Yup. I'm one of those people. Well, partially at least. I do a lot of distributed computing. But my PhD was in a statistical area. I used Octave for a while (m

Yup. I'm one of those people. Well, partially at least. I do a lot of distributed computing. But my PhD was in a statistical area. I used Octave for a while (matlab clone). But then as my data sets got larger and I mean really large (non-linear equation solving on 11m points on my puny desktop), I went full force on Python (NumPy, SciPy, Matplotlib). The reason - its is super easily scriptable, the libraries are great and easy to use and python allows me to use multi-processor capabilities to distribute my work to all my cpu cores. Keep in mind I could have used GSL. But Numpy/Scipy & matplotlib were just faster and more productive for me. That being said, I'd rather have one source of truth - i.e. GSL and have this be a wrapper around it as opposed to re-creating all the logic. Either way - its a fantastic effort. If at anytime I create systems that need numerical computation (as opposed to the hacks that I did for my thesis) I will definitely look into this.