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[REVIEW]: signnet: An R package for analyzing signed networks #4987

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editorialbot opened this issue Dec 1, 2022 · 56 comments
Closed

[REVIEW]: signnet: An R package for analyzing signed networks #4987

editorialbot opened this issue Dec 1, 2022 · 56 comments
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accepted C++ published Papers published in JOSS R recommend-accept Papers recommended for acceptance in JOSS. review TeX Track: 4 (SBCS) Social, Behavioral, and Cognitive Sciences

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editorialbot commented Dec 1, 2022

Submitting author: @schochastics (David Schoch)
Repository: https://github.com/schochastics/signnet
Branch with paper.md (empty if default branch):
Version: v1.0.0
Editor: @sbenthall
Reviewers: @cosimameyer, @zpneal
Archive: https://doi.org/10.5281/zenodo.7522563

Status

status

Status badge code:

HTML: <a href="https://joss.theoj.org/papers/9c54412321d25bfcd4fbde8ea3273cb6"><img src="https://joss.theoj.org/papers/9c54412321d25bfcd4fbde8ea3273cb6/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/9c54412321d25bfcd4fbde8ea3273cb6/status.svg)](https://joss.theoj.org/papers/9c54412321d25bfcd4fbde8ea3273cb6)

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

@cosimameyer & @zpneal, 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 @sbenthall 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 @cosimameyer

📝 Checklist for @zpneal

@editorialbot editorialbot added C++ R review TeX Track: 4 (SBCS) Social, Behavioral, and Cognitive Sciences labels Dec 1, 2022
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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:

@editorialbot commands

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

@editorialbot generate pdf

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.04 s (1177.8 files/s, 115917.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
R                               23            211            749           1475
C++                              6             46             84            481
Markdown                         7            139              0            459
TeX                              1             17              0            200
Rmd                              7            179            332            188
YAML                             4             22              5            137
-------------------------------------------------------------------------------
SUM:                            48            614           1170           2940
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

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Wordcount for paper.md is 1156

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

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1037/h0046049 is OK
- 10.1080/00223980.1946.9917275 is OK
- 10.1093/comnet/cnx044 is OK
- 10.1093/comnet/cny015 is OK
- 10.1016/0378-8733(95)00259-6 is OK
- 10.1016/j.socnet.2018.07.007 is OK
- 10.1145/1526709.1526808 is OK
- 10.1145/1526709.1526809 is OK
- 10.1016/j.socnet.2014.03.005 is OK
- 10.1016/j.socnet.2004.08.007 is OK
- 10.1007/BF02289026 is OK
- 10.1080/0022250X.2019.1711376 is OK
- 10.1371/journal.pone.0244363 is OK
- 10.48550/arXiv.2209.00676 is OK
- 10.1016/j.dam.2019.04.019 is OK
- 10.48550/arXiv.2205.13411 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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

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cosimameyer commented Dec 1, 2022

Review checklist for @cosimameyer

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

General checks

  • Repository: Is the source code for this software available at the https://github.com/schochastics/signnet?
  • License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@schochastics) 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?

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👋🏼 @schochastics @cosimameyer @zpneal 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.

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 #4987 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 (@sbenthall) if you have any questions/concerns.

@zpneal
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zpneal commented Dec 1, 2022

Review checklist for @zpneal

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

General checks

  • Repository: Is the source code for this software available at the https://github.com/schochastics/signnet?
  • License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@schochastics) 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?

@zpneal
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zpneal commented Dec 2, 2022

This is a much-needed package and very clear description of its features. I only have a few minor suggestions:

Installation - The package installs fine (I am reviewing the development version from GitHub). However, I suggest including the installation syntax directly in the manuscript. For example, maybe insert install.packages("signnet") (or similar, if it must be installed from GitHub) right before library(signnet) on page 1.

Reproducibility & Functionality -
When running frustration_exact(tribes) I get the error the package 'ompr' is needed for this function to work. Currently the ompt package is only suggested, but not imported. However, if it is critical to run frustration_exact(), which is such an important function that it is demonstrated in this paper, then I suggest it be imported.

State of the field -
You explain that computing the optimal partition that minimizes frustration is NP hard and can only be calculated for small signed networks. While it is NP hard, and perhaps the signnet implementation only works for small signed networks, Aref & Neal (2020, 2021 in Scientific Reports) demonstrate a method applied to much larger signed networks. I suggest either removing this claim, or adding a reference to this work.

You cite the R backbone package when you discuss the fact that a weighted projection can be converted into an unweighted network. It may also be worth noting, either here or elsewhere, that the backbone package can generate signed backbones (from projections, but also from unipartite graphs) in an igraph format that is compatible with signnet for subsequent analysis. This may highlight to readers one possible source of signed network data, since they may be able to generate signed networks from existing non-signed networks.

References -
You currently cite Domagalski et al (2021), however the backbone package has an updated reference. I suggest replacing this with Neal (2022, https://doi.org/10.1371/journal.pone.0269137).

schochastics added a commit to schochastics/signnet that referenced this issue Dec 2, 2022
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install.packages("signnet") (or similar, if it must be installed from GitHub) right before library(signnet) on page 1.

added. Good that you bring this up: The CRAN version is outdated at the moment but after this review process I am going to submit the new version again. So the version to be reviewed is on Github but eventually it will be on CRAN so I added install.packages("signnet")

Reproducibility & Functionality -
When running frustration_exact(tribes) I get the error the package 'ompr' is needed for this function to work. Currently the ompt package is only suggested, but not imported. However, if it is critical to run frustration_exact(), which is such an important function that it is demonstrated in this paper, then I suggest it be imported.

Happy to discuss this point, but I would like to keep it under Suggests. The ompr ecosystem includes several packages which I do not want to force onto every user. Of course the exact calculation is important, but I'd rather have those who want to use it go the extra mile given their might be quirks in the installation. I did add a sentence now explaining that more packages are needed to use the function. But as I said, I can still be convinced otherwise :)

State of the field
You explain that computing the optimal partition that minimizes frustration is NP hard and can only be calculated for small signed networks. While it is NP hard, and perhaps the signnet implementation only works for small signed networks, Aref & Neal (2020, 2021 in Scientific Reports) demonstrate a method applied to much larger signed networks. I suggest either removing this claim, or adding a reference to this work.

I think I went on auto pilot here. "NP hard-> small networks". Apologies for that. I did implement the efficient algorithm but the solver is not as efficient as the one used bei Samin, I believe. I did add a reference and also changed the sentence.

You cite the R backbone package when you discuss the fact that a weighted projection can be converted into an unweighted network. It may also be worth noting, either here or elsewhere, that the backbone package can generate signed backbones (from projections, but also from unipartite graphs) in an igraph format that is compatible with signnet for subsequent analysis. This may highlight to readers one possible source of signed network data, since they may be able to generate signed networks from existing non-signed networks.

good point! I added a sentence at the end of the Statement of need

References
You currently cite Domagalski et al (2021), however the backbone package has an updated reference. I suggest replacing this with Neal (2022, https://doi.org/10.1371/journal.pone.0269137).

changed

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

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zpneal commented Dec 2, 2022

Thanks for these revisions. (FYI - There's an extra quotation mark in the new line to install signnet)

Re: ompr - I agree about keeping required dependencies to a minimum. I think keeping this as suggests rather than imports makes sense, but this means the code in the paper won't replicate without some extra user steps. I suggest adding to the paper the extra install.packages("ompr") line so that the frustration_exact(tribes) function will replicate. You could add a note here explaining that ompr is only needed for certain package functions (which ones?), and so is not installed by default.

With that change, I can also tick off the "reproducibility" item from the checklist and would be satisfied with the submission.

schochastics added a commit to schochastics/signnet that referenced this issue Dec 2, 2022
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Thats of course a good point. I fixed the extra quotation and also now added the installation step.

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@editorialbot generate pdf

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

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zpneal commented Dec 2, 2022

Looks great! I've checked every item on the checklist and support publication of this paper.

@sbenthall Is there anything else I need to do to mark my review as complete?

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That was a very fast review, Zachary :) I’ll do my best to finish mine also as fast as possible. Just a quick note, as mentioned in the other issue, I‘m currently on holiday and will only get a chance to look into the package at the end of next week - but I‘m looking forward to digging into it! It looks very cool! 😊

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Done! Archive is now https://doi.org/10.5281/zenodo.7522563

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@editorialbot set v1.0.0 as version

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Done! version is now v1.0.0

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I recommend this submission for acceptance!

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@editorialbot recommend-accept

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Attempting dry run of processing paper acceptance...

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

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1037/h0046049 is OK
- 10.1080/00223980.1946.9917275 is OK
- 10.1093/comnet/cnx044 is OK
- 10.1093/comnet/cny015 is OK
- 10.1016/0378-8733(95)00259-6 is OK
- 10.1016/j.socnet.2018.07.007 is OK
- 10.1145/1526709.1526808 is OK
- 10.1145/1526709.1526809 is OK
- 10.1016/j.socnet.2014.03.005 is OK
- 10.1016/j.socnet.2004.08.007 is OK
- 10.1007/BF02289026 is OK
- 10.1080/0022250X.2019.1711376 is OK
- 10.1371/journal.pone.0244363 is OK
- 10.48550/arXiv.2209.00676 is OK
- 10.1016/j.dam.2019.04.019 is OK
- 10.48550/arXiv.2205.13411 is OK
- 10.1038/s41598-020-58471-z is OK
- 10.1371/journal.pone.0269137 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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👋 @openjournals/sbcs-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#3866, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

@editorialbot editorialbot added the recommend-accept Papers recommended for acceptance in JOSS. label Jan 10, 2023
@schochastics
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@sbenthall Just to double check: Is there anything needed from me to finalize the process? Thanks

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@schochastics You are all set, I believe. We are waiting for the editors to do the final sign off.

@schochastics
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ah perfect thanks

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@editorialbot check references

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@editorialbot recommend-accept

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Attempting dry run of processing paper acceptance...

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

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1037/h0046049 is OK
- 10.1080/00223980.1946.9917275 is OK
- 10.1093/comnet/cnx044 is OK
- 10.1093/comnet/cny015 is OK
- 10.1016/0378-8733(95)00259-6 is OK
- 10.1016/j.socnet.2018.07.007 is OK
- 10.1145/1526709.1526808 is OK
- 10.1145/1526709.1526809 is OK
- 10.1016/j.socnet.2014.03.005 is OK
- 10.1016/j.socnet.2004.08.007 is OK
- 10.1007/BF02289026 is OK
- 10.1080/0022250X.2019.1711376 is OK
- 10.1371/journal.pone.0244363 is OK
- 10.48550/arXiv.2209.00676 is OK
- 10.1016/j.dam.2019.04.019 is OK
- 10.48550/arXiv.2205.13411 is OK
- 10.1038/s41598-020-58471-z is OK
- 10.1371/journal.pone.0269137 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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

OK DOIs

- 10.18637/jss.v024.i06 is OK
- 10.1037/h0046049 is OK
- 10.1080/00223980.1946.9917275 is OK
- 10.1093/comnet/cnx044 is OK
- 10.1093/comnet/cny015 is OK
- 10.1016/0378-8733(95)00259-6 is OK
- 10.1016/j.socnet.2018.07.007 is OK
- 10.1145/1526709.1526808 is OK
- 10.1145/1526709.1526809 is OK
- 10.1016/j.socnet.2014.03.005 is OK
- 10.1016/j.socnet.2004.08.007 is OK
- 10.1007/BF02289026 is OK
- 10.1080/0022250X.2019.1711376 is OK
- 10.1371/journal.pone.0244363 is OK
- 10.48550/arXiv.2209.00676 is OK
- 10.1016/j.dam.2019.04.019 is OK
- 10.48550/arXiv.2205.13411 is OK
- 10.1038/s41598-020-58471-z is OK
- 10.1371/journal.pone.0269137 is OK

MISSING DOIs

- None

INVALID DOIs

- None

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@editorialbot accept

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

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👋 @openjournals/sbcs-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#3905, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

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🐦🐦🐦 👉 Tweet for this paper 👈 🐦🐦🐦

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🐘🐘🐘 👉 Toot for this paper 👈 🐘🐘🐘

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

Here's what you must now do:

  1. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.04987 joss-papers#3906
  2. Wait a couple of minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.04987
  3. If everything looks good, then close this review issue.
  4. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? Notify your editorial technical team...

@editorialbot editorialbot added accepted published Papers published in JOSS labels Jan 27, 2023
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oliviaguest commented Jan 27, 2023

@schochastics and @sbenthall, sorry for being delayed, I am ill. Congratulations! 🥳

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🎉🎉🎉 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:
[![DOI](https://joss.theoj.org/papers/10.21105/joss.04987/status.svg)](https://doi.org/10.21105/joss.04987)

HTML:
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  <img src="https://joss.theoj.org/papers/10.21105/joss.04987/status.svg" alt="DOI badge" >
</a>

reStructuredText:
.. image:: https://joss.theoj.org/papers/10.21105/joss.04987/status.svg
   :target: https://doi.org/10.21105/joss.04987

This is how it will look in your documentation:

DOI

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