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sgpp::base::InterpolantVectorFunctionGradient Class Reference

Sparse grid interpolant gradient of a vector-valued function. More...

#include <InterpolantVectorFunctionGradient.hpp>

Inheritance diagram for sgpp::base::InterpolantVectorFunctionGradient:
sgpp::base::VectorFunctionGradient

Public Member Functions

void clone (std::unique_ptr< VectorFunctionGradient > &clone) const override
 
void eval (const DataVector &x, DataVector &value, DataMatrix &gradient) override
 Evaluation of the function and its gradient.
 
const DataMatrixgetAlpha () const
 
 InterpolantVectorFunctionGradient (Grid &grid, const DataMatrix &alpha)
 Constructor.
 
void setAlpha (const DataMatrix &alpha)
 
 ~InterpolantVectorFunctionGradient () override
 Destructor.
 
- Public Member Functions inherited from sgpp::base::VectorFunctionGradient
size_t getNumberOfComponents () const
 
size_t getNumberOfParameters () const
 
 VectorFunctionGradient (size_t d, size_t m)
 Constructor.
 
virtual ~VectorFunctionGradient ()
 Destructor.
 

Protected Attributes

DataMatrix alpha
 coefficient matrix
 
Gridgrid
 sparse grid
 
std::unique_ptr< OperationEvalGradientopEvalGradient
 pointer to evaluation operation
 
- Protected Attributes inherited from sgpp::base::VectorFunctionGradient
size_t d
 dimension of the domain
 
size_t m
 number of components
 

Detailed Description

Sparse grid interpolant gradient of a vector-valued function.

See also
InterpolantVectorFunction

Constructor & Destructor Documentation

◆ InterpolantVectorFunctionGradient()

sgpp::base::InterpolantVectorFunctionGradient::InterpolantVectorFunctionGradient ( Grid grid,
const DataMatrix alpha 
)
inline

Constructor.

Do not destruct the grid before the InterpolantVectorFunctionGradient object!

Parameters
gridsparse grid
alphacoefficient matrix (j-th column contains hierarchical surplusses \(\alpha_{\cdot,j}\) of \(g_j\))

◆ ~InterpolantVectorFunctionGradient()

sgpp::base::InterpolantVectorFunctionGradient::~InterpolantVectorFunctionGradient ( )
inlineoverride

Destructor.

Member Function Documentation

◆ clone()

void sgpp::base::InterpolantVectorFunctionGradient::clone ( std::unique_ptr< VectorFunctionGradient > &  clone) const
inlineoverridevirtual
Parameters
[out]clonepointer to cloned object

Implements sgpp::base::VectorFunctionGradient.

References alpha, clone(), and grid.

Referenced by clone().

◆ eval()

void sgpp::base::InterpolantVectorFunctionGradient::eval ( const DataVector x,
DataVector value,
DataMatrix gradient 
)
inlineoverridevirtual

Evaluation of the function and its gradient.

Parameters
[in]xevaluation point \(\vec{x} \in [0, 1]^d\)
[out]value\(g(\vec{x})\)
[out]gradientJacobian \(\nabla g(\vec{x}) \in \mathbb{R}^{m \times d}\)

Implements sgpp::base::VectorFunctionGradient.

References alpha, sgpp::base::VectorFunctionGradient::d, opEvalGradient, and sgpp::base::DataVector::setAll().

Referenced by python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis::estimateDensity().

◆ getAlpha()

const DataMatrix & sgpp::base::InterpolantVectorFunctionGradient::getAlpha ( ) const
inline
Returns
coefficient matrix

References alpha.

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge::getSparseGridFunction().

◆ setAlpha()

void sgpp::base::InterpolantVectorFunctionGradient::setAlpha ( const DataMatrix alpha)
inline
Parameters
alphacoefficient matrix

References alpha.

Member Data Documentation

◆ alpha

◆ grid

Grid& sgpp::base::InterpolantVectorFunctionGradient::grid
protected

sparse grid

Referenced by python.uq.dists.SGDEdist.SGDEdist::__str__(), python.learner.Learner.Learner::applyData(), python.tools.Matrix::ApplyMatrix(), python.uq.dists.SGDEdist.SGDEdist::cdf(), clone(), python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Learner.Learner::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), python.tools.Matrix::generateb(), python.controller.CheckpointController.CheckpointController::generateFoldValidationJob(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), python.learner.Learner.Learner::learnData(), python.learner.Learner.Learner::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.learner.Learner.Learner::learnDataWithTest(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), python.controller.CheckpointController.CheckpointController::loadAll(), python.uq.operations.forcePositivity.operationMakePositive.OperationMakePositive::makePositive(), python.uq.operations.forcePositivity.operationMakePositiveFast.OperationMakePositiveFast::makePositive(), python.uq.dists.SGDEdist.SGDEdist::mean(), python.uq.dists.SGDEdist.SGDEdist::pdf(), python.uq.dists.SGDEdist.SGDEdist::ppf(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), python.controller.CheckpointController.CheckpointController::saveGrid(), python.controller.CheckpointController.CheckpointController::setGrid(), python.learner.Learner.Learner::setGrid(), python.uq.learner.Learner.Learner::setGrid(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid::split(), python.uq.dists.SGDEdist.SGDEdist::toJson(), and python.uq.dists.SGDEdist.SGDEdist::var().

◆ opEvalGradient

std::unique_ptr<OperationEvalGradient> sgpp::base::InterpolantVectorFunctionGradient::opEvalGradient
protected

pointer to evaluation operation

Referenced by eval().


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