mirror of https://github.com/CGAL/cgal
Remove duplicated file (.h + .hpp)
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Simon Giraudot
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// Copyright (c) 2012 INRIA Bordeaux Sud-Ouest (France), All rights reserved.
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//
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// This file is part of CGAL (www.cgal.org); you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public License as
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// published by the Free Software Foundation; either version 3 of the License,
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// or (at your option) any later version.
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//
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// Licensees holding a valid commercial license may use this file in
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// accordance with the commercial license agreement provided with the software.
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//
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// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
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// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
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//
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// $URL$
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// $Id$
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//
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// Author(s) : Gael Guennebaud
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#ifndef CGAL_EIGEN_SOLVER_TRAITS_H
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#define CGAL_EIGEN_SOLVER_TRAITS_H
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#include <CGAL/config.h> // include basic.h before testing #defines
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#if defined(BOOST_MSVC)
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# pragma warning(push)
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# pragma warning(disable:4244)
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#endif
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#include <Eigen/Sparse>
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#if EIGEN_VERSION_AT_LEAST(3, 1, 91)
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#include <Eigen/SparseLU>
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#endif
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#if defined(BOOST_MSVC)
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# pragma warning(pop)
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#endif
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#include <CGAL/Eigen_matrix.h>
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#include <CGAL/Eigen_vector.h>
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#include <boost/shared_ptr.hpp>
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namespace CGAL {
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namespace internal {
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template <class EigenSolver,class FT>
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struct Get_eigen_matrix{
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typedef Eigen_sparse_matrix<FT> type;
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};
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template <class FT,class EigenMatrix>
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struct Get_eigen_matrix< ::Eigen::ConjugateGradient<EigenMatrix>,FT>{
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typedef Eigen_sparse_symmetric_matrix<FT> type;
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};
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template <class FT,class EigenMatrix>
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struct Get_eigen_matrix< ::Eigen::SimplicialCholesky<EigenMatrix>,FT>{
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typedef Eigen_sparse_symmetric_matrix<FT> type;
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};
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#if EIGEN_VERSION_AT_LEAST(3, 1, 91)
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template <class FT, class EigenMatrix, class EigenOrdering>
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struct Get_eigen_matrix< ::Eigen::SparseLU<EigenMatrix, EigenOrdering >, FT> {
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typedef Eigen_sparse_matrix<FT> type;
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};
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#endif
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} //internal
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/// The class Eigen_solver_traits
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/// is a generic traits class for solving asymmetric or symmetric positive definite (SPD)
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/// sparse linear systems using one of the Eigen solvers.
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/// The default solver is the iterative bi-congugate gradient stabilized solver
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/// Eigen::BiCGSTAB for double.
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///
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/// \cgalModels `SparseLinearAlgebraTraitsWithFactor_d`.
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template<class EigenSolverT = Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType, Eigen::IncompleteLUT< double > > >
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class Eigen_solver_traits
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{
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typedef typename EigenSolverT::Scalar Scalar;
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// Public types
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public:
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typedef Scalar NT;
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typedef typename internal::Get_eigen_matrix<EigenSolverT,NT>::type Matrix;
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typedef Eigen_vector<Scalar> Vector;
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// Public operations
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public:
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Eigen_solver_traits():m_mat(NULL), m_solver_sptr(new EigenSolverT)
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{
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}
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EigenSolverT& solver() { return *m_solver_sptr; }
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/// Solve the sparse linear system "A*X = B".
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/// Return true on success. The solution is then (1/D) * X.
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///
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/// @commentheading Preconditions:
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/// - A.row_dimension() == B.dimension().
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/// - A.column_dimension() == X.dimension().
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bool linear_solver(const Matrix& A, const Vector& B, Vector& X, NT& D)
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{
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D = 1; // Eigen does not support homogeneous coordinates
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m_solver_sptr->compute(A.eigen_object());
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if(m_solver_sptr->info() != Eigen::Success)
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return false;
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X = m_solver_sptr->solve(B);
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return m_solver_sptr->info() == Eigen::Success;
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}
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bool factor (const Matrix& A, NT& D)
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{
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D = 1;
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m_mat = &A.eigen_object();
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solver().compute(*m_mat);
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return solver().info() == Eigen::Success;
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}
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bool linear_solver(const Vector& B, Vector& X)
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{
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CGAL_precondition(m_mat!=NULL); //factor should have been called first
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X = solver().solve(B);
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return solver().info() == Eigen::Success;
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}
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protected:
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const typename Matrix::EigenType* m_mat;
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boost::shared_ptr<EigenSolverT> m_solver_sptr;
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};
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//specilization of the solver for BiCGSTAB as for surface parameterization, the
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//intializer should be a vector of one's (this was the case in 3.1-alpha but not in the official 3.1).
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template<>
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class Eigen_solver_traits< Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType, Eigen::IncompleteLUT< double > > >
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{
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typedef Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType, Eigen::IncompleteLUT< double > > EigenSolverT;
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typedef EigenSolverT::Scalar Scalar;
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// Public types
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public:
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typedef Scalar NT;
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typedef internal::Get_eigen_matrix<EigenSolverT,NT>::type Matrix;
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typedef Eigen_vector<Scalar> Vector;
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// Public operations
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public:
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Eigen_solver_traits(): m_solver_sptr(new EigenSolverT)
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{
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}
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EigenSolverT& solver() { return *m_solver_sptr; }
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/// Solve the sparse linear system "A*X = B".
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/// Return true on success. The solution is then (1/D) * X.
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///
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/// @commentheading Preconditions:
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/// - A.row_dimension() == B.dimension().
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/// - A.column_dimension() == X.dimension().
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bool linear_solver(const Matrix& A, const Vector& B, Vector& X, NT& D)
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{
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D = 1; // Eigen does not support homogeneous coordinates
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m_solver_sptr->compute(A.eigen_object());
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if(m_solver_sptr->info() != Eigen::Success)
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return false;
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X.setOnes(B.rows());
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X = m_solver_sptr->solveWithGuess(B,X);
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return m_solver_sptr->info() == Eigen::Success;
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}
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protected:
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boost::shared_ptr<EigenSolverT> m_solver_sptr;
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};
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} //namespace CGAL
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#endif // CGAL_EIGEN_SOLVER_TRAITS_H
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