def test():
from pygmin.systems import LJCluster
natoms = 13
system = LJCluster(natoms)
db = system.create_database()
# get some minima
bh = system.get_basinhopping(database=db, outstream=None)
bh.run(100)
manager = ConnectManager(db, clust_min=2)
for i in range(4):
min1, min2 = manager.get_connect_job(strategy="random")
print "connecting", min1._id, min2._id
connect = system.get_double_ended_connect(min1, min2, db, verbosity=0)
connect.connect()
print "\n\ntesting untrap"
for i in range(10):
min1, min2 = manager.get_connect_job(strategy="untrap")
print min1._id, min2._id
print "\n\ntesting combine"
for i in range(5):
min1, min2 = manager.get_connect_job(strategy="combine")
print min1._id, min2._id
print "\n\ntesting gmin"
for i in range(5):
min1, min2 = manager.get_connect_job(strategy="gmin")
print min1._id, min2._id
def test():
from pygmin.systems import LJCluster
natoms = 13
system = LJCluster(natoms)
db = system.create_database()
# get some minima
bh = system.get_basinhopping(database=db, outstream=None)
bh.run(100)
manager = ConnectManager(db, clust_min=2)
for i in range(4):
min1, min2 = manager.get_connect_job(strategy="random")
print "connecting", min1._id, min2._id
connect = system.get_double_ended_connect(min1, min2, db, verbosity=0)
connect.connect()
print "\n\ntesting untrap"
for i in range(10):
min1, min2 = manager.get_connect_job(strategy="untrap")
print min1._id, min2._id
print "\n\ntesting combine"
for i in range(5):
min1, min2 = manager.get_connect_job(strategy="combine")
print min1._id, min2._id
print "\n\ntesting gmin"
for i in range(5):
min1, min2 = manager.get_connect_job(strategy="gmin")
print min1._id, min2._id
def get_database(natoms=13, nconn=5):
"""create a database for a lennard jones system
fill it with minima from a basinhopping run, then connect
some of those minima using DoubleEndedConnect
"""
ljsys = LJCluster(natoms)
db = ljsys.create_database()
bh = ljsys.get_basinhopping(database=db, outstream=None)
while (len(db.minima()) < nconn + 1):
bh.run(100)
minima = list(db.minima())
m1 = minima[0]
for m2 in minima[1:nconn + 1]:
connect = ljsys.get_double_ended_connect(m1, m2, db)
connect.connect()
return db
def get_database(natoms=13, nconn=5):
"""create a database for a lennard jones system
fill it with minima from a basinhopping run, then connect
some of those minima using DoubleEndedConnect
"""
ljsys = LJCluster(natoms)
db = ljsys.create_database()
bh = ljsys.get_basinhopping(database=db, outstream=None)
while len(db.minima()) < nconn + 1:
bh.run(100)
minima = list(db.minima())
m1 = minima[0]
for m2 in minima[1 : nconn + 1]:
connect = ljsys.get_double_ended_connect(m1, m2, db)
connect.connect()
return db
#get some minima
if False:
bh = system.get_basinhopping(database=db)
bh.run(10)
minima = db.minima()
else:
x1, e1 = system.get_random_minimized_configuration()[:2]
x2, e2 = system.get_random_minimized_configuration()[:2]
min1 = db.addMinimum(e1, x1)
min2 = db.addMinimum(e2, x2)
minima = [min1, min2]
# connect some of the minima
nmax = min(3, len(minima))
m1 = minima[0]
for m2 in minima[1:nmax]:
connect = system.get_double_ended_connect(m1, m2, db)
connect.connect()
wnd = GraphViewDialog(db, app=app)
# decrunner = DECRunner(system, db, min1, min2, outstream=wnd.textEdit_writer)
glutInit()
wnd.show()
from PyQt4.QtCore import QTimer
QTimer.singleShot(10, start)
sys.exit(app.exec_())
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"
# connect all minima to the lowest minimum
print "now connecting all the minima to the lowest energy minimum"
m1 = db.minima()[0]
for m2 in db.minima()[1:]:
print "connecting minima with id's", m1._id, m2._id
connect = system.get_double_ended_connect(m1, m2, db)
connect.connect()
# print some data about the database
print "database summary:"
NEBparams.iter_density = 40
# Transition State Search parameters:
tsparams = decparams.local_connect_params.tsSearchParams
# change the maximum uphill step
tsparams.max_uphill_step = 0.05
# change the number of steps in the transverse minimization
tsparams.nsteps_tangent1 = 4
#
# done modifying parameters
#
# do the double ended connect run
connect = system.get_double_ended_connect(min1, min2, db)
connect.connect()
success = connect.success()
if not success:
print "failed to find connection"
else:
mints, S, energies = connect.returnPath()
nts = (len(mints) - 1) / 2
print "found a path with", nts, "transition states"
print "plotting energies along the path"
import pylab as pl
pl.plot(S, energies, "-")
pl.xlabel("distance along path")
pl.ylabel("energy")
NEBparams.iter_density = 40
# Transition State Search parameters:
tsparams = decparams.local_connect_params.tsSearchParams
# change the maximum uphill step
tsparams.max_uphill_step = .05
# change the number of steps in the transverse minimization
tsparams.nsteps_tangent1 = 4
#
# done modifying parameters
#
# do the double ended connect run
connect = system.get_double_ended_connect(min1, min2, db)
connect.connect()
success = connect.success()
if not success:
print "failed to find connection"
else:
mints, S, energies = connect.returnPath()
nts = (len(mints) - 1)/2
print "found a path with", nts, "transition states"
print "plotting energies along the path"
import pylab as pl
pl.plot(S, energies, '-')
pl.xlabel("distance along path")
pl.ylabel("energy")
pl.show()