ecspy 0.6

Evolutionary Computations in Python

ECsPy (Evolutionary Computations in Python) is a free, open source framework for creating evolutionary computations in Python. Additionally, ECsPy provides an easy-to-use canonical genetic algorithm (GA), evolution strategy (ES), estimation of distribution algorithm (EDA), differential evolution algorithm (DEA), and particle swarm optimizer (PSO) for users who don’t need much customization. Please see the full documentation for more information.

Usage Example

from random import Random
from time import time
from ecspy import ec
from ecspy import terminators
from ecspy import observers


def generate_binary(random, args):
    bits = args.get('num_bits', 8)
    return [random.choice([0, 1]) for i in xrange(bits)]

def evaluate_binary(candidates, args):
    fitness = []
    base = args.get('base', 2)
    for cand in candidates:
        num = 0
        exp = len(cand) - 1
        for c in cand:
            num += c * (base ** exp)
            exp -= 1
        fitness.append(num)
    return fitness

rand = Random()
rand.seed(int(time()))
ga = ec.GA(rand)
ga.observer = observers.screen_observer
ga.terminator = terminators.evaluation_termination
final_population = ga.evolve(evaluator=evaluate_binary,
                             generator=generate_binary,
                             max_evaluations=1000,
                             num_elites=1,
                             pop_size=100,
                             num_bits=10)
for individual in final_population:
    print(individual)