import numpy as np from lj_run import LJClusterNew from pygmin.takestep import RandomDisplacement, AdaptiveStepsize, Reseeding if __name__ == "__main__": natoms = 75 system = LJClusterNew(natoms) ts = RandomDisplacement(stepsize=0.42) takestep = AdaptiveStepsize(ts) takestep = Reseeding(takestep,system.get_random_configuration(),maxnoimprove=80) label = "lj%d" % (natoms) dbname = label + ".db" db = system.create_database(dbname) bh = system.get_basinhopping(database=db, takestep=ts, temperature=0.45, insert_rejected=True) bh.run(1000000)
import numpy as np from src.runmc import mc_cython from lj_run import LJClusterNew, MonteCarloCompiled from nested_sampling import MonteCarloChain from pele.takestep import RandomDisplacement from pele.utils.xyz import write_xyz system = LJClusterNew(31) x = system.get_random_configuration() with open("test.xyz", "w") as fout: write_xyz(fout, x) mciter = 100000 stepsize = .01 Emax = 1e20 radius = 2.5 mcc = MonteCarloCompiled(system, radius) mcc(x.copy(), mciter, stepsize, Emax) print mcc.naccept, mcc.nsteps, mcc.energy takestep = RandomDisplacement(stepsize=stepsize) mc = MonteCarloChain(system.get_potential(), x.copy(), takestep, Emax, system.get_config_tests()) for i in xrange(mciter): mc.step() print mc.naccept, mc.nsteps, mc.energy
import numpy as np from src.runmc import mc_cython from lj_run import LJClusterNew, MonteCarloCompiled from nested_sampling import MonteCarloChain from pele.takestep import RandomDisplacement from pele.utils.xyz import write_xyz system = LJClusterNew(31) x = system.get_random_configuration() with open("test.xyz", "w") as fout: write_xyz(fout, x) mciter = 100000 stepsize = 0.01 Emax = 1e20 radius = 2.5 mcc = MonteCarloCompiled(system, radius) mcc(x.copy(), mciter, stepsize, Emax) print mcc.naccept, mcc.nsteps, mcc.energy takestep = RandomDisplacement(stepsize=stepsize) mc = MonteCarloChain(system.get_potential(), x.copy(), takestep, Emax, system.get_config_tests()) for i in xrange(mciter): mc.step()