Package org.hipparchus.optim.nonlinear.vector.constrained

Class TwiceDifferentiableFunction

java.lang.Object

org.hipparchus.optim.nonlinear.vector.constrained.TwiceDifferentiableFunction

All Implemented Interfaces:

MultivariateFunction

Direct Known Subclasses:

QuadraticFunction

public abstract class TwiceDifferentiableFunction
extends Object
implements MultivariateFunction

A MultivariateFunction that also has a defined gradient and Hessian.

Since:

3.1

Constructor Summary

Constructors

Constructor	Description
TwiceDifferentiableFunction()

Method Summary

Modifier and Type	Method	Description
abstract int	dim()	Returns the dimensionality of the function domain.
RealVector	gradient(double[] x)	Returns the gradient of this function at (x)
abstract RealVector	gradient(RealVector x)	Returns the gradient of this function at (x)
RealMatrix	hessian(double[] x)	The Hessian of this function at (x)
abstract RealMatrix	hessian(RealVector x)	The Hessian of this function at (x)
double	value(double[] x)	Returns the value of this function at (x)
abstract double	value(RealVector x)	Returns the value of this function at (x)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

TwiceDifferentiableFunction

public TwiceDifferentiableFunction()

Method Details

dim

public abstract int dim()

Returns the dimensionality of the function domain. If dim() returns (n) then this function expects an n-vector as its input.

Returns:

the expected dimension of the function's domain

value

public abstract double value(RealVector x)

Returns the value of this function at (x)

Parameters:

x - a point to evaluate this function at.

Returns:

the value of this function at (x)

gradient

public abstract RealVector gradient(RealVector x)

Returns the gradient of this function at (x)

Parameters:

x - a point to evaluate this gradient at

Returns:

the gradient of this function at (x)

hessian

public abstract RealMatrix hessian(RealVector x)

The Hessian of this function at (x)

Parameters:

x - a point to evaluate this Hessian at

Returns:

the Hessian of this function at (x)

value

public double value(double[] x)

Returns the value of this function at (x)

Specified by:

value in interface MultivariateFunction

Parameters:

x - a point to evaluate this function at.

Returns:

the value of this function at (x)

gradient

public RealVector gradient(double[] x)

Returns the gradient of this function at (x)

Parameters:

x - a point to evaluate this gradient at

Returns:

the gradient of this function at (x)

hessian

public RealMatrix hessian(double[] x)

The Hessian of this function at (x)

Parameters:

x - a point to evaluate this Hessian at

Returns:

the Hessian of this function at (x)