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):
# 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)
def get_double_ended_connect(self, min1, min2, database, **kwargs):
"""return a DoubleEndedConnect object
See Also
--------
pele.landscape
"""
kwargs = dict_copy_update(self.params["double_ended_connect"], kwargs)
pot = self.get_potential()
mindist = self.get_mindist()
# attach the function which orthogonalizes to known zero eigenvectors.
# This is amazingly ugly
# vr: yea, we should polish this parameters stuff and give create policies instead!
try:
kwargs["local_connect_params"]["tsSearchParams"]["orthogZeroEigs"]
except KeyError:
if "local_connect_params" in kwargs:
lcp = kwargs["local_connect_params"]
else:
lcp = kwargs["local_connect_params"] = BaseParameters()
if "tsSearchParams" in lcp:
tssp = lcp["tsSearchParams"]
else:
tssp = lcp["tsSearchParams"] = BaseParameters()
if not "orthogZeroEigs" in tssp:
tssp[
"orthogZeroEigs"] = self.get_orthogonalize_to_zero_eigenvectors(
)
try:
kwargs["local_connect_params"]["pushoff_params"]["quench"]
except Exception:
if not "pushoff_params" in kwargs["local_connect_params"]:
kwargs["local_connect_params"][
"pushoff_params"] = BaseParameters()
kwargs["local_connect_params"]["pushoff_params"][
"quench"] = self.get_minimizer()
return DoubleEndedConnect(min1, min2, pot, mindist, database, **kwargs)
def test2(self):
from pele.storage import Database
from pele.systems import LJCluster
np.random.seed(0)
natoms = 13
system = LJCluster(natoms)
pot = system.get_potential()
mindist = system.get_mindist(niter=1)
db = Database()
db.addMinimum(pot.getEnergy(_x1), _x1)
db.addMinimum(pot.getEnergy(_x2), _x2)
m1, m2 = db.minima()
connect = DoubleEndedConnect(m1, m2, pot, mindist, db, verbosity=10)
connect.connect()
self.assertTrue(connect.success())
path = connect.returnPath()
class TestDistanceGraph(unittest.TestCase):
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=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 make_result(self, coords, energy):
from pele.optimize import Result
res = Result()
res.coords = coords
res.energy = energy
res.eigenval = 1.
res.eigenvec = coords.copy()
return res
def add_ts(self, tse, tsx, m1e, m1x, m2e, m2x):
tsres = self.make_result(tsx, tse)
min_ret1 = self.make_result(m1x, m1e)
min_ret2 = self.make_result(m2x, m2e)
return self.connect._addTransitionState(tsres, min_ret1, min_ret2)
def test_merge_minima(self):
"""merge two minima and make sure the distance graph is still ok"""
min3, min4 = list(self.db.minima())[2:4]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3._id, min4._id, "are connected", self.connect.graph.areConnected(min3, min4)
print min3._id, "number of edges", self.connect.graph.graph.degree(min3)
print min4._id, "number of edges", self.connect.graph.graph.degree(min4)
self.connect.mergeMinima(min3, min4)
self.assertNotIn(min4, self.connect.graph.graph)
self.assertNotIn(min4, self.connect.dist_graph.Gdist)
self.assertNotIn(min4, self.db.minima())
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "merging broke the distance graph")
def test_add_TS_existing_minima(self):
from pele.optimize import Result
min3, min4 = list(self.db.minima())[4:6]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3._id, min4._id, "are connected", self.connect.graph.areConnected(min3, min4)
print min3._id, "number of edges", self.connect.graph.graph.degree(min3)
print min4._id, "number of edges", self.connect.graph.graph.degree(min4)
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min4.energy)
tsres = self.make_result(coords, E)
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(min4.coords, min4.energy)
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def test_add_TS_new_minima(self):
min3 = list(self.db.minima())[6]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
# print min3._id, min4._id, "are connected", self.connect.graph.areConnected(min3, min4)
print min3._id, "number of edges", self.connect.graph.graph.degree(min3)
#create new minimum from thin air
coords = np.random.uniform(-1,1,self.natoms*3)
E = np.random.rand()*10.
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(coords, E)
# min_ret2 = [coords, E]
# min_ret1 = [min3.coords, min3.energy]
#create new TS from thin air
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min_ret2.energy)
tsres = self.make_result(coords, E)
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def run_add_TS(self, min3, min4, nocheck=False):
if not nocheck:
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3._id, min4._id, "are connected", self.connect.graph.areConnected(min3, min4)
print min3._id, "number of edges", self.connect.graph.graph.degree(min3)
print min4._id, "number of edges", self.connect.graph.graph.degree(min4)
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min4.energy)
tsres = self.make_result(coords, E)
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(min4.coords, min4.energy)
# min_ret1 = [min3.coords, min3.energy]
# min_ret2 = [min4.coords, min4.energy]
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
if not nocheck:
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def test_add_TS_existing_not_connected(self):
minima = list(self.db.minima())
min3 = minima[2]
for min4 in minima[3:]:
if not self.connect.graph.areConnected(min3, min4):
break
self.run_add_TS(min3, min4)
def test_add_TS_existing_already_connected(self):
minima = list(self.db.minima())
min3 = minima[2]
for min4 in minima[3:]:
if self.connect.graph.areConnected(min3, min4):
break
self.run_add_TS(min3, min4)
def test_add_TS_multiple(self):
minima = list(self.db.minima())
min3 = minima[2]
nnew = 4
for min4 in minima[3:3+nnew]:
self.run_add_TS(min3, min4, nocheck=True)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding multiple transition states broke the distance graph")
class TestDistanceGraph(unittest.TestCase):
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=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 make_result(self, coords, energy):
from pele.optimize import Result
res = Result()
res.coords = coords
res.energy = energy
res.eigenval = 1.
res.eigenvec = coords.copy()
return res
def add_ts(self, tse, tsx, m1e, m1x, m2e, m2x):
tsres = self.make_result(tsx, tse)
min_ret1 = self.make_result(m1x, m1e)
min_ret2 = self.make_result(m2x, m2e)
return self.connect._addTransitionState(tsres, min_ret1, min_ret2)
def test_merge_minima(self):
# merge two minima and make sure the distance graph is still ok
min3, min4 = list(self.db.minima())[2:4]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3.id(), min4.id(), "are connected", self.connect.graph.areConnected(min3, min4)
print min3.id(), "number of edges", self.connect.graph.graph.degree(min3)
print min4.id(), "number of edges", self.connect.graph.graph.degree(min4)
self.connect.mergeMinima(min3, min4)
self.assertNotIn(min4, self.connect.graph.graph)
self.assertNotIn(min4, self.connect.dist_graph.Gdist)
self.assertNotIn(min4, self.db.minima())
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "merging broke the distance graph")
def test_add_TS_existing_minima(self):
min3, min4 = list(self.db.minima())[4:6]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3.id(), min4.id(), "are connected", self.connect.graph.areConnected(min3, min4)
print min3.id(), "number of edges", self.connect.graph.graph.degree(min3)
print min4.id(), "number of edges", self.connect.graph.graph.degree(min4)
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min4.energy)
tsres = self.make_result(coords, E)
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(min4.coords, min4.energy)
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def test_add_TS_new_minima(self):
min3 = list(self.db.minima())[6]
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
# print min3.id(), min4.id(), "are connected", self.connect.graph.areConnected(min3, min4)
print min3.id(), "number of edges", self.connect.graph.graph.degree(min3)
#create new minimum from thin air
coords = np.random.uniform(-1,1,self.natoms*3)
E = np.random.rand()*10.
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(coords, E)
# min_ret2 = [coords, E]
# min_ret1 = [min3.coords, min3.energy]
#create new TS from thin air
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min_ret2.energy)
tsres = self.make_result(coords, E)
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def run_add_TS(self, min3, min4, nocheck=False):
if not nocheck:
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "the distance graph is broken at the start")
print min3.id(), min4.id(), "are connected", self.connect.graph.areConnected(min3, min4)
print min3.id(), "number of edges", self.connect.graph.graph.degree(min3)
print min4.id(), "number of edges", self.connect.graph.graph.degree(min4)
coords = np.random.uniform(-1,1,self.natoms*3)
E = float(min3.energy + min4.energy)
tsres = self.make_result(coords, E)
min_ret1 = self.make_result(min3.coords, min3.energy)
min_ret2 = self.make_result(min4.coords, min4.energy)
# min_ret1 = [min3.coords, min3.energy]
# min_ret2 = [min4.coords, min4.energy]
self.connect._addTransitionState(tsres, min_ret1, min_ret2)
if not nocheck:
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding a transition state broke the distance graph")
def test_add_TS_existing_not_connected(self):
minima = list(self.db.minima())
min3 = minima[2]
for min4 in minima[3:]:
if not self.connect.graph.areConnected(min3, min4):
break
self.run_add_TS(min3, min4)
def test_add_TS_existing_already_connected(self):
minima = list(self.db.minima())
min3 = minima[2]
for min4 in minima[3:]:
if self.connect.graph.areConnected(min3, min4):
break
self.run_add_TS(min3, min4)
def test_add_TS_multiple(self):
minima = list(self.db.minima())
min3 = minima[2]
nnew = 4
for min4 in minima[3:3+nnew]:
self.run_add_TS(min3, min4, nocheck=True)
allok = self.connect.dist_graph.checkGraph()
self.assertTrue(allok, "adding multiple transition states broke the distance graph")
NEBquenchParams["iprint"] = 100
NEBparams = dict()
NEBparams["k"] = 5.
NEBparams["image_density"] = 15
NEBparams["NEBquenchParams"] = NEBquenchParams
local_connect_params = dict()
local_connect_params["tsSearchParams"] = tsSearchParams
local_connect_params["NEBparams"] = NEBparams
myconnect = DoubleEndedConnect(
min1, min2, pot, mindist, database,
local_connect_params=local_connect_params,
)
if (myconnect.graph.areConnected(min1, min2)):
print "ALERT: The minima are already connected in the database file", dbfile
print " Delete it for a fresh run."
myconnect.connect()
print ""
print "found a path!"
#the path is now saved in the database. Lets retrieve it and
#print it in a more visual format
#now retrieve the path for printing
tsSearchParams["nfail_max"] = 200
NEBquenchParams = dict()
NEBquenchParams["iprint"] = 100
NEBparams = dict()
NEBparams["k"] = 5.
NEBparams["image_density"] = 15
NEBparams["NEBquenchParams"] = NEBquenchParams
local_connect_params = dict()
local_connect_params["tsSearchParams"] = tsSearchParams
local_connect_params["NEBparams"] = NEBparams
myconnect = DoubleEndedConnect(min1, min2, pot, mindist, database,
local_connect_params=local_connect_params,
)
if (myconnect.graph.areConnected(min1, min2)):
print "ALERT: The minima are already connected in the database file", dbfile
print " Delete it for a fresh run."
myconnect.connect()
print ""
print "found a path!"
# the path is now saved in the database. Lets retrieve it and
# print it in a more visual format
# now retrieve the path for printing