[REVIEW]: HRDS: A Python package for hierarchical raster datasets

[whedon]

Submitting author: @jhill1 (Jon Hill)
Repository: https://github.com/EnvModellingGroup/hdrs
Version: 0.1.2
Editor: @kthyng
Reviewer: @edoddridge, @PythonCHB
Archive: 10.5281/zenodo.2691685

Status

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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) 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.)

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✨ Please try and complete your review in the next two weeks ✨

Review checklist for @edoddridge

Conflict of interest

• As the reviewer I confirm that I have read the JOSS conflict of interest policy and that there are no conflicts of interest for me to review this work.

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 repository url?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Version: 0.1.2
• Authorship: Has the submitting author (@jhill1) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?

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 function 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

• Authors: Does the paper.md file include a list of authors with their affiliations?
• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

Review checklist for @PythonCHB

Conflict of interest

• As the reviewer I confirm that I have read the JOSS conflict of interest policy and that there are no conflicts of interest for me to review this work.

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 repository url?
• License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• Version: 0.1.2
• Authorship: Has the submitting author (@jhill1) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?

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 function 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

• Authors: Does the paper.md file include a list of authors with their affiliations?
• A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

[whedon]

Hello human, I'm @whedon, a robot that can help you with some common editorial tasks. @edoddridge, it looks like you're currently assigned as the reviewer for this paper 🎉.

⭐ Important ⭐

If you haven't already, you should seriously consider unsubscribing from GitHub notifications for this (https://github.com/openjournals/joss-reviews) repository. As a reviewer, you're probably currently watching this repository which means for GitHub's default behaviour you will receive notifications (emails) for all reviews 😿

To fix this do the following two things:

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

@whedon commands

[whedon]

Attempting PDF compilation. Reticulating splines etc...

[whedon]

👉 Check article proof 📄 👈

[kthyng]

@ChrisBarker-NOAA Just a quick reminder to please do your JOSS review this week. Thanks!

[edoddridge]

I'm happy to say that I've finished my review of HRDS and can recommend it for publication. 👍

It is a well-written piece of code that solves a clearly stated problem. 'HRDS' provides a clean interface to mesh together multiple files with different resolutions and create manageable input files for variable resolution geophysical modelling.

While I've opened a number of issues in the code repository, they are all quite minor, and none of them should prevent publication of the paper. With perhaps one exception - it would be a shame to publish the paper before the typos are fixed.

I had very little difficulty obtaining a working version of the code. The dependencies were clearly identified. I encountered only one problem, and the documentation has now been updated to guide users around that issue. The test suite worked straight out of the box.

My only disappointment regarding the testing is the lack of a code coverage tool. The .travis.yml file contains some commented out lines for using coveralls to assess code coverage. I would recommend (re)implementing a code coverage tool.

The python code is laid out in a clear and logical way. I found it quite easy to work out what each piece of code does.

My biggest concern with this submission is the lack of a real-life worked example. However, @jhill1 has obtained the necessary data and has committed to implementing one soon. Once the data is included, the test suite could be altered to use those datasets instead of the proprietary ones that @jhill1 uses locally.

The overarching documentation is currently limited to the readme. However, given the nature of the software, this is perfectly acceptable. API documentation is contained in docstrings for the various methods and classes. Having extensive docstrings means that Sphinx based documentation could be added in the future without too much extra effort.

[jhill1]

@whedon generate pdf

[whedon]

Attempting PDF compilation. Reticulating splines etc...

[whedon]

👉 Check article proof 📄 👈

[kthyng]

@ChrisBarker-NOAA Will you be able to complete this JOSS review this week?

[kthyng]

Gah I forgot that you aren't working because of the government shutdown. Hm.

[PythonCHB]

Review of the HRDS software package:

https://github.com/EnvModellingGroup/hrds

Overall, this looks like a small, but useful package for raster data processing. But there are some issues with the package structure, tests, and documentation, outlines below.

I recommend that the package be published once the below issues are addressed.

Installation, etc:

Platform support:

From the README:

"These instructions assume a Debian-based Linux. HDRS should work on other
systems, but is currently untested."

There are a lot of users out there that are not running Debian-based Linux -- this project should attempt to provide some guidance for other platforms. UNfotunately, the GDAL stack is pretty ugly to install, so perhaps recommending conda and conda-forge would be a good way to get people rolling in a platform independent way.

I notice that conda is (partially) being used for the CI -- so could full conda instuctions could be provided.

I am testing on OS-X with conda and conda-forge, Python 3.7

In fact, I highly recommend that the project authors make hrds available in conda-forge: https://conda-forge.org/#add_recipe

Documentation and Examples:

In the main README, after providing Debian-only install instructions, the primary example is using the firedrake and thetis packages -- nifty use-case, but it would be much better, for a more general purpose package to have the primary examples be based only of the core package and its dependencies.

Install

The hrds package is using a standard setuptools / setup.py install. However, there are some issues:

The tests are put in a package that is next to the hrds package, and the setup.py uses setuptools.find_packages to to identify the packages to install. So when run, you get a top-level package called "tests" with the hrds tests in it. This is not good.

Here are some thoughts on where to put tests:

http://pythonchb.github.io/PythonTopics/where_to_put_tests.html

I've provided a PR here that puts the tests internal to the package:

EnvModellingGroup/hrds#18

I also added formatting, etc changes to the setup.py in that PR.

tests:

• The way the test files were found was fragile -- so would only run if the current working dir was the parent of the tests dir:

EnvModellingGroup/hrds#21

• There is a duplicate test name in: test_hrds.py -- those are skipped anyway due to lack of GEBCO data, but that should be fixed! Issue here:

EnvModellingGroup/hrds#20

PR for fixes to the file finding, and PEP8 compliance fixes is here:

EnvModellingGroup/hrds#24

temp files.

The HRDS class appears to be creating temp buffer files that it does not delete:

EnvModellingGroup/hrds#23

NOTE: computer memory is pretty huge these days -- are the buffer files even needed -- maybe only used when the rasters are really big?

JOSS paper

The JOSS paper is fine as it goes, but there are a few issues:

• There are a few references cited, but nothing in the references section -- are those defined somewhere else?

• "a linear distance buffer is created to smoothly blend the two datasets together."

  I would like to see some description (and ideally a reference) for this algorithm.

• The docs do note that two rasters "are unlikely to
  agree on the topographic/bathymetric height where they overlap", but there is no mention of (or algorithms for?) accounting for major differences -- different vertical datums, for instance.

Documentation

The only user docs I could find is the README and docstrings. Some more comprehensive user and reference docs would be good. Also, the docstrings are not complete nor PEP 257 compliant.

[kthyng]

Great! Thanks so much for the reviews, @edoddridge and @PythonCHB.

It looks like there are some unchecked check boxes for both reviews currently, and @jhill1 can work on addressing issues that have been brought up. Thanks again everyone.

[kthyng]

Just a note that I will have an away message popping up starting tomorrow and I will continue to respond here while I can; once I can't and if this review is still on-going, then another editor will take over.

[jhill1]

Thanks both for the reviews (especially whilst furloughed @PythonCHB - much appreciated).

[lheagy]

👋 Hi @jhill1, @edoddridge, @PythonCHB: just a quick note to say that I am happy to answer any questions or help out on the editor side while @kthyng is away.

[ooo]

👋 Hey @lheagy...

Letting you know, @kthyng is currently OOO until Sunday, March 31st 2019. ❤️

[arfon]

@jhill1 - I think we're waiting on your responses to @PythonCHB's review at this point.

[kthyng]

Great!

[kthyng]

@whedon set 10.5281/zenodo.2691685 as archive

[whedon]

OK. 10.5281/zenodo.2691685 is the archive.

[kthyng]

@whedon set <v0.1.2> as version

[whedon]

OK. <v0.1.2> is the version.

[kthyng]

@whedon set 0.1.2 as version

[whedon]

OK. 0.1.2 is the version.

[kthyng]

Ok @openjournals/joss-eics this submission is ready to be officially accepted!!! Congrats @jhill1!!

[PythonCHB]

Not really a big deal: but if you are publishing this, maybe it's time for version 1.0?

If it's not really ready for 1.0, it's not ready for publication, either.

[labarba]

@jhill1 — would you like to up you version number? We don't require it: it's up to you.

[jhill1]

Leave for now, please. @PythonCHB is right that it should have been made v1.0, but I've already pushed pip and conda updates with 0.12 and referred to the version being the one published. I'd rather keep a cleaner history.

[labarba]

@PythonCHB — you have the "References" item unchecked. Did you find something missing there?

[labarba]

@whedon check references

[whedon]

Attempting to check references...

[whedon]

OK DOIs

- 10.1016/j.renene.2017.09.058 is OK
- 10.1016/j.renene.2014.11.079 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[labarba]

@whedon accept

[whedon]

Attempting dry run of processing paper acceptance...

[whedon]

OK DOIs

- 10.1016/j.renene.2017.09.058 is OK
- 10.1016/j.renene.2014.11.079 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[whedon]

Check final proof 👉 openjournals/joss-papers#689

If the paper PDF and Crossref deposit XML look good in openjournals/joss-papers#689, then you can now move forward with accepting the submission by compiling again with the flag deposit=true e.g.

@whedon accept deposit=true

[labarba]

@whedon accept deposit=true

[whedon]

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

[whedon]

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

Here's what you must now do:

0. Check final PDF and Crossref metadata that was deposited 👉 Creating pull request for 10.21105.joss.01112 joss-papers#690
1. Wait a couple of minutes to verify that the paper DOI resolves https://doi.org/10.21105/joss.01112
2. If everything looks good, then close this review issue.
3. Party like you just published a paper! 🎉🌈🦄💃👻🤘

Any issues? notify your editorial technical team...

[labarba]

Congratulations, @jhill1, your JOSS paper is published 🚀

Sincere thanks to our editor: @kthyng, and the reviewers: @edoddridge, @PythonCHB — we appreciate your enormous contribution! 🙏

[whedon]

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

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