def create_paddings(self, cell, pbc, contributing_coords,
contributing_species_code):
# Cast things passed through kimpy to numpy arrays
cell = np.asarray(cell, dtype=np.double)
pbc = np.asarray(pbc, dtype=np.intc)
contributing_coords = np.asarray(contributing_coords, dtype=np.double)
return neighlist.create_paddings(
self.influence_dist,
cell,
pbc,
contributing_coords,
contributing_species_code,
)
def _update_neigh(self, influence_distance: float):
"""
Update neighbor list and model input.
"""
# inquire information from conf
cell = np.asarray(self.conf.cell, dtype=np.double)
PBC = np.asarray(self.conf.PBC, dtype=np.intc)
contributing_coords = np.asarray(self.conf.coords, dtype=np.double)
contributing_species = self.conf.species
num_contributing = self.conf.get_num_atoms()
self.num_contributing_particles = num_contributing
# species support and code
unique_species = list(set(contributing_species))
species_map = dict()
for s in unique_species:
if s in self.supported_species:
species_map[s] = self.supported_species[s]
else:
report_error(f"species `{s}` not supported by model")
contributing_species_code = np.array(
[species_map[s] for s in contributing_species], dtype=np.intc)
if any(PBC): # need padding atoms
out = nl.create_paddings(
influence_distance,
cell,
PBC,
contributing_coords,
contributing_species_code,
)
padding_coords, padding_species_code, self.padding_image_of, error = out
check_error(error, "nl.create_paddings")
num_padding = padding_species_code.size
self.num_particles = np.array([num_contributing + num_padding],
dtype=np.intc)
tmp = np.concatenate((contributing_coords, padding_coords))
self.coords = np.asarray(tmp, dtype=np.double)
tmp = np.concatenate(
(contributing_species_code, padding_species_code))
self.species_code = np.asarray(tmp, dtype=np.intc)
self.particle_contributing = np.ones(self.num_particles[0],
dtype=np.intc)
self.particle_contributing[num_contributing:] = 0
# TODO check whether padding need neigh and create accordingly
# for now, create neigh for all atoms, including paddings
need_neigh = np.ones(self.num_particles[0], dtype=np.intc)
else: # do not need padding atoms
self.padding_image_of = np.array([])
self.num_particles = np.array([num_contributing], dtype=np.intc)
self.coords = np.array(contributing_coords, dtype=np.double)
self.species_code = np.array(contributing_species_code,
dtype=np.intc)
self.particle_contributing = np.ones(num_contributing,
dtype=np.intc)
need_neigh = self.particle_contributing
error = nl.build(
self.neigh,
self.coords,
influence_distance,
np.asarray([influence_distance], dtype=np.double),
need_neigh,
)
check_error(error, "nl.build")
def _update_neigh(self, influence_distance: float):
"""
Update neighbor list and model input.
"""
# inquire information from conf
cell = np.asarray(self.conf.cell, dtype=np.double)
PBC = np.asarray(self.conf.PBC, dtype=np.intc)
contributing_coords = np.asarray(self.conf.coords, dtype=np.double)
contributing_species = self.conf.species
num_contributing = self.conf.get_num_atoms()
self.num_contributing_particles = num_contributing
# species support and code
unique_species = list(set(contributing_species))
species_map = dict()
for s in unique_species:
if s in self.supported_species:
species_map[s] = self.supported_species[s]
else:
KIMModelError(f"species `{s}` not supported by model")
contributing_species_code = np.array(
[species_map[s] for s in contributing_species], dtype=np.intc)
if any(PBC): # need padding atoms
try:
(
padding_coords,
padding_species_code,
self.padding_image_of,
) = nl.create_paddings(
influence_distance,
cell,
PBC,
contributing_coords,
contributing_species_code,
)
except RuntimeError:
raise kimpy.KimPyError(
"Calling `nl.create_paddings()` failed.")
num_padding = padding_species_code.size
self.num_particles = np.array([num_contributing + num_padding],
dtype=np.intc)
tmp = np.concatenate((contributing_coords, padding_coords))
self.coords = np.asarray(tmp, dtype=np.double)
tmp = np.concatenate(
(contributing_species_code, padding_species_code))
self.species_code = np.asarray(tmp, dtype=np.intc)
self.particle_contributing = np.ones(self.num_particles[0],
dtype=np.intc)
self.particle_contributing[num_contributing:] = 0
# for now, create neigh for all atoms, including paddings
need_neigh = np.ones(self.num_particles[0], dtype=np.intc)
else: # do not need padding atoms
self.padding_image_of = np.array([])
self.num_particles = np.array([num_contributing], dtype=np.intc)
self.coords = np.array(contributing_coords, dtype=np.double)
self.species_code = np.array(contributing_species_code,
dtype=np.intc)
self.particle_contributing = np.ones(num_contributing,
dtype=np.intc)
need_neigh = self.particle_contributing
try:
self.neigh.build(
self.coords,
influence_distance,
np.asarray([influence_distance], dtype=np.double),
need_neigh,
)
except RuntimeError:
raise kimpy.KimPyError("Calling `neigh.build()` failed.")
def test_main():
# create contributing atoms
alat = 2.46
d = 3.35
cell, contrib_coords, contrib_species = create_graphite_unit_cell(alat, d)
# create padding atoms
cutoffs = np.array([d + 0.01, d + 0.02], dtype=np.double)
influence_dist = cutoffs[1]
pbc = np.array([1, 1, 1], dtype=np.intc)
out = nl.create_paddings(influence_dist, cell, pbc,
contrib_coords, contrib_species)
pad_coords, pad_species, pad_image, error = out
check_error(error, 'nl.create_padding')
assert pad_coords.shape == (96, 3)
# print('pad_coords is of shape:', pad_coords.shape)
coords = np.concatenate((contrib_coords, pad_coords))
coords = np.asarray(coords, dtype=np.double)
species = np.concatenate((contrib_species, pad_species))
species = np.asarray(species, dtype=np.intc)
fname = 'atoms.xyz'
write_XYZ(fname, cell, species, coords)
# flag to indicate wheter create neighbor list for an atom
n_pad = pad_coords.shape[0]
n_contrib = contrib_coords.shape[0]
need_neigh = np.concatenate((np.ones(n_contrib), np.zeros(n_pad)))
need_neigh = np.asarray(need_neigh, dtype=np.intc)
# create neighbor list
neigh = nl.initialize()
error = nl.build(neigh, coords, influence_dist, cutoffs, need_neigh)
check_error(error, 'nl.build')
# build again (it will automatically empty previous neigh list)
error = nl.build(neigh, coords, influence_dist, cutoffs, need_neigh)
check_error(error, 'nl.build')
# test get neigh function
neigh_list_index = 0
particle = 1
num_neigh, neighbors, error = nl.get_neigh(
neigh, cutoffs, neigh_list_index, particle)
check_error(error, 'nl.get_neigh')
assert num_neigh == 14
# print('Atom 1 has {} neighbors:'.format(num_neigh), end=' ')
# for i in neighbors:
# print(i, end=' ')
neigh_list_index = 1
particle = 4
num_neigh, neighbors, error = nl.get_neigh(
neigh, cutoffs, neigh_list_index, particle)
check_error(error, 'nl.get_neigh')
assert num_neigh == 0
# expect error message from this
# neigh_list_index = 1
# particle = n_contrib + n_pad
# num_neigh, neighbors, error = nl.get_neigh(neigh, cutoffs, neigh_list_index, particle)
# assert error == 1
# delete neighbor list
nl.clean(neigh)
# remove the created file
try:
os.remove(fname)
os.remove('kim.log')
except:
pass
def test_main():
# create contributing atoms
alat = 2.46
d = 3.35
cell, contrib_coords, contrib_species = create_graphite_unit_cell(alat, d)
# create padding atoms
cutoffs = np.array([d + 0.01, d + 0.02], dtype=np.double)
influence_dist = cutoffs[1]
pbc = np.array([1, 1, 1], dtype=np.intc)
try:
pad_coords, pad_species, _ = nl.create_paddings(
influence_dist, cell, pbc, contrib_coords, contrib_species)
except RuntimeError:
msg = 'Calling "neighlist.create_paddings" failed.'
raise KimPyError(msg)
assert pad_coords.shape == (96, 3)
coords = np.concatenate((contrib_coords, pad_coords))
coords = np.asarray(coords, dtype=np.double)
species = np.concatenate((contrib_species, pad_species))
species = np.asarray(species, dtype=np.intc)
fname = 'atoms.xyz'
write_XYZ(fname, cell, species, coords)
# flag to indicate wheter create neighbor list for an atom
n_pad = pad_coords.shape[0]
n_contrib = contrib_coords.shape[0]
need_neigh = np.concatenate((np.ones(n_contrib), np.zeros(n_pad)))
need_neigh = np.asarray(need_neigh, dtype=np.intc)
# create neighbor list
neigh = nl.create()
try:
neigh.build(coords, influence_dist, cutoffs, need_neigh)
except RuntimeError:
msg = 'Calling "neighlist.build" failed.'
raise KimPyError(msg)
# build again (it will automatically empty previous neigh list)
try:
neigh.build(coords, influence_dist, cutoffs, need_neigh)
except RuntimeError:
msg = 'Calling "neighlist.build" failed.'
raise KimPyError(msg)
# test get neigh function
neigh_list_index = 0
particle = 1
try:
num_neigh, _ = neigh.get_neigh(cutoffs, neigh_list_index, particle)
except RuntimeError:
msg = 'KIM error. Calling "neighlist.get_neigh" failed.'
raise KimPyError(msg)
assert num_neigh == 14
neigh_list_index = 1
particle = 4
try:
num_neigh, _ = neigh.get_neigh(cutoffs, neigh_list_index, particle)
except RuntimeError:
msg = 'KIM error. Calling "neighlist.get_neigh" failed.'
raise KimPyError(msg)
assert num_neigh == 0
# remove the created file
try:
os.remove(fname)
os.remove('kim.log')
except:
pass