I am a bit worried about the differences in results. Just to be sure you are comparing apples with apples, it may be a good idea to set the seed at the beginning:
np.random.seed( SEED ) where SEED is an int. This way, you will be inverting always the same matrix, regardless of the Python version. I think, even if the timing is different, the results should be the same. http://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html#numpy.random.seed David. On 23 March 2013 15:39, Colin J. Williams <cjwilliam...@gmail.com> wrote: > On 23/03/2013 7:21 AM, Ralf Gommers wrote: > > > > > On Fri, Mar 22, 2013 at 10:39 PM, Colin J. Williams <cjwilliam...@gmail.com> > wrote: >> >> On 20/03/2013 11:12 AM, Frédéric Bastien wrote: >> >> On Wed, Mar 20, 2013 at 11:01 AM, Colin J. Williams >> <cjwilliam...@gmail.com> wrote: >> >> On 20/03/2013 10:30 AM, Frédéric Bastien wrote: >> >> Hi, >> >> win32 do not mean it is a 32 bits windows. sys.platform always return >> win32 on 32bits and 64 bits windows even for python 64 bits. >> >> But that is a good question, is your python 32 or 64 bits? >> >> 32 bits. >> >> That explain why you have memory problem but not other people with 64 >> bits version. So if you want to work with bigger input, change to a >> python 64 bits. >> >> Fred >> >> Thanks to the people who responded to my report that numpy, with Python >> 3.2 was significantly slower than with Python 2.7. >> >> I have updated to numpy 1.7.0 for each of the Pythons 2.7.3, 3.2.3 and >> 3.3.0. >> >> The Pythons came from python.org and the Numpys from PyPi. The SciPy site >> still points to Source Forge, I gathered from the responses that Source >> Forge is no longer recommended for downloads. > > > That's not the case. The official binaries for NumPy and SciPy are on > SourceForge. The Windows installers on PyPI are there to make easy_install > work, but they're likely slower than the SF installers (no SSE2/SSE3 > instructions). > > Ralf > > Thanks, I'll read over Robert Kern's comments. PyPi is the simpler process, > but, if the result is unoptimized code, then easy_install is not the way to > go. > > The code is available here(http://web.ncf.ca/cjw/testFPSpeed.py) > and the most recent test results are > here(http://web.ncf.ca/cjw/FP%2023-Mar-13%20Test%20Summary.txt). These are > using PyPi, I'll look into SourceForge. > > Colin W. > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
