[REVIEW]: powerbox: A Python package for creating structured fields with isotropic power spectra

whedon commented 6 years ago

Submitting author: @steven-murray (Steven Murray) Repository: https://github.com/steven-murray/powerbox Version: v0.5.5 Editor: @arfon Reviewer: @dfm Archive: 10.5281/zenodo.1400822

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General checks

[x] Repository: Is the source code for this software available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
[x] Version: Does the release version given match the GitHub release (v0.5.5)?
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Functionality

[x] Installation: Does installation proceed as outlined in the documentation?
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[x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
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[x] Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
[x] Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
[x] Automated tests: Are there automated tests or manual steps described so that the function of the software can be verified?
[x] 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

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whedon commented 6 years ago

Hello human, I'm @whedon. I'm here to help you with some common editorial tasks. @dfm it looks like you're currently assigned as the reviewer for this paper :tada:.

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whedon commented 6 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 6 years ago

--> Check article proof :page_facing_up: <--

steven-murray commented 6 years ago

@whedon generate pdf

whedon commented 6 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 6 years ago

--> Check article proof :page_facing_up: <--

dfm commented 6 years ago

I'm starting to go through this and here are a few comments as I go:

The travis build is currently failing with some sort of coverage bug.
I think that the quickstart tutorial could have a few more words about the details of what is meant by "power spectrum" (e.g. units, normalization, etc.) and what the properties are required by the function provided to the PowerBox class.
The powerbox version in the quickstart tutorial is not the same as the one that it is documenting (v0.5.4 vs 0.5.5).
The arguments to create_discrete_sample are not all documented. (I was not clear on what min_at_zero meant until I looked at the source)
I think that it would also be useful to have a discussion of the specific numerical method (perhaps in the context of the relevant literature) somewhere in the docs. For example, how does this method compare to a Gaussian Process method that wouldn't require discretization for sampling. This might also lead to a useful discussion of how to choose N for specific use cases.
The docs need a discussion of the dependencies and how to contribute.

dfm commented 6 years ago

Also:

a few of the references in the paper are missing DOIs

steven-murray commented 6 years ago

The travis build is currently failing with some sort of coverage bug.

This is fixed by https://github.com/steven-murray/powerbox/commit/59980d84365099fab31e56238dfeb4ec7d3c2cfc

steven-murray commented 6 years ago

The powerbox version in the quickstart tutorial is not the same as the one that it is documenting (v0.5.4 vs 0.5.5).

Fixed in https://github.com/steven-murray/powerbox/commit/50efcded235e8d046c4ef28447e41019b017b307

steven-murray commented 6 years ago

The arguments to create_discrete_sample are not all documented. (I was not clear on what min_at_zero meant until I looked at the source)

Fixed in https://github.com/steven-murray/powerbox/commit/4e7cdcb7bb36b9be4149adf9bcd4bda0a1ea4751

steven-murray commented 6 years ago

The docs need a discussion of the dependencies and how to contribute.

Added some of these in https://github.com/steven-murray/powerbox/commit/e49a26037b69c9c29f4d1006be68fe06d8a36c3f. Please let me know if they are not adequate.

steven-murray commented 6 years ago

I think that the quickstart tutorial could have a few more words about the details of what is meant by "power spectrum" (e.g. units, normalization, etc.) and what the properties are required by the function provided to the PowerBox class.

I've had a go of this in https://github.com/steven-murray/powerbox/commit/04e6a6de0f0c969e933affe1402b9a9ec45a833c.

The discussion is in the quickstart tutorial introduction. Please let me know if this is not quite what you were thinking and can be improved.

steven-murray commented 6 years ago

a few of the references in the paper are missing DOIs

I have added DOIs to Coles 1991 and Peacock 1999 (cf https://github.com/steven-murray/powerbox/commit/086cb71443cdcfbb0ce6f08a6ac08df72898c49a). The book "Statistical Fluid Mechanics" by Monin and Yaglom does not seem to have a DOI. The article by Wolz2018 does not yet have a DOI as it is not yet accepted.

steven-murray commented 6 years ago

I think that it would also be useful to have a discussion of the specific numerical method (perhaps in the context of the relevant literature) somewhere in the docs. For example, how does this method compare to a Gaussian Process method that wouldn't require discretization for sampling. This might also lead to a useful discussion of how to choose N for specific use cases.

In https://github.com/steven-murray/powerbox/commit/6078a428012ac6e8e496d8c77dae5baf680464f9 I have added a new example notebook discussing the algorithm in a little more depth. I am not quite sure how to relate this method to Gaussian Processes, so I have left this out for now. I have commented that no information on the power is available for scales less than L/N, and given a rule-of-thumb for choosing N.

Thank you for all your comments so far. I hope I have addressed them reasonably!

dfm commented 6 years ago

Good stuff! I'm happy with these changes and everything looks good to me now. @arfon: I'm happy to recommend this for acceptance. @steven-murray: congrats on the excellent software and documentation!

arfon commented 6 years ago

@arfon: I'm happy to recommend this for acceptance.

:zap: thanks @dfm.

@steven-murray - At this point could you make an archive of the reviewed software in Zenodo/figshare/other service and update this thread with the DOI of the archive? I can then move forward with accepting the submission.

steven-murray commented 6 years ago

@dfm : Thanks for the smooth and thorough review process! @arfon : Thanks, the DOI is 10.5281/zenodo.1400822 .

I will definitely be publishing with JOSS again!

arfon commented 6 years ago

@whedon set 10.5281/zenodo.1400822 as archive

whedon commented 6 years ago

OK. 10.5281/zenodo.1400822 is the archive.

arfon commented 6 years ago

@dfm - many thanks for your review here ✨

@steven-murray - your paper is now accepted into JOSS and your DOI is https://doi.org/10.21105/joss.00850 :zap: :rocket: :boom:

whedon commented 6 years ago

:tada::tada::tada: Congratulations on your paper acceptance! :tada::tada::tada:

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