Eigen Namespace Reference

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

Namespaces
namespace	Architecture
namespace	bfloat16_impl
namespace	half_impl
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	internal
namespace	numext
namespace	placeholders
namespace	symbolic
	This namespace defines a set of classes and functions to build and evaluate symbolic expressions of scalar type Index.

Classes
class	aligned_allocator
	STL compatible allocator to use with types requiring a non standrad alignment. More...
class	aligned_allocator_indirection
class	AlignedBox
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
class	ArithmeticSequence
	This class represents an arithmetic progression \( a_0, a_1, a_2, ..., a_{n-1}\) defined by its first value \( a_0 \), its size (aka length) n, and the increment (aka stride) that is equal to \( a_{i+1}-a_{i}\) 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	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
struct	HomogeneousShape
class	HouseholderQR
	Householder QR decomposition of a matrix. More...
class	HouseholderSequence
	\householder_module More...
class	Hyperplane
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...
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 SparseMatrix< MatScalar, MatOptions, MatIndex >, Options, StrideType >
class	Map< PermutationMatrix< SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex >, _PacketAccess >
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
	Proxy for the matrix power of some matrix (expression). More...
struct	MatrixExponentialReturnValue
	Proxy for the matrix exponential of some matrix (expression). More...
class	MatrixFunctionReturnValue
	Proxy for the matrix function of some matrix (expression). More...
class	MatrixLogarithmReturnValue
	Proxy for the matrix logarithm of some matrix (expression). More...
class	MatrixPower
	Class for computing matrix powers. More...
class	MatrixPowerAtomic
	Class for computing matrix powers. More...
class	MatrixPowerParenthesesReturnValue
	Proxy for the matrix power of some matrix. More...
class	MatrixPowerReturnValue
	Proxy for the matrix power of some matrix (expression). More...
class	MatrixSquareRootReturnValue
	Proxy for the matrix square root of some matrix (expression). More...
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	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
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	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
class	QuaternionBase
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
class	RotationBase
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...
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	Stride
	Holds strides information for Map. More...
class	SVDBase
	Base class of SVD algorithms. More...
class	SwapWrapper
class	Transform
class	Translation
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	UniformScaling
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. More...

Enumerations
enum	{ StandardCompressedFormat = 2 }
enum	AutoSize_t { AutoSize }
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	{ DontAlignCols = 1 }
enum	{ StreamPrecision = -1 , FullPrecision = -2 }
enum	{ Large = 2 , Small = 3 }
enum	SimplicialCholeskyMode { SimplicialCholeskyLLT , SimplicialCholeskyLDLT }

Functions
template<typename MatrixType , typename ResultType >
void	matrix_sqrt_quasi_triangular (const MatrixType &arg, ResultType &result)
	Compute matrix square root of quasi-triangular matrix. More...
template<typename MatrixType , typename ResultType >
void	matrix_sqrt_triangular (const MatrixType &arg, ResultType &result)
	Compute matrix square root of triangular matrix. More...
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)
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)
static const char *	SimdInstructionSetsInUse (void)
static const symbolic::AddExpr< symbolic::SymbolExpr< internal::symbolic_last_tag >, symbolic::ValueExpr< Eigen::internal::FixedInt< 1 > > >	lastp1 (last+fix< 1 >())
template<int N>
internal::FixedInt< N >	fix ()
template<int N, typename T >
internal::VariableAndFixedInt< N >	fix (T val)
void	initParallel ()
	Must be call first when calling Eigen from multiple threads. More...
int	nbThreads ()
void	setNbThreads (int v)
	Sets the max number of threads reserved for Eigen. More...
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). More...
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 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<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. More...
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType >	householderSequence (const VectorsType &v, const CoeffsType &h)
	\ More...
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType, OnTheRight >	rightHouseholderSequence (const VectorsType &v, const CoeffsType &h)
	\ More...

Variables
const int	CoherentAccessPattern = 0x1
const int	InnerRandomAccessPattern = 0x2 | CoherentAccessPattern
const int	OuterRandomAccessPattern = 0x4 | CoherentAccessPattern
const int	RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern
const int	AutoOrder = 2
static const symbolic::SymbolExpr< internal::symbolic_last_tag >	last
	Can be used as a parameter to Eigen::seq and Eigen::seqN functions to symbolically reference the last element/row/columns of the underlying vector or matrix once passed to DenseBase::operator()(const RowIndices&, const ColIndices&). More...
static const Eigen::internal::all_t	all
	Can be used as a parameter to DenseBase::operator()(const RowIndices&, const ColIndices&) to index all rows or columns. More...
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. More...
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. More...
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. More...
const int	Infinity = -1
	This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>(). More...
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. More...
const unsigned int	RowMajorBit = 0x1
	for a matrix, this means that the storage order is row-major. More...
const unsigned int	EvalBeforeNestingBit = 0x2
	means the expression should be evaluated by the calling expression More...
EIGEN_DEPRECATED const unsigned int	EvalBeforeAssigningBit = 0x4
const unsigned int	PacketAccessBit = 0x8
	Short version: means the expression might be vectorized. More...
const unsigned int	ActualPacketAccessBit = 0x0
const unsigned int	LinearAccessBit = 0x10
	Short version: means the expression can be seen as 1D vector. More...
const unsigned int	LvalueBit = 0x20
	Means the expression has a coeffRef() method, i.e. More...
const unsigned int	DirectAccessBit = 0x40
	Means that the underlying array of coefficients can be directly accessed as a plain strided array. More...
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. More...
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: More...
const unsigned int	HereditaryBits
EIGEN_DEVICE_FUNC const Eigen::ArrayBase< Derived > &	exponents

Detailed Description

Namespace containing all symbols from the Eigen library.

Typedef Documentation

DenseIndex

typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Eigen::DenseIndex

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
DontAlignCols

anonymous enum

anonymous enum

Enumerator
StreamPrecision
FullPrecision

anonymous enum

anonymous enum

Enumerator
Large
Small

anonymous enum

anonymous enum

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

Action

enum Eigen::Action

Enumerator
GetAction
SetAction

AmbiVectorMode

enum Eigen::AmbiVectorMode

Enumerator
IsDense
IsSparse

AutoSize_t

enum Eigen::AutoSize_t

Enumerator
AutoSize

Default_t

enum Eigen::Default_t

Enumerator
Default

NoChange_t

enum Eigen::NoChange_t

Enumerator
NoChange

ProductImplType

enum Eigen::ProductImplType

Enumerator
DefaultProduct
LazyProduct
AliasFreeProduct
CoeffBasedProductMode
LazyCoeffBasedProductMode
OuterProduct
InnerProduct
GemvProduct
GemmProduct

Sequential_t

enum Eigen::Sequential_t

Enumerator
Sequential

SimplicialCholeskyMode

enum Eigen::SimplicialCholeskyMode

Enumerator
SimplicialCholeskyLLT
SimplicialCholeskyLDLT

SpecializedType

enum Eigen::SpecializedType

Enumerator
Specialized
BuiltIn

TraversalType

enum Eigen::TraversalType

Enumerator
DefaultTraversal
LinearTraversal
InnerVectorizedTraversal
LinearVectorizedTraversal
SliceVectorizedTraversal
InvalidTraversal
AllAtOnceTraversal

UnrollingType

enum Eigen::UnrollingType

Enumerator
NoUnrolling
InnerUnrolling
CompleteUnrolling

Function Documentation

fix() [1/2]

template<int N>

internal::FixedInt< N > Eigen::fix ( )

inline

fix() [2/2]

template<int N, typename T >

internal::VariableAndFixedInt< N > Eigen::fix ( T  val )

inline

initParallel()

void Eigen::initParallel ( )

inline

Must be call first when calling Eigen from multiple threads.

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

lastp1()

static const symbolic::AddExpr< symbolic::SymbolExpr< internal::symbolic_last_tag >, symbolic::ValueExpr< Eigen::internal::FixedInt< 1 > > > Eigen::lastp1 ( last+fix< 1 >  () )

static

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 \( MH \) where \( M \) is the matrix other and \( H \) 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.

operator+() [1/2]

template<typename DenseDerived , typename SparseDerived >

EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_sum_op< typename DenseDerived::Scalar, typename SparseDerived::Scalar >, const DenseDerived, const SparseDerived > Eigen::operator+	(	const MatrixBase< DenseDerived > &	a,
		const SparseMatrixBase< SparseDerived > &	b
	)

operator+() [2/2]

template<typename SparseDerived , typename DenseDerived >

EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_sum_op< typename SparseDerived::Scalar, typename DenseDerived::Scalar >, const SparseDerived, const DenseDerived > Eigen::operator+	(	const SparseMatrixBase< SparseDerived > &	a,
		const MatrixBase< DenseDerived > &	b
	)

operator-() [1/2]

template<typename DenseDerived , typename SparseDerived >

EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_difference_op< typename DenseDerived::Scalar, typename SparseDerived::Scalar >, const DenseDerived, const SparseDerived > Eigen::operator-	(	const MatrixBase< DenseDerived > &	a,
		const SparseMatrixBase< SparseDerived > &	b
	)

operator-() [2/2]

template<typename SparseDerived , typename DenseDerived >

EIGEN_STRONG_INLINE const CwiseBinaryOp< internal::scalar_difference_op< typename SparseDerived::Scalar, typename DenseDerived::Scalar >, const SparseDerived, const DenseDerived > Eigen::operator-	(	const SparseMatrixBase< SparseDerived > &	a,
		const MatrixBase< DenseDerived > &	b
	)

seq() [1/8]

template<typename FirstTypeDerived , typename LastTypeDerived >

ArithmeticSequence< FirstTypeDerived, symbolic::AddExpr< symbolic::AddExpr< LastTypeDerived, symbolic::NegateExpr< FirstTypeDerived > >, symbolic::ValueExpr< internal::FixedInt< 1 > > > > Eigen::seq	(	const symbolic::BaseExpr< FirstTypeDerived > &	f,
		const symbolic::BaseExpr< LastTypeDerived > &	l
	)

seq() [2/8]

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 > Eigen::seq	(	const symbolic::BaseExpr< FirstTypeDerived > &	f,
		const symbolic::BaseExpr< LastTypeDerived > &	l,
		IncrType	incr
	)

seq() [3/8]

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 Eigen::seq	(	const symbolic::BaseExpr< FirstTypeDerived > &	f,
		LastType	l
	)

seq() [4/8]

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 Eigen::seq	(	const symbolic::BaseExpr< FirstTypeDerived > &	f,
		LastType	l,
		IncrType	incr
	)

seq() [5/8]

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 Eigen::seq	(	FirstType	f,
		const symbolic::BaseExpr< LastTypeDerived > &	l
	)

seq() [6/8]

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 Eigen::seq	(	FirstType	f,
		const symbolic::BaseExpr< LastTypeDerived > &	l,
		IncrType	incr
	)

seq() [7/8]

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 Eigen::seq	(	FirstType	f,
		LastType	l
	)

seq() [8/8]

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 Eigen::seq	(	FirstType	f,
		LastType	l,
		IncrType	incr
	)

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

SimdInstructionSetsInUse()

static const char * Eigen::SimdInstructionSetsInUse ( void  )

inlinestatic

Variable Documentation

ActualPacketAccessBit

const unsigned int Eigen::ActualPacketAccessBit = 0x0

AutoOrder

const int Eigen::AutoOrder = 2

CoherentAccessPattern

const int Eigen::CoherentAccessPattern = 0x1

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.

DynamicIndex

const int Eigen::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.

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.

InnerRandomAccessPattern

const int Eigen::InnerRandomAccessPattern = 0x2 | CoherentAccessPattern

NestByRefBit

const unsigned int Eigen::NestByRefBit = 0x100

OuterRandomAccessPattern

const int Eigen::OuterRandomAccessPattern = 0x4 | CoherentAccessPattern

RandomAccessPattern

const int Eigen::RandomAccessPattern = 0x8 | OuterRandomAccessPattern | InnerRandomAccessPattern

UndefinedIncr

const int Eigen::UndefinedIncr = 0xfffffe

This value means that the increment to go from one value to another in a sequence is not constant for each step.