def __call__(self):
t0 = time.time()
args = self.args
names_bounds = yield self.ev.setup().addErrback(oops)
self.p = Population(self.evaluate,
names_bounds[0],
names_bounds[1],
popsize=args.p)
yield self.p.setup().addErrback(oops)
reporter = Reporter(self.ev, self.p)
self.p.addCallback(reporter)
F = [float(x) for x in args.F.split(',')]
de = DifferentialEvolution(self.p,
CR=args.C,
F=F,
maxiter=args.m,
randomBase=not args.b,
uniform=args.u,
adaptive=not args.n,
bitterEnd=args.e,
logHandle=self.fh)
yield de()
yield self.shutdown()
msg(0, "Final population:\n{}", self.p)
msg(0, "Elapsed time: {:.2f} seconds", time.time() - t0, 0)
msg(None)
reactor.stop()
def setUp(self):
abort.restart()
from asynqueue.util import DeferredTracker
self.dt = DeferredTracker()
self.p = Population(self.fifthSecond, ["x"], [(-5, 5)])
self.de = de.DifferentialEvolution(self.p, maxiter=35)
self.de.fm = de.FManager(0.5, 0.5, self.p.Np, True)
return self.p.setup()
def makeDE(
self, Np, Nd,
slow=False, blank=False, randomBase=False, callback=None):
def slowAckley(X):
delay = np.random.sample()
return self.deferToDelay(delay).addCallback(lambda _: tb.ackley(X))
self.p = Population(
slowAckley if slow else tb.ackley,
[sub("x{:d}", k) for k in range(Nd)],
[(-5, 5)]*Nd, popsize=Np/Nd)
if callback: self.p.addCallback(callback)
self.de = de.DifferentialEvolution(
self.p, maxiter=35, randomBase=randomBase)
yield self.p.setup(blank=blank)
tb.evals_reset()