[SciPy-Dev] scikits contribution?
Jonathan Stickel
jjstickel at vcn.com
Wed Jul 14 13:36:57 EDT 2010
On 7/8/10 07:05 , scipy-dev-request at scipy.org wrote:
> Date: Thu, 8 Jul 2010 08:24:25 -0400
> From:josef.pktd at gmail.com
> Subject: Re: [SciPy-Dev] scikits contribution?
> To: SciPy Developers List<scipy-dev at scipy.org>
> Message-ID:
> <AANLkTimQBH1NSjDfovoZFu8gmVFVmpGIlBiB5tneQET7 at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
>
> On Wed, Jul 7, 2010 at 4:42 PM, Jonathan Stickel<jjstickel at 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 I think the template scikit in scikits svn is a bit out of date, the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?
Thanks,
Jonathan
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