Go to the documentation of this file.
    4 #define EIGEN_SUPERLU_SUPPORT 
    5 #define EIGEN_UMFPACK_SUPPORT 
    6 #include <Eigen/Sparse> 
   26 #define MINDENSITY 0.0004 
   35   for (int _j=0; _j<NBTRIES; ++_j) { \ 
   37     for (int _k=0; _k<REPEAT; ++_k) { \ 
   48   std::cout << 
name << 
"..." << std::flush;
 
   56     std::cout << 
":\t FAILED" << endl;
 
   65     std::cout << 
"  solve:\t" << 
timer.
value() << endl;
 
   67     std::cout << 
"  solve:\t" << 
" FAILED" << endl;
 
   72 int main(
int argc, 
char *argv[])
 
   82   bool densedone = 
false;
 
   95       std::cout << 
"Eigen Dense\t" << 
density*100 << 
"%\n";
 
  103       std::cout << 
"Eigen/dense:\t" << 
timer.
value() << endl;
 
  109       std::cout << 
"  solve:\t" << 
timer.
value() << endl;
 
  115     #ifdef EIGEN_UMFPACK_SUPPORT 
  117     doEigen<Eigen::UmfPack>(
"Eigen/UmfPack (auto)", sm1, 
b, 
x, 0);
 
  120     #ifdef EIGEN_SUPERLU_SUPPORT 
  125     doEigen<Eigen::SuperLU>(
"Eigen/SuperLU (COLAMD)", sm1, 
b, 
x, Eigen::ColApproxMinimumDegree);
 
  
void doEigen(const char *name, const EigenSparseMatrix &sm1, const VectorX &b, VectorX &x, int flags=0)
int main(int argc, char *argv[])
Annotation for function names.
void eiToDense(const EigenSparseMatrix &src, DenseMatrix &dst)
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix &dst)
set noclip points set clip one set noclip two set bar set border lt lw set xdata set ydata set zdata set x2data set y2data set boxwidth set dummy x
LU decomposition of a matrix with complete pivoting, and related features.
double value(int TIMER=CPU_TIMER) const
cout<< "Here is the matrix m:"<< endl<< m<< endl;Eigen::FullPivLU< Matrix5x3 > lu(m)
Matrix< Scalar, Dynamic, Dynamic > DenseMatrix
Matrix< Scalar, Dynamic, 1 > VectorX
Sparse supernodal LU factorization for general matrices.
gtsam
Author(s): 
autogenerated on Wed May 28 2025 03:03:23