roboptim::GenericIdentityFunction< T > Class Template Reference

Identity function. More...

#include <roboptim/core/function/identity.hh>

Inheritance diagram for roboptim::GenericIdentityFunction< T >:

List of all members.

Public Member Functions
	ROBOPTIM_TWICE_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_ (GenericLinearFunction< T >)
	GenericIdentityFunction (const vector_t &offset)
	Build an identity function.
	~GenericIdentityFunction ()
virtual std::ostream &	print (std::ostream &o) const
	Display the function on the specified output stream.
Protected Member Functions
void	impl_compute (result_ref result, const_argument_ref argument) const
	Function evaluation.
void	impl_jacobian (jacobian_ref jacobian, const_argument_ref) const
	Jacobian evaluation.
void	impl_gradient (gradient_ref gradient, const_argument_ref, size_type idFunction) const
	Gradient evaluation.
template<>
void	impl_gradient (gradient_ref gradient, const_argument_ref, size_type idFunction) const
	Gradient evaluation.

---

Detailed Description

template<typename T>
class roboptim::GenericIdentityFunction< T >

Identity function.

Implement a linear function using the formula:

where and are set when the class is instantiated.

---

Constructor & Destructor Documentation

template<typename T >

roboptim::GenericIdentityFunction< T >::GenericIdentityFunction

(

const vector_t &

offset

)

[inline]

Build an identity function.

Parameters:

offset

identity function offset

template<typename T >

roboptim::GenericIdentityFunction< T >::~GenericIdentityFunction

(

)

[inline]

---

Member Function Documentation

template<typename T >

void roboptim::GenericIdentityFunction< T >::impl_compute	(	result_ref	result,
		const_argument_ref	argument
	)		const [inline, protected, virtual]

Function evaluation.

Evaluate the function, has to be implemented in concrete classes.

Warning:

Do not call this function directly, call operator()(result_ref, const_argument_ref) const instead.

Parameters:

result	result will be stored in this vector
argument	point at which the function will be evaluated

Implements roboptim::GenericFunction< T >.

template<>

void roboptim::GenericIdentityFunction< EigenMatrixSparse >::impl_gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId
	)		const [inline, protected, virtual]

Gradient evaluation.

Compute the gradient, has to be implemented in concrete classes. The gradient is computed for a specific sub-function which id is passed through the functionId argument.

Warning:

Do not call this function directly, call gradient instead.

Parameters:

gradient	gradient will be store in this argument
argument	point where the gradient will be computed
functionId	evaluated function id in the split representation

Implements roboptim::GenericDifferentiableFunction< T >.

template<typename T >

void roboptim::GenericIdentityFunction< T >::impl_jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	arg
	)		const [inline, protected, virtual]

Jacobian evaluation.

Computes the jacobian, can be overridden by concrete classes. The default behavior is to compute the jacobian from the gradient.

Warning:

Do not call this function directly, call jacobian instead.

Parameters:

jacobian	jacobian will be store in this argument
arg	point where the jacobian will be computed

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

Reimplemented from roboptim::GenericDifferentiableFunction< T >.

template<typename T >

virtual std::ostream& roboptim::GenericIdentityFunction< T >::print

(

std::ostream &

o

)

const [inline, virtual]

Display the function on the specified output stream.

Parameters:

o	output stream used for display

Returns:

output stream

Reimplemented from roboptim::GenericLinearFunction< T >.

References roboptim::decindent(), roboptim::iendl(), and roboptim::incindent().

template<typename T >

roboptim::GenericIdentityFunction< T >::ROBOPTIM_TWICE_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_

(

GenericLinearFunction< T >

)