hypergeometric functions would be great, but this might be too difficult
I concur with too difficult. I don't think I would want to set a student a task that I'm not confident I could do myself. That being said, I could possibly help mentor a special functions project; there are plenty of more straightforward implementations to be done. Parabolic cylinder functions might be a good project; I started working on those a while ago but it's not looking like I'll have time to finish anytime soon. There's a sequence of papers that give a complete implementation. Since this would be from scratch the person would only have to know (or be able to pick up) Cython; the harder part would be finding someone comfortable with the math involved. On Wed, Jan 18, 2017 at 1:32 PM, Evgeni Burovski <evgeny.burovskiy@gmail.com> wrote:
On Wed, Jan 18, 2017 at 11:36 AM, Ralf Gommers <ralf.gommers@gmail.com> wrote:
Hi all,
It's that time of year again, we should think about GSoC participation. For SciPy participating in previous years has definitely been worth it.
Here is the ideas page from last year: https://github.com/scipy/scipy/wiki/GSoC-2016-project-ideas (not a whole lot to reuse).
New ideas very welcome (ideally with mentor attached ...).
Who is interested and available to (co-)mentor this year?
Thanks for starting it Ralf!
I might have some bandwidth this summer to co-mentor.
A few random ideas:
1. scipy.diff is still a nice one IMO. The focus can be on moving `approx_derivative` to be public facing. https://github.com/scipy/scipy/issues/6026
2. B-splines (again!). https://github.com/scipy/scipy/issues/6730 and https://github.com/scipy/scipy/issues/6710 list possible subprojects of ranging difficulty. This would require a student to be able to read literature though. Alternatively, there's rational interpolation, https://github.com/scipy/scipy/issues/6929 and Pauli's PR for barycentric interpolation.
3. hypergeometric functions would be great, but this might be too difficult. Josh, Nikolay, Ted --- you guys looked at this at some point; any comments?
4. Testing: A relatively easy task could be to enable a move away from nose to pytest, for both scipy and numpy. Ideally as a result the test suites can be run with either of those with all the bells and whistles, with fast/slow/xslow tests, skipifs and knownfailures.
Cheers,
Evgeni _______________________________________________ SciPy-Dev mailing list SciPy-Dev@scipy.org https://mail.scipy.org/mailman/listinfo/scipy-dev