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#include <Eigen/Dense>
#include <Spectra/DavidsonSymEigsSolver.h>
#include <Spectra/MatOp/DenseSymMatProd.h>
#include <iostream>
using namespace Spectra;
int main()
{
Eigen::Index n = 1000;
Eigen::MatrixXd mat = 0.03 * Eigen::MatrixXd::Random(n, n);
Eigen::MatrixXd mat1 = mat + mat.transpose();
for (Eigen::Index i = 0; i < n; i++)
{
mat1(i, i) += i + 1;
}
DenseSymMatProd<double> op_dense(mat1); // Create the Matrix Product operation
Eigen::Index num_of_eigenvalues = 5;
DavidsonSymEigsSolver<DenseSymMatProd<double>> solver(op_dense, num_of_eigenvalues); // Create Solver
Eigen::Index iterations = 100;
double tolerance = 1e-3;
int nconv = solver.compute(SortRule::LargestAlge, iterations, tolerance);
// Retrieve results
Eigen::VectorXd evalues;
if (solver.info() == CompInfo::Successful)
{
evalues = solver.eigenvalues();
std::cout << nconv << " Eigenvalues found:\n"
<< evalues << std::endl;
}
else
{
std::cout << "Calculation failed" << std::endl;
}
return 0;
}
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