def get_nsing(self,epsilon=1.0e-4):
        """ get the number of solution space dimensions given
        a ratio between the largest and smallest singular values

        Parameters
        ----------
        epsilon: float
            singular value ratio

        Returns
        -------
        nsing : float
            number of singular components above the epsilon ratio threshold
        
        Note
        -----
            If nsing == nadj_par, then None is returned
        
        """
        mx = self.xtqx.shape[0]
        nsing = mx - np.searchsorted(
                np.sort((self.xtqx.s.x / self.xtqx.s.x.max())[:,0]),epsilon)
        if nsing == mx:
            self.logger.warn("optimal nsing=npar")
            nsing = None
        return nsing
get the number of solution space dimensions given
        a ratio between the largest and smallest singular values

        Parameters
        ----------
        epsilon: float
            singular value ratio

        Returns
        -------
        nsing : float
            number of singular components above the epsilon ratio threshold
        
        Note
        -----
            If nsing == nadj_par, then None is returned