roboptim::DerivableParametrizedFunction< F > Class Template Reference

Parametrized function with parameter derivative available. More...

#include <roboptim/core/derivable-parametrized-function.hh>

Inheritance diagram for roboptim::DerivableParametrizedFunction< F >:

List of all members.

Public Types
typedef F::value_type	value_type
	Import value type.
typedef F::size_type	size_type
	Import size type.
typedef F::vector_t	vector_t
	Import vector type.
typedef F::matrix_t	matrix_t
	Import matrix type.
typedef F	result_t
	Import result type.
typedef F::argument_t	argument_t
	Import argument types.
typedef F::const_argument_ref	const_argument_ref
typedef F::gradient_t	gradient_t
	Import gradient type.
typedef F::gradient_ref	gradient_ref
typedef F::gradient_ref	const_gradient_ref
typedef F::jacobian_t	jacobian_t
	Import jacobian type.
typedef F::jacobian_ref	jacobian_ref
typedef F::const_jacobian_ref	const_jacobian_ref
typedef F::jacobianSize_t	jacobianSize_t
	Import jacobian size type (pair of values).
Public Member Functions
size_type	gradientSize () const
	Return the gradient size.
jacobianSize_t	jacobianSize () const
	Return the jacobian size as a pair.
bool	isValidGradient (const_gradient_ref gradient) const
	Check if the gradient is valid (check size).
bool	isValidJacobian (const_jacobian_ref jacobian) const throw ()
	Check if the jacobian is valid (check sizes).
jacobian_t	jacobian (const_argument_ref argument, size_type order=0) const
	Computes the jacobian.
void	jacobian (jacobian_ref jacobian, const_argument_ref argument, size_type order=0) const
	Computes the jacobian.
gradient_t	gradient (const_argument_ref argument, size_type functionId=0, size_type order=0) const
	Computes the gradient.
void	gradient (gradient_ref gradient, const_argument_ref argument, size_type functionId=0, size_type order=0) const
	Computes the gradient.
virtual std::ostream &	print (std::ostream &o) const
	Display the function on the specified output stream.
Protected Member Functions
	DerivableParametrizedFunction (size_type inputSize, size_type functionInputSize, size_type functionOutputSize)
	Concrete class constructor should call this constructor.
virtual void	impl_jacobian (jacobian_ref jacobian, const_argument_ref arg, size_type order=0) const
	Jacobian evaluation.
virtual void	impl_gradient (gradient_ref gradient, const_argument_ref argument, size_type functionId=0, size_type order=0) const =0
	Gradient evaluation.

---

Detailed Description

template<typename F>
class roboptim::DerivableParametrizedFunction< F >

Parametrized function with parameter derivative available.

Depending on inner function type, this class allows computation of parameter derivative or combined parameter/function derivative.

Template Parameters:

F	inner function type.

---

Member Typedef Documentation

template<typename F >

typedef F::argument_t roboptim::DerivableParametrizedFunction< F >::argument_t

Import argument types.

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F::const_argument_ref roboptim::DerivableParametrizedFunction< F >::const_argument_ref

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F::gradient_ref roboptim::DerivableParametrizedFunction< F >::const_gradient_ref

template<typename F >

typedef F::const_jacobian_ref roboptim::DerivableParametrizedFunction< F >::const_jacobian_ref

template<typename F >

typedef F::gradient_ref roboptim::DerivableParametrizedFunction< F >::gradient_ref

template<typename F >

typedef F::gradient_t roboptim::DerivableParametrizedFunction< F >::gradient_t

Import gradient type.

template<typename F >

typedef F::jacobian_ref roboptim::DerivableParametrizedFunction< F >::jacobian_ref

template<typename F >

typedef F::jacobian_t roboptim::DerivableParametrizedFunction< F >::jacobian_t

Import jacobian type.

template<typename F >

typedef F::jacobianSize_t roboptim::DerivableParametrizedFunction< F >::jacobianSize_t

Import jacobian size type (pair of values).

template<typename F >

typedef F::matrix_t roboptim::DerivableParametrizedFunction< F >::matrix_t

Import matrix type.

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F roboptim::DerivableParametrizedFunction< F >::result_t

Import result type.

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F::size_type roboptim::DerivableParametrizedFunction< F >::size_type

Import size type.

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F::value_type roboptim::DerivableParametrizedFunction< F >::value_type

Import value type.

Reimplemented from roboptim::ParametrizedFunction< F >.

template<typename F >

typedef F::vector_t roboptim::DerivableParametrizedFunction< F >::vector_t

Import vector type.

Reimplemented from roboptim::ParametrizedFunction< F >.

---

Constructor & Destructor Documentation

template<typename F >

roboptim::DerivableParametrizedFunction< F >::DerivableParametrizedFunction	(	size_type	inputSize,
		size_type	functionInputSize,
		size_type	functionOutputSize
	)		[inline, protected]

Concrete class constructor should call this constructor.

Parameters:

inputSize	parameter size
functionInputSize	inner function argument size
functionOutputSize	inner function result size

---

Member Function Documentation

template<typename F >

gradient_t roboptim::DerivableParametrizedFunction< F >::gradient	(	const_argument_ref	argument,
		size_type	functionId = 0,
		size_type	order = 0
	)		const [inline]

Computes the gradient.

Parameters:

argument	inner function argument value
functionId	function id in split representation
order	derivation order

Returns:

gradient vector

References roboptim::DerivableParametrizedFunction< F >::gradientSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::impl_jacobian().

template<typename F >

void roboptim::DerivableParametrizedFunction< F >::gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId = 0,
		size_type	order = 0
	)		const [inline]

Computes the gradient.

Program will abort if the gradient size is wrong before or after the gradient computation.

Parameters:

gradient	gradient will be stored in this argument
argument	inner function point argument value
functionId	function id in split representation
order	derivation order

Returns:

gradient vector

References roboptim::DerivableParametrizedFunction< F >::impl_gradient(), roboptim::ParametrizedFunction< F >::inputSize(), and roboptim::DerivableParametrizedFunction< F >::isValidGradient().

template<typename F >

size_type roboptim::DerivableParametrizedFunction< F >::gradientSize

(

)

const [inline]

Return the gradient size.

Gradient size is equals to the input size.

References roboptim::ParametrizedFunction< F >::inputSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::gradient(), and roboptim::DerivableParametrizedFunction< F >::isValidGradient().

template<typename F >

virtual void roboptim::DerivableParametrizedFunction< F >::impl_gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId = 0,
		size_type	order = 0
	)		const [protected, pure 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	inner function point argument value
functionId	evaluated function id in the split representation
order	derivation order

Referenced by roboptim::DerivableParametrizedFunction< F >::gradient().

template<typename F >

virtual void roboptim::DerivableParametrizedFunction< F >::impl_jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	arg,
		size_type	order = 0
	)		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
order	derivation order

References roboptim::ParametrizedFunction< F >::functionOutputSize(), roboptim::DerivableParametrizedFunction< F >::gradient(), and roboptim::ParametrizedFunction< F >::inputSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::jacobian().

template<typename F >

bool roboptim::DerivableParametrizedFunction< F >::isValidGradient

(

const_gradient_ref

gradient

)

const [inline]

Check if the gradient is valid (check size).

Parameters:

gradient

checked gradient

Returns:

true if valid, false if not

References roboptim::DerivableParametrizedFunction< F >::gradientSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::gradient().

template<typename F >

bool roboptim::DerivableParametrizedFunction< F >::isValidJacobian

(

const_jacobian_ref

jacobian

)

const throw () [inline]

Check if the jacobian is valid (check sizes).

Parameters:

jacobian

checked jacobian

Returns:

true if valid, false if not

References roboptim::DerivableParametrizedFunction< F >::jacobian(), and roboptim::DerivableParametrizedFunction< F >::jacobianSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::jacobian().

template<typename F >

jacobian_t roboptim::DerivableParametrizedFunction< F >::jacobian	(	const_argument_ref	argument,
		size_type	order = 0
	)		const [inline]

Computes the jacobian.

Parameters:

argument	point at which the jacobian will be computed
order	derivation order

Returns:

jacobian matrix

References roboptim::DerivableParametrizedFunction< F >::jacobianSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::isValidJacobian().

template<typename F >

void roboptim::DerivableParametrizedFunction< F >::jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	argument,
		size_type	order = 0
	)		const [inline]

Computes the jacobian.

Program will abort if the jacobian size is wrong before or after the jacobian computation.

Parameters:

jacobian	jacobian will be stored in this argument
order	derivation order
argument	inner function point argument value

References roboptim::DerivableParametrizedFunction< F >::impl_jacobian(), roboptim::ParametrizedFunction< F >::inputSize(), and roboptim::DerivableParametrizedFunction< F >::isValidJacobian().

template<typename F >

jacobianSize_t roboptim::DerivableParametrizedFunction< F >::jacobianSize

(

)

const [inline]

Return the jacobian size as a pair.

Gradient size is equals to (output size, input size).

References roboptim::ParametrizedFunction< F >::functionOutputSize(), and roboptim::ParametrizedFunction< F >::inputSize().

Referenced by roboptim::DerivableParametrizedFunction< F >::isValidJacobian(), and roboptim::DerivableParametrizedFunction< F >::jacobian().

template<typename F >

virtual std::ostream& roboptim::DerivableParametrizedFunction< F >::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::ParametrizedFunction< F >.