Copying upper MatrixXd to lower MatrixXd (Eigen3) C++ library
c++, eigen, eigenvalue, eigenvector
Solution
I assume here that you are referring to working with the Eigen3 c++ library. This is not clear from your question. if not, you should consider it. In any case, within Eigen, there is no need to actually copy the triangular part, to get a selfadjoint matrix. Eigen has the concept of views, and you can use a self adjoint view in order to perform an operation like e.g.
using namespace Eigen;
MatrixXd m(m,n);
...
(generate uppper triangular entries in m)
...
VectorXd r(n), p(n);
r = m.selfadjointView<Upper>() * p;
here is a small example to illustrate using fixed size matrices:
#include <Eigen/Core>
using namespace std;
using namespace Eigen;
int main()
{
Matrix2d m,c;
m << 1, 2,
0, 1;
Vector2d x(0,2), r;
// perform copy operation
c = m.selfadjointView<Upper>();
cout << c << endl;
// directly apply selfadjoint view in matrix operation
// (no entries are copied)
r = m.selfadjointView<Upper>() * x;
}
the output will be [1, 2, 2, 1]. now, the result in `r` is the same as if you had used `c * x` instead. Just that there is no need for copying the values in the original matrix to make it selfadjoint.
Problem
I've got a lower triangular MatrixXd and I want to copy its lower values to the upper side as it'll become a symmetric matrix. How can I do it? So far I've done: ``` MatrixXd m(n,n); ..... //do something with m for(j=0; j < n; j++) { for(i=0; i<j; i++) { m(i,j) = m(j,i); } } ``` Is there a fastest way to do it? I was thinking of some internal method that is able to "copy" the lower triangular matrix to the upper. Say I've got this matrix, we call `m`: ``` 1 2 3 4 5 6 7 8 9 ``` what I need to obtain in `m` is : ``` 1 4 7 4 5 8 7 8 9 ``` I also know you can get the upper or the lower part of the matrix to do something: ``` MatrixXd m1(n,n); m1 = m.triangularView<Eigen::Upper>(); cout << m1 <<endl; 1 2 3 0 5 6 0 0 9 ``` But I can't yet get what I want...