classifiers.py 文件源码

def compute_scores(self,Y):

        if Y.shape[1]==1:
            Y=self.get_Y_from_y(Y)

        P,N=Y.shape
        R=Y*Y.H/N

        S,U=lg.eig(R)
        eigenvalues=np.sort(np.real(S))[::-1]
        scores=np.zeros(len(self.L_vect))

        for index,L in enumerate(self.L_vect):

            if self.corrected==1:
                nb_free_parameters=L*(2*P-1-L)  #see [WIL94]
            else:
                nb_free_parameters=L*(2*P-L)    #see [WAX85]

            num=np.prod(eigenvalues[L:])
            den=np.mean(eigenvalues[L:])**(P-L)
            penalty_term=penalty_term_IC(nb_free_parameters,N,method=self.method)

            scores[index]=-2*N*np.log(num/den)+penalty_term

        self.scores=scores