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_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 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 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_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 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 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 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], [0.7, 0.4, 0.5]])
s2 = Structure(l, ["Si", "Si", "Ag"], [[0, 0.1, 0], [0, 0.1, -0.95], [0.7, 0.5, 0.375]])
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_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]])
match = sm._find_match(s1, s2, break_on_match = False,
use_rms = True, niggli = False)
scale_matrix = np.round(np.dot(match[2].matrix,
s2.lattice.inv_matrix)).astype('int')
s2.make_supercell(scale_matrix)
fc = s2.frac_coords + match[3]
fc -= np.round(fc)
self.assertAlmostEqual(np.sum(fc), 0.3)
self.assertAlmostEqual(np.sum(fc[:,:2]), 0)
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]])
match = sm._find_match(s1, s2, break_on_match = False,
use_rms = True, niggli = False)
scale_matrix = np.round(np.dot(match[2].matrix,
s2.lattice.inv_matrix)).astype('int')
s2.make_supercell(scale_matrix)
fc = s2.frac_coords + match[3]
fc -= np.round(fc)
self.assertAlmostEqual(np.sum(fc), 0.3)
self.assertAlmostEqual(np.sum(fc[:,:2]), 0)
def test_get_s2_like_s1(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
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_s2_like_s1(s1, s2)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0.35,0.4,0.5])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0,0,0.125])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0,0,0.175])), 1)
def test_get_s2_like_s1(self):
sm = StructureMatcher(ltol=0.2, stol=0.3, angle_tol=5,
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_s2_like_s1(s1, s2)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0.35,0.4,0.5])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0,0,0.125])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0,0,0.175])), 1)
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_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 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 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 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))
def tblg_nm(n=9, m=8):
import numpy as np
from pymatgen.core import Structure
"""Get the pymatgen structure of the twisted bilayer graphene for given n and m.
angle is given by arccos[ 0.5*(n**2+4*n*m+m**2) / (n**2+n*m+m**2) ]
Args:
n (int, optional): sc 1
m (int, optional): sc 2
Returns:
TYPE: pymatgen structure object
"""
def R(t): # Rotation matrix
c, s = np.cos(t), np.sin(t)
R = np.array(((c, -s), (s, c)))
R = np.vstack([R, [0, 0]])
R = np.hstack([R, [[0], [0], [1]]])
return R
t = np.arccos(0.5 * (n**2 + 4 * n * m + m**2) / (n**2 + n * m + m**2))
lattice_lower = [
3 * R(t / 2) @ i
for i in np.array([[1.0, 0.0, 0], [0.5, np.sqrt(3.0) /
2.0, 0], [0, 0, 10]])
] # lower lattice
lattice_upper = [
3 * R(-t / 2) @ i
for i in np.array([[1.0, 0.0, 0], [0.5, np.sqrt(3.0) /
2.0, 0], [0, 0, 10]])
] # top lattice
lower = Structure(lattice=lattice_lower,
species=["C", "C"],
coords=[[1. / 3., 1. / 3., 0.5], [2. / 3., 2. / 3.,
0.5]])
upper = Structure(lattice=lattice_upper,
species=["C", "C"],
coords=[[1. / 3., 1. / 3., 0.5], [2. / 3., 2. / 3.,
0.5]])
sc = np.eye(3)
sc[0][0] = n
sc[0][1] = m
sc[1][0] = -m
sc[1][1] = n + m
# supercell transfornation matrix for lower system
lower.make_supercell(sc)
sc = np.eye(3)
sc[0][0] = m
sc[0][1] = n
sc[1][0] = -n
sc[1][1] = m + n
# supercell transfornation matrix for upper system
upper.make_supercell(sc)
d = 1 # distance between layers
pos = []
for i in upper:
pos.append(i.coords + [0, 0, d])
for i in lower:
pos.append(i.coords + [0, 0, -d])
species = ["C"] * len(pos)
tblg = Structure(lattice=upper.lattice,
coords=pos,
species=species,
coords_are_cartesian=True)
print("angle of twist = {}".format(
np.rad2deg(
np.arccos(0.5 * (n**2 + 4 * n * m + m**2) /
(n**2 + n * m + m**2)))))
return tblg # return the twisted bilayer structure
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))
