void doDirectedRefinements(SGPP::base::AdpativityConfiguration& adaptConfig,
SGPP::base::Grid& grid, SGPP::base::GridGenerator& gridGen) {
double dummySurplusValue = 1.0;
SGPP::base::DataVector alphaRefine(grid.getSize());
for (size_t i = 0; i < alphaRefine.getSize(); i++) {
alphaRefine[i] = dummySurplusValue;
dummySurplusValue += 1.0;
}
for (size_t i = 0; i < adaptConfig.numRefinements_; i++) {
SGPP::base::SurplusRefinementFunctor* myRefineFunc = new
SGPP::base::SurplusRefinementFunctor(&alphaRefine,
adaptConfig.noPoints_, adaptConfig.threshold_);
gridGen.refine(myRefineFunc);
size_t oldSize = alphaRefine.getSize();
alphaRefine.resize(grid.getSize());
for (size_t j = oldSize; j < alphaRefine.getSize(); j++) {
alphaRefine[i] = dummySurplusValue;
}
//increment only once for added grid points
dummySurplusValue += 1.0;
delete myRefineFunc;
}
}
void doRandomRefinements(SGPP::base::AdpativityConfiguration& adaptConfig,
SGPP::base::Grid& grid, SGPP::base::GridGenerator& gridGen) {
std::random_device rd;
std::mt19937 mt(rd());
std::uniform_real_distribution<double> dist(1, 100);
SGPP::base::DataVector alphaRefine(grid.getSize());
for (size_t i = 0; i < alphaRefine.getSize(); i++) {
alphaRefine[i] = dist(mt);
}
for (size_t i = 0; i < adaptConfig.numRefinements_; i++) {
SGPP::base::SurplusRefinementFunctor* myRefineFunc = new
SGPP::base::SurplusRefinementFunctor(&alphaRefine,
adaptConfig.noPoints_, adaptConfig.threshold_);
gridGen.refine(myRefineFunc);
size_t oldSize = alphaRefine.getSize();
alphaRefine.resize(grid.getSize());
for (size_t j = oldSize; j < alphaRefine.getSize(); j++) {
alphaRefine[j] = dist(mt);
}
delete myRefineFunc;
}
}