[SciPy-Dev] scikits contribution?
Wed Jul 14 12:36:57 CDT 2010
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>
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> 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:
>> > 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 I think the template scikit in scikits svn is a bit out of date, the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.
>> > 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?
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