[Numpy-discussion] numpy : your experiences?
rahulgarg44 at gmail.com
Mon Nov 19 18:05:03 EST 2007
thanks for ur responses .. so it looks like python/numpy is used more
for gluing things together or doing things like postprocessing. is
anyone using it for core calculations .. as in long running python
i used numpy myself for some nonlinear dynamics and chaos related
calculations but they were usually very short running only for a few
seconds at a time.
On Nov 17, 2007 8:28 AM, Steve Lianoglou <lists.steve at arachnedesign.net> wrote:
> Hi Rahul,
> > a) Can you guys tell me briefly about the kind of problems you are
> > tackling with numpy and scipy?
> I'm a grad student "doing" computational biology. I primarily use the
> NumPy/SciPy/matplotlib triumvirate as a post processing tool to
> analyze what the heck happened after we run some learning algorithms
> we develop (or canned ones, like libsvm (for example)) to look for
> some sense in the results.
> I've been working w/ analyzing interaction networks/graphs, so I also
> use NetworkX quite a bit as well (it's also a nice package w/
> responsive authors).
> Many of the folks (in my lab, and collaborators) like to use MATLAB,
> so I've found scipy's io.loadmat invaluable for making this a bit more
> So, in general, for me (so far) numpy/scipy are generally used to
> integrate various datasets together and see if things "look
> kosher" (before runs and after runs).
> > b) Have you ever felt that numpy/scipy was slow and had to switch to
> > C/C++/Fortran?
> Yes, for things like boosting, svm, graph mining, etc ... but that's
> no real surprise since their iterative and need to run on large
> You should also note that there are python interfaces to these things
> out there as well, but I (thus far) haven't taken much of advantage of
> those and usually pipe out data into the expected text input formats
> and pull them back in when the algo is done.
> > c) Do you use any form of parallel processing? Multicores? SMPs?
> > Clusters? If yes how did u utilize them?
> I'd really like to (not just for Python), but I haven't.
>  NetworkX: https://networkx.lanl.gov/wiki
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