def fetch(self):
"""Creates a motion calculator object.
Returns:
An ensemble object of the appropriate mode and with the appropriate
objects given the attributes of the InputEnsemble object.
"""
super(InputMotionBase, self).fetch()
if self.mode.fetch() == "replay":
sc = Replay(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), intraj=self.file.fetch())
elif self.mode.fetch() == "minimize":
sc = GeopMotion(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.optimizer.fetch())
elif self.mode.fetch() == "neb":
sc = NEBMover(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.neb_optimizer.fetch())
elif self.mode.fetch() == "dynamics":
sc = Dynamics(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.dynamics.fetch())
elif self.mode.fetch() == "vibrations":
sc = DynMatrixMover(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.vibrations.fetch())
elif self.mode.fetch() == "alchemy":
sc = AlchemyMC(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.alchemy.fetch())
elif self.mode.fetch() == "instanton":
sc = InstantonMotion(fixcom=self.fixcom.fetch(), fixatoms=self.fixatoms.fetch(), **self.instanton.fetch())
elif self.mode.fetch() == "t_ramp":
sc = TemperatureRamp(**self.t_ramp.fetch())
elif self.mode.fetch() == "p_ramp":
sc = PressureRamp(**self.p_ramp.fetch())
else:
sc = Motion()
# raise ValueError("'" + self.mode.fetch() + "' is not a supported motion calculation mode.")
return sc
def __init__(self,
mode,
geop,
nstep,
a0,
ncell,
nvac,
nsi,
nmg,
neval,
diffusion_barrier_al,
diffusion_prefactor_al,
diffusion_barrier_mg,
diffusion_prefactor_mg,
diffusion_barrier_si,
diffusion_prefactor_si,
idx=[],
tottime=0,
ecache_file="",
qcache_file="",
thermostat=None,
barostat=None,
fixcom=False,
fixatoms=None,
nmts=None):
"""Initialises a "dynamics" motion object.
Args:
dt: The timestep of the simulation algorithms.
fixcom: An optional boolean which decides whether the centre of mass
motion will be constrained or not. Defaults to False.
"""
# This will generate a lattice model based on a primitive FCC cell. the lattice is represented in three ways:
# 1. as a string in which each lattice site is identified by a letter
# 2. by a list of the lattice sites in 3D space, in 1-1 mapping with the letters
# 3. by a list of the atoms, whose lattice position is indicated by an integer
self.nstep = nstep
self.ncell = ncell
self.nvac = nvac
self.nsi = nsi
self.nmg = nmg
self.nsites = self.ncell**3
self.natoms = self.nsites - self.nvac
self.neval = neval
self.diffusion_barrier_al = diffusion_barrier_al
self.diffusion_prefactor_al = diffusion_prefactor_al
if diffusion_barrier_mg > 0:
self.diffusion_barrier_mg = diffusion_barrier_mg
else:
self.diffusion_barrier_mg = diffusion_barrier_al
if diffusion_barrier_si > 0:
self.diffusion_barrier_si = diffusion_barrier_si
else:
self.diffusion_barrier_si = diffusion_barrier_al
if diffusion_prefactor_mg > 0:
self.diffusion_prefactor_mg = diffusion_prefactor_mg
else:
self.diffusion_prefactor_mg = diffusion_prefactor_al
if diffusion_prefactor_si > 0:
self.diffusion_prefactor_si = diffusion_prefactor_si
else:
self.diffusion_prefactor_si = diffusion_prefactor_al
self.barriers = {
"A": self.diffusion_barrier_al,
"M": self.diffusion_barrier_mg,
"S": self.diffusion_barrier_si
}
self.prefactors = {
"A": self.diffusion_prefactor_al,
"M": self.diffusion_prefactor_mg,
"S": self.diffusion_prefactor_si
}
self.a0 = a0
cell = np.zeros((3, 3))
cell[0] = [
0.7071067811865475, 0.35355339059327373, 0.35355339059327373
]
cell[1] = [0., 0.6123724356957945, 0.20412414523193154]
cell[2] = [0., 0., 0.5773502691896258]
self.scell = self.a0 * cell
self.dcell = Cell()
self.dcell.h = self.scell * self.ncell
print "LATTICE PARAM ", self.a0
# this is the list of lattice sites, in 3D coordinates
ix, iy, iz = np.meshgrid(range(self.ncell),
range(self.ncell),
range(self.ncell),
indexing='ij')
self.sites = np.dot(
np.asarray([ix.flatten(), iy.flatten(),
iz.flatten()]).T, self.scell.T)
print len(self.sites), self.nsites, "###"
# now we build list of nearest neighbors (fcc-lattice hardcoded!)
self.neigh = np.zeros((self.nsites, 12), int)
nneigh = np.zeros(self.nsites, int)
# could be done in a more analytic way but whatever, I'm too lazy
a02 = 1.01 * 0.5 * self.a0**2 # perhaps 1.01 it is not enough, must check!
for i in xrange(
self.nsites): # determines the connectivity of the lattice
rij = self.sites.copy().flatten()
for j in xrange(self.nsites):
rij[3 * j:3 * j + 3] -= self.sites[i]
self.dcell.array_pbc(rij)
rij.shape = (self.nsites, 3)
for j in xrange(i):
if np.dot(rij[j], rij[j]) < a02: # found nearest neighbor
self.neigh[i, nneigh[i]] = j
self.neigh[j, nneigh[j]] = i
nneigh[i] += 1
nneigh[j] += 1
self.idx = idx
# the KMC step is variable and so it cannot be stored as proper timing
dd(self).dt = depend_value(name="dt", value=0.0)
self.fixatoms = np.asarray([])
self.fixcom = True
self.geop = [None] * self.neval
# geop should not trigger exit if there is early convergence, but just carry on.
# we hard-code this option to avoid early-termination that would be hard to debug for a user
geop["exit_on_convergence"] = False
for i in xrange(self.neval):
# geometry optimizer should not have *any* hystory dependence
self.geop[i] = GeopMotion(
fixcom=fixcom, fixatoms=fixatoms, **geop
) #mode="cg", ls_options={"tolerance": 1, "iter": 20, "step": 1e-3, "adaptive": 0.0}, tolerances={"energy": 1e-7, "force": 1e-2, "position": 1e-4}, ) #!TODO: set the geop parameters properly
# dictionary of previous energy evaluations - kind of tricky to use this with the omaker thingie
self.ecache_file = ecache_file
self.qcache_file = qcache_file
try:
ff = open(self.ecache_file, "rb")
self.ecache = pickle.load(ff)
ff.close()
ff = open(self.qcache_file, "rb")
self.qcache = pickle.load(ff)
ff.close()
print "Loaded %d cached energies" % (len(self.ecache))
except:
print "Couldn't load cache files " + self.ecache_file + "," + self.qcache_file + " - resetting"
self.ecache = {}
self.qcache = {}
self.ncache = len(self.ecache)
self.ncache_stored = self.ncache
# no TS evaluation implemented yet
self.tscache = {}
self.tottime = tottime
def fetch(self):
"""Creates a motion calculator object.
Returns:
An ensemble object of the appropriate mode and with the appropriate
objects given the attributes of the InputEnsemble object.
"""
super(InputMotionBase, self).fetch()
if self.mode.fetch() == "replay":
sc = Replay(
fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
intraj=self.file.fetch(),
)
elif self.mode.fetch() == "minimize":
sc = GeopMotion(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.optimizer.fetch())
elif self.mode.fetch() == "neb":
raise ValueError(
"The nudged elastic band calculation has been temporarily disabled until further bug-fixes."
)
# sc = NEBMover(
# fixcom=self.fixcom.fetch(),
# fixatoms=self.fixatoms.fetch(),
# **self.neb_optimizer.fetch()
# )
elif self.mode.fetch() == "dynamics":
sc = Dynamics(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.dynamics.fetch())
elif self.mode.fetch() == "constrained_dynamics":
sc = ConstrainedDynamics(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.constrained_dynamics.fetch())
elif self.mode.fetch() == "vibrations":
sc = DynMatrixMover(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.vibrations.fetch())
elif self.mode.fetch() == "normalmodes":
sc = NormalModeMover(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.normalmodes.fetch())
elif self.mode.fetch() == "scp":
sc = SCPhononsMover(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.scp.fetch())
elif self.mode.fetch() == "alchemy":
sc = AlchemyMC(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.alchemy.fetch())
elif self.mode.fetch() == "atomswap":
sc = AtomSwap(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.atomswap.fetch())
elif self.mode.fetch() == "instanton":
sc = InstantonMotion(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.instanton.fetch())
elif self.mode.fetch() == "planetary":
sc = Planetary(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.planetary.fetch())
elif self.mode.fetch() == "t_ramp":
sc = TemperatureRamp(**self.t_ramp.fetch())
elif self.mode.fetch() == "p_ramp":
sc = PressureRamp(**self.p_ramp.fetch())
elif self.mode.fetch() == "al-kmc":
sc = AlKMC(fixcom=self.fixcom.fetch(),
fixatoms=self.fixatoms.fetch(),
**self.al6xxx_kmc.fetch())
else:
sc = Motion()
# raise ValueError("'" + self.mode.fetch() + "' is not a supported motion calculation mode.")
return sc