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
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 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
break
p2[:]=p2n
while True:
p2n = p2-n2
if(np.linalg.norm(p2n - p1) > np.linalg.norm(p2 - p1)):
break
p2[:]=p2n
defaults.NEBquenchParams["nsteps"]=2000
defaults.NEBquenchParams["maxErise"]=1e-1
defaults.NEBquenchParams["tol"]=1e-5
defaults.NEBquenchParams["iprint"]=1
defaults.NEBquenchParams["maxstep"]=.1
neb = NEB(path, pot, k=10., dneb=True, with_springenergy=True)
neb.optimize()
path = neb.coords
print np.linalg.norm(path[1] - path[0])
for x in neb.coords:
export_xyz(traj, x)
#np.savetxt("energies.txt", neb.energies)
import pylab as pl
pl.plot(neb.energies)
#pl.plot(e1)
#pl.plot(e2, "x")
pl.show()
defaults.NEBquenchParams["maxErise"] = 0.1
defaults.NEBquenchParams["tol"] = 1e-6
defaults.NEBquenchRoutine = mylbfgs
k = 10.
nimages=50
dneb=True
#print coords2[-6:],coords1[-6:]
path = tip4p.get_path(system, coords1, coords2, nimages)
path_energy = [pot.getEnergy(coords) for coords in path]
# try the old neb
dump_path("interpolate.xyz", system, path)
neb = NEB(path, pot, k=k, dneb=dneb, with_springenergy = False)
neb.optimize()
neb_1 = neb.copy()
dump_path("neb1.xyz", system, neb_1.coords)
neb.optimize()
neb_2 = neb
dump_path("neb2.xyz", system, neb_2.coords)
# try the new neb
aaneb = NEB(path, pot, distance=system.neb_distance, k=k/20., dneb=dneb, with_springenergy = False)
aaneb.optimize()
aaneb_1 = aaneb.copy()
dump_path("aaneb1.xyz", system, aaneb_1.coords)
aaneb.optimize()
aaneb_2 = aaneb
dump_path("aaneb2.xyz", system, aaneb_2.coords)
decp["local_connect_params"]["NEBparams"][
"NEBquenchRoutine"] = NEBquenchRoutine
k = 10.
nimages = 50
dneb = True
#print coords2[-6:],coords1[-6:]
path = tip4p.get_path(system, coords1, coords2, nimages)
path_energy = [pot.getEnergy(coords) for coords in path]
# try the old neb
dump_path("interpolate.xyz", system, path)
neb = NEB(path, pot, k=k, dneb=dneb, with_springenergy=False)
neb.optimize()
neb_1 = neb.copy()
dump_path("neb1.xyz", system, neb_1.coords)
neb.optimize()
neb_2 = neb
dump_path("neb2.xyz", system, neb_2.coords)
# try the new neb
aaneb = NEB(path,
pot,
distance=system.neb_distance,
k=k / 20.,
dneb=dneb,
with_springenergy=False)
aaneb.optimize()
aaneb_1 = aaneb.copy()
break
p2[:] = p2n
NEBquenchParams = dict()
NEBquenchParams["nsteps"] = 2000
NEBquenchParams["maxErise"] = 1e-1
NEBquenchParams["tol"] = 1e-5
NEBquenchParams["iprint"] = 1
NEBquenchParams["maxstep"] = .1
neb = NEB(path,
pot,
k=10.,
dneb=True,
with_springenergy=True,
quenchParams=NEBquenchParams)
neb.optimize()
path = neb.coords
print np.linalg.norm(path[1] - path[0])
for x in neb.coords:
export_xyz(traj, x)
#np.savetxt("energies.txt", neb.energies)
import pylab as pl
pl.plot(neb.energies)
#pl.plot(e1)
#pl.plot(e2, "x")
pl.show()
