mirror of
https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Clang-format tests, examples, libraries, benchmarks, etc.
This commit is contained in:
Antonio Sánchez
committed by
Rasmus Munk Larsen
Rasmus Munk Larsen
parent
3252ecc7a4
commit
46e9cdb7fe
@@ -9,7 +9,7 @@
|
||||
#include <Eigen/IterativeLinearSolvers>
|
||||
#include <Eigen/LU>
|
||||
#include <unsupported/Eigen/SparseExtra>
|
||||
//#include <Eigen/SparseLU>
|
||||
// #include <Eigen/SparseLU>
|
||||
#include <Eigen/SuperLUSupport>
|
||||
// #include <unsupported/Eigen/src/IterativeSolvers/Scaling.h>
|
||||
#include <bench/BenchTimer.h>
|
||||
@@ -17,109 +17,113 @@
|
||||
using namespace std;
|
||||
using namespace Eigen;
|
||||
|
||||
int main(int argc, char **args)
|
||||
{
|
||||
SparseMatrix<double, ColMajor> A;
|
||||
int main(int argc, char **args) {
|
||||
SparseMatrix<double, ColMajor> A;
|
||||
typedef SparseMatrix<double, ColMajor>::Index Index;
|
||||
typedef Matrix<double, Dynamic, Dynamic> DenseMatrix;
|
||||
typedef Matrix<double, Dynamic, 1> DenseRhs;
|
||||
VectorXd b, x, tmp;
|
||||
BenchTimer timer,totaltime;
|
||||
//SparseLU<SparseMatrix<double, ColMajor> > solver;
|
||||
// SuperLU<SparseMatrix<double, ColMajor> > solver;
|
||||
ConjugateGradient<SparseMatrix<double, ColMajor>, Lower,IncompleteCholesky<double,Lower> > solver;
|
||||
ifstream matrix_file;
|
||||
BenchTimer timer, totaltime;
|
||||
// SparseLU<SparseMatrix<double, ColMajor> > solver;
|
||||
// SuperLU<SparseMatrix<double, ColMajor> > solver;
|
||||
ConjugateGradient<SparseMatrix<double, ColMajor>, Lower, IncompleteCholesky<double, Lower> > solver;
|
||||
ifstream matrix_file;
|
||||
string line;
|
||||
int n;
|
||||
int n;
|
||||
// Set parameters
|
||||
// solver.iparm(IPARM_THREAD_NBR) = 4;
|
||||
// solver.iparm(IPARM_THREAD_NBR) = 4;
|
||||
/* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
|
||||
if (argc < 2) assert(false && "please, give the matrix market file ");
|
||||
|
||||
|
||||
timer.start();
|
||||
totaltime.start();
|
||||
loadMarket(A, args[1]);
|
||||
cout << "End charging matrix " << endl;
|
||||
bool iscomplex=false, isvector=false;
|
||||
bool iscomplex = false, isvector = false;
|
||||
int sym;
|
||||
getMarketHeader(args[1], sym, iscomplex, isvector);
|
||||
if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
|
||||
if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
|
||||
if (sym != 0) { // symmetric matrices, only the lower part is stored
|
||||
SparseMatrix<double, ColMajor> temp;
|
||||
if (iscomplex) {
|
||||
cout << " Not for complex matrices \n";
|
||||
return -1;
|
||||
}
|
||||
if (isvector) {
|
||||
cout << "The provided file is not a matrix file\n";
|
||||
return -1;
|
||||
}
|
||||
if (sym != 0) { // symmetric matrices, only the lower part is stored
|
||||
SparseMatrix<double, ColMajor> temp;
|
||||
temp = A;
|
||||
A = temp.selfadjointView<Lower>();
|
||||
}
|
||||
timer.stop();
|
||||
|
||||
|
||||
n = A.cols();
|
||||
// ====== TESTS FOR SPARSE TUTORIAL ======
|
||||
// cout<< "OuterSize " << A.outerSize() << " inner " << A.innerSize() << endl;
|
||||
// SparseMatrix<double, RowMajor> mat1(A);
|
||||
// SparseMatrix<double, RowMajor> mat2;
|
||||
// cout << " norm of A " << mat1.norm() << endl; ;
|
||||
// PermutationMatrix<Dynamic, Dynamic, int> perm(n);
|
||||
// perm.resize(n,1);
|
||||
// perm.indices().setLinSpaced(n, 0, n-1);
|
||||
// mat2 = perm * mat1;
|
||||
// mat.subrows();
|
||||
// mat2.resize(n,n);
|
||||
// mat2.reserve(10);
|
||||
// mat2.setConstant();
|
||||
// std::cout<< "NORM " << mat1.squaredNorm()<< endl;
|
||||
// cout<< "OuterSize " << A.outerSize() << " inner " << A.innerSize() << endl;
|
||||
// SparseMatrix<double, RowMajor> mat1(A);
|
||||
// SparseMatrix<double, RowMajor> mat2;
|
||||
// cout << " norm of A " << mat1.norm() << endl; ;
|
||||
// PermutationMatrix<Dynamic, Dynamic, int> perm(n);
|
||||
// perm.resize(n,1);
|
||||
// perm.indices().setLinSpaced(n, 0, n-1);
|
||||
// mat2 = perm * mat1;
|
||||
// mat.subrows();
|
||||
// mat2.resize(n,n);
|
||||
// mat2.reserve(10);
|
||||
// mat2.setConstant();
|
||||
// std::cout<< "NORM " << mat1.squaredNorm()<< endl;
|
||||
|
||||
cout<< "Time to load the matrix " << timer.value() <<endl;
|
||||
cout << "Time to load the matrix " << timer.value() << endl;
|
||||
/* Fill the right hand side */
|
||||
|
||||
// solver.set_restart(374);
|
||||
// solver.set_restart(374);
|
||||
if (argc > 2)
|
||||
loadMarketVector(b, args[2]);
|
||||
else
|
||||
{
|
||||
else {
|
||||
b.resize(n);
|
||||
tmp.resize(n);
|
||||
// tmp.setRandom();
|
||||
for (int i = 0; i < n; i++) tmp(i) = i;
|
||||
b = A * tmp ;
|
||||
// tmp.setRandom();
|
||||
for (int i = 0; i < n; i++) tmp(i) = i;
|
||||
b = A * tmp;
|
||||
}
|
||||
// Scaling<SparseMatrix<double> > scal;
|
||||
// scal.computeRef(A);
|
||||
// b = scal.LeftScaling().cwiseProduct(b);
|
||||
// Scaling<SparseMatrix<double> > scal;
|
||||
// scal.computeRef(A);
|
||||
// b = scal.LeftScaling().cwiseProduct(b);
|
||||
|
||||
/* Compute the factorization */
|
||||
cout<< "Starting the factorization "<< endl;
|
||||
cout << "Starting the factorization " << endl;
|
||||
timer.reset();
|
||||
timer.start();
|
||||
cout<< "Size of Input Matrix "<< b.size()<<"\n\n";
|
||||
cout<< "Rows and columns "<< A.rows() <<" " <<A.cols() <<"\n";
|
||||
timer.start();
|
||||
cout << "Size of Input Matrix " << b.size() << "\n\n";
|
||||
cout << "Rows and columns " << A.rows() << " " << A.cols() << "\n";
|
||||
solver.compute(A);
|
||||
// solver.analyzePattern(A);
|
||||
// solver.factorize(A);
|
||||
// solver.analyzePattern(A);
|
||||
// solver.factorize(A);
|
||||
if (solver.info() != Success) {
|
||||
std::cout<< "The solver failed \n";
|
||||
return -1;
|
||||
std::cout << "The solver failed \n";
|
||||
return -1;
|
||||
}
|
||||
timer.stop();
|
||||
float time_comp = timer.value();
|
||||
cout <<" Compute Time " << time_comp<< endl;
|
||||
|
||||
timer.stop();
|
||||
float time_comp = timer.value();
|
||||
cout << " Compute Time " << time_comp << endl;
|
||||
|
||||
timer.reset();
|
||||
timer.start();
|
||||
x = solver.solve(b);
|
||||
// x = scal.RightScaling().cwiseProduct(x);
|
||||
// x = scal.RightScaling().cwiseProduct(x);
|
||||
timer.stop();
|
||||
float time_solve = timer.value();
|
||||
cout<< " Time to solve " << time_solve << endl;
|
||||
|
||||
float time_solve = timer.value();
|
||||
cout << " Time to solve " << time_solve << endl;
|
||||
|
||||
/* Check the accuracy */
|
||||
VectorXd tmp2 = b - A*x;
|
||||
double tempNorm = tmp2.norm()/b.norm();
|
||||
cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
|
||||
// cout << "Iterations : " << solver.iterations() << "\n";
|
||||
|
||||
VectorXd tmp2 = b - A * x;
|
||||
double tempNorm = tmp2.norm() / b.norm();
|
||||
cout << "Relative norm of the computed solution : " << tempNorm << "\n";
|
||||
// cout << "Iterations : " << solver.iterations() << "\n";
|
||||
|
||||
totaltime.stop();
|
||||
cout << "Total time " << totaltime.value() << "\n";
|
||||
// std::cout<<x.transpose()<<"\n";
|
||||
|
||||
// std::cout<<x.transpose()<<"\n";
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user