|  | #include <Eigen/Sparse> | 
|  | #include <vector> | 
|  | #include <iostream> | 
|  |  | 
|  | 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; | 
|  | } | 
|  |  |