def do_ts_search(nmol=20):
from pele.transition_states import findTransitionState
system = OTPCluster(nmol)
db = system.create_database("test.sqlte")
orthogopt = system.get_orthogonalize_to_zero_eigenvectors()
for ts in db.transition_states():
coords = db.transition_states()[0].coords.copy()
coords += np.random.uniform(-.5,.5, coords.size)
print system.params.double_ended_connect.local_connect_params.tsSearchParams
findTransitionState(coords, system.get_potential(), orthogZeroEigs=orthogopt,
**system.params.double_ended_connect.local_connect_params.tsSearchParams)
def do_ts_search(nmol=20):
from pele.transition_states import findTransitionState
system = OTPCluster(nmol)
db = system.create_database("test.sqlte")
orthogopt = system.get_orthogonalize_to_zero_eigenvectors()
for ts in db.transition_states():
coords = db.transition_states()[0].coords.copy()
coords += np.random.uniform(-.5, .5, coords.size)
print system.params.double_ended_connect.local_connect_params.tsSearchParams
findTransitionState(coords,
system.get_potential(),
orthogZeroEigs=orthogopt,
**system.params.double_ended_connect.
local_connect_params.tsSearchParams)
def _refineTS(pot, coords, tsSearchParams=dict(), eigenvec0=None, pushoff_params=dict()):
"""
find nearest transition state to NEB climbing image. Then fall
off the transition state to find the associated minima.
This would naturally be a part of DoubleEndedConnect. I separated it
to make it more easily parallelizable.
"""
#run ts search algorithm
kwargs = dict(tsSearchParams.items())
ret = findTransitionState(coords, pot, eigenvec0=eigenvec0, **kwargs)
#check to make sure it is a valid transition state
coords = ret.coords
if not ret.success:
logger.info("transition state search failed")
return False, ret, None, None
if ret.eigenval >= 0.:
logger.info("transition state has positive lowest eigenvalue, skipping: %s %s %s", ret.eigenval, ret.energy, ret.rms)
logger.info( " not adding transition state")
return False, ret, None, None
#find the minima which this transition state connects
logger.info("falling off either side of transition state to find new minima")
ret1, ret2 = minima_from_ts(pot, coords, n = ret.eigenvec, \
**pushoff_params)
# print "testing", ret1.energy
return True, ret, ret1, ret2
def compare_HEF(x0, evec0, system, **kwargs):
from pele.transition_states import findTransitionState
pot = PotWrapper(system.get_potential())
ret = findTransitionState(x0, pot, eigenvec0=evec0, orthogZeroEigs=None, **kwargs)
print ret.eigenval
print pot.nfev
print ret.rms
def compare_HEF(x0, evec0, system, **kwargs): # pragma: no cover
from pele.transition_states import findTransitionState
pot = PotWrapper(system.get_potential())
ret = findTransitionState(x0, pot, eigenvec0=evec0, orthogZeroEigs=None, **kwargs)
print ret.eigenval
print pot.nfev
print ret.rms
def _refineTS(pot,
coords,
tsSearchParams=None,
eigenvec0=None,
pushoff_params=None):
"""
find nearest transition state to NEB climbing image. Then fall
off the transition state to find the associated minima.
This would naturally be a part of DoubleEndedConnect. I separated it
to make it more easily parallelizable.
"""
if pushoff_params is None: pushoff_params = dict()
if tsSearchParams is None: tsSearchParams = dict()
# run ts search algorithm
kwargs = dict(list(tsSearchParams.items()))
ret = findTransitionState(coords, pot, eigenvec0=eigenvec0, **kwargs)
# check to make sure it is a valid transition state
coords = ret.coords
if not ret.success:
logger.info("transition state search failed")
return False, ret, None, None
if ret.eigenval >= 0.:
logger.info(
"transition state has positive lowest eigenvalue, skipping: %s %s %s",
ret.eigenval, ret.energy, ret.rms)
logger.info(" not adding transition state")
return False, ret, None, None
# find the minima which this transition state connects
logger.info(
"falling off either side of transition state to find new minima")
ret1, ret2 = minima_from_ts(pot, coords, n=ret.eigenvec, **pushoff_params)
return True, ret, ret1, ret2
def test_wrapper(self):
ret = findTransitionState(self.x0, self.pot, orthogZeroEigs=None)
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
def test_wrapper(self):
ret = findTransitionState(self.x0, self.pot, orthogZeroEigs=None)
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
