[REVIEW]: PyProximal - scalable convex optimization in Python #6326

editorialbot · 2024-02-06T09:47:58Z

Submitting author: @mrava87 (Matteo Ravasi)
Repository: http://github.com/pylops/pyproximal/
Branch with paper.md (empty if default branch): joss
Version: v0.8.0
Editor: @sappelhoff
Reviewers: @nirum, @ewu63
Archive: 10.5281/zenodo.10805997

Status

Status badge code:

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Markdown: [![status](https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d/status.svg)](https://joss.theoj.org/papers/c953d2cc2f446d83595cc858baadb15d)

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

@nirum & @ewu63, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
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✨ 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 @ewu63

📝 Checklist for @nirum

The text was updated successfully, but these errors were encountered:

editorialbot · 2024-02-06T09:48:01Z

Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

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For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

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editorialbot · 2024-02-06T09:48:02Z

Software report:

github.com/AlDanial/cloc v 1.88  T=0.12 s (911.3 files/s, 106775.3 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          79           1983           3798           4820
Markdown                         5            145              0            527
reStructuredText                12            300            277            387
YAML                             8             29             47            190
TeX                              1             12              0             95
CSS                              1             23              7             87
make                             2             18              8             48
TOML                             1              4              0             45
HTML                             1              6              0             32
-------------------------------------------------------------------------------
SUM:                           110           2520           4137           6231
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

editorialbot · 2024-02-06T09:48:04Z

Wordcount for paper.md is 1319

editorialbot · 2024-02-06T09:48:14Z

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

OK DOIs

- 10.1016/j.softx.2019.100361 is OK
- 10.1561/2200000016 is OK
- 10.1007/s10851-010-0251-1 is OK
- 10.1093/gji/ggab388 is OK
- 10.1109/GlobalSIP.2013.6737048 is OK
- 10.1190/tle42070457.1 is OK
- 10.3997/2214-4609.2022616015 is OK
- 10.3997/2214-4609.2021612003 is OK

MISSING DOIs

- 10.1109/tci.2024.3359178 may be a valid DOI for title: Interferometric Lensless Imaging: Rank-one Projections of Image Frequencies with Speckle Illuminations

INVALID DOIs

- None

editorialbot · 2024-02-06T09:49:07Z

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

sappelhoff · 2024-02-06T09:52:52Z

Hello again! 👋 

@nirum, @ewu63, @Leo-Simpson

FYI @mrava87

This is the review thread for the paper. All of our higher-level communications will happen here from now on, review comments and discussion can happen in the repository of the project (details below).

📓 Please read the "Reviewer instructions & questions" in the comment from our editorialbot (above).

✅ All reviewers get their own checklist with the JOSS requirements - you generate them as per the details in the editorialbot comment. As you go over the submission, please check any items that you feel have been satisfied.

💻 The JOSS review is different from most other journals: The reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention the link to #6326 so that a link is created to this thread. That will also help me to keep track!

❓ Please also feel free to comment and ask questions on this thread if you are unsure about something!

🎯 We aim for the review process to be completed within about 4-6 weeks but please make a start well ahead of this as JOSS reviews are by their nature iterative and any early feedback you may be able to provide to the author will be very helpful in meeting this schedule.

ewu63 · 2024-02-18T06:58:22Z

Review checklist for @ewu63

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 http://github.com/pylops/pyproximal/?
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 (@mrava87) 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?

sappelhoff · 2024-02-19T09:16:03Z

@ewu63 thanks for getting started!

@nirum @Leo-Simpson friendly reminder about your review in this thread. 🙂

nirum · 2024-02-23T10:25:23Z

Review checklist for @nirum

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 http://github.com/pylops/pyproximal/?
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 (@mrava87) 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?

sappelhoff · 2024-02-26T12:32:07Z

@ewu63 if you are done with your review (seems like it from your checkmarks), I'd appreciate if you could write a short summary whether you recommend this paper for acceptance or/and if some points still need to be addressed.

Same for @nirum once you are finished, please 🙏

@Leo-Simpson I haven't heard back from you in 3 weeks -- would you still like to review this paper? Please just let me know if you cannot make it so that I can find a potential replacement for you. It would be great to have all reviews finished within the next three weeks, approximately.

ewu63 · 2024-02-26T22:22:59Z

@sappelhoff I recommend this paper for acceptance, pending the following points to be addressed:

In the statement of need, it would be helpful to cite a few well-known packages in order to highlight the key distinguishing features of this package. This is already done in the repo README and can probably be reused.
One DOI is missing -- see [REVIEW]: PyProximal - scalable convex optimization in Python #6326 (comment) for the suggested DOI

This is tracked at PyLops/pyproximal#166

mrava87 · 2024-02-29T07:42:56Z

Thanks @ewu63, I have included now your comments as also written in the Github issue. Let me know if you agree or if you have any further suggestion :)

mrava87 · 2024-02-29T07:44:02Z

@editorialbot generate pdf

editorialbot · 2024-02-29T07:45:12Z

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

ewu63 · 2024-03-01T07:20:24Z

@sappelhoff the authors have addressed all my concerns, I recommend this paper for publication.

nirum · 2024-03-02T18:21:08Z

@mrava87 I really enjoyed reading through your repository. I especially appreciated the nice set of tutorials. Overall everything is clearly written and nicely documented. @sappelhoff I recommend for publication

mrava87 · 2024-03-03T06:41:09Z

@nirum thanks a lot!

mrava87 · 2024-03-12T09:59:22Z

@editorialbot check references

editorialbot · 2024-03-12T09:59:54Z

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

OK DOIs

- 10.1016/j.softx.2019.100361 is OK
- 10.1007/978-1-4419-9569-8_10 is OK
- 10.1561/2200000016 is OK
- 10.1007/s10851-010-0251-1 is OK
- 10.1093/gji/ggab388 is OK
- 10.1109/GlobalSIP.2013.6737048 is OK
- 10.1190/tle42070457.1 is OK
- 10.3997/2214-4609.2022616015 is OK
- 10.1109/tci.2024.3359178 is OK
- 10.3997/2214-4609.2021612003 is OK
- 10.1007/s11081-018-9380-y is OK
- 10.5281/zenodo.4486431 is OK
- 10.1145/2897824.2925875 is OK

MISSING DOIs

- No DOI given, and none found for title: proxalgs
- No DOI given, and none found for title: The Proximity Operator Repository

INVALID DOIs

- doi.org/10.1561/2400000003 is INVALID because of 'doi.org/' prefix

mrava87 · 2024-03-12T10:02:31Z

Ops, I made a mistake… will fix the broken DOI soon :)

mrava87 · 2024-03-12T18:02:14Z

@editorialbot check references

editorialbot · 2024-03-12T18:02:37Z

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

OK DOIs

- 10.1016/j.softx.2019.100361 is OK
- 10.1561/2400000003 is OK
- 10.1007/978-1-4419-9569-8_10 is OK
- 10.1561/2200000016 is OK
- 10.1007/s10851-010-0251-1 is OK
- 10.1093/gji/ggab388 is OK
- 10.1109/GlobalSIP.2013.6737048 is OK
- 10.1190/tle42070457.1 is OK
- 10.3997/2214-4609.2022616015 is OK
- 10.1109/tci.2024.3359178 is OK
- 10.3997/2214-4609.2021612003 is OK
- 10.1007/s11081-018-9380-y is OK
- 10.5281/zenodo.4486431 is OK
- 10.1145/2897824.2925875 is OK

MISSING DOIs

- No DOI given, and none found for title: proxalgs
- No DOI given, and none found for title: The Proximity Operator Repository

INVALID DOIs

- None

mrava87 · 2024-03-12T18:02:51Z

@sappelhoff done :)

sappelhoff · 2024-03-12T18:15:53Z

@editorialbot set 10.5281/zenodo.10805997 as archive

editorialbot · 2024-03-12T18:15:56Z

Done! archive is now 10.5281/zenodo.10805997

sappelhoff · 2024-03-12T18:16:45Z

@editorialbot set v0.8.0 as version

editorialbot · 2024-03-12T18:16:47Z

Done! version is now v0.8.0

sappelhoff · 2024-03-12T18:16:58Z

@editorialbot generate pdf

editorialbot · 2024-03-12T18:18:08Z

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

sappelhoff · 2024-03-12T18:18:59Z

@editorialbot recommend-accept

editorialbot · 2024-03-12T18:19:02Z

Attempting dry run of processing paper acceptance...

editorialbot · 2024-03-12T18:19:24Z

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

OK DOIs

- 10.1016/j.softx.2019.100361 is OK
- 10.1561/2400000003 is OK
- 10.1007/978-1-4419-9569-8_10 is OK
- 10.1561/2200000016 is OK
- 10.1007/s10851-010-0251-1 is OK
- 10.1093/gji/ggab388 is OK
- 10.1109/GlobalSIP.2013.6737048 is OK
- 10.1190/tle42070457.1 is OK
- 10.3997/2214-4609.2022616015 is OK
- 10.1109/tci.2024.3359178 is OK
- 10.3997/2214-4609.2021612003 is OK
- 10.1007/s11081-018-9380-y is OK
- 10.5281/zenodo.4486431 is OK
- 10.1145/2897824.2925875 is OK

MISSING DOIs

- No DOI given, and none found for title: proxalgs
- No DOI given, and none found for title: The Proximity Operator Repository

INVALID DOIs

- None

editorialbot · 2024-03-12T18:20:34Z

👋 @openjournals/dsais-eics, this paper is ready to be accepted and published.

Check final proof 👉📄 Download article

If the paper PDF and the deposit XML files look good in openjournals/joss-papers#5121, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

sappelhoff · 2024-03-12T18:23:58Z

@mrava87 great, thanks! Our job is done for now. Let's wait for the editor in chief to do a final check and ship this :-)

mrava87 · 2024-03-12T18:28:58Z

Great! thanks a lot for guiding me through this @sappelhoff, it has been a pleasure :-)

arfon · 2024-03-13T19:35:17Z

@editorialbot accept

editorialbot · 2024-03-13T19:35:19Z

Doing it live! Attempting automated processing of paper acceptance...

editorialbot · 2024-03-13T19:42:00Z

Ensure proper citation by uploading a plain text CITATION.cff file to the default branch of your repository.

If using GitHub, a Cite this repository menu will appear in the About section, containing both APA and BibTeX formats. When exported to Zotero using a browser plugin, Zotero will automatically create an entry using the information contained in the .cff file.

You can copy the contents for your CITATION.cff file here:

CITATION.cff

cff-version: "1.2.0"
authors:
- family-names: Ravasi
  given-names: Matteo
  orcid: "https://orcid.org/0000-0003-0020-2721"
- family-names: Örnhag
  given-names: Marcus Valtonen
  orcid: "https://orcid.org/0000-0001-8687-227X"
- family-names: Luiken
  given-names: Nick
  orcid: "https://orcid.org/0000-0003-3307-1748"
- family-names: Leblanc
  given-names: Olivier
  orcid: "https://orcid.org/0000-0003-3641-1875"
- family-names: Uruñuela
  given-names: Eneko
  orcid: "https://orcid.org/0000-0001-6849-9088"
contact:
- family-names: Ravasi
  given-names: Matteo
  orcid: "https://orcid.org/0000-0003-0020-2721"
doi: 10.5281/zenodo.10805997
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Ravasi
    given-names: Matteo
    orcid: "https://orcid.org/0000-0003-0020-2721"
  - family-names: Örnhag
    given-names: Marcus Valtonen
    orcid: "https://orcid.org/0000-0001-8687-227X"
  - family-names: Luiken
    given-names: Nick
    orcid: "https://orcid.org/0000-0003-3307-1748"
  - family-names: Leblanc
    given-names: Olivier
    orcid: "https://orcid.org/0000-0003-3641-1875"
  - family-names: Uruñuela
    given-names: Eneko
    orcid: "https://orcid.org/0000-0001-6849-9088"
  date-published: 2024-03-13
  doi: 10.21105/joss.06326
  issn: 2475-9066
  issue: 95
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6326
  title: PyProximal - scalable convex optimization in Python
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06326"
  volume: 9
title: PyProximal - scalable convex optimization in Python

If the repository is not hosted on GitHub, a .cff file can still be uploaded to set your preferred citation. Users will be able to manually copy and paste the citation.

Find more information on .cff files here and here.

editorialbot · 2024-03-13T19:42:03Z

🐘🐘🐘 👉 Toot for this paper 👈 🐘🐘🐘

editorialbot · 2024-03-13T19:42:03Z

🚨🚨🚨 THIS IS NOT A DRILL, YOU HAVE JUST ACCEPTED A PAPER INTO JOSS! 🚨🚨🚨

Here's what you must now do:

Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.06326 joss-papers#5125
Wait five minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.06326
If everything looks good, then close this review issue.
Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

mrava87 · 2024-03-14T05:41:09Z

@sappelhoff just to confirm that the paper DOI works and everything looks good :)

But I do not seem to be able myself to close this issue (point 2), I guess you can...

Thanks again everyone, @sappelhoff @nirum and @ewu63!

sappelhoff · 2024-03-14T09:10:10Z

Thanks everyone!

editorialbot · 2024-03-14T09:10:11Z

🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉

If you would like to include a link to your paper from your README use the following code snippets:

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HTML:
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  <img src="https://joss.theoj.org/papers/10.21105/joss.06326/status.svg" alt="DOI badge" >
</a>

reStructuredText:
.. image:: https://joss.theoj.org/papers/10.21105/joss.06326/status.svg
   :target: https://doi.org/10.21105/joss.06326

This is how it will look in your documentation:

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editorialbot added Makefile Python review TeX Track: 5 (DSAIS) Data Science, Artificial Intelligence, and Machine Learning waitlisted Submissions in the JOSS backlog due to reduced service mode. labels Feb 6, 2024

editorialbot assigned sappelhoff Feb 6, 2024

editorialbot mentioned this issue Feb 6, 2024

[PRE REVIEW]: PyProximal - scalable convex optimization in Python #6185

Closed

sappelhoff mentioned this issue Feb 19, 2024

[REVIEW]: CalibrateEmulateSample.jl: Accelerated Parametric Uncertainty Quantification #6372

Closed

This was referenced Feb 22, 2024

Update repo link in documentation PyLops/pyproximal#161

Closed

Missing description of the Rosenbrock function in documentation PyLops/pyproximal#162

Closed

ewu63 mentioned this issue Feb 26, 2024

Comments on the JOSS paper PyLops/pyproximal#166

Closed

Kevin-Mattheus-Moerman removed the waitlisted Submissions in the JOSS backlog due to reduced service mode. label Mar 10, 2024

editorialbot added the recommend-accept Papers recommended for acceptance in JOSS. label Mar 12, 2024

editorialbot added accepted published Papers published in JOSS labels Mar 13, 2024

sappelhoff closed this as completed Mar 14, 2024

[REVIEW]: PyProximal - scalable convex optimization in Python #6326

[REVIEW]: PyProximal - scalable convex optimization in Python #6326

Comments

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Review checklist for @ewu63

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

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Review checklist for @nirum

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

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