Namespaces
namespace	anonymous_namespace{ocproblem-counters.cpp}
namespace	anonymous_namespace{problem-counters.cpp}
namespace	anonymous_namespace{qpalm-adapter.cpp}
namespace	casadi
namespace	casadi_loader
namespace	cutest
namespace	detail
namespace	dl
namespace	functions
namespace	lbfgsb
namespace	lbfgspp
namespace	params
namespace	sets
namespace	sparsity
namespace	util
namespace	vec_util

Classes
struct	ALMParams
	Parameters for the Augmented Lagrangian solver. More...
class	ALMSolver
	Augmented Lagrangian Method solver. More...
class	AndersonAccel
	Anderson Acceleration. More...
struct	AndersonAccelParams
	Parameters for the AndersonAccel class. More...
struct	AndersonDirection
struct	AndersonDirectionParams
	Parameters for the AndersonDirection class. More...
struct	Box
class	BoxConstrProblem
	Implements common problem functions for minimization problems with box constraints. More...
class	CasADiControlProblem
struct	CasADiFunctions
class	CasADiProblem
	Problem definition for a CasADi problem, loaded from a DLL. More...
struct	CBFGSParams
	Cautious BFGS update. More...
struct	ControlProblemVTable
struct	ControlProblemWithCounters
struct	ConvexNewtonDirection
struct	ConvexNewtonDirectionParams
	Parameters for the ConvexNewtonDirection class. More...
struct	ConvexNewtonRegularizationParams
	Parameters for the ConvexNewtonDirection class. More...
class	CUTEstLoader
class	CUTEstProblem
	Wrapper for CUTEst problems loaded from an external shared library. More...
struct	Dim
struct	EigenConfig
struct	EigenConfigd
	Double-precision double configuration. More...
struct	EigenConfigf
	Single-precision float configuration. More...
struct	EigenConfigl
	long double configuration. More...
struct	EvalCounter
struct	FISTAParams
	Tuning parameters for the FISTA algorithm. More...
struct	FISTAProgressInfo
class	FISTASolver
	FISTA solver for ALM. More...
struct	FISTAStats
class	FunctionalProblem
	Problem class that allows specifying the basic functions as C++ std::functions. More...
struct	InnerSolveOptions
struct	InnerStatsAccumulator
struct	InnerStatsAccumulator< FISTAStats< Conf > >
struct	InnerStatsAccumulator< lbfgsb::LBFGSBStats >
struct	InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > >
struct	InnerStatsAccumulator< PANOCOCPStats< Conf > >
struct	InnerStatsAccumulator< PANOCStats< Conf > >
struct	InnerStatsAccumulator< PANTRStats< Conf > >
struct	InnerStatsAccumulator< WolfeStats< Conf > >
struct	InnerStatsAccumulator< ZeroFPRStats< Conf > >
class	IpoptAdapter
	Based on https://coin-or.github.io/Ipopt/INTERFACES.html. More...
struct	is_config
struct	is_config< EigenConfigd >
struct	is_config< EigenConfigf >
struct	is_config< EigenConfigl >
struct	is_config< EigenConfigq >
struct	is_eigen_config
struct	is_eigen_config< EigenConfigd >
struct	is_eigen_config< EigenConfigf >
struct	is_eigen_config< EigenConfigl >
struct	is_eigen_config< EigenConfigq >
struct	KKTError
class	LBFGS
	Limited memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm. More...
struct	LBFGSDirection
struct	LBFGSDirectionParams
	Parameters for the LBFGSDirection class. More...
struct	LBFGSParams
	Parameters for the LBFGS class. More...
struct	LBFGSStorage
	Layout: More...
class	LimitedMemoryQR
	Incremental QR factorization using modified Gram-Schmidt with reorthogonalization. More...
struct	LinConstrConverter
struct	LipschitzEstimateParams
	Parameters for the estimation of the Lipschitz constant of the gradient of the smooth term of the cost. More...
struct	NewtonTRDirection
struct	NewtonTRDirectionParams
	Parameters for the NewtonTRDirection class. More...
struct	NoopDirection
	Direction provider that provides no directions (apply always returns false). More...
struct	OCPDim
struct	OCPEvalCounter
struct	OCPEvaluator
struct	OCPVariables
struct	OwningQPALMData
struct	PANOCDirection
	This class outlines the interface for direction providers used by PANOC-like algorithms. More...
struct	PANOCOCPParams
	Tuning parameters for the PANOC algorithm. More...
struct	PANOCOCPProgressInfo
class	PANOCOCPSolver
struct	PANOCOCPStats
struct	PANOCParams
	Tuning parameters for the PANOC algorithm. More...
struct	PANOCProgressInfo
class	PANOCSolver
	PANOC solver for ALM. More...
struct	PANOCStats
struct	PANTRDirection
	This class outlines the interface for direction providers used by PANTR-like algorithms. More...
struct	PANTRParams
	Tuning parameters for the PANTR algorithm. More...
struct	PANTRProgressInfo
class	PANTRSolver
	PANTR solver for ALM. More...
struct	PANTRStats
struct	ProblemVTable
	Struct containing function pointers to all problem functions (like the objective and constraint functions, with their derivatives, and more). More...
struct	ProblemWithCounters
	Problem wrapper that keeps track of the number of evaluations and the run time of each function. More...
struct	prox_fn
	Proximal mapping customization point. More...
struct	prox_step_fn
	Proximal mapping customization point for forward-backward steps. More...
struct	ScopedMallocAllower
struct	ScopedMallocBlocker
struct	ScopedMallocChecker
struct	SerializedCasADiFunctions
struct	StatefulLQRFactor
struct	SteihaugCG
	Steihaug conjugate gradients procedure based on https://github.com/scipy/scipy/blob/583e70a50573169fc352b5dc6d94588a97c7389a/scipy/optimize/_trustregion_ncg.py#L44. More...
struct	SteihaugCGParams
	Parameters for SteihaugCG. More...
struct	StructuredLBFGSDirection
struct	StructuredLBFGSDirectionParams
	Parameters for the StructuredLBFGSDirection class. More...
struct	StructuredNewtonDirection
struct	StructuredNewtonDirectionParams
	Parameters for the StructuredNewtonDirection class. More...
struct	StructuredNewtonRegularizationParams
	Parameters for the StructuredNewtonDirection class. More...
class	TypeErasedControlProblem
	Nonlinear optimal control problem with finite horizon \( N \). More...
class	TypeErasedProblem
	The main polymorphic minimization problem interface. More...
class	UnconstrProblem
	Implements common problem functions for minimization problems without constraints. More...
struct	WolfeParams
	Tuning parameters for the unconstrained solver with Wolfe line search. More...
struct	WolfeProgressInfo
	Iterate information for the unconstrained solver with Wolfe line search. More...
class	WolfeSolver
	Unconstrained solver with Wolfe line search. More...
struct	WolfeStats
	Statistics for the unconstrained solver with Wolfe line search. More...
struct	ZeroFPRParams
	Tuning parameters for the ZeroFPR algorithm. More...
struct	ZeroFPRProgressInfo
class	ZeroFPRSolver
	ZeroFPR solver for ALM. More...
struct	ZeroFPRStats

Concepts
concept	Config
concept	VectorRefLike

Typedefs
using	DefaultConfig = EigenConfigd
template<Config Conf = DefaultConfig>
using	real_t = typename Conf::real_t
template<Config Conf = DefaultConfig>
using	cplx_t = typename Conf::cplx_t
template<Config Conf = DefaultConfig>
using	vec = typename Conf::vec
template<Config Conf = DefaultConfig>
using	mvec = typename Conf::mvec
template<Config Conf = DefaultConfig>
using	cmvec = typename Conf::cmvec
template<Config Conf = DefaultConfig>
using	rvec = typename Conf::rvec
template<Config Conf = DefaultConfig>
using	crvec = typename Conf::crvec
template<Config Conf = DefaultConfig>
using	mat = typename Conf::mat
template<Config Conf = DefaultConfig>
using	mmat = typename Conf::mmat
template<Config Conf = DefaultConfig>
using	cmmat = typename Conf::cmmat
template<Config Conf = DefaultConfig>
using	rmat = typename Conf::rmat
template<Config Conf = DefaultConfig>
using	crmat = typename Conf::crmat
template<Config Conf = DefaultConfig>
using	cmat = typename Conf::cmat
template<Config Conf = DefaultConfig>
using	mcmat = typename Conf::mcmat
template<Config Conf = DefaultConfig>
using	cmcmat = typename Conf::cmcmat
template<Config Conf = DefaultConfig>
using	rcmat = typename Conf::rcmat
template<Config Conf = DefaultConfig>
using	crcmat = typename Conf::crcmat
template<Config Conf = DefaultConfig>
using	length_t = typename Conf::length_t
template<Config Conf = DefaultConfig>
using	index_t = typename Conf::index_t
template<Config Conf = DefaultConfig>
using	indexvec = typename Conf::indexvec
template<Config Conf = DefaultConfig>
using	rindexvec = typename Conf::rindexvec
template<Config Conf = DefaultConfig>
using	crindexvec = typename Conf::crindexvec
template<Config Conf = DefaultConfig>
using	mindexvec = typename Conf::mindexvec
template<Config Conf = DefaultConfig>
using	cmindexvec = typename Conf::cmindexvec
using	casadi_int = long long int
using	casadi_real = double
using	function_dict_t = alpaqa_function_dict_t
using	problem_register_t = alpaqa_problem_register_t
using	control_problem_register_t = alpaqa_control_problem_register_t
using	problem_functions_t = alpaqa_problem_functions_t
using	control_problem_functions_t = alpaqa_control_problem_functions_t

Enumerations
enum class	LBFGSStepSize { BasedOnExternalStepSize = 0 , BasedOnCurvature = 1 , BasedOnGradientStepSize }
	Which method to use to select the L-BFGS step size. More...
enum class	PANOCStopCrit { ApproxKKT = 0 , ApproxKKT2 , ProjGradNorm , ProjGradNorm2 , ProjGradUnitNorm , ProjGradUnitNorm2 , FPRNorm , FPRNorm2 , Ipopt , LBFGSBpp }
enum class	SolverStatus { Busy = 0 , Converged , MaxTime , MaxIter , NotFinite , NoProgress , Interrupted , Exception }
	Exit status of a numerical solver such as ALM or PANOC. More...

Functions
template<Config Conf = DefaultConfig>
void	minimize_update_anderson (LimitedMemoryQR< Conf > &qr, rmat< Conf > G̃, crvec< Conf > rₖ, crvec< Conf > rₗₐₛₜ, crvec< Conf > gₖ, real_t< Conf > min_div_fac, rvec< Conf > γ_LS, rvec< Conf > xₖ_aa)
	Solve one step of Anderson acceleration to find a fixed point of a function g(x):
constexpr const char *	enum_name (LBFGSStepSize s)
template<Config Conf, VectorRefLike< Conf > V>
constexpr auto	const_or_mut_rvec (V &&v)
template<Config Conf>
InnerStatsAccumulator< FISTAStats< Conf > > &	operator+= (InnerStatsAccumulator< FISTAStats< Conf > > &acc, const FISTAStats< Conf > &s)
constexpr const char *	enum_name (PANOCStopCrit s)
std::ostream &	operator<< (std::ostream &os, PANOCStopCrit s)
template<Config Conf>
InnerStatsAccumulator< PANOCOCPStats< Conf > > &	operator+= (InnerStatsAccumulator< PANOCOCPStats< Conf > > &acc, const PANOCOCPStats< Conf > &s)
template<Config Conf>
InnerStatsAccumulator< PANOCStats< Conf > > &	operator+= (InnerStatsAccumulator< PANOCStats< Conf > > &acc, const PANOCStats< Conf > &s)
template<Config Conf>
InnerStatsAccumulator< PANTRStats< Conf > > &	operator+= (InnerStatsAccumulator< PANTRStats< Conf > > &acc, const PANTRStats< Conf > &s)
template<Config Conf>
InnerStatsAccumulator< WolfeStats< Conf > > &	operator+= (InnerStatsAccumulator< WolfeStats< Conf > > &acc, const WolfeStats< Conf > &s)
template<Config Conf>
InnerStatsAccumulator< ZeroFPRStats< Conf > > &	operator+= (InnerStatsAccumulator< ZeroFPRStats< Conf > > &acc, const ZeroFPRStats< Conf > &s)
template<Config Conf>
KKTError< Conf >	compute_kkt_error (const TypeErasedProblem< Conf > &problem, crvec< Conf > x, crvec< Conf > y)
std::ostream &	operator<< (std::ostream &, const OCPEvalCounter &)
OCPEvalCounter::OCPEvalTimer &	operator+= (OCPEvalCounter::OCPEvalTimer &a, const OCPEvalCounter::OCPEvalTimer &b)
OCPEvalCounter &	operator+= (OCPEvalCounter &a, const OCPEvalCounter &b)
OCPEvalCounter	operator+ (OCPEvalCounter a, const OCPEvalCounter &b)
void	check_finiteness (const auto &v, std::string_view msg)
	If the given vector `v` is not finite, break or throw an exception with the given message `msg`.
void	check_finiteness (const std::floating_point auto &v, std::string_view msg)
template<class Problem>
auto	ocproblem_with_counters (Problem &&p)
template<class Problem>
auto	ocproblem_with_counters_ref (Problem &p)
std::ostream &	operator<< (std::ostream &, const EvalCounter &)
EvalCounter::EvalTimer &	operator+= (EvalCounter::EvalTimer &a, const EvalCounter::EvalTimer &b)
EvalCounter &	operator+= (EvalCounter &a, const EvalCounter &b)
EvalCounter	operator+ (EvalCounter a, const EvalCounter &b)
template<class Problem>
auto	problem_with_counters (Problem &&p)
	Wraps the given problem into a ProblemWithCounters and keeps track of how many times each function is called, and how long these calls took.
template<class Problem>
auto	problem_with_counters_ref (Problem &p)
	Wraps the given problem into a ProblemWithCounters and keeps track of how many times each function is called, and how long these calls took.
template<Config Conf>
void	print_provided_functions (std::ostream &os, const TypeErasedProblem< Conf > &problem)
template<class Derived>
std::ostream &	print_python (std::ostream &os, const Eigen::DenseBase< Derived > &M)
template<class Derived> requires (Derived::ColsAtCompileTime == 1)
auto	as_span (Eigen::DenseBase< Derived > &v)
	Convert an Eigen vector view to a std::span.
template<class Derived> requires (Derived::ColsAtCompileTime == 1)
auto	as_span (Eigen::DenseBase< Derived > &&v)
	Convert an Eigen vector view to a std::span.
template<class Derived> requires (Derived::ColsAtCompileTime == 1)
auto	as_span (const Eigen::DenseBase< Derived > &v)
	Convert an Eigen vector view to a std::span.
template<class T, size_t E>
auto	as_vec (std::span< T, E > s)
	Convert a std::span to an Eigen::Vector view.
template<class Solver>
auto	attach_cancellation (Solver &solver)
	Attach SIGINT and SIGTERM handlers to stop the given solver.
std::ostream &	operator<< (std::ostream &os, SolverStatus s)
template<Config Conf>
Sparsity	convert_csc (const auto &sp, sparsity::Symmetry symmetry)
template<class Func>
void	register_function (function_dict_t *&extra_functions, std::string name, Func &&func)
	Make the given function available to alpaqa.
template<class Func>
void	register_function (problem_register_t &result, std::string name, Func &&func)
template<class Func>
void	register_function (control_problem_register_t &result, std::string name, Func &&func)
template<class Result, class T, class Ret, class... Args>
void	register_member_function (Result &result, std::string name, Ret(T::*member)(Args...))
template<auto Member>
static auto	member_caller ()
	Wrap the given member function or variable into a (possibly generic) lambda function that accepts the instance as a type-erased void pointer.
void	unregister_functions (function_dict_t *&extra_functions)
	Cleans up the extra functions registered by register_function.
InnerStatsAccumulator< lbfgsb::LBFGSBStats > &	operator+= (InnerStatsAccumulator< lbfgsb::LBFGSBStats > &acc, const lbfgsb::LBFGSBStats &s)
template<Config Conf>
InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > > &	operator+= (InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > > &acc, const lbfgspp::LBFGSBStats< Conf > &s)
OwningQPALMData	build_qpalm_problem (const TypeErasedProblem< EigenConfigd > &problem)

Variables
template<class T>
constexpr bool	is_config_v = is_config<T>::value
template<class T>
constexpr bool	is_eigen_config_v = is_eigen_config<T>::value
template<Config Conf>
constexpr const auto	inf = std::numeric_limits<real_t<Conf>>::infinity()
template<Config Conf>
constexpr const auto	NaN = std::numeric_limits<real_t<Conf>>::quiet_NaN()
template<Config Conf>
const rvec< Conf >	null_vec = mvec<Conf>{nullptr, 0}
	Global empty vector for convenience.
template<Config Conf>
const rindexvec< Conf >	null_indexvec = mindexvec<Conf>{nullptr, 0}
	Global empty index vector for convenience.
struct alpaqa::prox_fn	prox
	Compute the proximal mapping.
struct alpaqa::prox_step_fn	prox_step
	Compute a generalized forward-backward step.

Class Documentation

◆ alpaqa::FISTAStats

struct alpaqa::FISTAStats

Collaboration diagram for FISTAStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	stepsize_backtracks = 0
real_t	final_γ = 0
real_t	final_ψ = 0
real_t	final_h = 0

◆ alpaqa::InnerSolveOptions

struct alpaqa::InnerSolveOptions

Collaboration diagram for InnerSolveOptions< Conf >:

Class Members
bool	always_overwrite_results = true	Return the final iterate and multipliers, even if the solver did not converge.
optional< nanoseconds >	max_time = std::nullopt	Maximum run time (in addition to the inner solver's own timeout). Zero means no timeout.
real_t	tolerance = 0	Desired tolerance (overrides the solver's own tolerance). Zero means no tolerance (use solver's own tolerance).
ostream *	os = nullptr	Output stream to print to.
unsigned	outer_iter = 0	The current iteration of the outer solver.
bool	check = true	Call check() before starting to solve.

◆ alpaqa::InnerStatsAccumulator

struct alpaqa::InnerStatsAccumulator

Collaboration diagram for InnerStatsAccumulator< InnerSolverStats >:

◆ alpaqa::InnerStatsAccumulator< FISTAStats< Conf > >

struct alpaqa::InnerStatsAccumulator< FISTAStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< FISTAStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner FISTA iterations.
unsigned	stepsize_backtracks = 0	Total number of FISTA step size reductions.
real_t	final_γ = 0	The final FISTA step size γ.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
real_t	final_h = 0	Final value of the nonsmooth cost \( h(\hat x) \).

◆ alpaqa::InnerStatsAccumulator< lbfgsb::LBFGSBStats >

struct alpaqa::InnerStatsAccumulator< lbfgsb::LBFGSBStats >

Collaboration diagram for InnerStatsAccumulator< lbfgsb::LBFGSBStats >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner PANOC iterations.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
unsigned	direction_update_rejected = 0	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).

◆ alpaqa::InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > >

struct alpaqa::InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
unsigned	iterations = 0	Total number of inner PANOC iterations.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).

◆ alpaqa::InnerStatsAccumulator< PANOCOCPStats< Conf > >

struct alpaqa::InnerStatsAccumulator< PANOCOCPStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< PANOCOCPStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_prox {}	Total time spent computing proximal mappings.
nanoseconds	time_forward {}	Total time spent doing forward simulations.
nanoseconds	time_backward {}	Total time spent doing backward gradient evaluations.
nanoseconds	time_jacobians {}	Total time spent computing dynamics Jacobians.
nanoseconds	time_hessians {}	Total time spent computing cost Hessians and Hessian-vector products.
nanoseconds	time_indices {}	Total time spent determining active indices.
nanoseconds	time_lqr_factor {}	Total time spent performing LQR factorizations.
nanoseconds	time_lqr_solve {}	Total time spent solving the (factorized) LQR problem.
nanoseconds	time_lbfgs_indices {}	Total time spent determining active indices for L-BFGS applications.
nanoseconds	time_lbfgs_apply {}	Total time spent applying L-BFGS estimates.
nanoseconds	time_lbfgs_update {}	Total time spent updating the L-BFGS estimate.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner PANOC iterations.
unsigned	linesearch_failures = 0	Total number of PANOC line search failures.
unsigned	linesearch_backtracks = 0	Total number of PANOC line search backtracking steps.
unsigned	stepsize_backtracks = 0	Total number of PANOC step size reductions.
unsigned	direction_failures = 0	Total number of times that the L-BFGS direction was not finite.
unsigned	direction_update_rejected = 0	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).
unsigned	τ_1_accepted = 0	Total number of times that a line search parameter of \( \tau = 1 \) was accepted (i.e. no backtracking necessary).
unsigned	count_τ = 0	The total number of line searches performed (used for computing the average value of \( \tau \)).
real_t	sum_τ = 0	The sum of the line search parameter \( \tau \) in all iterations (used for computing the average value of \( \tau \)).
real_t	final_γ = 0	The final PANOC step size γ.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
real_t	final_h = 0	Final value of the nonsmooth cost \( h(\hat x) \).
real_t	final_φγ = 0	Final value of the forward-backward envelope, \( \varphi_\gamma(x) \) (note that this is in the point \( x \), not \( \hat x \)).

◆ alpaqa::InnerStatsAccumulator< PANOCStats< Conf > >

struct alpaqa::InnerStatsAccumulator< PANOCStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< PANOCStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner PANOC iterations.
unsigned	linesearch_failures = 0	Total number of PANOC line search failures.
unsigned	linesearch_backtracks = 0	Total number of PANOC line search backtracking steps.
unsigned	stepsize_backtracks = 0	Total number of PANOC step size reductions.
unsigned	direction_failures = 0	Total number of times that the L-BFGS direction was not finite.
unsigned	direction_update_rejected = 0	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).
unsigned	τ_1_accepted = 0	Total number of times that a line search parameter of \( \tau = 1 \) was accepted (i.e. no backtracking necessary).
unsigned	count_τ = 0	The total number of line searches performed (used for computing the average value of \( \tau \)).
real_t	sum_τ = 0	The sum of the line search parameter \( \tau \) in all iterations (used for computing the average value of \( \tau \)).
real_t	final_γ = 0	The final PANOC step size γ.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
real_t	final_h = 0	Final value of the nonsmooth cost \( h(\hat x) \).
real_t	final_φγ = 0	Final value of the forward-backward envelope, \( \varphi_\gamma(x) \) (note that this is in the point \( x \), not \( \hat x \)).

◆ alpaqa::InnerStatsAccumulator< PANTRStats< Conf > >

struct alpaqa::InnerStatsAccumulator< PANTRStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< PANTRStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner PANTR iterations.
unsigned	accelerated_step_rejected = 0	Total number of PANTR rejected accelerated steps.
unsigned	stepsize_backtracks = 0	Total number of FB step size reductions.
unsigned	direction_failures = 0	Total number of times that the accelerated direction was not finite.
unsigned	direction_update_rejected = 0	Total number of times that the direction update was rejected (e.g. it could have resulted in a non-positive definite Hessian estimate).
real_t	final_γ = 0	The final FB step size γ.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
real_t	final_h = 0	Final value of the nonsmooth cost \( h(\hat x) \).
real_t	final_φγ = 0	Final value of the forward-backward envelope, \( \varphi_\gamma(x) \) (note that this is in the point \( x \), not \( \hat x \)).

◆ alpaqa::InnerStatsAccumulator< WolfeStats< Conf > >

struct alpaqa::InnerStatsAccumulator< WolfeStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< WolfeStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner Wolfe iterations.
unsigned	linesearch_failures = 0	Total number of Wolfe line search failures.
unsigned	linesearch_backtracks = 0	Total number of Wolfe line search backtracking steps.
unsigned	direction_failures = 0	Total number of times that the L-BFGS direction was not finite.
unsigned	direction_update_rejected = 0	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).
unsigned	τ_1_accepted = 0	Total number of times that a line search parameter of \( \tau = 1 \) was accepted (i.e. no backtracking necessary).
unsigned	count_τ = 0	The total number of line searches performed (used for computing the average value of \( \tau \)).
real_t	sum_τ = 0	The sum of the line search parameter \( \tau \) in all iterations (used for computing the average value of \( \tau \)).
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).

◆ alpaqa::InnerStatsAccumulator< ZeroFPRStats< Conf > >

struct alpaqa::InnerStatsAccumulator< ZeroFPRStats< Conf > >

Collaboration diagram for InnerStatsAccumulator< ZeroFPRStats< Conf > >:

Class Members
nanoseconds	elapsed_time {}	Total elapsed time in the inner solver.
nanoseconds	time_progress_callback {}	Total time spent in the user-provided progress callback.
unsigned	iterations = 0	Total number of inner ZeroFPR iterations.
unsigned	linesearch_failures = 0	Total number of ZeroFPR line search failures.
unsigned	linesearch_backtracks = 0	Total number of ZeroFPR line search backtracking steps.
unsigned	stepsize_backtracks = 0	Total number of ZeroFPR step size reductions.
unsigned	direction_failures = 0	Total number of times that the L-BFGS direction was not finite.
unsigned	direction_update_rejected = 0	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).
unsigned	τ_1_accepted = 0	Total number of times that a line search parameter of \( \tau = 1 \) was accepted (i.e. no backtracking necessary).
unsigned	count_τ = 0	The total number of line searches performed (used for computing the average value of \( \tau \)).
real_t	sum_τ = 0	The sum of the line search parameter \( \tau \) in all iterations (used for computing the average value of \( \tau \)).
real_t	final_γ = 0	The final ZeroFPR step size γ.
real_t	final_ψ = 0	Final value of the smooth cost \( \psi(\hat x) \).
real_t	final_h = 0	Final value of the nonsmooth cost \( h(\hat x) \).
real_t	final_φγ = 0	Final value of the forward-backward envelope, \( \varphi_\gamma(x) \) (note that this is in the point \( x \), not \( \hat x \)).

◆ alpaqa::OCPDim

struct alpaqa::OCPDim

Collaboration diagram for OCPDim< Conf >:

Class Members
length_t	N
length_t	nx
length_t	nu
length_t	nh
length_t	nc

◆ alpaqa::PANOCOCPStats

struct alpaqa::PANOCOCPStats

Collaboration diagram for PANOCOCPStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_prox {}
nanoseconds	time_forward {}
nanoseconds	time_backward {}
nanoseconds	time_jacobians {}
nanoseconds	time_hessians {}
nanoseconds	time_indices {}
nanoseconds	time_lqr_factor {}
nanoseconds	time_lqr_solve {}
nanoseconds	time_lbfgs_indices {}
nanoseconds	time_lbfgs_apply {}
nanoseconds	time_lbfgs_update {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	linesearch_failures = 0
unsigned	linesearch_backtracks = 0
unsigned	stepsize_backtracks = 0
unsigned	direction_failures = 0
unsigned	direction_update_rejected = 0
unsigned	τ_1_accepted = 0
unsigned	count_τ = 0
real_t	sum_τ = 0
real_t	final_γ = 0
real_t	final_ψ = 0
real_t	final_h = 0
real_t	final_φγ = 0

◆ alpaqa::PANOCStats

struct alpaqa::PANOCStats

Collaboration diagram for PANOCStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	linesearch_failures = 0
unsigned	linesearch_backtracks = 0
unsigned	stepsize_backtracks = 0
unsigned	direction_failures = 0
unsigned	direction_update_rejected = 0
unsigned	τ_1_accepted = 0
unsigned	count_τ = 0
real_t	sum_τ = 0
real_t	final_γ = 0
real_t	final_ψ = 0
real_t	final_h = 0
real_t	final_φγ = 0

◆ alpaqa::PANTRStats

struct alpaqa::PANTRStats

Collaboration diagram for PANTRStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	accelerated_step_rejected = 0
unsigned	stepsize_backtracks = 0
unsigned	direction_failures = 0
unsigned	direction_update_rejected = 0
real_t	final_γ = 0
real_t	final_ψ = 0
real_t	final_h = 0
real_t	final_φγ = 0

◆ alpaqa::SerializedCasADiFunctions

struct alpaqa::SerializedCasADiFunctions

Collaboration diagram for SerializedCasADiFunctions:

Class Members
map< string, string >	functions

◆ alpaqa::WolfeStats

struct alpaqa::WolfeStats

Collaboration diagram for WolfeStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	linesearch_failures = 0
unsigned	linesearch_backtracks = 0
unsigned	direction_failures = 0
unsigned	direction_update_rejected = 0
unsigned	τ_1_accepted = 0
unsigned	count_τ = 0
real_t	sum_τ = 0
real_t	final_ψ = 0

◆ alpaqa::ZeroFPRStats

struct alpaqa::ZeroFPRStats

Collaboration diagram for ZeroFPRStats< Conf >:

Class Members
SolverStatus	status = SolverStatus::Busy
real_t	ε = inf<config_t>
nanoseconds	elapsed_time {}
nanoseconds	time_progress_callback {}
unsigned	iterations = 0
unsigned	linesearch_failures = 0
unsigned	linesearch_backtracks = 0
unsigned	stepsize_backtracks = 0
unsigned	direction_failures = 0
unsigned	direction_update_rejected = 0
unsigned	τ_1_accepted = 0
unsigned	count_τ = 0
real_t	sum_τ = 0
real_t	final_γ = 0
real_t	final_ψ = 0
real_t	final_h = 0
real_t	final_φγ = 0

Typedef Documentation

◆ DefaultConfig

using DefaultConfig = EigenConfigd

Examples: C++/CustomControlCppProblem/main.cpp, C++/CustomCppProblem/main.cpp, C++/DLProblem/main.cpp, and problems/sparse-logistic-regression.cpp.

Definition at line 31 of file config.hpp.

◆ real_t

template<Config Conf = DefaultConfig>

using real_t = typename Conf::real_t

Definition at line 86 of file config.hpp.

◆ cplx_t

template<Config Conf = DefaultConfig>

using cplx_t = typename Conf::cplx_t

Definition at line 87 of file config.hpp.

◆ vec

template<Config Conf = DefaultConfig>

using vec = typename Conf::vec

Definition at line 88 of file config.hpp.

◆ mvec

template<Config Conf = DefaultConfig>

using mvec = typename Conf::mvec

Definition at line 89 of file config.hpp.

◆ cmvec

template<Config Conf = DefaultConfig>

using cmvec = typename Conf::cmvec

Definition at line 90 of file config.hpp.

◆ rvec

template<Config Conf = DefaultConfig>

using rvec = typename Conf::rvec

Definition at line 91 of file config.hpp.

◆ crvec

template<Config Conf = DefaultConfig>

using crvec = typename Conf::crvec

Definition at line 92 of file config.hpp.

◆ mat

template<Config Conf = DefaultConfig>

using mat = typename Conf::mat

Definition at line 93 of file config.hpp.

◆ mmat

template<Config Conf = DefaultConfig>

using mmat = typename Conf::mmat

Definition at line 94 of file config.hpp.

◆ cmmat

template<Config Conf = DefaultConfig>

using cmmat = typename Conf::cmmat

Definition at line 95 of file config.hpp.

◆ rmat

template<Config Conf = DefaultConfig>

using rmat = typename Conf::rmat

Definition at line 96 of file config.hpp.

◆ crmat

template<Config Conf = DefaultConfig>

using crmat = typename Conf::crmat

Definition at line 97 of file config.hpp.

◆ cmat

template<Config Conf = DefaultConfig>

using cmat = typename Conf::cmat

Definition at line 98 of file config.hpp.

◆ mcmat

template<Config Conf = DefaultConfig>

using mcmat = typename Conf::mcmat

Definition at line 99 of file config.hpp.

◆ cmcmat

template<Config Conf = DefaultConfig>

using cmcmat = typename Conf::cmcmat

Definition at line 100 of file config.hpp.

◆ rcmat

template<Config Conf = DefaultConfig>

using rcmat = typename Conf::rcmat

Definition at line 101 of file config.hpp.

◆ crcmat

template<Config Conf = DefaultConfig>

using crcmat = typename Conf::crcmat

Definition at line 102 of file config.hpp.

◆ length_t

template<Config Conf = DefaultConfig>

using length_t = typename Conf::length_t

Definition at line 103 of file config.hpp.

◆ index_t

template<Config Conf = DefaultConfig>

using index_t = typename Conf::index_t

Definition at line 104 of file config.hpp.

◆ indexvec

template<Config Conf = DefaultConfig>

using indexvec = typename Conf::indexvec

Definition at line 105 of file config.hpp.

◆ rindexvec

template<Config Conf = DefaultConfig>

using rindexvec = typename Conf::rindexvec

Definition at line 106 of file config.hpp.

◆ crindexvec

template<Config Conf = DefaultConfig>

using crindexvec = typename Conf::crindexvec

Definition at line 107 of file config.hpp.

◆ mindexvec

template<Config Conf = DefaultConfig>

using mindexvec = typename Conf::mindexvec

Definition at line 108 of file config.hpp.

◆ cmindexvec

template<Config Conf = DefaultConfig>

using cmindexvec = typename Conf::cmindexvec

Definition at line 109 of file config.hpp.

◆ casadi_int

using casadi_int = long long int

Definition at line 13 of file casadi-types.hpp.

◆ casadi_real

using casadi_real = double

Definition at line 16 of file casadi-types.hpp.

◆ function_dict_t

using function_dict_t = alpaqa_function_dict_t

Definition at line 687 of file dl-problem.h.

◆ problem_register_t

using problem_register_t = alpaqa_problem_register_t

Definition at line 688 of file dl-problem.h.

◆ control_problem_register_t

using control_problem_register_t = alpaqa_control_problem_register_t

Definition at line 689 of file dl-problem.h.

◆ problem_functions_t

using problem_functions_t = alpaqa_problem_functions_t

Definition at line 690 of file dl-problem.h.

◆ control_problem_functions_t

using control_problem_functions_t = alpaqa_control_problem_functions_t

Definition at line 691 of file dl-problem.h.

Enumeration Type Documentation

◆ LBFGSStepSize

enum class LBFGSStepSize

strong

Which method to use to select the L-BFGS step size.

Enumerator
BasedOnExternalStepSize	Initial inverse Hessian approximation is set to \( H_0 = \gamma I \), where \( \gamma \) is the forward-backward splitting step size.
BasedOnCurvature	Initial inverse Hessian approximation is set to \( H_0 = \frac{s^\top y}{y^\top y} I \).
BasedOnGradientStepSize

Definition at line 26 of file lbfgs.hpp.

◆ PANOCStopCrit

enum class PANOCStopCrit

strong

Enumerator
ApproxKKT	Find an ε-approximate KKT point in the ∞-norm: \[ \varepsilon = \left\\| \gamma_k^{-1} (x^k - \hat x^k) + \nabla \psi(\hat x^k) - \nabla \psi(x^k) \right\\|_\infty \]
ApproxKKT2	Find an ε-approximate KKT point in the 2-norm: \[ \varepsilon = \left\\| \gamma_k^{-1} (x^k - \hat x^k) + \nabla \psi(\hat x^k) - \nabla \psi(x^k) \right\\|_2 \]
ProjGradNorm	∞-norm of the projected gradient with step size γ: \[ \varepsilon = \left\\| x^k - \Pi_C\left(x^k - \gamma_k \nabla \psi(x^k)\right) \right\\|_\infty \]
ProjGradNorm2	2-norm of the projected gradient with step size γ: \[ \varepsilon = \left\\| x^k - \Pi_C\left(x^k - \gamma_k \nabla \psi(x^k)\right) \right\\|_2 \] This is the same criterion as used by OpEn.
ProjGradUnitNorm	∞-norm of the projected gradient with unit step size: \[ \varepsilon = \left\\| x^k - \Pi_C\left(x^k - \nabla \psi(x^k)\right) \right\\|_\infty \]
ProjGradUnitNorm2	2-norm of the projected gradient with unit step size: \[ \varepsilon = \left\\| x^k - \Pi_C\left(x^k - \nabla \psi(x^k)\right) \right\\|_2 \]
FPRNorm	∞-norm of fixed point residual: \[ \varepsilon = \gamma_k^{-1} \left\\| x^k - \Pi_C\left(x^k - \gamma_k \nabla \psi(x^k)\right) \right\\|_\infty \]
FPRNorm2	2-norm of fixed point residual: \[ \varepsilon = \gamma_k^{-1} \left\\| x^k - \Pi_C\left(x^k - \gamma_k \nabla \psi(x^k)\right) \right\\|_2 \]
Ipopt	The stopping criterion used by Ipopt, see https://link.springer.com/article/10.1007/s10107-004-0559-y equation (5). Given a candidate iterate \( \hat x^k \) and the corresponding candidate Lagrange multipliers \( \hat y^k \) for the general constraints \( g(x)\in D \), the multipliers \( w \) for the box constraints \( x\in C \) (that are otherwise not computed explicitly) are given by \[w^k = v^k - \Pi_C(v^k), \] where \[ \begin{aligned} v^k &\triangleq \hat x^k - \nabla f(\hat x^k) - \nabla g(\hat x^k)\, \hat y^k \\ &= \hat x^k - \nabla \psi(\hat x^k) \end{aligned} \] The quantity that is compared to the (scaled) tolerance is then given by \[ \begin{aligned} \varepsilon' &= \left\\| \nabla f(\hat x^k) + \nabla g(\hat x^k)\, \hat y^k + w^k \right\\|_\infty \\ &= \left\\| \hat x^k - \Pi_C\left(v^k\right) \right\\|_\infty \end{aligned} \] Finally, the quantity is scaled by the factor \[s_d \triangleq \max\left\{ s_\text{max},\;\frac{\\|\hat y^k\\|_1 + \\|w^k\\|_1}{2m + 2n} \right\} / s_\text{max}, \] i.e. \( \varepsilon = \varepsilon' / s_d \).
LBFGSBpp	The stopping criterion used by LBFGS++, see https://lbfgspp.statr.me/doc/classLBFGSpp_1_1LBFGSBParam.html#afb20e8fd6c6808c1f736218841ba6947. \[ \varepsilon = \frac{\left\\| x^k - \Pi_C\left(x^k - \nabla \psi(x^k)\right) \right\\|_\infty} {\max\left\{1, \\|x\\|_2 \right\}} \]

Definition at line 8 of file panoc-stop-crit.hpp.

◆ SolverStatus

enum class SolverStatus

strong

Exit status of a numerical solver such as ALM or PANOC.

Enumerator
Busy	In progress.
Converged	Converged and reached given tolerance.
MaxTime	Maximum allowed execution time exceeded.
MaxIter	Maximum number of iterations exceeded.
NotFinite	Intermediate results were infinite or not-a-number.
NoProgress	No progress was made in the last iteration.
Interrupted	Solver was interrupted by the user.
Exception	An unexpected exception was thrown.

Definition at line 11 of file solverstatus.hpp.

Function Documentation

◆ minimize_update_anderson()

template<Config Conf = DefaultConfig>

void minimize_update_anderson	(	LimitedMemoryQR< Conf > &	qr,
		rmat< Conf >	G̃,
		crvec< Conf >	rₖ,
		crvec< Conf >	rₗₐₛₜ,
		crvec< Conf >	gₖ,
		real_t< Conf >	min_div_fac,
		rvec< Conf >	γ_LS,
		rvec< Conf >	xₖ_aa )

inline

Solve one step of Anderson acceleration to find a fixed point of a function g(x):

\( g(x^\star) - x^\star = 0 \)

Updates the QR factorization of \( \mathcal{R}_k = QR \), solves the least squares problem to find \( \gamma_\text{LS} \), computes the next iterate \( x_{k+1} \), and stores the current function value \( g_k \) in the matrix \( G \), which is used as a circular buffer.

\[ \begin{aligned} \def\gammaLS{\gamma_\text{LS}} m_k &= \min \{k, m\} \\ g_i &= g(x_i) \\ r_i &= r(x_i) g_i - x_i \\ \Delta r_i &= r_i - r_{i-1} \\ \mathcal{R}_k &= \begin{pmatrix} \Delta r_{k-m_k+1} & \dots & \Delta r_k \end{pmatrix} \in \R^{n\times m_k} \\ \gammaLS &= \argmin_{\gamma \in \R^{m_k}}\; \norm{\mathcal{R}_k \gamma - r_k}_2 \\ \alpha_i &= \begin{cases} \gammaLS[0] & i = 0 \\ \gammaLS[i] - \gammaLS[i-1] & 0 \lt i \lt m_k \\ 1 - \gammaLS[m_k - 1] & i = m_k \end{cases} \\ \tilde G_k &= \begin{pmatrix} g_{k - m_k} & \dots & g_{k-1} \end{pmatrix} \\ G_k &= \begin{pmatrix} g_{k - m_k} & \dots & g_{k} \end{pmatrix} \\ &= \begin{pmatrix} \tilde G_k & g_{k} \end{pmatrix} \\ x_{k+1} &= \sum_{i=0}^{m_k} \alpha_i\,g_{k - m_k + i} \\ &= G_k \alpha \\ \end{aligned} \]

Parameters

[in,out]	qr	QR factorization of \( \mathcal{R}_k \)
[in,out]	G̃	Matrix of previous function values \( \tilde G_k \) (stored as ring buffer with the same indices as qr)
[in]	rₖ	Current residual \( r_k \)
[in]	rₗₐₛₜ	Previous residual \( r_{k-1} \)
[in]	gₖ	Current function value \( g_k \)
[in]	min_div_fac	Minimum divisor when solving close to singular systems, scaled by the maximum eigenvalue of R
[out]	γ_LS	Solution to the least squares system
[out]	xₖ_aa	Next Anderson iterate

Definition at line 39 of file anderson-helpers.hpp.

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◆ enum_name() [1/2]

const char * enum_name ( LBFGSStepSize s )

inlineconstexpr

Definition at line 229 of file lbfgs.hpp.

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◆ const_or_mut_rvec()

template<Config Conf, VectorRefLike< Conf > V>

auto const_or_mut_rvec ( V && v )

constexpr

Definition at line 15 of file ocp-vars.hpp.

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◆ operator+=() [1/12]

template<Config Conf>

InnerStatsAccumulator< FISTAStats< Conf > > & operator+=	(	InnerStatsAccumulator< FISTAStats< Conf > > &	acc,
		const FISTAStats< Conf > &	s )

Definition at line 191 of file fista.hpp.

◆ enum_name() [2/2]

const char * enum_name ( PANOCStopCrit s )

inlineconstexpr

Definition at line 105 of file panoc-stop-crit.hpp.

◆ operator<<() [1/4]

std::ostream & operator<<	(	std::ostream &	os,
		PANOCStopCrit	s )

Definition at line 7 of file panoc-stop-crit.cpp.

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◆ operator+=() [2/12]

template<Config Conf>

InnerStatsAccumulator< PANOCOCPStats< Conf > > & operator+=	(	InnerStatsAccumulator< PANOCOCPStats< Conf > > &	acc,
		const PANOCOCPStats< Conf > &	s )

Definition at line 273 of file panoc-ocp.hpp.

◆ operator+=() [3/12]

template<Config Conf>

InnerStatsAccumulator< PANOCStats< Conf > > & operator+=	(	InnerStatsAccumulator< PANOCStats< Conf > > &	acc,
		const PANOCStats< Conf > &	s )

Definition at line 256 of file panoc.hpp.

◆ operator+=() [4/12]

template<Config Conf>

InnerStatsAccumulator< PANTRStats< Conf > > & operator+=	(	InnerStatsAccumulator< PANTRStats< Conf > > &	acc,
		const PANTRStats< Conf > &	s )

Definition at line 254 of file pantr.hpp.

◆ operator+=() [5/12]

template<Config Conf>

InnerStatsAccumulator< WolfeStats< Conf > > & operator+=	(	InnerStatsAccumulator< WolfeStats< Conf > > &	acc,
		const WolfeStats< Conf > &	s )

Definition at line 205 of file wolfe.hpp.

◆ operator+=() [6/12]

template<Config Conf>

InnerStatsAccumulator< ZeroFPRStats< Conf > > & operator+=	(	InnerStatsAccumulator< ZeroFPRStats< Conf > > &	acc,
		const ZeroFPRStats< Conf > &	s )

Definition at line 254 of file zerofpr.hpp.

◆ compute_kkt_error()

template<Config Conf>

KKTError< Conf > compute_kkt_error	(	const TypeErasedProblem< Conf > &	problem,
		crvec< Conf >	x,
		crvec< Conf >	y )

Definition at line 17 of file kkt-error.hpp.

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◆ operator<<() [2/4]

std::ostream & operator<<	(	std::ostream &	os,
		const OCPEvalCounter &	c )

Definition at line 32 of file ocproblem-counters.cpp.

◆ operator+=() [7/12]

OCPEvalCounter::OCPEvalTimer & operator+=	(	OCPEvalCounter::OCPEvalTimer &	a,
		const OCPEvalCounter::OCPEvalTimer &	b )

inline

Definition at line 62 of file ocproblem-counters.hpp.

◆ operator+=() [8/12]

OCPEvalCounter & operator+=	(	OCPEvalCounter &	a,
		const OCPEvalCounter &	b )

inline

Definition at line 88 of file ocproblem-counters.hpp.

◆ operator+() [1/2]

OCPEvalCounter operator+	(	OCPEvalCounter	a,
		const OCPEvalCounter &	b )

inline

Definition at line 114 of file ocproblem-counters.hpp.

◆ check_finiteness() [1/2]

void check_finiteness	(	const auto &	v,
		std::string_view	msg )

inline

If the given vector v is not finite, break or throw an exception with the given message msg.

Definition at line 510 of file ocproblem.hpp.

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◆ check_finiteness() [2/2]

void check_finiteness	(	const std::floating_point auto &	v,
		std::string_view	msg )

inline

Definition at line 518 of file ocproblem.hpp.

◆ ocproblem_with_counters()

template<class Problem>

auto ocproblem_with_counters ( Problem && p )

nodiscard

Definition at line 650 of file ocproblem.hpp.

◆ ocproblem_with_counters_ref()

template<class Problem>

auto ocproblem_with_counters_ref ( Problem & p )

nodiscard

Definition at line 657 of file ocproblem.hpp.

◆ operator<<() [3/4]

std::ostream & operator<<	(	std::ostream &	os,
		const EvalCounter &	c )

Definition at line 40 of file problem-counters.cpp.

◆ operator+=() [9/12]

EvalCounter::EvalTimer & operator+=	(	EvalCounter::EvalTimer &	a,
		const EvalCounter::EvalTimer &	b )

inline

Definition at line 62 of file problem-counters.hpp.

◆ operator+=() [10/12]

EvalCounter & operator+=	(	EvalCounter &	a,
		const EvalCounter &	b )

inline

Definition at line 89 of file problem-counters.hpp.

◆ operator+() [2/2]

EvalCounter operator+	(	EvalCounter	a,
		const EvalCounter &	b )

inline

Definition at line 116 of file problem-counters.hpp.

◆ print_python()

template<class Derived>

std::ostream & print_python	(	std::ostream &	os,
		const Eigen::DenseBase< Derived > &	M )

Examples: C++/Advanced/lasso-fbs.cpp, and C++/CustomControlCppProblem/main.cpp.

Definition at line 13 of file print.hpp.

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◆ as_span() [1/3]

template<class Derived>
requires (Derived::ColsAtCompileTime == 1)

auto as_span ( Eigen::DenseBase< Derived > & v )

Convert an Eigen vector view to a std::span.

Examples: problems/sparse-logistic-regression.cpp.

Definition at line 21 of file span.hpp.

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◆ as_span() [2/3]

template<class Derived>
requires (Derived::ColsAtCompileTime == 1)

auto as_span ( Eigen::DenseBase< Derived > && v )

Convert an Eigen vector view to a std::span.

Definition at line 30 of file span.hpp.

◆ as_span() [3/3]

template<class Derived>
requires (Derived::ColsAtCompileTime == 1)

auto as_span ( const Eigen::DenseBase< Derived > & v )

Convert an Eigen vector view to a std::span.

Definition at line 43 of file span.hpp.

◆ as_vec()

template<class T, size_t E>

auto as_vec ( std::span< T, E > s )

Convert a std::span to an Eigen::Vector view.

Definition at line 51 of file span.hpp.

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◆ attach_cancellation()

template<class Solver>

auto attach_cancellation ( Solver & solver )

nodiscard

Attach SIGINT and SIGTERM handlers to stop the given solver.

Parameters

solver The solver that should be stopped by the handler.

Returns: A RAII object that detaches the handler when destroyed.

Definition at line 21 of file cancel.hpp.

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◆ operator<<() [4/4]

std::ostream & operator<<	(	std::ostream &	os,
		SolverStatus	s )

Definition at line 7 of file solverstatus.cpp.

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◆ convert_csc()

template<Config Conf>

Sparsity convert_csc	(	const auto &	sp,
		sparsity::Symmetry	symmetry )

Definition at line 390 of file CasADiProblem.tpp.

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◆ register_function() [1/3]

template<class Func>

void register_function	(	function_dict_t *&	extra_functions,
		std::string	name,
		Func &&	func )

Make the given function available to alpaqa.

See also: call_extra_func; call_extra_func

Definition at line 708 of file dl-problem.h.

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◆ register_function() [2/3]

template<class Func>

void register_function	(	problem_register_t &	result,
		std::string	name,
		Func &&	func )

Definition at line 718 of file dl-problem.h.

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◆ register_function() [3/3]

template<class Func>

void register_function	(	control_problem_register_t &	result,
		std::string	name,
		Func &&	func )

Definition at line 725 of file dl-problem.h.

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◆ register_member_function()

template<class Result, class T, class Ret, class... Args>

void register_member_function	(	Result &	result,
		std::string	name,
		Ret(T::*	member )(Args...) )

Definition at line 732 of file dl-problem.h.

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◆ member_caller()

template<auto Member>

auto member_caller ( )

static

Wrap the given member function or variable into a (possibly generic) lambda function that accepts the instance as a type-erased void pointer.

The signature of the resulting function depends on the signature of the member function:

Ret Class::member(args...) → Ret(void *self, args...)
Ret Class::member(args...) const → Ret(void *self, args...)
Ret Class::member(args...) const → Ret(const void *self, args...)

If the given member is a variable:

Type Class::member → Type &(void *self)
Type Class::member → const Type &(const void *self)

Examples: problems/sparse-logistic-regression.cpp.

Definition at line 802 of file dl-problem.h.

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◆ unregister_functions()

void unregister_functions ( function_dict_t *& extra_functions )

inline

Cleans up the extra functions registered by register_function.

Note: This does not need to be called for the functions returned by the registration function, those functions will be cleaned up by alpaqa.; The alpaqa_problem_register_t and alpaqa_control_problem_register_t structs are part of the C API and do not automatically clean up their resources when destroyed, you have to do it manually by calling this function.

Definition at line 813 of file dl-problem.h.

◆ operator+=() [11/12]

InnerStatsAccumulator< lbfgsb::LBFGSBStats > & operator+=	(	InnerStatsAccumulator< lbfgsb::LBFGSBStats > &	acc,
		const lbfgsb::LBFGSBStats &	s )

inline

Definition at line 136 of file lbfgsb-adapter.hpp.

◆ operator+=() [12/12]

template<Config Conf>

InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > > & operator+=	(	InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > > &	acc,
		const lbfgspp::LBFGSBStats< Conf > &	s )

Definition at line 102 of file lbfgsb-adapter.hpp.

◆ build_qpalm_problem()

OwningQPALMData build_qpalm_problem ( const TypeErasedProblem< EigenConfigd > & problem )

Definition at line 29 of file qpalm-adapter.cpp.

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Variable Documentation

◆ is_config_v

template<class T>

bool is_config_v = is_config<T>::value

inlineconstexpr

Definition at line 17 of file config.hpp.

◆ is_eigen_config_v

template<class T>

bool is_eigen_config_v = is_eigen_config<T>::value

inlineconstexpr

Definition at line 25 of file config.hpp.

◆ inf

template<Config Conf>

const auto inf = std::numeric_limits<real_t<Conf>>::infinity()

constexpr

Examples: C++/CasADi/Rosenbrock/main.cpp, C++/CustomCppProblem/main.cpp, C++/DLProblem/main.cpp, and C++/FortranProblem/main.cpp.

Definition at line 112 of file config.hpp.

◆ NaN

template<Config Conf>

const auto NaN = std::numeric_limits<real_t<Conf>>::quiet_NaN()

constexpr

Definition at line 114 of file config.hpp.

◆ null_vec

template<Config Conf>

const rvec<Conf> null_vec = mvec<Conf>{nullptr, 0}

inline

Global empty vector for convenience.

Definition at line 193 of file config.hpp.

◆ null_indexvec

template<Config Conf>

const rindexvec<Conf> null_indexvec = mindexvec<Conf>{nullptr, 0}

inline

Global empty index vector for convenience.

Definition at line 196 of file config.hpp.

Namespaces

Classes

Concepts

Typedefs

Enumerations

Functions

Variables

Class Documentation

◆ alpaqa::FISTAStats

◆ alpaqa::InnerSolveOptions

◆ alpaqa::InnerStatsAccumulator

◆ alpaqa::InnerStatsAccumulator< FISTAStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< lbfgsb::LBFGSBStats >

◆ alpaqa::InnerStatsAccumulator< lbfgspp::LBFGSBStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< PANOCOCPStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< PANOCStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< PANTRStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< WolfeStats< Conf > >

◆ alpaqa::InnerStatsAccumulator< ZeroFPRStats< Conf > >

◆ alpaqa::OCPDim

◆ alpaqa::PANOCOCPStats

◆ alpaqa::PANOCStats

◆ alpaqa::PANTRStats

◆ alpaqa::SerializedCasADiFunctions

◆ alpaqa::WolfeStats

◆ alpaqa::ZeroFPRStats

Typedef Documentation

◆ DefaultConfig

◆ real_t

◆ cplx_t

◆ vec

◆ mvec

◆ cmvec

◆ rvec

◆ crvec

◆ mat

◆ mmat

◆ cmmat

◆ rmat

◆ crmat

◆ cmat

◆ mcmat

◆ cmcmat

◆ rcmat

◆ crcmat

◆ length_t

◆ index_t

◆ indexvec

◆ rindexvec

◆ crindexvec

◆ mindexvec

◆ cmindexvec

◆ casadi_int

◆ casadi_real

◆ function_dict_t

◆ problem_register_t

◆ control_problem_register_t

◆ problem_functions_t

◆ control_problem_functions_t

Enumeration Type Documentation

◆ LBFGSStepSize

◆ PANOCStopCrit

◆ SolverStatus

Function Documentation

◆ minimize_update_anderson()

◆ enum_name() [1/2]

◆ const_or_mut_rvec()

◆ operator+=() [1/12]

◆ enum_name() [2/2]

◆ operator<<() [1/4]

◆ operator+=() [2/12]

◆ operator+=() [3/12]

◆ operator+=() [4/12]

◆ operator+=() [5/12]

◆ operator+=() [6/12]

◆ compute_kkt_error()

◆ operator<<() [2/4]

◆ operator+=() [7/12]

◆ operator+=() [8/12]

◆ operator+() [1/2]