On 10/26/07, Sebastian Haase <haase@msg.ucsf.edu> wrote:
On 10/26/07, David Cournapeau <david@ar.media.kyoto-u.ac.jp> wrote:
> P.S: IMHO, this is one of the main limitation of numpy (or any language
> using arrays for speed; and this is really difficult to optimize: you
> need compilation, JIT or similar to solve those efficiently).
This is where the scipy - sandbox numexpr project comes in
- if I'm not misaken ....
http://www.scipy.org/SciPyPackages/NumExpr
Description
The scipy.sandbox.numexpr package supplies routines for the fast
evaluation of array expressions elementwise by using a vector-based
virtual machine. It's comparable to
scipy.weave.blitz (in Weave), but
doesn't require a separate compile step of C or C++ code.
I hope that more noise around this will result in more interest and
subsequentially result in more support.
I think numexpr might be one of the most powerful ideas in numpy /
scipy "recently".
Did you know about numexpr - David ?
Sadly, I don't think numexpr will help here; It basically handles the same cases as numpy; only faster because it can avoid a lot of temporaries. I think he's going to need Psyco, Pyrex, Weave or similar.