generator(seed=2), # seed 12
- number_of_agents=1,
- random_seed=1,
- )
- # reset to initialize agents_static
- env.reset(False, False, activate_agents=True, random_seed=10)
- env.agents[0].malfunction_data['next_malfunction'] = 5
- env.agents[0].malfunction_data['malfunction_rate'] = 5
- env.agents[0].malfunction_data['malfunction'] = 0
- env.agents[0].target = (0, 0), # Move the target out of range
- print(env.agents[0].position, env.agents[0].malfunction_data['next_malfunction'])
-
- for time_step in range(1, 6):
- # Move in the env
- env.step(action_dict)
-
- # Check that next_step decreases as expected
- assert env.agents[0].malfunction_data['next_malfunction'] == 5 - time_step
+ assert env.agents[9].malfunction_data['malfunction'] == 9
def test_malfunction_values_and_behavior():
@@ -251,8 +213,7 @@ def test_malfunction_values_and_behavior():
rail, rail_map = make_simple_rail2()
action_dict: Dict[int, RailEnvActions] = {}
- stochastic_data = {'prop_malfunction': 1.,
- 'malfunction_rate': 5,
+ stochastic_data = {'malfunction_rate': 5,
'min_duration': 10,
'max_duration': 10}
env = RailEnv(width=25,
@@ -263,23 +224,18 @@ def test_malfunction_values_and_behavior():
number_of_agents=1,
random_seed=1,
)
+
# reset to initialize agents_static
env.reset(False, False, activate_agents=True, random_seed=10)
- env.agents[0].malfunction_data['next_malfunction'] = 5
- env.agents[0].malfunction_data['malfunction_rate'] = 50
- env.agents[0].malfunction_data['malfunction'] = 0
- env.agents[0].target = (0, 0), # Move the target out of range
- print(env.agents[0].position, env.agents[0].malfunction_data['next_malfunction'])
- for time_step in range(1, 16):
+ # Assertions
+ assert_list = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 0, 9, 8, 7, 6]
+ print("[")
+ for time_step in range(15):
# Move in the env
env.step(action_dict)
- print(time_step)
# Check that next_step decreases as expected
- if env.agents[0].malfunction_data['malfunction'] < 1:
- assert env.agents[0].malfunction_data['next_malfunction'] == np.clip(5 - time_step, 0, 100)
- else:
- assert env.agents[0].malfunction_data['malfunction'] == np.clip(10 - (time_step - 6), 0, 100)
+ assert env.agents[0].malfunction_data['malfunction'] == assert_list[time_step]
def test_initial_malfunction():
@@ -529,45 +485,14 @@ def test_initial_malfunction_do_nothing():
run_replay_config(env, [replay_config], activate_agents=False)
-def test_initial_nextmalfunction_not_below_zero():
- random.seed(0)
- np.random.seed(0)
-
- stochastic_data = {'prop_malfunction': 1., # Percentage of defective agents
- 'malfunction_rate': 70, # Rate of malfunction occurence
- 'min_duration': 2, # Minimal duration of malfunction
- 'max_duration': 5 # Max duration of malfunction
- }
-
- rail, rail_map = make_simple_rail2()
-
- env = RailEnv(width=25,
- height=30,
- rail_generator=rail_from_grid_transition_map(rail),
- schedule_generator=random_schedule_generator(),
- number_of_agents=1,
- stochastic_data=stochastic_data, # Malfunction data generator
- obs_builder_object=SingleAgentNavigationObs()
- )
- # reset to initialize agents_static
- env.reset()
- agent = env.agents[0]
- env.step({})
- # was next_malfunction was -1 befor the bugfix https://gitlab.aicrowd.com/flatland/flatland/issues/186
- assert agent.malfunction_data['next_malfunction'] >= 0, \
- "next_malfunction should be >=0, found {}".format(agent.malfunction_data['next_malfunction'])
-
-
def tests_random_interference_from_outside():
"""Tests that malfunctions are produced by stochastic_data!"""
# Set fixed malfunction duration for this test
- stochastic_data = {'prop_malfunction': 1.,
- 'malfunction_rate': 1,
+ stochastic_data = {'malfunction_rate': 1,
'min_duration': 10,
'max_duration': 10}
rail, rail_map = make_simple_rail2()
-
env = RailEnv(width=25,
height=30,
rail_generator=rail_from_grid_transition_map(rail),
@@ -579,9 +504,7 @@ def tests_random_interference_from_outside():
env.reset()
# reset to initialize agents_static
env.agents[0].speed_data['speed'] = 0.33
- env.agents[0].initial_position = (3, 0)
- env.agents[0].target = (3, 9)
- env.reset(False, False, False)
+ env.reset(False, False, False, random_seed=10)
env_data = []
for step in range(200):
@@ -612,11 +535,8 @@ def tests_random_interference_from_outside():
env.reset()
# reset to initialize agents_static
env.agents[0].speed_data['speed'] = 0.33
- env.agents[0].initial_position = (3, 0)
- env.agents[0].target = (3, 9)
- env.reset(False, False, False)
+ env.reset(False, False, False, random_seed=10)
- # Print for test generation
dummy_list = [1, 2, 6, 7, 8, 9, 4, 5, 4]
for step in range(200):
action_dict: Dict[int, RailEnvActions] = {}
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 1a98c161829dedc429465b6606101fd19784cbaa..80656cbb490c39fc7352327faa9bf5859a1123e9 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -118,8 +118,6 @@ def run_replay_config(env: RailEnv, test_configs: List[ReplayConfig], rendering:
# recognizes the agent as potentially malfuncitoning
# We also set next malfunction to infitiy to avoid interference with our tests
agent.malfunction_data['malfunction'] = replay.set_malfunction
- agent.malfunction_data['malfunction_rate'] = max(agent.malfunction_data['malfunction_rate'], 1)
- agent.malfunction_data['next_malfunction'] = np.inf
agent.malfunction_data['moving_before_malfunction'] = agent.moving
_assert(a, agent.malfunction_data['malfunction'], replay.malfunction, 'malfunction')
print(step)