This adresses issue #263 by adding tests to see that malfunciton works as expected

tests/test_flatland_malfunction.py

@@ -156,14 +156,20 @@ 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 = [[] 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]]
 
     for step in range(20):
         action_dict: Dict[int, RailEnvActions] = {}
@@ -175,7 +181,7 @@ def test_malfunction_process_statistically():
             assert env.agents[agent_idx].malfunction_data['malfunction'] == agent_malfunction_list[step][agent_idx]
         env.step(action_dict)
     # For generating test onlz
-    #print(agent_malfunction_list)
+    # print(agent_malfunction_list)
 
 
 def test_malfunction_before_entry():
@@ -213,6 +219,7 @@ def test_malfunction_before_entry():
     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
@@ -237,7 +244,7 @@ def test_next_malfunction_counter():
     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
+    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):
@@ -248,6 +255,47 @@ def test_next_malfunction_counter():
         assert env.agents[0].malfunction_data['next_malfunction'] == 5 - time_step
 
 
+def test_malfunction_values_and_behavior():
+    """
+    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] = {}
+    stochastic_data = {'prop_malfunction': 1.,
+                       'malfunction_rate': 5,
+                       'min_duration': 10,
+                       'max_duration': 10}
+    env = RailEnv(width=25,
+                  height=30,
+                  rail_generator=rail_from_grid_transition_map(rail),
+                  schedule_generator=random_schedule_generator(seed=2),  # seed 12
+                  stochastic_data=stochastic_data,
+                  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):
+        # 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)
+
 
 def test_initial_malfunction():
     stochastic_data = {'prop_malfunction': 1.,  # Percentage of defective agents
@@ -295,15 +343,15 @@ def test_initial_malfunction():
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=1,
-                reward= env.step_penalty * 1.0
+                reward=env.step_penalty * 1.0
 
-            ),# malfunctioning ends: starting and running at speed 1.0
+            ),  # malfunctioning ends: starting and running at speed 1.0
             Replay(
                 position=(3, 2),
                 direction=Grid4TransitionsEnum.EAST,
                 action=RailEnvActions.MOVE_FORWARD,
                 malfunction=0,
-                reward=env.start_penalty +env.step_penalty * 1.0  # running at speed 1.0
+                reward=env.start_penalty + env.step_penalty * 1.0  # running at speed 1.0
             ),
             Replay(
                 position=(3, 3),