> From: Robert Bradshaw <[email protected]> > Subject: Re: [Cython] Linking error - 64 bit problem? > > On Aug 22, 2009, at 7:40 PM, Adam Ginsburg wrote: > >> I reinstalled cython from source (instead of easy_install-ing it) and >> my code compiled successfully. Sorry about the previous e-mail. > > Great--I saw your previous email and started to get worried. I > thought easy_install was a source install (we didn't ship any > binaries until recently, and then just windows installers).
I'm not entirely sure what happened, but I have at least 3 python installs that I use routinely, so it was probably just a confusion issue on my end. >> Unfortunately, my code runs slower with cython than without, but at >> least now I know I can compile. In case anyone wants to offer >> assistance, the code I'm trying to optimize is: >> http://code.google.com/p/agpy/source/browse/trunk/plfit.py >> http://code.google.com/p/agpy/source/browse/trunk/cplfit.pyx > > My first piece of advice is to run cython -a over your code. This > will produce an html file which is most helpful in diagnosing where > you're wasting time. Just in a quick glance at your code I noticed: > > - You're calling Python's log, sqrt, max, abs, sum. This would negate > any gains you may hope to see. > - You're calling len a lot, either store it as a int somewhere, or > use .shape[0]. > - Unless n is huge, arange(n)/float(n) is probably way to expensive. > If the above don't help, try unrolling this. > > I bet there's a lot more performance that one could ring out of your > code, but the above should take you far. Much appreciated. I guess the various levels of yellow in the html file indicate the slow lines? I tried getting rid of all of my numpy calls in the loop by rewriting them as loops, but that hasn't improved speed at all, and in fact appears to have become slower. Right now a fortran (f2py) version goes ~75% faster and pure python goes ~25% faster, so I must be doing something wrong. Example: I changed this: dat[xm] = numpy.max(numpy.abs(cf-cx)) to this: for i from 0 <= i < n: val = abs(cf[i]-cx[i]) if dat[xm] < val: dat[xm] = val Is that the right approach for removing max/sum ? And is this: cdef extern from "math.h": double log(double theta) double sqrt(double theta) double abs(double theta) the right way to get rid of numpy log/abs/sqrt calls? If you'd rather see the whole code, it's been updated on the google code site. Thanks, Adam _______________________________________________ Cython-dev mailing list [email protected] http://codespeak.net/mailman/listinfo/cython-dev
