Some of the most important advantages noone has pointed out yet are:
Operating System Independent – Now I know Matlab has versions for Windows, *nix and OSX, but an institution will not always pay for licences for all three. At least with Python you can easily switch between systems at no additional cost. I guess this would fall under the category of free though, but the convenience that comes with the possibility to work on whatever operating system you happen to boot up your machine in is worth considering.

Also, once you write your script it’s a real program. Often people will use Matlab to prototype something up and then, once verified they will implement it again in another language. If you implement it in python to start with, it’s already a real program which just needs to be altered. The same script can be used as a command line script, can be expanded with a GUI, or can be used as the back-end for a web application. I know Matlab has the GUIDE and a websever but they are Matlab specific. At least Python has bindings for GUI frameworks you may already use, e.g. wx, QT etc…

I may be biased since I am a fan of open-source. I will say this though, I haven’t looked back since I first took the plunge.

YMMV though,

Cheers,

Jack

- enthought (http://www.enthought.com/products/epd.php), which is basically an enhanced version of numpy/scipy/matplotlib, from the developers of these libraries themselves. It is like a commercial (but academic free) version of Pylab.

- sage (http://www.sagemath.org/), which allows you to write programs that call different syntaxes and scripts in matlab, R, and other programming language, and to do it with a python syntax.

In general, I would not recommend you to switch to python, because it has -way- less libraries for what you want to do compared to Matlab. For the same reason, I wouldn’t recommend anyone to switch from R to python, and consider that I am a python freakie and user myself :-(

The Pylab libraries (numpy+scipy+matplotlib) have seen a lot of improvements lately, but don’t expect too much from them, unless you are wishing to contribute to these libraries.

@Rich: I will admit here that object oriented programming a la Python has never seemed like a good fit for anything I’ve done, but I learned Lisp before I wrote any object oriented code at all. This may be a peculiarity of my brain.

But why not take a look at Octave? It is very close to Matlab, much of the code runs entirely without modifications and it is easy to extend.

It would be an easier first step than porting a lot of code and knowledge to numpy.

It’s very easy to implement fundamental PG models in python. But, whatever optimizations and clever coding one uses it will be too slow for MCMC and other simulations. The can be said to certain dynamic programming techniques in bioinformatics. Good control of speed, concurrency and numerical precision is essential in those areas.

On the other hand, a combination of python/C/FORTRAN can be a real killer. Python can be an amazing integration language. The most important numerical tasks are already coded and optimized in excelent quality libs in C/FORTRAN. Most of my actual work is to reformat data to fit into this libs.

So, one don’t need to switch to python. Only needs to know where to use it. By the way, there are some wrappers to use matlab from a python shell and should be easy to write one from scratch.

Why put your resources to compete when they can just cooperate?

Matlab has had just-in-time compilation for quite some time (since v6.5), and it is even possible to partially precompile code to a bytecode format through the pcode function.

Newer versions have both classes and modules, and should be comparable to Python when it comes to code base organization.

IMHO, the real problem with Matlab is that there is some old legacy cruft which still enables people to “code FORTRAN” in it, and which Mathworks are reluctant to deprecate, in order to maintain backwards compatibility.

A “cleansed” version would be preferrable, and would probably feel a lot like Scheme with matrices instead of lists.

Thanks for all your feedback! This is something I’m genuinely thinking about at the moment, so I’m glad that people have valuable insights to offer.

Jordi – yes, perhaps I overstated slightly the number of benefits :-) One additional benefit I should also have mentioned is that I find the syntax of Matlab a little bit counter-intuitive sometimes (for example, the function zeros(4) would generate a 4-by-4 element array, not a 1D array with 4 elements).

I have in mind that I’ll write at least one update post on this subject at a later date, so watch this space!

Frederick – thanks for your comments. I don’t have any great knowledge of Lisp, so it’s great to have some feedback on that!

I disagree that OO is a “terrible way to organise mathematical code”. My experience (which is mainly with statistical modelling) is that the features of OO are pretty useful, for the usual reasons. I’d be happy to accept that it may not be well suited for all areas of mathematics, and I’d certainly be happy to acknowledge that there are other approaches (such as functional programming) that have a lot of merit. But I think it’s wrong to imply that there’s no merit to using OO in relation to mathematical code.