roboptim::IdentityFunction Class Reference

Identity function. More...

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

Inheritance diagram for roboptim::IdentityFunction:

Collaboration diagram for roboptim::IdentityFunction:

List of all members.

Public Member Functions
	IdentityFunction (const vector_t &offset) throw ()
	Build an identity function.
	~IdentityFunction () throw ()
virtual std::ostream &	print (std::ostream &) const throw ()
	Display the function on the specified output stream.
Protected Member Functions
void	impl_compute (result_t &, const argument_t &) const throw ()
	Function evaluation.
void	impl_gradient (gradient_t &, const argument_t &, size_type=0) const throw ()
	Gradient evaluation.
void	impl_jacobian (jacobian_t &, const argument_t &) const throw ()
	Jacobian evaluation.

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Detailed Description

Identity function.

Implement a linear function using the formula:

where and are set when the class is instantiated.

Examples:

identity-function.cc.

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Constructor & Destructor Documentation

roboptim::IdentityFunction::IdentityFunction

(

const vector_t &

offset

)

throw ()

Build an identity function.

Parameters:

offset

identity function offset

roboptim::IdentityFunction::~IdentityFunction

(

)

throw ()

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Member Function Documentation

void roboptim::IdentityFunction::impl_compute	(	result_t &	result,
		const argument_t &	argument
	)		const throw () [protected, virtual]

Function evaluation.

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

Warning:

Do not call this function directly, call operator()(result_t&, const argument_t&) const throw () instead.

Parameters:

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

Implements roboptim::GenericFunction< T >.

void roboptim::IdentityFunction::impl_gradient	(	gradient_t &	gradient,
		const argument_t &	argument,
		size_type	functionId = 0
	)		const throw () [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 >.

void roboptim::IdentityFunction::impl_jacobian	(	jacobian_t &	jacobian,
		const argument_t &	arg
	)		const throw () [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 >.

References roboptim::GenericDifferentiableFunction< T >::jacobianSize().

std::ostream & roboptim::IdentityFunction::print

(

std::ostream &

o

)

const throw () [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().