std::vector<double> LunacekBiRastriginFunction<T>::serialise() const noexcept {
std::vector<double> serialisedOptimisationProblem = BlackBoxOptimisationBenchmark<T, T>::serialise();
for(std::size_t n = 0; n < rotationQ_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(static_cast<double>(rotationQ_(n)));
}
return serialisedOptimisationProblem;
}
std::vector<double> AttractiveSectorFunction::serialise() const {
std::vector<double> serialisedOptimisationProblem = BlackBoxOptimisationBenchmark::serialise();
for (arma::uword n = 0; n < rotationQ_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(rotationQ_(n));
}
return serialisedOptimisationProblem;
}
void LunacekBiRastriginFunction<T>::deserialise(
const std::vector<double>& serialisedOptimisationProblem) {
rotationQ_.set_size(this->numberOfDimensions_, this->numberOfDimensions_);
for(std::size_t n = 0; n < rotationQ_.n_elem; ++n) {
rotationQ_(n) = static_cast<T>(serialisedOptimisationProblem.pop_back());
}
BlackBoxOptimisationBenchmark<T, T>::deserialise(serialisedOptimisationProblem);
}
void AttractiveSectorFunction::deserialise(
std::vector<double> serialisedOptimisationProblem) {
rotationQ_.set_size(numberOfDimensions_, numberOfDimensions_);
for (arma::uword n = 0; n < rotationQ_.n_elem; ++n) {
rotationQ_(n) = serialisedOptimisationProblem.back();
serialisedOptimisationProblem.pop_back();
}
BlackBoxOptimisationBenchmark::deserialise(serialisedOptimisationProblem);
}
std::vector<double> GallaghersGaussian101mePeaksFunction::serialise() const {
std::vector<double> serialisedOptimisationProblem = BlackBoxOptimisationBenchmark::serialise();
for (arma::uword n = 0; n < rotationQ_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(rotationQ_(n));
}
for (arma::uword n = 0; n < localParameterConditionings_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(localParameterConditionings_(n));
}
for (arma::uword n = 0; n < localParameterTranslations_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(localParameterTranslations_(n));
}
return serialisedOptimisationProblem;
}
std::vector<double> GallaghersGaussian21hiPeaksFunction<T>::serialise() const noexcept {
std::vector<double> serialisedOptimisationProblem = BlackBoxOptimisationBenchmark<T, T>::serialise();
for(std::size_t n = 0; n < rotationQ_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(static_cast<double>(rotationQ_(n)));
}
for(std::size_t n = 0; n < localParameterConditionings_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(static_cast<double>(localParameterConditionings_(n)));
}
for(std::size_t n = 0; n < localParameterTranslations_.n_elem; ++n) {
serialisedOptimisationProblem.push_back(static_cast<double>(localParameterTranslations_(n)));
}
return serialisedOptimisationProblem;
}
void GallaghersGaussian21hiPeaksFunction<T>::deserialise(
const std::vector<double>& serialisedOptimisationProblem) {
rotationQ_.set_size(this->numberOfDimensions_, this->numberOfDimensions_);
for(std::size_t n = 0; n < rotationQ_.n_elem; ++n) {
rotationQ_(n) = static_cast<T>(serialisedOptimisationProblem.pop_back());
}
localParameterConditionings_.set_size(this->numberOfDimensions_, 21);
for(std::size_t n = 0; n < localParameterConditionings_.n_elem; ++n) {
localParameterConditionings_(n) = static_cast<T>(serialisedOptimisationProblem.pop_back());
}
localParameterTranslations_.set_size(this->numberOfDimensions_, 21);
for(std::size_t n = 0; n < localParameterTranslations_.n_elem; ++n) {
localParameterTranslations_(n) = static_cast<T>(serialisedOptimisationProblem.pop_back());
}
BlackBoxOptimisationBenchmark<T, T>::deserialise(serialisedOptimisationProblem);
}
void GallaghersGaussian101mePeaksFunction::deserialise(
std::vector<double> serialisedOptimisationProblem) {
localParameterTranslations_.set_size(numberOfDimensions_, 21);
for (arma::uword n = 0; n < localParameterTranslations_.n_elem; ++n) {
localParameterTranslations_(n) = serialisedOptimisationProblem.back();
serialisedOptimisationProblem.pop_back();
}
localParameterConditionings_.set_size(numberOfDimensions_, 21);
for (arma::uword n = 0; n < localParameterConditionings_.n_elem; ++n) {
localParameterConditionings_(n) = serialisedOptimisationProblem.back();
serialisedOptimisationProblem.pop_back();
}
rotationQ_.set_size(numberOfDimensions_, numberOfDimensions_);
for (arma::uword n = 0; n < rotationQ_.n_elem; ++n) {
rotationQ_(n) = serialisedOptimisationProblem.back();
serialisedOptimisationProblem.pop_back();
}
BlackBoxOptimisationBenchmark::deserialise(serialisedOptimisationProblem);
}