SparseMatrix Class Reference

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

#include <Matrices.hpp>

Inheritance diagram for SparseMatrix:

List of all members.

Public Member Functions
	SparseMatrix ()
	SparseMatrix (int nr, int nc, sparse_int_t *r, sparse_int_t *c, real_t *v)
	SparseMatrix (int nr, int nc, int ld, const real_t *const v)
virtual	~SparseMatrix ()
virtual void	free ()
virtual Matrix *	duplicate () const
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	transTimes (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 (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
BooleanType	needToFreeMemory () const
void	doFreeMemory ()
void	doNotFreeMemory ()
Protected Attributes
int	nRows
int	nCols
sparse_int_t *	ir
sparse_int_t *	jc
sparse_int_t *	jd
real_t *	val
BooleanType	freeMemory

---

Detailed Description

Sparse matrix class (col compressed format).

Author:

Andreas Potschka, Christian Kirches, Hans Joachim Ferreau

Version:

3.1

Date:

2011-2015

---

Constructor & Destructor Documentation

SparseMatrix::SparseMatrix

(

)

Default constructor.

Referenced by duplicate().

SparseMatrix::SparseMatrix	(	int	nr,
		int	nc,
		sparse_int_t *	r,
		sparse_int_t *	c,
		real_t *	v
	)

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).

References Matrix::doNotFreeMemory().

SparseMatrix::SparseMatrix	(	int	nr,
		int	nc,
		int	ld,
		const real_t *const	v
	)

Constructor from dense matrix.

Parameters:

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

References BT_FALSE, Matrix::doFreeMemory(), ir, isZero(), jc, nCols, nRows, real_t, sparse_int_t, and val.

SparseMatrix::~SparseMatrix

(

)

[virtual]

Destructor.

References BT_TRUE, free(), jd, and Matrix::needToFreeMemory().

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Member Function Documentation

returnValue SparseMatrix::addToDiag

(

real_t

alpha

)

[virtual]

Adds given offset to diagonal of matrix.

Returns:

SUCCESSFUL_RETURN
RET_NO_DIAGONAL_AVAILABLE

Parameters:

alpha

Diagonal offset.

Implements Matrix.

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

sparse_int_t * SparseMatrix::createDiagInfo

(

)

Create jd field from ir and jc.

Returns:

Pointer to jd.

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

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

real_t SparseMatrix::diag

(

int

i

)

const [virtual]

Returns i-th diagonal entry.

Returns:

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

Parameters:

i

Index.

Implements Matrix.

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

void Matrix::doFreeMemory

(

)

[inline, inherited]

Enables de-allocation of internal memory.

References BT_TRUE, and Matrix::freeMemory.

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

void Matrix::doNotFreeMemory

(

)

[inline, inherited]

Disables de-allocation of internal memory.

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

Matrix * SparseMatrix::duplicate

(

)

const [virtual]

Returns a deep-copy of the Matrix object.

Returns:

Deep-copy of Matrix object

Implements Matrix.

Reimplemented in SymSparseMat.

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

void SparseMatrix::free

(

)

[virtual]

Frees all internal memory.

Implements Matrix.

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

Referenced by ~SparseMatrix().

real_t * SparseMatrix::full

(

)

const [virtual]

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 ir, jc, nCols, nRows, real_t, sparse_int_t, and val.

Referenced by main(), and print().

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

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

real_t SparseMatrix::getNorm

(

int

type = 2

)

const [virtual]

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 jc, nCols, REFER_NAMESPACE_QPOASES, and val.

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

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

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

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, ir, jc, nCols, real_t, REFER_NAMESPACE_QPOASES, RET_INVALID_ARGUMENTS, THROWERROR, and val.

BooleanType SparseMatrix::isDiag

(

)

const [virtual]

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, ir, jc, nCols, and 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(), and SparseMatrixRow::~SparseMatrixRow().

returnValue SparseMatrix::print

(

const char *

name = 0

)

const [virtual]

Prints matrix to screen.

Returns:

SUCCESSFUL_RETURN

Parameters:

name	Name of matrix.

Implements Matrix.

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

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

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, ir, isEqual(), isZero(), jc, nCols, nRows, SUCCESSFUL_RETURN, and 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]

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

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

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, ir, isEqual(), isZero(), jc, nCols, SUCCESSFUL_RETURN, and 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]

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

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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]

Row indices (length).

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

sparse_int_t* SparseMatrix::jc [protected]

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

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

sparse_int_t* SparseMatrix::jd [protected]

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

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

int SparseMatrix::nCols [protected]

Number of columns.

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

int SparseMatrix::nRows [protected]

Number of rows.

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

real_t* SparseMatrix::val [protected]

Vector of entries (length).

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

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

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