def test_serialization(self):
BaTiO3_se_fpath = os.path.join(
self.TEST_FILES_DIR,
"chemenv",
"structure_environments_files",
"se_mp-5020.json",
)
with open(BaTiO3_se_fpath) as f:
dd = json.load(f)
se = StructureEnvironments.from_dict(dd)
lse = LightStructureEnvironments.from_structure_environments(
strategy=SimplestChemenvStrategy(), structure_environments=se
)
cf = ConnectivityFinder()
sc = cf.get_structure_connectivity(light_structure_environments=lse)
sc_from_dict = StructureConnectivity.from_dict(sc.as_dict())
assert sc.light_structure_environments == sc_from_dict.light_structure_environments
assert set(sc._graph.nodes()) == set(sc_from_dict._graph.nodes())
assert set(sc._graph.edges()) == set(sc_from_dict._graph.edges())
sc_from_json = StructureConnectivity.from_dict(json.loads(json.dumps(sc.as_dict())))
assert sc.light_structure_environments == sc_from_json.light_structure_environments
assert set(sc._graph.nodes()) == set(sc_from_json._graph.nodes())
assert set(sc._graph.edges()) == set(sc_from_json._graph.edges())
if bson is not None:
bson_data = bson.BSON.encode(sc.as_dict())
sc_from_bson = StructureConnectivity.from_dict(bson_data.decode())
assert sc.light_structure_environments == sc_from_bson.light_structure_environments
assert set(sc._graph.nodes()) == set(sc_from_bson._graph.nodes())
assert set(sc._graph.edges()) == set(sc_from_bson._graph.edges())
def setUp(self):
self.lgf = LocalGeometryFinder()
self.lgf.setup_parameters(centering_type='standard')
self.strategies = [
SimplestChemenvStrategy(),
SimpleAbundanceChemenvStrategy()
]
def getSimplestChemenvStrategy(struct):
# Setup the local geometry finder
lgf = LocalGeometryFinder()
lgf.setup_parameters(centering_type='centroid',
include_central_site_in_centroid=True)
#you can also save the logging to a file, just remove the comment
# logging.basicConfig(#filename='chemenv_structure_environments.log',
# format='%(levelname)s:%(module)s:%(funcName)s:%(message)s',
# level=logging.DEBUG)
lgf.setup_structure(structure=struct)
se = lgf.compute_structure_environments(maximum_distance_factor=1.41,
only_cations=False)
strategy = SimplestChemenvStrategy(distance_cutoff=1.4, angle_cutoff=0.3)
lse = LightStructureEnvironments.from_structure_environments(
strategy=strategy, structure_environments=se)
return lse.coordination_environments
def test_read_write_structure_environments(self):
f = open(
"{}/{}".format(json_files_dir, "test_T--4_FePO4_icsd_4266.json"),
"r")
dd = json.load(f)
f.close()
atom_indices = dd["atom_indices"]
struct = Structure.from_dict(dd["structure"])
self.lgf.setup_structure(struct)
se = self.lgf.compute_structure_environments(
only_indices=atom_indices,
maximum_distance_factor=2.25,
get_from_hints=True)
f = open("tmp_dir/se.json", "w")
json.dump(se.as_dict(), f)
f.close()
f = open("tmp_dir/se.json", "r")
dd = json.load(f)
f.close()
se2 = StructureEnvironments.from_dict(dd)
self.assertEqual(se, se2)
strategy = SimplestChemenvStrategy()
lse = LightStructureEnvironments.from_structure_environments(
structure_environments=se, strategy=strategy, valences="undefined")
f = open("tmp_dir/lse.json", "w")
json.dump(lse.as_dict(), f)
f.close()
f = open("tmp_dir/lse.json", "r")
dd = json.load(f)
f.close()
lse2 = LightStructureEnvironments.from_dict(dd)
self.assertEqual(lse, lse2)
def test_read_structure_environments(self):
f = open("{}/{}".format(json_files_dir, 'test_T--4_FePO4_icsd_4266.json'), 'r')
dd = json.load(f)
f.close()
atom_indices = dd['atom_indices']
struct = Structure.from_dict(dd['structure'])
self.lgf.setup_structure(struct)
se = self.lgf.compute_structure_environments_detailed_voronoi(only_indices=atom_indices,
maximum_distance_factor=2.25)
f = open('tmp_dir/se.json', 'w')
json.dump(se.as_dict(), f)
f.close()
f = open('tmp_dir/se.json', 'r')
dd = json.load(f)
f.close()
se2 = StructureEnvironments.from_dict(dd)
self.assertEqual(se, se2)
_strategy = SimplestChemenvStrategy()
light_se = LightStructureEnvironments(_strategy, se)
f = open('tmp_dir/light_se.json', 'w')
json.dump(light_se.as_dict(), f)
f.close()
f = open('tmp_dir/light_se.json', 'r')
dd = json.load(f)
f.close()
light_se2 = LightStructureEnvironments.from_dict(dd)
self.assertEqual(light_se._strategy, light_se2._strategy)
self.assertEqual(light_se._structure, light_se2._structure)
self.assertEqual(light_se._bva_valences, light_se2._bva_valences)
self.assertEqual(light_se._coordination_environments, light_se2._coordination_environments)
self.assertEqual(light_se._neighbors, light_se2._neighbors)
self.assertEqual(light_se, light_se2)
def test_read_write_structure_environments(self):
f = open(
"{}/{}".format(json_files_dir, 'test_T--4_FePO4_icsd_4266.json'),
'r')
dd = json.load(f)
f.close()
atom_indices = dd['atom_indices']
struct = Structure.from_dict(dd['structure'])
self.lgf.setup_structure(struct)
se = self.lgf.compute_structure_environments(
only_indices=atom_indices, maximum_distance_factor=2.25)
f = open('tmp_dir/se.json', 'w')
json.dump(se.as_dict(), f)
f.close()
f = open('tmp_dir/se.json', 'r')
dd = json.load(f)
f.close()
se2 = StructureEnvironments.from_dict(dd)
self.assertEqual(se, se2)
strategy = SimplestChemenvStrategy()
lse = LightStructureEnvironments.from_structure_environments(
structure_environments=se, strategy=strategy, valences='undefined')
f = open('tmp_dir/lse.json', 'w')
json.dump(lse.as_dict(), f)
f.close()
f = open('tmp_dir/lse.json', 'r')
dd = json.load(f)
f.close()
lse2 = LightStructureEnvironments.from_dict(dd)
self.assertEqual(lse, lse2)
def from_preset(preset):
"""
Use a standard collection of CE types and
choose your ChemEnv neighbor-finding strategy.
Args:
preset (str): preset types ("simple" or
"multi_weights").
Returns:
ChemEnvSiteFingerprint object from a preset.
"""
cetypes = [
'S:1', 'L:2', 'A:2', 'TL:3', 'TY:3', 'TS:3', 'T:4', 'S:4', 'SY:4',
'SS:4', 'PP:5', 'S:5', 'T:5', 'O:6', 'T:6', 'PP:6', 'PB:7', 'ST:7',
'ET:7', 'FO:7', 'C:8', 'SA:8', 'SBT:8', 'TBT:8', 'DD:8', 'DDPN:8',
'HB:8', 'BO_1:8', 'BO_2:8', 'BO_3:8', 'TC:9', 'TT_1:9', 'TT_2:9',
'TT_3:9', 'HD:9', 'TI:9', 'SMA:9', 'SS:9', 'TO_1:9', 'TO_2:9',
'TO_3:9', 'PP:10', 'PA:10', 'SBSA:10', 'MI:10', 'S:10', 'H:10',
'BS_1:10', 'BS_2:10', 'TBSA:10', 'PCPA:11', 'H:11', 'SH:11',
'CO:11', 'DI:11', 'I:12', 'PBP:12', 'TT:12', 'C:12', 'AC:12',
'SC:12', 'S:12', 'HP:12', 'HA:12', 'SH:13', 'DD:20'
]
lgf = LocalGeometryFinder()
lgf.setup_parameters(
centering_type='centroid',
include_central_site_in_centroid=True,
structure_refinement=lgf.STRUCTURE_REFINEMENT_NONE)
if preset == "simple":
return ChemEnvSiteFingerprint(
cetypes,
SimplestChemenvStrategy(distance_cutoff=1.4, angle_cutoff=0.3),
lgf)
elif preset == "multi_weights":
return ChemEnvSiteFingerprint(
cetypes,
MultiWeightsChemenvStrategy.stats_article_weights_parameters(),
lgf)
else:
raise RuntimeError('unknown neighbor-finding strategy preset.')
def test_strategies(self):
simplest_strategy_1 = SimplestChemenvStrategy()
simplest_strategy_2 = SimplestChemenvStrategy(distance_cutoff=1.5,
angle_cutoff=0.5)
self.assertFalse(simplest_strategy_1 == simplest_strategy_2)
simplest_strategy_1_from_dict = SimplestChemenvStrategy.from_dict(
simplest_strategy_1.as_dict())
self.assertTrue(simplest_strategy_1, simplest_strategy_1_from_dict)
effective_csm_estimator = {
"function": "power2_inverse_decreasing",
"options": {
"max_csm": 8.0
},
}
self_csm_weight = SelfCSMNbSetWeight()
surface_definition = {
"type": "standard_elliptic",
"distance_bounds": {
"lower": 1.1,
"upper": 1.9
},
"angle_bounds": {
"lower": 0.1,
"upper": 0.9
},
}
surface_definition_2 = {
"type": "standard_elliptic",
"distance_bounds": {
"lower": 1.1,
"upper": 1.9
},
"angle_bounds": {
"lower": 0.1,
"upper": 0.95
},
}
da_area_weight = DistanceAngleAreaNbSetWeight(
weight_type="has_intersection",
surface_definition=surface_definition,
nb_sets_from_hints="fallback_to_source",
other_nb_sets="0_weight",
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB,
)
da_area_weight_2 = DistanceAngleAreaNbSetWeight(
weight_type="has_intersection",
surface_definition=surface_definition_2,
nb_sets_from_hints="fallback_to_source",
other_nb_sets="0_weight",
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB,
)
weight_estimator = {
"function": "smootherstep",
"options": {
"delta_csm_min": 0.5,
"delta_csm_max": 3.0
},
}
symmetry_measure_type = "csm_wcs_ctwcc"
delta_weight = DeltaCSMNbSetWeight(
effective_csm_estimator=effective_csm_estimator,
weight_estimator=weight_estimator,
symmetry_measure_type=symmetry_measure_type,
)
bias_weight = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0,
weight_cn13=4.0)
bias_weight_2 = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0,
weight_cn13=5.0)
angle_weight = AngleNbSetWeight()
nad_weight = NormalizedAngleDistanceNbSetWeight(
average_type="geometric", aa=1, bb=1)
multi_weights_strategy_1 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type,
)
multi_weights_strategy_2 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight_2,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type,
)
multi_weights_strategy_3 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight_2,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type,
)
multi_weights_strategy_1_from_dict = MultiWeightsChemenvStrategy.from_dict(
multi_weights_strategy_1.as_dict())
self.assertTrue(
multi_weights_strategy_1 == multi_weights_strategy_1_from_dict)
self.assertFalse(simplest_strategy_1 == multi_weights_strategy_1)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_2)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_3)
self.assertFalse(multi_weights_strategy_2 == multi_weights_strategy_3)
def test_light_structure_environments(self):
with ScratchDir("."):
f = open("{}/{}".format(se_files_dir, 'se_mp-7000.json'), 'r')
dd = json.load(f)
f.close()
se = StructureEnvironments.from_dict(dd)
strategy = SimplestChemenvStrategy()
lse = LightStructureEnvironments.from_structure_environments(
structure_environments=se,
strategy=strategy,
valences='undefined')
isite = 6
nb_set = lse.neighbors_sets[isite][0]
neighb_coords = [
np.array([0.2443798, 1.80409653, -1.13218359]),
np.array([1.44020353, 1.11368738, 1.13218359]),
np.array([2.75513098, 2.54465207, -0.70467298]),
np.array([0.82616785, 3.65833945, 0.70467298])
]
neighb_indices = [0, 3, 5, 1]
neighb_images = [[0, 0, -1], [0, 0, 0], [0, 0, -1], [0, 0, 0]]
np.testing.assert_array_almost_equal(neighb_coords,
nb_set.neighb_coords)
np.testing.assert_array_almost_equal(
neighb_coords, [s.coords for s in nb_set.neighb_sites])
nb_sai = nb_set.neighb_sites_and_indices
np.testing.assert_array_almost_equal(
neighb_coords, [sai['site'].coords for sai in nb_sai])
np.testing.assert_array_almost_equal(
neighb_indices, [sai['index'] for sai in nb_sai])
nb_iai = nb_set.neighb_indices_and_images
np.testing.assert_array_almost_equal(
neighb_indices, [iai['index'] for iai in nb_iai])
np.testing.assert_array_equal(
neighb_images, [iai['image_cell'] for iai in nb_iai])
self.assertEqual(nb_set.__len__(), 4)
self.assertEqual(nb_set.__hash__(), 4)
self.assertFalse(nb_set.__ne__(nb_set))
self.assertEqual(
nb_set.__str__(), 'Neighbors Set for site #6 :\n'
' - Coordination number : 4\n'
' - Neighbors sites indices : 0, 1, 2, 3\n')
stats = lse.get_statistics()
neighbors = lse.strategy.get_site_neighbors(
site=lse.structure[isite])
self.assertArrayAlmostEqual(
neighbors[0].coords,
np.array([0.2443798, 1.80409653, -1.13218359]))
self.assertArrayAlmostEqual(
neighbors[1].coords,
np.array([1.44020353, 1.11368738, 1.13218359]))
self.assertArrayAlmostEqual(
neighbors[2].coords,
np.array([2.75513098, 2.54465207, -0.70467298]))
self.assertArrayAlmostEqual(
neighbors[3].coords,
np.array([0.82616785, 3.65833945, 0.70467298]))
equiv_site_index_and_transform = lse.strategy.equivalent_site_index_and_transform(
neighbors[0])
self.assertEqual(equiv_site_index_and_transform[0], 0)
self.assertArrayAlmostEqual(equiv_site_index_and_transform[1],
[0.0, 0.0, 0.0])
self.assertArrayAlmostEqual(equiv_site_index_and_transform[2],
[0.0, 0.0, -1.0])
equiv_site_index_and_transform = lse.strategy.equivalent_site_index_and_transform(
neighbors[1])
self.assertEqual(equiv_site_index_and_transform[0], 3)
self.assertArrayAlmostEqual(equiv_site_index_and_transform[1],
[0.0, 0.0, 0.0])
self.assertArrayAlmostEqual(equiv_site_index_and_transform[2],
[0.0, 0.0, 0.0])
self.assertEqual(stats['atom_coordination_environments_present'],
{'Si': {
'T:4': 3.0
}})
self.assertEqual(stats['coordination_environments_atom_present'],
{'T:4': {
'Si': 3.0
}})
self.assertEqual(
stats['fraction_atom_coordination_environments_present'],
{'Si': {
'T:4': 1.0
}})
site_info_ce = lse.get_site_info_for_specie_ce(specie=Species(
'Si', 4),
ce_symbol='T:4')
np.testing.assert_array_almost_equal(site_info_ce['fractions'],
[1.0, 1.0, 1.0])
np.testing.assert_array_almost_equal(site_info_ce['csms'], [
0.009887784240541068, 0.009887786546730826,
0.009887787384385317
])
self.assertEqual(site_info_ce['isites'], [6, 7, 8])
site_info_allces = lse.get_site_info_for_specie_allces(
specie=Species('Si', 4))
self.assertEqual(site_info_allces['T:4'], site_info_ce)
self.assertFalse(lse.contains_only_one_anion('I-'))
self.assertFalse(lse.contains_only_one_anion_atom('I'))
self.assertTrue(
lse.site_contains_environment(isite=isite, ce_symbol='T:4'))
self.assertFalse(
lse.site_contains_environment(isite=isite, ce_symbol='S:4'))
self.assertFalse(
lse.structure_contains_atom_environment(atom_symbol='Si',
ce_symbol='S:4'))
self.assertTrue(
lse.structure_contains_atom_environment(atom_symbol='Si',
ce_symbol='T:4'))
self.assertFalse(
lse.structure_contains_atom_environment(atom_symbol='O',
ce_symbol='T:4'))
self.assertTrue(lse.uniquely_determines_coordination_environments)
self.assertFalse(lse.__ne__(lse))
envs = lse.strategy.get_site_coordination_environments(
lse.structure[6])
self.assertEqual(len(envs), 1)
self.assertEqual(envs[0][0], 'T:4')
multi_strategy = MultiWeightsChemenvStrategy.stats_article_weights_parameters(
)
lse_multi = LightStructureEnvironments.from_structure_environments(
strategy=multi_strategy,
structure_environments=se,
valences='undefined')
self.assertAlmostEqual(
lse_multi.coordination_environments[isite][0]['csm'],
0.009887784240541068)
self.assertAlmostEqual(
lse_multi.coordination_environments[isite][0]['ce_fraction'],
1.0)
self.assertEqual(
lse_multi.coordination_environments[isite][0]['ce_symbol'],
'T:4')
def test_coordination_sequences(self):
BaTiO3_se_fpath = os.path.join(
self.TEST_FILES_DIR,
"chemenv",
"structure_environments_files",
"se_mp-5020.json",
)
with open(BaTiO3_se_fpath, "r") as f:
dd = json.load(f)
se = StructureEnvironments.from_dict(dd)
lse = LightStructureEnvironments.from_structure_environments(
strategy=SimplestChemenvStrategy(), structure_environments=se)
cf = ConnectivityFinder()
sc = cf.get_structure_connectivity(light_structure_environments=lse)
ccs_oct = sc.get_connected_components(environments_symbols=["O:6"])
ccs_all = sc.get_connected_components(
environments_symbols=["O:6", "C:12"])
assert len(ccs_oct) == 1
assert len(ccs_all) == 1
cc_oct = ccs_oct[0]
cc_all = ccs_all[0]
cc_oct_node = list(cc_oct.graph.nodes())[0]
cseq = cc_oct.coordination_sequence(source_node=cc_oct_node,
path_size=6)
assert cseq == {1: 6, 2: 18, 3: 38, 4: 66, 5: 102, 6: 146}
cc_all_oct_node = next(n for n in cc_all.graph.nodes()
if n.coordination_environment == "O:6")
cc_all_cuboct_node = next(n for n in cc_all.graph.nodes()
if n.coordination_environment == "C:12")
cseq = cc_all.coordination_sequence(source_node=cc_all_oct_node,
path_size=6)
assert cseq == {1: 14, 2: 74, 3: 218, 4: 442, 5: 746, 6: 1130}
cseq = cc_all.coordination_sequence(source_node=cc_all_cuboct_node,
path_size=6)
assert cseq == {1: 26, 2: 122, 3: 298, 4: 554, 5: 890, 6: 1306}
cseq = cc_all.coordination_sequence(source_node=cc_all_cuboct_node,
path_size=6,
include_source=True)
assert cseq == {0: 1, 1: 26, 2: 122, 3: 298, 4: 554, 5: 890, 6: 1306}
cseq = cc_all.coordination_sequence(source_node=cc_all_oct_node,
path_size=4,
coordination="env:number")
assert cseq == {
1: {
"O:6": 6,
"C:12": 8
},
2: {
"O:6": 26,
"C:12": 48
},
3: {
"O:6": 90,
"C:12": 128
},
4: {
"O:6": 194,
"C:12": 248
},
}
cseq = cc_all.coordination_sequence(source_node=cc_all_cuboct_node,
path_size=4,
coordination="env:number")
assert cseq == {
1: {
"O:6": 8,
"C:12": 18
},
2: {
"O:6": 48,
"C:12": 74
},
3: {
"O:6": 128,
"C:12": 170
},
4: {
"O:6": 248,
"C:12": 306
},
}
cseq = cc_all.coordination_sequence(
source_node=cc_all_cuboct_node,
path_size=4,
coordination="env:number",
include_source=True,
)
assert cseq == {
0: {
"C:12": 1
},
1: {
"O:6": 8,
"C:12": 18
},
2: {
"O:6": 48,
"C:12": 74
},
3: {
"O:6": 128,
"C:12": 170
},
4: {
"O:6": 248,
"C:12": 306
},
}
def test_light_structure_environments(self):
with ScratchDir("."):
with open(f"{se_files_dir}/se_mp-7000.json") as f:
dd = json.load(f)
se = StructureEnvironments.from_dict(dd)
strategy = SimplestChemenvStrategy()
lse = LightStructureEnvironments.from_structure_environments(
structure_environments=se,
strategy=strategy,
valences="undefined")
isite = 6
nb_set = lse.neighbors_sets[isite][0]
neighb_coords = [
np.array([0.2443798, 1.80409653, -1.13218359]),
np.array([1.44020353, 1.11368738, 1.13218359]),
np.array([2.75513098, 2.54465207, -0.70467298]),
np.array([0.82616785, 3.65833945, 0.70467298]),
]
neighb_indices = [0, 3, 5, 1]
neighb_images = [[0, 0, -1], [0, 0, 0], [0, 0, -1], [0, 0, 0]]
np.testing.assert_array_almost_equal(neighb_coords,
nb_set.neighb_coords)
np.testing.assert_array_almost_equal(
neighb_coords, [s.coords for s in nb_set.neighb_sites])
nb_sai = nb_set.neighb_sites_and_indices
np.testing.assert_array_almost_equal(
neighb_coords, [sai["site"].coords for sai in nb_sai])
np.testing.assert_array_almost_equal(
neighb_indices, [sai["index"] for sai in nb_sai])
nb_iai = nb_set.neighb_indices_and_images
np.testing.assert_array_almost_equal(
neighb_indices, [iai["index"] for iai in nb_iai])
np.testing.assert_array_equal(
neighb_images, [iai["image_cell"] for iai in nb_iai])
self.assertEqual(nb_set.__len__(), 4)
self.assertEqual(nb_set.__hash__(), 4)
self.assertFalse(nb_set.__ne__(nb_set))
self.assertEqual(
nb_set.__str__(),
"Neighbors Set for site #6 :\n"
" - Coordination number : 4\n"
" - Neighbors sites indices : 0, 1, 2, 3\n",
)
stats = lse.get_statistics()
neighbors = lse.strategy.get_site_neighbors(
site=lse.structure[isite])
self.assertArrayAlmostEqual(
neighbors[0].coords,
np.array([0.2443798, 1.80409653, -1.13218359]))
self.assertArrayAlmostEqual(
neighbors[1].coords,
np.array([1.44020353, 1.11368738, 1.13218359]))
self.assertArrayAlmostEqual(
neighbors[2].coords,
np.array([2.75513098, 2.54465207, -0.70467298]))
self.assertArrayAlmostEqual(
neighbors[3].coords,
np.array([0.82616785, 3.65833945, 0.70467298]))
equiv_site_index_and_transform = lse.strategy.equivalent_site_index_and_transform(
neighbors[0])
self.assertEqual(equiv_site_index_and_transform[0], 0)
self.assertArrayAlmostEqual(equiv_site_index_and_transform[1],
[0.0, 0.0, 0.0])
self.assertArrayAlmostEqual(equiv_site_index_and_transform[2],
[0.0, 0.0, -1.0])
equiv_site_index_and_transform = lse.strategy.equivalent_site_index_and_transform(
neighbors[1])
self.assertEqual(equiv_site_index_and_transform[0], 3)
self.assertArrayAlmostEqual(equiv_site_index_and_transform[1],
[0.0, 0.0, 0.0])
self.assertArrayAlmostEqual(equiv_site_index_and_transform[2],
[0.0, 0.0, 0.0])
self.assertEqual(stats["atom_coordination_environments_present"],
{"Si": {
"T:4": 3.0
}})
self.assertEqual(stats["coordination_environments_atom_present"],
{"T:4": {
"Si": 3.0
}})
self.assertEqual(
stats["fraction_atom_coordination_environments_present"],
{"Si": {
"T:4": 1.0
}},
)
site_info_ce = lse.get_site_info_for_specie_ce(specie=Species(
"Si", 4),
ce_symbol="T:4")
np.testing.assert_array_almost_equal(site_info_ce["fractions"],
[1.0, 1.0, 1.0])
np.testing.assert_array_almost_equal(
site_info_ce["csms"],
[
0.009887784240541068, 0.009887786546730826,
0.009887787384385317
],
)
self.assertEqual(site_info_ce["isites"], [6, 7, 8])
site_info_allces = lse.get_site_info_for_specie_allces(
specie=Species("Si", 4))
self.assertEqual(site_info_allces["T:4"], site_info_ce)
self.assertFalse(lse.contains_only_one_anion("I-"))
self.assertFalse(lse.contains_only_one_anion_atom("I"))
self.assertTrue(
lse.site_contains_environment(isite=isite, ce_symbol="T:4"))
self.assertFalse(
lse.site_contains_environment(isite=isite, ce_symbol="S:4"))
self.assertFalse(
lse.structure_contains_atom_environment(atom_symbol="Si",
ce_symbol="S:4"))
self.assertTrue(
lse.structure_contains_atom_environment(atom_symbol="Si",
ce_symbol="T:4"))
self.assertFalse(
lse.structure_contains_atom_environment(atom_symbol="O",
ce_symbol="T:4"))
self.assertTrue(lse.uniquely_determines_coordination_environments)
self.assertFalse(lse.__ne__(lse))
envs = lse.strategy.get_site_coordination_environments(
lse.structure[6])
self.assertEqual(len(envs), 1)
self.assertEqual(envs[0][0], "T:4")
multi_strategy = MultiWeightsChemenvStrategy.stats_article_weights_parameters(
)
lse_multi = LightStructureEnvironments.from_structure_environments(
strategy=multi_strategy,
structure_environments=se,
valences="undefined")
self.assertAlmostEqual(
lse_multi.coordination_environments[isite][0]["csm"],
0.009887784240541068,
)
self.assertAlmostEqual(
lse_multi.coordination_environments[isite][0]["ce_fraction"],
1.0)
self.assertEqual(
lse_multi.coordination_environments[isite][0]["ce_symbol"],
"T:4")
def test_strategies(self):
simplest_strategy_1 = SimplestChemenvStrategy()
simplest_strategy_2 = SimplestChemenvStrategy(distance_cutoff=1.5, angle_cutoff=0.5)
self.assertFalse(simplest_strategy_1 == simplest_strategy_2)
simplest_strategy_1_from_dict = SimplestChemenvStrategy.from_dict(simplest_strategy_1.as_dict())
self.assertTrue(simplest_strategy_1, simplest_strategy_1_from_dict)
effective_csm_estimator = {'function': 'power2_inverse_decreasing',
'options': {'max_csm': 8.0}}
self_csm_weight = SelfCSMNbSetWeight()
surface_definition = {'type': 'standard_elliptic',
'distance_bounds': {'lower': 1.1, 'upper': 1.9},
'angle_bounds': {'lower': 0.1, 'upper': 0.9}}
surface_definition_2 = {'type': 'standard_elliptic',
'distance_bounds': {'lower': 1.1, 'upper': 1.9},
'angle_bounds': {'lower': 0.1, 'upper': 0.95}}
da_area_weight = DistanceAngleAreaNbSetWeight(weight_type='has_intersection',
surface_definition=surface_definition,
nb_sets_from_hints='fallback_to_source',
other_nb_sets='0_weight',
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB)
da_area_weight_2 = DistanceAngleAreaNbSetWeight(weight_type='has_intersection',
surface_definition=surface_definition_2,
nb_sets_from_hints='fallback_to_source',
other_nb_sets='0_weight',
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB)
weight_estimator = {'function': 'smootherstep',
'options': {'delta_csm_min': 0.5,
'delta_csm_max': 3.0}}
symmetry_measure_type = 'csm_wcs_ctwcc'
delta_weight = DeltaCSMNbSetWeight(effective_csm_estimator=effective_csm_estimator,
weight_estimator=weight_estimator,
symmetry_measure_type=symmetry_measure_type)
bias_weight = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0, weight_cn13=4.0)
bias_weight_2 = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0, weight_cn13=5.0)
angle_weight = AngleNbSetWeight()
nad_weight = NormalizedAngleDistanceNbSetWeight(average_type='geometric', aa=1, bb=1)
multi_weights_strategy_1 = MultiWeightsChemenvStrategy(dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_2 = MultiWeightsChemenvStrategy(dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight_2,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_3 = MultiWeightsChemenvStrategy(dist_ang_area_weight=da_area_weight_2,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_1_from_dict = MultiWeightsChemenvStrategy.from_dict(multi_weights_strategy_1.as_dict())
self.assertTrue(multi_weights_strategy_1 == multi_weights_strategy_1_from_dict)
self.assertFalse(simplest_strategy_1 == multi_weights_strategy_1)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_2)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_3)
self.assertFalse(multi_weights_strategy_2 == multi_weights_strategy_3)
def test_strategies(self):
simplest_strategy_1 = SimplestChemenvStrategy()
simplest_strategy_2 = SimplestChemenvStrategy(distance_cutoff=1.5,
angle_cutoff=0.5)
self.assertFalse(simplest_strategy_1 == simplest_strategy_2)
simplest_strategy_1_from_dict = SimplestChemenvStrategy.from_dict(
simplest_strategy_1.as_dict())
self.assertTrue(simplest_strategy_1, simplest_strategy_1_from_dict)
effective_csm_estimator = {
'function': 'power2_inverse_decreasing',
'options': {
'max_csm': 8.0
}
}
self_csm_weight = SelfCSMNbSetWeight()
surface_definition = {
'type': 'standard_elliptic',
'distance_bounds': {
'lower': 1.1,
'upper': 1.9
},
'angle_bounds': {
'lower': 0.1,
'upper': 0.9
}
}
surface_definition_2 = {
'type': 'standard_elliptic',
'distance_bounds': {
'lower': 1.1,
'upper': 1.9
},
'angle_bounds': {
'lower': 0.1,
'upper': 0.95
}
}
da_area_weight = DistanceAngleAreaNbSetWeight(
weight_type='has_intersection',
surface_definition=surface_definition,
nb_sets_from_hints='fallback_to_source',
other_nb_sets='0_weight',
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB)
da_area_weight_2 = DistanceAngleAreaNbSetWeight(
weight_type='has_intersection',
surface_definition=surface_definition_2,
nb_sets_from_hints='fallback_to_source',
other_nb_sets='0_weight',
additional_condition=DistanceAngleAreaNbSetWeight.AC.ONLY_ACB)
weight_estimator = {
'function': 'smootherstep',
'options': {
'delta_csm_min': 0.5,
'delta_csm_max': 3.0
}
}
symmetry_measure_type = 'csm_wcs_ctwcc'
delta_weight = DeltaCSMNbSetWeight(
effective_csm_estimator=effective_csm_estimator,
weight_estimator=weight_estimator,
symmetry_measure_type=symmetry_measure_type)
bias_weight = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0,
weight_cn13=4.0)
bias_weight_2 = CNBiasNbSetWeight.linearly_equidistant(weight_cn1=1.0,
weight_cn13=5.0)
angle_weight = AngleNbSetWeight()
nad_weight = NormalizedAngleDistanceNbSetWeight(
average_type='geometric', aa=1, bb=1)
multi_weights_strategy_1 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_2 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight_2,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_3 = MultiWeightsChemenvStrategy(
dist_ang_area_weight=da_area_weight_2,
self_csm_weight=self_csm_weight,
delta_csm_weight=delta_weight,
cn_bias_weight=bias_weight,
angle_weight=angle_weight,
normalized_angle_distance_weight=nad_weight,
symmetry_measure_type=symmetry_measure_type)
multi_weights_strategy_1_from_dict = MultiWeightsChemenvStrategy.from_dict(
multi_weights_strategy_1.as_dict())
self.assertTrue(
multi_weights_strategy_1 == multi_weights_strategy_1_from_dict)
self.assertFalse(simplest_strategy_1 == multi_weights_strategy_1)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_2)
self.assertFalse(multi_weights_strategy_1 == multi_weights_strategy_3)
self.assertFalse(multi_weights_strategy_2 == multi_weights_strategy_3)
def get_chemenv_analysis(struct, distance_cutoff, angle_cutoff):
if not struct:
raise PreventUpdate
struct = self.from_data(struct)
distance_cutoff = float(distance_cutoff)
angle_cutoff = float(angle_cutoff)
# decide which indices to present to user
sga = SpacegroupAnalyzer(struct)
symm_struct = sga.get_symmetrized_structure()
inequivalent_indices = [
indices[0] for indices in symm_struct.equivalent_indices
]
wyckoffs = symm_struct.wyckoff_symbols
lgf = LocalGeometryFinder()
lgf.setup_structure(structure=struct)
se = lgf.compute_structure_environments(
maximum_distance_factor=distance_cutoff + 0.01,
only_indices=inequivalent_indices,
)
strategy = SimplestChemenvStrategy(distance_cutoff=distance_cutoff,
angle_cutoff=angle_cutoff)
lse = LightStructureEnvironments.from_structure_environments(
strategy=strategy, structure_environments=se)
all_ce = AllCoordinationGeometries()
envs = []
unknown_sites = []
for index, wyckoff in zip(inequivalent_indices, wyckoffs):
datalist = {
"Site": struct[index].species_string,
"Wyckoff Label": wyckoff,
}
if not lse.neighbors_sets[index]:
unknown_sites.append(
f"{struct[index].species_string} ({wyckoff})")
continue
# represent the local environment as a molecule
mol = Molecule.from_sites(
[struct[index]] +
lse.neighbors_sets[index][0].neighb_sites)
mol = mol.get_centered_molecule()
mg = MoleculeGraph.with_empty_graph(molecule=mol)
for i in range(1, len(mol)):
mg.add_edge(0, i)
view = html.Div(
[
StructureMoleculeComponent(
struct_or_mol=mg,
static=True,
id=
f"{struct.composition.reduced_formula}_site_{index}",
scene_settings={
"enableZoom": False,
"defaultZoom": 0.6
},
).all_layouts["struct"]
],
style={
"width": "300px",
"height": "300px"
},
)
env = lse.coordination_environments[index]
co = all_ce.get_geometry_from_mp_symbol(env[0]["ce_symbol"])
name = co.name
if co.alternative_names:
name += f" (also known as {', '.join(co.alternative_names)})"
datalist.update({
"Environment":
name,
"IUPAC Symbol":
co.IUPAC_symbol_str,
get_tooltip(
"CSM",
'"Continuous Symmetry Measure," a measure of how symmetrical a '
"local environment is from most symmetrical at 0% to least "
"symmetrical at 100%",
):
f"{env[0]['csm']:.2f}%",
"Interactive View":
view,
})
envs.append(get_data_list(datalist))
# TODO: switch to tiles?
envs_grouped = [envs[i:i + 2] for i in range(0, len(envs), 2)]
analysis_contents = []
for env_group in envs_grouped:
analysis_contents.append(
Columns([Column(e, size=6) for e in env_group]))
if unknown_sites:
unknown_sites = html.Strong(
f"The following sites were not identified: {', '.join(unknown_sites)}. "
f"Please try changing the distance or angle cut-offs to identify these sites."
)
else:
unknown_sites = html.Span()
return html.Div(
[html.Div(analysis_contents),
html.Br(), unknown_sites])
def get_chemenv_analysis(struct, distance_cutoff, angle_cutoff):
if not struct:
raise PreventUpdate
struct = self.from_data(struct)
kwargs = self.reconstruct_kwargs_from_state(
callback_context.inputs)
distance_cutoff = kwargs["distance_cutoff"]
angle_cutoff = kwargs["angle_cutoff"]
# TODO: remove these brittle guard statements, figure out more robust way to handle multiple input types
if isinstance(struct, StructureGraph):
struct = struct.structure
def get_valences(struct):
valences = [
getattr(site.specie, "oxi_state", None) for site in struct
]
valences = [v for v in valences if v is not None]
if len(valences) == len(struct):
return valences
else:
return "undefined"
# decide which indices to present to user
sga = SpacegroupAnalyzer(struct)
symm_struct = sga.get_symmetrized_structure()
inequivalent_indices = [
indices[0] for indices in symm_struct.equivalent_indices
]
wyckoffs = symm_struct.wyckoff_symbols
lgf = LocalGeometryFinder()
lgf.setup_structure(structure=struct)
se = lgf.compute_structure_environments(
maximum_distance_factor=distance_cutoff + 0.01,
only_indices=inequivalent_indices,
valences=get_valences(struct),
)
strategy = SimplestChemenvStrategy(distance_cutoff=distance_cutoff,
angle_cutoff=angle_cutoff)
lse = LightStructureEnvironments.from_structure_environments(
strategy=strategy, structure_environments=se)
all_ce = AllCoordinationGeometries()
envs = []
unknown_sites = []
for index, wyckoff in zip(inequivalent_indices, wyckoffs):
datalist = {
"Site": unicodeify_species(struct[index].species_string),
"Wyckoff Label": wyckoff,
}
if not lse.neighbors_sets[index]:
unknown_sites.append(
f"{struct[index].species_string} ({wyckoff})")
continue
# represent the local environment as a molecule
mol = Molecule.from_sites(
[struct[index]] +
lse.neighbors_sets[index][0].neighb_sites)
mol = mol.get_centered_molecule()
mg = MoleculeGraph.with_empty_graph(molecule=mol)
for i in range(1, len(mol)):
mg.add_edge(0, i)
view = html.Div(
[
StructureMoleculeComponent(
struct_or_mol=mg,
disable_callbacks=True,
id=
f"{struct.composition.reduced_formula}_site_{index}",
scene_settings={
"enableZoom": False,
"defaultZoom": 0.6
},
)._sub_layouts["struct"]
],
style={
"width": "300px",
"height": "300px"
},
)
env = lse.coordination_environments[index]
co = all_ce.get_geometry_from_mp_symbol(env[0]["ce_symbol"])
name = co.name
if co.alternative_names:
name += f" (also known as {', '.join(co.alternative_names)})"
datalist.update({
"Environment":
name,
"IUPAC Symbol":
co.IUPAC_symbol_str,
get_tooltip(
"CSM",
"The continuous symmetry measure (CSM) describes the similarity to an "
"ideal coordination environment. It can be understood as a 'distance' to "
"a shape and ranges from 0 to 100 in which 0 corresponds to a "
"coordination environment that is exactly identical to the ideal one. A "
"CSM larger than 5.0 already indicates a relatively strong distortion of "
"the investigated coordination environment.",
):
f"{env[0]['csm']:.2f}",
"Interactive View":
view,
})
envs.append(get_data_list(datalist))
# TODO: switch to tiles?
envs_grouped = [envs[i:i + 2] for i in range(0, len(envs), 2)]
analysis_contents = []
for env_group in envs_grouped:
analysis_contents.append(
Columns([Column(e, size=6) for e in env_group]))
if unknown_sites:
unknown_sites = html.Strong(
f"The following sites were not identified: {', '.join(unknown_sites)}. "
f"Please try changing the distance or angle cut-offs to identify these sites, "
f"or try an alternative algorithm such as LocalEnv.")
else:
unknown_sites = html.Span()
return html.Div(
[html.Div(analysis_contents),
html.Br(), unknown_sites])
def test_strategies(self):
simplest_strategy = SimplestChemenvStrategy()
self.assertTrue(simplest_strategy.uniquely_determines_coordination_environments)
self.assertAlmostEqual(
simplest_strategy.continuous_symmetry_measure_cutoff, 10.0
)
self.assertAlmostEqual(simplest_strategy.distance_cutoff, 1.4)
self.assertAlmostEqual(simplest_strategy.angle_cutoff, 0.3)
simplest_strategy = SimplestChemenvStrategy(
distance_cutoff=1.3,
angle_cutoff=0.45,
continuous_symmetry_measure_cutoff=8.26,
)
self.assertAlmostEqual(
simplest_strategy.continuous_symmetry_measure_cutoff, 8.26
)
self.assertAlmostEqual(simplest_strategy.distance_cutoff, 1.3)
self.assertAlmostEqual(simplest_strategy.angle_cutoff, 0.45)
simplest_strategy.set_option("distance_cutoff", 1.5)
self.assertAlmostEqual(simplest_strategy.distance_cutoff, 1.5)
with self.assertRaises(ValueError) as cm:
simplest_strategy.set_option("distance_cutoff", 0.5)
self.assertEqual(
str(cm.exception), "Distance cutoff should be between 1.0 and +infinity"
)
simplest_strategy.set_option("angle_cutoff", 0.2)
self.assertAlmostEqual(simplest_strategy.angle_cutoff, 0.2)
with self.assertRaises(ValueError) as cm:
simplest_strategy.set_option("angle_cutoff", 1.5)
self.assertEqual(
str(cm.exception), "Angle cutoff should be between 0.0 and 1.0"
)
simplest_strategy.setup_options(
{
"distance_cutoff": 1.4,
"additional_condition": 3,
"continuous_symmetry_measure_cutoff": 8.5,
}
)
self.assertAlmostEqual(simplest_strategy.distance_cutoff, 1.4)
self.assertAlmostEqual(
simplest_strategy.continuous_symmetry_measure_cutoff, 8.5
)
self.assertEqual(simplest_strategy.additional_condition, 3)
with self.assertRaises(ValueError) as cm:
simplest_strategy.setup_options(
{"continuous_symmetry_measure_cutoff": -0.1}
)
self.assertEqual(
str(cm.exception),
"Continuous symmetry measure limits should be between 0.0 and 100.0",
)
with self.assertRaises(ValueError) as cm:
simplest_strategy.setup_options(
{"continuous_symmetry_measure_cutoff": 100.1}
)
self.assertEqual(
str(cm.exception),
"Continuous symmetry measure limits should be between 0.0 and 100.0",
)
def test_real_systems(self):
# Initialize geometry and connectivity finders
strat = SimplestChemenvStrategy()
lgf = LocalGeometryFinder()
cf = ConnectivityFinder()
# Connectivity of LiFePO4
struct = self.get_structure("LiFePO4")
lgf.setup_structure(structure=struct)
se = lgf.compute_structure_environments(only_atoms=["Li", "Fe", "P"],
maximum_distance_factor=1.2)
lse = LightStructureEnvironments.from_structure_environments(
strategy=strat, structure_environments=se)
# Make sure the initial structure and environments are correct
for isite in range(0, 4):
assert lse.structure[isite].specie.symbol == "Li"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "O:6"
for isite in range(4, 8):
assert lse.structure[isite].specie.symbol == "Fe"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "O:6"
for isite in range(8, 12):
assert lse.structure[isite].specie.symbol == "P"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "T:4"
# Get the connectivity including all environments and check results
sc = cf.get_structure_connectivity(lse)
assert len(sc.environment_subgraphs
) == 0 # Connected component not computed by default
ccs = sc.get_connected_components(
) # by default, will use all the environments (O:6 and T:4 here)
assert list(sc.environment_subgraphs.keys()) == [
"O:6-T:4"
] # Now the default components are there
assert len(sc.environment_subgraphs) == 1
assert len(ccs) == 1
cc = ccs[0]
assert len(cc) == 12
assert cc.periodicity == "3D"
assert (
cc.description() == """Connected component with environment nodes :
Node #0 Li (O:6)
Node #1 Li (O:6)
Node #2 Li (O:6)
Node #3 Li (O:6)
Node #4 Fe (O:6)
Node #5 Fe (O:6)
Node #6 Fe (O:6)
Node #7 Fe (O:6)
Node #8 P (T:4)
Node #9 P (T:4)
Node #10 P (T:4)
Node #11 P (T:4)""")
assert (cc.description(
full=True) == """Connected component with environment nodes :
Node #0 Li (O:6), connected to :
- Node #1 Li (O:6) with delta image cells
(-1 0 1)
(-1 1 1)
- Node #4 Fe (O:6) with delta image cells
(-1 1 1)
(0 1 1)
- Node #5 Fe (O:6) with delta image cells
(0 0 1)
- Node #6 Fe (O:6) with delta image cells
(-1 1 0)
- Node #7 Fe (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #8 P (T:4) with delta image cells
(-1 0 1)
(0 0 1)
- Node #11 P (T:4) with delta image cells
(-1 1 0)
(0 1 0)
Node #1 Li (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(1 -1 -1)
(1 0 -1)
- Node #4 Fe (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #5 Fe (O:6) with delta image cells
(1 0 0)
- Node #6 Fe (O:6) with delta image cells
(0 0 -1)
- Node #7 Fe (O:6) with delta image cells
(0 0 -1)
(1 0 -1)
- Node #8 P (T:4) with delta image cells
(0 0 0)
(1 0 0)
- Node #11 P (T:4) with delta image cells
(0 0 -1)
(1 0 -1)
Node #2 Li (O:6), connected to :
- Node #3 Li (O:6) with delta image cells
(0 0 0)
(0 1 0)
- Node #4 Fe (O:6) with delta image cells
(0 1 0)
- Node #5 Fe (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #6 Fe (O:6) with delta image cells
(-1 1 0)
(0 1 0)
- Node #7 Fe (O:6) with delta image cells
(0 0 0)
- Node #9 P (T:4) with delta image cells
(0 1 0)
(1 1 0)
- Node #10 P (T:4) with delta image cells
(-1 0 0)
(0 0 0)
Node #3 Li (O:6), connected to :
- Node #2 Li (O:6) with delta image cells
(0 -1 0)
(0 0 0)
- Node #4 Fe (O:6) with delta image cells
(0 0 0)
- Node #5 Fe (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #6 Fe (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #7 Fe (O:6) with delta image cells
(0 0 0)
- Node #9 P (T:4) with delta image cells
(0 0 0)
(1 0 0)
- Node #10 P (T:4) with delta image cells
(-1 0 0)
(0 0 0)
Node #4 Fe (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(0 -1 -1)
(1 -1 -1)
- Node #1 Li (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #2 Li (O:6) with delta image cells
(0 -1 0)
- Node #3 Li (O:6) with delta image cells
(0 0 0)
- Node #5 Fe (O:6) with delta image cells
(0 -1 0)
(0 0 0)
(1 -1 0)
(1 0 0)
- Node #8 P (T:4) with delta image cells
(0 -1 0)
(0 0 0)
- Node #9 P (T:4) with delta image cells
(0 0 0)
(1 0 0)
- Node #11 P (T:4) with delta image cells
(0 0 -1)
Node #5 Fe (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(0 0 -1)
- Node #1 Li (O:6) with delta image cells
(-1 0 0)
- Node #2 Li (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #3 Li (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #4 Fe (O:6) with delta image cells
(-1 0 0)
(-1 1 0)
(0 0 0)
(0 1 0)
- Node #8 P (T:4) with delta image cells
(-1 0 0)
(0 0 0)
- Node #9 P (T:4) with delta image cells
(0 0 0)
(0 1 0)
- Node #10 P (T:4) with delta image cells
(-1 0 0)
Node #6 Fe (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(1 -1 0)
- Node #1 Li (O:6) with delta image cells
(0 0 1)
- Node #2 Li (O:6) with delta image cells
(0 -1 0)
(1 -1 0)
- Node #3 Li (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #7 Fe (O:6) with delta image cells
(0 -1 0)
(0 0 0)
(1 -1 0)
(1 0 0)
- Node #9 P (T:4) with delta image cells
(1 0 0)
- Node #10 P (T:4) with delta image cells
(0 -1 0)
(0 0 0)
- Node #11 P (T:4) with delta image cells
(0 0 0)
(1 0 0)
Node #7 Fe (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #1 Li (O:6) with delta image cells
(-1 0 1)
(0 0 1)
- Node #2 Li (O:6) with delta image cells
(0 0 0)
- Node #3 Li (O:6) with delta image cells
(0 0 0)
- Node #6 Fe (O:6) with delta image cells
(-1 0 0)
(-1 1 0)
(0 0 0)
(0 1 0)
- Node #8 P (T:4) with delta image cells
(0 0 1)
- Node #10 P (T:4) with delta image cells
(-1 0 0)
(0 0 0)
- Node #11 P (T:4) with delta image cells
(0 0 0)
(0 1 0)
Node #8 P (T:4), connected to :
- Node #0 Li (O:6) with delta image cells
(0 0 -1)
(1 0 -1)
- Node #1 Li (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #4 Fe (O:6) with delta image cells
(0 0 0)
(0 1 0)
- Node #5 Fe (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #7 Fe (O:6) with delta image cells
(0 0 -1)
Node #9 P (T:4), connected to :
- Node #2 Li (O:6) with delta image cells
(-1 -1 0)
(0 -1 0)
- Node #3 Li (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #4 Fe (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #5 Fe (O:6) with delta image cells
(0 -1 0)
(0 0 0)
- Node #6 Fe (O:6) with delta image cells
(-1 0 0)
Node #10 P (T:4), connected to :
- Node #2 Li (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #3 Li (O:6) with delta image cells
(0 0 0)
(1 0 0)
- Node #5 Fe (O:6) with delta image cells
(1 0 0)
- Node #6 Fe (O:6) with delta image cells
(0 0 0)
(0 1 0)
- Node #7 Fe (O:6) with delta image cells
(0 0 0)
(1 0 0)
Node #11 P (T:4), connected to :
- Node #0 Li (O:6) with delta image cells
(0 -1 0)
(1 -1 0)
- Node #1 Li (O:6) with delta image cells
(-1 0 1)
(0 0 1)
- Node #4 Fe (O:6) with delta image cells
(0 0 1)
- Node #6 Fe (O:6) with delta image cells
(-1 0 0)
(0 0 0)
- Node #7 Fe (O:6) with delta image cells
(0 -1 0)
(0 0 0)""")
# Get the connectivity for T:4 and O:6 separately and check results
# Only tetrahedral
sc.setup_environment_subgraph(environments_symbols=["T:4"])
assert list(sc.environment_subgraphs.keys()) == ["O:6-T:4", "T:4"]
ccs = sc.get_connected_components()
assert len(ccs) == 4
for cc in ccs:
assert cc.periodicity == "0D"
# Only octahedral
sc.setup_environment_subgraph(environments_symbols=["O:6"])
assert list(
sc.environment_subgraphs.keys()) == ["O:6-T:4", "T:4", "O:6"]
ccs = sc.get_connected_components()
assert len(ccs) == 1
cc = ccs[0]
assert cc.periodicity == "3D"
# Only Manganese octahedral
sc.setup_environment_subgraph(environments_symbols=["O:6"],
only_atoms=["Fe"])
assert list(sc.environment_subgraphs.keys()) == [
"O:6-T:4",
"T:4",
"O:6",
"O:6#Fe",
]
ccs = sc.get_connected_components()
assert len(ccs) == 2
for cc in ccs:
assert cc.periodicity == "2D"
# Connectivity of Li4Fe3Mn1(PO4)4
struct = Structure.from_file(
os.path.join(self.TEST_FILES_DIR, "Li4Fe3Mn1(PO4)4.cif"))
lgf.setup_structure(structure=struct)
se = lgf.compute_structure_environments(
only_atoms=["Li", "Fe", "Mn", "P"], maximum_distance_factor=1.2)
lse = LightStructureEnvironments.from_structure_environments(
strategy=strat, structure_environments=se)
# Make sure the initial structure and environments are correct
for isite in range(0, 4):
assert lse.structure[isite].specie.symbol == "Li"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "O:6"
for isite in range(4, 5):
assert lse.structure[isite].specie.symbol == "Mn"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "O:6"
for isite in range(5, 8):
assert lse.structure[isite].specie.symbol == "Fe"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "O:6"
for isite in range(8, 12):
assert lse.structure[isite].specie.symbol == "P"
assert lse.coordination_environments[isite][0][
"ce_symbol"] == "T:4"
# Get the connectivity including all environments and check results
sc = cf.get_structure_connectivity(lse)
assert len(sc.environment_subgraphs
) == 0 # Connected component not computed by default
ccs = sc.get_connected_components(
) # by default, will use all the environments (O:6 and T:4 here)
# Now connected components for the defaults are there :
assert list(sc.environment_subgraphs.keys()) == ["O:6-T:4"]
assert len(sc.environment_subgraphs) == 1
assert len(ccs) == 1
cc = ccs[0]
assert cc.periodicity == "3D"
# Get the connectivity for Li octahedral only
ccs = sc.get_connected_components(environments_symbols=["O:6"],
only_atoms=["Li"])
assert list(sc.environment_subgraphs.keys()) == ["O:6-T:4", "O:6#Li"]
assert len(ccs) == 2
for cc in ccs:
assert cc.periodicity == "1D"
assert len(cc) == 2
# Sort connected components as they might
# come in a different order depending on
# the algorithm used to get them.
sorted_ccs = sorted(ccs, key=lambda x: sorted(x.graph.nodes())[0])
assert (sorted_ccs[0].description(
full=True) == """Connected component with environment nodes :
Node #0 Li (O:6), connected to :
- Node #1 Li (O:6) with delta image cells
(1 -1 1)
(1 0 1)
Node #1 Li (O:6), connected to :
- Node #0 Li (O:6) with delta image cells
(-1 0 -1)
(-1 1 -1)""")
assert (sorted_ccs[1].description(
full=True) == """Connected component with environment nodes :
Node #2 Li (O:6), connected to :
- Node #3 Li (O:6) with delta image cells
(0 -1 0)
(0 0 0)
Node #3 Li (O:6), connected to :
- Node #2 Li (O:6) with delta image cells
(0 0 0)
(0 1 0)""")
# Get the connectivity for Mn octahedral only
ccs = sc.get_connected_components(environments_symbols=["O:6"],
only_atoms=["Mn"])
assert list(sc.environment_subgraphs.keys()) == [
"O:6-T:4", "O:6#Li", "O:6#Mn"
]
assert len(ccs) == 1
assert ccs[0].periodicity == "0D"
# Get the connectivity for Fe octahedral only
ccs = sc.get_connected_components(environments_symbols=["O:6"],
only_atoms=["Fe"])
assert list(sc.environment_subgraphs.keys()) == [
"O:6-T:4",
"O:6#Li",
"O:6#Mn",
"O:6#Fe",
]
assert len(ccs) == 2
ccs_periodicities = set(cc.periodicity for cc in ccs)
assert ccs_periodicities == {"0D", "2D"}