def test_read_write_voronoi(self):
f = open(
"{}/{}".format(json_files_dir, "test_T--4_FePO4_icsd_4266.json"),
"r")
dd = json.load(f)
f.close()
struct = Structure.from_dict(dd["structure"])
valences = [site.specie.oxi_state for site in struct]
detailed_voronoi_container = DetailedVoronoiContainer(
structure=struct, valences=valences)
f = open("tmp_dir/se.json", "w")
json.dump(detailed_voronoi_container.as_dict(), f)
f.close()
f = open("tmp_dir/se.json", "r")
dd = json.load(f)
f.close()
detailed_voronoi_container2 = DetailedVoronoiContainer.from_dict(dd)
self.assertEqual(detailed_voronoi_container,
detailed_voronoi_container2)
def test_get_vertices_dist_ang_indices(self):
with ScratchDir("."):
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
#First fake structure
coords = [[5.0, 5.0, 5.0],
[6.01, 5.0, 5.0],
[5.0, 5.0, 3.96],
[4.0, 5.0, 5.0],
[5.0, 6.03, 5.0],
[5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
#First fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
normalized_distance_tolerance=0.0100001, isites=[0])
fake_parameter_indices_list = []
for ii in range(2, 5):
for jj in range(7, 14):
fake_parameter_indices_list.append((ii, jj))
for ii in range(5, 7):
for jj in range(10, 14):
fake_parameter_indices_list.append((ii, jj))
points = detailed_voronoi_container._get_vertices_dist_ang_indices(fake_parameter_indices_list)
self.assertEqual(points[0], (2, 7))
self.assertEqual(points[1], (4, 7))
self.assertEqual(points[2], (4, 10))
self.assertEqual(points[3], (6, 10))
self.assertEqual(points[4], (6, 13))
self.assertEqual(points[5], (2, 13))
def test_get_vertices_dist_ang_indices(self):
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
#First fake structure
coords = [[5.0, 5.0, 5.0],
[6.01, 5.0, 5.0],
[5.0, 5.0, 3.96],
[4.0, 5.0, 5.0],
[5.0, 6.03, 5.0],
[5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
#First fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
normalized_distance_tolerance=0.0100001, isites=[0])
fake_parameter_indices_list = []
for ii in range(2, 5):
for jj in range(7, 14):
fake_parameter_indices_list.append((ii, jj))
for ii in range(5, 7):
for jj in range(10, 14):
fake_parameter_indices_list.append((ii, jj))
points = detailed_voronoi_container._get_vertices_dist_ang_indices(fake_parameter_indices_list)
self.assertEqual(points[0], (2, 7))
self.assertEqual(points[1], (4, 7))
self.assertEqual(points[2], (4, 10))
self.assertEqual(points[3], (6, 10))
self.assertEqual(points[4], (6, 13))
self.assertEqual(points[5], (2, 13))
def test_read_write_voronoi(self):
with open(f"{json_files_dir}/test_T--4_FePO4_icsd_4266.json") as f:
dd = json.load(f)
struct = Structure.from_dict(dd["structure"])
valences = [site.specie.oxi_state for site in struct]
detailed_voronoi_container = DetailedVoronoiContainer(
structure=struct, valences=valences)
with open("tmp_dir/se.json", "w") as f:
json.dump(detailed_voronoi_container.as_dict(), f)
with open("tmp_dir/se.json") as f:
dd = json.load(f)
detailed_voronoi_container2 = DetailedVoronoiContainer.from_dict(dd)
self.assertEqual(detailed_voronoi_container,
detailed_voronoi_container2)
def voronoi(self):
"""
Pymatgen ChemEnv voronoi decomposition of the cathode structure.
Returns:
pymatgen.analysis.chemenv.coordination_environments.voronoi.\
DetailedVoronoiContainer
"""
if self._voronoi is None:
self._voronoi = DetailedVoronoiContainer(self)
return self._voronoi
def test_read_write_voronoi(self):
f = open("{}/{}".format(json_files_dir, 'test_T--4_FePO4_icsd_4266.json'), 'r')
dd = json.load(f)
f.close()
struct = Structure.from_dict(dd['structure'])
valences = [site.specie.oxi_state for site in struct]
detailed_voronoi_container = DetailedVoronoiContainer(structure=struct, valences=valences)
f = open('tmp_dir/se.json', 'w')
json.dump(detailed_voronoi_container.as_dict(), f)
f.close()
f = open('tmp_dir/se.json', 'r')
dd = json.load(f)
f.close()
detailed_voronoi_container2 = DetailedVoronoiContainer.from_dict(dd)
self.assertEqual(detailed_voronoi_container, detailed_voronoi_container2)
def test_voronoi(self):
with ScratchDir("."):
# Define a cubic lattice and a list of species (to be used for the fake structures)
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
# First fake structure
coords = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]), (2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]), (4, [5.0, 6.03, 5.0]),
(5, [5.0, 5.0, 3.96]), (6, [5.0, 5.0, 6.05])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords.extend([oc[1] for oc in order_and_coords])
fake_structure = Structure(cubic_lattice,
species,
coords,
coords_are_cartesian=True)
# First fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(
structure=fake_structure,
valences=valences,
normalized_distance_tolerance=0.0100001,
isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]),
6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(
0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(
0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
# First fake structure with a given normalized_distance_tolerance of 0.001
detailed_voronoi_container = DetailedVoronoiContainer(
structure=fake_structure,
valences=valences,
normalized_distance_tolerance=0.001,
isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]),
6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 1)
self.assertEqual(neighbors[0]['site'], fake_structure[sorted[0]])
neighbors = detailed_voronoi_container.neighbors(
0, 1.02, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in nbs)
self.assertTrue(fake_structure[sorted[1]] in nbs)
self.assertTrue(fake_structure[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(
0, 1.026, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in nbs)
self.assertTrue(fake_structure[sorted[1]] in nbs)
self.assertTrue(fake_structure[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
# Second fake structure
coords2 = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]), (2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]), (4, [5.0, 6.07, 5.0]),
(5, [5.0, 5.0, 3.92]), (6, [5.0, 5.0, 6.09])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords2.extend([oc[1] for oc in order_and_coords])
fake_structure2 = Structure(cubic_lattice,
species,
coords2,
coords_are_cartesian=True)
# Second fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(
structure=fake_structure2,
valences=valences,
normalized_distance_tolerance=0.0100001,
isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]),
6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(
0, 1.02, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(
0, 1.026, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
species = ['Cu', 'Cu', 'O', 'O', 'O', 'Cu', 'O']
valences = [2, 2, -2, -2, -2, 2, -2]
# Third fake structure (test of the only_anion_cation_bonds)
coords = [[5.0, 5.0, 5.0], [6.01, 5.0, 5.0], [5.0, 5.0, 3.96],
[4.0, 5.0, 5.0], [5.0, 6.03, 5.0], [5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure3 = Structure(cubic_lattice,
species,
coords,
coords_are_cartesian=True)
detailed_voronoi_container = DetailedVoronoiContainer(
structure=fake_structure3,
valences=valences,
normalized_distance_tolerance=0.0100001,
isites=[0],
additional_conditions=[DetailedVoronoiContainer.AC.ONLY_ACB])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]),
6)
neighbors = detailed_voronoi_container.neighbors(
0, 1.01, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 6)
self.assertTrue(fake_structure3[1] in nbs)
self.assertTrue(fake_structure3[2] in nbs)
self.assertTrue(fake_structure3[3] in nbs)
self.assertTrue(fake_structure3[4] in nbs)
self.assertTrue(fake_structure3[5] in nbs)
self.assertTrue(fake_structure3[6] in nbs)
# Test of the as_dict() and from_dict() methods as well as __eq__ method
other_detailed_voronoi_container = DetailedVoronoiContainer.from_dict(
detailed_voronoi_container.as_dict())
self.assertTrue(detailed_voronoi_container,
other_detailed_voronoi_container)
def test_voronoi(self):
#Define a cubic lattice and a list of species (to be used for the fake structures)
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
#First fake structure
coords = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.03, 5.0]),
(5, [5.0, 5.0, 3.96]),
(6, [5.0, 5.0, 6.05])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords.extend([oc[1] for oc in order_and_coords])
fake_structure = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
#First fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
normalized_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#First fake structure with a given normalized_distance_tolerance of 0.001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
normalized_distance_tolerance=0.001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 1)
self.assertEqual(neighbors[0]['site'], fake_structure[sorted[0]])
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in nbs)
self.assertTrue(fake_structure[sorted[1]] in nbs)
self.assertTrue(fake_structure[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in nbs)
self.assertTrue(fake_structure[sorted[1]] in nbs)
self.assertTrue(fake_structure[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#Second fake structure
coords2 = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.07, 5.0]),
(5, [5.0, 5.0, 3.92]),
(6, [5.0, 5.0, 6.09])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords2.extend([oc[1] for oc in order_and_coords])
fake_structure2 = Structure(cubic_lattice, species, coords2, coords_are_cartesian=True)
#Second fake structure with a given normalized_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure2, valences=valences,
normalized_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in nbs)
self.assertTrue(fake_structure2[sorted[1]] in nbs)
self.assertTrue(fake_structure2[sorted[2]] in nbs)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
species = ['Cu', 'Cu', 'O', 'O', 'O', 'Cu', 'O']
valences = [2, 2, -2, -2, -2, 2, -2]
#Third fake structure (test of the only_anion_cation_bonds)
coords = [[5.0, 5.0, 5.0],
[6.01, 5.0, 5.0],
[5.0, 5.0, 3.96],
[4.0, 5.0, 5.0],
[5.0, 6.03, 5.0],
[5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure3 = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure3, valences=valences,
normalized_distance_tolerance=0.0100001, isites=[0],
additional_conditions=
[DetailedVoronoiContainer.AC.ONLY_ACB])
self.assertEqual(len(detailed_voronoi_container.voronoi_list2[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.01, 0.5, True)
nbs = [nb['site'] for nb in neighbors]
self.assertEqual(len(neighbors), 6)
self.assertTrue(fake_structure3[1] in nbs)
self.assertTrue(fake_structure3[2] in nbs)
self.assertTrue(fake_structure3[3] in nbs)
self.assertTrue(fake_structure3[4] in nbs)
self.assertTrue(fake_structure3[5] in nbs)
self.assertTrue(fake_structure3[6] in nbs)
#Test of the as_dict() and from_dict() methods as well as __eq__ method
other_detailed_voronoi_container = DetailedVoronoiContainer.from_dict(detailed_voronoi_container.as_dict())
self.assertTrue(detailed_voronoi_container, other_detailed_voronoi_container)
def test_voronoi(self):
#Define a cubic lattice and a list of species (to be used for the fake structures)
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
#First fake structure
coords = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.03, 5.0]),
(5, [5.0, 5.0, 3.96]),
(6, [5.0, 5.0, 6.05])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords.extend([oc[1] for oc in order_and_coords])
fake_structure = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
#First fake structure with a given weighted_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#First fake structure with a given weighted_distance_tolerance of 0.001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
weighted_distance_tolerance=0.001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 1)
self.assertEqual(neighbors[0], fake_structure[sorted[0]])
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in neighbors)
self.assertTrue(fake_structure[sorted[1]] in neighbors)
self.assertTrue(fake_structure[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in neighbors)
self.assertTrue(fake_structure[sorted[1]] in neighbors)
self.assertTrue(fake_structure[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#Second fake structure
coords2 = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.07, 5.0]),
(5, [5.0, 5.0, 3.92]),
(6, [5.0, 5.0, 6.09])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords2.extend([oc[1] for oc in order_and_coords])
fake_structure2 = Structure(cubic_lattice, species, coords2, coords_are_cartesian=True)
#Second fake structure with a given weighted_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure2, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
species = ['Cu', 'Cu', 'O', 'O', 'O', 'Cu', 'O']
valences = [2, 2, -2, -2, -2, 2, -2]
#Third fake structure (test of the only_anion_cation_bonds)
coords = [[5.0, 5.0, 5.0],
[6.01, 5.0, 5.0],
[5.0, 5.0, 3.96],
[4.0, 5.0, 5.0],
[5.0, 6.03, 5.0],
[5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure3 = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure3, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0],
additional_conditions=
[DetailedVoronoiContainer.AC.ONLY_ACB])
#Plotting test
plot_type = {'distance_parameter': ('initial_inverse3_opposite', None),
'angle_parameter': ('initial_opposite', None)}
detailed_voronoi_container.save_coordination_numbers_figure(0, imagename='tmp_dir/tmpimage.png',
plot_type=plot_type,
title='Coordination numbers', max_dist=2.0,
figsize=(8, 6))
ref_image = mpimg.imread('{}/detailed_voronoi_container_coordination_numbers_1.png'.format(img_files_dir))
test_image = mpimg.imread('tmp_dir/tmpimage.png')
self.assertTrue(np.allclose(ref_image, test_image), msg='Image of the Detailed Voronoi Container is wrong')
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.01, 0.5, True)
self.assertEqual(len(neighbors), 4)
self.assertTrue(fake_structure3[2] in neighbors)
self.assertTrue(fake_structure3[3] in neighbors)
self.assertTrue(fake_structure3[4] in neighbors)
self.assertTrue(fake_structure3[6] in neighbors)
#Test of the as_dict() and from_dict() methods as well as __eq__ method
other_detailed_voronoi_container = DetailedVoronoiContainer.from_dict(detailed_voronoi_container.as_dict())
self.assertTrue(detailed_voronoi_container, other_detailed_voronoi_container)
def test_voronoi(self):
#Define a cubic lattice and a list of species (to be used for the fake structures)
cubic_lattice = Lattice.cubic(10.0)
species = ['Cu', 'O', 'O', 'O', 'O', 'O', 'O']
valences = 'undefined'
#First fake structure
coords = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.03, 5.0]),
(5, [5.0, 5.0, 3.96]),
(6, [5.0, 5.0, 6.05])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords.extend([oc[1] for oc in order_and_coords])
fake_structure = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
#First fake structure with a given weighted_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#First fake structure with a given weighted_distance_tolerance of 0.001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure, valences=valences,
weighted_distance_tolerance=0.001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 1)
self.assertEqual(neighbors[0], fake_structure[sorted[0]])
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in neighbors)
self.assertTrue(fake_structure[sorted[1]] in neighbors)
self.assertTrue(fake_structure[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure[sorted[0]] in neighbors)
self.assertTrue(fake_structure[sorted[1]] in neighbors)
self.assertTrue(fake_structure[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
#Second fake structure
coords2 = [[5.0, 5.0, 5.0]]
order_and_coords = [(1, [4.0, 5.0, 5.0]),
(2, [6.01, 5.0, 5.0]),
(3, [5.0, 3.98, 5.0]),
(4, [5.0, 6.07, 5.0]),
(5, [5.0, 5.0, 3.92]),
(6, [5.0, 5.0, 6.09])]
random.shuffle(order_and_coords)
sorted = np.argsort([oc[0] for oc in order_and_coords]) + 1
coords2.extend([oc[1] for oc in order_and_coords])
fake_structure2 = Structure(cubic_lattice, species, coords2, coords_are_cartesian=True)
#Second fake structure with a given weighted_distance_tolerance of 0.0100001
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure2, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0])
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.0, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.02, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.026, 0.5, True)
self.assertEqual(len(neighbors), 3)
self.assertTrue(fake_structure2[sorted[0]] in neighbors)
self.assertTrue(fake_structure2[sorted[1]] in neighbors)
self.assertTrue(fake_structure2[sorted[2]] in neighbors)
neighbors = detailed_voronoi_container.neighbors(0, 1.5, 0.5, True)
self.assertEqual(len(neighbors), 6)
species = ['Cu', 'Cu', 'O', 'O', 'O', 'Cu', 'O']
valences = [2, 2, -2, -2, -2, 2, -2]
#Third fake structure (test of the only_anion_cation_bonds)
coords = [[5.0, 5.0, 5.0],
[6.01, 5.0, 5.0],
[5.0, 5.0, 3.96],
[4.0, 5.0, 5.0],
[5.0, 6.03, 5.0],
[5.0, 3.98, 5.0],
[5.0, 5.0, 6.05]]
fake_structure3 = Structure(cubic_lattice, species, coords, coords_are_cartesian=True)
detailed_voronoi_container = DetailedVoronoiContainer(structure=fake_structure3, valences=valences,
weighted_distance_tolerance=0.0100001, isites=[0],
additional_conditions=
[DetailedVoronoiContainer.AC.ONLY_ACB])
#Plotting test
plot_type = {'distance_parameter': ('initial_inverse3_opposite', None),
'angle_parameter': ('initial_opposite', None)}
detailed_voronoi_container.save_coordination_numbers_figure(0, imagename='tmp_dir/tmpimage.png',
plot_type=plot_type,
title='Coordination numbers', max_dist=2.0,
figsize=(8, 6))
# TODO: This test needs to be fixed.
# ref_image = mpimg.imread('{}/detailed_voronoi_container_coordination_numbers_1.png'.format(img_files_dir))
# test_image = mpimg.imread('tmp_dir/tmpimage.png')
# self.assertTrue(np.allclose(ref_image, test_image), msg='Image of the Detailed Voronoi Container is wrong')
self.assertEqual(len(detailed_voronoi_container.voronoi_list[0]), 6)
neighbors = detailed_voronoi_container.neighbors(0, 1.01, 0.5, True)
self.assertEqual(len(neighbors), 4)
self.assertTrue(fake_structure3[2] in neighbors)
self.assertTrue(fake_structure3[3] in neighbors)
self.assertTrue(fake_structure3[4] in neighbors)
self.assertTrue(fake_structure3[6] in neighbors)
#Test of the as_dict() and from_dict() methods as well as __eq__ method
other_detailed_voronoi_container = DetailedVoronoiContainer.from_dict(detailed_voronoi_container.as_dict())
self.assertTrue(detailed_voronoi_container, other_detailed_voronoi_container)
