pep_models.py 文件源码

def sample(self, x):
        """Summary

        Args:
            x (TYPE): Description

        Returns:
            TYPE: Description
        """
        Su = self.Su
        mu = self.mu
        Lu = np.linalg.cholesky(Su)
        epsilon = np.random.randn(self.Dout, self.M)
        u_sample = mu + np.einsum('dab,db->da', Lu, epsilon)

        kff = compute_kernel(2 * self.ls, 2 * self.sf, x, x)
        kff += np.diag(JITTER * np.ones(x.shape[0]))
        kfu = compute_kernel(2 * self.ls, 2 * self.sf, x, self.zu)
        qfu = np.dot(kfu, self.Kuuinv)
        mf = np.einsum('nm,dm->nd', qfu, u_sample)
        vf = kff - np.dot(qfu, kfu.T)
        Lf = np.linalg.cholesky(vf)
        epsilon = np.random.randn(x.shape[0], self.Dout)
        f_sample = mf + np.einsum('ab,bd->ad', Lf, epsilon)
        return f_sample