[REVIEW]: FDApy: a Python package for functional data

[editorialbot]

Submitting author: @StevenGolovkine (Steven Golovkine)
Repository: https://github.com/StevenGolovkine/FDApy
Branch with paper.md (empty if default branch):
Version: v1.0.2
Editor: @mstimberg
Reviewers: @quantgirluk, @vnmabus
Archive: Pending

Status

Status badge code:

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Markdown: [![status](https://joss.theoj.org/papers/52409c2b91a69a153d09cb8b1a6c36e4/status.svg)](https://joss.theoj.org/papers/52409c2b91a69a153d09cb8b1a6c36e4)

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

@quantgirluk & @vnmabus, 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 @mstimberg 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 @vnmabus

📝 Checklist for @quantgirluk

[editorialbot]

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[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.19 s (567.4 files/s, 177841.0 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Python                          76           3868           7034          21263
TeX                              1             56              0            533
CSV                              3              0              0            439
YAML                             8             51             28            192
reStructuredText                17            141            220            174
TOML                             1              7              0             58
Markdown                         1             17              0             31
DOS Batch                        1              8              1             26
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                           109           4152           7290          22725
-------------------------------------------------------------------------------

Commit count by author:

  1152	StevenGolovkine
    12	Steven
     2	dependabot[bot]
     1	The Codacy Badger
     1	edwardgunning

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 680

✅ The paper includes a Statement of need section

[editorialbot]

License info:

✅ License found: MIT License (Valid open source OSI approved license)

[editorialbot]

👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

[editorialbot]

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

✅ OK DOIs

- 10.48550/arXiv.2211.02566 is OK
- 10.5281/zenodo.7117735 is OK
- 10.1007/978-0-387-98185-7 is OK
- 10.18637/jss.v094.i10 is OK
- 10.18637/jss.v093.i05 is OK
- 10.1016/0270-9139(94)90144-9 is OK
- 10.18637/jss.v035.i09 is OK
- 10.48550/arXiv.2310.07330 is OK
- 10.1017/9781108610247 is OK
- 10.48550/arXiv.2211.02566 is OK
- 10.5281/zenodo.7117735 is OK
- 10.1007/978-0-387-98185-7 is OK
- 10.18637/jss.v094.i10 is OK
- 10.18637/jss.v093.i05 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: PEP8 - Style Guide for Python Code
- No DOI given, and none found for title: Functional Data Analysis
- No DOI given, and none found for title: Inference for Functional Data with Applications
- No DOI given, and none found for title: Introduction to Functional Data Analysis
- No DOI given, and none found for title: Sparse Multivariate Functional Principal Component...
- No DOI given, and none found for title: Multivariate Functional Principal Component Analys...
- No DOI given, and none found for title: On the Use of the Gram Matrix for Multivariate Fun...
- No DOI given, and none found for title: Tslearn, A Machine Learning Toolkit for Time Serie...
- No DOI given, and none found for title: Fda: Functional Data Analysis
- No DOI given, and none found for title: Refund: Regression with Functional Data
- No DOI given, and none found for title: API Design for Machine Learning Software: Experien...
- No DOI given, and none found for title: R: A Language and Environment for Statistical Comp...
- No DOI given, and none found for title: Functional Data Analysis for Sparse Longitudinal D...
- No DOI given, and none found for title: PEP8 - Style Guide for Python Code
- No DOI given, and none found for title: Functional Data Analysis
- No DOI given, and none found for title: Inference for Functional Data with Applications
- No DOI given, and none found for title: Introduction to Functional Data Analysis
- No DOI given, and none found for title: Sparse Multivariate Functional Principal Component...
- No DOI given, and none found for title: Multivariate Functional Principal Component Analys...
- No DOI given, and none found for title: On the Use of the Gram Matrix for Multivariate Fun...
- No DOI given, and none found for title: Tslearn, A Machine Learning Toolkit for Time Serie...
- No DOI given, and none found for title: Fda: Functional Data Analysis
- No DOI given, and none found for title: Refund: Regression with Functional Data

❌ MISSING DOIs

- 10.1080/14763141.2017.1384050 may be a valid DOI for title: Bivariate Functional Principal Components Analysis...
- 10.1016/j.csda.2021.107376 may be a valid DOI for title: Clustering Multivariate Functional Data Using Unsu...
- 10.1016/j.chemolab.2015.09.018 may be a valid DOI for title: Fault Detection of Batch Processes Based on Multiv...
- 10.1109/camsap.2013.6714047 may be a valid DOI for title: Multi-Way Functional Principal Components Analysis
- 10.32614/cran.package.funfem may be a valid DOI for title: funFEM: Clustering in the Discriminative Functiona...
- 10.32614/cran.package.funlbm may be a valid DOI for title: funLBM: Model-Based Co-Clustering of Functional Da...
- 10.32614/cran.package.fdasrvf may be a valid DOI for title: Fdasrvf: Elastic Functional Data Analysis
- 10.32614/cran.package.mfpca may be a valid DOI for title: MFPCA: Multivariate Functional Principal Component...
- 10.1080/14763141.2017.1384050 may be a valid DOI for title: Bivariate Functional Principal Components Analysis...
- 10.1016/j.csda.2021.107376 may be a valid DOI for title: Clustering Multivariate Functional Data Using Unsu...
- 10.1016/j.chemolab.2015.09.018 may be a valid DOI for title: Fault Detection of Batch Processes Based on Multiv...
- 10.1109/camsap.2013.6714047 may be a valid DOI for title: Multi-Way Functional Principal Components Analysis
- 10.32614/cran.package.funfem may be a valid DOI for title: funFEM: Clustering in the Discriminative Functiona...
- 10.32614/cran.package.funlbm may be a valid DOI for title: funLBM: Model-Based Co-Clustering of Functional Da...
- 10.32614/cran.package.fdasrvf may be a valid DOI for title: Fdasrvf: Elastic Functional Data Analysis
- 10.32614/cran.package.mfpca may be a valid DOI for title: MFPCA: Multivariate Functional Principal Component...

❌ INVALID DOIs

- None

[mstimberg]

👋🏼 @StevenGolovkine, @quantgirluk, @vnmabus this is the review thread for the paper. All of our communications will happen here from now on.

As a reviewer, the first step is to create a checklist for your review by entering

@editorialbot generate my checklist

at the top of a new comment in this thread.

There are additional guidelines and links in the message at the start of this issue. Note that we usually ask reviewers to complete a first review within 4–6 weeks, but of course we know that this might not be feasible when end-of-year holidays get into the way. I will have limited availability from Dec 23–Jan 1st, myself.

Please feel free to ping me (@mstimberg) if you have any questions/concerns. Looking forward to working with you all!

[mstimberg]

@StevenGolovkine no rush, but please have a look at the editorialbot comments about DOIs above and add them to your bibliography list where appropriate.

[vnmabus]

Review checklist for @vnmabus

Conflict of interest

• 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

• 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 https://github.com/StevenGolovkine/FDApy?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@StevenGolovkine) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

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 functionality 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

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

[StevenGolovkine]

@StevenGolovkine no rush, but please have a look at the editorialbot comments about DOIs above and add them to your bibliography list where appropriate.

Hello, DOIs have been added.

[quantgirluk]

Review checklist for @quantgirluk

Conflict of interest

• 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

• 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 https://github.com/StevenGolovkine/FDApy?
• License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
• Contribution and authorship: Has the submitting author (@StevenGolovkine) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
• Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
• Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
• Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
• Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

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 functionality 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

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