Here are some general principles that have proven helpful for developing models.
A model should be contained in a folder named with lower-case letters and
underscores, such as
thunder_cats. Within that directory:
README.mddescribes the model, how to use it, and any other details. Github will automatically show this file to anyone visiting the directory.
model.pyshould contain the model class. If the file gets large, it may make sense to move the complex bits into other files, but this is the first place readers will look to figure out how the model works.
server.pyshould contain the visualization support, including the server class.
run.pyis a Python script that will run the model when invoked via
After the number of files grows beyond a half-dozen, try to use sub-folders to
organize them. For example, if the visualization uses image files, put those in
The Schelling model is a good example of a small well-packaged model.
It’s easy to create a cookiecutter mesa model by running
If your model involves some random choice, you can use the built-in
property that Mesa
Agent objects have. This works exactly
like the built-in
class AwesomeModel(Model): # ... def cool_method(self): interesting_number = self.random.random() print(interesting_number) class AwesomeAgent(Agent): # ... def __init__(self, unique_id, model, ...): super().__init__(unique_id, model) # ... def my_method(self): random_number = self.random.randint(0, 100)
(The agent’s random property is just a reference to its parent model’s
When a model object is created, its random property is automatically seeded
with the current time. The seed determines the sequence of random numbers; if
you instantiate a model with the same seed, you will get the same results.
To allow you to set the seed, make sure your model as a
seed argument in its
class AwesomeModel(Model): def __init__(self, seed=None): pass def cool_method(self): interesting_number = self.random.random() print(interesting_number) >>> model0 = AwesomeModel(seed=0) >>> model0._seed 0 >>> model0.cool_method() 0.8444218515250481 >>> model1 = AwesomeModel(seed=0) >>> model1.cool_method() 0.8444218515250481