Abstract base class for interfacing matrix-vector operations tailored to symmetric matrices. More...

#include <Matrices.hpp>

Inheritance diagram for SymmetricMatrix:

Public Member Functions
virtual SymmetricMatrix *	duplicateSym () const =0
virtual returnValue	bilinear (const Indexlist const icols, int xN, const real_t x, int xLD, real_t *y, int yLD) const =0
virtual void	free ()=0
virtual Matrix *	duplicate () const =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 ()
Protected Attributes
BooleanType	freeMemory

Detailed Description

Abstract base class for symmetric matrices. Extends Matrix interface with bilinear form evaluation.

Author:: Andreas Potschka, Christian Kirches, Hans Joachim Ferreau

Version:: 3.0

Date:: 2011-2014

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().

virtual returnValue SymmetricMatrix::bilinear	(	const Indexlist *const	icols,
		int	xN,
		const real_t *	x,
		int	xLD,
		real_t *	y,
		int	yLD
	)		const `[pure 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.

Implemented in SymSparseMat, and SymDenseMat.

Referenced by QProblem::computeProjectedCholesky().

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().

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(), SymSparseMat::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().

virtual Matrix* Matrix::duplicate ( ) const [pure virtual, inherited]

Returns a deep-copy of the Matrix object.

Returns:: Deep-copy of Matrix object

Implemented in SymSparseMat, SparseMatrixRow, SparseMatrix, SymDenseMat, and DenseMatrix.

Referenced by QProblem::copy().

virtual SymmetricMatrix* SymmetricMatrix::duplicateSym ( ) const [pure virtual]

Returns a deep-copy of the SymmetricMatrix object.

Returns:: Deep-copy of SymmetricMatrix object

Implemented in SymSparseMat, and SymDenseMat.

Referenced by QProblemB::copy().

virtual void Matrix::free ( ) [pure virtual, inherited]

Frees all internal memory.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

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().

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().

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().

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().

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().

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 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.

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.

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.

Member Data Documentation

BooleanType Matrix::freeMemory [protected, inherited]

Indicating whether internal memory needs to be de-allocated.

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

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

include/qpOASES/Matrices.hpp

Public Member Functions

Protected Attributes

Detailed Description

Member Function Documentation

Member Data Documentation