\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)

CGAL 4.8 - CGAL and Solvers

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Solver_interface/sparse_solvers.cpp
#include <CGAL/Eigen_solver_traits.h>
#include <CGAL/Eigen_matrix.h>
typedef CGAL::Eigen_solver_traits<> Eigen_solver;
typedef Eigen_solver::NT FT;
typedef Eigen_solver::Matrix Eigen_matrix;
typedef Eigen_solver::Vector Eigen_vector;
int main(void)
{
srand (static_cast<unsigned int>(time (NULL)));
std::size_t degree = 3000;
std::size_t nb_nonzero_coef = 100;
Eigen_vector B (degree); // Zero vector
Eigen_matrix A (degree);
Eigen_vector diag (degree);
// Randomly make some coefficients of the matrix non-zero
for (std::size_t i = 0; i < nb_nonzero_coef; ++ i)
{
int x = rand () % degree;
int y = rand () % degree;
FT value = rand () / (FT)RAND_MAX;
A.add_coef (x, y, value);
A.add_coef (y, x, value);
}
// Create sparse matrix
A.assemble_matrix();
Eigen_vector X (degree);
FT d;
Eigen_solver solver;
if (!(solver.linear_solver (A, B, X, d)))
{
std::cerr << "Error: linear solver failed" << std::endl;
return -1;
}
std::cerr << "Linear solve succeeded" << std::endl;
return 0;
}