[SciPy-Dev] scikits contribution?
Wed Jul 14 15:59:17 CDT 2010
On 7/14/10 12:01 , firstname.lastname@example.org wrote:
> forgot to CC
> ---------- Forwarded message ----------
> Date: Wed, Jul 14, 2010 at 1:57 PM
> Subject: Re: [SciPy-Dev] scikits contribution?
> To: SciPy Developers List<email@example.com>
> On Wed, Jul 14, 2010 at 1:36 PM, Jonathan Stickel<firstname.lastname@example.org> wrote:
>> On 7/8/10 07:05 , email@example.com wrote:
>>> Date: Thu, 8 Jul 2010 08:24:25 -0400
>>> Subject: Re: [SciPy-Dev] scikits contribution?
>>> To: SciPy Developers List<firstname.lastname@example.org>
>>> Content-Type: text/plain; charset=ISO-8859-1
>>> On Wed, Jul 7, 2010 at 4:42 PM, Jonathan Stickel<email@example.com> wrote:
>>>>> Some time ago, I offered to contribute (on the scipy-user list) some
>>>>> code to smooth 1-D data by regularization:
>>>>> Someone suggested that scikits might be the right place:
>>>>> 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,
>>> 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 I think the template scikit in scikits svn is a bit out of date, the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.
>>>>> 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.
It seems strange to me that each scikit would host its own development
sources in separate locations! I'd prefer to use the existing SVN tree
for my small contribution, if possible.
I did register at http://projects.scipy.org/scikits with the username
"jjstickel". The wiki page indicates that this is all that is needed to
edit the wiki, but I do not see a "Edit this page" link. So it does
seem that someone needs to give me permission. I also need permission
for commit access to svn.scipy.org/svn/scikits/.
If someone wants to see some code before giving out permissions willy
nilly, I can do that of course! Just let me know.
>> Please cc me in your reply since I receive list emails in digest form.
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