sgpp::optimization::ASInterpolantScalarFunctionGradient Class Reference

Sparse grid interpolant gradient of a scalar-valued function $f colon mathbb{R}^d to mathbb{R}$ (in contrast to ASInterpolantScalarFunctionGradient's $f colon [0,1]^d to mathbb{R}$) More...

#include <ASInterpolantScalarFunctionGradient.hpp>

Inheritance diagram for sgpp::optimization::ASInterpolantScalarFunctionGradient:

Public Member Functions
	ASInterpolantScalarFunctionGradient (base::Grid &grid, const base::DataVector &alpha)
	Constructor.
void	clone (std::unique_ptr< ScalarFunctionGradient > &clone) const override
double	eval (const base::DataVector &x, base::DataVector &gradient) override
	Evaluation of the function and its gradient.
const base::DataVector &	getAlpha () const
void	setAlpha (const base::DataVector &alpha)
	~ASInterpolantScalarFunctionGradient () override
	Destructor.
Public Member Functions inherited from sgpp::base::ScalarFunctionGradient
virtual void	clone (std::unique_ptr< ScalarFunctionGradient > &clone) const =0
	Pure virtual method for cloning the gradient.
virtual void	eval (const DataMatrix &x, DataVector &value, DataMatrix &gradient)
	Convenience method for calculating \(f(\vec{x})\) together with \(\nabla f(\vec{x})\) for multiple \(\vec{x}\).
size_t	getNumberOfParameters () const
	ScalarFunctionGradient (size_t d)
	Constructor.
virtual	~ScalarFunctionGradient ()
	Destructor.

Protected Attributes
base::DataVector	alpha
	coefficient vector
base::Grid &	grid
	sparse grid
std::unique_ptr< base::OperationEvalGradient >	opEvalGradient
	pointer to evaluation operation
Protected Attributes inherited from sgpp::base::ScalarFunctionGradient
size_t	d
	dimension of the domain

Detailed Description

Sparse grid interpolant gradient of a scalar-valued function $f colon mathbb{R}^d to mathbb{R}$ (in contrast to ASInterpolantScalarFunctionGradient's $f colon [0,1]^d to mathbb{R}$)

See also

ASInterpolantScalarFunction

Constructor & Destructor Documentation

ASInterpolantScalarFunctionGradient()

sgpp::optimization::ASInterpolantScalarFunctionGradient::ASInterpolantScalarFunctionGradient ( base::Grid &  grid, const base::DataVector &  alpha  )

inline

Constructor.

Do not destruct the grid before the ASInterpolantScalarFunctionGradient object!

Parameters

grid	sparse grid
alpha	coefficient vector

~ASInterpolantScalarFunctionGradient()

sgpp::optimization::ASInterpolantScalarFunctionGradient::~ASInterpolantScalarFunctionGradient ( )

inlineoverride

Destructor.

Member Function Documentation

clone()

void sgpp::optimization::ASInterpolantScalarFunctionGradient::clone ( std::unique_ptr< ScalarFunctionGradient > &  clone ) const

inlineoverride

Parameters

[out]

clone

pointer to cloned object

References alpha, clone(), and grid.

Referenced by clone().

eval()

double sgpp::optimization::ASInterpolantScalarFunctionGradient::eval ( const base::DataVector &  x, base::DataVector &  gradient  )

inlineoverridevirtual

Evaluation of the function and its gradient.

Parameters

	x	evaluation point $vec{x} in mathbb{R}^d$
[out]	gradient	gradient $nabla f(vec{x}) in mathbb{R}^d$

Returns

$f(vec{x})$

Implements sgpp::base::ScalarFunctionGradient.

References alpha, and opEvalGradient.

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

getAlpha()

const base::DataVector & sgpp::optimization::ASInterpolantScalarFunctionGradient::getAlpha ( ) const

inline

Returns

coefficient vector

References alpha.

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

setAlpha()

void sgpp::optimization::ASInterpolantScalarFunctionGradient::setAlpha ( const base::DataVector &  alpha )

inline

Parameters

alpha

coefficient vector

References alpha.

Member Data Documentation

alpha

base::DataVector sgpp::optimization::ASInterpolantScalarFunctionGradient::alpha

protected

coefficient vector

Referenced by clone(), python.learner.Learner.Learner::doLearningIteration(), eval(), getAlpha(), python.learner.Learner.Learner::learnData(), python.learner.Learner.Learner::learnDataWithTest(), python.uq.learner.Interpolant.Interpolant::learnDataWithTest(), python.uq.dists.SGDEdist.SGDEdist::pdf(), setAlpha(), and python.uq.dists.SGDEdist.SGDEdist::toJson().

grid

base::Grid& sgpp::optimization::ASInterpolantScalarFunctionGradient::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<base::OperationEvalGradient> sgpp::optimization::ASInterpolantScalarFunctionGradient::opEvalGradient

protected

pointer to evaluation operation

Referenced by eval().

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

• optimization/src/sgpp/optimization/function/scalar/ASInterpolantScalarFunctionGradient.hpp