[PRE REVIEW]: pykoop: a Python Library for Koopman Operator Approximation

[editorialbot]

Submitting author: !--author-handle-->@sdahdah<!--end-author-handle-- (Steven Dahdah) Repository: https://github.com/decargroup/pykoop Branch with paper.md (empty if default branch): paper Version: v2.0.1 Editor: Pending Reviewers: Pending Managing EiC: Arfon Smith

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[editorialbot]

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

✅ OK DOIs

- 10.1098/rspa.2022.0162 is OK
- 10.1088/2632-2153/ad45b0 is OK
- 10.5281/zenodo.5576490 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python
- No DOI given, and none found for title: DLKoopman: A deep learning software package for Ko...
- No DOI given, and none found for title: \textttMachine-Learning-Dynamical-Systems/kooplear...
- No DOI given, and none found for title: Forward-Backward Extended DMD with an Asymptotic S...
- No DOI given, and none found for title: Uncertainty Modelling and Robust Observer Synthesi...
- No DOI given, and none found for title: Asymptotically Stable Data-Driven Koopman Operator...

❌ MISSING DOIs

- 10.21105/joss.05881 may be a valid DOI for title: PyKoopman: A Python Package for Data-Driven Approx...

❌ INVALID DOIs

- None

[editorialbot]

Software report:

github.com/AlDanial/cloc v 1.90  T=0.12 s (563.4 files/s, 189093.9 lines/s)
--------------------------------------------------------------------------------
Language                      files          blank        comment           code
--------------------------------------------------------------------------------
Python                           34           1556           5402          11480
Jupyter Notebook                  8              0           2246            639
reStructuredText                  6            176            228            297
Markdown                          6             70              0            235
YAML                              7              1              5            159
TeX                               2             16              0            153
Bourne Again Shell                1             11             38             34
DOS Batch                         1              8              1             26
INI                               2              1              0             19
make                              1              4              7              9
--------------------------------------------------------------------------------
SUM:                             68           1843           7927          13051
--------------------------------------------------------------------------------

Commit count by author:

   622  Steven Dahdah
     1  James Forbes

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 615

✅ The paper includes a Statement of need section

[editorialbot]

License info:

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

[editorialbot]

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

[editorialbot]

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Simulation Decomposition in Python Submitting author: @tupui Handling editor: @crvernon (Active) Reviewers: @JoshuaOsborneDATA, @matt-graham Similarity score: 0.7171

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PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD) Submitting author: @mengaldo Handling editor: @eloisabentivegna (Retired) Reviewers: @albertonogueira, @joao-l-s-almeida, @jdmoorman Similarity score: 0.7094

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[arfon]

@sdahdah - thanks for your submission to JOSS. We're currently managing a large backlog of submissions and the editor most appropriate for your area is already rather busy.

For now, we will need to waitlist this paper and process it as the queue reduces. Thanks for your patience!

If you want to fix the DOIs (noting that @editorialbot's suggestions are not always right), you can, then use the following commands (one at a time, as the first line of a new comment) to regenerate the PDF and check the references.

@editorialbot generate pdf @editorialbot check references

[sdahdah]

Thank you, I will fix the DOIs in the meantime.

[sdahdah]

@editorialbot generate pdf

[editorialbot]

:warning: An error happened when generating the pdf.

[sdahdah]

@editorialbot generate pdf

[editorialbot]

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

[editorialbot]

Five most similar historical JOSS papers:

ddop: A python package for data-driven operations management Submitting author: @AndreasPhilippi Handling editor: @arfon (Active) Reviewers: @kramea, @g4brielvs Similarity score: 0.7618

dfba: Software for efficient simulation of dynamic flux-balance analysis models in Python Submitting author: @davidtourigny Handling editor: @marcosvital (Active) Reviewers: @jdbrunner, @pstjohn, @synchon Similarity score: 0.7265

Simulation Decomposition in Python Submitting author: @tupui Handling editor: @crvernon (Active) Reviewers: @JoshuaOsborneDATA, @matt-graham Similarity score: 0.7222

PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD) Submitting author: @mengaldo Handling editor: @eloisabentivegna (Retired) Reviewers: @albertonogueira, @joao-l-s-almeida, @jdmoorman Similarity score: 0.7160

giotto-deep: A Python Package for Topological Deep Learning Submitting author: @matteocao Handling editor: @osorensen (Active) Reviewers: @EduPH, @leotrs, @ismailguzel Similarity score: 0.7157

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[sdahdah]

@editorialbot check references

[editorialbot]

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

✅ OK DOIs

- 10.21105/joss.05881 is OK
- 10.1098/rspa.2022.0162 is OK
- 10.1088/2632-2153/ad45b0 is OK
- 10.48550/arXiv.2403.10623 is OK
- 10.48550/arXiv.2410.01057 is OK
- 10.48550/arXiv.2408.16846 is OK
- 10.5281/zenodo.5576490 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python
- No DOI given, and none found for title: DLKoopman: A deep learning software package for Ko...
- No DOI given, and none found for title: Machine-Learning-Dynamical-Systems/kooplearn v1.1....

❌ MISSING DOIs

- None

❌ INVALID DOIs

- None

[sdahdah]

The remaining references do not have DOIs as far as I can tell.

[danielskatz]

👋 @diehlpk - Do you think you could edit this submission?

[danielskatz]

@editorialbot invite @diehlpk as editor

[editorialbot]

Invitation to edit this submission sent!

[danielskatz]

👋 @drvinceknight - Do you think you could edit this submission?

[danielskatz]

@editorialbot invite @drvinceknight as editor

[editorialbot]

Invitation to edit this submission sent!