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| author | Stanislaw Halik <sthalik@misaki.pl> | 2016-09-18 12:42:15 +0200 |
|---|---|---|
| committer | Stanislaw Halik <sthalik@misaki.pl> | 2016-11-02 15:12:04 +0100 |
| commit | 44861dcbfeee041223c4aac1ee075e92fa4daa01 (patch) | |
| tree | 6dfdfd9637846a7aedd71ace97d7d2ad366496d7 /eigen/doc/special_examples/Tutorial_sparse_example.cpp | |
| parent | f3fe458b9e0a29a99a39d47d9a76dc18964b6fec (diff) | |
update
Diffstat (limited to 'eigen/doc/special_examples/Tutorial_sparse_example.cpp')
| -rw-r--r-- | eigen/doc/special_examples/Tutorial_sparse_example.cpp | 32 |
1 files changed, 32 insertions, 0 deletions
diff --git a/eigen/doc/special_examples/Tutorial_sparse_example.cpp b/eigen/doc/special_examples/Tutorial_sparse_example.cpp new file mode 100644 index 0000000..002f19f --- /dev/null +++ b/eigen/doc/special_examples/Tutorial_sparse_example.cpp @@ -0,0 +1,32 @@ +#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; +} + |
