[SciPy-User] Optimization, Matlab/Octave and Duplication
Sun Nov 20 18:42:08 CST 2011
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
2. Is there anything similar to Matlab's Toolboxes or Octave's
Octave-Forge? Or is it all a huge pack?
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...
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?
More information about the SciPy-User