(n_bodies, n_actuators, control_cost_coef, time_limit, random,
              environment_kwargs)
return control.Environment(physics, task, time_limit=time_limit,
                             **environment_kwargs)
Returns a LQR environment.

  Args:
    n_bodies: An int, number of bodies of the LQR.
    n_actuators: An int, number of actuated bodies of the LQR. `n_actuators`
      should be less or equal than `n_bodies`.
    control_cost_coef: A number, the coefficient of the control cost.
    time_limit: An int, maximum time for each episode in seconds.
    random: Either an existing `numpy.random.RandomState` instance, an
      integer seed for creating a new `RandomState`, or None to select a seed
      automatically.
    environment_kwargs: A `dict` specifying keyword arguments for the
      environment, or None.

  Returns:
    A LQR environment with `n_bodies` bodies of which first `n_actuators` are
    actuated.
Returns a LQR environment.
Returns a LQR environment .
def _make_lqr(n_bodies, n_actuators, control_cost_coef, time_limit, random,
              environment_kwargs):
  """Returns a LQR environment.

  Args:
    n_bodies: An int, number of bodies of the LQR.
    n_actuators: An int, number of actuated bodies of the LQR. `n_actuators`
      should be less or equal than `n_bodies`.
    control_cost_coef: A number, the coefficient of the control cost.
    time_limit: An int, maximum time for each episode in seconds.
    random: Either an existing `numpy.random.RandomState` instance, an
      integer seed for creating a new `RandomState`, or None to select a seed
      automatically.
    environment_kwargs: A `dict` specifying keyword arguments for the
      environment, or None.

  Returns:
    A LQR environment with `n_bodies` bodies of which first `n_actuators` are
    actuated.
  """

  if not isinstance(random, np.random.RandomState):
    random = np.random.RandomState(random)

  model_string, assets = get_model_and_assets(n_bodies, n_actuators,
                                              random=random)
  physics = Physics.from_xml_string(model_string, assets=assets)
  task = LQRLevel(control_cost_coef, random=random)
  environment_kwargs = environment_kwargs or {}
  return control.Environment(physics, task, time_limit=time_limit,
                             **environment_kwargs)
def _make_lqr ( n_bodies , n_actuators , control_cost_coef , time_limit , random , environment_kwargs ) : if not isinstance ( random , np . random . RandomState ) : random = np . random . RandomState ( random ) model_string , assets = get_model_and_assets ( n_bodies , n_actuators , random = random ) physics = Physics . from_xml_string ( model_string , assets = assets ) task = LQRLevel ( control_cost_coef , random = random ) environment_kwargs = environment_kwargs or { } return control . Environment ( physics , task , time_limit = time_limit , * * environment_kwargs )