Open JohannesBuchner opened 3 years ago
@JohannesBuchner thank you very much for sharing your new method and code! These would indeed be great additions.
@JohannesBuchner thanks again. We are proposing this as a Google Summer of Code project: https://github.com/OpenAstronomy/openastronomy.github.io/pull/300
@JohannesBuchner: @mihirtripathi97 was accepted for GSoC and is now in charge of implementing Bexvar in Stingray. One small issue: your code is released with a version of GPL, which might not be compatible with our license (BSD). Would you agree on re-using parts of the code in Stingray (so, on releasing them with a more permissive license)? Thanks a lot! Cc @dhuppenkothen
Sorry, somehow I missed your ping.
I was under the impression that licences like GPL apply per project, while licenses like BSD and MIT have to be copied into each file as a header. Even for GPL a short header is usually done (see for example Mozilla source code, or GPL instructions). But apparently this is not necessary (or people disagree about it): https://softwareengineering.stackexchange.com/questions/125836/do-you-have-to-include-a-license-notice-with-every-source-file https://stackoverflow.com/questions/845895/putting-license-in-each-code-file
Is there a way to avoid this code being namelessly swallowed? It would be nice to have the authorship in that file, i.e, the authors of bexvar plus whoever worked on it from your side.
In the case of scipy, they made v1.0 paper at some point, and invited everyone with substantial code contributions to be on the co-author list. I don't know if you have any plans in that direction in the future.
If the points above sound reasonable to you, then I'd be happy for this code to be merged under MIT licence.
Copyright 2020-2022 Johannes Buchner, David Bogensberger
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Hi @JohannesBuchner, inviting you in a future paper and as co-author of the next release on Zenodo and the other platform is the least we can do! I don't know how to preserve partial code contributions on git though, we did cite the relevant papers and the original code in the documentation. We might try the following: you make a PR with the original bexvar code, and we rebase the current bexvar PR on your code. Would it work?
Oh, I was thinking more of adding a copyright header to the file. Didn't think of the git commit (and don't care too much about it).
How do we merge the original contributions with the new ones? Something like this?
Copyright 2020-2022 Johannes Buchner, David Bogensberger
Copyright 2022 Mihir Tripathi and StingraySoftware
Permission is hereby granted, ...
Sounds fine
Thank you!
I guess the remainder of this issue is on ingestion of eROSITA data.
@JohannesBuchner do you have example eROSITA data you would like to analyze?
There are some example light curves in https://github.com/JohannesBuchner/bexvar/tree/main/examples The format is documented in https://erosita.mpe.mpg.de/edr/DataAnalysis/srctool_doc.html
Dear all,
I wanted to point out to you:
1) a paper released today comparing various methods for characterizing variability in gappy X-ray light curves in the Poisson regime, with potentially varying backgrounds https://arxiv.org/abs/2106.14529 2) A new method, Bayesian excess variance (bexvar) is presented. It is a simple Bayesian hierarchical model, which can be solved efficiently. 3) This and three other methods are implemented at https://github.com/JohannesBuchner/bexvar/ 4) Code for reading eROSITA light curves is there too.
So feel free to
Cheers, Johannes