/usr/include/CGAL/Eigen_matrix.h is in libcgal-dev 4.2-5ubuntu1.
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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_MATRIX_H
#define CGAL_EIGEN_MATRIX_H
#include <CGAL/basic.h> // include basic.h before testing #defines
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#include <Eigen/Sparse>
namespace CGAL {
/// The class Eigen_sparse_matrix
/// is a C++ wrapper around Eigen' matrix type SparseMatrix<>.
///
/// This kind of matrix can be either symmetric or not. Symmetric
/// matrices store only the lower triangle.
///
/// @heading Is Model for the Concepts: Model of the SparseLinearAlgebraTraits_d::Matrix concept.
///
/// @heading Parameters:
/// @param T Number type.
template<class T>
struct Eigen_sparse_matrix
{
// Public types
public:
typedef Eigen::SparseMatrix<T> EigenType;
typedef T NT;
// Public operations
public:
/// Create a square matrix initialized with zeros.
Eigen_sparse_matrix(int dim, ///< Matrix dimension.
bool is_symmetric = false) ///< Symmetric/hermitian?
: m_is_already_built(false), m_matrix(dim,dim)
{
CGAL_precondition(dim > 0);
m_is_symmetric = is_symmetric;
// reserve memory for a regular 3D grid
m_triplets.reserve(dim);
}
/// Create a rectangular matrix initialized with zeros.
///
/// @commentheading Precondition: rows == columns if is_symmetric is true.
Eigen_sparse_matrix(int rows, ///< Number of rows.
int columns, ///< Number of columns.
bool is_symmetric = false) ///< Symmetric/hermitian?
: m_is_already_built(false), m_matrix(rows,columns)
{
CGAL_precondition(rows > 0);
CGAL_precondition(columns > 0);
if (m_is_symmetric) {
CGAL_precondition(rows == columns);
}
m_is_symmetric = is_symmetric;
// reserve memory for a regular 3D grid
m_triplets.reserve(rows);
}
/// Delete this object and the wrapped TAUCS matrix.
~Eigen_sparse_matrix()
{
}
/// Return the matrix number of rows
int row_dimension() const { return m_matrix.rows(); }
/// Return the matrix number of columns
int column_dimension() const { return m_matrix.cols(); }
/// Write access to a matrix coefficient: a_ij <- val.
///
/// Optimizations:
/// - For symmetric matrices, Eigen_sparse_matrix stores only the lower triangle
/// set_coef() does nothing if (i, j) belongs to the upper triangle.
/// - Caller can optimize this call by setting 'new_coef' to true
/// if the coefficient does not already exist in the matrix.
///
/// @commentheading Preconditions:
/// - 0 <= i < row_dimension().
/// - 0 <= j < column_dimension().
void set_coef(int i, int j, T val, bool new_coef = false)
{
CGAL_precondition(i < row_dimension());
CGAL_precondition(j < column_dimension());
if (m_is_symmetric && (j > i))
return;
if (m_is_already_built)
m_matrix.coeffRef(i,j)=val;
else
{
if ( new_coef == false )
{
assemble_matrix();
m_matrix.coeffRef(i,j)=val;
}
else
m_triplets.push_back(Triplet(i,j,val));
}
}
/// Write access to a matrix coefficient: a_ij <- a_ij+val.
///
/// Optimizations:
/// - For symmetric matrices, Eigen_sparse_matrix stores only the lower triangle
/// add_coef() does nothing if (i, j) belongs to the upper triangle.
///
/// @commentheading Preconditions:
/// - 0 <= i < row_dimension().
/// - 0 <= j < column_dimension().
void add_coef(int i, int j, T val)
{
CGAL_precondition(i < row_dimension());
CGAL_precondition(j < column_dimension());
if (m_is_symmetric && (j > i))
return;
if (m_is_already_built)
m_matrix.coeffRef(i,j)+=val;
else
m_triplets.push_back(Triplet(i,j,val));
}
void assemble_matrix() const
{
m_matrix.setFromTriplets(m_triplets.begin(), m_triplets.end());
m_is_already_built = true;
m_triplets.clear(); //the matrix is built and will not be rebuilt
}
const EigenType& eigen_object() const
{
if(!m_is_already_built) assemble_matrix();
// turns the matrix into compressed mode:
// -> release some memory
// -> required for some external solvers
m_matrix.makeCompressed();
return m_matrix;
}
private:
/// Eigen_sparse_matrix cannot be copied (yet)
Eigen_sparse_matrix(const Eigen_sparse_matrix& rhs);
Eigen_sparse_matrix& operator=(const Eigen_sparse_matrix& rhs);
// Fields
private:
mutable bool m_is_already_built;
typedef Eigen::Triplet<T,int> Triplet;
mutable std::vector<Triplet> m_triplets;
mutable EigenType m_matrix;
// Symmetric/hermitian?
bool m_is_symmetric;
}; // Eigen_sparse_matrix
/// The class Eigen_sparse_symmetric_matrix is a C++ wrapper
/// around a Eigen sparse matrix (type Eigen::SparseMatrix).
///
/// Symmetric matrices store only the lower triangle.
///
/// @heading Is Model for the Concepts: Model of the SparseLinearAlgebraTraits_d::Matrix concept.
///
/// @heading Parameters:
/// @param T Number type.
template<class T>
struct Eigen_sparse_symmetric_matrix
: public Eigen_sparse_matrix<T>
{
// Public types
typedef T NT;
// Public operations
/// Create a square *symmetric* matrix initialized with zeros.
Eigen_sparse_symmetric_matrix(int dim) ///< Matrix dimension.
: Eigen_sparse_matrix<T>(dim, true /* symmetric */)
{
}
/// Create a square *symmetric* matrix initialized with zeros.
///
/// @commentheading Precondition: rows == columns.
Eigen_sparse_symmetric_matrix(int rows, ///< Number of rows.
int columns) ///< Number of columns.
: Eigen_sparse_matrix<T>(rows, columns, true /* symmetric */)
{
}
};
template <class FT>
struct Eigen_matrix : public ::Eigen::Matrix<FT,::Eigen::Dynamic,::Eigen::Dynamic>
{
typedef ::Eigen::Matrix<FT,::Eigen::Dynamic,::Eigen::Dynamic> EigenType;
Eigen_matrix( std::size_t n1, std::size_t n2):EigenType(n1,n2){}
std::size_t number_of_rows () const {return this->rows();}
std::size_t number_of_columns () const {return this->cols();}
FT operator()( std::size_t i , std::size_t j ) const {return this->operator()(i,j);}
void set( std::size_t i, std::size_t j,FT value){
this->coeffRef(i,j)=value;
}
const EigenType& eigen_object() const{
return static_cast<const EigenType&>(*this);
}
};
} //namespace CGAL
#endif // CGAL_EIGEN_MATRIX_H
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