def guessts(coords1, coords2, pot):
from pygmin.optimize import lbfgs_py as quench
# from pygmin.mindist.minpermdist_stochastic import minPermDistStochastic as mindist
from pygmin.transition_states import NEB
from pygmin.systems import LJCluster
ret1 = quench(coords1, pot.getEnergyGradient)
ret2 = quench(coords2, pot.getEnergyGradient)
coords1 = ret1[0]
coords2 = ret2[0]
natoms = len(coords1) / 3
system = LJCluster(natoms)
mindist = system.get_mindist()
dist, coords1, coords2 = mindist(coords1, coords2)
print "dist", dist
print "energy coords1", pot.getEnergy(coords1)
print "energy coords2", pot.getEnergy(coords2)
from pygmin.transition_states import InterpolatedPath
neb = NEB(InterpolatedPath(coords1, coords2, 20), pot)
#neb.optimize(quenchParams={"iprint" : 1})
neb.optimize(iprint=-30, nsteps=100)
neb.MakeAllMaximaClimbing()
#neb.optimize(quenchParams={"iprint": 30, "nsteps":100})
for i in xrange(len(neb.energies)):
if (neb.isclimbing[i]):
coords = neb.coords[i, :]
return pot, coords, neb.coords[0, :], neb.coords[-1, :]
def guesstsATLJ():
from pygmin.potentials.ATLJ import ATLJ
pot = ATLJ(Z=2.)
a = 1.12 #2.**(1./6.)
theta = 60. / 360 * np.pi
coords1 = np.array([ 0., 0., 0., \
-a, 0., 0., \
-a/2, -a*np.cos(theta), 0. ])
coords2 = np.array([ 0., 0., 0., \
-a, 0., 0., \
a, 0., 0. ])
from pygmin.optimize import lbfgs_py as quench
from pygmin.transition_states import InterpolatedPath
ret1 = quench(coords1, pot.getEnergyGradient)
ret2 = quench(coords2, pot.getEnergyGradient)
coords1 = ret1[0]
coords2 = ret2[0]
from pygmin.transition_states import NEB
neb = NEB(InterpolatedPath(coords1, coords2, 30), pot)
neb.optimize()
neb.MakeAllMaximaClimbing()
#neb.optimize()
for i in xrange(len(neb.energies)):
if (neb.isclimbing[i]):
coords = neb.coords[i, :]
return pot, coords
