libcgal-dev 4.7-4 / usr / include / CGAL / Eigen_matrix.h

// Copyright (c) 2012  INRIA Bordeaux Sud-Ouest (France), All rights reserved.
//
// 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(std::size_t  dim,                   ///< Matrix dimension.
                      bool is_symmetric = false)  ///< Symmetric/hermitian?
    : m_is_already_built(false), m_matrix(static_cast<int>(dim),static_cast<int>(dim))
  {
    CGAL_precondition(dim > 0);

    m_is_symmetric = is_symmetric;
    // reserve memory for a regular 3D grid
    m_triplets.reserve(dim);
  }

  /// 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(std::size_t  rows,                 ///< Number of rows.
                      std::size_t  columns,              ///< Number of columns.
                      bool is_symmetric = false) ///< Symmetric/hermitian?
    : m_is_already_built(false), m_matrix(static_cast<int>(rows),static_cast<int>(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 matrix.
  ~Eigen_sparse_matrix()
  {
  }

  /// 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 (is_symmetric) {
        CGAL_precondition(rows == columns);
    }

    m_is_symmetric = is_symmetric;
    // reserve memory for a regular 3D grid
    m_triplets.reserve(rows);
  }

  /// 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(std::size_t i_, std::size_t j_, T  val, bool new_coef = false)
  {
    int i = static_cast<int>(i_);
    int j = static_cast<int>(j_);
    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