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Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 123]
oNEigenNamespace containing all symbols from the Eigen library
|oNinternal
|oCAlignedVector3A vectorization friendly 3D vector
|oCAutoDiffScalarA scalar type replacement with automatic differentation capability
|oCBlockSparseMatrixA versatile sparse matrix representation where each element is a block
|oCDGMRESA Restarted GMRES with deflation. This class implements a modification of the GMRES solver for sparse linear systems. The basis is built with modified Gram-Schmidt. At each restart, a few approximated eigenvectors corresponding to the smallest eigenvalues are used to build a preconditioner for the next cycle. This preconditioner for deflation can be combined with any other preconditioner, the IncompleteLUT for instance. The preconditioner is applied at right of the matrix and the combination is multiplicative
|oCDynamicSGroupDynamic symmetry group
|oCDynamicSparseMatrixA sparse matrix class designed for matrix assembly purpose
|oCEulerAnglesRepresents a rotation in a 3 dimensional space as three Euler angles
|oCEulerSystemRepresents a fixed Euler rotation system
|oCGMRESA GMRES solver for sparse square problems
|oCHybridNonLinearSolverFinds a zero of a system of n nonlinear functions in n variables by a modification of the Powell hybrid method ("dogleg")
|oCIterationControllerControls the iterations of the iterative solvers
|oCIterScalingIterative scaling algorithm to equilibrate rows and column norms in matrices
|oCKdBVHA simple bounding volume hierarchy based on AlignedBox
|oCKroneckerProductKronecker tensor product helper class for dense matrices
|oCKroneckerProductBaseThe base class of dense and sparse Kronecker product
|oCKroneckerProductSparseKronecker tensor product helper class for sparse matrices
|oCLevenbergMarquardtPerforms non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm
|oCMatrixComplexPowerReturnValueProxy for the matrix power of some matrix (expression)
|oCMatrixExponentialReturnValueProxy for the matrix exponential of some matrix (expression)
|oCMatrixFunctionReturnValueProxy for the matrix function of some matrix (expression)
|oCMatrixLogarithmReturnValueProxy for the matrix logarithm of some matrix (expression)
|oCMatrixMarketIteratorIterator to browse matrices from a specified folder
|oCMatrixPowerClass for computing matrix powers
|oCMatrixPowerAtomicClass for computing matrix powers
|oCMatrixPowerParenthesesReturnValueProxy for the matrix power of some matrix
|oCMatrixPowerReturnValueProxy for the matrix power of some matrix (expression)
|oCMatrixSquareRootReturnValueProxy for the matrix square root of some matrix (expression)
|oCMaxSizeVectorThe MaxSizeVector class
|oCMINRESA minimal residual solver for sparse symmetric problems
|oCNumericalDiff
|oCPolynomialSolverA polynomial solver
|oCPolynomialSolverBaseDefined to be inherited by polynomial solvers: it provides convenient methods such as
|oCRandomSetterThe RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
|oCSGroupSymmetry group, initialized from template arguments
|oCSkylineInplaceLUInplace LU decomposition of a skyline matrix and associated features
|oCSkylineMatrixThe main skyline matrix class
|oCSkylineMatrixBaseBase class of any skyline matrices or skyline expressions
|oCSkylineStorage
|oCSplineA class representing multi-dimensional spline curves
|oCSplineFittingSpline fitting methods
|oCSplineTraits< Spline< _Scalar, _Dim, _Degree >, _DerivativeOrder >Compile-time attributes of the Spline class for fixed degree
|oCSplineTraits< Spline< _Scalar, _Dim, _Degree >, Dynamic >Compile-time attributes of the Spline class for Dynamic degree
|oCStaticSGroupStatic symmetry group
|oCStdMapTraits
|oCTensorThe tensor class
|oCTensorBaseThe tensor base class
|oCTensorConcatenationOpTensor concatenation class
|oCTensorConversionOpTensor conversion class. This class makes it possible to vectorize type casting operations when the number of scalars per packet in the source and the destination type differ
|oCTensorCustomBinaryOpTensor custom class
|oCTensorCustomUnaryOpTensor custom class
|oCTensorDevicePseudo expression providing an operator = that will evaluate its argument on the specified computing 'device' (GPU, thread pool, ...)
|oCTensorEvaluatorA cost model used to limit the number of threads used for evaluating tensor expression
|oCTensorFixedSizeThe fixed sized version of the tensor class
|oCTensorMapA tensor expression mapping an existing array of data
|\CTensorRefA reference to a tensor expression The expression will be evaluated lazily (as much as possible)
oNutility
|\Ntuple
| oCElemTypeHolderElemTypeHolder class is used to specify the types of the elements inside the tuple
| oCElemTypeHolder< 0, Tuple< T, Ts...> >Specialisation of the ElemTypeHolder class when the number of elements inside the tuple is 1
| oCElemTypeHolder< k, Tuple< T, Ts...> >Specialisation of the ElemTypeHolder class when the number of elements inside the tuple is bigger than 1. It recursively calls itself to detect the type of each element in the tuple
| oCIndexListCreates a list of index from the elements in the tuple
| oCIndexRangeIndexRange that returns a [MIN, MAX) index range
| oCRangeBuilderCollects internal details for generating index ranges [MIN, MAX) Declare primary template for index range builder
| oCRangeBuilder< MIN, MIN, Is...>Base Step: Specialisation of the RangeBuilder when the MIN==MAX. In this case the Is... is [0 to sizeof...(tuple elements))
| oCStaticIfThe StaticIf struct is used to statically choose the type based on the condition
| oCStaticIf< true, T >Specialisation of the StaticIf when the condition is true
| oCTupleFixed-size collection of heterogeneous values Ts... - the types of the elements that the tuple stores. Empty list is supported
| \CTuple< T, Ts...>Specialisation of the Tuple class when the tuple has at least one element
oCTensorAssignThe tensor assignment class
oCTensorBroadcastingTensor broadcasting class
oCTensorContractionTensor contraction class
oCTensorConvolutionTensor convolution class
oCTensorExecutorThe tensor executor class
oCTensorExprTensor expression classes
oCTensorForcedEvalTensor reshaping class
oCTensorForcedEvalTensor reshaping class
oCTensorGeneratorTensor generator class
oCTensorImagePatchPatch extraction specialized for image processing. This assumes that the input has a least 3 dimensions ordered as follow: 1st dimension: channels (of size d) 2nd dimension: rows (of size r) 3rd dimension: columns (of size c) There can be additional dimensions such as time (for video) or batch (for bulk processing after the first 3. Calling the image patch code with patch_rows and patch_cols is equivalent to calling the regular patch extraction code with parameters d, patch_rows, patch_cols, and 1 for all the additional dimensions
oCTensorIndexTupleTensor + Index Tuple class
oCTensorInflationTensor inflation class
oCTensorKChippingReshapingA chip is a thin slice, corresponding to a column or a row in a 2-d tensor
oCTensorLayoutSwapSwap the layout from col-major to row-major, or row-major to col-major, and invert the order of the dimensions
oCTensorPaddingTensor padding class. At the moment only padding with a constant value is supported
oCTensorPatchTensor patch class
oCTensorReductionTensor reduction class
oCTensorReshapingTensor reshaping class
oCTensorReverseTensor reverse elements class
oCTensorScanTensor scan class
oCTensorShufflingTensor shuffling class
oCTensorSlicingTensor slicing class
oCTensorStridingTensor striding class
oCTensorTupleIndexConverts to Tensor<Tuple<Index, Scalar> > and reduces to Tensor<Index>
\CTensorVolumePatchPatch extraction specialized for processing of volumetric data. This assumes that the input has a least 4 dimensions ordered as follows: