def make()

in hanabi-learning-environment/rl_env.py [0:0]

• 70 lines of code
• 7 McCabe index (conditional complexity)

def make(environment_name="Hanabi-Full", num_players=2, pyhanabi_path=None):
  """Make an environment.

  Args:
    environment_name: str, Name of the environment to instantiate.
    num_players: int, Number of players in this game.
    pyhanabi_path: str, absolute path to header files for c code linkage.

  Returns:
    env: An `Environment` object.

  Raises:
    ValueError: Unknown environment name.
  """

  if pyhanabi_path is not None:
    prefixes=(pyhanabi_path,)
    assert pyhanabi.try_cdef(prefixes=prefixes), "cdef failed to load"
    assert pyhanabi.try_load(prefixes=prefixes), "library failed to load"

  if (environment_name == "Hanabi-Full" or
      environment_name == "Hanabi-Full-CardKnowledge"):
    return HanabiEnv(
        config={
            "colors":
                5,
            "ranks":
                5,
            "players":
                num_players,
            "max_information_tokens":
                8,
            "max_life_tokens":
                3,
            "observation_type":
                pyhanabi.AgentObservationType.CARD_KNOWLEDGE.value
        })
  elif environment_name == "Hanabi-Full-Minimal":
    return HanabiEnv(
        config={
            "colors": 5,
            "ranks": 5,
            "players": num_players,
            "max_information_tokens": 8,
            "max_life_tokens": 3,
            "observation_type": pyhanabi.AgentObservationType.MINIMAL.value
        })
  elif environment_name == "Hanabi-Small":
    return HanabiEnv(
        config={
            "colors":
                2,
            "ranks":
                5,
            "players":
                num_players,
            "hand_size":
                2,
            "max_information_tokens":
                3,
            "max_life_tokens":
                1,
            "observation_type":
                pyhanabi.AgentObservationType.CARD_KNOWLEDGE.value
        })
  elif environment_name == "Hanabi-Very-Small":
    return HanabiEnv(
        config={
            "colors":
                1,
            "ranks":
                5,
            "players":
                num_players,
            "hand_size":
                2,
            "max_information_tokens":
                3,
            "max_life_tokens":
                1,
            "observation_type":
                pyhanabi.AgentObservationType.CARD_KNOWLEDGE.value
        })
  else:
    raise ValueError("Unknown environment {}".format(environment_name))