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

#include <Matrices.hpp>

Inheritance diagram for SymmetricMatrix:

Public Member Functions
	SymmetricMatrix ()
virtual	~SymmetricMatrix ()
virtual SymmetricMatrix *	duplicateSym () const =0
virtual returnValue	bilinear (const Indexlist const icols, int_t xN, const real_t x, int_t xLD, real_t *y, int_t yLD) const =0
virtual void	free ()=0
virtual Matrix *	duplicate () const =0
virtual real_t	diag (int_t i) const =0
virtual BooleanType	isDiag () const =0
virtual real_t	getNorm (int_t type=2) const =0
virtual real_t	getRowNorm (int_t rNum, int_t type=2) const =0
virtual returnValue	getRowNorm (real_t *norm, int_t type=2) const =0
virtual returnValue	getRow (int_t rNum, const Indexlist const icols, real_t alpha, real_t row) const =0
virtual returnValue	getCol (int_t cNum, const Indexlist const irows, real_t alpha, real_t col) const =0
virtual returnValue	getSparseSubmatrix (const Indexlist const irows, const Indexlist const icols, int_t rowoffset, int_t coloffset, int_t &numNonzeros, int_t irn, int_t jcn, real_t *avals, BooleanType only_lower_triangular=BT_FALSE) const
virtual returnValue	getSparseSubmatrix (const Indexlist const irows, int_t idx_icol, int_t rowoffset, int_t coloffset, int_t &numNonzeros, int_t irn, int_t jcn, real_t avals, BooleanType only_lower_triangular=BT_FALSE) const
virtual returnValue	getSparseSubmatrix (int_t idx_row, const Indexlist const icols, int_t rowoffset, int_t coloffset, int_t &numNonzeros, int_t irn, int_t jcn, real_t avals, BooleanType only_lower_triangular=BT_FALSE) const
virtual returnValue	getSparseSubmatrix (int_t irowsLength, const int_t const irowsNumber, int_t icolsLength, const int_t const icolsNumber, int_t rowoffset, int_t coloffset, int_t &numNonzeros, int_t irn, int_t jcn, real_t *avals, BooleanType only_lower_triangular=BT_FALSE) const =0
virtual returnValue	times (int_t xN, real_t alpha, const real_t x, int_t xLD, real_t beta, real_t y, int_t yLD) const =0
virtual returnValue	times (const Indexlist const irows, const Indexlist const icols, int_t xN, real_t alpha, const real_t x, int_t xLD, real_t beta, real_t y, int_t yLD, BooleanType yCompr=BT_TRUE) const =0
virtual returnValue	transTimes (int_t xN, real_t alpha, const real_t x, int_t xLD, real_t beta, real_t y, int_t yLD) const =0
virtual returnValue	transTimes (const Indexlist const irows, const Indexlist const icols, int_t xN, real_t alpha, const real_t x, int_t xLD, real_t beta, real_t y, int_t 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
virtual returnValue	writeToFile (FILE output_file, const char prefix) 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:: 3.2

Date:: 2011-2017

Constructor & Destructor Documentation

SymmetricMatrix::SymmetricMatrix ( ) [inline]

Default constructor.

virtual SymmetricMatrix::~SymmetricMatrix ( ) [inline, virtual]

Destructor.

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_t	xN,
		const real_t *	x,
		int_t	xLD,
		real_t *	y,
		int_t	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_t 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 SolutionAnalysis::getKktViolation(), and QProblem::writeQpDataIntoMatFile().

virtual returnValue Matrix::getCol	(	int_t	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_t 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_t	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(), SQProblemSchur::addConstraint_checkLISchur(), QProblem::addConstraint_ensureLI(), and QProblemB::removeBound().

virtual real_t Matrix::getRowNorm	(	int_t	rNum,
		int_t	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 returnValue Matrix::getRowNorm	(	real_t *	norm,
		int_t	type = `2`
	)		const `[pure virtual, inherited]`

Get the N-norm of all rows

Returns:: SUCCESSFUL_RETURN

Parameters:

norm	Norm of each row.
type	Norm type, 1: one-norm, 2: Euclidean norm.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

BEGIN_NAMESPACE_QPOASES returnValue Matrix::getSparseSubmatrix	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int_t	rowoffset,
		int_t	coloffset,
		int_t &	numNonzeros,
		int_t *	irn,
		int_t *	jcn,
		real_t *	avals,
		BooleanType	only_lower_triangular = `BT_FALSE`
	)		const `[virtual, inherited]`

Retrieve entries of submatrix in Harwell-Boeing sparse format. If irn, jcn, and avals are null, this only counts the number of nonzeros. Otherwise, numNonzeros containts the size of irn, jcn, and avals on entry, and the written number of entries on return.

Returns:: SUCCESSFUL_RETURN

Parameters:

irows	Index list specifying rows.
icols	Index list specifying columns.
rowoffset	Offset for row entries.
coloffset	Offset for row entries.
numNonzeros	Number of nonzeros in submatrix.
irn	Row position of entries (as position in irows) plus rowoffset.
jcn	Column position of entries (as position in irows) plus coloffset.
avals	Numerical values of the entries.
only_lower_triangular	if true, only the lower triangular portion is returned. This can only be true for symmetric matrices and if irows==jcols.

References Indexlist::getLength(), and Indexlist::getNumberArray().

Referenced by SQProblemSchur::addConstraint(), Matrix::getSparseSubmatrix(), SQProblemSchur::removeBound(), and SQProblemSchur::resetSchurComplement().

returnValue Matrix::getSparseSubmatrix	(	const Indexlist *const	irows,
		int_t	idx_icol,
		int_t	rowoffset,
		int_t	coloffset,
		int_t &	numNonzeros,
		int_t *	irn,
		int_t *	jcn,
		real_t *	avals,
		BooleanType	only_lower_triangular = `BT_FALSE`
	)		const `[virtual, inherited]`

Retrieve entries of submatrix in Harwell-Boeing sparse format. If irn, jcn, and avals are null, this only counts the number of nonzeros. Otherwise, numNonzeros containts the size of irn, jcn, and avals on entry, and the written number of entries on return. This version retrieves one column.

Returns:: SUCCESSFUL_RETURN

Parameters:

irows	Index list specifying rows.
idx_icol	Index list specifying columns.
rowoffset	Offset for row entries.
coloffset	Offset for row entries.
numNonzeros	Number of nonzeros in submatrix.
irn	Row position of entries (as position in irows) plus rowoffset.
jcn	Column position of entries (as position in irows) plus coloffset.
avals	Numerical values of the entries.
only_lower_triangular	if true, only the lower triangular portion is returned. This can only be true for symmetric matrices and if irows==jcols.

References Indexlist::getLength(), Indexlist::getNumberArray(), and Matrix::getSparseSubmatrix().

returnValue Matrix::getSparseSubmatrix	(	int_t	idx_row,
		const Indexlist *const	icols,
		int_t	rowoffset,
		int_t	coloffset,
		int_t &	numNonzeros,
		int_t *	irn,
		int_t *	jcn,
		real_t *	avals,
		BooleanType	only_lower_triangular = `BT_FALSE`
	)		const `[virtual, inherited]`

Retrieve entries of submatrix in Harwell-Boeing sparse format. If irn, jcn, and avals are null, this only counts the number of nonzeros. Otherwise, numNonzeros containts the size of irn, jcn, and avals on entry, and the written number of entries on return. This version retrieves one row.

Returns:: SUCCESSFUL_RETURN

Parameters:

idx_row	Row number.
icols	Index list specifying columns.
rowoffset	Offset for row entries.
coloffset	Offset for row entries.
numNonzeros	Number of nonzeros in submatrix.
irn	Row position of entries (as position in irows) plus rowoffset.
jcn	Column position of entries (as position in irows) plus coloffset.
avals	Numerical values of the entries.
only_lower_triangular	if true, only the lower triangular portion is returned. This can only be true for symmetric matrices and if irows==jcols.

References Indexlist::getLength(), Indexlist::getNumberArray(), and Matrix::getSparseSubmatrix().

virtual returnValue Matrix::getSparseSubmatrix	(	int_t	irowsLength,
		const int_t *const	irowsNumber,
		int_t	icolsLength,
		const int_t *const	icolsNumber,
		int_t	rowoffset,
		int_t	coloffset,
		int_t &	numNonzeros,
		int_t *	irn,
		int_t *	jcn,
		real_t *	avals,
		BooleanType	only_lower_triangular = `BT_FALSE`
	)		const `[pure virtual, inherited]`

Retrieve entries of submatrix in Harwell-Boeing sparse format. If irn, jcn, and avals are null, this only counts the number of nonzeros. Otherwise, numNonzeros containts the size of irn, jcn, and avals on entry, and the written number of entries on return.

Returns:: SUCCESSFUL_RETURN

Parameters:

irowsLength	Number of rows.
irowsNumber	Array with row numbers.
icolsLength	Number of columns.
icolsNumber	Array with column numbers.
rowoffset	Offset for row entries.
coloffset	Offset for row entries.
numNonzeros	Number of nonzeros in submatrix.
irn	Row position of entries (as position in irows) plus rowoffset.
jcn	Column position of entries (as position in irows) plus coloffset.
avals	Numerical values of the entries.
only_lower_triangular	if true, only the lower triangular portion is returned. This can only be true for symmetric matrices and if irows==jcols.

Implemented in SparseMatrixRow, SparseMatrix, and DenseMatrix.

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_t	xN,
		real_t	alpha,
		const real_t *	x,
		int_t	xLD,
		real_t	beta,
		real_t *	y,
		int_t	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(), QProblemB::getObjVal(), QProblem::performStep(), QProblem::printIteration(), QProblemB::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_t	xN,
		real_t	alpha,
		const real_t *	x,
		int_t	xLD,
		real_t	beta,
		real_t *	y,
		int_t	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_t	xN,
		real_t	alpha,
		const real_t *	x,
		int_t	xLD,
		real_t	beta,
		real_t *	y,
		int_t	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(), QProblem::printIteration(), and QProblem::setupAuxiliaryQPgradient().

virtual returnValue Matrix::transTimes	(	const Indexlist *const	irows,
		const Indexlist *const	icols,
		int_t	xN,
		real_t	alpha,
		const real_t *	x,
		int_t	xLD,
		real_t	beta,
		real_t *	y,
		int_t	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.