for i in range(nimages):
image = initial.copy()
image.set_calculator(LennardJones())
images.append(image)
images.append(final)
# Define the NEB and make a linear interpolation
# with removing translational
# and rotational degrees of freedom
neb = NEB(images,
remove_rotation_and_translation=remove_rotation_and_translation)
neb.interpolate()
# Test used these old defaults which are not optimial, but work
# in this particular system
neb.idpp_interpolate(fmax=0.1, optimizer=BFGS)
qn = FIRE(neb, dt=0.005, maxmove=0.05, dtmax=0.1)
qn.run(steps=20)
# Switch to CI-NEB, still removing the external degrees of freedom
# Also spesify the linearly varying spring constants
neb = NEB(images,
climb=True,
remove_rotation_and_translation=remove_rotation_and_translation)
qn = FIRE(neb, dt=0.005, maxmove=0.05, dtmax=0.1)
qn.run(fmax=fmax)
images = neb.images
nebtools = NEBTools(images)
for i in range(nimages):
image = initial.copy()
image.set_calculator(LennardJones())
images.append(image)
images.append(final)
# Define the NEB and make a linear interpolation
# with removing translational
# and rotational degrees of freedom
neb = NEB(images,
remove_rotation_and_translation=remove_rotation_and_translation)
neb.interpolate()
# Test used these old defaults which are not optimial, but work
# in this particular system
neb.idpp_interpolate(fmax=0.1, optimizer=BFGS)
qn = FIRE(neb, dt=0.005, maxmove=0.05, dtmax=0.1)
qn.run(steps=20)
# Switch to CI-NEB, still removing the external degrees of freedom
# Also spesify the linearly varying spring constants
neb = NEB(images, climb=True,
remove_rotation_and_translation=remove_rotation_and_translation)
qn = FIRE(neb, dt=0.005, maxmove=0.05, dtmax=0.1)
qn.run(fmax=fmax)
images = neb.images
nebtools = NEBTools(images)
Ef_neb, dE_neb = nebtools.get_barrier(fit=False)
from ase.build import molecule
from ase.neb import NEB
initial = molecule('C2H6')
final = initial.copy()
final.positions[2:5] = initial.positions[[3, 4, 2]]
images = [initial]
for i in range(5):
images.append(initial.copy())
images.append(final)
neb = NEB(images)
d0 = images[3].get_distance(2, 3)
neb.interpolate()
d1 = images[3].get_distance(2, 3)
neb.idpp_interpolate(fmax=0.005)
d2 = images[3].get_distance(2, 3)
print(d0, d1, d2)
assert abs(d2 - 1.74) < 0.01
from ase.build import molecule
from ase.neb import NEB
initial = molecule('C2H6')
final = initial.copy()
final.positions[2:5] = initial.positions[[3, 4, 2]]
images = [initial]
for i in range(5):
images.append(initial.copy())
images.append(final)
neb = NEB(images)
d0 = images[3].get_distance(2, 3)
neb.interpolate()
d1 = images[3].get_distance(2, 3)
neb.idpp_interpolate()
d2 = images[3].get_distance(2, 3)
print(d0, d1, d2)
assert abs(d2 - 1.74) < 0.01
from ase.structure import molecule
from ase.neb import NEB
initial = molecule('C2H6')
final = initial.copy()
final.positions[2:5] = initial.positions[[3, 4, 2]]
images = [initial]
for i in range(5):
images.append(initial.copy())
images.append(final)
neb = NEB(images)
d0 = images[3].get_distance(2, 3)
neb.interpolate()
d1 = images[3].get_distance(2, 3)
neb.idpp_interpolate()
d2 = images[3].get_distance(2, 3)
print(d0, d1, d2)
assert abs(d2 - 1.74) < 0.01
