[SciPy-User] Optimization, Matlab/Octave and Duplication
Mon Nov 21 02:58:29 CST 2011
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,
> SciPy-User mailing list
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Centre for Digital Music
Queen Mary, University of London
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