def setUp(self):
self.D = 20
self.x, self.task = rnd.uniform(-100, 100,
self.D), Task(self.D, 230, inf,
MyBenchmark())
self.s1, self.s2, self.s3 = Individual(x=self.x, e=False), Individual(
task=self.task, rand=rnd), Individual(task=self.task)
def setUp(self):
self.D = 20
rng = default_rng()
self.x, self.task = default_rng().uniform(
-100, 100, self.D), StoppingTask(D=self.D,
nFES=230,
nGEN=np.inf,
benchmark=MyBenchmark())
self.s1, self.s2, self.s3 = Individual(x=self.x, e=False), Individual(
task=self.task, rng=rng), Individual(task=self.task)
def runTask(self, task): pop = [Individual(task=task, e=True, rand=self.Rand) for _i in range(self.Np)] ib = argmin([x.f for x in pop]) x_b, x_bf = pop[ib].x, pop[ib].f while not task.stopCondI(): npop = [Individual(x=self.CrossMutt(pop, i, x_b, self.F, self.CR, rnd=self.Rand), task=task, e=True, rand=self.Rand) for i in range(self.Np)] pop = [np if np.f < pop[i].f else pop[i] for i, np in enumerate(npop)] ib = argmin([x.f for x in pop]) if x_bf > pop[ib].f: x_b, x_bf = pop[ib].x, pop[ib].f return x_b, x_bf
def runTask(self, task): """Run.""" pop = [Individual(task=task) for _i in range(self.Np)] pop = [self.evalPopulation(pop[i], pop[i], task) for i in range(self.Np)] x_b = pop[argmin([x.f for x in pop])] while not task.stopCond(): npop = [Individual(x=self.CrossMutt(pop, i, x_b, self.F, self.CR, self.Rand)) for i in range(self.Np)] pop = [self.evalPopulation(npop[i], pop[i], task) for i in range(self.Np)] ix_b = argmin([x.f for x in pop]) if x_b.f > pop[ix_b].f: x_b = pop[ix_b] return x_b.x, x_b.f
def runTask(self, task): Gr = task.nFES // (self.pmax * self.Np) + self.rp pop = [Individual(task=task, rand=self.Rand, e=True) for _i in range(self.Np)] x_b = pop[argmin([x.f for x in pop])] while not task.stopCondI(): npop = [Individual(x=self.CrossMutt(pop, i, x_b, self.F, self.CR, self.Rand), task=task, rand=self.Rand, e=True) for i in range(len(pop))] pop = [np if np.f < pop[i].f else pop[i] for i, np in enumerate(npop)] ix_b = argmin([x.f for x in pop]) if x_b.f > pop[ix_b].f: x_b = pop[ix_b] if task.Iters == Gr and len(pop) > 3: NP = int(len(pop) / 2) pop = [pop[i] if pop[i].f < pop[i + NP].f else pop[i + NP] for i in range(NP)] Gr += task.nFES // (self.pmax * NP) + self.rp return x_b.x, x_b.f
def test_init_population_individual_fine(self): r"""Test if custome generation initialization works ok.""" a = Algorithm(NP=10, InitPopFunc=init_pop_individual, itype=Individual) t = Task(D=20, benchmark=MyBenchmark()) i = Individual(x=full(t.D, 0.0), task=t) pop, fpop, d = a.initPopulation(t) for e in pop: self.assertEqual(i, e)
def evolve(self, pop, x_b, task): npop, x_bc = list(), pop[argmin([x.f for x in pop])] for i in range(self.NP): ind = Individual(x=self.Selection(pop, i, self.Ts, x_bc, self.Rand), e=False) ind.x = self.Crossover(pop, i, self.Cr, self.Rand) ind.x = self.Mutation(pop, i, self.Mr, task, self.Rand) ind.evaluate(task) npop.append(ind) if x_b.f > ind.f: x_b = ind return npop, x_b
def runTask(self, task): Gr = task.nFES // (self.pmax * self.Np) + self.rp pop = [Individual(task=task, e=True, rand=self.Rand) for _i in range(self.Np)] ib = argmin([x.f for x in pop]) x_b, x_bf = pop[ib].x, pop[ib].f while not task.stopCondI(): npop = [self.multiMutations(pop, i, x_b, task) for i in range(len(pop))] pop = [np if np.f < pop[i].f else pop[i] for i, np in enumerate(npop)] ib = argmin([x.f for x in pop]) if x_bf > pop[ib].f: x_b, x_bf = pop[ib].x, pop[ib].f if task.Iters == Gr and len(pop) > 3: NP = int(len(pop) / 2) pop = [pop[i] if pop[i].f < pop[i + NP].f else pop[i + NP] for i in range(NP)] Gr += task.nFES // (self.pmax * NP) + self.rp return x_b, x_bf
def test_eq_fine(self):
self.assertFalse(self.s1 == self.s2)
self.assertTrue(self.s1 == self.s1)
s = Individual(x=self.s1.x)
self.assertTrue(s == self.s1)
def test_repair_fine(self):
s = Individual(x=full(self.D, 100))
self.assertFalse(self.task.isFeasible(s.x))
s.repair(self.task)
self.assertTrue(self.task.isFeasible(s.x))
def setUp(self):
self.D = 20
self.x, self.task = rnd.uniform(-100, 100, self.D), StoppingTask(
D=self.D, nFES=230, nGEN=inf, benchmark=MyBenchmark())
self.s1, self.s2, self.s3 = Individual(x=self.x, e=False), Individual(
task=self.task, rand=rnd), Individual(task=self.task)
def runTask(self, task): pop = [Individual(task=task, rand=self.Rand) for _i in range(self.NP)] x_b = pop[argmin([c.f for c in pop])] while not task.stopCond(): pop, x_b = self.evolve(pop, x_b, task) return x_b.x, x_b.f
def multiMutations(self, pop, i, x_b, task): L = [Individual(x=strategy(pop, i, x_b, self.F, self.CR, rnd=self.Rand), task=task, e=True, rand=self.Rand) for strategy in self.strategys] return L[argmin([x.f for x in L])]