sgpp::optimization::InterpolantScalarFunction Class Reference

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

#include <InterpolantScalarFunction.hpp>

Inheritance diagram for sgpp::optimization::InterpolantScalarFunction:

Public Member Functions
void	clone (std::unique_ptr< ScalarFunction > &clone) const override
double	eval (const base::DataVector &x) override
	Evaluation of the function. More...
const base::DataVector &	getAlpha () const
	InterpolantScalarFunction (base::Grid &grid, const base::DataVector &alpha)
	Constructor. More...
void	setAlpha (const base::DataVector &alpha)
	~InterpolantScalarFunction () override
	Destructor. More...
Public Member Functions inherited from sgpp::optimization::ScalarFunction
size_t	getNumberOfParameters () const
	ScalarFunction (size_t d)
	Constructor. More...
virtual	~ScalarFunction ()
	Destructor. More...

Protected Attributes
base::DataVector	alpha
	coefficient vector More...
base::Grid &	grid
	sparse grid More...
std::unique_ptr< base::OperationEval >	opEval
	pointer to evaluation operation More...
Protected Attributes inherited from sgpp::optimization::ScalarFunction
size_t	d
	dimension of the domain More...

Detailed Description

Sparse grid interpolant of a scalar-valued function.

More generally, the function can be any linear combination \(f\colon [0, 1]^d \to \mathbb{R}\), \(f(\vec{x}) = \sum_{k=1}^N \alpha_k \varphi_k(\vec{x})\) of the basis functions \(\varphi_k = \varphi_{\vec{\ell}_k,\vec{i}_k}\) of a sparse grid with grid points \(\vec{x}_k = \vec{x}_{\vec{\ell}_k,\vec{i}_k}\). But most often, the function (e.g., its coefficients) is constructed as an interpolant at the grid points for some function values.

Constructor & Destructor Documentation

InterpolantScalarFunction()

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

inline

Constructor.

Do not destruct the grid before the InterpolantScalarFunction object!

Parameters

grid	sparse grid
alpha	coefficient vector

Referenced by clone().

~InterpolantScalarFunction()

sgpp::optimization::InterpolantScalarFunction::~InterpolantScalarFunction ( )

inlineoverride

Destructor.

Member Function Documentation

clone()

void sgpp::optimization::InterpolantScalarFunction::clone ( std::unique_ptr< ScalarFunction > &  clone ) const

inlineoverridevirtual

Parameters

[out]

clone

pointer to cloned object

Implements sgpp::optimization::ScalarFunction.

References alpha, grid, and InterpolantScalarFunction().

eval()

double sgpp::optimization::InterpolantScalarFunction::eval ( const base::DataVector &  x )

inlineoverridevirtual

Evaluation of the function.

Parameters

x	evaluation point \(\vec{x} \in [0, 1]^d\)

Returns

\(f(\vec{x})\)

Implements sgpp::optimization::ScalarFunction.

References alpha, sgpp::optimization::ScalarFunction::d, and opEval.

getAlpha()

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

inline

Returns

coefficient vector

References alpha.

setAlpha()

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

inline

Parameters

alpha

coefficient vector

References alpha.

Member Data Documentation

alpha

base::DataVector sgpp::optimization::InterpolantScalarFunction::alpha

protected

coefficient vector

Referenced by clone(), eval(), getAlpha(), python.learner.Classifier.Classifier::refineGrid(), and setAlpha().

grid

base::Grid& sgpp::optimization::InterpolantScalarFunction::grid

protected

sparse grid

Referenced by clone(), python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), python.uq.learner.Regressor.Regressor::learnData(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), python.learner.Classifier.Classifier::updateResults(), python.learner.Regressor.Regressor::updateResults(), and python.uq.learner.Regressor.Regressor::updateResults().

opEval

std::unique_ptr<base::OperationEval> sgpp::optimization::InterpolantScalarFunction::opEval

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/InterpolantScalarFunction.hpp