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. -- . __ . |-\ . . tim.hochberg@ieee.org