[REVIEW]: PyNM: a Lightweight Python implementation of Normative Modeling

[editorialbot]

Submitting author: @harveyaa (Annabelle Harvey) Repository: https://github.com/ppsp-team/PyNM Branch with paper.md (empty if default branch): joss_submission Version: 1.0.0b1 Editor: @dfm Reviewers: @smkia, @saigerutherford Archive: Pending

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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) 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

@smkia & @saigerutherford, 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 @dfm 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 @smkia

📝 Checklist for @saigerutherford

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.88  T=0.11 s (191.3 files/s, 125593.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                           9            334            720           1544
Jupyter Notebook                 7              0          10636            534
Markdown                         3             80              0            306
TeX                              1             11              0            240
YAML                             2              1              7             29
-------------------------------------------------------------------------------
SUM:                            22            426          11363           2653
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 863

[editorialbot]

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

OK DOIs

- 10.1038/s41380-019-0441-1 is OK
- 10.1016/j.biopsych.2015.12.023 is OK
- 10.1371/journal.pcbi.1009477 is OK
- 10.1371/journal.pone.0252108 is OK
- 10.1101/2021.08.08.455583 is OK
- 10.3389/fnins.2018.00662 is OK
- 10.3389/fpsyt.2019.00011 is OK
- 10.1038/s42003-020-01212-9 is OK

MISSING DOIs

- None

INVALID DOIs

- https://doi.org/10.1016/j.neuroimage.2021.118715 is INVALID because of 'https://doi.org/' prefix

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[dfm]

@harveyaa, @smkia, @saigerutherford — This is the review thread for the paper. All of our communications will happen here from now on. Thanks again for agreeing to participate!

Please read the "Reviewer instructions & questions" in the first comment above, and generate your checklists by commenting @editorialbot generate my checklist on this issue ASAP. As you go over the submission, please check any items that you feel have been satisfied. There are also 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 openjournals/joss-reviews#4321 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 the review process to be completed within about 4-6 weeks but please try to make a start ahead of this as JOSS reviews are by their nature iterative and any early feedback you may be able to provide to the author will be very helpful in meeting this schedule.

[dfm]

@harveyaa — Can you take a look at fixing the DOI issue mentioned above by the bot?

[smkia]

Review checklist for @smkia

Conflict of interest

• [x] 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

• [x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• [x] Repository: Is the source code for this software available at the https://github.com/ppsp-team/PyNM?
• [x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• [x] Contribution and authorship: Has the submitting author (@harveyaa) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• [x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

• [x] Installation: Does installation proceed as outlined in the documentation?
• [x] Functionality: Have the functional claims of the software been confirmed?
• [x] 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

• [x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• [x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• [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 functionality 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

• [x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• [x] 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 and who the target audience is?
• [x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
• [x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• [x] 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?

[harveyaa]

Hi,

I made a couple changes to the joss_submission branch to fix an import error a colleague caught - hopefully this doesn't confuse the review process too much - should I update pypi with the change or leave it in github for now?

Thank you,

Annabelle

[dfm]

@harveyaa — Sorry for the delayed response! We generally suggest minting a new release at the end of the review process, but you're also welcome to release new versions throughout the process and it shouldn't cause any problems.

[saigerutherford]

Review checklist for @saigerutherford

Conflict of interest

• [x] 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

• [x] I confirm that I read and will adhere to the JOSS code of conduct.

General checks

• [x] Repository: Is the source code for this software available at the https://github.com/ppsp-team/PyNM?
• [x] License: Does the repository contain a plain-text LICENSE file with the contents of an OSI approved software license?
• [x] Contribution and authorship: Has the submitting author (@harveyaa) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• [x] Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines

Functionality

• [x] Installation: Does installation proceed as outlined in the documentation?
• [x] Functionality: Have the functional claims of the software been confirmed?
• [x] 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

• [x] A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
• [x] Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
• [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 functionality 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

• [x] Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
• [x] 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 and who the target audience is?
• [x] State of the field: Do the authors describe how this software compares to other commonly-used packages?
• [x] Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
• [x] 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?

[dfm]

@smkia, @saigerutherford — This is just a little ping to make sure that this review stays on your radar. It's good to start chipping away at the checklists sooner rather than later!

[smkia]

Checking the functionality of the package, I am trying to run the first tutorial at https://github.com/ppsp-team/PyNM/blob/master/tutorials/1-getting_started.ipynb in Google Colab (see https://colab.research.google.com/drive/1LNEIT2T2omOr3iKa4qqUPz9VlwaxeuNG?usp=sharing). I receive the following error:

ModuleNotFoundError                       Traceback (most recent call last)
[<ipython-input-2-1a8dca4f882a>](https://localhost:8080/#) in <module>()
      1 import pandas as pd
      2 import numpy as np
----> 3 from pynm.pynm import PyNM
      4 import matplotlib.pyplot as plt
      5 import seaborn as sns

[/usr/local/lib/python3.7/dist-packages/pynm/pynm.py](https://localhost:8080/#) in <module>()
     36 
     37 from pynm.util import *
---> 38 from pynm.models.loess import *
     39 from pynm.models.centiles import *
     40 

ModuleNotFoundError: No module named 'pynm.models'

I suspect to the version difference between the package and the code in the tutorial. Would you please hint at that?

[dfm]

@smkia: Can you open this issue over on https://github.com/ppsp-team/PyNM/issues, referencing this thread instead? That tends to be a better workflow than putting issues in this thread. Thanks!

[deep-introspection]

Dear @smkia, it should be okay now.

[dfm]

@smkia, @saigerutherford — Just checking in here to see how your reviews are going and to keep this on your radar. Let me know if you have any questions or sticking points. Thanks!

(@smkia I see your most recent issue - thanks!)

[saigerutherford]

@dfm my sincere apologies for being so behind schedule with this review. Attending the first in-person conference of my Ph.D. plus a second round of being sick with COVID really put my schedule off track. Completing this review is my top priority this week!

[dfm]

@saigerutherford — thanks for the update and no stress - we all appreciate the time that you're able to volunteer! Let me know if there's anything comes up or if you have any questions!

[dfm]

@harveyaa — It looks like @saigerutherford and @smkia have a couple of open issues on the https://github.com/ppsp-team/PyNM repo. Can you update on your status tackling these issues? Thanks!!

[harveyaa]

Hi @dfm, I'm very sorry for the delay. I responded to all but one of the issues, which is only waiting on a pypi update and will be done shortly. Thank you for your patience and time!!

[dfm]

@smkia, @saigerutherford — Can I get you to check in on your checklists again and @harveyaa's responses to the issues you raised? Thanks!!

[saigerutherford]

Hi @dfm, I have reviewed @harveyaa's responses to my issues and feel that all of my concerns were properly addressed. I finished the review checklist and have no outstanding comments at this time. I am happy to support this work being published.

[dfm]

@smkia — Can you take a look at your remaining checklist items? It looks like we're just about there!

[smkia]

Dear @dfm, the package passes all my tests and I have no further concerns regarding the functionality of the implemented modules. I think this is a useful resource for new users of NM and, therefore, I support this work being published.

[dfm]

Awesome!! Thanks @smkia and @saigerutherford for your constructive reviews! I really appreciate all the time that you volunteered to this process.

@harveyaa — I have a couple of final edits to do then I'll have some quick tasks for you before we publish. I'm totally swamped today, but I'll get to this before the end of the week. Thanks for your patience!

[harveyaa]

Thank you so much @smkia and @saigerutherford! The reviews were very helpful and I'm extremely grateful for your time.

@dfm Thank you! Please take your time, I have limited internet access/time for the next two weeks so I might not be able to get to the tasks promptly.

[dfm]

@editorialbot generate pdf

[dfm]

@editorialbot check references

[editorialbot]

Couldn't check the bibtex because branch name is incorrect: joss_submission

[editorialbot]

:warning: An error happened when generating the pdf.