| typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double | |
| typedef Eigen::Triplet<double> T; | |
| void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n); | |
| void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename); | |
| int main(int argc, char** argv) | |
| { | |
| if(argc!=2) { | |
| std::cerr << "Error: expected one and only one argument.\n"; | |
| return -1; | |
| } | |
| int n = 300; // size of the image | |
| int m = n*n; // number of unknowns (=number of pixels) | |
| // Assembly: | |
| std::vector<T> coefficients; // list of non-zeros coefficients | |
| Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints | |
| buildProblem(coefficients, b, n); | |
| SpMat A(m,m); | |
| A.setFromTriplets(coefficients.begin(), coefficients.end()); | |
| // Solving: | |
| Eigen::SimplicialCholesky<SpMat> chol(A); // performs a Cholesky factorization of A | |
| Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side | |
| // Export the result to a file: | |
| saveAsBitmap(x, n, argv[1]); | |
| return 0; | |
| } | |