Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 123]
 NEigenNamespace containing all symbols from the Eigen library
 CAlignedVector3A vectorization friendly 3D vector
 CAutoDiffScalarA scalar type replacement with automatic differentation capability
 CBlockSparseMatrixA versatile sparse matrix representation where each element is a block
 CDGMRESA 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
 CDynamicSGroupDynamic symmetry group
 CDynamicSparseMatrixA sparse matrix class designed for matrix assembly purpose
 CEulerAnglesRepresents a rotation in a 3 dimensional space as three Euler angles
 CEulerSystemRepresents a fixed Euler rotation system
 CGMRESA GMRES solver for sparse square problems
 CHybridNonLinearSolverFinds a zero of a system of n nonlinear functions in n variables by a modification of the Powell hybrid method ("dogleg")
 CIterationControllerControls the iterations of the iterative solvers
 CIterScalingIterative scaling algorithm to equilibrate rows and column norms in matrices
 CKdBVHA simple bounding volume hierarchy based on AlignedBox
 CKroneckerProductKronecker tensor product helper class for dense matrices
 CKroneckerProductBaseThe base class of dense and sparse Kronecker product
 CKroneckerProductSparseKronecker tensor product helper class for sparse matrices
 CLevenbergMarquardtPerforms non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm
 CMatrixComplexPowerReturnValueProxy for the matrix power of some matrix (expression)
 CMatrixExponentialReturnValueProxy for the matrix exponential of some matrix (expression)
 CMatrixFunctionReturnValueProxy for the matrix function of some matrix (expression)
 CMatrixLogarithmReturnValueProxy for the matrix logarithm of some matrix (expression)
 CMatrixMarketIteratorIterator to browse matrices from a specified folder
 CMatrixPowerClass for computing matrix powers
 CMatrixPowerAtomicClass for computing matrix powers
 CMatrixPowerParenthesesReturnValueProxy for the matrix power of some matrix
 CMatrixPowerReturnValueProxy for the matrix power of some matrix (expression)
 CMatrixSquareRootReturnValueProxy for the matrix square root of some matrix (expression)
 CMaxSizeVectorThe MaxSizeVector class
 CMINRESA minimal residual solver for sparse symmetric problems
 CNumericalDiff
 CPolynomialSolverA polynomial solver
 CPolynomialSolverBaseDefined to be inherited by polynomial solvers: it provides convenient methods such as
 CRandomSetterThe RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
 CSGroupSymmetry group, initialized from template arguments
 CSkylineInplaceLUInplace LU decomposition of a skyline matrix and associated features
 CSkylineMatrixThe main skyline matrix class
 CSkylineMatrixBaseBase class of any skyline matrices or skyline expressions
 CSkylineStorage
 CSplineA class representing multi-dimensional spline curves
 CSplineFittingSpline fitting methods
 CSplineTraits< Spline< _Scalar, _Dim, _Degree >, _DerivativeOrder >Compile-time attributes of the Spline class for fixed degree
 CSplineTraits< Spline< _Scalar, _Dim, _Degree >, Dynamic >Compile-time attributes of the Spline class for Dynamic degree
 CStaticSGroupStatic symmetry group
 CStdMapTraits
 CTensorThe tensor class
 CTensorBaseThe tensor base class
 CTensorConcatenationOpTensor concatenation class
 CTensorConversionOpTensor 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
 CTensorCustomBinaryOpTensor custom class
 CTensorCustomUnaryOpTensor custom class
 CTensorDevicePseudo expression providing an operator = that will evaluate its argument on the specified computing 'device' (GPU, thread pool, ...)
 CTensorEvaluatorA cost model used to limit the number of threads used for evaluating tensor expression
 CTensorFixedSizeThe fixed sized version of the tensor class
 CTensorMapA tensor expression mapping an existing array of data
 CTensorRefA reference to a tensor expression The expression will be evaluated lazily (as much as possible)
 Nutility
 Ntuple
 CElemTypeHolderElemTypeHolder class is used to specify the types of the elements inside the tuple
 CElemTypeHolder< 0, Tuple< T, Ts... > >Specialisation of the ElemTypeHolder class when the number of elements inside the tuple is 1
 CElemTypeHolder< 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
 CIndexListCreates a list of index from the elements in the tuple
 CIndexRangeIndexRange that returns a [MIN, MAX) index range
 CRangeBuilderCollects internal details for generating index ranges [MIN, MAX) Declare primary template for index range builder
 CRangeBuilder< MIN, MIN, Is... >Base Step: Specialisation of the RangeBuilder when the MIN==MAX. In this case the Is... is [0 to sizeof...(tuple elements))
 CStaticIfThe StaticIf struct is used to statically choose the type based on the condition
 CStaticIf< true, T >Specialisation of the StaticIf when the condition is true
 CTupleFixed-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
 CTensorAssignThe tensor assignment class
 CTensorBroadcastingTensor broadcasting class
 CTensorContractionTensor contraction class
 CTensorConvolutionTensor convolution class
 CTensorExecutorThe tensor executor class
 CTensorExprTensor expression classes
 CTensorForcedEvalTensor reshaping class
 CTensorForcedEvalTensor reshaping class
 CTensorGeneratorTensor generator class
 CTensorImagePatchPatch 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
 CTensorIndexTupleTensor + Index Tuple class
 CTensorInflationTensor inflation class
 CTensorKChippingReshapingA chip is a thin slice, corresponding to a column or a row in a 2-d tensor
 CTensorLayoutSwapSwap the layout from col-major to row-major, or row-major to col-major, and invert the order of the dimensions
 CTensorPaddingTensor padding class. At the moment only padding with a constant value is supported
 CTensorPatchTensor patch class
 CTensorReductionTensor reduction class
 CTensorReshapingTensor reshaping class
 CTensorReverseTensor reverse elements class
 CTensorScanTensor scan class
 CTensorShufflingTensor shuffling class
 CTensorSlicingTensor slicing class
 CTensorStridingTensor striding class
 CTensorTupleIndexConverts 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: