Is it possible in Eigen to do the equivalent of the following operation in Matlab?
A=rand(10,10);
indices = [2,5,6,8,9];
B=A(indices,indices)
I want to have a submatrix as a view on the original matrix with given, non consecutive indices. The best option would be to have a shared memory view of the original matrix, is this possible?
I've figured out a method that works but is not very fast, since it involves non vectorized for loops:
MatrixXi slice(const MatrixXi &A, const std::set<int> &indices)
{
int n = indices.size();
Eigen::MatrixXi B;
B.setZero(n,n);
std::set<int>::const_iterator iInd1 = indices.begin();
for (int i=0; i<n;++i)
{
std::set<int>::const_iterator iInd2=indices.begin();
for (int j=0; j<n;++j)
{
B(i,j) = A.coeffRef(*iInd1,*iInd2);
++iInd2;
}
++iInd1;
}
return B;
}
How can this be made faster?
