merged stochastic breaking branch for testing.

examples/flatland_2_0_example.py

@@ -29,7 +29,7 @@ env = RailEnv(width=50,
                                                    num_neighb=4,  # Number of connections to other cities
                                                    seed=15,  # Random seed
                                                    ),
-              number_of_agents=35,
+              number_of_agents=10,
               stochastic_data=stochastic_data,  # Malfunction generator data
               obs_builder_object=TreeObservation)
 
@@ -74,7 +74,7 @@ class RandomAgent:
 # Initialize the agent with the parameters corresponding to the environment and observation_builder
 # Set action space to 4 to remove stop action
 agent = RandomAgent(218, 4)
-n_trials = 5
+n_trials = 1
 
 # Empty dictionary for all agent action
 action_dict = dict()
@@ -94,6 +94,7 @@ for trials in range(1, n_trials + 1):
 
     score = 0
     # Run episode
+    frame_step = 0
     for step in range(500):
         # Chose an action for each agent in the environment
         for a in range(env.get_num_agents()):
@@ -104,7 +105,8 @@ for trials in range(1, n_trials + 1):
         # reward and whether their are done
         next_obs, all_rewards, done, _ = env.step(action_dict)
         env_renderer.render_env(show=True, show_observations=False, show_predictions=False)
-
+        env_renderer.gl.save_image("./Images/flatland_2_0_frame_{:04d}.bmp".format(frame_step))
+        frame_step += 1
         # Update replay buffer and train agent
         for a in range(env.get_num_agents()):
             agent.step((obs[a], action_dict[a], all_rewards[a], next_obs[a], done[a]))