fullrank.py 文件源码

def fullrank(X):
    '''
    return full-rank decomposition of X = FG^T
    '''
    rankX = rank(X)

    U, eigvals, Vh = la.svd(X)

    #construct a r-rank sigma-square-root matrix

    sigma = np.eye(rankX)
    for i in range(sigma.shape[0]):
        sigma[i, i] = np.sqrt(eigvals[i])

    F = U.dot(np.vstack((sigma, np.zeros((X.shape[0] - rankX, rankX)))))
    Gh = np.hstack((sigma, np.zeros((rankX, X.shape[1] - rankX)))).dot(Vh)

    return F, Gh