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Re: Python from Matlab

In my experience (for what it is worth) I eventually found the time spent hacking together increasingly convoluted ways of passing data structures between Python and Matlab was better spent (1) converting Matlab code to Python and (2) dispensing with Matlab altogether.

A fairly basic introductory comparison between Python (using NumPy) and Matlab can be found here:


For fans of the Matlab IDE, I think the nearest for Python development would be Eclipse using the PyDev plug-in. Eclipse (via other plug-ins) also supports R, C/C++, Java and other languages.

I use Eclipse pretty much exclusively, but as I have failed to persuade anyone else in my department to use it, it's obviously an acquired taste.



On 22/08/14 12:47, Jan Schnupp wrote:
Hi Alain,

"calling" python from matlab is easy (as you are probably aware, you
can all anything from Matlab using the dos() function, and I often
conjure up little python helpers from matlab in this way). The hard
part is shifting data between python and matlab in a way that is
efficient, elegant and easy to implement, and which works on UNIX
based systems as well as on Windows (i.e. no proprietary OLE). You can
always hack together a kludge that writes temporary binary files in
one environment and reads it in the other (which is what I tend to
do), but that is inelegant and has nontrivial overheads. Or you could
python and matlab work together on some sort of client/server model.
That would be more elegant - the matlab and python parts then wouldn't
even have to be on the same machine, but the programming investment is
very large. I don't know of any developments to make this sort of
stuff easier that are even on the distant horizon. If other list
members know of any I would be interested to hear about them.



On 22 August 2014 08:44, Alain de Cheveigne <alain.de.cheveigne@xxxxxx> wrote:
Hi Marek,

I am looking for the opposite: an easy, efficient  and reliable way to call Python from Matlab.  My programming environment nowdays is matlab and I can't easily change.  The best course that I see is to implement new code in Python and call it from matlab, and make the switch to Python when Python code reaches critical mass.  I suspect many people are in a similar position.


On 21 Aug 2014, at 11:20, Marek Rudnicki <marek.rudnicki@xxxxxx> wrote:

Etienne Gaudrain <e.p.c.gaudrain@xxxxxxx> writes:

Dear Marek,

This looks very promising, I'm glad to finally see the first signs of a
shift from Matlab to Python. Thanks a lot for sharing this!!

Dear Etienne

I'm glad you like it.

BTW, if you still have some MATLAB legacy code that you would like to
use in Python, then matlab_wrapper [1] could be helpful.  It allows you
to call MATLAB functions directly from Python environment (the MATLAB
process is started in the background), e.g.:

matlab.workspace.sin([0.1, 0.2, 0.3])


[1] https://github.com/mrkrd/matlab_wrapper

On 19/08/2014 14:50, Marek Rudnicki wrote:
Hi all,

we would like to announce *cochlea* -- a collection of inner ear
models in Python.  It was developed in the group of Werner Hemmert [1]
at the Technische Universität München.  After a few years of
development, we decided that it is stable and would like to contribute
it to the auditory community.

The main features of the package are:

   - simple to use (each model is implemented as a single Python
     function: sound in, spikes out)
   - fast (you can generate responses of hundreds or even thousands of
     nerve fibers)
   - all models have the same interface (easy to make comparisons and
     pick the one that best suits your needs)
   - up-to-date (recent models included)

Currently implemented models are:

   - Zilany, M. S., Bruce, I. C., & Carney, L. H. (2014). Updated
     parameters and expanded simulation options for a model of the
     auditory periphery. The Journal of the Acoustical Society of
     America, 135(1), 283-286.
   - Zilany, M. S., Bruce, I. C., Nelson, P. C., & Carney,
     L. H. (2009). A phenomenological model of the synapse between the
     inner hair cell and auditory nerve: long-term adaptation with
     power-law dynamics. The Journal of the Acoustical Society of
     America, 126(5), 2390-2412.
   - Holmberg, M. (2007). Speech Encoding in the Human Auditory
     Periphery: Modeling and Quantitative Assessment by Means of
     Automatic Speech Recognition. PhD thesis, Technical University
   - MATLAB Auditory Periphery by Meddis et al. (external model, not
     implemented in the package, but easily accessible through

We are really grateful to the authors of those models for allowing us
to use their code it in *cochlea*.  We release the package under the
GNU General Public License, so that you are free to copy, use and
modify the code.  We also encourage you to contribute back your

The code is distributed on GitHub [2] and the package/documentation
are hosted on the Python Package Index [3].  Check also our demo [4]!

If you would like to give a feedback, have questions or found some
problem, do not hesitate to email me or open an issue on GitHub [2].

Thank you and best regards
Marek Rudnicki

[1] http://www.imetum.tum.de/research/bai/home/?L=1
[2] https://github.com/mrkrd/cochlea
[3] https://pythonhosted.org/cochlea/
[4] http://nbviewer.ipython.org/github/mrkrd/cochlea/blob/master/examples/cochlea_demo.ipynb

Mark Wibrow
PhD candidate
Department of Speech Hearing and Phonetic Sciences
University College London
Room 326, Chandler House
2 Wakefield Street
United Kingdom