def test_return_ranked_list(self):
# list of structures
pztstructs2 = loadfn(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"mcsqs/pztstructs2.json"))
trans = SQSTransformation(scaling=2,
search_time=0.01,
instances=8,
wd=0)
struc = self.get_structure("Pb2TiZrO6").copy()
struc.replace_species({
"Ti": {
"Ti": 0.5,
"Zr": 0.5
},
"Zr": {
"Ti": 0.5,
"Zr": 0.5
}
})
ranked_list_out = trans.apply_transformation(struc,
return_ranked_list=True)
matches = [
ranked_list_out[0]["structure"].matches(s) for s in pztstructs2
]
self.assertIn(True, matches)
def test_apply_transformation(self):
# non-sensical example just for testing purposes
self.pztstrings = np.load(os.path.join(test_dir,
"mcsqs/pztstrings.npy"),
allow_pickle=True)
self.struct = self.get_structure('Pb2TiZrO6')
trans = SQSTransformation({
2: 6,
3: 4
},
supercell=[2, 1, 1],
total_atoms=None,
search_time=0.01)
struct = self.struct.copy()
struct.replace_species({
'Ti': {
'Ti': 0.5,
'Zr': 0.5
},
'Zr': {
'Ti': 0.5,
'Zr': 0.5
}
})
sqs = trans.apply_transformation(struct)
self.assertEqual(atat.Mcsqs(sqs).to_string() in self.pztstrings, True)
os.remove('sqscell.out')
os.remove('rndstrgrp.out')
os.remove('bestcorr.out')
os.remove('rndstr.in')
os.remove('sym.out')
os.remove('mcsqs.log')
os.remove('bestsqs.out')
os.remove('clusters.out')
def test_apply_transformation(self):
pztstructs = loadfn(os.path.join(PymatgenTest.TEST_FILES_DIR, "mcsqs/pztstructs.json"))
trans = SQSTransformation(scaling=[2, 1, 1], search_time=0.01, instances=1, wd=0)
# nonsensical example just for testing purposes
struc = self.get_structure("Pb2TiZrO6").copy()
struc.replace_species({"Ti": {"Ti": 0.5, "Zr": 0.5}, "Zr": {"Ti": 0.5, "Zr": 0.5}})
struc_out = trans.apply_transformation(struc)
matches = [struc_out.matches(s) for s in pztstructs]
self.assertIn(True, matches)
def test_spin(self):
trans = SQSTransformation(scaling=[2, 1, 1], search_time=0.01, instances=1, wd=0)
# nonsensical example just for testing purposes
struc = self.get_structure("Pb2TiZrO6").copy()
struc.replace_species({"Ti": {"Ti,spin=5": 0.5, "Ti,spin=-5": 0.5}})
struc_out = trans.apply_transformation(struc)
struc_out_specie_strings = [site.species_string for site in struc_out]
self.assertIn("Ti,spin=-5", struc_out_specie_strings)
self.assertIn("Ti,spin=5", struc_out_specie_strings)
def solid_solution_sqs(structure, elem_frac_site, elem_frac_comp, sqs_scaling):
'''
Use pymatgen SQSTransformation (which call ATAT mcsqs program)
to generate disordered structure.
Args:
structure: pymatgen structure
elem_frac_site: the factional occupy site in the original structure, e.g. 'Ti'
elem_frac_comp: solid solution composition, e.g. 'Ti0.25Zr0.25Hf0.25Nb0.25'
sqs_scaling (int or list): (same as pymatgen scaling in SQSTransformation)
Scaling factor to determine supercell. Two options are possible:
a. (preferred) Scales number of atoms, e.g., for a structure with 8 atoms,
scaling=4 would lead to a 32 atom supercell
b. A sequence of three scaling factors, e.g., [2, 1, 1], which
specifies that the supercell should have dimensions 2a x b x c
Return:
pymatgen structure, SQS
'''
# build another pymatgen structure
structure[elem_frac_site] = elem_frac_comp
ts = TransformedStructure(structure, [])
# the directory must be set in SQSTransformation, otherwise the work dir
# will be changed by this function
workdir = os.getcwd()
ts.append_transformation(
SQSTransformation(scaling=sqs_scaling,
search_time=1,
directory=workdir,
reduction_algo=False))
return ts.structures[-1]