double Information::upper_bound_entropy(GMM &gmm) {
double HU = 0;
for(unsigned int i = 0; i < gmm.K; i++){
HU = HU - gmm.get_weigts()[i]*log(gmm.get_weigts()[i]) + 0.5*gmm.get_weigts()[i] *log(std::pow(2*M_PI*exp(1),(double)gmm.D) * arma::det(gmm.get_covariances()[i])) ;
//log(std::pow(2*M_PI*exp(1),(double)gmm.D) * arma::det(gmm.getSigma(i)))
}
HU = checkForNan(HU,qHu);
return HU;
}
double Information::lower_bound_entropy(GMM& gmm) {
double HL = 0;
double tmp = 0;
for(unsigned int i = 0; i < gmm.K;i++){
tmp = 0;
for(unsigned int j = 0; j < gmm.K;j++){
tmp = tmp + gmm.get_weigts()[i] * mvnpdf(gmm.get_means()[i],gmm.get_means()[j],gmm.get_covariances()[i] + gmm.get_covariances()[j]);
}
tmp = log(tmp);
HL = HL + gmm.get_weigts()[i] * tmp;
}
HL = -1*HL;
HL = checkForNan(HL,qHl);
return HL;
}
void cGMM::condition(const arma::colvec& x_in, const GMM &gmm_in){
// std::cout<< "cGMM::condition dependent x" << std::endl;
// x_in.print("x_in");
for(std::size_t k = 0; k < gmm_in.K;k++){
// \mu_a + Sig_12 * Sig_22^{-1} * (x - \mu_b)
gaussian_c[k].mu_condition(x_in);
gmm_c.set_mu(k,gaussian_c[k].Mean_c);
gmm_c.set_prior(k,gmm_in.get_weigts()[k] * stats::mvnpdf(x_in,gaussian_c[k].Mu_2,gaussian_c[k].invSigma22,gaussian_c[k].det_22));
}
gmm_c.set_prior( gmm_c.get_weigts() / arma::sum( gmm_c.get_weigts() + std::numeric_limits<double>::min()) );
}
