[REVIEW]: DIFFICE-jax: Differentiable neural-network solver for data assimilation of ice shelves in JAX
editorialbot opened this issue · comments
Submitting author: @wangyji (Yongji Wang)
Repository: https://github.com/YaoGroup/DIFFICE_jax
Branch with paper.md (empty if default branch):
Version: v1.0.0
Editor: @AnjaliSandip
Reviewers: @daniel-cheng, @nmcardoso, @RahulSundar
Archive: Pending
Status
Status badge code:
HTML: <a href="https://joss.theoj.org/papers/4cf986d53809937f2352b5fc2b7a6120"><img src="https://joss.theoj.org/papers/4cf986d53809937f2352b5fc2b7a6120/status.svg"></a>
Markdown: [](https://joss.theoj.org/papers/4cf986d53809937f2352b5fc2b7a6120)
Reviewers and authors:
Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)
Reviewer instructions & questions
@daniel-cheng & @nmcardoso & @RahulSundar, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:
@editorialbot generate my checklist
The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @AnjaliSandip know.
✨ Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest ✨
Checklists
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Software report:
github.com/AlDanial/cloc v 1.90 T=0.04 s (1153.2 files/s, 212526.9 lines/s)
-------------------------------------------------------------------------------
Language files blank comment code
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Python 21 491 777 1510
TeX 2 247 0 1456
Jupyter Notebook 5 0 960 1273
Markdown 10 232 0 634
YAML 2 8 10 45
TOML 1 6 0 34
MATLAB 1 12 13 32
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SUM: 42 996 1760 4984
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Commit count by author:
616 yjwang
111 Yao Lai
6 Yongi Wang
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):
✅ OK DOIs
- 10.5194/tc-15-1975-2021 is OK
- 10.1002/2014JF003181 is OK
- 10.1029/2024JH000169 is OK
- 10.1017/jog.2020.112 is OK
- 10.1016/j.jcp.2023.112428 is OK
- 10.5194/gmd-16-6671-2023 is OK
- 10.1017/jog.2021.120 is OK
- 10.1017/jog.2022.41 is OK
- 10.1017/jog.2023.73 is OK
- 10.1016/j.jcp.2024.112865 is OK
- 10.21203/rs.3.rs-2135795/v1 is OK
- 10.1029/JB094iB04p04071 is OK
- 10.3189/S0022143000015744 is OK
- 10.1038/s43247-022-00385-x is OK
- 10.1073/pnas.2309788121 is OK
- 10.5194/tc-9-1427-2015 is OK
- 10.1002/jgrf.20125 is OK
- 10.5194/tc-5-315-2011 is OK
- 10.3189/172756403781816338 is OK
- 10.1137/19M1274067 is OK
- 10.48550/arXiv.2207.02338 is OK
- 10.1016/j.jcp.2018.10.045 is OK
- 10.1029/2021MS002621 is OK
- 10.1017/jog.2023.8 is OK
- 10.1029/2010GL043853 is OK
- 10.1016/j.jcp.2023.112435 is OK
- 10.4208/cicp.oa-2020-0164 is OK
🟡 SKIP DOIs
- No DOI given, and none found for title: Deep learning the flow law of Antarctic Ice Shelve...
- No DOI given, and none found for title: MEaSUREs Phase-Based Antarctica Ice Velocity Map, ...
- No DOI given, and none found for title: MEaSUREs BedMachine Antarctica, Version 2
- No DOI given, and none found for title: Euler operators for mis-specified physics-informed...
- No DOI given, and none found for title: JAX: composable transformations of Python+NumPy pr...
❌ MISSING DOIs
- None
❌ INVALID DOIs
- None
Paper file info:
📄 Wordcount for paper.md is 1315
✅ The paper includes a Statement of need section
License info:
✅ License found: MIT License (Valid open source OSI approved license)
Review checklist for @nmcardoso
Conflict of interest
- I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.
Code of Conduct
- I confirm that I read and will adhere to the JOSS code of conduct.
General checks
- Repository: Is the source code for this software available at the https://github.com/YaoGroup/DIFFICE_jax?
- License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
- Contribution and authorship: Has the submitting author (@wangyji) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
- Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
- Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
- Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
- Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.
Functionality
- Installation: Does installation proceed as outlined in the documentation?
- Functionality: Have the functional claims of the software been confirmed?
- Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)
Documentation
- A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
- Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
- Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
- Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
- Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
- Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the software 2) Report issues or problems with the software 3) Seek support
Software paper
- Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
- A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
- State of the field: Do the authors describe how this software compares to other commonly-used packages?
- Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
- References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?