SymSparseMat Class Reference

Interfaces matrix-vector operations tailored to symmetric sparse matrices. More...

#include <Matrices.hpp>

Inheritance diagram for SymSparseMat:

List of all members.

Public Member Functions
	SymSparseMat ()
	SymSparseMat (int nr, int nc, sparse_int_t *r, sparse_int_t *c, real_t *v)
	SymSparseMat (int nr, int nc, int ld, const real_t *const v)
virtual Matrix *	duplicate () const
virtual SymmetricMatrix *	duplicateSym () const
virtual returnValue	bilinear (const Indexlist *const icols, int xN, const real_t *x, int xLD, real_t *y, int yLD) const
virtual void	free ()=0
virtual real_t	diag (int i) const =0
virtual BooleanType	isDiag () const =0
virtual real_t	getNorm (int type=2) const =0
virtual real_t	getRowNorm (int rNum, int type=2) const =0
virtual returnValue	getRow (int rNum, const Indexlist *const icols, real_t alpha, real_t *row) const =0
virtual returnValue	getCol (int cNum, const Indexlist *const irows, real_t alpha, real_t *col) const =0
virtual returnValue	times (int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const =0
virtual returnValue	times (const Indexlist *const irows, const Indexlist *const icols, int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD, BooleanType yCompr=BT_TRUE) const =0
virtual returnValue	transTimes (int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const =0
virtual returnValue	transTimes (const Indexlist *const irows, const Indexlist *const icols, int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const =0
virtual returnValue	addToDiag (real_t alpha)=0
virtual real_t *	full () const =0
virtual returnValue	print (const char *name=0) const =0
BooleanType	needToFreeMemory () const
void	doFreeMemory ()
void	doNotFreeMemory ()
virtual void	free ()
virtual real_t	diag (int i) const
virtual BooleanType	isDiag () const
virtual real_t	getNorm (int type=2) const
virtual real_t	getRowNorm (int rNum, int type=2) const
virtual returnValue	getRow (int rNum, const Indexlist *const icols, real_t alpha, real_t *row) const
virtual returnValue	getCol (int cNum, const Indexlist *const irows, real_t alpha, real_t *col) const
virtual returnValue	times (int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const
virtual returnValue	times (const Indexlist *const irows, const Indexlist *const icols, int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD, BooleanType yCompr=BT_TRUE) const
virtual returnValue	transTimes (int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const
virtual returnValue	transTimes (const Indexlist *const irows, const Indexlist *const icols, int xN, real_t alpha, const real_t *x, int xLD, real_t beta, real_t *y, int yLD) const
virtual returnValue	addToDiag (real_t alpha)
sparse_int_t *	createDiagInfo ()
virtual real_t *	full () const
virtual returnValue	print (const char *name=0) const
Protected Attributes
BooleanType	freeMemory
int	nRows
int	nCols
sparse_int_t *	ir
sparse_int_t *	jc
sparse_int_t *	jd
real_t *	val

---

Detailed Description

Symmetric sparse matrix class (column compressed format).

Author:

Andreas Potschka, Christian Kirches, Hans Joachim Ferreau

Version:

3.0

Date:

2011-2014

---

Constructor & Destructor Documentation

SymSparseMat::SymSparseMat

(

)

[inline]

Default constructor.

Referenced by duplicateSym().

SymSparseMat::SymSparseMat	(	int	nr,
		int	nc,
		sparse_int_t *	r,
		sparse_int_t *	c,
		real_t *	v
	)		[inline]

Constructor with arguments.

Parameters:

nr	Number of rows.
nc	Number of columns.
r	Row indices (length).
c	Indices to first entry of columns (nCols+1).
v	Vector of entries (length).

SymSparseMat::SymSparseMat	(	int	nr,
		int	nc,
		int	ld,
		const real_t *const	v
	)		[inline]

Constructor from dense matrix.

Parameters:

nr	Number of rows.
nc	Number of columns.
ld	Leading dimension.
v	Row major stored matrix elements.

---

Member Function Documentation

virtual returnValue Matrix::addToDiag

(

real_t

alpha

)

[pure virtual, inherited]

Adds given offset to diagonal of matrix.

Returns:

SUCCESSFUL_RETURN
RET_NO_DIAGONAL_AVAILABLE

Parameters:

alpha

Diagonal offset.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblemB::regulariseHessian().

returnValue SparseMatrix::addToDiag

(

real_t

alpha

)

[virtual, inherited]

Adds given offset to diagonal of matrix.

Returns:

SUCCESSFUL_RETURN
RET_NO_DIAGONAL_AVAILABLE

Parameters:

alpha

Diagonal offset.

Implements Matrix.

References BT_FALSE, SparseMatrix::ir, isZero(), SparseMatrix::jd, SparseMatrix::nCols, SparseMatrix::nRows, RET_DIAGONAL_NOT_INITIALISED, RET_NO_DIAGONAL_AVAILABLE, SUCCESSFUL_RETURN, THROWERROR, and SparseMatrix::val.

returnValue SymSparseMat::bilinear	(	const Indexlist *const	icols,
		int	xN,
		const real_t *	x,
		int	xLD,
		real_t *	y,
		int	yLD
	)		const [virtual]

Compute bilinear form y = x'*H*x using submatrix given by index list.

Returns:

SUCCESSFUL_RETURN

Parameters:

icols	Index list specifying columns of x.
xN	Number of vectors to multiply.
x	Input vector to be multiplied (uncompressed).
xLD	Leading dimension of input x.
y	Output vector of results (compressed).
yLD	Leading dimension of output y.

Implements SymmetricMatrix.

References SparseMatrix::ir, Indexlist::iSort, SparseMatrix::jc, SparseMatrix::jd, Indexlist::length, Indexlist::number, RET_DIAGONAL_NOT_INITIALISED, SUCCESSFUL_RETURN, THROWERROR, and SparseMatrix::val.

Referenced by QProblem::computeProjectedCholesky().

sparse_int_t * SparseMatrix::createDiagInfo

(

)

[inherited]

Create jd field from ir and jc.

Returns:

Pointer to jd.

References SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::jd, SparseMatrix::nCols, and sparse_int_t.

Referenced by QProblemB::createDiagSparseMat(), main(), and solveOQPbenchmark().

virtual real_t Matrix::diag

(

int

i

)

const [pure virtual, inherited]

Returns i-th diagonal entry.

Returns:

i-th diagonal entry

Parameters:

i

Index.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblemB::determineHessianType(), QProblem::removeBound(), and QProblemB::removeBound().

real_t SparseMatrix::diag

(

int

i

)

const [virtual, inherited]

Returns i-th diagonal entry.

Returns:

i-th diagonal entry (or INFTY if diagonal does not exist)

Parameters:

i

Index.

Implements Matrix.

References INFTY, SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::jd, RET_DIAGONAL_NOT_INITIALISED, THROWERROR, and SparseMatrix::val.

void Matrix::doFreeMemory

(

)

[inline, inherited]

Enables de-allocation of internal memory.

References BT_TRUE, and Matrix::freeMemory.

Referenced by QProblemB::createDiagSparseMat(), DenseMatrix::duplicate(), SparseMatrix::duplicate(), SparseMatrixRow::duplicate(), SymDenseMat::duplicateSym(), duplicateSym(), QProblemB::setupQPdataFromFile(), QProblem::setupQPdataFromFile(), solveOQPbenchmark(), SparseMatrix::SparseMatrix(), and SparseMatrixRow::SparseMatrixRow().

void Matrix::doNotFreeMemory

(

)

[inline, inherited]

Disables de-allocation of internal memory.

Referenced by SparseMatrix::free(), SparseMatrixRow::free(), Matrix::Matrix(), SparseMatrix::SparseMatrix(), and SparseMatrixRow::SparseMatrixRow().

Matrix * SymSparseMat::duplicate

(

)

const [virtual]

Returns a deep-copy of the Matrix object.

Returns:

Deep-copy of Matrix object

Reimplemented from SparseMatrix.

References duplicateSym().

SymmetricMatrix * SymSparseMat::duplicateSym

(

)

const [virtual]

Returns a deep-copy of the SymmetricMatrix object.

Returns:

Deep-copy of SymmetricMatrix object

Implements SymmetricMatrix.

References Matrix::doFreeMemory(), SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::jd, SparseMatrix::nCols, SparseMatrix::nRows, real_t, sparse_int_t, SymSparseMat(), and SparseMatrix::val.

Referenced by duplicate().

virtual void Matrix::free

(

)

[pure virtual, inherited]

Frees all internal memory.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

void SparseMatrix::free

(

)

[virtual, inherited]

Frees all internal memory.

Implements Matrix.

References Matrix::doNotFreeMemory(), SparseMatrix::ir, SparseMatrix::jc, and SparseMatrix::val.

Referenced by SparseMatrix::~SparseMatrix().

virtual real_t* Matrix::full

(

)

const [pure virtual, inherited]

Allocates and creates dense matrix array in row major format.

Note: Calling function has to free allocated memory!

Returns:

Pointer to matrix array.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblem::writeQpDataIntoMatFile().

real_t * SparseMatrix::full

(

)

const [virtual, inherited]

Allocates and creates dense matrix array in row major format.

Note: Calling function has to free allocated memory!

Returns:

Pointer to matrix array.

Implements Matrix.

References SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::nCols, SparseMatrix::nRows, real_t, and SparseMatrix::val.

Referenced by main(), and SparseMatrix::print().

virtual returnValue Matrix::getCol	(	int	cNum,
		const Indexlist *const	irows,
		real_t	alpha,
		real_t *	col
	)		const [pure virtual, inherited]

Retrieve indexed entries of matrix column multiplied by alpha.

Returns:

SUCCESSFUL_RETURN

Parameters:

cNum	Column number.
irows	Index list specifying rows.
alpha	Scalar factor.
col	Output column vector.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblemB::computeCholesky(), QProblem::computeProjectedCholesky(), and QProblem::removeBound().

returnValue SparseMatrix::getCol	(	int	cNum,
		const Indexlist *const	irows,
		real_t	alpha,
		real_t *	col
	)		const [virtual, inherited]

Retrieve indexed entries of matrix column multiplied by alpha.

Parameters:

cNum	Column number.
irows	Index list specifying rows.
alpha	Scalar factor.
col	Output column vector.

Implements Matrix.

References BT_TRUE, SparseMatrix::ir, isEqual(), Indexlist::iSort, SparseMatrix::jc, Indexlist::number, SUCCESSFUL_RETURN, and SparseMatrix::val.

virtual real_t Matrix::getNorm

(

int

type = 2

)

const [pure virtual, inherited]

Get the N-norm of the matrix

Returns:

N-norm of the matrix

Parameters:

type	Norm type, 1: one-norm, 2: Euclidean norm.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblemB::regulariseHessian().

real_t SparseMatrix::getNorm

(

int

type = 2

)

const [virtual, inherited]

Get the N-norm of the matrix

Returns:

N-norm of the matrix

Parameters:

type	Norm type, 1: one-norm, 2: Euclidean norm.

Implements Matrix.

References SparseMatrix::jc, SparseMatrix::nCols, REFER_NAMESPACE_QPOASES, and SparseMatrix::val.

virtual returnValue Matrix::getRow	(	int	rNum,
		const Indexlist *const	icols,
		real_t	alpha,
		real_t *	row
	)		const [pure virtual, inherited]

Retrieve indexed entries of matrix row multiplied by alpha.

Returns:

SUCCESSFUL_RETURN

Parameters:

rNum	Row number.
icols	Index list specifying columns.
alpha	Scalar factor.
row	Output row vector.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblem::addConstraint(), QProblem::addConstraint_checkLI(), QProblem::addConstraint_ensureLI(), and QProblemB::removeBound().

returnValue SparseMatrix::getRow	(	int	rNum,
		const Indexlist *const	icols,
		real_t	alpha,
		real_t *	row
	)		const [virtual, inherited]

Retrieve indexed entries of matrix row multiplied by alpha.

Parameters:

rNum	Row number.
icols	Index list specifying columns.
alpha	Scalar factor.
row	Output row vector.

Implements Matrix.

References BT_TRUE, SparseMatrix::ir, isEqual(), Indexlist::iSort, SparseMatrix::jc, Indexlist::length, SparseMatrix::nCols, Indexlist::number, SUCCESSFUL_RETURN, and SparseMatrix::val.

virtual real_t Matrix::getRowNorm	(	int	rNum,
		int	type = 2
	)		const [pure virtual, inherited]

Get the N-norm of a row

Returns:

N-norm of row rNum

Parameters:

rNum	Row number.
type	Norm type, 1: one-norm, 2: Euclidean norm.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblem::setA().

real_t SparseMatrix::getRowNorm	(	int	rNum,
		int	type = 2
	)		const [virtual, inherited]

Get the N-norm of a row

Returns:

N-norm of row rNum

Parameters:

rNum	Row number.
type	Norm type, 1: one-norm, 2: Euclidean norm.

Implements Matrix.

References getAbs(), getSqrt(), INFTY, SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::nCols, real_t, REFER_NAMESPACE_QPOASES, RET_INVALID_ARGUMENTS, THROWERROR, and SparseMatrix::val.

virtual BooleanType Matrix::isDiag

(

)

const [pure virtual, inherited]

Checks whether matrix is square and diagonal.

Returns:

BT_TRUE iff matrix is square and diagonal;
BT_FALSE otherwise.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblemB::determineHessianType().

BooleanType SparseMatrix::isDiag

(

)

const [virtual, inherited]

Checks whether matrix is square and diagonal.

Returns:

BT_TRUE iff matrix is square and diagonal;
BT_FALSE otherwise.

Implements Matrix.

References BT_FALSE, BT_TRUE, SparseMatrix::ir, SparseMatrix::jc, SparseMatrix::nCols, and SparseMatrix::nRows.

BooleanType Matrix::needToFreeMemory

(

)

const [inline, inherited]

Returns whether internal memory needs to be de-allocated.

Returns:

BT_TRUE iff internal memory needs to be de-allocated,
BT_FALSE otherwise

References Matrix::freeMemory.

Referenced by DenseMatrix::duplicate(), SymDenseMat::duplicateSym(), DenseMatrix::~DenseMatrix(), SparseMatrix::~SparseMatrix(), and SparseMatrixRow::~SparseMatrixRow().

virtual returnValue Matrix::print

(

const char *

name = 0

)

const [pure virtual, inherited]

Prints matrix to screen.

Returns:

SUCCESSFUL_RETURN

Parameters:

name	Name of matrix.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

returnValue SparseMatrix::print

(

const char *

name = 0

)

const [virtual, inherited]

Prints matrix to screen.

Returns:

SUCCESSFUL_RETURN

Parameters:

name	Name of matrix.

Implements Matrix.

References SparseMatrix::full(), SparseMatrix::nCols, SparseMatrix::nRows, real_t, and REFER_NAMESPACE_QPOASES.

virtual returnValue Matrix::times	(	int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [pure virtual, inherited]

Evaluate Y=alpha*A*X + beta*Y.

Returns:

SUCCESSFUL_RETURN

Parameters:

xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblem::determineStepDirection(), QProblemB::determineStepDirection(), QProblem::ensureNonzeroCurvature(), SolutionAnalysis::getMaxKKTviolation(), QProblemB::getObjVal(), QProblem::performStep(), QProblemB::printIteration(), QProblem::printIteration(), QProblem::removeBound(), QProblem::removeConstraint(), QProblem::setA(), QProblem::setupAuxiliaryQP(), QProblem::setupAuxiliaryQPgradient(), QProblemB::setupAuxiliaryQPgradient(), and QProblem::setupAuxiliaryQPsolution().

virtual returnValue Matrix::times	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD,
		BooleanType	yCompr = BT_TRUE
	)		const [pure virtual, inherited]

Evaluate matrix vector product with submatrix given by Indexlist.

Returns:

SUCCESSFUL_RETURN

Parameters:

irows	Index list specifying rows.
icols	Index list specifying columns.
xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.
yCompr	Compressed storage for y.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

returnValue SparseMatrix::times	(	int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [virtual, inherited]

Evaluate Y=alpha*A*X + beta*Y.

Parameters:

xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implements Matrix.

References BT_FALSE, BT_TRUE, SparseMatrix::ir, isEqual(), isZero(), SparseMatrix::jc, SparseMatrix::nCols, SparseMatrix::nRows, SUCCESSFUL_RETURN, and SparseMatrix::val.

returnValue SparseMatrix::times	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD,
		BooleanType	yCompr = BT_TRUE
	)		const [virtual, inherited]

Evaluate matrix vector product with submatrix given by Indexlist.

Parameters:

irows	Index list specifying rows.
icols	Index list specifying columns.
xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.
yCompr	Compressed storage for y.

Implements Matrix.

References BT_FALSE, BT_TRUE, SparseMatrix::ir, isEqual(), Indexlist::iSort, isZero(), SparseMatrix::jc, Indexlist::length, SparseMatrix::nCols, Indexlist::number, SUCCESSFUL_RETURN, and SparseMatrix::val.

virtual returnValue Matrix::transTimes	(	int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [pure virtual, inherited]

Evaluate Y=alpha*A'*X + beta*Y.

Returns:

SUCCESSFUL_RETURN

Parameters:

xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

Referenced by QProblem::addBound_ensureLI(), QProblem::addConstraint_ensureLI(), QProblem::determineStepDirection(), SolutionAnalysis::getMaxKKTviolation(), QProblem::printIteration(), and QProblem::setupAuxiliaryQPgradient().

virtual returnValue Matrix::transTimes	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [pure virtual, inherited]

Evaluate matrix transpose vector product.

Returns:

SUCCESSFUL_RETURN

Parameters:

irows	Index list specifying rows.
icols	Index list specifying columns.
xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

returnValue SparseMatrix::transTimes	(	int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [virtual, inherited]

Evaluate Y=alpha*A'*X + beta*Y.

Parameters:

xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implements Matrix.

References BT_FALSE, BT_TRUE, SparseMatrix::ir, isEqual(), isZero(), SparseMatrix::jc, SparseMatrix::nCols, SUCCESSFUL_RETURN, and SparseMatrix::val.

returnValue SparseMatrix::transTimes	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int	xN,
		real_t	alpha,
		const real_t *	x,
		int	xLD,
		real_t	beta,
		real_t *	y,
		int	yLD
	)		const [virtual, inherited]

Evaluate matrix transpose vector product.

Parameters:

irows	Index list specifying rows.
icols	Index list specifying columns.
xN	Number of vectors to multiply.
alpha	Scalar factor for matrix vector product.
x	Input vector to be multiplied.
xLD	Leading dimension of input x.
beta	Scalar factor for y.
y	Output vector of results.
yLD	Leading dimension of output y.

Implements Matrix.

References BT_FALSE, BT_TRUE, SparseMatrix::ir, isEqual(), Indexlist::iSort, isZero(), SparseMatrix::jc, Indexlist::length, Indexlist::number, SUCCESSFUL_RETURN, and SparseMatrix::val.

---

Member Data Documentation

BooleanType Matrix::freeMemory [protected, inherited]

Indicating whether internal memory needs to be de-allocated.

Referenced by Matrix::doFreeMemory(), and Matrix::needToFreeMemory().

sparse_int_t* SparseMatrix::ir [protected, inherited]

Row indices (length).

Referenced by SparseMatrix::addToDiag(), bilinear(), SparseMatrix::createDiagInfo(), SparseMatrix::diag(), SparseMatrix::duplicate(), duplicateSym(), SparseMatrix::free(), SparseMatrix::full(), SparseMatrix::getCol(), SparseMatrix::getRow(), SparseMatrix::getRowNorm(), SparseMatrix::isDiag(), SparseMatrix::SparseMatrix(), SparseMatrix::times(), and SparseMatrix::transTimes().

sparse_int_t* SparseMatrix::jc [protected, inherited]

Indices to first entry of columns (nCols+1).

Referenced by bilinear(), SparseMatrix::createDiagInfo(), SparseMatrix::diag(), SparseMatrix::duplicate(), duplicateSym(), SparseMatrix::free(), SparseMatrix::full(), SparseMatrix::getCol(), SparseMatrix::getNorm(), SparseMatrix::getRow(), SparseMatrix::getRowNorm(), SparseMatrix::isDiag(), SparseMatrix::SparseMatrix(), SparseMatrix::times(), and SparseMatrix::transTimes().

sparse_int_t* SparseMatrix::jd [protected, inherited]

Indices to first entry of lower triangle (including diagonal) (nCols).

Referenced by SparseMatrix::addToDiag(), bilinear(), SparseMatrix::createDiagInfo(), SparseMatrix::diag(), SparseMatrix::duplicate(), duplicateSym(), and SparseMatrix::~SparseMatrix().

int SparseMatrix::nCols [protected, inherited]

Number of columns.

Referenced by SparseMatrix::addToDiag(), SparseMatrix::createDiagInfo(), SparseMatrix::duplicate(), duplicateSym(), SparseMatrix::full(), SparseMatrix::getNorm(), SparseMatrix::getRow(), SparseMatrix::getRowNorm(), SparseMatrix::isDiag(), SparseMatrix::print(), SparseMatrix::SparseMatrix(), SparseMatrix::times(), and SparseMatrix::transTimes().

int SparseMatrix::nRows [protected, inherited]

Number of rows.

Referenced by SparseMatrix::addToDiag(), SparseMatrix::duplicate(), duplicateSym(), SparseMatrix::full(), SparseMatrix::isDiag(), SparseMatrix::print(), SparseMatrix::SparseMatrix(), and SparseMatrix::times().

real_t* SparseMatrix::val [protected, inherited]

Vector of entries (length).

Referenced by SparseMatrix::addToDiag(), bilinear(), SparseMatrix::diag(), SparseMatrix::duplicate(), duplicateSym(), SparseMatrix::free(), SparseMatrix::full(), SparseMatrix::getCol(), SparseMatrix::getNorm(), SparseMatrix::getRow(), SparseMatrix::getRowNorm(), SparseMatrix::SparseMatrix(), SparseMatrix::times(), and SparseMatrix::transTimes().

---

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

• include/qpOASES/Matrices.hpp
• src/Matrices.cpp