def lj_system(box_length, cutoff):
system = feasst.System()
config = feasst.Configuration(
feasst.MakeDomain(feasst.args({"cubic_box_length": str(box_length)})),
feasst.args(
{"particle_type": feasst.install_dir() + "/forcefield/lj.fstprt"}))
config.set_model_param("cutoff", 0, cutoff)
system.add(config)
system.add(feasst.Potential(feasst.MakeLennardJones()))
if system.configuration().domain().is_cell_enabled():
#system.add_to_optimized(feasst.Potential(feasst.MakeLennardJones(), feasst.MakeVisitModelCell()))
system.add_to_reference(
feasst.Potential(feasst.MakeHardSphere(),
feasst.MakeVisitModelCell()))
return system
def configuration(box_length=8, forcefield='data.lj', num=0):
"""Return an LJ configuration with cubic box and (optionally) cell list.
box_length -- the length of the cubic peroidic boundary conditions
forcefield -- the file describing the particle
num -- the number of particles of the first type to add.
"""
config = feasst.Configuration(
feasst.MakeDomain(
feasst.args({
"cubic_box_length": str(box_length),
"init_cells": "3"
})), # optionally attempt to create a cell list
feasst.args({
"particle_type":
feasst.install_dir() + '/forcefield/' + forcefield
}))
for _ in range(num):
config.add_particle_of_type(0)
return config
def system(config=None,
box_length=8.109613,
alphaL=6.870983963962610000,
kmax_squared=38,
rcut=4.891304347826090):
if not config:
config = feasst.Configuration(
feasst.MakeDomain(
feasst.args({"cubic_box_length": str(box_length)})),
feasst.args({
"particle_type0":
feasst.install_dir() +
"/plugin/ewald/forcefield/data.rpm_plus",
"particle_type1":
feasst.install_dir() +
"/plugin/ewald/forcefield/data.rpm_minus"
}))
config.set_model_param("cutoff", 0, rcut)
config.set_model_param("cutoff", 1, rcut)
system = feasst.System()
system.add(config)
system.add(
feasst.Potential(
feasst.MakeEwald(
feasst.args({
"kmax_squared":
str(kmax_squared),
"alpha":
str(alphaL /
system.configuration().domain().min_side_length())
}))))
# Unfortunatley, swig isn't accepting the below method of constructing a two body factory
# system.add(feasst.Potential(feasst.MakeModelTwoBodyFactory(
# feasst.ModelTwoBodyVector([feasst.MakeLennardJones(), feasst.MakeChargeScreened()]))))
two = feasst.MakeModelTwoBodyFactory()
two.add(feasst.MakeHardSphere())
two.add(feasst.MakeChargeScreened())
system.add(feasst.Potential(two))
system.add(feasst.Potential(feasst.MakeChargeSelf()))
# system.precompute()
return system
help="number of hours before restart",
default=1.)
args = parser.parse_args()
print("args:", args)
mc = fst.MonteCarlo()
if args.task > 0:
mc = fst.MakeMonteCarlo("checkpoint.fst")
mc.attempt(args.trials - mc.trials().num_attempts())
quit()
mc.set(fst.MakeRandomMT19937(fst.args({"seed": args.seed})))
mc.add(
fst.Configuration(
fst.MakeDomain(
fst.args({
"cubic_box_length":
str((args.num / args.density)**(1. / 3.))
})), fst.args({"particle_type": args.data})))
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
mc.set(fst.MakeThermoParams(fst.args({"beta": str(args.beta)})))
mc.set(fst.MakeMetropolis())
mc.add(
fst.MakeTrialTranslate(
fst.args({
"tunable_param": "0.2",
"tunable_target_acceptance": "0.2"
})))
mc.add(fst.MakeTrialAdd(fst.args({"particle_type": "0"})))
mc.run(fst.MakeRun(fst.args({"until_num_particles": str(args.num)})))
mc.run(fst.MakeRemoveTrial(fst.args({"name": "TrialAdd"})))
import feasst
monte_carlo = feasst.MonteCarlo()
monte_carlo.set(feasst.MakeRandomMT19937(feasst.args({"seed": "time"})))
monte_carlo.add(
feasst.Configuration(
feasst.MakeDomain(feasst.args({"cubic_box_length": "8"})),
feasst.args(
{"particle_type": feasst.install_dir() + "/forcefield/data.lj"})))
monte_carlo.add(feasst.Potential(feasst.MakeLennardJones()))
monte_carlo.add(feasst.Potential(feasst.MakeLongRangeCorrections()))
monte_carlo.add(feasst.MakeMetropolis(feasst.args({"beta": "1.5"})))
monte_carlo.add(
feasst.MakeTrialTranslate(
feasst.args({
"tunable_param": "2.",
"tunable_target_acceptance": "0.2"
})))
steps_per = int(1e3)
monte_carlo.add(feasst.MakeTuner(feasst.args({"steps_per": str(steps_per)})))
feasst.SeekNumParticles(50)\
.with_metropolis(feasst.args({"beta": "0.1", "chemical_potential": "10"}))\
.with_trial_add().run(monte_carlo)
monte_carlo.add(feasst.MakeLog(feasst.args({"steps_per": str(steps_per)})))
monte_carlo.add(
feasst.MakeMovie(
feasst.args({
"steps_per": str(steps_per),
"file_name": "movie.xyz"
})))
monte_carlo.add(
parser.add_argument("--equilibration_trials", type=int, help="number of trials for equilibration",
default=int(5e7))
parser.add_argument("--trials", type=int, help="total number of trials (equilibration and production)",
default=int(3e8))
parser.add_argument("--num_hours", type=float, help="number of hours before restart", default=1.)
args = parser.parse_args()
print("args:", args)
mc = fst.MonteCarlo()
if args.task > 0:
mc = fst.MakeMonteCarlo("checkpoint.fst")
mc.attempt(args.trials - mc.trials().num_attempts())
quit()
mc.set(fst.MakeRandomMT19937(fst.args({"seed" : args.seed})))
mc.add(fst.Configuration(
fst.MakeDomain(fst.args({"cubic_box_length": str((args.num/args.density)**(1./3.))})),
fst.args({"particle_type": args.data})))
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
mc.set(fst.MakeThermoParams(fst.args({"beta": str(args.beta)})))
mc.set(fst.MakeMetropolis())
mc.add(fst.MakeTrialTranslate(fst.args(
{"tunable_param": "0.2", "tunable_target_acceptance": "0.2"})))
mc.add(fst.MakeTrialAdd(fst.args({"particle_type": "0"})))
mc.run(fst.MakeRun(fst.args({"until_num_particles": str(args.num)})))
mc.run(fst.MakeRemoveTrial(fst.args({"name": "TrialAdd"})))
trials_per = str(int(1e5))
mc.add(fst.MakeCheckEnergy(fst.args({"trials_per" : trials_per, "tolerance" : "1e-8"})))
mc.add(fst.MakeTune())
mc.set(fst.MakeCheckpoint(fst.args({"file_name": "checkpoint.fst",
"num_hours": str(0.95*args.num_hours),