/usr/include/CGAL/Eigen_solver_traits.h is in libcgal-dev 4.5-2.
This file is owned by root:root, with mode 0o644.
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//
// This file is part of CGAL (www.cgal.org); you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public License as
// published by the Free Software Foundation; either version 3 of the License,
// or (at your option) any later version.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
//
// Author(s) : Gael Guennebaud
#ifndef CGAL_EIGEN_SOLVER_TRAITS_H
#define CGAL_EIGEN_SOLVER_TRAITS_H
#include <CGAL/config.h> // include basic.h before testing #defines
#if defined(BOOST_MSVC)
# pragma warning(push)
# pragma warning(disable:4244)
#endif
#include <Eigen/Sparse>
#if EIGEN_VERSION_AT_LEAST(3, 1, 91)
#include <Eigen/SparseLU>
#endif
#if defined(BOOST_MSVC)
# pragma warning(pop)
#endif
#include <CGAL/Eigen_matrix.h>
#include <CGAL/Eigen_vector.h>
#include <boost/shared_ptr.hpp>
namespace CGAL {
namespace internal {
template <class EigenSolver,class FT>
struct Get_eigen_matrix{
typedef Eigen_sparse_matrix<FT> type;
};
template <class FT,class EigenMatrix>
struct Get_eigen_matrix< ::Eigen::ConjugateGradient<EigenMatrix>,FT>{
typedef Eigen_sparse_symmetric_matrix<FT> type;
};
template <class FT,class EigenMatrix>
struct Get_eigen_matrix< ::Eigen::SimplicialCholesky<EigenMatrix>,FT>{
typedef Eigen_sparse_symmetric_matrix<FT> type;
};
#if EIGEN_VERSION_AT_LEAST(3, 1, 91)
template <class FT, class EigenMatrix, class EigenOrdering>
struct Get_eigen_matrix< ::Eigen::SparseLU<EigenMatrix, EigenOrdering >, FT> {
typedef Eigen_sparse_matrix<FT> type;
};
#endif
} //internal
/// The class Eigen_solver_traits
/// is a generic traits class for solving asymmetric or symmetric positive definite (SPD)
/// sparse linear systems using one of the Eigen solvers.
/// The default solver is the iterative bi-congugate gradient stabilized solver
/// Eigen::BiCGSTAB for double.
///
/// \cgalModels `SparseLinearAlgebraTraitsWithFactor_d`.
template<class EigenSolverT = Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType> >
class Eigen_solver_traits
{
typedef typename EigenSolverT::Scalar Scalar;
// Public types
public:
typedef Scalar NT;
typedef typename internal::Get_eigen_matrix<EigenSolverT,NT>::type Matrix;
typedef Eigen_vector<Scalar> Vector;
// Public operations
public:
Eigen_solver_traits():m_mat(NULL), m_solver_sptr(new EigenSolverT)
{
}
EigenSolverT& solver() { return *m_solver_sptr; }
/// Solve the sparse linear system "A*X = B".
/// Return true on success. The solution is then (1/D) * X.
///
/// @commentheading Preconditions:
/// - A.row_dimension() == B.dimension().
/// - A.column_dimension() == X.dimension().
bool linear_solver(const Matrix& A, const Vector& B, Vector& X, NT& D)
{
D = 1; // Eigen does not support homogeneous coordinates
m_solver_sptr->compute(A.eigen_object());
if(m_solver_sptr->info() != Eigen::Success)
return false;
X = m_solver_sptr->solve(B);
return m_solver_sptr->info() == Eigen::Success;
}
bool factor (const Matrix& A, NT& D)
{
D = 1;
m_mat = &A.eigen_object();
solver().compute(*m_mat);
return solver().info() == Eigen::Success;
}
bool linear_solver(const Vector& B, Vector& X)
{
CGAL_precondition(m_mat!=NULL); //factor should have been called first
X = solver().solve(B);
return solver().info() == Eigen::Success;
}
protected:
const typename Matrix::EigenType* m_mat;
boost::shared_ptr<EigenSolverT> m_solver_sptr;
};
//specilization of the solver for BiCGSTAB as for surface parameterization, the
//intializer should be a vector of one's (this was the case in 3.1-alpha but not in the official 3.1).
template<>
class Eigen_solver_traits< Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType> >
{
typedef Eigen::BiCGSTAB<Eigen_sparse_matrix<double>::EigenType> EigenSolverT;
typedef EigenSolverT::Scalar Scalar;
// Public types
public:
typedef Scalar NT;
typedef internal::Get_eigen_matrix<EigenSolverT,NT>::type Matrix;
typedef Eigen_vector<Scalar> Vector;
// Public operations
public:
Eigen_solver_traits(): m_solver_sptr(new EigenSolverT)
{
}
EigenSolverT& solver() { return *m_solver_sptr; }
/// Solve the sparse linear system "A*X = B".
/// Return true on success. The solution is then (1/D) * X.
///
/// @commentheading Preconditions:
/// - A.row_dimension() == B.dimension().
/// - A.column_dimension() == X.dimension().
bool linear_solver(const Matrix& A, const Vector& B, Vector& X, NT& D)
{
D = 1; // Eigen does not support homogeneous coordinates
m_solver_sptr->compute(A.eigen_object());
if(m_solver_sptr->info() != Eigen::Success)
return false;
X.setOnes(B.rows());
X = m_solver_sptr->solveWithGuess(B,X);
return m_solver_sptr->info() == Eigen::Success;
}
protected:
boost::shared_ptr<EigenSolverT> m_solver_sptr;
};
} //namespace CGAL
#endif // CGAL_EIGEN_SOLVER_TRAITS_H
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