def produce_fc2(self,
forces_fc2,
displacement_dataset=None,
is_translational_symmetry=False,
is_permutation_symmetry=False,
translational_symmetry_type=None):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc2, disp_dataset['first_atoms']):
disp1['forces'] = forces
self._fc2 = get_fc2(self._phonon_supercell,
self._phonon_supercell_symmetry,
disp_dataset)
if is_permutation_symmetry:
set_permutation_symmetry(self._fc2)
if is_translational_symmetry:
tsym_type = 1
else:
tsym_type = 0
if translational_symmetry_type:
tsym_type = translational_symmetry_type
if tsym_type:
set_translational_invariance(
self._fc2,
translational_symmetry_type=tsym_type)
def produce_fc2(self,
forces_fc2,
displacement_dataset=None,
symmetrize_fc2=False,
is_compact_fc=False,
use_alm=False):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
if use_alm:
from phono3py.other.alm_wrapper import get_fc2 as get_fc2_alm
self._fc2 = get_fc2_alm(self._phonon_supercell, forces_fc2,
disp_dataset,
self._phonon_supercell_symmetry)
else:
for forces, disp1 in zip(forces_fc2, disp_dataset['first_atoms']):
disp1['forces'] = forces
if is_compact_fc:
p2s_map = self._phonon_primitive.get_primitive_to_supercell_map(
)
else:
p2s_map = None
self._fc2 = get_fc2(self._phonon_supercell,
self._phonon_supercell_symmetry,
disp_dataset,
atom_list=p2s_map)
if symmetrize_fc2:
if is_compact_fc:
symmetrize_compact_force_constants(self._fc2,
self._phonon_primitive)
else:
symmetrize_force_constants(self._fc2)
def produce_fc2(self,
forces_fc2,
displacement_dataset=None,
is_translational_symmetry=False,
is_permutation_symmetry=False,
translational_symmetry_type=None,
use_alm=False):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
if use_alm:
from phono3py.other.alm_wrapper import get_fc2 as get_fc2_alm
self._fc2 = get_fc2_alm(self._phonon_supercell, forces_fc2,
disp_dataset,
self._phonon_supercell_symmetry)
else:
for forces, disp1 in zip(forces_fc2, disp_dataset['first_atoms']):
disp1['forces'] = forces
self._fc2 = get_fc2(self._phonon_supercell,
self._phonon_supercell_symmetry, disp_dataset)
if is_permutation_symmetry:
set_permutation_symmetry(self._fc2)
if is_translational_symmetry:
tsym_type = 1
else:
tsym_type = 0
if translational_symmetry_type:
tsym_type = translational_symmetry_type
if tsym_type:
set_translational_invariance(
self._fc2, translational_symmetry_type=tsym_type)
def get_fc3(supercell,
primitive,
disp_dataset,
symmetry,
is_compact_fc=False,
verbose=False):
# fc2 has to be full matrix to compute delta-fc2
# p2s_map elements are extracted if is_compact_fc=True at the last part.
fc2 = get_fc2(supercell, symmetry, disp_dataset)
fc3 = _get_fc3_least_atoms(supercell,
primitive,
disp_dataset,
fc2,
symmetry,
is_compact_fc=is_compact_fc,
verbose=verbose)
if verbose:
print("Expanding fc3")
first_disp_atoms = np.unique(
[x['number'] for x in disp_dataset['first_atoms']])
rotations = symmetry.get_symmetry_operations()['rotations']
lattice = supercell.get_cell().T
permutations = symmetry.get_atomic_permutations()
if is_compact_fc:
s2p_map = primitive.get_supercell_to_primitive_map()
p2s_map = primitive.get_primitive_to_supercell_map()
p2p_map = primitive.get_primitive_to_primitive_map()
s2compact = np.array([p2p_map[i] for i in s2p_map], dtype='intc')
for i in first_disp_atoms:
assert i in p2s_map
target_atoms = [i for i in p2s_map if i not in first_disp_atoms]
else:
s2compact = np.arange(supercell.get_number_of_atoms(), dtype='intc')
target_atoms = [i for i in s2compact if i not in first_disp_atoms]
distribute_fc3(fc3,
first_disp_atoms,
target_atoms,
lattice,
rotations,
permutations,
s2compact,
verbose=verbose)
if 'cutoff_distance' in disp_dataset:
if verbose:
print("Cutting-off fc3 (cut-off distance: %f)" %
disp_dataset['cutoff_distance'])
if is_compact_fc:
print("cutoff_fc3 doesn't support compact-fc3 yet.")
raise ValueError
cutoff_fc3(fc3, supercell, disp_dataset, symmetry, verbose=verbose)
if is_compact_fc:
p2s_map = primitive.get_primitive_to_supercell_map()
fc2 = np.array(fc2[p2s_map], dtype='double', order='C')
return fc2, fc3
def produce_fc2(
self,
forces_fc2,
displacement_dataset=None,
is_translational_symmetry=False,
is_permutation_symmetry=False,
translational_symmetry_type=None,
):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc2, disp_dataset["first_atoms"]):
disp1["forces"] = forces
self._fc2 = get_fc2(self._phonon_supercell, self._phonon_supercell_symmetry, disp_dataset)
if is_permutation_symmetry:
set_permutation_symmetry(self._fc2)
if is_translational_symmetry:
tsym_type = 1
else:
tsym_type = 0
if translational_symmetry_type:
tsym_type = translational_symmetry_type
if tsym_type:
set_translational_invariance(self._fc2, translational_symmetry_type=tsym_type)
def _run_force_constants_from_forces(self,
distributed_atom_list=None,
decimals=None):
if self._displacement_dataset is not None:
self._force_constants = get_fc2(
self._supercell,
self._symmetry,
self._displacement_dataset,
atom_list=distributed_atom_list,
decimals=decimals)
def produce_fc3(self,
forces_fc3,
displacement_dataset=None,
cutoff_distance=None, # set fc3 zero
is_translational_symmetry=False,
is_permutation_symmetry=False,
is_permutation_symmetry_fc2=False,
translational_symmetry_type=None):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc3, disp_dataset['first_atoms']):
disp1['forces'] = forces
fc2 = get_fc2(self._supercell, self._symmetry, disp_dataset)
if is_permutation_symmetry_fc2:
set_permutation_symmetry(fc2)
if is_translational_symmetry:
tsym_type = 1
else:
tsym_type = 0
if translational_symmetry_type:
tsym_type = translational_symmetry_type
if tsym_type:
set_translational_invariance(
fc2,
translational_symmetry_type=tsym_type)
count = len(disp_dataset['first_atoms'])
for disp1 in disp_dataset['first_atoms']:
for disp2 in disp1['second_atoms']:
disp2['delta_forces'] = forces_fc3[count] - disp1['forces']
count += 1
self._fc3 = get_fc3(
self._supercell,
disp_dataset,
fc2,
self._symmetry,
translational_symmetry_type=tsym_type,
is_permutation_symmetry=is_permutation_symmetry,
verbose=self._log_level)
# Set fc3 elements zero beyond cutoff_distance
if cutoff_distance:
if self._log_level:
print("Cutting-off fc3 by zero (cut-off distance: %f)" %
cutoff_distance)
self.cutoff_fc3_by_zero(cutoff_distance)
# Set fc2
if self._fc2 is None:
self._fc2 = fc2
def produce_fc3(
self,
forces_fc3,
displacement_dataset=None,
cutoff_distance=None, # set fc3 zero
is_translational_symmetry=False,
is_permutation_symmetry=False,
is_permutation_symmetry_fc2=False,
translational_symmetry_type=None,
):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc3, disp_dataset["first_atoms"]):
disp1["forces"] = forces
fc2 = get_fc2(self._supercell, self._symmetry, disp_dataset)
if is_permutation_symmetry_fc2:
set_permutation_symmetry(fc2)
if is_translational_symmetry:
tsym_type = 1
else:
tsym_type = 0
if translational_symmetry_type:
tsym_type = translational_symmetry_type
if tsym_type:
set_translational_invariance(fc2, translational_symmetry_type=tsym_type)
count = len(disp_dataset["first_atoms"])
for disp1 in disp_dataset["first_atoms"]:
for disp2 in disp1["second_atoms"]:
disp2["delta_forces"] = forces_fc3[count] - disp1["forces"]
count += 1
self._fc3 = get_fc3(
self._supercell,
disp_dataset,
fc2,
self._symmetry,
translational_symmetry_type=tsym_type,
is_permutation_symmetry=is_permutation_symmetry,
verbose=self._log_level,
)
# Set fc3 elements zero beyond cutoff_distance
if cutoff_distance:
if self._log_level:
print("Cutting-off fc3 by zero (cut-off distance: %f)" % cutoff_distance)
self.cutoff_fc3_by_zero(cutoff_distance)
# Set fc2
if self._fc2 is None:
self._fc2 = fc2
def _run_force_constants_from_forces(self,
distributed_atom_list=None,
decimals=None,
computation_algorithm="svd"):
if self._displacement_dataset is not None:
self._force_constants = get_fc2(
self._supercell,
self._symmetry,
self._displacement_dataset,
atom_list=distributed_atom_list,
decimals=decimals,
computation_algorithm=computation_algorithm)
def _run_force_constants_from_forces(self,
distributed_atom_list=None,
decimals=None,
computation_algorithm="svd"):
if self._displacement_dataset is not None:
self._force_constants = get_fc2(
self._supercell,
self._symmetry,
self._displacement_dataset,
atom_list=distributed_atom_list,
decimals=decimals,
computation_algorithm=computation_algorithm)
def produce_fc4(
self,
forces_fc4,
displacement_dataset,
translational_symmetry_type=0,
is_permutation_symmetry=False,
is_permutation_symmetry_fc3=False,
is_permutation_symmetry_fc2=False,
):
disp_dataset = displacement_dataset
file_count = 0
for disp1 in disp_dataset["first_atoms"]:
disp1["forces"] = forces_fc4[file_count]
file_count += 1
self._fc2 = get_fc2(self._supercell, self._symmetry, disp_dataset)
if is_permutation_symmetry_fc2:
set_permutation_symmetry(self._fc2)
if translational_symmetry_type:
set_translational_invariance(self._fc2, translational_symmetry_type=translational_symmetry_type)
for disp1 in disp_dataset["first_atoms"]:
for disp2 in disp1["second_atoms"]:
disp2["forces"] = forces_fc4[file_count]
disp2["delta_forces"] = disp2["forces"] - disp1["forces"]
file_count += 1
self._fc3 = get_fc3(
self._supercell,
disp_dataset,
self._fc2,
self._symmetry,
translational_symmetry_type=translational_symmetry_type,
is_permutation_symmetry=is_permutation_symmetry_fc3,
verbose=self._log_level,
)
for disp1 in disp_dataset["first_atoms"]:
for disp2 in disp1["second_atoms"]:
for disp3 in disp2["third_atoms"]:
disp3["delta_forces"] = forces_fc4[file_count] - disp2["forces"]
file_count += 1
self._fc4 = get_fc4(
self._supercell,
disp_dataset,
self._fc3,
self._symmetry,
translational_symmetry_type=translational_symmetry_type,
is_permutation_symmetry=is_permutation_symmetry,
verbose=self._log_level,
)
def produce_fc4(self,
forces_fc4,
displacement_dataset,
translational_symmetry_type=0,
is_permutation_symmetry=False,
is_permutation_symmetry_fc3=False,
is_permutation_symmetry_fc2=False):
disp_dataset = displacement_dataset
file_count = 0
for disp1 in disp_dataset['first_atoms']:
disp1['forces'] = forces_fc4[file_count]
file_count += 1
self._fc2 = get_fc2(self._supercell, self._symmetry, disp_dataset)
if is_permutation_symmetry_fc2:
set_permutation_symmetry(self._fc2)
if translational_symmetry_type:
set_translational_invariance(
self._fc2,
translational_symmetry_type=translational_symmetry_type)
for disp1 in disp_dataset['first_atoms']:
for disp2 in disp1['second_atoms']:
disp2['forces'] = forces_fc4[file_count]
disp2['delta_forces'] = disp2['forces'] - disp1['forces']
file_count += 1
self._fc3 = get_fc3(
self._supercell,
disp_dataset,
self._fc2,
self._symmetry,
translational_symmetry_type=translational_symmetry_type,
is_permutation_symmetry=is_permutation_symmetry_fc3,
verbose=self._log_level)
for disp1 in disp_dataset['first_atoms']:
for disp2 in disp1['second_atoms']:
for disp3 in disp2['third_atoms']:
disp3['delta_forces'] = (forces_fc4[file_count] -
disp2['forces'])
file_count += 1
self._fc4 = get_fc4(
self._supercell,
disp_dataset,
self._fc3,
self._symmetry,
translational_symmetry_type=translational_symmetry_type,
is_permutation_symmetry=is_permutation_symmetry,
verbose=self._log_level)
def produce_fc2(self,
forces_fc2,
displacement_dataset=None,
is_permutation_symmetry=False,
is_translational_symmetry=False):
if displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc2, disp_dataset['first_atoms']):
disp1['forces'] = forces
self._fc2 = get_fc2(self._phonon_supercell,
self._phonon_supercell_symmetry,
disp_dataset)
if is_permutation_symmetry:
set_permutation_symmetry(self._fc2)
if is_translational_symmetry:
set_translational_invariance(self._fc2)
def produce_fc2(self,
forces_fc2,
displacement_dataset=None,
symmetrize_fc2=False,
is_compact_fc=False,
use_alm=False,
alm_options=None):
if displacement_dataset is None:
if self._phonon_displacement_dataset is None:
disp_dataset = self._displacement_dataset
else:
disp_dataset = self._phonon_displacement_dataset
else:
disp_dataset = displacement_dataset
for forces, disp1 in zip(forces_fc2, disp_dataset['first_atoms']):
disp1['forces'] = forces
if is_compact_fc:
p2s_map = self._phonon_primitive.p2s_map
else:
p2s_map = None
if use_alm:
from phonopy.interface.alm import get_fc2 as get_fc2_alm
self._fc2 = get_fc2_alm(self._phonon_supercell,
self._phonon_primitive,
disp_dataset,
atom_list=p2s_map,
alm_options=alm_options,
log_level=self._log_level)
else:
self._fc2 = get_fc2(self._phonon_supercell,
self._phonon_supercell_symmetry,
disp_dataset,
atom_list=p2s_map)
if symmetrize_fc2:
if is_compact_fc:
symmetrize_compact_force_constants(
self._fc2, self._phonon_primitive)
else:
symmetrize_force_constants(self._fc2)
def get_fc3(
supercell: PhonopyAtoms,
primitive: Primitive,
disp_dataset,
symmetry: Symmetry,
is_compact_fc=False,
verbose=False,
):
"""Calculate fc3.
Even when 'cutoff_distance' in dataset, all displacements are in the dataset,
but force-sets out of cutoff-pair-distance are zero. fc3 is solved in exactly
the same way. Then post-clean-up
is performed.
"""
# fc2 has to be full matrix to compute delta-fc2
# p2s_map elements are extracted if is_compact_fc=True at the last part.
fc2 = get_fc2(supercell, symmetry, disp_dataset)
fc3 = _get_fc3_least_atoms(
supercell,
primitive,
disp_dataset,
fc2,
symmetry,
is_compact_fc=is_compact_fc,
verbose=verbose,
)
if verbose:
print("Expanding fc3.")
first_disp_atoms = np.unique(
[x["number"] for x in disp_dataset["first_atoms"]])
rotations = symmetry.symmetry_operations["rotations"]
lattice = supercell.cell.T
permutations = symmetry.atomic_permutations
if is_compact_fc:
s2p_map = primitive.s2p_map
p2s_map = primitive.p2s_map
p2p_map = primitive.p2p_map
s2compact = np.array([p2p_map[i] for i in s2p_map], dtype="int_")
for i in first_disp_atoms:
assert i in p2s_map
target_atoms = [i for i in p2s_map if i not in first_disp_atoms]
else:
s2compact = np.arange(len(supercell), dtype="int_")
target_atoms = [i for i in s2compact if i not in first_disp_atoms]
distribute_fc3(
fc3,
first_disp_atoms,
target_atoms,
lattice,
rotations,
permutations,
s2compact,
verbose=verbose,
)
if "cutoff_distance" in disp_dataset:
if verbose:
print("Cutting-off fc3 (cut-off distance: %f)" %
disp_dataset["cutoff_distance"])
if is_compact_fc:
print("cutoff_fc3 doesn't support compact-fc3 yet.")
raise ValueError
_cutoff_fc3_for_cutoff_pairs(fc3,
supercell,
disp_dataset,
symmetry,
verbose=verbose)
if is_compact_fc:
p2s_map = primitive.p2s_map
fc2 = np.array(fc2[p2s_map], dtype="double", order="C")
return fc2, fc3
