Enumerations

Enumerations
enum	Eigen::UpLoType {   Eigen::Lower = 0x1 , Eigen::Upper = 0x2 , Eigen::UnitDiag = 0x4 , Eigen::ZeroDiag = 0x8 ,   Eigen::UnitLower = UnitDiag | Lower , Eigen::UnitUpper = UnitDiag | Upper , Eigen::StrictlyLower = ZeroDiag | Lower , Eigen::StrictlyUpper = ZeroDiag | Upper ,   Eigen::SelfAdjoint = 0x10 , Eigen::Symmetric = 0x20 }
enum	Eigen::AlignmentType {   Eigen::Unaligned = 0 , Eigen::Aligned8 = 8 , Eigen::Aligned16 = 16 , Eigen::Aligned32 = 32 ,   Eigen::Aligned64 = 64 , Eigen::Aligned128 = 128 , Eigen::AlignedMask = 255 , Eigen::Aligned = 16 ,   Eigen::AlignedMax = Unaligned }
enum	Eigen::DirectionType { Eigen::Vertical , Eigen::Horizontal , Eigen::BothDirections }
enum	Eigen::TraversalType {   Eigen::DefaultTraversal , Eigen::LinearTraversal , Eigen::InnerVectorizedTraversal , Eigen::LinearVectorizedTraversal ,   Eigen::SliceVectorizedTraversal , Eigen::InvalidTraversal , Eigen::AllAtOnceTraversal }
enum	Eigen::UnrollingType { Eigen::NoUnrolling , Eigen::InnerUnrolling , Eigen::CompleteUnrolling }
enum	Eigen::SpecializedType { Eigen::Specialized , Eigen::BuiltIn }
enum	Eigen::StorageOptions { Eigen::ColMajor = 0 , Eigen::RowMajor = 0x1 , Eigen::AutoAlign = 0 , Eigen::DontAlign = 0x2 }
enum	Eigen::SideType { Eigen::OnTheLeft = 1 , Eigen::OnTheRight = 2 }
enum	Eigen::NaNPropagationOptions { Eigen::PropagateFast = 0 , Eigen::PropagateNaN , Eigen::PropagateNumbers }
enum	Eigen::AmbiVectorMode { Eigen::IsDense = 0 , Eigen::IsSparse }
enum	Eigen::AccessorLevels { Eigen::ReadOnlyAccessors , Eigen::WriteAccessors , Eigen::DirectAccessors , Eigen::DirectWriteAccessors }
enum	Eigen::DecompositionOptions {   Eigen::Pivoting = 0x01 , Eigen::NoPivoting = 0x02 , Eigen::ComputeFullU = 0x04 , Eigen::ComputeThinU = 0x08 ,   Eigen::ComputeFullV = 0x10 , Eigen::ComputeThinV = 0x20 , Eigen::EigenvaluesOnly = 0x40 , Eigen::ComputeEigenvectors = 0x80 ,   Eigen::EigVecMask = EigenvaluesOnly | ComputeEigenvectors , Eigen::Ax_lBx = 0x100 , Eigen::ABx_lx = 0x200 , Eigen::BAx_lx = 0x400 ,   Eigen::GenEigMask = Ax_lBx | ABx_lx | BAx_lx }
enum	Eigen::QRPreconditioners {   Eigen::ColPivHouseholderQRPreconditioner = 0x0 , Eigen::NoQRPreconditioner = 0x40 , Eigen::HouseholderQRPreconditioner = 0x80 , Eigen::FullPivHouseholderQRPreconditioner = 0xC0 ,   Eigen::DisableQRDecomposition = NoQRPreconditioner }
enum	Eigen::ComputationInfo { Eigen::Success = 0 , Eigen::NumericalIssue = 1 , Eigen::NoConvergence = 2 , Eigen::InvalidInput = 3 }
enum	Eigen::TransformTraits { Eigen::Isometry = 0x1 , Eigen::Affine = 0x2 , Eigen::AffineCompact = 0x10 | Affine , Eigen::Projective = 0x20 }
enum	Eigen::ProductImplType {   Eigen::DefaultProduct = 0 , Eigen::LazyProduct , Eigen::AliasFreeProduct , Eigen::CoeffBasedProductMode ,   Eigen::LazyCoeffBasedProductMode , Eigen::OuterProduct , Eigen::InnerProduct , Eigen::GemvProduct ,   Eigen::GemmProduct }
enum	Eigen::Action { Eigen::GetAction , Eigen::SetAction }

Detailed Description

Various enumerations used in Eigen. Many of these are used as template parameters.

Enumeration Type Documentation

AccessorLevels

enum Eigen::AccessorLevels

Used as template parameter in DenseCoeffBase and MapBase to indicate which accessors should be provided.

Enumerator
ReadOnlyAccessors	Read-only access via a member function.
WriteAccessors	Read/write access via member functions.
DirectAccessors	Direct read-only access to the coefficients.
DirectWriteAccessors	Direct read/write access to the coefficients.

                    {
  ReadOnlyAccessors,
  WriteAccessors,
  DirectAccessors,
  DirectWriteAccessors
};

Action

enum Eigen::Action

Enum used in experimental parallel implementation.

Enumerator
GetAction
SetAction

{ GetAction, SetAction };

AlignmentType

enum Eigen::AlignmentType

Enum for indicating whether a buffer is aligned or not.

Enumerator
Unaligned	Data pointer has no specific alignment.
Aligned8	Data pointer is aligned on a 8 bytes boundary.
Aligned16	Data pointer is aligned on a 16 bytes boundary.
Aligned32	Data pointer is aligned on a 32 bytes boundary.
Aligned64	Data pointer is aligned on a 64 bytes boundary.
Aligned128	Data pointer is aligned on a 128 bytes boundary.
AlignedMask
Aligned	Deprecated: Synonym for Aligned16.
AlignedMax

                   {
  Unaligned = 0,    
  Aligned8 = 8,     
  Aligned16 = 16,   
  Aligned32 = 32,   
  Aligned64 = 64,   
  Aligned128 = 128, 
  AlignedMask = 255,
  Aligned = 16, 
#if EIGEN_MAX_ALIGN_BYTES == 128
  AlignedMax = Aligned128
#elif EIGEN_MAX_ALIGN_BYTES == 64
  AlignedMax = Aligned64
#elif EIGEN_MAX_ALIGN_BYTES == 32
  AlignedMax = Aligned32
#elif EIGEN_MAX_ALIGN_BYTES == 16
  AlignedMax = Aligned16
#elif EIGEN_MAX_ALIGN_BYTES == 8
  AlignedMax = Aligned8
#elif EIGEN_MAX_ALIGN_BYTES == 0
  AlignedMax = Unaligned
#else
#error Invalid value for EIGEN_MAX_ALIGN_BYTES
#endif
};

AmbiVectorMode

enum Eigen::AmbiVectorMode

Used in AmbiVector.

Enumerator
IsDense
IsSparse

{ IsDense = 0, IsSparse };

ComputationInfo

enum Eigen::ComputationInfo

Enum for reporting the status of a computation.

Enumerator
Success	Computation was successful.
NumericalIssue	The provided data did not satisfy the prerequisites.
NoConvergence	Iterative procedure did not converge.
InvalidInput	The inputs are invalid, or the algorithm has been improperly called. When assertions are enabled, such errors trigger an assert.

                     {
  Success = 0,
  NumericalIssue = 1,
  NoConvergence = 2,
  InvalidInput = 3
};

DecompositionOptions

enum Eigen::DecompositionOptions

Enum with options to give to various decompositions.

Enumerator
Pivoting	Not used (meant for LDLT?).
NoPivoting	Not used (meant for LDLT?).
ComputeFullU	Used in JacobiSVD to indicate that the square matrix U is to be computed.
ComputeThinU	Used in JacobiSVD to indicate that the thin matrix U is to be computed.
ComputeFullV	Used in JacobiSVD to indicate that the square matrix V is to be computed.
ComputeThinV	Used in JacobiSVD to indicate that the thin matrix V is to be computed.
EigenvaluesOnly	Used in SelfAdjointEigenSolver and GeneralizedSelfAdjointEigenSolver to specify that only the eigenvalues are to be computed and not the eigenvectors.
ComputeEigenvectors	Used in SelfAdjointEigenSolver and GeneralizedSelfAdjointEigenSolver to specify that both the eigenvalues and the eigenvectors are to be computed.
EigVecMask
Ax_lBx	Used in GeneralizedSelfAdjointEigenSolver to indicate that it should solve the generalized eigenproblem \( Ax = \lambda B x \).
ABx_lx	Used in GeneralizedSelfAdjointEigenSolver to indicate that it should solve the generalized eigenproblem \( ABx = \lambda x \).
BAx_lx	Used in GeneralizedSelfAdjointEigenSolver to indicate that it should solve the generalized eigenproblem \( BAx = \lambda x \).
GenEigMask

                          {
  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
};

DirectionType

enum Eigen::DirectionType

Enum containing possible values for the Direction parameter of Reverse, PartialReduxExpr and VectorwiseOp.

Enumerator
Vertical	For Reverse, all columns are reversed; for PartialReduxExpr and VectorwiseOp, act on columns.
Horizontal	For Reverse, all rows are reversed; for PartialReduxExpr and VectorwiseOp, act on rows.
BothDirections	For Reverse, both rows and columns are reversed; not used for PartialReduxExpr and VectorwiseOp.

                   {
  Vertical,
  Horizontal,
  BothDirections
};

NaNPropagationOptions

enum Eigen::NaNPropagationOptions

Enum for specifying NaN-propagation behavior, e.g. for coeff-wise min/max.

Enumerator
PropagateFast	Implementation defined behavior if NaNs are present.
PropagateNaN	Always propagate NaNs.
PropagateNumbers	Always propagate not-NaNs.

                           {
  PropagateFast = 0,
  PropagateNaN,
  PropagateNumbers
};

ProductImplType

enum Eigen::ProductImplType

Enum used as template parameter in Product and product evaluators.

Enumerator
DefaultProduct
LazyProduct
AliasFreeProduct
CoeffBasedProductMode
LazyCoeffBasedProductMode
OuterProduct
InnerProduct
GemvProduct
GemmProduct

                     {
  DefaultProduct = 0,
  LazyProduct,
  AliasFreeProduct,
  CoeffBasedProductMode,
  LazyCoeffBasedProductMode,
  OuterProduct,
  InnerProduct,
  GemvProduct,
  GemmProduct
};

QRPreconditioners

enum Eigen::QRPreconditioners

Possible values for the QRPreconditioner template parameter of JacobiSVD.

Enumerator
ColPivHouseholderQRPreconditioner	Use a QR decomposition with column pivoting as the first step.
NoQRPreconditioner	Do not specify what is to be done if the SVD of a non-square matrix is asked for.
HouseholderQRPreconditioner	Use a QR decomposition without pivoting as the first step.
FullPivHouseholderQRPreconditioner	Use a QR decomposition with full pivoting as the first step.
DisableQRDecomposition	Used to disable the QR Preconditioner in BDCSVD.

                       {
  ColPivHouseholderQRPreconditioner = 0x0,
  NoQRPreconditioner = 0x40,
  HouseholderQRPreconditioner = 0x80,
  FullPivHouseholderQRPreconditioner = 0xC0,
  DisableQRDecomposition = NoQRPreconditioner
};

SideType

enum Eigen::SideType

Enum for specifying whether to apply or solve on the left or right.

Enumerator
OnTheLeft	Apply transformation on the left.
OnTheRight	Apply transformation on the right.

              {
  OnTheLeft = 1,
  OnTheRight = 2
};

SpecializedType

enum Eigen::SpecializedType

Enum to specify whether to use the default (built-in) implementation or the specialization.

Enumerator
Specialized
BuiltIn

{ Specialized, BuiltIn };

StorageOptions

enum Eigen::StorageOptions

Enum containing possible values for the Options_ template parameter of Matrix, Array and BandMatrix.

Enumerator
ColMajor	Storage order is column major (see TopicStorageOrders).
RowMajor	Storage order is row major (see TopicStorageOrders).
AutoAlign	Align the matrix itself if it is vectorizable fixed-size
DontAlign	Don't require alignment for the matrix itself (the array of coefficients, if dynamically allocated, may still be requested to be aligned)

                    {
  ColMajor = 0,
  RowMajor = 0x1,  // it is only a coincidence that this is equal to RowMajorBit -- don't rely on that
  AutoAlign = 0, // FIXME --- clarify the situation
  DontAlign = 0x2
};

TransformTraits

enum Eigen::TransformTraits

Enum used to specify how a particular transformation is stored in a matrix.

See also

Transform, Hyperplane::transform().

Enumerator
Isometry	Transformation is an isometry.
Affine	Transformation is an affine transformation stored as a (Dim+1)^2 matrix whose last row is assumed to be [0 ... 0 1].
AffineCompact	Transformation is an affine transformation stored as a (Dim) x (Dim+1) matrix.
Projective	Transformation is a general projective transformation stored as a (Dim+1)^2 matrix.

                     {
  Isometry = 0x1,
  Affine = 0x2,
  AffineCompact = 0x10 | Affine,
  Projective = 0x20
};

TraversalType

enum Eigen::TraversalType

Enum to specify how to traverse the entries of a matrix.

Enumerator
DefaultTraversal	Default traversal, no vectorization, no index-based access
LinearTraversal	No vectorization, use index-based access to have only one for loop instead of 2 nested loops
InnerVectorizedTraversal	Equivalent to a slice vectorization for fixed-size matrices having good alignment and good size
LinearVectorizedTraversal	Vectorization path using a single loop plus scalar loops for the unaligned boundaries
SliceVectorizedTraversal	Generic vectorization path using one vectorized loop per row/column with some scalar loops to handle the unaligned boundaries
InvalidTraversal	Special case to properly handle incompatible scalar types or other defecting cases
AllAtOnceTraversal	Evaluate all entries at once

                   {
  DefaultTraversal,
  LinearTraversal,
  InnerVectorizedTraversal,
  LinearVectorizedTraversal,
  SliceVectorizedTraversal,
  InvalidTraversal,
  AllAtOnceTraversal
};

UnrollingType

enum Eigen::UnrollingType

Enum to specify whether to unroll loops when traversing over the entries of a matrix.

Enumerator
NoUnrolling	Do not unroll loops.
InnerUnrolling	Unroll only the inner loop, but not the outer loop.
CompleteUnrolling	Unroll both the inner and the outer loop. If there is only one loop, because linear traversal is used, then unroll that loop.

                   {
  NoUnrolling,
  InnerUnrolling,
  CompleteUnrolling
};

UpLoType

enum Eigen::UpLoType

Enum containing possible values for the Mode or UpLo parameter of MatrixBase::selfadjointView() and MatrixBase::triangularView(), and selfadjoint solvers.

Enumerator
Lower	View matrix as a lower triangular matrix.
Upper	View matrix as an upper triangular matrix.
UnitDiag	Matrix has ones on the diagonal; to be used in combination with Lower or Upper.
ZeroDiag	Matrix has zeros on the diagonal; to be used in combination with Lower or Upper.
UnitLower	View matrix as a lower triangular matrix with ones on the diagonal.
UnitUpper	View matrix as an upper triangular matrix with ones on the diagonal.
StrictlyLower	View matrix as a lower triangular matrix with zeros on the diagonal.
StrictlyUpper	View matrix as an upper triangular matrix with zeros on the diagonal.
SelfAdjoint	Used in BandMatrix and SelfAdjointView to indicate that the matrix is self-adjoint.
Symmetric	Used to support symmetric, non-selfadjoint, complex matrices.

              {
  Lower = 0x1,
  Upper = 0x2,
  UnitDiag = 0x4,
  ZeroDiag = 0x8,
  UnitLower = UnitDiag | Lower,
  UnitUpper = UnitDiag | Upper,
  StrictlyLower = ZeroDiag | Lower,
  StrictlyUpper = ZeroDiag | Upper,
  SelfAdjoint = 0x10,
  Symmetric = 0x20
};