GaussObsModel.py 文件源码

def _calcPredProbVec_Fast(self, SS, x):
        nu, B, m, kappa = self.calcPostParams(SS)
        kB = B
        kB *= ((kappa + 1) / kappa)[:, np.newaxis, np.newaxis]
        logp = np.zeros(SS.K)
        p = logp  # Rename so its not confusing what we're returning
        for k in xrange(SS.K):
            cholKB = scipy.linalg.cholesky(kB[k], lower=1)
            logdetKB = 2 * np.sum(np.log(np.diag(cholKB)))
            mVec = np.linalg.solve(cholKB, x - m[k])
            mDist_k = np.inner(mVec, mVec)
            logp[k] = -0.5 * logdetKB - 0.5 * \
                (nu[k] + 1) * np.log(1.0 + mDist_k)
        logp += gammaln(0.5 * (nu + 1)) - gammaln(0.5 * (nu + 1 - self.D))
        logp -= np.max(logp)
        np.exp(logp, out=p)
        return p