def create_random_database(nmin=20, nts=None, natoms=2):
"""
create a database for test purposes
"""
from pygmin.storage import Database
import numpy as np
if nts is None:
nts = nmin
db = Database()
#generate random structures
minlist = []
for i in range(nmin):
coords = np.random.uniform(-1,1,natoms*3)
e = float(i) #make up a fake energy
minlist.append( db.addMinimum(e, coords) )
#add random transition states
for i in range(nts):
j1, j2 = 1, 1
while j1 == j2:
j1, j2 = np.random.randint(0, nmin, 2)
m1, m2 = minlist[j1], minlist[j2]
coords = np.random.uniform(-1,1,natoms*3)
e = float(j1 + j2)
db.addTransitionState(e, coords, m1, m2)
return db
def create_random_database(nmin=20, nts=None, natoms=2):
"""
create a database for test purposes
"""
from pygmin.storage import Database
import numpy as np
if nts is None:
nts = nmin
db = Database()
#generate random structures
minlist = []
for i in range(nmin):
coords = np.random.uniform(-1,1,natoms*3)
e = float(i) #make up a fake energy
minlist.append( db.addMinimum(e, coords) )
#add random transition states
for i in range(nts):
j1, j2 = 1, 1
while j1 == j2:
j1, j2 = np.random.randint(0, nmin, 2)
m1, m2 = minlist[j1], minlist[j2]
coords = np.random.uniform(-1,1,natoms*3)
e = float(j1 + j2)
db.addTransitionState(e, coords, m1, m2)
return db
def test():
from pygmin.storage import Database
coords1, coords2, pot, mindist, E1, E2 = getPairLJ()
db = Database()
min1 = db.addMinimum(E1, coords1)
min2 = db.addMinimum(E2, coords2)
local_connect = LocalConnect(pot, mindist)
local_connect.connect(min1, min2)
def test():
from pygmin.storage import Database
coords1, coords2, pot, mindist, E1, E2 = getPairLJ()
db = Database()
min1 = db.addMinimum(E1, coords1)
min2 = db.addMinimum(E2, coords2)
local_connect = LocalConnect(pot, mindist)
local_connect.connect(min1, min2)
def create_database(self, *args, **kwargs):
"""return a new database object
See Also
--------
pygmin.storage
"""
kwargs = dict_copy_update(self.params["database"], kwargs)
#note this syntax is quite ugly, but we would like to be able to
#create a new database by passing the filename as the first arg,
#not as a kwarg.
if len(args) > 1:
raise ValueError(
"create_database can only take one non-keyword argument")
if len(args) == 1:
if "db" not in kwargs:
kwargs["db"] = args[0]
#get a routine to compare the minima as exact
try:
if not "compareMinima" in kwargs:
try:
compare_minima = self.get_compare_minima()
kwargs["compareMinima"] = compare_minima
except NotImplementedError:
pass
except NotImplementedError:
#compareMinima is optional
pass
return Database(**kwargs)
def create_neb(self, coords1, coords2):
"""setup the NEB object"""
system = self.system
throwaway_db = Database()
min1 = throwaway_db.addMinimum(0., coords1)
min2 = throwaway_db.addMinimum(1., coords2)
#use the functions in DoubleEndedConnect to set up the NEB in the proper way
double_ended = system.get_double_ended_connect(min1, min2,
throwaway_db,
fresh_connect=True)
local_connect = double_ended._getLocalConnectObject()
self.local_connect = local_connect
return local_connect.create_neb(system.get_potential(),
coords1, coords2,
**local_connect.NEBparams)
def create_neb(self, coords1, coords2):
"""setup the NEB object"""
system = self.system
throwaway_db = Database()
min1 = throwaway_db.addMinimum(0., coords1)
min2 = throwaway_db.addMinimum(1., coords2)
#use the functions in DoubleEndedConnect to set up the NEB in the proper way
double_ended = system.get_double_ended_connect(min1,
min2,
throwaway_db,
fresh_connect=True)
local_connect = double_ended._getLocalConnectObject()
self.local_connect = local_connect
return local_connect.create_neb(system.get_potential(), coords1,
coords2, **local_connect.NEBparams)
def getNEB(coords1, coords2, system):
"""setup the NEB object"""
throwaway_db = Database()
min1 = throwaway_db.addMinimum(0., coords1)
min2 = throwaway_db.addMinimum(1., coords2)
#use the functions in DoubleEndedConnect to set up the NEB in the proper way
double_ended = system.get_double_ended_connect(min1, min2,
throwaway_db,
fresh_connect=True)
local_connect = double_ended._getLocalConnectObject()
neb = local_connect._getNEB(system.get_potential(),
coords1, coords2,
verbose=True,
**local_connect.NEBparams)
return neb
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 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 __init__(self,
ndof,
db_name="Database.db",
mindata="min.data",
tsdata="ts.data",
pointsmin="points.min",
pointsts="points.ts",
endianness="="):
self.ndof = ndof
self.db_name = db_name
self.mindata = mindata
self.tsdata = tsdata
self.pointsmin = pointsmin
self.pointsts = pointsts
self.endianness = endianness
self.db = Database(self.db_name)
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()
path_xyz.append(coords)
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)
return db
def make_graph(database):
#make a graph from the database
graphwrapper = TSGraph(db)
#turn the graph into a disconnectivity graph
mydg = dg.DisconnectivityGraph(
graphwrapper.graph,
nlevels=5,
center_gmin=False,
order_by_energy=True,
# Emax=-169.
)
mydg.calculate()
print "number of minima:", mydg.tree_graph.number_of_leaves()
mydg.plot()
plt.show()
if __name__ == "__main__":
if True:
db = get_database()
else:
db = Database("lj38.sqlite")
#db = Database("database.sqlite.large")
make_graph(db)
app = QApplication(sys.argv)
def process_events():
app.processEvents()
#setup system
natoms = 13
system = LJCluster(natoms)
system.params.double_ended_connect.local_connect_params.NEBparams.iter_density = 10.
system.params.double_ended_connect.local_connect_params.NEBparams.image_density = 3.
# system.params.double_ended_connect.local_connect_params.NEBparams.adaptive_nimages = 5.
system.params.double_ended_connect.local_connect_params.NEBparams.reinterpolate = 400
system.params.double_ended_connect.local_connect_params.NEBparams.max_images = 40
x1, e1 = system.get_random_minimized_configuration()[:2]
x2, e2 = system.get_random_minimized_configuration()[:2]
db = Database()
min1 = db.addMinimum(e1, x1)
min2 = db.addMinimum(e2, x2)
#setup neb dialog
wnd = ConnectExplorerDialog(system, app)
wnd.show()
glutInit()
#initilize the NEB and run it.
#we have to do it through QTimer because the gui has to
#be intitialized first... I don't really understand it
from PyQt4.QtCore import QTimer
QTimer.singleShot(10, start)
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
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())
#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])
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)
MAXBFGS 0.1
NAB start
"""
fout.write(odatastr)
fout.write("\n")
# ============================ MAIN ================================
if __name__ == "__main__":
# create new amber system
sysAmb = AMBERSystem('/home/ss2029/WORK/PyGMIN/examples/amber/coords.prmtop', '/home/ss2029/WORK/PyGMIN/examples/amber/coords.inpcrd')
# load existing database
from pygmin.storage import Database
dbcurr = Database(db="/home/ss2029/WORK/PyGMIN/examples/amber/aladipep.db")
coords = sysAmb.get_random_configuration()
aa = sysAmb.get_metric_tensor(coords)
exit()
# ------- TEST gui
from pygmin.gui import run as gr
gr.run_gui(sysAmb)
# ------ Test potential
sysAmb.test_potential('coords.pdb')
# ------ BH
sysAmb.test_BH(dbcurr)
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_())
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()
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_())
parser.add_argument("--Tmax", type=float, help="Minimum temperature for the calculation.", default=1.0)
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)
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())
if __name__ == "__main__":
from pygmin.systems import LJCluster
from pygmin.storage import Database
import pylab as pl
app = QApplication(sys.argv)
def process_events():
app.processEvents()
#setup system
natoms = 13
system = LJCluster(natoms)
system.params.double_ended_connect.local_connect_params.NEBparams.iter_density = 5.
x1, e1 = system.get_random_minimized_configuration()[:2]
x2, e2 = system.get_random_minimized_configuration()[:2]
db = Database()
min1 = db.addMinimum(e1, x1)
min2 = db.addMinimum(e2, x2)
#setup neb dialog
pl.ion()
# pl.show()
dlg = NEBDialog()
wnd = dlg.nebwgt
dlg.show()
wnd.process_events.connect(process_events)
#initilize the NEB and run it.
#we have to do it through QTimer because the gui has to
#be intitialized first... I don't really understand it
from PyQt4.QtCore import QTimer
pot = LJ()
#import the starting and ending points and quench them,
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
def main():
if len(sys.argv) < 2:
usage()
exit(1)
kwargs = {}
outfile = None
OPTIM = False
opts, args = getopt.gnu_getopt(sys.argv[1:], "ho:",
["help", "nlevels=", "subgraph_size=", "OPTIM",
"order_by_basin_size", "order_by_energy",
"include_gmin",
"center_gmin",
"Emax=",
])
for o, a in opts:
if o == "-h" or o == "--help":
usage()
exit(1)
if o == "-o":
outfile = a
elif o == "--nlevels":
kwargs["nlevels"] = int(a)
elif o == "--Emax":
kwargs["Emax"] = float(a)
elif o == "--subgraph_size":
kwargs["subgraph_size"] = int(a)
elif o == "--order_by_basin_size":
kwargs["order_by_basin_size"] = True
elif o == "--order_by_energy":
kwargs["order_by_energy"] = True
elif o == "--includer_gmin":
kwargs["includer_gmin"] = True
elif o == "--center_gmin":
kwargs["center_gmin"] = True
elif o == "--OPTIM":
OPTIM = True
else:
print "don't understand", o, a
print ""
usage()
exit(1)
if OPTIM:
#make database from min.data ts.data
graph = make_graph_from_files()
else:
if len(args) == 0:
print "you must specify database file"
print ""
usage()
exit()
dbfile = args[0]
if not os.path.exists(dbfile):
print "database file doesn't exist", dbfile
exit()
db = Database(dbfile)
if outfile is None and use_gui:
app = QApplication(sys.argv)
kwargs["show_minima"] = False
md = DGraphDialog(db, params=kwargs)
md.rebuild_disconnectivity_graph()
md.show()
sys.exit(app.exec_())
if not OPTIM:
# make graph from database
if "Emax" in kwargs and use_gui:
graph = reduced_db2graph(db, kwargs['Emax'])
else:
graph = dg.database2graph(db)
# do the disconnectivity graph analysis
mydg = dg.DisconnectivityGraph(graph, **kwargs)
print "doing disconnectivity graph analysis"
sys.stdout.flush()
t1 = time.time()
mydg.calculate()
t2 = time.time()
print "d-graph analysis finished in", t2-t1, "seconds"
print "number of minima:", mydg.tree_graph.number_of_leaves()
print "plotting disconnectivigy graph"
sys.stdout.flush()
# make the figure and save it
mydg.plot()
if outfile is None:
plt.show()
else:
plt.savefig(outfile)
t3 = time.time()
print "plotting finished in", t3-t2, "seconds"