def createBasinHopping(self):
GMIN.initialize()
pot = gminpot.GMINPotental(GMIN)
coords = pot.getCoords()
step = displace.RandomDisplacement()
opt = bh.BasinHopping(coords, pot, takeStep=step, temperature=0.4, storage=self.storage)
return opt
def __init__(self, pot, T=10., nsteps=100, stepsize=0.1):
self.potential = pot
self.T = T
self.nsteps = nsteps
self.mcstep = displace.RandomDisplacement(stepsize=stepsize)
import numpy as np
import oxdnagmin_ as GMIN
from pele.potentials.gminpotential import GMINPotential
import pele.basinhopping as bh
from pele.takestep import displace
from pele.storage.database import Database
# initialize GMIN
GMIN.initialize()
# create a potential which calls GMIN
potential = GMINPotential(GMIN)
# get the initial coorinates
coords = potential.getCoords()
coords = np.random.random(coords.shape)
# create takestep routine
step = displace.RandomDisplacement(stepsize=1.)
# store all minima in a database
db = Database(db="storage.sqlite", accuracy=1e-2)
# create Basinhopping object
opt = bh.BasinHopping(coords, potential, step, db.minimum_adder())
# run for 100 steps
opt.run(1000)
# now dump all the minima
i = 0
for m in db.minima():
i += 1
GMIN.userpot_dump("lowest_%03d.dat" % (i), m.coords)
temperature=self.T,
outstream=None)
mc.run(self.nsteps)
coords[:] = mc.coords[:]
def updateStep(self, acc, **kwargs):
pass
natoms = 12
# random initial coordinates
coords = np.random.random(3 * natoms)
potential = lj.LJ()
reseed = TakeStepMonteCarlo(potential, T=100, nsteps=1000)
takestep = displace.RandomDisplacement(stepsize=0.5)
stepGroup = group.Reseeding(takestep, reseed, maxnoimprove=20)
opt = bh.BasinHopping(coords, potential, takeStep=stepGroup)
opt.run(100)
# some visualization
try:
import pele.utils.pymolwrapper as pym
pym.start()
pym.draw_spheres(opt.coords, "A", 1)
except:
print "Could not draw using pymol, skipping this step"
