docs: def get_residual_norms(H, self_adjoint=False):
      '''Compute relative residual norms from Hessenberg matrix.
  
      It is assumed that the initial guess is chosen as zero.'''
      H = H.copy()
      n_, n = H.shape
      y = numpy.eye(n_, 1, dtype=H.dtype)
      resnorms = [1.]
      for i in range(n_-1):
          G = Givens(H[i:i+2, [i]])
          if self_adjoint:
              H[i:i+2, i:i+3] = G.apply(H[i:i+2, i:i+3])
          else:
              H[i:i+2, i:] = G.apply(H[i:i+2, i:])
          y[i:i+2] = G.apply(y[i:i+2])
          resnorms.append(numpy.abs(y[i+1, 0]))
      if n_ == n:
          resnorms.append(0.)
      return numpy.array(resnorms)