diff --git a/examples/flatland_2_0_example.py b/examples/flatland_2_0_example.py index 71a4e0e03e827e6a375ebb4e59f3bde3029e15c6..bd0aa3ff4773609841e7bf4fbeacac3c062a0f92 100644 --- a/examples/flatland_2_0_example.py +++ b/examples/flatland_2_0_example.py @@ -37,7 +37,11 @@ env = RailEnv(width=100, seed=14, # Random seed grid_mode=False, max_rails_between_cities=2, +<<<<<<< HEAD max_rails_in_city=13, +======= + max_rails_in_city=8, +>>>>>>> fixed first tests in malfunction test ), schedule_generator=sparse_schedule_generator(speed_ration_map), number_of_agents=100, diff --git a/flatland/envs/distance_map.py b/flatland/envs/distance_map.py index 2bc1a5117794959cca82d2edad821cb629397f78..c6e73b0bdbe752b8d5df9c4a0697bb621e5276ec 100644 --- a/flatland/envs/distance_map.py +++ b/flatland/envs/distance_map.py @@ -55,6 +55,7 @@ class DistanceMap: self.env_width = rail.width def _compute(self, agents: List[EnvAgent], rail: GridTransitionMap): + print("computing distance map") self.agents_previous_computation = self.agents self.distance_map = np.inf * np.ones(shape=(len(agents), self.env_height, diff --git a/tests/test_flatland_malfunction.py b/tests/test_flatland_malfunction.py index 571d2010520407e13f21b4c8827d737b8dbf41ac..faf4a4cc7dffaf1ef57c8dbbcc9bf84d2a19d6ff 100644 --- a/tests/test_flatland_malfunction.py +++ b/tests/test_flatland_malfunction.py @@ -82,7 +82,11 @@ def test_malfunction_process(): obs_builder_object=SingleAgentNavigationObs() ) # reset to initialize agents_static +<<<<<<< HEAD obs, info = env.reset(False, False, True, random_seed=10) +======= + obs, info = env.reset(False, False, True, random_seed=0) +>>>>>>> fixed first tests in malfunction test print(env.agents[0].malfunction_data) # Check that a initial duration for malfunction was assigned assert env.agents[0].malfunction_data['next_malfunction'] > 0 @@ -151,7 +155,11 @@ def test_malfunction_process_statistically(): obs_builder_object=SingleAgentNavigationObs() ) # reset to initialize agents_static +<<<<<<< HEAD env.reset(True, True, False, random_seed=10) +======= + env.reset(False, False, False, random_seed=0) +>>>>>>> fixed first tests in malfunction test env.agents[0].target = (0, 0) nb_malfunction = 0