def test():
from pele.systems import LJCluster
from pele.landscape import ConnectManager
system = LJCluster(13)
db = system.create_database()
bh = system.get_basinhopping(db, outstream=None)
bh.run(200)
manager = ConnectManager(db)
for i in range(3):
min1, min2 = manager.get_connect_job()
connect = system.get_double_ended_connect(min1, min2, db)
connect.connect()
# get_thermodynamic_information(system, db)
print "getting thermodynamic info", db.number_of_minima()
get_thermodynamic_information(system, db, nproc=4)
for m in db.minima():
print m.id(), m.pgorder, m.fvib
print "\nnow transition states"
for ts in db.transition_states():
print ts.id(), ts.pgorder, ts.fvib
class TestFindTransitionState_NFEV(unittest.TestCase):
def setUp(self):
from pele.optimize.tests.test_nfev import _PotWrapper
np.random.seed(0)
self.system = LJCluster(18)
self.pot = _PotWrapper(self.system.get_potential())
self.x = self.system.get_random_minimized_configuration(tol=10.).coords
def do_check(self, **kwargs):
self.pot.nfev = 0
opt = FindTransitionState(self.x, self.pot, **kwargs)
ret = opt.run()
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertTrue(ret.success)
self.assertGreater(ret.nfev, 0)
def test(self):
self.do_check()
# def test1(self):
# self.do_check(invert_gradient=True)
def test2(self):
self.do_check(lowestEigenvectorQuenchParams=dict(first_order=True)
)
def setUp(self):
nmin = 10
natoms = 13
sys = LJCluster(natoms)
pot = sys.get_potential()
mindist = sys.get_mindist()
db = create_random_database(nmin=nmin,
natoms=natoms,
nts=old_div(nmin, 2))
min1, min2 = list(db.minima())[:2]
self.db = db
self.natoms = natoms
self.connect = DoubleEndedConnect(min1,
min2,
pot,
mindist,
db,
merge_minima=True,
max_dist_merge=1e100)
# for ts in db.transition_states():
# self.add_ts(ts.energy, ts.coords,
# ts.minimum1.energy, ts.minimum1.coords,
# ts.minimum2.energy, ts.minimum2.coords)
for m in db.minima():
self.connect.dist_graph.addMinimum(m)
def setUp(self):
natoms = 18
self.system = LJCluster(natoms)
self.pot = self.system.get_potential()
self.evec = vec_random_ndim(3 * natoms)
self.evec /= np.linalg.norm(self.evec)
self.x = self.system.get_random_configuration()
def setUp(self, **kwargs):
from pele.optimize.tests.test_nfev import _PotWrapper
natoms = 18
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(
tol=100.).coords
self.pot = _PotWrapper(self.system.get_potential())
class TestFindTransitionState_NFEV(unittest.TestCase):
def setUp(self):
from pele.optimize.tests.test_nfev import _PotWrapper
np.random.seed(0)
self.system = LJCluster(18)
self.pot = _PotWrapper(self.system.get_potential())
self.x = self.system.get_random_minimized_configuration(tol=10.).coords
def do_check(self, **kwargs):
self.pot.nfev = 0
opt = FindTransitionState(self.x, self.pot, **kwargs)
ret = opt.run()
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertTrue(ret.success)
self.assertGreater(ret.nfev, 0)
def test(self):
self.do_check()
# def test1(self):
# self.do_check(invert_gradient=True)
def test2(self):
self.do_check(lowestEigenvectorQuenchParams=dict(first_order=True))
class TestGeneralizedDimer(unittest.TestCase):
def setUp(self):
self.system = LJCluster(18)
self.pot = self.system.get_potential()
def make_dimer(self, x):
return GeneralizedDimer(x, self.pot,
leig_kwargs=dict(orthogZeroEigs=self.system.get_orthogonalize_to_zero_eigenvectors()
) ,
)
def test1(self):
x = self.system.get_random_configuration()
dimer = self.make_dimer(x)
res = dimer.run()
self.assertTrue(res.success)
def test2(self):
# get the path of the file directory
path = os.path.dirname(os.path.abspath(__file__))
xyz = read_xyz(open(path+"/lj18_ts.xyz", "r"))
x = xyz.coords.flatten()
dimer = self.make_dimer(x)
res = dimer.run()
self.assertTrue(res.success)
self.assertLess(res.nsteps, 5)
def test1(self):
natoms = 13
system = LJCluster(natoms)
ts1 = RDWrap()
ts2 = RDWrap()
ts = BlockMoves()
n1 = 3
n2 = 5
ts.addBlock(n1, ts1)
ts.addBlock(n2, ts2)
bh = system.get_basinhopping(takestep=ts)
bh.run(n1)
self.assertEqual(ts1.count, n1)
self.assertEqual(ts2.count, 0)
bh.run(n2)
self.assertEqual(ts1.count, n1)
self.assertEqual(ts2.count, n2)
bh.run(n1 + n2)
self.assertEqual(ts1.count, 2 * n1)
self.assertEqual(ts2.count, 2 * n2)
bh.run(5 * (n1 + n2) - 1)
self.assertEqual(ts1.count, 7 * n1)
self.assertEqual(ts2.count, 7 * n2 - 1)
def test1(self):
# lj cluster with 4 atoms has only one minimum
natoms = 4
system = LJCluster(natoms)
ts1 = RDWrap()
reseed = RDWrap()
maxnoimprove = 20
ts = Reseeding(ts1, reseed, maxnoimprove=maxnoimprove)
bh = system.get_basinhopping(takestep=ts)
bh.run(1) # find the global minimum
bh.run(maxnoimprove - 1)
self.assertEqual(reseed.count, 0)
self.assertEqual(ts1.count, maxnoimprove)
bh.run(1)
self.assertEqual(reseed.count, 1)
self.assertEqual(ts1.count, maxnoimprove)
bh.run(maxnoimprove - 1)
self.assertEqual(reseed.count, 1)
self.assertEqual(ts1.count, 2 * maxnoimprove - 1)
bh.run(1)
self.assertEqual(reseed.count, 2)
self.assertEqual(ts1.count, 2 * maxnoimprove - 1)
def setUp1(self, verbose=False, **kwargs):
np.random.seed(0)
natoms = 18
self.system = LJCluster(natoms)
self.pot = self.system.get_potential()
x = self.system.get_random_configuration()
ret = lbfgs_py(x, self.pot, tol=10)
self.x = ret.coords
self.kwargs = kwargs
self.verbose = verbose
self.M = 4
if self.verbose: iprint = 1
else: iprint = -1
self.myo = MYLBFGS(self.x,
self.pot,
iprint=iprint,
debug=True,
M=self.M)
self.o = LBFGS(self.x,
self.pot,
iprint=iprint,
debug=True,
M=self.M,
**self.kwargs)
def bh_with_system_class():
from pele.systems import LJCluster
natoms = 17
system = LJCluster(natoms)
database = system.create_database('lj17.sqlite')
bh = system.get_basinhopping(database)
bh.run(10)
def main():
parser = argparse.ArgumentParser(
description="do nested sampling on a Lennard Jones cluster")
parser.add_argument("natoms", type=int, help="number of atoms")
parser.add_argument("db", type=str, help="location of the database")
parser.add_argument("--normalmodes",
type=str,
help="store the full normalmodes as well")
args = parser.parse_args()
system = LJCluster(args.natoms, )
if False:
# build the database
database = system.create_database(args.db, createdb=True)
bh = system.get_basinhopping(database)
bh.run(1000)
else:
database = system.create_database(args.db, createdb=False)
assert database.number_of_minima() > 0
print "computing the vibrational free energy and the point group order"
get_thermodynamic_information(system, database)
print "computing the normal modes"
get_all_normalmodes(system, database)
def guessts(coords1, coords2, pot):
from pele.optimize import lbfgs_py as quench
# from pele.mindist.minpermdist_stochastic import minPermDistStochastic as mindist
from pele.transition_states import NEB
from pele.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 pele.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():
from pele.systems import LJCluster
from pele.landscape import ConnectManager
system = LJCluster(13)
db = system.create_database()
bh = system.get_basinhopping(db, outstream=None)
bh.run(200)
manager = ConnectManager(db)
for i in range(3):
min1, min2 = manager.get_connect_job()
connect = system.get_double_ended_connect(min1, min2, db)
connect.connect()
# get_thermodynamic_information(system, db)
print "getting thermodynamic info", db.number_of_minima()
get_thermodynamic_information(system, db, nproc=4)
for m in db.minima():
print m._id, m.pgorder, m.fvib
print "\nnow transition states"
for ts in db.transition_states():
print ts._id, ts.pgorder, ts.fvib
def test(): # pragma: no cover
from pele.systems import LJCluster
natoms = 30
system = LJCluster(natoms)
pot = system.get_potential()
coords = system.get_random_configuration()
xmin = system.get_random_minimized_configuration()[0]
e, g, h = pot.getEnergyGradientHessian(xmin)
evals = get_eigvals(h)
print(evals)
quencher = system.get_minimizer(tol=10.)
coords = quencher(coords)[0]
e, g, h = pot.getEnergyGradientHessian(coords)
w1, v1 = get_smallest_eig(h)
print(w1)
w, v = get_smallest_eig_arpack(h)
print(w)
w2, v2 = get_smallest_eig_sparse(h)
print(w2, w2 / w1)
w3, v3 = get_smallest_eig_nohess(coords, system)
print(w3, w3 / w1)
# plot_hist(h)
# exit()
if False:
n = 10
while n < 500:
size_scaling_smallest_eig(int(n))
n *= 1.2
def setUp(self):
# from pele.mindist import minPermDistStochastic, MinDistWrapper
# from pele.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]
self.db = db
self.natoms = natoms
self.connect = DoubleEndedConnect(min1, min2, pot, mindist, db,
merge_minima=True, max_dist_merge=1e100)
# for ts in db.transition_states():
# self.add_ts(ts.energy, ts.coords,
# ts.minimum1.energy, ts.minimum1.coords,
# ts.minimum2.energy, ts.minimum2.coords)
for m in db.minima():
self.connect.dist_graph.addMinimum(m)
class TestFindLowestEigenvector(unittest.TestCase):
def setUp(self):
self.setUp1()
def setUp1(self, **kwargs):
natoms = 18
# s = LJCluster(natoms)
# nfrozen = 6
# reference_coords = s.get_random_configuration()
# self.system = LJClusterFrozen(13, range(nfrozen), reference_coords)
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(tol=100.).coords
self.pot = self.system.get_potential()
self.finder = FindLowestEigenVector(self.x.copy(), self.pot, **kwargs)
def test(self):
lval, lvec = analyticalLowestEigenvalue(self.x, self.pot)
ret = self.finder.run(100)
self.assertLess(np.abs(ret.eigenval - lval) / np.abs(lval), 1e-2)
def test2(self):
lval, lvec = analyticalLowestEigenvalue(self.x, self.pot)
ret = findLowestEigenVector(self.x.copy(), self.pot)
self.assertLess(np.abs(ret.eigenval - lval) / np.abs(lval), 1e-2)
def test1(self):
natoms = 13
system = LJCluster(natoms)
ts1 = RDWrap()
ts2 = RDWrap()
ts = BlockMoves()
n1 = 3
n2 = 5
ts.addBlock(n1, ts1)
ts.addBlock(n2, ts2)
bh = system.get_basinhopping(takestep=ts)
bh.run(n1)
self.assertEqual(ts1.count, n1)
self.assertEqual(ts2.count, 0)
bh.run(n2)
self.assertEqual(ts1.count, n1)
self.assertEqual(ts2.count, n2)
bh.run(n1 + n2)
self.assertEqual(ts1.count, 2*n1)
self.assertEqual(ts2.count, 2*n2)
bh.run(5*(n1 + n2) - 1)
self.assertEqual(ts1.count, 7*n1)
self.assertEqual(ts2.count, 7*n2 - 1)
def test1(self):
# lj cluster with 4 atoms has only one minimum
natoms = 4
system = LJCluster(natoms)
ts1 = RDWrap()
reseed = RDWrap()
maxnoimprove = 20
ts = Reseeding(ts1, reseed, maxnoimprove=maxnoimprove)
bh = system.get_basinhopping(takestep=ts)
bh.run(1) # find the global minimum
bh.run(maxnoimprove - 1)
self.assertEqual(reseed.count, 0)
self.assertEqual(ts1.count, maxnoimprove)
bh.run(1)
self.assertEqual(reseed.count, 1)
self.assertEqual(ts1.count, maxnoimprove)
bh.run(maxnoimprove-1)
self.assertEqual(reseed.count, 1)
self.assertEqual(ts1.count, 2*maxnoimprove-1)
bh.run(1)
self.assertEqual(reseed.count, 2)
self.assertEqual(ts1.count, 2*maxnoimprove-1)
def main():
parser = argparse.ArgumentParser(description="do nested sampling on a Lennard Jones cluster")
parser.add_argument("natoms", type=int, help="number of atoms")
parser.add_argument("db", type=str, help="location of the database")
parser.add_argument("--normalmodes", type=str, help="store the full normalmodes as well")
args = parser.parse_args()
system = LJCluster(args.natoms,)
if False:
# build the database
database = system.create_database(args.db, createdb=True)
bh = system.get_basinhopping(database)
bh.run(1000)
else:
database = system.create_database(args.db, createdb=False)
assert database.number_of_minima() > 0
print "computing the vibrational free energy and the point group order"
get_thermodynamic_information(system, database)
print "computing the normal modes"
get_all_normalmodes(system, database)
def test():
from pele.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 setUp(self):
current_dir = os.path.dirname(__file__)
dbfname = os.path.join(current_dir, "lj15.sqlite")
print(dbfname)
self.system = LJCluster(15)
self.system.params.structural_quench_params.tol = 1e-6
self.db = self.system.create_database(dbfname, createdb=False)
def test(): # pragma: no cover
from pele.systems import LJCluster
from pele.transition_states import GeneralizedDimer
from pele.transition_states import FindTransitionState
from pele.utils.xyz import read_xyz
system = LJCluster(13)
x = system.get_random_configuration()
x = read_xyz(open("tests/lj18_ts.xyz", "r")).coords.flatten()
dimer = GeneralizedDimer(x.copy(), system.get_potential(),
rotational_steps=40,
dimer=False,
leig_kwargs=dict(iprint=10, maxstep=2.,
tol=.1,
),
translator_kwargs=dict(iprint=1,
verbosity=10,
),
)
ret = dimer.run()
print(ret)
print("\n\nnow the same with the old version")
searcher = FindTransitionState(x.copy(), system.get_potential(), iprint=1, verbosity=10)
# print ret
ret = searcher.run()
print(ret)
class TestFindLowestEigenvector(unittest.TestCase):
def setUp(self):
self.setUp1()
def setUp1(self, **kwargs):
natoms = 18
# s = LJCluster(natoms)
# nfrozen = 6
# reference_coords = s.get_random_configuration()
# self.system = LJClusterFrozen(13, range(nfrozen), reference_coords)
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(
tol=100.).coords
self.pot = self.system.get_potential()
self.finder = FindLowestEigenVector(self.x.copy(), self.pot, **kwargs)
def test(self):
lval, lvec = analyticalLowestEigenvalue(self.x, self.pot)
ret = self.finder.run(100)
self.assertLess(np.abs(ret.eigenval - lval) / np.abs(lval), 1e-2)
def test2(self):
lval, lvec = analyticalLowestEigenvalue(self.x, self.pot)
ret = findLowestEigenVector(self.x.copy(), self.pot)
self.assertLess(np.abs(ret.eigenval - lval) / np.abs(lval), 1e-2)
class TestGeneralizedDimer(unittest.TestCase):
def setUp(self):
self.system = LJCluster(18)
self.pot = self.system.get_potential()
def make_dimer(self, x):
return GeneralizedDimer(
x,
self.pot,
leig_kwargs=dict(orthogZeroEigs=self.system.
get_orthogonalize_to_zero_eigenvectors()),
)
def test1(self):
x = self.system.get_random_configuration()
dimer = self.make_dimer(x)
res = dimer.run()
self.assertTrue(res.success)
def test2(self):
# get the path of the file directory
path = os.path.dirname(os.path.abspath(__file__))
xyz = read_xyz(open(path + "/lj18_ts.xyz", "r"))
x = xyz.coords.flatten()
dimer = self.make_dimer(x)
res = dimer.run()
self.assertTrue(res.success)
self.assertLess(res.nsteps, 5)
def prepare_system(self, frozen_atoms=[0, 2, 4]):
self.natoms = 13
fsys = LJCluster(self.natoms)
self.reference_coords = fsys.get_random_configuration()
self.system = LJClusterFrozen(self.natoms, frozen_atoms, self.reference_coords)
def setUp(self):
import pele.rates.tests.__init__ as f
dirname = os.path.dirname(f.__file__)
dbfname = os.path.join(dirname, "lj15.sqlite")
if not os.path.exists(dbfname):
raise IOError("database file %s does not exist" % dbfname)
self.system = LJCluster(15)
self.db = self.system.create_database(dbfname, createdb=False)
def prepare_system(self, frozen_atoms=None):
if not frozen_atoms: frozen_atoms = [0, 2, 4]
self.natoms = 13
fsys = LJCluster(self.natoms)
self.reference_coords = fsys.get_random_configuration()
self.system = LJClusterFrozen(self.natoms, frozen_atoms, self.reference_coords)
def test1(self):
system = LJCluster(6)
ss0 = 1.
displace = RandomDisplacement(stepsize=ss0)
ts = AdaptiveStepsize(displace, interval=10)
bh = system.get_basinhopping(takestep=ts)
bh.run(9)
self.assertAlmostEqual(displace.stepsize, ss0, 10)
bh.run(2)
self.assertNotAlmostEqual(displace.stepsize, ss0, 1)
def setUp(self):
import pele.rates.tests.__init__ as f
dirname = os.path.dirname(f.__file__)
dbfname = os.path.join(dirname, "lj15.{}.sqlite".format(sys.version_info.major))
if not os.path.exists(dbfname):
raise IOError("database file %s does not exist" % dbfname)
self.system = LJCluster(15)
self.db = self.system.create_database(dbfname, createdb=False)
get_thermodynamic_information(self.system, self.db, nproc=None)
def test():
from pele.gui import run_gui
natoms = 13
fsys = LJCluster(natoms)
reference_coords = fsys.get_random_configuration()
frozen_atoms = [0,2,3,4]
system = LJClusterFrozen(natoms, frozen_atoms, reference_coords)
run_gui(system)
def test1(self):
system = LJCluster(6)
ss0 = 1.
displace = RandomDisplacement(stepsize=ss0)
ts = AdaptiveStepsize(displace, interval=10)
bh = system.get_basinhopping(takestep=ts)
bh.run(9)
self.assertAlmostEqual(displace.stepsize, ss0, 10)
bh.run(2)
self.assertNotAlmostEqual(displace.stepsize, ss0, 1)
def test1(self):
natoms = 13
system = LJCluster(natoms)
ts1 = RDWrap()
ts2 = RDWrap()
ts = GroupSteps([ts1, ts2])
bh = system.get_basinhopping(takestep=ts)
bh.run(2)
self.assertEqual(ts1.count, 2)
self.assertEqual(ts2.count, 2)
def test1(self):
natoms = 13
system = LJCluster(natoms)
ts1 = RDWrap()
ts2 = RDWrap()
ts = GroupSteps([ts1, ts2])
bh = system.get_basinhopping(takestep=ts)
bh.run(2)
self.assertEqual(ts1.count, 2)
self.assertEqual(ts2.count, 2)
def test(): # pragma: no cover
from pele.gui import run_gui
natoms = 13
fsys = LJCluster(natoms)
reference_coords = fsys.get_random_configuration()
frozen_atoms = [0, 2, 3, 4]
system = LJClusterFrozen(natoms, frozen_atoms, reference_coords)
run_gui(system)
def initialize_system():
system = LJCluster(natoms)
x0 = np.random.random(natoms*3)#.reshape(natoms,3)
db = system.create_database()
step = RandomDisplacement(stepsize=1.0)
bh = system.get_basinhopping(database=db,
takestep=step,
coords=x0,temperature = 10.0)
return system, db, bh
def getPairLJ(natoms=38):
from pele.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 pele.landscape import TSGraph
# from pele.storage.database import Database
from pele.systems import LJCluster
#get min1
system = LJCluster(natoms)
pot, database = getSetOfMinLJ(system)
# from pele.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)
class TestEigPot(unittest.TestCase):
def setUp(self):
self.first_order = False
self.setUp1()
def setUp1(self):
np.random.seed(0)
natoms = 18
# s = LJCluster(natoms)
# nfrozen = 6
# reference_coords = s.get_random_configuration()
# self.system = LJClusterFrozen(13, range(nfrozen), reference_coords)
self.system = LJCluster(natoms)
self.x = self.system.get_random_configuration()
#ret = self.system.get_random_minimized_configuration(tol=100.)
#self.x = ret.coords
self.pot = self.system.get_potential()
self.eigpot = LowestEigPot(self.x, self.pot,
orthogZeroEigs=self.system.get_orthogonalize_to_zero_eigenvectors(),
first_order=self.first_order,
)
def test_gradient(self):
vec = np.random.rand(self.x.size)
vec /= np.linalg.norm(vec)
e1 = self.eigpot.getEnergy(vec)
e, g = self.eigpot.getEnergyGradient(vec)
gnum = self.eigpot.NumericalDerivative(vec, eps=1e-6)
gnum -= np.dot(gnum, vec)
self.assertLess(np.max(np.abs(g-gnum)) / np.max(np.abs(g)), 1e-2)
self.assertAlmostEqual(e, e1, delta=e * 1e-4)
self.assertAlmostEqual(1., np.dot(g, gnum) / np.linalg.norm(g) / np.linalg.norm(gnum), 3)
def test_ts(self):
from pele.utils.xyz import read_xyz
path = os.path.dirname(os.path.abspath(__file__))
xyz = read_xyz(open(path + "/lj18_ts.xyz", "r"))
x = xyz.coords.flatten()
vec = np.random.rand(x.size)
vec /= np.linalg.norm(vec)
self.eigpot = LowestEigPot(x, self.pot,
orthogZeroEigs=self.system.get_orthogonalize_to_zero_eigenvectors(),
first_order=self.first_order)
e1 = self.eigpot.getEnergy(vec)
e, g = self.eigpot.getEnergyGradient(vec)
gnum = self.eigpot.NumericalDerivative(vec, eps=1e-4)
gnum -= np.dot(gnum, vec)
self.assertLess(np.max(np.abs(g-gnum)) / np.max(np.abs(g)), 1e-3)
self.assertAlmostEqual(e, e1, delta=e * 1e-4)
self.assertAlmostEqual(1., np.dot(g, gnum) / np.linalg.norm(g) / np.linalg.norm(gnum), 3)
def initialize_system():
system = LJCluster(natoms)
x0 = np.random.random(natoms * 3) #.reshape(natoms,3)
db = system.create_database()
step = RandomDisplacement(stepsize=1.0)
bh = system.get_basinhopping(database=db,
takestep=step,
coords=x0,
temperature=10.0)
return system, db, bh
def setUp1(self, **kwargs):
natoms = 18
# s = LJCluster(natoms)
# nfrozen = 6
# reference_coords = s.get_random_configuration()
# self.system = LJClusterFrozen(13, range(nfrozen), reference_coords)
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(
tol=100.).coords
self.pot = self.system.get_potential()
self.finder = FindLowestEigenVector(self.x.copy(), self.pot, **kwargs)
def setUp(self):
self.natoms = 6
self.system = LJCluster(self.natoms)
# create a database
self.database = self.system.create_database()
# add some minima to the database
bh = self.system.get_basinhopping(self.database, outstream=None)
while self.database.number_of_minima() < 2:
bh.run(1)
get_thermodynamic_information(self.system, self.database)
def testlj6(): # pragma: no cover
from pele.systems import LJCluster
from pele.thermodynamics import get_thermodynamic_information
system = LJCluster(6)
db = system.create_database()
bh = system.get_basinhopping(db)
bh.setPrinting(ostream=None)
bh.run(10)
get_thermodynamic_information(system, db)
for m in db.minima():
print(m.energy, m.pgorder)
def getPairLJ(natoms=38): # pragma: no cover
from pele.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 testlj6(): # pragma: no cover
from pele.systems import LJCluster
from pele.thermodynamics import get_thermodynamic_information
system = LJCluster(6)
db = system.create_database()
bh = system.get_basinhopping(db)
bh.setPrinting(ostream=None)
bh.run(10)
get_thermodynamic_information(system, db)
for m in db.minima():
print(m.energy, m.pgorder)
def setUp(self):
np.random.seed(0)
natoms = 31
self.system = LJCluster(natoms)
self.pot = self.system.get_potential()
# get a partially minimized structure
self.x0 = _x0.copy()
self.E0 = -128.289209867
ret = _quench.lbfgs_py(self.x0, self.pot, tol=1e-7)
self.x = ret.coords.copy()
self.E = ret.energy
def setUp(self):
natoms = 31
self.system = LJCluster(natoms)
self.pot = _PotWrapper(self.system.get_potential())
# get a partially minimized structure
self.x0 = _x0.copy()
self.minimizers = [
_quench.lbfgs_py,
_quench.mylbfgs,
_quench.lbfgs_scipy,
]
def size_scaling_smallest_eig(natoms): # pragma: no cover
from pele.systems import LJCluster
import time, sys
system = LJCluster(natoms)
pot = system.get_potential()
quencher = system.get_minimizer(tol=10.)
time1 = 0.
time2 = 0.
time3 = 0.
time4 = 0.
for i in range(100):
coords = system.get_random_configuration()
# print "len(coords)", len(coords)
coords = quencher(coords)[0]
e, g, h = pot.getEnergyGradientHessian(coords)
t0 = time.time()
w1, v1 = get_smallest_eig(h)
t1 = time.time()
w, v = get_smallest_eig_arpack(h)
t2 = time.time()
w2, v2 = get_smallest_eig_sparse(h)
t3 = time.time()
w3, v3 = get_smallest_eig_nohess(coords, system, tol=1e-3)
t4 = time.time()
time1 += t1 - t0
time2 += t2 - t1
time3 += t3 - t2
time4 += t4 - t3
wdiff = np.abs(w - w1) / np.max(np.abs([w, w1]))
if wdiff > 5e-3:
sys.stderr.write(
"eigenvalues for dense are different %g %g normalized diff %g\n"
% (w1, w, wdiff))
wdiff = np.abs(w - w2) / np.max(np.abs([w, w2]))
if wdiff > 5e-2:
sys.stderr.write(
"eigenvalues for sparse are different %g %g normalized diff %g\n"
% (w2, w, wdiff))
wdiff = np.abs(w - w3) / np.max(np.abs([w, w3]))
if wdiff > 5e-2:
sys.stderr.write(
"eigenvalues for nohess are different %g %g normalized diff %g\n"
% (w3, w, wdiff))
# print "times", n, t1-t0, t2-t1, w1, w
print("times", n, time1, time2, time3, time4)
sys.stdout.flush()
class TestNormalModes(unittest.TestCase):
def setUp(self):
import pele.rates.tests.__init__ as f
dirname = os.path.dirname(f.__file__)
dbfname = os.path.join(dirname, "lj15.sqlite")
if not os.path.exists(dbfname):
raise IOError("database file %s does not exist" % dbfname)
self.system = LJCluster(15)
self.db = self.system.create_database(dbfname, createdb=False)
def check(self, fvib_expected, coords, nzero, nnegative, metric=None):
pot = self.system.get_potential()
hess = pot.getHessian(coords)
freqs, modes = normalmodes(hess, metric=metric)
# print v
n, fvib = logproduct_freq2(freqs, nzero=nzero, nnegative=nnegative)
self.assertAlmostEqual(fvib, fvib_expected, 4)
self.assertEqual(n, len(coords) - nzero - nnegative)
def test_minimum(self):
m = self.db.minima()[0]
self.check(m.fvib, m.coords, 6, 0)
def test_transition_state(self):
ts = self.db.transition_states()[0]
self.check(ts.fvib, ts.coords, 6, 1)
def test_metric_tensor(self):
m = self.db.minima()[0]
mt = np.eye(m.coords.size)
self.check(m.fvib, m.coords, 6, 0, metric=mt)
def test_get_thermo_info(self):
newdb = self.system.create_database()
new2old = dict()
for ts in self.db.transition_states()[:5]:
m1 = newdb.addMinimum(ts.minimum1.energy, ts.minimum1.coords)
m2 = newdb.addMinimum(ts.minimum2.energy, ts.minimum2.coords)
newts = newdb.addTransitionState(ts.energy, ts.coords, m1, m2)
new2old[m1] = ts.minimum1
new2old[m2] = ts.minimum2
new2old[newts] = ts
get_thermodynamic_information(self.system, newdb, nproc=2)
for new in newdb.minima() + newdb.transition_states():
old = new2old[new]
self.assertAlmostEqual(new.energy, old.energy, 4)
self.assertAlmostEqual(new.fvib, old.fvib, 4)
self.assertEqual(new.pgorder, old.pgorder)
class TestLBFGS_General(unittest.TestCase):
def setUp(self):
self.system = LJCluster(13)
self.x0 = self.system.get_random_minimized_configuration(tol=1).coords
self.pot = self.system.get_potential()
def test_event(self):
self.called = False
def event(coords=None, energy=None, rms=None):
self.called = True
opt = LBFGS(self.x0, self.pot, events=[event])
opt.one_iteration()
self.assertTrue(self.called)
class TestTransverseWalker_NFEV(unittest.TestCase):
def setUp(self):
from pele.optimize.tests.test_nfev import _PotWrapper
self.system = LJCluster(18)
self.pot = _PotWrapper(self.system.get_potential())
def test(self):
x = self.system.get_random_configuration()
evec = vec_random_ndim(x.size)
evec /= np.linalg.norm(evec)
opt = _TransverseWalker(x, self.pot, evec)
ret = opt.run(10)
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertGreater(ret.nfev, 0)
class TestTransverseWalker_NFEV(unittest.TestCase):
def setUp(self):
from pele.optimize.tests.test_nfev import _PotWrapper
self.system = LJCluster(18)
self.pot = _PotWrapper(self.system.get_potential())
def test(self):
x = self.system.get_random_configuration()
evec = vec_random_ndim(x.size)
evec /= np.linalg.norm(evec)
opt = _DimerTranslator(x, self.pot, evec)
ret = opt.run(10)
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertGreater(ret.nfev, 0)
def test():
from OpenGL.GLUT import glutInit
import sys
import pylab as pl
app = QtGui.QApplication(sys.argv)
from pele.systems import LJCluster
pl.ion()
natoms = 13
system = LJCluster(natoms)
system.params.double_ended_connect.local_connect_params.NEBparams.iter_density = 5.
dbname = "lj%dtest.db" % (natoms,)
db = system.create_database(dbname)
#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()
if True:
from pele.thermodynamics import get_thermodynamic_information
get_thermodynamic_information(system, db, nproc=4)
wnd = GraphViewDialog(db, app=app)
# decrunner = DECRunner(system, db, min1, min2, outstream=wnd.textEdit_writer)
glutInit()
wnd.show()
from PyQt4.QtCore import QTimer
def start():
wnd.start()
QTimer.singleShot(10, start)
sys.exit(app.exec_())
class TestLBFGSFortran(unittest.TestCase):
def setUp(self):
self.system = LJCluster(13)
self.x = self.system.get_random_configuration()
self.pot = self.system.get_potential()
def test(self):
minimizer = LBFGS(self.x.copy(), self.pot, fortran=True, debug=True)
ret = minimizer.run()
m2 = LBFGS(self.x.copy(), self.pot, fortran=False, debug=True)
ret2 = m2.run()
print "fortran", ret.nfev, ret2.nfev
# self.assertEqual(ret.nfev, ret2.nfev)
self.assertAlmostEqual(ret.energy, ret2.energy, 5)
class TestFindLowestEigenvector_NFEV(unittest.TestCase):
def setUp(self, **kwargs):
from pele.optimize.tests._test_nfev import _PotWrapper
natoms = 18
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(tol=100.).coords
self.pot = _PotWrapper(self.system.get_potential())
def test(self):
self.pot.nfev = 0
ret = findLowestEigenVector(self.x.copy(), self.pot)
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertTrue(ret.success)
self.assertGreater(ret.nfev, 0)
class TestFindLowestEigenvector_NFEV(unittest.TestCase):
def setUp(self, **kwargs):
from pele.optimize.tests.test_nfev import _PotWrapper
natoms = 18
self.system = LJCluster(natoms)
self.x = self.system.get_random_minimized_configuration(
tol=100.).coords
self.pot = _PotWrapper(self.system.get_potential())
def test(self):
self.pot.nfev = 0
ret = findLowestEigenVector(self.x.copy(), self.pot)
self.assertEqual(ret.nfev, self.pot.nfev)
self.assertTrue(ret.success)
self.assertGreater(ret.nfev, 0)
def setUp(self):
import numpy as np
s = np.random.randint(1000000)
s = 322846
self.seed = s
sys.stderr.write("setUp: seed {}\n".format(self.seed))
np.random.seed(s)
import pele.rates.tests.__init__ as f
dirname = os.path.dirname(f.__file__)
dbfname = os.path.join(dirname, "lj15.sqlite")
if not os.path.exists(dbfname):
raise IOError("database file %s does not exist" % dbfname)
self.system = LJCluster(15)
self.db = self.system.create_database(dbfname, createdb=False)
def setUp(self):
natoms = 18
self.system = LJCluster(natoms)
self.pot = self.system.get_potential()
self.evec = vec_random_ndim(3*natoms)
self.evec /= np.linalg.norm(self.evec)
self.x = self.system.get_random_configuration()
def setUp(self):
current_dir = os.path.dirname(__file__)
dbfname = os.path.join(current_dir, "lj15.sqlite")
print dbfname
self.system = LJCluster(15)
self.system.params.structural_quench_params.tol = 1e-6
self.db = self.system.create_database(dbfname, createdb=False)
