Mesa-Geo 0.3.0

GIS extension for the Mesa agent-based modeling framework in Python

Mesa-Geo: a GIS extension for the Mesa agent-based modeling framework in Python

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.

Installation

To install Mesa-Geo on linux or macOS run

pip install mesa-geo

On windows you should first use Anaconda to install some of the requirements with

conda install fiona pyproj rtree shapely
pip install mesa-geo

Since Mesa-Geo is in early development you could also install the latest version directly from Github via

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

Getting started

You should be familiar with how Mesa works.

So let's get started with some geometries! We will work with records of US states. We use the requests library to retrieve the data, but of course you can work with local data.

from mesa_geo import GeoSpace, GeoAgent, AgentCreator
from mesa import Model
import requests
url = 'http://eric.clst.org/assets/wiki/uploads/Stuff/gz_2010_us_040_00_20m.json'
r = requests.get(url)
geojson_states = r.json()

First we create a State Agent and a GeoModel. Both should look familiar if you have worked with mesa before.

class State(GeoAgent):
    def __init__(self, unique_id, model, geometry, crs):
        super().__init__(unique_id, model, geometry, crs)

class GeoModel(Model):
    def __init__(self):
        self.space = GeoSpace()
        
        ac = AgentCreator(agent_class=State, model=self)
        agents = ac.from_GeoJSON(GeoJSON=geojson_states, unique_id="NAME")
        self.space.add_agents(agents)

In the GeoModel we first create an instance of AgentCreator, where we provide the Agent class (State) and its required arguments, except geometry and unique_id. We then use the .from_GeoJSON function to create our agents from the geometries in the GeoJSON file. We provide the feature "name" as the key from which the agents get their unique_ids. Finally, we add the agents to the GeoSpace

Let's instantiate our model and look at one of the agents:

m = GeoModel()

agent = m.space.agents[0]
print(agent.unique_id)
agent.geometry

If you work in the Jupyter Notebook your output should give you the name of the state and a visual representation of the geometry.

Arizona

By default the AgentCreator also sets further agent attributes from the Feature properties.

agent.CENSUSAREA

113594.084

Let's start to do some spatial analysis. We can use usual Mesa function names to get neighboring states

neighbors = m.space.get_neighbors(agent)
print([a.unique_id for a in neighbors])

California
Colorado
New Mexico
Utah
Nevada

To get a list of all states within a certain distance you can use the following

[a.unique_id for a in m.space.get_neighbors_within_distance(agent, 600000)]

['California',
'Colorado',
'New Mexico',
'Oklahoma',
'Wyoming',
'Idaho',
'Utah',
'Nevada']

The unit for the distance depends on the coordinate reference system (CRS) of the GeoSpace. Since we did not specify the CRS, Mesa-Geo defaults to the 'Web Mercator' projection (in meters). If you want to do some serious measurements you should always set an appropriate CRS, since the accuracy of Web Mercator declines with distance from the equator. We can achieve this by initializing the AgentCreator and the GeoSpace with the crs keyword crs="epsg:2163". Mesa-Geo then transforms all coordinates from the GeoJSON geographic coordinates into the set crs.

Going further

To get a deeper understanding of Mesa-Geo you should check out the GeoSchelling example. It implements a Leaflet visualization which is similar to use as the CanvasGridVisualization of Mesa.

To add further functionality, I need feedback on which functionality is desired by users. Please post a message at Mesa-Geo discussions or open an issue if you have any ideas or recommendations.

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.