def _fit_elastic_tensor(stresses, strains, strain_magnitudes,
equilibrium_structure, equilibrium_stress,
symmetric_strains_only=True):
symm_eql_stresses = copy.deepcopy(stresses)
symm_eql_strains = copy.deepcopy(strains)
if symmetric_strains_only:
all_deformations = _get_deformed_structures(equilibrium_structure,
strain_magnitudes,
symmetric_strains_only=False)[0]
symmetry_operations_dict = symmetry_reduce(all_deformations, equilibrium_structure)
deformations = [deformation for deformation in symmetry_operations_dict]
for i in range(len(deformations)):
deformation = deformations[i]
symmetry_operations = [x for x in symmetry_operations_dict[deformation]]
for symm_op in symmetry_operations:
symm_eql_strains.append(strains[i].transform(symm_op))
symm_eql_stresses.append(stresses[i].transform(symm_op))
# Fit the elastic constants
compliance_tensor = ElasticTensor.from_independent_strains(
stresses=symm_eql_stresses,
strains=symm_eql_strains,
eq_stress=equilibrium_stress
)
compliance_tensor = -1.0 * compliance_tensor # pymatgen has opposite sign convention
return symm_eql_stresses, symm_eql_strains, compliance_tensor
def set_outputs(self):
self.report('Setting Outputs')
elastic_outputs = ArrayData()
#An ugly ugly function to make the symmetry_operations_dict storable
def make_symmopdict_aiidafriendly(symmopdict):
aiida_symmopdict = dict((str(k).replace('.',','), [x.as_dict() for x in v])
for k, v in symmopdict.items())
return aiida_symmopdict
equilibrium_structure = self.ctx.equilibrium_structure.get_pymatgen_structure()
symmetry_operations_dict = symmetry_reduce(self.ctx.deformations,
equilibrium_structure)
symmetry_mapping = make_symmopdict_aiidafriendly(symmetry_operations_dict)
symmetry_mapping = Dict(dict=symmetry_mapping)
elastic_outputs.set_array('strains', np.array(self.ctx.strains))
elastic_outputs.set_array('stresses', np.array(self.ctx.stresses))
elastic_outputs.set_array('elastic_tensor',
np.array(self.ctx.elastic_tensor))
elastic_outputs.set_array("symm_eql_strains",
np.array(self.ctx.symm_eql_strains))
elastic_outputs.set_array("symm_eql_stresses",
np.array(self.ctx.symm_eql_stresses))
elastic_outputs.store()
symmetry_mapping.store()
self.out('equilibrium_structure', self.ctx.equilibrium_structure)
self.out('elastic_outputs', elastic_outputs)
self.out('symmetry_mapping', symmetry_mapping)
def generate_elastic_workflow(structure, tags=None):
"""
Generates a standard production workflow.
Notes:
Uses a primitive structure transformed into
the conventional basis (for equivalent deformations).
Adds the "minimal" category to the minimal portion
of the workflow necessary to generate the elastic tensor,
and the "minimal_full_stencil" category to the portion that
includes all of the strain stencil, but is symmetrically complete
"""
if tags == None:
tags = []
# transform the structure
ieee_rot = Tensor.get_ieee_rotation(structure)
if not SquareTensor(ieee_rot).is_rotation(tol=0.005):
raise ValueError(
"Rotation matrix does not satisfy rotation conditions")
symm_op = SymmOp.from_rotation_and_translation(ieee_rot)
ieee_structure = structure.copy()
ieee_structure.apply_operation(symm_op)
# construct workflow
wf = wf_elastic_constant(ieee_structure)
# Set categories, starting with optimization
opt_fws = get_fws_and_tasks(wf, fw_name_constraint="optimization")
wf.fws[opt_fws[0][0]].spec['elastic_category'] = "minimal"
# find minimal set of fireworks using symmetry reduction
fws_by_strain = {
Strain(fw.tasks[-1]['pass_dict']['strain']): n
for n, fw in enumerate(wf.fws) if 'deformation' in fw.name
}
unique_tensors = symmetry_reduce(list(fws_by_strain.keys()),
ieee_structure)
for unique_tensor in unique_tensors:
fw_index = get_tkd_value(fws_by_strain, unique_tensor)
if np.isclose(unique_tensor, 0.005).any():
wf.fws[fw_index].spec['elastic_category'] = "minimal"
else:
wf.fws[fw_index].spec['elastic_category'] = "minimal_full_stencil"
# Add tags
if tags:
wf = add_tags(wf, tags)
wf = add_modify_incar(wf)
priority = 500 - structure.num_sites
wf = add_priority(wf, priority)
for fw in wf.fws:
if fw.spec.get('elastic_category') == 'minimal':
fw.spec['_priority'] += 2000
elif fw.spec.get('elastic_category') == 'minimal_full_stencil':
fw.spec['_priority'] += 1000
return wf
def test_symmetry_reduce(self):
tbs = [Tensor.from_voigt(row) for row in np.eye(6) * 0.01]
reduced = symmetry_reduce(tbs, self.get_structure("Sn"))
self.assertEqual(len(reduced), 2)
self.assertArrayEqual([len(i) for i in reduced.values()], [2, 2])
reconstructed = []
for k, v in reduced.items():
reconstructed.extend([k.voigt] +
[k.transform(op).voigt for op in v])
reconstructed = sorted(reconstructed, key=lambda x: np.argmax(x))
self.assertArrayAlmostEqual([tb for tb in reconstructed],
np.eye(6) * 0.01)
def test_tensor_mapping(self):
# Test get
tbs = [Tensor.from_voigt(row) for row in np.eye(6) * 0.01]
reduced = symmetry_reduce(tbs, self.get_structure("Sn"))
tkey = Tensor.from_values_indices([0.01], [(0, 0)])
tval = reduced[tkey]
for tens_1, tens_2 in zip(tval, reduced[tbs[0]]):
self.assertAlmostEqual(tens_1, tens_2)
# Test set
reduced[tkey] = "test_val"
self.assertEqual(reduced[tkey], "test_val")
# Test empty initialization
empty = TensorMapping()
self.assertEqual(empty._tensor_list, [])
def test_process_elastic_calcs_toec(self):
# Test TOEC tasks
test_struct = PymatgenTest.get_structure('Sn') # use cubic test struct
strain_states = get_default_strain_states(3)
# Default stencil in atomate, this maybe shouldn't be hard-coded
stencil = np.linspace(-0.075, 0.075, 7)
strains = [
Strain.from_voigt(s * np.array(strain_state))
for s, strain_state in product(stencil, strain_states)
]
strains = [s for s in strains if not np.allclose(s, 0)]
sym_reduced = symmetry_reduce(strains, test_struct)
opt_task = {
"output": {
"structure": test_struct.as_dict()
},
"input": {
"structure": test_struct.as_dict()
}
}
defo_tasks = []
for n, strain in enumerate(sym_reduced):
defo = strain.get_deformation_matrix()
new_struct = defo.apply_to_structure(test_struct)
defo_task = {
"output": {
"structure": new_struct.as_dict(),
"stress": (strain * 5).tolist()
},
"input": None,
"task_id": n,
"completed_at": datetime.utcnow()
}
defo_task.update({
"transmuter": {
"transformation_params": [{
"deformation": defo
}]
}
})
defo_tasks.append(defo_task)
explicit, derived = process_elastic_calcs(opt_task, defo_tasks)
self.assertEqual(len(explicit), len(sym_reduced))
self.assertEqual(len(derived), len(strains) - len(sym_reduced))
for calc in derived:
self.assertTrue(
np.allclose(calc['strain'], calc['cauchy_stress'] / -0.5))
def _get_deformed_structures(equilibrium_structure, strain_magnitudes,
symmetric_strains_only=True):
deformed_mat_set = DeformedStructureSet(equilibrium_structure,
norm_strains=strain_magnitudes,
shear_strains=strain_magnitudes)
symmetry_operations_dict = {}
deformations = deformed_mat_set.deformations
if symmetric_strains_only:
symmetry_operations_dict = symmetry_reduce(deformations,equilibrium_structure)
deformations = [x for x in symmetry_operations_dict]
deformed_structures = []
for i in range(len(deformations)):
mg_deformed_structure = deformations[i].apply_to_structure(equilibrium_structure)
deformed_structure = StructureData(pymatgen_structure=mg_deformed_structure)
deformed_structures.append(deformed_structure)
return deformations, deformed_structures
def __init__(self,
structure,
norm_strains=None,
shear_strains=None,
symmetry=False):
"""
constructs the deformed geometries of a structure. Generates
m + n deformed structures according to the supplied parameters.
Args:
structure (Structure): structure to undergo deformation
norm_strains (list of floats): strain values to apply
to each normal mode.
shear_strains (list of floats): strain values to apply
to each shear mode.
symmetry (bool): whether or not to use symmetry reduction.
"""
norm_strains = norm_strains or [-0.01, -0.005, 0.005, 0.01]
shear_strains = shear_strains or [-0.06, -0.03, 0.03, 0.06]
self.undeformed_structure = structure
self.deformations = []
self.def_structs = []
# Generate deformations
for ind in [(0, 0), (1, 1), (2, 2)]:
for amount in norm_strains:
strain = Strain.from_index_amount(ind, amount)
self.deformations.append(strain.get_deformation_matrix())
for ind in [(0, 1), (0, 2), (1, 2)]:
for amount in shear_strains:
strain = Strain.from_index_amount(ind, amount)
self.deformations.append(strain.get_deformation_matrix())
# Perform symmetry reduction if specified
if symmetry:
self.sym_dict = symmetry_reduce(self.deformations, structure)
self.deformations = list(self.sym_dict.keys())
self.deformed_structures = [
defo.apply_to_structure(structure) for defo in self.deformations
]
def create(**kwargs):
"""
Generate deformed structures for calculating deformation potentials.
"""
from pymatgen.core.structure import Structure
from pymatgen.core.tensors import symmetry_reduce
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.util.string import unicodeify_spacegroup
from amset.deformation.common import get_formatted_tensors
from amset.deformation.generation import get_deformations, get_deformed_structures
from amset.deformation.io import write_deformed_poscars
symprec = _parse_symprec(kwargs["symprec"])
structure = Structure.from_file(kwargs["filename"])
click.echo("Generating deformations:")
click.echo(" - Strain distance: {:g}".format(kwargs["distance"]))
deformations = get_deformations(kwargs["distance"])
click.echo(" - # Total deformations: {}".format(len(deformations)))
if symprec is not None:
sga = SpacegroupAnalyzer(structure, symprec=symprec)
spg_symbol = unicodeify_spacegroup(sga.get_space_group_symbol())
spg_number = sga.get_space_group_number()
click.echo(" - Spacegroup: {} ({})".format(spg_symbol, spg_number))
deformations = list(symmetry_reduce(deformations, structure, symprec=symprec))
click.echo(" - # Inequivalent deformations: {}".format(len(deformations)))
click.echo("\nDeformations:")
click.echo(" - " + "\n - ".join(get_formatted_tensors(deformations)))
deformed_structures = get_deformed_structures(structure, deformations)
write_deformed_poscars(deformed_structures, directory=kwargs["directory"])
click.echo("\nDeformed structures have been created")
def get_strained_structures(equilibrium_structure,
norm_strains,
shear_strains,
symmetric_strains_only=True):
import pymatgen as mg
from pymatgen.analysis.elasticity import DeformedStructureSet
from pymatgen.io.ase import AseAtomsAdaptor
from pymatgen.core.tensors import symmetry_reduce
#global debug_global
#debug_global += 1
#equilibrium_structure.write("/tmp/tmp_POSCAR/POSCAR_{}".format(debug_global),
# format='vasp')
try:
equilibrium_structure_mg = AseAtomsAdaptor.get_structure(
equilibrium_structure)
deformed_mat_set = DeformedStructureSet(equilibrium_structure_mg,
norm_strains=norm_strains,
shear_strains=shear_strains)
except Exception:
equilibrium_structure.write("/tmp/POSCAR_fail", format='vasp')
raise Exception("Something spoooky!")
symmetry_operations_dict = {}
deformations = deformed_mat_set.deformations
if symmetric_strains_only:
symmetry_operations_dict = symmetry_reduce(deformations,
equilibrium_structure_mg)
deformations = [x for x in symmetry_operations_dict]
strained_structures = []
for i in range(len(deformations)):
mg_deformed_structure = deformations[i].apply_to_structure(
equilibrium_structure_mg)
deformed_structure = AseAtomsAdaptor.get_atoms(mg_deformed_structure)
strained_structures.append(deformed_structure)
deformations = [np.array(x).tolist() for x in deformations]
return deformations, strained_structures
def __init__(self, structure, norm_strains=None, shear_strains=None,
symmetry=False):
"""
constructs the deformed geometries of a structure. Generates
m + n deformed structures according to the supplied parameters.
Args:
structure (Structure): structure to undergo deformation
norm_strains (list of floats): strain values to apply
to each normal mode.
shear_strains (list of floats): strain values to apply
to each shear mode.
symmetry (bool): whether or not to use symmetry reduction.
"""
norm_strains = norm_strains or [-0.01, -0.005, 0.005, 0.01]
shear_strains = shear_strains or [-0.06, -0.03, 0.03, 0.06]
self.undeformed_structure = structure
self.deformations = []
self.def_structs = []
# Generate deformations
for ind in [(0, 0), (1, 1), (2, 2)]:
for amount in norm_strains:
strain = Strain.from_index_amount(ind, amount)
self.deformations.append(strain.get_deformation_matrix())
for ind in [(0, 1), (0, 2), (1, 2)]:
for amount in shear_strains:
strain = Strain.from_index_amount(ind, amount)
self.deformations.append(strain.get_deformation_matrix())
# Perform symmetry reduction if specified
if symmetry:
self.sym_dict = symmetry_reduce(self.deformations, structure)
self.deformations = list(self.sym_dict.keys())
self.deformed_structures = [defo.apply_to_structure(structure)
for defo in self.deformations]
def get_wf_elastic_constant(structure,
metadata,
strain_states=None,
stencils=None,
db_file=None,
conventional=False,
order=2,
vasp_input_set=None,
analysis=True,
sym_reduce=False,
tag='elastic',
copy_vasp_outputs=False,
**kwargs):
"""
Returns a workflow to calculate elastic constants.
Firework 1 : write vasp input set for structural relaxation,
run vasp,
pass run location,
database insertion.
Firework 2 - number of total deformations: Static runs on the deformed structures
last Firework : Analyze Stress/Strain data and fit the elastic tensor
Args:
structure (Structure): input structure to be optimized and run.
strain_states (list of Voigt-notation strains): list of ratios of nonzero elements
of Voigt-notation strain, e. g. [(1, 0, 0, 0, 0, 0), (0, 1, 0, 0, 0, 0), etc.].
stencils (list of floats, or list of list of floats): values of strain to multiply
by for each strain state, i. e. stencil for the perturbation along the strain
state direction, e. g. [-0.01, -0.005, 0.005, 0.01]. If a list of lists,
stencils must correspond to each strain state provided.
db_file (str): path to file containing the database credentials.
conventional (bool): flag to convert input structure to conventional structure,
defaults to False.
order (int): order of the tensor expansion to be determined. Defaults to 2 and
currently supports up to 3.
vasp_input_set (VaspInputSet): vasp input set to be used. Defaults to static
set with ionic relaxation parameters set. Take care if replacing this,
default ensures that ionic relaxation is done and that stress is calculated
for each vasp run.
analysis (bool): flag to indicate whether analysis task should be added
and stresses and strains passed to that task
sym_reduce (bool): Whether or not to apply symmetry reductions
tag (str):
copy_vasp_outputs (bool): whether or not to copy previous vasp outputs.
kwargs (keyword arguments): additional kwargs to be passed to get_wf_deformations
Returns:
Workflow
"""
# Convert to conventional if specified
if conventional:
structure = SpacegroupAnalyzer(
structure).get_conventional_standard_structure()
uis_elastic = {
"IBRION": 2,
"NSW": 99,
"ISIF": 2,
"ISTART": 1,
"PREC": "High"
}
vis = vasp_input_set or MPStaticSet(structure,
user_incar_settings=uis_elastic)
strains = []
if strain_states is None:
strain_states = get_default_strain_states(order)
if stencils is None:
stencils = [np.linspace(-0.01, 0.01, 5 +
(order - 2) * 2)] * len(strain_states)
if np.array(stencils).ndim == 1:
stencils = [stencils] * len(strain_states)
for state, stencil in zip(strain_states, stencils):
strains.extend(
[Strain.from_voigt(s * np.array(state)) for s in stencil])
# Remove zero strains
strains = [strain for strain in strains if not (abs(strain) < 1e-10).all()]
# Adding the zero strains for the purpose of calculating at finite pressure or thermal expansion
_strains = [Strain.from_deformation([[1, 0, 0], [0, 1, 0], [0, 0, 1]])]
strains.extend(_strains)
"""
"""
vstrains = [strain.voigt for strain in strains]
if np.linalg.matrix_rank(vstrains) < 6:
# TODO: check for sufficiency of input for nth order
raise ValueError(
"Strain list is insufficient to fit an elastic tensor")
deformations = [s.get_deformation_matrix() for s in strains]
"""
print(strains)
print(deformations)
"""
if sym_reduce:
# Note this casts deformations to a TensorMapping
# with unique deformations as keys to symmops
deformations = symmetry_reduce(deformations, structure)
wf_elastic = get_wf_deformations(structure,
deformations,
tag=tag,
db_file=db_file,
vasp_input_set=vis,
copy_vasp_outputs=copy_vasp_outputs,
**kwargs)
if analysis:
defo_fws_and_tasks = get_fws_and_tasks(
wf_elastic,
fw_name_constraint="deformation",
task_name_constraint="Transmuted")
for idx_fw, idx_t in defo_fws_and_tasks:
defo = \
wf_elastic.fws[idx_fw].tasks[idx_t]['transformation_params'][0][
'deformation']
pass_dict = {
'strain': Deformation(defo).green_lagrange_strain.tolist(),
'stress': '>>output.ionic_steps.-1.stress',
'deformation_matrix': defo
}
if sym_reduce:
pass_dict.update({'symmops': deformations[defo]})
mod_spec_key = "deformation_tasks->{}".format(idx_fw)
pass_task = pass_vasp_result(pass_dict=pass_dict,
mod_spec_key=mod_spec_key)
wf_elastic.fws[idx_fw].tasks.append(pass_task)
fw_analysis = Firework(ElasticTensorToDb(structure=structure,
db_file=db_file,
order=order,
fw_spec_field='tags',
metadata=metadata,
vasp_input_set=vis),
name="Analyze Elastic Data",
spec={"_allow_fizzled_parents": True})
wf_elastic.append_wf(Workflow.from_Firework(fw_analysis),
wf_elastic.leaf_fw_ids)
wf_elastic.name = "{}:{}".format(structure.composition.reduced_formula,
"elastic constants")
return wf_elastic
def get_wf_elastic_constant(structure, strain_states=None, stencils=None,
db_file=None,
conventional=False, order=2, vasp_input_set=None,
analysis=True,
sym_reduce=False, tag='elastic',
copy_vasp_outputs=False, **kwargs):
"""
Returns a workflow to calculate elastic constants.
Firework 1 : write vasp input set for structural relaxation,
run vasp,
pass run location,
database insertion.
Firework 2 - number of total deformations: Static runs on the deformed structures
last Firework : Analyze Stress/Strain data and fit the elastic tensor
Args:
structure (Structure): input structure to be optimized and run.
strain_states (list of Voigt-notation strains): list of ratios of nonzero elements
of Voigt-notation strain, e. g. [(1, 0, 0, 0, 0, 0), (0, 1, 0, 0, 0, 0), etc.].
stencils (list of floats, or list of list of floats): values of strain to multiply
by for each strain state, i. e. stencil for the perturbation along the strain
state direction, e. g. [-0.01, -0.005, 0.005, 0.01]. If a list of lists,
stencils must correspond to each strain state provided.
db_file (str): path to file containing the database credentials.
conventional (bool): flag to convert input structure to conventional structure,
defaults to False.
order (int): order of the tensor expansion to be determined. Defaults to 2 and
currently supports up to 3.
vasp_input_set (VaspInputSet): vasp input set to be used. Defaults to static
set with ionic relaxation parameters set. Take care if replacing this,
default ensures that ionic relaxation is done and that stress is calculated
for each vasp run.
analysis (bool): flag to indicate whether analysis task should be added
and stresses and strains passed to that task
sym_reduce (bool): Whether or not to apply symmetry reductions
tag (str):
copy_vasp_outputs (bool): whether or not to copy previous vasp outputs.
kwargs (keyword arguments): additional kwargs to be passed to get_wf_deformations
Returns:
Workflow
"""
# Convert to conventional if specified
if conventional:
structure = SpacegroupAnalyzer(
structure).get_conventional_standard_structure()
uis_elastic = {"IBRION": 2, "NSW": 99, "ISIF": 2, "ISTART": 1,
"PREC": "High"}
vis = vasp_input_set or MPStaticSet(structure,
user_incar_settings=uis_elastic)
strains = []
if strain_states is None:
strain_states = get_default_strain_states(order)
if stencils is None:
stencils = [np.linspace(-0.01, 0.01, 5 + (order - 2) * 2)] * len(
strain_states)
if np.array(stencils).ndim == 1:
stencils = [stencils] * len(strain_states)
for state, stencil in zip(strain_states, stencils):
strains.extend(
[Strain.from_voigt(s * np.array(state)) for s in stencil])
# Remove zero strains
strains = [strain for strain in strains if not (abs(strain) < 1e-10).all()]
vstrains = [strain.voigt for strain in strains]
if np.linalg.matrix_rank(vstrains) < 6:
# TODO: check for sufficiency of input for nth order
raise ValueError("Strain list is insufficient to fit an elastic tensor")
deformations = [s.get_deformation_matrix() for s in strains]
if sym_reduce:
# Note this casts deformations to a TensorMapping
# with unique deformations as keys to symmops
deformations = symmetry_reduce(deformations, structure)
wf_elastic = get_wf_deformations(structure, deformations, tag=tag,
db_file=db_file,
vasp_input_set=vis,
copy_vasp_outputs=copy_vasp_outputs,
**kwargs)
if analysis:
defo_fws_and_tasks = get_fws_and_tasks(wf_elastic,
fw_name_constraint="deformation",
task_name_constraint="Transmuted")
for idx_fw, idx_t in defo_fws_and_tasks:
defo = \
wf_elastic.fws[idx_fw].tasks[idx_t]['transformation_params'][0][
'deformation']
pass_dict = {
'strain': Deformation(defo).green_lagrange_strain.tolist(),
'stress': '>>output.ionic_steps.-1.stress',
'deformation_matrix': defo}
if sym_reduce:
pass_dict.update({'symmops': deformations[defo]})
mod_spec_key = "deformation_tasks->{}".format(idx_fw)
pass_task = pass_vasp_result(pass_dict=pass_dict,
mod_spec_key=mod_spec_key)
wf_elastic.fws[idx_fw].tasks.append(pass_task)
fw_analysis = Firework(
ElasticTensorToDb(structure=structure, db_file=db_file,
order=order, fw_spec_field='tags'),
name="Analyze Elastic Data", spec={"_allow_fizzled_parents": True})
wf_elastic.append_wf(Workflow.from_Firework(fw_analysis),
wf_elastic.leaf_fw_ids)
wf_elastic.name = "{}:{}".format(structure.composition.reduced_formula,
"elastic constants")
return wf_elastic
