Class TwiceDifferentiableFunction
- java.lang.Object
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- org.hipparchus.optim.nonlinear.vector.constrained.TwiceDifferentiableFunction
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- 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
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Constructor Summary
Constructors Constructor Description TwiceDifferentiableFunction()
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Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description abstract intdim()Returns the dimensionality of the function domain.RealVectorgradient(double[] x)Returns the gradient of this function at (x)abstract RealVectorgradient(RealVector x)Returns the gradient of this function at (x)RealMatrixhessian(double[] x)The Hessian of this function at (x)abstract RealMatrixhessian(RealVector x)The Hessian of this function at (x)doublevalue(double[] x)Returns the value of this function at (x)abstract doublevalue(RealVector x)Returns the value of this function at (x)
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Method Detail
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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
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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)
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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)
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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)
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value
public double value(double[] x)
Returns the value of this function at (x)- Specified by:
valuein interfaceMultivariateFunction- Parameters:
x- a point to evaluate this function at.- Returns:
- the value of this function at (x)
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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)
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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)
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