Home | History | Annotate | Download | only in special_examples
      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 
     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