The Pyticle Swarm is a library created with Python 3.9 capable of running a particle swarm optimization for an array given a fitness function. To use it simply install anaconda ou any other software that allows the creation of a python environment and you will be able to run it.
The library has dependencies on the following packages:
- numpy
- matplotlib
- matplotlib-inline
- joblib
To create an anaconda environment run:
$ conda create -n {name_of_environment} python=3.9
To activate the anaconda environment execute:
$ conda activate {name_of_environment}
To install the library simply run:
$ pip install pyticle-swarm
To upgrade the library run:
$ pip install pyticle-swarm -U
To import the library and the PSO algorithm:
from pyticleswarm import run_pso
To try the example given in github:
$ python example.py
Pyticle Swarm was developed at GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development by:
- Bruno Veiga - btsve@isep.ipp.pt
- Ricardo Faia - rfmfa@isep.ipp.pt
- Tiago Pinto - tcp@isep.ipp.pt
- Zita Vale - zav@isep.ipp.pt
