def get_fc2(supercell,
primitive,
displacements,
forces,
atom_list=None,
options=None,
log_level=0):
if options is None:
option_dict = {}
else:
option_dict = decode_options(options)
structures = []
for d, f in zip(displacements, forces):
structure = Atoms(cell=supercell.cell,
scaled_positions=supercell.scaled_positions,
numbers=supercell.numbers,
pbc=True)
structure.new_array('displacements', d)
structure.new_array('forces', f)
structure.calc = None
structures.append(structure)
cutoffs = [
option_dict['cutoff'],
]
cs = ClusterSpace(structures[0], cutoffs)
print(cs)
cs.print_orbits()
sc = StructureContainer(cs)
for structure in structures:
sc.add_structure(structure)
print(sc)
opt = Optimizer(sc.get_fit_data())
opt.train()
print(opt)
fcp = ForceConstantPotential(cs, opt.parameters)
print(fcp)
def run_hiphive(supercell, primitive, displacements, forces, options, symprec,
log_level):
"""Run hiphive
supercell : Supercell
Perfect supercell.
primitive : Primitive
Primitive cell.
displacements : ndarray
Displacements of atoms in supercell.
shape=(supercells, natom, 3)
forces : ndarray
Forces on atoms in supercell.
shape=(supercells, natom, 3)
options : str
Force constants calculation options.
log_level : int
Log control. 0: quiet, 1: normal, 2: verbose 3: debug
"""
ase_supercell = phonopy_atoms_to_ase(supercell)
ase_prim = phonopy_atoms_to_ase(primitive)
# setup training structures
structures = []
for d, f in zip(displacements, forces):
structure = ase_supercell.copy()
structure.new_array('displacements', d)
structure.new_array('forces', f)
structures.append(structure)
# parse options
if options is None:
options_dict = {}
else:
options_dict = _decode_options(options)
# select cutoff
max_cutoff = estimate_maximum_cutoff(ase_supercell) - 1e-5
if 'cutoff' in options_dict:
cutoff = options_dict['cutoff']
if cutoff > max_cutoff:
raise ValueError(
'Cutoff {:.4f} is larger than maximum allowed '
'cutoff, {:.4f}, for the given supercell.'
'\nDecrease cutoff or provide larger supercells.'.format(
cutoff, max_cutoff))
else:
cutoff = max_cutoff
# setup ClusterSpace
cutoffs = [cutoff]
cs = ClusterSpace(ase_prim, cutoffs, symprec=symprec)
cs.print_orbits()
sc = StructureContainer(cs)
for structure in structures:
sc.add_structure(structure)
n_rows, n_cols = sc.data_shape
if n_rows < n_cols:
raise ValueError('Fitting problem is under-determined.'
'\nProvide more structures or decrease cutoff.')
# Estimate error
opt = Optimizer(sc.get_fit_data(), train_size=0.75)
opt.train()
print(opt)
print('RMSE train : {:.4f}'.format(opt.rmse_train))
print('RMSE test : {:.4f}'.format(opt.rmse_test))
# Final train
opt = Optimizer(sc.get_fit_data(), train_size=1.0)
opt.train()
# get force constants
fcp = ForceConstantPotential(cs, opt.parameters)
fcs = fcp.get_force_constants(ase_supercell)
fc2 = fcs.get_fc_array(order=2)
return fc2
def run_hiphive(supercell, primitive, displacements, forces, options, symprec,
log_level):
"""Run hiphive.
supercell : Supercell
Perfect supercell.
primitive : Primitive
Primitive cell.
displacements : ndarray
Displacements of atoms in supercell.
shape=(supercells, natom, 3)
forces : ndarray
Forces on atoms in supercell.
shape=(supercells, natom, 3)
options : str
Force constants calculation options.
log_level : int
Log control. 0: quiet, 1: normal, 2: verbose 3: debug
"""
try:
from hiphive import ClusterSpace, ForceConstantPotential, StructureContainer
from hiphive.cutoffs import estimate_maximum_cutoff
from hiphive.fitting import Optimizer
from hiphive.input_output.logging_tools import set_config
except ImportError:
raise ImportError("hiPhive python module was not found.")
set_config(level=30)
ase_supercell = phonopy_atoms_to_ase(supercell)
ase_prim = phonopy_atoms_to_ase(primitive)
# setup training structures
structures = []
for d, f in zip(displacements, forces):
structure = ase_supercell.copy()
structure.new_array("displacements", d)
structure.new_array("forces", f)
structures.append(structure)
# parse options
if options is None:
options_dict = {}
else:
options_dict = _decode_options(options)
# select cutoff
max_cutoff = estimate_maximum_cutoff(ase_supercell) - 1e-5
if "cutoff" in options_dict:
cutoff = options_dict["cutoff"]
if cutoff > max_cutoff:
raise ValueError(
"Cutoff {:.4f} is larger than maximum allowed "
"cutoff, {:.4f}, for the given supercell."
"\nDecrease cutoff or provide larger supercells.".format(
cutoff, max_cutoff))
else:
cutoff = max_cutoff
# setup ClusterSpace
cutoffs = [cutoff]
cs = ClusterSpace(ase_prim, cutoffs, symprec=symprec)
cs.print_orbits()
sc = StructureContainer(cs)
for structure in structures:
sc.add_structure(structure)
n_rows, n_cols = sc.data_shape
if n_rows < n_cols:
raise ValueError("Fitting problem is under-determined."
"\nProvide more structures or decrease cutoff.")
# Estimate error
opt = Optimizer(sc.get_fit_data(), train_size=0.75)
opt.train()
print(opt)
print("RMSE train : {:.4f}".format(opt.rmse_train))
print("RMSE test : {:.4f}".format(opt.rmse_test))
# Final train
opt = Optimizer(sc.get_fit_data(), train_size=1.0)
opt.train()
# get force constants
fcp = ForceConstantPotential(cs, opt.parameters)
fcs = fcp.get_force_constants(ase_supercell)
fc2 = fcs.get_fc_array(order=2)
return fc2