Standard CMA

import numpy
from deap_er import Fitness, Toolbox, creator, tools

tools.rng.seed(1234)  # disables randomization


def setup():
    creator.create_type("FitnessMin", Fitness, weights=(-1.0,))
    creator.create_type("Individual", list, fitness=creator.FitnessMin)
    strategy = tools.Strategy(centroid=[5.0] * 30, sigma=5.0, offsprings=600, survivors=30)
    toolbox = Toolbox()
    toolbox.register("evaluate", tools.bm_rastrigin)
    toolbox.register("generate", strategy.generate, creator.Individual)
    toolbox.register("update", strategy.update)

    stats = tools.Statistics(lambda ind: ind.fitness.values)
    stats.register("avg", numpy.mean)
    stats.register("std", numpy.std)
    stats.register("min", numpy.min)
    stats.register("max", numpy.max)

    return toolbox, stats


def print_results(best_ind):
    if best_ind.fitness.values >= (20,):
        raise RuntimeError("Evolution failed to converge.")
    print("\nEvolution converged correctly.")


def main():
    toolbox, stats = setup()
    hof = tools.HallOfFame(1)
    args = {
        "toolbox": toolbox,
        "generations": 250,
        "hof": hof,
        "stats": stats,
        "verbose": True,  # prints stats
    }
    tools.ea_generate_update(**args)
    print_results(hof[0])


if __name__ == "__main__":
    main()