def obfn_f(self, Xf=None):
        r"""Compute data fidelity term :math:`(1/2) \| \sum_m
        \mathbf{d}_m * \mathbf{x}_m - \mathbf{s} \|_2^2`.
        This is used for backtracking. Since the backtracking is
        computed in the DFT, it is important to preserve the
        DFT scaling.
        """
        if Xf is None:
            Xf = self.Xf

        Rf = self.eval_Rf(Xf)
        return 0.5 * np.linalg.norm(Rf.flatten(), 2)**2
def obfn_f ( self , Xf = None ) : if Xf is None : Xf = self . Xf Rf = self . eval_Rf ( Xf ) return 0.5 * np . linalg . norm ( Rf . flatten ( ) , 2 ) ** 2
r"""Compute data fidelity term :math:`(1/2) \| \sum_m
        \mathbf{d}_m * \mathbf{x}_m - \mathbf{s} \|_2^2`.
        This is used for backtracking. Since the backtracking is
        computed in the DFT, it is important to preserve the
        DFT scaling.