If you think I should split the message so that things get more clear...
But the things are: 1) How to document numpy-heavy projects? 2) How to better make these contributions available to the numpy/scipy community?
Directions will be greatly appreciated. I suspect that this info is all gathered somewhere I did not find.
PS. I apologize for the cross-post, this is a message sent to numpy list but without any replies, so I found fit to send the message to both lists.
Thanks in advance, Best, R.
---------- Forwarded message ---------- From: Renato Fabbri firstname.lastname@example.org Date: Tue, Jan 30, 2018 at 8:32 PM Subject: doc? music through mathematical relations between LPCM samples and musical elements/characteristics To: Discussion of Numerical Python email@example.com
the half-shape suite: archive.org/details/ShapeSuite was completely synthesized using psychophysical relations for each resulting 16bit 44kHz samples: https://arxiv.org/abs/1412.6853
I am thinking about the ways in which to make the documentation at least to: * mass (music and audio in sample sequences): the framework. It might be considered a toolbox, but it is not a package: https://github.com/ttm/mass/
* music: a package for making music, including the routines used to make the half-shape suite: https://github.com/ttm/music
== It seems reasonable at first to:
* upload the package to PyPI (mass is not a package), music is there (beta but there).
* Make available some summary of the file tree, including some automated code documentation. As I follow numpy's convention (or try to), and the package and framework are particularly useful for proficient numpy users, I used Sphinx. The very preliminary version is: https://pythonmusic.github.io/
* Make a nice readthedocs documentation. "music" project name was taken so I made: http://music-documentation.readthedocs.io/en/latest/ "mass" project name was also taken so I made: http://musicmass.readthedocs.io/en/latest/
And I found these URLs clumsy. Is there a standard or would you go with musicpackage.read.. and massframework.read... ?
More importantly: * would you use readthedocs for the sphinx/doxigen output? * would you use readthedocs.org or a gitbook would be better or...?
Should I contact the scipy community to make available a scikit or integrate it to numpy in any way beyond using and citing it appropriately?.
BTW. I am using vimwiki with some constant attempt to organize and track my I/O: https://arxiv.org/abs/1712.06933 So maybe a unified solution for all these documentation instances using a wiki structure seems reasonable at the moment. Maybe upload the generated html from Sphinx and from Vimwiki to readthedocs...?