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[PRE REVIEW]: 4DModeller: a spatio-temporal modelling package #6996
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Five most similar historical JOSS papers: nsink: An R package for flow path nitrogen removal estimation GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields WorldDynamics.jl: A Julia Package for Developing and Simulating Integrated Assessment Models parafields: A generator for distributed, stationary Gaussian processes dlmmc: Dynamical linear model regression for atmospheric time-series analysis |
👋 @Nikoleta-v3 - Here's a second submission that I wonder if you could edit? If you can take this one or the other, it would be great! |
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Potential reviewers based on topic areas (none are known to us): Fernando de Pol Mayer, James Mba Azam, Nicholas Tierney, wcjochem, adithirgis, thomaspinder, stevenpawley |
@danielskatz 👋🏻 I'm happy to review this submission 😄 Unfortunately, I can't do both at the moment. |
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Thank you for your submission and for suggesting reviewers @rwestaway. I have successfully managed to install the package and run a few examples. The package is very well documented, and the readme is very clear and well organized 😄 I am going to contact some of the authors of recent publications as well (see #6996 (comment)) to see if they can review the paper. In the meantime, could you please address some of my comments and questions? PaperThere are some minor typos in the paper:
Also in the paper, you have two references for TestsI see that you have some tests. Could you include some information on how to run the test suite? I really like your contribution guidelines; they are short and to the point. Maybe adding the test information there? or would be a bit much? Whatever you decide, it would just be useful to know how to run the tests locally since the tests run when people open pull requests. |
👋🏻 @jhollist @PieterjanRobbe @wcjochem @thomaspinder would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html The submission I'd like you to review is titled: "4DModeller: a spatio-temporal modelling package". You can find more information at the top of this Github issue 🆙 Please let me know if you're available 😄 Thank you! |
Thank you @Nikoleta-v3 for your prompt feedback. Should we make changes to the paper.md file as we go along or is that now 'frozen' until all reviewers have responded? We haven't submitted to JOSS before so are unsure of the process... PaperTypos will be corrected. The distinction is between (1) the applications/tutorials of inlabru which are only available via the GitHub repository (cited as Lindgren et al., 2024) and (2) the underlying statistics/method for which the package authors provide two references at https://inlabru-org.github.io/inlabru/authors.html#citation (Bachl et al., 2019 and Yuan et al., 2017). Does that make sense or does it need further clarification in the text? TestsI will have to consult the project team on this one. |
FYI @mnky9800n is John Aiken and that is me. so don't know why it counts me separate but it s not a big deal i guess. |
@Nikoleta-v3 I'm happy to help, but I do want to mention that I'm not an R expert. |
Either is fine! If you push to the JOSS branch, everything will be updated. To be honest, I used to wait until I found reviewers to give any feedback on the paper, but since finding reviewers can be quite challenging at times, I started giving feedback beforehand so there is not too much time wasted. This is new territory for me too, haha. I think you are fine to make the changes, at least the paper changes, and push so the reviewers will have the latest version with the corrections.
Thank you, I understand; I believe it's fine as it is!
Great; thank you. |
@PieterjanRobbe Amazing, thank you! That is fine; between myself and the second reviewer, it should be fine! |
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Five most similar historical JOSS papers: GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields WorldDynamics.jl: A Julia Package for Developing and Simulating Integrated Assessment Models nsink: An R package for flow path nitrogen removal estimation dlmmc: Dynamical linear model regression for atmospheric time-series analysis parafields: A generator for distributed, stationary Gaussian processes |
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@Nikoleta-v3 - To respond to your query, the testing suite is a relic of some old code so thank you for flagging that! At the time we had some ideas for testing meshes, and other topics, but as it stands we haven't really built it out or developed it further. However it is something planned for future work. |
Five most similar historical JOSS papers: GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields WorldDynamics.jl: A Julia Package for Developing and Simulating Integrated Assessment Models nsink: An R package for flow path nitrogen removal estimation dlmmc: Dynamical linear model regression for atmospheric time-series analysis parafields: A generator for distributed, stationary Gaussian processes |
Five most similar historical JOSS papers: GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields WorldDynamics.jl: A Julia Package for Developing and Simulating Integrated Assessment Models nsink: An R package for flow path nitrogen removal estimation dlmmc: Dynamical linear model regression for atmospheric time-series analysis parafields: A generator for distributed, stationary Gaussian processes |
@wcjochem amazing thank you! 🙏🏻 |
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OK, I've started the review over in #7047. |
Submitting author: @rwestaway (Richard Westaway)
Repository: https://github.com/4DModeller/fdmr
Branch with paper.md (empty if default branch): JOSS
Version: v0.2.0
Editor: @Nikoleta-v3
Reviewers: @PieterjanRobbe, @wcjochem
Managing EiC: Daniel S. Katz
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