Eigen Namespace Reference

Namespace containing all symbols from the Eigen library. More...

Namespaces
namespace	indexing
	The sole purpose of this namespace is to be able to import all functions and symbols that are expected to be used within operator() for indexing and slicing.
namespace	symbolic
	This namespace defines a set of classes and functions to build and evaluate symbolic expressions of scalar type Index.

Data Structures
class	aligned_allocator
	STL compatible allocator to use with types requiring a non standrad alignment. More...
class	aligned_allocator_indirection
class	AlignedBox
	\geometry_module More...
class	AMDOrdering
	Functor computing the approximate minimum degree ordering If the matrix is not structurally symmetric, an ordering of A^T+A is computed. More...
class	AngleAxis
	\geometry_module More...
class	ArithmeticSequence
	This class represents an arithmetic progression defined by its first value , its size (aka length) n, and the increment (aka stride) that is equal to for any i. More...
class	Array
	General-purpose arrays with easy API for coefficient-wise operations. More...
class	ArrayBase
	Base class for all 1D and 2D array, and related expressions. More...
class	ArrayWrapper
	Expression of a mathematical vector or matrix as an array object. More...
struct	ArrayXpr
	The type used to identify an array expression. More...
struct	BandShape
class	BDCSVD
	class Bidiagonal Divide and Conquer SVD More...
struct	bfloat16
class	BiCGSTAB
	A bi conjugate gradient stabilized solver for sparse square problems. More...
class	Block
	Expression of a fixed-size or dynamic-size block. More...
class	BlockImpl
class	BlockImpl< const SparseMatrix< _Scalar, _Options, _StorageIndex >, BlockRows, BlockCols, true, Sparse >
class	BlockImpl< SparseMatrix< _Scalar, _Options, _StorageIndex >, BlockRows, BlockCols, true, Sparse >
class	BlockImpl< XprType, BlockRows, BlockCols, InnerPanel, Dense >
class	BlockImpl< XprType, BlockRows, BlockCols, InnerPanel, Sparse >
	Generic implementation of sparse Block expression. More...
class	BlockImpl< XprType, BlockRows, BlockCols, true, Sparse >
class	CholmodBase
	The base class for the direct Cholesky factorization of Cholmod. More...
class	CholmodDecomposition
	A general Cholesky factorization and solver based on Cholmod. More...
class	CholmodSimplicialLDLT
	A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod. More...
class	CholmodSimplicialLLT
	A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod. More...
class	CholmodSupernodalLLT
	A supernodal Cholesky (LLT) factorization and solver based on Cholmod. More...
class	COLAMDOrdering
class	ColPivHouseholderQR
	Householder rank-revealing QR decomposition of a matrix with column-pivoting. More...
class	CommaInitializer
	Helper class used by the comma initializer operator. More...
class	CompleteOrthogonalDecomposition
	Complete orthogonal decomposition (COD) of a matrix. More...
class	ComplexEigenSolver
	\eigenvalues_module More...
class	ComplexSchur
	\eigenvalues_module More...
class	Conjugate
class	ConjugateGradient
	A conjugate gradient solver for sparse (or dense) self-adjoint problems. More...
class	Cross
class	CwiseBinaryOp
	Generic expression where a coefficient-wise binary operator is applied to two expressions. More...
class	CwiseBinaryOpImpl
class	CwiseBinaryOpImpl< BinaryOp, Lhs, Rhs, Sparse >
class	CwiseNullaryOp
	Generic expression of a matrix where all coefficients are defined by a functor. More...
class	CwiseTernaryOp
	Generic expression where a coefficient-wise ternary operator is applied to two expressions. More...
class	CwiseTernaryOpImpl
class	CwiseUnaryOp
	Generic expression where a coefficient-wise unary operator is applied to an expression. More...
class	CwiseUnaryOpImpl
class	CwiseUnaryView
	Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector. More...
class	CwiseUnaryViewImpl
class	CwiseUnaryViewImpl< ViewOp, MatrixType, Dense >
struct	Dense
	The type used to identify a dense storage. More...
class	DenseBase
	Base class for all dense matrices, vectors, and arrays. More...
class	DenseCoeffsBase
class	DenseCoeffsBase< Derived, DirectAccessors >
	Base class providing direct read-only coefficient access to matrices and arrays. More...
class	DenseCoeffsBase< Derived, DirectWriteAccessors >
	Base class providing direct read/write coefficient access to matrices and arrays. More...
class	DenseCoeffsBase< Derived, ReadOnlyAccessors >
	Base class providing read-only coefficient access to matrices and arrays. More...
class	DenseCoeffsBase< Derived, WriteAccessors >
	Base class providing read/write coefficient access to matrices and arrays. More...
struct	DenseShape
struct	DenseSparseProductReturnType
class	DenseStorage
class	DenseStorage< T, 0, _Rows, _Cols, _Options >
class	DenseStorage< T, 0, _Rows, Dynamic, _Options >
class	DenseStorage< T, 0, Dynamic, _Cols, _Options >
class	DenseStorage< T, 0, Dynamic, Dynamic, _Options >
class	DenseStorage< T, Dynamic, _Rows, Dynamic, _Options >
class	DenseStorage< T, Dynamic, Dynamic, _Cols, _Options >
class	DenseStorage< T, Dynamic, Dynamic, Dynamic, _Options >
class	DenseStorage< T, Size, _Rows, Dynamic, _Options >
class	DenseStorage< T, Size, Dynamic, _Cols, _Options >
class	DenseStorage< T, Size, Dynamic, Dynamic, _Options >
class	DenseTimeSparseProduct
class	Diagonal
	Expression of a diagonal/subdiagonal/superdiagonal in a matrix. More...
class	DiagonalBase
class	DiagonalMatrix
	Represents a diagonal matrix with its storage. More...
class	DiagonalPreconditioner
	A preconditioner based on the digonal entries. More...
class	DiagonalProduct
struct	DiagonalShape
class	DiagonalWrapper
	Expression of a diagonal matrix. More...
class	DynamicSparseMatrix
class	EigenBase
	Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T). More...
class	EigenSolver
	\eigenvalues_module More...
class	Flagged
class	ForceAlignedAccess
	Enforce aligned packet loads and stores regardless of what is requested. More...
class	FullPivHouseholderQR
	Householder rank-revealing QR decomposition of a matrix with full pivoting. More...
class	FullPivLU
	LU decomposition of a matrix with complete pivoting, and related features. More...
struct	general_product_to_triangular_selector
struct	general_product_to_triangular_selector< MatrixType, ProductType, UpLo, false >
struct	general_product_to_triangular_selector< MatrixType, ProductType, UpLo, true >
class	GeneralizedEigenSolver
	\eigenvalues_module More...
class	GeneralizedSelfAdjointEigenSolver
	\eigenvalues_module More...
struct	GenericNumTraits
struct	half
class	HessenbergDecomposition
	\eigenvalues_module More...
class	Homogeneous
	\geometry_module More...
struct	HomogeneousShape
class	HouseholderQR
	Householder QR decomposition of a matrix. More...
class	HouseholderSequence
	\householder_module More...
class	Hyperplane
	\geometry_module More...
class	IdentityPreconditioner
	A naive preconditioner which approximates any matrix as the identity matrix. More...
class	IncompleteCholesky
	Modified Incomplete Cholesky with dual threshold. More...
class	IncompleteLUT
	Incomplete LU factorization with dual-threshold strategy. More...
class	IndexedView
	Expression of a non-sequential sub-matrix defined by arbitrary sequences of row and column indices. More...
class	IndexedViewImpl
class	InnerIterator
	An InnerIterator allows to loop over the element of any matrix expression. More...
class	InnerStride
	Convenience specialization of Stride to specify only an inner stride See class Map for some examples. More...
class	Inverse
	Expression of the inverse of another expression. More...
class	InverseImpl
class	InverseImpl< PermutationType, PermutationStorage >
class	IOFormat
	Stores a set of parameters controlling the way matrices are printed. More...
class	IterativeSolverBase
	Base class for linear iterative solvers. More...
class	JacobiRotation
	\jacobi_module More...
class	JacobiSVD
	Two-sided Jacobi SVD decomposition of a rectangular matrix. More...
class	KLU
struct	LazyProductReturnType
class	LDLT
	Robust Cholesky decomposition of a matrix with pivoting. More...
class	LeastSquareDiagonalPreconditioner
	Jacobi preconditioner for LeastSquaresConjugateGradient. More...
class	LeastSquaresConjugateGradient
	A conjugate gradient solver for sparse (or dense) least-square problems. More...
class	LLT
	Standard Cholesky decomposition (LL^T) of a matrix and associated features. More...
class	Map
	A matrix or vector expression mapping an existing array of data. More...
class	Map< const Quaternion< _Scalar >, _Options >
	Quaternion expression mapping a constant memory buffer. More...
class	Map< const SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >
class	Map< PermutationMatrix< SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex >, _PacketAccess >
class	Map< Quaternion< _Scalar >, _Options >
	Expression of a quaternion from a memory buffer. More...
class	Map< SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >
	Specialization of class Map for SparseMatrix-like storage. More...
class	Map< Transpositions< SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex >, PacketAccess >
class	MapBase
class	MapBase< Derived, ReadOnlyAccessors >
	Base class for dense Map and Block expression with direct access. More...
class	MapBase< Derived, WriteAccessors >
	Base class for non-const dense Map and Block expression with direct access. More...
class	MappedSparseMatrix
	Sparse matrix. More...
class	Matrix
	The matrix class, also used for vectors and row-vectors. More...
class	MatrixBase
	Base class for all dense matrices, vectors, and expressions. More...
class	MatrixComplexPowerReturnValue
struct	MatrixExponentialReturnValue
class	MatrixFunctionReturnValue
class	MatrixLogarithmReturnValue
class	MatrixPowerReturnValue
class	MatrixSquareRootReturnValue
class	MatrixWrapper
	Expression of an array as a mathematical vector or matrix. More...
struct	MatrixXpr
	The type used to identify a matrix expression. More...
class	MetisOrdering
	Get the fill-reducing ordering from the METIS package. More...
class	NaturalOrdering
	Functor computing the natural ordering (identity) More...
class	NestByValue
	Expression which must be nested by value. More...
class	NoAlias
	Pseudo expression providing an operator = assuming no aliasing. More...
class	NumTraits
	Holds information about the various numeric (i.e. More...
struct	NumTraits< Array< Scalar, Rows, Cols, Options, MaxRows, MaxCols > >
struct	NumTraits< bool >
struct	NumTraits< double >
struct	NumTraits< Eigen::bfloat16 >
struct	NumTraits< Eigen::half >
struct	NumTraits< float >
struct	NumTraits< long double >
struct	NumTraits< std::complex< _Real > >
struct	NumTraits< std::string >
struct	NumTraits< void >
class	OuterStride
	Convenience specialization of Stride to specify only an outer stride See class Map for some examples. More...
class	ParametrizedLine
	\geometry_module More...
class	PardisoImpl
class	PardisoLDLT
	A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library. More...
class	PardisoLLT
	A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library. More...
class	PardisoLU
	A sparse direct LU factorization and solver based on the PARDISO library. More...
struct	partial_redux_dummy_func
class	PartialPivLU
	LU decomposition of a matrix with partial pivoting, and related features. More...
class	PartialReduxExpr
	Generic expression of a partially reduxed matrix. More...
class	PastixBase
class	PastixLDLT
	A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library. More...
class	PastixLLT
	A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library. More...
class	PastixLU
	Interface to the PaStix solver. More...
class	PermutationBase
	Base class for permutations. More...
class	PermutationMatrix
	Permutation matrix. More...
struct	PermutationShape
struct	PermutationStorage
	The type used to identify a permutation storage. More...
class	PermutationWrapper
	Class to view a vector of integers as a permutation matrix. More...
class	PlainObjectBase
class	Product
	Expression of the product of two arbitrary matrices or vectors. More...
class	ProductImpl
class	ProductImpl< Lhs, Rhs, Option, Dense >
struct	ProductReturnType
class	Quaternion
	\geometry_module More...
class	QuaternionBase
	\geometry_module More...
class	RealQZ
	\eigenvalues_module More...
class	RealSchur
	\eigenvalues_module More...
class	Ref
	A matrix or vector expression mapping an existing expression. More...
class	Ref< const SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >
class	Ref< const SparseVector< MatScalar, MatOptions, MatIndex >, Options, StrideType >
class	Ref< const TPlainObjectType, Options, StrideType >
class	Ref< SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >
	A sparse matrix expression referencing an existing sparse expression. More...
class	Ref< SparseVector< MatScalar, MatOptions, MatIndex >, Options, StrideType >
	A sparse vector expression referencing an existing sparse vector expression. More...
class	RefBase
class	Replicate
	Expression of the multiple replication of a matrix or vector. More...
class	Reshaped
	Expression of a fixed-size or dynamic-size reshape. More...
class	ReshapedImpl
class	ReshapedImpl< XprType, Rows, Cols, Order, Dense >
class	ReturnByValue
class	Reverse
	Expression of the reverse of a vector or matrix. More...
class	Rotation2D
	\geometry_module More...
class	RotationBase
	Common base class for compact rotation representations. More...
class	ScalarBinaryOpTraits
	Determines whether the given binary operation of two numeric types is allowed and what the scalar return type is. More...
struct	ScalarBinaryOpTraits< T, T, BinaryOp >
struct	ScalarBinaryOpTraits< T, typename NumTraits< typename internal::enable_if< NumTraits< T >::IsComplex, T >::type >::Real, BinaryOp >
struct	ScalarBinaryOpTraits< T, void, BinaryOp >
struct	ScalarBinaryOpTraits< typename NumTraits< typename internal::enable_if< NumTraits< T >::IsComplex, T >::type >::Real, T, BinaryOp >
struct	ScalarBinaryOpTraits< void, T, BinaryOp >
struct	ScalarBinaryOpTraits< void, void, BinaryOp >
class	Select
	Expression of a coefficient wise version of the C++ ternary operator ?: More...
struct	selfadjoint_product_selector
struct	selfadjoint_product_selector< MatrixType, OtherType, UpLo, false >
struct	selfadjoint_product_selector< MatrixType, OtherType, UpLo, true >
struct	selfadjoint_rank1_update
struct	selfadjoint_rank1_update< Scalar, Index, ColMajor, UpLo, ConjLhs, ConjRhs >
struct	selfadjoint_rank1_update< Scalar, Index, RowMajor, UpLo, ConjLhs, ConjRhs >
class	SelfAdjointEigenSolver
	\eigenvalues_module More...
struct	SelfAdjointShape
class	SelfAdjointView
	Expression of a selfadjoint matrix from a triangular part of a dense matrix. More...
class	SimplicialCholesky
class	SimplicialCholeskyBase
	A base class for direct sparse Cholesky factorizations. More...
class	SimplicialLDLT
	A direct sparse LDLT Cholesky factorizations without square root. More...
class	SimplicialLLT
	A direct sparse LLT Cholesky factorizations. More...
struct	SluMatrix
struct	SluMatrixMapHelper
struct	SluMatrixMapHelper< Matrix< Scalar, Rows, Cols, Options, MRows, MCols > >
struct	SluMatrixMapHelper< SparseMatrixBase< Derived > >
class	Solve
	Pseudo expression representing a solving operation. More...
class	SolveImpl
class	SolveImpl< Decomposition, RhsType, Dense >
class	SolverBase
	A base class for matrix decomposition and solvers. More...
struct	SolverShape
struct	SolverStorage
	The type used to identify a general solver (factored) storage. More...
class	SolveWithGuess
	Pseudo expression representing a solving operation. More...
struct	Sparse
	The type used to identify a general sparse storage. More...
class	SparseCompressedBase
	Common base class for sparse [compressed]-{row|column}-storage format. More...
class	SparseDenseOuterProduct
struct	SparseDenseProductReturnType
class	SparseDiagonalProduct
class	SparseLU
	Sparse supernodal LU factorization for general matrices. More...
struct	SparseLUMatrixLReturnType
struct	SparseLUMatrixUReturnType
class	SparseLUTransposeView
class	SparseMapBase
class	SparseMapBase< Derived, ReadOnlyAccessors >
	class SparseMapBase More...
class	SparseMapBase< Derived, WriteAccessors >
	class SparseMapBase More...
class	SparseMatrix
	A versatible sparse matrix representation. More...
class	SparseMatrixBase
	Base class of any sparse matrices or sparse expressions. More...
class	SparseQR
	Sparse left-looking QR factorization with numerical column pivoting. More...
struct	SparseQR_QProduct
struct	SparseQRMatrixQReturnType
struct	SparseQRMatrixQTransposeReturnType
class	SparseSelfAdjointView
	Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. More...
struct	SparseShape
class	SparseSolverBase
	A base class for sparse solvers. More...
class	SparseSparseProduct
struct	SparseSparseProductReturnType
class	SparseSymmetricPermutationProduct
class	SparseTimeDenseProduct
class	SparseVector
	a sparse vector class More...
class	SparseView
	Expression of a dense or sparse matrix with zero or too small values removed. More...
class	SPQR
	Sparse QR factorization based on SuiteSparseQR library. More...
struct	SPQR_QProduct
struct	SPQRMatrixQReturnType
struct	SPQRMatrixQTransposeReturnType
class	Stride
	Holds strides information for Map. More...
class	SuperLU
	A sparse direct LU factorization and solver based on the SuperLU library. More...
class	SuperLUBase
	The base class for the direct and incomplete LU factorization of SuperLU. More...
class	SVDBase
	Base class of SVD algorithms. More...
class	SwapWrapper
class	Transform
	\geometry_module More...
class	Translation
	\geometry_module More...
class	Transpose
	Expression of the transpose of a matrix. More...
class	Transpose< TranspositionsBase< TranspositionsDerived > >
class	TransposeImpl
class	TransposeImpl< MatrixType, Dense >
class	TransposeImpl< MatrixType, Sparse >
class	Transpositions
	Represents a sequence of transpositions (row/column interchange) More...
class	TranspositionsBase
struct	TranspositionsShape
struct	TranspositionsStorage
	The type used to identify a permutation storage. More...
class	TranspositionsWrapper
class	TriangularBase
	Base class for triangular part in a matrix. More...
struct	TriangularShape
class	TriangularView
	Expression of a triangular part in a matrix. More...
class	TriangularViewImpl
class	TriangularViewImpl< _MatrixType, _Mode, Dense >
	Base class for a triangular part in a dense matrix. More...
class	TriangularViewImpl< MatrixType, Mode, Sparse >
	Base class for a triangular part in a sparse matrix. More...
class	Tridiagonalization
	\eigenvalues_module More...
class	Triplet
	A small structure to hold a non zero as a triplet (i,j,value). More...
class	UmfPackLU
	A sparse LU factorization and solver based on UmfPack. More...
class	UniformScaling
	\geometry_module More...
class	VectorBlock
	Expression of a fixed-size or dynamic-size sub-vector. More...
class	VectorwiseOp
	Pseudo expression providing broadcasting and partial reduction operations. More...
class	WithFormat
	Pseudo expression providing matrix output with given format. More...

Typedefs
typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE	DenseIndex
typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE	Index
	The Index type as used for the API.
typedef std::complex< double >	dcomplex
typedef std::complex< float >	scomplex
typedef int	BlasIndex
typedef AngleAxis< float >	AngleAxisf
	single precision angle-axis type
typedef AngleAxis< double >	AngleAxisd
	double precision angle-axis type
typedef Quaternion< float >	Quaternionf
	single precision quaternion type
typedef Quaternion< double >	Quaterniond
	double precision quaternion type
typedef Map< Quaternion< float >, 0 >	QuaternionMapf
	Map an unaligned array of single precision scalars as a quaternion.
typedef Map< Quaternion< double >, 0 >	QuaternionMapd
	Map an unaligned array of double precision scalars as a quaternion.
typedef Map< Quaternion< float >, Aligned >	QuaternionMapAlignedf
	Map a 16-byte aligned array of single precision scalars as a quaternion.
typedef Map< Quaternion< double >, Aligned >	QuaternionMapAlignedd
	Map a 16-byte aligned array of double precision scalars as a quaternion.
typedef Rotation2D< float >	Rotation2Df
	single precision 2D rotation type
typedef Rotation2D< double >	Rotation2Dd
	double precision 2D rotation type
typedef DiagonalMatrix< float, 2 >	AlignedScaling2f
typedef DiagonalMatrix< double, 2 >	AlignedScaling2d
typedef DiagonalMatrix< float, 3 >	AlignedScaling3f
typedef DiagonalMatrix< double, 3 >	AlignedScaling3d
typedef Transform< float, 2, Isometry >	Isometry2f
typedef Transform< float, 3, Isometry >	Isometry3f
typedef Transform< double, 2, Isometry >	Isometry2d
typedef Transform< double, 3, Isometry >	Isometry3d
typedef Transform< float, 2, Affine >	Affine2f
typedef Transform< float, 3, Affine >	Affine3f
typedef Transform< double, 2, Affine >	Affine2d
typedef Transform< double, 3, Affine >	Affine3d
typedef Transform< float, 2, AffineCompact >	AffineCompact2f
typedef Transform< float, 3, AffineCompact >	AffineCompact3f
typedef Transform< double, 2, AffineCompact >	AffineCompact2d
typedef Transform< double, 3, AffineCompact >	AffineCompact3d
typedef Transform< float, 2, Projective >	Projective2f
typedef Transform< float, 3, Projective >	Projective3f
typedef Transform< double, 2, Projective >	Projective2d
typedef Transform< double, 3, Projective >	Projective3d
typedef Translation< float, 2 >	Translation2f
typedef Translation< double, 2 >	Translation2d
typedef Translation< float, 3 >	Translation3f
typedef Translation< double, 3 >	Translation3d

Enumerations
enum	CholmodMode { CholmodAuto , CholmodSimplicialLLt , CholmodSupernodalLLt , CholmodLDLt }
enum	{ Large = 2 , Small = 3 }
enum	{ DontAlignCols = 1 }
enum	{ StreamPrecision = -1 , FullPrecision = -2 }
enum	UpLoType {   Lower =0x1 , Upper =0x2 , UnitDiag =0x4 , ZeroDiag =0x8 ,   UnitLower =UnitDiag|Lower , UnitUpper =UnitDiag|Upper , StrictlyLower =ZeroDiag|Lower , StrictlyUpper =ZeroDiag|Upper ,   SelfAdjoint =0x10 , Symmetric =0x20 }
	Enum containing possible values for the Mode or UpLo parameter of MatrixBase::selfadjointView() and MatrixBase::triangularView(), and selfadjoint solvers. More...
enum	AlignmentType {   Unaligned =0 , Aligned8 =8 , Aligned16 =16 , Aligned32 =32 ,   Aligned64 =64 , Aligned128 =128 , AlignedMask =255 , Aligned =16 ,   AlignedMax = Unaligned }
	Enum for indicating whether a buffer is aligned or not. More...
enum	DirectionType { Vertical , Horizontal , BothDirections }
	Enum containing possible values for the Direction parameter of Reverse, PartialReduxExpr and VectorwiseOp. More...
enum	TraversalType {   DefaultTraversal , LinearTraversal , InnerVectorizedTraversal , LinearVectorizedTraversal ,   SliceVectorizedTraversal , InvalidTraversal , AllAtOnceTraversal }
enum	UnrollingType { NoUnrolling , InnerUnrolling , CompleteUnrolling }
enum	SpecializedType { Specialized , BuiltIn }
enum	StorageOptions { ColMajor = 0 , RowMajor = 0x1 , AutoAlign = 0 , DontAlign = 0x2 }
	Enum containing possible values for the _Options template parameter of Matrix, Array and BandMatrix. More...
enum	SideType { OnTheLeft = 1 , OnTheRight = 2 }
	Enum for specifying whether to apply or solve on the left or right. More...
enum	NaNPropagationOptions { PropagateFast = 0 , PropagateNaN , PropagateNumbers }
	Enum for specifying NaN-propagation behavior, e.g. More...
enum	NoChange_t { NoChange }
enum	Sequential_t { Sequential }
enum	Default_t { Default }
enum	AmbiVectorMode { IsDense = 0 , IsSparse }
enum	AccessorLevels { ReadOnlyAccessors , WriteAccessors , DirectAccessors , DirectWriteAccessors }
	Used as template parameter in DenseCoeffBase and MapBase to indicate which accessors should be provided. More...
enum	DecompositionOptions {   Pivoting = 0x01 , NoPivoting = 0x02 , ComputeFullU = 0x04 , ComputeThinU = 0x08 ,   ComputeFullV = 0x10 , ComputeThinV = 0x20 , EigenvaluesOnly = 0x40 , ComputeEigenvectors = 0x80 ,   EigVecMask = EigenvaluesOnly | ComputeEigenvectors , Ax_lBx = 0x100 , ABx_lx = 0x200 , BAx_lx = 0x400 ,   GenEigMask = Ax_lBx | ABx_lx | BAx_lx }
	Enum with options to give to various decompositions. More...
enum	QRPreconditioners { NoQRPreconditioner , HouseholderQRPreconditioner , ColPivHouseholderQRPreconditioner , FullPivHouseholderQRPreconditioner }
	Possible values for the QRPreconditioner template parameter of JacobiSVD. More...
enum	ComputationInfo { Success = 0 , NumericalIssue = 1 , NoConvergence = 2 , InvalidInput = 3 }
	Enum for reporting the status of a computation. More...
enum	TransformTraits { Isometry = 0x1 , Affine = 0x2 , AffineCompact = 0x10 | Affine , Projective = 0x20 }
	Enum used to specify how a particular transformation is stored in a matrix. More...
enum	ProductImplType {   DefaultProduct =0 , LazyProduct , AliasFreeProduct , CoeffBasedProductMode ,   LazyCoeffBasedProductMode , OuterProduct , InnerProduct , GemvProduct ,   GemmProduct }
enum	Action { GetAction , SetAction }
enum	AutoSize_t { AutoSize }
enum	SimplicialCholeskyMode { SimplicialCholeskyLLT , SimplicialCholeskyLDLT }
enum	{ StandardCompressedFormat = 2 }

Functions
template<typename _Scalar , int _Options, typename _StorageIndex >
cholmod_sparse	viewAsCholmod (Ref< SparseMatrix< _Scalar, _Options, _StorageIndex > > mat)
	Wraps the Eigen sparse matrix mat into a Cholmod sparse matrix object.
template<typename _Scalar , int _Options, typename _Index >
const cholmod_sparse	viewAsCholmod (const SparseMatrix< _Scalar, _Options, _Index > &mat)
template<typename _Scalar , int _Options, typename _Index >
const cholmod_sparse	viewAsCholmod (const SparseVector< _Scalar, _Options, _Index > &mat)
template<typename _Scalar , int _Options, typename _Index , unsigned int UpLo>
cholmod_sparse	viewAsCholmod (const SparseSelfAdjointView< const SparseMatrix< _Scalar, _Options, _Index >, UpLo > &mat)
	Returns a view of the Eigen sparse matrix mat as Cholmod sparse matrix.
template<typename Derived >
cholmod_dense	viewAsCholmod (MatrixBase< Derived > &mat)
	Returns a view of the Eigen dense matrix mat as Cholmod dense matrix.
template<typename Scalar , int Flags, typename StorageIndex >
MappedSparseMatrix< Scalar, Flags, StorageIndex >	viewAsEigen (cholmod_sparse &cm)
	Returns a view of the Cholmod sparse matrix cm as an Eigen sparse matrix.
template<typename FirstType , typename SizeType , typename IncrType >
ArithmeticSequence< typename internal::cleanup_index_type< FirstType >::type, typename internal::cleanup_index_type< SizeType >::type, typename internal::cleanup_seq_incr< IncrType >::type >	seqN (FirstType first, SizeType size, IncrType incr)
template<typename FirstType , typename SizeType >
ArithmeticSequence< typename internal::cleanup_index_type< FirstType >::type, typename internal::cleanup_index_type< SizeType >::type >	seqN (FirstType first, SizeType size)
template<typename FirstType , typename LastType >
internal::enable_if<!(symbolic::is_symbolic< FirstType >::value||symbolic::is_symbolic< LastType >::value), ArithmeticSequence< typenameinternal::cleanup_index_type< FirstType >::type, Index > >::type	seq (FirstType f, LastType l)
template<typename FirstTypeDerived , typename LastType >
internal::enable_if<!symbolic::is_symbolic< LastType >::value, ArithmeticSequence< FirstTypeDerived, symbolic::AddExpr< symbolic::AddExpr< symbolic::NegateExpr< FirstTypeDerived >, symbolic::ValueExpr<> >, symbolic::ValueExpr< internal::FixedInt< 1 > > > > >::type	seq (const symbolic::BaseExpr< FirstTypeDerived > &f, LastType l)
template<typename FirstType , typename LastTypeDerived >
internal::enable_if<!symbolic::is_symbolic< FirstType >::value, ArithmeticSequence< typenameinternal::cleanup_index_type< FirstType >::type, symbolic::AddExpr< symbolic::AddExpr< LastTypeDerived, symbolic::ValueExpr<> >, symbolic::ValueExpr< internal::FixedInt< 1 > > > > >::type	seq (FirstType f, const symbolic::BaseExpr< LastTypeDerived > &l)
template<typename FirstTypeDerived , typename LastTypeDerived >
ArithmeticSequence< FirstTypeDerived, symbolic::AddExpr< symbolic::AddExpr< LastTypeDerived, symbolic::NegateExpr< FirstTypeDerived > >, symbolic::ValueExpr< internal::FixedInt< 1 > > > >	seq (const symbolic::BaseExpr< FirstTypeDerived > &f, const symbolic::BaseExpr< LastTypeDerived > &l)
template<typename FirstType , typename LastType , typename IncrType >
internal::enable_if<!(symbolic::is_symbolic< FirstType >::value||symbolic::is_symbolic< LastType >::value), ArithmeticSequence< typenameinternal::cleanup_index_type< FirstType >::type, Index, typenameinternal::cleanup_seq_incr< IncrType >::type > >::type	seq (FirstType f, LastType l, IncrType incr)
template<typename FirstTypeDerived , typename LastType , typename IncrType >
internal::enable_if<!symbolic::is_symbolic< LastType >::value, ArithmeticSequence< FirstTypeDerived, symbolic::QuotientExpr< symbolic::AddExpr< symbolic::AddExpr< symbolic::NegateExpr< FirstTypeDerived >, symbolic::ValueExpr<> >, symbolic::ValueExpr< typenameinternal::cleanup_seq_incr< IncrType >::type > >, symbolic::ValueExpr< typenameinternal::cleanup_seq_incr< IncrType >::type > >, typenameinternal::cleanup_seq_incr< IncrType >::type > >::type	seq (const symbolic::BaseExpr< FirstTypeDerived > &f, LastType l, IncrType incr)
template<typename FirstType , typename LastTypeDerived , typename IncrType >
internal::enable_if<!symbolic::is_symbolic< FirstType >::value, ArithmeticSequence< typenameinternal::cleanup_index_type< FirstType >::type, symbolic::QuotientExpr< symbolic::AddExpr< symbolic::AddExpr< LastTypeDerived, symbolic::ValueExpr<> >, symbolic::ValueExpr< typenameinternal::cleanup_seq_incr< IncrType >::type > >, symbolic::ValueExpr< typenameinternal::cleanup_seq_incr< IncrType >::type > >, typenameinternal::cleanup_seq_incr< IncrType >::type > >::type	seq (FirstType f, const symbolic::BaseExpr< LastTypeDerived > &l, IncrType incr)
template<typename FirstTypeDerived , typename LastTypeDerived , typename IncrType >
ArithmeticSequence< FirstTypeDerived, symbolic::QuotientExpr< symbolic::AddExpr< symbolic::AddExpr< LastTypeDerived, symbolic::NegateExpr< FirstTypeDerived > >, symbolic::ValueExpr< typename internal::cleanup_seq_incr< IncrType >::type > >, symbolic::ValueExpr< typename internal::cleanup_seq_incr< IncrType >::type > >, typename internal::cleanup_seq_incr< IncrType >::type >	seq (const symbolic::BaseExpr< FirstTypeDerived > &f, const symbolic::BaseExpr< LastTypeDerived > &l, IncrType incr)
template<typename MatrixDerived , typename PermutationDerived >
EIGEN_DEVICE_FUNC const Product< MatrixDerived, PermutationDerived, AliasFreeProduct >	operator* (const MatrixBase< MatrixDerived > &matrix, const PermutationBase< PermutationDerived > &permutation)
template<typename PermutationDerived , typename MatrixDerived >
EIGEN_DEVICE_FUNC const Product< PermutationDerived, MatrixDerived, AliasFreeProduct >	operator* (const PermutationBase< PermutationDerived > &permutation, const MatrixBase< MatrixDerived > &matrix)
std::ptrdiff_t	l1CacheSize ()
std::ptrdiff_t	l2CacheSize ()
std::ptrdiff_t	l3CacheSize ()
void	setCpuCacheSizes (std::ptrdiff_t l1, std::ptrdiff_t l2, std::ptrdiff_t l3)
	Set the cpu L1 and L2 cache sizes (in bytes).
void	initParallel ()
	Must be call first when calling Eigen from multiple threads.
int	nbThreads ()
void	setNbThreads (int v)
	Sets the max number of threads reserved for Eigen.
template<typename MatrixDerived , typename TranspositionsDerived >
EIGEN_DEVICE_FUNC const Product< MatrixDerived, TranspositionsDerived, AliasFreeProduct >	operator* (const MatrixBase< MatrixDerived > &matrix, const TranspositionsBase< TranspositionsDerived > &transpositions)
template<typename TranspositionsDerived , typename MatrixDerived >
EIGEN_DEVICE_FUNC const Product< TranspositionsDerived, MatrixDerived, AliasFreeProduct >	operator* (const TranspositionsBase< TranspositionsDerived > &transpositions, const MatrixBase< MatrixDerived > &matrix)
template<int N>
internal::FixedInt< N >	fix ()
template<int N, typename T >
internal::VariableAndFixedInt< N >	fix (T val)
UniformScaling< float >	Scaling (float s)
	Constructs a uniform scaling from scale factor s.
UniformScaling< double >	Scaling (double s)
	Constructs a uniform scaling from scale factor s.
template<typename RealScalar >
UniformScaling< std::complex< RealScalar > >	Scaling (const std::complex< RealScalar > &s)
	Constructs a uniform scaling from scale factor s.
template<typename Scalar >
DiagonalMatrix< Scalar, 2 >	Scaling (const Scalar &sx, const Scalar &sy)
	Constructs a 2D axis aligned scaling.
template<typename Scalar >
DiagonalMatrix< Scalar, 3 >	Scaling (const Scalar &sx, const Scalar &sy, const Scalar &sz)
	Constructs a 3D axis aligned scaling.
template<typename Derived >
const DiagonalWrapper< const Derived >	Scaling (const MatrixBase< Derived > &coeffs)
	Constructs an axis aligned scaling expression from vector expression coeffs This is an alias for coeffs.asDiagonal()
template<typename Derived , typename OtherDerived >
internal::umeyama_transform_matrix_type< Derived, OtherDerived >::type	umeyama (const MatrixBase< Derived > &src, const MatrixBase< OtherDerived > &dst, bool with_scaling=true)
	\geometry_module
template<typename OtherDerived , typename VectorsType , typename CoeffsType , int Side>
internal::matrix_type_times_scalar_type< typenameVectorsType::Scalar, OtherDerived >::Type	operator* (const MatrixBase< OtherDerived > &other, const HouseholderSequence< VectorsType, CoeffsType, Side > &h)
	Computes the product of a matrix with a Householder sequence.
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType >	householderSequence (const VectorsType &v, const CoeffsType &h)
	\householder_module
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType, OnTheRight >	rightHouseholderSequence (const VectorsType &v, const CoeffsType &h)
	\householder_module
int	klu_solve (klu_symbolic *Symbolic, klu_numeric *Numeric, Index ldim, Index nrhs, double B[], klu_common *Common, double)
	A sparse LU factorization and solver based on KLU.
int	klu_solve (klu_symbolic *Symbolic, klu_numeric *Numeric, Index ldim, Index nrhs, std::complex< double >B[], klu_common *Common, std::complex< double >)
int	klu_tsolve (klu_symbolic *Symbolic, klu_numeric *Numeric, Index ldim, Index nrhs, double B[], klu_common *Common, double)
int	klu_tsolve (klu_symbolic *Symbolic, klu_numeric *Numeric, Index ldim, Index nrhs, std::complex< double >B[], klu_common *Common, std::complex< double >)
klu_numeric *	klu_factor (int Ap[], int Ai[], double Ax[], klu_symbolic *Symbolic, klu_common *Common, double)
klu_numeric *	klu_factor (int Ap[], int Ai[], std::complex< double > Ax[], klu_symbolic *Symbolic, klu_common *Common, std::complex< double >)
template<typename DenseDerived , typename SparseDerived >
EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_sum_op< typename DenseDerived::Scalar, typename SparseDerived::Scalar >, const DenseDerived, const SparseDerived >	operator+ (const MatrixBase< DenseDerived > &a, const SparseMatrixBase< SparseDerived > &b)
template<typename SparseDerived , typename DenseDerived >
EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_sum_op< typename SparseDerived::Scalar, typename DenseDerived::Scalar >, const SparseDerived, const DenseDerived >	operator+ (const SparseMatrixBase< SparseDerived > &a, const MatrixBase< DenseDerived > &b)
template<typename DenseDerived , typename SparseDerived >
EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_difference_op< typename DenseDerived::Scalar, typename SparseDerived::Scalar >, const DenseDerived, const SparseDerived >	operator- (const MatrixBase< DenseDerived > &a, const SparseMatrixBase< SparseDerived > &b)
template<typename SparseDerived , typename DenseDerived >
EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_difference_op< typename SparseDerived::Scalar, typename DenseDerived::Scalar >, const SparseDerived, const DenseDerived >	operator- (const SparseMatrixBase< SparseDerived > &a, const MatrixBase< DenseDerived > &b)
template<typename SparseDerived , typename PermDerived >
const Product< SparseDerived, PermDerived, AliasFreeProduct >	operator* (const SparseMatrixBase< SparseDerived > &matrix, const PermutationBase< PermDerived > &perm)
template<typename SparseDerived , typename PermDerived >
const Product< PermDerived, SparseDerived, AliasFreeProduct >	operator* (const PermutationBase< PermDerived > &perm, const SparseMatrixBase< SparseDerived > &matrix)
template<typename SparseDerived , typename PermutationType >
const Product< SparseDerived, Inverse< PermutationType >, AliasFreeProduct >	operator* (const SparseMatrixBase< SparseDerived > &matrix, const InverseImpl< PermutationType, PermutationStorage > &tperm)
template<typename SparseDerived , typename PermutationType >
const Product< Inverse< PermutationType >, SparseDerived, AliasFreeProduct >	operator* (const InverseImpl< PermutationType, PermutationStorage > &tperm, const SparseMatrixBase< SparseDerived > &matrix)
void	umfpack_defaults (double control[UMFPACK_CONTROL], double, int)
void	umfpack_defaults (double control[UMFPACK_CONTROL], std::complex< double >, int)
void	umfpack_defaults (double control[UMFPACK_CONTROL], double, SuiteSparse_long)
void	umfpack_defaults (double control[UMFPACK_CONTROL], std::complex< double >, SuiteSparse_long)
void	umfpack_report_info (double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], double, int)
void	umfpack_report_info (double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], std::complex< double >, int)
void	umfpack_report_info (double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], double, SuiteSparse_long)
void	umfpack_report_info (double control[UMFPACK_CONTROL], double info[UMFPACK_INFO], std::complex< double >, SuiteSparse_long)
void	umfpack_report_status (double control[UMFPACK_CONTROL], int status, double, int)
void	umfpack_report_status (double control[UMFPACK_CONTROL], int status, std::complex< double >, int)
void	umfpack_report_status (double control[UMFPACK_CONTROL], int status, double, SuiteSparse_long)
void	umfpack_report_status (double control[UMFPACK_CONTROL], int status, std::complex< double >, SuiteSparse_long)
void	umfpack_report_control (double control[UMFPACK_CONTROL], double, int)
void	umfpack_report_control (double control[UMFPACK_CONTROL], std::complex< double >, int)
void	umfpack_report_control (double control[UMFPACK_CONTROL], double, SuiteSparse_long)
void	umfpack_report_control (double control[UMFPACK_CONTROL], std::complex< double >, SuiteSparse_long)
void	umfpack_free_numeric (void **Numeric, double, int)
void	umfpack_free_numeric (void **Numeric, std::complex< double >, int)
void	umfpack_free_numeric (void **Numeric, double, SuiteSparse_long)
void	umfpack_free_numeric (void **Numeric, std::complex< double >, SuiteSparse_long)
void	umfpack_free_symbolic (void **Symbolic, double, int)
void	umfpack_free_symbolic (void **Symbolic, std::complex< double >, int)
void	umfpack_free_symbolic (void **Symbolic, double, SuiteSparse_long)
void	umfpack_free_symbolic (void **Symbolic, std::complex< double >, SuiteSparse_long)
int	umfpack_symbolic (int n_row, int n_col, const int Ap[], const int Ai[], const double Ax[], void **Symbolic, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_symbolic (int n_row, int n_col, const int Ap[], const int Ai[], const std::complex< double > Ax[], void **Symbolic, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_symbolic (SuiteSparse_long n_row, SuiteSparse_long n_col, const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const double Ax[], void **Symbolic, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_symbolic (SuiteSparse_long n_row, SuiteSparse_long n_col, const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const std::complex< double > Ax[], void **Symbolic, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_numeric (const int Ap[], const int Ai[], const double Ax[], void *Symbolic, void **Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_numeric (const int Ap[], const int Ai[], const std::complex< double > Ax[], void *Symbolic, void **Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_numeric (const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const double Ax[], void *Symbolic, void **Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_numeric (const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const std::complex< double > Ax[], void *Symbolic, void **Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_solve (int sys, const int Ap[], const int Ai[], const double Ax[], double X[], const double B[], void *Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_solve (int sys, const int Ap[], const int Ai[], const std::complex< double > Ax[], std::complex< double > X[], const std::complex< double > B[], void *Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_solve (int sys, const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const double Ax[], double X[], const double B[], void *Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
SuiteSparse_long	umfpack_solve (int sys, const SuiteSparse_long Ap[], const SuiteSparse_long Ai[], const std::complex< double > Ax[], std::complex< double > X[], const std::complex< double > B[], void *Numeric, const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
int	umfpack_get_lunz (int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double)
int	umfpack_get_lunz (int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex< double >)
SuiteSparse_long	umfpack_get_lunz (SuiteSparse_long *lnz, SuiteSparse_long *unz, SuiteSparse_long *n_row, SuiteSparse_long *n_col, SuiteSparse_long *nz_udiag, void *Numeric, double)
SuiteSparse_long	umfpack_get_lunz (SuiteSparse_long *lnz, SuiteSparse_long *unz, SuiteSparse_long *n_row, SuiteSparse_long *n_col, SuiteSparse_long *nz_udiag, void *Numeric, std::complex< double >)
int	umfpack_get_numeric (int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[], int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric)
int	umfpack_get_numeric (int Lp[], int Lj[], std::complex< double > Lx[], int Up[], int Ui[], std::complex< double > Ux[], int P[], int Q[], std::complex< double > Dx[], int *do_recip, double Rs[], void *Numeric)
SuiteSparse_long	umfpack_get_numeric (SuiteSparse_long Lp[], SuiteSparse_long Lj[], double Lx[], SuiteSparse_long Up[], SuiteSparse_long Ui[], double Ux[], SuiteSparse_long P[], SuiteSparse_long Q[], double Dx[], SuiteSparse_long *do_recip, double Rs[], void *Numeric)
SuiteSparse_long	umfpack_get_numeric (SuiteSparse_long Lp[], SuiteSparse_long Lj[], std::complex< double > Lx[], SuiteSparse_long Up[], SuiteSparse_long Ui[], std::complex< double > Ux[], SuiteSparse_long P[], SuiteSparse_long Q[], std::complex< double > Dx[], SuiteSparse_long *do_recip, double Rs[], void *Numeric)
int	umfpack_get_determinant (double *Mx, double *Ex, void *NumericHandle, double User_Info[UMFPACK_INFO], int)
int	umfpack_get_determinant (std::complex< double > *Mx, double *Ex, void *NumericHandle, double User_Info[UMFPACK_INFO], int)
SuiteSparse_long	umfpack_get_determinant (double *Mx, double *Ex, void *NumericHandle, double User_Info[UMFPACK_INFO], SuiteSparse_long)
SuiteSparse_long	umfpack_get_determinant (std::complex< double > *Mx, double *Ex, void *NumericHandle, double User_Info[UMFPACK_INFO], SuiteSparse_long)

Variables
EIGEN_DEVICE_FUNC const Eigen::ArrayBase< Derived > &	exponents
const int	Dynamic = -1
	This value means that a positive quantity (e.g., a size) is not known at compile-time, and that instead the value is stored in some runtime variable.
const int	DynamicIndex = 0xffffff
	This value means that a signed quantity (e.g., a signed index) is not known at compile-time, and that instead its value has to be specified at runtime.
const int	UndefinedIncr = 0xfffffe
	This value means that the increment to go from one value to another in a sequence is not constant for each step.
const int	Infinity = -1
	This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>().
const int	HugeCost = 10000
	This value means that the cost to evaluate an expression coefficient is either very expensive or cannot be known at compile time.
const unsigned int	RowMajorBit = 0x1
	for a matrix, this means that the storage order is row-major.
const unsigned int	EvalBeforeNestingBit = 0x2
	means the expression should be evaluated by the calling expression
EIGEN_DEPRECATED const unsigned int	EvalBeforeAssigningBit = 0x4
const unsigned int	PacketAccessBit = 0x8
	Short version: means the expression might be vectorized.
const unsigned int	ActualPacketAccessBit = 0x0
const unsigned int	LinearAccessBit = 0x10
	Short version: means the expression can be seen as 1D vector.
const unsigned int	LvalueBit = 0x20
	Means the expression has a coeffRef() method, i.e.
const unsigned int	DirectAccessBit = 0x40
	Means that the underlying array of coefficients can be directly accessed as a plain strided array.
EIGEN_DEPRECATED const unsigned int	AlignedBit = 0x80
const unsigned int	NestByRefBit = 0x100
const unsigned int	NoPreferredStorageOrderBit = 0x200
	for an expression, this means that the storage order can be either row-major or column-major.
const unsigned int	CompressedAccessBit = 0x400
	Means that the underlying coefficients can be accessed through pointers to the sparse (un)compressed storage format, that is, the expression provides:
const unsigned int	HereditaryBits
const int	AutoOrder = 2
const int	CoherentAccessPattern = 0x1
const int	InnerRandomAccessPattern = 0x2 | CoherentAccessPattern
const int	OuterRandomAccessPattern = 0x4 | CoherentAccessPattern
const int	RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern

Detailed Description

Namespace containing all symbols from the Eigen library.

Typedef Documentation

AlignedScaling2d

typedef DiagonalMatrix<double,2> Eigen::AlignedScaling2d

Deprecated:

AlignedScaling2f

typedef DiagonalMatrix<float, 2> Eigen::AlignedScaling2f

Deprecated:

AlignedScaling3d

typedef DiagonalMatrix<double,3> Eigen::AlignedScaling3d

Deprecated:

AlignedScaling3f

typedef DiagonalMatrix<float, 3> Eigen::AlignedScaling3f

Deprecated:

Index

typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Eigen::Index

The Index type as used for the API.

To change this, #define the preprocessor symbol EIGEN_DEFAULT_DENSE_INDEX_TYPE.

See also

\blank TopicPreprocessorDirectives, StorageIndex.

Enumeration Type Documentation

anonymous enum

anonymous enum

Enumerator
StandardCompressedFormat	used by Ref<SparseMatrix> to specify whether the input storage must be in standard compressed form

Function Documentation

householderSequence()

template<typename VectorsType , typename CoeffsType >

HouseholderSequence< VectorsType, CoeffsType > Eigen::householderSequence	(	const VectorsType &	v,
		const CoeffsType &	h
	)

\householder_module

Convenience function for constructing a Householder sequence.

Returns

A HouseholderSequence constructed from the specified arguments.

klu_solve()

int Eigen::klu_solve ( klu_symbolic *  Symbolic, klu_numeric *  Numeric, Index  ldim, Index  nrhs, double  B[], klu_common *  Common, double    )

inline

A sparse LU factorization and solver based on KLU.

This class allows to solve for A.X = B sparse linear problems via a LU factorization using the KLU library. The sparse matrix A must be squared and full rank. The vectors or matrices X and B can be either dense or sparse.

Warning

The input matrix A should be in a compressed and column-major form. Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.

Template Parameters

_MatrixType

the type of the sparse matrix A, it must be a SparseMatrix<>

\implsparsesolverconcept

See also

TutorialSparseSolverConcept, class UmfPackLU, class SparseLU

l1CacheSize()

std::ptrdiff_t Eigen::l1CacheSize ( )

inline

Returns

the currently set level 1 cpu cache size (in bytes) used to estimate the ideal blocking size parameters.

See also

setCpuCacheSize

l2CacheSize()

std::ptrdiff_t Eigen::l2CacheSize ( )

inline

Returns

the currently set level 2 cpu cache size (in bytes) used to estimate the ideal blocking size parameters.

See also

setCpuCacheSize

l3CacheSize()

std::ptrdiff_t Eigen::l3CacheSize ( )

inline

Returns

the currently set level 3 cpu cache size (in bytes) used to estimate the ideal blocking size paramete\ rs.

See also

setCpuCacheSize

nbThreads()

int Eigen::nbThreads ( )

inline

Returns

the max number of threads reserved for Eigen

See also

setNbThreads

operator*() [1/9]

template<typename SparseDerived , typename PermutationType >

const Product< Inverse< PermutationType >, SparseDerived, AliasFreeProduct > Eigen::operator* ( const InverseImpl< PermutationType, PermutationStorage > &  tperm, const SparseMatrixBase< SparseDerived > &  matrix  )

inline

Returns

the matrix with the inverse permutation applied to the rows.

operator*() [2/9]

template<typename MatrixDerived , typename PermutationDerived >

EIGEN_DEVICE_FUNC const Product< MatrixDerived, PermutationDerived, AliasFreeProduct > Eigen::operator*	(	const MatrixBase< MatrixDerived > &	matrix,
		const PermutationBase< PermutationDerived > &	permutation
	)

Returns

the matrix with the permutation applied to the columns.

operator*() [3/9]

template<typename MatrixDerived , typename TranspositionsDerived >

EIGEN_DEVICE_FUNC const Product< MatrixDerived, TranspositionsDerived, AliasFreeProduct > Eigen::operator*	(	const MatrixBase< MatrixDerived > &	matrix,
		const TranspositionsBase< TranspositionsDerived > &	transpositions
	)

Returns

the matrix with the transpositions applied to the columns.

operator*() [4/9]

template<typename OtherDerived , typename VectorsType , typename CoeffsType , int Side>

internal::matrix_type_times_scalar_type< typenameVectorsType::Scalar, OtherDerived >::Type Eigen::operator*	(	const MatrixBase< OtherDerived > &	other,
		const HouseholderSequence< VectorsType, CoeffsType, Side > &	h
	)

Computes the product of a matrix with a Householder sequence.

Parameters

[in]	other	Matrix being multiplied.
[in]	h	HouseholderSequence being multiplied.

Returns

Expression object representing the product.

This function computes where is the matrix other and is the Householder sequence represented by h.

operator*() [5/9]

template<typename SparseDerived , typename PermDerived >

const Product< PermDerived, SparseDerived, AliasFreeProduct > Eigen::operator* ( const PermutationBase< PermDerived > &  perm, const SparseMatrixBase< SparseDerived > &  matrix  )

inline

Returns

the matrix with the permutation applied to the rows

operator*() [6/9]

template<typename PermutationDerived , typename MatrixDerived >

EIGEN_DEVICE_FUNC const Product< PermutationDerived, MatrixDerived, AliasFreeProduct > Eigen::operator*	(	const PermutationBase< PermutationDerived > &	permutation,
		const MatrixBase< MatrixDerived > &	matrix
	)

Returns

the matrix with the permutation applied to the rows.

operator*() [7/9]

template<typename SparseDerived , typename PermutationType >

const Product< SparseDerived, Inverse< PermutationType >, AliasFreeProduct > Eigen::operator* ( const SparseMatrixBase< SparseDerived > &  matrix, const InverseImpl< PermutationType, PermutationStorage > &  tperm  )

inline

Returns

the matrix with the inverse permutation applied to the columns.

operator*() [8/9]

template<typename SparseDerived , typename PermDerived >

const Product< SparseDerived, PermDerived, AliasFreeProduct > Eigen::operator* ( const SparseMatrixBase< SparseDerived > &  matrix, const PermutationBase< PermDerived > &  perm  )

inline

Returns

the matrix with the permutation applied to the columns

operator*() [9/9]

template<typename TranspositionsDerived , typename MatrixDerived >

EIGEN_DEVICE_FUNC const Product< TranspositionsDerived, MatrixDerived, AliasFreeProduct > Eigen::operator*	(	const TranspositionsBase< TranspositionsDerived > &	transpositions,
		const MatrixBase< MatrixDerived > &	matrix
	)

Returns

the matrix with the transpositions applied to the rows.

rightHouseholderSequence()

template<typename VectorsType , typename CoeffsType >

HouseholderSequence< VectorsType, CoeffsType, OnTheRight > Eigen::rightHouseholderSequence	(	const VectorsType &	v,
		const CoeffsType &	h
	)

\householder_module

Convenience function for constructing a Householder sequence.

Returns

A HouseholderSequence constructed from the specified arguments.

This function differs from householderSequence() in that the template argument OnTheSide of the constructed HouseholderSequence is set to OnTheRight, instead of the default OnTheLeft.

seqN() [1/2]

template<typename FirstType , typename SizeType >

ArithmeticSequence< typename internal::cleanup_index_type< FirstType >::type, typename internal::cleanup_index_type< SizeType >::type > Eigen::seqN	(	FirstType	first,
		SizeType	size
	)

Returns

an ArithmeticSequence starting at first, of length size, and unit increment

See also

seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType)

seqN() [2/2]

template<typename FirstType , typename SizeType , typename IncrType >

ArithmeticSequence< typename internal::cleanup_index_type< FirstType >::type, typename internal::cleanup_index_type< SizeType >::type, typename internal::cleanup_seq_incr< IncrType >::type > Eigen::seqN	(	FirstType	first,
		SizeType	size,
		IncrType	incr
	)

Returns

an ArithmeticSequence starting at first, of length size, and increment incr

See also

seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType)

setCpuCacheSizes()

void Eigen::setCpuCacheSizes ( std::ptrdiff_t  l1, std::ptrdiff_t  l2, std::ptrdiff_t  l3  )

inline

Set the cpu L1 and L2 cache sizes (in bytes).

These values are use to adjust the size of the blocks for the algorithms working per blocks.

See also

computeProductBlockingSizes

setNbThreads()

void Eigen::setNbThreads ( int  v )

inline

Sets the max number of threads reserved for Eigen.

See also

nbThreads

viewAsCholmod() [1/3]

template<typename _Scalar , int _Options, typename _Index , unsigned int UpLo>

cholmod_sparse Eigen::viewAsCholmod

(

const SparseSelfAdjointView< const SparseMatrix< _Scalar, _Options, _Index >, UpLo > &

mat

)

Returns a view of the Eigen sparse matrix mat as Cholmod sparse matrix.

The data are not copied but shared.

viewAsCholmod() [2/3]

template<typename Derived >

cholmod_dense Eigen::viewAsCholmod

(

MatrixBase< Derived > &

mat

)

Returns a view of the Eigen dense matrix mat as Cholmod dense matrix.

The data are not copied but shared.

viewAsCholmod() [3/3]

template<typename _Scalar , int _Options, typename _StorageIndex >

cholmod_sparse Eigen::viewAsCholmod

(

Ref< SparseMatrix< _Scalar, _Options, _StorageIndex > >

mat

)

Wraps the Eigen sparse matrix mat into a Cholmod sparse matrix object.

Note that the data are shared.

viewAsEigen()

template<typename Scalar , int Flags, typename StorageIndex >

MappedSparseMatrix< Scalar, Flags, StorageIndex > Eigen::viewAsEigen

(

cholmod_sparse &

cm

)

Returns a view of the Cholmod sparse matrix cm as an Eigen sparse matrix.

The data are not copied but shared.

Variable Documentation

Dynamic

const int Eigen::Dynamic = -1

This value means that a positive quantity (e.g., a size) is not known at compile-time, and that instead the value is stored in some runtime variable.

Changing the value of Dynamic breaks the ABI, as Dynamic is often used as a template parameter for Matrix.

exponents

EIGEN_DEVICE_FUNC const Eigen::ArrayBase<Derived>& Eigen::exponents

Initial value:

{
    typedef typename internal::promote_scalar_arg<typename Derived::Scalar,Scalar,
                                                  EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar)>::type PromotedScalar

HereditaryBits

const unsigned int Eigen::HereditaryBits

Initial value:

= RowMajorBit
                                  | EvalBeforeNestingBit

HugeCost

const int Eigen::HugeCost = 10000

This value means that the cost to evaluate an expression coefficient is either very expensive or cannot be known at compile time.

This value has to be positive to (1) simplify cost computation, and (2) allow to distinguish between a very expensive and very very expensive expressions. It thus must also be large enough to make sure unrolling won't happen and that sub expressions will be evaluated, but not too large to avoid overflow.

Infinity

const int Eigen::Infinity = -1

This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>().

The value Infinity there means the L-infinity norm.