code: def ystep(self):
          r
  
          AXU = self.AX + self.U
          Y0 = np.asarray(sp.prox_l1(self.block_sep0(AXU), self.wl1 / self.rho),
                          dtype=self.dtype)
          if self.opt['NonNegCoef']:
              Y0[Y0 < 0.0] = 0.0
          Y1 = sl.proj_l2ball(self.block_sep1(AXU), self.S, self.epsilon, axes=0)
          self.Y = self.block_cat(Y0, Y1)
docs: r"""Minimise Augmented Lagrangian with respect to
          :math:`\mathbf{y}`.