DiagGaussObsModel.py 文件源码

def _calcPredProbVec_Fast(self, SS, x):
        p = np.zeros(SS.K)
        nu, beta, m, kappa = self.calcPostParams(SS)
        kbeta = beta
        kbeta *= ((kappa + 1) / kappa)[:, np.newaxis]
        base = np.square(x - m)
        base /= kbeta
        base += 1
        # logp : 2D array, size K x D
        logp = (-0.5 * (nu + 1))[:, np.newaxis] * np.log(base)
        logp += (gammaln(0.5 * (nu + 1)) - gammaln(0.5 * nu))[:, np.newaxis]
        logp -= 0.5 * np.log(kbeta)

        # p : 1D array, size K
        p = np.sum(logp, axis=1)
        p -= np.max(p)
        np.exp(p, out=p)
        return p