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 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)
from lj_run import LJClusterNew
import sys
from pele.landscape import Graph
natoms = int(sys.argv[1])
dbname = sys.argv[2]
system = LJClusterNew(natoms)
db = system.create_database(dbname)
while True:
min1 = db.minima()[0]
graph = Graph(db)
all_connected = True
for m2 in db.minima()[1:]:
if not graph.areConnected(min1, m2):
all_connected = False
break
if all_connected:
print "minima are all connected, ending"
exit(1)
connect = system.get_double_ended_connect(min1, m2, db, fresh_connect=True, load_no_distances=True)
connect.connect()
def build_lj_nested_sampling(system, db):
from pele.takestep import RandomDisplacement
nreplicas = 20
mciter = 10000
nminima = 10000
minima = db.minima()
if len(minima) > nminima:
minima = minima[:nminima]
takestep = RandomDisplacement(stepsize=0.5)
accept_tests = system.get_config_tests()
ns = NestedSamplingBS(system,
nreplicas,
takestep,
minima,
mciter=mciter,
accept_tests=accept_tests)
return ns
if __name__ == "__main__":
from lj_run import LJClusterNew
natoms = 31
system = LJClusterNew(31)
dbname = "lj%d.db" % (natoms)
db = system.create_database(dbname)
ns = build_lj_nested_sampling(system, db)
run_gui(system, ns)
onset_prob = self.onset_prob_func(Emax)
prob = onset_prob / float(self.nreplicas)
for i in range(len(configs)):
if np.random.uniform(0, 1) < prob:
x, energy = self.get_starting_configuration_minima(Emax)
configs[i] = Replica(x, energy, from_random=False)
if self.verbose:
print "sampling from minima, E minimum:", energy, "with probability:", prob
return configs
if __name__ == "__main__":
# define the system
from lj_run import LJClusterNew
natoms = 13
system = LJClusterNew(natoms)
db = system.create_database("lj%d.db" % (natoms))
# if True:
# populate_database(system, db, niter=100)
print "pgorder", db.minima()[0].pgorder
print "fvib", db.minima()[0].fvib
get_thermodynamic_information(system, db)
print "pgorder", db.minima()[0].pgorder
print "fvib", db.minima()[0].fvib
Emin = db.minima()[0].energy
Emax = Emin + 1.
k = system.k
# refresh_timer.timeout.connect(refresh_pl)
# refresh_timer.start(0.)
#
# myapp.show()
# sys.exit(app.exec_())
def build_lj_nested_sampling(system, db):
from pele.takestep import RandomDisplacement
nreplicas = 20
mciter = 10000
nminima = 10000
minima = db.minima()
if len(minima) > nminima:
minima = minima[:nminima]
takestep = RandomDisplacement(stepsize=0.5)
accept_tests = system.get_config_tests()
ns = NestedSamplingBS(system, nreplicas, takestep, minima, mciter=mciter, accept_tests=accept_tests)
return ns
if __name__ == "__main__":
from lj_run import LJClusterNew
natoms = 31
system = LJClusterNew(31)
dbname = "lj%d.db" % (natoms)
db = system.create_database(dbname)
ns = build_lj_nested_sampling(system, db)
run_gui(system, ns)
from lj_run import LJClusterNew
import sys
from pele.landscape import Graph
natoms = int(sys.argv[1])
dbname = sys.argv[2]
system = LJClusterNew(natoms)
db = system.create_database(dbname)
while True:
min1 = db.minima()[0]
graph = Graph(db)
all_connected = True
for m2 in db.minima()[1:]:
if not graph.areConnected(min1, m2):
all_connected = False
break
if all_connected:
print "minima are all connected, ending"
exit(1)
connect = system.get_double_ended_connect(min1,
m2,
db,
fresh_connect=True,
load_no_distances=True)
connect.connect()
from pele.gui import run_gui from lj_run import LJClusterNew import sys natoms = int(sys.argv[1]) dbname = sys.argv[2] #natoms = 31 system = LJClusterNew(natoms) #label = "lj%d" % (natoms) #dbname = label + ".db" run_gui(system, dbname) #db = system.create_database(dbname)
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()
# from the minima with probability prob
onset_prob = self.onset_prob_func(Emax)
prob = onset_prob / float(self.nreplicas)
for i in range(len(configs)):
if np.random.uniform(0,1) < prob:
x, energy = self.get_starting_configuration_minima(Emax)
configs[i] = Replica(x, energy, from_random=False)
if self.verbose:
print "sampling from minima, E minimum:", energy, "with probability:", prob
return configs
if __name__ == "__main__":
# define the system
from lj_run import LJClusterNew
natoms = 13
system = LJClusterNew(natoms)
db = system.create_database("lj%d.db" % (natoms))
# if True:
# populate_database(system, db, niter=100)
print "pgorder", db.minima()[0].pgorder
print "fvib", db.minima()[0].fvib
get_thermodynamic_information(system, db)
print "pgorder", db.minima()[0].pgorder
print "fvib", db.minima()[0].fvib
Emin = db.minima()[0].energy
Emax = Emin + 1.
k = system.k
