[SciPy-User] Optimization, Matlab/Octave and Duplication
Mon Nov 21 03:40:12 CST 2011
Is there somebody, who has experience with R and sparse data structures
from a performance point of view (compared to scipy)?
On Mon, Nov 21, 2011 at 9:58 AM, Dan Stowell <firstname.lastname@example.org>wrote:
> On 21/11/11 00:42, Felipe Schneider wrote:
> > Hi all,
> > I'm new to SciPy and even scientific computing in general, but I have
> > some basic experience with Octave. Reading about Python and how it can
> > be amazing but still very fast and all, I started to get some interest
> > on SciPy/NumPy. I would like to ask some questions, hoping it's the
> > right place to make them:
> > 1. It seems Octave is really slow compared to the SciPy approach. I
> > would like to know if it's due to some low level coding, Cython, etc.
> > How's the procedure when someone wants to, say, create a new routine
> > for SciPy?
> One of the reasons for slowness in Octave might be the data copying
> where python often passes-by-reference. Matlab includes some 'tricks' to
> avoid too much data copying, but Octave doesn't have those tricks, so it
> loses out compared against both matlab and python.
> > 2. Is there anything similar to Matlab's Toolboxes or Octave's
> > Octave-Forge? Or is it all a huge pack?
> Scikits is one collection that you might think of in that way:
> > 3. I was searching for a LP solver and it seems SciPy doesn't have it!
> > But there's cvxopt, am I wrong? So, there's no future plans on this
> > area, I presume, i. e., no LP solver for SciPy? I would like to have a
> > general answer (i. e., "when and when not should SciPy has this/that
> > funtionality?"), which leads to my third question...
> You might find it in scikits, or http://openopt.org
> > 4. It seems that there are way more than one implemention in the
> > Python world for a lot of things, am I wrong? How come? Why
> > reinventing the wheel? Where does SciPy stand on this matter?
> > Really thanks,
> > Felipe.
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> Dan Stowell
> Postdoctoral Research Assistant
> Centre for Digital Music
> Queen Mary, University of London
> Mile End Road, London E1 4NS
> SciPy-User mailing list
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