removed unused example

examples/simple_example_3.py

-import random
-
-import numpy as np
-
-from flatland.envs.observations import TreeObsForRailEnv
-from flatland.envs.rail_env import RailEnv
-from flatland.envs.rail_generators import complex_rail_generator
-from flatland.envs.schedule_generators import complex_schedule_generator
-from flatland.utils.rendertools import RenderTool
-
-random.seed(1)
-np.random.seed(1)
-
-env = RailEnv(width=7,
-              height=7,
-              rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=1, min_dist=5, max_dist=99999, seed=1),
-              schedule_generator=complex_schedule_generator(),
-              number_of_agents=2,
-              obs_builder_object=TreeObsForRailEnv(max_depth=2))
-
-env.reset()
-
-# Print the observation vector for agent 0
-obs, all_rewards, done, _ = env.step({0: 0})
-for i in range(env.get_num_agents()):
-    env.obs_builder.util_print_obs_subtree(tree=obs[i])
-
-env_renderer = RenderTool(env)
-env_renderer.render_env(show=True, frames=True)
-
-print("Manual control: s=perform step, q=quit, [agent id] [1-2-3 action] \
-       (turnleft+move, move to front, turnright+move)")
-for step in range(100):
-    cmd = input(">> ")
-    cmds = cmd.split(" ")
-
-    action_dict = {}
-
-    i = 0
-    while i < len(cmds):
-        if cmds[i] == 'q':
-            break
-        elif cmds[i] == 's':
-            obs, all_rewards, done, _ = env.step(action_dict)
-            action_dict = {}
-            print("Rewards: ", all_rewards, "  [done=", done, "]")
-        else:
-            agent_id = int(cmds[i])
-            action = int(cmds[i + 1])
-            action_dict[agent_id] = action
-            i = i + 1
-        i += 1
-        env_renderer.render_env(show=True, frames=True)