def test_desc():
fname = "./configs_extxyz/Si.xyz"
conf = Configuration(format="extxyz")
conf.read(fname)
cut_name = "cos"
cut_dists = {"Si-Si": 5.0}
hyperparams = {
"jmax": 2,
"rfac0": 1,
"diagonalstyle": 3,
"rmin0": 0,
"switch_flag": 1,
"bzero_flag": 0,
"weight": {"Si": 1.0},
}
desc = Bispectrum(cut_dists, cut_name, hyperparams)
zeta, dzeta_dr = desc.transform(conf, grad=True)
assert desc.get_size() == 14
assert np.allclose(zeta, zeta_ref)
assert np.allclose(dzeta_dr[0][:2], dzeta_dr_001)
assert np.allclose(dzeta_dr[-1][-2:], dzeta_dr_minus_121)
zeta, dzeta_dr = desc.transform(conf, grad=False)
assert np.allclose(zeta, zeta_ref)
assert dzeta_dr is None
def test_neigh():
conf = Configuration()
fname = "configs_extxyz/bilayer_graphene/bilayer_sep3.36_i0_j0.xyz"
conf.read(fname)
conf.species[0] = "O"
neigh = NeighborList(conf, infl_dist=2, padding_need_neigh=False)
fname = "tmp_test_neighbor.xyz"
cell = conf.get_cell()
PBC = conf.get_PBC()
coords = neigh.get_coords()
species = neigh.get_species()
write_config(fname, cell, PBC, species, coords, fmt="extxyz")
assert np.allclose(coords, target_coords)
assert np.array_equal(species, target_species)
# contributing
for i in range(conf.get_number_of_atoms()):
nei_indices, nei_coords, nei_species = neigh.get_neigh(i)
assert np.allclose(nei_indices, all_indices[i])
# padding
for i in range(conf.get_number_of_atoms(), len(coords)):
nei_indices, nei_coords, nei_species = neigh.get_neigh(i)
assert nei_indices.size == 0
assert nei_coords.size == 0
assert nei_species.size == 0
numneigh, neighlist = neigh.get_numneigh_and_neighlist_1D(
request_padding=False)
np.array_equal(numneigh, all_numneigh)
np.array_equal(neighlist, np.concatenate(all_indices))
def test_lj():
def params_relation(params):
sigma = params.get_value("sigma")
epsilon = params.get_value("epsilon")
epsilon[0] = 2 * sigma[0]
params.set_value("epsilon", epsilon)
model = LennardJones(params_relation_callback=params_relation)
# set optimizing parameters
model.set_opt_params(sigma=[[1.1, "fix"]], epsilon=[[2.1, None, 3.0]])
model.echo_model_params()
model.echo_opt_params()
with warnings.catch_warnings(): # context manager to ignore warning
warnings.simplefilter("ignore")
# set model_params by reading from file (the same as set model_params directly)
filename = "tmp_lj_params.txt"
write_tmp_params(filename)
model.read_opt_params(filename)
delete_tmp_params(filename)
model.echo_model_params()
model.echo_opt_params()
path = (Path(__file__).parents[1].joinpath(
"configs_extxyz/MoS2/MoS2_energy_forces_stress.xyz"))
config = Configuration.from_file(path)
energy_forces_stress(model, config, True, False, False)
energy_forces_stress(model, config, True, True, False)
energy_forces_stress(model, config, True, True, True)
def test_desc():
config = Configuration(format="extxyz")
config.read("./configs_extxyz/Si.xyz")
desc = get_descriptor()
for fit_forces, fit_stress in itertools.product([False, True], [False, True]):
zeta, dzetadr_forces, dzetadr_stress = desc.transform(
config, fit_forces, fit_stress
)
assert np.allclose(zeta, zeta_ref)
if fit_forces:
assert np.allclose(dzetadr_forces[0], dzetadr_forces_ref)
if fit_stress:
assert np.allclose(dzetadr_stress[0], dzetadr_stress_ref)
def test_desc():
test_file_path = Path(__file__).parents[1].joinpath("configs_extxyz")
conf = Configuration.from_file(test_file_path.joinpath("Si.xyz"))
cut_name = "cos"
cut_dists = {"Si-Si": 5.0}
hyperparams = {
"jmax": 2,
"rfac0": 1,
"diagonalstyle": 3,
"rmin0": 0,
"switch_flag": 1,
"bzero_flag": 0,
"weight": {
"Si": 1.0
},
}
desc = Bispectrum(cut_dists, cut_name, hyperparams)
zeta, dzeta_dr = desc.transform(conf, grad=True)
assert desc.get_size() == 14
assert np.allclose(zeta, zeta_ref)
assert np.allclose(dzeta_dr[0][:2], dzeta_dr_001)
assert np.allclose(dzeta_dr[-1][-2:], dzeta_dr_minus_121)
zeta, dzeta_dr = desc.transform(conf, grad=False)
assert np.allclose(zeta, zeta_ref)
assert dzeta_dr is None
def test_desc():
test_file_path = Path(__file__).parents[1].joinpath("configs_extxyz")
config = Configuration.from_file(test_file_path.joinpath("Si.xyz"))
desc = get_descriptor()
for fit_forces, fit_stress in itertools.product([False, True],
[False, True]):
zeta, dzetadr_forces, dzetadr_stress = desc.transform(
config, fit_forces, fit_stress)
assert np.allclose(zeta, zeta_ref)
if fit_forces:
assert np.allclose(dzetadr_forces[0], dzetadr_forces_ref)
if fit_stress:
assert np.allclose(dzetadr_stress[0], dzetadr_stress_ref)
def test_descriptor():
test_file_path = Path(__file__).parents[1].joinpath("configs_extxyz")
fname = test_file_path.joinpath("Si.xyz")
conf = Configuration.from_file(fname)
conf.identifier = str(fname)
configs = [conf, conf]
for normalize, fit_forces, fit_stress, serial in itertools.product(
[False, True], [False, True], [False, True], [False, True]):
desc = ExampleDescriptor(normalize)
desc.generate_fingerprints(configs,
fit_forces,
fit_stress,
use_welford_method=serial)
data = load_fingerprints("fingerprints.pkl")[0]
if normalize:
assert_mean_stdev(desc.mean, desc.stdev, _mean, _stdev)
assert np.allclose(data["zeta"], _normalized_zeta)
if fit_forces:
assert np.allclose(data["dzetadr_forces"],
_normalized_dzetadr_forces)
if fit_stress:
assert np.allclose(data["dzetadr_stress"],
_normalized_dzetadr_stress)
else:
assert_mean_stdev(desc.mean, desc.stdev, None, None)
assert np.allclose(data["zeta"], _zeta)
if fit_forces:
assert np.allclose(data["dzetadr_forces"], _dzetadr_forces)
if fit_stress:
assert np.allclose(data["dzetadr_stress"], _dzetadr_stress)
# check when normalize is True, if mean and stdev is provided by user, it has to be
# correct.
for normalize, fp_path, mean_std_path in itertools.product(
[False, True], ["fp.pkl"], [None, "ms.pkl"]):
delete_file("fingerprints.pkl")
delete_file("fingerprints_mean_and_stdev.pkl")
delete_file("fp.pkl")
delete_file("ms.pkl")
desc = ExampleDescriptor(normalize)
if normalize and mean_std_path is not None:
# will raise exception because the file mean_std_path does not exist
try:
desc.generate_fingerprints(
configs,
fingerprints_filename=fp_path,
fingerprints_mean_stdev_filename=mean_std_path,
)
except DescriptorError:
pass
else:
desc.generate_fingerprints(
configs,
fingerprints_filename=fp_path,
fingerprints_mean_stdev_filename=mean_std_path,
)
if fp_path is None:
fp_path = "fingerprints.pkl"
data = load_fingerprints(fp_path)[0]
if normalize:
assert_mean_stdev(desc.mean, desc.stdev, _mean, _stdev)
assert np.allclose(data["zeta"], _normalized_zeta)
else:
assert_mean_stdev(desc.mean, desc.stdev, None, None)
assert np.allclose(data["zeta"], _zeta)
def test_descriptor():
fname = "./configs_extxyz/Si.xyz"
conf = Configuration(format="extxyz", identifier=fname)
conf.read(fname)
configs = [conf, conf]
# reuse should be the last and `True` should be after `False` so as to test reuse for
# each case of normalize, fit_forces, and fit_stress
for normalize, fit_forces, fit_stress, serial, reuse in itertools.product(
[False, True], [False, True], [False, True], [False, True],
[False, True]):
desc = ExampleDescriptor(normalize)
desc.generate_fingerprints(configs,
fit_forces,
fit_stress,
reuse=reuse,
serial=serial)
data = load_fingerprints("fingerprints.pkl")[0]
if normalize:
assert_mean_stdev(desc.mean, desc.stdev, _mean, _stdev)
assert np.allclose(data["zeta"], _normalized_zeta)
if fit_forces:
assert np.allclose(data["dzetadr_forces"],
_normalized_dzetadr_forces)
if fit_stress:
assert np.allclose(data["dzetadr_stress"],
_normalized_dzetadr_stress)
else:
assert_mean_stdev(desc.mean, desc.stdev, None, None)
assert np.allclose(data["zeta"], _zeta)
if fit_forces:
assert np.allclose(data["dzetadr_forces"], _dzetadr_forces)
if fit_stress:
assert np.allclose(data["dzetadr_stress"], _dzetadr_stress)
# check when normalize is True, if mean and stdev is provided by user, it has to be
# correct.
for normalize, fp_path, mean_std_path in itertools.product(
[False, True], [None, "fp.pkl"], [None, "ms.pkl"]):
delete_file("fingerprints.pkl")
delete_file("fingerprints_mean_and_stdev.pkl")
delete_file("fp.pkl")
delete_file("ms.pkl")
desc = ExampleDescriptor(normalize)
if normalize and mean_std_path is not None:
# will raise exception because the file mean_std_path does not exist
try:
desc.generate_fingerprints(
configs,
fingerprints_path=fp_path,
fingerprints_mean_and_stdev_path=mean_std_path,
)
except DescriptorError:
pass
else:
desc.generate_fingerprints(
configs,
fingerprints_path=fp_path,
fingerprints_mean_and_stdev_path=mean_std_path,
)
if fp_path is None:
fp_path = "fingerprints.pkl"
data = load_fingerprints(fp_path)[0]
if normalize:
assert_mean_stdev(desc.mean, desc.stdev, _mean, _stdev)
assert np.allclose(data["zeta"], _normalized_zeta)
else:
assert_mean_stdev(desc.mean, desc.stdev, None, None)
assert np.allclose(data["zeta"], _zeta)
def test_configuration(e=True, f=False, s=False, order=False):
fname = "./configs_extxyz/MoS2/MoS2"
if e:
fname += "_energy"
if f:
fname += "_forces"
if s:
fname += "_stress"
fname += ".xyz"
config = Configuration(format="extxyz", order_by_species=order)
config.read(fname)
natoms = config.get_number_of_atoms()
cell = config.get_cell()
PBC = config.get_PBC()
species = config.get_species()
coords = config.get_coordinates()
if e:
energy = config.get_energy()
if f:
forces = config.get_forces()
if s:
stress = config.get_stress()
assert natoms == 288
assert np.allclose(
cell,
[
[33.337151, 0.035285, 0.03087],
[0.027151, 25.621674, -0.000664],
[0.027093, 9e-05, 30.262626],
],
)
assert np.allclose(PBC, [1, 1, 1])
if e:
assert energy == -5.302666
if s:
assert np.allclose(stress, [1.1, 2.2, 3.3, 4.4, 5.5, 6.6])
if order:
ref_species = ["Mo", "Mo", "Mo", "Mo", "Mo", "Mo"]
ref_coords = [
[0.051823, -0.017150, 16.736001],
[2.819495, 1.607633, 16.734550],
[5.601008, 0.015314, 16.738646],
]
ref_forces = [
[-0.425324, 0.295866, -0.065479],
[0.245043, -0.061658, 0.264104],
[-0.164382, -0.103679, -0.050262],
]
else:
ref_species = ["Mo", "Mo", "S", "S", "S", "S"]
ref_coords = [
[0.051823, -0.017150, 16.736001],
[2.819495, 1.607633, 16.734550],
[1.901722, -0.004881, 18.317009],
]
ref_forces = [
[-0.425324, 0.295866, -0.065479],
[0.245043, -0.061658, 0.264104],
[0.010127, 0.041539, 0.301571],
]
assert_1d_array(species[:6], ref_species)
assert np.allclose(coords[:3], ref_coords)
if f:
assert np.allclose(forces[:3], ref_forces)
natoms_by_species = config.count_atoms_by_species()
assert natoms_by_species["Mo"] == 96
assert natoms_by_species["S"] == 192
if not e:
energy = None
if not f:
forces = None
if not s:
stress = None
outname = fname.replace("./configs_extxyz/MoS2/MoS2", "tmp_Mos2")
write_extxyz(outname, cell, PBC, species, coords, energy, forces, stress)