def test_ignore_species(self):
s1 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
s2 = Structure.from_file(os.path.join(test_dir, "POSCAR"))
m = StructureMatcher(ignored_species=["Li"],
primitive_cell=False,
attempt_supercell=True)
self.assertTrue(m.fit(s1, s2))
self.assertTrue(m.fit_anonymous(s1, s2))
groups = m.group_structures([s1, s2])
self.assertEqual(len(groups), 1)
s2.make_supercell((2, 1, 1))
ss1 = m.get_s2_like_s1(s2, s1, include_ignored_species=True)
self.assertAlmostEqual(ss1.lattice.a, 20.820740000000001)
self.assertEqual(ss1.composition.reduced_formula, "LiFePO4")
self.assertEqual(
{
k.symbol: v.symbol
for k, v in m.get_best_electronegativity_anonymous_mapping(
s1, s2).items()
}, {
"Fe": "Fe",
"P": "P",
"O": "O"
})
def apply_transformation(self, structure):
"""
Returns a copy of structure with lattice parameters
and sites scaled to the same degree as the relaxed_structure.
Arg:
structure (Structure): A structurally similar structure in
regards to crystal and site positions.
"""
if self.species_map is None:
match = StructureMatcher()
s_map = match.get_best_electronegativity_anonymous_mapping(self.unrelaxed_structure, structure)
else:
s_map = self.species_map
params = list(structure.lattice.abc)
params.extend(structure.lattice.angles)
new_lattice = Lattice.from_parameters(*(p * self.params_percent_change[i] for i, p in enumerate(params)))
species, frac_coords = [], []
for site in self.relaxed_structure:
species.append(s_map[site.specie])
frac_coords.append(site.frac_coords)
return Structure(new_lattice, species, frac_coords)
def apply_transformation(self, structure):
"""
Returns a copy of structure with lattice parameters
and sites scaled to the same degree as the relaxed_structure.
Arg:
structure (Structure): A structurally similar structure in
regards to crystal and site positions.
"""
if self.species_map == None:
match = StructureMatcher()
s_map = \
match.get_best_electronegativity_anonymous_mapping(self.unrelaxed_structure,
structure)
else:
s_map = self.species_map
params = list(structure.lattice.abc)
params.extend(structure.lattice.angles)
new_lattice = Lattice.from_parameters(*[p*self.params_percent_change[i] \
for i, p in enumerate(params)])
species, frac_coords = [], []
for site in self.relaxed_structure:
species.append(s_map[site.specie])
frac_coords.append(site.frac_coords)
return Structure(new_lattice, species, frac_coords)
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def predict(self, structure, ref_structure, test_isostructural=True):
"""
Given a structure, returns back the predicted volume.
Args:
structure (Structure): structure w/unknown volume
ref_structure (Structure): A reference structure with a similar
structure but different species.
test_isostructural (bool): Whether to test that the two
structures are isostructural. This algo works best for
isostructural compounds. Defaults to True.
Returns:
a float value of the predicted volume
"""
if not is_ox(structure):
a = BVAnalyzer()
structure = a.get_oxi_state_decorated_structure(structure)
if not is_ox(ref_structure):
a = BVAnalyzer()
ref_structure = a.get_oxi_state_decorated_structure(ref_structure)
if test_isostructural:
m = StructureMatcher()
mapping = m.get_best_electronegativity_anonymous_mapping(
structure, ref_structure)
if mapping is None:
raise ValueError("Input structures do not match!")
comp = structure.composition
ref_comp = ref_structure.composition
numerator = 0
denominator = 0
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
# TODO: AJ doesn't understand the (1/3). It would make sense to him
# if you were doing atomic volume and not atomic radius
for k, v in comp.items():
numerator += k.ionic_radius * v**(1 / 3)
for k, v in ref_comp.items():
denominator += k.ionic_radius * v**(1 / 3)
# The scaling factor is based on lengths. We apply a power of 3.
return ref_structure.volume * (numerator / denominator)**3
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(
sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{
Element("S"): Element("Se"),
Element("As"): Element("N"),
Element("Fe"): Element("Fe"),
Element("Na"): Element("Na"),
Element("P"): Element("P"),
Element("O"): Element("O"),
},
)
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
def test_ignore_species(self):
s1 = Structure.from_file(os.path.join(test_dir, "LiFePO4.cif"))
s2 = Structure.from_file(os.path.join(test_dir, "POSCAR"))
m = StructureMatcher(ignored_species=["Li"], primitive_cell=False, attempt_supercell=True)
self.assertTrue(m.fit(s1, s2))
self.assertTrue(m.fit_anonymous(s1, s2))
groups = m.group_structures([s1, s2])
self.assertEqual(len(groups), 1)
s2.make_supercell((2, 1, 1))
ss1 = m.get_s2_like_s1(s2, s1, include_ignored_species=True)
self.assertAlmostEqual(ss1.lattice.a, 20.820740000000001)
self.assertEqual(ss1.composition.reduced_formula, "LiFePO4")
self.assertEqual(
{k.symbol: v.symbol for k, v in m.get_best_electronegativity_anonymous_mapping(s1, s2).items()},
{"Fe": "Fe", "P": "P", "O": "O"},
)
def predict(self, structure, ref_structure, test_isostructural=True):
"""
Given a structure, returns back the predicted volume.
Args:
structure (Structure): structure w/unknown volume
ref_structure (Structure): A reference structure with a similar
structure but different species.
test_isostructural (bool): Whether to test that the two
structures are isostructural. This algo works best for
isostructural compounds. Defaults to True.
Returns:
a float value of the predicted volume
"""
if not is_ox(structure):
a = BVAnalyzer()
structure = a.get_oxi_state_decorated_structure(structure)
if not is_ox(ref_structure):
a = BVAnalyzer()
ref_structure = a.get_oxi_state_decorated_structure(ref_structure)
if test_isostructural:
m = StructureMatcher()
mapping = m.get_best_electronegativity_anonymous_mapping(structure, ref_structure)
if mapping is None:
raise ValueError("Input structures do not match!")
comp = structure.composition
ref_comp = ref_structure.composition
numerator = 0
denominator = 0
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
# TODO: AJ doesn't understand the (1/3). It would make sense to him
# if you were doing atomic volume and not atomic radius
for k, v in comp.items():
numerator += k.ionic_radius * v ** (1 / 3)
for k, v in ref_comp.items():
denominator += k.ionic_radius * v ** (1 / 3)
# The scaling factor is based on lengths. We apply a power of 3.
return ref_structure.volume * (numerator / denominator) ** 3
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
# test include_dist
dists = {Element('N'): 0, Element('P'): 0.0010725064}
for mapping, d in sm.get_all_anonymous_mappings(s1, s2, include_dist=True):
self.assertAlmostEqual(dists[mapping[Element('As')]], d)
def test_electronegativity(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5)
s1 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PAsO4S4.json"))
s2 = Structure.from_file(os.path.join(test_dir, "Na2Fe2PNO4Se4.json"))
self.assertEqual(sm.get_best_electronegativity_anonymous_mapping(s1, s2),
{Element('S'): Element('Se'),
Element('As'): Element('N'),
Element('Fe'): Element('Fe'),
Element('Na'): Element('Na'),
Element('P'): Element('P'),
Element('O'): Element('O'),})
self.assertEqual(len(sm.get_all_anonymous_mappings(s1, s2)), 2)
# test include_dist
dists = {Element('N'): 0, Element('P'): 0.0010725064}
for mapping, d in sm.get_all_anonymous_mappings(s1, s2, include_dist=True):
self.assertAlmostEqual(dists[mapping[Element('As')]], d)
def predict(self, structure, ref_structure):
"""
Given a structure, returns the predicted volume.
Args:
structure (Structure): structure w/unknown volume
ref_structure (Structure): A reference structure with a similar
structure but different species.
Returns:
a float value of the predicted volume
"""
if self.check_isostructural:
m = StructureMatcher()
mapping = m.get_best_electronegativity_anonymous_mapping(structure, ref_structure)
if mapping is None:
raise ValueError("Input structures do not match!")
if "ionic" in self.radii_type:
try:
# Use BV analyzer to determine oxidation states only if the
# oxidation states are not already specified in the structure
# and use_bv is true.
if (not _is_ox(structure)) and self.use_bv:
a = BVAnalyzer()
structure = a.get_oxi_state_decorated_structure(structure)
if (not _is_ox(ref_structure)) and self.use_bv:
a = BVAnalyzer()
ref_structure = a.get_oxi_state_decorated_structure(ref_structure)
comp = structure.composition
ref_comp = ref_structure.composition
# Check if all the associated ionic radii are available.
if any(k.ionic_radius is None for k in list(comp.keys())) or any(
k.ionic_radius is None for k in list(ref_comp.keys())
):
raise ValueError("Not all the ionic radii are available!")
numerator = 0
denominator = 0
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
for k, v in comp.items():
numerator += k.ionic_radius * v ** (1 / 3)
for k, v in ref_comp.items():
denominator += k.ionic_radius * v ** (1 / 3)
return ref_structure.volume * (numerator / denominator) ** 3
except Exception:
warnings.warn("Exception occured. Will attempt atomic radii.")
# If error occurs during use of ionic radii scheme, pass
# and see if we can resolve it using atomic radii.
pass
if "atomic" in self.radii_type:
comp = structure.composition
ref_comp = ref_structure.composition
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
numerator = 0
denominator = 0
for k, v in comp.items():
numerator += k.atomic_radius * v ** (1 / 3)
for k, v in ref_comp.items():
denominator += k.atomic_radius * v ** (1 / 3)
return ref_structure.volume * (numerator / denominator) ** 3
raise ValueError("Cannot find volume scaling based on radii choices specified!")
def predict(self, structure, ref_structure):
"""
Given a structure, returns the predicted volume.
Args:
structure (Structure): structure w/unknown volume
ref_structure (Structure): A reference structure with a similar
structure but different species.
Returns:
a float value of the predicted volume
"""
if self.check_isostructural:
m = StructureMatcher()
mapping = m.get_best_electronegativity_anonymous_mapping(
structure, ref_structure)
if mapping is None:
raise ValueError("Input structures do not match!")
if "ionic" in self.radii_type:
try:
# Use BV analyzer to determine oxidation states only if the
# oxidation states are not already specified in the structure
# and use_bv is true.
if (not is_ox(structure)) and self.use_bv:
a = BVAnalyzer()
structure = a.get_oxi_state_decorated_structure(structure)
if (not is_ox(ref_structure)) and self.use_bv:
a = BVAnalyzer()
ref_structure = a.get_oxi_state_decorated_structure(
ref_structure)
comp = structure.composition
ref_comp = ref_structure.composition
# Check if all the associated ionic radii are available.
if any([k.ionic_radius is None for k in list(comp.keys())]) or \
any([k.ionic_radius is None for k in
list(ref_comp.keys())]):
raise ValueError("Not all the ionic radii are available!")
numerator = 0
denominator = 0
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
for k, v in comp.items():
numerator += k.ionic_radius * v ** (1 / 3)
for k, v in ref_comp.items():
denominator += k.ionic_radius * v ** (1 / 3)
return ref_structure.volume * (numerator / denominator) ** 3
except Exception as ex:
warnings.warn("Exception occured. Will attempt atomic radii.")
# If error occurs during use of ionic radii scheme, pass
# and see if we can resolve it using atomic radii.
pass
if "atomic" in self.radii_type:
comp = structure.composition
ref_comp = ref_structure.composition
# Here, the 1/3 factor on the composition accounts for atomic
# packing. We want the number per unit length.
numerator = 0
denominator = 0
for k, v in comp.items():
numerator += k.atomic_radius * v ** (1 / 3)
for k, v in ref_comp.items():
denominator += k.atomic_radius * v ** (1 / 3)
return ref_structure.volume * (numerator / denominator) ** 3
raise ValueError("Cannot find volume scaling based on radii choices "
"specified!")
