added and fixed tests for sparse_rail_generator

tests/test_flatland_malfunction.py

@@ -9,8 +9,9 @@ from flatland.core.grid.grid4 import Grid4TransitionsEnum
 from flatland.core.grid.grid4_utils import get_new_position
 from flatland.envs.agent_utils import RailAgentStatus
 from flatland.envs.rail_env import RailEnv, RailEnvActions
-from flatland.envs.rail_generators import complex_rail_generator, sparse_rail_generator
-from flatland.envs.schedule_generators import complex_schedule_generator, sparse_schedule_generator
+from flatland.envs.rail_generators import rail_from_grid_transition_map
+from flatland.envs.schedule_generators import random_schedule_generator
+from flatland.utils.simple_rail import make_simple_rail2
 
 
 class SingleAgentNavigationObs(ObservationBuilder):
@@ -69,16 +70,27 @@ def test_malfunction_process():
                        'malfunction_rate': 1000,
                        'min_duration': 3,
                        'max_duration': 3}
-    np.random.seed(5)
+    random.seed(0)
+    np.random.seed(0)
 
-    env = RailEnv(width=20,
-                  height=20,
-                  rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=1, min_dist=5, max_dist=99999,
-                                                        seed=0),
-                  schedule_generator=complex_schedule_generator(),
-                  number_of_agents=2,
-                  obs_builder_object=SingleAgentNavigationObs(),
-                  stochastic_data=stochastic_data)
+    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()
 
     obs = env.reset(False, False, True)
 
@@ -117,7 +129,7 @@ def test_malfunction_process():
         total_down_time += env.agents[0].malfunction_data['malfunction']
 
     # Check that the appropriate number of malfunctions is achieved
-    assert env.agents[0].malfunction_data['nr_malfunctions'] == 21, "Actual {}".format(
+    assert env.agents[0].malfunction_data['nr_malfunctions'] == 11, "Actual {}".format(
         env.agents[0].malfunction_data['nr_malfunctions'])
 
     # Check that 20 stops where performed
@@ -135,16 +147,26 @@ def test_malfunction_process_statistically():
                        'min_duration': 3,
                        'max_duration': 3}
 
-    env = RailEnv(width=20,
-                  height=20,
-                  rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=1, min_dist=5, max_dist=99999,
-                                                        seed=0),
-                  schedule_generator=complex_schedule_generator(),
-                  number_of_agents=2,
-                  obs_builder_object=SingleAgentNavigationObs(),
-                  stochastic_data=stochastic_data)
-    np.random.seed(5)
     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(False, False, True)
     nb_malfunction = 0
     for step in range(100):
@@ -158,38 +180,39 @@ def test_malfunction_process_statistically():
         env.step(action_dict)
 
     # check that generation of malfunctions works as expected
-    assert nb_malfunction == 128, "nb_malfunction={}".format(nb_malfunction)
+    assert nb_malfunction == 3, "nb_malfunction={}".format(nb_malfunction)
 
 
 def test_initial_malfunction():
+
+    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
                        }
 
-    speed_ration_map = {1.: 1.,  # Fast passenger train
-                        1. / 2.: 0.,  # Fast freight train
-                        1. / 3.: 0.,  # Slow commuter train
-                        1. / 4.: 0.}  # Slow freight train
-    np.random.seed(5)
-    random.seed(0)
+    rail, rail_map = make_simple_rail2()
+
     env = RailEnv(width=25,
                   height=30,
-                  rail_generator=sparse_rail_generator(max_num_cities=5,
-                                                       max_rails_between_cities=3,
-                                                       seed=215545,
-                                                       grid_mode=True
-                                                       ),
-                  schedule_generator=sparse_schedule_generator(speed_ration_map),
+                  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(False, False, True)
+
     set_penalties_for_replay(env)
     replay_config = ReplayConfig(
         replay=[
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 set_malfunction=3,
@@ -197,7 +220,7 @@ def test_initial_malfunction():
                 reward=env.step_penalty  # full step penalty when malfunctioning
             ),
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=2,
@@ -206,7 +229,7 @@ def test_initial_malfunction():
             # malfunction stops in the next step and we're still at the beginning of the cell
             # --> if we take action MOVE_FORWARD, agent should restart and move to the next cell
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=1,
@@ -214,15 +237,15 @@ def test_initial_malfunction():
                 # malfunctioning ends: starting and running at speed 1.0
             ),
             Replay(
-                position=(28, 6),
+                position=(3, 3),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
                 reward=env.step_penalty * 1.0  # running at speed 1.0
             ),
             Replay(
-                position=(27, 6),
-                direction=Grid4TransitionsEnum.NORTH,
+                position=(3, 4),
+                direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
                 reward=env.step_penalty * 1.0  # running at speed 1.0
@@ -230,37 +253,36 @@ def test_initial_malfunction():
         ],
         speed=env.agents[0].speed_data['speed'],
         target=env.agents[0].target,
-        initial_position=(28, 5),
+        initial_position=(3, 2),
         initial_direction=Grid4TransitionsEnum.EAST,
     )
-    sparse_generator_stable = False
-    if sparse_generator_stable:
-        run_replay_config(env, [replay_config])
+    run_replay_config(env, [replay_config])
 
 
 def test_initial_malfunction_stop_moving():
+    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
                        }
 
-    speed_ration_map = {1.: 1.,  # Fast passenger train
-                        1. / 2.: 0.,  # Fast freight train
-                        1. / 3.: 0.,  # Slow commuter train
-                        1. / 4.: 0.}  # Slow freight train
+    rail, rail_map = make_simple_rail2()
 
     env = RailEnv(width=25,
                   height=30,
-                  rail_generator=sparse_rail_generator(max_num_cities=5,
-                                                       max_rails_between_cities=3,
-                                                       seed=215545,
-                                                       grid_mode=True
-                                                       ),
-                  schedule_generator=sparse_schedule_generator(speed_ration_map),
+                  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
+
+    print(env.agents[0].initial_position, env.agents[0].direction, env.agents[0].position, env.agents[0].status)
+
     set_penalties_for_replay(env)
     replay_config = ReplayConfig(
         replay=[
@@ -274,7 +296,7 @@ def test_initial_malfunction_stop_moving():
                 status=RailAgentStatus.READY_TO_DEPART
             ),
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.DO_NOTHING,
                 malfunction=2,
@@ -285,7 +307,7 @@ def test_initial_malfunction_stop_moving():
             # --> if we take action STOP_MOVING, agent should restart without moving
             #
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.STOP_MOVING,
                 malfunction=1,
@@ -294,7 +316,7 @@ def test_initial_malfunction_stop_moving():
             ),
             # we have stopped and do nothing --> should stand still
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.DO_NOTHING,
                 malfunction=0,
@@ -303,7 +325,7 @@ def test_initial_malfunction_stop_moving():
             ),
             # we start to move forward --> should go to next cell now
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
@@ -311,7 +333,7 @@ def test_initial_malfunction_stop_moving():
                 status=RailAgentStatus.ACTIVE
             ),
             Replay(
-                position=(28, 6),
+                position=(3, 3),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
@@ -321,12 +343,11 @@ def test_initial_malfunction_stop_moving():
         ],
         speed=env.agents[0].speed_data['speed'],
         target=env.agents[0].target,
-        initial_position=(28, 5),
+        initial_position=(3, 2),
         initial_direction=Grid4TransitionsEnum.EAST,
     )
-    sparse_generator_stable = False
-    if sparse_generator_stable:
-        run_replay_config(env, [replay_config], activate_agents=False)
+
+    run_replay_config(env, [replay_config], activate_agents=False)
 
 
 def test_initial_malfunction_do_nothing():
@@ -339,22 +360,18 @@ def test_initial_malfunction_do_nothing():
                        'max_duration': 5  # Max duration of malfunction
                        }
 
-    speed_ration_map = {1.: 1.,  # Fast passenger train
-                        1. / 2.: 0.,  # Fast freight train
-                        1. / 3.: 0.,  # Slow commuter train
-                        1. / 4.: 0.}  # Slow freight train
+    rail, rail_map = make_simple_rail2()
+
 
     env = RailEnv(width=25,
                   height=30,
-                  rail_generator=sparse_rail_generator(max_num_cities=5,
-                                                       max_rails_between_cities=3,
-                                                       seed=215545,
-                                                       grid_mode=True
-                                                       ),
-                  schedule_generator=sparse_schedule_generator(speed_ration_map),
+                  rail_generator=rail_from_grid_transition_map(rail),
+                  schedule_generator=random_schedule_generator(),
                   number_of_agents=1,
                   stochastic_data=stochastic_data,  # Malfunction data generator
                   )
+    # reset to initialize agents_static
+    env.reset()
     set_penalties_for_replay(env)
     replay_config = ReplayConfig(
         replay=[
@@ -368,7 +385,7 @@ def test_initial_malfunction_do_nothing():
                 status=RailAgentStatus.READY_TO_DEPART
             ),
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.DO_NOTHING,
                 malfunction=2,
@@ -379,7 +396,7 @@ def test_initial_malfunction_do_nothing():
             # --> if we take action DO_NOTHING, agent should restart without moving
             #
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.DO_NOTHING,
                 malfunction=1,
@@ -388,24 +405,24 @@ def test_initial_malfunction_do_nothing():
             ),
             # we haven't started moving yet --> stay here
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.DO_NOTHING,
                 malfunction=0,
                 reward=env.step_penalty,  # full step penalty while stopped
                 status=RailAgentStatus.ACTIVE
             ),
-            # we start to move forward --> should go to next cell now
+
             Replay(
-                position=(28, 5),
+                position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
                 reward=env.start_penalty + env.step_penalty * 1.0,  # start penalty + step penalty for speed 1.0
                 status=RailAgentStatus.ACTIVE
-            ),
+            ),  # we start to move forward --> should go to next cell now
             Replay(
-                position=(28, 6),
+                position=(3, 3),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
@@ -415,12 +432,10 @@ def test_initial_malfunction_do_nothing():
         ],
         speed=env.agents[0].speed_data['speed'],
         target=env.agents[0].target,
-        initial_position=(28, 5),
+        initial_position=(3, 2),
         initial_direction=Grid4TransitionsEnum.EAST,
     )
-    sparse_generator_stable = False
-    if sparse_generator_stable:
-        run_replay_config(env, [replay_config], activate_agents=False)
+    run_replay_config(env, [replay_config], activate_agents=False)
 
 
 def test_initial_nextmalfunction_not_below_zero():
@@ -428,27 +443,23 @@ def test_initial_nextmalfunction_not_below_zero():
     np.random.seed(0)
 
     stochastic_data = {'prop_malfunction': 1.,  # Percentage of defective agents
-                       'malfunction_rate': 0.5,  # Rate of malfunction occurence
-                       'min_duration': 5,  # Minimal duration of malfunction
+                       'malfunction_rate': 70,  # Rate of malfunction occurence
+                       'min_duration': 2,  # Minimal duration of malfunction
                        'max_duration': 5  # Max duration of malfunction
                        }
 
-    speed_ration_map = {1.: 1.,  # Fast passenger train
-                        1. / 2.: 0.,  # Fast freight train
-                        1. / 3.: 0.,  # Slow commuter train
-                        1. / 4.: 0.}  # Slow freight train
+    rail, rail_map = make_simple_rail2()
 
     env = RailEnv(width=25,
                   height=30,
-                  rail_generator=sparse_rail_generator(max_num_cities=5,
-                                                       max_rails_between_cities=3,
-                                                       seed=215545,
-                                                       grid_mode=True
-                                                       ),
-                  schedule_generator=sparse_schedule_generator(speed_ration_map),
+                  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