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egtplot

egtplot: A Python Package for Three-Strategy Evolutionary Games - Published in JOSS (2018)

https://github.com/mirzaevinom/egtplot

Science Score: 93.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 5 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: biorxiv.org, joss.theoj.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

dynamical-systems evolutionary-game-theory game-theory visualization

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 6 months ago · JSON representation

Repository

egtplot: A python package for 3-Strategy Evolutionary Games

Basic Info
  • Host: GitHub
  • Owner: mirzaevinom
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 24 MB
Statistics
  • Stars: 50
  • Watchers: 3
  • Forks: 6
  • Open Issues: 0
  • Releases: 0
Topics
dynamical-systems evolutionary-game-theory game-theory visualization
Created almost 8 years ago · Last pushed 9 months ago
Metadata Files
Readme License

readme.md

egtplot: A Python Package for Three-Strategy Evolutionary Games

DOI PyPi Downloads

This is a software package for plotting and animating three-strategy evolutionary games on a triangular simplex. * The package can be used to create phase portraits of 3-strategy games

  • It can also be used to animate transient behavior of the game

Use Cases

While there are many use cases for this software, our group's particular focus is on the mathematical modeling of cancer and cancer therapies through evolutionary game theory [@kaznatcheev2017cancer, @kaznatcheev2015edge, @Kaznatcheev179259]. For details on analytical treatments of evolutionary games, please see Artem Kaznatcheev's blog at Theory, Evolution, and Games Group.

Authorship

Inom Mirzaev and Drew FK Williamson contributed equally to this work.

Dependencies

The program is written and tested on Python >=3.5. This software package depends on the following libraries:

  • numpy>=1.13, scipy, shapely for computations
  • matplotlib for static plots
  • imageio, moviepy for animations
  • tqdm for progress bar

Installing the package from PyPi will take care of all the dependencies pip install egtplot

Installation

  • Easiest way to install the package is through PyPi pip install egtplot

  • You can clone this repository using git software and run setup. git clone https://github.com/mirzaevinom/egtplot.git cd egtplot python setup.py install

  • Alternatively you can download and extract a zip file of this repo: cd egtplot-master python setup.py install

  • Finally, we also have created a Docker container for running a jupyter notebook with egtplot: drewfkw/egtplot

Specific Usage

  • This software has two main functions: plot_static for plotting static simplex figures and plot_animated for generating simplex animations.
  • For detailed usage of these functions we refer to our interactive jupyter notebook: egtplot_demonstration.ipynb
  • We also welcome comments and questions regarding our whitepaper on bioRxiv which describes the package and its usage. The content is nearly identical to the jupyter notebook linked above.

Citation

If you use this program to do research that leads to publication, we ask that you acknowledge use of this program by citing the following in your publication:

Mirzaev I., Williamson D. and Scott J., egtplot: A Python Package for 3-Strategy Evolutionary Games, https://doi.org/10.1101/300004

Acknowledgements

  • The authors would like to thank Mathematical Biosciences Institue (MBI) at Ohio State University, for partially supporting this research. MBI receives its funding through the National Science Foundation grant DMS 1440386.
  • We gratefully acknowledge the work of Hanna Schenk whose code on her github inspired this project.

Contributing and Issues

Please use GitHub Issues for issue tracking and bugs. Feel free to contact Drew and Inom if you would like to contribute to egtplot or with questions and comments.

Owner

  • Name: Inom Mirzaev
  • Login: mirzaevinom
  • Kind: user
  • Location: San Francisco, CA
  • Company: Twitter Inc

Machine Learning Engineer

JOSS Publication

egtplot: A Python Package for Three-Strategy Evolutionary Games
Published
June 17, 2018
DOI
Volume 3, Issue 26, Page 735
Authors
Inom Mirzaev ORCID
Mathematical Biosciences Institute, The Ohio State University, Department of Translational Hematology and Oncology Research, Cleveland Clinic Foundation
Drew Fk Williamson ORCID
Department of Translational Hematology and Oncology Research, Cleveland Clinic Foundation
Jacob G. Scott ORCID
Department of Translational Hematology and Oncology Research, Cleveland Clinic Foundation, Department of Radiation Oncology, Cleveland Clinic Foundation
Editor
Arfon Smith ORCID
Tags
python evolutionary game theory visualization
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GitHub Events

Total
  • Issue comment event: 1
  • Pull request event: 2
  • Fork event: 1
Last Year
  • Issue comment event: 1
  • Pull request event: 2
  • Fork event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 54
  • Total Committers: 3
  • Avg Commits per committer: 18.0
  • Development Distribution Score (DDS): 0.278
Past Year
  • Commits: 1
  • Committers: 1
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
DFKW d****n@g****m 39
mirzaevinom m****m@g****m 14
Rowan 7****e 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 1
  • Average time to close issues: 19 days
  • Average time to close pull requests: 6 days
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 2.5
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jmbr (1)
  • Fil (1)
Pull Request Authors
  • rbarkerclarke (2)
Top Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 16 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 9
  • Total maintainers: 1
pypi.org: egtplot

a package for plotting 3-strategy evolutionary game solutions

  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 16 Last month
Rankings
Dependent packages count: 10.0%
Stargazers count: 10.0%
Forks count: 14.2%
Average: 16.2%
Dependent repos count: 21.7%
Downloads: 25.3%
Maintainers (1)
drew-williamson
Last synced: 6 months ago

Dependencies

setup.py pypi
  • imageio *
  • matplotlib *
  • moviepy *
  • requests *
  • scipy *
  • shapely *
  • tqdm *
docker_build/Dockerfile docker
  • jupyter/base-notebook latest build