Hello.
Le jeu. 27 janv. 2022 à 18:09, Alex Herbert <alex.d.herb...@gmail.com> a écrit :
>
> I would be willing to go through GSOC again.
Thanks; I know that back in 2020, it had been a disproportionate
amount of work...
> I think that the
> statistics component could again serve as a project. There are some
> packages in Math that could be moved to make use of the updated
> distributions (e.g. math.stat.inference)
That would be great, although I seem to notice that there
might be some dependency issues...
> or perhaps a reworking of the
> math.stat.descriptive package to support using them with streams.
+1
> In the last iteration (GSOC 2020) we failed to get enough of a picture
> of the competence of candidates in the 'bonding phase' before places
> were formally allocated. I think we should require that a candidate
> can:
>
> - Open a PR on GitHub to add a feature in the topic area. It should be
> of non-trivial complexity and delivered to a quality ready to merge.
Do you think that the above "stream support" could be that task?
> - Show knowledge of the topic area beyond this single feature,
> demonstrating ability to continue to significantly contribute through
> a 3 month period in the subject area.
That seems more fuzzy to define and assess (?).
Some ideas (for "Commons Math"):
1. Redesign and modularization of the "ml" package
-> main goal: enable multi-thread usage
2. Abstracting the linear algebra utilities
-> main goal: allow (runtime?) switch to alternative implementations
3. Redesign and modularization of the "random" package
-> main goal: general support of low-discrepancy sequences
4. Refactoring and modularization of the "special" package
-> main goal: ensure accuracy and performance and better API,
add other functions (?).
> Without this set of skills there will be little progress in the formal
> code period.
:-}
Shall we open a "GSoC 2022" report in each concerned JIRA project?
Regards,
Gilles
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