text: import numpy as np
  from gym import make
  import matplotlib.pyplot as plt
  import multigoal_env
  np.set_printoptions(precision=2)
  env = make('TwoObjectRandomSize-v0')
  ind = 0
  for i in range(100):
      env.reset()
      env.set_goals(sub_goal_ind=ind)
      time_done = False
      while not time_done:
          # a = env.action_space.sample()
          a = np.array([0.0, -0.0, 0.0, 0.0])
          obs_, act_reward, time_done, act_info = env.step(a)
          # using sim.render needs to empty the LD_PRELOAD path and execute the script on terminal
          # export LD_PRELOAD=
          # img = env.env.sim.render(width=400, height=400, depth=True)
          # plt.imshow(img[1], cmap='Greys')
          # plt.show()
          # env.render()
      ind = (ind+1) % len(env.sub_goal_space)