make FLATland core useable without rendering

flatland/action_plan/action_plan.py

@@ -7,7 +7,6 @@ from flatland.core.grid.grid_utils import Vec2dOperations as Vec2d
 from flatland.envs.rail_env import RailEnv, RailEnvActions
 from flatland.envs.rail_env_shortest_paths import get_action_for_move
 from flatland.envs.rail_trainrun_data_structures import Waypoint, Trainrun, TrainrunWaypoint
-from flatland.utils.rendertools import RenderTool, AgentRenderVariant
 
 # ---- ActionPlan ---------------
 # an action plan element represents the actions to be taken by an agent at the given time step
@@ -264,35 +263,3 @@ class ControllerFromTrainruns():
         # execute the action exactly minimum_cell_time before the entry into the next cell
         action = ActionPlanElement(next_trainrun_waypoint.scheduled_at - minimum_cell_time, next_action)
         action_plan.append(action)
-
-
-class ControllerFromTrainrunsReplayer():
-    """Allows to verify a `DeterministicController` by replaying it against a FLATland env without malfunction."""
-
-    @staticmethod
-    def replay_verify(ctl: ControllerFromTrainruns, env: RailEnv, rendering: bool):
-        """Replays this deterministic `ActionPlan` and verifies whether it is feasible."""
-        if rendering:
-            renderer = RenderTool(env, gl="PILSVG",
-                                  agent_render_variant=AgentRenderVariant.AGENT_SHOWS_OPTIONS_AND_BOX,
-                                  show_debug=True,
-                                  clear_debug_text=True,
-                                  screen_height=1000,
-                                  screen_width=1000)
-            renderer.render_env(show=True, show_observations=False, show_predictions=False)
-        i = 0
-        while not env.dones['__all__'] and i <= env._max_episode_steps:
-            for agent_id, agent in enumerate(env.agents):
-                waypoint: Waypoint = ctl.get_waypoint_before_or_at_step(agent_id, i)
-                assert agent.position == waypoint.position, \
-                    "before {}, agent {} at {}, expected {}".format(i, agent_id, agent.position,
-                                                                    waypoint.position)
-            actions = ctl.act(i)
-            print("actions for {}: {}".format(i, actions))
-
-            obs, all_rewards, done, _ = env.step(actions)
-
-            if rendering:
-                renderer.render_env(show=True, show_observations=False, show_predictions=False)
-
-            i += 1

flatland/action_plan/action_plan_player.py

+from flatland.action_plan.action_plan import ControllerFromTrainruns
+from flatland.envs.rail_env import RailEnv
+from flatland.envs.rail_trainrun_data_structures import Waypoint
+from flatland.utils.rendertools import RenderTool, AgentRenderVariant
+
+
+class ControllerFromTrainrunsReplayer():
+    """Allows to verify a `DeterministicController` by replaying it against a FLATland env without malfunction."""
+
+    @staticmethod
+    def replay_verify(ctl: ControllerFromTrainruns, env: RailEnv, rendering: bool):
+        """Replays this deterministic `ActionPlan` and verifies whether it is feasible."""
+        if rendering:
+            renderer = RenderTool(env, gl="PILSVG",
+                                  agent_render_variant=AgentRenderVariant.AGENT_SHOWS_OPTIONS_AND_BOX,
+                                  show_debug=True,
+                                  clear_debug_text=True,
+                                  screen_height=1000,
+                                  screen_width=1000)
+            renderer.render_env(show=True, show_observations=False, show_predictions=False)
+        i = 0
+        while not env.dones['__all__'] and i <= env._max_episode_steps:
+            for agent_id, agent in enumerate(env.agents):
+                waypoint: Waypoint = ctl.get_waypoint_before_or_at_step(agent_id, i)
+                assert agent.position == waypoint.position, \
+                    "before {}, agent {} at {}, expected {}".format(i, agent_id, agent.position,
+                                                                    waypoint.position)
+            actions = ctl.act(i)
+            print("actions for {}: {}".format(i, actions))
+
+            obs, all_rewards, done, _ = env.step(actions)
+
+            if rendering:
+                renderer.render_env(show=True, show_observations=False, show_predictions=False)
+
+            i += 1

tests/test_action_plan.py

-from flatland.action_plan.action_plan import TrainrunWaypoint, ControllerFromTrainrunsReplayer, ActionPlanElement, \
+from flatland.action_plan.action_plan import TrainrunWaypoint, ActionPlanElement, \
     ControllerFromTrainruns
+from flatland.action_plan.action_plan_player import ControllerFromTrainrunsReplayer
 from flatland.core.grid.grid4 import Grid4TransitionsEnum
 from flatland.envs.observations import GlobalObsForRailEnv
 from flatland.envs.rail_env import RailEnv, RailEnvActions