Fitting/minimizing Python functions.

Hi,

I'm looking for a good way to develop a fitter (chi-squared minimization) in Python (ie, a Python-defined model) with the option to later port everything to C++ after the kinks are worked out and only if necessary for runtime speed.

I'm a little confused about the available options. What I've found:

• ROOT has a Python interface to its TMinuit F77->C++ transliteration. This appears to be best supported in ROOT, has been made to accept Python functions but keeps and exposes a very F77 interface.
• ROOT has a copy of the C++ rewrite, Minuit2. In principle this would give a more "pythonic" interface but currently requires subclassing from C++ so is apparently a non-starter for Python functions (?) There has been some discussion in the forum about this but I don't find a conclusion.
• There are two related projects on google code[1] which provide Python interfaces to the stand-alone Minuit2 and ROOT's slightly modified version. This looks good but it means yet another package for our code base (not a deal breaker) and I'm unclear as to future plans.
• There is ROOT.Fit.Fitter() but it won't accept a Python function (?)
• I find RooFit available Python-side but its largeness has kept me away so far.

Any opinions on the "best" route to take for a Python-side fitter? Pointers to docs/examples are also appreciated.

Thanks,
-Brett.

[1] http://code.google.com/p/pyminuit/ and http://code.google.com/p/pyminuit2/