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[REVIEW]: giotto-deep: A Python Package for Topological Deep Learning #4846

Closed editorialbot closed 1 year ago

editorialbot commented 1 year ago

Submitting author: !--author-handle-->@matteocao<!--end-author-handle-- (Matteo Caorsi) Repository: https://github.com/giotto-ai/giotto-deep Branch with paper.md (empty if default branch): paper Version: v0.0.3 Editor: !--editor-->@osorensen<!--end-editor-- Reviewers: @EduPH, @leotrs, @ismailguzel Archive: 10.5281/zenodo.7243721

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Markdown: [![status](https://joss.theoj.org/papers/f1f94829081bb7f0f16c48cafe1524d7/status.svg)](https://joss.theoj.org/papers/f1f94829081bb7f0f16c48cafe1524d7)

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

@EduPH & @leotrs & @ismailguzel, 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:

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The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @osorensen 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 @EduPH

📝 Checklist for @leotrs

📝 Checklist for @ismailguzel

editorialbot commented 1 year ago

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
editorialbot commented 1 year ago
Software report:

github.com/AlDanial/cloc v 1.88  T=0.01 s (201.3 files/s, 13287.6 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Markdown                         1             15              0             77
TeX                              1              9              0             74
YAML                             1              1              4             18
-------------------------------------------------------------------------------
SUM:                             3             25              4            169
-------------------------------------------------------------------------------

gitinspector failed to run statistical information for the repository
editorialbot commented 1 year ago

Wordcount for paper.md is 663

editorialbot commented 1 year ago

Failed to discover a valid open source license

editorialbot commented 1 year ago

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

editorialbot commented 1 year ago
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- None

MISSING DOIs

- 10.1017/9781316671665.004 may be a valid DOI for title: Topological data analysis
- 10.1145/1873951.1874254 may be a valid DOI for title: Torchvision the machine-vision package of torch
- 10.3389/frai.2021.681108 may be a valid DOI for title: A survey of topological machine learning methods

INVALID DOIs

- None
leotrs commented 1 year ago

Review checklist for @leotrs

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

EduPH commented 1 year ago

Review checklist for @EduPH

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

leotrs commented 1 year ago

Hello @matteocao! The paper has three authors and I see that all three are contributors to the repository. However, there are two contributors that i) are not authors, and ii) have contributed more than one contributor who is an author (at least by GitHub's measures here)

Could you please clarify how authorship was determined for your JOSS submission?

matteocao commented 1 year ago

Dear @leotrs , Thank you for your question. Of the two contributors (that are not authors) you mention, one has joined the efforts very recently and hence has not (yet) contributed to any design/core functionality of the library. The other one, on the other hand, after the initial contributions (1y ago) has completely gone silent and still today we are not able to reach him. This is why we did not include him. Let me know if this answer is satisfactory enough and/or if you have any suggestion on how to best proceed.

To further clarify: @giotto-learn and @matteocao are the same physical person.

leotrs commented 1 year ago

Thanks for the clarification. I think the current author list makes sense. Do consider to add the names of other/past contributors in the acknowledgements section of the paper.

ismailguzel commented 1 year ago

Review checklist for @ismailguzel

Conflict of interest

Code of Conduct

General checks

Functionality

Documentation

Software paper

leotrs commented 1 year ago

@matteocao I can see your CI runs pytest on the root directory but wasn't able to find a directory containing a test suite. Could you please point me to it? Thanks!

leotrs commented 1 year ago

@matteocao I see no mention of related/similar software in the current paper. Are there absolutely no other options for using topological techniques in deep learning?

matteocao commented 1 year ago

Dear @leotrs , Thank you for your message.

@matteocao I can see your CI runs pytest on the root directory but wasn't able to find a directory containing a test suite. Could you please point me to it? Thanks!

The unit tests are written per module, meaning that there is a folder called tests in each module folder. Here some examples:

The integration tests (or maybe even callable e2e tests) are the notebookes themselves: all of those in here

We find this way of organising tests reasonable (as opposed to putting all tests in one single folder). Please let us know if this feels reasonable for you as well.

@matteocao I see no mention of related/similar software in the current paper. Are there absolutely no other options for using topological techniques in deep learning?

There are indeed no package that try to do what we do. I would like however to mention the only possibly similar one, though much more limited in scope: https://github.com/MathieuCarriere/perslay. This packages implements one single technique that is topology-flavoured for feed-forward deep networks. Important note: even though we understood the paper (and we did cite such paper) and later were able to reproduce its content, we have not been able to use ay part of this "PersLay" package due to the total lack of documentation and structure. Please feel free to advise on what's the best course of action. Thank you!

leotrs commented 1 year ago

Both responses sound reasonable to me. Thanks.

leotrs commented 1 year ago

I have finished my review and I believe the paper can be accepted as is.

osorensen commented 1 year ago

Thanks a lot for your time and efforts, @leotrs

EduPH commented 1 year ago

Congratulations @matteocao, it is a nice library for the TDA community. I think the paper can be accepted. Just a remark, it would be nice to mention in the paper that previously, people have used TDA libraries such as Gudhi together with deep learning libraries such as scikit-learn, TensorFlow or PyTorch.

ismailguzel commented 1 year ago

I tested the package installation on both Windows and Ubuntu. Good for both platforms, actually. I'm grateful for @matteocao . I also didn't see anything different from what other reviewers had already noted. Finally, my review is completed, and I think the document can be accepted just as it is. It will be a great package for TDA folks.

osorensen commented 1 year ago

Wow! Thanks to all of @EduPH, @leotrs, @ismailguzel for completing your reviews so quickly!

@matteocao, I will now read through the paper a final time, and let you know if I have any suggested changes. In the meantime, could you please

osorensen commented 1 year ago

@editorialbot generate pdf

osorensen commented 1 year ago

@editorialbot check references

editorialbot commented 1 year ago

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

editorialbot commented 1 year ago
Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- None

MISSING DOIs

- 10.1017/9781316671665.004 may be a valid DOI for title: Topological data analysis
- 10.1145/1873951.1874254 may be a valid DOI for title: Torchvision the machine-vision package of torch
- 10.3389/frai.2021.681108 may be a valid DOI for title: A survey of topological machine learning methods

INVALID DOIs

- None
matteocao commented 1 year ago

Dear @osorensen ,

Thank you for your message. Here the data you asked for:

osorensen commented 1 year ago

Thanks @matteocao

A few comments on the manuscript

Please let me know when this is done, and I can move forward with accepting the publication.

matteocao commented 1 year ago

Dear @osorensen ,

Thank you for your message and for your suggestions. All the changes have been made and the pdf compilation worked. Please let me know if there is anything else I need to do.

Thank you!

osorensen commented 1 year ago

@editorialbot generate pdf

osorensen commented 1 year ago

@editorialbot set v0.0.3 as archive

editorialbot commented 1 year ago

Done! Archive is now v0.0.3

editorialbot commented 1 year ago

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

osorensen commented 1 year ago

@editorialbot set 10.5281/zenodo.7243721 as archive

editorialbot commented 1 year ago

Done! Archive is now 10.5281/zenodo.7243721

osorensen commented 1 year ago

@editorialbot set v0.0.3 as version

editorialbot commented 1 year ago

Done! version is now v0.0.3

osorensen commented 1 year ago

@editorialbot set v0.0.3 as version

editorialbot commented 1 year ago

Done! version is now v0.0.3

osorensen commented 1 year ago

@editorialbot set 10.5281/zenodo.7243721 as archive

editorialbot commented 1 year ago

Done! Archive is now 10.5281/zenodo.7243721

osorensen commented 1 year ago

Sorry for all the posts, I mixed up the commands a bit :-)

osorensen commented 1 year ago

@editorialbot recommend-accept

editorialbot commented 1 year ago
Attempting dry run of processing paper acceptance...
editorialbot commented 1 year ago

:wave: @openjournals/dsais-eics, this paper is ready to be accepted and published.

Check final proof :point_right::page_facing_up: Download article

If the paper PDF and the deposit XML files look good in https://github.com/openjournals/joss-papers/pull/3640, then you can now move forward with accepting the submission by compiling again with the command @editorialbot accept

arfon commented 1 year ago

@editorialbot accept

editorialbot commented 1 year ago
Doing it live! Attempting automated processing of paper acceptance...
editorialbot commented 1 year ago

🐦🐦🐦 👉 Tweet for this paper 👈 🐦🐦🐦

editorialbot commented 1 year ago

🚨🚨🚨 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 :point_right: https://github.com/openjournals/joss-papers/pull/3689
  2. Wait a couple of minutes, then verify that the paper DOI resolves https://doi.org/10.21105/joss.04846
  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...

arfon commented 1 year ago

@EduPH, @leotrs, @ismailguzel – many thanks for your reviews here and to @osorensen for editing this submission! JOSS relies upon the volunteer effort of people like you and we simply wouldn't be able to do this without you ✨

@matteocao – your paper is now accepted and published in JOSS :zap::rocket::boom:

editorialbot commented 1 year ago

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