def setUp(self):
from pygmin.landscape import DoubleEndedConnect
from pygmin.landscape._graph import create_random_database
from pygmin.systems import LJCluster
# from pygmin.mindist import minPermDistStochastic, MinDistWrapper
# from pygmin.potentials import LJ
nmin = 10
natoms = 13
sys = LJCluster(natoms)
pot = sys.get_potential()
mindist = sys.get_mindist()
db = create_random_database(nmin=nmin, natoms=natoms, nts=nmin / 2)
min1, min2 = list(db.minima())[:2]
connect = DoubleEndedConnect(min1,
min2,
pot,
mindist,
db,
use_all_min=True,
merge_minima=True,
max_dist_merge=1e100)
self.connect = connect
self.db = db
self.natoms = natoms
def setUp(self):
from pygmin.landscape import DoubleEndedConnect
from pygmin.landscape._graph import create_random_database
from pygmin.systems import LJCluster
# from pygmin.mindist import minPermDistStochastic, MinDistWrapper
# from pygmin.potentials import LJ
nmin = 10
natoms=13
sys = LJCluster(natoms)
pot = sys.get_potential()
mindist = sys.get_mindist()
db = create_random_database(nmin=nmin, natoms=natoms, nts=nmin/2)
min1, min2 = list(db.minima())[:2]
connect = DoubleEndedConnect(min1, min2, pot, mindist, db, use_all_min=True,
merge_minima=True, max_dist_merge=1e100)
self.connect = connect
self.db = db
self.natoms = natoms
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 test(Connect=DoubleEndedConnect, natoms=16):
# from pygmin.landscape import Graph
# from pygmin.storage.database import Database
from pygmin.systems import LJCluster
#get min1
system = LJCluster(natoms)
pot, database = getSetOfMinLJ(system)
# from pygmin.potentials.lj import LJ
# pot = LJ()
# saveit = Database(db="test.db")
minima = database.minima()
min1 = minima[0]
min2 = minima[1]
print min1.energy, min2.energy
mindist = system.get_mindist()
if False:
#test to see if min1 and min2 are already connected
connected = graph.areConnected(min1, min2)
print "at start are minima connected?", connected
return
connect = Connect(min1, min2, pot, mindist, database)
connect.connect()
graph = connect.graph
if False:
print graph
for node in graph.graph.nodes():
print node._id, node.energy
for ts in graph.storage.transition_states():
print ts.minimum1._id,ts.minimum2._id, "E", ts.minimum1.energy, ts.minimum2.energy, ts.energy
ret = graph.getPath(min1, min2)
if ret is None:
print "no path found"
return
distances, path = ret
with open("path.out", "w") as fout:
for i in range(len(path)-1):
m1 = path[i]
m2 = path[i+1]
n1 = m1._id
m2 = m2._id
# ts = graph._getTS(n1, n2)
# print "path", n1, "->", n2, m1.E, "/->", ts.E, "\->", m2.E
fout.write("%f\n" % m1.energy)
fout.write("%f\n" % ts.energy)
m2 = path[-1]
n2 = m2._id
fout.write("%f\n" % m2.energy)
def getPairLJ(natoms=38):
from pygmin.systems import LJCluster
system = LJCluster(natoms)
ret1 = system.get_random_minimized_configuration()
ret2 = system.get_random_minimized_configuration()
coords1, coords2 = ret1[0], ret2[0]
E1, E2 = ret1[1], ret2[1]
mindist = system.get_mindist()
mindist(coords1, coords2)
return coords1, coords2, system.get_potential(), mindist, E1, E2
def getPairLJ(natoms=38):
from pygmin.systems import LJCluster
system = LJCluster(natoms)
ret1 = system.get_random_minimized_configuration()
ret2 = system.get_random_minimized_configuration()
coords1, coords2 = ret1[0], ret2[0]
E1, E2 = ret1[1], ret2[1]
mindist = system.get_mindist()
mindist(coords1, coords2)
return coords1, coords2, system.get_potential(), mindist, E1, E2
def test(Connect=DoubleEndedConnect, natoms=16):
# from pygmin.landscape import TSGraph
# from pygmin.storage.database import Database
from pygmin.systems import LJCluster
#get min1
system = LJCluster(natoms)
pot, database = getSetOfMinLJ(system)
# from pygmin.potentials.lj import LJ
# pot = LJ()
# saveit = Database(db="test.db")
minima = database.minima()
min1 = minima[0]
min2 = minima[1]
print min1.energy, min2.energy
mindist = system.get_mindist()
if False:
#test to see if min1 and min2 are already connected
connected = graph.areConnected(min1, min2)
print "at start are minima connected?", connected
return
connect = Connect(min1, min2, pot, mindist, database)
connect.connect()
graph = connect.graph
if False:
print graph
for node in graph.graph.nodes():
print node._id, node.energy
for ts in graph.storage.transition_states():
print ts.minimum1._id, ts.minimum2._id, "E", ts.minimum1.energy, ts.minimum2.energy, ts.energy
ret = graph.getPath(min1, min2)
if ret is None:
print "no path found"
return
distances, path = ret
with open("path.out", "w") as fout:
for i in range(len(path) - 1):
m1 = path[i]
m2 = path[i + 1]
n1 = m1._id
m2 = m2._id
# ts = graph._getTS(n1, n2)
# print "path", n1, "->", n2, m1.E, "/->", ts.E, "\->", m2.E
fout.write("%f\n" % m1.energy)
fout.write("%f\n" % ts.energy)
m2 = path[-1]
n2 = m2._id
fout.write("%f\n" % m2.energy)
# do a basinhopping run to find the global minimum and build up the database of minima
bh = system.get_basinhopping(database=db, outstream=None)
niter = 20
bh.run(niter)
print "the lowest energy found after", niter, " basinhopping steps is", db.minima(
)[0].energy
# print the energies of all the minima found
print "the minima in the database have energies"
for minimum in db.minima():
print " ", minimum.energy
# find the minimum distance (a.k.a. mindist) between the two lowest minima
m1, m2 = db.minima()[:2]
mindist = system.get_mindist()
dist, coords1, coords2 = mindist(m1.coords, m2.coords)
print "the minimum distance between the two lowest minima is", dist
# find a connected series of minima and transition states between m1 and m2
#
# first use the logging module to turn off the status messages
logger = logging.getLogger("pygmin.connect")
logger.setLevel("WARNING")
# now create the double ended connect object
connect = system.get_double_ended_connect(m1, m2, db)
connect.connect()
mints, S, energies = connect.returnPath()
nts = (len(mints) - 1) / 2
print "\nprint found a connection with", nts, "transition states"
minimum2 = db.addMinimum(e2, coords2)
# do a basinhopping run to find the global minimum and build up the database of minima
bh = system.get_basinhopping(database=db, outstream=None)
niter = 20
bh.run(niter)
print "the lowest energy found after", niter, " basinhopping steps is", db.minima()[0].energy
# print the energies of all the minima found
print "the minima in the database have energies"
for minimum in db.minima():
print " ", minimum.energy
# find the minimum distance (a.k.a. mindist) between the two lowest minima
m1, m2 = db.minima()[:2]
mindist = system.get_mindist()
dist, coords1, coords2 = mindist(m1.coords, m2.coords)
print "the minimum distance between the two lowest minima is", dist
# find a connected series of minima and transition states between m1 and m2
#
# first use the logging module to turn off the status messages
logger = logging.getLogger("pygmin.connect")
logger.setLevel("WARNING")
# now create the double ended connect object
connect = system.get_double_ended_connect(m1, m2, db)
connect.connect()
mints, S, energies = connect.returnPath()
nts = (len(mints) - 1)/2
print "\nprint found a connection with", nts, "transition states"
