def test_species_from_light_structure_chemenv(self):
"""Test finding the ce's (mp symbols) of a species but starting from a Light Structure Environment object"""
s1_finder = polyfinder.LocalGeometryFinder()
s1_finder.setup_structure(self.structure)
s1_finder.setup_parameters(centering_type='standard', structure_refinement='none')
environments = s1_finder.compute_structure_environments_detailed_voronoi(maximum_distance_factor=1.5)
light_se = se.LightStructureEnvironments(strategies.SimplestChemenvStrategy(), environments)
ces = find_species_ce_from_light_se(light_se, self.first_site.species_string)
for ce in ces:
with open(self.path_to_jsons+"/%s.json" % ce) as json_file:
data = json.load(json_file)
self.assertEqual(data['mp_symbol'], "O:6", "Li polyhedra should be 6-coordinated octahedron")
self.assertEqual(data['coordination'], 6, "Li polyhedra should be 6-coordinated octahedron")
self.assertEqual(data['name'], "Octahedron", "Li polyhedra should be 6-coordinated octahedron")
def get_connectivity_description_2(structure, radius=2.6, peripheral_species=None, central_species=None):
"""
Writes a verbal description of the connectivity between cations in a structure and does not differentiate between
species on different sites in the unit cell. Uses the Chemenv module in Pymatgen to calculate the coordination
environment for specific species.
:param structure: (Structure) target Structure
:param radius: (float) radius within which to determine whether a nearby atom is a peripheral ion
:param peripheral_species: (List of Strings) list of species strings of what we consider the peripheral species of
the polyhedra in the structure
:param central_species: (List of Strings) list of species strings of what we consider the central species of the
polyhedra in the structure
:return: (dict) dictionary of strings containing verbal descriptions of connectivites between cations in the given
structure; keys = cation tag (eg: Li1, Na2, where the letters represent the species and the number distinguishes
the species from the other instances of that same species in the unit cell); dict values = String descriptions of
connectivity
"""
if peripheral_species is None:
peripheral_species = ['O2-', 'O', 'F-', 'F', 'Cl-', 'Cl', 'I-', 'I', 'Br-', 'Br', 'S2-', 'S', 'N', 'N3-']
if central_species is None:
central_species = []
connectivity_matrix, all_polyhedra, supercell = \
get_connectivity_matrix(structure, True, radius, peripheral_species, central_species)
lgf = polyfinder.LocalGeometryFinder()
lgf.setup_parameters(centering_type='standard', structure_refinement='none')
lgf.setup_structure(supercell)
environments = lgf.compute_structure_environments_detailed_voronoi(maximum_distance_factor=1.5)
light_se = se.LightStructureEnvironments(strategies.SimplestChemenvStrategy(), environments)
path_to_jsons = os.path.dirname(cg_files.__file__)
descriptions = {}
for cation_1 in connectivity_matrix.keys():
descriptions[cation_1] = ""
for cation_1 in connectivity_matrix.keys():
site_ces1 = find_species_ce_from_light_se(light_se, cation_1)
cn1 = []
for ce in site_ces1:
with open(path_to_jsons+"/%s.json" % ce) as json_file:
data1 = json.load(json_file)
cn1.append(data1['name'])
descriptions[cation_1] += cation_1 + " are " + cn1 + ". \n"
for cation_2 in connectivity_matrix[cation_1].keys():
connected = False
for connectivity_type in connectivity_matrix[cation_1][cation_2].keys():
if connectivity_matrix[cation_1][cation_2][connectivity_type] != 0:
connected = True
if connected:
descriptions[cation_1] += "They are "
first = True
for connectivity_type in connectivity_matrix[cation_1][cation_2].keys():
if connectivity_matrix[cation_1][cation_2][connectivity_type] != 0:
if first:
descriptions[cation_1] += connectivity_type + "-connected "
first = False
else:
descriptions[cation_1] += "and " + connectivity_type + "-connected "
site_ces2 = find_species_ce_from_light_se(light_se, cation_1)
cn2 = []
for ce in site_ces2:
with open(path_to_jsons+"/%s.json" % ce) as json_file:
data2 = json.load(json_file)
cn2.append(data2['name'])
descriptions[cation_1] += "to " + cn2 + " " + cation_2 + ". "
return descriptions
