Skip to main content

Particle Swarm Optimisation implementation.

Project description

PyShoal is an implementation of <Particle Swarm Optimisation> in Python.

Typical usage:

#!/usr/bin/env python
from pso import PSO

def rastrigin(a,b):
    return 0- (10 * 2 + \
           (a**2 - (10 * np.cos(2 * np.pi * a))) + \
           (b**2 - (10 * np.cos(2 * np.pi * b))))

obj_func = rastrigin
o = PSO(obj_func = obj_func,
        init_var_ranges = ((-500,500),(-500,500)),
        n_parts = 144,
        topo="gbest",
        weights=[0.9, 0.4, 1.0, 2.5])
res = o.opt(max_itr = 100,
            tol_thres = (0.01,0.01),
            tol_win = 5,
            plot = True,
            save_plots=False)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PyShoal-0.1.0.tar.gz (18.3 kB view details)

Uploaded Source

File details

Details for the file PyShoal-0.1.0.tar.gz.

File metadata

  • Download URL: PyShoal-0.1.0.tar.gz
  • Upload date:
  • Size: 18.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for PyShoal-0.1.0.tar.gz
Algorithm Hash digest
SHA256 f9a8a084dd11d87e4eb60fa15691aa1e2333079f746b71444782cbad5f8d3b8c
MD5 ea42045134df6e229fe9c43bb5d6f71d
BLAKE2b-256 81c7f052d735534d0c1902e8366ccbf83f7ea181f82ac32b4c987d752c60f3b1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page