def __init__(self):
BaseSystem.__init__(self)
# js850> we should really change this name from self.aasystem to self.aatopology
self.aasystem = self.setup_aatopology()
self.aatopology = self.aasystem
self.params.basinhopping["temperature"] = 8.
self.params.takestep["translate"] = 0.0
self.params.takestep["rotate"] = 1.6
self.params.double_ended_connect.local_connect_params.nrefine_max = 5
NEBparams = self.params.double_ended_connect.local_connect_params.NEBparams
self.params.double_ended_connect.local_connect_params.NEBparams.distance = self.aasystem.neb_distance
NEBparams.max_images = 200
NEBparams.image_density = 3.0
NEBparams.iter_density = 10
NEBparams.k = 400.
NEBparams.adjustk_freq = 5
NEBparams.reinterpolate = 50
NEBparams.adaptive_nimages = True
NEBparams.adaptive_niter = True
NEBparams.interpolator = self.aasystem.interpolate
NEBparams.verbose = -1
# quenchParams = NEBparams.NEBquenchParams
# quenchParams["nsteps"] = 1000
# quenchParams["iprint"] = -1
# quenchParams["maxstep"] = 0.1
# quenchParams["maxErise"] = 1000
# quenchParams["tol"] = 1e-6
tsSearchParams = self.params.double_ended_connect.local_connect_params.tsSearchParams
tsSearchParams["nfail_max"] = 20
def __init__(self,
natoms,
eps=1.,
sig=1.,
c=1.,
boxvec=[10., 10., 10.],
rcut=2.5,
n=10,
m=8):
BaseSystem.__init__(self)
self.potential_kwargs = dict(eps=eps,
sig=sig,
c=c,
boxvec=boxvec,
rcut=rcut,
n=n,
m=m)
self.natoms = natoms
self.boxvec = np.array(boxvec, dtype=float)
self.periodic = True
self.r0 = sig # the equilibrium separation of the atoms.
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
def __init__(self):
BaseSystem.__init__(self)
self.aasystem = self.setup_aatopology()
self.params.basinhopping["temperature"]=8.
self.params.takestep["translate"]=0.0
self.params.takestep["rotate"]=1.6
self.params.double_ended_connect.local_connect_params.nrefine_max = 5
NEBparams = self.params.double_ended_connect.local_connect_params.NEBparams
self.params.double_ended_connect.local_connect_params.NEBparams.distance=self.aasystem.neb_distance
NEBparams.max_images=200
NEBparams.image_density=3.0
NEBparams.iter_density=10
NEBparams.k = 400.
NEBparams.adjustk_freq = 5
NEBparams.reinterpolate = 50
NEBparams.adaptive_nimages = True
NEBparams.adaptive_niter = True
NEBparams.interpolator=self.aasystem.interpolate
NEBparams.verbose = -1
quenchParams = NEBparams.NEBquenchParams
#quenchParams["nsteps"] = 1000
# quenchParams["iprint"] = -1
# quenchParams["maxstep"] = 0.1
# quenchParams["maxErise"] = 1000
# quenchParams["tol"] = 1e-6
#
tsSearchParams = self.params.double_ended_connect.local_connect_params.tsSearchParams
tsSearchParams["nfail_max"]=20
def __init__(self, nspins, p=3):
BaseSystem.__init__(self)
self.nspins = nspins
self.p = p
self.interactions = self.get_interactions(self.nspins, self.p)
self.pot = self.get_potential()
self.zerov = None
self.setup_params(self.params)
def __init__(self, nspins, p=3):
BaseSystem.__init__(self)
self.nspins = nspins
self.p = p
self.interactions = self.get_interactions(self.nspins, self.p)
self.pot = self.get_potential()
self.zerov = None
self.setup_params(self.params)
def __init__(self, x_train_data, y_train_data, scale=1, dtype='float64', device='cpu'):
BaseSystem.__init__(self)
self.dtype = dtype
self.device = device
self.x_train_data = np.array(x_train_data, dtype=dtype)
self.y_train_data = np.array(y_train_data, dtype=dtype)
self.setup_params(self.params)
self.scale = scale
def __init__(self, dim=[4, 4], phi_disorder=np.pi, phases=None):
BaseSystem.__init__(self)
self.one_frozen = True
self.dim = dim
self.phi_disorder = phi_disorder
self.pot = self.get_potential(phases=phases)
self.nspins = np.prod(dim)
self.setup_params(self.params)
def __init__(self, dim=[4, 4], phi_disorder=np.pi, phases=None):
BaseSystem.__init__(self)
self.one_frozen = True
self.dim = dim
self.phi_disorder = phi_disorder
self.pot = self.get_potential(phases=phases)
self.nspins = np.prod(dim)
self.setup_params(self.params)
def __init__(self, nspins, p=3, interactions=None):
BaseSystem.__init__(self)
self.nspins = nspins
self.p = p
if interactions is not None:
self.interactions = np.array(interactions)
else:
self.interactions = self.get_interactions(self.nspins, self.p)
self.pot = self.get_potential()
self.setup_params(self.params)
def __init__(self, nspins, p=3, interactions=None):
BaseSystem.__init__(self)
self.nspins = nspins
self.p = p
if interactions is not None:
self.interactions = np.array(interactions)
else:
self.interactions = self.get_interactions(self.nspins, self.p)
self.pot = self.get_potential()
self.setup_params(self.params)
def __init__(self, natoms, p=5.206, q=1.220, A=0.6124, xi=2.441):
BaseSystem.__init__(self)
self.potential_kwargs = dict(p=p, q=q, A=A, xi=xi)
self.natoms = natoms
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
def __init__(self, natoms, d=4.114825, A=1.887117, beta=0.0, c=3.25,
c0=43.4475218, c1=-31.9332978, c2=6.0804249):
BaseSystem.__init__(self)
self.potential_kwargs = dict(d=d, A=A, beta=beta, c=c, c0=c0, c1=c1, c2=c2)
self.natoms = natoms
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
def __init__(self, natoms,
p=5.206, q=1.220, A=0.6124, xi=2.441):
BaseSystem.__init__(self)
self.potential_kwargs = dict(p=p,q=q,A=A,xi=xi)
self.natoms = natoms
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
def __init__(self, dims=[4,4], field_disorder=1., disorder=False):
BaseSystem.__init__(self)
self.dims = dims
self.field_disorder = field_disorder
self.nspins = np.prod(dims)
self.one_frozen = False
if field_disorder == 0. or not disorder:
self.one_frozen = True
self.pot = self.get_potential()
self.setup_params(self.params)
def __init__(self, dims=[4,4], field_disorder=1., disorder=False):
BaseSystem.__init__(self)
self.dims = dims
self.field_disorder = field_disorder
self.nspins = np.prod(dims)
self.one_frozen = False
if field_disorder == 0. or not disorder:
self.one_frozen = True
self.pot = self.get_potential()
self.setup_params(self.params)
def __init__(self, natoms, eps=1., sig=1., c=1., boxvec=[10., 10., 10.], rcut=2.5,
n=10, m=8):
BaseSystem.__init__(self)
self.potential_kwargs = dict(eps=eps, sig=sig, c=c, boxvec=boxvec, rcut=rcut, n=n, m=m)
self.natoms = natoms
self.boxvec = np.array(boxvec, dtype=float)
self.periodic = True
self.r0 = sig # the equilibrium separation of the atoms.
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
def __init__(self,
nspins,
p=3,
interactions=None,
dtype='float64',
device='cpu'):
BaseSystem.__init__(self)
self.nspins = nspins
self.p = p
if interactions is not None:
self.interactions = np.array(interactions)
else:
self.interactions = self.get_interactions(self.nspins, self.p,
dtype)
self.pot = self.get_potential(dtype=dtype, device=device)
self.setup_params(self.params)
def __init__(self,
natoms,
d=4.114825,
A=1.887117,
beta=0.0,
c=3.25,
c0=43.4475218,
c1=-31.9332978,
c2=6.0804249):
BaseSystem.__init__(self)
self.potential_kwargs = dict(d=d,
A=A,
beta=beta,
c=c,
c0=c0,
c1=c1,
c2=c2)
self.natoms = natoms
self.params.database.accuracy = 1e-3
self.params.basinhopping["temperature"] = 1.0
self.params.gui.basinhopping_nsteps = 100
