def runptmc(nsteps_tot = 100000): natoms = 31 nreplicas = 4 Tmin = 0.2 Tmax = 0.4 nsteps_equil = 10000 nsteps_tot = 100000 histiprint = nsteps_tot / 10 exchange_frq = 100*nreplicas coords=np.random.random(3*natoms) #quench the coords so we start from a reasonable location mypot = lj.LJ() ret = quench(coords, mypot.getEnergyGradient) coords = ret[0] Tlist = getTemps(Tmin, Tmax, nreplicas) replicas = [] ostreams = [] histograms = [] takesteplist = [] radius = 2.5 for i in range(nreplicas): T = Tlist[i] potential = lj.LJ() takestep = RandomDisplacement( stepsize=0.01) adaptive = AdaptiveStepsize(takestep, last_step = nsteps_equil) takesteplist.append( adaptive ) file = "mcout." + str(i+1) ostream = open(file, "w") hist = EnergyHistogram( -134., 10., 1000) histograms.append(hist) event_after_step=[hist] radiustest = SphericalContainer(radius) accept_tests = [radiustest] mc = MonteCarlo(coords, potential, takeStep=takestep, temperature=T, \ outstream=ostream, event_after_step = event_after_step, \ confCheck = accept_tests) mc.histogram = hist #for convienence mc.printfrq = 1 replicas.append(mc) #is it possible to pickle a mc object? #cp = copy.deepcopy(replicas[0]) #import pickle #with open("mc.pickle", "w") as fout: #pickle.dump(takesteplist[0], fout) #attach an event to print xyz coords from pygmin.printing.print_atoms_xyz import PrintEvent printxyzlist = [] for n, rep in enumerate(replicas): outf = "dumpstruct.%d.xyz" % (n+1) printxyz = PrintEvent(outf, frq=500) printxyzlist.append( printxyz) rep.addEventAfterStep(printxyz) #attach an event to print histograms for n, rep in enumerate(replicas): outf = "hist.%d" % (n+1) histprint = PrintHistogram(outf, rep.histogram, histiprint) rep.addEventAfterStep(histprint) ptmc = PTMC(replicas) ptmc.use_independent_exchange = True ptmc.exchange_frq = exchange_frq ptmc.run(nsteps_tot) #do production run #fix the step sizes #for takestep in takesteplist: # takestep.useFixedStep() #ptmc.run(30000) if False: #this doesn't work print "final energies" for rep in ptmc.replicas: print rep.temperature, rep.markovE for rep in ptmc.replicas_par: print rep.mcsys.markovE for k in range(nreplicas): e,T = ptmc.getRepEnergyT(k) print T, e if False: #this doesn't work print "histograms" for i,hist in enumerate(histograms): fname = "hist." + str(i) print fname with open(fname, "w") as fout: for (e, visits) in hist: fout.write( "%g %d\n" % (e, visits) ) ptmc.end() #close the open threads
def runptmc(nsteps_tot=100000): natoms = 31 nreplicas = 4 Tmin = 0.2 Tmax = 0.4 nsteps_equil = 10000 nsteps_tot = 100000 histiprint = nsteps_tot / 10 exchange_frq = 100 * nreplicas coords = np.random.random(3 * natoms) #quench the coords so we start from a reasonable location mypot = lj.LJ() ret = quench(coords, mypot) coords = ret.coords Tlist = getTemps(Tmin, Tmax, nreplicas) replicas = [] ostreams = [] histograms = [] takesteplist = [] radius = 2.5 # create all the replicas which will be passed to PTMC for i in range(nreplicas): T = Tlist[i] potential = lj.LJ() takestep = RandomDisplacement(stepsize=0.01) adaptive = AdaptiveStepsize(takestep, last_step=nsteps_equil) takesteplist.append(adaptive) file = "mcout." + str(i + 1) ostream = open(file, "w") hist = EnergyHistogram(-134., 10., 1000) histograms.append(hist) event_after_step = [hist] radiustest = SphericalContainer(radius) accept_tests = [radiustest] mc = MonteCarlo(coords, potential, takeStep=takestep, temperature=T, \ outstream=ostream, event_after_step = event_after_step, \ confCheck = accept_tests) mc.histogram = hist #for convienence mc.printfrq = 1 replicas.append(mc) #is it possible to pickle a mc object? #cp = copy.deepcopy(replicas[0]) #import pickle #with open("mc.pickle", "w") as fout: #pickle.dump(takesteplist[0], fout) #attach an event to print xyz coords from pygmin.printing.print_atoms_xyz import PrintEvent printxyzlist = [] for n, rep in enumerate(replicas): outf = "dumpstruct.%d.xyz" % (n + 1) printxyz = PrintEvent(outf, frq=500) printxyzlist.append(printxyz) rep.addEventAfterStep(printxyz) #attach an event to print histograms for n, rep in enumerate(replicas): outf = "hist.%d" % (n + 1) histprint = PrintHistogram(outf, rep.histogram, histiprint) rep.addEventAfterStep(histprint) ptmc = PTMC(replicas) ptmc.use_independent_exchange = True ptmc.exchange_frq = exchange_frq ptmc.run(nsteps_tot) #do production run #fix the step sizes #for takestep in takesteplist: # takestep.useFixedStep() #ptmc.run(30000) if False: #this doesn't work print "final energies" for rep in ptmc.replicas: print rep.temperature, rep.markovE for rep in ptmc.replicas_par: print rep.mcsys.markovE for k in range(nreplicas): e, T = ptmc.getRepEnergyT(k) print T, e if False: #this doesn't work print "histograms" for i, hist in enumerate(histograms): fname = "hist." + str(i) print fname with open(fname, "w") as fout: for (e, visits) in hist: fout.write("%g %d\n" % (e, visits)) ptmc.end() #close the open threads