1 #include <Eigen/Sparse>
2 #include <vector>
3
4 typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
5 typedef Eigen::Triplet<double> T;
6
7 void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n);
8 void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename);
9
main(int argc,char ** argv)10 int main(int argc, char** argv)
11 {
12 int n = 300; // size of the image
13 int m = n*n; // number of unknows (=number of pixels)
14
15 // Assembly:
16 std::vector<T> coefficients; // list of non-zeros coefficients
17 Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints
18 buildProblem(coefficients, b, n);
19
20 SpMat A(m,m);
21 A.setFromTriplets(coefficients.begin(), coefficients.end());
22
23 // Solving:
24 Eigen::SimplicialCholesky<SpMat> chol(A); // performs a Cholesky factorization of A
25 Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side
26
27 // Export the result to a file:
28 saveAsBitmap(x, n, argv[1]);
29
30 return 0;
31 }
32
33