Derive a concrete class from this one if you have a scalar function of multiple variables that you want to differentiate. More...

Inheritance diagram for SimTK::Differentiator::GradientFunction:

Public Member Functions
virtual int	f (const Vector &y, Real &fy) const =0

Public Member Functions inherited from SimTK::Differentiator::Function
Function &	setNumFunctions (int)

Function &	setNumParameters (int)

Function &	setEstimatedAccuracy (Real)

int	getNumFunctions () const

int	getNumParameters () const

Real	getEstimatedAccuracy () const

void	resetAllStatistics ()

int	getNumCalls () const

int	getNumFailures () const

Protected Member Functions
	GradientFunction (int ny=-1, Real acc=-1)

virtual	~GradientFunction ()

Protected Member Functions inherited from SimTK::Differentiator::Function
	Function ()

	~Function ()

Additional Inherited Members
Protected Attributes inherited from SimTK::Differentiator::Function
FunctionRep *	rep

Detailed Description

Derive a concrete class from this one if you have a scalar function of multiple variables that you want to differentiate.

This is the typical form for an optimization objective function, for example.

Constructor & Destructor Documentation

SimTK::Differentiator::GradientFunction::GradientFunction	(	int	ny = `-1`,
		Real	acc = `-1`
	)

explicitprotected

virtual SimTK::Differentiator::GradientFunction::~GradientFunction ( )

inlineprotectedvirtual

virtual int SimTK::Differentiator::GradientFunction::f	(	const Vector &	y,
		Real &	fy
	)		const

pure virtual

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