Closed nogueirapeterson closed 2 years ago
Hi @nogueirapeterson. This is amazing thanks a lot for the contribution. I'll have a look and get back to you for updates/compat and I'll be happy to help with any change needed.
Super cool!!!!!
Yes, super cool! The work was hard. We were new to Julia land. But in the end reward! We are impressed with how JUDI makes the application (FWI, LSRTM) easier.
Wow, this is such a helpful and timely addition! I work on medical images and currently ignore attenuation losses. These operators will be helpful to make my simulations more realistic.
Thank you so much for the contribution! I will try to help in the PR process as much as I can.
Yes, @rafaelorozco . They are quite useful in the medical imaging field as well. These operators are second-order and based on the SLS rheological model. I am available to provide you with any clarification regarding this implementation.
Although equations based on the SLS model are the best in physical terms, I also implemented viscoacoustic equations (forward and adjoint) based on the Kelvin-Voigt (ren_1st_order / ren_2nd_order
) and Maxwell (deng_1st_order / deng_2nd_order
) rheological model on Devito (https://github.com /devitocodes/devito/blob/master/examples/seismic/viscoacoustic/operators.py).
needs rebase on master too
Concerning the DFT
, we already included it in our case and it seems fine.
Another point is concerning the boundary effect that I mentioned in your PR in Devito…should I keep solve
implementation even with strong boundary effects?
Sorry for delay, will get back to you after SEG deadline
@mloubout I did the rebase, but we still change the tests files. I'll let you know when everything is ok.
@mloubout sorry for the delay. We did the rebase and fixed the conflicts. I think that is all ready for you to take a look at.
Great will have a look asap. Thanks
Merging #95 (1ed1f21) into master (cada5b3) will decrease coverage by
4.96%
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## master #95 +/- ##
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- Coverage 85.12% 80.16% -4.97%
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Files 30 30
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...rc/TimeModeling/Modeling/lsrtm_objective_serial.jl | 0.00% <0.00%> (-78.58%) |
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src/TimeModeling/Modeling/twri_objective_serial.jl | 0.00% <ø> (ø) |
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src/TimeModeling/Utils/auxiliaryFunctions.jl | 80.20% <50.00%> (-2.69%) |
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src/TimeModeling/Modeling/python_interface.jl | 75.00% <70.00%> (-16.08%) |
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src/TimeModeling/Modeling/fwi_objective_serial.jl | 95.45% <100.00%> (+7.45%) |
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src/TimeModeling/Types/ModelStructure.jl | 87.31% <100.00%> (+0.19%) |
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src/TimeModeling/Types/OptionsStructure.jl | 100.00% <100.00%> (ø) |
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...TimeModeling/LinearOperators/judiExtendedSource.jl | 18.18% <0.00%> (-60.61%) |
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...ling/LinearOperators/judiJacobianExtendedSource.jl | 66.66% <0.00%> (-29.17%) |
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... and 13 more |
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@mloubout we reviewed the last suggestions/corrections. Below is the pending test list. Thanks for your patience.
file: test_all_options.jl
Testing isic
opt = Options(sum_padding=true, free_surface=parsed_args["fs"], isic=true)
Testing subsampling
opt = Options(sum_padding=true, free_surface=parsed_args["fs"], subsampling_factor=4)
Testing isic+dft
opt = Options(sum_padding=true, free_surface=parsed_args["fs"], isic=true, frequencies=[2.5, 4.5])
file: test_jacobian_extended.jl
Sounds great. I'll try to help out this week to get this merged since I would prefer merging this first because my pending one would be a pain to rebase for you
@nogueirapeterson I pushed a commit to the PR if you don't mind. It's mostly small changes here and there and should now support all the options (except freesurface) including extended jacobian case. I made some small change to the PDE (I added the link to paper) so that it passes adjoint better. It's still the correct PDE but feel free to check you still get the data correctly.
Should be GTG (and part of CI) now. Let me know if you happy with my change and I'll merge is as soon as CI is green
Very nice @mloubout ! I understand the changes you made to the equations. Thanks a lot for the changes and support. I am very happy about these contributions! I'm really enjoying the JUDI.
My road map on JUDI is:
What do you think? Great for you? Thank you so much again!
Sounds like a good plan. Elastic would be great.
Still figuring out few failing tests but will merge this soon
Thanks a lot for the merge!
Thanks a lot for the super nice contribution
Hi @mloubout, How are you? I hope you are well. First of all, congratulations on the work you have been developing in JUDI. The framework is very great!
@lauerami and I have been working in JUDI for a while. Now, we incorporate the viscoacoustic operators (forward, adjoint, Born, and gradient) into it. I hope you appreciate our contribution. Very soon I will do more PRs.
Regards, Peterson Nogueira