docs: def stationary_distribution_from_backward_iteration(P, eps=1e-15):
      r"""Fast computation of the stationary vector using backward
      iteration.
  
      Parameters
      ----------
      P : (M, M) scipy.sparse matrix
          Transition matrix
      eps : float (optional)
          Perturbation parameter for the true eigenvalue.
  
      Returns
      -------
      pi : (M,) ndarray
          Stationary vector
  
      """
      A = P.transpose()
      mu = 1.0 - eps
      x0 = np.ones(P.shape[0])
      y = backward_iteration(A, mu, x0)
      pi = y / y.sum()
      return pi