SG++-Doxygen-Documentation
sgpp::base::OperationHierarchisationPrewavelet Class Reference

Hierarchisation on sparse grid with prewavelets and no boundary. More...

#include <OperationHierarchisationPrewavelet.hpp>

Inheritance diagram for sgpp::base::OperationHierarchisationPrewavelet:
sgpp::base::OperationHierarchisation

Public Member Functions

void doDehierarchisation (DataVector &alpha) override
 Implements the dehierarchisation on a sparse grid. More...
 
void doHierarchisation (DataVector &node_values) override
 Implements the hierarchisation on a sparse grid. More...
 
 OperationHierarchisationPrewavelet (GridStorage &storage, GridStorage &shadowStorage)
 Constructor of OperationHierarchisationPrewavelet. More...
 
virtual ~OperationHierarchisationPrewavelet ()
 Destructor. More...
 
- Public Member Functions inherited from sgpp::base::OperationHierarchisation
 OperationHierarchisation ()
 Constructor. More...
 
virtual ~OperationHierarchisation ()
 Destructor. More...
 

Protected Member Functions

void expandGrid ()
 
void shrinkGrid ()
 

Protected Attributes

GridStorageshadowStorage
 
GridStoragestorage
 reference to the grid's GridStorage object More...
 

Detailed Description

Hierarchisation on sparse grid with prewavelets and no boundary.

Please note, that there is no efficient way to directly calculate the hierarchical surpluses for the prewavelet base. But there is a fast and efficient way to transform hierarchical surpluses of the normal linear ansatzfunctions into the prewavelet base and vice versa. Thus, we use the normal hierarchisation of the linear basis and afterwards transform the resulting Vector into prewavelets (see ConvertLinearToPrewavelet.hpp). For the Dehierarchisation, this process is reversed (see ConvertPrewaveletToLinear.hpp)

Constructor & Destructor Documentation

sgpp::base::OperationHierarchisationPrewavelet::OperationHierarchisationPrewavelet ( GridStorage storage,
GridStorage shadowStorage 
)
inline

Constructor of OperationHierarchisationPrewavelet.

An adaptive grid with prewavelet ansatz functions requires for operations using the up-down algorithm shadow points. These shadow points a needed just for data transport, thus they do not have an influence on the final function. Please refer to sgpp::pde::UpDownOneOpDimWithShadow for more information.

Parameters
storagePointer to the grid's gridstorage obejct
shadowStorageshadow points (see detailed description)
virtual sgpp::base::OperationHierarchisationPrewavelet::~OperationHierarchisationPrewavelet ( )
inlinevirtual

Destructor.

References alpha, doDehierarchisation(), and doHierarchisation().

Member Function Documentation

void sgpp::base::OperationHierarchisationPrewavelet::doDehierarchisation ( DataVector alpha)
overridevirtual

Implements the dehierarchisation on a sparse grid.

Parameters
alphathe coefficients of the sparse grid's basis functions

Implements sgpp::base::OperationHierarchisation.

References sgpp::base::HashGridStorage::getDimension(), python.statsfileInfo::i, create_scripts::s, storage, and sgpp::base::sweep< FUNC >::sweep1D().

Referenced by ~OperationHierarchisationPrewavelet().

void sgpp::base::OperationHierarchisationPrewavelet::doHierarchisation ( DataVector node_values)
overridevirtual

Implements the hierarchisation on a sparse grid.

Parameters
node_valuesthe function's values in the nodal basis

Implements sgpp::base::OperationHierarchisation.

References sgpp::base::HashGridStorage::getDimension(), python.statsfileInfo::i, create_scripts::s, shadowStorage, storage, and sgpp::base::sweep< FUNC >::sweep1D().

Referenced by ~OperationHierarchisationPrewavelet().

void sgpp::base::OperationHierarchisationPrewavelet::shrinkGrid ( )
protected

Member Data Documentation

GridStorage& sgpp::base::OperationHierarchisationPrewavelet::shadowStorage
protected
GridStorage& sgpp::base::OperationHierarchisationPrewavelet::storage
protected

reference to the grid's GridStorage object

Referenced by doDehierarchisation(), doHierarchisation(), expandGrid(), and shrinkGrid().


The documentation for this class was generated from the following files: