Generic interface for sparse solvers to be coupled with ACADO Toolkit. More...

#include <sparse_solver.hpp>

Inheritance diagram for SparseSolver:

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Public Member Functions
virtual SparseSolver *	clone () const =0

virtual returnValue	factorize ()=0

virtual int_t	getNegativeEigenvalues ()

virtual int_t	getRank ()

virtual returnValue	getX (double *x)=0

virtual returnValue	getZeroPivots (int_t *&zeroPivots)

virtual SparseSolver &	operator= (const SparseSolver &rhs)

virtual returnValue	reset ()

virtual returnValue	setDimension (const int &n)=0

virtual returnValue	setIndices (const int rowIdx_, const int colIdx_)=0

virtual returnValue	setMatrix (double *A_)=0

virtual returnValue	setMatrixData (int_t dim, int_t numNonzeros, const int_t const airn, const int_t const acjn, const real_t *const avals)=0

virtual returnValue	setNumberOfEntries (const int &nDense_)=0

virtual returnValue	setPrintLevel (PrintLevel PrintLevel_)=0

virtual returnValue	setTolerance (double TOL)=0

virtual returnValue	solve (int_t dim, const real_t const rhs, real_t const sol)=0

virtual returnValue	solve (double *b)=0

virtual returnValue	solveTranspose (double *b)

	SparseSolver ()

	SparseSolver (const SparseSolver &rhs)

	SparseSolver ()

virtual	~SparseSolver ()

virtual	~SparseSolver ()

Protected Member Functions
returnValue	clear ()

returnValue	copy (const SparseSolver &rhs)

Detailed Description

Generic interface for sparse solvers to be coupled with ACADO Toolkit.

Base class for linear solvers that are used in a Schur-complement implementation in qpOASES.

The class SparseSolver is a generic interface for sparse solver to be coupled with ACADO Toolkit.

A SparseSolver deals with linear equations of the form

A * x = b

where A is (a possibly large but sparse) given matrix and b a given vector. Here, the non-zero elements of A need to be specified by one of the routines that are provided in this class. The aim of the sparse solver is to find the vector x, which is assumed to be uniquely defined by the above equation. For solving the linear equation the zero entries of the matrix A are used efficiently.

Author: Boris Houska, Hans Joachim Ferreau; Andreas Waechter, Dennis Janka

Version: 3.2

Date: 2012-2015

Definition at line 66 of file sparse_solver.hpp.

Constructor & Destructor Documentation

BEGIN_NAMESPACE_QPOASES SparseSolver::SparseSolver ( )

Default constructor.

Definition at line 47 of file sparse_solver.cpp.

SparseSolver::~SparseSolver ( )

virtual

Destructor.

Definition at line 52 of file sparse_solver.cpp.

SparseSolver::SparseSolver ( )

Default constructor.

SparseSolver::SparseSolver ( const SparseSolver & rhs )

Copy constructor (deep copy).

Parameters

rhs	Rhs object.

Definition at line 67 of file SparseSolver.cpp.

virtual SparseSolver::~SparseSolver ( )

virtual

Destructor.

Member Function Documentation

returnValue SparseSolver::clear ( )

protected

Frees all allocated memory.

Returns: SUCCESSFUL_RETURN

Definition at line 137 of file SparseSolver.cpp.

virtual SparseSolver* SparseSolver::clone ( ) const

pure virtual

Clone operator (deep copy).

Implemented in ACADOcsparse, SymmetricConjugateGradientMethod, NormalConjugateGradientMethod, and ConjugateGradientMethod.

returnValue SparseSolver::copy ( const SparseSolver & rhs )

protected

Copies all members from given rhs object.

Returns: SUCCESSFUL_RETURN

Parameters

rhs	Rhs object.

Definition at line 146 of file SparseSolver.cpp.

virtual returnValue SparseSolver::factorize ( )

pure virtual

Compute factorization of current matrix. This method must be called before solve.

int_t SparseSolver::getNegativeEigenvalues ( )

virtual

Return the number of negative eigenvalues.

Definition at line 107 of file SparseSolver.cpp.

int_t SparseSolver::getRank ( )

virtual

Return the rank after a factorization

Definition at line 115 of file SparseSolver.cpp.

virtual returnValue SparseSolver::getX ( double * x )

pure virtual

Returns the solution of the equation A*x = b if solved.

Returns: SUCCESSFUL_RETURN

Implemented in ACADOcsparse, and ConjugateGradientMethod.

returnValue SparseSolver::getZeroPivots ( int_t *& zeroPivots )

virtual

Returns the zero pivots in case the matrix is rank deficient

Definition at line 123 of file SparseSolver.cpp.

SparseSolver & SparseSolver::operator= ( const SparseSolver & rhs )

virtual

Assignment operator (deep copy).

Parameters

rhs	Rhs object.

Definition at line 85 of file SparseSolver.cpp.

returnValue SparseSolver::reset ( )

virtual

Clears all data structures.

Definition at line 99 of file SparseSolver.cpp.

virtual returnValue SparseSolver::setDimension ( const int & n )

pure virtual

Defines the dimension n of A R^{n n}

Returns: SUCCESSFUL_RETURN

Implemented in ACADOcsparse, and ConjugateGradientMethod.

virtual returnValue SparseSolver::setIndices	(	const int *	rowIdx_,
		const int *	colIdx_
	)

pure virtual

Sets an index list containing the positions of the
non-zero elements in the matrix A.

Implemented in ACADOcsparse, ConjugateGradientMethod, SymmetricConjugateGradientMethod, and NormalConjugateGradientMethod.

virtual returnValue SparseSolver::setMatrix ( double * A_ )

pure virtual

Sets the non-zero elements of the matrix A. The double* A
is assumed to contain nDense entries corresponding to
non-zero elements of A.

Implemented in ACADOcsparse, and ConjugateGradientMethod.

virtual returnValue SparseSolver::setMatrixData	(	int_t	dim,
		int_t	numNonzeros,
		const int_t *const	airn,
		const int_t *const	acjn,
		const real_t *const	avals
	)

pure virtual

Set new matrix data. The matrix is to be provided in the Harwell-Boeing format. Only the lower triangular part should be set.

Parameters

dim	Dimension of the linear system.
numNonzeros	Number of nonzeros in the matrix.
airn	Row indices for each matrix entry.
acjn	Column indices for each matrix entry.
avals	Values for each matrix entry.

virtual returnValue SparseSolver::setNumberOfEntries ( const int & nDense_ )

pure virtual

Defines the number of non-zero elements in the
matrix A

Returns: SUCCESSFUL_RETURN

Implemented in ACADOcsparse, and ConjugateGradientMethod.

virtual returnValue SparseSolver::setPrintLevel ( PrintLevel PrintLevel_ )

pure virtual

Sets the print level.

Returns: SUCCESSFUL_RETURN

Implemented in ACADOcsparse, and ConjugateGradientMethod.

virtual returnValue SparseSolver::setTolerance ( double TOL )

pure virtual

Sets the required tolerance (accuracy) for the solution of
the linear equation. For large tolerances an iterative
algorithm might converge earlier.

Requires || A*x - b || <= TOL

The norm || . || is possibly scaled by a preconditioner.

Returns: SUCCESSFUL_RETURN

Implemented in ACADOcsparse, and ConjugateGradientMethod.

virtual returnValue SparseSolver::solve	(	int_t	dim,
		const real_t *const	rhs,
		real_t *const	sol
	)

pure virtual

Solve linear system with most recently set matrix data.

Parameters

dim	Dimension of the linear system.
rhs	Values for the right hand side.
sol	Solution of the linear system.

virtual returnValue SparseSolver::solve ( double * b )

pure virtual

Solves the system A*x = b for the specified data.

Returns: SUCCESSFUL_RETURN
RET_LINEAR_SYSTEM_NUMERICALLY_SINGULAR

Implemented in ACADOcsparse, and ConjugateGradientMethod.

returnValue SparseSolver::solveTranspose ( double * b )

virtual

Solves the system A^T*x = b for the specified data.

Returns: SUCCESSFUL_RETURN
RET_LINEAR_SYSTEM_NUMERICALLY_SINGULAR

Reimplemented in ACADOcsparse.

Definition at line 58 of file sparse_solver.cpp.

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

Public Member Functions

Protected Member Functions

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation