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...
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.