regionsRanker.py 文件源码

def eigenDecompose(self, X, K, normalize=True):
        if (X.shape[1] >= X.shape[0]):
            s,U = la.eigh(K)
        else:
            U, s, _ = la.svd(X, check_finite=False, full_matrices=False)
            if (s.shape[0] < U.shape[1]): s = np.concatenate((s, np.zeros(U.shape[1]-s.shape[0])))  #note: can use low-rank formulas here           
            s=s**2
            if normalize: s /= float(X.shape[1])
        if (np.min(s) < -1e-10): raise Exception('Negative eigenvalues found')
        s[s<0]=0    
        ind = np.argsort(s)[::-1]
        U = U[:, ind]
        s = s[ind]  

        return s,U