void run_test(const Matrix &mat, int k, int m)
{
DenseGenMatProd<double> op(mat);
GenEigsSolver<double, SelectionRule, DenseGenMatProd<double>> eigs(&op, k, m);
eigs.init();
int nconv = eigs.compute();
int niter = eigs.num_iterations();
int nops = eigs.num_operations();
REQUIRE( nconv > 0 );
ComplexVector evals = eigs.eigenvalues();
ComplexMatrix evecs = eigs.eigenvectors();
ComplexMatrix err = mat * evecs - evecs * evals.asDiagonal();
INFO( "nconv = " << nconv );
INFO( "niter = " << niter );
INFO( "nops = " << nops );
INFO( "||AU - UD||_inf = " << err.array().abs().maxCoeff() );
REQUIRE( err.array().abs().maxCoeff() == Approx(0.0) );
}
void run_test(const MatType& mat, int k, int m, double sigma, bool allow_fail = false)
{
typename OpTypeTrait<MatType>::OpType op(mat);
GenEigsRealShiftSolver<double, SelectionRule, typename OpTypeTrait<MatType>::OpType>
eigs(&op, k, m, sigma);
eigs.init();
int nconv = eigs.compute();
int niter = eigs.num_iterations();
int nops = eigs.num_operations();
if(allow_fail)
{
if( eigs.info() != SUCCESSFUL )
{
WARN( "FAILED on this test" );
std::cout << "nconv = " << nconv << std::endl;
std::cout << "niter = " << niter << std::endl;
std::cout << "nops = " << nops << std::endl;
return;
}
} else {
INFO( "nconv = " << nconv );
INFO( "niter = " << niter );
INFO( "nops = " << nops );
REQUIRE( eigs.info() == SUCCESSFUL );
}
ComplexVector evals = eigs.eigenvalues();
ComplexMatrix evecs = eigs.eigenvectors();
ComplexMatrix resid = mat * evecs - evecs * evals.asDiagonal();
const double err = resid.array().abs().maxCoeff();
INFO( "||AU - UD||_inf = " << err );
REQUIRE( err == Approx(0.0) );
}