tgdane / pygix

A python library for reduction of 2-dimensional grazing-incidence and fibre diffraction data
MIT License
6 stars 18 forks source link

status of the project? #2

Open mikapfl opened 7 years ago

mikapfl commented 7 years ago

Hi,

I'm very interested in using pyFAI to transform GISAXS and GIWAXS images, so I found pygix. However, I'm not quite sure what the status of the project is. As far as I can see, only the angular and q_z vs. q_xy mapping works at the moment (and using transform_image directly, also q_z vs. q_y), but I'm interested in q_x vs q_y mapping, which is useful for highly ordered samples like gratings where q_x=0 is particularily interesting. At the same time, this transformation is highly non-linear and would benefit a lot from pixel splitting (vs stupid interpolation), so pyFAI should be a good fit.

Maybe I'd find the time to implement the appropriate transformations myself, but I haven't yet figured out what would be necessary to provide to the pyFAI functions to do the q_x mapping.

I guess my questions are: Is pygix still in development or maintenance? Are there resources which explain how to use the 2d-histogramming functions of pyFAI so I could try to implement it myself?

Cheers

Mika

mrakitin commented 3 years ago

Hello @tgdane, I wonder how open you are to review/merge potential pull requests? There were some efforts to update the code for the Python 3+ compatibility - see https://github.com/tgdane/pygix/compare/master...ronpandolfi:master for the changes.

Also, the repository is missing the license file. Do you mind adding the file, so that the fork from your repo could be used and developed by others? Our interest at NSLS-II is to package the code with conda, and PyPI release is normally the best source for that package. Do you mind if we maintain the package there?

Interested parties: @gfreychet, @ronpandolfi

Thank you!

tgdane commented 3 years ago

Hey @mikapfl! Sorry that I missed this issue a few years ago! I saw @mrakitin's PR for the python3 changes and have merged. Did you manage to find a way to use the library for your use case?

In terms of the status of the project, I'm no longer working in research and am not actively maintaining the repo but after putting a lot of work, I'd be really happy for someone to take over maintenance! I can contribute where needed from time to time. I have added @mrakitin as a contributor for now but happy to add anyone else.

A long time ago @kif (author of pyFAI - the library which this was based on) and I discussed incorporating pygix into pyFAI. Jerome, I don't know if there's been any interest in grazing incidence data with pyFAI in recent years? I imagine pyFAI has probably changed a lot since I originally wrote pygix!

mikapfl commented 3 years ago

@tgdane Thanks for asking, I managed without pygix since my problems weren't so time-critical.

I'm also not working with grazing incidence scattering anymore, so I'm not the right person to take over maintenance, unfortunately. Because I think it could be really useful for some former colleagues, I would be willing to review some changes or such if that helps. (-:

kif commented 3 years ago

Hi Thomas, Nice to read from you. I have rarely requests about grazing incidence scattering, and especially not from ESRF. That said, the internals from pyFAI have evolved and now, most rebinning engines are really separated from the geometry, which is useful for your project since you use a separated geometry. I consider tagging pyFAI 1.0 when all rebinning engines are squared out, i.e. all cut corners are properly handled.

I always considered to have a pluggable geometry but this is a project for pyFAI2, on which I did not start working yet.

Cheers,

Jerome

ctakacs commented 2 years ago

Hi Jerome, @kif

Incorporating grazing incidence scattering natively into pyFAI would be absolutely fantastic in my opinion. I forked the original repository and crudely updated the code to work with python 3 (and some newer versions of pyFAI).

I use it for a number of grazing incidents experiments here at SSRL and have a number of users/collaborators using it as well. Getting this to all work is a bit of an endeavor and having it be natively supported into pyFAI would be a real help.

Cheers, Chris