+1 I like the idea of code promoted upstream for usefulness, I think it
will reduce bloat that typically comes with associated projects.
On Tue, Jan 22, 2013 at 1:53 PM, Jake Vanderplas <
[email protected]> wrote:
> Hi all,
> I've been having some discussions with folks about the relationship
> between astropy and astroML, two complementary python astronomy
> packages, and I wonder if some of these ideas could be useful as we
> think about the future of scikit-learn.
>
> In particular, astropy has the concept of "affiliated packages", which
> are listed on their website and have some level of enforced
> compatibility with the core astropy packages (see their list here:
> http://affiliated.astropy.org/ ). They have a well-defined set of
> criteria for packages seeking affiliation. One nice thing they've done
> is to create a template for the code and documentation, so that any
> package which wants to seek affiliation can provide a uniform code and
> documentation style (see the template here:
> https://github.com/astropy/package-template ).
>
> This may be an idea we could use in the future to encourage development
> of algorithms which may be too specialized or otherwise not fit well
> within scikit-learn. In some ways, it would lead to a hierarchical
> relationship similar to that between the various scikits and the core
> scipy package. Just as we've seen useful features from the scikits
> moved upstream into scipy, we might end up with useful development in
> affiliated packages moved upstream into scikit-learn.
>
> Just food for thought - we can probably shelve the idea for the time
> being, but I anticipate it may be a useful concept sometime in the near
> future.
> Jake
>
>
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