code: def test_additive_ou(action_size, sigma_type):
      def greedy_action_func():
          return np.asarray([0] * action_size, dtype=np.float32)
  
      if sigma_type == "scalar":
          sigma = np.random.rand()
      elif sigma_type == "ndarray":
          sigma = np.random.rand(action_size)
      theta = np.random.rand()
  
      explorer = AdditiveOU(theta=theta, sigma=sigma)
  
      print("theta:", theta, "sigma", sigma)
      for t in range(100):
          a = explorer.select_action(t, greedy_action_func)
          print(t, a)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_additive_ou(action_size, sigma_type) and returns: np