Implementing your own optimizer

PySwarms aims to be the go-to library for various PSO implementations, so if you are a researcher in swarm intelligence or a developer who wants to contribute, then read on this guide!

As a preliminary, here is a checklist whenever you will implement an optimizer:

  • Propose an optimizer
  • Write optimizer by inheriting from base classes
  • Write a unit test

Proposing an optimizer

We wanted to make sure that PySwarms is highly-usable, and thus it is important that optimizers included in this library are either (1) classic textbook-PSO techniques or (2) highly-cited, published, optimization algorithms.

In case you wanted to include your optimization algorithm in this library, please raise an issue and add a short abstract on what your optimizer does. A link to a published paper (it’s okay if it’s behind a paywall) would be really helpful!

Inheriting from base classes

Most optimizers in this library inherit its attributes and methods from a set of built-in base classes. You can check the existing classes in pyswarms.base.

For example, if we take the pyswarms.base.base_single class, a base-class for standard single-objective continuous optimization algorithms such as global-best PSO (pyswarms.single.global_best) and local-best PSO (pyswarms.single.local_best), we can see that it inherits a set of methods as seen below:

Inheritance from base class

The required methods can be seen in the base classes, and will raise a NotImplementedError if not called. Additional methods, private or not, can also be added depending on the needs of your optimizer.

A short note on keyword arguments

The role of keyword arguments, or kwargs in short, is to act as a container for all other parameters needed for the optimizer. You can define these things in your code, and create assertions to make all of them required. However, note that in some implementations, required options might include c1, c2, and w. This is the case in pyswarms.base.bases for instance.

A short note on assertions()

You might notice that in most base classes, an assertions() method is being called. This aims to check if the user-facing input are correct. Although the method is called “assertions”, please make all user-facing catches as raised Exceptions.

A short note on __init__.py

We make sure that everything can be imported when the whole pyswarms library is called. Thus, please make sure to also edit the accompanying __init__.py file in the directory you are working on.

For example, if you write your optimizer class MyOptimizer inside a file called my_optimizer.py, and you are working under the /single directory, please update the __init__.py like the following:

from .global_best import GlobalBestPSO
from .local_best import LocalBestPSO
# Add your module
from .my_optimizer import MyOptimizer

__all__ = [
    "GlobalBestPSO",
    "LocalBestPSO",
    "MyOptimizer" # Add your class
    ]

This ensures that it will be automatically initialized when the whole library is imported.

Writing unit tests

Testing is an important element of developing PySwarms, and we wanted everything to be as smooth as possible, especially when doing the build and integrating. In this case, we provide the tests module in the package. In case you add a test for your optimizer, simply name them with the same convention as in those tests.

You can perform separate checks by

$ python -m unittest tests.optimizers.<test_myoptimizer>