class ROOT::Math::IGradientMultiDim


       Documentation for the abstract class IBaseFunctionMultiDim.
       Interface (abstract class) for generic functions objects of multi-dimension
       Provides a method to evaluate the function given a vector of coordinate values,
       by implementing operator() (const double *).
       In addition it defines the interface for copying functions via the pure virtual method Clone()
       and the interface for getting the function dimension via the NDim() method.
       Derived classes must implement the pure private virtual method DoEval(const double *) for the
       function evaluation in addition to NDim() and Clone().

       @ingroup  GenFunc

Function Members (Methods)

This is an abstract class, constructors will not be documented.
Look at the header to check for available constructors.

public:

virtual	~IGradientMultiDim()
double	Derivative(const double* x, unsigned int icoord = 0) const
virtual void	FdF(const double* x, double& f, double* df) const
virtual void	Gradient(const double* x, double* grad) const
ROOT::Math::IGradientMultiDim	IGradientMultiDim()
ROOT::Math::IGradientMultiDim	IGradientMultiDim(const ROOT::Math::IGradientMultiDim&)
ROOT::Math::IGradientMultiDim&	operator=(const ROOT::Math::IGradientMultiDim&)

private:

virtual double

DoDerivative(const double* x, unsigned int icoord) const

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

virtual ~IGradientMultiDim()

 virual destructor

{}

void Gradient(const double* x, double* grad) const

          Evaluate all the vector of function derivatives (gradient)  at a point x.
          Derived classes must re-implement if it is more efficient than evaluting one at a time

double Derivative(const double* x, unsigned int icoord = 0) const

         Return the partial derivative with respect to the passed coordinate

return DoDerivative(x, icoord)

void FdF(const double* x, double& f, double* df) const

          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