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Enumeration Types

Extreme Optimization Numerical Libraries for .NET Professional

This section lists the enumeration types defined in the Extreme Optimization Numerical Libraries for .NET.

AlgorithmStatus

Enumerates the possible result codes for classes that inherit from ManagedIterativeAlgorithmT class.

Member Name	Description
NoResult	The algorithm has not been executed.
Busy	The algorithm has not yet ended.
Converged	The algorithm has converged.
ConvergedToFalseSolution	The algorithm converged, but the result is not a solution of the problem.
IterationLimitExceeded	The maximum number of iterations was exceeded.
EvaluationLimitExceeded	The maximum number of function evaluations was exceeded.
RoundOffError	Round-off prevented the algorithm from achieving a result within the desired tolerance.
BadFunction	A badly behaved function prevented the algorithm from achieving a result within the desired tolerance.
Divergent	the algorithm diverges.

ConvergenceCriterion

Enumerates possible values for the ConvergenceCriterion property of classes that inherit from the IterativeAlgorithm class or the ConvergenceTestT class.

Member Name	Description
WithinAbsoluteTolerance	The result should be within the tolerance specified by the AbsoluteTolerance property.
WithinRelativeTolerance	The result should be within the tolerance specified by the RelativeTolerance property.
WithinAnyTolerance	The result should be within either of the tolerances specified by the AbsoluteTolerance and RelativeTolerance properties.
NumberOfIterations	Convergence should be expected at the specified by the MaxIterations property. The estimated error is ignored.

ConvergenceTestQuantifier

Enumerates the possible ways tests in a ConvergenceTestCollectionT are combined.

Member Name	Description
Any	The convergence test succeeds if any of the tests in the collection succeeds.
All	The convergence test succeeds if all of the tests in the collection succeed.

DifferencesDirection

Enumerates the possible values that specify the type of divided differences to be used in numerical differentiation.

Member Name	Description
Backward	Only function values at the target point and to the left of the target point are used.
Central	Function values at the target point and on both sides of the target point are used.
Forward	Only function values at the target point and to the right of the target point are used.

CloningMethod

Enumerates the methods that can be used to clone a VectorT or MatrixT.

Member Name	Description
Complete	Makes an exact clone of the object.
NonzeroElementsWriteable	Makes a copy of the object such that all non-zero elements are writable.
AllElementsWriteable	Makes a copy of the object such that all elements are writable.

ConjugateGradientMethod

Enumerates the variants of the conjugate gradient method. This enumeration is used by the Method property of the ConjugateGradientOptimizer class to specify the formula that is used to construct the next conjugate direction.

Member Name	Description
FletcherReeves	The method of Fletcher and Reeves
PolakRibiere	The method of Polak and Ribiere
PositivePolakRibiere	The method of Polak and Ribiere with positive coefficient.

DimensionType

Enumerates the possible values for the type of dimension in a DimensionMismatchException.

Member Name	Description
Unknown	The mismatched dimension is unknown.
Row	The number of rows of a MatrixT is mismatched.
Column	The number of columns of a MatrixT is mismatched.
Length	The length of a VectorT is mismatched.

ExtremumType

Enumerates the possible values for the type of extremum an optimizer is to look for.

Member Name	Description
Minimum	A minimum of the objective function is requested. (This is the default.)
Maximum	A maximum of the objective function is requested.

LeastSquaresSolutionMethod

Enumerates the possible methods for solving a least squares problem.

Member Name	Description
NormalEquations	Use the normal equations computed from the input.
QRDecomposition	Use a QR decomposition of the input matrix. This is the default.
SingularValueDecomposition	Use a singular value decomposition. This is the most stable and reliable method, but also the slowest.

LinearLeastSquaresMethod

Enumerates the possible methods for solving a least squares problem. This enumeration is used by the LinearCurveFitter class to specify how the least squares solution is to be calculated.

Member Name	Description
NormalEquations	Use the normal equations computed from the input.
QRDecomposition	Use a QR decomposition of the input matrix. This is the most stable method.
SingularValueDecomposition	Use a singular value decomposition. This is the most stable and reliable method, but also the slowest.

MatrixDiagonal

Represents the possible values that specify whether or not a MatrixT has 1's on its diagonal.

This enumeration corresponds to the DIAG parameter in the BLAS and LAPACK routines, and the CBLAS_DIAG enum in the CBLAS interface definition.

Member Name	Description
NonUnitDiagonal	The matrix is not unit-diagonal.
UnitDiagonal	The matrix is unit-diagonal.

MatrixElementOrder

Represents the possible values for the order in which elements of a MatrixT are stored. The matrix elements must be contiguous in the storage array in the direction specified by this value.

This enumeration corresponds to the CBLAS_ORDER enum in the CBLAS interface definition.

Member Name	Description
RowMajor	The elements are stored in row major order. Elements in the same row are stored in one contiguous block.
ColumnMajor	The elements are stored in column major order. Elements in the same column are stored in one contiguous block.
NotApplicable	The element order is meaningless for the type of matrix.

MatrixOperationSide

Represents the possible values that specify on which side of the operator a MatrixT argument is to be multiplied. The value always refers to the side relative to the current instance.

This enumeration corresponds to the SIDE parameter in the BLAS and LAPACK routines, and the CBLAS_SIDE enum in the CBLAS interface definition.

Member Name	Description
Left	The MatrixT is to be multiplied on the left side.
Right	The MatrixT is to be multiplied on the right side.

MatrixTriangle

Represents the possible values specifying a triangular part of a matrix. It is used to specify whether a triangular matrix is upper or lower triangular, and to specify which part of a symmetric or Hermitian matrix is stored.

This enumeration corresponds to the UPLO parameter in the BLAS and LAPACK routines, and the CBLAS_UPLO enum in the CBLAS interface definition.

Member Name	Description
Upper	The matrix is upper triangular, or the matrix elements are stored in the upper triangular portion of the storage array.
Lower	The matrix is lower triangular, or the matrix elements are stored in the lower triangular portion of the storage array.
Both	Both upper and lower diagonal elements are present.

QuasiNewtonMethod

Enumerates the variants of the quasi-Newton method.

Member Name	Description
Bfgs	The Broyden-Fletcher-Goldfard-Shanno method. (This is the default.)
Dfp	The Davidon-Fletcher-Powell method.

SingularValueDecompositionFactors

Represents the possible values specifying which factors of a SingularValueDecompositionT are to be computed.

Member Name	Description
SingularValues	The singular values are required. This is always included.
LeftSingularVectors	The left singular vectors are required.
RightSingularVectors	The right singular vectors are required.
All	The singular values as well as the left and right singular vectors are required.

TransposeOperation

Represents the possible values of an operation to be performed on a MatrixT before it is multiplied.

This enumeration corresponds to the TRANS parameters in the BLAS and LAPACK routines, and the CBLAS_TRANSPOSE enum in the CBLAS interface definition.

Member Name	Description
None	No operation is performed. The matrix is multiplied 'as is.'
Transpose	The transpose of the matrix is multiplied.
ConjugateTranspose	The conjugate transpose of the matrix is multiplied. For real matrices, this is the same as Transpose.
Conjugate	The conjugate of the matrix is multiplied. For real matrices, this is the same as None.

VectorConvergenceErrorMeasure

Enumerates the ways to measure the error in a VectorConvergenceTestT.

Member Name	Description
Norm	Use the norm of the error vector as the measure.
Elementwise	Calculate the errors on individual elements.

VectorConvergenceNorm

Enumerates the possible norms to be used in a VectorConvergenceTestT.

Member Name	Description
EuclideanNorm	Use the Euclidean (two-norm).
Maximum	Use the maximum absolute value (infinity norm).
SumOfAbsoluteValues	Use the sum of the absolute values (one norm).

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