code: def xstep(self):
          r
  
          ngsit = 0
          gsrrs = np.inf
          while gsrrs > self.opt['GSTol'] and ngsit < self.opt['MaxGSIter']:
              self.X = self.GaussSeidelStep(self.S, self.X,
                                            self.cnst_AT(self.Y-self.U),
                                            self.rho, self.lcw, self.Wdf2)
              gsrrs = sl.rrs(
                  self.rho*self.cnst_AT(self.cnst_A(self.X)) +
                  self.Wdf2*self.X, self.Wdf2*self.S +
                  self.rho*self.cnst_AT(self.Y - self.U))
              ngsit += 1
  
          self.xs = (ngsit, gsrrs)
docs: r"""Minimise Augmented Lagrangian with respect to
          :math:`\mathbf{x}`.