eigen/doc/special_examples/Tutorial_sparse_example.cpp

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#include <Eigen/Sparse>
#include <vector>
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)
{
int n = 300; // size of the image
int m = n*n; // number of unknows (=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;
}