> Can solve it with Matlab or GNU octave, but couldn’t have developed easily the whole system with user interface in them.
This is a very key point. I still find that Matlab often has a larger set of features and better efficiency for linear algebra. But thanks to Scipy, you really can expand your mind about what kinds of systems to interface with.
GNU Octave is indeed faster than numpy. This may be because GNU Octave uses highly optimized solvers (like the famous modified Cholesky method). Due to scipy's license fundamentalism, they refuse to use many of these solvers because they are GPL-licensed. It is a bit sad to see how these ridiculous ideological constraints taint an otherwise excellent software package.
Much as I'm personally very pro-GPL, I think there are good reasons to avoid licensing fundamental parts of the SciPy stack under a copyleft license, since anything built on top would also need to be GPLed.
A scipy-copyleft for such GPLed components would be nice though.
This is a very key point. I still find that Matlab often has a larger set of features and better efficiency for linear algebra. But thanks to Scipy, you really can expand your mind about what kinds of systems to interface with.