a) Can you guys tell me briefly about the kind of problems you are tackling with numpy and scipy?
I'm using python with numpy,scipy, pytables and matplotlib for data analysis in the field of high energy particle physics. Most of the work is histograming millions of events, fitting functions to the distributions or applying cuts to yield optimized signal/background ratios. I often use the random number and optimization facilities for these purposes.
Cool! Me, too! In addition I am using Paida (http:// paida.sourceforge.net) for histogramming. I am interfacing that with matplotlib for the plotting, though.
Most of my colleagues use ROOT (root.cern.ch) which has also a python binding, however, I love the simplicity of numpy's ufuncs and indexing capabilities, which makes the code much denser and readable. In addition to more reliable in my experience.
In particular for the simulation yes, depending on the level of detail of course. But only parts, eg. random number generation for certain distributions had to be coded in C/C++.
Are you saying you extended the scipy/numpy tools for this? Do you think it would make sense to put some of that stuff on the wiki?
Cheers! Bernhard
Cheers, Jan