def test_minimum_image_convention(dim):
size = 2
if dim == 2:
pbc = [True, True, False]
else:
pbc = [True, True, True]
atoms = FaceCenteredCubic(size=[size, size, size],
symbol='Cu',
latticeconstant=2,
pbc=pbc)
if dim == 2:
cell = atoms.cell.uncomplete(atoms.pbc)
atoms.set_cell(cell, scale_atoms=False)
d0 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
if dim == 2:
U = np.array([[1, 2, 0], [0, 1, 0], [0, 0, 1]])
else:
U = np.array([[1, 2, 2], [0, 1, 2], [0, 0, 1]])
assert np.linalg.det(U) == 1
atoms.set_cell(U.T @ atoms.cell, scale_atoms=False)
atoms.wrap()
d1 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
assert_allclose(d0, d1)
vnbrlist = NeighborListMic(atoms.get_positions(), atoms.cell, atoms.pbc)
d2 = np.linalg.norm(vnbrlist, axis=1)
assert_allclose(d0, d2)
nl = NeighborList(np.ones(len(atoms)) * 2 * size * np.sqrt(3),
bothways=True,
primitive=PrimitiveNeighborList)
nl.update(atoms)
indices, offsets = nl.get_neighbors(0)
d3 = float("inf") * np.ones(len(atoms))
for i, offset in zip(indices, offsets):
p = atoms.positions[i] + offset @ atoms.get_cell()
d = np.linalg.norm(p - atoms.positions[0])
d3[i] = min(d3[i], d)
assert_allclose(d0, d3)
def test_minimum_image_convention():
import numpy as np
from numpy.testing import assert_allclose
from ase.lattice.cubic import FaceCenteredCubic
from ase.neighborlist import mic as NeighborListMic
from ase.neighborlist import NeighborList, PrimitiveNeighborList
size = 2
atoms = FaceCenteredCubic(size=[size, size, size],
symbol='Cu',
latticeconstant=2,
pbc=(1, 1, 1))
d0 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
U = np.array([[1, 2, 2], [0, 1, 2], [0, 0, 1]])
assert np.linalg.det(U) == 1
atoms.set_cell(U.T @ atoms.cell, scale_atoms=False)
atoms.wrap()
d1 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
assert_allclose(d0, d1)
vnbrlist = NeighborListMic(atoms.get_positions(), atoms.cell, atoms.pbc)
d2 = np.linalg.norm(vnbrlist, axis=1)
assert_allclose(d0, d2)
nl = NeighborList(np.ones(len(atoms)) * 2 * size * np.sqrt(3),
bothways=True,
primitive=PrimitiveNeighborList)
nl.update(atoms)
indices, offsets = nl.get_neighbors(0)
d3 = float("inf") * np.ones(len(atoms))
for i, offset in zip(indices, offsets):
p = atoms.positions[i] + offset @ atoms.get_cell()
d = np.linalg.norm(p - atoms.positions[0])
d3[i] = min(d3[i], d)
assert_allclose(d0, d3)
import numpy as np
from numpy.testing import assert_allclose
from ase.lattice.cubic import FaceCenteredCubic
from ase.neighborlist import mic as NeighborListMic
from ase.neighborlist import NeighborList, PrimitiveNeighborList
size = 2
atoms = FaceCenteredCubic(size=[size, size, size],
symbol='Cu',
latticeconstant=2,
pbc=(1, 1, 1))
d0 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
U = np.array([[1, 2, 2],
[0, 1, 2],
[0, 0, 1]])
assert np.linalg.det(U) == 1
atoms.set_cell(U.T @ atoms.cell, scale_atoms=False)
atoms.wrap()
d1 = atoms.get_distances(0, np.arange(len(atoms)), mic=True)
assert_allclose(d0, d1)
vnbrlist = NeighborListMic(atoms.get_positions(), atoms.cell, atoms.pbc)
d2 = np.linalg.norm(vnbrlist, axis=1)
assert_allclose(d0, d2)
nl = NeighborList(np.ones(len(atoms)) * 2 * size * np.sqrt(3),
