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_ordered_primitive_to_disordered_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],
[0.5, 0, 0],
[0.25, 0.5, 0.5],
[0.75, 0.5, 0.5]]
s1 = Structure(lp, ['Na', 'Cl'], pcoords)
s2 = Structure(ls, [{'Na': 0.5}, {'Na': 0.5}, {'Cl': 0.5}, {'Cl': 0.5}],
scoords)
self.assertTrue(sm_sites.fit(s1, s2))
self.assertFalse(sm_atoms.fit(s1, s2))
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_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_lattice_2_lmpbox(self):
matrix = np.diag(np.random.randint(5, 14, size=(3,))) \
+ np.random.rand(3, 3) * 0.2 - 0.1
init_latt = Lattice(matrix)
frac_coords = np.random.rand(10, 3)
init_structure = Structure(init_latt, ["H"] * 10, frac_coords)
origin = np.random.rand(3) * 10 - 5
box, symmop = lattice_2_lmpbox(lattice=init_latt, origin=origin)
boxed_latt = box.to_lattice()
np.testing.assert_array_almost_equal(init_latt.abc, boxed_latt.abc)
np.testing.assert_array_almost_equal(init_latt.angles,
boxed_latt.angles)
cart_coords = symmop.operate_multi(init_structure.cart_coords) - origin
boxed_structure = Structure(boxed_latt, ["H"] * 10,
cart_coords,
coords_are_cartesian=True)
np.testing.assert_array_almost_equal(boxed_structure.frac_coords,
frac_coords)
tetra_latt = Lattice.tetragonal(5, 5)
tetra_box, _ = lattice_2_lmpbox(tetra_latt)
self.assertIsNone(tetra_box.tilt)
ortho_latt = Lattice.orthorhombic(5, 5, 5)
ortho_box, _ = lattice_2_lmpbox(ortho_latt)
self.assertIsNone(ortho_box.tilt)
rot_tetra_latt = Lattice([[5, 0, 0], [0, 2, 2], [0, -2, 2]])
_, rotop = lattice_2_lmpbox(rot_tetra_latt)
np.testing. \
assert_array_almost_equal(rotop.rotation_matrix,
[[1, 0, 0],
[0, 2 ** 0.5 / 2, 2 ** 0.5 / 2],
[0, -2 ** 0.5 / 2, 2 ** 0.5 / 2]])
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_sulfide_type(self):
# NaS2 -> polysulfide
latt = Lattice.tetragonal(9.59650, 11.78850)
species = ["Na"] * 2 + ["S"] * 2
coords = [[0.00000, 0.00000, 0.17000], [0.27600, 0.25000, 0.12500],
[0.03400, 0.25000, 0.29600], [0.14700, 0.11600, 0.40000]]
struct = Structure.from_spacegroup(122, latt, species, coords)
self.assertEqual(sulfide_type(struct), "polysulfide")
# NaCl type NaS -> sulfide
latt = Lattice.cubic(5.75)
species = ["Na", "S"]
coords = [[0.00000, 0.00000, 0.00000], [0.50000, 0.50000, 0.50000]]
struct = Structure.from_spacegroup(225, latt, species, coords)
self.assertEqual(sulfide_type(struct), "sulfide")
# Na2S2O3 -> None (sulfate)
latt = Lattice.monoclinic(6.40100, 8.10000, 8.47400, 96.8800)
species = ["Na"] * 2 + ["S"] * 2 + ["O"] * 3
coords = [[0.29706, 0.62396, 0.08575], [0.37673, 0.30411, 0.45416],
[0.52324, 0.10651, 0.21126], [0.29660, -0.04671, 0.26607],
[0.17577, 0.03720, 0.38049], [0.38604, -0.20144, 0.33624],
[0.16248, -0.08546, 0.11608]]
struct = Structure.from_spacegroup(14, latt, species, coords)
self.assertEqual(sulfide_type(struct), None)
# Na3PS3O -> sulfide
latt = Lattice.orthorhombic(9.51050, 11.54630, 5.93230)
species = ["Na"] * 2 + ["S"] * 2 + ["P", "O"]
coords = [[0.19920, 0.11580, 0.24950], [0.00000, 0.36840, 0.29380],
[0.32210, 0.36730, 0.22530], [0.50000, 0.11910, 0.27210],
[0.50000, 0.29400, 0.35500], [0.50000, 0.30300, 0.61140]]
struct = Structure.from_spacegroup(36, latt, species, coords)
self.assertEqual(sulfide_type(struct), "sulfide")
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_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_lattice_2_lmpbox(self):
matrix = np.diag(np.random.randint(5, 14, size=(3,))) \
+ np.random.rand(3, 3) * 0.2 - 0.1
init_latt = Lattice(matrix)
frac_coords = np.random.rand(10, 3)
init_structure = Structure(init_latt, ["H"] * 10, frac_coords)
origin = np.random.rand(3) * 10 - 5
box, symmop = lattice_2_lmpbox(lattice=init_latt, origin=origin)
boxed_latt = box.to_lattice()
np.testing.assert_array_almost_equal(init_latt.abc, boxed_latt.abc)
np.testing.assert_array_almost_equal(init_latt.angles,
boxed_latt.angles)
cart_coords = symmop.operate_multi(init_structure.cart_coords) \
- origin
boxed_structure = Structure(boxed_latt, ["H"] * 10, cart_coords,
coords_are_cartesian=True)
np.testing.assert_array_almost_equal(boxed_structure.frac_coords,
frac_coords)
tetra_latt = Lattice.tetragonal(5, 5)
tetra_box, _ = lattice_2_lmpbox(tetra_latt)
self.assertIsNone(tetra_box.tilt)
ortho_latt = Lattice.orthorhombic(5, 5, 5)
ortho_box, _ = lattice_2_lmpbox(ortho_latt)
self.assertIsNone(ortho_box.tilt)
rot_tetra_latt = Lattice([[5, 0, 0], [0, 2, 2], [0, -2, 2]])
_, rotop = lattice_2_lmpbox(rot_tetra_latt)
np.testing.\
assert_array_almost_equal(rotop.rotation_matrix,
[[1, 0, 0],
[0, 2 ** 0.5 / 2, 2 ** 0.5 / 2],
[0, -2 ** 0.5 / 2, 2 ** 0.5 / 2]])
def test_create_supercell(a_centered_orthorhombic):
cs = SupercellMaker(a_centered_orthorhombic)
actual_lattice = cs.conv_structure.lattice
expected = Lattice.orthorhombic(1, 4, 6)
assert actual_lattice == expected
actual = cs.supercell.matrix
expected = [[6, 0, 0], [0, 2, 0], [0, 0, 1]]
np.testing.assert_array_equal(actual, expected)
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 ortho_conventional():
lattice = Lattice.orthorhombic(5, 6, 7)
coords = [
[0.0, 0.0, 0.0],
[0.5, 0.5, 0.0],
[0.5, 0.0, 0.5],
[0.0, 0.5, 0.5],
[0.0, 0.0, 0.5],
[0.0, 0.5, 0.0],
[0.5, 0.0, 0.0],
[0.5, 0.5, 0.5],
]
return IStructure(lattice=lattice,
species=["H"] * 4 + ["He"] * 4,
coords=coords)
def test_rms_vs_minimax(self):
# This tests that structures with adjusted RMS less than stol, but minimax
# greater than stol are treated properly
# stol=0.3 gives exactly an ftol of 0.1 on the c axis
sm = StructureMatcher(ltol=0.2, stol=0.301, angle_tol=1, primitive_cell=False)
l = Lattice.orthorhombic(1, 2, 12)
sp = ["Si", "Si", "Al"]
s1 = Structure(l, sp, [[0.5, 0, 0], [0, 0, 0], [0, 0, 0.5]])
s2 = Structure(l, sp, [[0.5, 0, 0], [0, 0, 0], [0, 0, 0.6]])
self.assertArrayAlmostEqual(sm.get_rms_dist(s1, s2),
(0.32 ** 0.5 / 2, 0.4))
self.assertEqual(sm.fit(s1, s2), False)
self.assertEqual(sm.fit_anonymous(s1, s2), False)
self.assertEqual(sm.get_mapping(s1, s2), None)
def test_rms_vs_minimax(self):
# This tests that structures with adjusted RMS less than stol, but minimax
# greater than stol are treated properly
# stol=0.3 gives exactly an ftol of 0.1 on the c axis
sm = StructureMatcher(ltol=0.2, stol=0.301, angle_tol=1, primitive_cell=False)
l = Lattice.orthorhombic(1, 2, 12)
sp = ["Si", "Si", "Al"]
s1 = Structure(l, sp, [[0.5, 0, 0], [0, 0, 0], [0, 0, 0.5]])
s2 = Structure(l, sp, [[0.5, 0, 0], [0, 0, 0], [0, 0, 0.6]])
self.assertArrayAlmostEqual(sm.get_rms_dist(s1, s2),
(0.32 ** 0.5 / 2, 0.4))
self.assertEqual(sm.fit(s1, s2), False)
self.assertEqual(sm.fit_anonymous(s1, s2), False)
self.assertEqual(sm.get_mapping(s1, s2), None)
def test_sulfide_type(self):
# NaS2 -> polysulfide
latt = Lattice.tetragonal(9.59650, 11.78850)
species = ["Na"] * 2 + ["S"] * 2
coords = [[0.00000, 0.00000, 0.17000],
[0.27600, 0.25000, 0.12500],
[0.03400, 0.25000, 0.29600],
[0.14700, 0.11600, 0.40000]]
struct = Structure.from_spacegroup(122, latt, species, coords)
self.assertEqual(sulfide_type(struct), "polysulfide")
# NaCl type NaS -> sulfide
latt = Lattice.cubic(5.75)
species = ["Na", "S"]
coords = [[0.00000, 0.00000, 0.00000],
[0.50000, 0.50000, 0.50000]]
struct = Structure.from_spacegroup(225, latt, species, coords)
self.assertEqual(sulfide_type(struct), "sulfide")
# Na2S2O3 -> None (sulfate)
latt = Lattice.monoclinic(6.40100, 8.10000, 8.47400, 96.8800)
species = ["Na"] * 2 + ["S"] * 2 + ["O"] * 3
coords = [[0.29706, 0.62396, 0.08575],
[0.37673, 0.30411, 0.45416],
[0.52324, 0.10651, 0.21126],
[0.29660, -0.04671, 0.26607],
[0.17577, 0.03720, 0.38049],
[0.38604, -0.20144, 0.33624],
[0.16248, -0.08546, 0.11608]]
struct = Structure.from_spacegroup(14, latt, species, coords)
self.assertEqual(sulfide_type(struct), None)
# Na3PS3O -> sulfide
latt = Lattice.orthorhombic(9.51050, 11.54630, 5.93230)
species = ["Na"] * 2 + ["S"] * 2 + ["P", "O"]
coords = [[0.19920, 0.11580, 0.24950],
[0.00000, 0.36840, 0.29380],
[0.32210, 0.36730, 0.22530],
[0.50000, 0.11910, 0.27210],
[0.50000, 0.29400, 0.35500],
[0.50000, 0.30300, 0.61140]]
struct = Structure.from_spacegroup(36, latt, species, coords)
self.assertEqual(sulfide_type(struct), "sulfide")
# test for unphysical cells
struct.scale_lattice(struct.volume*10)
self.assertEqual(sulfide_type(struct), "sulfide")
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_oi_ti_bravais():
structure = Structure(Lattice.orthorhombic(20, 8, 6),
species=["H"] * 2,
coords=[[0.0] * 3, [0.5] * 3])
generator = StructureKpointsGenerator(structure,
task=Task.structure_opt,
kpt_density=5)
generator.generate_input()
primitive_structure = StructureSymmetrizer(structure).primitive
expected_generator = StructureKpointsGenerator(primitive_structure,
task=Task.structure_opt,
kpt_density=5)
expected_generator.generate_input()
assert generator.num_kpts == expected_generator.num_kpts
assert generator.kpoints.kpts_shift == expected_generator.kpoints.kpts_shift
def test_occupancy_comparator(self):
lp = Lattice.orthorhombic(10, 20, 30)
pcoords = [[0, 0, 0],
[0.5, 0.5, 0.5]]
s1 = Structure(lp, [{'Na': 0.6, 'K': 0.4}, 'Cl'], pcoords)
s2 = Structure(lp, [{'Xa': 0.4, 'Xb': 0.6}, 'Cl'], pcoords)
s3 = Structure(lp, [{'Xa': 0.5, 'Xb': 0.5}, 'Cl'], pcoords)
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=OccupancyComparator())
self.assertTrue(sm_sites.fit(s1, s2))
self.assertFalse(sm_sites.fit(s1, s3))
def test_species_order():
lattice = Lattice.orthorhombic(5, 6, 7)
coords = [
[0.0, 0.0, 0.0],
[0.5, 0.5, 0.0],
[0.5, 0.0, 0.5],
[0.0, 0.5, 0.5],
[0.0, 0.0, 0.5],
[0.0, 0.5, 0.0],
[0.5, 0.0, 0.0],
[0.5, 0.5, 0.5],
]
structure = Structure(lattice=lattice,
species=["H"] * 4 + ["He"] * 4,
coords=coords)
supercell = structure * [1, 1, 2]
actual = [e.specie for e in StructureSymmetrizer(supercell).conventional]
expected = [Element.H] * 4 + [Element.He] * 4
assert actual == expected
def test_subset(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(10, 20, 30)
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Ag'], [[0, 0.1, 0], [-.7, .5, .4]])
result = sm.get_s2_like_s1(s1, s2)
self.assertEqual(
len(find_in_coord_list_pbc(result.frac_coords, [0, 0, 0.1])), 1)
self.assertEqual(
len(find_in_coord_list_pbc(result.frac_coords, [0.7, 0.4, 0.5])),
1)
#test with fewer species in s2
s1 = Structure(l, ['Si', 'Ag', 'Si'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Si'], [[0, 0.1, 0], [-.7, .5, .4]])
result = sm.get_s2_like_s1(s1, s2)
mindists = np.min(s1.lattice.get_all_distances(s1.frac_coords,
result.frac_coords),
axis=0)
self.assertLess(np.max(mindists), 1e-6)
self.assertEqual(
len(find_in_coord_list_pbc(result.frac_coords, [0, 0, 0.1])), 1)
self.assertEqual(
len(find_in_coord_list_pbc(result.frac_coords, [0.7, 0.4, 0.5])),
1)
#test with not enough sites in s1
#test with fewer species in s2
s1 = Structure(l, ['Si', 'Ag', 'Cl'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Si'], [[0, 0.1, 0], [-.7, .5, .4]])
self.assertEqual(sm.get_s2_like_s1(s1, s2), None)
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_cart_dists(self):
sm = StructureMatcher()
l = Lattice.orthorhombic(1, 2, 3)
s1 = np.array([[0.13, 0.25, 0.37], [0.1, 0.2, 0.3]])
s2 = np.array([[0.11, 0.22, 0.33]])
s3 = np.array([[0.1, 0.2, 0.3], [0.11, 0.2, 0.3]])
s4 = np.array([[0.1, 0.2, 0.3], [0.1, 0.6, 0.7]])
mask = np.array([[False, False]])
mask2 = np.array([[False, True]])
mask3 = np.array([[False, False], [False, False]])
mask4 = np.array([[False, True], [False, True]])
n1 = (len(s1) / l.volume)**(1 / 3)
n2 = (len(s2) / l.volume)**(1 / 3)
self.assertRaises(ValueError, sm._cart_dists, s2, s1, l, mask.T, n2)
self.assertRaises(ValueError, sm._cart_dists, s1, s2, l, mask.T, n1)
d, ft, s = sm._cart_dists(s1, s2, l, mask, n1)
self.assertTrue(np.allclose(d, [0]))
self.assertTrue(np.allclose(ft, [-0.01, -0.02, -0.03]))
self.assertTrue(np.allclose(s, [1]))
#check that masking best value works
d, ft, s = sm._cart_dists(s1, s2, l, mask2, n1)
self.assertTrue(np.allclose(d, [0]))
self.assertTrue(np.allclose(ft, [0.02, 0.03, 0.04]))
self.assertTrue(np.allclose(s, [0]))
#check that averaging of translation is done properly
d, ft, s = sm._cart_dists(s1, s3, l, mask3, n1)
self.assertTrue(np.allclose(d, [0.08093341] * 2))
self.assertTrue(np.allclose(ft, [0.01, 0.025, 0.035]))
self.assertTrue(np.allclose(s, [1, 0]))
#check distances are large when mask allows no 'real' mapping
d, ft, s = sm._cart_dists(s1, s4, l, mask4, n1)
self.assertTrue(np.min(d) > 1e8)
self.assertTrue(np.min(ft) > 1e8)
def test_cart_dists(self):
sm = StructureMatcher()
l = Lattice.orthorhombic(1, 2, 3)
s1 = np.array([[0.13, 0.25, 0.37], [0.1, 0.2, 0.3]])
s2 = np.array([[0.11, 0.22, 0.33]])
s3 = np.array([[0.1, 0.2, 0.3], [0.11, 0.2, 0.3]])
s4 = np.array([[0.1, 0.2, 0.3], [0.1, 0.6, 0.7]])
mask = np.array([[False, False]])
mask2 = np.array([[False, True]])
mask3 = np.array([[False, False], [False, False]])
mask4 = np.array([[False, True], [False, True]])
n1 = (len(s1) / l.volume) ** (1 / 3)
n2 = (len(s2) / l.volume) ** (1 / 3)
self.assertRaises(ValueError, sm._cart_dists, s2, s1, l, mask.T, n2)
self.assertRaises(ValueError, sm._cart_dists, s1, s2, l, mask.T, n1)
d, ft, s = sm._cart_dists(s1, s2, l, mask, n1)
self.assertTrue(np.allclose(d, [0]))
self.assertTrue(np.allclose(ft, [-0.01, -0.02, -0.03]))
self.assertTrue(np.allclose(s, [1]))
# check that masking best value works
d, ft, s = sm._cart_dists(s1, s2, l, mask2, n1)
self.assertTrue(np.allclose(d, [0]))
self.assertTrue(np.allclose(ft, [0.02, 0.03, 0.04]))
self.assertTrue(np.allclose(s, [0]))
# check that averaging of translation is done properly
d, ft, s = sm._cart_dists(s1, s3, l, mask3, n1)
self.assertTrue(np.allclose(d, [0.08093341] * 2))
self.assertTrue(np.allclose(ft, [0.01, 0.025, 0.035]))
self.assertTrue(np.allclose(s, [1, 0]))
# check distances are large when mask allows no 'real' mapping
d, ft, s = sm._cart_dists(s1, s4, l, mask4, n1)
self.assertTrue(np.min(d) > 1e8)
self.assertTrue(np.min(ft) > 1e8)
def test_subset(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(10, 20, 30)
s1 = Structure(l, ['Si', 'Si', 'Ag'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Ag'],
[[0, 0.1, 0], [-.7, .5, .4]])
result = sm.get_s2_like_s1(s1, s2)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0, 0, 0.1])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0.7, 0.4, 0.5])), 1)
# test with fewer species in s2
s1 = Structure(l, ['Si', 'Ag', 'Si'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Si'],
[[0, 0.1, 0], [-.7, .5, .4]])
result = sm.get_s2_like_s1(s1, s2)
mindists = np.min(s1.lattice.get_all_distances(
s1.frac_coords, result.frac_coords), axis=0)
self.assertLess(np.max(mindists), 1e-6)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0, 0, 0.1])), 1)
self.assertEqual(len(find_in_coord_list_pbc(result.frac_coords,
[0.7, 0.4, 0.5])), 1)
# test with not enough sites in s1
# test with fewer species in s2
s1 = Structure(l, ['Si', 'Ag', 'Cl'],
[[0, 0, 0.1], [0, 0, 0.2], [.7, .4, .5]])
s2 = Structure(l, ['Si', 'Si'],
[[0, 0.1, 0], [-.7, .5, .4]])
self.assertEqual(sm.get_s2_like_s1(s1, s2), None)
def test_init(self):
filepath = os.path.join(test_dir, 'input/23221-ZDsSsJoEW14.res')
res = Res.from_file(filepath)
comp = res.structure.composition
self.assertEqual(comp, Composition.from_formula("C194H60"))
#print res
res_string = """TITL
CELL 1.0 1.0 1.0 1.0 90.0 90.0 90.0
LATT -1
SFAC Si F
Si 1 0.000000 0.000000 0.000000 1.0
F 2 0.750000 0.500000 0.750000 1.0"""
res = Res.from_string(res_string)
self.assertEqual(res.structure.composition, Composition("SiF"))
self.assertEquals(res.structure.num_sites, 2)
#print res
struct = Structure(Lattice.orthorhombic(2.5, 3.5, 7.0), ['Na', 'Cl'], [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]])
res = Res(struct)
res_string = str(res)
lines = res_string.splitlines()
self.assertEqual(lines[1], "CELL 1.0 2.5 3.5 7.0 90.0 90.0 90.0")
def get_orthogonal_grain(self):
a, b, c = self.lattice.abc
new_latt = Lattice.orthorhombic(a, b, c)
return Structure(new_latt, self.species, self.frac_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_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 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))
def simple_cubic_2x1x1():
lattice = Lattice.orthorhombic(2.0, 1.0, 1.0)
coords = [[0.0, 0.0, 0.0], [0.5, 0.0, 0.0]]
return IStructure(lattice=lattice, species=["H", "H"], coords=coords)
