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 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)