def lower_bound_for_data_score(self,selected_data_empty):
        if self.prior!=None:
            return 0.0
        HP=self.HP(selected_data_empty.vertex,[])
        H=self.H(selected_data_empty.vertex,[])
        stats_all,stats_par = selected_data_empty.stats()
        if selected_data_empty.vertex.n_disc:
            s = 0
            for a,cv in stats_all.items():
                for i in range(0,cv):
                    s-=log(H+i)
                    s+=log(HP+i)
        else:
            return 0.0