Namespaces
namespace	autodiff
	Automatic differentiation utilities.

namespace	context

namespace	helpers
	Helper functions and structs.

namespace	linalg
	Specific linear algebra routines.

namespace	math
	Math utilities.

namespace	python
	Python bindings.

Classes
struct	ALMeritFunctionTpl
	Primal-dual augmented Lagrangian-type merit function. More...

class	ArmijoLinesearch
	Basic backtracking Armijo line-search strategy. More...

struct	BaseFunctionTpl
	Base function type. More...

struct	BaseLogger
	A logging utility. More...

struct	BCLParamsTpl

struct	BoxConstraintTpl
	Box constraint set \(z \in [z_\min, z_\max]\). More...

struct	C1FunctionTpl
	Differentiable function, with method for the Jacobian. More...

struct	C2FunctionTpl
	Twice-differentiable function, with method Jacobian and vector-hessian product evaluation. More...

struct	CartesianProductTpl
	The cartesian product of two or more manifolds. More...

struct	ComposeFunctionTpl
	Composition of two functions \(f \circ g\). More...

struct	ComputeSignatureVisitor

struct	ConstraintObjectTpl
	Packs a ConstraintSetTpl and C2FunctionTpl together. More...

struct	ConstraintSetProductTpl
	Cartesian product of multiple constraint sets. This class makes computing multipliers and Jacobian matrix projections more convenient. More...

struct	ConstraintSetTpl
	Base constraint set type. More...

struct	CostFunctionBaseTpl
	Base class for differentiable cost functions. More...

struct	CostSumTpl
	Defines the sum of one or more cost functions \(c_1 + c_2 + \cdots\). More...

struct	EqualityConstraintTpl
	Equality constraints \(c(x) = 0\). More...

struct	func_to_cost

struct	LinearFunctionDifferenceToPoint
	Linear function of difference vector on a manifold, of the form \( r(x) = A(x \ominus \bar{x}) + b \). More...

struct	LinearFunctionTpl
	Linear residuals \(r(x) = Ax + b\). More...

class	Linesearch
	Base linesearch class. Design pattern inspired by Google Ceres-Solver. More...

struct	LogRecord

struct	ManifoldAbstractTpl

struct	ManifoldDifferenceToPoint

struct	math_types
	Typedefs for math (Eigen vectors, matrices) depending on scalar type. More...

struct	MultibodyConfiguration
	Multibody configuration group \(\mathcal{Q}\), defined using the Pinocchio library. More...

struct	MultibodyPhaseSpace
	The tangent bundle of a multibody configuration group. More...

struct	NegativeOrthantTpl
	Negative orthant, for constraints \(h(x)\leq 0\). More...

struct	NonsmoothPenaltyL1Tpl
	Composite \(\ell_1\)-penalty function \( \\|c(x)\\|_1 \). More...

struct	PinocchioLieGroup
	Wrap a Pinocchio Lie group into a ManifoldAbstractTpl object. More...

struct	PolynomialTpl
	Polynomials represented by their coefficients in decreasing order of degree. More...

struct	ProblemTpl

class	ProxNLPSolverTpl

struct	QuadraticDistanceCostTpl
	Weighted quadratic distance \(\frac{1}{2}\\|x\ominus \bar{x}\\|^2_W\) on a space. More...

struct	QuadraticResidualCostTpl
	Quadratic function \(\frac{1}{2} r^\top Qr + b^\top r + c\) of a residual. More...

struct	ResultsTpl
	Results struct, holding the returned data from the solver. More...

struct	RigidTransformationPointActionTpl

class	RuntimeError

struct	TangentBundleTpl
	Tangent bundle of a base manifold M. More...

struct	VectorSpaceTpl
	Standard Euclidean vector space. More...

struct	WorkspaceTpl

Typedefs
template<typename Scalar , class MatrixType = typename math_types<Scalar>::MatrixXs>
using	LDLTVariant

template<typename T , typename T2 = void>
using	enable_if_eigen_dense = std::enable_if_t<is_eigen_dense_type<T>, T2>

template<int D, typename Scalar >
using	SETpl

template<int D, typename Scalar >
using	SOTpl

Enumerations
enum	VerboseLevel { QUIET = 0 , VERBOSE = 1 , VERYVERBOSE = 2 }
	Verbosity level. More...

enum class	LDLTChoice { DENSE , BUNCHKAUFMAN , BLOCKSPARSE , EIGEN , PROXSUITE }

enum class	LinesearchStrategy { ARMIJO , WOLFE }

enum class	LSInterpolation { BISECTION , QUADRATIC , CUBIC }

enum class	MultiplierUpdateMode { NEWTON , PRIMAL , PRIMAL_DUAL }

enum class	HessianApprox { EXACT , GAUSS_NEWTON }

enum	InertiaFlag { INERTIA_OK = 0 , INERTIA_BAD = 1 , INERTIA_HAS_ZEROS = 2 }

enum	KktSystem { KKT_CLASSIC , KKT_PRIMAL_DUAL }

enum	ConvergenceFlag { UNINIT = -1 , SUCCESS = 0 , MAX_ITERS_REACHED = 1 }

Functions
template<typename Scalar >
auto	downcast_function_to_cost (const shared_ptr< C2FunctionTpl< Scalar > > &func) -> shared_ptr< CostFunctionBaseTpl< Scalar > >

template<typename Scalar >
auto	compose (const shared_ptr< C2FunctionTpl< Scalar > > &left, const shared_ptr< C2FunctionTpl< Scalar > > &right)
	Compose two function objects.

linalg::SymbolicBlockMatrix	create_default_block_structure (const std::vector< isize > &dims_primal, const std::vector< isize > &dims_dual)

isize	get_total_dim_helper (const std::vector< isize > &nprims, const std::vector< isize > &nduals)

template<typename Scalar >
LDLTVariant< Scalar >	allocate_ldlt_from_sizes (const std::vector< isize > &nprims, const std::vector< isize > &nduals, LDLTChoice choice)

std::array< int, 3 >	computeInertiaTuple (const Eigen::Ref< Eigen::VectorXi const > &signature)

template<typename Derived >
auto	blockMatrixGetRow (const Eigen::MatrixBase< Derived > &matrix, const std::vector< Eigen::Index > &rowBlockSizes, std::size_t rowIdx)

template<typename Derived >
auto	blockVectorGetRow (const Eigen::MatrixBase< Derived > &matrix, const std::vector< Eigen::Index > &blockSizes, std::size_t blockIdx)

template<typename T >
auto	operator* (const polymorphic< ManifoldAbstractTpl< T > > &left, const polymorphic< ManifoldAbstractTpl< T > > &right)

template<typename T >
auto	operator* (const CartesianProductTpl< T > &left, const polymorphic< ManifoldAbstractTpl< T > > &right)

template<typename T >
auto	operator* (const polymorphic< ManifoldAbstractTpl< T > > &left, const CartesianProductTpl< T > &right)

template<typename T >
auto	operator* (const CartesianProductTpl< T > &left, const CartesianProductTpl< T > &right)

InertiaFlag	checkInertia (const int ndx, const int nc, const Eigen::VectorXi &signature)
	Check the matrix has the desired inertia.

auto	format_as (ConvergenceFlag fl)

std::string	printVersion (const std::string &delimiter=".")
	Pretty-print the package version number.

template<typename Scalar >
auto	allocate_ldlt_from_problem (const ProblemTpl< Scalar > &prob, LDLTChoice choice)

Variables
constexpr int	NUM_KEYS = 10

const std::array< std::string, NUM_KEYS >	BASIC_KEYS

constexpr char	int_format [] = "{: >{}d}"

constexpr char	sci_format [] = "{: > {}.{}e}"

constexpr char	dbl_format [] = "{: > {}.{}g}"

template<typename T >
constexpr bool	is_eigen_dense_type

template<typename T >
constexpr bool	is_eigen_matrix_type

Typedef Documentation

◆ LDLTVariant

template<typename Scalar , class MatrixType = typename math_types<Scalar>::MatrixXs>

using proxsuite::nlp::LDLTVariant

Initial value:

 
    boost::variant<linalg::DenseLDLT<Scalar>, linalg::BlockLDLT<Scalar>,
                   Eigen::LDLT<MatrixType>, Eigen::BunchKaufman<MatrixType>
 
                   >

Definition at line 37 of file ldlt-allocator.hpp.

◆ enable_if_eigen_dense

template<typename T , typename T2 = void>

using proxsuite::nlp::enable_if_eigen_dense = std::enable_if_t<is_eigen_dense_type<T>, T2>

Definition at line 21 of file math.hpp.

◆ SETpl

template<int D, typename Scalar >

using proxsuite::nlp::SETpl

Initial value:

PinocchioLieGroup<pinocchio::SpecialEuclideanOperationTpl<D, Scalar>>

Definition at line 104 of file pinocchio-groups.hpp.

◆ SOTpl

template<int D, typename Scalar >

using proxsuite::nlp::SOTpl

Initial value:

PinocchioLieGroup<pinocchio::SpecialOrthogonalOperationTpl<D, Scalar>>

Definition at line 108 of file pinocchio-groups.hpp.

Enumeration Type Documentation

◆ VerboseLevel

enum proxsuite::nlp::VerboseLevel

Verbosity level.

Enumerator
QUIET
VERBOSE
VERYVERBOSE

Definition at line 126 of file fwd.hpp.

◆ LDLTChoice

enum class proxsuite::nlp::LDLTChoice

strong

Enumerator
DENSE	Use our dense LDLT.
BUNCHKAUFMAN	Use Bunch-Kaufman factorization.
BLOCKSPARSE	Use blocked LDLT.
EIGEN	Use Eigen's implementation.
PROXSUITE	Use Proxsuite's LDLT.

Definition at line 22 of file ldlt-allocator.hpp.

◆ LinesearchStrategy

enum class proxsuite::nlp::LinesearchStrategy

strong

Enumerator
ARMIJO
WOLFE

Definition at line 11 of file linesearch-base.hpp.

◆ LSInterpolation

enum class proxsuite::nlp::LSInterpolation

strong

Enumerator
BISECTION
QUADRATIC
CUBIC

Definition at line 12 of file linesearch-base.hpp.

◆ MultiplierUpdateMode

enum class proxsuite::nlp::MultiplierUpdateMode

strong

Enumerator
NEWTON
PRIMAL
PRIMAL_DUAL

Definition at line 23 of file prox-solver.hpp.

◆ HessianApprox

enum class proxsuite::nlp::HessianApprox

strong

Enumerator
EXACT	Exact Hessian construction from provided function Hessians.
GAUSS_NEWTON	Gauss-Newton (or rather SCQP) approximation.

Definition at line 25 of file prox-solver.hpp.

◆ InertiaFlag

enum proxsuite::nlp::InertiaFlag

Enumerator
INERTIA_OK
INERTIA_BAD
INERTIA_HAS_ZEROS

Definition at line 32 of file prox-solver.hpp.

◆ KktSystem

enum proxsuite::nlp::KktSystem

Enumerator
KKT_CLASSIC
KKT_PRIMAL_DUAL

Definition at line 34 of file prox-solver.hpp.

◆ ConvergenceFlag

enum proxsuite::nlp::ConvergenceFlag

Enumerator
UNINIT
SUCCESS
MAX_ITERS_REACHED

Definition at line 11 of file results.hpp.

Function Documentation

◆ downcast_function_to_cost()

template<typename Scalar >

auto proxsuite::nlp::downcast_function_to_cost ( const shared_ptr< C2FunctionTpl< Scalar > > & func ) -> shared_ptr<CostFunctionBaseTpl<Scalar>>

Definition at line 15 of file cost-function.hpp.

◆ compose()

template<typename Scalar >

auto proxsuite::nlp::compose	(	const shared_ptr< C2FunctionTpl< Scalar > > &	left,
		const shared_ptr< C2FunctionTpl< Scalar > > &	right )

Compose two function objects.

Returns: ComposeFunctionTpl object representing the composition of left and right.

Definition at line 56 of file function-ops.hpp.

◆ create_default_block_structure()

linalg::SymbolicBlockMatrix proxsuite::nlp::create_default_block_structure	(	const std::vector< isize > &	dims_primal,
		const std::vector< isize > &	dims_dual )

inline

Definition at line 47 of file ldlt-allocator.hpp.

◆ get_total_dim_helper()

isize proxsuite::nlp::get_total_dim_helper	(	const std::vector< isize > &	nprims,
		const std::vector< isize > &	nduals )

inline

Definition at line 95 of file ldlt-allocator.hpp.

◆ allocate_ldlt_from_sizes()

template<typename Scalar >

LDLTVariant< Scalar > proxsuite::nlp::allocate_ldlt_from_sizes	(	const std::vector< isize > &	nprims,
		const std::vector< isize > &	nduals,
		LDLTChoice	choice )

Definition at line 102 of file ldlt-allocator.hpp.

◆ computeInertiaTuple()

std::array< int, 3 > proxsuite::nlp::computeInertiaTuple ( const Eigen::Ref< Eigen::VectorXi const > & signature )

inline

Definition at line 197 of file ldlt-allocator.hpp.

◆ blockMatrixGetRow()

template<typename Derived >

auto proxsuite::nlp::blockMatrixGetRow	(	const Eigen::MatrixBase< Derived > &	matrix,
		const std::vector< Eigen::Index > &	rowBlockSizes,
		std::size_t	rowIdx )

Definition at line 8 of file constraint-set-product.hpp.

◆ blockVectorGetRow()

template<typename Derived >

auto proxsuite::nlp::blockVectorGetRow	(	const Eigen::MatrixBase< Derived > &	matrix,
		const std::vector< Eigen::Index > &	blockSizes,
		std::size_t	blockIdx )

Definition at line 20 of file constraint-set-product.hpp.

◆ operator*() [1/4]

template<typename T >

auto proxsuite::nlp::operator*	(	const polymorphic< ManifoldAbstractTpl< T > > &	left,
		const polymorphic< ManifoldAbstractTpl< T > > &	right )

Definition at line 126 of file cartesian-product.hpp.

◆ operator*() [2/4]

template<typename T >

auto proxsuite::nlp::operator*	(	const CartesianProductTpl< T > &	left,
		const polymorphic< ManifoldAbstractTpl< T > > &	right )

Definition at line 132 of file cartesian-product.hpp.

◆ operator*() [3/4]

template<typename T >

auto proxsuite::nlp::operator*	(	const polymorphic< ManifoldAbstractTpl< T > > &	left,
		const CartesianProductTpl< T > &	right )

Definition at line 140 of file cartesian-product.hpp.

◆ operator*() [4/4]

template<typename T >

auto proxsuite::nlp::operator*	(	const CartesianProductTpl< T > &	left,
		const CartesianProductTpl< T > &	right )

Definition at line 146 of file cartesian-product.hpp.

◆ checkInertia()

InertiaFlag proxsuite::nlp::checkInertia	(	const int	ndx,
		const int	nc,
		const Eigen::VectorXi &	signature )

inline

Check the matrix has the desired inertia.

Parameters

signature	The computed inertia as a vector of ints valued -1, 0, or 1.
delta	Scale factor for the identity matrix to add

◆ format_as()

auto proxsuite::nlp::format_as ( ConvergenceFlag fl )

inline

Definition at line 12 of file results.hpp.

◆ printVersion()

std::string proxsuite::nlp::printVersion ( const std::string & delimiter = "." )

inline

Pretty-print the package version number.

Parameters

delimiter The delimiter between the major/minor/patch version components.

Definition at line 15 of file version.hpp.

◆ allocate_ldlt_from_problem()

template<typename Scalar >

auto proxsuite::nlp::allocate_ldlt_from_problem	(	const ProblemTpl< Scalar > &	prob,
		LDLTChoice	choice )

Definition at line 14 of file workspace.hpp.

Variable Documentation

◆ NUM_KEYS

int proxsuite::nlp::NUM_KEYS = 10

constexpr

Definition at line 13 of file logger.hpp.

◆ BASIC_KEYS

const std::array<std::string, NUM_KEYS> proxsuite::nlp::BASIC_KEYS

Initial value:

= {
    "iter", "step_size", "inner_crit", "prim_err", "dual_err",
    "xreg", "dphi0",     "merit",      "dM",       "al_iter"}

Definition at line 14 of file logger.hpp.

◆ int_format

char proxsuite::nlp::int_format[] = "{: >{}d}"

constexpr

Definition at line 17 of file logger.hpp.

◆ sci_format

char proxsuite::nlp::sci_format[] = "{: > {}.{}e}"

constexpr

Definition at line 18 of file logger.hpp.

◆ dbl_format

char proxsuite::nlp::dbl_format[] = "{: > {}.{}g}"

constexpr

Definition at line 19 of file logger.hpp.

◆ is_eigen_dense_type

template<typename T >

bool proxsuite::nlp::is_eigen_dense_type

constexpr

Initial value:

=

std::is_base_of<Eigen::DenseBase<T>, T>::value

Definition at line 13 of file math.hpp.

◆ is_eigen_matrix_type

template<typename T >

bool proxsuite::nlp::is_eigen_matrix_type

constexpr

Initial value:

=

std::is_base_of<Eigen::MatrixBase<T>, T>::value

Definition at line 17 of file math.hpp.

Namespaces

Classes

Typedefs

Enumerations

Functions

Variables

Typedef Documentation

◆ LDLTVariant

◆ enable_if_eigen_dense

◆ SETpl

◆ SOTpl

Enumeration Type Documentation

◆ VerboseLevel

◆ LDLTChoice

◆ LinesearchStrategy

◆ LSInterpolation

◆ MultiplierUpdateMode

◆ HessianApprox

◆ InertiaFlag

◆ KktSystem

◆ ConvergenceFlag

Function Documentation

◆ downcast_function_to_cost()

◆ compose()

◆ create_default_block_structure()

◆ get_total_dim_helper()

◆ allocate_ldlt_from_sizes()

◆ computeInertiaTuple()

◆ blockMatrixGetRow()

◆ blockVectorGetRow()

◆ operator*() [1/4]

◆ operator*() [2/4]

◆ operator*() [3/4]

◆ operator*() [4/4]

◆ checkInertia()

◆ format_as()

◆ printVersion()

◆ allocate_ldlt_from_problem()

Variable Documentation

◆ NUM_KEYS

◆ BASIC_KEYS

◆ int_format

◆ sci_format

◆ dbl_format

◆ is_eigen_dense_type

◆ is_eigen_matrix_type