def benchmark_number_of_minima():
import time, sys
import numpy as np
db = Database("test.large.db")
if True:
istart = np.random.randint(0, sys.maxint)
for i in xrange(istart, istart + 10000):
e = float(i)
db.addMinimum(e, [e], commit=False)
db.session.commit()
else:
i = 1
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock()
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock()
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock()
t1 = time.clock()
e = float(i + 1)
db.addMinimum(e, [e], commit=False)
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock()
t1 = time.clock()
print len(db.minima())
print "time", t1 - time.clock()
t1 = time.clock()
def benchmark_number_of_minima():
import time, sys
import numpy as np
db = Database("test.large.db")
if True:
istart = np.random.randint(0, sys.maxint)
for i in xrange(istart,istart+10000):
e = float(i)
db.addMinimum(e, [e], commit=False)
db.session.commit()
else:
i=1
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock(); t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock(); t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock(); t1 = time.clock()
e = float(i+1)
db.addMinimum(e, [e], commit=False)
t1 = time.clock()
print db.number_of_minima()
print "time", t1 - time.clock(); t1 = time.clock()
print len(db.minima())
print "time", t1 - time.clock(); t1 = time.clock()
coords1 = np.genfromtxt("coords.A")
coords2 = np.genfromtxt("coords.B")
res1 = lbfgs_py(coords1.reshape(-1), pot)
res2 = lbfgs_py(coords2.reshape(-1), pot)
coords1 = res1.coords
coords2 = res2.coords
E1 = res1.energy
E2 = res2.energy
natoms = len(coords1)/3
#add the minima to a database
dbfile = "database.sqlite"
database = Database(dbfile)
database.addMinimum(E1, coords1)
database.addMinimum(E2, coords2)
min1 = database.minima()[0]
min2 = database.minima()[1]
#set up the structural alignment routine.
#we have to deal with global translational, global rotational,
#and permutational symmetry.
permlist = [range(natoms)]
mindist = MinPermDistAtomicCluster(permlist=permlist, niter=10)
#The transition state search needs to know what the eigenvector corresponding
#to the lowest nonzero eigenvector is. For this we need to know what the
#eivenvector corresponding to the zero eigenvalues are. These are related
#to global symmetries. for this system we have 3 zero eigenvalues for translational
class TestDB(unittest.TestCase):
def setUp(self):
self.db = Database()
self.nminima = 10
for i in range(self.nminima):
e = float(i)
self.db.addMinimum(e, [e])
self.nts = 3
self.db.addTransitionState(0., [0.],
self.db.minima()[0],
self.db.minima()[1],
eigenval=0.,
eigenvec=[0.])
self.db.addTransitionState(0., [0.],
self.db.minima()[1],
self.db.minima()[2],
eigenval=0.,
eigenvec=[0.])
self.db.addTransitionState(0., [0.],
self.db.minima()[0],
self.db.minima()[2],
eigenval=0.,
eigenvec=[0.])
def test_size(self):
self.assertEqual(len(self.db.minima()), self.nminima)
def test_energy(self):
m = self.db.minima()[0]
self.assertEqual(m.energy, 0.)
def test_coords(self):
m = self.db.minima()[0]
self.assertEqual(m.coords, [0.])
def test_sizets(self):
self.assertEqual(len(self.db.transition_states()), self.nts)
def test_energyts(self):
ts = self.db.transition_states()[0]
self.assertEqual(ts.energy, 0.)
def test_coordsts(self):
ts = self.db.transition_states()[0]
self.assertEqual(ts.coords, [0.])
def test_remove_minimum(self):
m = self.db.minima()[0]
self.db.removeMinimum(m)
self.assertEqual(len(self.db.minima()), self.nminima - 1)
self.assertNotIn(m, self.db.minima())
# m should have 2 minima. both of those should be gone
self.assertEqual(len(self.db.transition_states()), self.nts - 2)
def test_remove_ts(self):
ts = self.db.transition_states()[0]
self.db.remove_transition_state(ts)
self.assertEqual(self.db.number_of_transition_states(), self.nts - 1)
self.assertNotIn(ts, self.db.transition_states())
# m should have 2 minima. both of those should be gone
self.assertEqual(self.db.number_of_minima(), self.nminima)
def test_getTransitionState(self):
m1 = self.db.minima()[0]
m2 = self.db.minima()[1]
m3 = self.db.minima()[-1]
self.assertIsNotNone(self.db.getTransitionState(m1, m2))
self.assertIsNone(self.db.getTransitionState(m1, m3))
def test_getMinimum(self):
m = self.db.minima()[0]
self.assertEqual(m, self.db.getMinimum(m._id))
def test_minimum_adder(self):
ma = self.db.minimum_adder()
ma(101., [101.])
self.assertEqual(len(self.db.minima()), self.nminima + 1)
def test_merge_minima(self):
m1 = self.db.minima()[0]
m2 = self.db.minima()[1]
self.db.mergeMinima(m1, m2)
self.assertEqual(len(self.db.minima()), self.nminima - 1)
# transition states shouldn't be deleted
self.assertEqual(len(self.db.transition_states()), self.nts)
def test_number_of_minima(self):
self.assertEqual(self.nminima, self.db.number_of_minima())
def test_number_of_transition_states(self):
self.assertEqual(self.nts, self.db.number_of_transition_states())
def test_highest_energy_minimum(self):
m1 = self.db._highest_energy_minimum()
m2 = self.db.minima()[-1]
self.assertEqual(m1, m2)
def test_maximum_number_of_minima(self):
m = self.db.addMinimum(-1., [-1.], max_n_minima=self.nminima)
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIn(m, self.db.minima())
def test_maximum_number_of_minima_largestE(self):
e = float(self.nminima + 1)
m = self.db.addMinimum(e, [e], max_n_minima=self.nminima)
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIsNone(m)
#ensure the highest energy minimum is still in the database
mmax = self.db._highest_energy_minimum()
self.assertEqual(mmax.energy, float(self.nminima - 1))
def test_maximum_number_of_minima_minima_adder(self):
ma = self.db.minimum_adder(max_n_minima=self.nminima)
m = ma(-1., [-1.])
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIn(m, self.db.minima())
self.setCentralWidget(self.dgraph_widget)
def rebuild_disconnectivity_graph(self):
self.dgraph_widget.rebuild_disconnectivity_graph()
def reduced_db2graph(db, Emax):
'''
make a networkx graph from a database including only transition states with energy < Emax
'''
g = nx.Graph()
ts = db.session.query(TransitionState).filter(
TransitionState.energy <= Emax).all()
for t in ts:
g.add_edge(t.minimum1, t.minimum2, ts=t)
return g
if __name__ == "__main__":
db = Database("lj31.db")
if len(db.minima()) < 2:
raise Exception("database has no minima")
app = QApplication(sys.argv)
md = DGraphDialog(db)
md.show()
md.rebuild_disconnectivity_graph()
sys.exit(app.exec_())
print "length of path:", len(path_xyz)
path = [ map_to_aa(xyz) for xyz in path_xyz]
#p#ath = [ x for x in IntterpolatedPath(db.minima[19], )]
#path = [ x for x in InterpolatedPath(path[0].copy(), path[-1].copy(), 34) ]
traj = open("traj.xyz", "w")
#for x in path:
# #export_xyz(traj, x)
# #ret = quench.mylbfgs(x, pot.getEnergyGradient)
# #print i,pot.getEnergy(x), ret[1]
#
# # export_xyz(traj, ret[0])
db=Database(db="oxdna.sqlite")
path[0]=db.minima()[19].coords
path[-1]=db.minima()[0].coords
e1 = []
e2 = []
e1.append(pot.getEnergy(path[0]))
e2.append(pot.getEnergy(path[0]))
for i in xrange(1):
for i in xrange(len(path)-1):
e1.append(pot.getEnergy(path[i+1]))
c1 = CoordsAdapter(nrigid=13, coords = path[i])
c2 = CoordsAdapter(nrigid=13, coords = path[i+1])
com1 = np.sum(c1.posRigid,axis=0) / float(13)
com2 = np.sum(c1.posRigid,axis=0) / float(13)
from pygmin.utils.disconnectivity_graph import DisconnectivityGraph
from pygmin.storage import Database
from pygmin.landscape import TSGraph
import pylab as pl
import numpy as np
kbT = 0.75
db = Database(db="tip4p_8.sqlite", createdb=False)
graph = TSGraph(db)
dg = DisconnectivityGraph(graph.graph, db.minima(), subgraph_size=20)
dg.calculate()
dg.plot()
for m in db.minima():
if m.pgorder != 2:
print m.pgorder
m.free_energy = m.energy + kbT * 0.5*m.fvib + kbT*np.log(m.pgorder)
for ts in db.transition_states():
# if ts.pgorder != 2:
print ts.pgorder
#assert ts.pgorder == 2
ts.free_energy = ts.energy + kbT * 0.5*ts.fvib + kbT*np.log(ts.pgorder) + kbT*np.log(kbT)
if ts.free_energy > ts.minimum1.free_energy or ts.free_energy > ts.minimum2.free_energy:
print "warning, free energy of transition state lower than minimum"
print ts.free_energy, ts.minimum1.free_energy, ts.minimum2.free_energy
parser.add_argument("--Tcount", type=int, help="Number of temperature points for the calculation.", default=300)
parser.add_argument("--OPTIM", action="store_true", help="read data from a min.data file instead."
"fname should be the filename of the min.data file")
args = parser.parse_args()
print args.fname
print args
k = args.k
# get the list of minima
if args.OPTIM:
# fname is a min.data file
minima = read_min_data(args.fname)
else:
dbfname = args.fname
db = Database(dbfname, createdb=False)
minima = [m for m in db.minima() if m.fvib is not None and m.pgorder is not None]
if len(minima) == 0:
print "There are not minima with the necessary thermodynamic information in the database. Have you computed the normal mode"\
" frequencies and point group order for all the minima? See pygmin.thermodynamics "\
" for more information"
exit(1)
print "computing heat capacity from", len(minima), "minima"
Tmin = args.Tmin
Tmax = args.Tmax
nT = args.Tcount
dT = (Tmax-Tmin) / nT
T = np.array([Tmin + dT*i for i in range(nT)])
Z, U, U2, Cv = minima_to_cv(minima, T, k)
from pygmin.utils.disconnectivity_graph import DisconnectivityGraph
from pygmin.storage import Database
from pygmin.landscape import TSGraph
import pylab as pl
import numpy as np
kbT = 0.75
db = Database(db="tip4p_8.sqlite", createdb=False)
graph = TSGraph(db)
dg = DisconnectivityGraph(graph.graph, db.minima(), subgraph_size=20)
dg.calculate()
dg.plot()
for m in db.minima():
if m.pgorder != 2:
print m.pgorder
m.free_energy = m.energy + kbT * 0.5 * m.fvib + kbT * np.log(m.pgorder)
for ts in db.transition_states():
# if ts.pgorder != 2:
print ts.pgorder
#assert ts.pgorder == 2
ts.free_energy = ts.energy + kbT * 0.5 * ts.fvib + kbT * np.log(
ts.pgorder) + kbT * np.log(kbT)
if ts.free_energy > ts.minimum1.free_energy or ts.free_energy > ts.minimum2.free_energy:
print "warning, free energy of transition state lower than minimum"
print ts.free_energy, ts.minimum1.free_energy, ts.minimum2.free_energy
self.setCentralWidget(self.dgraph_widget)
def rebuild_disconnectivity_graph(self):
self.dgraph_widget.rebuild_disconnectivity_graph()
def reduced_db2graph(db, Emax):
'''
make a networkx graph from a database including only transition states with energy < Emax
'''
g = nx.Graph()
ts = db.session.query(TransitionState).filter(TransitionState.energy <= Emax).all()
for t in ts:
g.add_edge(t.minimum1, t.minimum2, ts=t)
return g
if __name__ == "__main__":
db = Database("lj31.db")
if len(db.minima()) < 2:
raise Exception("database has no minima")
app = QApplication(sys.argv)
md = DGraphDialog(db)
md.show()
md.rebuild_disconnectivity_graph()
sys.exit(app.exec_())
#path = [ x for x in InterpolatedPath(path[0].copy(), path[-1].copy(), 34) ]
traj = open("traj.xyz", "w")
#for x in path:
# #export_xyz(traj, x)
# #ret = quench.mylbfgs(x, pot.getEnergyGradient)
# #print i,pot.getEnergy(x), ret[1]
#
# # export_xyz(traj, ret[0])
for x in path:
export_xyz(traj, x)
import pickle
pickle.dump(path, open("interpolate.pickle", "w"))
exit()
db = Database(db="oxdna.sqlite")
path[0] = db.minima()[19].coords
path[-1] = db.minima()[0].coords
e1 = []
e2 = []
e1.append(pot.getEnergy(path[0]))
e2.append(pot.getEnergy(path[0]))
for i in xrange(1):
for i in xrange(len(path) - 1):
e1.append(pot.getEnergy(path[i + 1]))
c1 = CoordsAdapter(nrigid=13, coords=path[i])
c2 = CoordsAdapter(nrigid=13, coords=path[i + 1])
com1 = np.sum(c1.posRigid, axis=0) / float(13)
com2 = np.sum(c1.posRigid, axis=0) / float(13)
class TestDB(unittest.TestCase):
def setUp(self):
self.db = Database()
self.nminima = 10
for i in range(self.nminima):
e = float(i)
self.db.addMinimum(e, [e])
self.nts = 3
self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[1], eigenval=0., eigenvec=[0.])
self.db.addTransitionState(0., [0.], self.db.minima()[1], self.db.minima()[2], eigenval=0., eigenvec=[0.])
self.db.addTransitionState(0., [0.], self.db.minima()[0], self.db.minima()[2], eigenval=0., eigenvec=[0.])
def test_size(self):
self.assertEqual(len(self.db.minima()), self.nminima)
def test_energy(self):
m = self.db.minima()[0]
self.assertEqual(m.energy, 0.)
def test_coords(self):
m = self.db.minima()[0]
self.assertEqual(m.coords, [0.])
def test_sizets(self):
self.assertEqual(len(self.db.transition_states()), self.nts)
def test_energyts(self):
ts = self.db.transition_states()[0]
self.assertEqual(ts.energy, 0.)
def test_coordsts(self):
ts = self.db.transition_states()[0]
self.assertEqual(ts.coords, [0.])
def test_remove_minimum(self):
m = self.db.minima()[0]
self.db.removeMinimum(m)
self.assertEqual(len(self.db.minima()), self.nminima-1)
self.assertNotIn(m, self.db.minima())
# m should have 2 minima. both of those should be gone
self.assertEqual(len(self.db.transition_states()), self.nts-2)
def test_remove_ts(self):
ts = self.db.transition_states()[0]
self.db.remove_transition_state(ts)
self.assertEqual(self.db.number_of_transition_states(), self.nts-1)
self.assertNotIn(ts, self.db.transition_states())
# m should have 2 minima. both of those should be gone
self.assertEqual(self.db.number_of_minima(), self.nminima)
def test_getTransitionState(self):
m1 = self.db.minima()[0]
m2 = self.db.minima()[1]
m3 = self.db.minima()[-1]
self.assertIsNotNone(self.db.getTransitionState(m1, m2))
self.assertIsNone(self.db.getTransitionState(m1, m3))
def test_getMinimum(self):
m = self.db.minima()[0]
self.assertEqual(m, self.db.getMinimum(m._id))
def test_minimum_adder(self):
ma = self.db.minimum_adder()
ma(101., [101.])
self.assertEqual(len(self.db.minima()), self.nminima+1)
def test_merge_minima(self):
m1 = self.db.minima()[0]
m2 = self.db.minima()[1]
self.db.mergeMinima(m1, m2)
self.assertEqual(len(self.db.minima()), self.nminima-1)
# transition states shouldn't be deleted
self.assertEqual(len(self.db.transition_states()), self.nts)
def test_number_of_minima(self):
self.assertEqual(self.nminima, self.db.number_of_minima())
def test_number_of_transition_states(self):
self.assertEqual(self.nts, self.db.number_of_transition_states())
def test_highest_energy_minimum(self):
m1 = self.db._highest_energy_minimum()
m2 = self.db.minima()[-1]
self.assertEqual(m1, m2)
def test_maximum_number_of_minima(self):
m = self.db.addMinimum(-1., [-1.], max_n_minima=self.nminima)
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIn(m, self.db.minima())
def test_maximum_number_of_minima_largestE(self):
e = float(self.nminima + 1)
m = self.db.addMinimum(e, [e], max_n_minima=self.nminima)
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIsNone(m)
#ensure the highest energy minimum is still in the database
mmax = self.db._highest_energy_minimum()
self.assertEqual(mmax.energy, float(self.nminima-1))
def test_maximum_number_of_minima_minima_adder(self):
ma = self.db.minimum_adder(max_n_minima=self.nminima)
m = ma(-1., [-1.])
self.assertEqual(self.nminima, self.db.number_of_minima())
self.assertIn(m, self.db.minima())
