def __init__(self, start_run, end_run, method):
path = method.path(start_run.system())
Run.__init__(self,
path,
identifier=end_run.system().name(),
program=AseInterface(Siesta()),
dependency_runs=(start_run, end_run),
)
self.__start_run = start_run
self.__end_run = end_run
self.__method = method
def runDirectory(self):
if self.__make_sub_directory:
path = Run.runDirectory(self)
else:
path = self.path()
return path
def directoryBaseName(self):
system = self.system()
if isinstance(system, Run):
basename = system.directoryBaseName()
else:
basename = Run.directoryBaseName(self)
return basename
def __init__(self,
system,
method=Siesta(),
path=DEFAULT,
identifier=DEFAULT,
parameters=DEFAULT,
inputs=tuple(),
):
parameters = system.defaultParameters(parameters)
identifier = parameters.identifier()
self.__parameters=parameters
self.__system = system.fullyUnrelaxed()
self.__method = method
Run.__init__(
self,
path=path,
identifier=identifier,
inputs=inputs,
)
def __init__(self,
system,
method=NickTransiesta(),
path=DEFAULT,
identifier=None,
parameters=DEFAULT,
inputs=tuple(),
):
self.__system = system
self.__method = method
self.__parameters = parameters
inputs = list(inputs)
inputs.extend(self.determineDependencies(system))
Run.__init__(
self,
path=path,
method=method,
identifier=identifier,
inputs=inputs,
)
def write(self):
Run.write(self)
method = self.__method
initial, final = self.makeInitialAndFinal()
kpts = method.setKpts(initial, method.correlationLength())
initial.set_calculator(method.calculator(kpts, label='siesta_0'))
groups = groupAtoms(initial, (2,), tolerance=1e-1)
max_z = groups[1].positions[:, 2].max()
initial = fixBelow(initial, max_z)
final = fixBelow(final, max_z)
diff = final.positions - initial.positions
diff = vectorLength(diff, 1)
if diff.max() < 0.4:
with open(self.runFile(), 'w') as f:
f.write("""raise Exception('Initial and final image too close.')""")
return
n_images = int(np.ceil(diff.max()/0.4))
images = [initial]
for i in range(n_images):
image = initial.copy()
image = fixBelow(image, max_z)
images.append(image)
final.set_calculator(method.calculator(kpts, label='siesta_%d'%i))
images.append(final)
neb = NEB(images)
neb.interpolate()
filename = join(self.runDirectory(), 'neb.traj')
if not os.path.exists(filename):
io.write(filename, images)
kpts_string = '(%d, %d, %d)'%tuple(kpts)
with open(self.runFile(), 'w') as f:
f.write(
"""from ase import io
from ase.neb import NEB
from ase.optimize import FIRE, BFGS
from Methods import TTT
images = io.read('neb.traj@-%d:')
for i, image in enumerate(images):
image.set_calculator(TTT.calculator(kpts=%s,"""%(n_images + 2, kpts_string) + """label='siesta_%d'%i))
image.get_total_energy()
""" + """
k=0.5
neb = NEB(images, k=k, climb=True)
qn = FIRE(neb, trajectory='neb.traj')
qn.run(fmax=%.3f)
"""%(method.parameters()['force_tolerance'], method.parameters()['force_tolerance'])
)
self.program().saveRunScript(self.runDirectory())
pseudo_dir = join(self.runDirectory(), 'PSEUDO')
if not os.path.exists(pseudo_dir):
os.makedirs(pseudo_dir)
self.program().copyPseudoPotentials(path=pseudo_dir,
atoms=initial,
parameters=method.parameters(),
)