def system(config):
"""Return an LJ system with long-range corrections and (optionally)
an optimized potential.
config -- the configuration
"""
sys = feasst.System()
sys.add(config)
sys.add(feasst.Potential(feasst.MakeLennardJones()))
sys.add(feasst.Potential(feasst.MakeLongRangeCorrections()))
# If the requested cell list spacing is not large enough for the box, the cell list will
# be disabled even if a cell list was requested previously.
if sys.configuration().domain().is_cell_enabled():
# While adding a potential is by default considered an "unoptimized"
# potential, a system may also contain an optimized potential.
# Optimized potentials are used for most energy calculations, but
# CheckEnergy asserts that it is equivalent to the unoptimized
# potential.
sys.add_to_optimized(
feasst.Potential(feasst.MakeLennardJones(),
feasst.MakeVisitModelCell()))
sys.add_to_optimized(
feasst.Potential(feasst.MakeLongRangeCorrections()))
# While the cell list is optimized, the LRCs are not. Regardless, the LRCs are added so
# that the energy is equivalent to the unoptimized potentials.
return sys
def nvtw(num_particles, num_procs, num_equil, num_prod, num_hours, dccb_begin, temperature, mu, steps_per, model):
mc = fst.MakeMonteCarlo()
#mc.set(fst.MakeRandomMT19937(fst.args({"seed": "1633373856"})))
beta = 1./temperature
if model == "lj":
mc.add(fst.MakeConfiguration(fst.args({"cubic_box_length": "8",
"particle_type0": fst.install_dir() + "/forcefield/lj.fstprt"})))
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
elif model == "sqw":
config = fst.MakeConfiguration(fst.args({"cubic_box_length": "8", "particle_type0": fst.install_dir() + "/forcefield/atom.fstprt"}))
config.set_model_param("cutoff", 0, 1.5)
mc.add(config)
mc.add(fst.MakePotential(fst.MakeSquareWell()))
elif model == "spce":
mc.add(fst.MakeConfiguration(fst.args({"cubic_box_length": "20",
"particle_type0": fst.install_dir() + "/forcefield/spce.fstprt"})))
mc.add(fst.MakePotential(fst.MakeEwald(fst.args({"alpha": str(5.6/20),
"kmax_squared": "38"}))))
mc.add(fst.MakePotential(fst.MakeModelTwoBodyFactory(fst.MakeLennardJones(), fst.MakeChargeScreened()),
fst.args({"table_size": "1e6"})))
mc.add(fst.MakePotential(fst.MakeChargeScreenedIntra(), fst.MakeVisitModelBond()))
mc.add(fst.MakePotential(fst.MakeChargeSelf()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
beta = 1./fst.kelvin2kJpermol(temperature, mc.configuration())
else:
assert(False) # model not recognized
# fill box with larger temperature and mu
mc.set(fst.MakeThermoParams(fst.args({"beta": "0.01", "chemical_potential": "10"})))
mc.set(fst.MakeMetropolis());
#trial_args = {"particle_type": "0", "site": "0", "reference_index": ref, "num_steps": num_steps}
mc.add(fst.MakeTrialTranslate(fst.args({"tunable_param": "0.1"})))
#mc.add(fst.MakeTrialGrow(fst.ArgsVector([dict({"translate": "true", "tunable_param": "0.1"}, **trial_args)])))
mc.add(fst.MakeTrialAdd(fst.args({"particle_type": "0", "weight": "4"})))
mc.add(fst.MakeTune(fst.args({"steps_per": steps_per})))
mc.add(fst.MakeCheckEnergy(fst.args({"steps_per": steps_per, "tolerance": "0.0001"})))
mc.add(fst.MakeLogAndMovie(fst.args({"steps_per": steps_per,
"file_name": model + str(num_particles)})))
mc.set(fst.MakeCheckpoint(fst.args({"file_name": "checkpoint" + str(num_particles) + ".fst",
"num_hours": str(0.1*num_procs*num_hours),
"num_hours_terminate": str(0.9*num_procs*num_hours)})))
mc.run(fst.MakeRun(fst.args({"until_num_particles": str(num_particles)})))
mc.run(fst.MakeRemoveTrial(fst.args({"name": "TrialAdd"})))
# nvt equilibration at desired temperature
mc.set(fst.MakeThermoParams(fst.args({"beta": str(beta),
"chemical_potential": str(mu)})))
mc.attempt(int((num_particles+1)*num_equil))
mc.run(fst.MakeRemoveModify(fst.args({"name": "Tune"})))
mc.add(fst.MakeTrialTransfer(fst.args({"particle_type": "0", "weight": "4"})))
#mc.add(fst.MakeTrialGrow(fst.ArgsVector([dict({"transfer": "true", "weight": "4"}, **trial_args)])))
mc.set(fst.MakeFlatHistogram(fst.args({
"Macrostate": "MacrostateNumParticles", "width": "1", "max": str(num_particles), "min": str(num_particles),
"Bias": "TransitionMatrix", "min_sweeps": "1"})))
mc.add(fst.MakeEnergy(fst.args({"steps_per_write": steps_per,
"file_name": "en" + str(num_particles) + ".txt"})))
mc.add(fst.MakeCriteriaWriter(fst.args({"steps_per": steps_per,
"file_name": "crit" + str(num_particles) + ".txt"})))
mc.attempt(int((num_particles+1)*num_prod))
def system(config, alphaL=5.6, kmax_squared=38, rcut=False):
if rcut:
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.MakeLennardJones())
two.add(feasst.MakeChargeScreened())
system.add(feasst.Potential(two))
system.add(
feasst.Potential(feasst.MakeChargeScreenedIntra(),
feasst.MakeVisitModelBond()))
system.add(feasst.Potential(feasst.MakeChargeSelf()))
system.add(feasst.Potential(feasst.MakeLongRangeCorrections()))
# system.precompute()
return system
def lj_system(box_length):
system = feasst.System()
config = feasst.Configuration(
feasst.Domain(feasst.args({"cubic_box_length": str(box_length)})),
feasst.args({"particle_type": feasst.install_dir() + "/forcefield/lj.fstprt"}))
config.set_model_param("cutoff", 0, args.cutoff)
system.add(config)
system.add(feasst.Potential(feasst.MakeLennardJones()))
return system
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 initialize_neighbor_list(mc):
neigh_crit = fst.MakeNeighborCriteria(
fst.args({
"maximum_distance": "10",
"minimum_distance": "2.5",
"site_type0": "0",
"site_type1": "0",
"potential_index": "1"
}))
mc.add(neigh_crit)
lj_and_coul = fst.MakeModelTwoBodyFactory()
lj_and_coul.add(fst.MakeLennardJones())
lj_and_coul.add(fst.MakeChargeScreened(fst.args({"table_size": "0"})))
mc.set(
1,
fst.MakePotential(
lj_and_coul,
fst.MakeVisitModel(
fst.MakeVisitModelInner(
fst.MakeEnergyMapNeighborCriteria(neigh_crit))),
fst.args({"table_size": "1e6"})))
def mc(thread, mn, mx):
steps_per = str(int(1e6))
mc = fst.MakeMonteCarlo()
mc.add(
fst.MakeConfiguration(
fst.args({
"cubic_box_length":
"8",
"particle_type0":
fst.install_dir() + "/forcefield/lj.fstprt"
})))
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
trial_args = {"particle_type": "0", "site": "0"}
if mx >= args.dccb_begin:
mc.run(
fst.MakeAddReference(fst.args({
"cutoff": "1",
"use_cell": "true"
})))
trial_args["reference_index"] = "0"
trial_args["num_steps"] = "4"
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": str(1. / args.temperature),
"chemical_potential": str(args.mu)
})))
mc.set(
fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"max": str(mx),
"min": str(mn)
}))),
# fst.MakeTransitionMatrix(fst.args({"min_sweeps": str(args.min_sweeps)})),
fst.MakeWLTM(
fst.args({
"collect_flatness": "18",
"min_flatness": "22",
"min_sweeps": str(args.min_sweeps)
}))))
#mc.add(fst.MakeTrialTranslate(fst.args({"weight": "1.", "tunable_param": "1."})))
#mc.add(fst.MakeTrialTransfer(fst.args({"weight": "4", "particle_type": "0",
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector([
dict({
"translate": "true",
"tunable_param": "1"
}, **trial_args)
])))
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(
[dict({
"transfer": "true",
"weight": "4"
}, **trial_args)])))
mc.add(
fst.MakeCheckEnergy(
fst.args({
"steps_per": steps_per,
"tolerance": "0.0001"
})))
mc.add(
fst.MakeTune(
fst.args({
"steps_per": steps_per,
"stop_after_phase": "0"
})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"steps_per": steps_per,
"file_name": "clones" + str(thread),
"file_name_append_phase": "True"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"steps_per_write": steps_per,
"file_name": "en" + str(thread) + ".txt",
"file_name_append_phase": "True",
"start_after_phase": "0",
"multistate": "True"
})))
mc.add(fst.MakeCriteriaUpdater(fst.args({"steps_per": steps_per})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"steps_per": steps_per,
"file_name": "clones" + str(thread) + "_crit.txt",
"file_name_append_phase": "True"
})))
mc.set(
fst.MakeCheckpoint(
fst.args({
"file_name":
"checkpoint" + str(thread) + ".fst",
"num_hours":
str(0.1 * args.num_procs * args.num_hours),
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
def mc(thread, mn, mx):
mc = fst.MakeMonteCarlo()
mc.set(fst.MakeRandomMT19937(fst.args({"seed": "123"})))
mc.add(
fst.MakeConfiguration(
fst.args({
"side_length0": str(args.lx),
"side_length1": str(args.ly),
"side_length2": str(args.lz),
"particle_type0": args.particle
})))
for site_type in range(mc.configuration().num_site_types()):
mc.get_system().get_configuration().set_model_param(
"cutoff", site_type, args.cutoff)
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(
fst.MakePotential(fst.MakeLennardJones(),
fst.MakeVisitModelIntra(fst.args({"cutoff": "4"}))))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
if mx > args.dccb_begin:
reference = fst.Potential(
fst.MakeLennardJones(),
fst.MakeVisitModelCell(
fst.args({"min_length": str(args.dccb_cutoff)})))
reference.set_model_params(mc.configuration())
for site_type in range(mc.configuration().num_site_types()):
reference.set_model_param("cutoff", site_type, args.dccb_cutoff)
mc.add_to_reference(reference)
#mc.add_to_reference(fst.MakePotential(fst.MakeLennardJones(),
# fst.MakeVisitModelIntra(fst.args({"cutoff": "4"}))))
stage_args = {"reference_index": "0", "num_steps": "4"}
else:
mc.add_to_reference(fst.MakePotential(fst.DontVisitModel()))
stage_args = {"reference_index": "0", "num_steps": "1"}
beta = 1. / fst.kelvin2kJpermol(args.temperature)
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": str(beta),
"chemical_potential0": str(args.beta_mu / beta)
})))
mc.set(fst.MakeMetropolis())
mc.add(fst.MakeTrialTranslate(fst.args({"weight": "0.5"})))
mc.add(fst.MakeTrialRotate(fst.args({"weight": "0.5"})))
print('thread', thread, 'mn', mn, 'mx', mx)
if thread == 0 and mn > 0:
mc.add(fst.MakeTrialAdd(fst.args({"particle_type": "0"})))
mc.run(fst.MakeRun(fst.args({"until_num_particles": str(mn)})))
mc.run(fst.RemoveTrial(fst.args({"name": "TrialAdd"})))
mc.set(
fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"max": str(mx),
"min": str(mn)
}))),
# fst.MakeTransitionMatrix(fst.args({"min_sweeps": str(args.sweeps)})),
fst.MakeWLTM(
fst.args({
"collect_flatness": str(args.collect_flatness),
"min_flatness": str(args.min_flatness),
"min_sweeps": "1000"
}))))
# configurational bias with TrialGrow: full and partial regrows from 0-site, and reverse
num_sites = mc.configuration().particle_type(0).num_sites()
for site in range(num_sites):
for g in gen_grow(num_sites, reptate=False):
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(add_particle_type_weight(
site, num_sites, g)), fst.args(stage_args)))
# reptation
if num_sites > 3:
for g in gen_grow(num_sites, reptate=True):
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(add_particle_type_weight(0, num_sites, g)),
fst.args(stage_args)))
# these moves may not take bond energies into consideration properly. Instead, should implement a dihedral rotation.
#mc.add(fst.MakeTrialCrankshaft(fst.args(dict({"weight": "0.25", "tunable_param": "25.", "max_length": "5."}, **stage_args))))
#mc.add(fst.MakeTrialPivot(fst.args(dict({"weight": "0.25", "tunable_param": "25.", "max_length": "5."}, **stage_args))))
mc.add(
fst.MakeCheckEnergy(
fst.args({
"steps_per": str(args.steps_per),
"tolerance": "0.0001"
})))
mc.add(
fst.MakeTune(
fst.args({
"steps_per": str(args.steps_per),
"stop_after_phase": "0"
})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"steps_per": str(args.steps_per),
"file_name": "clones" + str(thread),
"file_name_append_phase": "True"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"file_name": "en" + str(thread) + '.txt',
"file_name_append_phase": "True",
"start_after_phase": "0",
"steps_per_write": str(args.steps_per),
"steps_per_update": "1",
"multistate": "True"
})))
mc.add(
fst.MakeCriteriaUpdater(fst.args({"steps_per": str(args.steps_per)})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"steps_per": str(args.steps_per),
"file_name": "clones" + str(thread) + "_crit.txt",
"file_name_append_phase": "True"
})))
mc.set(
fst.MakeCheckpoint(
fst.args({
"file_name":
"checkpoint" + str(thread) + ".fst",
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
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"})))
steps_per = str(int(1e5))
mc.add(
fst.MakeCheckEnergyAndTune(
def mc(thread, mn, mx):
steps_per = int(1e5)
avb, dccb = avb_or_dccb(mx)
mc = fst.MakeMonteCarlo()
mc.add(
fst.MakeConfiguration(
fst.args({
"cubic_box_length":
"20",
"physical_constants":
"CODATA2010",
"particle_type0":
fst.install_dir() + "/forcefield/spce.fstprt"
})))
mc.add(
fst.MakePotential(
fst.MakeEwald(
fst.args({
"alpha": str(5.6 / 20),
"kmax_squared": "38"
}))))
mc.add(
fst.MakePotential(
fst.MakeModelTwoBodyFactory(fst.MakeLennardJones(),
fst.MakeChargeScreened()),
fst.args({"table_size": "1e6"})))
mc.add(
fst.MakePotential(fst.MakeChargeScreenedIntra(),
fst.MakeVisitModelBond()))
mc.add(fst.MakePotential(fst.MakeChargeSelf()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
if dccb or avb:
mc.run(
fst.MakeAddReference(
fst.args({
"potential_index": "1",
"cutoff": "3.16555789",
"use_cell": "true"
})))
if avb:
initialize_neighbor_list(mc)
beta = 1. / fst.kelvin2kJpermol(525, mc.configuration())
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": str(beta),
"chemical_potential": str(-8.14 / beta)
})))
mc.set(
fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"max": str(mx),
"min": str(mn)
}))),
fst.MakeTransitionMatrix(fst.args({"min_sweeps": "10"}))))
mc.add(
fst.MakeTrialTranslate(
fst.args({
"weight": "1.",
"tunable_param": "1.",
})))
mc.add(
fst.MakeTrialRotate(fst.args({
"weight": "1.",
"tunable_param": "1."
})))
mc.add(
fst.MakeTrialTransfer(fst.args({
"particle_type": "0",
"weight": "4"
})))
regrow1 = [{
"angle": "true",
"mobile_site": "1",
"anchor_site": "0",
"anchor_site2": "2"
}]
regrow2 = [{
"angle": "true",
"mobile_site": "2",
"anchor_site": "0",
"anchor_site2": "1"
}]
regrow12 = [{
"bond": "true",
"mobile_site": "1",
"anchor_site": "0"
}] + copy.deepcopy(regrow2)
regrow21 = [{
"bond": "true",
"mobile_site": "2",
"anchor_site": "0"
}] + copy.deepcopy(regrow1)
if dccb:
grow012 = [{
"transfer": "true",
"site": "0",
"weight": "4"
}] + copy.deepcopy(regrow12)
grow021 = [{
"transfer": "true",
"site": "0",
"weight": "4"
}] + copy.deepcopy(regrow21)
for grow in [regrow1, regrow2]:
grow[0]["weight"] = "0.3"
for grow in [regrow12, regrow21]:
grow[0]["weight"] = "0.2"
for grow in [grow012, grow021, regrow12, regrow21, regrow1, regrow2]:
grow[0]["particle_type"] = "0"
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(grow),
fst.args({
"reference_index": "0",
"num_steps": "4"
})))
if avb:
for avbtype in ["transfer_avb", "regrow_avb2", "regrow_avb4"]:
avb = [{
avbtype: "true",
"site": "0",
"neighbor_index": "0",
"target_particle_type": "0",
"target_site": "0"
}]
avb_012 = copy.deepcopy(avb) + copy.deepcopy(regrow12)
avb_021 = copy.deepcopy(avb) + copy.deepcopy(regrow21)
for grow in [avb_012, avb_021]:
grow[0]["weight"] = "0.5"
grow[0]["particle_type"] = "0"
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(grow),
fst.args({
"num_steps": "4",
"reference_index": "0"
})))
mc.add(
fst.MakeCheckEnergyAndTune(
fst.args({
"steps_per": str(steps_per),
"tolerance": "0.0001"
})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"steps_per": str(steps_per),
"file_name": "clones" + str(thread)
})))
mc.add(fst.MakeCriteriaUpdater(fst.args({"steps_per": str(steps_per)})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"steps_per": str(steps_per),
"file_name": "clones" + str(thread) + "_crit.txt"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"steps_per_write": str(steps_per),
"file_name": "en" + str(thread),
"multistate": "true"
})))
mc.set(
fst.MakeCheckpoint(
fst.args({
"file_name":
"checkpoint" + str(thread) + ".fst",
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
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(
def mc(thread, mn, mx):
mc = fst.MakeMonteCarlo()
#mc.set(fst.MakeRandomMT19937(fst.args({"seed": "123"})))
mc.add(
fst.MakeConfiguration(
fst.args({
"cubic_box_length": str(args.cubic_box_length),
"physical_constants": "CODATA2010",
"particle_type0": args.molecule
})))
mc.add(
fst.MakePotential(
fst.MakeEwald(
fst.args({
"alpha": str(5.6 / args.cubic_box_length),
"kmax_squared": "38"
}))))
mc.add(
fst.MakePotential(
fst.MakeModelTwoBodyFactory(fst.MakeLennardJones(),
fst.MakeChargeScreened()),
fst.args({"table_size": "1e6"})))
mc.add(
fst.MakePotential(fst.MakeChargeScreenedIntra(),
fst.MakeVisitModelBond()))
mc.add(fst.MakePotential(fst.MakeChargeSelf()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
if mx > args.dccb_begin:
mc.run(
fst.MakeAddReference(
fst.args({
"potential_index": "1",
"cutoff": "3.16555789",
"use_cell": "true"
})))
beta = 1. / fst.kelvin2kJpermol(args.temperature, mc.configuration())
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": str(beta),
"chemical_potential": str(args.beta_mu / beta)
})))
mc.set(
fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"max": str(mx),
"min": str(mn)
}))),
fst.MakeTransitionMatrix(fst.args({"min_sweeps": "10"}))))
mc.add(
fst.MakeTrialTranslate(
fst.args({
"weight": "1.",
"tunable_param": "1.",
})))
if mx > args.dccb_begin:
regrow1 = [{
"angle": "true",
"mobile_site": "1",
"anchor_site": "0",
"anchor_site2": "2"
}]
regrow2 = [{
"angle": "true",
"mobile_site": "2",
"anchor_site": "0",
"anchor_site2": "1"
}]
regrow12 = [{
"bond": "true",
"mobile_site": "1",
"anchor_site": "0"
}] + copy.deepcopy(regrow2)
regrow21 = [{
"bond": "true",
"mobile_site": "2",
"anchor_site": "0"
}] + copy.deepcopy(regrow1)
grow012 = [{
"transfer": "true",
"site": "0",
"weight": "4"
}] + copy.deepcopy(regrow12)
grow021 = [{
"transfer": "true",
"site": "0",
"weight": "4"
}] + copy.deepcopy(regrow21)
for grow in [regrow1, regrow2]:
grow[0]["weight"] = "0.3"
for grow in [regrow12, regrow21]:
grow[0]["weight"] = "0.2"
for grow in [grow012, grow021, regrow12, regrow21, regrow1, regrow2]:
grow[0]["particle_type"] = "0"
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector(grow),
fst.args({
"reference_index": "0",
"num_steps": "4"
})))
else:
mc.add(
fst.MakeTrialRotate(
fst.args({
"weight": "1.",
"tunable_param": "1."
})))
mc.add(
fst.MakeTrialTransfer(
fst.args({
"particle_type": "0",
"weight": "4"
})))
mc.add(
fst.MakeCheckEnergyAndTune(
fst.args({
"steps_per": str(args.steps_per),
"tolerance": "0.0001"
})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"steps_per": str(args.steps_per),
"file_name": "clones" + str(thread)
})))
mc.add(
fst.MakeCriteriaUpdater(fst.args({"steps_per": str(args.steps_per)})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"steps_per": str(args.steps_per),
"file_name": "clones" + str(thread) + "_crit.txt"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"steps_per_write": str(args.steps_per),
"file_name": "en" + str(thread),
"multistate": "true"
})))
mc.set(
fst.MakeCheckpoint(
fst.args({
"file_name":
"checkpoint" + str(thread) + ".fst",
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
def mc(thread, mn, mx):
steps_per = int(1e4)
mc = fst.MakeMonteCarlo()
if mx > args.dccb_begin:
ref = "0"
num = "4"
else:
ref = "-1"
num = "1"
config_args = dict()
index = 0
thermo_params = {"beta": str(1. / args.temperature)}
for part in args.particles:
config_args["particle_type" + str(index)] = part
thermo_params["chemical_potential" + str(index)] = str(
args.beta_mu * args.temperature)
index += 1
thermo_params["chemical_potential0"] = str(
(args.delta_betamu_0 + args.beta_mu) * args.temperature)
mc.add(
fst.MakeConfiguration(
fst.args(
dict(
{
"side_length0": str(args.lx),
"side_length1": str(args.ly),
"side_length2": str(args.lz)
}, **config_args))))
mc.add(fst.MakePotential(fst.MakeLennardJones()))
mc.add(fst.MakePotential(fst.MakeLongRangeCorrections()))
if mx > args.dccb_begin:
reference = fst.Potential(
fst.MakeLennardJones(),
fst.MakeVisitModelCell(
fst.args({"min_length": str(args.dccb_cutoff)})))
reference.set_model_params(mc.configuration())
for site_type in range(mc.configuration().num_site_types()):
reference.set_model_param("cutoff", site_type, args.dccb_cutoff)
mc.add_to_reference(reference)
mc.set(fst.MakeThermoParams(thermo_params))
mc.set(
fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"max": str(mx),
"min": str(mn)
}))),
# fst.MakeTransitionMatrix(fst.args({"min_sweeps": str(args.sweeps)})),
fst.MakeWLTM(
fst.args({
"collect_flatness": str(args.collect_flatness),
"min_flatness": str(args.min_flatness),
"min_sweeps": "1000"
}))))
for particle_type in range(mc.configuration().num_particle_types()):
mc.add(
fst.MakeTrialTranslate(
fst.args({
"particle_type": str(particle_type),
"weight": "1.",
"tunable_param": "1."
})))
if mx > args.dccb_begin and mc.configuration().particle_type(
particle_type).num_sites() == 2:
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector([
{
"transfer":
"true", # "regrow": "true", # regrow isn't very efficient
"particle_type": str(particle_type),
"site": "0",
"weight": "4"
},
{
"bond": "true",
"mobile_site": "1",
"anchor_site": "0"
}
]),
fst.args({
"reference_index": ref,
"num_steps": num
})))
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector([{
"particle_type": str(particle_type),
"weight": "0.5",
"bond": "true",
"mobile_site": "1",
"anchor_site": "0",
"reference_index": ref,
"num_steps": num
}])))
mc.add(
fst.MakeTrialGrow(
fst.ArgsVector([{
"particle_type": str(particle_type),
"weight": "0.5",
"bond": "true",
"mobile_site": "0",
"anchor_site": "1",
"reference_index": ref,
"num_steps": num
}])))
else:
mc.add(
fst.MakeTrialRotate(
fst.args({
"particle_type": str(particle_type),
"weight": "1.",
"tunable_param": "1."
})))
mc.add(
fst.MakeTrialTransfer(
fst.args({
"particle_type": str(particle_type),
"weight": "4"
})))
mc.add(
fst.MakeCheckEnergy(
fst.args({
"steps_per": str(steps_per),
"tolerance": "0.0001"
})))
mc.add(
fst.MakeTune(
fst.args({
"steps_per": str(steps_per),
"stop_after_phase": "0"
})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"steps_per": str(steps_per),
"file_name": "clones" + str(thread),
"file_name_append_phase": "True"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"file_name": "en" + str(thread) + '.txt',
"file_name_append_phase": "True",
"start_after_phase": "0",
"steps_per_write": str(steps_per),
"steps_per_update": "1",
"multistate": "True"
})))
if mc.configuration().num_particle_types() > 1:
mc.add(
fst.MakeNumParticles(
fst.args({
"particle_type": "0",
"file_name": "num" + str(thread) + '.txt',
"file_name_append_phase": "True",
"start_after_phase": "0",
"steps_per_write": str(steps_per),
"steps_per_update": "1",
"multistate": "True"
})))
mc.add(
fst.MakeExtensiveMoments(
fst.args({
"steps_per_write": str(steps_per),
"file_name": "extmom" + str(thread) + ".txt",
"file_name_append_phase": "True",
"start_after_phase":
"0", # do not update until equilibration complete (phase 1)
"max_order": "3",
"multistate": "True"
})))
mc.add(fst.MakeCriteriaUpdater(fst.args({"steps_per": str(steps_per)})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"steps_per": str(steps_per),
"file_name": "clones" + str(thread) + "_crit.txt",
"file_name_append_phase": "True"
})))
print(0.9 * args.num_procs * args.num_hours)
mc.set(
fst.MakeCheckpoint(
fst.args({
"file_name":
"checkpoint" + str(thread) + ".fst",
"num_hours_terminate":
str(0.9 * args.num_procs * args.num_hours)
})))
return mc
