def test_disordered_primitive_to_ordered_supercell(self):
sm_atoms = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=True,
attempt_supercell=True,
allow_subset=True,
supercell_size='num_atoms',
comparator=OrderDisorderElementComparator())
sm_sites = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=True,
attempt_supercell=True,
allow_subset=True,
supercell_size='num_sites',
comparator=OrderDisorderElementComparator())
lp = Lattice.orthorhombic(10, 20, 30)
pcoords = [[0, 0, 0],
[0.5, 0.5, 0.5]]
ls = Lattice.orthorhombic(20, 20, 30)
scoords = [[0, 0, 0],
[0.75, 0.5, 0.5]]
prim = Structure(lp, [{'Na': 0.5}, {'Cl': 0.5}], pcoords)
supercell = Structure(ls, ['Na', 'Cl'], scoords)
supercell.make_supercell([[-1, 1, 0], [0, 1, 1], [1, 0, 0]])
self.assertFalse(sm_sites.fit(prim, supercell))
self.assertTrue(sm_atoms.fit(prim, supercell))
self.assertRaises(ValueError, sm_atoms.get_s2_like_s1, prim, supercell)
self.assertEqual(len(sm_atoms.get_s2_like_s1(supercell, prim)), 4)
def test_get_supercell_matrix(self):
sm = StructureMatcher(ltol=0.1, stol=0.3, angle_tol=2,
primitive_cell=False, scale=True,
attempt_supercell=True)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s1.make_supercell([2, 1, 1])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, 0], [0, 0.1, -0.95], [-.7, .5, .375]])
result = sm.get_supercell_matrix(s1, s2)
self.assertTrue((result == [[-2, 0, 0], [0, 1, 0], [0, 0, 1]]).all())
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s1.make_supercell([[1, -1, 0], [0, 0, -1], [0, 1, 0]])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, 0], [0, 0.1, -0.95], [-.7, .5, .375]])
result = sm.get_supercell_matrix(s1, s2)
self.assertTrue((result == [[-1, -1, 0], [0, 0, -1], [0, 1, 0]]).all())
# test when the supercell is a subset
sm = StructureMatcher(ltol=0.1, stol=0.3, angle_tol=2,
primitive_cell=False, scale=True,
attempt_supercell=True, allow_subset=True)
del s1[0]
result = sm.get_supercell_matrix(s1, s2)
self.assertTrue((result == [[-1, -1, 0], [0, 0, -1], [0, 1, 0]]).all())
def get_min_distance(self, connected_nodes, loc):
str_formula = str(self.structure.species_and_occu[loc].formula)
nodes = np.array([node for node in connected_nodes \
if self.structure.species_and_occu[node] == self.structure.species_and_occu[loc]])
#get nearest magnetic_metal angle neighbors with a tolerance of 0.1 A.
lattice_species = [
self.structure.species_and_occu[node] for node in nodes
]
s = Structure(self.structure.lattice, lattice_species,
self.frac_coords[nodes])
s.make_supercell([3, 3, 3])
new_frac_coords = np.round(s.frac_coords, decimals=3)
new_frac_coords[new_frac_coords == 1.] = 0.
distances = []
for i in range(len(new_frac_coords)):
distances.append(
np.linalg.norm(
s.lattice.get_cartesian_coords(new_frac_coords[i]) -
s.lattice.get_cartesian_coords([0.5, 0.5, 0.5])))
new_loc = np.argmin(distances)
loc_cart_coords = s.lattice.get_cartesian_coords(
new_frac_coords[new_loc])
#identify the two closest same species to the specie under consideration (new_loc)
nodes = np.arange(len(s))
distances = [s.distance_matrix[node, new_loc] for node in nodes]
nodes = nodes[np.argsort(distances)]
distances = np.sort(distances)
return distances[1]
def test_find_match2(self):
sm = StructureMatcher(ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=True,
scale=True,
attempt_supercell=False)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Si', 'Si'], [[0, 0, 0.1], [0, 0, 0.2]])
s2 = Structure(l, ['Si', 'Si'], [[0, 0.1, 0], [0, 0.1, -0.95]])
s1, s2, fu, s1_supercell = sm._preprocess(s1, s2, False)
match = sm._strict_match(s1,
s2,
fu,
s1_supercell=False,
use_rms=True,
break_on_match=False)
scale_matrix = match[2]
s2.make_supercell(scale_matrix)
s2.translate_sites(range(len(s2)), match[3])
self.assertAlmostEqual(np.sum(s2.frac_coords), 0.3)
self.assertAlmostEqual(np.sum(s2.frac_coords[:, :2]), 0)
def to_xyz(self):
u = Universe('reduced.xyz')
name = []
for a in u.atoms:
name.append(a.name)
a = [
float(r) for r in
'8.0136733451350004 2.7785351250530002 0.0000007466930000'.
split()
]
b = [
float(r) for r in
'-1.6027324335730000 8.3356053751600001 0.0000022400790000'.
split()
]
c = [
float(r) for r in
'0.0000000000000000 0.0000000000000000 25.3395087497430005'.
split()
]
lat = Lattice([a, b, c])
s = Structure(lat, name, u.trajectory[0], coords_are_cartesian=True)
s.make_supercell([2, 2, 1])
print(s)
def test_find_match1(self):
sm = StructureMatcher(ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=True,
scale=True,
attempt_supercell=False)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, 0], [0, 0.1, -0.95], [.7, .5, .375]])
s1, s2, fu, s1_supercell = sm._preprocess(s1, s2, False)
match = sm._strict_match(s1,
s2,
fu,
s1_supercell=True,
use_rms=True,
break_on_match=False)
scale_matrix = match[2]
s2.make_supercell(scale_matrix)
fc = s2.frac_coords + match[3]
fc -= np.round(fc)
self.assertAlmostEqual(np.sum(fc), 0.9)
self.assertAlmostEqual(np.sum(fc[:, :2]), 0.1)
cart_dist = np.sum(match[1] * (l.volume / 3)**(1 / 3))
self.assertAlmostEqual(cart_dist, 0.15)
def test_get_mapping(self):
sm = StructureMatcher(ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=False,
scale=True,
attempt_supercell=False,
allow_subset=True)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Ag', 'Si', 'Si'],
[[.7, .4, .5], [0, 0, 0.1], [0, 0, 0.2]])
s1.make_supercell([2, 1, 1])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, -0.95], [0, 0.1, 0], [-.7, .5, .375]])
shuffle = [2, 0, 1, 3, 5, 4]
s1 = Structure.from_sites([s1[i] for i in shuffle])
#test the mapping
s2.make_supercell([2, 1, 1])
#equal sizes
for i, x in enumerate(sm.get_mapping(s1, s2)):
self.assertEqual(s1[x].species_and_occu, s2[i].species_and_occu)
del s1[0]
#s1 is subset of s2
for i, x in enumerate(sm.get_mapping(s2, s1)):
self.assertEqual(s1[i].species_and_occu, s2[x].species_and_occu)
#s2 is smaller than s1
del s2[0]
del s2[1]
self.assertRaises(ValueError, sm.get_mapping, s2, s1)
def test_disordered_primitive_to_ordered_supercell(self):
sm_atoms = StructureMatcher(
ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=False,
scale=True,
attempt_supercell=True,
allow_subset=True,
supercell_size='num_atoms',
comparator=OrderDisorderElementComparator())
sm_sites = StructureMatcher(
ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=False,
scale=True,
attempt_supercell=True,
allow_subset=True,
supercell_size='num_sites',
comparator=OrderDisorderElementComparator())
lp = Lattice.orthorhombic(10, 20, 30)
pcoords = [[0, 0, 0], [0.5, 0.5, 0.5]]
ls = Lattice.orthorhombic(20, 20, 30)
scoords = [[0, 0, 0], [0.75, 0.5, 0.5]]
prim = Structure(lp, [{'Na': 0.5}, {'Cl': 0.5}], pcoords)
supercell = Structure(ls, ['Na', 'Cl'], scoords)
supercell.make_supercell([[-1, 1, 0], [0, 1, 1], [1, 0, 0]])
self.assertFalse(sm_sites.fit(prim, supercell))
self.assertTrue(sm_atoms.fit(prim, supercell))
self.assertRaises(ValueError, sm_atoms.get_s2_like_s1, prim, supercell)
self.assertEqual(len(sm_atoms.get_s2_like_s1(supercell, prim)), 4)
def create_TiAlN_structure(shuffle=True):
''' Attributes:
number_of_lattice > maximum Total number of atoms in structure
a > lattice parameter
Returns:
Pymatgen structure TiAlN. Creates possible largest square supercell '''
lattice = Lattice.cubic(a=4.16)
coords = [
[0, 0, 0],
[0.5, 0.5, 0],
[0.5, 0, 0.5],
[0, 0.5, 0.5],
[0, 0, 0.5],
[0.5, 0, 0],
[0, 0.5, 0],
[0.5, 0.5, 0.5],
]
matrix = [[1, 0, 0], [0, 5, 0], [0, 0, 5]]
struct = Structure(lattice, ["Ti", "Ti", "Al", "Al", "N", "N", "N", "N"],
coords)
struct.make_supercell(matrix)
site_size = len(struct)
element_number = int(site_size / 4)
Al_Ti_array = ['Al'] * element_number + ['Ti'] * element_number
if shuffle == True:
random.shuffle(Al_Ti_array)
for e, i in enumerate(Al_Ti_array):
struct.replace(e, i)
return struct
def test_get_mapping(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=True,
attempt_supercell=False,
allow_subset=True)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Ag', 'Si', 'Si'],
[[.7, .4, .5], [0, 0, 0.1], [0, 0, 0.2]])
s1.make_supercell([2, 1, 1])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, -0.95], [0, 0.1, 0], [-.7, .5, .375]])
shuffle = [2, 0, 1, 3, 5, 4]
s1 = Structure.from_sites([s1[i] for i in shuffle])
# test the mapping
s2.make_supercell([2, 1, 1])
# equal sizes
for i, x in enumerate(sm.get_mapping(s1, s2)):
self.assertEqual(s1[x].species,
s2[i].species)
del s1[0]
# s1 is subset of s2
for i, x in enumerate(sm.get_mapping(s2, s1)):
self.assertEqual(s1[i].species,
s2[x].species)
# s2 is smaller than s1
del s2[0]
del s2[1]
self.assertRaises(ValueError, sm.get_mapping, s2, s1)
def test_apply_transformation_mult(self):
# Test returning multiple structures from each transformation.
disord = Structure(np.eye(3) * 4.209, [{"Cs+": 0.5, "K+": 0.5}, "Cl-"], [[0, 0, 0], [0.5, 0.5, 0.5]])
disord.make_supercell([2, 2, 1])
tl = [EnumerateStructureTransformation(), OrderDisorderedStructureTransformation()]
t = SuperTransformation(tl, nstructures_per_trans=10)
self.assertEqual(len(t.apply_transformation(disord, return_ranked_list=20)), 8)
t = SuperTransformation(tl)
self.assertEqual(len(t.apply_transformation(disord, return_ranked_list=20)), 2)
def test_apply_transformation_mult(self):
# Test returning multiple structures from each transformation.
disord = Structure(np.eye(3) * 4.209, [{"Cs+": 0.5, "K+": 0.5}, "Cl-"],
[[0, 0, 0], [0.5, 0.5, 0.5]])
disord.make_supercell([2, 2, 1])
tl = [EnumerateStructureTransformation(),
OrderDisorderedStructureTransformation()]
t = SuperTransformation(tl, nstructures_per_trans=10)
self.assertEqual(len(t.apply_transformation(disord,
return_ranked_list=20)), 8)
t = SuperTransformation(tl)
self.assertEqual(len(t.apply_transformation(disord,
return_ranked_list=20)), 2)
def test_find_match2(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=True, scale=True,
attempt_supercell=False)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Si', 'Si'], [[0, 0, 0.1], [0, 0, 0.2]])
s2 = Structure(l, ['Si', 'Si'], [[0, 0.1, 0], [0, 0.1, -0.95]])
s1, s2, fu, s1_supercell = sm._preprocess(s1, s2, False)
match = sm._strict_match(s1, s2, fu, s1_supercell=False,
use_rms=True, break_on_match=False)
scale_matrix = match[2]
s2.make_supercell(scale_matrix)
s2.translate_sites(range(len(s2)), match[3])
self.assertAlmostEqual(np.sum(s2.frac_coords) % 1, 0.3)
self.assertAlmostEqual(np.sum(s2.frac_coords[:, :2]) % 1, 0)
def test_get_s2_large_s2(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=False,
attempt_supercell=True, allow_subset=False,
supercell_size='volume')
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Ag', 'Si', 'Si'],
[[.7, .4, .5], [0, 0, 0.1], [0, 0, 0.2]])
l2 = Lattice.orthorhombic(1.01, 2.01, 3.01)
s2 = Structure(l2, ['Si', 'Si', 'Ag'],
[[0, 0.1, -0.95], [0, 0.1, 0], [-.7, .5, .375]])
s2.make_supercell([[0, -1, 0], [1, 0, 0], [0, 0, 1]])
result = sm.get_s2_like_s1(s1, s2)
for x, y in zip(s1, result):
self.assertLess(x.distance(y), 0.08)
def test_find_match1(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=True, scale=True,
attempt_supercell=False)
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0,0,0.1],[0,0,0.2],[.7,.4,.5]])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0,0.1,0],[0,0.1,-0.95],[.7,.5,.375]])
s1, s2, fu, s1_supercell = sm._preprocess(s1, s2, False)
match = sm._strict_match(s1, s2, fu, s1_supercell = True, use_rms = True, break_on_match = False)
scale_matrix = match[2]
s2.make_supercell(scale_matrix)
fc = s2.frac_coords + match[3]
fc -= np.round(fc)
self.assertAlmostEqual(np.sum(fc), 0.9)
self.assertAlmostEqual(np.sum(fc[:,:2]), 0.1)
cart_dist = np.sum(match[1] * (l.volume/3) ** (1/3))
self.assertAlmostEqual(cart_dist, 0.15)
def getFccEquilibrium():
# alat = 1.0
alat = math.sqrt(2.0)
fcc = Structure(
Lattice.cubic(alat), ["Co", "Co", "Co", "Co"],
[[0.0, 0.0, 0.0], [0.0, 0.5, 0.5], [0.5, 0.0, 0.5], [0.5, 0.5, 0.0]])
# fcc = Structure( Lattice.cubic(alat), ["Co"],
# [[0.0, 0.0, 0.0]]
# )
# Find the primitive unit cell:
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
sym_finder = SpacegroupAnalyzer(fcc)
fcc = sym_finder.get_primitive_standard_structure()
# new_structure.to(fmt='poscar', filename='POSCAR_test_2')
# Make a supercell
n = 3 #3
fcc.make_supercell([n, n, n])
return fcc
def run_displacement(file_primitive, prefix, scaling_matrix,
disp_magnitude_angstrom):
qeobj = QEParser()
qeobj.load_initial_structure(file_primitive)
structure = Structure(qeobj.lattice_vector.transpose(), qeobj.kd_in_str,
qeobj.x_fractional)
Structure.make_supercell(structure, scaling_matrix)
print("Supercell generated. # Atoms: %i" % structure.num_sites)
print("")
prefix0 = 'supercell'
disp = np.zeros((structure.num_sites, 3))
# update structural information of qeobj
qeobj_mod = update_qeobj(qeobj, structure)
# create the supercell structure
qeobj_mod.generate_structures(prefix0, ['original'], [disp])
# rename the file
command = ("mv %s1.pw.in %s0.scf.in" % (prefix0, prefix0))
os.system(command)
# Generate displacement files
gen_alm_input('ALM0.in', prefix0, 'suggest', structure, 1, "*-* None")
command = ("%s/alm/alm ALM0.in > ALM0.log" % ALAMODE_root)
os.system(command)
dispobj = AlamodeDisplace("fd", qeobj_mod, verbosity=0)
header_list, disp_list \
= dispobj.generate(file_pattern=["%s.pattern_HARMONIC" % prefix0],
magnitude=disp_magnitude_angstrom)
qeobj_mod.generate_structures(prefix, header_list, disp_list)
def run_optimize(file_primitive, file_dfset, scaling_matrix):
qeobj = QEParser()
qeobj.load_initial_structure(file_primitive)
structure = Structure(qeobj.lattice_vector.transpose(), qeobj.kd_in_str,
qeobj.x_fractional)
Structure.make_supercell(structure, scaling_matrix)
print("Supercell generated. # Atoms: %i" % structure.num_sites)
print("")
prefix0 = 'supercell'
# Generate displacement files
gen_alm_input('ALM1.in',
prefix0,
'optimize',
structure,
1,
"*-* None",
dfset=file_dfset)
command = ("%s/alm/alm ALM1.in > ALM1.log" % ALAMODE_root)
os.system(command)
def get_elem_info(
structure: mg.Structure,
makesupercell: bool = True) -> Tuple[Dict, Dict, mg.Structure]:
"""
Helper function for calc_mx/mm/xx_distances()
Get information on the element composition and the site indices for all element of a structure
:param structure: Pymatgen Structure, the structure of a compound
:param makesupercell: Boolean, whether or not to make a supercell
:return: Tuple, (a dictionary with key-value pair - element: [list of indices],
a dictionary with key-value pair - element_type: [list of elements],
Pymatgen Structure)
"""
# create a copy of the original structure
structure = structure.copy()
# create a list with all the elements
elem_lst = structure.composition.element_composition.elements
# initialize a dictionary with each element as the key and an empty list as the value
elem_indices = {element: [] for element in elem_lst}
# classify all elements into a metal group and a non-metal group
elem_group = parse_element(structure)
# iterate over all sites
for i, site in enumerate(structure.sites):
# record the site index for the all the element(s) on this site
for element in site.species.element_composition.elements:
elem_indices[element].append(i)
# in the case that an element only appears in one site, make a supercell (inplace)
if makesupercell and (np.sum(
[len(lst) == 1 for lst in elem_indices.values()]) > 0):
# make a supercell of a'=2a, b'=b, c'=c
structure.make_supercell(scaling_matrix=[2, 1, 1])
elem_indices, elem_group, structure = get_elem_info(structure)
return elem_indices, elem_group, structure
class Test2D(unittest.TestCase):
def setUp(self):
## simple toy structure for preliminary testing
self.a0 = 3.0
self.c = 20.0
self.structure = Structure(
Lattice.from_parameters(a=self.a0,
b=self.a0,
c=self.c,
alpha=90,
beta=90,
gamma=90), ["O", "O"],
[[0.0, 0.0, 0.1], [0.5, 0.5, 0.3]])
self.nvecs = [3, 3, 1]
self.vacuum = 20
self.q = 0
self.structure.make_supercell(self.nvecs)
self.structure_bulk = self.structure.copy()
self.initdef_list = []
self.initdef_list.append(
{"def1": {
"type": "vac",
"species": "O",
"index": 0
}})
self.initdef_list.append({
"def1": {
"type": "sub",
"index": -1,
"species": "O",
"species_new": "N"
}
})
self.initdef_list.append({
"def1": {
"type": "sub",
"index": -1,
"species": "O",
"species_new": "N"
},
"def2": {
"type": "vac",
"index": -1,
"species": "O",
"index_offset_n1n2": -1
}
})
self.initdef_list.append({
"def1": {
"type": "ad",
"index": [-1],
"species": ["O"],
"species_new": "N",
"shift_z": "3.0"
}
})
self.initdef_list.append({
"def1": {
"type": "int",
"index": [0, 0, 0, 0],
"index_offset_n1": [0, 1, 0, 0],
"index_offset_n2": [0, 0, 0, 2],
"index_offset_n1n2": [0, 0, 1, 1],
"species": 4 * ["O"],
"species_new": "N"
}
})
self.create_defects()
self.siteinds_list = [[0], [17], [17, 8], [[17]], [[0, 3, 9, 11]]]
self.defcoords_list = [[[0.0, 0.0, 0.1]], [[0.833333, 0.833333, 0.3]],
[[0.833333, 0.833333, 0.3],
[0.666667, 0.666667, 0.1]],
[[0.833333, 0.833333, 0.45]],
[[0.166667, 0.0, 0.2]]]
self.natoms_list = [17, 18, 17, 19, 19]
def create_defects(self):
## create defects
self.defects_list = []
for initdef in self.initdef_list:
## initialize defect object
defect = gen_defect_supercells.Defect(self.structure_bulk,
self.structure.copy(),
self.nvecs, self.vacuum,
self.q)
## set the defect info (type, site, species) for each defect
for d in initdef:
initdef[d]["index_offset_n1"] = initdef[d].get(
"index_offset_n1", 0)
initdef[d]["index_offset_n2"] = initdef[d].get(
"index_offset_n2", 0)
initdef[d]["index_offset_n1n2"] = initdef[d].get(
"index_offset_n1n2", 0)
defect_site, siteinds = defect.get_defect_site(initdef[d])
defect.add_defect_info(initdef[d], defect_site)
## create defect(s)
defect.remove_atom()
defect.replace_atom()
defect.add_atom()
self.defects_list.append(defect)
def test_get_site_index(self):
## test get_site_index returns the correct absolute site indices
## initialize dummy "defect" object
defect = gen_defect_supercells.Defect(self.structure_bulk,
self.structure.copy(),
self.nvecs, self.vacuum, self.q)
for initdef, siteinds in zip(self.initdef_list, self.siteinds_list):
for d, siteind_ref in zip(initdef, siteinds):
if initdef[d]["type"][0] == "v" or initdef[d]["type"][0] == "s":
siteind = defect.get_site_ind(
initdef[d]["index"], initdef[d]["species"],
initdef[d]["index_offset_n1"],
initdef[d]["index_offset_n2"],
initdef[d]["index_offset_n1n2"])
self.assertEqual(siteind, siteind_ref)
if initdef[d]["type"][0] == "a" or initdef[d]["type"][0] == "i":
for siteindi_ref,ind,sp,offset_n1,offset_n2,offset_n1n2 \
in zip(siteind_ref,
initdef[d]["index"],
initdef[d]["species"],
initdef[d]["index_offset_n1"],
initdef[d]["index_offset_n2"],
initdef[d]["index_offset_n1n2"]):
siteind = defect.get_site_ind(ind, sp, offset_n1,
offset_n2, offset_n1n2)
self.assertEqual(siteind, siteindi_ref)
def test_defcoords(self):
## test that the defect(s) are created at the correct position
## essentially tests the get_defect_site function
for defects, defcoords_ref in zip(self.defects_list,
self.defcoords_list):
for defect_site, defcoord_ref in zip(defects.defect_site,
defcoords_ref):
defcoord = defect_site.lattice.get_fractional_coords(
defect_site.coords)
# defcoord = defect_site.frac_coords
for j in range(3):
self.assertAlmostEqual(defcoord[j] % 1 % 1,
defcoord_ref[j] % 1 % 1,
places=6)
def test_natoms(self):
## test that the defect creation results in the correct number of atoms
for defect, natoms in zip(self.defects_list, self.natoms_list):
self.assertEqual(defect.structure.num_sites, natoms)
def test_supercell_subsets(self):
sm = StructureMatcher(ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=False,
scale=True,
attempt_supercell=True,
allow_subset=True,
supercell_size='volume')
sm_no_s = StructureMatcher(ltol=0.2,
stol=0.3,
angle_tol=5,
primitive_cell=False,
scale=True,
attempt_supercell=True,
allow_subset=False,
supercell_size='volume')
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Ag', 'Si', 'Si'],
[[.7, .4, .5], [0, 0, 0.1], [0, 0, 0.2]])
s1.make_supercell([2, 1, 1])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, -0.95], [0, 0.1, 0], [-.7, .5, .375]])
shuffle = [0, 2, 1, 3, 4, 5]
s1 = Structure.from_sites([s1[i] for i in shuffle])
#test when s1 is exact supercell of s2
result = sm.get_s2_like_s1(s1, s2)
for a, b in zip(s1, result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species_and_occu, b.species_and_occu)
self.assertTrue(sm.fit(s1, s2))
self.assertTrue(sm.fit(s2, s1))
self.assertTrue(sm_no_s.fit(s1, s2))
self.assertTrue(sm_no_s.fit(s2, s1))
rms = (0.048604032430991401, 0.059527539448807391)
self.assertTrue(np.allclose(sm.get_rms_dist(s1, s2), rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2, s1), rms))
#test when the supercell is a subset of s2
subset_supercell = s1.copy()
del subset_supercell[0]
result = sm.get_s2_like_s1(subset_supercell, s2)
self.assertEqual(len(result), 6)
for a, b in zip(subset_supercell, result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species_and_occu, b.species_and_occu)
self.assertTrue(sm.fit(subset_supercell, s2))
self.assertTrue(sm.fit(s2, subset_supercell))
self.assertFalse(sm_no_s.fit(subset_supercell, s2))
self.assertFalse(sm_no_s.fit(s2, subset_supercell))
rms = (0.053243049896333279, 0.059527539448807336)
self.assertTrue(np.allclose(sm.get_rms_dist(subset_supercell, s2),
rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2, subset_supercell),
rms))
#test when s2 (once made a supercell) is a subset of s1
s2_missing_site = s2.copy()
del s2_missing_site[1]
result = sm.get_s2_like_s1(s1, s2_missing_site)
for a, b in zip((s1[i] for i in (0, 2, 4, 5)), result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species_and_occu, b.species_and_occu)
self.assertTrue(sm.fit(s1, s2_missing_site))
self.assertTrue(sm.fit(s2_missing_site, s1))
self.assertFalse(sm_no_s.fit(s1, s2_missing_site))
self.assertFalse(sm_no_s.fit(s2_missing_site, s1))
rms = (0.029763769724403633, 0.029763769724403987)
self.assertTrue(np.allclose(sm.get_rms_dist(s1, s2_missing_site), rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2_missing_site, s1), rms))
#%%
import math
from pymatgen import Structure, Molecule, Lattice
import os
os.chdir(
'/home/jinho93/oxides/perobskite/lanthanum-aluminate/slab/gulp/nonstochio/La-vac/two'
)
m = Molecule.from_file('tail.xyz')
l = Lattice.from_lengths_and_angles([11.46615, 15.2882, 50], [90, 90, 90])
s = Structure(l, m.species, m.cart_coords, coords_are_cartesian=True)
s.make_supercell([[4, 0, 0], [0, 3, 0], [0, 0, 1]])
s.make_supercell([[1, 1, 0], [1, -1, 0], [0, 0, 1]])
s.sort()
# ll = Lattice.from_lengths_and_angles([s.lattice.a / 2, s.lattice.b / 2, s.lattice.c], s.lattice.angles)
ll = Lattice.from_lengths_and_angles(s.lattice.abc, s.lattice.angles)
s = Structure(ll, s.species, s.cart_coords, coords_are_cartesian=True)
indi = []
for i, site in enumerate(s.sites):
if site.x + site.y < ll.b / math.sqrt(2):
indi.append(i)
# s.remove_sites(indi)
# s = Structure(ll, s.species, s.cart_coords, coords_are_cartesian=True)
# s.to('POSCAR', 'POSCAR')
def angle_calculation(self, connected_nodes, loc):
angle = []
nn_coords = []
str_formula = str(self.structure.species_and_occu[loc].formula)
nodes = np.array([node for node in connected_nodes \
if self.structure.species_and_occu[node] == self.structure.species_and_occu[loc]])
#get nearest magnetic_metal angle neighbors with a tolerance of 0.1 A.
lattice_species = [
self.structure.species_and_occu[node] for node in nodes
]
s = Structure(self.structure.lattice, lattice_species,
self.frac_coords[nodes])
s.make_supercell([3, 3, 3])
new_frac_coords = np.round(s.frac_coords, decimals=3)
new_frac_coords[new_frac_coords == 1.] = 0.
distances = []
for i in range(len(new_frac_coords)):
distances.append(
np.linalg.norm(
s.lattice.get_cartesian_coords(new_frac_coords[i]) -
s.lattice.get_cartesian_coords([0.5, 0.5, 0.5])))
new_loc = np.argmin(distances)
loc_cart_coords = s.lattice.get_cartesian_coords(
new_frac_coords[new_loc])
#identify the two closest same species to the specie under consideration (new_loc)
nodes = np.arange(len(s))
distances = [s.distance_matrix[node, new_loc] for node in nodes]
nodes = nodes[np.argsort(distances)]
distances = np.sort(distances)
#identify other potential second closest atoms. Useful if there are multiple such atoms.
min_dist_node1 = nodes[1]
try: #for 1D compounds. Not applicable now.
min_dist_node2 = nodes[2]
except IndexError:
angle = '180.0'
nn_coords = [
s.lattice.get_cartesian_coords(new_frac_coords[nodes[1]]) -
loc_cart_coords
]
return angle, nn_coords
nnn_list = [
nodes[i] for i in range(2, len(nodes))
if distances[i] < distances[2] + 0.1
]
#get the image of the neighbors if they are closer than the one inside the cell
nnn_coords = []
for node in nnn_list:
nnn_coords.append(
s.lattice.get_cartesian_coords(new_frac_coords[node]))
#get the angles between the atoms and take the non-zero minimum value.
angles = []
v1 = s.lattice.get_cartesian_coords(
new_frac_coords[min_dist_node1]) - loc_cart_coords
for coords in nnn_coords:
v2 = coords - loc_cart_coords
cos_theta = np.dot(v1,
v2) / (np.linalg.norm(v1) * np.linalg.norm(v2))
if np.round(cos_theta, decimals=1) == -1.0:
angles.append(180.0)
else:
angles.append(np.arccos(cos_theta) * 180 / np.pi)
try:
angle.append(min(i for i in angles if i > 0.1))
except ValueError:
angle.append(0.0)
angle = str(np.round(min(angle), decimals=2))
nn_list = [
nodes[i] for i in range(1, len(nodes))
if distances[i] <= distances[1] + 0.1
]
for node in nn_list:
nn_coords.append(
s.lattice.get_cartesian_coords(new_frac_coords[node]))
nn_coords = [coord - loc_cart_coords for coord in nn_coords]
return angle, nn_coords
def test_supercell_subsets(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=True,
attempt_supercell=True, allow_subset=True,
supercell_size='volume')
sm_no_s = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
primitive_cell=False, scale=True,
attempt_supercell=True, allow_subset=False,
supercell_size='volume')
l = Lattice.orthorhombic(1, 2, 3)
s1 = Structure(l, ['Ag', 'Si', 'Si'],
[[.7, .4, .5], [0, 0, 0.1], [0, 0, 0.2]])
s1.make_supercell([2, 1, 1])
s2 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0.1, -0.95], [0, 0.1, 0], [-.7, .5, .375]])
shuffle = [0, 2, 1, 3, 4, 5]
s1 = Structure.from_sites([s1[i] for i in shuffle])
# test when s1 is exact supercell of s2
result = sm.get_s2_like_s1(s1, s2)
for a, b in zip(s1, result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species, b.species)
self.assertTrue(sm.fit(s1, s2))
self.assertTrue(sm.fit(s2, s1))
self.assertTrue(sm_no_s.fit(s1, s2))
self.assertTrue(sm_no_s.fit(s2, s1))
rms = (0.048604032430991401, 0.059527539448807391)
self.assertTrue(np.allclose(sm.get_rms_dist(s1, s2), rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2, s1), rms))
# test when the supercell is a subset of s2
subset_supercell = s1.copy()
del subset_supercell[0]
result = sm.get_s2_like_s1(subset_supercell, s2)
self.assertEqual(len(result), 6)
for a, b in zip(subset_supercell, result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species, b.species)
self.assertTrue(sm.fit(subset_supercell, s2))
self.assertTrue(sm.fit(s2, subset_supercell))
self.assertFalse(sm_no_s.fit(subset_supercell, s2))
self.assertFalse(sm_no_s.fit(s2, subset_supercell))
rms = (0.053243049896333279, 0.059527539448807336)
self.assertTrue(np.allclose(sm.get_rms_dist(subset_supercell, s2), rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2, subset_supercell), rms))
# test when s2 (once made a supercell) is a subset of s1
s2_missing_site = s2.copy()
del s2_missing_site[1]
result = sm.get_s2_like_s1(s1, s2_missing_site)
for a, b in zip((s1[i] for i in (0, 2, 4, 5)), result):
self.assertTrue(a.distance(b) < 0.08)
self.assertEqual(a.species, b.species)
self.assertTrue(sm.fit(s1, s2_missing_site))
self.assertTrue(sm.fit(s2_missing_site, s1))
self.assertFalse(sm_no_s.fit(s1, s2_missing_site))
self.assertFalse(sm_no_s.fit(s2_missing_site, s1))
rms = (0.029763769724403633, 0.029763769724403987)
self.assertTrue(np.allclose(sm.get_rms_dist(s1, s2_missing_site), rms))
self.assertTrue(np.allclose(sm.get_rms_dist(s2_missing_site, s1), rms))
class Test2D_WSe2(Test2D):
def setUp(self):
## hexagonal WSe2 unitcell
self.a0 = 3.287596
self.c = 23.360843
self.structure = Structure(
Lattice.from_parameters(a=self.a0,
b=self.a0,
c=self.c,
alpha=90,
beta=90,
gamma=120), ["W", "Se", "Se"],
[[0.0, 0.0, 0.5], [0.333333, 0.666667, 0.571091],
[0.333333, 0.666667, 0.428909]])
self.nvecs = [4, 4, 1]
self.vacuum = 20
self.q = 0
self.structure.make_supercell(self.nvecs)
self.structure_bulk = self.structure.copy()
self.initdef_list = []
self.initdef_list.append(
{"def1": {
"type": "vac",
"species": "Se",
"index": 0
}})
self.initdef_list.append({
"def1": {
"type": "sub",
"index": -1,
"species": "W",
"species_new": "Re"
}
})
self.initdef_list.append({
"def1": {
"type": "sub",
"index": -1,
"species": "W",
"species_new": "Re"
},
"def2": {
"type": "vac",
"index": -1,
"species": "Se",
"index_offset_n1n2": -1
}
})
self.initdef_list.append({
"def1": {
"type": "ad-W",
"index": [-1],
"species": ["W"],
"species_new": "Re",
"shift_z": "3.36"
}
})
self.initdef_list.append({
"def1": {
"type": "int-hex",
"index": [0, 1, 0],
"index_offset_n1": [1, 1, 0],
"species": 3 * ["W"],
"species_new": "Re"
}
})
self.create_defects()
self.siteinds_list = [[16], [15], [15, 31], [[15]], [[4, 5, 0]]]
self.defcoords_list = [[[0.083333, 0.166667, 0.571091]],
[[0.75, 0.75, 0.5]],
[[0.75, 0.75, 0.5],
[0.833333, 0.916667, 0.571091]],
[[0.75, 0.75, 0.643830]],
[[0.166667, 0.083333, 0.5]]]
self.natoms_list = [47, 48, 47, 49, 49]