SG++-Doxygen-Documentation
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Implementation for PolyClenshawCurtis functions of Laplace Operation, linear grids without boundaries. More...
#include <OperationLaplacePolyClenshawCurtis.hpp>
Public Member Functions | |
virtual void | mult (sgpp::base::DataVector &alpha, sgpp::base::DataVector &result) |
Implementation of standard matrix multiplication. More... | |
OperationLaplacePolyClenshawCurtis (sgpp::base::Grid *grid) | |
Constructor that creates an own matrix i.e. More... | |
virtual | ~OperationLaplacePolyClenshawCurtis () |
Destructor. More... | |
Public Member Functions inherited from sgpp::base::OperationMatrix | |
OperationMatrix () | |
Constructor. More... | |
virtual | ~OperationMatrix () |
Destructor. More... | |
Implementation for PolyClenshawCurtis functions of Laplace Operation, linear grids without boundaries.
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explicit |
Constructor that creates an own matrix i.e.
matrix is destroyed by the destructor of OperationLaplacePolyClenshawCurtis
grid | the sparse grid |
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virtual |
Destructor.
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virtual |
Implementation of standard matrix multiplication.
alpha | DataVector that is multiplied to the matrix |
result | DataVector into which the result of multiplication is stored |
int nabla phi_i(x) * nabla phi_j(x) dx = sum_k int (dx_k phi_i(x)) * (dx_k phi_j(x)) dx = sum_k int (phi'_{i_k}(x_k) * phi'_{i_k}(x_k) * prod_{l!=k} phi_{i_l}(x_l) * phi_{j_l}(x_l)) dx = sum_k int (phi'_{i_k}(x_k) * phi'_{j_k}(x_k)) dx_k * prod_{l!=k} int (phi_{i_l}(x_l) * phi_{j_l}(x_l)) dx_l
Implements sgpp::base::OperationMatrix.
References sgpp::base::PolyClenshawCurtisBasis< LT, IT >::eval(), sgpp::base::PolyClenshawCurtisBasis< LT, IT >::evalDx(), sgpp::base::Grid::getBasis(), python.uq.operations.sparse_grid::getDegree(), sgpp::base::Grid::getDimension(), sgpp::base::GaussLegendreQuadRule1D::getLevelPointsAndWeightsNormalized(), sgpp::base::ClenshawCurtisTable::getPoint(), sgpp::base::HashGridStorage::getSize(), sgpp::base::DataVector::getSize(), sgpp::base::Grid::getSize(), sgpp::base::Grid::getStorage(), python.statsfileInfo::i, python.utils.statsfile2gnuplot::j, and friedman::p.