[SciPy-Dev] scikits contribution?

josef.pktd@gmai... josef.pktd@gmai...
Wed Jul 14 12:57:49 CDT 2010


On Wed, Jul 14, 2010 at 1:36 PM, Jonathan Stickel <jjstickel@vcn.com> wrote:
> On 7/8/10 07:05 , scipy-dev-request@scipy.org wrote:
>> Date: Thu, 8 Jul 2010 08:24:25 -0400
>> From:josef.pktd@gmail.com
>> Subject: Re: [SciPy-Dev] scikits contribution?
>> To: SciPy Developers List<scipy-dev@scipy.org>
>> Message-ID:
>>       <AANLkTimQBH1NSjDfovoZFu8gmVFVmpGIlBiB5tneQET7@mail.gmail.com>
>> Content-Type: text/plain; charset=ISO-8859-1
>>
>> On Wed, Jul 7, 2010 at 4:42 PM, Jonathan Stickel<jjstickel@vcn.com>  wrote:
>>> >  Some time ago, I offered to contribute (on the scipy-user list) some
>>> >  code to smooth 1-D data by regularization:
>>> >
>>> >  http://mail.scipy.org/pipermail/scipy-user/2010-February/024351.html
>>> >
>>> >  Someone suggested that scikits might be the right place:
>>> >
>>> >  http://mail.scipy.org/pipermail/scipy-user/2010-February/024408.html
>>> >
>>> >  So I am finally looking into scikits, and I am not sure how to proceed.
>>> >  ?My code consists of several functions in a single .py file. ?It seems
>>> >  overkill to create a new scikit for just one file, but I do not see an
>>> >  existing scikit that matches. ?'Optimization' would be the closest; in
>>> >  core scipy I would put it in 'interpolate'.
>>> >
>>> >  So, what is the minimum that I need to do to create a scikit and upload
>>> >  my code? ?Any suggestions for the name of the scikit (interpolate,
>>> >  data_smoothing)?
>>
>> The easiest to get started is to copy the setup structure from another scikit.
>> I think the template scikit in scikits svn is a bit out of date, the
>> last time I looked.
>>
>> If you think your model could form the basis for enhancing the
>> smoother or noisy interpolation category in scipy, then a scikits
>> would be the best way, as we discussed.
>>
>> If you want to add it to an existing scikits, then statsmodels would
>> be a possibility.
>> Although statsmodels is more oriented towards multivariate approaches,
>> I think a smoother category, together with some non-parametric
>> methods, e.g. the existing kernel regression, would be an appropriate
>> fit. There is a need for smoothers in gam, Generalized Additive
>> Models, but that one is not cleaned up yet.
>>
>> And I think there will be more applications where it would be useful
>> to share the cross-validation code as far as possible.
>>
>> Josef
>>
>>> >
>>> >  Please know that I am just starting to learn python, being a convert
>>> >  from matlab/octave. ?Although I have become fairly proficient using
>>> >  numpy/scipy in ipython, I do not know much about python internals,
>>> >  setuptools, etc.
>>> >
>
> OK, I created a scikit named "datasmooth" and included my current code.
>  It seems to install OK with "python setup install" and import
> correctly.  However, I am not able to commit to the svn repository.  I
> registered on the scikits wiki, but I guess there is something else I
> need to do?

Sharing the code would be much easier if you pick your favorite
decentralized revision control system, git, bazaar or mercurial, and
host it at the corresponding website.
It would also avoid any permission questions. I don't know who handles
setup and administration of http://projects.scipy.org/scikits.

Josef


>
> Thanks,
> Jonathan
>
> P.S.
> Please cc me in your reply since I receive list emails in digest form.
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