def __init__(self, cutoff_a, cell_cv, pbc_c, self_interaction):
self.neighbors = PrimitiveNeighborList(
cutoff_a,
skin=0,
sorted=True,
self_interaction=self_interaction,
use_scaled_positions=True)
self.cell_cv = cell_cv
self.pbc_c = pbc_c
def __init__(self,
cutoffs,
skin=0.3,
sorted=False,
self_interaction=True,
bothways=False):
PrimitiveNeighborList.__init__(
self,
cutoffs,
skin=skin,
sorted=sorted,
self_interaction=self_interaction,
bothways=bothways)
self.sndict = {}
self.axis = np.eye(3)
def test_hexagonal_cell_and_large_cutoff():
# Test hexagonal cell and large cutoff
pbc_c = np.array([True, True, True])
cutoff_a = np.array([8.0, 8.0])
cell_cv = np.array([[0., 3.37316113, 3.37316113],
[3.37316113, 0., 3.37316113],
[3.37316113, 3.37316113, 0.]])
spos_ac = np.array([[0., 0., 0.], [0.25, 0.25, 0.25]])
nl = PrimitiveNeighborList(cutoff_a,
skin=0.0,
sorted=True,
use_scaled_positions=True)
nl2 = NewPrimitiveNeighborList(cutoff_a,
skin=0.0,
sorted=True,
use_scaled_positions=True)
nl.update(pbc_c, cell_cv, spos_ac)
nl2.update(pbc_c, cell_cv, spos_ac)
a0, offsets0 = nl.get_neighbors(0)
b0 = np.zeros_like(a0)
d0 = np.dot(spos_ac[a0] + offsets0 - spos_ac[0], cell_cv)
a1, offsets1 = nl.get_neighbors(1)
d1 = np.dot(spos_ac[a1] + offsets1 - spos_ac[1], cell_cv)
b1 = np.ones_like(a1)
a = np.concatenate([a0, a1])
b = np.concatenate([b0, b1])
d = np.concatenate([d0, d1])
_a = np.concatenate([a, b])
_b = np.concatenate([b, a])
a = _a
b = _b
d = np.concatenate([d, -d])
a0, offsets0 = nl2.get_neighbors(0)
d0 = np.dot(spos_ac[a0] + offsets0 - spos_ac[0], cell_cv)
b0 = np.zeros_like(a0)
a1, offsets1 = nl2.get_neighbors(1)
d1 = np.dot(spos_ac[a1] + offsets1 - spos_ac[1], cell_cv)
b1 = np.ones_like(a1)
a2 = np.concatenate([a0, a1])
b2 = np.concatenate([b0, b1])
d2 = np.concatenate([d0, d1])
_a2 = np.concatenate([a2, b2])
_b2 = np.concatenate([b2, a2])
a2 = _a2
b2 = _b2
d2 = np.concatenate([d2, -d2])
i = np.argsort(d[:, 0] + d[:, 1] * 1e2 + d[:, 2] * 1e4 + a * 1e6)
i2 = np.argsort(d2[:, 0] + d2[:, 1] * 1e2 + d2[:, 2] * 1e4 + a2 * 1e6)
assert np.all(a[i] == a2[i2])
assert np.all(b[i] == b2[i2])
assert np.allclose(d[i], d2[i2])
def __init__(self, cutoff_a, pbc_c, cell_cv, spos_ac):
nl = PrimitiveNeighborList(cutoff_a,
skin=0,
sorted=True,
self_interaction=True,
use_scaled_positions=True)
nl.update(pbc=pbc_c, cell=cell_cv, coordinates=spos_ac)
r_and_offset_aao = {}
def add(a1, a2, R_c, offset):
r_and_offset_aao.setdefault((a1, a2), []).append((R_c, offset))
for a1, spos1_c in enumerate(spos_ac):
a2_a, offsets = nl.get_neighbors(a1)
for a2, offset in zip(a2_a, offsets):
spos2_c = spos_ac[a2] + offset
R_c = np.dot(spos2_c - spos1_c, cell_cv)
add(a1, a2, R_c, offset)
if a1 != a2 or offset.any():
add(a2, a1, -R_c, -offset)
self.r_and_offset_aao = r_and_offset_aao
class NeighborPairs:
"""Class for looping over pairs of atoms using a neighbor list."""
def __init__(self, cutoff_a, cell_cv, pbc_c, self_interaction):
self.neighbors = PrimitiveNeighborList(
cutoff_a,
skin=0,
sorted=True,
self_interaction=self_interaction,
use_scaled_positions=True)
self.cell_cv = cell_cv
self.pbc_c = pbc_c
def set_positions(self, spos_ac):
self.spos_ac = spos_ac
self.neighbors.update(self.pbc_c, self.cell_cv, spos_ac)
def iter(self):
cell_cv = self.cell_cv
for a1, spos1_c in enumerate(self.spos_ac):
a2_a, offsets = self.neighbors.get_neighbors(a1)
for a2, offset in zip(a2_a, offsets):
spos2_c = self.spos_ac[a2] + offset
R_c = np.dot(spos2_c - spos1_c, cell_cv)
yield a1, a2, R_c, offset
def test_empty_neighbor_list():
# Test empty neighbor list
nl = PrimitiveNeighborList([])
nl.update([True, True, True], np.eye(3) * 7.56, np.zeros((0, 3)))
for NeighborListClass in [PrimitiveNeighborList, NewPrimitiveNeighborList]:
nl = NeighborListClass([c, c],
skin=0.0,
sorted=True,
self_interaction=False,
use_scaled_positions=True)
nl.update([True, True, True],
np.eye(3) * 7.56, np.array([[0, 0, 0], [0, 0, 0.99875]]))
n0, d0 = nl.get_neighbors(0)
n1, d1 = nl.get_neighbors(1)
# != is xor
assert (np.all(n0 == [0]) and np.all(d0 == [0, 0, 1])) != \
(np.all(n1 == [1]) and np.all(d1 == [0, 0, -1]))
# Test empty neighbor list
nl = PrimitiveNeighborList([])
nl.update([True, True, True], np.eye(3) * 7.56, np.zeros((0, 3)))
# Test hexagonal cell and large cutoff
pbc_c = np.array([True, True, True])
cutoff_a = np.array([8.0, 8.0])
cell_cv = np.array([[0., 3.37316113, 3.37316113], [3.37316113, 0., 3.37316113],
[3.37316113, 3.37316113, 0.]])
spos_ac = np.array([[0., 0., 0.], [0.25, 0.25, 0.25]])
nl = PrimitiveNeighborList(cutoff_a,
skin=0.0,
sorted=True,
use_scaled_positions=True)
nl2 = NewPrimitiveNeighborList(cutoff_a,
skin=0.0,
def test_neighbor():
atoms = Atoms(numbers=range(10),
cell=[(0.2, 1.2, 1.4), (1.4, 0.1, 1.6), (1.3, 2.0, -0.1)])
atoms.set_scaled_positions(3 * random.random((10, 3)) - 1)
for sorted in [False, True]:
for p1 in range(2):
for p2 in range(2):
for p3 in range(2):
# print(p1, p2, p3)
atoms.set_pbc((p1, p2, p3))
nl = NeighborList(atoms.numbers * 0.2 + 0.5,
skin=0.0,
sorted=sorted)
nl.update(atoms)
d, c = count(nl, atoms)
atoms2 = atoms.repeat((p1 + 1, p2 + 1, p3 + 1))
nl2 = NeighborList(atoms2.numbers * 0.2 + 0.5,
skin=0.0,
sorted=sorted)
nl2.update(atoms2)
d2, c2 = count(nl2, atoms2)
c2.shape = (-1, 10)
dd = d * (p1 + 1) * (p2 + 1) * (p3 + 1) - d2
assert abs(dd) < 1e-10
assert not (c2 - c).any()
h2 = Atoms('H2', positions=[(0, 0, 0), (0, 0, 1)])
nl = NeighborList([0.5, 0.5],
skin=0.1,
sorted=True,
self_interaction=False)
nl2 = NeighborList([0.5, 0.5],
skin=0.1,
sorted=True,
self_interaction=False,
primitive=NewPrimitiveNeighborList)
assert nl2.update(h2)
assert nl.update(h2)
assert not nl.update(h2)
assert (nl.get_neighbors(0)[0] == [1]).all()
m = np.zeros((2, 2))
m[0, 1] = 1
assert np.array_equal(nl.get_connectivity_matrix(sparse=False), m)
assert np.array_equal(nl.get_connectivity_matrix(sparse=True).todense(), m)
assert np.array_equal(nl.get_connectivity_matrix().todense(),
nl2.get_connectivity_matrix().todense())
h2[1].z += 0.09
assert not nl.update(h2)
assert (nl.get_neighbors(0)[0] == [1]).all()
h2[1].z += 0.09
assert nl.update(h2)
assert (nl.get_neighbors(0)[0] == []).all()
assert nl.nupdates == 2
h2 = Atoms('H2', positions=[(0, 0, 0), (0, 0, 1)])
nl = NeighborList([0.1, 0.1],
skin=0.1,
bothways=True,
self_interaction=False)
assert nl.update(h2)
assert nl.get_neighbors(0)[1].shape == (0, 3)
assert nl.get_neighbors(0)[1].dtype == int
x = bulk('X', 'fcc', a=2**0.5)
nl = NeighborList([0.5], skin=0.01, bothways=True, self_interaction=False)
nl.update(x)
assert len(nl.get_neighbors(0)[0]) == 12
nl = NeighborList([0.5] * 27,
skin=0.01,
bothways=True,
self_interaction=False)
nl.update(x * (3, 3, 3))
for a in range(27):
assert len(nl.get_neighbors(a)[0]) == 12
assert not np.any(nl.get_neighbors(13)[1])
c = 0.0058
for NeighborListClass in [PrimitiveNeighborList, NewPrimitiveNeighborList]:
nl = NeighborListClass([c, c],
skin=0.0,
sorted=True,
self_interaction=False,
use_scaled_positions=True)
nl.update([True, True, True],
np.eye(3) * 7.56, np.array([[0, 0, 0], [0, 0, 0.99875]]))
n0, d0 = nl.get_neighbors(0)
n1, d1 = nl.get_neighbors(1)
# != is xor
assert (np.all(n0 == [0]) and np.all(d0 == [0, 0, 1])) != \
(np.all(n1 == [1]) and np.all(d1 == [0, 0, -1]))
# Test empty neighbor list
nl = PrimitiveNeighborList([])
nl.update([True, True, True], np.eye(3) * 7.56, np.zeros((0, 3)))
# Test hexagonal cell and large cutoff
pbc_c = np.array([True, True, True])
cutoff_a = np.array([8.0, 8.0])
cell_cv = np.array([[0., 3.37316113, 3.37316113],
[3.37316113, 0., 3.37316113],
[3.37316113, 3.37316113, 0.]])
spos_ac = np.array([[0., 0., 0.], [0.25, 0.25, 0.25]])
nl = PrimitiveNeighborList(cutoff_a,
skin=0.0,
sorted=True,
use_scaled_positions=True)
nl2 = NewPrimitiveNeighborList(cutoff_a,
skin=0.0,
sorted=True,
use_scaled_positions=True)
nl.update(pbc_c, cell_cv, spos_ac)
nl2.update(pbc_c, cell_cv, spos_ac)
a0, offsets0 = nl.get_neighbors(0)
b0 = np.zeros_like(a0)
d0 = np.dot(spos_ac[a0] + offsets0 - spos_ac[0], cell_cv)
a1, offsets1 = nl.get_neighbors(1)
d1 = np.dot(spos_ac[a1] + offsets1 - spos_ac[1], cell_cv)
b1 = np.ones_like(a1)
a = np.concatenate([a0, a1])
b = np.concatenate([b0, b1])
d = np.concatenate([d0, d1])
_a = np.concatenate([a, b])
_b = np.concatenate([b, a])
a = _a
b = _b
d = np.concatenate([d, -d])
a0, offsets0 = nl2.get_neighbors(0)
d0 = np.dot(spos_ac[a0] + offsets0 - spos_ac[0], cell_cv)
b0 = np.zeros_like(a0)
a1, offsets1 = nl2.get_neighbors(1)
d1 = np.dot(spos_ac[a1] + offsets1 - spos_ac[1], cell_cv)
b1 = np.ones_like(a1)
a2 = np.concatenate([a0, a1])
b2 = np.concatenate([b0, b1])
d2 = np.concatenate([d0, d1])
_a2 = np.concatenate([a2, b2])
_b2 = np.concatenate([b2, a2])
a2 = _a2
b2 = _b2
d2 = np.concatenate([d2, -d2])
i = np.argsort(d[:, 0] + d[:, 1] * 1e2 + d[:, 2] * 1e4 + a * 1e6)
i2 = np.argsort(d2[:, 0] + d2[:, 1] * 1e2 + d2[:, 2] * 1e4 + a2 * 1e6)
assert np.all(a[i] == a2[i2])
assert np.all(b[i] == b2[i2])
assert np.allclose(d[i], d2[i2])