Thanks all for your suggestions. I see it brought up a lot of interesting asides. But my loop was simple enough that I was able to figure it out.
I also took a look at NumExpr. While it wasn't something I needed for vectorizing, it still looks very interesting. What kinds of performance improvements would be expected using this? Mathew Sebastian Haase wrote: > On 10/26/07, David Cournapeau <[EMAIL PROTECTED]> 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 ? > > Cheers, > Sebastian Haase > _______________________________________________ > Numpy-discussion mailing list > [email protected] > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
