The main problem is that it cannot really be determined before whether the
eigen solution is real or complex before the calculation is over in
contrast to the `sqrt` case. I think it would be a little annoying to get a
complex result from a symmetric matrix. Like if
julia sqrt(4.0)
2.0 + 0.0im
Le mercredi 29 janvier 2014 à 13:42 +0100, Andreas Noack Jensen a
écrit :
The main problem is that it cannot really be determined before whether
the eigen solution is real or complex before the calculation is over
in contrast to the `sqrt` case. I think it would be a little annoying
to get a
There is a way to do that already. If you know that A is symmetric, you can
do eigfact(Symmetric(A)), bypass the check for symmetry and go directly to
the symmetric solver. This method should of course always return a real
result so the alternative solution is: let eigfact(StridedMatrix) always
How much worse would performance be if we “upgraded” all results to complex
matrices?
— John
On Jan 28, 2014, at 8:38 PM, Jiahao Chen jia...@mit.edu wrote:
The reason is primarily for performance and secondarily for numerical
stability. eig() on a Matrix implements a polyalgorithm depending
