sgpp::optimization::InterpolantVectorFunction Class Reference

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

#include <InterpolantVectorFunction.hpp>

Inheritance diagram for sgpp::optimization::InterpolantVectorFunction:

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

Protected Attributes
base::DataMatrix	alpha
	coefficient matrix More...
base::Grid &	grid
	sparse grid More...
std::unique_ptr< base::OperationEval >	opEval
	pointer to evaluation operation More...
Protected Attributes inherited from sgpp::optimization::VectorFunction
size_t	d
	dimension of the domain More...
size_t	m
	number of components More...

Detailed Description

Sparse grid interpolant of a vector-valued function.

More generally, the function can be any linear combination \(g\colon [0, 1]^d \to \mathbb{R}^m\), \(g_j(\vec{x}) = \sum_{k=1}^N \alpha_{k,j} \varphi_k(\vec{x})\) 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

InterpolantVectorFunction()

sgpp::optimization::InterpolantVectorFunction::InterpolantVectorFunction ( base::Grid &  grid, const base::DataMatrix &  alpha  )

inline

Constructor.

Do not destruct the grid before the InterpolantVectorFunction object!

Parameters

grid	sparse grid
alpha	coefficient matrix (j-th column contains hierarchical surplusses \(\alpha_{\cdot,j}\) of \(g_j\))

Referenced by clone().

~InterpolantVectorFunction()

sgpp::optimization::InterpolantVectorFunction::~InterpolantVectorFunction ( )

inlineoverride

Destructor.

Member Function Documentation

clone()

void sgpp::optimization::InterpolantVectorFunction::clone ( std::unique_ptr< VectorFunction > &  clone ) const

inlineoverridevirtual

Parameters

[out]

clone

pointer to cloned object

Implements sgpp::optimization::VectorFunction.

References alpha, grid, and InterpolantVectorFunction().

eval()

void sgpp::optimization::InterpolantVectorFunction::eval ( const base::DataVector &  x, base::DataVector &  value  )

inlineoverridevirtual

Evaluation of the function.

Parameters

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

Implements sgpp::optimization::VectorFunction.

References alpha, sgpp::optimization::VectorFunction::d, opEval, and sgpp::base::DataVector::setAll().

getAlpha()

const base::DataMatrix& sgpp::optimization::InterpolantVectorFunction::getAlpha ( ) const

inline

Returns

coefficient matrix

References alpha.

setAlpha()

void sgpp::optimization::InterpolantVectorFunction::setAlpha ( const base::DataMatrix &  alpha )

inline

Parameters

alpha

coefficient matrix

References alpha.

Member Data Documentation

alpha

base::DataMatrix sgpp::optimization::InterpolantVectorFunction::alpha

protected

coefficient matrix

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

grid

base::Grid& sgpp::optimization::InterpolantVectorFunction::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::InterpolantVectorFunction::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/vector/InterpolantVectorFunction.hpp