def criteria_flathist(
temperature=1.5,
chemical_potential=-2.352321,
macro_min=0, # minimum macrostate
macro_max=370, # maximum macrostate
tmmc=True, # use Transition-Matrix (TM) if true, else Wang-Landau (WL)
iterations=20): # number of sweeps (TM) or flatness (WL)
"""Return a flat histogram acceptance criteria with number of particles as the macrostate"""
if tmmc:
bias = fst.MakeTransitionMatrix(
fst.args({"min_sweeps": str(iterations)}))
else:
bias = fst.MakeWangLandau(fst.args({"min_flatness": str(iterations)}))
return fst.MakeFlatHistogram(
fst.MakeMacrostateNumParticles(
fst.Histogram(
fst.args({
"width": "1",
"min": str(macro_min),
"max": str(macro_max)
}))), bias,
fst.args({
"beta": str(1. / temperature),
"chemical_potential": str(chemical_potential)
}))
def test(self):
#return
serial = False
serial = True
if serial:
criteria = feasst.MakeFlatHistogram(feasst.args(
{"beta": str(1./1.5),
"chemical_potential": "-2.35231"}
))
criteria.set(feasst.MakeMacrostateGrowthExpanded(
feasst.Histogram(feasst.args({"width": "0.5", "max": "10"})),
#feasst.args({"soft_max": "10"})
))
criteria.set(feasst.MakeTransitionMatrix(feasst.args({"min_sweeps": "10"})))
, "num_steps_to_update": str(int(1e6))}
mc2 = fh.monte_carlo(criteria=criteria, forcefield='data.dimer', run=False)
mc2.add(feasst.MakeCriteriaWriter(feasst.args({"steps_per": str(int(1e6))})))
mc2.run_until_complete()
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, trials_per=str(int(1e6))):
mc = fst.MakeMonteCarlo()
mc.add(config())
mc.add(fst.MakePotential(fst.MakeLennardJonesForceShift()))
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.MakeTrialRotate(fst.args({
"weight": "1.",
"tunable_param": "20."
})))
mc.add(
fst.MakeTrialTransfer(fst.args({
"weight": "4",
"particle_type": "0"
})))
mc.add(
fst.MakeCheckEnergy(
fst.args({
"trials_per": trials_per,
"tolerance": "0.0001"
})))
mc.add(fst.MakeTune(fst.args({"stop_after_phase": "0"})))
mc.add(
fst.MakeLogAndMovie(
fst.args({
"trials_per": trials_per,
"file_name": "clones" + str(thread),
"file_name_append_phase": "True"
})))
mc.add(
fst.MakeEnergy(
fst.args({
"trials_per_write": trials_per,
"file_name": "en" + str(thread) + ".txt",
"file_name_append_phase": "True",
"start_after_phase": "0",
"multistate": "True"
})))
mc.add(fst.MakeCriteriaUpdater(fst.args({"trials_per": trials_per})))
mc.add(
fst.MakeCriteriaWriter(
fst.args({
"trials_per": trials_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
import pandas as pd
import argparse
import matplotlib.pyplot as plt
import feasst as fst
import pyfeasst
parser = argparse.ArgumentParser()
parser.add_argument("--file_name", "-f", type=str, help="file name", action='append', required=True)
parser.add_argument("--label", "-l", type=str, help="variable label", default='ln_prob')
parser.add_argument("--delta_conjugate", "-d", type=float, help="reweight by change in conjugate variable", default=0.)
args = parser.parse_args()
print(args.file_name)
for fname in args.file_name:
df = pd.read_csv(fname, header=pyfeasst.line_beginning_with_state(fname))
gce = fst.GrandCanonicalEnsemble(
fst.Histogram(fst.args({"width": "1", "max": str(df["state"].iloc[-1]),
"min": str(df["state"].iloc[0])})),
fst.LnProbability(fst.DoubleVector(df["ln_prob"])))
#print(df)
#plt.plot(df['state'], df[args.label], label=fname)
gce.reweight(args.delta_conjugate)
plt.plot(df['state'], gce.ln_prob().values(), label=fname)
plt.legend()
plt.show()
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
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
def mc(thread, mn, mx):
steps_per = str(int(1e6))
mc = fst.MakeMonteCarlo()
mc.add(
fst.MakeConfiguration(
fst.args({
"cubic_box_length":
str(args.cubic_box_length),
"particle_type0":
fst.install_dir() + "/forcefield/hard_sphere.fstprt"
})))
mc.add(fst.MakePotential(fst.MakeHardSphere()))
# mc.add_to_optimized(fst.MakePotential(fst.MakeHardSphere(), fst.MakeVisitModelCell(fst.args({"min_length": "1"}))))
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": "1",
"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({
"new_only": "true",
"weight": "1.",
"tunable_param": "1."
})))
mc.add(
fst.MakeTrialTransfer(fst.args({
"weight": "4",
"particle_type": "0"
})))
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.MakePairDistribution(
fst.args({
"steps_per_update": "1000",
"steps_per_write": steps_per,
"dr": "0.025",
"file_name": "gr" + str(thread) + ".txt",
"file_name_append_phase": "True",
"start_after_phase": "0",
"multistate": "True",
"multistate_aggregate": "False"
})))
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({
"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()
mc.add(
fst.MakeConfiguration(
fst.args({
"cubic_box_length":
"12",
"particle_type0":
fst.install_dir() +
"/plugin/charge/forcefield/rpm_plus.fstprt",
"particle_type1":
fst.install_dir() +
"/plugin/charge/forcefield/rpm_minus.fstprt",
"cutoff":
"4.891304347826090",
"charge0":
str(1. / math.sqrt(fst.CODATA2018().charge_conversion())),
"charge1":
str(-1. / math.sqrt(fst.CODATA2018().charge_conversion()))
})))
mc.add(
fst.MakePotential(
fst.MakeEwald(
fst.args({
"alpha": str(6.87098396396261 / 12),
"kmax_squared": "38"
}))))
mc.add(
fst.MakePotential(
fst.MakeModelTwoBodyFactory(fst.MakeHardSphere(),
fst.MakeChargeScreened()),
fst.args({"table_size": "1e6"})))
mc.add(fst.MakePotential(fst.MakeChargeSelf()))
num_steps = "1"
ref = "-1"
if mx >= args.dccb_begin:
mc.run(
fst.MakeAddReference(
fst.args({
"potential_index": "1",
"cutoff": "1",
"use_cell": "true"
})))
ref = "0"
num_steps = "4"
beta = 1. / args.temperature
mc.set(
fst.MakeThermoParams(
fst.args({
"beta": str(beta),
"chemical_potential0": str(args.beta_mu / beta),
"chemical_potential1": 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": str(args.min_sweeps)})),
fst.MakeWLTM(
fst.args({
"collect_flatness": "18",
"min_flatness": "22",
"min_sweeps": str(args.min_sweeps)
})),
fst.MakeAEqualB(fst.args({"extra_A": "1"}))))
mc.add(
fst.MakeTrialTranslate(
fst.args({
"weight": "1.",
"tunable_param": "1."
})))
for particle_type in range(mc.configuration().num_particle_types()):
mc.add(
fst.MakeTrialTransfer(
fst.args({
"weight": "4",
"particle_type": str(particle_type),
"reference_index": ref,
"num_steps": num_steps
})))
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({
"steps_per_write": str(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": 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"
})))
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):
steps_per = str(int(1e5))
mc = fst.MakeMonteCarlo()
#mc.set(fst.MakeRandomMT19937(fst.args({"seed": "12345"})))
#mc.set(fst.MakeRandomMT19937(fst.args({"seed": "1634926410"})))
chi = 0.7 # patch coverage
patch_angle = 2 * math.asin(math.sqrt(chi / 2)) * 180 / math.pi
print('patch_angle', patch_angle)
mc = fst.MonteCarlo()
config = fst.MakeConfiguration(
fst.args({
"cubic_box_length":
"8",
"particle_type0":
fst.install_dir() +
"/plugin/patch/forcefield/two_patch_linear.fstprt"
}))
config.add(fst.MakeGroup(fst.args({"site_type0": "0"})))
mc.add(config)
mc.add(
fst.MakePotential(
fst.MakeHardSphere(),
fst.MakeVisitModelCell(
fst.args({
"min_length": "1",
"cell_group": "1"
})), fst.args({"group_index": "1"})))
patch = fst.MakeVisitModelInnerPatch(
fst.args({"patch_degrees_of_type1": str(patch_angle)}))
mc.add(
fst.MakePotential(
fst.MakeSquareWell(),
fst.MakeVisitModel(patch),
#fst.MakeVisitModelCell(patch, fst.args({"min_length": "1.5", "cell_group": "1"})),
fst.args({"group_index": "1"})))
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": "0.5",
"tunable_param": "0.1"
})))
mc.add(
fst.MakeTrialRotate(fst.args({
"weight": "0.5",
"tunable_param": "20."
})))
mc.add(
fst.MakeTrialTransfer(fst.args({
"weight": "4",
"particle_type": "0"
})))
# mc.add(fst.MakeTrialGrow(fst.ArgsVector([{"translate": "true", "site": "0", "tunable_param": "1"}]),
# {"reference_index": ref, "num_steps": num_steps}))
# mc.add(fst.MakeTrialGrow(fst.ArgsVector([{"transfer": "true", "site": "0", "weight": "4"}]),
# {"reference_index": ref, "num_steps": num_steps}))
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.MakeLog(
fst.args({
"steps_per": steps_per,
"file_name": "clones" + str(thread) + ".txt",
"file_name_append_phase": "True"
})))
mc.add(
fst.MakeMoviePatch(
fst.args({
"steps_per": steps_per,
"file_name": "clones" + str(thread) + ".xyz",
"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):
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