top_n_mc.py 文件源码

def update_X(X, mu, k=6):
    #U, S, VT = svdp(X, k=k)
    U, S, VT = svds(X, k=k, which='LM')
    P = np.c_[np.ones((k, 1)), 1-S, 1./2./mu-S]
    sigma_star = np.zeros(k)
    for t in range(k):
        p = P[t, :]
        delta = p[1]**2 - 4 * p[0] * p[2]
        if delta <= 0:
            sigma_star[t] = 0.
        else:
            solution = np.roots(p)
            solution = solution.tolist()
            solution.sort(key=abs)
            solution = np.array(solution)
            if solution[0] * solution[1] <= 0:
                sigma_star[t] = solution[1]
            elif solution[1] < 0:
                sigma_star[t] = 0.
            else:
                f = np.log(1 + solution[1]) + mu * (solution[1] - s[t])**2
                if f > mu *s[t]**2:
                    sigma_star[t] = 0.
                else:
                    sigma_star[t] = solution[1]

    sigma_star = sp.csr_matrix(np.diag(sigma_star))
    sigma_star = safe_sparse_dot(safe_sparse_dot(U, sigma_star), VT)
    sigma_star[abs(sigma_star)<1e-10] = 0
    return sp.lil_matrix(sigma_star)