sgpp::optimization::ScalarFunctionHessian Class Reference

Abstract base class for scalar-valued functions \(f\colon [0, 1]^d \to \mathbb{R}\) together with their gradients \(\nabla f\colon [0, 1]^d \to \mathbb{R}^d\) and Hessians \(H_f\colon [0, 1]^d \to \mathbb{R}^{d \times d}\) (e.g., Hessians of objective functions in optimization). More...

#include <ScalarFunctionHessian.hpp>

Inheritance diagram for sgpp::optimization::ScalarFunctionHessian:

Public Member Functions
virtual void	clone (std::unique_ptr< ScalarFunctionHessian > &clone) const =0
	Pure virtual method for cloning the Hessian. More...
virtual double	eval (const base::DataVector &x, base::DataVector &gradient, base::DataMatrix &hessian)=0
	Pure virtual method for calculating \(f(\vec{x})\) together with \(\nabla f(\vec{x})\) and \(H_f(\vec{x}) \in \mathbb{R}^{d \times d}\). More...
size_t	getNumberOfParameters () const
	ScalarFunctionHessian (size_t d)
	Constructor. More...
virtual	~ScalarFunctionHessian ()
	Destructor. More...

Protected Attributes
size_t	d
	dimension of the domain More...

Detailed Description

Abstract base class for scalar-valued functions \(f\colon [0, 1]^d \to \mathbb{R}\) together with their gradients \(\nabla f\colon [0, 1]^d \to \mathbb{R}^d\) and Hessians \(H_f\colon [0, 1]^d \to \mathbb{R}^{d \times d}\) (e.g., Hessians of objective functions in optimization).

Constructor & Destructor Documentation

ScalarFunctionHessian()

sgpp::optimization::ScalarFunctionHessian::ScalarFunctionHessian ( size_t  d )

inlineexplicit

Constructor.

Parameters

d	dimension of the domain

~ScalarFunctionHessian()

virtual sgpp::optimization::ScalarFunctionHessian::~ScalarFunctionHessian ( )

inlinevirtual

Destructor.

References eval().

Member Function Documentation

clone()

virtual void sgpp::optimization::ScalarFunctionHessian::clone ( std::unique_ptr< ScalarFunctionHessian > &  clone ) const

pure virtual

Pure virtual method for cloning the Hessian.

It should generate a pointer to the cloned object and it's used for parallel computations (the eval() method might not be thread-safe).

Parameters

[out]

clone

pointer to cloned object

Implemented in sgpp::optimization::ComponentScalarFunctionHessian, sgpp::optimization::InterpolantScalarFunctionHessian, and sgpp::optimization::WrapperScalarFunctionHessian.

Referenced by sgpp::optimization::optimizer::AdaptiveNewton::AdaptiveNewton(), getNumberOfParameters(), and sgpp::optimization::optimizer::Newton::Newton().

eval()

virtual double sgpp::optimization::ScalarFunctionHessian::eval ( const base::DataVector &  x, base::DataVector &  gradient, base::DataMatrix &  hessian  )

pure virtual

Pure virtual method for calculating \(f(\vec{x})\) together with \(\nabla f(\vec{x})\) and \(H_f(\vec{x}) \in \mathbb{R}^{d \times d}\).

Parameters

	x	evaluation point \(\vec{x} \in [0, 1]^d\)
[out]	gradient	gradient \(\nabla f(\vec{x}) \in \mathbb{R}^d\)
[out]	hessian	Hessian matrix \(H_f(\vec{x}) \in \mathbb{R}^{d \times d}\)

Returns

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

Implemented in sgpp::optimization::ComponentScalarFunctionHessian, sgpp::optimization::InterpolantScalarFunctionHessian, and sgpp::optimization::WrapperScalarFunctionHessian.

Referenced by sgpp::optimization::ComponentScalarFunctionHessian::eval(), and ~ScalarFunctionHessian().

getNumberOfParameters()

size_t sgpp::optimization::ScalarFunctionHessian::getNumberOfParameters ( ) const

inline

Returns

dimension \(d\) of the domain

References clone(), and d.

Member Data Documentation

d

size_t sgpp::optimization::ScalarFunctionHessian::d

protected

dimension of the domain

Referenced by sgpp::optimization::WrapperScalarFunctionHessian::clone(), sgpp::optimization::InterpolantScalarFunctionHessian::eval(), and getNumberOfParameters().

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

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