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;
53 std::cout <<
":\t" << timer.
value() << endl;
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);
Matrix< Scalar, Dynamic, Dynamic > DenseMatrix
Matrix< Scalar, Dynamic, 1 > VectorX
const Solve< SparseLU< _MatrixType, _OrderingType >, Rhs > solve(const MatrixBase< Rhs > &b) const
Sparse supernodal LU factorization for general matrices.
int main(int argc, char *argv[])
void eiToDense(const EigenSparseMatrix &src, DenseMatrix &dst)
cout<< "Here is the matrix m:"<< endl<< m<< endl;Eigen::FullPivLU< Matrix5x3 > lu(m)
void fillMatrix(float density, int rows, int cols, EigenSparseMatrix &dst)
void doEigen(const char *name, const EigenSparseMatrix &sm1, const VectorX &b, VectorX &x, int flags=0)
double value(int TIMER=CPU_TIMER) const
LU decomposition of a matrix with complete pivoting, and related features.
Annotation for function names.
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const Solve< FullPivLU, Rhs > solve(const MatrixBase< Rhs > &b) const