f76b988862e07b4dcfae78ff8fa98e2e77fc7f1d,examples/nd_example.py,,main,#,51

Before Change

def main():
    pop_size = 100
    loop = toolz.iterate(toolz.compose(algorithm.evolve, update_fitness), MyNDTree.create_population(pop_size))
    populations = list(toolz.take(10, loop))
    best = selBest(populations[-1], 1)[0]
    print(best)


if __name__ == "__main__":

After Change

    mutate = partial(nd_mutation, mut1d=mutuniform(pset=pset))
    mate = partial(nd_crossover, cx1d=cxonepoint())

    algorithm = AgeFitness(mate, mutate, selNSGA2, MyNDTree.create_population)

    pop = update_fitness(MyNDTree.create_population(pop_size))

    for gen in range(20):
        pop = algorithm.evolve(pop)
        pop = update_fitness(pop)
        best = selBest(pop, 1)[0]
        print(best, best.fitness.values)


if __name__ == "__main__":

Instances