GithubHelp home page GithubHelp logo

jeremander / mesa Goto Github PK

View Code? Open in Web Editor NEW

This project forked from projectmesa/mesa

0.0 0.0 0.0 10.13 MB

Mesa is an agent-based modeling framework in Python

License: Other

Shell 0.04% JavaScript 17.87% Python 79.91% CSS 0.13% HTML 1.53% Dockerfile 0.53%

mesa's Introduction

Mesa: Agent-based modeling in Python 3+

image

image

image

Mesa allows users to quickly create agent-based models using built-in core components (such as spatial grids and agent schedulers) or customized implementations; visualize them using a browser-based interface; and analyze their results using Python's data analysis tools. Its goal is to be the Python 3-based alternative to NetLogo, Repast, or MASON.

A screenshot of the Schelling Model in Mesa

Above: A Mesa implementation of the Schelling segregation model, being visualized in a browser window and analyzed in a Jupyter notebook.

Features

  • Modular components
  • Browser-based visualization
  • Built-in tools for analysis
  • Example model library

Using Mesa

Getting started quickly:

pip install mesa

You can also use pip to install the github version:

pip install -U -e git+https://github.com/projectmesa/mesa@main#egg=mesa

Or any other (development) branch on this repo or your own fork:

pip install -U -e git+https://github.com/YOUR_FORK/mesa@YOUR_BRANCH#egg=mesa

For resources or help on using Mesa, check out the following:

  • Intro to Mesa Tutorial (An introductory model, the Boltzmann Wealth Model, for beginners or those new to Mesa.)
  • Complexity Explorer Tutorial (An advanced-beginner model, SugarScape with Traders, with instructional videos)
  • Mesa Examples (A repository of seminal ABMs using Mesa and examples of employing specific Mesa Features)
  • Docs (Mesa's documentation, API and useful snippets)
  • Discussions (GitHub threaded discussions about Mesa)
  • Matrix Chat (Chat Forum via Matrix to talk about Mesa)

Running Mesa in Docker

You can run Mesa in a Docker container in a few ways.

If you are a Mesa developer, first install Docker Compose and then, in the folder containing the Mesa Git repository, you run:

$ docker compose up
# If you want to make it run in the background, you instead run
$ docker compose up -d

This runs the wolf-sheep predation model, as an example.

With the docker-compose.yml file in this Git repository, the docker compose up command does two important things:

  • It mounts the mesa root directory (relative to the docker-compose.yml file) into /opt/mesa and runs pip install -e on that directory so your changes to mesa should be reflected in the running container.
  • It binds the docker container's port 8521 to your host system's port 8521 so you can interact with the running model as usual by visiting localhost:8521 on your browser

If you are a model developer that wants to run Mesa on a model, you need to:

  • make sure that your model folder is inside the folder containing the docker-compose.yml file
  • change the MODEL_DIR variable in docker-compose.yml to point to the path of your model
  • make sure that the model folder contains a run.py file

Then, you just need to run docker compose up -d to make it accessible from localhost:8521.

Contributing to Mesa

Want to join the Mesa team or just curious about what is happening with Mesa? You can...

  • Join our Matrix chat room in which questions, issues, and ideas can be (informally) discussed.
  • Come to a monthly dev session (you can find dev session times, agendas and notes on Mesa discussions).
  • Just check out the code on GitHub.

If you run into an issue, please file a ticket for us to discuss. If possible, follow up with a pull request.

If you would like to add a feature, please reach out via ticket or join a dev session (see Mesa discussions). A feature is most likely to be added if you build it!

Don't forget to checkout the Contributors guide.

Citing Mesa

To cite Mesa in your publication, you can use the CITATION.bib.

mesa's People

Contributors

jackiekazil avatar dmasad avatar rht avatar corvince avatar tpike3 avatar tortar avatar taylormutch avatar ewouth avatar cauemello avatar djmitche avatar reblochonmasque avatar lowcloudnine avatar sebastianof avatar drewrey avatar jamesarruda avatar jiffyclub avatar njvrzm avatar gcallah avatar joedight avatar ihopethiswillfi avatar pre-commit-ci[bot] avatar smacleod avatar deepsource-autofix[bot] avatar jess010 avatar chendaniely avatar devforfu avatar dependabot[bot] avatar yannickjadoul avatar holzhauer avatar dcunning11235 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.