/usr/include/CGAL/OpenNL/sparse_matrix.h is in libcgal-dev 4.7-4.
This file is owned by root:root, with mode 0o644.
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/*
* author: Bruno Levy, INRIA, project ALICE
* website: http://www.loria.fr/~levy/software
*
* This library is free software; 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.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*
* Scientific work that use this software can reference the website and
* the following publication:
*
* @INPROCEEDINGS {levy:NMDGP:05,
* AUTHOR = Bruno Levy,
* TITLE = Numerical Methods for Digital Geometry Processing,
* BOOKTITLE =Israel Korea Bi-National Conference,
* YEAR=November 2005,
* URL=http://www.loria.fr/~levy/php/article.php?pub=../publications/papers/2005/Numerics
* }
*
* Laurent Saboret 01/2005: Change for CGAL:
* - Added OpenNL namespace
* - SparseMatrix is now a model of the SparseLinearAlgebraTraits_d::Matrix concept
*/
#ifndef __OPENNL_SPARSE_MATRIX__
#define __OPENNL_SPARSE_MATRIX__
#include <CGAL/OpenNL/full_vector.h>
#include <CGAL/assertions.h>
#include <CGAL/use.h>
#include <vector>
#include <cstdlib>
namespace OpenNL {
//________________________________________________________________
// Class SparseMatrix
// Model of the SparseLinearAlgebraTraits_d::Matrix concept
template <class T> class SparseMatrix
{
// Public types
public:
typedef T CoeffType ;
// added for SparseLinearAlgebraTraits_d::Matrix concept
typedef T NT;
struct Coeff {
Coeff() { }
Coeff(unsigned int i, T val) : index(i), a(val) { }
unsigned int index ;
T a ;
} ;
//__________________________________________________
/**
* A row or a column of a SparseMatrix. The row/column is
* compressed, and stored in the form of a list of
* (value,index) couples.
*/
class Row : public std::vector<Coeff> {
typedef typename std::vector<Coeff> superclass ;
public:
/** a_{index} <- a_{index} + val */
void add_coef(unsigned int index, T val)
{
// search for coefficient in superclass vector
for(typename superclass::iterator it = superclass::begin() ;
it != superclass::end() ;
it++)
{
if(it->index == index) {
it->a += val ; // +=
return ;
}
}
// coefficient doesn't exist yet if we reach this point
superclass::push_back(Coeff(index, val)) ;
}
// a_{index} <- val
// (added for SparseLinearAlgebraTraits_d::Matrix concept)
//
// Optimization:
// - Caller can optimize this call by setting 'new_coef' to true
// if the coefficient does not already exists in the matrix.
void set_coef(unsigned int index, T val, bool new_coef)
{
if (!new_coef)
{
// search for coefficient in superclass vector
for(typename superclass::iterator it = superclass::begin() ;
it != superclass::end() ;
it++)
{
if(it->index == index) {
it->a = val ; // =
return ;
}
}
}
// coefficient doesn't exist yet if we reach this point
superclass::push_back(Coeff(index, val)) ;
}
// return a_{index} (0 by default)
// (added for SparseLinearAlgebraTraits_d::Matrix concept)
T get_coef(unsigned int index) const
{
// search for coefficient in superclass vector
for(typename superclass::const_iterator it = superclass::begin() ;
it != superclass::end() ;
it++)
{
if(it->index == index)
return it->a ; // return value
}
// coefficient doesn't exist if we reach this point
return 0 ;
}
} ;
// Public operations
public:
//__________ constructors / destructor _____
// Create a square matrix initialized with zeros
SparseMatrix(unsigned int dim) {
CGAL_assertion(dim > 0);
dimension_ = dim ;
row_ = new Row[dimension_] ;
}
// Create a rectangular matrix initialized with zeros
// (added for SparseLinearAlgebraTraits_d::Matrix concept)
// WARNING: this class supports square matrices only
SparseMatrix (unsigned int rows, unsigned int columns ) {
CGAL_USE(rows);
CGAL_assertion(rows == columns);
CGAL_assertion(columns > 0);
dimension_ = columns ;
row_ = new Row[dimension_] ;
}
~SparseMatrix() {
delete[] row_ ;
row_ = NULL ;
}
//___________ access ________________________
// Return the matrix dimension
unsigned int dimension() const { return dimension_ ; }
// Added for SparseLinearAlgebraTraits_d::Matrix concept:
// Return the matrix number of rows
unsigned int row_dimension() const { return dimension(); }
// Return the matrix number of columns
unsigned int column_dimension() const { return dimension(); }
Row& row(unsigned int i) {
CGAL_assertion(i < dimension_) ;
return row_[i] ;
}
const Row& row(unsigned int i) const {
CGAL_assertion(i < dimension_) ;
return row_[i] ;
}
// Read access to 1 matrix coefficient
// (added for SparseLinearAlgebraTraits_d::Matrix concept)
//
// Preconditions:
// * 0 <= i < row_dimension()
// * 0 <= j < column_dimension()
NT get_coef (unsigned int i, unsigned int j) const {
CGAL_assertion(i < dimension_) ;
CGAL_assertion(j < dimension_) ;
return row(i).get_coef(j) ;
}
// Write access to 1 matrix coefficient: a_ij <- a_ij + val
//
// Preconditions:
// * 0 <= i < row_dimension()
// * 0 <= j < column_dimension()
void add_coef(unsigned int i, unsigned int j, T val) {
CGAL_assertion(i < dimension_) ;
CGAL_assertion(j < dimension_) ;
row(i).add_coef(j, val) ;
}
// Write access to 1 matrix coefficient: a_ij <- val
//(added for SparseLinearAlgebraTraits_d::Matrix concept)
//
// Optimization:
// - Caller can optimize this call by setting 'new_coef' to true
// if the coefficient does not already exists in the matrix.
//
// Preconditions:
// - 0 <= i < row_dimension().
// - 0 <= j < column_dimension().
void set_coef(unsigned int i, unsigned int j, NT val, bool new_coef = false) {
CGAL_assertion(i < dimension_) ;
CGAL_assertion(j < dimension_) ;
row(i).set_coef(j, val, new_coef) ;
}
/**
* removes all the coefficients and frees the allocated
* space.
*/
void clear() {
for(unsigned int i=0; i<dimension_; i++) {
row(i).clear() ;
}
}
private:
unsigned int dimension_ ;
Row* row_ ;
// SparseMatrix cannot be copied
// (for the moment, could be implemented if needed).
SparseMatrix(const SparseMatrix& rhs) ;
SparseMatrix& operator=(const SparseMatrix& rhs) ;
} ;
/** y <- M*x */
template <class T>
void mult(const SparseMatrix<T>& M, const FullVector<T>& x, FullVector<T>& y) {
unsigned int N = M.dimension() ;
CGAL_assertion(x.dimension() == N) ;
CGAL_assertion(y.dimension() == N) ;
for(unsigned int i=0; i<N; i++) {
y[i] = 0 ;
const typename SparseMatrix<T>::Row& R = M.row(i) ;
for(unsigned int jj=0; jj<R.size(); jj++) {
unsigned int j = R[jj].index ;
y[i] += R[jj].a * x[j] ;
}
}
}
} // namespace OpenNL
#endif // __OPENNL_SPARSE_MATRIX__
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