In MATLAB, I can do the following
A = [1 2 3; 4 5 6];
A(:)
to get:
ans =
1
4
2
5
3
6
How would I do this with an Eigen3 Matrix?
The best way is to use Map:
Map<VectorXd> v(A.data(),A.size());
because in this case Eigen knows at compile time that you now have a 1D vector.
Of course, the result will depend on the storage order of A, that is, for a column major matrix (the default):
[1 4 2 5 3 6]^T
and for a row-major one:
[1 2 3 4 5 6]^T