Namespaces
namespace	Architecture
namespace	HybridNonLinearSolverSpace
namespace	internal
namespace	LevenbergMarquardtSpace
Classes
class	aligned_allocator
	STL compatible allocator to use with with 16 byte aligned types. More...
class	aligned_allocator_indirection
class	AlignedBox
	An axis aligned box. More...
class	AngleAxis
	Represents a 3D rotation as a rotation angle around an arbitrary 3D axis. 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
class	AutoDiffJacobian
class	AutoDiffScalar
	A scalar type replacement with automatic differentation capability. More...
class	AutoDiffVector
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	Block< XprType, BlockRows, BlockCols, InnerPanel, true >
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	CoeffBasedProduct
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	ComplexEigenSolver
	Computes eigenvalues and eigenvectors of general complex matrices. More...
class	ComplexSchur
	Performs a complex Schur decomposition of a real or complex square matrix. More...
class	ConjugateGradient
	A conjugate gradient solver for sparse self-adjoint problems. More...
class	Cwise
	Pseudo expression providing additional coefficient-wise operations. More...
class	CwiseBinaryOp
	Generic expression where a coefficient-wise binary operator is applied to two expressions. More...
class	CwiseBinaryOpImpl< BinaryOp, Lhs, Rhs, Dense >
class	CwiseBinaryOpImpl< BinaryOp, Lhs, Rhs, Sparse >
class	CwiseNullaryOp
	Generic expression of a matrix where all coefficients are defined by a functor. More...
class	CwiseUnaryOp
	Generic expression where a coefficient-wise unary operator is applied to an expression. More...
class	CwiseUnaryOpImpl< UnaryOp, MatrixType, Sparse >
class	CwiseUnaryOpImpl< UnaryOp, XprType, Dense >
class	CwiseUnaryView
	Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector. More...
class	CwiseUnaryViewImpl< ViewOp, MatrixType, Dense >
class	CwiseUnaryViewImpl< ViewOp, MatrixType, Sparse >
struct	Dense
class	DenseBase
	Base class for all dense matrices, vectors, and arrays. More...
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	DenseSparseProductReturnType
struct	DenseSparseProductReturnType< Lhs, Rhs, 1 >
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	DenseTimeSparseSelfAdjointProduct
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
class	DiagonalWrapper
	Expression of a diagonal matrix. More...
class	DynamicSparseMatrix
	A sparse matrix class designed for matrix assembly purpose. More...
struct	ei_cleantype
struct	ei_cleantype< const T & >
struct	ei_cleantype< const T * >
struct	ei_cleantype< const T >
struct	ei_cleantype< T & >
struct	ei_cleantype< T * >
struct	ei_is_same_type
struct	ei_is_same_type< T, T >
struct	ei_meta_false
struct	ei_meta_if
struct	ei_meta_if< false, Then, Else >
class	ei_meta_sqrt
class	ei_meta_sqrt< Y, InfX, SupX, true >
struct	ei_meta_true
struct	ei_quaternion_assign_impl< Other, 3, 3 >
struct	ei_quaternion_assign_impl< Other, 4, 1 >
struct	ei_traits
struct	ei_traits< AngleAxis< _Scalar > >
struct	ei_traits< Quaternion< _Scalar > >
struct	ei_traits< Rotation2D< _Scalar > >
struct	ei_transform_product_impl< Other, Dim, HDim, Dim, 1 >
struct	ei_transform_product_impl< Other, Dim, HDim, Dim, Dim >
struct	ei_transform_product_impl< Other, Dim, HDim, HDim, 1 >
struct	ei_transform_product_impl< Other, Dim, HDim, HDim, HDim >
struct	ei_unconst
struct	ei_unconst< const T >
struct	ei_unconst< T const & >
struct	ei_unconst< T const * >
struct	ei_unpointer
struct	ei_unpointer< T * >
struct	ei_unpointer< T *const >
struct	ei_unref
struct	ei_unref< T & >
struct	EigenBase
class	EigenSolver
	Computes eigenvalues and eigenvectors of general matrices. More...
class	Flagged
	Expression with modified flags. More...
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...
class	GeneralizedSelfAdjointEigenSolver
	Computes eigenvalues and eigenvectors of the generalized selfadjoint eigen problem. More...
class	GeneralProduct< Lhs, Rhs, GemmProduct >
class	GeneralProduct< Lhs, Rhs, GemvProduct >
class	GeneralProduct< Lhs, Rhs, InnerProduct >
class	GeneralProduct< Lhs, Rhs, OuterProduct >
struct	GenericNumTraits
class	GMRES
	A GMRES solver for sparse square problems. More...
class	HessenbergDecomposition
	Reduces a square matrix to Hessenberg form by an orthogonal similarity transformation. More...
class	Homogeneous
	Expression of one (or a set of) homogeneous vector(s) More...
class	HouseholderQR
	Householder QR decomposition of a matrix. More...
class	HouseholderSequence
	Sequence of Householder reflections acting on subspaces with decreasing size. More...
class	HybridNonLinearSolver
	Finds a zero of a system of n nonlinear functions in n variables by a modification of the Powell hybrid method ("dogleg"). More...
class	Hyperplane
	A hyperplane. More...
class	IdentityPreconditioner
	A naive preconditioner which approximates any matrix as the identity matrix. More...
class	IncompleteLU
class	IncompleteLUT
	Incomplete LU factorization with dual-threshold strategy During the numerical factorization, two dropping rules are used : 1) any element whose magnitude is less than some tolerance is dropped. This tolerance is obtained by multiplying the input tolerance `droptol` by the average magnitude of all the original elements in the current row. 2) After the elimination of the row, only the `fill` largest elements in the L part and the `fill` largest elements in the U part are kept (in addition to the diagonal element ). Note that `fill` is computed from the input parameter `fillfactor` which is used the ratio to control the fill_in relatively to the initial number of nonzero elements. More...
class	InnerStride
	Convenience specialization of Stride to specify only an inner stride See class Map for some examples. More...
class	IOFormat
	Stores a set of parameters controlling the way matrices are printed. More...
class	IterationController
	Controls the iterations of the iterative solvers. More...
class	IterativeSolverBase
	Base class for linear iterative solvers. More...
class	JacobiRotation
	Rotation given by a cosine-sine pair. More...
class	JacobiSVD
	Two-sided Jacobi SVD decomposition of a rectangular matrix. More...
class	KdBVH
	A simple bounding volume hierarchy based on AlignedBox. More...
struct	LazyProductReturnType
class	LDLT
	Robust Cholesky decomposition of a matrix with pivoting. More...
class	LevenbergMarquardt
	Performs non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm. More...
class	LLT
	Standard Cholesky decomposition (LL^T) of a matrix and associated features. More...
class	LU
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< PermutationMatrix< SizeAtCompileTime, MaxSizeAtCompileTime, IndexType >, _PacketAccess >
class	Map< Quaternion< _Scalar >, _Options >
	Expression of a quaternion from a memory buffer. More...
class	Map< Transpositions< SizeAtCompileTime, MaxSizeAtCompileTime, IndexType >, PacketAccess >
class	MapBase< Derived, ReadOnlyAccessors >
class	MapBase< Derived, WriteAccessors >
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	MatrixExponential
	Class for computing the matrix exponential. More...
struct	MatrixExponentialReturnValue
	Proxy for the matrix exponential of some matrix (expression). More...
class	MatrixFunction
	Class for computing matrix functions. More...
class	MatrixFunction< MatrixType, AtomicType, 0 >
class	MatrixFunction< MatrixType, AtomicType, 1 >
class	MatrixFunctionAtomic
	Helper class for computing matrix functions of atomic matrices. More...
class	MatrixFunctionReturnValue
	Proxy for the matrix function of some matrix (expression). More...
class	MatrixLogarithmAtomic
	Helper class for computing matrix logarithm of atomic matrices. More...
class	MatrixLogarithmReturnValue
	Proxy for the matrix logarithm of some matrix (expression). More...
class	MatrixMarketIterator
	Iterator to browse matrices from a specified folder. More...
class	MatrixSquareRoot
	Class for computing matrix square roots of general matrices. More...
class	MatrixSquareRoot< MatrixType, 0 >
class	MatrixSquareRoot< MatrixType, 1 >
class	MatrixSquareRootQuasiTriangular
	Class for computing matrix square roots of upper quasi-triangular matrices. More...
class	MatrixSquareRootReturnValue
	Proxy for the matrix square root of some matrix (expression). More...
class	MatrixSquareRootTriangular
	Class for computing matrix square roots of upper triangular matrices. More...
class	MatrixWrapper
	Expression of an array as a mathematical vector or matrix. More...
struct	MatrixXpr
class	Minor
	Expression of a minor. More...
class	NestByValue
	Expression which must be nested by value. More...
class	NoAlias
	Pseudo expression providing an operator = assuming no aliasing. More...
class	NumericalDiff
class	NumTraits
	Holds information about the various numeric (i.e. scalar) types allowed by Eigen. More...
struct	NumTraits< Array< Scalar, Rows, Cols, Options, MaxRows, MaxCols > >
struct	NumTraits< double >
struct	NumTraits< float >
struct	NumTraits< long double >
struct	NumTraits< std::complex< _Real > >
class	OuterStride
	Convenience specialization of Stride to specify only an outer stride See class Map for some examples. More...
class	ParametrizedLine
	A parametrized line. 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...
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
	Sparse direct LU solver based on PaStiX library. More...
class	PermutationBase
	Base class for permutations. More...
class	PermutationMatrix
	Permutation matrix. More...
struct	PermutationStorage
class	PermutationWrapper
	Class to view a vector of integers as a permutation matrix. More...
class	PlainObjectBase
	Dense storage base class for matrices and arrays. More...
class	PolynomialSolver
	A polynomial solver. More...
class	PolynomialSolver< _Scalar, 1 >
class	PolynomialSolverBase
	Defined to be inherited by polynomial solvers: it provides convenient methods such as. More...
class	ProductBase
class	ProductReturnType
	Helper class to get the correct and optimized returned type of operator*. More...
struct	ProductReturnType< Lhs, Rhs, CoeffBasedProductMode >
struct	ProductReturnType< Lhs, Rhs, LazyCoeffBasedProductMode >
class	QR
class	Quaternion
	The quaternion class used to represent 3D orientations and rotations. More...
class	QuaternionBase
	Base class for quaternion expressions. More...
class	RandomSetter
	The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access. More...
class	RealSchur
	Performs a real Schur decomposition of a square matrix. More...
class	Replicate
	Expression of the multiple replication of a matrix or vector. More...
class	ReturnByValue
class	Reverse
	Expression of the reverse of a vector or matrix. More...
class	Rotation2D
	Represents a rotation/orientation in a 2 dimensional space. More...
class	RotationBase
	Common base class for compact rotation representations. More...
class	ScaledProduct
class	Scaling
	Represents a possibly non uniform scaling transformation. More...
class	Select
	Expression of a coefficient wise version of the C++ ternary operator ?: More...
struct	selfadjoint_product_selector< MatrixType, OtherType, UpLo, false >
struct	selfadjoint_product_selector< MatrixType, OtherType, UpLo, true >
struct	selfadjoint_rank1_update< Scalar, Index, ColMajor, UpLo, ConjLhs, ConjRhs >
struct	selfadjoint_rank1_update< Scalar, Index, RowMajor, UpLo, ConjLhs, ConjRhs >
class	SelfAdjointEigenSolver
	Computes eigenvalues and eigenvectors of selfadjoint matrices. More...
struct	SelfadjointProductMatrix< Lhs, 0, true, Rhs, RhsMode, false >
struct	SelfadjointProductMatrix< Lhs, LhsMode, false, Rhs, 0, true >
struct	SelfadjointProductMatrix< Lhs, LhsMode, false, Rhs, RhsMode, false >
class	SelfAdjointView
	Expression of a selfadjoint matrix from a triangular part of a dense matrix. More...
class	SelfCwiseBinaryOp
class	SimplicialCholesky
class	SimplicialCholeskyBase
	A 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	SkylineInplaceLU
	Inplace LU decomposition of a skyline matrix and associated features. More...
class	SkylineMatrix
	The main skyline matrix class. More...
class	SkylineMatrixBase
	Base class of any skyline matrices or skyline expressions. More...
struct	SkylineProductReturnType
class	SkylineStorage
struct	SluMatrix
struct	SluMatrixMapHelper< Matrix< Scalar, Rows, Cols, Options, MRows, MCols > >
struct	SluMatrixMapHelper< SparseMatrixBase< Derived > >
class	SparseDenseOuterProduct
struct	SparseDenseProductReturnType
struct	SparseDenseProductReturnType< Lhs, Rhs, 1 >
class	SparseDiagonalProduct
class	SparseInnerVectorSet
class	SparseInnerVectorSet< DynamicSparseMatrix< _Scalar, _Options, _Index >, Size >
class	SparseInnerVectorSet< SparseMatrix< _Scalar, _Options, _Index >, Size >
class	SparseMatrix
	A versatible sparse matrix representation. More...
class	SparseMatrixBase
	Base class of any sparse matrices or sparse expressions. More...
class	SparseSelfAdjointTimeDenseProduct
class	SparseSelfAdjointView
	Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. More...
class	SparseSparseProduct
struct	SparseSparseProductReturnType
class	SparseSymmetricPermutationProduct
class	SparseTimeDenseProduct
class	SparseTriangularView
class	SparseVector
	a sparse vector class More...
class	SparseView
class	Spline
	A class representing multi-dimensional spline curves. More...
struct	SplineFitting
	Spline fitting methods. More...
struct	SplineTraits
struct	SplineTraits< Spline< _Scalar, _Dim, _Degree >, _DerivativeOrder >
	Compile-time attributes of the Spline class for fixed degree. More...
struct	SplineTraits< Spline< _Scalar, _Dim, _Degree >, Dynamic >
	Compile-time attributes of the Spline class for Dynamic degree. More...
struct	StdMapTraits
class	StdStemFunctions
	Stem functions corresponding to standard mathematical functions. More...
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	SVD
	Standard SVD decomposition of a matrix and associated features. More...
class	SwapWrapper
class	Transform
	Represents an homogeneous transformation in a N dimensional space. More...
class	Translation
	Represents a translation transformation. More...
class	Transpose
	Expression of the transpose of a matrix. More...
class	Transpose< PermutationBase< Derived > >
class	Transpose< TranspositionsBase< TranspositionsDerived > >
class	TransposeImpl< MatrixType, Dense >
class	TransposeImpl< MatrixType, Sparse >
class	Transpositions
	Represents a sequence of transpositions (row/column interchange) More...
class	TranspositionsBase
class	TranspositionsWrapper
class	TriangularBase
struct	TriangularProduct< Mode, false, Lhs, true, Rhs, false >
struct	TriangularProduct< Mode, LhsIsTriangular, Lhs, false, Rhs, false >
struct	TriangularProduct< Mode, true, Lhs, false, Rhs, true >
class	TriangularView
	Base class for triangular part in a matrix. More...
class	Tridiagonalization
	Tridiagonal decomposition of a selfadjoint matrix. 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
class	VectorBlock
	Expression of a fixed-size or dynamic-size sub-vector. More...
class	VectorwiseOp
	Pseudo expression providing partial reduction operations. More...
class	WithFormat
	Pseudo expression providing matrix output with given format. More...
Typedefs
typedef Transform< double, 2, Affine >	Affine2d
typedef Transform< float, 2, Affine >	Affine2f
typedef Transform< double, 3, Affine >	Affine3d
typedef Transform< float, 3, Affine >	Affine3f
typedef Transform< double, 2, AffineCompact >	AffineCompact2d
typedef Transform< float, 2, AffineCompact >	AffineCompact2f
typedef Transform< double, 3, AffineCompact >	AffineCompact3d
typedef Transform< float, 3, AffineCompact >	AffineCompact3f
typedef DiagonalMatrix< double, 2 >	AlignedScaling2d
typedef DiagonalMatrix< float, 2 >	AlignedScaling2f
typedef DiagonalMatrix< double, 3 >	AlignedScaling3d
typedef DiagonalMatrix< float, 3 >	AlignedScaling3f
typedef AngleAxis< double >	AngleAxisd
typedef AngleAxis< float >	AngleAxisf
typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE	DenseIndex
typedef Transform< double, 2, Isometry >	Isometry2d
typedef Transform< float, 2, Isometry >	Isometry2f
typedef Transform< double, 3, Isometry >	Isometry3d
typedef Transform< float, 3, Isometry >	Isometry3f
typedef Transform< double, 2, Projective >	Projective2d
typedef Transform< float, 2, Projective >	Projective2f
typedef Transform< double, 3, Projective >	Projective3d
typedef Transform< float, 3, Projective >	Projective3f
typedef Quaternion< double >	Quaterniond
typedef Quaternion< float >	Quaternionf
typedef Map< Quaternion < double >, Aligned >	QuaternionMapAlignedd
typedef Map< Quaternion< float > , Aligned >	QuaternionMapAlignedf
typedef Map< Quaternion < double >, 0 >	QuaternionMapd
typedef Map< Quaternion< float >, 0 >	QuaternionMapf
typedef Rotation2D< double >	Rotation2Dd
typedef Rotation2D< float >	Rotation2Df
typedef Scaling< double, 2 >	Scaling2d
typedef Scaling< float, 2 >	Scaling2f
typedef Scaling< double, 3 >	Scaling3d
typedef Scaling< float, 3 >	Scaling3f
typedef Spline< double, 2 >	Spline2d
	2D double B-spline with dynamic degree.
typedef Spline< float, 2 >	Spline2f
	2D float B-spline with dynamic degree.
typedef Spline< double, 3 >	Spline3d
	3D double B-spline with dynamic degree.
typedef Spline< float, 3 >	Spline3f
	3D float B-spline with dynamic degree.
typedef Transform< double, 2 >	Transform2d
typedef Transform< float, 2 >	Transform2f
typedef Transform< double, 3 >	Transform3d
typedef Transform< float, 3 >	Transform3f
typedef Translation< double, 2 >	Translation2d
typedef Translation< float, 2 >	Translation2f
typedef Translation< double, 3 >	Translation3d
typedef Translation< float, 3 >	Translation3f
Enumerations
enum	{ Large = 2, Small = 3 }
enum	{ DontAlignCols = 1 }
enum	{ StreamPrecision = -1, FullPrecision = -2 }
enum	{ 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	{ Unaligned = 0, Aligned = 1 }
enum	{ DefaultTraversal, LinearTraversal, InnerVectorizedTraversal, LinearVectorizedTraversal, SliceVectorizedTraversal, InvalidTraversal }
enum	{ NoUnrolling, InnerUnrolling, CompleteUnrolling }
enum	{ Specialized, BuiltIn }
enum	{ ColMajor = 0, RowMajor = 0x1, AutoAlign = 0, DontAlign = 0x2 }
enum	{ OnTheLeft = 1, OnTheRight = 2 }
enum	{ IsDense = 0, IsSparse }
enum	{ CoeffBasedProductMode, LazyCoeffBasedProductMode, OuterProduct, InnerProduct, GemvProduct, GemmProduct }
enum	{ IsSkyline = SkylineBit }
enum	{ SPD = 0x100, NonSymmetric = 0x0 }
enum	AccessorLevels { ReadOnlyAccessors, WriteAccessors, DirectAccessors, DirectWriteAccessors }
enum	Action { GetAction, SetAction }
enum	AdditionalProductEvaluationMode { SkylineTimeDenseProduct, SkylineTimeSkylineProduct, DenseTimeSkylineProduct }
enum	CholmodMode { CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt }
enum	ComputationInfo { Success = 0, NumericalIssue = 1, NoConvergence = 2, InvalidInput = 3 }
enum	CornerType { TopLeft, TopRight, BottomLeft, BottomRight }
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	Default_t { Default }
enum	DirectionType { Vertical, Horizontal, BothDirections }
enum	NoChange_t { NoChange }
enum	NumericalDiffMode { Forward, Central }
enum	QRPreconditioners { NoQRPreconditioner, HouseholderQRPreconditioner, ColPivHouseholderQRPreconditioner, FullPivHouseholderQRPreconditioner }
enum	Sequential_t { Sequential }
enum	SimplicialCholeskyMode { SimplicialCholeskyLLT, SimplicialCholeskyLDLT }
enum	TransformTraits { Isometry = 0x1, Affine = 0x2, AffineCompact = 0x10 \| Affine, Projective = 0x20 }
Functions
template<typename DerTypeA , typename DerTypeB >
const AutoDiffScalar< Matrix < typename internal::traits < DerTypeA >::Scalar, Dynamic, 1 > >	atan2 (const AutoDiffScalar< DerTypeA > &a, const AutoDiffScalar< DerTypeB > &b)
template<typename DerType , typename T >
	AutoDiffScalar< DerType > (min)(const AutoDiffScalar< DerType > &x
T	AutoDiffScalar< DerType > (max)(const AutoDiffScalar< DerType > &x
template<typename SplineType , typename DerivativeType >
void	basisFunctionDerivativesImpl (const SplineType &spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType &N_)
template<typename BVH , typename Intersector >
void	BVIntersect (const BVH &tree, Intersector &intersector)
template<typename BVH1 , typename BVH2 , typename Intersector >
void	BVIntersect (const BVH1 &tree1, const BVH2 &tree2, Intersector &intersector)
template<typename BVH , typename Minimizer >
Minimizer::Scalar	BVMinimize (const BVH &tree, Minimizer &minimizer)
template<typename BVH1 , typename BVH2 , typename Minimizer >
Minimizer::Scalar	BVMinimize (const BVH1 &tree1, const BVH2 &tree2, Minimizer &minimizer)
template<typename Polynomial >
NumTraits< typename Polynomial::Scalar >::Real	cauchy_max_bound (const Polynomial &poly)
template<typename Polynomial >
NumTraits< typename Polynomial::Scalar >::Real	cauchy_min_bound (const Polynomial &poly)
template<typename Scalar >
std::complex< Scalar >	cdiv (Scalar xr, Scalar xi, Scalar yr, Scalar yi)
template<typename PointArrayType , typename KnotVectorType >
void	ChordLengths (const PointArrayType &pts, KnotVectorType &chord_lengths)
	Computes chord length parameters which are required for spline interpolation.
template<typename DerType >
const AutoDiffScalar< DerType > &	conj (const AutoDiffScalar< DerType > &x)
template<typename SplineType , typename DerivativeType >
void	derivativesImpl (const SplineType &spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType &der)
template<typename T >
NumTraits< T >::Real	ei_abs (const T &x)
template<typename T >
NumTraits< T >::Real	ei_abs2 (const T &x)
template<typename T >
void	ei_aligned_delete (T *ptr, size_t size)
void	ei_aligned_free (void *ptr)
void *	ei_aligned_malloc (size_t size)
template<typename T >
T *	ei_aligned_new (size_t size)
void *	ei_aligned_realloc (void *ptr, size_t new_size, size_t old_size)
template<typename T >
T	ei_atan2 (const T &x, const T &y)
template<bool Align>
void	ei_conditional_aligned_free (void *ptr)
template<bool Align>
void *	ei_conditional_aligned_malloc (size_t size)
template<bool Align>
void *	ei_conditional_aligned_realloc (void *ptr, size_t new_size, size_t old_size)
template<typename T >
T	ei_conj (const T &x)
template<typename T >
T	ei_cos (const T &x)
template<typename T >
T	ei_exp (const T &x)
void	ei_handmade_aligned_free (void *ptr)
void *	ei_handmade_aligned_malloc (size_t size)
template<typename T >
NumTraits< T >::Real	ei_imag (const T &x)
template<typename Scalar >
bool	ei_isApprox (const Scalar &x, const Scalar &y, typename NumTraits< Scalar >::Real precision=NumTraits< Scalar >::dummy_precision())
template<typename Scalar >
bool	ei_isApproxOrLessThan (const Scalar &x, const Scalar &y, typename NumTraits< Scalar >::Real precision=NumTraits< Scalar >::dummy_precision())
template<typename Scalar , typename OtherScalar >
bool	ei_isMuchSmallerThan (const Scalar &x, const OtherScalar &y, typename NumTraits< Scalar >::Real precision=NumTraits< Scalar >::dummy_precision())
template<typename T >
T	ei_log (const T &x)
template<typename T >
T	ei_pow (const T &x, const T &y)
template<typename Scalar >
Quaternion< Scalar >	ei_quaternion_product (const Quaternion< Scalar > &a, const Quaternion< Scalar > &b)
template<typename T >
T	ei_random ()
template<typename T >
T	ei_random (const T &x, const T &y)
template<typename T >
NumTraits< T >::Real	ei_real (const T &x)
template<typename T >
T	ei_sin (const T &x)
template<typename T >
T	ei_sqrt (const T &x)
template<typename Scalar , int Dim>
static Matrix< Scalar, 2, 2 >	ei_toRotationMatrix (const Scalar &s)
template<typename Scalar , int Dim, typename OtherDerived >
static Matrix< Scalar, Dim, Dim >	ei_toRotationMatrix (const RotationBase< OtherDerived, Dim > &r)
template<typename Scalar , int Dim, typename OtherDerived >
static const MatrixBase < OtherDerived > &	ei_toRotationMatrix (const MatrixBase< OtherDerived > &mat)
	EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY (tan, using std::tan;using std::cos;return ReturnType(tan(x.value()), x.derivatives()*(Scalar(1)/internal::abs2(cos(x.value()))));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin
	EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY (acos, using std::sqrt;using std::acos;return ReturnType(acos(x.value()), x.derivatives()*(Scalar(-1)/sqrt(1-internal::abs2(x.value()))));) template< typename DerType > struct NumTraits< AutoDiffScalar< DerType > >
template<typename OtherDerived >
EIGEN_STRONG_INLINE const	EIGEN_CWISE_BINOP_RETURN_TYPE (internal::scalar_quotient_op) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::less) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::less_equal) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::greater) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::greater_equal) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::equal_to) Cwise< ExpressionType >
template<typename OtherDerived >
const	EIGEN_CWISE_BINOP_RETURN_TYPE (std::not_equal_to) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::less) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::less_equal) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::greater) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::greater_equal) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::equal_to) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE (std::not_equal_to) Cwise< ExpressionType >
template<typename OtherDerived >
EIGEN_STRONG_INLINE const	EIGEN_CWISE_PRODUCT_RETURN_TYPE (ExpressionType, OtherDerived) Cwise< ExpressionType >
template<typename ExpressionType >
EIGEN_STRONG_INLINE const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_abs_op) Cwise< ExpressionType >
template<typename ExpressionType >
EIGEN_STRONG_INLINE const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_abs2_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_exp_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_log_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_sqrt_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_cos_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_sin_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_pow_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_inverse_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_square_op) Cwise< ExpressionType >
template<typename ExpressionType >
const	EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_cube_op) Cwise< ExpressionType >
template<typename VectorType , typename HyperplaneType >
void	fitHyperplane (int numPoints, VectorType *points, HyperplaneType result, typename NumTraits< typename VectorType::Scalar >::Real *soundness=0)
bool	getMarketHeader (const std::string &filename, int &sym, bool &iscomplex, bool &isvector)
template<typename VectorsType , typename CoeffsType >
HouseholderSequence < VectorsType, CoeffsType >	householderSequence (const VectorsType &v, const CoeffsType &h)
	Convenience function for constructing a Householder sequence.
template<typename DerType >
DerType::Scalar	imag (const AutoDiffScalar< DerType > &)
void	initParallel ()
template<typename KnotVectorType >
void	KnotAveraging (const KnotVectorType &parameters, DenseIndex degree, KnotVectorType &knots)
	Computes knot averages.The knots are computed as $\begin{align} u_0 & = \hdots = u_p = 0 \\ u_{m-p} & = \hdots = u_{m} = 1 \\ u_{j+p} & = \frac{1}{p}\sum_{i=j}^{j+p-1}\bar{u}_i \quad\quad j=1,\hdots,n-p \end{align}$ where is the degree and the number knots of the desired interpolating spline.
template<typename A , typename B , typename CScalar , int CRows, int CCols, int COptions, int CMaxRows, int CMaxCols>
void	kroneckerProduct (const MatrixBase< A > &a, const MatrixBase< B > &b, Matrix< CScalar, CRows, CCols, COptions, CMaxRows, CMaxCols > &c)
template<typename A , typename B , typename C >
void	kroneckerProduct (const MatrixBase< A > &a, const MatrixBase< B > &b, MatrixBase< C > const &c_)
template<typename A , typename B , typename C >
void	kroneckerProduct (const MatrixBase< A > &a, const SparseMatrixBase< B > &b, SparseMatrixBase< C > &c)
template<typename A , typename B , typename C >
void	kroneckerProduct (const SparseMatrixBase< A > &a, const MatrixBase< B > &b, SparseMatrixBase< C > &c)
template<typename A , typename B , typename C >
void	kroneckerProduct (const SparseMatrixBase< A > &a, const SparseMatrixBase< B > &b, SparseMatrixBase< C > &c)
std::ptrdiff_t	l1CacheSize ()
std::ptrdiff_t	l2CacheSize ()
template<typename VectorType >
void	linearRegression (int numPoints, VectorType *points, VectorType result, int funcOfOthers)
template<typename SparseMatrixType >
bool	loadMarket (SparseMatrixType &mat, const std::string &filename)
template<typename VectorType >
bool	loadMarketVector (VectorType &vec, const std::string &filename)
template<typename T >
T	machine_epsilon ()
int	nbThreads ()
template<typename SparseDerived , typename PermDerived >
const internal::permut_sparsematrix_product_retval < PermutationBase< PermDerived > , SparseDerived, OnTheRight, false >	operator* (const SparseMatrixBase< SparseDerived > &matrix, const PermutationBase< PermDerived > &perm)
template<typename SparseDerived , typename PermDerived >
const internal::permut_sparsematrix_product_retval < PermutationBase< PermDerived > , SparseDerived, OnTheLeft, false >	operator* (const PermutationBase< PermDerived > &perm, const SparseMatrixBase< SparseDerived > &matrix)
template<typename SparseDerived , typename PermDerived >
const internal::permut_sparsematrix_product_retval < PermutationBase< PermDerived > , SparseDerived, OnTheRight, true >	operator* (const SparseMatrixBase< SparseDerived > &matrix, const Transpose< PermutationBase< PermDerived > > &tperm)
template<typename SparseDerived , typename PermDerived >
const internal::permut_sparsematrix_product_retval < PermutationBase< PermDerived > , SparseDerived, OnTheLeft, true >	operator* (const Transpose< PermutationBase< PermDerived > > &tperm, const SparseMatrixBase< SparseDerived > &matrix)
template<typename Derived , typename Lhs , typename Rhs >
const ScaledProduct< Derived >	operator* (const ProductBase< Derived, Lhs, Rhs > &prod, typename Derived::Scalar x)
template<typename Derived , typename Lhs , typename Rhs >
internal::enable_if <!internal::is_same< typename Derived::Scalar, typename Derived::RealScalar >::value, const ScaledProduct< Derived > >::type	operator* (const ProductBase< Derived, Lhs, Rhs > &prod, typename Derived::RealScalar x)
template<typename Derived , typename Lhs , typename Rhs >
const ScaledProduct< Derived >	operator* (typename Derived::Scalar x, const ProductBase< Derived, Lhs, Rhs > &prod)
template<typename Derived , typename Lhs , typename Rhs >
internal::enable_if <!internal::is_same< typename Derived::Scalar, typename Derived::RealScalar >::value, const ScaledProduct< Derived > >::type	operator* (typename Derived::RealScalar x, const ProductBase< Derived, Lhs, Rhs > &prod)
template<typename Derived , typename TranspositionsDerived >
const internal::transposition_matrix_product_retval < TranspositionsDerived, Derived, OnTheRight >	operator* (const MatrixBase< Derived > &matrix, const TranspositionsBase< TranspositionsDerived > &transpositions)
template<typename Derived , typename TranspositionDerived >
const internal::transposition_matrix_product_retval < TranspositionDerived, Derived, OnTheLeft >	operator* (const TranspositionsBase< TranspositionDerived > &transpositions, const MatrixBase< Derived > &matrix)
template<typename OtherDerived , typename VectorsType , typename CoeffsType , int Side>
internal::matrix_type_times_scalar_type < typename VectorsType::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 Derived , typename PermutationDerived >
const internal::permut_matrix_product_retval < PermutationDerived, Derived, OnTheRight >	operator* (const MatrixBase< Derived > &matrix, const PermutationBase< PermutationDerived > &permutation)
template<typename Derived , typename PermutationDerived >
const internal::permut_matrix_product_retval < PermutationDerived, Derived, OnTheLeft >	operator* (const PermutationBase< PermutationDerived > &permutation, const MatrixBase< Derived > &matrix)
template<typename Derived >
const Eigen::CwiseUnaryOp < Eigen::internal::scalar_inverse_mult_op < typename Derived::Scalar > , const Derived >	operator/ (typename Derived::Scalar s, const Eigen::ArrayBase< Derived > &a)
	Component-wise division of a scalar by array elements.
template<typename Polynomials , typename T >
T	poly_eval (const Polynomials &poly, const T &x)
template<typename Polynomials , typename T >
T	poly_eval_horner (const Polynomials &poly, const T &x)
const DerType	pow (const Eigen::AutoDiffScalar< DerType > &x, typename Eigen::internal::traits< DerType >::Scalar y)
template<typename T >
T	precision ()
template<typename DerType >
const AutoDiffScalar< DerType > &	real (const AutoDiffScalar< DerType > &x)
return	ReturnType (asin(x.value()), x.derivatives()*(Scalar(1)/sqrt(1-internal::abs2(x.value()))))
template<typename VectorsType , typename CoeffsType >
HouseholderSequence < VectorsType, CoeffsType, OnTheRight >	rightHouseholderSequence (const VectorsType &v, const CoeffsType &h)
	Convenience function for constructing a Householder sequence.
template<typename RootVector , typename Polynomial >
void	roots_to_monicPolynomial (const RootVector &rv, Polynomial &poly)
template<typename SparseMatrixType >
bool	saveMarket (const SparseMatrixType &mat, const std::string &filename, int sym=0)
template<typename VectorType >
bool	saveMarketVector (const VectorType &vec, const std::string &filename)
static UniformScaling< float >	Scaling (float s)
static UniformScaling< double >	Scaling (double s)
template<typename RealScalar >
static UniformScaling < std::complex< RealScalar > >	Scaling (const std::complex< RealScalar > &s)
template<typename Scalar >
static DiagonalMatrix< Scalar, 2 >	Scaling (Scalar sx, Scalar sy)
template<typename Scalar >
static DiagonalMatrix< Scalar, 3 >	Scaling (Scalar sx, Scalar sy, Scalar sz)
template<typename Derived >
static const DiagonalWrapper < const Derived >	Scaling (const MatrixBase< Derived > &coeffs)
void	setCpuCacheSizes (std::ptrdiff_t l1, std::ptrdiff_t l2)
void	setNbThreads (int v)
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)
	Returns the transformation between two point sets.
void	umfpack_free_numeric (void **Numeric, double)
void	umfpack_free_numeric (void **Numeric, std::complex< double >)
void	umfpack_free_symbolic (void **Symbolic, double)
void	umfpack_free_symbolic (void **Symbolic, std::complex< double >)
int	umfpack_get_determinant (double Mx, double Ex, void *NumericHandle, double User_Info[UMFPACK_INFO])
int	umfpack_get_determinant (std::complex< double > Mx, double Ex, void *NumericHandle, double User_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 >)
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)
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])
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])
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])
template<typename _Scalar , int _Options, typename _Index >
cholmod_sparse	viewAsCholmod (SparseMatrix< _Scalar, _Options, _Index > &mat)
template<typename _Scalar , int _Options, typename _Index >
const cholmod_sparse	viewAsCholmod (const SparseMatrix< _Scalar, _Options, _Index > &mat)
template<typename _Scalar , int _Options, typename _Index , unsigned int UpLo>
cholmod_sparse	viewAsCholmod (const SparseSelfAdjointView< SparseMatrix< _Scalar, _Options, _Index >, UpLo > &mat)
template<typename Derived >
cholmod_dense	viewAsCholmod (MatrixBase< Derived > &mat)
template<typename Scalar , int Flags, typename Index >
MappedSparseMatrix< Scalar, Flags, Index >	viewAsEigen (cholmod_sparse &cm)
Variables
const unsigned int	ActualPacketAccessBit = 0x0
const unsigned int	AlignedBit = 0x80
const int	CoherentAccessPattern = 0x1
const unsigned int	DirectAccessBit = 0x40
const int	Dynamic = -1
const unsigned int	EvalBeforeAssigningBit = 0x4
const unsigned int	EvalBeforeNestingBit = 0x2
const unsigned int	HereditaryBits
const int	Infinity = -1
const int	InnerRandomAccessPattern = 0x2 \| CoherentAccessPattern
const unsigned int	LinearAccessBit = 0x10
const unsigned int	LowerTriangular = Lower
const unsigned int	LowerTriangularBit = Lower
const unsigned int	LvalueBit = 0x20
const unsigned int	NestByRefBit = 0x100
const int	OuterRandomAccessPattern = 0x4 \| CoherentAccessPattern
const unsigned int	PacketAccessBit = 0x8
const int	RandomAccessPattern = 0x8 \| OuterRandomAccessPattern \| InnerRandomAccessPattern
const unsigned int	RowMajorBit = 0x1
const unsigned int	SelfAdjointBit = SelfAdjoint
const unsigned int	SkylineBit = 0x1200
const unsigned int	UnitDiagBit = UnitDiag
const unsigned int	UnitLowerTriangular = UnitLower
const unsigned int	UnitUpperTriangular = UnitUpper
const unsigned int	UpperTriangular = Upper
const unsigned int	UpperTriangularBit = Upper

Typedef Documentation

typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE Eigen::DenseIndex

Definition at line 27 of file XprHelper.h.

typedef Spline<double,2> Eigen::Spline2d

2D double B-spline with dynamic degree.

Definition at line 80 of file SplineFwd.h.

typedef Spline<float,2> Eigen::Spline2f

2D float B-spline with dynamic degree.

Definition at line 74 of file SplineFwd.h.

typedef Spline<double,3> Eigen::Spline3d

3D double B-spline with dynamic degree.

Definition at line 83 of file SplineFwd.h.

typedef Spline<float,3> Eigen::Spline3f

3D float B-spline with dynamic degree.

Definition at line 77 of file SplineFwd.h.

Enumeration Type Documentation

anonymous enum

Enumerator:

Large
Small

Definition at line 38 of file GeneralProduct.h.

anonymous enum

Enumerator:

DontAlignCols

Definition at line 16 of file IO.h.

anonymous enum

Enumerator:

StreamPrecision
FullPrecision

Definition at line 17 of file IO.h.

anonymous enum

Enumerator:

DefaultTraversal
LinearTraversal
InnerVectorizedTraversal
LinearVectorizedTraversal
SliceVectorizedTraversal
InvalidTraversal

Definition at line 215 of file Constants.h.

anonymous enum

Enumerator:

NoUnrolling
InnerUnrolling
CompleteUnrolling

Definition at line 235 of file Constants.h.

anonymous enum

Enumerator:

Specialized
BuiltIn

Definition at line 247 of file Constants.h.

anonymous enum

Enumerator:

IsDense
IsSparse

Definition at line 293 of file Constants.h.

anonymous enum

Enumerator:

CoeffBasedProductMode
LazyCoeffBasedProductMode
OuterProduct
InnerProduct
GemvProduct
GemmProduct

Definition at line 414 of file Constants.h.

anonymous enum

Enumerator:

IsSkyline

Definition at line 24 of file SkylineUtil.h.

anonymous enum

Enumerator:

SPD
NonSymmetric

Definition at line 16 of file MatrixMarketIterator.h.

enum Eigen::Action

Enumerator:

GetAction
SetAction

Definition at line 418 of file Constants.h.

enum Eigen::AdditionalProductEvaluationMode

Enumerator:

SkylineTimeDenseProduct
SkylineTimeSkylineProduct
DenseTimeSkylineProduct

Definition at line 23 of file SkylineUtil.h.

enum Eigen::CholmodMode

Enumerator:

CholmodAuto
CholmodSimplicialLLt
CholmodSupernodalLLt
CholmodLDLt

Definition at line 144 of file CholmodSupport.h.

enum Eigen::Default_t

Enumerator:

Default

Definition at line 289 of file Constants.h.

enum Eigen::NoChange_t

Enumerator:

NoChange

Definition at line 287 of file Constants.h.

enum Eigen::NumericalDiffMode

Enumerator:

Forward
Central

Definition at line 18 of file NumericalDiff.h.

enum Eigen::Sequential_t

Enumerator:

Sequential

Definition at line 288 of file Constants.h.

enum Eigen::SimplicialCholeskyMode

Enumerator:

SimplicialCholeskyLLT
SimplicialCholeskyLDLT

Definition at line 55 of file SimplicialCholesky.h.

Function Documentation

template<typename DerTypeA , typename DerTypeB >

const AutoDiffScalar<Matrix<typename internal::traits<DerTypeA>::Scalar,Dynamic,1> > Eigen::atan2	(	const AutoDiffScalar< DerTypeA > &	a,
		const AutoDiffScalar< DerTypeB > &	b
	)		`[inline]`

Definition at line 583 of file AutoDiffScalar.h.

template<typename DerType , typename T >

T Eigen::AutoDiffScalar< DerType > ( min ) const [inline]

T Eigen::AutoDiffScalar< DerType > ( max ) const [inline]

template<typename SplineType , typename DerivativeType >

void Eigen::basisFunctionDerivativesImpl	(	const SplineType &	spline,
		typename SplineType::Scalar	u,
		DenseIndex	order,
		DerivativeType &	N_
	)

Definition at line 339 of file Spline.h.

template<typename BVH , typename Intersector >

void Eigen::BVIntersect	(	const BVH &	tree,
		Intersector &	intersector
	)

Given a BVH, runs the query encapsulated by intersector. The Intersector type must provide the following members:

     bool intersectVolume(const BVH::Volume &volume) //returns true if volume intersects the query
     bool intersectObject(const BVH::Object &object) //returns true if the search should terminate immediately

Definition at line 79 of file BVAlgorithms.h.

template<typename BVH1 , typename BVH2 , typename Intersector >

void Eigen::BVIntersect	(	const BVH1 &	tree1,
		const BVH2 &	tree2,
		Intersector &	intersector
	)

Given two BVH's, runs the query on their Cartesian product encapsulated by intersector. The Intersector type must provide the following members:

     bool intersectVolumeVolume(const BVH1::Volume &v1, const BVH2::Volume &v2) //returns true if product of volumes intersects the query
     bool intersectVolumeObject(const BVH1::Volume &v1, const BVH2::Object &o2) //returns true if the volume-object product intersects the query
     bool intersectObjectVolume(const BVH1::Object &o1, const BVH2::Volume &v2) //returns true if the volume-object product intersects the query
     bool intersectObjectObject(const BVH1::Object &o1, const BVH2::Object &o2) //returns true if the search should terminate immediately

Definition at line 93 of file BVAlgorithms.h.

template<typename BVH , typename Minimizer >

Minimizer::Scalar Eigen::BVMinimize	(	const BVH &	tree,
		Minimizer &	minimizer
	)

Given a BVH, runs the query encapsulated by minimizer.

Returns:

the minimum value. The Minimizer type must provide the following members:

     typedef Scalar //the numeric type of what is being minimized--not necessarily the Scalar type of the BVH (if it has one)
     Scalar minimumOnVolume(const BVH::Volume &volume)
     Scalar minimumOnObject(const BVH::Object &object)

Definition at line 219 of file BVAlgorithms.h.

template<typename BVH1 , typename BVH2 , typename Minimizer >

Minimizer::Scalar Eigen::BVMinimize	(	const BVH1 &	tree1,
		const BVH2 &	tree2,
		Minimizer &	minimizer
	)

Given two BVH's, runs the query on their cartesian product encapsulated by minimizer.

Returns:

the minimum value. The Minimizer type must provide the following members:

     typedef Scalar //the numeric type of what is being minimized--not necessarily the Scalar type of the BVH (if it has one)
     Scalar minimumOnVolumeVolume(const BVH1::Volume &v1, const BVH2::Volume &v2)
     Scalar minimumOnVolumeObject(const BVH1::Volume &v1, const BVH2::Object &o2)
     Scalar minimumOnObjectVolume(const BVH1::Object &o1, const BVH2::Volume &v2)
     Scalar minimumOnObjectObject(const BVH1::Object &o1, const BVH2::Object &o2)

Definition at line 235 of file BVAlgorithms.h.

template<typename Polynomial >

NumTraits<typename Polynomial::Scalar>::Real Eigen::cauchy_max_bound ( const Polynomial & poly ) [inline]

Returns:: a maximum bound for the absolute value of any root of the polynomial.

Parameters:

[in] poly : the vector of coefficients of the polynomial ordered by degrees i.e. poly[i] is the coefficient of degree i of the polynomial e.g. is stored as a vector .

Precondition: the leading coefficient of the input polynomial poly must be non zero

Definition at line 75 of file PolynomialUtils.h.

template<typename Polynomial >

NumTraits<typename Polynomial::Scalar>::Real Eigen::cauchy_min_bound ( const Polynomial & poly ) [inline]

Returns:: a minimum bound for the absolute value of any non zero root of the polynomial.

Parameters:

[in] poly : the vector of coefficients of the polynomial ordered by degrees i.e. poly[i] is the coefficient of degree i of the polynomial e.g. is stored as a vector .

Definition at line 97 of file PolynomialUtils.h.

template<typename Scalar >

std::complex<Scalar> Eigen::cdiv	(	Scalar	xr,
		Scalar	xi,
		Scalar	yr,
		Scalar	yi
	)

Definition at line 396 of file EigenSolver.h.

template<typename PointArrayType , typename KnotVectorType >

void Eigen::ChordLengths	(	const PointArrayType &	pts,
		KnotVectorType &	chord_lengths
	)

Computes chord length parameters which are required for spline interpolation.

Parameters:

[in]	pts	The data points to which a spline should be fit.
[out]	chord_lengths	The resulting chord lenggth vector.

See also:: Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data

Definition at line 64 of file SplineFitting.h.

template<typename DerType >

const AutoDiffScalar<DerType>& Eigen::conj ( const AutoDiffScalar< DerType > & x ) [inline]

Definition at line 521 of file AutoDiffScalar.h.

template<typename SplineType , typename DerivativeType >

void Eigen::derivativesImpl	(	const SplineType &	spline,
		typename SplineType::Scalar	u,
		DenseIndex	order,
		DerivativeType &	der
	)

Definition at line 277 of file Spline.h.

template<typename T >

NumTraits<T>::Real Eigen::ei_abs ( const T & x ) [inline]

Definition at line 18 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

NumTraits<T>::Real Eigen::ei_abs2 ( const T & x ) [inline]

Definition at line 19 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

void Eigen::ei_aligned_delete	(	T *	ptr,
		size_t	size
	)		`[inline]`

Definition at line 38 of file Eigen2Support/Memory.h.

void Eigen::ei_aligned_free ( void * ptr ) [inline]

Definition at line 16 of file Eigen2Support/Memory.h.

void* Eigen::ei_aligned_malloc ( size_t size ) [inline]

Definition at line 15 of file Eigen2Support/Memory.h.

template<typename T >

T* Eigen::ei_aligned_new ( size_t size ) [inline]

Definition at line 34 of file Eigen2Support/Memory.h.

void* Eigen::ei_aligned_realloc	(	void *	ptr,
		size_t	new_size,
		size_t	old_size
	)		`[inline]`

Definition at line 17 of file Eigen2Support/Memory.h.

template<typename T >

T Eigen::ei_atan2	(	const T &	x,
		const T &	y
	)		`[inline]`

Definition at line 25 of file src/Eigen2Support/MathFunctions.h.

template<bool Align>

void Eigen::ei_conditional_aligned_free ( void * ptr ) [inline]

Definition at line 25 of file Eigen2Support/Memory.h.

template<bool Align>

void* Eigen::ei_conditional_aligned_malloc ( size_t size ) [inline]

Definition at line 21 of file Eigen2Support/Memory.h.

template<bool Align>

void* Eigen::ei_conditional_aligned_realloc	(	void *	ptr,
		size_t	new_size,
		size_t	old_size
	)		`[inline]`

Definition at line 29 of file Eigen2Support/Memory.h.

template<typename T >

T Eigen::ei_conj ( const T & x ) [inline]

Definition at line 17 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_cos ( const T & x ) [inline]

Definition at line 24 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_exp ( const T & x ) [inline]

Definition at line 21 of file src/Eigen2Support/MathFunctions.h.

void Eigen::ei_handmade_aligned_free ( void * ptr ) [inline]

Definition at line 19 of file Eigen2Support/Memory.h.

void* Eigen::ei_handmade_aligned_malloc ( size_t size ) [inline]

Definition at line 18 of file Eigen2Support/Memory.h.

template<typename T >

NumTraits<T>::Real Eigen::ei_imag ( const T & x ) [inline]

Definition at line 16 of file src/Eigen2Support/MathFunctions.h.

template<typename Scalar >

bool Eigen::ei_isApprox	(	const Scalar &	x,
		const Scalar &	y,
		typename NumTraits< Scalar >::Real	precision = `NumTraits<Scalar>::dummy_precision()`
	)		`[inline]`

Definition at line 42 of file src/Eigen2Support/MathFunctions.h.

template<typename Scalar >

bool Eigen::ei_isApproxOrLessThan	(	const Scalar &	x,
		const Scalar &	y,
		typename NumTraits< Scalar >::Real	precision = `NumTraits<Scalar>::dummy_precision()`
	)		`[inline]`

Definition at line 49 of file src/Eigen2Support/MathFunctions.h.

template<typename Scalar , typename OtherScalar >

bool Eigen::ei_isMuchSmallerThan	(	const Scalar &	x,
		const OtherScalar &	y,
		typename NumTraits< Scalar >::Real	precision = `NumTraits<Scalar>::dummy_precision()`
	)		`[inline]`

Definition at line 35 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_log ( const T & x ) [inline]

Definition at line 22 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_pow	(	const T &	x,
		const T &	y
	)		`[inline]`

Definition at line 26 of file src/Eigen2Support/MathFunctions.h.

template<typename Scalar >

Quaternion<Scalar> Eigen::ei_quaternion_product	(	const Quaternion< Scalar > &	a,
		const Quaternion< Scalar > &	b
	)		`[inline]`

Definition at line 215 of file Eigen2Support/Geometry/Quaternion.h.

template<typename T >

T Eigen::ei_random ( ) [inline]

Definition at line 27 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_random	(	const T &	x,
		const T &	y
	)		`[inline]`

Definition at line 28 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

NumTraits<T>::Real Eigen::ei_real ( const T & x ) [inline]

Definition at line 15 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_sin ( const T & x ) [inline]

Definition at line 23 of file src/Eigen2Support/MathFunctions.h.

template<typename T >

T Eigen::ei_sqrt ( const T & x ) [inline]

Definition at line 20 of file src/Eigen2Support/MathFunctions.h.

template<typename Scalar , int Dim>

static Matrix<Scalar,2,2> Eigen::ei_toRotationMatrix ( const Scalar & s ) [inline, static]

Definition at line 103 of file Eigen2Support/Geometry/RotationBase.h.

template<typename Scalar , int Dim, typename OtherDerived >

static Matrix<Scalar,Dim,Dim> Eigen::ei_toRotationMatrix ( const RotationBase< OtherDerived, Dim > & r ) [inline, static]

Definition at line 110 of file Eigen2Support/Geometry/RotationBase.h.

template<typename Scalar , int Dim, typename OtherDerived >

static const MatrixBase<OtherDerived>& Eigen::ei_toRotationMatrix ( const MatrixBase< OtherDerived > & mat ) [inline, static]

Definition at line 116 of file Eigen2Support/Geometry/RotationBase.h.

Eigen::EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY	(	tan	,
		using std::tan;using std::cos;return ReturnType(tan(x.value()), x.derivatives()*(Scalar(1)/internal::abs2(cos(x.value()))));
	)

Eigen::EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY	(	acos	,
		using std::sqrt;using std::acos;return ReturnType(acos(x.value()), x.derivatives()*(Scalar(-1)/sqrt(1-internal::abs2(x.value()))));
	)

Definition at line 612 of file AutoDiffScalar.h.

template<typename OtherDerived >

EIGEN_STRONG_INLINE const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( internal::scalar_quotient_op )

Deprecated:: ArrayBase::operator/()

Definition at line 64 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::less ) [inline]

Deprecated:: ArrayBase::operator<()

Definition at line 157 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::less_equal ) [inline]

Deprecated:: ArrayBase::<=()

Definition at line 166 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::greater ) [inline]

Deprecated:: ArrayBase::operator>()

Definition at line 175 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::greater_equal ) [inline]

Deprecated:: ArrayBase::operator>=()

Definition at line 184 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::equal_to ) [inline]

Deprecated:: ArrayBase::operator==()

Definition at line 193 of file CwiseOperators.h.

template<typename OtherDerived >

const Eigen::EIGEN_CWISE_BINOP_RETURN_TYPE ( std::not_equal_to ) [inline]

Deprecated:: ArrayBase::operator!=()

Definition at line 202 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::less ) [inline]

Deprecated:: ArrayBase::operator<(Scalar)

Definition at line 212 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::less_equal ) [inline]

Deprecated:: ArrayBase::operator<=(Scalar)

Definition at line 221 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::greater ) [inline]

Deprecated:: ArrayBase::operator>(Scalar)

Definition at line 230 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::greater_equal ) [inline]

Deprecated:: ArrayBase::operator>=(Scalar)

Definition at line 239 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::equal_to ) [inline]

Deprecated:: ArrayBase::operator==(Scalar)

Definition at line 248 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE ( std::not_equal_to ) [inline]

Deprecated:: ArrayBase::operator!=(Scalar)

Definition at line 257 of file CwiseOperators.h.

template<typename OtherDerived >

EIGEN_STRONG_INLINE const Eigen::EIGEN_CWISE_PRODUCT_RETURN_TYPE	(	ExpressionType	,
		OtherDerived
	)

Deprecated:: ArrayBase::operator*()

Definition at line 55 of file CwiseOperators.h.

template<typename ExpressionType >

EIGEN_STRONG_INLINE const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_abs_op )

Deprecated:: ArrayBase::abs()

Definition at line 22 of file CwiseOperators.h.

template<typename ExpressionType >

EIGEN_STRONG_INLINE const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_abs2_op )

Deprecated:: ArrayBase::abs2()

Definition at line 30 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_exp_op ) [inline]

Deprecated:: ArrayBase::exp()

Definition at line 38 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_log_op ) [inline]

Deprecated:: ArrayBase::log()

Definition at line 46 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_sqrt_op ) [inline]

Deprecated:: ArrayBase::sqrt()

Definition at line 94 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_cos_op ) [inline]

Deprecated:: ArrayBase::cos()

Definition at line 102 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_sin_op ) [inline]

Deprecated:: ArrayBase::sin()

Definition at line 111 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_pow_op ) [inline]

Deprecated:: ArrayBase::log()

Definition at line 120 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_inverse_op ) [inline]

Deprecated:: ArrayBase::inverse()

Definition at line 129 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_square_op ) [inline]

Deprecated:: ArrayBase::square()

Definition at line 137 of file CwiseOperators.h.

template<typename ExpressionType >

const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_cube_op ) [inline]

Deprecated:: ArrayBase::cube()

Definition at line 145 of file CwiseOperators.h.

template<typename VectorType , typename HyperplaneType >

void Eigen::fitHyperplane	(	int	numPoints,
		VectorType **	points,
		HyperplaneType *	result,
		typename NumTraits< typename VectorType::Scalar >::Real *	soundness = `0`
	)

This function is quite similar to linearRegression(), so we refer to the documentation of this function and only list here the differences.

The main difference from linearRegression() is that this function doesn't take a funcOfOthers argument. Instead, it finds a general equation of the form

$r_0 x_0 + \cdots + r_{n-1}x_{n-1} + r_n = 0,$

where $n=Size$ , $r_i=retCoefficients[i]$ , and we denote by $x_0,\ldots,x_{n-1}$ the n coordinates in the n-dimensional space.

Thus, the vector retCoefficients has size $n+1$ , which is another difference from linearRegression().

In practice, this function performs an hyper-plane fit in a total least square sense via the following steps: 1 - center the data to the mean 2 - compute the covariance matrix 3 - pick the eigenvector corresponding to the smallest eigenvalue of the covariance matrix The ratio of the smallest eigenvalue and the second one gives us a hint about the relevance of the solution. This value is optionally returned in soundness.

See also:: linearRegression()

Definition at line 130 of file LeastSquares.h.

bool Eigen::getMarketHeader	(	const std::string &	filename,
		int &	sym,
		bool &	iscomplex,
		bool &	isvector
	)		`[inline]`

Definition at line 109 of file MarketIO.h.

template<typename VectorsType , typename CoeffsType >

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

Convenience function for constructing a Householder sequence.

\

Returns:: A HouseholderSequence constructed from the specified arguments.

Definition at line 422 of file HouseholderSequence.h.

template<typename DerType >

DerType::Scalar Eigen::imag ( const AutoDiffScalar< DerType > & ) [inline]

Definition at line 525 of file AutoDiffScalar.h.

void Eigen::initParallel ( ) [inline]

Must be call first when calling Eigen from multiple threads

Definition at line 48 of file Parallelizer.h.

template<typename KnotVectorType >

void Eigen::KnotAveraging	(	const KnotVectorType &	parameters,
		DenseIndex	degree,
		KnotVectorType &	knots
	)

Computes knot averages.The knots are computed as

$\begin{align*} u_0 & = \hdots = u_p = 0 \\ u_{m-p} & = \hdots = u_{m} = 1 \\ u_{j+p} & = \frac{1}{p}\sum_{i=j}^{j+p-1}\bar{u}_i \quad\quad j=1,\hdots,n-p \end{align*}$

where $p$ is the degree and $m+1$ the number knots of the desired interpolating spline.

Parameters:

[in]	parameters	The input parameters. During interpolation one for each data point.
[in]	degree	The spline degree which is used during the interpolation.
[out]	knots	The output knot vector.

See also:: Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data

Definition at line 41 of file SplineFitting.h.

template<typename A , typename B , typename CScalar , int CRows, int CCols, int COptions, int CMaxRows, int CMaxCols>

void Eigen::kroneckerProduct	(	const MatrixBase< A > &	a,
		const MatrixBase< B > &	b,
		Matrix< CScalar, CRows, CCols, COptions, CMaxRows, CMaxCols > &	c
	)

Computes Kronecker tensor product of two dense matrices

Parameters:

a	Dense matrix a
b	Dense matrix b
c	Kronecker tensor product of a and b

Definition at line 91 of file KroneckerTensorProduct.h.

template<typename A , typename B , typename C >

void Eigen::kroneckerProduct	(	const MatrixBase< A > &	a,
		const MatrixBase< B > &	b,
		MatrixBase< C > const &	c_
	)

Computes Kronecker tensor product of two dense matrices

Remark: this function uses the const cast hack and has been implemented to make the function call possible, where the output matrix is a submatrix, e.g. kroneckerProduct(A,B,AB.block(2,5,6,6));

Parameters:

a	Dense matrix a
b	Dense matrix b
c	Kronecker tensor product of a and b

Definition at line 110 of file KroneckerTensorProduct.h.

template<typename A , typename B , typename C >

void Eigen::kroneckerProduct	(	const MatrixBase< A > &	a,
		const SparseMatrixBase< B > &	b,
		SparseMatrixBase< C > &	c
	)

Computes Kronecker tensor product of a dense and a sparse matrix

Parameters:

a	Dense matrix a
b	Sparse matrix b
c	Kronecker tensor product of a and b

Definition at line 124 of file KroneckerTensorProduct.h.

template<typename A , typename B , typename C >

void Eigen::kroneckerProduct	(	const SparseMatrixBase< A > &	a,
		const MatrixBase< B > &	b,
		SparseMatrixBase< C > &	c
	)

Computes Kronecker tensor product of a sparse and a dense matrix

Parameters:

a	Sparse matrix a
b	Dense matrix b
c	Kronecker tensor product of a and b

Definition at line 137 of file KroneckerTensorProduct.h.

template<typename A , typename B , typename C >

void Eigen::kroneckerProduct	(	const SparseMatrixBase< A > &	a,
		const SparseMatrixBase< B > &	b,
		SparseMatrixBase< C > &	c
	)

Computes Kronecker tensor product of two sparse matrices

Parameters:

a	Sparse matrix a
b	Sparse matrix b
c	Kronecker tensor product of a and b

Definition at line 150 of file KroneckerTensorProduct.h.

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

Definition at line 1291 of file GeneralBlockPanelKernel.h.

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

Definition at line 1300 of file GeneralBlockPanelKernel.h.

template<typename VectorType >

void Eigen::linearRegression	(	int	numPoints,
		VectorType **	points,
		VectorType *	result,
		int	funcOfOthers
	)

For a set of points, this function tries to express one of the coords as a linear (affine) function of the other coords.

This is best explained by an example. This function works in full generality, for points in a space of arbitrary dimension, and also over the complex numbers, but for this example we will work in dimension 3 over the real numbers (doubles).

So let us work with the following set of 5 points given by their $(x,y,z)$ coordinates:

    Vector3d points[5];
    points[0] = Vector3d( 3.02, 6.89, -4.32 );
    points[1] = Vector3d( 2.01, 5.39, -3.79 );
    points[2] = Vector3d( 2.41, 6.01, -4.01 );
    points[3] = Vector3d( 2.09, 5.55, -3.86 );
    points[4] = Vector3d( 2.58, 6.32, -4.10 );

Suppose that we want to express the second coordinate ( $y$ ) as a linear expression in $x$ and $z$ , that is,

$y=ax+bz+c$

for some constants $a,b,c$ . Thus, we want to find the best possible constants $a,b,c$ so that the plane of equation $y=ax+bz+c$ fits best the five above points. To do that, call this function as follows:

    Vector3d coeffs; // will store the coefficients a, b, c
    linearRegression(
      5,
      &points,
      &coeffs,
      1 // the coord to express as a function of
        // the other ones. 0 means x, 1 means y, 2 means z.
    );

Now the vector coeffs is approximately $( 0.495 , -1.927 , -2.906 )$ . Thus, we get $a=0.495, b = -1.927, c = -2.906$ . Let us check for instance how near points[0] is from the plane of equation $y=ax+bz+c$ . Looking at the coords of points[0], we see that:

$ax+bz+c = 0.495 * 3.02 + (-1.927) * (-4.32) + (-2.906) = 6.91.$

On the other hand, we have $y=6.89$ . We see that the values $6.91$ and $6.89$ are near, so points[0] is very near the plane of equation $y=ax+bz+c$ .

Let's now describe precisely the parameters:

Parameters:

numPoints	the number of points
points	the array of pointers to the points on which to perform the linear regression
result	pointer to the vector in which to store the result. This vector must be of the same type and size as the data points. The meaning of its coords is as follows. For brevity, let , , and . Denote by $x_0,\ldots,x_{n-1}$ the n coordinates in the n-dimensional space. Then the resulting equation is: $x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1} + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n.$
funcOfOthers	Determines which coord to express as a function of the others. Coords are numbered starting from 0, so that a value of 0 means , 1 means , 2 means , ...

See also:: fitHyperplane()

Definition at line 85 of file LeastSquares.h.

template<typename SparseMatrixType >

bool Eigen::loadMarket	(	SparseMatrixType &	mat,
		const std::string &	filename
	)

Definition at line 133 of file MarketIO.h.

template<typename VectorType >

bool Eigen::loadMarketVector	(	VectorType &	vec,
		const std::string &	filename
	)

Definition at line 192 of file MarketIO.h.

template<typename T >

T Eigen::machine_epsilon ( ) [inline]

Definition at line 31 of file src/Eigen2Support/MathFunctions.h.

int Eigen::nbThreads ( ) [inline]

Returns:: the max number of threads reserved for Eigen

See also:: setNbThreads

Definition at line 58 of file Parallelizer.h.

template<typename SparseDerived , typename PermDerived >

const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false> Eigen::operator*	(	const SparseMatrixBase< SparseDerived > &	matrix,
		const PermutationBase< PermDerived > &	perm
	)		`[inline]`

Returns:: the matrix with the permutation applied to the columns

Definition at line 112 of file SparsePermutation.h.

template<typename SparseDerived , typename PermDerived >

const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false> Eigen::operator*	(	const PermutationBase< PermDerived > &	perm,
		const SparseMatrixBase< SparseDerived > &	matrix
	)		`[inline]`

Returns:: the matrix with the permutation applied to the rows

Definition at line 121 of file SparsePermutation.h.

template<typename SparseDerived , typename PermDerived >

const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true> Eigen::operator*	(	const SparseMatrixBase< SparseDerived > &	matrix,
		const Transpose< PermutationBase< PermDerived > > &	tperm
	)		`[inline]`

Returns:: the matrix with the inverse permutation applied to the columns.

Definition at line 132 of file SparsePermutation.h.

template<typename SparseDerived , typename PermDerived >

const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true> Eigen::operator*	(	const Transpose< PermutationBase< PermDerived > > &	tperm,
		const SparseMatrixBase< SparseDerived > &	matrix
	)		`[inline]`

Returns:: the matrix with the inverse permutation applied to the rows.

Definition at line 141 of file SparsePermutation.h.

template<typename Derived , typename Lhs , typename Rhs >

const ScaledProduct<Derived> Eigen::operator*	(	const ProductBase< Derived, Lhs, Rhs > &	prod,
		typename Derived::Scalar	x
	)

Definition at line 198 of file ProductBase.h.

template<typename Derived , typename Lhs , typename Rhs >

internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value, const ScaledProduct<Derived> >::type Eigen::operator*	(	const ProductBase< Derived, Lhs, Rhs > &	prod,
		typename Derived::RealScalar	x
	)

Definition at line 204 of file ProductBase.h.

template<typename Derived , typename Lhs , typename Rhs >

const ScaledProduct<Derived> Eigen::operator*	(	typename Derived::Scalar	x,
		const ProductBase< Derived, Lhs, Rhs > &	prod
	)

Definition at line 210 of file ProductBase.h.

template<typename Derived , typename Lhs , typename Rhs >

internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value, const ScaledProduct<Derived> >::type Eigen::operator*	(	typename Derived::RealScalar	x,
		const ProductBase< Derived, Lhs, Rhs > &	prod
	)

Definition at line 216 of file ProductBase.h.

template<typename Derived , typename TranspositionsDerived >

const internal::transposition_matrix_product_retval<TranspositionsDerived, Derived, OnTheRight> Eigen::operator*	(	const MatrixBase< Derived > &	matrix,
		const TranspositionsBase< TranspositionsDerived > &	transpositions
	)		`[inline]`

Returns:: the matrix with the transpositions applied to the columns.

Definition at line 331 of file Transpositions.h.

template<typename Derived , typename TranspositionDerived >

const internal::transposition_matrix_product_retval<TranspositionDerived, Derived, OnTheLeft> Eigen::operator*	(	const TranspositionsBase< TranspositionDerived > &	transpositions,
		const MatrixBase< Derived > &	matrix
	)		`[inline]`

Returns:: the matrix with the transpositions applied to the rows.

Definition at line 344 of file Transpositions.h.

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

internal::matrix_type_times_scalar_type<typename VectorsType::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.

Definition at line 409 of file HouseholderSequence.h.

template<typename Derived , typename PermutationDerived >

const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheRight> Eigen::operator*	(	const MatrixBase< Derived > &	matrix,
		const PermutationBase< PermutationDerived > &	permutation
	)		`[inline]`

Returns:: the matrix with the permutation applied to the columns.

Definition at line 510 of file PermutationMatrix.h.

template<typename Derived , typename PermutationDerived >

const internal::permut_matrix_product_retval<PermutationDerived, Derived, OnTheLeft> Eigen::operator*	(	const PermutationBase< PermutationDerived > &	permutation,
		const MatrixBase< Derived > &	matrix
	)		`[inline]`

Returns:: the matrix with the permutation applied to the rows.

Definition at line 523 of file PermutationMatrix.h.

template<typename Derived >

const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived> Eigen::operator/	(	typename Derived::Scalar	s,
		const Eigen::ArrayBase< Derived > &	a
	)		`[inline]`

Component-wise division of a scalar by array elements.

Definition at line 76 of file GlobalFunctions.h.

template<typename Polynomials , typename T >

T Eigen::poly_eval	(	const Polynomials &	poly,
		const T &	x
	)		`[inline]`

Returns:: the evaluation of the polynomial at x using stabilized Horner algorithm.

Parameters:

[in]	poly	: the vector of coefficients of the polynomial ordered by degrees i.e. poly[i] is the coefficient of degree i of the polynomial e.g. is stored as a vector .
[in]	x	: the value to evaluate the polynomial at.

Definition at line 46 of file PolynomialUtils.h.

template<typename Polynomials , typename T >

T Eigen::poly_eval_horner	(	const Polynomials &	poly,
		const T &	x
	)		`[inline]`

Returns:: the evaluation of the polynomial at x using Horner algorithm.

Parameters:

[in]	poly	: the vector of coefficients of the polynomial ordered by degrees i.e. poly[i] is the coefficient of degree i of the polynomial e.g. is stored as a vector .
[in]	x	: the value to evaluate the polynomial at.

Note for stability: $|x| \le 1$

Definition at line 28 of file PolynomialUtils.h.

const DerType Eigen::pow	(	const Eigen::AutoDiffScalar< DerType > &	x,
		typename Eigen::internal::traits< DerType >::Scalar	y
	)

Definition at line 571 of file AutoDiffScalar.h.

template<typename T >

T Eigen::precision ( ) [inline]

Definition at line 30 of file src/Eigen2Support/MathFunctions.h.

template<typename DerType >

const AutoDiffScalar<DerType>& Eigen::real ( const AutoDiffScalar< DerType > & x ) [inline]

Definition at line 523 of file AutoDiffScalar.h.

return Eigen::ReturnType	(	asin(x.value())	,
		x.	derivatives)*(Scalar(1)/sqrt(1-internal::abs2(x.value()))
	)

template<typename VectorsType , typename CoeffsType >

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

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.

Definition at line 434 of file HouseholderSequence.h.

template<typename RootVector , typename Polynomial >

void Eigen::roots_to_monicPolynomial	(	const RootVector &	rv,
		Polynomial &	poly
	)

Given the roots of a polynomial compute the coefficients in the monomial basis of the monic polynomial with same roots and minimal degree. If RootVector is a vector of complexes, Polynomial should also be a vector of complexes.

Parameters:

[in]	rv	: a vector containing the roots of a polynomial.
[out]	poly	: the vector of coefficients of the polynomial ordered by degrees i.e. poly[i] is the coefficient of degree i of the polynomial e.g. is stored as a vector .

Definition at line 125 of file PolynomialUtils.h.

template<typename SparseMatrixType >

bool Eigen::saveMarket	(	const SparseMatrixType &	mat,
		const std::string &	filename,
		int	sym = `0`
	)

Definition at line 224 of file MarketIO.h.

template<typename VectorType >

bool Eigen::saveMarketVector	(	const VectorType &	vec,
		const std::string &	filename
	)

Definition at line 250 of file MarketIO.h.

static UniformScaling<float> Eigen::Scaling ( float s ) [inline, static]

Constructs a uniform scaling from scale factor s

Definition at line 115 of file src/Geometry/Scaling.h.

static UniformScaling<double> Eigen::Scaling ( double s ) [inline, static]

Constructs a uniform scaling from scale factor s

Definition at line 117 of file src/Geometry/Scaling.h.

template<typename RealScalar >

static UniformScaling<std::complex<RealScalar> > Eigen::Scaling ( const std::complex< RealScalar > & s ) [inline, static]

Constructs a uniform scaling from scale factor s

Definition at line 120 of file src/Geometry/Scaling.h.

template<typename Scalar >

static DiagonalMatrix<Scalar,2> Eigen::Scaling	(	Scalar	sx,
		Scalar	sy
	)		`[inline, static]`

Constructs a 2D axis aligned scaling

Definition at line 125 of file src/Geometry/Scaling.h.

template<typename Scalar >

static DiagonalMatrix<Scalar,3> Eigen::Scaling	(	Scalar	sx,
		Scalar	sy,
		Scalar	sz
	)		`[inline, static]`

Constructs a 3D axis aligned scaling

Definition at line 129 of file src/Geometry/Scaling.h.

template<typename Derived >

static const DiagonalWrapper<const Derived> Eigen::Scaling ( const MatrixBase< Derived > & coeffs ) [inline, static]

Constructs an axis aligned scaling expression from vector expression coeffs This is an alias for coeffs.asDiagonal()

Definition at line 136 of file src/Geometry/Scaling.h.

void Eigen::setCpuCacheSizes	(	std::ptrdiff_t	l1,
		std::ptrdiff_t	l2
	)		`[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

Definition at line 1312 of file GeneralBlockPanelKernel.h.

void Eigen::setNbThreads ( int v ) [inline]

Sets the max number of threads reserved for Eigen

See also:: nbThreads

Definition at line 67 of file Parallelizer.h.

void Eigen::umfpack_free_numeric	(	void **	Numeric,
		double
	)		`[inline]`

Definition at line 19 of file UmfPackSupport.h.

void Eigen::umfpack_free_numeric	(	void **	Numeric,
		std::complex< double >
	)		`[inline]`

Definition at line 22 of file UmfPackSupport.h.

void Eigen::umfpack_free_symbolic	(	void **	Symbolic,
		double
	)		`[inline]`

Definition at line 25 of file UmfPackSupport.h.

void Eigen::umfpack_free_symbolic	(	void **	Symbolic,
		std::complex< double >
	)		`[inline]`

Definition at line 28 of file UmfPackSupport.h.

int Eigen::umfpack_get_determinant	(	double *	Mx,
		double *	Ex,
		void *	NumericHandle,
		double	User_Info[UMFPACK_INFO]
	)		`[inline]`

Definition at line 99 of file UmfPackSupport.h.

int Eigen::umfpack_get_determinant	(	std::complex< double > *	Mx,
		double *	Ex,
		void *	NumericHandle,
		double	User_Info[UMFPACK_INFO]
	)		`[inline]`

Definition at line 104 of file UmfPackSupport.h.

int Eigen::umfpack_get_lunz	(	int *	lnz,
		int *	unz,
		int *	n_row,
		int *	n_col,
		int *	nz_udiag,
		void *	Numeric,
		double
	)		`[inline]`

Definition at line 73 of file UmfPackSupport.h.

int Eigen::umfpack_get_lunz	(	int *	lnz,
		int *	unz,
		int *	n_row,
		int *	n_col,
		int *	nz_udiag,
		void *	Numeric,
		std::complex< double >
	)		`[inline]`

Definition at line 78 of file UmfPackSupport.h.

int Eigen::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
	)		`[inline]`

Definition at line 83 of file UmfPackSupport.h.

int Eigen::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
	)		`[inline]`

Definition at line 89 of file UmfPackSupport.h.

int Eigen::umfpack_numeric	(	const int	Ap[],
		const int	Ai[],
		const double	Ax[],
		void *	Symbolic,
		void **	Numeric,
		const double	Control[UMFPACK_CONTROL],
		double	Info[UMFPACK_INFO]
	)		`[inline]`

Definition at line 45 of file UmfPackSupport.h.

int Eigen::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]
	)		`[inline]`

Definition at line 52 of file UmfPackSupport.h.

int Eigen::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]
	)		`[inline]`

Definition at line 59 of file UmfPackSupport.h.

int Eigen::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]
	)		`[inline]`

Definition at line 66 of file UmfPackSupport.h.

int Eigen::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]
	)		`[inline]`

Definition at line 31 of file UmfPackSupport.h.

int Eigen::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]
	)		`[inline]`

Definition at line 38 of file UmfPackSupport.h.

template<typename _Scalar , int _Options, typename _Index >

cholmod_sparse Eigen::viewAsCholmod ( SparseMatrix< _Scalar, _Options, _Index > & mat )

Wraps the Eigen sparse matrix mat into a Cholmod sparse matrix object. Note that the data are shared.

Definition at line 52 of file CholmodSupport.h.

template<typename _Scalar , int _Options, typename _Index >

const cholmod_sparse Eigen::viewAsCholmod ( const SparseMatrix< _Scalar, _Options, _Index > & mat )

Definition at line 94 of file CholmodSupport.h.

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

cholmod_sparse Eigen::viewAsCholmod ( const SparseSelfAdjointView< 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.

Definition at line 103 of file CholmodSupport.h.

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.

Definition at line 116 of file CholmodSupport.h.

template<typename Scalar , int Flags, typename Index >

MappedSparseMatrix<Scalar,Flags,Index> 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.

Definition at line 137 of file CholmodSupport.h.

Variable Documentation

const unsigned int Eigen::ActualPacketAccessBit = 0x0

Definition at line 89 of file Constants.h.

const int Eigen::CoherentAccessPattern = 0x1

Definition at line 65 of file SparseUtil.h.

const int Eigen::Dynamic = -1

This value means that a quantity 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.

Definition at line 21 of file Constants.h.

const unsigned int Eigen::HereditaryBits

Initial value:

 RowMajorBit
                                  | EvalBeforeNestingBit
                                  | EvalBeforeAssigningBit

Definition at line 147 of file Constants.h.

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.

Definition at line 26 of file Constants.h.

const int Eigen::InnerRandomAccessPattern = 0x2 | CoherentAccessPattern

Definition at line 66 of file SparseUtil.h.

const unsigned int Eigen::LowerTriangular = Lower

Definition at line 21 of file Eigen2Support/TriangularSolver.h.

const unsigned int Eigen::LowerTriangularBit = Lower

Definition at line 18 of file Eigen2Support/TriangularSolver.h.

const unsigned int Eigen::NestByRefBit = 0x100

Definition at line 144 of file Constants.h.

const int Eigen::OuterRandomAccessPattern = 0x4 | CoherentAccessPattern

Definition at line 67 of file SparseUtil.h.

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