roboptim::GenericNumericLinearFunction< T > Class Template Reference

Build a linear function from a vector and a matrix. More...

#include <roboptim/core/numeric-linear-function.hh>

Inheritance diagram for roboptim::GenericNumericLinearFunction< T >:

List of all members.

Public Member Functions
	ROBOPTIM_TWICE_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_ (GenericLinearFunction< T >)
	GenericNumericLinearFunction (const_matrix_ref A, const_vector_ref b)
	Build a linear function from a matrix and a vector.
	GenericNumericLinearFunction (const GenericLinearFunction< T > &)
	Build a linear function from another one.
	~GenericNumericLinearFunction ()
virtual std::ostream &	print (std::ostream &) const
	Display the function on the specified output stream.
const_matrix_ref	A () const
const_vector_ref	b () const
matrix_ref	A ()
vector_ref	b ()
void	impl_compute (result_ref, const_argument_ref) const
	Function evaluation.
void	impl_gradient (gradient_ref, const_argument_ref, size_type=0) const
	Gradient evaluation.
void	impl_jacobian (jacobian_ref, const_argument_ref) const
	Jacobian evaluation.
template<>
void	impl_gradient (gradient_ref gradient, const_argument_ref, size_type idFunction) const
	Gradient evaluation.

---

Detailed Description

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

Build a linear function from a vector and a matrix.

Implement a linear function using the general formula:

where and are set when the class is instantiated.

Examples:

numeric-linear-function.cc.

---

Constructor & Destructor Documentation

template<typename T >

roboptim::GenericNumericLinearFunction< T >::GenericNumericLinearFunction	(	const_matrix_ref	A,
		const_vector_ref	b
	)

Build a linear function from a matrix and a vector.

See class documentation for A and b definition.

Parameters:

A	A matrix
b	b vector

template<typename T >

roboptim::GenericNumericLinearFunction< T >::GenericNumericLinearFunction

(

const GenericLinearFunction< T > &

function

)

Build a linear function from another one.

template<typename T >

roboptim::GenericNumericLinearFunction< T >::~GenericNumericLinearFunction

(

)

---

Member Function Documentation

template<typename T>

const_matrix_ref roboptim::GenericNumericLinearFunction< T >::A

(

)

const [inline]

template<typename T>

matrix_ref roboptim::GenericNumericLinearFunction< T >::A

(

)

[inline]

template<typename T>

const_vector_ref roboptim::GenericNumericLinearFunction< T >::b

(

)

const [inline]

template<typename T>

vector_ref roboptim::GenericNumericLinearFunction< T >::b

(

)

[inline]

template<typename T >

void roboptim::GenericNumericLinearFunction< T >::impl_compute	(	result_ref	result,
		const_argument_ref	argument
	)		const [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<typename T >

void roboptim::GenericNumericLinearFunction< T >::impl_gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId = 0
	)		const [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<>

void roboptim::GenericNumericLinearFunction< EigenMatrixSparse >::impl_gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId
	)		const [inline, 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::GenericNumericLinearFunction< T >::impl_jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	arg
	)		const [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

Reimplemented from roboptim::GenericDifferentiableFunction< T >.

template<typename T >

std::ostream & roboptim::GenericNumericLinearFunction< T >::print

(

std::ostream &

o

)

const [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::GenericNumericLinearFunction< T >::ROBOPTIM_TWICE_DIFFERENTIABLE_FUNCTION_FWD_TYPEDEFS_

(

GenericLinearFunction< T >

)