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sgpp::base::InterpolantScalarFunctionHessian Class Reference

Sparse grid interpolant Hessian of a scalar-valued function. More...

#include <InterpolantScalarFunctionHessian.hpp>

Inheritance diagram for sgpp::base::InterpolantScalarFunctionHessian:
sgpp::base::ScalarFunctionHessian

Public Member Functions

void clone (std::unique_ptr< ScalarFunctionHessian > &clone) const override
 
double eval (const DataVector &x, DataVector &gradient, DataMatrix &hessian) override
 Evaluation of the function, its gradient and its Hessian.
 
const DataVectorgetAlpha () const
 
 InterpolantScalarFunctionHessian (Grid &grid, const DataVector &alpha)
 Constructor.
 
void setAlpha (const DataVector &alpha)
 
 ~InterpolantScalarFunctionHessian () override
 Destructor.
 
- Public Member Functions inherited from sgpp::base::ScalarFunctionHessian
void eval (const DataMatrix &x, DataVector &value, DataMatrix &gradient, std::vector< DataMatrix > &hessian)
 Convenience method for calculating \(f(\vec{x})\) together with \(\nabla f(\vec{x})\) and \(H_f(\vec{x}) \in \mathbb{R}^{d \times d}\) for multiple \(\vec{x}\).
 
size_t getNumberOfParameters () const
 
 ScalarFunctionHessian (size_t d)
 Constructor.
 
virtual ~ScalarFunctionHessian ()
 Destructor.
 

Protected Attributes

DataVector alpha
 coefficient vector
 
Gridgrid
 sparse grid
 
std::unique_ptr< OperationEvalHessianopEvalHessian
 pointer to evaluation operation
 
- Protected Attributes inherited from sgpp::base::ScalarFunctionHessian
size_t d
 dimension of the domain
 

Detailed Description

Sparse grid interpolant Hessian of a scalar-valued function.

See also
InterpolantScalarFunction

Constructor & Destructor Documentation

◆ InterpolantScalarFunctionHessian()

sgpp::base::InterpolantScalarFunctionHessian::InterpolantScalarFunctionHessian ( Grid grid,
const DataVector alpha 
)
inline

Constructor.

Do not destruct the grid before the InterpolantScalarFunctionHessian object!

Parameters
gridsparse grid
alphacoefficient vector

◆ ~InterpolantScalarFunctionHessian()

sgpp::base::InterpolantScalarFunctionHessian::~InterpolantScalarFunctionHessian ( )
inlineoverride

Destructor.

Member Function Documentation

◆ clone()

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

Implements sgpp::base::ScalarFunctionHessian.

References alpha, clone(), and grid.

Referenced by clone().

◆ eval()

double sgpp::base::InterpolantScalarFunctionHessian::eval ( const DataVector x,
DataVector gradient,
DataMatrix hessian 
)
inlineoverridevirtual

Evaluation of the function, its gradient and its Hessian.

Parameters
xevaluation point \(\vec{x} \in [0, 1]^d\)
[out]gradientgradient \(\nabla f(\vec{x}) \in \mathbb{R}^d\)
[out]hessianHessian matrix \(H_f(\vec{x}) \in \mathbb{R}^{d \times d}\)
Returns
\(f(\vec{x})\)

Implements sgpp::base::ScalarFunctionHessian.

References alpha, sgpp::base::ScalarFunctionHessian::d, and opEvalHessian.

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

◆ getAlpha()

const DataVector & sgpp::base::InterpolantScalarFunctionHessian::getAlpha ( ) const
inline
Returns
coefficient vector

References alpha.

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

◆ setAlpha()

void sgpp::base::InterpolantScalarFunctionHessian::setAlpha ( const DataVector alpha)
inline
Parameters
alphacoefficient vector

References alpha.

Member Data Documentation

◆ alpha

◆ grid

Grid& sgpp::base::InterpolantScalarFunctionHessian::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().

◆ opEvalHessian

std::unique_ptr<OperationEvalHessian> sgpp::base::InterpolantScalarFunctionHessian::opEvalHessian
protected

pointer to evaluation operation

Referenced by eval().


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