I have 2 matrices.
Code:
F =
-0.1000 0.0200 0.0200 0.0104
1.0000 0 0 0
0 1.0000 0 0
0 0 1.0000 0
F1 =
1 0 0 0
0 1 0 0
0 0 1 0
0 0 0 1
I need to calculate the generalized eigenvalues of these 2 matrices in ALGLIB.
I found alglib::smatrixgevd() function. But as far as I can see, it doesn't return complex values.
I've already done that in MATLAB and Visual Studio (Eigen library).
1) Matlab code:
Code:
F=[-0.1,0.02,0.02,0.0104;1,0,0,0;0,1,0,0;0,0,1,0];
F1=[1,0,0,0;0,1,0,0;0,0,1,0;0,0,0,1];
eigenvalues = eig(F,F1);
|---------------------------------------------------------------------------|
The results is:
eigenvalues =
0.3531 + 0.0000i
-0.0723 + 0.3003i
-0.0723 - 0.3003i
-0.3086 + 0.0000i
2) C++ code (Eigen library):
Code:
#include <iostream>
#include <Eigen/Eigenvalues>
using namespace std;
using Eigen::MatrixXd;
using Eigen::VectorXcd;
using Eigen::GeneralizedEigenSolver;
int main()
{
//--- 1) Matrices
MatrixXd F_MX(4,4);
F_MX.row(0) << -0.1, 0.02, 0.02, 0.0104;
F_MX.row(1) << 1, 0, 0, 0;
F_MX.row(2) << 0, 1, 0, 0;
F_MX.row(3) << 0, 0, 1, 0;
MatrixXd F1_MX = MatrixXd::Identity(4, 4);
//--- 2) the generalized eigenvalues of square matrices F_MX and F1_MX
GeneralizedEigenSolver<MatrixXd> ges;
ges.compute(F_MX, F1_MX,true);
cout << "The (complex) generalized eigenvalues are (alphas./beta): \n" << ges.eigenvalues() << endl;
}
|---------------------------------------------------------------------------|
The results is:
eigenvalues =
(0.353145,-0)
(-0.0722619,-0.300335)
(-0.0722619,0.300335)
(-0.308622,0)
Please give a hint to solving the problem.
Thanks.
Login
Register
FAQ
Search
