defined(EIGEN_RUNTIME_NO_MALLOC) && !defined(ROBOPTIM_DO_NOT_CHECK_ALLOCATION) More...

Namespaces
namespace	callback
namespace	detail
namespace	fg
namespace	finiteDifferenceGradientPolicies
	Contains finite difference gradients policies.
namespace	visualization
	Graphical visualization.
Classes
class	LRUCache
	LRU (Least Recently Used) cache. More...
struct	Hasher
	Hash generator for argument vector. More...
class	CachedFunction
	Store previous function computation. More...
class	BadGradient
	Exception thrown when a gradient check fails. More...
class	BadJacobian
	Exception thrown when a Jacobian check fails. More...
class	GenericFiniteDifferenceGradient
	Compute automatically a gradient with finite differences. More...
class	DerivableParametrizedFunction
	Parametrized function with parameter derivative available. More...
struct	derivativeSize< GenericFunction< T > >
struct	derivativeSize< GenericDifferentiableFunction< T > >
struct	derivativeSize< GenericTwiceDifferentiableFunction< T > >
struct	derivativeSize< NTimesDerivableFunction< N > >
class	GenericDifferentiableFunction
	Define an abstract derivable function ( \(C^1\)). More...
class	GenericConstantFunction
	Constant function. More...
class	Cos
	Cos function. More...
class	GenericIdentityFunction
	Identity function. More...
class	Polynomial
	Polynomial function. More...
class	Sin
	Sin function. More...
class	FunctionPool
	A pool of functions that will be processed together. More...
struct	GenericFunctionTraits
	GenericFunction traits. More...
class	GenericFunction
	Define an abstract mathematical function ( \(C^0\)). More...
struct	GenericFunctionTraits< EigenMatrixDense >
	Trait specializing GenericFunction for Eigen dense matrices. More...
struct	GenericFunctionTraits< EigenMatrixSparse >
	Trait specializing GenericFunction for Eigen sparse matrices. More...
class	NoSolution
	Tag a result if no solution has been found. More...
struct	EigenMatrixDense
	Tag type for functions using Eigen dense matrices. More...
struct	EigenMatrixSparse
	Tag type for functions using Eigen sparse matrices. More...
class	GenericSolver
	Abstract interface satisfied by all solvers. More...
class	GenericLinearFunction
	Define an abstract linear function. More...
class	NTimesDerivableFunction< 2 >
	Explicit specialization for the stop case of NTimesDerivable class. More...
class	NTimesDerivableFunction
	Define a \(\mathbb{R} \rightarrow \mathbb{R}^m\) function, derivable n times ( \(n \geq 2\)). More...
class	GenericNumericLinearFunction
	Build a linear function from a vector and a matrix. More...
class	GenericNumericQuadraticFunction
	Build a quadratic function from a matrix and a vector. More...
class	Bind
	Bind some function input to a constant value. More...
class	Chain
	Chain two RobOptim functions. More...
class	Concatenate
	Concatenate the output of two functions. More...
class	Derivative
	Return the derivative of a function w.r.t. More...
class	Map
	Apply a function several times to an input vector. More...
class	Minus
	Subtract two RobOptim functions. More...
class	Plus
	Sum two RobOptim functions. More...
class	Product
	Product of two RobOptim functions. More...
class	Scalar
	Multiply by a constant scalar value. More...
class	SelectionById
	Select part of a function. More...
class	Selection
	Select a block of a function's output. More...
class	Split
	Select an element of a function's output. More...
class	OptimizationLogger
	Log the optimization process (values, Jacobians, time taken etc.). More...
class	ParametrizedFunction
	Define an abstract parametrized mathematical function ( \(C^0\)). More...
class	GenericDummySolverLastState
	Dummy solver which always fails, but returns the last state of the solver. More...
class	DummySolverTd
	Dummy solver which always fails. More...
class	DummySolver
	Dummy solver which always fails. More...
class	Problem
class	GenericQuadraticFunction
	Define an abstract quadratic function. More...
class	ResultWithWarnings
	Represents the solution of an optimization problem when errors occurred during the solving process. More...
class	Result
	Represents the solution of an optimization problem. More...
class	SolverCallback
	Solver per-iteration callback wrapper. More...
class	SolverError
	Base exception class for solving errors. More...
class	SolverFactory
	Define a solver factory that instanciate the plug-ins. More...
struct	StateParameter
	Solver state parameters type. More...
class	SolverState
	State of the solver. More...
class	SolverWarning
	Exception used for non-critical errors during optimization. More...
struct	Parameter
	Solver parameter type. More...
class	Solver
	Solver for a specific problem class. More...
class	GenericSumOfC1Squares
	Generic sum of the squares of differentiable functions. More...
class	GenericTwiceDifferentiableFunction
	Define an abstract function which is twice-derivable ( \(C^2\)). More...
Typedefs
typedef DifferentiableFunction	DerivableFunction
	Legacy name of TwiceDifferentiableFunction.
typedef DifferentiableSparseFunction	DerivableSparseFunction
	Legacy name of TwiceDifferentiableSparseFunction.
typedef GenericFunction < EigenMatrixDense >	Function
	Dense function.
typedef GenericFunction < EigenMatrixSparse >	SparseFunction
	Sparse function.
typedef GenericDifferentiableFunction < EigenMatrixDense >	DifferentiableFunction
	Dense differentiable function.
typedef GenericDifferentiableFunction < EigenMatrixSparse >	DifferentiableSparseFunction
	Sparse differentiable function.
typedef GenericNumericLinearFunction < EigenMatrixDense >	NumericLinearFunction
typedef GenericNumericLinearFunction < EigenMatrixSparse >	NumericLinearSparseFunction
typedef GenericNumericQuadraticFunction < EigenMatrixDense >	NumericQuadraticFunction
typedef GenericNumericQuadraticFunction < EigenMatrixSparse >	NumericQuadraticSparseFunction
typedef GenericConstantFunction < EigenMatrixDense >	ConstantFunction
typedef GenericIdentityFunction < EigenMatrixDense >	IdentityFunction
typedef GenericTwiceDifferentiableFunction < EigenMatrixDense >	TwiceDifferentiableFunction
typedef GenericTwiceDifferentiableFunction < EigenMatrixSparse >	TwiceDifferentiableSparseFunction
typedef GenericLinearFunction < EigenMatrixDense >	LinearFunction
typedef GenericLinearFunction < EigenMatrixSparse >	LinearSparseFunction
typedef GenericQuadraticFunction < EigenMatrixDense >	QuadraticFunction
typedef GenericQuadraticFunction < EigenMatrixSparse >	QuadraticSparseFunction
typedef GenericDummySolverLastState < EigenMatrixDense >	DummySolverLastState
typedef GenericDummySolverLastState < EigenMatrixSparse >	DummyDifferentiableSparseSolverLastState
typedef GenericSumOfC1Squares < EigenMatrixDense >	SumOfC1Squares
	Sum of the squares of dense differentiable functions.
typedef GenericSumOfC1Squares < EigenMatrixSparse >	SumOfC1SquaresSparse
	Sum of the squares of sparse differentiable functions.
typedef TwiceDifferentiableFunction	TwiceDerivableFunction
	Legacy name of DifferentiableFunction.
Enumerations
enum	FunctionFlag { ROBOPTIM_IS_FUNCTION = 1 << 0, ROBOPTIM_IS_DIFFERENTIABLE = 1 << 1, ROBOPTIM_IS_TWICE_DIFFERENTIABLE = 1 << 2, ROBOPTIM_IS_QUADRATIC = 1 << 3, ROBOPTIM_IS_NUMERIC_QUADRATIC = 1 << 4, ROBOPTIM_IS_LINEAR = 1 << 5, ROBOPTIM_IS_NUMERIC_LINEAR = 1 << 6, ROBOPTIM_IS_POLYNOMIAL = 1 << 7, ROBOPTIM_IS_CONSTANT = 1 << 8 }
	Bit flags describing the type of function. More...
Functions
ROBOPTIM_DLLAPI bool	is_malloc_allowed_update (bool update=false, bool new_value=false)
	Update the static variable used for Eigen::set_is_malloc_allowed.
bool	set_is_malloc_allowed (bool allow)
	Manage the calls to Eigen::set_is_malloc_allowed.
bool	is_malloc_allowed ()
	Whether dynamic allocation is allowed.
template<typename K , typename V , typename H >
std::ostream &	operator<< (std::ostream &o, const LRUCache< K, V, H > &cache)
template<typename T >
std::ostream &	operator<< (std::ostream &o, const BadGradient< T > &f)
	Override operator<< to handle exception display.
template<typename T >
std::ostream &	operator<< (std::ostream &o, const BadJacobian< T > &f)
	Override operator<< to handle exception display.
template<typename T >
bool	checkGradient (const GenericDifferentiableFunction< T > &function, typename GenericDifferentiableFunction< T >::size_type functionId, typename GenericDifferentiableFunction< T >::const_argument_ref x, typename GenericDifferentiableFunction< T >::value_type threshold=finiteDifferenceThreshold)
	Check if a gradient is valid.
template<typename T >
void	checkGradientAndThrow (const GenericDifferentiableFunction< T > &function, typename GenericDifferentiableFunction< T >::size_type functionId, typename GenericDifferentiableFunction< T >::const_argument_ref x, typename GenericDifferentiableFunction< T >::value_type threshold=finiteDifferenceThreshold) throw (BadGradient<T>)
template<typename T >
bool	checkJacobian (const GenericDifferentiableFunction< T > &function, typename GenericDifferentiableFunction< T >::const_argument_ref x, typename GenericDifferentiableFunction< T >::value_type threshold=finiteDifferenceThreshold)
	Check if a Jacobian is valid.
template<typename T >
void	checkJacobianAndThrow (const GenericDifferentiableFunction< T > &function, typename GenericDifferentiableFunction< T >::const_argument_ref x, typename GenericDifferentiableFunction< T >::value_type threshold=finiteDifferenceThreshold) throw (BadJacobian<T>)
template<typename T >
std::ostream &	operator<< (std::ostream &o, const GenericFunction< T > &f)
	Override operator<< to handle function display.
template<typename U , typename V >
boost::shared_ptr< V >	castInto (boost::shared_ptr< U > &u)
	Cast a shared_ptr of function to a different function type.
template<typename U , typename V >
const boost::shared_ptr< V >	castInto (const boost::shared_ptr< U > &u)
	Cast a shared_ptr of function to a different function type.
template<typename T >
std::string	typeString ()
	Return a string describing the type of T.
ROBOPTIM_DLLAPI std::ostream &	operator<< (std::ostream &o, const GenericSolver &gs)
	Override operator<< to handle solver display.
ROBOPTIM_DLLAPI std::ostream &	operator<< (std::ostream &o, const NoSolution &ns)
	Override operator<< to display ``no solution'' objects.
ROBOPTIM_DLLAPI long int &	indent (std::ostream &o)
	The current indentation level for o.
ROBOPTIM_DLLAPI std::ostream &	incindent (std::ostream &o)
	Increment the indentation.
ROBOPTIM_DLLAPI std::ostream &	decindent (std::ostream &o)
	Decrement the indentation.
ROBOPTIM_DLLAPI std::ostream &	resetindent (std::ostream &o)
	Reset the indentation.
ROBOPTIM_DLLAPI std::ostream &	iendl (std::ostream &o)
	Print an end of line, then set the indentation.
ROBOPTIM_DLLAPI std::ostream &	incendl (std::ostream &o)
	Increment the indentation, print an end of line, and set the indentation.
ROBOPTIM_DLLAPI std::ostream &	decendl (std::ostream &o)
	Decrement the indentation, print an end of line, and set the indentation.
template<typename U >
boost::shared_ptr< Bind< U > >	bind (boost::shared_ptr< U > origin, const typename Bind< U >::boundValues_t &boundValues)
template<typename U , typename V >
boost::shared_ptr< Chain< U, V > >	chain (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
	Chain two RobOptim functions.
template<typename U , typename V >
boost::shared_ptr< Concatenate < typename detail::PromoteTrait< U, V > ::T_promote > >	concatenate (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U >
boost::shared_ptr< Derivative < U > >	derivative (boost::shared_ptr< U > origin, typename Derivative< U >::size_type variableId=0)
template<typename U >
boost::shared_ptr< Map< U > >	map (boost::shared_ptr< U > origin, typename U::size_type repeat)
template<typename U , typename V >
boost::shared_ptr< Minus< U, V > >	minus (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U , typename V >
boost::shared_ptr< Minus< U, V > >	operator- (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U , typename V >
boost::shared_ptr< Plus< U, V > >	plus (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U , typename V >
boost::shared_ptr< Plus< U, V > >	operator+ (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U , typename V >
boost::shared_ptr< Product< U, V > >	product (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U , typename V >
boost::shared_ptr< Product< U, V > >	operator* (boost::shared_ptr< U > left, boost::shared_ptr< V > right)
template<typename U >
boost::shared_ptr< Scalar< U > >	scalar (boost::shared_ptr< U > origin, typename Scalar< U >::size_type start=0, typename Scalar< U >::size_type size=1)
template<typename U >
boost::shared_ptr< Scalar< U > >	operator* (typename Scalar< U >::value_type scalar, boost::shared_ptr< U > origin)
template<typename U >
boost::shared_ptr< Scalar< U > >	operator* (boost::shared_ptr< U > origin, typename Scalar< U >::value_type scalar)
template<typename U >
boost::shared_ptr< U >	operator+ (boost::shared_ptr< U > origin)
template<typename U >
boost::shared_ptr< Scalar< U > >	operator- (boost::shared_ptr< U > origin)
template<typename U >
boost::shared_ptr < SelectionById< U > >	selectionById (boost::shared_ptr< U > origin, std::vector< bool > selector)
template<typename U >
boost::shared_ptr< Selection< U > >	selection (boost::shared_ptr< U > origin, typename Selection< U >::size_type start=0, typename Selection< U >::size_type size=1)
template<typename P , typename C >
void	addNonScalarConstraint (P &problem, boost::shared_ptr< C > constraint, std::vector< Function::interval_t > interval, std::vector< Function::value_type > scale=std::vector< Function::value_type >())
template<typename F >
std::ostream &	operator<< (std::ostream &o, const ParametrizedFunction< F > &f)
	Override operator<< to handle function display.
template<typename T >
std::ostream &	operator<< (std::ostream &o, const Problem< T > &pb)
	Override operator<< to handle problem display.
ROBOPTIM_DLLAPI std::ostream &	operator<< (std::ostream &o, const Result &r)
	Override operator<< to handle result display.
template<typename S >
std::ostream &	operator<< (std::ostream &o, const SolverCallback< S > &c)
ROBOPTIM_DLLAPI std::ostream &	operator<< (std::ostream &o, const SolverError &e)
	Override operator<< to handle error display.
template<typename S >
S *	unionCast (void *ptr)
template<typename F >
std::ostream &	operator<< (std::ostream &o, const StateParameter< F > &parameter)
	Override operator<< to display ``parameters'' objects.
template<typename P >
std::ostream &	operator<< (std::ostream &o, const SolverState< P > &state)
	Override operator<< to display ``parameters'' objects.
ROBOPTIM_DLLAPI std::ostream &	operator<< (std::ostream &o, const Parameter &parameter)
	Override operator<< to display ``parameters'' objects.
template<typename T >
std::ostream &	operator<< (std::ostream &, const std::vector< T > &)
	Display a vector.
template<typename T1 , typename T2 >
std::ostream &	operator<< (std::ostream &, const std::pair< T1, T2 > &)
	Display a pair.
template<typename T1 , typename T2 >
std::ostream &	operator<< (std::ostream &, const std::map< T1, T2 > &)
	Display a map.
template<typename T >
std::ostream &	operator<< (std::ostream &, const Eigen::MatrixBase< T > &)
	Display an Eigen object with the appropriate IOFormat.
ROBOPTIM_DLLAPI const std::string	demangle (const char *name)
	Demangle (if available).
ROBOPTIM_DLLAPI GenericFunctionTraits < EigenMatrixDense >::matrix_t	sparse_to_dense (GenericFunctionTraits< EigenMatrixSparse >::const_matrix_ref m)
	Convert a sparse matrix into a dense matrix.
ROBOPTIM_DLLAPI GenericFunctionTraits < EigenMatrixDense >::vector_t	sparse_to_dense (GenericFunctionTraits< EigenMatrixSparse >::const_gradient_ref v)
	Convert a sparse vector into a dense vector.
ROBOPTIM_DLLAPI GenericFunctionTraits < EigenMatrixDense > ::gradient_t	toDense (GenericFunctionTraits< EigenMatrixSparse >::const_gradient_ref g)
	Convert an input gradient to a dense gradient (e.g.
ROBOPTIM_DLLAPI GenericFunctionTraits < EigenMatrixDense >::matrix_t	toDense (GenericFunctionTraits< EigenMatrixSparse >::const_matrix_ref m)
	Convert an input matrix to a dense matrix (e.g.
ROBOPTIM_DLLAPI GenericFunctionTraits < EigenMatrixDense > ::const_matrix_ref	toDense (GenericFunctionTraits< EigenMatrixDense >::const_matrix_ref m)
	Convert an input matrix to a dense matrix (e.g.
ROBOPTIM_DLLAPI bool	allclose (const Eigen::SparseMatrix< double > &a, const Eigen::SparseMatrix< double > &b, double rtol=Eigen::NumTraits< double >::dummy_precision(), double atol=Eigen::NumTraits< double >::epsilon())
	Compare sparse vectors (matrices) using both relative and absolute tolerances.
ROBOPTIM_DLLAPI bool	allclose (const Eigen::Ref< const Eigen::MatrixXd > &a, const Eigen::Ref< const Eigen::MatrixXd > &b, double rtol=Eigen::NumTraits< double >::dummy_precision(), double atol=Eigen::NumTraits< double >::epsilon())
	Compare dense vectors (matrices) using both relative and absolute tolerances.
template<typename U >
void	copySparseBlock (U &m, const U &b, Function::size_type startRow, Function::size_type startCol, bool compress=false)
	Copy a sparse block into a sparse matrix.
template<typename M , typename B >
void	updateSparseBlock (M &m, const B &b, Function::size_type startRow, Function::size_type startCol)
	Update a sparse block of a sparse matrix.
double	normalize (double x, double eps=1e-8)
	Apply normalize to a scalar.
template<typename T >
T	normalize (const T &x, double eps=1e-8)
	Apply normalize to each element of an Eigen vector.
GenericFunctionTraits < EigenMatrixDense > ::const_gradient_ref	toDense (GenericFunctionTraits< EigenMatrixDense >::const_gradient_ref m)
Variables
static const double	finiteDifferenceThreshold = 1e-4
	Default threshold for checkGradient.
static const double	finiteDifferenceEpsilon = 1e-8
	Default epsilon for finite difference class.
static const int	StorageOrder = Eigen::ROBOPTIM_STORAGE_ORDER
	Default matrix storage order.
ROBOPTIM_ALLOW_ATTRIBUTES_ON template class ROBOPTIM_DLLAPI	GenericFunction< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	GenericFunction< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	GenericNumericQuadraticFunction< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	GenericNumericQuadraticFunction< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	GenericNumericLinearFunction< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	GenericNumericLinearFunction< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	GenericSumOfC1Squares< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	GenericSumOfC1Squares< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	Problem< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	Problem< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	Solver< EigenMatrixDense >
template class ROBOPTIM_DLLAPI	Solver< EigenMatrixSparse >
template class ROBOPTIM_DLLAPI	SolverFactory< Solver< EigenMatrixDense > >
template class ROBOPTIM_DLLAPI	SolverFactory< Solver< EigenMatrixSparse > >
template class ROBOPTIM_DLLAPI	SolverState< Problem< EigenMatrixDense > >
template class ROBOPTIM_DLLAPI	SolverState< Problem< EigenMatrixSparse > >
template class ROBOPTIM_DLLAPI	SolverCallback< Solver< EigenMatrixDense > >
template class ROBOPTIM_DLLAPI	SolverCallback< Solver< EigenMatrixSparse > >
template class ROBOPTIM_DLLAPI	OptimizationLogger< Solver< EigenMatrixDense > >
template class ROBOPTIM_DLLAPI	OptimizationLogger< Solver< EigenMatrixSparse > >

Detailed Description

defined(EIGEN_RUNTIME_NO_MALLOC) && !defined(ROBOPTIM_DO_NOT_CHECK_ALLOCATION)

Meta-functions, functions and solver-related classes.

ROBOPTIM_CHECK_ALLOCATION

Typedef Documentation

typedef GenericConstantFunction<EigenMatrixDense> roboptim::ConstantFunction

typedef DifferentiableFunction roboptim::DerivableFunction

Legacy name of TwiceDifferentiableFunction.

typedef DifferentiableSparseFunction roboptim::DerivableSparseFunction

Legacy name of TwiceDifferentiableSparseFunction.

typedef GenericDifferentiableFunction<EigenMatrixDense> roboptim::DifferentiableFunction

Dense differentiable function.

typedef GenericDifferentiableFunction<EigenMatrixSparse> roboptim::DifferentiableSparseFunction

Sparse differentiable function.

typedef GenericDummySolverLastState<EigenMatrixSparse> roboptim::DummyDifferentiableSparseSolverLastState

typedef GenericDummySolverLastState<EigenMatrixDense> roboptim::DummySolverLastState

typedef GenericFunction<EigenMatrixDense> roboptim::Function

Dense function.

Examples:: result.cc, visualization-gnuplot-function.cc, and visualization-matplotlib-function.cc.

typedef GenericIdentityFunction<EigenMatrixDense> roboptim::IdentityFunction

typedef GenericLinearFunction<EigenMatrixDense> roboptim::LinearFunction

typedef GenericLinearFunction<EigenMatrixSparse> roboptim::LinearSparseFunction

typedef GenericNumericLinearFunction<EigenMatrixDense> roboptim::NumericLinearFunction

typedef GenericNumericLinearFunction<EigenMatrixSparse> roboptim::NumericLinearSparseFunction

typedef GenericNumericQuadraticFunction<EigenMatrixDense> roboptim::NumericQuadraticFunction

typedef GenericNumericQuadraticFunction<EigenMatrixSparse> roboptim::NumericQuadraticSparseFunction

typedef GenericQuadraticFunction<EigenMatrixDense> roboptim::QuadraticFunction

typedef GenericQuadraticFunction<EigenMatrixSparse> roboptim::QuadraticSparseFunction

typedef GenericFunction<EigenMatrixSparse> roboptim::SparseFunction

Sparse function.

typedef TwiceDifferentiableFunction roboptim::TwiceDerivableFunction

Legacy name of DifferentiableFunction.

typedef GenericTwiceDifferentiableFunction<EigenMatrixDense> roboptim::TwiceDifferentiableFunction

typedef GenericTwiceDifferentiableFunction<EigenMatrixSparse> roboptim::TwiceDifferentiableSparseFunction

Function Documentation

bool roboptim::allclose	(	const Eigen::SparseMatrix< double > &	a,
		const Eigen::SparseMatrix< double > &	b,
		double	rtol = `Eigen::NumTraits<double>::dummy_precision ()`,
		double	atol = `Eigen::NumTraits<double>::epsilon ()`
	)

Compare sparse vectors (matrices) using both relative and absolute tolerances.

See also:: http://stackoverflow.com/a/15052131/1043187

Examples:: numeric-linear-function.cc, and numeric-quadratic-function.cc.

Referenced by checkGradient(), and checkJacobian().

bool roboptim::allclose	(	const Eigen::Ref< const Eigen::MatrixXd > &	a,
		const Eigen::Ref< const Eigen::MatrixXd > &	b,
		double	rtol = `Eigen::NumTraits<double>::dummy_precision ()`,
		double	atol = `Eigen::NumTraits<double>::epsilon ()`
	)

Compare dense vectors (matrices) using both relative and absolute tolerances.

See also:: http://stackoverflow.com/a/15052131/1043187

template<typename U , typename V >

boost::shared_ptr< V > roboptim::castInto ( boost::shared_ptr & u )

Cast a shared_ptr of function to a different function type.

This throws if the cast is not possible.

Template Parameters:

U	type of the origin function.
V	new function type.

Parameters:

u	input shared_ptr to a function.

Returns:: shared_ptr cast to the appropriate type.

template<typename U , typename V >

const boost::shared_ptr< V > roboptim::castInto ( const boost::shared_ptr & u )

Cast a shared_ptr of function to a different function type.

This throws if the cast is not possible. Const version.

Template Parameters:

U	type of the origin function.
V	new function type.

Parameters:

u	input shared_ptr to a function.

Returns:: shared_ptr cast to the appropriate type.

template<typename U >

void roboptim::copySparseBlock	(	U &	m,
		const U &	b,
		Function::size_type	startRow,
		Function::size_type	startCol,
		bool	compress = `false`
	)

Copy a sparse block into a sparse matrix.

This function involves filling a vector of triplets, so this should be avoided in critical sections.

Parameters:

m	matrix to fill.
b	block to copy to m.
startRow	start row of the block in m where b will be copied.
startCol	start col of the block in m where b will be copied.
compress	whether to compress the sparse matrix at the end.

std::ostream & roboptim::decendl ( std::ostream & o )

Decrement the indentation, print an end of line, and set the indentation.

References decindent(), and iendl().

std::ostream & roboptim::decindent ( std::ostream & o )

Decrement the indentation.

References indent().

const std::string roboptim::demangle ( const char * name )

Demangle (if available).

Referenced by roboptim::SolverFactory< S >::SolverFactory(), and typeString().

std::ostream & roboptim::iendl ( std::ostream & o )

Print an end of line, then set the indentation.

References indent().

std::ostream & roboptim::incendl ( std::ostream & o )

Increment the indentation, print an end of line, and set the indentation.

References iendl(), and incindent().

Referenced by roboptim::Problem< T >::print().

std::ostream & roboptim::incindent ( std::ostream & o )

Increment the indentation.

References indent().

long int & roboptim::indent ( std::ostream & o )

The current indentation level for o.

Referenced by decindent(), iendl(), incindent(), roboptim::GenericTwiceDifferentiableFunction< T >::print(), roboptim::GenericDifferentiableFunction< T >::print(), roboptim::GenericFunction< T >::print(), and resetindent().

bool roboptim::is_malloc_allowed ( ) [inline]

Whether dynamic allocation is allowed.

References is_malloc_allowed_update().

Referenced by roboptim::CachedFunction< T >::cachedFunctionGradient(), roboptim::CachedFunction< T >::cachedFunctionHessian(), roboptim::CachedFunction< T >::cachedFunctionJacobian(), roboptim::finiteDifferenceGradientPolicies::Policy< T >::computeJacobian(), roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeJacobian(), roboptim::GenericDifferentiableFunction< T >::gradient(), roboptim::GenericTwiceDifferentiableFunction< T >::hessian(), roboptim::CachedFunction< T >::impl_compute(), roboptim::NTimesDerivableFunction< 2 >::impl_gradient(), roboptim::NTimesDerivableFunction< 2 >::impl_hessian(), roboptim::GenericDifferentiableFunction< T >::impl_jacobian(), roboptim::GenericNumericQuadraticFunction< T >::impl_jacobian(), roboptim::GenericDifferentiableFunction< T >::jacobian(), roboptim::detail::ProductDifferentiation::jacobian(), and roboptim::GenericFunction< T >::operator()().

bool roboptim::is_malloc_allowed_update	(	bool	update = `false`,
		bool	new_value = `false`
	)

Update the static variable used for Eigen::set_is_malloc_allowed.

Referenced by is_malloc_allowed(), and set_is_malloc_allowed().

double roboptim::normalize	(	double	x,
		double	eps = `1e-8`
	)		`[inline]`

Apply normalize to a scalar.

Referenced by roboptim::visualization::gnuplot::detail::dense_matrix_to_gnuplot(), roboptim::visualization::matplotlib::detail::dense_matrix_to_matplotlib(), roboptim::visualization::gnuplot::plot(), roboptim::visualization::gnuplot::plot_xy(), and roboptim::visualization::matplotlib::detail::sparse_matrix_to_matplotlib().

template<typename T >

T roboptim::normalize	(	const T &	x,
		double	eps = `1e-8`
	)		`[inline]`

Apply normalize to each element of an Eigen vector.

template<typename T >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const std::vector< T > &	vect
	)

Display a vector.

template<typename T1 , typename T2 >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const std::pair< T1, T2 > &	p
	)

Display a pair.

template<typename T1 , typename T2 >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const std::map< T1, T2 > &	m
	)

Display a map.

template<typename T >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const Eigen::MatrixBase< T > &	matrix
	)

Display an Eigen object with the appropriate IOFormat.

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const SolverError &	e
	)

Override operator<< to handle error display.

Parameters:

o	output stream used for display
e	error to be displayed

Returns:: output stream

References roboptim::SolverError::print().

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const Result &	r
	)

Override operator<< to handle result display.

Parameters:

o	output stream used for display
r	result to be displayed

Returns:: output stream

References roboptim::Result::print().

template<typename S >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const SolverCallback< S > &	c
	)

template<typename F >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const ParametrizedFunction< F > &	f
	)

Override operator<< to handle function display.

Parameters:

o	output stream used for display
f	function to be displayed

Returns:: output stream

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const GenericSolver &	gs
	)

Override operator<< to handle solver display.

Parameters:

o	output stream used for display
gs	solver to be displayed

Returns:: output stream

References roboptim::GenericSolver::print().

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const NoSolution &	ns
	)

Override operator<< to display ``no solution'' objects.

Parameters:

o	output stream used for display
ns	NoSolution object, ignored

Returns:: output stream

template<typename K , typename V , typename H >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const LRUCache< K, V, H > &	cache
	)

template<typename T >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const Problem< T > &	pb
	)

Override operator<< to handle problem display.

Parameters:

o	output stream used for display
pb	problem to be displayed

Returns:: output stream

template<typename T >

std::ostream & roboptim::operator<<	(	std::ostream &	o,
		const GenericFunction< T > &	f
	)

Override operator<< to handle function display.

Parameters:

o	output stream used for display
f	function to be displayed

Returns:: output stream

std::ostream & roboptim::resetindent ( std::ostream & o )

Reset the indentation.

References indent().

bool roboptim::set_is_malloc_allowed ( bool allow ) [inline]

Manage the calls to Eigen::set_is_malloc_allowed.

Parameters:

allow whether to allow dynamic allocations.

ROBOPTIM_CHECK_ALLOCATION

References is_malloc_allowed_update().

Referenced by roboptim::CachedFunction< T >::cachedFunctionGradient(), roboptim::CachedFunction< T >::cachedFunctionHessian(), roboptim::CachedFunction< T >::cachedFunctionJacobian(), roboptim::finiteDifferenceGradientPolicies::Policy< T >::computeJacobian(), roboptim::finiteDifferenceGradientPolicies::FivePointsRule< T >::computeJacobian(), roboptim::GenericDifferentiableFunction< T >::gradient(), roboptim::GenericTwiceDifferentiableFunction< T >::hessian(), roboptim::CachedFunction< T >::impl_compute(), roboptim::NTimesDerivableFunction< 2 >::impl_gradient(), roboptim::NTimesDerivableFunction< 2 >::impl_hessian(), roboptim::GenericDifferentiableFunction< T >::impl_jacobian(), roboptim::GenericNumericQuadraticFunction< T >::impl_jacobian(), roboptim::GenericDifferentiableFunction< T >::jacobian(), roboptim::detail::ProductDifferentiation::jacobian(), and roboptim::GenericFunction< T >::operator()().

GenericFunctionTraits< EigenMatrixDense >::matrix_t roboptim::sparse_to_dense ( GenericFunctionTraits< EigenMatrixSparse >::const_matrix_ref m )

Convert a sparse matrix into a dense matrix.

GenericFunctionTraits< EigenMatrixDense >::vector_t roboptim::sparse_to_dense ( GenericFunctionTraits< EigenMatrixSparse >::const_gradient_ref v )

Convert a sparse vector into a dense vector.

GenericFunctionTraits< EigenMatrixDense >::gradient_t roboptim::toDense ( GenericFunctionTraits< EigenMatrixSparse >::const_gradient_ref g )

Convert an input gradient to a dense gradient (e.g.

for printing).

Parameters:

g	input gradient.

Examples:: numeric-linear-function.cc, and numeric-quadratic-function.cc.

Referenced by roboptim::GenericNumericLinearFunction< T >::print(), and roboptim::GenericNumericQuadraticFunction< T >::print().

GenericFunctionTraits< EigenMatrixDense >::matrix_t roboptim::toDense ( GenericFunctionTraits< EigenMatrixSparse >::const_matrix_ref m )

Convert an input matrix to a dense matrix (e.g.

for printing).

Parameters:

m	input matrix.

GenericFunctionTraits< EigenMatrixDense >::const_matrix_ref roboptim::toDense ( GenericFunctionTraits< EigenMatrixDense >::const_matrix_ref m )

Convert an input matrix to a dense matrix (e.g.

for printing).

Parameters:

m	input matrix. Note: since the input is a dense matrix, we just return it.

GenericFunctionTraits<EigenMatrixDense>::const_gradient_ref roboptim::toDense ( GenericFunctionTraits< EigenMatrixDense >::const_gradient_ref m )

template<typename T >

std::string roboptim::typeString ( )

Return a string describing the type of T.

References demangle().

template<typename S >

S* roboptim::unionCast ( void * ptr )

template<typename M , typename B >

void roboptim::updateSparseBlock	(	M &	m,
		const B &	b,
		Function::size_type	startRow,
		Function::size_type	startCol
	)

Update a sparse block of a sparse matrix.

This function expects the sparse matrix to have its structure set already, thus it can easily iterate over the values and copy them without any extra allocation. If that's not the case, the behavior is undefined.

Parameters:

m	sparse matrix to update.
b	sparse block to copy to m.
startRow	start row of the block in m where b will be copied.
startCol	start col of the block in m where b will be copied.

Template Parameters: