[REVIEW]: LINFA: a Python library for variational inference with normalizing flow and annealing

[editorialbot]

Submitting author: @daneschi (Daniele E. Schiavazzi)
Repository: https://github.com/desResLab/LINFA
Branch with paper.md (empty if default branch): master
Version: 1.5.1
Editor: @lrnv
Reviewers: @robmoss, @selimfirat
Archive: 10.5281/zenodo.10883597

Status

Status badge code:

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Markdown: [![status](https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b/status.svg)](https://joss.theoj.org/papers/adb20d3d808e8b369e827b5d9fba277b)

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

@robmoss & @selimfirat, 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 @lrnv 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 @robmoss

📝 Checklist for @selimfirat

[editorialbot]

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

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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]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.08 s (832.3 files/s, 167375.2 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          26           1011            893           2939
XML                              6              0            129           1842
Jupyter Notebook                 2              0           4069            440
Markdown                         2            124              0            416
TeX                              2             45              0            379
reStructuredText                19            158            336             93
YAML                             3             14             14             63
TOML                             1              5              1             29
DOS Batch                        1              8              1             26
Bourne Shell                     2              1              0             16
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            65           1370           5450           6252
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 5049

[editorialbot]

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

[lrnv]

👋🏼 @robmoss & @selimfirat this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step is to create a checklist for your review by entering

@editorialbot generate my checklist

as the top of a new comment in this thread.

These checklists contain the JOSS requirements. As you go over the submission, please check any items that you feel have been satisfied. The first comment in this thread also contains links to the JOSS reviewer guidelines (there : https://joss.readthedocs.io/en/latest/reviewer_guidelines.html)

The JOSS review is different from most other journals. Our goal is to work with the authors to help them meet our criteria instead of merely passing judgment on the submission. As such, the reviewers are encouraged to submit issues and pull requests on the software repository. When doing so, please mention openjournals/joss-reviews#6309 so that a link is created to this thread (and I can keep an eye on what is happening). Please also feel free to comment and ask questions on this thread. In my experience, it is better to post comments/questions/suggestions as you come across them instead of waiting until you've reviewed the entire package.

We aim for reviews to be completed within about 2-4 weeks. Please let me know if any of you require some more time. We can also use EditorialBot (our bot) to set automatic reminders if you know you'll be away for a known period of time.

Please feel free to ping me (@lrnv) if you have any questions/concerns.

[editorialbot]

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

OK DOIs

- None

MISSING DOIs

- 10.1016/b978-0-08-051581-6.50057-x may be a valid DOI for title: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
- 10.2172/4390578 may be a valid DOI for title: Equation of state calculations by fast computing machines
- 10.1093/oso/9780198509936.003.0015 may be a valid DOI for title: Monte Carlo sampling methods using Markov chains and their applications
- 10.21236/ada208388 may be a valid DOI for title: Sampling-based approaches to calculating marginal densities
- 10.1561/9781601981851 may be a valid DOI for title: Graphical models, exponential families, and variational inference
- 10.1109/tpami.2020.2992934 may be a valid DOI for title: Normalizing flows: An introduction and review of current methods
- 10.1016/j.jcp.2022.111454 may be a valid DOI for title: Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models
- 10.1615/int.j.uncertaintyquantification.2022043110 may be a valid DOI for title: AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
- 10.1016/s0951-8320(02)00229-6 may be a valid DOI for title: Theorems and examples on high dimensional model representation
- 10.1016/0041-5553(67)90144-9 may be a valid DOI for title: On the distribution of points in a cube and the approximate evaluation of integrals

INVALID DOIs

- None

[robmoss]

Review checklist for @robmoss

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/desResLab/LINFA?
• 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 (@daneschi) 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?

[lrnv]

@robmoss I see your review already started, how is it going ?

@selimfirat It's been two weeks did you have the time to take a look at this submission ? If you need more time, simply tell me I can setup automatic reminders for you if you want.

[robmoss]

@lrnv thanks for checking in. I've made some progress, but have had to take some personal leave due to unforeseen circumstances. I will return to work next week, and continue my review. I identified a packaging issue, which is related to the paper but only applies to the software itself. Should I ask the authors to respond to this issue as part of the review process? Thanks in advance for your advice :)

[lrnv]

@robmoss thanks for your reply. It is definitely expected from you to raise issues that apply to the software: the subject an the content of the review should be the software, the paper is just a side-effect IMHO. So if you found bugs or problems with the software, yes you can ask the authors to fix things as part of the review process. You can ask for new features if you think they would be logically inserted into the current project, or even for more detailled documentation, refactoring of API or even refactoring of internals, if you think that some other decision would have made more sense. Sky is the limit.

[robmoss]

@lrnv Thanks very much for your advice. I've noted a number of small things to raise with the authors (mostly related to the few remaining unchecked items in my checklist) and will file a few issues in their repo later this week.

[selimfirat]

Review checklist for @selimfirat

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/desResLab/LINFA?
• 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 (@daneschi) 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?

[editorialbot]

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

[selimfirat]

@editorialbot commands

[editorialbot]

Hello @selimfirat, here are the things you can ask me to do:

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# Get a link to the complete list of reviewers
@editorialbot list reviewers

[selimfirat]

@robmoss I see your review already started, how is it going ?

@selimfirat It's been two weeks did you have the time to take a look at this submission ? If you need more time, simply tell me I can setup automatic reminders for you if you want.

Hello again. I requested revisions by creating issues in the repository regarding the unchecked items: https://github.com/desResLab/LINFA/issues

Now, I am waiting until the author makes neccessary changes. Is there any other action I should take?

[lrnv]

@selimfirat Well done, this is great. 👍

Note that you are allowed and encouraged to also make comments and revisions requests about the code itself and not only the paper (this is the main point of JOSS reviews: to get reviewers oppinon and knowledge on the codebase). E.g., if you think the tests cases are not good enough, or if some implementation of a functionality looks clunky to you, or if you think something should be done in some other manner, like an API that does not look right etc... or, more trivially, if you find a straight up bug.

Sky is your limit.

Otherwise, everything looks good on my part :)

[robmoss]

@lrnv Likewise, I've created issues for each of my comments and questions, I'm now waiting for the authors to respond.

[lrnv]

@daneschi it has been two weeks. Would it be possible to have a status update on the issues that were raised ?

[lrnv]

@editorialbot commands

[editorialbot]

Hello @lrnv, here are the things you can ask me to do:

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[editorialbot]

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

OK DOIs

- 10.1109/TPAMI.1984.4767596 is OK
- 10.1063/1.1699114 is OK
- 10.1093/biomet/57.1.97 is OK
- 10.1080/01621459.1990.10476213 is OK
- 10.1561/2200000001 is OK
- 10.1007/978-3-540-71050-9 is OK
- 10.1109/TPAMI.2020.2992934 is OK
- 10.1016/j.jcp.2022.111454 is OK
- 10.1615/Int.J.UncertaintyQuantification.2022043110 is OK
- 10.1214/aos/1176347963 is OK
- 10.18637/jss.v019.i09 is OK
- 10.1016/S0951-8320(02)00229-6 is OK
- 10.1016/j.jcp.2012.07.022 is OK
- 10.1016/0041-5553(67)90144-9 is OK
- 10.7717/peerj-cs.1516 is OK
- 10.21105/joss.05428 is OK

MISSING DOIs

- No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...
- No DOI given, and none found for title: Variational inference with normalizing flows
- No DOI given, and none found for title: Density estimation using real NVP
- No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...
- No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation
- No DOI given, and none found for title: Improved variational inference with inverse autore...
- No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...
- No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...
- No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...
- No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...
- No DOI given, and none found for title: Preconditioned training of normalizing flows for v...
- No DOI given, and none found for title: Bayespy: variational Bayesian inference in Python
- No DOI given, and none found for title: Pyro: Deep universal probabilistic programming

INVALID DOIs

- None

[selimfirat]

I checked the repository and updated the checklist, in case still needed :). All issues seem resolved.

[daneschi]

Thanks @lrnv. Is there anything else needed on my end?

…

On Tue, Apr 2, 2024 at 6:06 AM Selim Firat Yilmaz ***@***.***> wrote: I checked the repository and updated the checklist, in case still needed :). All issues seem resolved. — Reply to this email directly, view it on GitHub <#6309 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADJL6ENWZWZOFIDZN23UUVTY3J7JPAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMZRGU4TEMZZGU> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[lrnv]

@daneschi Not for the moment, you have to wait for the aEiC to take care of the publication. Congratulation :)

[daneschi]

Thank you very much for all your Help and Kind Supervision throughout this review!

…

On Tue, Apr 2, 2024 at 10:29 AM Oskar Laverny ***@***.***> wrote: @daneschi <https://github.com/daneschi> Not for the moment, you have to wait for the aEiC to take care of the publication. Congratulation :) — Reply to this email directly, view it on GitHub <#6309 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADJL6EMOBEIIMZPT7OU6RCLY3K6GNAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMZSGE4TSMJSGQ> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[arfon]

👋 folks. A few things with the paper here: It looks to be 'off' in a few places:

• The AAS link in the margin - is this paper being jointly published with AAS? If not, please remove those sections from your paper.md.
• A table in the appendix is overflowing in the references. Please see if you can fix this with a \newpage or similar in the paper.
• The paper is waaaaaaay longer than we like to typically publish in JOSS (guideline is ~1000 words). Given this submission is ready to go I'm not going ask for changes now, but in the future @lrnv please look out for this.

[lrnv]

Thanks a lot @arfon for catching theses. I will be more careful in the future w.r.t. text length. Since here ~75% of it is in appendix, I thought it was OK, but reading the guidelines once more, I see that it is not.

[daneschi]

Hi @lrnv should I fix these problems in the md file? Sorry for the length, I also thought it was OK to have more material in the appendix. Thanks

…

On Thu, Apr 4, 2024 at 11:03 AM Oskar Laverny ***@***.***> wrote: Thanks a lot @arfon <https://github.com/arfon> for catching theses. I will be more careful in the future w.r.t. text length. Since here ~75% of it is in appendix, I thought it was OK, but reading the guidelines once more, I see that it is not. — Reply to this email directly, view it on GitHub <#6309 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADJL6EMMUAPLQGC6TCSKVG3Y3VTVZAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMZXGQ3DENRUHE> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[lrnv]

Yes please. You are not publishing in the AAS ? Thus the AAS section of your .md file should not be there.

[daneschi]

Thank you @lrnv I have fixed both issues.

…

On Thu, Apr 4, 2024 at 11:21 AM Oskar Laverny ***@***.***> wrote: Yes please. You are not publishing in the AAS ? Thus the AAS section of your .md file should not be there. — Reply to this email directly, view it on GitHub <#6309 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADJL6EKWN7UGV5WEBRP6IRTY3VVXTAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMZXGUYDGNBTG4> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[lrnv]

@editorialbot generate pdf

[editorialbot]

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

[lrnv]

Ok @arfon should be good to go now. @daneschi thanks for fixing.

[arfon]

@editorialbot recommend-accept

[editorialbot]

Attempting dry run of processing paper acceptance...

[editorialbot]

👋 @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#5214, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

[editorialbot]

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

OK DOIs

- 10.1109/TPAMI.1984.4767596 is OK
- 10.1063/1.1699114 is OK
- 10.1093/biomet/57.1.97 is OK
- 10.1080/01621459.1990.10476213 is OK
- 10.1561/2200000001 is OK
- 10.1007/978-3-540-71050-9 is OK
- 10.1109/TPAMI.2020.2992934 is OK
- 10.1016/j.jcp.2022.111454 is OK
- 10.1615/Int.J.UncertaintyQuantification.2022043110 is OK
- 10.1214/aos/1176347963 is OK
- 10.18637/jss.v019.i09 is OK
- 10.1016/S0951-8320(02)00229-6 is OK
- 10.1016/j.jcp.2012.07.022 is OK
- 10.1016/0041-5553(67)90144-9 is OK
- 10.7717/peerj-cs.1516 is OK
- 10.21105/joss.05428 is OK

MISSING DOIs

- No DOI given, and none found for title: Normalizing flows for probabilistic modeling and i...
- No DOI given, and none found for title: Variational inference with normalizing flows
- No DOI given, and none found for title: Density estimation using real NVP
- No DOI given, and none found for title: Glow: Generative flow with invertible 1x1 convolut...
- No DOI given, and none found for title: Masked Autoregressive Flow for Density Estimation
- No DOI given, and none found for title: Improved variational inference with inverse autore...
- No DOI given, and none found for title: MADE: Masked autoencoder for distribution estimati...
- No DOI given, and none found for title: Batch normalization: Accelerating deep network tra...
- No DOI given, and none found for title: Differentially Private Normalizing Flows for Densi...
- No DOI given, and none found for title: Greedy inference with structure-exploiting lazy ma...
- No DOI given, and none found for title: Preconditioned training of normalizing flows for v...
- No DOI given, and none found for title: Bayespy: variational Bayesian inference in Python
- No DOI given, and none found for title: Pyro: Deep universal probabilistic programming

INVALID DOIs

- None

[arfon]

@editorialbot accept

[editorialbot]

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

[editorialbot]

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:
- email: [email protected]
  family-names: Wang
  given-names: Yu
- email: [email protected]
  family-names: Cobian
  given-names: Emma R.
- email: [email protected]
  family-names: Lee
  given-names: Jubilee
- email: [email protected]
  family-names: Liu
  given-names: Fang
- email: [email protected]
  family-names: Hauenstein
  given-names: Jonathan D.
- email: [email protected]
  family-names: Schiavazzi
  given-names: Daniele E.
contact:
- email: [email protected]
  family-names: Schiavazzi
  given-names: Daniele E.
doi: 10.5281/zenodo.10883597
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - email: [email protected]
    family-names: Wang
    given-names: Yu
  - email: [email protected]
    family-names: Cobian
    given-names: Emma R.
  - email: [email protected]
    family-names: Lee
    given-names: Jubilee
  - email: [email protected]
    family-names: Liu
    given-names: Fang
  - email: [email protected]
    family-names: Hauenstein
    given-names: Jonathan D.
  - email: [email protected]
    family-names: Schiavazzi
    given-names: Daniele E.
  date-published: 2024-04-05
  doi: 10.21105/joss.06309
  issn: 2475-9066
  issue: 96
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6309
  title: "LINFA: a Python library for variational inference with
    normalizing flow and annealing"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06309"
  volume: 9
title: "LINFA: a Python library for variational inference with
  normalizing flow and annealing"

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[editorialbot]

🐘🐘🐘 👉 Toot for this paper 👈 🐘🐘🐘

[editorialbot]

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

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0. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.06309 joss-papers#5220
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[arfon]

@robmoss, @selimfirat – many thanks for your reviews here and to @lrnv for editing this submission! JOSS relies upon the volunteer effort of people like you and we simply wouldn't be able to do this without you ✨

@daneschi – your paper is now accepted and published in JOSS ⚡🚀💥

[editorialbot]

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

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[daneschi]

Thank you all very much for your Kind Assistance with this review! Thanks @robmoss, @selimfirat for your comments and @lrnv for your editorial supervision and your patience!

…

On Fri, Apr 5, 2024 at 4:20 PM The Open Journals editorial robot < ***@***.***> wrote: 🎉🎉🎉 Congratulations on your paper acceptance! 🎉🎉🎉 If you would like to include a link to your paper from your README use the following code snippets: Markdown: [](https://doi.org/10.21105/joss.06309) HTML: <a style="border-width:0" href="https://doi.org/10.21105/joss.06309"> <img src="https://joss.theoj.org/papers/10.21105/joss.06309/status.svg" alt="DOI badge" > </a> reStructuredText: .. image:: https://joss.theoj.org/papers/10.21105/joss.06309/status.svg :target: https://doi.org/10.21105/joss.06309 This is how it will look in your documentation: [image: DOI] <https://doi.org/10.21105/joss.06309> *We need your help!* The Journal of Open Source Software is a community-run journal and relies upon volunteer effort. If you'd like to support us please consider doing either one (or both) of the the following: - Volunteering to review for us sometime in the future. You can add your name to the reviewer list here: https://reviewers.joss.theoj.org/join - Making a small donation to support our running costs here: https://numfocus.org/donate-to-joss — Reply to this email directly, view it on GitHub <#6309 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADJL6EI6L46RJXKVPCS5JMTY34BPNAVCNFSM6AAAAABCSWRGUSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDANBQGU3DOMRTGQ> . You are receiving this because you were mentioned.Message ID: ***@***.***>