[SciPy-user] Constrained least-squares fitting routine?

[Robert Kern]

On Fri, May 1, 2009 at 23:43, william ratcliff
<william.ratcliff at gmail.com> wrote:
> Some time back, there was a python port of mpfit, using Numeric.   I talked
> to that author and he is happy with a BSD license.  Since, several people
> have patched it to use numpy (see http://code.google.com/p/astrolibpy/) and
> the author there is happy with a BSD license--though there is room for
> cosmetic improvement.  Does anyone know the original license for minpack?
> I plan to talk to the author of mpfit next week and see if he is amenable to
> a BSD license.  If so, would this fit into numpy?  It takes care of the
> annoyance of making a wrapper to leastsq for the simple case of fixed
> parameters and has an ansatz for deaing with limits.  It relies on a qr
> factorization, but we could either switch out the python chunks of code
> which do that for their minpack equivalents, or use the Numerical Recipes
> suggestion (not the code!!!!) to use SVD instead of QR--but as a stop-gap,
> could one of the developers tell me if we do manage to get BSD licensing
> agreements, can this go into scipy, or do we have to implement from scratch?

It can go into scipy.

> Also, for the BSD agreements, are emails sufficient, or do I need to try to
> get faxes?

Emails are sufficient. Try to get a clear, full statement (e.g. "I
release SuchAndSuch under the BSD license.") rather than something
like "Sure."  :-)

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco