[SciPy-User] forcing curve fit

[josef.pktd at gmail.com]

On Sun, May 11, 2014 at 4:03 AM, Ralf Gommers <ralf.gommers at gmail.com>wrote:

>
>
>
> On Sat, May 10, 2014 at 2:37 AM, Matt Newville <newville at cars.uchicago.edu
> > wrote:
>
>> Hi Thoger,
>>
>>
>> On Fri, May 9, 2014 at 4:02 PM, Thøger Emil Rivera-Thorsen <
>> trive at astro.su.se> wrote:
>>
>>> Matt, are you the aothor of lmfit?
>>> I am using it for a project I am working on at the moment and am very
>>> happy with it.
>>>
>>>
>> I am, or I think I'm the main author.   There have been many
>> contributions, especially from Till Stensitzki (who may have written more
>> code than I), but several others as well, and it is certainly built on
>> many previous works (ie, scipy.optimize).  I think such a high level
>> wrapping of scipy.optimize addresses the common needs of fitting
>> experimental data (such as adding bounds and "frozen" parameters)  is
>> needed, and believe that may people using curve_fit() would find it useful.
>>
>>
>> But I also feel somewhat detached from this. It's one of several
>> side-projects somewhat related to my main research and responsibilities.
>> One might view it as essentially a "scikit", and if so I might be able to
>> kid myself that this was giving something of value back to the scipy
>> ecosystem.  I know that's not true,
>>
>
> Not sure if you meant that or not, but I'm going to have to disagree
> anyway. Packages like lmfit, which provide regularly requested
> functionality and are documented and maintained well, are *very* valuable.
> The scientific Python ecosystem is so strong mainly because there are
> packages like that for almost everything one needs. A few big packages like
> numpy/scipy/pandas/scikit-learn could never contain all that functionality
> (for lots of reasons, release timing, maintainer load, etc.), we need a lot
> of small specialized ones.
>
> So thank you for lmfit!
>

I fully agree with Ralf.
And I'm glad to point to lmfit when someone asks why statsmodels doesn't
have non-linear least squares.

And even when statsmodels gets nonlinear least squares, it won't have the
same parameter oriented interface.

Josef



>
> Cheers,
> Ralf
>
>
> but I will support lmfit to the best of my abilities for the foreseeable
>> future.  Then again, I feel no ownership of it, and if someone is
>> interested in contributing or taking over, I'd be happy to help and
>> encourage as much as I can.
>>
>> Anyway, I'm very glad to hear you're happy with it.
>>
>> --Matt Newville
>>
>>
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