ROOT   6.08/07 Reference Guide

Gradient interface (abstract class) defining the signature for calculating the gradient of a multi-dimensional function.

Three methods are provided:

• Gradient(const double *x, double * grad) evaluate the full gradient vector at the vector value x
• Derivative(const double * x, int icoord) evaluate the partial derivative for the icoord coordinate
• FdF(const double *x, double &f, double * g) evaluate at the same time gradient and function/

Concrete classes should derive from ROOT::Math::IGradientFunctionMultiDim and not from this class.

Definition at line 196 of file IFunction.h.

## Public Member Functions

virual destructor More...

double Derivative (const double *x, unsigned int icoord=0) const
Return the partial derivative with respect to the passed coordinate. More...

virtual void FdF (const double *x, double &f, double *df) const =0
Optimized method to evaluate at the same time the function value and derivative at a point x. More...

Evaluate all the vector of function derivatives (gradient) at a point x. More...

## Private Member Functions

virtual double DoDerivative (const double *x, unsigned int icoord) const =0
function to evaluate the derivative with respect each coordinate. More...

#include <Math/IFunction.h>

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## Constructor & Destructor Documentation

inlinevirtual

virual destructor

Definition at line 201 of file IFunction.h.

## ◆ Derivative()

 double ROOT::Math::IGradientMultiDim::Derivative ( const double * x, unsigned int icoord = 0 ) const
inline

Return the partial derivative with respect to the passed coordinate.

Definition at line 212 of file IFunction.h.

## ◆ DoDerivative()

 virtual double ROOT::Math::IGradientMultiDim::DoDerivative ( const double * x, unsigned int icoord ) const
privatepure virtual

function to evaluate the derivative with respect each coordinate.

To be implemented by the derived class

## ◆ FdF()

 virtual void ROOT::Math::IGradientMultiDim::FdF ( const double * x, double & f, double * df ) const
pure virtual

Optimized method to evaluate at the same time the function value and derivative at a point x.

Often both value and derivatives are needed and it is often more efficient to compute them at the same time. Derived class should implement this method if performances play an important role and if it is faster to evaluate value and derivative at the same time