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Hierarchisation operation for B-spline basis functions on Clenshaw-Curtis grids. More...
#include <OperationMultipleHierarchisationBsplineClenshawCurtis.hpp>
  
 Public Member Functions | |
| void | doDehierarchisation (base::DataVector &alpha) override | 
| void | doDehierarchisation (base::DataMatrix &alpha) override | 
| bool | doHierarchisation (base::DataVector &nodeValues) override | 
| bool | doHierarchisation (base::DataMatrix &nodeValues) override | 
| OperationMultipleHierarchisationBsplineClenshawCurtis (base::BsplineClenshawCurtisGrid &grid) | |
| Constructor.  More... | |
| ~OperationMultipleHierarchisationBsplineClenshawCurtis () override | |
| Destructor.  More... | |
  Public Member Functions inherited from sgpp::optimization::OperationMultipleHierarchisation | |
| OperationMultipleHierarchisation () | |
| Constructor.  More... | |
| virtual | ~OperationMultipleHierarchisation () | 
| Destructor.  More... | |
Protected Attributes | |
| base::BsplineClenshawCurtisGrid & | grid | 
| storage of the sparse grid  More... | |
Hierarchisation operation for B-spline basis functions on Clenshaw-Curtis grids.
      
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  explicit | 
Constructor.
| grid | grid | 
References ~OperationMultipleHierarchisationBsplineClenshawCurtis().
      
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  override | 
Destructor.
Referenced by OperationMultipleHierarchisationBsplineClenshawCurtis().
      
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  overridevirtual | 
| [in,out] | alpha | before: vector of hierarchical coefficients, after: vector of function values at the grid points | 
Implements sgpp::optimization::OperationMultipleHierarchisation.
References sgpp::base::HashGridStorage::getCoordinates(), sgpp::base::BsplineClenshawCurtisGrid::getDegree(), sgpp::base::HashGridStorage::getDimension(), sgpp::base::HashGridStorage::getSize(), sgpp::base::Grid::getStorage(), grid, and python.utils.statsfile2gnuplot::j.
      
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  overridevirtual | 
| [in,out] | alpha | before: matrix of hierarchical coefficients, after: matrix of function values at the grid points | 
Implements sgpp::optimization::OperationMultipleHierarchisation.
References sgpp::base::DataMatrix::getColumn(), sgpp::base::HashGridStorage::getCoordinates(), sgpp::base::BsplineClenshawCurtisGrid::getDegree(), sgpp::base::HashGridStorage::getDimension(), sgpp::base::DataMatrix::getNcols(), sgpp::base::HashGridStorage::getSize(), sgpp::base::Grid::getStorage(), grid, python.statsfileInfo::i, python.utils.statsfile2gnuplot::j, and sgpp::base::DataMatrix::setColumn().
      
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  overridevirtual | 
| [in,out] | nodeValues | before: vector of function values at the grid points, after: vector of hierarchical coefficients | 
Implements sgpp::optimization::OperationMultipleHierarchisation.
References chess::b, grid, and sgpp::optimization::sle_solver::Auto::solve().
      
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  overridevirtual | 
| [in,out] | nodeValues | before: matrix of function values at the grid points, after: matrix of hierarchical coefficients | 
Implements sgpp::optimization::OperationMultipleHierarchisation.
References grid, and sgpp::optimization::sle_solver::Auto::solve().
      
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  protected | 
storage of the sparse grid
Referenced by doDehierarchisation(), doHierarchisation(), python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), python.uq.learner.Regressor.Regressor::learnData(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), python.learner.Classifier.Classifier::updateResults(), python.learner.Regressor.Regressor::updateResults(), and python.uq.learner.Regressor.Regressor::updateResults().