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 generate_enlarged_force_constants(self):
"""
natoms: The number of atoms in the enlarged cell.
"""
enlarged_cell = self._enlarged_cell
scaled_positions = enlarged_cell.get_scaled_positions()
symbols = enlarged_cell.get_chemical_symbols()
s2u_map = enlarged_cell.get_supercell_to_unitcell_map()
natoms = enlarged_cell.get_number_of_atoms()
enlarged_force_constants = np.zeros((natoms, natoms, 3, 3))
for i in range(natoms):
i_equivalent = s2u_map[i]
relative_positions = self._relative_positions_site[i_equivalent]
fc_tmp1 = self._force_constants_site[i_equivalent]
for relative_position, fc_tmp2 in zip(relative_positions, fc_tmp1):
j = get_index_at_relative_position(
i,
scaled_positions,
relative_position,
symprec=self._symprec)
s_i = symbols[i]
s_j = symbols[j]
enlarged_force_constants[i, j] += fc_tmp2[(s_i, s_j)]
set_permutation_symmetry(enlarged_force_constants)
set_translational_invariance_for_diagonal(enlarged_force_constants)
self._fc_enlarged = enlarged_force_constants
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 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_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 get_constrained_fc2(
supercell,
dataset_second_atoms,
atom1,
reduced_site_sym,
translational_symmetry_type,
is_permutation_symmetry,
symprec,
):
"""
dataset_second_atoms: [{'number': 7,
'displacement': [],
'delta_forces': []}, ...]
"""
num_atom = supercell.get_number_of_atoms()
fc2 = np.zeros((num_atom, num_atom, 3, 3), dtype="double")
atom_list = np.unique([x["number"] for x in dataset_second_atoms])
for atom2 in atom_list:
disps2 = []
sets_of_forces = []
for disps_second in dataset_second_atoms:
if atom2 != disps_second["number"]:
continue
bond_sym = get_bond_symmetry(reduced_site_sym, supercell.get_scaled_positions(), atom1, atom2, symprec)
disps2.append(disps_second["displacement"])
sets_of_forces.append(disps_second["delta_forces"])
solve_force_constants(fc2, atom2, disps2, sets_of_forces, supercell, bond_sym, symprec)
# Shift positions according to set atom1 is at origin
lattice = supercell.get_cell().T
positions = supercell.get_scaled_positions()
pos_center = positions[atom1].copy()
positions -= pos_center
distribute_force_constants(
fc2,
range(num_atom),
atom_list,
lattice,
positions,
np.array(reduced_site_sym, dtype="intc", order="C"),
np.zeros((len(reduced_site_sym), 3), dtype="double"),
symprec,
)
if translational_symmetry_type:
set_translational_invariance(fc2, translational_symmetry_type=translational_symmetry_type)
if is_permutation_symmetry:
set_permutation_symmetry(fc2)
return fc2
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 get_constrained_fc2(supercell, dataset_second_atoms, atom1,
reduced_site_sym, translational_symmetry_type,
is_permutation_symmetry, symprec):
"""
dataset_second_atoms: [{'number': 7,
'displacement': [],
'delta_forces': []}, ...]
"""
num_atom = supercell.get_number_of_atoms()
fc2 = np.zeros((num_atom, num_atom, 3, 3), dtype='double')
atom_list = np.unique([x['number'] for x in dataset_second_atoms])
atom_list_done = []
for atom2 in atom_list:
disps2 = []
sets_of_forces = []
for disps_second in dataset_second_atoms:
if atom2 != disps_second['number']:
continue
atom_list_done.append(atom2)
bond_sym = get_bond_symmetry(reduced_site_sym,
supercell.get_scaled_positions(),
atom1, atom2, symprec)
disps2.append(disps_second['displacement'])
sets_of_forces.append(disps_second['delta_forces'])
solve_force_constants(fc2, atom2, disps2, sets_of_forces, supercell,
bond_sym, symprec)
# Shift positions according to set atom1 is at origin
lattice = supercell.get_cell().T
positions = supercell.get_scaled_positions()
pos_center = positions[atom1].copy()
positions -= pos_center
distribute_force_constants(
fc2, range(num_atom), atom_list_done, lattice, positions,
np.array(reduced_site_sym, dtype='intc', order='C'),
np.zeros((len(reduced_site_sym), 3), dtype='double'), symprec)
if translational_symmetry_type:
set_translational_invariance(
fc2, translational_symmetry_type=translational_symmetry_type)
if is_permutation_symmetry:
set_permutation_symmetry(fc2)
return fc2
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 set_permutation_symmetry(self):
if self._fc2 is not None:
set_permutation_symmetry(self._fc2)
if self._fc3 is not None:
set_permutation_symmetry_fc3(self._fc3)
def set_permutation_symmetry(self):
if self._fc2 is not None:
set_permutation_symmetry(self._fc2)
if self._fc3 is not None:
set_permutation_symmetry_fc3(self._fc3)
