code: def eigenvectors_nrev(T, right=True):
      r
      if right:
          val, R = eig(T, left=False, right=True)
          """ Sorted eigenvalues and left and right eigenvectors. """
          perm = np.argsort(np.abs(val))[::-1]
          # eigval=val[perm]
          eigvec = R[:, perm]
  
      else:
          val, L = eig(T, left=True, right=False)
  
          """ Sorted eigenvalues and left and right eigenvectors. """
          perm = np.argsort(np.abs(val))[::-1]
          # eigval=val[perm]
          eigvec = L[:, perm]
      return eigvec
docs: r"""Compute eigenvectors of transition matrix.
  
      Parameters
      ----------
      T : (d, d) ndarray
          Transition matrix (stochastic matrix)
      k : int or tuple of ints, optional
          Compute the first k eigenvalues of T
      right : bool, optional
          If right=True compute right eigenvectors, left eigenvectors
          otherwise
  
      Returns
      -------
      eigvec : (d, d) ndarray
          The eigenvectors of T ordered with decreasing absolute value
          of the corresponding eigenvalue