code: def MAenv(scenario_name, continuous_actions=False):
      env_list = [
          "simple",
          "simple_adversary",
          "simple_crypto",
          "simple_push",
          "simple_speaker_listener",
          "simple_spread",
          "simple_tag",
          "simple_world_comm",
      ]
      assert (
          scenario_name in env_list
      ), "Env {} not found (valid envs include {})".format(
          scenario_name, env_list
      )
      if scenario_name == "simple":
          env = simple_v2.parallel_env(
              max_cycles=25, continuous_actions=continuous_actions
          )
      elif scenario_name == "simple_adversary":
          env = simple_adversary_v2.parallel_env(
              N=2, max_cycles=25, continuous_actions=continuous_actions
          )
      elif scenario_name == "simple_crypto":
          env = simple_crypto_v2.parallel_env(
              max_cycles=25, continuous_actions=continuous_actions
          )
      elif scenario_name == "simple_push":
          env = simple_push_v2.parallel_env(
              max_cycles=25, continuous_actions=continuous_actions
          )
      elif scenario_name == "simple_speaker_listener":
          env = simple_speaker_listener_v3.parallel_env(
              max_cycles=25, continuous_actions=continuous_actions
          )
      elif scenario_name == "simple_spread":
          env = simple_spread_v2.parallel_env(
              N=3,
              local_ratio=0,
              max_cycles=25,
              continuous_actions=continuous_actions,
          )
      elif scenario_name == "simple_tag":
          env = simple_tag_v2.parallel_env(
              num_good=1,
              num_adversaries=3,
              num_obstacles=2,
              max_cycles=25,
              continuous_actions=continuous_actions,
          )
      elif scenario_name == "simple_world_comm":
          env = simple_world_comm_v2.parallel_env(
              num_good=2,
              num_adversaries=4,
              num_obstacles=1,
              num_food=2,
              max_cycles=25,
              num_forests=2,
              continuous_actions=continuous_actions,
          )
      else:
          pass
  
      env = mpe_wrapper_for_pettingzoo(env, continuous_actions)
      return env
  
file_path: PARL/parl/env/multiagent_env.py
imports: import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: MAenv(scenario_name, continuous_actions) and returns: env