def setUp1(self, nproc=1):
self.set_up_system()
self.nreplicas = 10
self.stepsize = 0.01
self.nproc = nproc
self.database = self.system.create_database("lj13.db")
self.minima = self.database.minima()
assert self.database.number_of_minima(
) > 1, "%d minima" % self.database.number_of_minima()
self.mc_runner = self.system.get_mc_walker(mciter=100)
self.ns = NestedSamplingSA(self.system,
self.nreplicas,
self.mc_runner,
minima=self.minima,
minprob=0.9,
energy_offset=100.,
stepsize=0.1,
nproc=nproc,
verbose=False)
self.Emax0 = self.ns.replicas[-1].energy
self.niter = 100
for i in xrange(self.niter):
self.ns.one_iteration()
self.Emax = self.ns.replicas[-1].energy
self.Emin = self.ns.replicas[0].energy
def setUp1(self, nproc=4):
self.set_up_system()
self.nreplicas = 50
self.stepsize = 0.01
self.nproc = nproc
self.database = self.system.create_database("lj13.db")
self.minima = self.database.minima()
self.mc_runner = self.system.get_mc_walker(mciter=10000)
self.ns = NestedSamplingSA(self.system, self.nreplicas, self.mc_runner,
minima=self.minima, minprob=0.1,
stepsize=0.1, nproc=nproc, verbose=True,
iprint=100)
self.Emax0 = self.ns.replicas[-1].energy
max_iter = 10000
self.Etol = .01
for i in xrange(max_iter):
self.ns.one_iteration()
deltaE = self.ns.replicas[-1].energy - self.ns.replicas[0].energy
if deltaE < self.Etol:
break
self.niter = i + 1
self.Emax = self.ns.replicas[-1].energy
self.Emin = self.ns.replicas[0].energy
