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#n...
David.
On 23 March 2013 15:39, Colin J. Williams
On 23/03/2013 7:21 AM, Ralf Gommers wrote:
On Fri, Mar 22, 2013 at 10:39 PM, Colin J. Williams
wrote: On 20/03/2013 11:12 AM, Frédéric Bastien wrote:
On Wed, Mar 20, 2013 at 11:01 AM, Colin J. Williams
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