#include <alpaqa/problem/functional-problem.hpp>

Detailed Description

template<Config Conf = DefaultConfig>
class alpaqa::FunctionalProblem< Conf >

Problem class that allows specifying the basic functions as C++ std::functions.

Definition at line 12 of file functional-problem.hpp.

Inheritance diagram for FunctionalProblem< Conf >:

Collaboration diagram for FunctionalProblem< Conf >:

Public Types
using	Box = alpaqa::Box< config_t >

Public Member Functions
real_t	eval_f (crvec x) const

void	eval_grad_f (crvec x, rvec grad_fx) const

void	eval_g (crvec x, rvec gx) const

void	eval_grad_g_prod (crvec x, crvec y, rvec grad_gxy) const

void	eval_grad_gi (crvec x, index_t i, rvec grad_gix) const

void	eval_hess_L_prod (crvec x, crvec y, real_t scale, crvec v, rvec Hv) const

void	eval_hess_ψ_prod (crvec x, crvec y, crvec Σ, real_t scale, crvec v, rvec Hv) const

void	eval_jac_g (crvec x, rvec J_values) const

void	eval_hess_L (crvec x, crvec y, real_t scale, rvec H_values) const

void	eval_hess_ψ (crvec x, crvec y, crvec Σ, real_t scale, rvec H_values) const

bool	provides_eval_grad_gi () const

bool	provides_eval_jac_g () const

bool	provides_eval_hess_L_prod () const

bool	provides_eval_hess_L () const

bool	provides_eval_hess_ψ_prod () const

bool	provides_eval_hess_ψ () const

std::string	get_name () const

	FunctionalProblem (const FunctionalProblem &)=default

FunctionalProblem &	operator= (const FunctionalProblem &)=default

	FunctionalProblem (FunctionalProblem &&) noexcept=default

FunctionalProblem &	operator= (FunctionalProblem &&) noexcept=default

void	resize (length_t n, length_t m)
	Change the dimensions of the problem (number of decision variables and number of constaints).

length_t	get_n () const
	Number of decision variables, n.

length_t	get_m () const
	Number of constraints, m.

real_t	eval_prox_grad_step (real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p) const

void	eval_proj_diff_g (crvec z, rvec p) const

void	eval_proj_multipliers (rvec y, real_t M) const

const Box &	get_box_C () const

const Box &	get_box_D () const

bool	provides_get_box_C () const
	Only supported if the ℓ₁-regularization term is zero.

index_t	eval_inactive_indices_res_lna (real_t γ, crvec x, crvec grad_ψ, rindexvec J) const

void	check () const

Static Public Member Functions
static real_t	eval_proj_grad_step_box (const Box &C, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
	Projected gradient step for rectangular box C.

static void	eval_prox_grad_step_box_l1_impl (const Box &C, const auto &λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
	Proximal gradient step for rectangular box C with ℓ₁-regularization.

static real_t	eval_prox_grad_step_box_l1 (const Box &C, const auto &λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
	Proximal gradient step for rectangular box C with ℓ₁-regularization.

static real_t	eval_prox_grad_step_box_l1_scal (const Box &C, real_t λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
	Proximal gradient step for rectangular box C with ℓ₁-regularization.

static void	eval_proj_multipliers_box (const Box &D, rvec y, real_t M, index_t penalty_alm_split)

Public Attributes
std::function< real_t(crvec)>	f

std::function< void(crvec, rvec)>	grad_f

std::function< void(crvec, rvec)>	g

std::function< void(crvec, crvec, rvec)>	grad_g_prod

std::function< void(crvec, index_t, rvec)>	grad_gi

std::function< void(crvec, rmat)>	jac_g

std::function< void(crvec, crvec, real_t, crvec, rvec)>	hess_L_prod

std::function< void(crvec, crvec, real_t, rmat)>	hess_L

std::function< void(crvec, crvec, crvec, real_t, crvec, rvec)>	hess_ψ_prod

std::function< void(crvec, crvec, crvec, real_t, rmat)>	hess_ψ

length_t	n
	Number of decision variables, dimension of x.

length_t	m
	Number of constraints, dimension of g(x) and z.

Box	C {this->n}
	Constraints of the decision variables, \( x \in C \).

Box	D {this->m}
	Other constraints, \( g(x) \in D \).

vec	l1_reg {}
	\( \ell_1 \) (1-norm) regularization parameter.

index_t	penalty_alm_split = 0
	Components of the constraint function with indices below this number are handled using a quadratic penalty method rather than using an augmented Lagrangian method.

Member Typedef Documentation

◆ Box

template<Config Conf>

using Box = alpaqa::Box<config_t>

inherited

Definition at line 19 of file box-constr-problem.hpp.

Constructor & Destructor Documentation

◆ FunctionalProblem() [1/2]

template<Config Conf = DefaultConfig>

FunctionalProblem ( const FunctionalProblem< Conf > & )

default

◆ FunctionalProblem() [2/2]

template<Config Conf = DefaultConfig>

FunctionalProblem ( FunctionalProblem< Conf > && )

defaultnoexcept

Member Function Documentation

◆ eval_f()

template<Config Conf = DefaultConfig>

real_t eval_f ( crvec x ) const

inline

Definition at line 29 of file functional-problem.hpp.

◆ eval_grad_f()

template<Config Conf = DefaultConfig>

void eval_grad_f	(	crvec	x,
		rvec	grad_fx
	)		const

inline

Definition at line 30 of file functional-problem.hpp.

◆ eval_g()

template<Config Conf = DefaultConfig>

void eval_g	(	crvec	x,
		rvec	gx
	)		const

inline

Definition at line 31 of file functional-problem.hpp.

◆ eval_grad_g_prod()

template<Config Conf = DefaultConfig>

void eval_grad_g_prod	(	crvec	x,
		crvec	y,
		rvec	grad_gxy
	)		const

inline

Definition at line 32 of file functional-problem.hpp.

◆ eval_grad_gi()

template<Config Conf = DefaultConfig>

void eval_grad_gi	(	crvec	x,
		index_t	i,
		rvec	grad_gix
	)		const

inline

Definition at line 33 of file functional-problem.hpp.

◆ eval_hess_L_prod()

template<Config Conf = DefaultConfig>

void eval_hess_L_prod	(	crvec	x,
		crvec	y,
		real_t	scale,
		crvec	v,
		rvec	Hv
	)		const

inline

Definition at line 34 of file functional-problem.hpp.

◆ eval_hess_ψ_prod()

template<Config Conf = DefaultConfig>

void eval_hess_ψ_prod	(	crvec	x,
		crvec	y,
		crvec	Σ,
		real_t	scale,
		crvec	v,
		rvec	Hv
	)		const

inline

Definition at line 35 of file functional-problem.hpp.

◆ eval_jac_g()

template<Config Conf = DefaultConfig>

void eval_jac_g	(	crvec	x,
		rvec	J_values
	)		const

inline

Definition at line 37 of file functional-problem.hpp.

◆ eval_hess_L()

template<Config Conf = DefaultConfig>

void eval_hess_L	(	crvec	x,
		crvec	y,
		real_t	scale,
		rvec	H_values
	)		const

inline

Definition at line 41 of file functional-problem.hpp.

◆ eval_hess_ψ()

template<Config Conf = DefaultConfig>

void eval_hess_ψ	(	crvec	x,
		crvec	y,
		crvec	Σ,
		real_t	scale,
		rvec	H_values
	)		const

inline

Definition at line 45 of file functional-problem.hpp.

◆ provides_eval_grad_gi()

template<Config Conf = DefaultConfig>

bool provides_eval_grad_gi ( ) const

inline

See also: TypeErasedProblem::provides_eval_grad_gi

Definition at line 51 of file functional-problem.hpp.

◆ provides_eval_jac_g()

template<Config Conf = DefaultConfig>

bool provides_eval_jac_g ( ) const

inline

See also: TypeErasedProblem::provides_eval_jac_g

Definition at line 53 of file functional-problem.hpp.

◆ provides_eval_hess_L_prod()

template<Config Conf = DefaultConfig>

bool provides_eval_hess_L_prod ( ) const

inline

See also: TypeErasedProblem::provides_eval_hess_L_prod

Definition at line 55 of file functional-problem.hpp.

◆ provides_eval_hess_L()

template<Config Conf = DefaultConfig>

bool provides_eval_hess_L ( ) const

inline

See also: TypeErasedProblem::provides_eval_hess_L

Definition at line 57 of file functional-problem.hpp.

◆ provides_eval_hess_ψ_prod()

template<Config Conf = DefaultConfig>

bool provides_eval_hess_ψ_prod ( ) const

inline

See also: TypeErasedProblem::provides_eval_hess_ψ_prod

Definition at line 59 of file functional-problem.hpp.

◆ provides_eval_hess_ψ()

template<Config Conf = DefaultConfig>

bool provides_eval_hess_ψ ( ) const

inline

See also: TypeErasedProblem::provides_eval_hess_ψ

Definition at line 61 of file functional-problem.hpp.

◆ get_name()

template<Config Conf = DefaultConfig>

std::string get_name ( ) const

inline

See also: TypeErasedProblem::get_name

Definition at line 64 of file functional-problem.hpp.

◆ operator=() [1/2]

template<Config Conf = DefaultConfig>

FunctionalProblem & operator= ( const FunctionalProblem< Conf > & )

default

◆ operator=() [2/2]

template<Config Conf = DefaultConfig>

FunctionalProblem & operator= ( FunctionalProblem< Conf > && )

defaultnoexcept

◆ resize()

template<Config Conf>

void resize	(	length_t	n,
		length_t	m
	)

inlineinherited

Change the dimensions of the problem (number of decision variables and number of constaints).

Destructive: resizes and/or resets the members C, D, l1_reg and penalty_alm_split.

Parameters

n	Number of decision variables
m	Number of constraints

Definition at line 45 of file box-constr-problem.hpp.

◆ get_n()

template<Config Conf>

length_t get_n ( ) const

inlineinherited

Number of decision variables, n.

Definition at line 81 of file box-constr-problem.hpp.

◆ get_m()

template<Config Conf>

length_t get_m ( ) const

inlineinherited

Number of constraints, m.

Definition at line 83 of file box-constr-problem.hpp.

◆ eval_proj_grad_step_box()

template<Config Conf>

static real_t eval_proj_grad_step_box	(	const Box &	C,
		real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rvec	x̂,
		rvec	p
	)

inlinestaticinherited

Projected gradient step for rectangular box C.

\[ \begin{aligned} \hat x &= \Pi_C(x - \gamma\nabla\psi(x)) \\ p &= \hat x - x \\ &= \max(\underline x - x, \;\min(-\gamma\nabla\psi(x), \overline x - x) \end{aligned} \]

Definition at line 90 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1_impl()

template<Config Conf>

static void eval_prox_grad_step_box_l1_impl	(	const Box &	C,
		const auto &	λ,
		real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rvec	x̂,
		rvec	p
	)

inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 113 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1()

template<Config Conf>

static real_t eval_prox_grad_step_box_l1	(	const Box &	C,
		const auto &	λ,
		real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rvec	x̂,
		rvec	p
	)

inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 122 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1_scal()

template<Config Conf>

static real_t eval_prox_grad_step_box_l1_scal	(	const Box &	C,
		real_t	λ,
		real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rvec	x̂,
		rvec	p
	)

inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 130 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step()

template<Config Conf>

real_t eval_prox_grad_step	(	real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rvec	x̂,
		rvec	p
	)		const

inlineinherited

See also: TypeErasedProblem::eval_prox_grad_step

Definition at line 140 of file box-constr-problem.hpp.

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◆ eval_proj_diff_g()

template<Config Conf>

void eval_proj_diff_g	(	crvec	z,
		rvec	p
	)		const

inlineinherited

See also: TypeErasedProblem::eval_proj_diff_g

Definition at line 150 of file box-constr-problem.hpp.

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◆ eval_proj_multipliers_box()

template<Config Conf>

static void eval_proj_multipliers_box	(	const Box &	D,
		rvec	y,
		real_t	M,
		index_t	penalty_alm_split
	)

inlinestaticinherited

Definition at line 152 of file box-constr-problem.hpp.

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◆ eval_proj_multipliers()

template<Config Conf>

void eval_proj_multipliers	(	rvec	y,
		real_t	M
	)		const

inlineinherited

See also: TypeErasedProblem::eval_proj_multipliers

Definition at line 168 of file box-constr-problem.hpp.

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◆ get_box_C()

template<Config Conf>

const Box & get_box_C ( ) const

inlineinherited

See also: TypeErasedProblem::get_box_C

Definition at line 173 of file box-constr-problem.hpp.

◆ get_box_D()

template<Config Conf>

const Box & get_box_D ( ) const

inlineinherited

See also: TypeErasedProblem::get_box_D

Definition at line 175 of file box-constr-problem.hpp.

◆ provides_get_box_C()

template<Config Conf>

bool provides_get_box_C ( ) const

inlineinherited

Only supported if the ℓ₁-regularization term is zero.

See also: TypeErasedProblem::provides_get_box_C

Definition at line 179 of file box-constr-problem.hpp.

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◆ eval_inactive_indices_res_lna()

template<Config Conf>

index_t eval_inactive_indices_res_lna	(	real_t	γ,
		crvec	x,
		crvec	grad_ψ,
		rindexvec	J
	)		const

inlineinherited

See also: TypeErasedProblem::eval_inactive_indices_res_lna

Definition at line 185 of file box-constr-problem.hpp.

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◆ check()

template<Config Conf>

void check ( ) const

inlineinherited

See also: TypeErasedProblem::check

Definition at line 222 of file box-constr-problem.hpp.

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Member Data Documentation

◆ f

template<Config Conf = DefaultConfig>

std::function<real_t(crvec)> f

Definition at line 17 of file functional-problem.hpp.

◆ grad_f

template<Config Conf = DefaultConfig>

std::function<void(crvec, rvec)> grad_f

Definition at line 18 of file functional-problem.hpp.

◆ g

template<Config Conf = DefaultConfig>

std::function<void(crvec, rvec)> g

Definition at line 19 of file functional-problem.hpp.

◆ grad_g_prod

template<Config Conf = DefaultConfig>

std::function<void(crvec, crvec, rvec)> grad_g_prod

Definition at line 20 of file functional-problem.hpp.

◆ grad_gi

template<Config Conf = DefaultConfig>

std::function<void(crvec, index_t, rvec)> grad_gi

Definition at line 21 of file functional-problem.hpp.

◆ jac_g

template<Config Conf = DefaultConfig>

std::function<void(crvec, rmat)> jac_g

Definition at line 22 of file functional-problem.hpp.

◆ hess_L_prod

template<Config Conf = DefaultConfig>

std::function<void(crvec, crvec, real_t, crvec, rvec)> hess_L_prod

Definition at line 23 of file functional-problem.hpp.

◆ hess_L

template<Config Conf = DefaultConfig>

std::function<void(crvec, crvec, real_t, rmat)> hess_L

Definition at line 24 of file functional-problem.hpp.

◆ hess_ψ_prod

template<Config Conf = DefaultConfig>

std::function<void(crvec, crvec, crvec, real_t, crvec, rvec)> hess_ψ_prod

Definition at line 25 of file functional-problem.hpp.

◆ hess_ψ

template<Config Conf = DefaultConfig>

std::function<void(crvec, crvec, crvec, real_t, rmat)> hess_ψ

Definition at line 26 of file functional-problem.hpp.

◆ n

template<Config Conf>

length_t n

inherited

Number of decision variables, dimension of x.

Examples: C++/CustomCppProblem/main.cpp.

Definition at line 22 of file box-constr-problem.hpp.

◆ m

template<Config Conf>

length_t m

inherited

Number of constraints, dimension of g(x) and z.

Examples: C++/CustomCppProblem/main.cpp.

Definition at line 24 of file box-constr-problem.hpp.

◆ C

template<Config Conf>

Box C {this->n}

inherited

Constraints of the decision variables, \( x \in C \).

Definition at line 65 of file box-constr-problem.hpp.

◆ D

template<Config Conf>

Box D {this->m}

inherited

Other constraints, \( g(x) \in D \).

Definition at line 67 of file box-constr-problem.hpp.

◆ l1_reg

template<Config Conf>

vec l1_reg {}

inherited

\( \ell_1 \) (1-norm) regularization parameter.

Possible dimensions are: \( 0 \) (no regularization), \( 1 \) (a single scalar factor), or \( n \) (a different factor for each variable).

Definition at line 72 of file box-constr-problem.hpp.

◆ penalty_alm_split

template<Config Conf>

index_t penalty_alm_split = 0

inherited

Components of the constraint function with indices below this number are handled using a quadratic penalty method rather than using an augmented Lagrangian method.

Specifically, the Lagrange multipliers for these components (which determine the shifts in ALM) are kept at zero.

Definition at line 78 of file box-constr-problem.hpp.

The documentation for this class was generated from the following file:

src/alpaqa/include/alpaqa/problem/functional-problem.hpp

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Member Typedef Documentation

◆ Box

Constructor & Destructor Documentation

◆ FunctionalProblem() [1/2]

◆ FunctionalProblem() [2/2]

Member Function Documentation

◆ eval_f()

◆ eval_grad_f()

◆ eval_g()

◆ eval_grad_g_prod()

◆ eval_grad_gi()

◆ eval_hess_L_prod()

◆ eval_hess_ψ_prod()

◆ eval_jac_g()

◆ eval_hess_L()

◆ eval_hess_ψ()

◆ provides_eval_grad_gi()

◆ provides_eval_jac_g()

◆ provides_eval_hess_L_prod()

◆ provides_eval_hess_L()

◆ provides_eval_hess_ψ_prod()

◆ provides_eval_hess_ψ()

◆ get_name()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ resize()

◆ get_n()

◆ get_m()

◆ eval_proj_grad_step_box()

◆ eval_prox_grad_step_box_l1_impl()

◆ eval_prox_grad_step_box_l1()

◆ eval_prox_grad_step_box_l1_scal()

◆ eval_prox_grad_step()

◆ eval_proj_diff_g()

◆ eval_proj_multipliers_box()

◆ eval_proj_multipliers()

◆ get_box_C()

◆ get_box_D()

◆ provides_get_box_C()

◆ eval_inactive_indices_res_lna()

◆ check()

Member Data Documentation

◆ f

◆ grad_f

◆ g

◆ grad_g_prod

◆ grad_gi

◆ jac_g

◆ hess_L_prod

◆ hess_L

◆ hess_ψ_prod

◆ hess_ψ

◆ n

◆ m

◆ C

◆ D

◆ l1_reg

◆ penalty_alm_split