def METHOD_NAME(self, ts_length, init_actions=None, t_init=0, **options):
    """
    Return a tuple of arrays representing a time series of mixed action
    profiles.
    Parameters
    ----------
    ts_length : scalar(int)
        The number of iterations.
    init_actions : tuple(int), optional(default=None)
        The action profile in the initial period. If None, selected
        randomly.
    t_init : scalar(int), optional(default=0)
        The period when the game starts.
    **options : Keyword arguments passed to the best response method and
                other methods.
    Returns
    -------
    tuple(ndarray(float, ndim=2))
        Tuple of arrays representing time series of mixed action profile.
    """
    tie_breaking = options.get('tie_breaking', self.tie_breaking)
    tol = options.get('tol', None)
    random_state = check_random_state(options.get('random_state', None))
    out = tuple(np.empty((ts_length, n)) for n in self.nums_actions)
    out_init = tuple(out[i][0, :] for i in range(self.N))
    if init_actions is None:
        _random_mixed_actions(out_init, random_state)
    else:
        _copy_action_profile_to(out_init, init_actions)
    actions = tuple(np.copy(action) for action in out_init)
    brs = np.empty(self.N, dtype=int)
    for j in range(1, ts_length):
        self._play(actions, t_init+j-1, brs,
                   tie_breaking, tol, random_state)
        for i in range(self.N):
            np.copyto(out[i][j, :], actions[i])
    return out