[REVIEW]: DiffOpt: Parallel optimization of Jax models

[editorialbot]

Submitting author: @AlanPearl (Alan Pearl)
Repository: https://github.com/AlanPearl/diffopt
Branch with paper.md (empty if default branch): paper
Version: v1.0.0
Editor: @jbytecode
Reviewers: @landreman, @ewu63
Archive: Pending

Status

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Reviewers and authors:

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Reviewer instructions & questions

@landreman & @ewu63, 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:

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The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @jbytecode 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

📝 Checklist for @landreman

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.04 s (1131.6 files/s, 181175.3 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          23            532            805           1893
Jupyter Notebook                 5              0           1789            782
Markdown                         2             36              0            165
TeX                              1              6              0             86
YAML                             3              6              4             59
reStructuredText                 3             48             54             50
TOML                             1              5              0             29
DOS Batch                        1              8              1             26
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            40            645           2660           3099
-------------------------------------------------------------------------------

Commit count by author:

    17	Alan Pearl

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

✅ OK DOIs

- 10.21105/astro.2105.05859 is OK
- 10.1093/mnras/stac3118 is OK
- 10.1093/mnras/stad456 is OK
- 10.1109/ICNN.1995.488968 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: JAX: composable transformations of Python+NumPy pr...
- No DOI given, and none found for title: Multivariate Density Estimation
- No DOI given, and none found for title: Mathematical methods of statistics

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1259

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[jbytecode]

Dear Reviewers @landreman and @ewu63

You can start by creating your task lists. Each list will contain several tasks.

As you complete each task, you can check off the corresponding checkbox. Since the review process for JOSS is interactive, you are encouraged to engage with the author, other reviewers, and the editor throughout. You can open issues and submit pull requests in the target repository. Please include the URL of this page in those interactions, so we can keep track of activities outside of the platform.

To generate your task list, simply type:

@editorialbot generate my checklist

Thank you in advance.

[landreman]

Review checklist for @landreman

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/AlanPearl/diffopt?
• 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 (@AlanPearl) 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?