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, 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, 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, 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)