A versatible sparse matrix representation. More...

#include <src/eigen/Eigen/src/SparseCore/SparseMatrix.h>

Inheritance diagram for Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >:

Collaboration diagram for Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >:

Classes
struct	default_prunning_func

class	SingletonVector

Public Types
enum	{ Options = _Options }

typedef MappedSparseMatrix< Scalar, Flags >	Map

typedef Diagonal< SparseMatrix >	DiagonalReturnType

typedef Diagonal< const SparseMatrix >	ConstDiagonalReturnType

typedef Base::InnerIterator	InnerIterator

typedef Base::ReverseInnerIterator	ReverseInnerIterator

typedef internal::CompressedStorage< Scalar, StorageIndex >	Storage

typedef Base::IndexVector	IndexVector

typedef Base::ScalarVector	ScalarVector

enum	{ RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime , ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime , SizeAtCompileTime , MaxRowsAtCompileTime = RowsAtCompileTime , MaxColsAtCompileTime = ColsAtCompileTime , MaxSizeAtCompileTime , IsVectorAtCompileTime = RowsAtCompileTime == 1 \|\| ColsAtCompileTime == 1 , Flags = internal::traits<Derived>::Flags , IsRowMajor = Flags&RowMajorBit ? 1 : 0 , InnerSizeAtCompileTime , _HasDirectAccess = (int(Flags)&DirectAccessBit) ? 1 : 0 }

typedef internal::traits< Derived >::Scalar	Scalar

typedef Scalar	value_type

typedef internal::packet_traits< Scalar >::type	PacketScalar

typedef internal::traits< Derived >::StorageKind	StorageKind

typedef internal::traits< Derived >::StorageIndex	StorageIndex

typedef internal::add_const_on_value_type_if_arithmetic< typenameinternal::packet_traits< Scalar >::type >::type	PacketReturnType

typedef SparseMatrixBase	StorageBaseType

typedef internal::conditional< NumTraits< Scalar >::IsComplex, CwiseUnaryOp< internal::scalar_conjugate_op< Scalar >, Eigen::Transpose< constDerived > >, Transpose< constDerived > >::type	AdjointReturnType

typedef Transpose< Derived >	TransposeReturnType

typedef internal::add_const< Transpose< constDerived > >::type	ConstTransposeReturnType

typedef SparseMatrix< Scalar, Flags &RowMajorBit ? RowMajor :ColMajor, StorageIndex >	PlainObject

typedef NumTraits< Scalar >::Real	RealScalar

typedef internal::conditional< _HasDirectAccess, constScalar &, Scalar >::type	CoeffReturnType

typedef CwiseNullaryOp< internal::scalar_constant_op< Scalar >, Matrix< Scalar, Dynamic, Dynamic > >	ConstantReturnType

typedef Matrix< Scalar, RowsAtCompileTime, ColsAtCompileTime >	DenseMatrixType

typedef Matrix< Scalar, EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime), EIGEN_SIZE_MAX(RowsAtCompileTime, ColsAtCompileTime)>	SquareMatrixType

typedef Block< Derived, IsRowMajor?1:Dynamic, IsRowMajor?Dynamic:1, true >	InnerVectorReturnType

typedef Block< const Derived, IsRowMajor?1:Dynamic, IsRowMajor?Dynamic:1, true >	ConstInnerVectorReturnType

typedef Block< Derived, Dynamic, Dynamic, true >	InnerVectorsReturnType

typedef Block< const Derived, Dynamic, Dynamic, true >	ConstInnerVectorsReturnType

typedef Eigen::Index	Index
	The interface type of indices.

Public Member Functions
Index	rows () const

Index	cols () const

Index	innerSize () const

Index	outerSize () const

const Scalar *	valuePtr () const

Scalar *	valuePtr ()

const StorageIndex *	innerIndexPtr () const

StorageIndex *	innerIndexPtr ()

const StorageIndex *	outerIndexPtr () const

StorageIndex *	outerIndexPtr ()

const StorageIndex *	innerNonZeroPtr () const

StorageIndex *	innerNonZeroPtr ()

Storage &	data ()

const Storage &	data () const

Scalar	coeff (Index row, Index col) const

Scalar &	coeffRef (Index row, Index col)

Scalar &	insert (Index row, Index col)

void	setZero ()

void	reserve (Index reserveSize)

template<class SizesType >
void	reserve (const SizesType &reserveSizes, const typename SizesType::value_type &enableif=typename SizesType::value_type())

Scalar &	insertBack (Index row, Index col)

Scalar &	insertBackByOuterInner (Index outer, Index inner)

Scalar &	insertBackByOuterInnerUnordered (Index outer, Index inner)

void	startVec (Index outer)

void	finalize ()

template<typename InputIterators >
void	setFromTriplets (const InputIterators &begin, const InputIterators &end)

template<typename InputIterators , typename DupFunctor >
void	setFromTriplets (const InputIterators &begin, const InputIterators &end, DupFunctor dup_func)

void	sumupDuplicates ()

template<typename DupFunctor >
void	collapseDuplicates (DupFunctor dup_func=DupFunctor())

Scalar &	insertByOuterInner (Index j, Index i)

void	makeCompressed ()

void	uncompress ()

void	prune (const Scalar &reference, const RealScalar &epsilon=NumTraits< RealScalar >::dummy_precision())

template<typename KeepFunc >
void	prune (const KeepFunc &keep=KeepFunc())

void	conservativeResize (Index rows, Index cols)

void	resize (Index rows, Index cols)

void	resizeNonZeros (Index size)

const ConstDiagonalReturnType	diagonal () const

DiagonalReturnType	diagonal ()

	SparseMatrix ()

	SparseMatrix (Index rows, Index cols)

template<typename OtherDerived >
	SparseMatrix (const SparseMatrixBase< OtherDerived > &other)

template<typename OtherDerived , unsigned int UpLo>
	SparseMatrix (const SparseSelfAdjointView< OtherDerived, UpLo > &other)

	SparseMatrix (const SparseMatrix &other)

template<typename OtherDerived >
	SparseMatrix (const ReturnByValue< OtherDerived > &other)
	Copy constructor with in-place evaluation.

template<typename OtherDerived >
	SparseMatrix (const DiagonalBase< OtherDerived > &other)
	Copy constructor with in-place evaluation.

void	swap (SparseMatrix &other)

void	setIdentity ()

SparseMatrix &	operator= (const SparseMatrix &other)

template<typename OtherDerived >
SparseMatrix &	operator= (const EigenBase< OtherDerived > &other)

template<typename OtherDerived >
EIGEN_DONT_INLINE SparseMatrix &	operator= (const SparseMatrixBase< OtherDerived > &other)

	~SparseMatrix ()

Scalar	sum () const

EIGEN_STRONG_INLINE Scalar &	insertBackUncompressed (Index row, Index col)

template<typename OtherDerived >
EIGEN_DONT_INLINE SparseMatrix< Scalar, _Options, _StorageIndex > &	operator= (const SparseMatrixBase< OtherDerived > &other)

bool	isCompressed () const

Index	nonZeros () const

const Map< const Array< Scalar, Dynamic, 1 > >	coeffs () const

Map< Array< Scalar, Dynamic, 1 > >	coeffs ()

const Derived &	derived () const

Derived &	derived ()

Derived &	const_cast_derived () const

Index	size () const

bool	isVector () const

bool	isRValue () const

Derived &	markAsRValue ()

template<typename OtherDerived >
Derived &	operator+= (const SparseMatrixBase< OtherDerived > &other)

template<typename OtherDerived >
Derived &	operator+= (const DiagonalBase< OtherDerived > &other)

template<typename OtherDerived >
Derived &	operator+= (const EigenBase< OtherDerived > &other)

template<typename OtherDerived >
EIGEN_STRONG_INLINE Derived &	operator+= (const SparseMatrixBase< OtherDerived > &other)

template<typename OtherDerived >
Derived &	operator-= (const SparseMatrixBase< OtherDerived > &other)

template<typename OtherDerived >
Derived &	operator-= (const DiagonalBase< OtherDerived > &other)

template<typename OtherDerived >
Derived &	operator-= (const EigenBase< OtherDerived > &other)

template<typename OtherDerived >
EIGEN_STRONG_INLINE Derived &	operator-= (const SparseMatrixBase< OtherDerived > &other)

Derived &	operator*= (const Scalar &other)

template<typename OtherDerived >
Derived &	operator*= (const SparseMatrixBase< OtherDerived > &other)

Derived &	operator/= (const Scalar &other)

template<typename OtherDerived >
EIGEN_STRONG_INLINE const CwiseProductDenseReturnType< OtherDerived >::Type	cwiseProduct (const MatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
EIGEN_STRONG_INLINE const SparseMatrixBase< Derived >::template CwiseProductDenseReturnType< OtherDerived >::Type	cwiseProduct (const MatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
const Product< Derived, OtherDerived >	operator* (const DiagonalBase< OtherDerived > &other) const

template<typename OtherDerived >
const Product< Derived, OtherDerived, AliasFreeProduct >	operator* (const SparseMatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
const Product< Derived, OtherDerived >	operator* (const MatrixBase< OtherDerived > &other) const

SparseSymmetricPermutationProduct< Derived, Upper\|Lower >	twistedBy (const PermutationMatrix< Dynamic, Dynamic, StorageIndex > &perm) const

template<int Mode>
const TriangularView< const Derived, Mode >	triangularView () const

template<unsigned int UpLo>
ConstSelfAdjointViewReturnType< UpLo >::Type	selfadjointView () const

template<unsigned int UpLo>
SelfAdjointViewReturnType< UpLo >::Type	selfadjointView ()

template<unsigned int UpLo>
SparseMatrixBase< Derived >::template ConstSelfAdjointViewReturnType< UpLo >::Type	selfadjointView () const

template<unsigned int UpLo>
SparseMatrixBase< Derived >::template SelfAdjointViewReturnType< UpLo >::Type	selfadjointView ()

template<typename OtherDerived >
Scalar	dot (const MatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
Scalar	dot (const SparseMatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
internal::traits< Derived >::Scalar	dot (const MatrixBase< OtherDerived > &other) const

template<typename OtherDerived >
internal::traits< Derived >::Scalar	dot (const SparseMatrixBase< OtherDerived > &other) const

RealScalar	squaredNorm () const

RealScalar	norm () const

RealScalar	blueNorm () const

TransposeReturnType	transpose ()

const ConstTransposeReturnType	transpose () const

const AdjointReturnType	adjoint () const

InnerVectorReturnType	innerVector (Index outer)

const ConstInnerVectorReturnType	innerVector (Index outer) const

InnerVectorsReturnType	innerVectors (Index outerStart, Index outerSize)

const ConstInnerVectorsReturnType	innerVectors (Index outerStart, Index outerSize) const

DenseMatrixType	toDense () const

template<typename OtherDerived >
bool	isApprox (const SparseMatrixBase< OtherDerived > &other, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const

template<typename OtherDerived >
bool	isApprox (const MatrixBase< OtherDerived > &other, const RealScalar &prec=NumTraits< Scalar >::dummy_precision()) const

const internal::eval< Derived >::type	eval () const

const SparseView< Derived >	pruned (const Scalar &reference=Scalar(0), const RealScalar &epsilon=NumTraits< Scalar >::dummy_precision()) const

EIGEN_DEVICE_FUNC const Derived &	const_derived () const

template<typename Dest >
EIGEN_DEVICE_FUNC void	addTo (Dest &dst) const

template<typename Dest >
EIGEN_DEVICE_FUNC void	subTo (Dest &dst) const

template<typename Dest >
EIGEN_DEVICE_FUNC void	applyThisOnTheRight (Dest &dst) const

template<typename Dest >
EIGEN_DEVICE_FUNC void	applyThisOnTheLeft (Dest &dst) const

Protected Types
typedef SparseMatrix< Scalar,(Flags &~RowMajorBit)\|(IsRowMajor?RowMajorBit:0)>	TransposedSparseMatrix

Protected Member Functions
template<class SizesType >
void	reserveInnerVectors (const SizesType &reserveSizes)

template<typename Other >
void	initAssignment (const Other &other)

EIGEN_DONT_INLINE Scalar &	insertCompressed (Index row, Index col)

EIGEN_DONT_INLINE Scalar &	insertUncompressed (Index row, Index col)

Eigen::Map< IndexVector >	innerNonZeros ()

const Eigen::Map< const IndexVector >	innerNonZeros () const

template<typename OtherDerived >
Derived &	assign (const OtherDerived &other)

template<typename OtherDerived >
void	assignGeneric (const OtherDerived &other)

Static Protected Member Functions
static StorageIndex	convert_index (const Index idx)

Protected Attributes
Index	m_outerSize

Index	m_innerSize

StorageIndex *	m_outerIndex

StorageIndex *	m_innerNonZeros

Storage	m_data

bool	m_isRValue

Private Types
typedef SparseCompressedBase< SparseMatrix >	Base

Private Member Functions
template<typename Dest >
void	evalTo (Dest &) const

Static Private Member Functions
static void	check_template_parameters ()

Friends
class	SparseVector< _Scalar, 0, _StorageIndex >

std::ostream &	operator<< (std::ostream &s, const SparseMatrix &m)

Detailed Description

template<typename _Scalar, int _Options, typename _StorageIndex>
class Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >

A versatible sparse matrix representation.

This class implements a more versatile variants of the common compressed row/column storage format. Each colmun's (resp. row) non zeros are stored as a pair of value with associated row (resp. colmiun) index. All the non zeros are stored in a single large buffer. Unlike the compressed format, there might be extra space inbetween the nonzeros of two successive colmuns (resp. rows) such that insertion of new non-zero can be done with limited memory reallocation and copies.

A call to the function makeCompressed() turns the matrix into the standard compressed format compatible with many library.

More details on this storage sceheme are given in the manual pages.

Template Parameters

_Scalar	the scalar type, i.e. the type of the coefficients
_Options	Union of bit flags controlling the storage scheme. Currently the only possibility is ColMajor or RowMajor. The default is 0 which means column-major.
_StorageIndex	the type of the indices. It has to be a signed type (e.g., short, int, std::ptrdiff_t). Default is `int`.

Warning: In Eigen 3.2, the undocumented type SparseMatrix::Index was improperly defined as the storage index type (e.g., int), whereas it is now (starting from Eigen 3.3) deprecated and always defined as Eigen::Index. Codes making use of SparseMatrix::Index, might thus likely have to be changed to use SparseMatrix::StorageIndex instead.

This class can be extended with the help of the plugin mechanism described on the page TopicCustomizing_Plugins by defining the preprocessor symbol EIGEN_SPARSEMATRIX_PLUGIN.

Member Typedef Documentation

◆ AdjointReturnType

template<typename Derived >

typedef internal::conditional<NumTraits<Scalar>::IsComplex,CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,Eigen::Transpose<constDerived>>,Transpose<constDerived>>::type Eigen::SparseMatrixBase< Derived >::AdjointReturnType

inherited

◆ Base

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef SparseCompressedBase<SparseMatrix> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::Base

private

◆ CoeffReturnType

template<typename Derived >

typedef internal::conditional<_HasDirectAccess,constScalar&,Scalar>::type Eigen::SparseMatrixBase< Derived >::CoeffReturnType

inherited

◆ ConstantReturnType

template<typename Derived >

typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Matrix<Scalar,Dynamic,Dynamic> > Eigen::SparseMatrixBase< Derived >::ConstantReturnType

inherited

◆ ConstDiagonalReturnType

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Diagonal<const SparseMatrix> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::ConstDiagonalReturnType

◆ ConstInnerVectorReturnType

template<typename Derived >

typedef Block<const Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true> Eigen::SparseMatrixBase< Derived >::ConstInnerVectorReturnType

inherited

◆ ConstInnerVectorsReturnType

template<typename Derived >

typedef Block<const Derived,Dynamic,Dynamic,true> Eigen::SparseMatrixBase< Derived >::ConstInnerVectorsReturnType

inherited

◆ ConstTransposeReturnType

template<typename Derived >

typedef internal::add_const<Transpose<constDerived>>::type Eigen::SparseMatrixBase< Derived >::ConstTransposeReturnType

inherited

◆ DenseMatrixType

template<typename Derived >

typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> Eigen::SparseMatrixBase< Derived >::DenseMatrixType

inherited

type of the equivalent dense matrix

◆ DiagonalReturnType

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Diagonal<SparseMatrix> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::DiagonalReturnType

◆ Index

template<typename Derived >

typedef Eigen::Index Eigen::EigenBase< Derived >::Index

inherited

The interface type of indices.

To change this, #define the preprocessor symbol EIGEN_DEFAULT_DENSE_INDEX_TYPE.

See also: StorageIndex, TopicPreprocessorDirectives.

◆ IndexVector

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Base::IndexVector Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IndexVector

◆ InnerIterator

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Base::InnerIterator Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::InnerIterator

◆ InnerVectorReturnType

template<typename Derived >

typedef Block<Derived,IsRowMajor?1:Dynamic,IsRowMajor?Dynamic:1,true> Eigen::SparseMatrixBase< Derived >::InnerVectorReturnType

inherited

◆ InnerVectorsReturnType

template<typename Derived >

typedef Block<Derived,Dynamic,Dynamic,true> Eigen::SparseMatrixBase< Derived >::InnerVectorsReturnType

inherited

◆ Map

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef MappedSparseMatrix<Scalar,Flags> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::Map

◆ PacketReturnType

template<typename Derived >

typedef internal::add_const_on_value_type_if_arithmetic<typenameinternal::packet_traits<Scalar>::type>::type Eigen::SparseMatrixBase< Derived >::PacketReturnType

inherited

◆ PacketScalar

template<typename Derived >

typedef internal::packet_traits<Scalar>::type Eigen::SparseMatrixBase< Derived >::PacketScalar

inherited

◆ PlainObject

template<typename Derived >

typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor, StorageIndex> Eigen::SparseMatrixBase< Derived >::PlainObject

inherited

◆ RealScalar

template<typename Derived >

typedef NumTraits<Scalar>::Real Eigen::SparseMatrixBase< Derived >::RealScalar

inherited

This is the "real scalar" type; if the Scalar type is already real numbers (e.g. int, float or double) then RealScalar is just the same as Scalar. If Scalar is std::complex<T> then RealScalar is T.

See also: class NumTraits

◆ ReverseInnerIterator

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Base::ReverseInnerIterator Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::ReverseInnerIterator

◆ Scalar

template<typename Derived >

typedef internal::traits<Derived>::Scalar Eigen::SparseMatrixBase< Derived >::Scalar

inherited

◆ ScalarVector

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef Base::ScalarVector Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::ScalarVector

◆ SquareMatrixType

template<typename Derived >

typedef Matrix<Scalar,EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime), EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> Eigen::SparseMatrixBase< Derived >::SquareMatrixType

inherited

type of the equivalent square matrix

◆ Storage

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef internal::CompressedStorage<Scalar,StorageIndex> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::Storage

◆ StorageBaseType

template<typename Derived >

typedef SparseMatrixBase Eigen::SparseMatrixBase< Derived >::StorageBaseType

inherited

◆ StorageIndex

template<typename Derived >

typedef internal::traits<Derived>::StorageIndex Eigen::SparseMatrixBase< Derived >::StorageIndex

inherited

The integer type used to store indices within a SparseMatrix. For a SparseMatrix<Scalar,Options,IndexType> it an alias of the third template parameter IndexType.

◆ StorageKind

template<typename Derived >

typedef internal::traits<Derived>::StorageKind Eigen::SparseMatrixBase< Derived >::StorageKind

inherited

◆ TransposedSparseMatrix

template<typename _Scalar , int _Options, typename _StorageIndex >

typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::TransposedSparseMatrix

protected

◆ TransposeReturnType

template<typename Derived >

typedef Transpose<Derived> Eigen::SparseMatrixBase< Derived >::TransposeReturnType

inherited

◆ value_type

template<typename Derived >

typedef Scalar Eigen::SparseMatrixBase< Derived >::value_type

inherited

The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.

It is an alias for the Scalar type

Member Enumeration Documentation

◆ anonymous enum

template<typename Derived >

anonymous enum

inherited

Enumerator
RowsAtCompileTime	The number of rows at compile-time. This is just a copy of the value provided by the Derived type. If a value is not known at compile-time, it is set to the Dynamic constant. See also MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime
ColsAtCompileTime	The number of columns at compile-time. This is just a copy of the value provided by the Derived type. If a value is not known at compile-time, it is set to the Dynamic constant. See also MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime
SizeAtCompileTime	This is equal to the number of coefficients, i.e. the number of rows times the number of columns, or to Dynamic if this is not known at compile-time. See also RowsAtCompileTime, ColsAtCompileTime
MaxRowsAtCompileTime
MaxColsAtCompileTime
MaxSizeAtCompileTime
IsVectorAtCompileTime	This is set to true if either the number of rows or the number of columns is known at compile-time to be equal to 1. Indeed, in that case, we are dealing with a column-vector (if there is only one column) or with a row-vector (if there is only one row).
Flags	This stores expression Flags flags which may or may not be inherited by new expressions constructed from this one. See the list of flags.
IsRowMajor
InnerSizeAtCompileTime
_HasDirectAccess

         {
 
      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
      MaxRowsAtCompileTime = RowsAtCompileTime,
      MaxColsAtCompileTime = ColsAtCompileTime,
 
      MaxSizeAtCompileTime = (internal::size_at_compile_time<MaxRowsAtCompileTime,
                                                      MaxColsAtCompileTime>::ret),
 
      IsVectorAtCompileTime = RowsAtCompileTime == 1 || ColsAtCompileTime == 1,
      Flags = internal::traits<Derived>::Flags,
      IsRowMajor = Flags&RowMajorBit ? 1 : 0,
      
      InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
                             : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
 
      #ifndef EIGEN_PARSED_BY_DOXYGEN
      _HasDirectAccess = (int(Flags)&DirectAccessBit) ? 1 : 0 // workaround sunCC
      #endif
    };

◆ anonymous enum

template<typename _Scalar , int _Options, typename _StorageIndex >

anonymous enum

Enumerator
Options

         {
      Options = _Options
    };

Constructor & Destructor Documentation

◆ SparseMatrix() [1/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( )

inline

Default constructor yielding an empty 0 x 0 matrix

      : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      resize(0, 0);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize().

Here is the call graph for this function:

◆ SparseMatrix() [2/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix	(	Index	rows,
		Index	cols
	)

inline

Constructs a rows x cols empty matrix

      : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      resize(rows, cols);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows().

Here is the call graph for this function:

◆ SparseMatrix() [3/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( const SparseMatrixBase< OtherDerived > & other )

inline

Constructs a sparse matrix from the sparse expression other

      : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
      check_template_parameters();
      const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit);
      if (needToTranspose)
        *this = other.derived();
      else
      {
        #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
          EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
        #endif
        internal::call_assignment_no_alias(*this, other.derived());
      }
    }

References Eigen::internal::call_assignment_no_alias(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), Eigen::SparseMatrixBase< Derived >::derived(), EIGEN_STATIC_ASSERT, Eigen::SparseMatrixBase< Derived >::Flags, and Eigen::RowMajorBit.

Here is the call graph for this function:

◆ SparseMatrix() [4/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived , unsigned int UpLo>

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( const SparseSelfAdjointView< OtherDerived, UpLo > & other )

inline

Constructs a sparse matrix from the sparse selfadjoint view other

      : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      Base::operator=(other);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), and Eigen::SparseCompressedBase< Derived >::operator=().

Here is the call graph for this function:

◆ SparseMatrix() [5/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( const SparseMatrix< _Scalar, _Options, _StorageIndex > & other )

inline

Copy constructor (it performs a deep copy)

      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      *this = other.derived();
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), and Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ SparseMatrix() [6/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( const ReturnByValue< OtherDerived > & other )

inline

Copy constructor with in-place evaluation.

      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      initAssignment(other);
      other.evalTo(*this);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), Eigen::ReturnByValue< Derived >::evalTo(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::initAssignment().

Here is the call graph for this function:

◆ SparseMatrix() [7/7]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix ( const DiagonalBase< OtherDerived > & other )

inlineexplicit

Copy constructor with in-place evaluation.

      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
    {
      check_template_parameters();
      *this = other.derived();
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters(), and Eigen::DiagonalBase< Derived >::derived().

Here is the call graph for this function:

◆ ~SparseMatrix()

template<typename _Scalar , int _Options, typename _StorageIndex >

Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::~SparseMatrix ( )

inline

Destructor

    {
      std::free(m_outerIndex);
      std::free(m_innerNonZeros);
    }

Member Function Documentation

◆ addTo()

template<typename Derived >

template<typename Dest >

EIGEN_DEVICE_FUNC void Eigen::EigenBase< Derived >::addTo ( Dest & dst ) const

inlineinherited

  {
    // This is the default implementation,
    // derived class can reimplement it in a more optimized way.
    typename Dest::PlainObject res(rows(),cols());
    evalTo(res);
    dst += res;
  }

◆ adjoint()

template<typename Derived >

const AdjointReturnType Eigen::SparseMatrixBase< Derived >::adjoint ( ) const

inlineinherited

351{ return AdjointReturnType(transpose()); }

Eigen::SparseMatrixBase::AdjointReturnType

internal::conditional< NumTraits< Scalar >::IsComplex, CwiseUnaryOp< internal::scalar_conjugate_op< Scalar >, Eigen::Transpose< constDerived > >, Transpose< constDerived > >::type AdjointReturnType

Definition SparseMatrixBase.h:109

Eigen::SparseMatrixBase::transpose

TransposeReturnType transpose()

Definition SparseMatrixBase.h:349

References Eigen::SparseMatrixBase< Derived >::transpose().

Referenced by Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::_solve_impl(), and Eigen::SparseSelfAdjointView< MatrixType, _Mode >::rankUpdate().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ applyThisOnTheLeft()

template<typename Derived >

template<typename Dest >

EIGEN_DEVICE_FUNC void Eigen::EigenBase< Derived >::applyThisOnTheLeft ( Dest & dst ) const

inlineinherited

  {
    // This is the default implementation,
    // derived class can reimplement it in a more optimized way.
    dst = this->derived() * dst;
  }

References Eigen::EigenBase< Derived >::derived().

Here is the call graph for this function:

◆ applyThisOnTheRight()

template<typename Derived >

template<typename Dest >

EIGEN_DEVICE_FUNC void Eigen::EigenBase< Derived >::applyThisOnTheRight ( Dest & dst ) const

inlineinherited

  {
    // This is the default implementation,
    // derived class can reimplement it in a more optimized way.
    dst = dst * this->derived();
  }

References Eigen::EigenBase< Derived >::derived().

Here is the call graph for this function:

◆ assign()

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::assign ( const OtherDerived & other )

inlineprotectedinherited

◆ assignGeneric()

template<typename Derived >

template<typename OtherDerived >

void Eigen::SparseMatrixBase< Derived >::assignGeneric ( const OtherDerived & other )

inlineprotectedinherited

◆ blueNorm()

template<typename Derived >

NumTraits< typenameinternal::traits< Derived >::Scalar >::Real Eigen::SparseMatrixBase< Derived >::blueNorm

inlineinherited

{
  return internal::blueNorm_impl(*this);
}

References Eigen::internal::blueNorm_impl().

Here is the call graph for this function:

◆ check_template_parameters()

template<typename _Scalar , int _Options, typename _StorageIndex >

static void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::check_template_parameters ( )

inlinestaticprivate

  {
    EIGEN_STATIC_ASSERT(NumTraits<StorageIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
    EIGEN_STATIC_ASSERT((Options&(ColMajor|RowMajor))==Options,INVALID_MATRIX_TEMPLATE_PARAMETERS);
  }

References Eigen::ColMajor, EIGEN_STATIC_ASSERT, and Eigen::RowMajor.

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix().

Here is the caller graph for this function:

◆ coeff()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeff	(	Index	row,
		Index	col
	)		const

inline

Returns: the value of the matrix at position i, j This function returns Scalar(0) if the element is an explicit zero

    {
      eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
      
      const Index outer = IsRowMajor ? row : col;
      const Index inner = IsRowMajor ? col : row;
      Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
      return m_data.atInRange(m_outerIndex[outer], end, StorageIndex(inner));
    }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::atInRange(), col(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols(), eigen_assert, Eigen::end(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, row(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows().

Here is the call graph for this function:

◆ coeffRef()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeffRef	(	Index	row,
		Index	col
	)

inline

Returns: a non-const reference to the value of the matrix at position i, j

If the element does not exist then it is inserted via the insert(Index,Index) function which itself turns the matrix into a non compressed form if that was not the case.

This is a O(log(nnz_j)) operation (binary search) plus the cost of insert(Index,Index) function if the element does not already exist.

    {
      eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
      
      const Index outer = IsRowMajor ? row : col;
      const Index inner = IsRowMajor ? col : row;
 
      Index start = m_outerIndex[outer];
      Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
      eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
      if(end<=start)
        return insert(row,col);
      const Index p = m_data.searchLowerIndex(start,end-1,StorageIndex(inner));
      if((p<end) && (m_data.index(p)==inner))
        return m_data.value(p);
      else
        return insert(row,col);
    }

References col(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols(), eigen_assert, Eigen::end(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insert(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, row(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::searchLowerIndex(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by igl::adjacency_matrix(), and igl::orientable_patches().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ coeffs() [1/2]

Map< Array< Scalar, Dynamic, 1 > > Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::coeffs ( )

inlineinherited

Returns: a read-write view of the stored coefficients as a 1D array expression

Warning: this method is for compressed storage only, and it will trigger an assertion otherwise.

Here is an example:

and the output is:

See also: valuePtr(), isCompressed()

126{ eigen_assert(isCompressed()); return Array<Scalar,Dynamic,1>::Map(valuePtr(),nonZeros()); }

Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::nonZeros

Index nonZeros() const

Definition SparseCompressedBase.h:56

Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::valuePtr

const Scalar * valuePtr() const

Definition SparseCompressedBase.h:71

Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::isCompressed

bool isCompressed() const

Definition SparseCompressedBase.h:107

◆ coeffs() [2/2]

const Map< const Array< Scalar, Dynamic, 1 > > Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::coeffs ( ) const

inlineinherited

Returns: a read-only view of the stored coefficients as a 1D array expression.

Warning: this method is for compressed storage only, and it will trigger an assertion otherwise.

See also: valuePtr(), isCompressed()

114{ eigen_assert(isCompressed()); return Array<Scalar,Dynamic,1>::Map(valuePtr(),nonZeros()); }

◆ collapseDuplicates()

template<typename Scalar , int _Options, typename _StorageIndex >

template<typename DupFunctor >

void Eigen::SparseMatrix< Scalar, _Options, _StorageIndex >::collapseDuplicates ( DupFunctor dup_func = DupFunctor() )

{
  eigen_assert(!isCompressed());
  // TODO, in practice we should be able to use m_innerNonZeros for that task
  IndexVector wi(innerSize());
  wi.fill(-1);
  StorageIndex count = 0;
  // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers
  for(Index j=0; j<outerSize(); ++j)
  {
    StorageIndex start   = count;
    Index oldEnd  = m_outerIndex[j]+m_innerNonZeros[j];
    for(Index k=m_outerIndex[j]; k<oldEnd; ++k)
    {
      Index i = m_data.index(k);
      if(wi(i)>=start)
      {
        // we already meet this entry => accumulate it
        m_data.value(wi(i)) = dup_func(m_data.value(wi(i)), m_data.value(k));
      }
      else
      {
        m_data.value(count) = m_data.value(k);
        m_data.index(count) = m_data.index(k);
        wi(i) = count;
        ++count;
      }
    }
    m_outerIndex[j] = start;
  }
  m_outerIndex[m_outerSize] = count;
 
  // turn the matrix into compressed form
  std::free(m_innerNonZeros);
  m_innerNonZeros = 0;
  m_data.resize(m_outerIndex[m_outerSize]);
}

References eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by Eigen::internal::set_from_triplets(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::sumupDuplicates().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ cols()

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols ( ) const

inline

Returns: the number of columns of the matrix

138{ return IsRowMajor ? m_innerSize : m_outerSize; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerSize, and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize.

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), igl::active_set(), igl::arap_dof_precomputation(), igl::arap_dof_recomputation(), igl::arap_precomputation(), igl::arap_rhs(), igl::AtA_cached_precompute(), igl::bfs(), igl::slim::build_linear_system(), igl::cat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeff(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeffRef(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::cols(), Eigen::IncompleteLUT< _Scalar, _StorageIndex >::cols(), Eigen::SimplicialCholeskyBase< Derived >::cols(), Eigen::SparseLU< _MatrixType, _OrderingType >::cols(), Eigen::SparseQR< _MatrixType, _OrderingType >::cols(), Eigen::SuperLUBase< _MatrixType, Derived >::cols(), igl::components(), Eigen::PastixBase< Derived >::compute(), Eigen::SPQR< _MatrixType >::compute(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize(), Eigen::SimplicialCholeskyBase< Derived >::dumpMemory(), igl::eigs(), Eigen::SimplicialCholeskyBase< Derived >::factorize_preordered(), igl::find_zero(), igl::harmonic(), igl::harmonic(), igl::harwell_boeing(), igl::matlab_format(), igl::max(), igl::min(), igl::min_quad_with_fixed_precompute(), Eigen::internal::minimum_degree_ordering(), igl::matlab::mlsetmatrix(), igl::mosek::mosek_linprog(), igl::mosek::mosek_quadprog(), igl::matlab::prepare_lhs_double(), igl::redux(), Eigen::MatrixMarketIterator< Scalar >::refX(), igl::repdiag(), igl::repmat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize(), Eigen::MatrixMarketIterator< Scalar >::rhs(), Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run(), igl::matlab::MatlabWorkspace::save(), igl::serialization::serialize(), igl::xml::serialization_xml::serialize(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::setIdentity().

Here is the caller graph for this function:

◆ conservativeResize()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize	(	Index	rows,
		Index	cols
	)

inline

Resizes the matrix to a rows x cols matrix leaving old values untouched.

If the sizes of the matrix are decreased, then the matrix is turned to uncompressed-mode and the storage of the out of bounds coefficients is kept and reserved. Call makeCompressed() to pack the entries and squeeze extra memory.

See also: reserve(), setZero(), makeCompressed()

    {
      // No change
      if (this->rows() == rows && this->cols() == cols) return;
      
      // If one dimension is null, then there is nothing to be preserved
      if(rows==0 || cols==0) return resize(rows,cols);
 
      Index innerChange = IsRowMajor ? cols - this->cols() : rows - this->rows();
      Index outerChange = IsRowMajor ? rows - this->rows() : cols - this->cols();
      StorageIndex newInnerSize = convert_index(IsRowMajor ? cols : rows);
 
      // Deals with inner non zeros
      if (m_innerNonZeros)
      {
        // Resize m_innerNonZeros
        StorageIndex *newInnerNonZeros = static_cast<StorageIndex*>(std::realloc(m_innerNonZeros, (m_outerSize + outerChange) * sizeof(StorageIndex)));
        if (!newInnerNonZeros) internal::throw_std_bad_alloc();
        m_innerNonZeros = newInnerNonZeros;
        
        for(Index i=m_outerSize; i<m_outerSize+outerChange; i++)          
          m_innerNonZeros[i] = 0;
      } 
      else if (innerChange < 0) 
      {
        // Inner size decreased: allocate a new m_innerNonZeros
        m_innerNonZeros = static_cast<StorageIndex*>(std::malloc((m_outerSize+outerChange+1) * sizeof(StorageIndex)));
        if (!m_innerNonZeros) internal::throw_std_bad_alloc();
        for(Index i = 0; i < m_outerSize; i++)
          m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i];
      }
      
      // Change the m_innerNonZeros in case of a decrease of inner size
      if (m_innerNonZeros && innerChange < 0)
      {
        for(Index i = 0; i < m_outerSize + (std::min)(outerChange, Index(0)); i++)
        {
          StorageIndex &n = m_innerNonZeros[i];
          StorageIndex start = m_outerIndex[i];
          while (n > 0 && m_data.index(start+n-1) >= newInnerSize) --n; 
        }
      }
      
      m_innerSize = newInnerSize;
 
      // Re-allocate outer index structure if necessary
      if (outerChange == 0)
        return;
          
      StorageIndex *newOuterIndex = static_cast<StorageIndex*>(std::realloc(m_outerIndex, (m_outerSize + outerChange + 1) * sizeof(StorageIndex)));
      if (!newOuterIndex) internal::throw_std_bad_alloc();
      m_outerIndex = newOuterIndex;
      if (outerChange > 0)
      {
        StorageIndex last = m_outerSize == 0 ? 0 : m_outerIndex[m_outerSize];
        for(Index i=m_outerSize; i<m_outerSize+outerChange+1; i++)          
          m_outerIndex[i] = last; 
      }
      m_outerSize += outerChange;
    }

Referenced by igl::shapeup_precomputation().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ const_cast_derived()

template<typename Derived >

Derived & Eigen::SparseMatrixBase< Derived >::const_cast_derived ( ) const

inlineinherited

141 { return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }

Eigen::SparseMatrixBase::SparseMatrixBase

SparseMatrixBase()

Definition SparseMatrixBase.h:192

Referenced by Eigen::Ref< SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >::Ref(), Eigen::Ref< SparseVector< MatScalar, MatOptions, MatIndex >, Options, StrideType >::Ref(), Eigen::internal::evaluator< DynamicSparseMatrix< _Scalar, _Options, _StorageIndex > >::operator SparseMatrixType &(), Eigen::internal::evaluator< SparseVector< _Scalar, _Options, _Index > >::operator SparseVectorType &(), Eigen::DynamicSparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::viewAsCholmod(), and Eigen::viewAsCholmod().

Here is the caller graph for this function:

◆ const_derived()

template<typename Derived >

EIGEN_DEVICE_FUNC const Derived & Eigen::EigenBase< Derived >::const_derived ( ) const

inlineinherited

55 { return *static_cast<const Derived*>(this); }

◆ convert_index()

template<typename Derived >

static StorageIndex Eigen::SparseMatrixBase< Derived >::convert_index ( const Index idx )

inlinestaticprotectedinherited

                                                              {
      return internal::convert_index<StorageIndex>(idx);
    }

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize().

Here is the caller graph for this function:

◆ cwiseProduct() [1/2]

template<typename Derived >

template<typename OtherDerived >

EIGEN_STRONG_INLINE const SparseMatrixBase< Derived >::template CwiseProductDenseReturnType< OtherDerived >::Type Eigen::SparseMatrixBase< Derived >::cwiseProduct ( const MatrixBase< OtherDerived > & other ) const

inherited

{
  return typename CwiseProductDenseReturnType<OtherDerived>::Type(derived(), other.derived());
}

◆ cwiseProduct() [2/2]

template<typename Derived >

template<typename OtherDerived >

EIGEN_STRONG_INLINE const CwiseProductDenseReturnType< OtherDerived >::Type Eigen::SparseMatrixBase< Derived >::cwiseProduct ( const MatrixBase< OtherDerived > & other ) const

inherited

Referenced by Eigen::MatrixBase< Derived >::cwiseProduct().

Here is the caller graph for this function:

◆ data() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

Storage & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::data ( )

inline

182{ return m_data; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data.

◆ data() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const Storage & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::data ( ) const

inline

184{ return m_data; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data.

◆ derived() [1/2]

template<typename Derived >

Derived & Eigen::SparseMatrixBase< Derived >::derived ( )

inlineinherited

139{ return *static_cast<Derived*>(this); }

◆ derived() [2/2]

template<typename Derived >

const Derived & Eigen::SparseMatrixBase< Derived >::derived ( ) const

inlineinherited

138{ return *static_cast<const Derived*>(this); }

◆ diagonal() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

DiagonalReturnType Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::diagonal ( )

inline

Returns: a read-write expression of the diagonal coefficients.

Warning: If the diagonal entries are written, then all diagonal entries must already exist, otherwise an assertion will be raised.

656{ return DiagonalReturnType(*this); }

Eigen::SparseMatrix::DiagonalReturnType

Diagonal< SparseMatrix > DiagonalReturnType

Definition SparseMatrix.h:110

◆ diagonal() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const ConstDiagonalReturnType Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::diagonal ( ) const

inline

Returns: a const expression of the diagonal coefficients.

650{ return ConstDiagonalReturnType(*this); }

Eigen::SparseMatrix::ConstDiagonalReturnType

Diagonal< const SparseMatrix > ConstDiagonalReturnType

Definition SparseMatrix.h:111

Referenced by igl::biharmonic_coordinates(), Eigen::SimplicialLLT< _MatrixType, _UpLo, _Ordering >::determinant(), igl::eigs(), and Eigen::MatrixMarketIterator< Scalar >::matrix().

Here is the caller graph for this function:

◆ dot() [1/4]

template<typename Derived >

template<typename OtherDerived >

internal::traits< Derived >::Scalar Eigen::SparseMatrixBase< Derived >::dot ( const MatrixBase< OtherDerived > & other ) const

inherited

{
  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
  eigen_assert(size() == other.size());
  eigen_assert(other.size()>0 && "you are using a non initialized vector");
 
  internal::evaluator<Derived> thisEval(derived());
  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
  Scalar res(0);
  while (i)
  {
    res += numext::conj(i.value()) * other.coeff(i.index());
    ++i;
  }
  return res;
}

References eigen_assert, EIGEN_STATIC_ASSERT, EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE, and EIGEN_STATIC_ASSERT_VECTOR_ONLY.

◆ dot() [2/4]

template<typename Derived >

template<typename OtherDerived >

Scalar Eigen::SparseMatrixBase< Derived >::dot ( const MatrixBase< OtherDerived > & other ) const

inherited

◆ dot() [3/4]

template<typename Derived >

template<typename OtherDerived >

internal::traits< Derived >::Scalar Eigen::SparseMatrixBase< Derived >::dot ( const SparseMatrixBase< OtherDerived > & other ) const

inherited

{
  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
  eigen_assert(size() == other.size());
 
  internal::evaluator<Derived> thisEval(derived());
  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
  
  internal::evaluator<OtherDerived>  otherEval(other.derived());
  typename internal::evaluator<OtherDerived>::InnerIterator j(otherEval, 0);
 
  Scalar res(0);
  while (i && j)
  {
    if (i.index()==j.index())
    {
      res += numext::conj(i.value()) * j.value();
      ++i; ++j;
    }
    else if (i.index()<j.index())
      ++i;
    else
      ++j;
  }
  return res;
}

References Eigen::SparseMatrixBase< Derived >::derived(), eigen_assert, EIGEN_STATIC_ASSERT, EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE, EIGEN_STATIC_ASSERT_VECTOR_ONLY, and Eigen::SparseMatrixBase< Derived >::size().

Here is the call graph for this function:

◆ dot() [4/4]

template<typename Derived >

template<typename OtherDerived >

Scalar Eigen::SparseMatrixBase< Derived >::dot ( const SparseMatrixBase< OtherDerived > & other ) const

inherited

◆ eval()

template<typename Derived >

const internal::eval< Derived >::type Eigen::SparseMatrixBase< Derived >::eval ( ) const

inlineinherited

Returns: the matrix or vector obtained by evaluating this expression.

Notice that in the case of a plain matrix or vector (not an expression) this function just returns a const reference, in order to avoid a useless copy.

385 { return typename internal::eval<Derived>::type(derived()); }

References Eigen::SparseMatrixBase< Derived >::derived().

Referenced by igl::biharmonic_coordinates().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ evalTo()

template<typename Derived >

template<typename Dest >

void Eigen::SparseMatrixBase< Derived >::evalTo ( Dest & ) const

privateinherited

◆ finalize()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::finalize ( )

inline

    {
      if(isCompressed())
      {
        StorageIndex size = internal::convert_index<StorageIndex>(m_data.size());
        Index i = m_outerSize;
        // find the last filled column
        while (i>=0 && m_outerIndex[i]==0)
          --i;
        ++i;
        while (i<=m_outerSize)
        {
          m_outerIndex[i] = size;
          ++i;
        }
      }
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::isCompressed(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::size(), and Eigen::SparseMatrixBase< Derived >::size().

Referenced by igl::repmat(), and igl::speye().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ initAssignment()

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename Other >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::initAssignment ( const Other & other )

inlineprotected

    {
      resize(other.rows(), other.cols());
      if(m_innerNonZeros)
      {
        std::free(m_innerNonZeros);
        m_innerNonZeros = 0;
      }
    }

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=().

Here is the caller graph for this function:

◆ innerIndexPtr() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerIndexPtr ( )

inline

Returns: a non-const pointer to the array of inner indices. This function is aimed at interoperability with other libraries.

See also: valuePtr(), outerIndexPtr()

161{ return m_data.indexPtr(); }

Eigen::internal::CompressedStorage::indexPtr

const StorageIndex * indexPtr() const

Definition CompressedStorage.h:115

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::indexPtr(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data.

Here is the call graph for this function:

◆ innerIndexPtr() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerIndexPtr ( ) const

inline

Returns: a const pointer to the array of inner indices. This function is aimed at interoperability with other libraries.

See also: valuePtr(), outerIndexPtr()

157{ return m_data.indexPtr(); }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::indexPtr(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data.

Referenced by Eigen::PastixBase< Derived >::analyzePattern(), igl::AtA_cached_precompute(), Eigen::PastixBase< Derived >::factorize(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize(), Eigen::internal::minimum_degree_ordering(), Eigen::internal::permute_symm_to_symm(), and Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ innerNonZeroPtr() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerNonZeroPtr ( )

inline

Returns: a non-const pointer to the array of the number of non zeros of the inner vectors. This function is aimed at interoperability with other libraries.

Warning: it returns the null pointer 0 in compressed mode

179{ return m_innerNonZeros; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros.

◆ innerNonZeroPtr() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerNonZeroPtr ( ) const

inline

Returns: a const pointer to the array of the number of non zeros of the inner vectors. This function is aimed at interoperability with other libraries.

Warning: it returns the null pointer 0 in compressed mode

175{ return m_innerNonZeros; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros.

◆ innerNonZeros() [1/2]

Eigen::Map< IndexVector > Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::innerNonZeros ( )

inlineprotectedinherited

50{ return Eigen::Map<IndexVector>(innerNonZeroPtr(), isCompressed()?0:derived().outerSize()); }

Eigen::Map

A matrix or vector expression mapping an existing array of data.

Definition Map.h:96

Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::innerNonZeroPtr

const StorageIndex * innerNonZeroPtr() const

Definition SparseCompressedBase.h:100

Eigen::SparseMatrixBase::outerSize

Index outerSize() const

Definition SparseMatrixBase.h:184

◆ innerNonZeros() [2/2]

const Eigen::Map< const IndexVector > Eigen::SparseCompressedBase< SparseMatrix< _Scalar, _Options, _StorageIndex > >::innerNonZeros ( ) const

inlineprotectedinherited

51{ return Eigen::Map<const IndexVector>(innerNonZeroPtr(), isCompressed()?0:derived().outerSize()); }

◆ innerSize()

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerSize ( ) const

inline

Returns: the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major)

141{ return m_innerSize; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerSize.

◆ innerVector() [1/2]

template<typename Derived >

SparseMatrixBase< Derived >::InnerVectorReturnType Eigen::SparseMatrixBase< Derived >::innerVector ( Index outer )

inherited

Returns: the outer -th column (resp. row) of the matrix *this if *this is col-major (resp. row-major).

334{ return InnerVectorReturnType(derived(), outer); }

Eigen::SparseMatrixBase::InnerVectorReturnType

Block< Derived, IsRowMajor?1:Dynamic, IsRowMajor?Dynamic:1, true > InnerVectorReturnType

Definition SparseMatrixBase.h:354

◆ innerVector() [2/2]

template<typename Derived >

const SparseMatrixBase< Derived >::ConstInnerVectorReturnType Eigen::SparseMatrixBase< Derived >::innerVector ( Index outer ) const

inherited

Returns: the outer -th column (resp. row) of the matrix *this if *this is col-major (resp. row-major). Read-only.

341{ return ConstInnerVectorReturnType(derived(), outer); }

Eigen::SparseMatrixBase::ConstInnerVectorReturnType

Block< const Derived, IsRowMajor?1:Dynamic, IsRowMajor?Dynamic:1, true > ConstInnerVectorReturnType

Definition SparseMatrixBase.h:355

◆ innerVectors() [1/2]

template<typename Derived >

SparseMatrixBase< Derived >::InnerVectorsReturnType Eigen::SparseMatrixBase< Derived >::innerVectors	(	Index	outerStart,
		Index	outerSize
	)

inherited

Returns: the outer -th column (resp. row) of the matrix *this if *this is col-major (resp. row-major).

{
  return Block<Derived,Dynamic,Dynamic,true>(derived(),
                                             IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
                                             IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize);
 
}

◆ innerVectors() [2/2]

template<typename Derived >

const SparseMatrixBase< Derived >::ConstInnerVectorsReturnType Eigen::SparseMatrixBase< Derived >::innerVectors	(	Index	outerStart,
		Index	outerSize
	)		const

inherited

Returns: the outer -th column (resp. row) of the matrix *this if *this is col-major (resp. row-major). Read-only.

{
  return Block<const Derived,Dynamic,Dynamic,true>(derived(),
                                                  IsRowMajor ? outerStart : 0, IsRowMajor ? 0 : outerStart,
                                                  IsRowMajor ? outerSize : rows(), IsRowMajor ? cols() : outerSize);
 
}

◆ insert()

template<typename _Scalar , int _Options, typename _StorageIndex >

SparseMatrix< _Scalar, _Options, _StorageIndex >::Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insert	(	Index	row,
		Index	col
	)

Returns: a reference to a novel non zero coefficient with coordinates row x col. The non zero coefficient must not already exist.

If the matrix *this is in compressed mode, then *this is turned into uncompressed mode while reserving room for 2 x this->innerSize() non zeros if reserve(Index) has not been called earlier. In this case, the insertion procedure is optimized for a sequential insertion mode where elements are assumed to be inserted by increasing outer-indices.

If that's not the case, then it is strongly recommended to either use a triplet-list to assemble the matrix, or to first call reserve(const SizesType &) to reserve the appropriate number of non-zero elements per inner vector.

Assuming memory has been appropriately reserved, this function performs a sorted insertion in O(1) if the elements of each inner vector are inserted in increasing inner index order, and in O(nnz_j) for a random insertion.

{
  eigen_assert(row>=0 && row<rows() && col>=0 && col<cols());
  
  const Index outer = IsRowMajor ? row : col;
  const Index inner = IsRowMajor ? col : row;
  
  if(isCompressed())
  {
    if(nonZeros()==0)
    {
      // reserve space if not already done
      if(m_data.allocatedSize()==0)
        m_data.reserve(2*m_innerSize);
      
      // turn the matrix into non-compressed mode
      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
      if(!m_innerNonZeros) internal::throw_std_bad_alloc();
      
      memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex));
      
      // pack all inner-vectors to the end of the pre-allocated space
      // and allocate the entire free-space to the first inner-vector
      StorageIndex end = convert_index(m_data.allocatedSize());
      for(Index j=1; j<=m_outerSize; ++j)
        m_outerIndex[j] = end;
    }
    else
    {
      // turn the matrix into non-compressed mode
      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
      if(!m_innerNonZeros) internal::throw_std_bad_alloc();
      for(Index j=0; j<m_outerSize; ++j)
        m_innerNonZeros[j] = m_outerIndex[j+1]-m_outerIndex[j];
    }
  }
  
  // check whether we can do a fast "push back" insertion
  Index data_end = m_data.allocatedSize();
  
  // First case: we are filling a new inner vector which is packed at the end.
  // We assume that all remaining inner-vectors are also empty and packed to the end.
  if(m_outerIndex[outer]==data_end)
  {
    eigen_internal_assert(m_innerNonZeros[outer]==0);
    
    // pack previous empty inner-vectors to end of the used-space
    // and allocate the entire free-space to the current inner-vector.
    StorageIndex p = convert_index(m_data.size());
    Index j = outer;
    while(j>=0 && m_innerNonZeros[j]==0)
      m_outerIndex[j--] = p;
    
    // push back the new element
    ++m_innerNonZeros[outer];
    m_data.append(Scalar(0), inner);
    
    // check for reallocation
    if(data_end != m_data.allocatedSize())
    {
      // m_data has been reallocated
      //  -> move remaining inner-vectors back to the end of the free-space
      //     so that the entire free-space is allocated to the current inner-vector.
      eigen_internal_assert(data_end < m_data.allocatedSize());
      StorageIndex new_end = convert_index(m_data.allocatedSize());
      for(Index k=outer+1; k<=m_outerSize; ++k)
        if(m_outerIndex[k]==data_end)
          m_outerIndex[k] = new_end;
    }
    return m_data.value(p);
  }
  
  // Second case: the next inner-vector is packed to the end
  // and the current inner-vector end match the used-space.
  if(m_outerIndex[outer+1]==data_end && m_outerIndex[outer]+m_innerNonZeros[outer]==m_data.size())
  {
    eigen_internal_assert(outer+1==m_outerSize || m_innerNonZeros[outer+1]==0);
    
    // add space for the new element
    ++m_innerNonZeros[outer];
    m_data.resize(m_data.size()+1);
    
    // check for reallocation
    if(data_end != m_data.allocatedSize())
    {
      // m_data has been reallocated
      //  -> move remaining inner-vectors back to the end of the free-space
      //     so that the entire free-space is allocated to the current inner-vector.
      eigen_internal_assert(data_end < m_data.allocatedSize());
      StorageIndex new_end = convert_index(m_data.allocatedSize());
      for(Index k=outer+1; k<=m_outerSize; ++k)
        if(m_outerIndex[k]==data_end)
          m_outerIndex[k] = new_end;
    }
    
    // and insert it at the right position (sorted insertion)
    Index startId = m_outerIndex[outer];
    Index p = m_outerIndex[outer]+m_innerNonZeros[outer]-1;
    while ( (p > startId) && (m_data.index(p-1) > inner) )
    {
      m_data.index(p) = m_data.index(p-1);
      m_data.value(p) = m_data.value(p-1);
      --p;
    }
    
    m_data.index(p) = convert_index(inner);
    return (m_data.value(p) = 0);
  }
  
  if(m_data.size() != m_data.allocatedSize())
  {
    // make sure the matrix is compatible to random un-compressed insertion:
    m_data.resize(m_data.allocatedSize());
    this->reserveInnerVectors(Array<StorageIndex,Dynamic,1>::Constant(m_outerSize, 2));
  }
  
  return insertUncompressed(row,col);
}

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::allocatedSize(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::append(), col(), eigen_assert, eigen_internal_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::reserve(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), row(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::size(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by igl::cat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeffRef(), igl::group_sum_matrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertByOuterInner(), igl::lbs_matrix_column(), igl::lbs_matrix_column(), igl::repdiag(), igl::repmat(), and igl::speye().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ insertBack()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBack	(	Index	row,
		Index	col
	)

inline

    {
      return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
    }

References col(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBackByOuterInner(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, and row().

Here is the call graph for this function:

◆ insertBackByOuterInner()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBackByOuterInner	(	Index	outer,
		Index	inner
	)

inline

    {
      eigen_assert(Index(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)");
      eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)");
      Index p = m_outerIndex[outer+1];
      ++m_outerIndex[outer+1];
      m_data.append(Scalar(0), inner);
      return m_data.value(p);
    }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::append(), eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::size(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBack().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ insertBackByOuterInnerUnordered()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBackByOuterInnerUnordered	(	Index	outer,
		Index	inner
	)

inline

    {
      Index p = m_outerIndex[outer+1];
      ++m_outerIndex[outer+1];
      m_data.append(Scalar(0), inner);
      return m_data.value(p);
    }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::append(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Here is the call graph for this function:

◆ insertBackUncompressed()

template<typename _Scalar , int _Options, typename _StorageIndex >

EIGEN_STRONG_INLINE Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertBackUncompressed	(	Index	row,
		Index	col
	)

inline

    {
      const Index outer = IsRowMajor ? row : col;
      const Index inner = IsRowMajor ? col : row;
 
      eigen_assert(!isCompressed());
      eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer]));
 
      Index p = m_outerIndex[outer] + m_innerNonZeros[outer]++;
      m_data.index(p) = convert_index(inner);
      return (m_data.value(p) = Scalar(0));
    }

References col(), eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), row(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by Eigen::internal::set_from_triplets().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ insertByOuterInner()

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertByOuterInner	(	Index	j,
		Index	i
	)

inline

    {
      return insert(IsRowMajor ? j : i, IsRowMajor ? i : j);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insert(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor.

Referenced by Eigen::internal::permutation_matrix_product< ExpressionType, Side, Transposed, SparseShape >::run().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ insertCompressed()

template<typename _Scalar , int _Options, typename _StorageIndex >

EIGEN_DONT_INLINE SparseMatrix< _Scalar, _Options, _StorageIndex >::Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertCompressed	(	Index	row,
		Index	col
	)

protected

{
  eigen_assert(isCompressed());
 
  const Index outer = IsRowMajor ? row : col;
  const Index inner = IsRowMajor ? col : row;
 
  Index previousOuter = outer;
  if (m_outerIndex[outer+1]==0)
  {
    // we start a new inner vector
    while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
    {
      m_outerIndex[previousOuter] = convert_index(m_data.size());
      --previousOuter;
    }
    m_outerIndex[outer+1] = m_outerIndex[outer];
  }
 
  // here we have to handle the tricky case where the outerIndex array
  // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g.,
  // the 2nd inner vector...
  bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
                && (std::size_t(m_outerIndex[outer+1]) == m_data.size());
 
  std::size_t startId = m_outerIndex[outer];
  // FIXME let's make sure sizeof(long int) == sizeof(std::size_t)
  std::size_t p = m_outerIndex[outer+1];
  ++m_outerIndex[outer+1];
 
  double reallocRatio = 1;
  if (m_data.allocatedSize()<=m_data.size())
  {
    // if there is no preallocated memory, let's reserve a minimum of 32 elements
    if (m_data.size()==0)
    {
      m_data.reserve(32);
    }
    else
    {
      // we need to reallocate the data, to reduce multiple reallocations
      // we use a smart resize algorithm based on the current filling ratio
      // in addition, we use double to avoid integers overflows
      double nnzEstimate = double(m_outerIndex[outer])*double(m_outerSize)/double(outer+1);
      reallocRatio = (nnzEstimate-double(m_data.size()))/double(m_data.size());
      // furthermore we bound the realloc ratio to:
      //   1) reduce multiple minor realloc when the matrix is almost filled
      //   2) avoid to allocate too much memory when the matrix is almost empty
      reallocRatio = (std::min)((std::max)(reallocRatio,1.5),8.);
    }
  }
  m_data.resize(m_data.size()+1,reallocRatio);
 
  if (!isLastVec)
  {
    if (previousOuter==-1)
    {
      // oops wrong guess.
      // let's correct the outer offsets
      for (Index k=0; k<=(outer+1); ++k)
        m_outerIndex[k] = 0;
      Index k=outer+1;
      while(m_outerIndex[k]==0)
        m_outerIndex[k++] = 1;
      while (k<=m_outerSize && m_outerIndex[k]!=0)
        m_outerIndex[k++]++;
      p = 0;
      --k;
      k = m_outerIndex[k]-1;
      while (k>0)
      {
        m_data.index(k) = m_data.index(k-1);
        m_data.value(k) = m_data.value(k-1);
        k--;
      }
    }
    else
    {
      // we are not inserting into the last inner vec
      // update outer indices:
      Index j = outer+2;
      while (j<=m_outerSize && m_outerIndex[j]!=0)
        m_outerIndex[j++]++;
      --j;
      // shift data of last vecs:
      Index k = m_outerIndex[j]-1;
      while (k>=Index(p))
      {
        m_data.index(k) = m_data.index(k-1);
        m_data.value(k) = m_data.value(k-1);
        k--;
      }
    }
  }
 
  while ( (p > startId) && (m_data.index(p-1) > inner) )
  {
    m_data.index(p) = m_data.index(p-1);
    m_data.value(p) = m_data.value(p-1);
    --p;
  }
 
  m_data.index(p) = inner;
  return (m_data.value(p) = Scalar(0));
}

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::allocatedSize(), col(), eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::reserve(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), row(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::size(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Here is the call graph for this function:

◆ insertUncompressed()

template<typename _Scalar , int _Options, typename _StorageIndex >

EIGEN_DONT_INLINE SparseMatrix< _Scalar, _Options, _StorageIndex >::Scalar & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::insertUncompressed	(	Index	row,
		Index	col
	)

protected

{
  eigen_assert(!isCompressed());
 
  const Index outer = IsRowMajor ? row : col;
  const StorageIndex inner = convert_index(IsRowMajor ? col : row);
 
  Index room = m_outerIndex[outer+1] - m_outerIndex[outer];
  StorageIndex innerNNZ = m_innerNonZeros[outer];
  if(innerNNZ>=room)
  {
    // this inner vector is full, we need to reallocate the whole buffer :(
    reserve(SingletonVector(outer,std::max<StorageIndex>(2,innerNNZ)));
  }
 
  Index startId = m_outerIndex[outer];
  Index p = startId + m_innerNonZeros[outer];
  while ( (p > startId) && (m_data.index(p-1) > inner) )
  {
    m_data.index(p) = m_data.index(p-1);
    m_data.value(p) = m_data.value(p-1);
    --p;
  }
  eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exists, you must call coeffRef to this end");
 
  m_innerNonZeros[outer]++;
 
  m_data.index(p) = inner;
  return (m_data.value(p) = Scalar(0));
}

References col(), eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), row(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Here is the call graph for this function:

◆ isApprox() [1/2]

template<typename Derived >

template<typename OtherDerived >

bool Eigen::SparseMatrixBase< Derived >::isApprox	(	const MatrixBase< OtherDerived > &	other,
		const RealScalar &	prec = `NumTraits<Scalar>::dummy_precision()`
	)		const

inlineinherited

377 { return toDense().isApprox(other,prec); }

Eigen::SparseMatrixBase::toDense

DenseMatrixType toDense() const

Definition SparseMatrixBase.h:365

References Eigen::SparseMatrixBase< Derived >::toDense().

Here is the call graph for this function:

◆ isApprox() [2/2]

template<typename Derived >

template<typename OtherDerived >

bool Eigen::SparseMatrixBase< Derived >::isApprox	(	const SparseMatrixBase< OtherDerived > &	other,
		const RealScalar &	prec = `NumTraits<Scalar>::dummy_precision()`
	)		const

inherited

{
  const typename internal::nested_eval<Derived,2,PlainObject>::type actualA(derived());
  typename internal::conditional<bool(IsRowMajor)==bool(OtherDerived::IsRowMajor),
    const typename internal::nested_eval<OtherDerived,2,PlainObject>::type,
    const PlainObject>::type actualB(other.derived());
 
  return (actualA - actualB).squaredNorm() <= prec * prec * numext::mini(actualA.squaredNorm(), actualB.squaredNorm());
}

References Eigen::SparseMatrixBase< Derived >::derived(), and Eigen::numext::mini().

Here is the call graph for this function:

◆ isCompressed()

template<typename _Scalar , int _Options, typename _StorageIndex >

bool Eigen::SparseCompressedBase< Derived >::isCompressed ( ) const

inline

Returns: whether *this is in compressed form.

107{ return innerNonZeroPtr()==0; }

Eigen::SparseMatrix::innerNonZeroPtr

const StorageIndex * innerNonZeroPtr() const

Definition SparseMatrix.h:175

Referenced by Eigen::Ref< SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >::Ref(), igl::AtA_cached_precompute(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::finalize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::makeCompressed(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserve(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserveInnerVectors().

Here is the caller graph for this function:

◆ isRValue()

template<typename Derived >

bool Eigen::SparseMatrixBase< Derived >::isRValue ( ) const

inlineinherited

189{ return m_isRValue; }

Eigen::SparseMatrixBase::m_isRValue

bool m_isRValue

Definition SparseMatrixBase.h:394

References Eigen::SparseMatrixBase< Derived >::m_isRValue.

Referenced by Eigen::DynamicSparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), and Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::operator=().

Here is the caller graph for this function:

◆ isVector()

template<typename Derived >

bool Eigen::SparseMatrixBase< Derived >::isVector ( ) const

inlineinherited

Returns: true if either the number of rows or the number of columns is equal to 1. In other words, this function returns
rows()==1 || cols()==1

See also: rows(), cols(), IsVectorAtCompileTime.

181{ return rows()==1 || cols()==1; }

References Eigen::SparseMatrixBase< Derived >::cols(), and Eigen::SparseMatrixBase< Derived >::rows().

Here is the call graph for this function:

◆ makeCompressed()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::makeCompressed ( )

inline

Turns the matrix into the compressed format.

    {
      if(isCompressed())
        return;
      
      eigen_internal_assert(m_outerIndex!=0 && m_outerSize>0);
      
      Index oldStart = m_outerIndex[1];
      m_outerIndex[1] = m_innerNonZeros[0];
      for(Index j=1; j<m_outerSize; ++j)
      {
        Index nextOldStart = m_outerIndex[j+1];
        Index offset = oldStart - m_outerIndex[j];
        if(offset>0)
        {
          for(Index k=0; k<m_innerNonZeros[j]; ++k)
          {
            m_data.index(m_outerIndex[j]+k) = m_data.index(oldStart+k);
            m_data.value(m_outerIndex[j]+k) = m_data.value(oldStart+k);
          }
        }
        m_outerIndex[j+1] = m_outerIndex[j] + m_innerNonZeros[j];
        oldStart = nextOldStart;
      }
      std::free(m_innerNonZeros);
      m_innerNonZeros = 0;
      m_data.resize(m_outerIndex[m_outerSize]);
      m_data.squeeze();
    }

References eigen_internal_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::isCompressed(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::squeeze(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by igl::arap_linear_block_elements(), igl::arap_linear_block_spokes(), igl::arap_linear_block_spokes_and_rims(), igl::AtA_cached_precompute(), igl::slim::build_linear_system(), igl::cat(), Eigen::PardisoLU< MatrixType >::getMatrix(), Eigen::PardisoLLT< MatrixType, _UpLo >::getMatrix(), Eigen::PardisoLDLT< MatrixType, Options >::getMatrix(), igl::group_sum_matrix(), igl::lbs_matrix_column(), igl::lbs_matrix_column(), igl::slim::pre_calc(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::prune(), igl::repdiag(), Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run(), and igl::slice_cached_precompute().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ markAsRValue()

template<typename Derived >

Derived & Eigen::SparseMatrixBase< Derived >::markAsRValue ( )

inlineinherited

190{ m_isRValue = true; return derived(); }

References Eigen::SparseMatrixBase< Derived >::derived(), and Eigen::SparseMatrixBase< Derived >::m_isRValue.

Here is the call graph for this function:

◆ nonZeros()

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseCompressedBase< Derived >::nonZeros ( ) const

inline

Returns: the number of non zero coefficients

    {
      if(Derived::IsVectorAtCompileTime && outerIndexPtr()==0)
        return derived().nonZeros();
      else if(isCompressed())
        return outerIndexPtr()[derived().outerSize()]-outerIndexPtr()[0];
      else if(derived().outerSize()==0)
        return 0;
      else
        return innerNonZeros().sum();
    }

Referenced by Eigen::SimplicialCholeskyBase< Derived >::_solve_impl(), igl::AtA_cached_precompute(), igl::cat(), Eigen::SimplicialCholeskyBase< Derived >::dumpMemory(), igl::edges(), igl::serialization::getByteSize(), igl::harwell_boeing(), igl::min_quad_with_fixed_precompute(), Eigen::internal::minimum_degree_ordering(), igl::matlab::mlsetmatrix(), igl::matlab::prepare_lhs_double(), igl::repdiag(), igl::repmat(), igl::matlab::MatlabWorkspace::save(), igl::serialization::serialize(), and igl::slice_cached_precompute().

Here is the caller graph for this function:

◆ norm()

template<typename Derived >

NumTraits< typenameinternal::traits< Derived >::Scalar >::Real Eigen::SparseMatrixBase< Derived >::norm

inlineinherited

{
  using std::sqrt;
  return sqrt(squaredNorm());
}

References sqrt().

Referenced by Eigen::SPQR< _MatrixType >::compute(), and Eigen::MatrixMarketIterator< Scalar >::matrix().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ operator*() [1/3]

template<typename Derived >

template<typename OtherDerived >

const Product< Derived, OtherDerived > Eigen::SparseMatrixBase< Derived >::operator* ( const DiagonalBase< OtherDerived > & other ) const

inlineinherited

298 { return Product<Derived,OtherDerived>(derived(), other.derived()); }

References Eigen::DiagonalBase< Derived >::derived(), and Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ operator*() [2/3]

template<typename Derived >

template<typename OtherDerived >

const Product< Derived, OtherDerived > Eigen::SparseMatrixBase< Derived >::operator* ( const MatrixBase< OtherDerived > & other ) const

inlineinherited

315 { return Product<Derived,OtherDerived>(derived(), other.derived()); }

References Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ operator*() [3/3]

template<typename Derived >

template<typename OtherDerived >

const Product< Derived, OtherDerived, AliasFreeProduct > Eigen::SparseMatrixBase< Derived >::operator* ( const SparseMatrixBase< OtherDerived > & other ) const

inlineinherited

Returns: an expression of the product of two sparse matrices. By default a conservative product preserving the symbolic non zeros is performed. The automatic pruning of the small values can be achieved by calling the pruned() function in which case a totally different product algorithm is employed:
C = (A*B).pruned(); // supress numerical zeros (exact)

C = (A*B).pruned(ref);

C = (A*B).pruned(ref,epsilon);

Eigen::SparseMatrixBase::pruned
const SparseView< Derived > pruned(const Scalar &reference=Scalar(0), const RealScalar &epsilon=NumTraits< Scalar >::dummy_precision()) const
Definition SparseView.h:245

where ref is a meaningful non zero reference value.

{
  return Product<Derived,OtherDerived,AliasFreeProduct>(derived(), other.derived());
}

References Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ operator*=() [1/2]

template<typename Derived >

EIGEN_STRONG_INLINE Derived & Eigen::SparseMatrixBase< Derived >::operator*= ( const Scalar & other )

inherited

{
  typedef typename internal::evaluator<Derived>::InnerIterator EvalIterator;
  internal::evaluator<Derived> thisEval(derived());
  for (Index j=0; j<outerSize(); ++j)
    for (EvalIterator i(thisEval,j); i; ++i)
      i.valueRef() *= other;
  return derived();
}

◆ operator*=() [2/2]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator*= ( const SparseMatrixBase< OtherDerived > & other )

inherited

◆ operator+=() [1/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator+= ( const DiagonalBase< OtherDerived > & other )

inherited

{
  call_assignment_no_alias(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
  return derived();
}

References Eigen::DiagonalBase< Derived >::derived().

Here is the call graph for this function:

◆ operator+=() [2/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator+= ( const EigenBase< OtherDerived > & other )

inherited

{
  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());
  return derived();
}

References Eigen::EigenBase< Derived >::derived().

Here is the call graph for this function:

◆ operator+=() [3/4]

template<typename Derived >

template<typename OtherDerived >

EIGEN_STRONG_INLINE Derived & Eigen::SparseMatrixBase< Derived >::operator+= ( const SparseMatrixBase< OtherDerived > & other )

inherited

{
  return derived() = derived() + other.derived();
}

References Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ operator+=() [4/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator+= ( const SparseMatrixBase< OtherDerived > & other )

inherited

◆ operator-=() [1/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator-= ( const DiagonalBase< OtherDerived > & other )

inherited

{
  call_assignment_no_alias(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
  return derived();
}

References Eigen::DiagonalBase< Derived >::derived().

Here is the call graph for this function:

◆ operator-=() [2/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator-= ( const EigenBase< OtherDerived > & other )

inherited

{
  call_assignment(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
  return derived();
}

References Eigen::EigenBase< Derived >::derived().

Here is the call graph for this function:

◆ operator-=() [3/4]

template<typename Derived >

template<typename OtherDerived >

EIGEN_STRONG_INLINE Derived & Eigen::SparseMatrixBase< Derived >::operator-= ( const SparseMatrixBase< OtherDerived > & other )

inherited

{
  return derived() = derived() - other.derived();
}

References Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ operator-=() [4/4]

template<typename Derived >

template<typename OtherDerived >

Derived & Eigen::SparseMatrixBase< Derived >::operator-= ( const SparseMatrixBase< OtherDerived > & other )

inherited

◆ operator/=()

template<typename Derived >

EIGEN_STRONG_INLINE Derived & Eigen::SparseMatrixBase< Derived >::operator/= ( const Scalar & other )

inherited

{
  typedef typename internal::evaluator<Derived>::InnerIterator EvalIterator;
  internal::evaluator<Derived> thisEval(derived());
  for (Index j=0; j<outerSize(); ++j)
    for (EvalIterator i(thisEval,j); i; ++i)
      i.valueRef() /= other;
  return derived();
}

◆ operator=() [1/4]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

SparseMatrix & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator= ( const EigenBase< OtherDerived > & other )

inline

782 { return Base::operator=(other.derived()); }

References Eigen::EigenBase< Derived >::derived(), and Eigen::SparseCompressedBase< Derived >::operator=().

Here is the call graph for this function:

◆ operator=() [2/4]

template<typename _Scalar , int _Options, typename _StorageIndex >

SparseMatrix & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator= ( const SparseMatrix< _Scalar, _Options, _StorageIndex > & other )

inline

    {
      if (other.isRValue())
      {
        swap(other.const_cast_derived());
      }
      else if(this!=&other)
      {
        #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
          EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
        #endif
        initAssignment(other);
        if(other.isCompressed())
        {
          internal::smart_copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex);
          m_data = other.m_data;
        }
        else
        {
          Base::operator=(other);
        }
      }
      return *this;
    }

References Eigen::SparseMatrixBase< Derived >::const_cast_derived(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::initAssignment(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::isCompressed(), Eigen::SparseMatrixBase< Derived >::isRValue(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, Eigen::SparseCompressedBase< Derived >::operator=(), Eigen::internal::smart_copy(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::swap().

Here is the call graph for this function:

◆ operator=() [3/4]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

EIGEN_DONT_INLINE SparseMatrix & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator= ( const SparseMatrixBase< OtherDerived > & other )

◆ operator=() [4/4]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename OtherDerived >

EIGEN_DONT_INLINE SparseMatrix< Scalar, _Options, _StorageIndex > & Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator= ( const SparseMatrixBase< OtherDerived > & other )

{
  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
  #ifdef EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
    EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN
  #endif
      
  const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit);
  if (needToTranspose)
  {
    #ifdef EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
      EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
    #endif
    // two passes algorithm:
    //  1 - compute the number of coeffs per dest inner vector
    //  2 - do the actual copy/eval
    // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
    typedef typename internal::nested_eval<OtherDerived,2,typename internal::plain_matrix_type<OtherDerived>::type >::type OtherCopy;
    typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
    typedef internal::evaluator<_OtherCopy> OtherCopyEval;
    OtherCopy otherCopy(other.derived());
    OtherCopyEval otherCopyEval(otherCopy);
 
    SparseMatrix dest(other.rows(),other.cols());
    Eigen::Map<IndexVector> (dest.m_outerIndex,dest.outerSize()).setZero();
 
    // pass 1
    // FIXME the above copy could be merged with that pass
    for (Index j=0; j<otherCopy.outerSize(); ++j)
      for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
        ++dest.m_outerIndex[it.index()];
 
    // prefix sum
    StorageIndex count = 0;
    IndexVector positions(dest.outerSize());
    for (Index j=0; j<dest.outerSize(); ++j)
    {
      StorageIndex tmp = dest.m_outerIndex[j];
      dest.m_outerIndex[j] = count;
      positions[j] = count;
      count += tmp;
    }
    dest.m_outerIndex[dest.outerSize()] = count;
    // alloc
    dest.m_data.resize(count);
    // pass 2
    for (StorageIndex j=0; j<otherCopy.outerSize(); ++j)
    {
      for (typename OtherCopyEval::InnerIterator it(otherCopyEval, j); it; ++it)
      {
        Index pos = positions[it.index()]++;
        dest.m_data.index(pos) = j;
        dest.m_data.value(pos) = it.value();
      }
    }
    this->swap(dest);
    return *this;
  }
  else
  {
    if(other.isRValue())
    {
      initAssignment(other.derived());
    }
    // there is no special optimization
    return Base::operator=(other.derived());
  }
}

References Eigen::SparseMatrixBase< Derived >::cols(), Eigen::SparseMatrixBase< Derived >::derived(), EIGEN_STATIC_ASSERT, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrixBase< Derived >::isRValue(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::outerSize(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), Eigen::RowMajorBit, Eigen::SparseMatrixBase< Derived >::rows(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Here is the call graph for this function:

◆ outerIndexPtr() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::outerIndexPtr ( )

inline

Returns: a non-const pointer to the array of the starting positions of the inner vectors. This function is aimed at interoperability with other libraries.

See also: valuePtr(), innerIndexPtr()

170{ return m_outerIndex; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex.

◆ outerIndexPtr() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const StorageIndex * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::outerIndexPtr ( ) const

inline

Returns: a const pointer to the array of the starting positions of the inner vectors. This function is aimed at interoperability with other libraries.

See also: valuePtr(), innerIndexPtr()

166{ return m_outerIndex; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex.

Referenced by Eigen::PastixBase< Derived >::analyzePattern(), igl::AtA_cached_precompute(), Eigen::PastixBase< Derived >::factorize(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize(), Eigen::internal::minimum_degree_ordering(), and Eigen::internal::permute_symm_to_symm().

Here is the caller graph for this function:

◆ outerSize()

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::outerSize ( ) const

inline

Returns: the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major)

143{ return m_outerSize; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize.

Referenced by igl::adjacency_matrix(), igl::PlanarizerShapeUp< DerivedV, DerivedF >::assembleQ(), igl::AtA_cached_precompute(), igl::slim::buildA(), igl::cat(), igl::components(), igl::edges(), igl::for_each(), Eigen::PastixLU< _MatrixType, IsStrSym >::grabMatrix(), igl::harwell_boeing(), igl::isdiag(), igl::matlab::mlsetmatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=(), igl::orientable_patches(), igl::matlab::prepare_lhs_double(), igl::repdiag(), igl::repmat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize(), igl::matlab::MatlabWorkspace::save(), igl::serialization::serialize(), igl::xml::serialization_xml::serialize(), Eigen::internal::set_from_triplets(), and Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::swap().

Here is the caller graph for this function:

◆ prune() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<typename KeepFunc >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::prune ( const KeepFunc & keep = KeepFunc() )

inline

Turns the matrix into compressed format, and suppresses all nonzeros which do not satisfy the predicate keep. The functor type KeepFunc must implement the following function:

bool operator() (const Index& row, const Index& col, const Scalar& value) const;

See also: prune(Scalar,RealScalar)

    {
      // TODO optimize the uncompressed mode to avoid moving and allocating the data twice
      makeCompressed();
 
      StorageIndex k = 0;
      for(Index j=0; j<m_outerSize; ++j)
      {
        Index previousStart = m_outerIndex[j];
        m_outerIndex[j] = k;
        Index end = m_outerIndex[j+1];
        for(Index i=previousStart; i<end; ++i)
        {
          if(keep(IsRowMajor?j:m_data.index(i), IsRowMajor?m_data.index(i):j, m_data.value(i)))
          {
            m_data.value(k) = m_data.value(i);
            m_data.index(k) = m_data.index(i);
            ++k;
          }
        }
      }
      m_outerIndex[m_outerSize] = k;
      m_data.resize(k,0);
    }

References Eigen::end(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::makeCompressed(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Here is the call graph for this function:

◆ prune() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::prune	(	const Scalar &	reference,
		const RealScalar &	epsilon = `NumTraits<RealScalar>::dummy_precision()`
	)

inline

Suppresses all nonzeros which are much smaller than reference under the tolerence epsilon

    {
      prune(default_prunning_func(reference,epsilon));
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::prune().

Referenced by igl::min_quad_with_fixed_precompute(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::prune(), and igl::straighten_seams().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ pruned()

template<typename Derived >

const SparseView< Derived > Eigen::SparseMatrixBase< Derived >::pruned	(	const Scalar &	reference = `Scalar(0)`,
		const RealScalar &	epsilon = `NumTraits<Scalar>::dummy_precision()`
	)		const

inlineinherited

Returns: an expression of *this with values smaller than reference * epsilon removed.

This method is typically used in conjunction with the product of two sparse matrices to automatically prune the smallest values as follows:

C = (A*B).pruned();             // suppress numerical zeros (exact)
C = (A*B).pruned(ref);
C = (A*B).pruned(ref,epsilon);

where ref is a meaningful non zero reference value.

{
  return SparseView<Derived>(derived(), reference, epsilon);
}

◆ reserve() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

template<class SizesType >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserve	(	const SizesType &	reserveSizes,
		const typename SizesType::value_type &	enableif = `typename SizesType::value_type()`
	)

inline

    {
      EIGEN_UNUSED_VARIABLE(enableif);
      reserveInnerVectors(reserveSizes);
    }

References EIGEN_UNUSED_VARIABLE, and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserveInnerVectors().

Here is the call graph for this function:

◆ reserve() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserve ( Index reserveSize )

inline

Preallocates reserveSize non zeros.

Precondition: the matrix must be in compressed mode.

    {
      eigen_assert(isCompressed() && "This function does not make sense in non compressed mode.");
      m_data.reserve(reserveSize);
    }

References eigen_assert, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::isCompressed(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::reserve().

Referenced by igl::adjacency_matrix(), igl::arap_linear_block_elements(), igl::arap_linear_block_spokes(), igl::arap_linear_block_spokes_and_rims(), igl::cat(), igl::random_points_on_mesh(), igl::repdiag(), igl::repmat(), Eigen::internal::permutation_matrix_product< ExpressionType, Side, Transposed, SparseShape >::run(), Eigen::internal::set_from_triplets(), and igl::speye().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ reserveInnerVectors()

template<typename _Scalar , int _Options, typename _StorageIndex >

template<class SizesType >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserveInnerVectors ( const SizesType & reserveSizes )

inlineprotected

    {
      if(isCompressed())
      {
        Index totalReserveSize = 0;
        // turn the matrix into non-compressed mode
        m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
        if (!m_innerNonZeros) internal::throw_std_bad_alloc();
        
        // temporarily use m_innerSizes to hold the new starting points.
        StorageIndex* newOuterIndex = m_innerNonZeros;
        
        StorageIndex count = 0;
        for(Index j=0; j<m_outerSize; ++j)
        {
          newOuterIndex[j] = count;
          count += reserveSizes[j] + (m_outerIndex[j+1]-m_outerIndex[j]);
          totalReserveSize += reserveSizes[j];
        }
        m_data.reserve(totalReserveSize);
        StorageIndex previousOuterIndex = m_outerIndex[m_outerSize];
        for(Index j=m_outerSize-1; j>=0; --j)
        {
          StorageIndex innerNNZ = previousOuterIndex - m_outerIndex[j];
          for(Index i=innerNNZ-1; i>=0; --i)
          {
            m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
            m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
          }
          previousOuterIndex = m_outerIndex[j];
          m_outerIndex[j] = newOuterIndex[j];
          m_innerNonZeros[j] = innerNNZ;
        }
        m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1];
        
        m_data.resize(m_outerIndex[m_outerSize]);
      }
      else
      {
        StorageIndex* newOuterIndex = static_cast<StorageIndex*>(std::malloc((m_outerSize+1)*sizeof(StorageIndex)));
        if (!newOuterIndex) internal::throw_std_bad_alloc();
        
        StorageIndex count = 0;
        for(Index j=0; j<m_outerSize; ++j)
        {
          newOuterIndex[j] = count;
          StorageIndex alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j];
          StorageIndex toReserve = std::max<StorageIndex>(reserveSizes[j], alreadyReserved);
          count += toReserve + m_innerNonZeros[j];
        }
        newOuterIndex[m_outerSize] = count;
        
        m_data.resize(count);
        for(Index j=m_outerSize-1; j>=0; --j)
        {
          Index offset = newOuterIndex[j] - m_outerIndex[j];
          if(offset>0)
          {
            StorageIndex innerNNZ = m_innerNonZeros[j];
            for(Index i=innerNNZ-1; i>=0; --i)
            {
              m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
              m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
            }
          }
        }
        
        std::swap(m_outerIndex, newOuterIndex);
        std::free(newOuterIndex);
      }
      
    }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::index(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::isCompressed(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::reserve(), Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), Eigen::internal::throw_std_bad_alloc(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::value().

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::reserve().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ resize()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize	(	Index	rows,
		Index	cols
	)

inline

Resizes the matrix to a rows x cols matrix and initializes it to zero.

This function does not free the currently allocated memory. To release as much as memory as possible, call

mat.data().squeeze();

after resizing it.

See also: reserve(), setZero()

    {
      const Index outerSize = IsRowMajor ? rows : cols;
      m_innerSize = IsRowMajor ? cols : rows;
      m_data.clear();
      if (m_outerSize != outerSize || m_outerSize==0)
      {
        std::free(m_outerIndex);
        m_outerIndex = static_cast<StorageIndex*>(std::malloc((outerSize + 1) * sizeof(StorageIndex)));
        if (!m_outerIndex) internal::throw_std_bad_alloc();
        
        m_outerSize = outerSize;
      }
      if(m_innerNonZeros)
      {
        std::free(m_innerNonZeros);
        m_innerNonZeros = 0;
      }
      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex));
    }

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), igl::adjacency_matrix(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::analyzePattern(), igl::arap_linear_block_elements(), igl::arap_linear_block_spokes(), igl::arap_linear_block_spokes_and_rims(), igl::PlanarizerShapeUp< DerivedV, DerivedF >::assembleSelector(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize(), igl::crouzeix_raviart_massmatrix(), igl::xml::serialization_xml::deserialize(), igl::serialization::deserialize(), igl::matlab::MatlabWorkspace::find(), Eigen::PardisoLLT< MatrixType, _UpLo >::getMatrix(), Eigen::PardisoLDLT< MatrixType, Options >::getMatrix(), Eigen::PastixLLT< _MatrixType, _UpLo >::grabMatrix(), Eigen::PastixLDLT< _MatrixType, _UpLo >::grabMatrix(), grad_tet(), grad_tri(), igl::group_sum_matrix(), igl::in_element(), igl::lbs_matrix_column(), igl::lbs_matrix_column(), igl::loop(), igl::normal_derivative(), Eigen::SimplicialCholeskyBase< Derived >::ordering(), Eigen::internal::permute_symm_to_symm(), igl::project_isometrically_to_plane(), igl::random_points_on_mesh(), igl::remesh_along_isoline(), igl::repdiag(), igl::repmat(), Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run(), igl::slice_tets(), igl::upsample(), and igl::vector_area_matrix().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ resizeNonZeros()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resizeNonZeros ( Index size )

inline

    {
      m_data.resize(size);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), and Eigen::SparseMatrixBase< Derived >::size().

Referenced by Eigen::internal::minimum_degree_ordering(), Eigen::internal::permute_symm_to_symm(), and Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ rows()

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows ( ) const

inline

Returns: the number of rows of the matrix

136{ return IsRowMajor ? m_outerSize : m_innerSize; }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::IsRowMajor, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerSize, and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize.

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::SparseMatrix(), Eigen::SimplicialCholeskyBase< Derived >::_solve_impl(), igl::active_set(), Eigen::PastixBase< Derived >::analyzePattern(), Eigen::SimplicialCholeskyBase< Derived >::analyzePattern_preordered(), igl::arap_dof_precomputation(), igl::arap_dof_recomputation(), igl::arap_rhs(), igl::AtA_cached_precompute(), igl::bfs(), igl::biharmonic_coordinates(), igl::slim::build_linear_system(), igl::cat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeff(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::coeffRef(), igl::components(), Eigen::PastixBase< Derived >::compute(), Eigen::SPQR< _MatrixType >::compute(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize(), igl::eigs(), Eigen::PastixBase< Derived >::factorize(), Eigen::SimplicialCholeskyBase< Derived >::factorize_preordered(), igl::find_zero(), igl::harmonic(), igl::harmonic(), igl::harwell_boeing(), igl::matlab_format(), igl::max(), igl::min(), igl::min_quad_with_fixed_precompute(), igl::matlab::mlsetmatrix(), igl::mosek::mosek_linprog(), igl::mosek::mosek_quadprog(), igl::matlab::prepare_lhs_double(), igl::redux(), igl::repdiag(), igl::repmat(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::rows(), Eigen::IncompleteLUT< _Scalar, _StorageIndex >::rows(), Eigen::SimplicialCholeskyBase< Derived >::rows(), Eigen::SparseLU< _MatrixType, _OrderingType >::rows(), Eigen::SparseQR< _MatrixType, _OrderingType >::rows(), Eigen::SuperLUBase< _MatrixType, Derived >::rows(), Eigen::internal::Assignment< DstXprType, SrcXprType, Functor, Diagonal2Sparse >::run(), igl::matlab::MatlabWorkspace::save(), igl::serialization::serialize(), igl::xml::serialization_xml::serialize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::setIdentity(), and igl::shapeup_solve().

◆ selfadjointView() [1/4]

template<typename Derived >

template<unsigned int UpLo>

SelfAdjointViewReturnType< UpLo >::Type Eigen::SparseMatrixBase< Derived >::selfadjointView ( )

inlineinherited

◆ selfadjointView() [2/4]

template<typename Derived >

template<unsigned int UpLo>

SparseMatrixBase< Derived >::template SelfAdjointViewReturnType< UpLo >::Type Eigen::SparseMatrixBase< Derived >::selfadjointView ( )

inherited

{
  return SparseSelfAdjointView<Derived, UpLo>(derived());
}

References Eigen::EigenBase< SparseSelfAdjointView< MatrixType, _Mode > >::derived().

Here is the call graph for this function:

◆ selfadjointView() [3/4]

template<typename Derived >

template<unsigned int UpLo>

ConstSelfAdjointViewReturnType< UpLo >::Type Eigen::SparseMatrixBase< Derived >::selfadjointView ( ) const

inlineinherited

◆ selfadjointView() [4/4]

template<typename Derived >

template<unsigned int UpLo>

SparseMatrixBase< Derived >::template ConstSelfAdjointViewReturnType< UpLo >::Type Eigen::SparseMatrixBase< Derived >::selfadjointView ( ) const

inherited

{
  return SparseSelfAdjointView<const Derived, UpLo>(derived());
}

References Eigen::EigenBase< SparseSelfAdjointView< MatrixType, _Mode > >::derived().

Here is the call graph for this function:

◆ setFromTriplets() [1/2]

template<typename Scalar , int _Options, typename _StorageIndex >

template<typename InputIterators >

void Eigen::SparseMatrix< Scalar, _Options, _StorageIndex >::setFromTriplets	(	const InputIterators &	begin,
		const InputIterators &	end
	)

Fill the matrix *this with the list of triplets defined by the iterator range begin - end.

A triplet is a tuple (i,j,value) defining a non-zero element. The input list of triplets does not have to be sorted, and can contains duplicated elements. In any case, the result is a sorted and compressed sparse matrix where the duplicates have been summed up. This is a O(n) operation, with n the number of triplet elements. The initial contents of *this is destroyed. The matrix *this must be properly resized beforehand using the SparseMatrix(Index,Index) constructor, or the resize(Index,Index) method. The sizes are not extracted from the triplet list.

The InputIterators value_type must provide the following interface:

Scalar value() const; // the value
Scalar row() const;   // the row index i
Scalar col() const;   // the column index j

See for instance the Eigen::Triplet template class.

Here is a typical usage example:

typedef Triplet<double> T;
std::vector<T> tripletList;
triplets.reserve(estimation_of_entries);
for(...)
{
  // ...
  tripletList.push_back(T(i,j,v_ij));
}
SparseMatrixType m(rows,cols);
m.setFromTriplets(tripletList.begin(), tripletList.end());
// m is ready to go!

Warning: The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather be explicitely stored into a std::vector for instance.

{
  internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex> >(begin, end, *this, internal::scalar_sum_op<Scalar,Scalar>());
}

Referenced by igl::adjacency_matrix(), igl::arap_linear_block_elements(), igl::arap_linear_block_spokes(), igl::arap_linear_block_spokes_and_rims(), igl::PlanarizerShapeUp< DerivedV, DerivedF >::assembleSelector(), igl::biharmonic_coordinates(), igl::slim::build_linear_system(), igl::cat(), igl::crouzeix_raviart_massmatrix(), igl::xml::serialization_xml::deserialize(), igl::serialization::deserialize(), igl::Frame_field_deformer::extractBlock(), igl::matlab::MatlabWorkspace::find(), grad_tet(), grad_tri(), igl::in_element(), igl::copyleft::comiso::FrameInterpolator::interpolateSymmetric(), igl::loop(), igl::normal_derivative(), igl::orientable_patches(), igl::copyleft::comiso::NRosyField::prepareSystemMatrix(), igl::project_isometrically_to_plane(), igl::random_points_on_mesh(), igl::remesh_along_isoline(), igl::repdiag(), igl::shapeup_precomputation(), igl::slice_tets(), igl::upsample(), and igl::vector_area_matrix().

Here is the caller graph for this function:

◆ setFromTriplets() [2/2]

template<typename Scalar , int _Options, typename _StorageIndex >

template<typename InputIterators , typename DupFunctor >

void Eigen::SparseMatrix< Scalar, _Options, _StorageIndex >::setFromTriplets	(	const InputIterators &	begin,
		const InputIterators &	end,
		DupFunctor	dup_func
	)

The same as setFromTriplets but when duplicates are met the functor dup_func is applied:

value = dup_func(OldValue, NewValue)

Here is a C++11 example keeping the latest entry only:

mat.setFromTriplets(triplets.begin(), triplets.end(), [] (const Scalar&,const Scalar &b) { return b; });

{
  internal::set_from_triplets<InputIterators, SparseMatrix<Scalar,_Options,_StorageIndex>, DupFunctor>(begin, end, *this, dup_func);
}

◆ setIdentity()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::setIdentity ( )

inline

Sets *this to the identity matrix. This function also turns the matrix into compressed mode, and drop any reserved memory.

    {
      eigen_assert(rows() == cols() && "ONLY FOR SQUARED MATRICES");
      this->m_data.resize(rows());
      Eigen::Map<IndexVector>(this->m_data.indexPtr(), rows()).setLinSpaced(0, StorageIndex(rows()-1));
      Eigen::Map<ScalarVector>(this->m_data.valuePtr(), rows()).setOnes();
      Eigen::Map<IndexVector>(this->m_outerIndex, rows()+1).setLinSpaced(0, StorageIndex(rows()));
      std::free(m_innerNonZeros);
      m_innerNonZeros = 0;
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols(), eigen_assert, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::indexPtr(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::resize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows(), and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::valuePtr().

Referenced by igl::slim::build_linear_system(), and igl::min_quad_with_fixed_precompute().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ setZero()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::setZero ( )

inline

Removes all non zeros but keep allocated memory

This function does not free the currently allocated memory. To release as much as memory as possible, call

mat.data().squeeze();

after resizing it.

See also: resize(Index,Index), data()

    {
      m_data.clear();
      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(StorageIndex));
      if(m_innerNonZeros)
        memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(StorageIndex));
    }

References Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::clear(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize.

Referenced by igl::xml::serialization_xml::deserialize(), and igl::serialization::deserialize().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ size()

template<typename Derived >

Index Eigen::SparseMatrixBase< Derived >::size ( ) const

inlineinherited

Returns: the number of coefficients, which is rows()*cols().

See also: rows(), cols().

176{ return rows() * cols(); }

References Eigen::SparseMatrixBase< Derived >::cols(), and Eigen::SparseMatrixBase< Derived >::rows().

Referenced by igl::active_set(), igl::cat(), igl::diag(), Eigen::SparseMatrixBase< Derived >::dot(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::finalize(), igl::invert_diag(), igl::min_quad_with_fixed_precompute(), Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::operator=(), Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::operator=(), and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resizeNonZeros().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ squaredNorm()

template<typename Derived >

NumTraits< typenameinternal::traits< Derived >::Scalar >::Real Eigen::SparseMatrixBase< Derived >::squaredNorm

inlineinherited

{
  return numext::real((*this).cwiseAbs2().sum());
}

◆ startVec()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::startVec ( Index outer )

inline

    {
      eigen_assert(m_outerIndex[outer]==Index(m_data.size()) && "You must call startVec for each inner vector sequentially");
      eigen_assert(m_outerIndex[outer+1]==0 && "You must call startVec for each inner vector sequentially");
      m_outerIndex[outer+1] = m_outerIndex[outer];
    }

References eigen_assert, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::size().

Here is the call graph for this function:

◆ subTo()

template<typename Derived >

template<typename Dest >

EIGEN_DEVICE_FUNC void Eigen::EigenBase< Derived >::subTo ( Dest & dst ) const

inlineinherited

  {
    // This is the default implementation,
    // derived class can reimplement it in a more optimized way.
    typename Dest::PlainObject res(rows(),cols());
    evalTo(res);
    dst -= res;
  }

References Eigen::EigenBase< Derived >::cols(), Eigen::EigenBase< Derived >::evalTo(), and Eigen::EigenBase< Derived >::rows().

Here is the call graph for this function:

◆ sum()

template<typename _Scalar , int _Options, typename _Index >

internal::traits< SparseMatrix< _Scalar, _Options, _Index > >::Scalar Eigen::SparseMatrix< _Scalar, _Options, _Index >::sum

Overloaded for performance

{
  eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
  if(this->isCompressed())
    return Matrix<Scalar,1,Dynamic>::Map(m_data.valuePtr(), m_data.size()).sum();
  else
    return Base::sum();
}

References Eigen::PlainObjectBase< Matrix< _Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols > >::Eigen::Map, and eigen_assert.

◆ sumupDuplicates()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::sumupDuplicates ( )

inline

448{ collapseDuplicates(internal::scalar_sum_op<Scalar,Scalar>()); }

Eigen::SparseMatrix::collapseDuplicates

void collapseDuplicates(DupFunctor dup_func=DupFunctor())

Definition SparseMatrix.h:1017

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::collapseDuplicates().

Here is the call graph for this function:

◆ swap()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::swap ( SparseMatrix< _Scalar, _Options, _StorageIndex > & other )

inline

Swaps the content of two sparse matrices of the same type. This is a fast operation that simply swaps the underlying pointers and parameters.

    {
      //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
      std::swap(m_outerIndex, other.m_outerIndex);
      std::swap(m_innerSize, other.m_innerSize);
      std::swap(m_outerSize, other.m_outerSize);
      std::swap(m_innerNonZeros, other.m_innerNonZeros);
      m_data.swap(other.m_data);
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerSize, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::swap().

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::operator=().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ toDense()

template<typename Derived >

DenseMatrixType Eigen::SparseMatrixBase< Derived >::toDense ( ) const

inlineinherited

    {
      return DenseMatrixType(derived());
    }

References Eigen::SparseMatrixBase< Derived >::derived().

Referenced by Eigen::SparseMatrixBase< Derived >::isApprox().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ transpose() [1/2]

template<typename Derived >

TransposeReturnType Eigen::SparseMatrixBase< Derived >::transpose ( )

inlineinherited

349{ return TransposeReturnType(derived()); }

Eigen::SparseMatrixBase::TransposeReturnType

Transpose< Derived > TransposeReturnType

Definition SparseMatrixBase.h:110

References Eigen::SparseMatrixBase< Derived >::derived().

Referenced by Eigen::SparseMatrixBase< Derived >::adjoint(), Eigen::IncompleteLUT< _Scalar, _StorageIndex >::analyzePattern(), igl::arap_dof_precomputation(), igl::AtA_cached_precompute(), igl::slim::build_linear_system(), igl::copyleft::comiso::PoissonSolver< DerivedV, DerivedF >::BuildLaplacianMatrix(), Eigen::PastixLU< _MatrixType, IsStrSym >::grabMatrix(), igl::hessian(), igl::hessian_energy(), igl::min_quad_with_fixed_precompute(), igl::mosek::mosek_quadprog(), igl::orientable_patches(), igl::shapeup_precomputation(), and igl::straighten_seams().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ transpose() [2/2]

template<typename Derived >

const ConstTransposeReturnType Eigen::SparseMatrixBase< Derived >::transpose ( ) const

inlineinherited

350{ return ConstTransposeReturnType(derived()); }

Eigen::SparseMatrixBase::ConstTransposeReturnType

internal::add_const< Transpose< constDerived > >::type ConstTransposeReturnType

Definition SparseMatrixBase.h:111

References Eigen::SparseMatrixBase< Derived >::derived().

Here is the call graph for this function:

◆ triangularView()

template<typename Derived >

template<int Mode>

const TriangularView< const Derived, Mode > Eigen::SparseMatrixBase< Derived >::triangularView

inlineinherited

{
  return TriangularView<const Derived, Mode>(derived());
}

Referenced by igl::mosek::mosek_quadprog().

Here is the caller graph for this function:

◆ twistedBy()

template<typename Derived >

SparseSymmetricPermutationProduct< Derived, Upper|Lower > Eigen::SparseMatrixBase< Derived >::twistedBy ( const PermutationMatrix< Dynamic, Dynamic, StorageIndex > & perm ) const

inlineinherited

Returns: an expression of P H P^-1 where H is the matrix represented by *this

    {
      return SparseSymmetricPermutationProduct<Derived,Upper|Lower>(derived(), perm);
    }

References Eigen::SparseMatrixBase< Derived >::derived().

Referenced by Eigen::IncompleteLUT< _Scalar, _StorageIndex >::factorize(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize(), Eigen::PardisoLLT< MatrixType, _UpLo >::getMatrix(), and Eigen::PardisoLDLT< MatrixType, Options >::getMatrix().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ uncompress()

template<typename _Scalar , int _Options, typename _StorageIndex >

void Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::uncompress ( )

inline

Turns the matrix into the uncompressed mode

    {
      if(m_innerNonZeros != 0)
        return; 
      m_innerNonZeros = static_cast<StorageIndex*>(std::malloc(m_outerSize * sizeof(StorageIndex)));
      for (Index i = 0; i < m_outerSize; i++)
      {
        m_innerNonZeros[i] = m_outerIndex[i+1] - m_outerIndex[i]; 
      }
    }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros, Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex, and Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize.

◆ valuePtr() [1/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

Scalar * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::valuePtr ( )

inline

Returns: a non-const pointer to the array of values. This function is aimed at interoperability with other libraries.

See also: innerIndexPtr(), outerIndexPtr()

152{ return m_data.valuePtr(); }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::valuePtr().

Here is the call graph for this function:

◆ valuePtr() [2/2]

template<typename _Scalar , int _Options, typename _StorageIndex >

const Scalar * Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::valuePtr ( ) const

inline

Returns: a const pointer to the array of values. This function is aimed at interoperability with other libraries.

See also: innerIndexPtr(), outerIndexPtr()

148{ return m_data.valuePtr(); }

References Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data, and Eigen::internal::CompressedStorage< _Scalar, _StorageIndex >::valuePtr().

Referenced by Eigen::PastixBase< Derived >::analyzePattern(), igl::AtA_cached(), Eigen::PastixBase< Derived >::factorize(), Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize(), Eigen::internal::permute_symm_to_symm(), and igl::slice_cached_precompute().

Here is the call graph for this function:

Here is the caller graph for this function:

Friends And Related Symbol Documentation

◆ operator<<

template<typename _Scalar , int _Options, typename _StorageIndex >

std::ostream & operator<<	(	std::ostream &	s,
		const SparseMatrix< _Scalar, _Options, _StorageIndex > &	m
	)

friend

    {
      EIGEN_DBG_SPARSE(
        s << "Nonzero entries:\n";
        if(m.isCompressed())
        {
          for (Index i=0; i<m.nonZeros(); ++i)
            s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
        }
        else
        {
          for (Index i=0; i<m.outerSize(); ++i)
          {
            Index p = m.m_outerIndex[i];
            Index pe = m.m_outerIndex[i]+m.m_innerNonZeros[i];
            Index k=p;
            for (; k<pe; ++k) {
              s << "(" << m.m_data.value(k) << "," << m.m_data.index(k) << ") ";
            }
            for (; k<m.m_outerIndex[i+1]; ++k) {
              s << "(_,_) ";
            }
          }
        }
        s << std::endl;
        s << std::endl;
        s << "Outer pointers:\n";
        for (Index i=0; i<m.outerSize(); ++i) {
          s << m.m_outerIndex[i] << " ";
        }
        s << " $" << std::endl;
        if(!m.isCompressed())
        {
          s << "Inner non zeros:\n";
          for (Index i=0; i<m.outerSize(); ++i) {
            s << m.m_innerNonZeros[i] << " ";
          }
          s << " $" << std::endl;
        }
        s << std::endl;
      );
      s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m);
      return s;
    }

◆ SparseVector< _Scalar, 0, _StorageIndex >

template<typename _Scalar , int _Options, typename _StorageIndex >

friend class SparseVector< _Scalar, 0, _StorageIndex >

friend

Member Data Documentation

◆ m_data

template<typename _Scalar , int _Options, typename _StorageIndex >

Storage Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_data

protected

◆ m_innerNonZeros

template<typename _Scalar , int _Options, typename _StorageIndex >

StorageIndex* Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerNonZeros

protected

◆ m_innerSize

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_innerSize

protected

Referenced by Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::cols(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::conservativeResize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::innerSize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::resize(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::rows(), Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::swap(), and Eigen::SparseVector< _Scalar, _Options, _StorageIndex >::swap().

◆ m_isRValue

template<typename Derived >

bool Eigen::SparseMatrixBase< Derived >::m_isRValue

protectedinherited

Referenced by Eigen::SparseMatrixBase< Derived >::isRValue(), and Eigen::SparseMatrixBase< Derived >::markAsRValue().

◆ m_outerIndex

template<typename _Scalar , int _Options, typename _StorageIndex >

StorageIndex* Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerIndex

protected

◆ m_outerSize

template<typename _Scalar , int _Options, typename _StorageIndex >

Index Eigen::SparseMatrix< _Scalar, _Options, _StorageIndex >::m_outerSize

protected

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

src/eigen/Eigen/src/SparseCore/SparseMatrix.h
src/eigen/Eigen/src/SparseCore/SparseRedux.h

Classes

Public Types

Public Member Functions

Protected Types

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Private Types

Private Member Functions

Static Private Member Functions

Friends

Detailed Description

Member Typedef Documentation

◆ AdjointReturnType

◆ Base

◆ CoeffReturnType

◆ ConstantReturnType

◆ ConstDiagonalReturnType

◆ ConstInnerVectorReturnType

◆ ConstInnerVectorsReturnType

◆ ConstTransposeReturnType

◆ DenseMatrixType

◆ DiagonalReturnType

◆ Index

◆ IndexVector

◆ InnerIterator

◆ InnerVectorReturnType

◆ InnerVectorsReturnType

◆ Map

◆ PacketReturnType

◆ PacketScalar

◆ PlainObject

◆ RealScalar

◆ ReverseInnerIterator

◆ Scalar

◆ ScalarVector

◆ SquareMatrixType

◆ Storage

◆ StorageBaseType

◆ StorageIndex

◆ StorageKind

◆ TransposedSparseMatrix

◆ TransposeReturnType

◆ value_type

Member Enumeration Documentation

◆ anonymous enum

◆ anonymous enum

Constructor & Destructor Documentation

◆ SparseMatrix() [1/7]

◆ SparseMatrix() [2/7]

◆ SparseMatrix() [3/7]

◆ SparseMatrix() [4/7]

◆ SparseMatrix() [5/7]

◆ SparseMatrix() [6/7]

◆ SparseMatrix() [7/7]

◆ ~SparseMatrix()

Member Function Documentation

◆ addTo()

◆ adjoint()

◆ applyThisOnTheLeft()

◆ applyThisOnTheRight()

◆ assign()

◆ assignGeneric()

◆ blueNorm()

◆ check_template_parameters()

◆ coeff()

◆ coeffRef()

◆ coeffs() [1/2]

◆ coeffs() [2/2]

◆ collapseDuplicates()

◆ cols()

◆ conservativeResize()

◆ const_cast_derived()

◆ const_derived()

◆ convert_index()

◆ cwiseProduct() [1/2]

◆ cwiseProduct() [2/2]

◆ data() [1/2]

◆ data() [2/2]

◆ derived() [1/2]