I find it as a difficult balance. Sometimes I tend to spend to much time commenting what the code pieces are doing and then I suddenly get an awesome new approach/idea and implement it straight away – deleting without look back (it’s hard but necessary sometimes).

So my advice would be: make it work first (proof-of-concept) and only comment on things that are new or difficult to make sense of. When the code is working and you are satisfied then take your time to make good comments.
The last thing I must admit I don’t always do since a code is never truly done (always room for optimization) or I quickly start a new project – it’s always easier to give advice than doing it yourself.

Additionally, if you eventually decide to speed up your code, you can write parts of your algorithm in a C++ module and call it from python. This gives you the speed of a C++ implementation as well as the interactivity and plotting functionality of python.

Best
–Peter

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

I did not use mex-functions for passing and handling objects though (structures, cell arrays, etc.)

Although, I feel that Fortran is somewhat undersold here. One of the main reasons Fortran is still so popular today is not just because the old fuddy-duddies can’t be bothered to learn C and recode commonly-used libraries, but is because for many problems (particularly in science) it is simply faster than many of its counterparts, including C/C++. This is, for instance, due to it having stronger aliasing rules for memory pointers.

With regards to speed, well-written Java code generally isn’t much slower than C++ from version 5 up. The main bottleneck, in my experience, is with the maths functionality – particularly trig – but this can often be circumvented with the use of precomputed lookup tables.

I am designing a machine. It’s a virtual machine that’s invisible to us, but it’s a machine nonetheless. The machine needs to have certain functionality, but it is totally up to me how it will carry out its functions, and there are million ways it could be done.

Since I am designing a machine, I need to break it down into its components, and figure out how they will fit together in the end. I also need to figure out which components I need to make myself and which ones I can find ready-made. If I use ready-made ones, I need to make sure they will work and figure out how to use them properly

Once I’ve assembled my machine, it often doesn’t work quite right at first, and I need to pay close attention to all its components as it operates in order to locate the hang-up.