345 lines
10 KiB
C
345 lines
10 KiB
C
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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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// SPDX-License-Identifier: LGPL-3.0+
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//
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// Author(s) : Gael Guennebaud
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#ifndef CGAL_EIGEN_MATRIX_H
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#define CGAL_EIGEN_MATRIX_H
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#include <CGAL/basic.h> // include basic.h before testing #defines
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#include <Eigen/Sparse>
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namespace CGAL {
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/*!
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\ingroup PkgSolver
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The class `Eigen_sparse_matrix` is a wrapper around \ref thirdpartyEigen "Eigen" matrix type
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<a href="http://eigen.tuxfamily.org/dox/classEigen_1_1SparseMatrix.html">`Eigen::SparseMatrix`</a>
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that represents general matrices, be they symmetric or not.
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\cgalModels `SparseLinearAlgebraTraits_d::Matrix`
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\tparam T Number type.
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\sa `CGAL::Eigen_vector<T>`
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\sa `CGAL::Eigen_matrix<T>`
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\sa `CGAL::Eigen_sparse_symmetric_matrix<T>`
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*/
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template<class T>
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struct Eigen_sparse_matrix
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{
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// Public types
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public:
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/// \name Types
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/// @{
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/// The internal matrix type from \ref thirdpartyEigen "Eigen".
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typedef Eigen::SparseMatrix<T> EigenType;
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typedef T NT;
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/// @}
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// Public operations
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public:
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/// Create a square matrix initialized with zeros.
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Eigen_sparse_matrix(std::size_t dim, ///< Matrix dimension.
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bool is_symmetric = false) ///< Symmetric/hermitian?
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:
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m_is_already_built(false),
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m_matrix(static_cast<int>(dim), static_cast<int>(dim))
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{
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CGAL_precondition(dim > 0);
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m_is_symmetric = is_symmetric;
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m_triplets.reserve(dim); // reserve memory for a regular 3D grid
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}
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/// Create a square matrix initialized with zeros.
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Eigen_sparse_matrix(int dim, ///< Matrix dimension.
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bool is_symmetric = false) ///< Symmetric/hermitian?
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: m_is_already_built(false),
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m_matrix(dim, dim)
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{
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CGAL_precondition(dim > 0);
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m_is_symmetric = is_symmetric;
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// reserve memory for a regular 3D grid
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m_triplets.reserve(dim);
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}
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/// Create a rectangular matrix initialized with zeros.
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///
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/// \pre rows == columns if `is_symmetric` is true.
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Eigen_sparse_matrix(std::size_t rows, ///< Number of rows.
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std::size_t columns, ///< Number of columns.
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bool is_symmetric = false) ///< Symmetric/hermitian?
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: m_is_already_built(false),
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m_matrix(static_cast<int>(rows), static_cast<int>(columns))
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{
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CGAL_precondition(rows > 0);
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CGAL_precondition(columns > 0);
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if(m_is_symmetric)
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{
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CGAL_precondition(rows == columns);
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}
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m_is_symmetric = is_symmetric;
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// reserve memory for a regular 3D grid
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m_triplets.reserve(rows);
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}
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/// Delete this object and the wrapped matrix.
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~Eigen_sparse_matrix() { }
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/// Create a rectangular matrix initialized with zeros.
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///
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/// \pre rows == columns if `is_symmetric` is true.
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Eigen_sparse_matrix(int rows, ///< Number of rows.
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int columns, ///< Number of columns.
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bool is_symmetric = false) ///< Symmetric/hermitian?
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: m_is_already_built(false),
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m_matrix(rows,columns)
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{
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CGAL_precondition(rows > 0);
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CGAL_precondition(columns > 0);
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if(is_symmetric)
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{
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CGAL_precondition(rows == columns);
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}
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m_is_symmetric = is_symmetric;
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// reserve memory for a regular 3D grid
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m_triplets.reserve(rows);
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}
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/// Return the matrix number of rows
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int row_dimension() const { return static_cast<int>(m_matrix.rows()); }
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/// Return the matrix number of columns
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int column_dimension() const { return static_cast<int>(m_matrix.cols()); }
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/// Write access to a matrix coefficient: a_ij <- val.
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///
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/// Users can optimize calls to this function by setting 'new_coef' to `true`
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/// if the coefficient does not already exist in the matrix.
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///
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/// \warning For symmetric matrices, `Eigen_sparse_matrix` only stores the lower triangle
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/// and `set_coef()` does nothing if (i, j) belongs to the upper triangle.
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///
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/// \pre 0 <= i < row_dimension().
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/// \pre 0 <= j < column_dimension().
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void set_coef(std::size_t i_, std::size_t j_, T val, bool new_coef = false)
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{
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int i = static_cast<int>(i_);
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int j = static_cast<int>(j_);
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CGAL_precondition(i < row_dimension());
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CGAL_precondition(j < column_dimension());
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if (m_is_symmetric && (j > i))
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return;
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if(m_is_already_built)
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{
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m_matrix.coeffRef(i,j) = val;
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}
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else
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{
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if(new_coef == false)
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{
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assemble_matrix();
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m_matrix.coeffRef(i,j) = val;
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}
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else
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{
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m_triplets.push_back(Triplet(i,j,val));
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}
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}
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}
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/// Write access to a matrix coefficient: a_ij <- a_ij + val.
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///
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/// \warning For symmetric matrices, Eigen_sparse_matrix only stores the lower triangle
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/// `add_coef()` does nothing if (i, j) belongs to the upper triangle.
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///
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/// \pre 0 <= i < row_dimension().
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/// \pre 0 <= j < column_dimension().
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void add_coef(int i, int j, T val)
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{
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CGAL_precondition(i < row_dimension());
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CGAL_precondition(j < column_dimension());
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if(m_is_symmetric && (j > i))
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return;
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if(m_is_already_built)
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m_matrix.coeffRef(i,j) += val;
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else
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m_triplets.push_back(Triplet(i,j,val));
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}
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/// Read access to a matrix coefficient.
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///
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/// \warning Complexity:
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/// - O(log(n)) if the matrix is already built.
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/// - O(n) if the matrix is not built.
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/// `n` being the number of entries in the matrix.
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///
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/// \pre 0 <= i < row_dimension().
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/// \pre 0 <= j < column_dimension().
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NT get_coef (unsigned int i, unsigned int j) const
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{
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CGAL_precondition(i < row_dimension());
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CGAL_precondition(j < column_dimension());
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if(m_is_symmetric && j > i)
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std::swap(i, j);
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if (m_is_already_built)
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return m_matrix.coeffRef(i,j);
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else
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{
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NT val = 0;
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for(std::size_t t=0; t<m_triplets.size(); ++t)
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{
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if(m_triplets[t].col() == j &&
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m_triplets[t].row() == i)
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val += m_triplets[t].value();
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}
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return val;
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}
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}
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/// \cond SKIP_IN_MANUAL
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void assemble_matrix() const
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{
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m_matrix.setFromTriplets(m_triplets.begin(), m_triplets.end());
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m_is_already_built = true;
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m_triplets.clear(); // the matrix is built and will not be rebuilt
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}
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/// \endcond
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/// Return the internal matrix, with type `EigenType`.
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const EigenType& eigen_object() const
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{
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if(!m_is_already_built)
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assemble_matrix();
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// turns the matrix into compressed mode:
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// -> release some memory
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// -> required for some external solvers
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m_matrix.makeCompressed();
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return m_matrix;
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}
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private:
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/// Eigen_sparse_matrix cannot be copied (yet)
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Eigen_sparse_matrix(const Eigen_sparse_matrix& rhs);
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Eigen_sparse_matrix& operator=(const Eigen_sparse_matrix& rhs);
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// Fields
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private:
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mutable bool m_is_already_built;
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typedef Eigen::Triplet<T,int> Triplet;
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mutable std::vector<Triplet> m_triplets;
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mutable EigenType m_matrix;
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// Symmetric/hermitian?
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bool m_is_symmetric;
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}; // Eigen_sparse_matrix
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/*!
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\ingroup PkgSolver
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The class `Eigen_sparse_symmetric_matrix` is a wrapper around \ref thirdpartyEigen "Eigen" matrix type
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<a href="http://eigen.tuxfamily.org/dox/classEigen_1_1SparseMatrix.html">`Eigen::SparseMatrix` </a>
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Since the matrix is symmetric, only the lower triangle part is stored.
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\cgalModels `SparseLinearAlgebraTraits_d::Matrix`
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\tparam T Number type.
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\sa `CGAL::Eigen_vector<T>`
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\sa `CGAL::Eigen_sparse_matrix<T>`
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*/
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template<class T>
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struct Eigen_sparse_symmetric_matrix
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: public Eigen_sparse_matrix<T>
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{
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/// Create a square *symmetric* matrix initialized with zeros.
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Eigen_sparse_symmetric_matrix(int dim) ///< Matrix dimension.
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: Eigen_sparse_matrix<T>(dim, true /* symmetric */)
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{
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}
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/// Create a square *symmetric* matrix initialized with zeros.
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///
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/// \pre rows == columns.
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Eigen_sparse_symmetric_matrix(int rows, ///< Number of rows.
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int columns) ///< Number of columns.
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: Eigen_sparse_matrix<T>(rows, columns, true /* symmetric */)
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{
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}
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};
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/*!
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\ingroup PkgSolver
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The class `Eigen_matrix` is a wrapper around \ref thirdpartyEigen "Eigen" matrix type
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<a href="http://eigen.tuxfamily.org/dox/classEigen_1_1Matrix.html">`Eigen::Matrix`</a>.
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\cgalModels `SvdTraits::Matrix`
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\tparam T Number type.
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\sa `CGAL::Eigen_vector<T>`
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\sa `CGAL::Eigen_sparse_matrix<T>`
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\sa `CGAL::Eigen_sparse_symmetric_matrix<T>`
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*/
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template <class FT>
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struct Eigen_matrix
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: public ::Eigen::Matrix<FT, ::Eigen::Dynamic, ::Eigen::Dynamic>
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{
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/// The internal matrix type from \ref thirdpartyEigen "Eigen".
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typedef ::Eigen::Matrix<FT, ::Eigen::Dynamic, ::Eigen::Dynamic> EigenType;
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/// Construct a matrix with `nr` rows and `nc` columns.
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Eigen_matrix(std::size_t nr, std::size_t nc) : EigenType(nr, nc) { }
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/// Return the matrix number of rows.
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std::size_t number_of_rows() const { return this->rows(); }
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/// Return the matrix number of columns.
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std::size_t number_of_columns() const { return this->cols(); }
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/// Return the value of the matrix at position (i,j).
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FT operator()( std::size_t i , std::size_t j ) const { return EigenType::operator()(i,j); }
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/// Write access to a matrix coefficient: `a_ij` <- `val`.
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void set(std::size_t i, std::size_t j, FT value) { this->coeffRef(i,j) = value; }
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/// Return the internal matrix, with type `EigenType`.
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const EigenType& eigen_object() const { return static_cast<const EigenType&>(*this); }
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};
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} //namespace CGAL
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#endif // CGAL_EIGEN_MATRIX_H
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