Namespaces | Classes | Typedefs | Enumerations | Functions | Variables
Eigen Namespace Reference

Namespaces

 Architecture
 
 internal
 
 numext
 

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  AMDOrdering
 
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  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< SparseMatrix< _Scalar, _Options, _Index >, BlockRows, BlockCols, true, Sparse >
 
class  BlockImpl< XprType, BlockRows, BlockCols, InnerPanel, Dense >
 
class  BlockImpl< XprType, BlockRows, BlockCols, InnerPanel, Sparse >
 
class  BlockImpl< XprType, BlockRows, BlockCols, true, Sparse >
 
class  CholmodBase
 The base class for the direct Cholesky factorization of Cholmod. More...
 
class  CholmodDecomposition
 A general Cholesky factorization and solver based on Cholmod. More...
 
class  CholmodSimplicialLDLT
 A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod. More...
 
class  CholmodSimplicialLLT
 A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod. More...
 
class  CholmodSupernodalLLT
 A supernodal Cholesky (LLT) factorization and solver based on Cholmod. More...
 
class  CoeffBasedProduct
 
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  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  Conjugate
 
class  ConjugateGradient
 A conjugate gradient solver for sparse self-adjoint problems. More...
 
class  Cross
 
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
 
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
 
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
 
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
 
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
 
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
 
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
 
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...
 
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
 Computes the generalized eigenvalues and eigenvectors of a pair of general matrices. More...
 
class  GeneralizedSelfAdjointEigenSolver
 Computes eigenvalues and eigenvectors of the generalized selfadjoint eigen problem. More...
 
class  GeneralProduct
 Expression of the product of two general matrices or vectors. More...
 
class  GeneralProduct< Lhs, Rhs, GemmProduct >
 
class  GeneralProduct< Lhs, Rhs, GemvProduct >
 
class  GeneralProduct< Lhs, Rhs, InnerProduct >
 
class  GeneralProduct< Lhs, Rhs, OuterProduct >
 
struct  GenericNumTraits
 
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  Hyperplane
 A hyperplane. More...
 
class  IdentityPreconditioner
 A naive preconditioner which approximates any matrix as the identity matrix. More...
 
class  IncompleteLUT
 Incomplete LU factorization with dual-threshold strategy. 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  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...
 
struct  LazyProductReturnType
 
class  LDLT
 Robust Cholesky decomposition of a matrix with pivoting. 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
 Base class for Map and Block expression with direct access. More...
 
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...
 
struct  MatrixExponentialReturnValue
 
class  MatrixFunctionReturnValue
 
class  MatrixLogarithmReturnValue
 
class  MatrixPowerProduct
 
class  MatrixPowerReturnValue
 
class  MatrixSquareRootReturnValue
 
class  MatrixWrapper
 Expression of an array as a mathematical vector or matrix. More...
 
struct  MatrixXpr
 
class  MetisOrdering
 
class  Minor
 Expression of a minor. More...
 
class  NaturalOrdering
 
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. 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
 Interface to the PaStix solver. 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  PermutedImpl
 
class  PlainObjectBase
 Dense storage base class for matrices and arrays. 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  RealQZ
 Performs a real QZ decomposition of a pair of square matrices. More...
 
class  RealSchur
 Performs a real Schur decomposition of a square matrix. More...
 
class  Ref
 A matrix or vector expression mapping an existing expressions. More...
 
class  Ref< const TPlainObjectType, Options, StrideType >
 
class  RefBase
 
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
 
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
 Computes eigenvalues and eigenvectors of selfadjoint matrices. More...
 
struct  SelfadjointProductMatrix
 
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...
 
struct  SluMatrix
 
struct  SluMatrixMapHelper
 
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  SparseLU
 Sparse supernodal LU factorization for general matrices. More...
 
struct  SparseLUMatrixLReturnType
 
struct  SparseLUMatrixUReturnType
 
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 rank-revealing QR factorization. More...
 
struct  SparseQR_QProduct
 
struct  SparseQRMatrixQReturnType
 
struct  SparseQRMatrixQTransposeReturnType
 
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  SPQR
 Sparse QR factorization based on SuiteSparseQR library. More...
 
struct  SPQR_QProduct
 
struct  SPQRMatrixQReturnType
 
struct  SPQRMatrixQTransposeReturnType
 
class  Stride
 Holds strides information for Map. More...
 
class  SuperLU
 A sparse direct LU factorization and solver based on the SuperLU library. More...
 
class  SuperLUBase
 The base class for the direct and incomplete LU factorization of SuperLU. More...
 
class  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
 
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
 
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, AffineAffine2d
 
typedef Transform< float, 2, AffineAffine2f
 
typedef Transform< double, 3, AffineAffine3d
 
typedef Transform< float, 3, AffineAffine3f
 
typedef Transform< double, 2, AffineCompactAffineCompact2d
 
typedef Transform< float, 2, AffineCompactAffineCompact2f
 
typedef Transform< double, 3, AffineCompactAffineCompact3d
 
typedef Transform< float, 3, AffineCompactAffineCompact3f
 
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, IsometryIsometry2d
 
typedef Transform< float, 2, IsometryIsometry2f
 
typedef Transform< double, 3, IsometryIsometry3d
 
typedef Transform< float, 3, IsometryIsometry3f
 
typedef Transform< double, 2, ProjectiveProjective2d
 
typedef Transform< float, 2, ProjectiveProjective2f
 
typedef Transform< double, 3, ProjectiveProjective3d
 
typedef Transform< float, 3, ProjectiveProjective3f
 
typedef Quaternion< double > Quaterniond
 
typedef Quaternion< float > Quaternionf
 
typedef Map< Quaternion< double >, AlignedQuaternionMapAlignedd
 
typedef Map< Quaternion< float >, AlignedQuaternionMapAlignedf
 
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 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, AllAtOnceTraversal
}
 
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  AccessorLevels { ReadOnlyAccessors, WriteAccessors, DirectAccessors, DirectWriteAccessors }
 
enum  Action { GetAction, SetAction }
 
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  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 Scalar >
std::complex< Scalar > cdiv (const Scalar &xr, const Scalar &xi, const Scalar &yr, const Scalar &yi)
 
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 >
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 >
ei_conj (const T &x)
 
template<typename T >
ei_cos (const T &x)
 
template<typename 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 >
ei_log (const T &x)
 
template<typename 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 >
ei_random ()
 
template<typename T >
ei_random (const T &x, const T &y)
 
template<typename T >
NumTraits< T >::Real ei_real (const T &x)
 
template<typename T >
ei_sin (const T &x)
 
template<typename 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)
 
template<typename ExpressionType >
EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_abs_op) Cwise< ExpressionType >
 
template<typename ExpressionType >
const EIGEN_CWISE_UNOP_RETURN_TYPE (internal::scalar_sqrt_op) Cwise< ExpressionType >
 
template<typename VectorType , typename HyperplaneType >
void fitHyperplane (int numPoints, VectorType **points, HyperplaneType *result, typename NumTraits< typename VectorType::Scalar >::Real *soundness=0)
 
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType > householderSequence (const VectorsType &v, const CoeffsType &h)
 Convenience function for constructing a Householder sequence. More...
 
void initParallel ()
 
std::ptrdiff_t l1CacheSize ()
 
std::ptrdiff_t l2CacheSize ()
 
template<typename VectorType >
void linearRegression (int numPoints, VectorType **points, VectorType *result, int funcOfOthers)
 
template<typename 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, const 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, const typename Derived::RealScalar &x)
 
template<typename Derived , typename Lhs , typename Rhs >
const ScaledProduct< Derived > operator* (const 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* (const typename Derived::RealScalar &x, const ProductBase< Derived, Lhs, Rhs > &prod)
 
template<typename Derived , typename TranspositionsDerived >
const internal::transposition_matrix_product_retval< TranspositionsDerived, Derived, OnTheRightoperator* (const MatrixBase< Derived > &matrix, const TranspositionsBase< TranspositionsDerived > &transpositions)
 
template<typename Derived , typename TranspositionDerived >
const internal::transposition_matrix_product_retval< TranspositionDerived, Derived, OnTheLeftoperator* (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. More...
 
template<typename Derived , typename PermutationDerived >
const internal::permut_matrix_product_retval< PermutationDerived, Derived, OnTheRightoperator* (const MatrixBase< Derived > &matrix, const PermutationBase< PermutationDerived > &permutation)
 
template<typename Derived , typename PermutationDerived >
const internal::permut_matrix_product_retval< PermutationDerived, Derived, OnTheLeftoperator* (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/ (const typename Derived::Scalar &s, const Eigen::ArrayBase< Derived > &a)
 Component-wise division of a scalar by array elements. More...
 
template<typename Derived >
const Eigen::CwiseUnaryOp< Eigen::internal::scalar_pow_op< typename Derived::Scalar >, const Derived > pow (const Eigen::ArrayBase< Derived > &x, const typename Derived::Scalar &exponent)
 
template<typename Derived >
const Eigen::CwiseBinaryOp< Eigen::internal::scalar_binary_pow_op< typename Derived::Scalar, typename Derived::Scalar >, const Derived, const Derived > pow (const Eigen::ArrayBase< Derived > &x, const Eigen::ArrayBase< Derived > &exponents)
 
template<typename T >
precision ()
 
template<typename VectorsType , typename CoeffsType >
HouseholderSequence< VectorsType, CoeffsType, OnTheRightrightHouseholderSequence (const VectorsType &v, const CoeffsType &h)
 Convenience function for constructing a Householder sequence. More...
 
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 (const Scalar &sx, const Scalar &sy)
 
template<typename Scalar >
static DiagonalMatrix< Scalar, 3 > Scaling (const Scalar &sx, const Scalar &sy, const 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. More...
 
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 int DynamicIndex = 0xffffff
 
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 UnitDiagBit = UnitDiag
 
const unsigned int UnitLowerTriangular = UnitLower
 
const unsigned int UnitUpperTriangular = UnitUpper
 
const unsigned int UpperTriangular = Upper
 
const unsigned int UpperTriangularBit = Upper
 

Typedef Documentation

◆ DenseIndex

Definition at line 27 of file XprHelper.h.

Enumeration Type Documentation

◆ anonymous enum

anonymous enum
Enumerator
Large 
Small 

Definition at line 38 of file GeneralProduct.h.

◆ anonymous enum

anonymous enum
Enumerator
DontAlignCols 

Definition at line 16 of file IO.h.

◆ anonymous enum

anonymous enum
Enumerator
StreamPrecision 
FullPrecision 

Definition at line 17 of file IO.h.

◆ anonymous enum

anonymous enum
Enumerator
DefaultTraversal 
LinearTraversal 
InnerVectorizedTraversal 
LinearVectorizedTraversal 
SliceVectorizedTraversal 
InvalidTraversal 
AllAtOnceTraversal 

Definition at line 220 of file Constants.h.

◆ anonymous enum

anonymous enum
Enumerator
NoUnrolling 
InnerUnrolling 
CompleteUnrolling 

Definition at line 242 of file Constants.h.

◆ anonymous enum

anonymous enum
Enumerator
Specialized 
BuiltIn 

Definition at line 254 of file Constants.h.

◆ anonymous enum

anonymous enum
Enumerator
IsDense 
IsSparse 

Definition at line 300 of file Constants.h.

◆ anonymous enum

anonymous enum
Enumerator
CoeffBasedProductMode 
LazyCoeffBasedProductMode 
OuterProduct 
InnerProduct 
GemvProduct 
GemmProduct 

Definition at line 421 of file Constants.h.

◆ Action

Enumerator
GetAction 
SetAction 

Definition at line 425 of file Constants.h.

◆ CholmodMode

Enumerator
CholmodAuto 
CholmodSimplicialLLt 
CholmodSupernodalLLt 
CholmodLDLt 

Definition at line 147 of file CholmodSupport.h.

◆ Default_t

Enumerator
Default 

Definition at line 296 of file Constants.h.

◆ NoChange_t

Enumerator
NoChange 

Definition at line 294 of file Constants.h.

◆ Sequential_t

Enumerator
Sequential 

Definition at line 295 of file Constants.h.

◆ SimplicialCholeskyMode

Enumerator
SimplicialCholeskyLLT 
SimplicialCholeskyLDLT 

Definition at line 15 of file SimplicialCholesky.h.

Function Documentation

◆ cdiv()

template<typename Scalar >
std::complex<Scalar> Eigen::cdiv ( const Scalar &  xr,
const Scalar &  xi,
const Scalar &  yr,
const Scalar &  yi 
)

Definition at line 413 of file EigenSolver.h.

◆ ei_abs()

template<typename T >
NumTraits<T>::Real Eigen::ei_abs ( const T &  x)
inline

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

◆ ei_abs2()

template<typename T >
NumTraits<T>::Real Eigen::ei_abs2 ( const T &  x)
inline

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

◆ ei_aligned_delete()

template<typename T >
void Eigen::ei_aligned_delete ( T *  ptr,
size_t  size 
)
inline

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

◆ ei_aligned_free()

void Eigen::ei_aligned_free ( void *  ptr)
inline

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

◆ ei_aligned_malloc()

void* Eigen::ei_aligned_malloc ( size_t  size)
inline

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

◆ ei_aligned_new()

template<typename T >
T* Eigen::ei_aligned_new ( size_t  size)
inline

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

◆ ei_aligned_realloc()

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.

◆ ei_atan2()

template<typename T >
T Eigen::ei_atan2 ( const T &  x,
const T &  y 
)
inline

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

◆ ei_conditional_aligned_free()

template<bool Align>
void Eigen::ei_conditional_aligned_free ( void *  ptr)
inline

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

◆ ei_conditional_aligned_malloc()

template<bool Align>
void* Eigen::ei_conditional_aligned_malloc ( size_t  size)
inline

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

◆ ei_conditional_aligned_realloc()

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.

◆ ei_conj()

template<typename T >
T Eigen::ei_conj ( const T &  x)
inline

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

◆ ei_cos()

template<typename T >
T Eigen::ei_cos ( const T &  x)
inline

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

◆ ei_exp()

template<typename T >
T Eigen::ei_exp ( const T &  x)
inline

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

◆ ei_handmade_aligned_free()

void Eigen::ei_handmade_aligned_free ( void *  ptr)
inline

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

◆ ei_handmade_aligned_malloc()

void* Eigen::ei_handmade_aligned_malloc ( size_t  size)
inline

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

◆ ei_imag()

template<typename T >
NumTraits<T>::Real Eigen::ei_imag ( const T &  x)
inline

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

◆ ei_isApprox()

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 Eigen2Support/MathFunctions.h.

◆ ei_isApproxOrLessThan()

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 Eigen2Support/MathFunctions.h.

◆ ei_isMuchSmallerThan()

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 Eigen2Support/MathFunctions.h.

◆ ei_log()

template<typename T >
T Eigen::ei_log ( const T &  x)
inline

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

◆ ei_pow()

template<typename T >
T Eigen::ei_pow ( const T &  x,
const T &  y 
)
inline

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

◆ ei_quaternion_product()

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.

◆ ei_random() [1/2]

template<typename T >
T Eigen::ei_random ( )
inline

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

◆ ei_random() [2/2]

template<typename T >
T Eigen::ei_random ( const T &  x,
const T &  y 
)
inline

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

◆ ei_real()

template<typename T >
NumTraits<T>::Real Eigen::ei_real ( const T &  x)
inline

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

◆ ei_sin()

template<typename T >
T Eigen::ei_sin ( const T &  x)
inline

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

◆ ei_sqrt()

template<typename T >
T Eigen::ei_sqrt ( const T &  x)
inline

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

◆ ei_toRotationMatrix() [1/3]

template<typename Scalar , int Dim>
static Matrix<Scalar,2,2> Eigen::ei_toRotationMatrix ( const Scalar &  s)
inlinestatic

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

◆ ei_toRotationMatrix() [2/3]

template<typename Scalar , int Dim, typename OtherDerived >
static Matrix<Scalar,Dim,Dim> Eigen::ei_toRotationMatrix ( const RotationBase< OtherDerived, Dim > &  r)
inlinestatic

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

◆ ei_toRotationMatrix() [3/3]

template<typename Scalar , int Dim, typename OtherDerived >
static const MatrixBase<OtherDerived>& Eigen::ei_toRotationMatrix ( const MatrixBase< OtherDerived > &  mat)
inlinestatic

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

◆ EIGEN_CWISE_UNOP_RETURN_TYPE() [1/2]

template<typename ExpressionType >
EIGEN_STRONG_INLINE const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_abs_op  )

◆ EIGEN_CWISE_UNOP_RETURN_TYPE() [2/2]

template<typename ExpressionType >
const Eigen::EIGEN_CWISE_UNOP_RETURN_TYPE ( internal::scalar_sqrt_op  )
inline
Deprecated:
ArrayBase::sqrt()
Deprecated:
ArrayBase::cos()
Deprecated:
ArrayBase::sin()
Deprecated:
ArrayBase::log()
Deprecated:
ArrayBase::inverse()
Deprecated:
ArrayBase::square()
Deprecated:
ArrayBase::cube()
Deprecated:
ArrayBase::operator<()
Deprecated:
ArrayBase::<=()
Deprecated:
ArrayBase::operator>()
Deprecated:
ArrayBase::operator>=()
Deprecated:
ArrayBase::operator==()
Deprecated:
ArrayBase::operator!=()
Deprecated:
ArrayBase::operator<(Scalar)
Deprecated:
ArrayBase::operator<=(Scalar)
Deprecated:
ArrayBase::operator>(Scalar)
Deprecated:
ArrayBase::operator>=(Scalar)
Deprecated:
ArrayBase::operator==(Scalar)
Deprecated:
ArrayBase::operator!=(Scalar)
Deprecated:
ArrayBase::operator+(Scalar)
Deprecated:
ArrayBase::operator+=(Scalar)

Definition at line 94 of file CwiseOperators.h.

◆ fitHyperplane()

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.

◆ householderSequence()

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.

◆ initParallel()

void Eigen::initParallel ( )
inline

Must be call first when calling Eigen from multiple threads

Definition at line 48 of file Parallelizer.h.

◆ 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

Definition at line 1307 of file GeneralBlockPanelKernel.h.

◆ 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

Definition at line 1316 of file GeneralBlockPanelKernel.h.

◆ linearRegression()

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
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
numPointsthe number of points
pointsthe array of pointers to the points on which to perform the linear regression
resultpointer 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 $n=Size$, $r_i=result[i]$, and $f=funcOfOthers$. Denote by $x_0,\ldots,x_{n-1}$ the n coordinates in the n-dimensional space. Then the resulting equation is:

\[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1} + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \]

funcOfOthersDetermines which coord to express as a function of the others. Coords are numbered starting from 0, so that a value of 0 means $x$, 1 means $y$, 2 means $z$, ...
See also
fitHyperplane()

Definition at line 85 of file LeastSquares.h.

◆ machine_epsilon()

template<typename T >
T Eigen::machine_epsilon ( )
inline

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

◆ nbThreads()

int Eigen::nbThreads ( )
inline
Returns
the max number of threads reserved for Eigen
See also
setNbThreads

Definition at line 58 of file Parallelizer.h.

◆ operator*() [1/13]

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.

◆ operator*() [2/13]

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.

◆ operator*() [3/13]

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.

◆ operator*() [4/13]

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.

◆ operator*() [5/13]

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

Definition at line 198 of file ProductBase.h.

◆ operator*() [6/13]

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,
const typename Derived::RealScalar &  x 
)

Definition at line 204 of file ProductBase.h.

◆ operator*() [7/13]

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

Definition at line 210 of file ProductBase.h.

◆ operator*() [8/13]

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 typename Derived::RealScalar &  x,
const ProductBase< Derived, Lhs, Rhs > &  prod 
)

Definition at line 216 of file ProductBase.h.

◆ operator*() [9/13]

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.

◆ operator*() [10/13]

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.

◆ operator*() [11/13]

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]otherMatrix being multiplied.
[in]hHouseholderSequence 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.

◆ operator*() [12/13]

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.

◆ operator*() [13/13]

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.

◆ operator/()

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

Component-wise division of a scalar by array elements.

Definition at line 74 of file GlobalFunctions.h.

◆ pow() [1/2]

template<typename Derived >
const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived> Eigen::pow ( const Eigen::ArrayBase< Derived > &  x,
const typename Derived::Scalar &  exponent 
)
inline

Definition at line 55 of file GlobalFunctions.h.

◆ pow() [2/2]

template<typename Derived >
const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived> Eigen::pow ( const Eigen::ArrayBase< Derived > &  x,
const Eigen::ArrayBase< Derived > &  exponents 
)
inline

Definition at line 61 of file GlobalFunctions.h.

◆ precision()

template<typename T >
T Eigen::precision ( )
inline

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

◆ rightHouseholderSequence()

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.

◆ Scaling() [1/6]

static UniformScaling<float> Eigen::Scaling ( float  s)
inlinestatic

Constructs a uniform scaling from scale factor s

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

◆ Scaling() [2/6]

static UniformScaling<double> Eigen::Scaling ( double  s)
inlinestatic

Constructs a uniform scaling from scale factor s

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

◆ Scaling() [3/6]

template<typename RealScalar >
static UniformScaling<std::complex<RealScalar> > Eigen::Scaling ( const std::complex< RealScalar > &  s)
inlinestatic

Constructs a uniform scaling from scale factor s

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

◆ Scaling() [4/6]

template<typename Scalar >
static DiagonalMatrix<Scalar,2> Eigen::Scaling ( const Scalar &  sx,
const Scalar &  sy 
)
inlinestatic

Constructs a 2D axis aligned scaling

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

◆ Scaling() [5/6]

template<typename Scalar >
static DiagonalMatrix<Scalar,3> Eigen::Scaling ( const Scalar &  sx,
const Scalar &  sy,
const Scalar &  sz 
)
inlinestatic

Constructs a 3D axis aligned scaling

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

◆ Scaling() [6/6]

template<typename Derived >
static const DiagonalWrapper<const Derived> Eigen::Scaling ( const MatrixBase< Derived > &  coeffs)
inlinestatic

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

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

◆ setCpuCacheSizes()

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 1328 of file GeneralBlockPanelKernel.h.

◆ setNbThreads()

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.

◆ umfpack_free_numeric() [1/2]

void Eigen::umfpack_free_numeric ( void **  Numeric,
double   
)
inline

Definition at line 19 of file UmfPackSupport.h.

◆ umfpack_free_numeric() [2/2]

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

Definition at line 22 of file UmfPackSupport.h.

◆ umfpack_free_symbolic() [1/2]

void Eigen::umfpack_free_symbolic ( void **  Symbolic,
double   
)
inline

Definition at line 25 of file UmfPackSupport.h.

◆ umfpack_free_symbolic() [2/2]

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

Definition at line 28 of file UmfPackSupport.h.

◆ umfpack_get_determinant() [1/2]

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.

◆ umfpack_get_determinant() [2/2]

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.

◆ umfpack_get_lunz() [1/2]

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.

◆ umfpack_get_lunz() [2/2]

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.

◆ umfpack_get_numeric() [1/2]

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.

◆ umfpack_get_numeric() [2/2]

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.

◆ umfpack_numeric() [1/2]

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.

◆ umfpack_numeric() [2/2]

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.

◆ umfpack_solve() [1/2]

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.

◆ umfpack_solve() [2/2]

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.

◆ umfpack_symbolic() [1/2]

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.

◆ umfpack_symbolic() [2/2]

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.

◆ viewAsCholmod() [1/4]

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.

◆ viewAsCholmod() [2/4]

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

Definition at line 97 of file CholmodSupport.h.

◆ viewAsCholmod() [3/4]

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 106 of file CholmodSupport.h.

◆ viewAsCholmod() [4/4]

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 119 of file CholmodSupport.h.

◆ viewAsEigen()

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 140 of file CholmodSupport.h.

Variable Documentation

◆ ActualPacketAccessBit

const unsigned int Eigen::ActualPacketAccessBit = 0x0

Definition at line 94 of file Constants.h.

◆ CoherentAccessPattern

const int Eigen::CoherentAccessPattern = 0x1

Definition at line 65 of file SparseUtil.h.

◆ 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.

Definition at line 21 of file Constants.h.

◆ 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.

Definition at line 26 of file Constants.h.

◆ HereditaryBits

const unsigned int Eigen::HereditaryBits
Initial value:
const unsigned int RowMajorBit
Definition: Constants.h:53
const unsigned int EvalBeforeAssigningBit
Definition: Constants.h:63
const unsigned int EvalBeforeNestingBit
Definition: Constants.h:58

Definition at line 152 of file Constants.h.

◆ 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.

Definition at line 31 of file Constants.h.

◆ InnerRandomAccessPattern

const int Eigen::InnerRandomAccessPattern = 0x2 | CoherentAccessPattern

Definition at line 66 of file SparseUtil.h.

◆ LowerTriangular

const unsigned int Eigen::LowerTriangular = Lower

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

◆ LowerTriangularBit

const unsigned int Eigen::LowerTriangularBit = Lower

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

◆ NestByRefBit

const unsigned int Eigen::NestByRefBit = 0x100

Definition at line 149 of file Constants.h.

◆ OuterRandomAccessPattern

const int Eigen::OuterRandomAccessPattern = 0x4 | CoherentAccessPattern

Definition at line 67 of file SparseUtil.h.

◆ RandomAccessPattern

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

Definition at line 68 of file SparseUtil.h.

◆ SelfAdjointBit

const unsigned int Eigen::SelfAdjointBit = SelfAdjoint

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

◆ UnitDiagBit

const unsigned int Eigen::UnitDiagBit = UnitDiag

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

◆ UnitLowerTriangular

const unsigned int Eigen::UnitLowerTriangular = UnitLower

Definition at line 23 of file Eigen2Support/TriangularSolver.h.

◆ UnitUpperTriangular

const unsigned int Eigen::UnitUpperTriangular = UnitUpper

Definition at line 22 of file Eigen2Support/TriangularSolver.h.

◆ UpperTriangular

const unsigned int Eigen::UpperTriangular = Upper

Definition at line 20 of file Eigen2Support/TriangularSolver.h.

◆ UpperTriangularBit

const unsigned int Eigen::UpperTriangularBit = Upper

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



tuw_aruco
Author(s): Lukas Pfeifhofer
autogenerated on Mon Feb 28 2022 23:58:06