def substitution_structures(self, mp_struct, mpid):
''' Predicts substituted compounds from a given Materials Project structure (mp_struct) and ID (mpid) '''
''' flat_predictions: a list of predicted structures as pymatgen.alchemy.materials.TransformedStructure objects '''
auto_oxi = AutoOxiStateDecorationTransformation() #initialize the automatic oxidation state transformation
structures = []
try:
oxi_struct = auto_oxi.apply_transformation(mp_struct) # get oxidized reference structure
subs = SubstitutionPredictor().composition_prediction(oxi_struct.composition) # from a given charge-balanced
trial_subs = [list(sub['substitutions'].keys()) for sub in subs] # returns the potential substitutions
sbr = Substitutor()
for sub in trial_subs:
run = True
for specie in sub:
if str(specie.element) not in self.elements:
run = False
if run == True:
structs = sbr.pred_from_structures(sub, [{'structure':oxi_struct, 'id':mpid}])
structures.append(structs)
except:
pass
flat_predictions = [structure for substitution in structures for structure in substitution]
return flat_predictions
def predict_structure(species, struc_list, check_dir=False, threshold=0.00001):
""" Predicted structures for set of pymatgen species using the Pymatgen structure predictor
and save as cif file.
TODO: This will be superceded by our own implementation of the structure prediction algorithm
in future versions of SMACT.
Args:
species (list): Pymatgen Species for which structure should be predicted.
struc_list (list): Pymatgen Structure objects to consider as parent structures in the
substitution algorithm.
check_dir (bool): check if directory already exists and only carry out
prediction and write new files if it doesn't.
threshold (float): Log-probability threshold for the Pymatgen structure predictor.
Returns:
Saves cif files of possible structures in new directory along with a summary .txt file
containing info including probabilities.
"""
sub = Substitutor(threshold=0.00001)
print('{} ........'.format(species))
dirname = ''.join([str(i) for i in species])
path_exists = True if os.path.exists(
'./SP_results/{0}'.format(dirname)) else False
if (check_dir and path_exists):
print('Already exists')
else:
print('{} not already there'.format(dirname))
suggested_strucs = sub.pred_from_structures(target_species=species,
structures_list=struc_list,
remove_existing=False,
remove_duplicates=True)
suggested_strucs = sorted(suggested_strucs,
key=lambda k: k.other_parameters['proba'],
reverse=True)
# Save the structures as cifs
if not path_exists:
os.makedirs('./SP_results/{0}'.format(dirname))
for i, d in enumerate(suggested_strucs):
cw = CifWriter(d.final_structure)
cw.write_file("SP_results/{0}/{1}_BasedOn_{2}.cif".format(
dirname, i, d.history[0]['source']))
# Save the summary as a text file
with open('SP_results/{0}/{0}_summary.txt'.format(dirname), 'w') as f:
f.write('Formula, Probability, Based on, Substitutions \n')
for i, struc in enumerate(suggested_strucs):
f.write(
' {0}, {1:12}, {2:.5f}, {3:9}, {4} \n'.format(
i, struc.composition.reduced_formula,
struc.other_parameters['proba'],
struc.history[0]['source'],
re.sub('Specie', '',
str(struc.history[1]['species_map']))))
print('Done.')
def predict_structure(species, struc_list, check_dir=False):
""" Save cif files of predicted structures for set of pymatgen species.
Args:
species (list): pymatgen species to predict structures for
struc_list (list): pymatgen structures to substitute species into
check_dir (bool): check if directory already exists and only carry out
prediction if it doesn't.
"""
sub = Substitutor(threshold=0.00001)
print('{} ........'.format(species))
dirname = ''.join([str(i) for i in species])
path_exists = True if os.path.exists(
'./SP_results/{0}'.format(dirname)) else False
if (check_dir and path_exists):
print('Already exists')
else:
print('{} not already there'.format(dirname))
suggested_strucs = sub.pred_from_structures(target_species=species,
structures_list=struc_list,
remove_existing=False,
remove_duplicates=True)
suggested_strucs = sorted(suggested_strucs,
key=lambda k: k.other_parameters['proba'],
reverse=True)
# Save the structures as cifs
if not path_exists:
os.makedirs('./SP_results/{0}'.format(dirname))
for i, d in enumerate(suggested_strucs):
cw = CifWriter(d.final_structure)
cw.write_file("SP_results/{0}/{1}_BasedOn_{2}.cif".format(
dirname, i, d.history[0]['source']))
# Save the summary as a text file
with open('SP_results/{0}/{0}_summary.txt'.format(dirname), 'w') as f:
f.write('Formula, Probability, Based on, Substitutions \n')
for i, struc in enumerate(suggested_strucs):
f.write(
' {0}, {1:12}, {2:.5f}, {3:9}, {4} \n'.format(
i, struc.composition.reduced_formula,
struc.other_parameters['proba'],
struc.history[0]['source'],
re.sub('Specie', '',
str(struc.history[1]['species_map']))))
print('Done.')
class SubstitutorTest(PymatgenTest):
def setUp(self):
self.s = Substitutor(threshold=1e-3,
lambda_table=get_table(),
alpha=-5.)
def test_substitutor(self):
s_list = [Specie('O', -2), Specie('Li', 1)]
subs = self.s.pred_from_list(s_list)
self.assertEqual(len(subs), 4, 'incorrect number of substitutions')
c = Composition({'O2-': 1, 'Li1+': 2})
subs = self.s.pred_from_comp(c)
self.assertEqual(len(subs), 4, 'incorrect number of substitutions')
structures = [{
"structure": PymatgenTest.get_structure("Li2O"),
"id": "pmgtest"
}]
subs = self.s.pred_from_structures(["Na+", "O2-"], structures)
self.assertEqual(subs[0].formula, "Na2 O1")
def test_as_dict(self):
Substitutor.from_dict(self.s.as_dict())
class SubstitutorTest(PymatgenTest):
def setUp(self):
self.s = Substitutor(threshold=1e-3, lambda_table=get_table(),
alpha= -5.)
def test_substitutor(self):
s_list = [Specie('O', -2), Specie('Li', 1)]
subs = self.s.pred_from_list(s_list)
self.assertEqual(len(subs), 4
, 'incorrect number of substitutions')
c = Composition({'O2-': 1, 'Li1+': 2})
subs = self.s.pred_from_comp(c)
self.assertEqual(len(subs), 4
, 'incorrect number of substitutions')
structures = [{"structure": PymatgenTest.get_structure("Li2O"),
"id": "pmgtest"}]
subs = self.s.pred_from_structures(["Na+", "O2-"], structures)
self.assertEqual(subs[0].formula, "Na2 O1")
def test_as_dict(self):
Substitutor.from_dict(self.s.as_dict())