Namespaces
	detail

	problems

	vec_util

Classes
struct	ALMParams
	Parameters for the Augmented Lagrangian solver. More...

class	ALMSolver
	Augmented Lagrangian Method solver. More...

class	ALMSolverFull

class	AndersonAccel
	Anderson Acceleration. More...

class	AtomicStopSignal

struct	Box

struct	CircularIndexIterator

struct	CircularIndices

class	CircularRange

struct	EvalCounter

struct	EvalCounterFull

struct	GAAPGAParams

struct	GAAPGAProgressInfo

class	GAAPGASolver
	Guarded Anderson Accelerated Proximal Gradient Algorithm. More...

struct	InnerStatsAccumulator

struct	InnerStatsAccumulator< GAAPGASolver::Stats >

struct	InnerStatsAccumulator< LBFGSBStats >

struct	InnerStatsAccumulator< PANOCStats >

struct	InnerStatsAccumulator< PGASolver::Stats >

struct	InnerStatsAccumulator< PolymorphicInnerSolverWrapper::Stats >

struct	InnerStatsAccumulator< SecondOrderPANOCSolver::Stats >

struct	InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats >

class	LBFGS
	Limited memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm. More...

class	LBFGSBSolver
	Box-constrained LBFGS solver for ALM. More...

struct	LBFGSBStats

struct	LBFGSParams
	Parameters for the LBFGS and SpecializedLBFGS classes. More...

struct	LBFGSParams.cbfgs

class	LBFGSSolver
	Unconstrained LBFGS solver for ALM. More...

class	LimitedMemoryQR
	Incremental QR factorization using modified Gram-Schmidt with reorthogonalization. More...

struct	LipschitzEstimateParams

struct	PANOCDirection

struct	PANOCDirection< AndersonAccel >

struct	PANOCDirection< LBFGS >

struct	PANOCDirection< PolymorphicPANOCDirectionBase >

struct	PANOCDirection< SpecializedLBFGS >

struct	PANOCFullProgressInfo

struct	PANOCParams
	Tuning parameters for the PANOC algorithm. More...

struct	PANOCProgressInfo

class	PANOCSolver
	PANOC solver for ALM. More...

class	PANOCSolverFull

struct	PANOCStats

struct	PGAParams

struct	PGAProgressInfo

class	PGASolver
	Standard Proximal Gradient Algorithm without any bells and whistles. More...

class	PolymorphicInnerSolver

class	PolymorphicInnerSolverBase

class	PolymorphicInnerSolverStatsAccumulatorBase

class	PolymorphicInnerSolverStatsBase

class	PolymorphicInnerSolverTrampoline

struct	PolymorphicInnerSolverWrapper

class	PolymorphicPANOCDirection

class	PolymorphicPANOCDirectionBase

class	PolymorphicPANOCDirectionTrampoline

class	Problem
	Problem description for minimization problems. More...

class	ProblemFull
	Problem description for minimization problems. More...

class	ProblemFullWithParam

class	ProblemOnlyD
	Moves the state constraints in the set C to the set D, resulting in an unconstraint inner problem. More...

class	ProblemWithCounters

class	ProblemWithParam

struct	ReverseCircularIndexIterator

class	ReverseCircularRange

struct	SecondOrderPANOCParams
	Tuning parameters for the second order PANOC algorithm. More...

class	SecondOrderPANOCSolver
	Second order PANOC solver for ALM. More...

class	SpecializedLBFGS
	Limited memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm that can handle updates of the γ parameter. More...

struct	StructuredPANOCLBFGSParams
	Tuning parameters for the second order PANOC algorithm. More...

struct	StructuredPANOCLBFGSProgressInfo

class	StructuredPANOCLBFGSSolver
	Second order PANOC solver for ALM. More...

class	vec_allocator

Typedefs
using	real_t = double
	Default floating point type. More...

using	realvec = Eigen::Matrix< real_t, Eigen::Dynamic, 1 >
	Default type for floating point vectors. More...

using	realmat = Eigen::Matrix< real_t, Eigen::Dynamic, Eigen::Dynamic >
	Default type for floating point matrices. More...

using	vec = realvec
	Default type for vectors. More...

using	rvec = Eigen::Ref< vec >
	Default type for mutable references to vectors. More...

using	crvec = Eigen::Ref< const vec >
	Default type for immutable references to vectors. More...

using	mat = realmat
	Default type for matrices. More...

using	rmat = Eigen::Ref< mat >
	Default type for mutable references to matrices. More...

using	crmat = Eigen::Ref< const mat >
	Default type for immutable references to matrices. More...

using	PolymorphicPGASolver = PolymorphicInnerSolver< PGASolver >

using	PolymorphicGAAPGASolver = PolymorphicInnerSolver< GAAPGASolver >

using	PolymorphicPANOCSolver = PolymorphicInnerSolver< PANOCSolver< PolymorphicPANOCDirectionBase > >

using	PolymorphicPANOCSolverFull = PolymorphicInnerSolver< PANOCSolverFull< PolymorphicPANOCDirectionBase > >

using	PolymorphicStructuredPANOCLBFGSSolver = PolymorphicInnerSolver< StructuredPANOCLBFGSSolver >

using	PolymorphicALMSolver = ALMSolver< PolymorphicInnerSolverWrapper >

using	PolymorphicLBFGSDirection = PolymorphicPANOCDirection< LBFGS >

Enumerations
enum	LBFGSStepSize { BasedOnGradientStepSize = 0, BasedOnCurvature = 1 }
	Which method to use to select the L-BFGS step size. More...

enum	PANOCStopCrit { ApproxKKT = 0, ProjGradNorm, ProjGradUnitNorm, FPRNorm }

enum	SolverStatus { Unknown = 0, Converged, MaxTime, MaxIter, NotFinite, NoProgress, Interrupted }
	Exit status of a numerical solver such as ALM or PANOC. More...

Functions
const char *	enum_name (PANOCStopCrit s)

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

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

InnerStatsAccumulator< SecondOrderPANOCSolver::Stats > &	operator+= (InnerStatsAccumulator< SecondOrderPANOCSolver::Stats > &acc, const SecondOrderPANOCSolver::Stats &s)

InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats > &	operator+= (InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats > &acc, const StructuredPANOCLBFGSSolver::Stats &s)

void	minimize_update_anderson (LimitedMemoryQR &qr, rmat G, crvec rₖ, crvec rₖ₋₁, crvec gₖ, rvec γ_LS, rvec xₖ_aa)
	Solve one step of Anderson acceleration to find a fixed point of a function g(x): More...

InnerStatsAccumulator< GAAPGASolver::Stats > &	operator+= (InnerStatsAccumulator< GAAPGASolver::Stats > &acc, const GAAPGASolver::Stats &s)

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

InnerStatsAccumulator< PGASolver::Stats > &	operator+= (InnerStatsAccumulator< PGASolver::Stats > &acc, const PGASolver::Stats &s)

std::function< pa::Problem::f_sig >	load_CasADi_objective (const std::string &so_name, const std::string &fun_name="f")
	Load an objective function generated by CasADi. More...

std::function< pa::Problem::grad_f_sig >	load_CasADi_gradient_objective (const std::string &so_name, const std::string &fun_name="grad_f")
	Load the gradient of an objective function generated by CasADi. More...

std::function< pa::Problem::g_sig >	load_CasADi_constraints (const std::string &so_name, const std::string &fun_name="g")
	Load a constraint function generated by CasADi. More...

std::function< pa::Problem::grad_g_prod_sig >	load_CasADi_gradient_constraints_prod (const std::string &so_name, const std::string &fun_name="grad_g")
	Load the gradient-vector product of a constraint function generated by CasADi. More...

std::function< pa::Problem::hess_L_sig >	load_CasADi_hessian_lagrangian (const std::string &so_name, const std::string &fun_name="hess_L")
	Load the Hessian of a Lagrangian function generated by CasADi. More...

std::function< pa::Problem::hess_L_prod_sig >	load_CasADi_hessian_lagrangian_prod (const std::string &so_name, const std::string &fun_name="hess_L_prod")
	Load the Hessian-vector product of a Lagrangian function generated by CasADi. More...

pa::Problem	load_CasADi_problem (const std::string &filename, unsigned n, unsigned m, bool second_order=false)
	Load a problem generated by CasADi (without parameters). More...

pa::ProblemWithParam	load_CasADi_problem_with_param (const std::string &filename, unsigned n, unsigned m, bool second_order=false)
	Load a problem generated by CasADi (with parameters). More...

pa::ProblemFull	load_CasADi_problem_full (const char *filename, unsigned n, unsigned m1, unsigned m2, bool second_order=false)
	Load a problem generated by CasADi (without parameters). More...

pa::ProblemFullWithParam	load_CasADi_problem_full_with_param (const char *filename, unsigned n, unsigned m1, unsigned m2, bool second_order=false)
	Load a problem generated by CasADi (with parameters). More...

template<class ObjFunT , class ObjGradFunT , class DirectionT >
PANOCStats	panoc_impl (ObjFunT &ψ, ObjGradFunT &grad_ψ, const Box &C, rvec x, real_t ε, const PANOCParams &params, vec_allocator &alloc, DirectionT &direction_provider)

template<class DirectionProviderT = LBFGS, class ObjFunT , class ObjGradFunT >
PANOCStats	panoc (ObjFunT &ψ, ObjGradFunT &grad_ψ, const Box &C, rvec x, real_t ε, const PANOCParams &params, PANOCDirection< DirectionProviderT > direction, vec_allocator &alloc)

template<class DirectionProviderT = LBFGS, class ObjFunT , class ObjGradFunT >
PANOCStats	panoc (ObjFunT &ψ, ObjGradFunT &grad_ψ, const Box &C, rvec x, real_t ε, const PANOCParams &params, PANOCDirection< DirectionProviderT > direction)

template<class Vec >
auto	project (const Vec &v, const Box &box)
	Project a vector onto a box. More...

template<class Vec >
auto	projecting_difference (const Vec &v, const Box &box)
	Get the difference between the given vector and its projection. More...

real_t	dist_squared (crvec v, const Box &box)
	Get the distance squared between the given vector and its projection. More...

real_t	dist_squared (crvec v, const Box &box, crvec Σ)
	Get the distance squared between the given vector and its projection in the Σ norm. More...

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

EvalCounter	operator+ (EvalCounter a, EvalCounter b)

EvalCounterFull &	operator+= (EvalCounterFull &a, EvalCounterFull b)

EvalCounterFull	operator+ (EvalCounterFull a, EvalCounterFull b)

template<class InnerSolver >
auto	InnerSolverCallWrapper ()

template<class InnerSolver >
auto	InnerSolverFullCallWrapper ()

InnerStatsAccumulator< PolymorphicInnerSolverWrapper::Stats > &	operator+= (InnerStatsAccumulator< PolymorphicInnerSolverWrapper::Stats > &acc, const PolymorphicInnerSolverWrapper::Stats &s)

py::dict	stats_to_dict (const PANOCStats &s)

py::dict	stats_to_dict (const InnerStatsAccumulator< PANOCStats > &s)

py::dict	stats_to_dict (const StructuredPANOCLBFGSSolver::Stats &s)

py::dict	stats_to_dict (const PGASolver::Stats &s)

py::dict	stats_to_dict (const GAAPGASolver::Stats &s)

py::dict	stats_to_dict (const InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats > &s)

py::dict	stats_to_dict (const InnerStatsAccumulator< PGASolver::Stats > &s)

py::dict	stats_to_dict (const InnerStatsAccumulator< GAAPGASolver::Stats > &s)

py::dict	stats_to_dict (const PolymorphicALMSolver::Stats &s)

template<class InnerSolver >
py::dict	stats_to_dict (typename pa::ALMSolverFull< PANOCSolverFull<>>::Stats &s)

const char *	enum_name (SolverStatus s)

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

Variables
constexpr size_t	panoc_min_alloc_size = 10

constexpr real_t	inf = std::numeric_limits<real_t>::infinity()
	\( \infty \) More...

constexpr real_t	NaN = std::numeric_limits<real_t>::quiet_NaN()
	Not a number. More...

Class Documentation

◆ pa::ALMParams

struct pa::ALMParams

Collaboration diagram for ALMParams:

Class Members
real_t	ε	Primal tolerance.
real_t	δ	Dual tolerance.
real_t	Δ	Factor used in updating the penalty parameters.
real_t	Δ_lower	Factor to reduce ALMParams::Δ when inner convergence fails.
real_t	Σ₀	Initial penalty parameter. When set to zero (which is the default), it is computed automatically, based on the constraint violation in the starting point and the parameter ALMParams::σ₀.
real_t	σ₀	Initial penalty parameter factor. Active if ALMParams::Σ₀ is set to zero.
real_t	Σ₀_lower	Factor to reduce the initial penalty factor by if convergence fails in in the first iteration.
real_t	ε₀	Initial primal tolerance.
real_t	ε₀_increase	Factor to increase the initial primal tolerance if convergence fails in the first iteration.
real_t	ρ	Update factor for primal tolerance.
real_t	ρ_increase	Factor to increase the primal tolerance update factor by if convergence fails.
real_t	θ	Error tolerance for penalty increase.
real_t	M	Lagrange multiplier bound.
real_t	Σ_max	Maximum penalty factor.
real_t	Σ_min	Minimum penalty factor (used during initialization).
unsigned int	max_iter	Maximum number of outer ALM iterations.
microseconds	max_time	Maximum duration.
unsigned	max_num_initial_retries	How many times can the initial penalty ALMParams::Σ₀ or ALMParams::σ₀ and the initial primal tolerance ALMParams::ε₀ be reduced.
unsigned	max_num_retries	How many times can the penalty update factor ALMParams::Δ and the primal tolerance factor ALMParams::ρ be reduced.
unsigned	max_total_num_retries	Combined limit for ALMParams::max_num_initial_retries and ALMParams::max_num_retries.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
bool	preconditioning	Apply preconditioning to the problem, based on the gradients in the starting point.
bool	single_penalty_factor	Use one penalty factor for all m constraints.

◆ pa::Box

struct pa::Box

Collaboration diagram for Box:

Class Members
vec	upperbound
vec	lowerbound

◆ pa::GAAPGAParams

struct pa::GAAPGAParams

Collaboration diagram for GAAPGAParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	limitedqr_mem	Length of the history to keep in the limited-memory QR algorithm.
unsigned	max_iter	Maximum number of inner iterations.
microseconds	max_time	Maximum duration.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
PANOCStopCrit	stop_crit	What stopping criterion to use.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor
unsigned	max_no_progress	Maximum number of iterations without any progress before giving up.
bool	full_flush_on_γ_change

◆ pa::GAAPGAProgressInfo

struct pa::GAAPGAProgressInfo

Collaboration diagram for GAAPGAProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	ε
crvec	Σ
crvec	y
const Problem &	problem
const GAAPGAParams &	params

◆ pa::InnerStatsAccumulator

struct pa::InnerStatsAccumulator

Collaboration diagram for InnerStatsAccumulator< InnerSolverStats >:

◆ pa::InnerStatsAccumulator< GAAPGASolver::Stats >

struct pa::InnerStatsAccumulator< GAAPGASolver::Stats >

Collaboration diagram for InnerStatsAccumulator< GAAPGASolver::Stats >:

Class Members
microseconds	elapsed_time
unsigned	iterations
unsigned	accelerated_steps_accepted

◆ pa::InnerStatsAccumulator< LBFGSBStats >

struct pa::InnerStatsAccumulator< LBFGSBStats >

Collaboration diagram for InnerStatsAccumulator< LBFGSBStats >:

Class Members
microseconds	elapsed_time
unsigned	iterations

◆ pa::InnerStatsAccumulator< PANOCStats >

struct pa::InnerStatsAccumulator< PANOCStats >

Collaboration diagram for InnerStatsAccumulator< PANOCStats >:

Class Members
microseconds	elapsed_time
unsigned	iterations
unsigned	linesearch_failures
unsigned	lbfgs_failures
unsigned	lbfgs_rejected
unsigned	τ_1_accepted
unsigned	count_τ
real_t	sum_τ

◆ pa::InnerStatsAccumulator< PGASolver::Stats >

struct pa::InnerStatsAccumulator< PGASolver::Stats >

Collaboration diagram for InnerStatsAccumulator< PGASolver::Stats >:

Class Members
microseconds	elapsed_time
unsigned	iterations

◆ pa::InnerStatsAccumulator< SecondOrderPANOCSolver::Stats >

struct pa::InnerStatsAccumulator< SecondOrderPANOCSolver::Stats >

Collaboration diagram for InnerStatsAccumulator< SecondOrderPANOCSolver::Stats >:

Class Members
microseconds	elapsed_time
unsigned	iterations
unsigned	newton_failures
unsigned	linesearch_failures
unsigned	τ_1_accepted
unsigned	count_τ
real_t	sum_τ

◆ pa::InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats >

struct pa::InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats >

Collaboration diagram for InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats >:

Class Members
microseconds	elapsed_time
unsigned	iterations
unsigned	linesearch_failures
unsigned	lbfgs_failures
unsigned	lbfgs_rejected
unsigned	τ_1_accepted
unsigned	count_τ
real_t	sum_τ

◆ pa::LBFGSBStats

struct pa::LBFGSBStats

Collaboration diagram for LBFGSBStats:

Class Members
SolverStatus	status
real_t	ε
microseconds	elapsed_time
unsigned	iterations

◆ pa::LBFGSParams

struct pa::LBFGSParams

Collaboration diagram for LBFGSParams:

Class Members

unsigned memory Length of the history to keep.

struct LBFGSParams

cbfgs

Parameters in the cautious BFGS update condition.

\[ \frac{y^\top s}{s^\top s} \ge \epsilon \| g \|^\alpha \]

See also: https://epubs.siam.org/doi/10.1137/S1052623499354242

bool rescale_when_γ_changes

◆ pa::LBFGSParams.cbfgs

struct pa::LBFGSParams.cbfgs

Collaboration diagram for LBFGSParams.cbfgs:

Class Members
real_t	α
real_t	ϵ

◆ pa::LipschitzEstimateParams

struct pa::LipschitzEstimateParams

Collaboration diagram for LipschitzEstimateParams:

Class Members
real_t	L₀	Initial estimate of the Lipschitz constant of ∇ψ(x)
real_t	ε	Relative step size for initial finite difference Lipschitz estimate.
real_t	δ	Minimum step size for initial finite difference Lipschitz estimate.
real_t	Lγ_factor	Factor that relates step size γ and Lipschitz constant.

◆ pa::PANOCFullProgressInfo

struct pa::PANOCFullProgressInfo

Collaboration diagram for PANOCFullProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	φγ
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	τ
real_t	ε
crvec	Σ1
crvec	Σ2
crvec	y
const ProblemFull &	problem
const PANOCParams &	params

◆ pa::PANOCParams

struct pa::PANOCParams

Collaboration diagram for PANOCParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	max_iter	Maximum number of inner PANOC iterations.
microseconds	max_time	Maximum duration.
real_t	τ_min	Minimum weight factor between Newton step and projected gradient step.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
PANOCStopCrit	stop_crit	What stopping criterion to use.
unsigned	max_no_progress	Maximum number of iterations without any progress before giving up.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor
bool	update_lipschitz_in_linesearch
bool	alternative_linesearch_cond
LBFGSStepSize	lbfgs_stepsize

◆ pa::PANOCProgressInfo

struct pa::PANOCProgressInfo

Collaboration diagram for PANOCProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	φγ
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	τ
real_t	ε
crvec	Σ
crvec	y
const Problem &	problem
const PANOCParams &	params

◆ pa::PANOCStats

struct pa::PANOCStats

Collaboration diagram for PANOCStats:

Class Members
SolverStatus	status
real_t	ε
microseconds	elapsed_time
unsigned	iterations
unsigned	linesearch_failures
unsigned	lbfgs_failures
unsigned	lbfgs_rejected
unsigned	τ_1_accepted
unsigned	count_τ
real_t	sum_τ

◆ pa::PGAParams

struct pa::PGAParams

Collaboration diagram for PGAParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	max_iter	Maximum number of inner iterations.
microseconds	max_time	Maximum duration.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
PANOCStopCrit	stop_crit	What stop criterion to use.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor

◆ pa::PGAProgressInfo

struct pa::PGAProgressInfo

Collaboration diagram for PGAProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	ε
crvec	Σ
crvec	y
const Problem &	problem
const PGAParams &	params

◆ pa::SecondOrderPANOCParams

struct pa::SecondOrderPANOCParams

Collaboration diagram for SecondOrderPANOCParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	max_iter	Maximum number of inner PANOC iterations.
microseconds	max_time	Maximum duration.
real_t	τ_min	Minimum weight factor between Newton step and projected gradient step.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
PANOCStopCrit	stop_crit	What stopping criterion to use.
unsigned	max_no_progress	Maximum number of iterations without any progress before giving up.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor
bool	update_lipschitz_in_linesearch
bool	alternative_linesearch_cond

◆ pa::StructuredPANOCLBFGSParams

struct pa::StructuredPANOCLBFGSParams

Collaboration diagram for StructuredPANOCLBFGSParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	max_iter	Maximum number of inner PANOC iterations.
microseconds	max_time	Maximum duration.
real_t	τ_min	Minimum weight factor between Newton step and projected gradient step.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
real_t	nonmonotone_linesearch	Factor used in update for exponentially weighted nonmonotone line search. Zero means monotone line search.
PANOCStopCrit	stop_crit	What stopping criterion to use.
unsigned	max_no_progress	Maximum number of iterations without any progress before giving up.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor
bool	update_lipschitz_in_linesearch
bool	alternative_linesearch_cond
bool	hessian_vec_finited_differences
bool	full_augmented_hessian
LBFGSStepSize	lbfgs_stepsize

◆ pa::StructuredPANOCLBFGSProgressInfo

struct pa::StructuredPANOCLBFGSProgressInfo

Collaboration diagram for StructuredPANOCLBFGSProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	φγ
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	τ
real_t	ε
crvec	Σ
crvec	y
const Problem &	problem
const StructuredPANOCLBFGSParams &	params

Typedef Documentation

◆ real_t

using real_t = double

Default floating point type.

Definition at line 8 of file vec.hpp.

◆ realvec

using realvec = Eigen::Matrix<real_t, Eigen::Dynamic, 1>

Default type for floating point vectors.

Definition at line 10 of file vec.hpp.

◆ realmat

using realmat = Eigen::Matrix<real_t, Eigen::Dynamic, Eigen::Dynamic>

Default type for floating point matrices.

Definition at line 12 of file vec.hpp.

◆ vec

using vec = realvec

Default type for vectors.

Examples: CasADi/Rosenbrock/main.cpp, and CUTEst/Rosenbrock/main.cpp.

Definition at line 14 of file vec.hpp.

◆ rvec

using rvec = Eigen::Ref<vec>

Default type for mutable references to vectors.

Definition at line 16 of file vec.hpp.

◆ crvec

using crvec = Eigen::Ref<const vec>

Default type for immutable references to vectors.

Definition at line 18 of file vec.hpp.

◆ mat

using mat = realmat

Default type for matrices.

Definition at line 20 of file vec.hpp.

◆ rmat

using rmat = Eigen::Ref<mat>

Default type for mutable references to matrices.

Definition at line 22 of file vec.hpp.

◆ crmat

using crmat = Eigen::Ref<const mat>

Default type for immutable references to matrices.

Definition at line 24 of file vec.hpp.

◆ PolymorphicPGASolver

using PolymorphicPGASolver = PolymorphicInnerSolver<PGASolver>

Definition at line 468 of file polymorphic-inner-solver.hpp.

◆ PolymorphicGAAPGASolver

using PolymorphicGAAPGASolver = PolymorphicInnerSolver<GAAPGASolver>

Definition at line 469 of file polymorphic-inner-solver.hpp.

◆ PolymorphicPANOCSolver

using PolymorphicPANOCSolver = PolymorphicInnerSolver<PANOCSolver<PolymorphicPANOCDirectionBase> >

Definition at line 470 of file polymorphic-inner-solver.hpp.

◆ PolymorphicPANOCSolverFull

using PolymorphicPANOCSolverFull = PolymorphicInnerSolver<PANOCSolverFull<PolymorphicPANOCDirectionBase> >

Definition at line 472 of file polymorphic-inner-solver.hpp.

◆ PolymorphicStructuredPANOCLBFGSSolver

using PolymorphicStructuredPANOCLBFGSSolver = PolymorphicInnerSolver<StructuredPANOCLBFGSSolver>

Definition at line 474 of file polymorphic-inner-solver.hpp.

◆ PolymorphicALMSolver

using PolymorphicALMSolver = ALMSolver<PolymorphicInnerSolverWrapper>

Definition at line 477 of file polymorphic-inner-solver.hpp.

◆ PolymorphicLBFGSDirection

using PolymorphicLBFGSDirection = PolymorphicPANOCDirection<LBFGS>

Definition at line 128 of file polymorphic-panoc-direction.hpp.

Enumeration Type Documentation

◆ LBFGSStepSize

enum LBFGSStepSize

strong

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

Enumerator
BasedOnGradientStepSize
BasedOnCurvature

Definition at line 6 of file lbfgs-stepsize.hpp.

◆ PANOCStopCrit

enum PANOCStopCrit

strong

Enumerator
ApproxKKT	Find a ε-approximate KKT point.
ProjGradNorm	∞-norm of the projected gradient with step size γ
ProjGradUnitNorm	∞-norm of the projected gradient with unit step size
FPRNorm	∞-norm of fixed point residual

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

◆ SolverStatus

enum SolverStatus

strong

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

Enumerator
Unknown	Initial value.
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.

Definition at line 7 of file solverstatus.hpp.

Function Documentation

◆ enum_name() [1/2]

const char* pa::enum_name ( PANOCStopCrit s )

inline

Definition at line 15 of file panoc-stop-crit.hpp.

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◆ operator<<() [1/2]

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

inline

Definition at line 25 of file panoc-stop-crit.hpp.

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◆ operator+=() [1/9]

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

inline

Definition at line 217 of file inner/decl/panoc.hpp.

◆ operator+=() [2/9]

InnerStatsAccumulator<SecondOrderPANOCSolver::Stats>& pa::operator+=	(	InnerStatsAccumulator< SecondOrderPANOCSolver::Stats > &	acc,
		const SecondOrderPANOCSolver::Stats &	s
	)

inline

Definition at line 127 of file decl/second-order-panoc.hpp.

◆ operator+=() [3/9]

InnerStatsAccumulator<StructuredPANOCLBFGSSolver::Stats>& pa::operator+=	(	InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats > &	acc,
		const StructuredPANOCLBFGSSolver::Stats &	s
	)

inline

Definition at line 147 of file decl/structured-panoc-lbfgs.hpp.

◆ minimize_update_anderson()

void pa::minimize_update_anderson	(	LimitedMemoryQR &	qr,
		rmat	G,
		crvec	rₖ,
		crvec	rₖ₋₁,
		crvec	gₖ,
		rvec	γ_LS,
		rvec	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.

\[ \begin{aligned} \mathcal{R}_k &= \begin{pmatrix} \Delta r_{k-m_k} & \dots & \Delta r_{k-1} \end{pmatrix} \in \mathbb{R}^{n\times m_k} \\ \Delta r_i &= r_{i+1} - r_i \\ r_i &= g_i - x_i \\ g_i &= g(x_i) \\ \DeclareMathOperator*{\argmin}{argmin} \gamma_\text{LS} &= \argmin_\gamma \left\| \mathcal{R}_k \gamma - r_k \right\|_2 \\ \alpha_i &= \begin{cases} \gamma_\text{LS}[0] & i = 0 \\ \gamma_\text{LS}[i] - \gamma_\text{LS}[i-1] & 0 < i < m_k \\ 1 - \gamma_\text{LS}[m_k - 1] & i = m_k \end{cases} \\ x_{k+1} &= \sum_{i=0}^{m_k} \alpha_i\,g_i \end{aligned} \]

Definition at line 30 of file anderson-helpers.hpp.

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◆ operator+=() [4/9]

InnerStatsAccumulator<GAAPGASolver::Stats>& pa::operator+=	(	InnerStatsAccumulator< GAAPGASolver::Stats > &	acc,
		const GAAPGASolver::Stats &	s
	)

inline

Definition at line 361 of file guarded-aa-pga.hpp.

◆ operator+=() [5/9]

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

inline

Definition at line 193 of file lbfgspp.hpp.

◆ operator+=() [6/9]

InnerStatsAccumulator<PGASolver::Stats>& pa::operator+=	(	InnerStatsAccumulator< PGASolver::Stats > &	acc,
		const PGASolver::Stats &	s
	)

inline

Definition at line 283 of file pga.hpp.

◆ panoc_impl()

PANOCStats pa::panoc_impl	(	ObjFunT &	ψ,
		ObjGradFunT &	grad_ψ,
		const Box &	C,
		rvec	x,
		real_t	ε,
		const PANOCParams &	params,
		vec_allocator &	alloc,
		DirectionT &	direction_provider
	)

inline

Definition at line 157 of file standalone/panoc.hpp.

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◆ panoc() [1/2]

PANOCStats pa::panoc	(	ObjFunT &	ψ,
		ObjGradFunT &	grad_ψ,
		const Box &	C,
		rvec	x,
		real_t	ε,
		const PANOCParams &	params,
		PANOCDirection< DirectionProviderT >	direction,
		vec_allocator &	alloc
	)

Definition at line 370 of file standalone/panoc.hpp.

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◆ panoc() [2/2]

PANOCStats pa::panoc	(	ObjFunT &	ψ,
		ObjGradFunT &	grad_ψ,
		const Box &	C,
		rvec	x,
		real_t	ε,
		const PANOCParams &	params,
		PANOCDirection< DirectionProviderT >	direction
	)

Definition at line 385 of file standalone/panoc.hpp.

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◆ project()

auto pa::project	(	const Vec &	v,
		const Box &	box
	)

inline

Project a vector onto a box.

\[ \Pi_C(v) \]

Parameters

[in]	v	The vector to project
[in]	box	The box to project onto

Definition at line 15 of file box.hpp.

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◆ projecting_difference()

auto pa::projecting_difference	(	const Vec &	v,
		const Box &	box
	)

inline

Get the difference between the given vector and its projection.

\[ v - \Pi_C(v) \]

Warning: Beware catastrophic cancellation!

Parameters

[in]	v	The vector to project
[in]	box	The box to project onto

Definition at line 28 of file box.hpp.

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◆ dist_squared() [1/2]

real_t pa::dist_squared	(	crvec	v,
		const Box &	box
	)

inline

Get the distance squared between the given vector and its projection.

\[ \left\| v - \Pi_C(v) \right\|_2^2 \]

Warning: Beware catastrophic cancellation!

Parameters

[in]	v	The vector to project
[in]	box	The box to project onto

Definition at line 37 of file box.hpp.

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◆ dist_squared() [2/2]

real_t pa::dist_squared	(	crvec	v,
		const Box &	box,
		crvec	Σ
	)

inline

Get the distance squared between the given vector and its projection in the Σ norm.

\[ \left\| v - \Pi_C(v) \right\|_\Sigma^2 = \left(v - \Pi_C(v)\right)^\top \Sigma \left(v - \Pi_C(v)\right) \]

Warning: Beware catastrophic cancellation!

Parameters

[in]	v	The vector to project
[in]	box	The box to project onto
[in]	Σ	Diagonal matrix defining norm

Definition at line 48 of file box.hpp.

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◆ operator+=() [7/9]

EvalCounter& pa::operator+=	(	EvalCounter &	a,
		EvalCounter	b
	)

inline

Definition at line 149 of file include/panoc-alm/util/problem.hpp.

◆ operator+() [1/2]

EvalCounter pa::operator+	(	EvalCounter	a,
		EvalCounter	b
	)

inline

Definition at line 160 of file include/panoc-alm/util/problem.hpp.

◆ operator+=() [8/9]

EvalCounterFull& pa::operator+=	(	EvalCounterFull &	a,
		EvalCounterFull	b
	)

inline

Definition at line 383 of file include/panoc-alm/util/problem.hpp.

◆ operator+() [2/2]

EvalCounterFull pa::operator+	(	EvalCounterFull	a,
		EvalCounterFull	b
	)

inline

Definition at line 394 of file include/panoc-alm/util/problem.hpp.

◆ InnerSolverCallWrapper()

auto pa::InnerSolverCallWrapper ( )

Definition at line 20 of file polymorphic-inner-solver.hpp.

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◆ InnerSolverFullCallWrapper()

auto pa::InnerSolverFullCallWrapper ( )

Definition at line 32 of file polymorphic-inner-solver.hpp.

◆ operator+=() [9/9]

InnerStatsAccumulator<PolymorphicInnerSolverWrapper::Stats>& pa::operator+=	(	InnerStatsAccumulator< PolymorphicInnerSolverWrapper::Stats > &	acc,
		const PolymorphicInnerSolverWrapper::Stats &	s
	)

inline

Definition at line 165 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [1/10]

py::dict pa::stats_to_dict ( const PANOCStats & s )

inline

Definition at line 205 of file polymorphic-inner-solver.hpp.

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◆ stats_to_dict() [2/10]

py::dict pa::stats_to_dict ( const InnerStatsAccumulator< PANOCStats > & s )

inline

Definition at line 221 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [3/10]

py::dict pa::stats_to_dict ( const StructuredPANOCLBFGSSolver::Stats & s )

inline

Definition at line 235 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [4/10]

py::dict pa::stats_to_dict ( const PGASolver::Stats & s )

inline

Definition at line 251 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [5/10]

py::dict pa::stats_to_dict ( const GAAPGASolver::Stats & s )

inline

Definition at line 261 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [6/10]

py::dict pa::stats_to_dict ( const InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats > & s )

inline

Definition at line 272 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [7/10]

py::dict pa::stats_to_dict ( const InnerStatsAccumulator< PGASolver::Stats > & s )

inline

Definition at line 288 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [8/10]

py::dict pa::stats_to_dict ( const InnerStatsAccumulator< GAAPGASolver::Stats > & s )

inline

Definition at line 297 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [9/10]

py::dict pa::stats_to_dict ( const PolymorphicALMSolver::Stats & s )

inline

Definition at line 479 of file polymorphic-inner-solver.hpp.

◆ stats_to_dict() [10/10]

py::dict pa::stats_to_dict ( typename pa::ALMSolverFull< PANOCSolverFull<>>::Stats & s )

inline

Definition at line 497 of file polymorphic-inner-solver.hpp.

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◆ enum_name() [2/2]

const char* pa::enum_name ( SolverStatus s )

Definition at line 8 of file solverstatus.cpp.

◆ operator<<() [2/2]

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

Definition at line 22 of file solverstatus.cpp.

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Variable Documentation

◆ panoc_min_alloc_size

constexpr size_t panoc_min_alloc_size = 10

constexpr

Definition at line 154 of file standalone/panoc.hpp.

◆ inf

constexpr real_t inf = std::numeric_limits<real_t>::infinity()

constexpr

\( \infty \)

Examples: CasADi/Rosenbrock/main.cpp.

Definition at line 26 of file vec.hpp.

◆ NaN

constexpr real_t NaN = std::numeric_limits<real_t>::quiet_NaN()

constexpr

Not a number.

Definition at line 28 of file vec.hpp.

Namespaces

Classes

Typedefs

Enumerations

Functions

Variables

Class Documentation

◆ pa::ALMParams

◆ pa::Box

◆ pa::GAAPGAParams

◆ pa::GAAPGAProgressInfo

◆ pa::InnerStatsAccumulator

◆ pa::InnerStatsAccumulator< GAAPGASolver::Stats >

◆ pa::InnerStatsAccumulator< LBFGSBStats >

◆ pa::InnerStatsAccumulator< PANOCStats >

◆ pa::InnerStatsAccumulator< PGASolver::Stats >

◆ pa::InnerStatsAccumulator< SecondOrderPANOCSolver::Stats >

◆ pa::InnerStatsAccumulator< StructuredPANOCLBFGSSolver::Stats >

◆ pa::LBFGSBStats

◆ pa::LBFGSParams

◆ pa::LBFGSParams.cbfgs

◆ pa::LipschitzEstimateParams

◆ pa::PANOCFullProgressInfo

◆ pa::PANOCParams

◆ pa::PANOCProgressInfo

◆ pa::PANOCStats

◆ pa::PGAParams

◆ pa::PGAProgressInfo

◆ pa::SecondOrderPANOCParams

◆ pa::StructuredPANOCLBFGSParams

◆ pa::StructuredPANOCLBFGSProgressInfo

Typedef Documentation

◆ real_t

◆ realvec

◆ realmat

◆ vec

◆ rvec

◆ crvec

◆ mat

◆ rmat

◆ crmat

◆ PolymorphicPGASolver

◆ PolymorphicGAAPGASolver

◆ PolymorphicPANOCSolver

◆ PolymorphicPANOCSolverFull

◆ PolymorphicStructuredPANOCLBFGSSolver

◆ PolymorphicALMSolver

◆ PolymorphicLBFGSDirection

Enumeration Type Documentation

◆ LBFGSStepSize

◆ PANOCStopCrit

◆ SolverStatus

Function Documentation

◆ enum_name() [1/2]

◆ operator<<() [1/2]

◆ operator+=() [1/9]

◆ operator+=() [2/9]

◆ operator+=() [3/9]

◆ minimize_update_anderson()

◆ operator+=() [4/9]

◆ operator+=() [5/9]

◆ operator+=() [6/9]

◆ panoc_impl()

◆ panoc() [1/2]

◆ panoc() [2/2]

◆ project()

◆ projecting_difference()

◆ dist_squared() [1/2]

◆ dist_squared() [2/2]

◆ operator+=() [7/9]

◆ operator+() [1/2]

◆ operator+=() [8/9]

◆ operator+() [2/2]

◆ InnerSolverCallWrapper()

◆ InnerSolverFullCallWrapper()

◆ operator+=() [9/9]

◆ stats_to_dict() [1/10]

◆ stats_to_dict() [2/10]

◆ stats_to_dict() [3/10]

◆ stats_to_dict() [4/10]