def main():
parser = argparse.ArgumentParser(
description=
"do nested sampling on a p[article in a n-dimensional Harmonic well")
# parser.add_argument("--db", type=str, nargs=1, help="database filename",
# default="otp.db")
parser.add_argument("-K",
"--nreplicas",
type=int,
help="number of replicas",
default=300)
parser.add_argument("-A",
"--ndof",
type=int,
help="number of degrees of freedom",
default=4)
parser.add_argument("-P",
"--nproc",
type=int,
help="number of processors",
default=1)
parser.add_argument("--trivparal",
action='store_true',
help="set whether to do trivial parallelisation",
default=False)
parser.add_argument(
"-q",
action="store_true",
help="turn off verbose printing of information at every step")
args = parser.parse_args()
system = HarParticle(args.ndof, Emax_init=1000.)
mcrunner = HarRunner(system)
# ns = NestedSamplingSerial(system, args.nreplicas, mcrunner,
# verbose=not args.q)
ns = NestedSampling(system,
args.nreplicas,
mcrunner,
nproc=args.nproc,
triv_paral=args.trivparal,
verbose=not args.q)
print "harmonic particle ndof", args.ndof
run_nested_sampling(ns, label="hparticle", etol=.00000001)
def main():
parser = argparse.ArgumentParser(description="do nested sampling on a p[article in a n-dimensional Harmonic well")
# parser.add_argument("--db", type=str, nargs=1, help="database filename",
# default="otp.db")
parser.add_argument("-K", "--nreplicas", type=int, help="number of replicas", default=300)
parser.add_argument("-A", "--ndof", type=int, help="number of degrees of freedom", default=4)
parser.add_argument("-P", "--nproc", type=int, help="number of processors", default=1)
parser.add_argument("--trivparal", action='store_true', help="set whether to do trivial parallelisation",default=False)
parser.add_argument("-q", action="store_true", help="turn off verbose printing of information at every step")
args = parser.parse_args()
system = HarParticle(args.ndof, Emax_init=1000.)
mcrunner = HarRunner(system)
# ns = NestedSamplingSerial(system, args.nreplicas, mcrunner,
# verbose=not args.q)
ns = NestedSampling(system, args.nreplicas, mcrunner, nproc=args.nproc,
triv_paral=args.trivparal, verbose=not args.q)
print "harmonic particle ndof", args.ndof
run_nested_sampling(ns, label="hparticle", etol=.00000001)
def run_nested_sampling_lj(system, nreplicas=300, mciter=1000, target_ratio=0.7, label="test",
minima=None, use_compiled=True, nproc=1,
triv_paral=True, minprob=1, maxiter=1e100, **kwargs):
takestep = RandomDisplacement(stepsize=0.07)
accept_tests = system.get_config_tests()
if type(system) is LJClusterNew:
if use_compiled:
mc_runner = MonteCarloCompiled(system.radius)
# import pickle
# with open("testpickle", "w") as pout:
# pickle.dump(mc_runner, pout)
else:
mc_runner = MonteCarloChain(system.get_potential(), takestep, accept_tests=accept_tests)
print "using the compiled MC = ", use_compiled
elif type(system) is HarParticle:
mc_runner = HarRunner(system)
print "using HarRunner"
elif type(system) is IsingSystem:
mc_runner = IsingRunnerC(system)
print "using IsingRunner"
else:
raise TypeError('system type is not known')
print "using", nproc, "processors"
if minima is not None:
assert(len(minima) > 0)
print "using", len(minima), "minima"
ns = NestedSamplingBS(system, nreplicas, mc_runner, minima,
mciter=mciter, target_ratio=target_ratio,stepsize=0.07,
nproc=nproc, triv_paral=triv_paral, minprob=minprob, **kwargs)
else:
ns = NestedSampling(system, nreplicas, mc_runner,
mciter=mciter, target_ratio=target_ratio,stepsize=0.07,
nproc=nproc, triv_paral=triv_paral, **kwargs)
etol = 0.01
ns = run_nested_sampling(ns, label, etol, maxiter=maxiter)
return ns
def run_nested_sampling_lj(system,
nreplicas=300,
mciter=1000,
target_ratio=0.7,
label="test",
minima=None,
use_compiled=True,
nproc=1,
triv_paral=True,
minprob=1,
maxiter=1e100,
**kwargs):
takestep = RandomDisplacement(stepsize=0.07)
accept_tests = system.get_config_tests()
if type(system) is LJClusterNew:
if use_compiled:
mc_runner = MonteCarloCompiled(system.radius)
# import pickle
# with open("testpickle", "w") as pout:
# pickle.dump(mc_runner, pout)
else:
mc_runner = MonteCarloChain(system.get_potential(),
takestep,
accept_tests=accept_tests)
print "using the compiled MC = ", use_compiled
elif type(system) is HarParticle:
mc_runner = HarRunner(system)
print "using HarRunner"
elif type(system) is IsingSystem:
mc_runner = IsingRunnerC(system)
print "using IsingRunner"
else:
raise TypeError('system type is not known')
print "using", nproc, "processors"
if minima is not None:
assert (len(minima) > 0)
print "using", len(minima), "minima"
ns = NestedSamplingBS(system,
nreplicas,
mc_runner,
minima,
mciter=mciter,
target_ratio=target_ratio,
stepsize=0.07,
nproc=nproc,
triv_paral=triv_paral,
minprob=minprob,
**kwargs)
else:
ns = NestedSampling(system,
nreplicas,
mc_runner,
mciter=mciter,
target_ratio=target_ratio,
stepsize=0.07,
nproc=nproc,
triv_paral=triv_paral,
**kwargs)
etol = 0.01
ns = run_nested_sampling(ns, label, etol, maxiter=maxiter)
return ns
