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
class TestSENS_LJ(_test_ns_lj.TestNS_LJ):
def setUp(self):
self.setUp1()
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 test2(self):
self.assertGreater(self.ns.count_sampled_minima, 0)
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
def setUp1(self, nproc=1):
self.set_up_system()
self.nreplicas = 10
self.stepsize = 0.01
self.nproc = nproc
try:
self.database = self.system.create_database("lj13.db", createdb=False)
except IOError:
self.database = build_database(self.system, 20, dbfname="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)
replicas = create_replicas(self.system, self.nreplicas)
self.ns = NestedSamplingSA(replicas, self.mc_runner, self.minima, self.system.k,
config_tests=self.system.get_config_tests(),
minprob=0.9, energy_offset=100.,
stepsize=0.1, nproc=nproc, verbose=False,
center_minima=True)
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
class TestSENS_LJ_Long(_test_ns_lj.TestNS_LJ):
def setUp(self):
self.setUp1()
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
def test1(self):
super(TestSENS_LJ_Long, self).test1()
self.assertTrue(self.Emin < self.gmin + 1.,
"Nested sampling did not get to the bottom of the landscape: %g != %g" % (self.gmin, self.Emin))
self.assertGreater(self.ns.count_sampled_minima, 0)
