[PRE REVIEW]: PyOTC: A Python Package for Optimal Transition Coupling

[editorialbot]

Submitting author: @austinyi (Bongsoo Yi)
Repository: https://github.com/pyotc/pyotc
Branch with paper.md (empty if default branch):
Version: v0.3.1
Editor: Pending
Reviewers: Pending
Managing EiC: Chris Vernon

Status

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

✅ OK DOIs

- 10.48550/arXiv.2503.15830 is OK
- 10.48550/arXiv.1803.00567 is OK
- 10.5281/zenodo.15773589 is OK

🟡 SKIP DOIs

- No DOI given, and none found for title: Optimal Transport for Stationary Markov Chains via...
- No DOI given, and none found for title: Distances for Markov chains, and their differentia...
- No DOI given, and none found for title: POT: Python Optimal Transport
- No DOI given, and none found for title: Scikit-learn: Machine Learning in Python
- No DOI given, and none found for title: austinyi/NetOTC
- No DOI given, and none found for title: oconnor-kevin/OTC
- No DOI given, and none found for title: YusuLab/ot_markov_distances
- No DOI given, and none found for title: SergioCalo/SVI
- No DOI given, and none found for title: pytest 8.3
- No DOI given, and none found for title: Optimal graph joining with applications to isomorp...
- No DOI given, and none found for title: Introduction to entropic optimal transport

❌ MISSING DOIs

- 10.1093/jrsssb/qkae085 may be a valid DOI for title: Alignment and comparison of directed networks via ...
- 10.52202/079017-4269 may be a valid DOI for title: Bisimulation metrics are optimal transport distanc...
- 10.25080/tcwv9851 may be a valid DOI for title: Exploring network structure, dynamics, and functio...

❌ INVALID DOIs

- None

[editorialbot]

Repository Analysis Report

Code breakdown

github.com/AlDanial/cloc v 1.98  T=0.06 s (1243.4 files/s, 391787.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
JSON                             2              0              0          18164
Python                          30            412            653           1134
Markdown                        12            151              6            401
Jupyter Notebook                 5              0           1734            353
TeX                              1             17              0            161
reStructuredText                18            111            176            134
YAML                             3             27             24            111
TOML                             2             10              0             98
DOS Batch                        1              8              1             27
make                             1              6              9             18
INI                              1              0              0              2
-------------------------------------------------------------------------------
SUM:                            76            742           2603          20603
-------------------------------------------------------------------------------

Commit Count by Author

36	Bongsoo Yi
    33	Jay Hineman
     7	icyyyyy730

Repository History

Repository age: First commit on February 27, 2024

Code distribution (top 3 48-hour windows):

Period	Insertions	% of Total	Signal	View Changes
Aug 27, 2025 - Aug 29, 2025	19196	32.8%	🟡	View diff
Aug 05, 2025 - Aug 07, 2025	18205	31.1%	🟡	View commit
Jan 02, 2025 - Jan 04, 2025	1859	3.2%	🟢	View diff

GitHub Activity Metrics

Metric	Count
GitHub stars	3
Forks	0
GitHub contributors	4
Releases	6
Total issues	51
Total pull requests	50
Unique commenters/reviewers (excluding authors)	3

[editorialbot]

Paper file info:

📄 Wordcount for paper.md is 1256

✅ The paper includes a Statement of need section

🔴 Failed to discover a State of the field section in paper

🔴 Failed to discover a Software design section in paper

🔴 Failed to discover a Research impact statement section in paper

🔴 Failed to discover an AI usage disclosure section in paper

[editorialbot]

License info:

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

[editorialbot]

⚠️ An error happened when generating the pdf.