void optimize(const EvalFunction& feval, bool reset = true)
{
this->_init(feval, FirstElem(), reset);
acqui_optimizer_t inner_opt;
while (this->_samples.size() == 0 || !this->_stop(*this, FirstElem())) {
this->template update_pareto_model<EvalFunction::dim_in>();
this->update_pareto_data();
// copy in the ehvi structure to compute expected improvement
std::deque<individual*> pop;
for (auto x : this->pareto_data()) {
individual* ind = new individual;
ind->f[0] = std::get<1>(x)(0);
ind->f[1] = std::get<1>(x)(1);
ind->f[2] = 0;
pop.push_back(ind);
}
auto acqui = acqui::Ehvi<Params, model_t>(
this->_models, pop,
Eigen::Vector3d(Params::bayes_opt_ehvi::x_ref(), Params::bayes_opt_ehvi::y_ref(), 0));
// maximize with inner opt
using pair_t = std::pair<Eigen::VectorXd, double>;
pair_t init(Eigen::VectorXd::Zero(1), -std::numeric_limits<float>::max());
auto body = [&](int i) -> pair_t {
auto x = this->pareto_data()[i];
auto acqui_optimization =
[&](const Eigen::VectorXd& x, bool g) { return opt::no_grad(acqui(x)); };
Eigen::VectorXd s = inner_opt(acqui_optimization, std::get<0>(x), true);
double hv = acqui(s);
return std::make_pair(s, hv);
};
auto comp = [](const pair_t& v1, const pair_t& v2) {
return v1.second > v2.second;
};
auto m = tools::par::max(init, this->pareto_data().size(), body, comp);
// take the best
Eigen::VectorXd new_sample = m.first;
// delete pop
for (auto x : pop)
delete x;
// add sample
this->add_new_sample(new_sample, feval(new_sample));
this->_update_stats(*this, FirstElem());
this->_current_iteration++;
this->_total_iterations++;
}
}
void function_minimizer::pre_userfunction(void)
{
if (lapprox)
{
if (lapprox->hesstype==2)
{
//lapprox->num_separable_calls=0;
lapprox->separable_calls_counter=0;
}
}
userfunction();
if (lapprox)
{
if (lapprox->hesstype==2)
{
lapprox->num_separable_calls=lapprox->separable_calls_counter;
double tmp=0.0;
int inner_opt_value=inner_opt();
if (lapprox->saddlepointflag==2)
{
if (inner_opt_value !=0 )
{
for (int i = 1; i <= lapprox->num_separable_calls; i++)
{
tmp-=(*lapprox->separable_function_difference)(i);
}
value(*objective_function_value::pobjfun)=tmp;
}
}
else
{
for (int i = 1; i <= lapprox->num_separable_calls; i++)
{
tmp+=(*lapprox->separable_function_difference)(i);
}
value(*objective_function_value::pobjfun)=tmp;
}
}
}
}
