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4 #include <Eigen/Sparse>
26 #define MINDENSITY 0.0004
35 for (int _j=0; _j<NBTRIES; ++_j) { \
37 for (int _k=0; _k<REPEAT; ++_k) { \
49 dst.fill(
j,
j) = internal::random<Scalar>(10,20);
52 Scalar v = (internal::random<float>(0,1) <
density) ? internal::random<Scalar>() : 0;
61 #include <Eigen/Cholesky>
66 std::cout <<
name <<
"..." << std::flush;
69 SparseLLT<EigenSparseSelfAdjointMatrix,Backend> chol(sm1, flags);
73 std::cout <<
" nnz: " << sm1.
nonZeros() <<
" => " << chol.matrixL().nonZeros() <<
"\n";
77 int main(
int argc,
char *argv[])
84 VectorXf
b = VectorXf::Random(
cols);
85 VectorXf
x = VectorXf::Random(
cols);
87 bool densedone =
false;
93 std::cout <<
"Generate sparse matrix (might take a while)...\n";
95 std::cout <<
"DONE\n\n";
102 std::cout <<
"Eigen Dense\t" <<
density*100 <<
"%\n";
106 m1.diagonal() *= 0.5;
115 std::cout <<
"dense:\t" <<
timer.
value() << endl;
121 std::cout <<
"dense: " <<
"nnz = " << count <<
"\n";
127 doEigen<Eigen::DefaultBackend>(
"Eigen/Sparse", sm1, Eigen::IncompleteFactorization);
129 #ifdef EIGEN_CHOLMOD_SUPPORT
130 doEigen<Eigen::Cholmod>(
"Eigen/Cholmod", sm1, Eigen::IncompleteFactorization);
133 #ifdef EIGEN_TAUCS_SUPPORT
134 doEigen<Eigen::Taucs>(
"Eigen/Taucs", sm1, Eigen::IncompleteFactorization);
140 taucs_ccs_matrix
A = sm1.asTaucsMatrix();
146 taucs_ccs_matrix* chol = taucs_ccs_factor_llt(&
A, 0, 0);
150 for (
int i=chol->colptr[
j]; i<chol->colptr[
j+1]; ++
i)
151 std::cout << chol->values.d[
i] <<
" ";
156 #ifdef EIGEN_CHOLMOD_SUPPORT
163 A = sm1.asCholmodMatrix();
175 c.method [0].ordering = CHOLMOD_NATURAL;
181 std::cout <<
"cholmod/analyze:\t" <<
timer.
value() << endl;
184 cholmod_factorize(&
A,
L, &
c);
186 std::cout <<
"cholmod/factorize:\t" <<
timer.
value() << endl;
188 cholmod_sparse* cholmat = cholmod_factor_to_sparse(
L, &
c);
190 cholmod_print_factor(
L,
"Factors", &
c);
192 cholmod_print_sparse(cholmat,
"Chol", &
c);
193 cholmod_write_sparse(
stdout, cholmat, 0, 0, &
c);
void doEigen(const char *name, const EigenSparseSelfAdjointMatrix &sm1, int flags=0)
idx_t idx_t idx_t idx_t idx_t * perm
Annotation for function names.
A versatible sparse matrix representation.
void eiToDense(const EigenSparseMatrix &src, DenseMatrix &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
EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const Scalar &x, const OtherScalar &y, const typename NumTraits< Scalar >::Real &precision=NumTraits< Scalar >::dummy_precision())
Matrix< SCALARA, Dynamic, Dynamic, opt_A > A
double value(int TIMER=CPU_TIMER) const
void fillSpdMatrix(float density, int rows, int cols, EigenSparseSelfAdjointMatrix &dst)
Traits::MatrixL matrixL() const
int main(int argc, char *argv[])
Standard Cholesky decomposition (LL^T) of a matrix and associated features.
Array< int, Dynamic, 1 > v
Matrix< Scalar, Dynamic, Dynamic > DenseMatrix
internal::nested_eval< T, 1 >::type eval(const T &xpr)
SparseMatrix< Scalar, SelfAdjoint|LowerTriangular > EigenSparseSelfAdjointMatrix
gtsam
Author(s):
autogenerated on Fri Nov 1 2024 03:35:33