[SciPy-Dev] Proposal for Scikit-Signal - a SciPy toolbox for signal processing
Tue Jan 3 14:37:10 CST 2012
On Tue, Jan 3, 2012 at 9:18 PM, David Cournapeau <email@example.com> wrote:
> On Tue, Jan 3, 2012 at 9:00 AM, Travis Oliphant <firstname.lastname@example.org>
> > I don't know if this has already been discussed or not. But, I really
> don't understand the reasoning behind "yet-another-project" for signal
> processing. That is the whole-point of the signal sub-project under the
> scipy namespace. Why not just develop there? Github access is easy to
> > I must admit, I've never been a fan of the scikits namespace. I would
> prefer that we just stick with the scipy namespace and work on making scipy
> more modular and easy to distribute as separate modules in the first place.
> If you don't want to do that, then just pick a top-level name and use it.
> As mentioned by other, there are multiple reasons why one may not want
> to put something in scipy. I would note that putting something in
> scikits today means it cannot be integrated into scipy later. But
> putting things in scipy has (implicitly at least) much stronger
> requirements around API stability than a scikit, and a much slower
> release process (I think on average, we made one release year).
> Integrating code into scipy after initially developing it as a separate
package is something that is not really happening right now though. In
cases like scikits.image/learn/statsmodels, which are active, growing
projects, that of course doesn't make sense, but for packages that are
stable and see little active development it should happen more imho.
Example 1: numerical differentiation. Algopy and numdifftools are two
mature packages that are general enough that it would make sense to
integrate them. Especially algopy has quite good docs. Not much active
development, and the respective authors would be in favor, see
Example 2: pywavelets. Nice complete package with good docs, much better
than scipy.signal.wavelets. Very little development activity for the
package, and wavelets are of interest for a wide variety of applications.
Would have helped with the recent peak finding additions by Jacob Silterra
for example. (Not sure how the author of pywavelets would feel about this,
it's just an example).
I'm sure it's not difficult to find more examples. Scipy is getting
released more frequently now than before, and I hope we can keep it that
way. Perhaps there are simple reasons that integrating code doesn't happen,
like lack of time of the main developer. But on the other hand, maybe we as
scipy developers aren't as welcoming as we should be, or should just go and
ask developers how they would feel about incorporating their mature code?
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