Detailed Description

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

Enumerations
enum	{ Lower, Upper, UnitDiag, ZeroDiag, UnitLower, UnitUpper, StrictlyLower, StrictlyUpper, SelfAdjoint, Symmetric }

enum	{ Unaligned, Aligned }

enum	{ ColMajor, RowMajor, AutoAlign, DontAlign }

enum	{ OnTheLeft, OnTheRight }

enum	AccessorLevels { ReadOnlyAccessors, WriteAccessors, DirectAccessors, DirectWriteAccessors }

enum	ComputationInfo { Success, NumericalIssue, NoConvergence, InvalidInput }

enum	CornerType

enum	DecompositionOptions { , ComputeFullU, ComputeThinU, ComputeFullV, ComputeThinV, EigenvaluesOnly, ComputeEigenvectors , Ax_lBx, ABx_lx, BAx_lx }

enum	DirectionType { Vertical, Horizontal, BothDirections }

enum	QRPreconditioners { NoQRPreconditioner, HouseholderQRPreconditioner, ColPivHouseholderQRPreconditioner, FullPivHouseholderQRPreconditioner }

enum	TransformTraits { Isometry, Affine, AffineCompact, Projective }

Enumeration Type Documentation

anonymous enum

Enum containing possible values for the Mode parameter of MatrixBase::selfadjointView() and MatrixBase::triangularView().

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.

anonymous enum

Enum for indicating whether an object is aligned or not.

Enumerator
Unaligned	Object is not correctly aligned for vectorization.
Aligned	Object is aligned for vectorization.

anonymous enum

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

Enumerator
ColMajor	Storage order is column major (see Storage orders).
RowMajor	Storage order is row major (see Storage orders).
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)

anonymous enum

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.

enum 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.

enum 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.

enum CornerType

Enum used by DenseBase::corner() in Eigen2 compatibility mode.

enum DecompositionOptions

Enum with options to give to various decompositions.

Enumerator
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.
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 $BAx = \lambda x$ .

enum 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.

enum QRPreconditioners

Possible values for the QRPreconditioner template parameter of JacobiSVD.

Enumerator
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.
ColPivHouseholderQRPreconditioner	Use a QR decomposition with column pivoting as the first step.
FullPivHouseholderQRPreconditioner	Use a QR decomposition with full pivoting as the first step.

enum TransformTraits

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

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.