This class adapts the TNLP interface so it looks like an NLP interface. More...

#include <IpTNLPAdapter.hpp>

Inheritance diagram for Ipopt::TNLPAdapter:

Public Types
enum	FixedVariableTreatmentEnum { MAKE_PARAMETER = 0 , MAKE_PARAMETER_NODUAL , MAKE_CONSTRAINT , RELAX_BOUNDS }
	Enum for treatment of fixed variables option. More...

enum	DerivativeTestEnum { NO_TEST = 0 , FIRST_ORDER_TEST , SECOND_ORDER_TEST , ONLY_SECOND_ORDER_TEST }
	Enum for specifying which derivative test is to be performed. More...

enum	JacobianApproxEnum { JAC_EXACT = 0 , JAC_FINDIFF_VALUES }
	Enum for specifying technique for computing Jacobian. More...

enum	GradientApproxEnum { OBJGRAD_EXACT = 0 , OBJGRAD_FINDIFF_VALUES }
	Enum for specifying technique for computing objective Gradient. More...

Public Member Functions
virtual void	GetQuasiNewtonApproximationSpaces (SmartPtr< VectorSpace > &approx_space, SmartPtr< Matrix > &P_approx)
	Method returning information on quasi-Newton approximation.

bool	CheckDerivatives (DerivativeTestEnum deriv_test, Index deriv_test_start_index)
	Method for performing the derivative test.

SmartPtr< TNLP >	tnlp () const
	Accessor method for the underlying TNLP.

Constructors/Destructors
	TNLPAdapter (const SmartPtr< TNLP > tnlp, const SmartPtr< const Journalist > jnlst=NULL)
	Default constructor.

virtual	~TNLPAdapter ()
	Default destructor.

Exceptions
	DECLARE_STD_EXCEPTION (INVALID_TNLP)

	DECLARE_STD_EXCEPTION (ERROR_IN_TNLP_DERIVATIVE_TEST)

TNLPAdapter Initialization.
virtual bool	ProcessOptions (const OptionsList &options, const std::string &prefix)
	Overload if you want the chance to process options or parameters that may be specific to the NLP.

virtual bool	GetSpaces (SmartPtr< const VectorSpace > &x_space, SmartPtr< const VectorSpace > &c_space, SmartPtr< const VectorSpace > &d_space, SmartPtr< const VectorSpace > &x_l_space, SmartPtr< const MatrixSpace > &px_l_space, SmartPtr< const VectorSpace > &x_u_space, SmartPtr< const MatrixSpace > &px_u_space, SmartPtr< const VectorSpace > &d_l_space, SmartPtr< const MatrixSpace > &pd_l_space, SmartPtr< const VectorSpace > &d_u_space, SmartPtr< const MatrixSpace > &pd_u_space, SmartPtr< const MatrixSpace > &Jac_c_space, SmartPtr< const MatrixSpace > &Jac_d_space, SmartPtr< const SymMatrixSpace > &Hess_lagrangian_space)
	Method for creating the derived vector / matrix types.

virtual bool	GetBoundsInformation (const Matrix &Px_L, Vector &x_L, const Matrix &Px_U, Vector &x_U, const Matrix &Pd_L, Vector &d_L, const Matrix &Pd_U, Vector &d_U)
	Method for obtaining the bounds information.

virtual bool	GetStartingPoint (SmartPtr< Vector > x, bool need_x, SmartPtr< Vector > y_c, bool need_y_c, SmartPtr< Vector > y_d, bool need_y_d, SmartPtr< Vector > z_L, bool need_z_L, SmartPtr< Vector > z_U, bool need_z_U)
	Method for obtaining the starting point for all the iterates.

virtual bool	GetWarmStartIterate (IteratesVector &warm_start_iterate)
	Method for obtaining an entire iterate as a warmstart point.

TNLPAdapter evaluation routines.
virtual bool	Eval_f (const Vector &x, Number &f)

virtual bool	Eval_grad_f (const Vector &x, Vector &g_f)

virtual bool	Eval_c (const Vector &x, Vector &c)

virtual bool	Eval_jac_c (const Vector &x, Matrix &jac_c)

virtual bool	Eval_d (const Vector &x, Vector &d)

virtual bool	Eval_jac_d (const Vector &x, Matrix &jac_d)

virtual bool	Eval_h (const Vector &x, Number obj_factor, const Vector &yc, const Vector &yd, SymMatrix &h)

virtual void	GetScalingParameters (const SmartPtr< const VectorSpace > x_space, const SmartPtr< const VectorSpace > c_space, const SmartPtr< const VectorSpace > d_space, Number &obj_scaling, SmartPtr< Vector > &x_scaling, SmartPtr< Vector > &c_scaling, SmartPtr< Vector > &d_scaling) const
	Routines to get the scaling parameters.

Solution Reporting Methods
virtual void	FinalizeSolution (SolverReturn status, const Vector &x, const Vector &z_L, const Vector &z_U, const Vector &c, const Vector &d, const Vector &y_c, const Vector &y_d, Number obj_value, const IpoptData ip_data, IpoptCalculatedQuantities ip_cq)
	This method is called at the very end of the optimization.

virtual bool	IntermediateCallBack (AlgorithmMode mode, Index iter, Number obj_value, Number inf_pr, Number inf_du, Number mu, Number d_norm, Number regularization_size, Number alpha_du, Number alpha_pr, Index ls_trials, const IpoptData ip_data, IpoptCalculatedQuantities ip_cq)
	This method is called once per iteration, after the iteration summary output has been printed.

Methods for translating data for IpoptNLP into the TNLP data.
These methods are used to obtain the current (or final) data for the TNLP formulation from the IpoptNLP structure.
void	ResortX (const Vector &x, Number *x_orig, bool usefixedvals=true)
	Sort the primal variables, and add the fixed values in x_orig.

void	ResortG (const Vector &c, const Vector &d, Number *g_orig, bool correctrhs=false)
	Sort constraint values.

void	ResortBounds (const Vector &x_L, Number x_L_orig, const Vector &x_U, Number x_U_orig)
	Provides values for lower and upper bounds on variables for given Ipopt-internal vectors.

IPOPT_DEPRECATED void	ResortBnds (const Vector &x_L, Number x_L_orig, const Vector &x_U, Number x_U_orig, bool clearorig=true)
	Provides values for lower and upper bounds on variables for given Ipopt-internal vectors.

bool	ResortBoundMultipliers (const Vector &x, const Vector &y_c, const Vector &y_d, const Vector &z_L, Number z_L_orig, const Vector &z_U, Number z_U_orig)
	Provides values for dual multipliers on lower and upper bounds on variables for given Ipopt-internal vectors.

void	GetFullDimensions (Index &n, Index &m) const
	Get number of variables and number of constraints in TNLP.

void	GetFixedVariables (Index &n_x_fixed, Index *&x_fixed_map, FixedVariableTreatmentEnum &fixed_variable_treatment) const
	Get number and indices of fixed variables.

void	GetPermutationMatrices (SmartPtr< const ExpansionMatrix > &P_x_full_x, SmartPtr< const ExpansionMatrix > &P_x_x_L, SmartPtr< const ExpansionMatrix > &P_x_x_U, SmartPtr< const ExpansionMatrix > &P_c_g, SmartPtr< const ExpansionMatrix > &P_d_g) const
	Get mappings between TNLP indices and Ipopt internal indices for variables and constraints.

const Number *	GetC_Rhs () const
	Get right-hand-sides that are added into c(x)

Public Member Functions inherited from Ipopt::NLP
	NLP ()
	Default constructor.

virtual	~NLP ()
	Default destructor.

	DECLARE_STD_EXCEPTION (USER_SCALING_NOT_IMPLEMENTED)
	Exceptions.

	DECLARE_STD_EXCEPTION (INVALID_NLP)

Public Member Functions inherited from Ipopt::ReferencedObject
	ReferencedObject ()

virtual	~ReferencedObject ()

Index	ReferenceCount () const

void	AddRef (const Referencer *referencer) const

void	ReleaseRef (const Referencer *referencer) const

Static Public Member Functions
static void	RegisterOptions (SmartPtr< RegisteredOptions > roptions)

Private Member Functions
Default Compiler Generated Methods
(Hidden to avoid implicit creation/calling). These methods are not implemented and we do not want the compiler to implement them for us, so we declare them private and do not define them. This ensures that they will not be implicitly created/called.
	TNLPAdapter (const TNLPAdapter &)
	Copy Constructor.

void	operator= (const TNLPAdapter &)
	Default Assignment Operator.

Methods to update the values in the local copies of vectors
bool	update_local_x (const Vector &x)

bool	update_local_lambda (const Vector &y_c, const Vector &y_d)

Internal routines for evaluating g and jac_g.
Values stored since they are used in both c and d routines.
bool	internal_eval_g (bool new_x)

bool	internal_eval_jac_g (bool new_x)

Internal methods for dealing with finite difference approximation
void	initialize_findiff_jac (const Index iRow, const Index jCol)
	Initialize sparsity structure for finite difference Jacobian.

Private Attributes
TNLP::IndexStyleEnum	index_style_
	Numbering style of variables and constraints.

Algorithmic parameters
Number	nlp_lower_bound_inf_
	Value for a lower bound that denotes -infinity.

Number	nlp_upper_bound_inf_
	Value for a upper bound that denotes infinity.

FixedVariableTreatmentEnum	fixed_variable_treatment_
	Flag indicating how fixed variables should be handled.

Number	bound_relax_factor_
	Determines relaxation of fixing bound for RELAX_BOUNDS.

DerivativeTestEnum	derivative_test_
	Maximal slack for one-sidedly bounded variables.

Number	derivative_test_perturbation_
	Size of the perturbation for the derivative test.

Number	derivative_test_tol_
	Relative threshold for marking deviation from finite difference test.

bool	derivative_test_print_all_
	Flag indicating if all test values should be printed, or only those violating the threshold.

Index	derivative_test_first_index_
	Index of first quantity to be checked.

bool	warm_start_same_structure_
	Flag indicating whether the TNLP with identical structure has already been solved before.

HessianApproximationType	hessian_approximation_
	Flag indicating what Hessian information is to be used.

Index	num_linear_variables_
	Number of linear variables.

JacobianApproxEnum	jacobian_approximation_
	Flag indicating how Jacobian is computed.

GradientApproxEnum	gradient_approximation_
	Flag indicating how objective Gradient is computed.

Number	findiff_perturbation_
	Size of the perturbation for the derivative approximation.

Number	point_perturbation_radius_
	Maximal perturbation of the initial point.

bool	dependency_detection_with_rhs_
	Flag indicating if rhs should be considered during dependency detection.

Number	tol_
	Overall convergence tolerance.

Problem Size Data
Index	n_full_x_
	full dimension of x (fixed + non-fixed)

Index	n_full_g_
	full dimension of g (c + d)

Index	nz_jac_c_
	non-zeros of the jacobian of c

Index	nz_jac_c_no_extra_
	non-zeros of the jacobian of c without added constraints for fixed variables.

Index	nz_jac_d_
	non-zeros of the jacobian of d

Index	nz_full_jac_g_
	number of non-zeros in full-size Jacobian of g

Index	nz_full_h_
	number of non-zeros in full-size Hessian

Index	nz_h_
	number of non-zeros in the non-fixed-size Hessian

Index	n_x_fixed_
	Number of fixed variables.

Local copy of spaces (for warm start)
SmartPtr< const VectorSpace >	x_space_

SmartPtr< const VectorSpace >	c_space_

SmartPtr< const VectorSpace >	d_space_

SmartPtr< const VectorSpace >	x_l_space_

SmartPtr< const MatrixSpace >	px_l_space_

SmartPtr< const VectorSpace >	x_u_space_

SmartPtr< const MatrixSpace >	px_u_space_

SmartPtr< const VectorSpace >	d_l_space_

SmartPtr< const MatrixSpace >	pd_l_space_

SmartPtr< const VectorSpace >	d_u_space_

SmartPtr< const MatrixSpace >	pd_u_space_

SmartPtr< const MatrixSpace >	Jac_c_space_

SmartPtr< const MatrixSpace >	Jac_d_space_

SmartPtr< const SymMatrixSpace >	Hess_lagrangian_space_

Local Copy of the Data
Number *	full_x_

Number *	full_lambda_
	copy of the full x vector (fixed & non-fixed)

Number *	full_g_
	copy of lambda (yc & yd)

Number *	jac_g_
	copy of g (c & d)

Number *	c_rhs_
	the values for the full jacobian of g

Tags for deciding when to update internal copies of vectors
the rhs values of c
TaggedObject::Tag	x_tag_for_iterates_

TaggedObject::Tag	y_c_tag_for_iterates_

TaggedObject::Tag	y_d_tag_for_iterates_

TaggedObject::Tag	x_tag_for_g_

TaggedObject::Tag	x_tag_for_jac_g_

Internal Permutation Spaces and matrices
SmartPtr< ExpansionMatrix >	P_x_full_x_
	Expansion from fixed x (ipopt) to full x.

SmartPtr< ExpansionMatrixSpace >	P_x_full_x_space_

SmartPtr< ExpansionMatrix >	P_x_x_L_
	Expansion from fixed x_L (ipopt) to full x.

SmartPtr< ExpansionMatrixSpace >	P_x_x_L_space_

SmartPtr< ExpansionMatrix >	P_x_x_U_
	Expansion from fixed x_U (ipopt) to full x.

SmartPtr< ExpansionMatrixSpace >	P_x_x_U_space_

SmartPtr< ExpansionMatrixSpace >	P_c_g_space_
	Expansion from c only (ipopt) to full ampl c.

SmartPtr< ExpansionMatrix >	P_c_g_

SmartPtr< ExpansionMatrixSpace >	P_d_g_space_
	Expansion from d only (ipopt) to full ampl d.

SmartPtr< ExpansionMatrix >	P_d_g_

Index *	jac_idx_map_

Index *	h_idx_map_

Index *	x_fixed_map_
	Position of fixed variables.

std::vector< Index >	jac_fixed_idx_map_
	Index mapping of Jacobian w.r.t.

std::vector< Index >	jac_fixed_iRow_

std::vector< Index >	jac_fixed_jCol_

Data for finite difference approximations of derivatives
Index	findiff_jac_nnz_
	Number of unique nonzeros in constraint Jacobian.

Index *	findiff_jac_ia_
	Start position for nonzero indices in ja for each column of Jacobian.

Index *	findiff_jac_ja_
	Ordered by columns, for each column the row indices in Jacobian.

Index *	findiff_jac_postriplet_
	Position of entry in original triplet matrix.

Number *	findiff_x_l_
	Copy of the lower bounds.

Number *	findiff_x_u_
	Copy of the upper bounds.

Method implementing the detection of linearly dependent equality constraints
SmartPtr< TNLP >	tnlp_
	Pointer to the TNLP class (class specific to Number* vectors and triplet matrices)

SmartPtr< const Journalist >	jnlst_
	Journalist.

SmartPtr< TDependencyDetector >	dependency_detector_
	Object that can be used to detect linearly dependent rows in the equality constraint Jacobian.

bool	DetermineDependentConstraints (Index n_x_var, const Index x_not_fixed_map, const Number x_l, const Number x_u, const Number g_l, const Number g_u, Index n_c, const Index c_map, std::list< Index > &c_deps)

Detailed Description

This class adapts the TNLP interface so it looks like an NLP interface.

This is an Adapter class (Design Patterns) that converts a TNLP to an NLP. This allows users to write to the "more convenient" TNLP interface.

Given a TNLP

\begin{eqnarray*} \mathrm{min} && f(x), \\ \mathrm{s.t.} && g_L \leq g(x) \leq g_U, &\qquad \lambda\\ && x_L \leq x \leq x_U, &\qquad z_L, z_U \end{eqnarray*}

let \(E = \{i : g_{L,i} = g_{U,i}\}\) and \(I = \{i : g_{L,i} \neq g_{U,i}\}\) be the indices of equality and inequality constraints, respectively. The dual variables for the constraints are \(\lambda\). The dual variables for the variable bounds are \(z_L\) and \(z_U\).

A TNLPAdapter represents the problem

\begin{eqnarray*} \mathrm{min} && f(x), \\ \mathrm{s.t.} && c(x) = 0, &\qquad y_c\\ && d_L \leq d(x) \leq d_U, &\qquad y_d \\ && x_L \leq x \leq x_U, &\qquad z_L, z_U \end{eqnarray*}

where \(c(x) = g_E(x) - g_{L,E}\), i.e., corresponding to equality constraints of TNLP, and \(d(x) = g_I(x)\), \(d_L = g_{L,I}\), \(d_U = g_{U,I}\), i.e., corresponding to inequality constraints of TNLP.

The dual variables for the constraints are \(y_c\) and \(y_d\). The dual variables for the bounds on slack and original variables are \(s_L\), \(s_U\), \(z_L\), \(z_U\).

Internally, Ipopt reformulates \(d_L \leq d(x) \leq d_U\) as

\begin{eqnarray*} && d(x) - s = 0 &\qquad y_d\\ && d_L \leq s \leq d_U &\qquad v_L, v_U \\ \end{eqnarray*}

If fixed variables are present ( \(x_{L,i} = x_{U,i}\)) in the TNLP and fixed_variable_treatment is set to make_parameter, then these variables are not made visible to Ipopt internally. If fixed_variable_treatment is set to make_constraint, then their bounds relaxed and equality constraints \(x_i - x_{L,i} = 0\) are added to the end of \(c(x) = 0\).

Definition at line 65 of file IpTNLPAdapter.hpp.

Member Enumeration Documentation

◆ FixedVariableTreatmentEnum

enum Ipopt::TNLPAdapter::FixedVariableTreatmentEnum

Enum for treatment of fixed variables option.

Enumerator
MAKE_PARAMETER
MAKE_PARAMETER_NODUAL	Since 3.14.0
MAKE_CONSTRAINT
RELAX_BOUNDS

Definition at line 240 of file IpTNLPAdapter.hpp.

◆ DerivativeTestEnum

enum Ipopt::TNLPAdapter::DerivativeTestEnum

Enum for specifying which derivative test is to be performed.

Enumerator
NO_TEST
FIRST_ORDER_TEST
SECOND_ORDER_TEST
ONLY_SECOND_ORDER_TEST

Definition at line 249 of file IpTNLPAdapter.hpp.

◆ JacobianApproxEnum

enum Ipopt::TNLPAdapter::JacobianApproxEnum

Enum for specifying technique for computing Jacobian.

Enumerator
JAC_EXACT
JAC_FINDIFF_VALUES

Definition at line 258 of file IpTNLPAdapter.hpp.

◆ GradientApproxEnum

enum Ipopt::TNLPAdapter::GradientApproxEnum

Enum for specifying technique for computing objective Gradient.

Enumerator
OBJGRAD_EXACT
OBJGRAD_FINDIFF_VALUES

Definition at line 265 of file IpTNLPAdapter.hpp.

Constructor & Destructor Documentation

◆ TNLPAdapter() [1/2]

Ipopt::TNLPAdapter::TNLPAdapter	(	const SmartPtr< TNLP >	tnlp,
		const SmartPtr< const Journalist >	jnlst = `NULL`
	)

Default constructor.

◆ ~TNLPAdapter()

virtual Ipopt::TNLPAdapter::~TNLPAdapter ( )

virtual

Default destructor.

◆ TNLPAdapter() [2/2]

Ipopt::TNLPAdapter::TNLPAdapter ( const TNLPAdapter & )

private

Copy Constructor.

Member Function Documentation

◆ DECLARE_STD_EXCEPTION() [1/2]

Ipopt::TNLPAdapter::DECLARE_STD_EXCEPTION ( INVALID_TNLP )

◆ DECLARE_STD_EXCEPTION() [2/2]

Ipopt::TNLPAdapter::DECLARE_STD_EXCEPTION ( ERROR_IN_TNLP_DERIVATIVE_TEST )

◆ ProcessOptions()

virtual bool Ipopt::TNLPAdapter::ProcessOptions	(	const OptionsList &	,
		const std::string &
	)

virtual

Overload if you want the chance to process options or parameters that may be specific to the NLP.

Reimplemented from Ipopt::NLP.

◆ GetSpaces()

virtual bool Ipopt::TNLPAdapter::GetSpaces	(	SmartPtr< const VectorSpace > &	x_space,
		SmartPtr< const VectorSpace > &	c_space,
		SmartPtr< const VectorSpace > &	d_space,
		SmartPtr< const VectorSpace > &	x_l_space,
		SmartPtr< const MatrixSpace > &	px_l_space,
		SmartPtr< const VectorSpace > &	x_u_space,
		SmartPtr< const MatrixSpace > &	px_u_space,
		SmartPtr< const VectorSpace > &	d_l_space,
		SmartPtr< const MatrixSpace > &	pd_l_space,
		SmartPtr< const VectorSpace > &	d_u_space,
		SmartPtr< const MatrixSpace > &	pd_u_space,
		SmartPtr< const MatrixSpace > &	Jac_c_space,
		SmartPtr< const MatrixSpace > &	Jac_d_space,
		SmartPtr< const SymMatrixSpace > &	Hess_lagrangian_space
	)

virtual

Method for creating the derived vector / matrix types.

Do not delete these.

Implements Ipopt::NLP.

◆ GetBoundsInformation()

virtual bool Ipopt::TNLPAdapter::GetBoundsInformation	(	const Matrix &	Px_L,
		Vector &	x_L,
		const Matrix &	Px_U,
		Vector &	x_U,
		const Matrix &	Pd_L,
		Vector &	d_L,
		const Matrix &	Pd_U,
		Vector &	d_U
	)

virtual

Method for obtaining the bounds information.

Implements Ipopt::NLP.

◆ GetStartingPoint()

virtual bool Ipopt::TNLPAdapter::GetStartingPoint	(	SmartPtr< Vector >	x,
		bool	need_x,
		SmartPtr< Vector >	y_c,
		bool	need_y_c,
		SmartPtr< Vector >	y_d,
		bool	need_y_d,
		SmartPtr< Vector >	z_L,
		bool	need_z_L,
		SmartPtr< Vector >	z_U,
		bool	need_z_U
	)

virtual

Method for obtaining the starting point for all the iterates.

Implements Ipopt::NLP.

◆ GetWarmStartIterate()

virtual bool Ipopt::TNLPAdapter::GetWarmStartIterate ( IteratesVector & warm_start_iterate )

virtual

Method for obtaining an entire iterate as a warmstart point.

The incoming IteratesVector has to be filled.

Reimplemented from Ipopt::NLP.

◆ Eval_f()

virtual bool Ipopt::TNLPAdapter::Eval_f	(	const Vector &	x,
		Number &	f
	)

virtual

Implements Ipopt::NLP.

◆ Eval_grad_f()

virtual bool Ipopt::TNLPAdapter::Eval_grad_f	(	const Vector &	x,
		Vector &	g_f
	)

virtual

Implements Ipopt::NLP.

◆ Eval_c()

virtual bool Ipopt::TNLPAdapter::Eval_c	(	const Vector &	x,
		Vector &	c
	)

virtual

Implements Ipopt::NLP.

◆ Eval_jac_c()

virtual bool Ipopt::TNLPAdapter::Eval_jac_c	(	const Vector &	x,
		Matrix &	jac_c
	)

virtual

Implements Ipopt::NLP.

◆ Eval_d()

virtual bool Ipopt::TNLPAdapter::Eval_d	(	const Vector &	x,
		Vector &	d
	)

virtual

Implements Ipopt::NLP.

◆ Eval_jac_d()

virtual bool Ipopt::TNLPAdapter::Eval_jac_d	(	const Vector &	x,
		Matrix &	jac_d
	)

virtual

Implements Ipopt::NLP.

◆ Eval_h()

virtual bool Ipopt::TNLPAdapter::Eval_h	(	const Vector &	x,
		Number	obj_factor,
		const Vector &	yc,
		const Vector &	yd,
		SymMatrix &	h
	)

virtual

Implements Ipopt::NLP.

◆ GetScalingParameters()

virtual void Ipopt::TNLPAdapter::GetScalingParameters	(	const SmartPtr< const VectorSpace >	,
		const SmartPtr< const VectorSpace >	,
		const SmartPtr< const VectorSpace >	,
		Number &	,
		SmartPtr< Vector > &	,
		SmartPtr< Vector > &	,
		SmartPtr< Vector > &
	)		const

virtual

Routines to get the scaling parameters.

These do not need to be overloaded unless the options are set for user scaling.

Reimplemented from Ipopt::NLP.

◆ FinalizeSolution()

virtual void Ipopt::TNLPAdapter::FinalizeSolution	(	SolverReturn	,
		const Vector &	,
		const Vector &	,
		const Vector &	,
		const Vector &	,
		const Vector &	,
		const Vector &	,
		const Vector &	,
		Number	,
		const IpoptData *	,
		IpoptCalculatedQuantities *
	)

virtual

This method is called at the very end of the optimization.

It provides the final iterate to the user, so that it can be stored as the solution. The status flag indicates the outcome of the optimization, where SolverReturn is defined in IpAlgTypes.hpp.

Reimplemented from Ipopt::NLP.

◆ IntermediateCallBack()

virtual bool Ipopt::TNLPAdapter::IntermediateCallBack	(	AlgorithmMode	,
		Index	,
		Number	,
		Number	,
		Number	,
		Number	,
		Number	,
		Number	,
		Number	,
		Number	,
		Index	,
		const IpoptData *	,
		IpoptCalculatedQuantities *
	)

virtual

This method is called once per iteration, after the iteration summary output has been printed.

It provides the current information to the user to do with it anything she wants. It also allows the user to ask for a premature termination of the optimization by returning false, in which case Ipopt will terminate with a corresponding return status. The basic information provided in the argument list has the quantities values printed in the iteration summary line. If more information is required, a user can obtain it from the IpData and IpCalculatedQuantities objects. However, note that the provided quantities are all for the problem that Ipopt sees, i.e., the quantities might be scaled, fixed variables might be sorted out, etc. The status indicates things like whether the algorithm is in the restoration phase... In the restoration phase, the dual variables are probably not not changing.

Reimplemented from Ipopt::NLP.

◆ GetQuasiNewtonApproximationSpaces()

virtual void Ipopt::TNLPAdapter::GetQuasiNewtonApproximationSpaces	(	SmartPtr< VectorSpace > &	approx_space,
		SmartPtr< Matrix > &	P_approx
	)

virtual

Method returning information on quasi-Newton approximation.

Reimplemented from Ipopt::NLP.

◆ CheckDerivatives()

bool Ipopt::TNLPAdapter::CheckDerivatives	(	DerivativeTestEnum	deriv_test,
		Index	deriv_test_start_index
	)

Method for performing the derivative test.

◆ RegisterOptions()

static void Ipopt::TNLPAdapter::RegisterOptions ( SmartPtr< RegisteredOptions > roptions )

static

◆ tnlp()

SmartPtr< TNLP > Ipopt::TNLPAdapter::tnlp ( ) const

inline

Accessor method for the underlying TNLP.

Definition at line 282 of file IpTNLPAdapter.hpp.

◆ ResortX()

void Ipopt::TNLPAdapter::ResortX	(	const Vector &	x,
		Number *	x_orig,
		bool	usefixedvals = `true`
	)

Sort the primal variables, and add the fixed values in x_orig.

Parameters

x	internal values for primal variables x
x_orig	vector to fill with values from x
usefixedvals	whether to use stored variable fixings for fixed variables (true), or zero (false)

Since: 3.14.0

◆ ResortG()

void Ipopt::TNLPAdapter::ResortG	(	const Vector &	c,
		const Vector &	d,
		Number *	g_orig,
		bool	correctrhs = `false`
	)

Sort constraint values.

To Ipopt, the equality constraints are presented with right hand side zero. Specifying correctrhs=true corrects for the original right hand side.

Parameters

c	internal activity for equality constraints
d	internal activity for inequality constraints
g_orig	vector to fill with values from c and d
correctrhs	whether to add unscaled rhs-values for constraints that internally correspond to c(x)=0

Since: 3.14.0

◆ ResortBounds()

void Ipopt::TNLPAdapter::ResortBounds	(	const Vector &	x_L,
		Number *	x_L_orig,
		const Vector &	x_U,
		Number *	x_U_orig
	)

Provides values for lower and upper bounds on variables for given Ipopt-internal vectors.

Similar to ResortX, but does so for two arrays and does not set any values for fixed variables.

Since: 3.14.0

Parameters

x_L	internal values for lower bounds on x
x_L_orig	vector to fill with values from x_L
x_U	internal values for upper bounds on x
x_U_orig	vector to fill with values from x_U

◆ ResortBnds()

IPOPT_DEPRECATED void Ipopt::TNLPAdapter::ResortBnds	(	const Vector &	x_L,
		Number *	x_L_orig,
		const Vector &	x_U,
		Number *	x_U_orig,
		bool	clearorig = `true`
	)

inline

Provides values for lower and upper bounds on variables for given Ipopt-internal vectors.

Similar to ResortX, but does so for two arrays and does not set any values for fixed variables.

Deprecated:: Use ResortBounds() instead.

Parameters

x_L	internal values for lower bounds on x
x_L_orig	vector to fill with values from x_L
x_U	internal values for upper bounds on x
x_U_orig	vector to fill with values from x_U
clearorig	whether to initialize complete x_L_orig and x_U_orig to 0.0 before setting values for non-fixed variables - ignored

Definition at line 331 of file IpTNLPAdapter.hpp.

◆ ResortBoundMultipliers()

bool Ipopt::TNLPAdapter::ResortBoundMultipliers	(	const Vector &	x,
		const Vector &	y_c,
		const Vector &	y_d,
		const Vector &	z_L,
		Number *	z_L_orig,
		const Vector &	z_U,
		Number *	z_U_orig
	)

Provides values for dual multipliers on lower and upper bounds on variables for given Ipopt-internal vectors.

Similar to ResortBounds, but also provides dual values for fixed variables if fixed_variable_treatment is set to make_constraint or make_parameter.

Attention: If there are fixed variables and fixed_variable_treatment is make_parameter (the default), then the Gradient of f(x) and the Jacobian of g(x) may be reevaluated here (that's why the function needs x). Further, in this setting, this function only provides correct bound multipliers for fixed variables if x, y_c, and y_d correspond to the unscaled problem.

Returns: True, if bound multipliers could be assigned. False if there was an evaluation error when calculating bound multipliers for fixed variables.

Since: 3.14.0

Parameters

x	internal values for primal variables x
y_c	internal values for equality constraint multipliers
y_d	internal values for inequality constraint multipliers
z_L	internal values for lower bound multipliers
z_L_orig	vector to fill with values from z_L
z_U	internal values for upper bound multipliers
z_U_orig	vector to fill with values from z_U

◆ GetFullDimensions()

void Ipopt::TNLPAdapter::GetFullDimensions	(	Index &	n,
		Index &	m
	)		const

inline

Get number of variables and number of constraints in TNLP.

Since: 3.14.0

Parameters

n	storage for full dimension of x (fixed + non-fixed)
m	storage for full dimension of g (c + d)

Definition at line 368 of file IpTNLPAdapter.hpp.

◆ GetFixedVariables()

void Ipopt::TNLPAdapter::GetFixedVariables	(	Index &	n_x_fixed,
		Index *&	x_fixed_map,
		FixedVariableTreatmentEnum &	fixed_variable_treatment
	)		const

inline

Get number and indices of fixed variables.

Since: 3.14.0

Parameters

n_x_fixed	storage for number of fixed variables in TNLP
x_fixed_map	storage for pointer to array that holds indices of fixed variables (has length n_fixed_x, can be NULL if n_fixed_x=0)
fixed_variable_treatment	treatment for fixed variables as used by TNLP

Definition at line 380 of file IpTNLPAdapter.hpp.

◆ GetPermutationMatrices()

void Ipopt::TNLPAdapter::GetPermutationMatrices	(	SmartPtr< const ExpansionMatrix > &	P_x_full_x,
		SmartPtr< const ExpansionMatrix > &	P_x_x_L,
		SmartPtr< const ExpansionMatrix > &	P_x_x_U,
		SmartPtr< const ExpansionMatrix > &	P_c_g,
		SmartPtr< const ExpansionMatrix > &	P_d_g
	)		const

inline

Get mappings between TNLP indices and Ipopt internal indices for variables and constraints.

See the various ResortXyz functions on usage.

Attention: P_x_full_x is set to NULL if there are no fixed variables or fixed_variable_treatment is not make_parameter

Since: 3.14.0

Parameters

P_x_full_x	map from TNLP variable indices to Ipopt internal indices, filtered variables get mapped to -1
P_x_x_L	map from indices on lower bounds on x to Ipopt internal indices for x
P_x_x_U	map from indices on upper bounds on x to Ipopt internal indices for x
P_c_g	map from indices on equality constraints (c(x)=0) into TNLP constraint indices (g_l <= g(x) <= g_u)
P_d_g	map from indices on inequality constraints (d(x)-s=0) into TNLP constraint indices (g_l <= g(x) <= g_u)

Definition at line 398 of file IpTNLPAdapter.hpp.

◆ GetC_Rhs()

const Number * Ipopt::TNLPAdapter::GetC_Rhs ( ) const

inline

Get right-hand-sides that are added into c(x)

Since: 3.14.0

Definition at line 416 of file IpTNLPAdapter.hpp.

◆ operator=()

void Ipopt::TNLPAdapter::operator= ( const TNLPAdapter & )

private

Default Assignment Operator.

◆ DetermineDependentConstraints()

bool Ipopt::TNLPAdapter::DetermineDependentConstraints	(	Index	n_x_var,
		const Index *	x_not_fixed_map,
		const Number *	x_l,
		const Number *	x_u,
		const Number *	g_l,
		const Number *	g_u,
		Index	n_c,
		const Index *	c_map,
		std::list< Index > &	c_deps
	)

private

◆ update_local_x()

bool Ipopt::TNLPAdapter::update_local_x ( const Vector & x )

private

◆ update_local_lambda()

bool Ipopt::TNLPAdapter::update_local_lambda	(	const Vector &	y_c,
		const Vector &	y_d
	)

private

◆ internal_eval_g()

bool Ipopt::TNLPAdapter::internal_eval_g ( bool new_x )

private

◆ internal_eval_jac_g()

bool Ipopt::TNLPAdapter::internal_eval_jac_g ( bool new_x )

private

◆ initialize_findiff_jac()

void Ipopt::TNLPAdapter::initialize_findiff_jac	(	const Index *	iRow,
		const Index *	jCol
	)

private

Initialize sparsity structure for finite difference Jacobian.

Member Data Documentation

◆ tnlp_

SmartPtr<TNLP> Ipopt::TNLPAdapter::tnlp_

private

Pointer to the TNLP class (class specific to Number* vectors and triplet matrices)

Definition at line 458 of file IpTNLPAdapter.hpp.

◆ jnlst_

SmartPtr<const Journalist> Ipopt::TNLPAdapter::jnlst_

private

Journalist.

Definition at line 461 of file IpTNLPAdapter.hpp.

◆ dependency_detector_

SmartPtr<TDependencyDetector> Ipopt::TNLPAdapter::dependency_detector_

private

Object that can be used to detect linearly dependent rows in the equality constraint Jacobian.

Definition at line 464 of file IpTNLPAdapter.hpp.

◆ nlp_lower_bound_inf_

Number Ipopt::TNLPAdapter::nlp_lower_bound_inf_

private

Value for a lower bound that denotes -infinity.

Definition at line 469 of file IpTNLPAdapter.hpp.

◆ nlp_upper_bound_inf_

Number Ipopt::TNLPAdapter::nlp_upper_bound_inf_

private

Value for a upper bound that denotes infinity.

Definition at line 471 of file IpTNLPAdapter.hpp.

◆ fixed_variable_treatment_

FixedVariableTreatmentEnum Ipopt::TNLPAdapter::fixed_variable_treatment_

private

Flag indicating how fixed variables should be handled.

Definition at line 473 of file IpTNLPAdapter.hpp.

◆ bound_relax_factor_

Number Ipopt::TNLPAdapter::bound_relax_factor_

private

Determines relaxation of fixing bound for RELAX_BOUNDS.

Definition at line 475 of file IpTNLPAdapter.hpp.

◆ derivative_test_

DerivativeTestEnum Ipopt::TNLPAdapter::derivative_test_

private

Maximal slack for one-sidedly bounded variables.

If a variable has only one bound, say a lower bound xL, then an upper bound xL + max_onesided_bound_slack_. If this value is zero, no upper bound is added. Whether and which derivative test should be performed at starting point

Definition at line 482 of file IpTNLPAdapter.hpp.

◆ derivative_test_perturbation_

Number Ipopt::TNLPAdapter::derivative_test_perturbation_

private

Size of the perturbation for the derivative test.

Definition at line 484 of file IpTNLPAdapter.hpp.

◆ derivative_test_tol_

Number Ipopt::TNLPAdapter::derivative_test_tol_

private

Relative threshold for marking deviation from finite difference test.

Definition at line 486 of file IpTNLPAdapter.hpp.

◆ derivative_test_print_all_

bool Ipopt::TNLPAdapter::derivative_test_print_all_

private

Flag indicating if all test values should be printed, or only those violating the threshold.

Definition at line 488 of file IpTNLPAdapter.hpp.

◆ derivative_test_first_index_

Index Ipopt::TNLPAdapter::derivative_test_first_index_

private

Index of first quantity to be checked.

Definition at line 490 of file IpTNLPAdapter.hpp.

◆ warm_start_same_structure_

bool Ipopt::TNLPAdapter::warm_start_same_structure_

private

Flag indicating whether the TNLP with identical structure has already been solved before.

Definition at line 492 of file IpTNLPAdapter.hpp.

◆ hessian_approximation_

HessianApproximationType Ipopt::TNLPAdapter::hessian_approximation_

private

Flag indicating what Hessian information is to be used.

Definition at line 494 of file IpTNLPAdapter.hpp.

◆ num_linear_variables_

Index Ipopt::TNLPAdapter::num_linear_variables_

private

Number of linear variables.

Definition at line 496 of file IpTNLPAdapter.hpp.

◆ jacobian_approximation_

JacobianApproxEnum Ipopt::TNLPAdapter::jacobian_approximation_

private

Flag indicating how Jacobian is computed.

Definition at line 498 of file IpTNLPAdapter.hpp.

◆ gradient_approximation_

GradientApproxEnum Ipopt::TNLPAdapter::gradient_approximation_

private

Flag indicating how objective Gradient is computed.

Definition at line 500 of file IpTNLPAdapter.hpp.

◆ findiff_perturbation_

Number Ipopt::TNLPAdapter::findiff_perturbation_

private

Size of the perturbation for the derivative approximation.

Definition at line 502 of file IpTNLPAdapter.hpp.

◆ point_perturbation_radius_

Number Ipopt::TNLPAdapter::point_perturbation_radius_

private

Maximal perturbation of the initial point.

Definition at line 504 of file IpTNLPAdapter.hpp.

◆ dependency_detection_with_rhs_

bool Ipopt::TNLPAdapter::dependency_detection_with_rhs_

private

Flag indicating if rhs should be considered during dependency detection.

Definition at line 506 of file IpTNLPAdapter.hpp.

◆ tol_

Number Ipopt::TNLPAdapter::tol_

private

Overall convergence tolerance.

Definition at line 509 of file IpTNLPAdapter.hpp.

◆ n_full_x_

Index Ipopt::TNLPAdapter::n_full_x_

private

full dimension of x (fixed + non-fixed)

Definition at line 515 of file IpTNLPAdapter.hpp.

◆ n_full_g_

Index Ipopt::TNLPAdapter::n_full_g_

private

full dimension of g (c + d)

Definition at line 517 of file IpTNLPAdapter.hpp.

◆ nz_jac_c_

Index Ipopt::TNLPAdapter::nz_jac_c_

private

non-zeros of the jacobian of c

Definition at line 519 of file IpTNLPAdapter.hpp.

◆ nz_jac_c_no_extra_

Index Ipopt::TNLPAdapter::nz_jac_c_no_extra_

private

non-zeros of the jacobian of c without added constraints for fixed variables.

Definition at line 521 of file IpTNLPAdapter.hpp.

◆ nz_jac_d_

Index Ipopt::TNLPAdapter::nz_jac_d_

private

non-zeros of the jacobian of d

Definition at line 523 of file IpTNLPAdapter.hpp.

◆ nz_full_jac_g_

Index Ipopt::TNLPAdapter::nz_full_jac_g_

private

number of non-zeros in full-size Jacobian of g

Definition at line 525 of file IpTNLPAdapter.hpp.

◆ nz_full_h_

Index Ipopt::TNLPAdapter::nz_full_h_

private

number of non-zeros in full-size Hessian

Definition at line 527 of file IpTNLPAdapter.hpp.

◆ nz_h_

Index Ipopt::TNLPAdapter::nz_h_

private

number of non-zeros in the non-fixed-size Hessian

Definition at line 529 of file IpTNLPAdapter.hpp.

◆ n_x_fixed_

Index Ipopt::TNLPAdapter::n_x_fixed_

private

Number of fixed variables.

Definition at line 531 of file IpTNLPAdapter.hpp.

◆ index_style_

TNLP::IndexStyleEnum Ipopt::TNLPAdapter::index_style_

private

Numbering style of variables and constraints.

Definition at line 535 of file IpTNLPAdapter.hpp.

◆ x_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::x_space_

private

Definition at line 539 of file IpTNLPAdapter.hpp.

◆ c_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::c_space_

private

Definition at line 540 of file IpTNLPAdapter.hpp.

◆ d_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::d_space_

private

Definition at line 541 of file IpTNLPAdapter.hpp.

◆ x_l_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::x_l_space_

private

Definition at line 542 of file IpTNLPAdapter.hpp.

◆ px_l_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::px_l_space_

private

Definition at line 543 of file IpTNLPAdapter.hpp.

◆ x_u_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::x_u_space_

private

Definition at line 544 of file IpTNLPAdapter.hpp.

◆ px_u_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::px_u_space_

private

Definition at line 545 of file IpTNLPAdapter.hpp.

◆ d_l_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::d_l_space_

private

Definition at line 546 of file IpTNLPAdapter.hpp.

◆ pd_l_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::pd_l_space_

private

Definition at line 547 of file IpTNLPAdapter.hpp.

◆ d_u_space_

SmartPtr<const VectorSpace> Ipopt::TNLPAdapter::d_u_space_

private

Definition at line 548 of file IpTNLPAdapter.hpp.

◆ pd_u_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::pd_u_space_

private

Definition at line 549 of file IpTNLPAdapter.hpp.

◆ Jac_c_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::Jac_c_space_

private

Definition at line 550 of file IpTNLPAdapter.hpp.

◆ Jac_d_space_

SmartPtr<const MatrixSpace> Ipopt::TNLPAdapter::Jac_d_space_

private

Definition at line 551 of file IpTNLPAdapter.hpp.

◆ Hess_lagrangian_space_

SmartPtr<const SymMatrixSpace> Ipopt::TNLPAdapter::Hess_lagrangian_space_

private

Definition at line 552 of file IpTNLPAdapter.hpp.

◆ full_x_

Number* Ipopt::TNLPAdapter::full_x_

private

Definition at line 557 of file IpTNLPAdapter.hpp.

◆ full_lambda_

Number* Ipopt::TNLPAdapter::full_lambda_

private

copy of the full x vector (fixed & non-fixed)

Definition at line 558 of file IpTNLPAdapter.hpp.

◆ full_g_

Number* Ipopt::TNLPAdapter::full_g_

private

copy of lambda (yc & yd)

Definition at line 559 of file IpTNLPAdapter.hpp.

◆ jac_g_

Number* Ipopt::TNLPAdapter::jac_g_

private

copy of g (c & d)

Definition at line 560 of file IpTNLPAdapter.hpp.

◆ c_rhs_

Number* Ipopt::TNLPAdapter::c_rhs_

private

the values for the full jacobian of g

Definition at line 561 of file IpTNLPAdapter.hpp.

◆ x_tag_for_iterates_

TaggedObject::Tag Ipopt::TNLPAdapter::x_tag_for_iterates_

private

Definition at line 566 of file IpTNLPAdapter.hpp.

◆ y_c_tag_for_iterates_

TaggedObject::Tag Ipopt::TNLPAdapter::y_c_tag_for_iterates_

private

Definition at line 567 of file IpTNLPAdapter.hpp.

◆ y_d_tag_for_iterates_

TaggedObject::Tag Ipopt::TNLPAdapter::y_d_tag_for_iterates_

private

Definition at line 568 of file IpTNLPAdapter.hpp.

◆ x_tag_for_g_

TaggedObject::Tag Ipopt::TNLPAdapter::x_tag_for_g_

private

Definition at line 569 of file IpTNLPAdapter.hpp.

◆ x_tag_for_jac_g_

TaggedObject::Tag Ipopt::TNLPAdapter::x_tag_for_jac_g_

private

Definition at line 570 of file IpTNLPAdapter.hpp.

◆ P_x_full_x_

SmartPtr<ExpansionMatrix> Ipopt::TNLPAdapter::P_x_full_x_

private

Expansion from fixed x (ipopt) to full x.

Definition at line 598 of file IpTNLPAdapter.hpp.

◆ P_x_full_x_space_

SmartPtr<ExpansionMatrixSpace> Ipopt::TNLPAdapter::P_x_full_x_space_

private

Definition at line 599 of file IpTNLPAdapter.hpp.

◆ P_x_x_L_

SmartPtr<ExpansionMatrix> Ipopt::TNLPAdapter::P_x_x_L_

private

Expansion from fixed x_L (ipopt) to full x.

Definition at line 602 of file IpTNLPAdapter.hpp.

◆ P_x_x_L_space_

SmartPtr<ExpansionMatrixSpace> Ipopt::TNLPAdapter::P_x_x_L_space_

private

Definition at line 603 of file IpTNLPAdapter.hpp.

◆ P_x_x_U_

SmartPtr<ExpansionMatrix> Ipopt::TNLPAdapter::P_x_x_U_

private

Expansion from fixed x_U (ipopt) to full x.

Definition at line 606 of file IpTNLPAdapter.hpp.

◆ P_x_x_U_space_

SmartPtr<ExpansionMatrixSpace> Ipopt::TNLPAdapter::P_x_x_U_space_

private

Definition at line 607 of file IpTNLPAdapter.hpp.

◆ P_c_g_space_

SmartPtr<ExpansionMatrixSpace> Ipopt::TNLPAdapter::P_c_g_space_

private

Expansion from c only (ipopt) to full ampl c.

Definition at line 610 of file IpTNLPAdapter.hpp.

◆ P_c_g_

SmartPtr<ExpansionMatrix> Ipopt::TNLPAdapter::P_c_g_

private

Definition at line 611 of file IpTNLPAdapter.hpp.

◆ P_d_g_space_

SmartPtr<ExpansionMatrixSpace> Ipopt::TNLPAdapter::P_d_g_space_

private

Expansion from d only (ipopt) to full ampl d.

Definition at line 614 of file IpTNLPAdapter.hpp.

◆ P_d_g_

SmartPtr<ExpansionMatrix> Ipopt::TNLPAdapter::P_d_g_

private

Definition at line 615 of file IpTNLPAdapter.hpp.

◆ jac_idx_map_

Index* Ipopt::TNLPAdapter::jac_idx_map_

private

Definition at line 617 of file IpTNLPAdapter.hpp.

◆ h_idx_map_

Index* Ipopt::TNLPAdapter::h_idx_map_

private

Definition at line 618 of file IpTNLPAdapter.hpp.

◆ x_fixed_map_

Index* Ipopt::TNLPAdapter::x_fixed_map_

private

Position of fixed variables.

This is required for a warm start

Definition at line 621 of file IpTNLPAdapter.hpp.

◆ jac_fixed_idx_map_

std::vector<Index> Ipopt::TNLPAdapter::jac_fixed_idx_map_

private

Index mapping of Jacobian w.r.t.

fixed variables.

Definition at line 624 of file IpTNLPAdapter.hpp.

◆ jac_fixed_iRow_

std::vector<Index> Ipopt::TNLPAdapter::jac_fixed_iRow_

private

Definition at line 625 of file IpTNLPAdapter.hpp.

◆ jac_fixed_jCol_

std::vector<Index> Ipopt::TNLPAdapter::jac_fixed_jCol_

private

Definition at line 626 of file IpTNLPAdapter.hpp.

◆ findiff_jac_nnz_

Index Ipopt::TNLPAdapter::findiff_jac_nnz_

private

Number of unique nonzeros in constraint Jacobian.

Definition at line 632 of file IpTNLPAdapter.hpp.

◆ findiff_jac_ia_

Index* Ipopt::TNLPAdapter::findiff_jac_ia_

private

Start position for nonzero indices in ja for each column of Jacobian.

Definition at line 634 of file IpTNLPAdapter.hpp.

◆ findiff_jac_ja_

Index* Ipopt::TNLPAdapter::findiff_jac_ja_

private

Ordered by columns, for each column the row indices in Jacobian.

Definition at line 636 of file IpTNLPAdapter.hpp.

◆ findiff_jac_postriplet_

Index* Ipopt::TNLPAdapter::findiff_jac_postriplet_

private

Position of entry in original triplet matrix.

Definition at line 638 of file IpTNLPAdapter.hpp.

◆ findiff_x_l_

Number* Ipopt::TNLPAdapter::findiff_x_l_

private

Copy of the lower bounds.

Definition at line 640 of file IpTNLPAdapter.hpp.

◆ findiff_x_u_

Number* Ipopt::TNLPAdapter::findiff_x_u_

private

Copy of the upper bounds.

Definition at line 642 of file IpTNLPAdapter.hpp.

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

src/Interfaces/IpTNLPAdapter.hpp

Public Types

Public Member Functions

Static Public Member Functions

Private Member Functions

Private Attributes

Method implementing the detection of linearly dependent equality constraints

Detailed Description

Member Enumeration Documentation

◆ FixedVariableTreatmentEnum

◆ DerivativeTestEnum

◆ JacobianApproxEnum

◆ GradientApproxEnum

Constructor & Destructor Documentation

◆ TNLPAdapter() [1/2]

◆ ~TNLPAdapter()

◆ TNLPAdapter() [2/2]

Member Function Documentation

◆ DECLARE_STD_EXCEPTION() [1/2]

◆ DECLARE_STD_EXCEPTION() [2/2]

◆ ProcessOptions()

◆ GetSpaces()

◆ GetBoundsInformation()

◆ GetStartingPoint()

◆ GetWarmStartIterate()

◆ Eval_f()

◆ Eval_grad_f()

◆ Eval_c()

◆ Eval_jac_c()

◆ Eval_d()

◆ Eval_jac_d()

◆ Eval_h()

◆ GetScalingParameters()

◆ FinalizeSolution()

◆ IntermediateCallBack()

◆ GetQuasiNewtonApproximationSpaces()

◆ CheckDerivatives()

◆ RegisterOptions()

◆ tnlp()

◆ ResortX()

◆ ResortG()

◆ ResortBounds()

◆ ResortBnds()

◆ ResortBoundMultipliers()

◆ GetFullDimensions()

◆ GetFixedVariables()

◆ GetPermutationMatrices()

◆ GetC_Rhs()

◆ operator=()

◆ DetermineDependentConstraints()

◆ update_local_x()

◆ update_local_lambda()

◆ internal_eval_g()

◆ internal_eval_jac_g()

◆ initialize_findiff_jac()

Member Data Documentation

◆ tnlp_

◆ jnlst_

◆ dependency_detector_

◆ nlp_lower_bound_inf_

◆ nlp_upper_bound_inf_

◆ fixed_variable_treatment_

◆ bound_relax_factor_

◆ derivative_test_

◆ derivative_test_perturbation_

◆ derivative_test_tol_

◆ derivative_test_print_all_

◆ derivative_test_first_index_

◆ warm_start_same_structure_

◆ hessian_approximation_

◆ num_linear_variables_

◆ jacobian_approximation_

◆ gradient_approximation_

◆ findiff_perturbation_

◆ point_perturbation_radius_

◆ dependency_detection_with_rhs_

◆ tol_

◆ n_full_x_

◆ n_full_g_

◆ nz_jac_c_

◆ nz_jac_c_no_extra_