util.py 文件源码

def evd_r0(Vorg, 
        no_order=None, 
        no_samples=1000,
        output_l=None):
    """
    if output_l is not None, outputs will be saved to output_l
    output_l = [generated_samples]
    """
    n =  Vorg - np.mean(Vorg, axis=0)
    y0 =  np.mean(Vorg, axis=0)
    Rnn = np.dot(n.T, n) / n.shape[0]
    if no_order is not None:
        w, v = np.linalg.eig(Rnn)
        w, v = w[:no_order], v[:,:no_order]
        Rnn = np.dot(np.dot(v, np.diag(w)), v.T)
    new_n = np.random.randn(no_samples, Vorg.shape[1]) 
    y = y0.reshape(1,-1) + np.dot(new_n, linalg.sqrtm(Rnn))

    if output_l is not None:
        output_l.append(y)