Example #1
0
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;
  }
}
Example #2
0
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;
  }
}