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

#include <Matrices.hpp>

Inheritance diagram for SymDenseMat:

Public Member Functions
	SymDenseMat ()
	SymDenseMat (int m, int n, int lD, real_t *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 ()
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
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
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)
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
int	leaDim
real_t *	val
BooleanType	freeMemory

Detailed Description

Symmetric dense matrix class.

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

Version:: 3.0

Date:: 2011-2014

Constructor & Destructor Documentation

SymDenseMat::SymDenseMat ( ) [inline]

Default constructor.

Referenced by duplicateSym().

SymDenseMat::SymDenseMat	(	int	m,
		int	n,
		int	lD,
		real_t *	v
	)		`[inline]`

Constructor from vector of values.

Parameters:

m	Number of rows.
n	Number of columns.
lD	Leading dimension.
v	Values.

Member Function Documentation

returnValue DenseMatrix::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 DenseMatrix::leaDim, DenseMatrix::nCols, DenseMatrix::nRows, SUCCESSFUL_RETURN, and DenseMatrix::val.

returnValue SymDenseMat::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 DenseMatrix::leaDim, Indexlist::length, Indexlist::number, real_t, SUCCESSFUL_RETURN, and DenseMatrix::val.

real_t DenseMatrix::diag ( int i ) const [virtual, inherited]

Returns i-th diagonal entry.

Returns:: i-th diagonal entry

Parameters:

i Index.

Implements Matrix.

References DenseMatrix::leaDim, and DenseMatrix::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(), 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().

Matrix * SymDenseMat::duplicate ( ) const [virtual]

Returns a deep-copy of the Matrix object.

Returns:: Deep-copy of Matrix object

Reimplemented from DenseMatrix.

References duplicateSym().

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

Returns a deep-copy of the SymmetricMatrix object.

Returns:: Deep-copy of SymmetricMatrix object

Implements SymmetricMatrix.

References BT_TRUE, Matrix::doFreeMemory(), DenseMatrix::nCols, Matrix::needToFreeMemory(), DenseMatrix::nRows, real_t, SymDenseMat(), and DenseMatrix::val.

Referenced by duplicate().

void DenseMatrix::free ( ) [virtual, inherited]

Frees all internal memory.

Implements Matrix.

References DenseMatrix::val.

Referenced by DenseMatrix::~DenseMatrix().

real_t * DenseMatrix::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 DenseMatrix::nCols, DenseMatrix::nRows, real_t, and DenseMatrix::val.

returnValue DenseMatrix::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.

Returns:: SUCCESSFUL_RETURN

Parameters:

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

Implements Matrix.

References BT_TRUE, isEqual(), DenseMatrix::leaDim, Indexlist::length, Indexlist::number, SUCCESSFUL_RETURN, and DenseMatrix::val.

real_t DenseMatrix::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 DenseMatrix::nCols, DenseMatrix::nRows, REFER_NAMESPACE_QPOASES, and DenseMatrix::val.

Referenced by DenseMatrix::getRowNorm().

returnValue DenseMatrix::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.

Returns:: SUCCESSFUL_RETURN

Parameters:

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

Implements Matrix.

References BT_TRUE, isEqual(), DenseMatrix::leaDim, Indexlist::length, DenseMatrix::nCols, Indexlist::number, SUCCESSFUL_RETURN, and DenseMatrix::val.

real_t DenseMatrix::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 DenseMatrix::getNorm(), DenseMatrix::leaDim, DenseMatrix::nCols, REFER_NAMESPACE_QPOASES, and DenseMatrix::val.

BooleanType DenseMatrix::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, EPS, getAbs(), DenseMatrix::leaDim, DenseMatrix::nCols, DenseMatrix::nRows, and DenseMatrix::val.

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(), duplicateSym(), DenseMatrix::~DenseMatrix(), SparseMatrix::~SparseMatrix(), and SparseMatrixRow::~SparseMatrixRow().

returnValue DenseMatrix::print ( const char * name = 0 ) const [virtual, inherited]

Prints matrix to screen.

Returns:: SUCCESSFUL_RETURN

Parameters:

name	Name of matrix.

Implements Matrix.

References DenseMatrix::nCols, DenseMatrix::nRows, REFER_NAMESPACE_QPOASES, and DenseMatrix::val.

returnValue DenseMatrix::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.

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.

Implements Matrix.

References GEMM, getMax(), DenseMatrix::nCols, DenseMatrix::nRows, SUCCESSFUL_RETURN, and DenseMatrix::val.

returnValue DenseMatrix::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.

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.

Implements Matrix.

References BT_FALSE, BT_TRUE, isEqual(), Indexlist::iSort, isZero(), DenseMatrix::leaDim, Indexlist::length, DenseMatrix::nCols, Indexlist::number, SUCCESSFUL_RETURN, and DenseMatrix::val.

returnValue DenseMatrix::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.

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.

Implements Matrix.

References GEMM, getMax(), DenseMatrix::nCols, DenseMatrix::nRows, SUCCESSFUL_RETURN, and DenseMatrix::val.

returnValue DenseMatrix::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.

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.