def test(self):
feasst.ranInitByDate()
space = feasst.makeSpace(
feasst.args({
"dimen": "3",
"boxLength": "24.8586887"
}))
pair = feasst.makePairLJCoulEwald(
space,
feasst.args({
"rCut": str(space.minl() / 2.),
"molTypeInForcefield": "data.spce",
"alphaL": "5.6",
"k2max": "38"
}))
# acceptance criteria
temperature = 298 # Kelvin
beta = 1. / (temperature * feasst.idealGasConstant / 1e3) # mol/KJ
criteria = feasst.CriteriaMetropolis(beta, 1.)
mc = feasst.MC(space, pair, criteria)
feasst.transformTrial(mc, "translate", 0.1)
feasst.transformTrial(mc, "rotate", 0.1)
mc.initLog("log", int(1e4))
mc.initMovie("movie", int(1e4))
mc.initRestart("tmp/rst", int(1e4))
mc.setNFreqTune(int(1e4))
mc.setNFreqCheckE(int(1e4), 1e-6)
mc.nMolSeek(512)
mc.runNumTrials(int(1e6)) # run equilibration
# Run the production simulation
mc.initProduction()
mc.zeroStat()
mc.setNFreqTune(0)
mc.runNumTrials(int(1e6))
# Check average energy against Gerhard Hummer
# https:#doi.org/10.1063/1.476834
peAv = mc.peAccumulator().average() / float(space.nMol())
peStd = mc.peAccumulator().blockStdev() / float(space.nMol())
pePublish = -46.82 # published value
pePublishStd = 0.02
self.assertAlmostEqual(peAv,
pePublish,
delta=2.576 * (pePublishStd + peStd))
def test(self):
space = feasst.Space(3)
space.initBoxLength(24.8586887) # molecule-center based cut-off
pair = feasst.PairLJCoulEwald(space, space.minl() / 2.)
pair.initData(space.install_dir() + "/forcefield/data.spce")
pair.initKSpace(
5.6, # alpha*L
38) # k^2 < k2max cutoff
# Read the pre-equilibrated configuration of 512 water molecules
conf_file = feasst.make_ifstream(space.install_dir() + \
"/testcase/3_spce/2_nvt-mc/test.xyz")
pair.readxyz(conf_file)
pair.initEnergy()
# acceptance criteria
temperature = 298 # Kelvin
beta = 1. / (temperature * feasst.idealGasConstant / 1e3) # mol/KJ
criteria = feasst.CriteriaMetropolis(beta, 1.)
mc = feasst.MC(space, pair, criteria)
feasst.transformTrial(mc, "translate", 0.1)
mc.initLog("log", int(1e4))
mc.initMovie("movie", int(1e4))
mc.initRestart("tmp/rst", int(1e4))
mc.setNFreqTune(int(1e4))
mc.runNumTrials(int(1e6)) # run equilibration
# Run the production simulation
mc.zeroStat()
mc.runNumTrials(int(1e6))
# Check average energy against Gerhard Hummer
# https:#doi.org/10.1063/1.476834
peAv = mc.peAccumulator().average() / float(space.nMol())
peStd = mc.peAccumulator().blockStdev() / float(space.nMol())
pePublish = -46.
# pePublish = -46.82 # published value
pePublishStd = 0.02
self.assertAlmostEqual(peAv,
pePublish,
delta=2.576 * (pePublishStd + peStd))
def test(self):
space = feasst.Space(3)
rho = 1e-3 # number density
nMol = 500 # number of particles
space.initBoxLength(
(float(nMol) / rho)**(1. / 3.)) # set the cubic PBCs
pair = feasst.PairHardSphere(space)
pair.initData(space.install_dir() + "/forcefield/data.atom")
pair.initEnergy()
criteria = feasst.CriteriaMetropolis(1., 1.)
mc = feasst.MC(space, pair, criteria)
feasst.transformTrial(mc, "translate", 0.1)
mc.nMolSeek(nMol)
mc.initLog("log", int(1e4))
mc.initMovie("movie", int(1e4))
mc.initRestart("tmp/rst", int(1e4))
mc.setNFreqTune(int(1e4))
mc.runNumTrials(int(1e7)) # run equilibration
# Run the production simulation
mc.runNumTrials(int(1e7))
def test(self):
space = feasst.Space(3)
rho = 1e-3 # number density
nMol = 500 # number of particles
space.initBoxLength(
(float(nMol) / rho)**(1. / 3.)) # set the cubic PBCs
molNameSS = space.install_dir() + "/forcefield/data.lj"
space.addMolInit(molNameSS)
pair = feasst.PairLJ(space, 3) # potential truncation at 3
pair.initEnergy()
temperature = 0.9
criteria = feasst.CriteriaMetropolis(1. / temperature, 1.)
mc = feasst.MC(space, pair, criteria)
feasst.transformTrial(mc, "translate", 0.1)
mc.nMolSeek(nMol)
mc.initLog("log", int(1e4))
mc.initMovie("movie", int(1e4))
mc.initRestart("tmp/rst", int(1e4))
mc.setNFreqTune(int(1e4))
mc.runNumTrials(int(1e7)) # run equilibration
# Run the production simulation and compute statistics on potential energy
mc.setNFreqTune(0) # do not tune during production
pe = feasst.Accumulator()
from itertools import islice, count
for itrial in islice(count(1), int(1e7) - 1):
mc.runNumTrials(1)
pe.accumulate(pair.peTot() / float(space.nMol()))
# Check average energy against the NIST SRSW
# https:#mmlapps.nist.gov/srs/LJ_PURE/mc.htm
# https:#www.nist.gov/programs-projects/nist-standard-reference-simulation-website
peAv = pe.average()
peStd = pe.blockStdev()
peSRSW = -9.9165E-03
peSRSWstd = 1.89E-05
self.assertAlmostEqual(peAv, peSRSW, delta=2.576 * (peSRSWstd + peStd))
def run(self,
orderMax=100,
orderMin=0,
temp=1.50,
mu1=0.0,
dmu2=0.0,
order=3,
steps=10000):
"""
Run a new simulation from scratch.
Parameters
----------
orderMax : int
Max number of particles to allow in this window (default=100)
orderMin : int
Min number of particles to allow in this window (default=0)
temp : double
Temperature (default = 1.5)
mu1 : double
Chemical potential of species 1
dmu2 : double
mu2 - mu1
order : int
Max order to record extensive moments up to
steps : int
Number of MC steps to perform
"""
s = feasst.Space(3, 0)
s.lset(15)
p = feasst.PairLJMulti(s, s.minl() / 4.0)
molA = os.path.dirname(os.path.realpath(__file__)) + "/data.lj"
molB = os.path.dirname(os.path.realpath(__file__)) + "/data.ljb"
s.addMolInit(molA)
p.initLMPData(molA)
s.addMolInit(molB)
p.initLMPData(molB)
p.rCutijset(0, 0, (p.sig(0) + p.sig(0)) / 2 * 3.0)
p.rCutijset(0, 1, (p.sig(0) + p.sig(1)) / 2 * 3.0)
p.rCutijset(1, 1, (p.sig(1) + p.sig(1)) / 2 * 3.0)
for i in range(2):
for j in range(2):
p.linearShiftijset(i, j, True)
s.updateCells(
p.rCutMaxAll()) # intermolecular potential needs max rcut
barrier = feasst.SpeciesBarriers(s.nParticleTypes())
radius = 4.0 # this goes to CENTER OF MASS, so pore radius actually = 4.5 with sigma/2 exclusion
eps_w = 3.0
width = 0.5
pt = [0.0, 0.0, 0.0]
barrier.addSqwCylinder(0, pt, radius, eps_w, width, 0)
barrier.addSqwCylinder(1, pt, radius - (p.sig(1) - p.sig(0)) / 2,
eps_w / 2.0, width, 0)
pairBarr = feasst.PairBarriers(s, barrier)
ipair = feasst.PairHybrid(s, max(p.rCutMaxAll(), width))
ipair.addPair(p)
ipair.addPair(pairBarr)
ipair.initEnergy()
assert (
barrier.safe(ipair)
) # check barrier doesn't violate any boundary conditions or allow periodic interactions
orderParam = "nmol"
beta = 1.0 / temp
cc = feasst.CriteriaWLTMMC(beta, math.exp(beta * mu1), orderParam,
orderMin - 0.5 * 1.0, orderMax + 0.5 * 1.0,
orderMax - orderMin + 1)
cc.addActivity(math.exp(beta * (mu1 + dmu2)))
mc = feasst.WLTMMC(s, ipair, cc)
em = feasst.AnalyzeExtensiveMoments(s, ipair)
em.setOrderParam(order, cc)
mc.weight = 0.6
feasst.deleteTrial(mc, molA)
mc.weight = 0.6
feasst.deleteTrial(mc, molB)
mc.weight = 0.6
feasst.addTrial(mc, molA)
mc.weight = 0.6
feasst.addTrial(mc, molB)
mc.weight = 0.2
feasst.xswapTrial(mc)
mc.weight = 0.4
feasst.transformTrial(mc, "translate", 0.4)
mc.nMolSeek(
orderMin, molA,
1000000) # mininum bound with pure A (smaller of the 2 species)
nfreq = 100000
mc.initLog("log", nfreq)
mc.initColMat("colMat", nfreq)
mc.setNFreqCheckE(nfreq, 1e-8)
mc.setNFreqTune(nfreq)
mc.initMovie("movie", nfreq * 1000)
mc.initRestart("tmp/rst", nfreq * 1000)
em.initFreq(5)
em.initPrintFreq(nfreq * 1000)
em.initFileName("extMom")
mc.initAnalyze(em)
cc.collectInit(4.0e-6) # start collecting TMMC matric at wlFlat == 18
cc.tmmcInit(5.0e-7) # switch to TMMC after 22
mc.wlFlatProduction(
22
) # after this # iterations, switch to "production" phase and measure
mc.runNumTrials(steps)
em.write()
def test(self):
feasst.ranInitByDate() # initialize random number generator
space = feasst.Space(3, 0) # initialize simulation domain
space.initBoxLength(args.boxl)
addMolType = space.install_dir() + "/forcefield/" + args.molName
space.addMolInit(addMolType)
# initialize pair-wise interactions
pair = feasst.PairLJ(space, args.rCut)
pair.initEnergy()
# acceptance criteria
nMolMin = 0
import math
criteria = feasst.CriteriaWLTMMC(1. / args.temp, math.exp(args.lnz),
"nmol", nMolMin, args.nMolMax)
criteria.collectInit()
criteria.tmmcInit()
# initialize monte carlo
mc = feasst.WLTMMC(space, pair, criteria)
mc.weight = 3. / 4.
feasst.transformTrial(mc, "translate")
mc.weight = 1. / 8.
feasst.deleteTrial(mc)
mc.weight = 1. / 8.
feasst.addTrial(mc, addMolType)
# output log, lnpi and movie
mc.initLog("log", args.nfreq)
mc.initColMat("colMat", args.ncfreq)
mc.setNFreqCheckE(args.ncfreq, 1e-8)
mc.setNFreqTune(args.nfreq)
mc.initMovie("movie", args.nfreq)
#mc.initXTC("movie", args.nfreq)
mc.initRestart("tmp/rst", args.ncfreq)
# production tmmc simulation
if args.openMP:
mc.initWindows(
2., # exponent that determines size of windows
0) # extra macrostate overlap between processors
mc.runNumSweeps(
20, # number of "sweeps"
-1) # maximum number of trials. Infinite if "-1".
# test against SRSW values
self.assertAlmostEqual(criteria.pe(0).average(), 0, 13)
compareEnergyAndMacro(criteria, 1, self, -0.0006057402333333332,
6.709197666659334e-10,
-270.0061768 + 274.6763737666667,
0.037092307087640365)
compareEnergyAndMacro(criteria, 2, self, -0.030574223333333334,
9.649146611661053e-06,
-266.0191155333334 + 274.6763737666667,
0.03696447428346385)
compareEnergyAndMacro(criteria, 3, self, -0.089928316,
0.0001387472078025413,
-262.4277240666667 + 274.6763737666667,
0.037746391500313385)
compareEnergyAndMacro(criteria, 4, self, -0.1784570533333333,
3.3152449884326804e-05,
-259.11444086666665 + 274.6763737666667,
0.03809721387875822)
compareEnergyAndMacro(criteria, 5, self, -0.29619201333333334,
1.3487910636322294e-05,
-256.0144809 + 274.6763737666667,
0.03845757460933292)
def run (self, **kwargs):
"""
Run a new simulation from scratch.
Parameters
----------
orderMax : int
Max number of particles to allow in this window (default=100)
orderMin : int
Min number of particles to allow in this window (default=0)
temp : double
Temperature (default = 1.5)
mu1 : double
Chemical potential of species 1
dmu2 : double
mu2 - mu1
order : int
Max order to record extensive moments up to
steps : int
Number of MC steps to perform
lam11 : float
Value of lambda_11
lam22 : float
Value of lambda_22
molA : string
Filename for molA (1)
molB : string
Filename for molB (2)
"""
self.parse(kwargs)
s = feasst.Space(3,0)
s.lset(9.0)
p = feasst.PairLJMulti(s, s.minl()/2.0)
s.addMolInit(self.molA)
p.initLMPData(self.molA)
s.addMolInit(self.molB)
p.initLMPData(self.molB)
# Force-shift potential for each pair
p.rCutijset(0,0,(p.sig(0)+p.sig(0))/2*3.0)
p.rCutijset(0,1,(p.sig(0)+p.sig(1))/2*3.0)
p.rCutijset(1,1,(p.sig(1)+p.sig(1))/2*3.0)
p.setLambdaij(0,0, self.lam11)
p.setLambdaij(0,1, 0.5*(self.lamm11+self.lam22)) # LB mixing
p.setLambdaij(1,1, self.lam22)
p.lrcFlag = 0;
for i in range(2):
for j in range(2):
p.linearShiftijset(i,j,True)
s.updateCells(p.rCutMaxAll()) # intermolecular potential needs max rcut
ipair = feasst.PairHybrid (s, p.rCutMaxAll())
ipair.addPair(p)
ipair.initEnergy()
orderParam = "nmol"
beta = 1.0/self.temp
cc = feasst.CriteriaWLTMMC (beta, math.exp(beta*self.mu1), orderParam, self.orderMin-0.5*1.0, self.orderMax+0.5*1.0, self.orderMax-self.orderMin+1)
cc.addActivity(math.exp(beta*(self.mu1+self.dmu2)))
mc = feasst.WLTMMC (s, ipair, cc)
em = feasst.AnalyzeExtensiveMoments(s, ipair)
em.setOrderParam (self.order, cc)
mc.weight = 0.6
feasst.deleteTrial(mc, self.molA)
mc.weight = 0.6
feasst.deleteTrial(mc, self.molB)
mc.weight = 0.6
feasst.addTrial(mc, self.molA)
mc.weight = 0.6
feasst.addTrial(mc, self.molB)
mc.weight = 0.2
feasst.xswapTrial(mc)
mc.weight = 0.4
feasst.transformTrial(mc, "translate", 0.4)
mc.nMolSeek(self.orderMin, self.molA, 1000000) # mininum bound with pure A (smaller of the 2 species)
nfreq = 100000
mc.initLog("log", nfreq)
mc.initColMat("colMat", nfreq*1000)
mc.setNFreqCheckE(nfreq*1000, 1e-8)
mc.setNFreqTune(nfreq*1000)
mc.initMovie("movie", nfreq*1000)
mc.initRestart("tmp/rst", nfreq*1000)
em.initFreq(5) # from 1 -> 5 makes this as efficient as measuring 2nd vs 3rd order moments
em.initPrintFreq(nfreq*1000)
em.initFileName("extMom")
mc.initAnalyze(em)
cc.collectInit(4.0e-6) # start collecting TMMC matric at wlFlat == 18
cc.tmmcInit(5.0e-7) # switch to TMMC after 22
mc.wlFlatProduction(22) # after this number of iterations, switch to "production" phase and measure
mc.runNumTrials(self.steps)
em.write() # write at the end to ensure up-to-date
* Harold W. Hatch, [email protected] * * Permission to use this data/software is contingent upon your acceptance of * the terms of LICENSE.txt and upon your providing * appropriate acknowledgments of NIST's creation of the data/software. """ # # The following three lines are an alternative method to link _feasst.so # import os, sys # feasstdir = os.getenv("FEASST_INSTALL_DIR_") + "/build" # sys.path.append(feasstdir) import feasst feasst.ranInitByDate() space = feasst.makeSpace(3) space.initBoxLength(8) space.addMolInit("../forcefield/data.lj") pair = feasst.PairLJ(space, 3) # potential truncation at 3 pair.initEnergy() criteria = feasst.CriteriaMetropolis(1.2, 1.) # 1/kT = 1.2 mc = feasst.MC(space, pair, criteria) maxMoveParam = 0.1 feasst.transformTrial(mc, "translate", maxMoveParam) mc.nMolSeek(50) # add 50 particles mc.initLog("log", int(1e4)) mc.initMovie("movie", int(1e4)) mc.runNumTrials(int(1e6)) # mc.initWindows(1) # initialize parallel windows # mc.runNumSweeps(1, -1) # run until all windows sweep once
* http:#pages.nist.gov/feasst, National Institute of Standards and Technology * Harold W. Hatch, [email protected] * * Permission to use this data/software is contingent upon your acceptance of * the terms of LICENSE.txt and upon your providing * appropriate acknowledgments of NIST's creation of the data/software. """ import feasst space = feasst.Space(3) rho = 1e-3 # number density nMol = 500 # number of particles space.initBoxLength((float(nMol)/rho)**(1./3.)) # set the cubic PBCs pair = feasst.PairHardSphere(space) pair.initData(space.install_dir() + "/forcefield/data.atom") pair.initEnergy() criteria = feasst.CriteriaMetropolis(1., 1.) mc = feasst.MC(space, pair, criteria) feasst.transformTrial(mc, "translate", 0.1) mc.nMolSeek(nMol) mc.initLog("log", int(1e4)) mc.initMovie("movie", int(1e4)) mc.initRestart("tmp/rst", int(1e4)) mc.setNFreqTune(int(1e4)) mc.runNumTrials(int(1e7)) # run equilibration # Run the production simulation mc.runNumTrials(int(1e7))
