MatlabProgram Class Reference

#include <matlabprogram.h>

Inheritance diagram for MatlabProgram:

Collaboration diagram for MatlabProgram:

Public Member Functions
	MatlabProgram (const ArrayOfMatrices &x0, const ArrayOfMatrices &lb, const ArrayOfMatrices &ub, const Matrix &constraintlb, const Matrix &constraintub, const MatlabFunctionHandle &objFunc, const MatlabFunctionHandle &gradFunc, const MatlabFunctionHandle &constraintFunc, const MatlabFunctionHandle &jacobianFunc, const MatlabFunctionHandle &hessianFunc, const MatlabFunctionHandle &iterFunc, const mxArray auxData, ArrayOfMatrices &xsol, bool useQuasiNewton, Multipliers initialMultipliers=0, Multipliers *multipliers=0)
virtual	~MatlabProgram ()
char *	geterrormsg () const
int	getnumiterations () const
virtual bool	get_nlp_info (int &numVariables, int &numConstraints, int &sizeOfJ, int &sizeOfH, IndexStyleEnum &indexStyle)
	overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.
virtual bool	get_bounds_info (int numVariables, double lbptr, double ubptr, int numConstraints, double clbptr, double cubptr)
	overload this method to return the information about the bound on the variables and constraints.
virtual bool	get_starting_point (int numVariables, bool initializeVars, double variables, bool initializez, double zl, double zu, int numConstraints, bool initializeLambda, double lambda)
	overload this method to return the starting point.
virtual bool	eval_f (int numVariables, const double *variables, bool ignoreThis, double &objective)
	overload this method to return the value of the objective function
virtual bool	eval_grad_f (int numVariables, const double variables, bool ignoreThis, double gradient)
	overload this method to return the vector of the gradient of the objective w.r.t.
virtual bool	eval_g (int numVariables, const double variables, bool ignoreThis, int numConstraints, double constraints)
	overload this method to return the vector of constraint values
virtual bool	eval_jac_g (int numVariables, const double variables, bool ignoreThis, int numConstraints, int sizeOfJ, int rows, int cols, double Jacobian)
	overload this method to return the jacobian of the constraints.
virtual bool	eval_h (int numVariables, const double variables, bool ignoreThis, double sigma, int numConstraints, const double multipliers, bool ignoreThisToo, int sizeOfH, int rows, int cols, double *Hessian)
	overload this method to return the hessian of the lagrangian.
virtual void	finalize_solution (SolverReturn status, int numVariables, const double variables, const double zl, const double zu, int numConstraints, const double constraints, const double lambda, double objective, const IpoptData ip_data, IpoptCalculatedQuantities *ip_cq)
virtual bool	intermediate_callback (AlgorithmMode mode, int iteration, double objective, double inf_pr, double inf_du, double mu, double d_norm, double regularization_ize, double alpha_du, double alpha_pr, int ls_trials, const IpoptData ip_data, IpoptCalculatedQuantities ip_cq)
Protected Member Functions
	MatlabProgram (const MatlabProgram &source)
MatlabProgram &	operator= (const MatlabProgram &source)
	Overloaded Equals Operator.
Protected Attributes
const ArrayOfMatrices &	x0
const ArrayOfMatrices &	lb
const ArrayOfMatrices &	ub
const Matrix &	constraintlb
const Matrix &	constraintub
const mxArray *	auxData
ArrayOfMatrices &	xsol
ArrayOfMatrices *	x
Multipliers *	initialMultipliers
Multipliers *	multipliers
Array< double > *	lambda
int	numiter
mxArray **	prhs
mxArray *	lambdarhs
bool	useQuasiNewton
SparseMatrixStructure *	JacobianStructure
SparseMatrixStructure *	HessianStructure
const MatlabFunctionHandle &	objFunc
const MatlabFunctionHandle &	gradFunc
const MatlabFunctionHandle &	constraintFunc
const MatlabFunctionHandle &	jacobianFunc
const MatlabFunctionHandle &	hessianFunc
const MatlabFunctionHandle &	iterFunc
Private Member Functions
double	computeObjective (const ArrayOfMatrices &x)
void	computeGradient (const ArrayOfMatrices &x, ArrayOfMatrices &grad)
void	computeConstraints (const ArrayOfMatrices &x, Array< double > &g)
void	computeJacobian (const ArrayOfMatrices &x, double *Jacobian)
void	computeHessian (const ArrayOfMatrices &x, const Array< double > &lambda, double sigma, double *Hessian)
mxArray *	callMatlabJacobianRoutine (const ArrayOfMatrices &x, bool returnStructureOnly=true)
mxArray *	callMatlabHessianRoutine (const ArrayOfMatrices &x, const Array< double > &lambda, bool returnStructureOnly=true, double sigma=0)

Detailed Description

Definition at line 30 of file matlabprogram.h.

Constructor & Destructor Documentation

MatlabProgram::MatlabProgram	(	const ArrayOfMatrices &	x0,
		const ArrayOfMatrices &	lb,
		const ArrayOfMatrices &	ub,
		const Matrix &	constraintlb,
		const Matrix &	constraintub,
		const MatlabFunctionHandle &	objFunc,
		const MatlabFunctionHandle &	gradFunc,
		const MatlabFunctionHandle &	constraintFunc,
		const MatlabFunctionHandle &	jacobianFunc,
		const MatlabFunctionHandle &	hessianFunc,
		const MatlabFunctionHandle &	iterFunc,
		const mxArray *	auxData,
		ArrayOfMatrices &	xsol,
		bool	useQuasiNewton,
		Multipliers *	initialMultipliers = `0`,
		Multipliers *	multipliers = `0`
	)

virtual MatlabProgram::~MatlabProgram ( ) [virtual]

MatlabProgram::MatlabProgram ( const MatlabProgram & source ) [protected]

Member Function Documentation

char* MatlabProgram::geterrormsg ( ) const

int MatlabProgram::getnumiterations ( ) const [inline]

Definition at line 57 of file matlabprogram.h.

virtual bool MatlabProgram::get_nlp_info	(	int &	n,
		int &	m,
		int &	nnz_jac_g,
		int &	nnz_h_lag,
		IndexStyleEnum &	index_style
	)			`[virtual]`

overload this method to return the number of variables and constraints, and the number of non-zeros in the jacobian and the hessian.

The index_style parameter lets you specify C or Fortran style indexing for the sparse matrix iRow and jCol parameters. C_STYLE is 0-based, and FORTRAN_STYLE is 1-based.

Implements Ipopt::TNLP.

virtual bool MatlabProgram::get_bounds_info	(	int	n,
		double *	x_l,
		double *	x_u,
		int	m,
		double *	g_l,
		double *	g_u
	)			`[virtual]`

overload this method to return the information about the bound on the variables and constraints.

The value that indicates that a bound does not exist is specified in the parameters nlp_lower_bound_inf and nlp_upper_bound_inf. By default, nlp_lower_bound_inf is -1e19 and nlp_upper_bound_inf is 1e19. (see TNLPAdapter)

Implements Ipopt::TNLP.

virtual bool MatlabProgram::get_starting_point	(	int	n,
		bool	init_x,
		double *	x,
		bool	init_z,
		double *	z_L,
		double *	z_U,
		int	m,
		bool	init_lambda,
		double *	lambda
	)			`[virtual]`

overload this method to return the starting point.

The bools init_x and init_lambda are both inputs and outputs. As inputs, they indicate whether or not the algorithm wants you to initialize x and lambda respectively. If, for some reason, the algorithm wants you to initialize these and you cannot, set the respective bool to false.

Implements Ipopt::TNLP.

virtual bool MatlabProgram::eval_f	(	int	n,
		const double *	x,
		bool	new_x,
		double &	obj_value
	)			`[virtual]`

overload this method to return the value of the objective function

Implements Ipopt::TNLP.

virtual bool MatlabProgram::eval_grad_f	(	int	n,
		const double *	x,
		bool	new_x,
		double *	grad_f
	)			`[virtual]`

overload this method to return the vector of the gradient of the objective w.r.t.

x

Implements Ipopt::TNLP.

virtual bool MatlabProgram::eval_g	(	int	n,
		const double *	x,
		bool	new_x,
		int	m,
		double *	g
	)			`[virtual]`

overload this method to return the vector of constraint values

Implements Ipopt::TNLP.

virtual bool MatlabProgram::eval_jac_g	(	int	n,
		const double *	x,
		bool	new_x,
		int	m,
		int	nele_jac,
		int *	iRow,
		int *	jCol,
		double *	values
	)			`[virtual]`

overload this method to return the jacobian of the constraints.

The vectors iRow and jCol only need to be set once. The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL.

Implements Ipopt::TNLP.

virtual bool MatlabProgram::eval_h	(	int	n,
		const double *	x,
		bool	new_x,
		double	obj_factor,
		int	m,
		const double *	lambda,
		bool	new_lambda,
		int	nele_hess,
		int *	iRow,
		int *	jCol,
		double *	values
	)			`[virtual]`

overload this method to return the hessian of the lagrangian.

The vectors iRow and jCol only need to be set once (during the first call). The first call is used to set the structure only (iRow and jCol will be non-NULL, and values will be NULL) For subsequent calls, iRow and jCol will be NULL. This matrix is symmetric - specify the lower diagonal only. A default implementation is provided, in case the user wants to se quasi-Newton approximations to estimate the second derivatives and doesn't not neet to implement this method.

Reimplemented from Ipopt::TNLP.

virtual void MatlabProgram::finalize_solution	(	SolverReturn	status,
		int	numVariables,
		const double *	variables,
		const double *	zl,
		const double *	zu,
		int	numConstraints,
		const double *	constraints,
		const double *	lambda,
		double	objective,
		const IpoptData *	ip_data,
		IpoptCalculatedQuantities *	ip_cq
	)			`[virtual]`

virtual bool MatlabProgram::intermediate_callback	(	AlgorithmMode	mode,
		int	iteration,
		double	objective,
		double	inf_pr,
		double	inf_du,
		double	mu,
		double	d_norm,
		double	regularization_ize,
		double	alpha_du,
		double	alpha_pr,
		int	ls_trials,
		const IpoptData *	ip_data,
		IpoptCalculatedQuantities *	ip_cq
	)			`[virtual]`

MatlabProgram& MatlabProgram::operator= ( const MatlabProgram & ) [inline, protected]

Overloaded Equals Operator.

Reimplemented from Ipopt::TNLP.

Definition at line 175 of file matlabprogram.h.

double MatlabProgram::computeObjective ( const ArrayOfMatrices & x ) [private]

void MatlabProgram::computeGradient	(	const ArrayOfMatrices &	x,
		ArrayOfMatrices &	grad
	)			`[private]`

void MatlabProgram::computeConstraints	(	const ArrayOfMatrices &	x,
		Array< double > &	g
	)			`[private]`

void MatlabProgram::computeJacobian	(	const ArrayOfMatrices &	x,
		double *	Jacobian
	)			`[private]`

void MatlabProgram::computeHessian	(	const ArrayOfMatrices &	x,
		const Array< double > &	lambda,
		double	sigma,
		double *	Hessian
	)			`[private]`

mxArray* MatlabProgram::callMatlabJacobianRoutine	(	const ArrayOfMatrices &	x,
		bool	returnStructureOnly = `true`
	)			`[private]`

mxArray* MatlabProgram::callMatlabHessianRoutine	(	const ArrayOfMatrices &	x,
		const Array< double > &	lambda,
		bool	returnStructureOnly = `true`,
		double	sigma = `0`
	)			`[private]`