Define an abstract derivable function ( \(C^1\)). More...

#include <roboptim/core/fwd.hh>

Inheritance diagram for roboptim::GenericDifferentiableFunction< T >:

Public Types
typedef std::pair< size_type, size_type >	jacobianSize_t
	Jacobian size type (pair of values). More...

Public Types inherited from roboptim::GenericFunction< T >
typedef T	traits_t
	Traits type. More...

typedef GenericFunctionTraits < T >::value_type	value_type
	Values type. More...

typedef GenericFunctionTraits < T >::size_type	size_type
	Size type. More...

typedef std::string	name_t
	Type of a function argument name. More...

typedef std::vector< name_t >	names_t
	Type of a vector of function argument names. More...

typedef std::pair< value_type, value_type >	interval_t
	Interval type (lower, upper). More...

typedef std::vector< interval_t >	intervals_t
	Vector of intervals. More...

typedef boost::tuple < value_type, value_type, value_type >	discreteInterval_t
	Types representing a discrete interval. More...

Public Member Functions
	ROBOPTIM_FUNCTION_FWD_TYPEDEFS_ (GenericFunction< T >)

	ROBOPTIM_ADD_FLAG (ROBOPTIM_IS_DIFFERENTIABLE)

	ROBOPTIM_GENERATE_TRAITS_REFS_ (gradient)
	Gradient type. More...

	ROBOPTIM_GENERATE_TRAITS_REFS_ (jacobian)
	Jacobian type. More...

size_type	gradientSize () const
	Return the gradient size. More...

jacobianSize_t	jacobianSize () const
	Return the jacobian size as a pair. More...

bool	isValidGradient (const_gradient_ref gradient) const
	Check if the gradient is valid (check size). More...

bool	isValidJacobian (const_jacobian_ref jacobian) const
	Check if the jacobian is valid (check sizes). More...

jacobian_t	jacobian (const_argument_ref argument) const
	Computes the jacobian. More...

void	jacobian (jacobian_ref jacobian, const_argument_ref argument) const
	Computes the jacobian. More...

gradient_t	gradient (const_argument_ref argument, size_type functionId=0) const
	Computes the gradient. More...

void	gradient (gradient_ref gradient, const_argument_ref argument, size_type functionId=0) const
	Computes the gradient. More...

virtual std::ostream &	print (std::ostream &o) const
	Display the function on the specified output stream. More...

Public Member Functions inherited from roboptim::GenericFunction< T >
	ROBOPTIM_DEFINE_FLAG_TYPE ()

	ROBOPTIM_GENERATE_TRAITS_REFS_ (vector)
	Basic (column) vector type. More...

	ROBOPTIM_GENERATE_TRAITS_REFS_ (rowVector)
	Row vector type. More...

	ROBOPTIM_GENERATE_TRAITS_REFS_ (matrix)
	Basic matrix type. More...

	ROBOPTIM_GENERATE_TRAITS_REFS_ (result)
	Type of a function evaluation result. More...

	ROBOPTIM_GENERATE_TRAITS_REFS_ (argument)
	Type of a function evaluation argument. More...

bool	isValidResult (const_result_ref result) const
	Check the given result size is valid. More...

GenericFunction< T >::size_type	inputSize () const
	Return the input size (i.e. More...

GenericFunction< T >::size_type	outputSize () const
	Return the output size (i.e. More...

virtual	~GenericFunction ()
	Trivial destructor. More...

result_t	operator() (const_argument_ref argument) const
	Evaluate the function at a specified point. More...

void	operator() (result_ref result, const_argument_ref argument) const
	Evaluate the function at a specified point. More...

const std::string &	getName () const
	Get function name. More...

virtual flag_t	getFlags () const
	Get the type-checking flag. More...

template<typename F >
void	foreach (const discreteInterval_t interval, F functor)

template<typename F >
void	foreach (const interval_t interval, const size_type n, F functor)

template<class ExpectedType >
ExpectedType *	castInto (bool check=false)
	Cast function to ExpectedType. More...

template<class ExpectedType >
const ExpectedType *	castInto (bool check=false) const
	Cast function to ExpectedType (const). More...

template<class ExpectedType >
bool	asType () const
	Fonction type checking. More...

Protected Member Functions
	GenericDifferentiableFunction (size_type inputSize, size_type outputSize=1, std::string name=std::string())
	Concrete class constructor should call this constructor. More...

virtual void	impl_jacobian (jacobian_ref jacobian, const_argument_ref arg) const
	Jacobian evaluation. More...

virtual void	impl_gradient (gradient_ref gradient, const_argument_ref argument, size_type functionId=0) const =0
	Gradient evaluation. More...

template<>
void	impl_jacobian (jacobian_ref jacobian, const_argument_ref argument) const

Protected Member Functions inherited from roboptim::GenericFunction< T >
	GenericFunction (size_type inputSize, size_type outputSize=1, std::string name=std::string())
	Concrete class constructor should call this constructor. More...

virtual void	impl_compute (result_ref result, const_argument_ref argument) const =0
	Function evaluation. More...

Additional Inherited Members
Static Public Member Functions inherited from roboptim::GenericFunction< T >
static value_type	epsilon ()
	Get the value of the machine epsilon, useful for floating types comparison. More...

static value_type	infinity ()
	Get the value that symbolizes positive infinity. More...

static interval_t	makeInterval (value_type l, value_type u)
	Construct an interval from a lower and upper bound. More...

static interval_t	makeInfiniteInterval ()
	Construct an infinite interval. More...

static interval_t	makeLowerInterval (value_type l)
	Construct an interval from a lower bound. More...

static interval_t	makeUpperInterval (value_type u)
	Construct an interval from an upper bound. More...

static value_type	getLowerBound (const interval_t &interval)
	Get the lower bound of an interval. More...

static value_type	getUpperBound (const interval_t &interval)
	Get the upper bound of an interval. More...

static discreteInterval_t	makeDiscreteInterval (value_type min, value_type max, value_type step)
	Construct a discrete interval. More...

static discreteInterval_t	makeDiscreteInterval (interval_t interval, value_type step)
	Construct a discrete interval. More...

static value_type	getLowerBound (const discreteInterval_t &interval)
	Get the lower bound of a discrete interval. More...

static value_type	getUpperBound (const discreteInterval_t &interval)
	Get the upper bound of a discrete interval. More...

static value_type	getStep (const discreteInterval_t &interval)
	Get the upper step of a discrete interval. More...

template<typename F >
static void	foreach (const discreteInterval_t interval, F functor)
	Iterate on an interval. More...

template<typename F >
static void	foreach (const interval_t interval, const size_type n, F functor)
	Iterate on an interval. More...

Static Public Attributes inherited from roboptim::GenericFunction< T >
static const flag_t	flags = ROBOPTIM_IS_FUNCTION
	Flag representing the Roboptim Function type. More...

Detailed Description

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

Define an abstract derivable function ( \(C^1\)).

A derivable function which provides a way to compute its gradient/jacobian.

\[ f : x \rightarrow f(x) \]

\(x \in \mathbb{R}^n\), \(f(x) \in \mathbb{R}^m\) where \(n\) is the input size and \(m\) is the output size.

Gradient computation is done through the impl_gradient method that has to implemented by the concrete class inheriting this class.

Jacobian computation is automatically done by concatenating gradients together, however this naive implementation can be overridden by the concrete class.

The gradient of a \(\mathbb{R}^n \rightarrow \mathbb{R}^m\) function where \(n > 1\) and \(m > 1\) is a matrix. As this representation is costly, RobOptim considers these functions as \(m\) \(\mathbb{R}^n \rightarrow \mathbb{R}\) functions. Through that mechanism, gradients are always vectors and jacobian are always matrices. When the gradient or the jacobian has to be computed, one has to precise which of the \(m\) functions should be considered.

If \(m = 1\), then the function id must always be 0 and can be safely ignored in the gradient/jacobian computation. The class provides a default value for the function id so that these functions do not have to explicitly set the function id.

Examples:: problem-cc.cc.

Member Typedef Documentation

template<typename T>

typedef std::pair<size_type, size_type> roboptim::GenericDifferentiableFunction< T >::jacobianSize_t

Jacobian size type (pair of values).

Constructor & Destructor Documentation

template<typename T >

roboptim::GenericDifferentiableFunction< T >::GenericDifferentiableFunction	(	size_type	inputSize,
		size_type	outputSize = `1`,
		std::string	name = `std::string ()`
	)

protected

Concrete class constructor should call this constructor.

Parameters

inputSize	input size (argument size)
outputSize	output size (result size)
name	function's name

Member Function Documentation

template<typename T>

gradient_t roboptim::GenericDifferentiableFunction< T >::gradient	(	const_argument_ref	argument,
		size_type	functionId = `0`
	)		const

inline

Computes the gradient.

Parameters

argument	point at which the gradient will be computed
functionId	function id in split representation

Returns: gradient vector

Referenced by roboptim::checkGradient(), and roboptim::checkGradientAndThrow().

template<typename T>

void roboptim::GenericDifferentiableFunction< T >::gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId = `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	point at which the gradient will be computed
functionId	function id in split representation

Returns: gradient vector

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

References roboptim::is_malloc_allowed(), and roboptim::set_is_malloc_allowed().

template<typename T>

size_type roboptim::GenericDifferentiableFunction< T >::gradientSize ( ) const

inline

Return the gradient size.

Gradient size is equals to the input size.

template<typename T>

virtual void roboptim::GenericDifferentiableFunction< T >::impl_gradient	(	gradient_ref	gradient,
		const_argument_ref	argument,
		size_type	functionId = `0`
	)		const

protectedpure virtual

Gradient evaluation.

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

Warning: Do not call this function directly, call gradient instead.

Parameters

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

Implemented in roboptim::GenericFiniteDifferenceGradient< T, FdgPolicy >, roboptim::NTimesDerivableFunction< 2 >, roboptim::GenericNumericQuadraticFunction< T >, roboptim::GenericNumericQuadraticFunction< T >, roboptim::GenericIdentityFunction< T >, roboptim::GenericNumericLinearFunction< T >, roboptim::GenericNumericLinearFunction< T >, roboptim::GenericConstantFunction< T >, roboptim::GenericIdentityFunction< T >, roboptim::Cos< T >, roboptim::Sin< T >, roboptim::GenericSumOfC1Squares< T >, roboptim::Cos< T >, roboptim::Polynomial< T >, and roboptim::Sin< T >.

template<>

void roboptim::GenericDifferentiableFunction< EigenMatrixSparse >::impl_jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	argument
	)		const

inlineprotected

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

References roboptim::is_malloc_allowed(), and roboptim::set_is_malloc_allowed().

template<typename T >

void roboptim::GenericDifferentiableFunction< T >::impl_jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	arg
	)		const

protectedvirtual

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 in roboptim::GenericFiniteDifferenceGradient< T, FdgPolicy >, roboptim::GenericNumericQuadraticFunction< T >, roboptim::Cos< T >, roboptim::GenericConstantFunction< T >, roboptim::Sin< T >, roboptim::GenericNumericLinearFunction< T >, roboptim::GenericNumericQuadraticFunction< T >, roboptim::GenericIdentityFunction< T >, roboptim::Polynomial< T >, roboptim::Cos< T >, and roboptim::Sin< T >.

template<typename T>

bool roboptim::GenericDifferentiableFunction< T >::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

template<typename T>

bool roboptim::GenericDifferentiableFunction< T >::isValidJacobian ( const_jacobian_ref jacobian ) const

inline

Check if the jacobian is valid (check sizes).

Parameters

jacobian checked jacobian

Returns: true if valid, false if not

template<typename T>

jacobian_t roboptim::GenericDifferentiableFunction< T >::jacobian ( const_argument_ref argument ) const

inline

Computes the jacobian.

Parameters

argument point at which the jacobian will be computed

Returns: jacobian matrix

Referenced by roboptim::checkJacobian(), roboptim::checkJacobianAndThrow(), roboptim::ScalingHelper< T >::computeScaling(), and roboptim::visualization::gnuplot::plot_jac().

template<typename T>

void roboptim::GenericDifferentiableFunction< T >::jacobian	(	jacobian_ref	jacobian,
		const_argument_ref	argument
	)		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
argument	point at which the jacobian will be computed

ROBOPTIM_DO_NOT_CHECK_ALLOCATION

References roboptim::is_malloc_allowed(), and roboptim::set_is_malloc_allowed().

template<typename T>

jacobianSize_t roboptim::GenericDifferentiableFunction< T >::jacobianSize ( ) const

inline

Return the jacobian size as a pair.

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

template<typename T >

std::ostream & roboptim::GenericDifferentiableFunction< 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::GenericFunction< T >.

Reimplemented in roboptim::GenericFiniteDifferenceGradient< T, FdgPolicy >, roboptim::NTimesDerivableFunction< 2 >, roboptim::GenericTwiceDifferentiableFunction< T >, roboptim::GenericNumericQuadraticFunction< T >, roboptim::GenericConstantFunction< T >, roboptim::GenericNumericLinearFunction< T >, roboptim::Polynomial< T >, roboptim::GenericIdentityFunction< T >, roboptim::GenericLinearFunction< T >, roboptim::GenericQuadraticFunction< T >, roboptim::Cos< T >, and roboptim::Sin< T >.

References roboptim::indent().

template<typename T>

roboptim::GenericDifferentiableFunction< T >::ROBOPTIM_ADD_FLAG ( ROBOPTIM_IS_DIFFERENTIABLE )

template<typename T>

roboptim::GenericDifferentiableFunction< T >::ROBOPTIM_FUNCTION_FWD_TYPEDEFS_ ( GenericFunction< T > )

template<typename T>

roboptim::GenericDifferentiableFunction< T >::ROBOPTIM_GENERATE_TRAITS_REFS_ ( gradient )

Gradient type.

template<typename T>

roboptim::GenericDifferentiableFunction< T >::ROBOPTIM_GENERATE_TRAITS_REFS_ ( jacobian )

Jacobian type.

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

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