示例#1
0
void SumFactor::_internal_update(
    Variable* var,
    std::vector<Gaussian*> y,
    std::vector<Gaussian*> fy,
    std::vector<double>* a) {

    double sum_pi = 0.0, sum_tau = 0.0, new_pi, new_tau, da;
    unsigned int i = 0, size = a->size();
    Gaussian gy, gfy;

    for (i = 0; i < size; ++i) {
        da = (*a)[i];
        gy = *y[i];
        gfy = *fy[i];

        sum_pi = sum_pi + ((da * da) / (gy.pi - gfy.pi));
        sum_tau = sum_tau + (da * (gy.tau - gfy.tau) / (gy.pi - gfy.pi));
    }

    new_pi = 1.0 / sum_pi;
    new_tau = new_pi * sum_tau;

    Gaussian* gaussian = new Gaussian();
    gaussian->init_pi_tau(new_pi, new_tau);
    var->update_message(this, gaussian);
}
示例#2
0
void LikelihoodFactor::update_mean() {
    Gaussian x = *this->value->value;
    Gaussian fx = *this->value->get_message(this);
    double a = 1.0 / (1.0 + this->variance * (x.pi - fx.pi));

    Gaussian* gaussian = new Gaussian();
    gaussian->init_pi_tau(
        a * (x.pi - fx.pi),
        a * (x.tau - fx.tau)
    );
    this->mean->update_message(this, gaussian);
}
示例#3
0
void TruncateFactorDraw::update() {
    Gaussian* x = this->variable->value;
    Gaussian* fx = this->variable->get_message(this);

    double c, d, sqrt_c, V, W, t, e, mW;
    c = x->pi - fx->pi;
    d = x->tau = fx->tau;
    sqrt_c = sqrt(c);

    t = d / sqrt_c;
    e = epsilon * sqrt_c;

    V = Vdraw(t, e);
    W = Wdraw(t, e);
    mW = 1.0 - W;

    Gaussian* gaussian = new Gaussian();
    gaussian->init_pi_tau(c / mW, (d + sqrt_c * V) / mW);
    this->variable->update_value(this, gaussian);
}