projectmesa_mesa-geo
Science Score: 54.0%
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Found 3 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (16.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: BigBuildBench
- License: apache-2.0
- Language: Python
- Default Branch: master
- Size: 81.1 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Mesa-Geo: GIS Extension for Mesa Agent-Based Modeling
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Mesa-Geo implements a GeoSpace that can host GIS-based GeoAgents, which are like normal Agents, except they have a geometry attribute that is a Shapely object and a crs attribute for its Coordinate Reference System. You can use Shapely directly to create arbitrary geometries, but in most cases you will want to import your geometries from a file. Mesa-Geo allows you to create GeoAgents from any vector data file (e.g. shapefiles), valid GeoJSON objects or a GeoPandas GeoDataFrame.
Using Mesa-Geo
To install Mesa-Geo, run:
bash
pip install -U mesa-geo
Mesa-Geo pre-releases can be installed with:
bash
pip install -U --pre mesa-geo
You can also use pip to install the GitHub version:
bash
pip install -U -e git+https://github.com/projectmesa/mesa-geo.git#egg=mesa-geo
Or any other (development) branch on this repo or your own fork:
bash
pip install -U -e git+https://github.com/YOUR_FORK/mesa-geo@YOUR_BRANCH#egg=mesa-geo
Take a look at the examples repository for sample models demonstrating Mesa-Geo features.
For more help on using Mesa-Geo, check out the following resources:
Contributing to Mesa-Geo
Want to join the team or just curious about what is happening with Mesa & Mesa-Geo? 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 at Mesa discussions.
- Just check out the code at 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 check out the Contributors guide.
Citing Mesa-Geo
To cite Mesa-Geo in your publication, you can use the CITATION.bib.
Owner
- Name: BigBuildBench
- Login: BigBuildBench
- Kind: organization
- Repositories: 1
- Profile: https://github.com/BigBuildBench
abbr. B3, benchmarking the repo-level understanding capability of your LLMs by reconstructing project build-file.
Citation (CITATION.bib)
@inproceedings{wang_mesa-geo_2022,
author = {Wang, Boyu and Hess, Vincent and Crooks, Andrew},
title = {Mesa-Geo: A GIS Extension for the Mesa Agent-Based Modeling Framework in Python},
year = {2022},
isbn = {9781450395373},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3557989.3566157},
doi = {10.1145/3557989.3566157},
abstract = {Mesa is an open-source agent-based modeling (ABM) framework implemented in the Python programming language, allowing users to build and visualize agent-based models. It has been used in a diverse range of application areas over the years ranging from biology to workforce dynamics. However, there has been no direct support for integrating geographical data from geographical information systems (GIS) into models created with Mesa. Users have had to rely on their own implementations to meet such needs. In this paper we present Mesa-Geo, a GIS extension for Mesa, which allows users to import, manipulate, visualise and export geographical data for ABM. We introduce the main components and functionalities of Mesa-Geo, followed by example applications utilizing geographical data which demonstrates Mesa-Geo's core functionalities and features common to agent-based models. Finally, we conclude with a discussion and outlook on future directions for Mesa-Geo.},
booktitle = {Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoSpatial Simulation},
pages = {1–10},
numpages = {10},
keywords = {agent-based modeling (ABM), geographic information systems (GIS), complex systems, Python},
location = {Seattle, Washington},
series = {GeoSim '22}
}
GitHub Events
Total
- Pull request event: 2
- Create event: 5
Last Year
- Pull request event: 2
- Create event: 5
Dependencies
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- actions/setup-python v5 composite
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