def test1(self):
system = LJCluster(6)
ss0 = 1.
displace = RandomDisplacement(stepsize=ss0)
ts = AdaptiveStepsizeTemperature(displace, interval=10)
bh = system.get_basinhopping(takestep=ts)
bh.run(9)
self.assertAlmostEqual(displace.stepsize, ss0, 10)
bh.run(2)
self.assertNotAlmostEqual(displace.stepsize, ss0, 1)
def get_takestep(self, **kwargs):
"""return the takestep object for use in basinhopping, etc.
Notes
-----
default is random displacement with adaptive step size and
adaptive temperature
See Also
--------
pele.takestep
"""
kwargs = dict_copy_update(self.params["takestep"], kwargs)
try:
stepsize = kwargs.pop("stepsize")
except KeyError:
stepsize = 0.6
takeStep = RandomDisplacement(stepsize=stepsize)
tsAdaptive = AdaptiveStepsizeTemperature(takeStep, **kwargs)
return tsAdaptive
def bh_no_system_class():
import numpy as np
from pele.potentials import LJ
natoms = 17
potential = LJ()
x0 = np.random.uniform(-1, 1, 3*natoms)
from pele.takestep import RandomDisplacement, AdaptiveStepsizeTemperature
displace = RandomDisplacement()
adaptive_displacement = AdaptiveStepsizeTemperature(displace)
from pele.storage import Database
database = Database("lj17.sqlite")
from pele.basinhopping import BasinHopping
bh = BasinHopping(x0, potential, adaptive_displacement, storage=database.minimum_adder)
bh.run(10)
for m in database.minima():
print m.energy
def test_BH(self, db, nsteps):
self.potential = self.get_potential()
from pele.takestep import RandomDisplacement, AdaptiveStepsizeTemperature
takeStepRnd = RandomDisplacement(stepsize=2)
tsAdaptive = AdaptiveStepsizeTemperature(takeStepRnd,
interval=10,
verbose=True)
self.params.basinhopping["temperature"] = 10.0
# todo - how do you save N lowest?
bh = self.get_basinhopping(database=db, takestep=takeStepRnd)
bh = self.get_basinhopping(database=db, takestep=tsAdaptive)
print 'Running BH .. '
bh.run(nsteps)
print "Number of minima found = ", len(db.minima())
min0 = db.minima()[0]
print "lowest minimum found has energy = ", min0.energy
"""
Example 4: modify the parameters of the adaptive stepsize
note that the system class uses adaptive stepsize by default,
so the previous examples also use adaptive stepsize
"""
from __future__ import print_function
from pele.systems import LJCluster
from pele.takestep import RandomDisplacement, AdaptiveStepsizeTemperature
natoms = 12
niter = 100
system = LJCluster(natoms)
db = system.create_database()
# create takestep routine manually
step = RandomDisplacement(stepsize=0.3)
# wrap it in the class which will adaptively improve the stepsize
wrapped_step = AdaptiveStepsizeTemperature(step, interval=30)
bh = system.get_basinhopping(database=db, takestep=wrapped_step)
bh.run(niter)
print("the lowest energy found after", niter, " basinhopping steps is", db.minima()[0].energy)
print("")