Simon Giraudot, Pierre Alliez, Frédéric Cazals, Gaël Guennebaud, Bruno Lévy, Marc Pouget, and Laurent Saboret

This package provides concepts and models for solving linear systems with dense or sparse matrices.

Introduced in: CGAL 4.8
BibTeX: cgal:eb-solver-20a
License: LGPL

Classified Reference Pages

Concepts

Classes
class	CGAL::Eigen_diagonalize_traits< FT, dim >
	The class `Eigen_diagonalize_traits` provides an interface to the diagonalization of covariance matrices of Eigen. More...

struct	CGAL::Eigen_sparse_matrix< T >
	The class `Eigen_sparse_matrix` is a wrapper around `Eigen` matrix type `Eigen::SparseMatrix` that represents general matrices, be they symmetric or not. More...

struct	CGAL::Eigen_sparse_symmetric_matrix< T >
	The class `Eigen_sparse_symmetric_matrix` is a wrapper around `Eigen` matrix type `Eigen::SparseMatrix` More...

struct	CGAL::Eigen_matrix< FT >
	The class `Eigen_matrix` is a wrapper around `Eigen` matrix type `Eigen::Matrix`. More...

class	CGAL::Eigen_solver_traits< EigenSolverT >
	The class `Eigen_solver_traits` provides an interface to the sparse solvers of Eigen. More...

class	CGAL::Eigen_svd
	The class `Eigen_svd` provides an algorithm to solve in the least square sense a linear system with a singular value decomposition using Eigen. More...

class	CGAL::Eigen_vector< T >
	The class `Eigen_vector` is a wrapper around `Eigen` vector type, which is a simple array of numbers. More...

class	CGAL::Lapack_vector
	A matrix class to be used in the class `Lapack_svd`. More...

class	CGAL::Lapack_matrix
	In CLAPACK, matrices are one-dimensional arrays and elements are column-major ordered. More...

class	CGAL::Lapack_svd
	This class is a wrapper to the singular value decomposition algorithm of LAPACK. More...