def test_relax():
"""
Test that a static relaxation that requires multiple neighbor list
rebuilds can be carried out successfully. This is verified by relaxing
an icosahedral cluster of atoms and checking that the relaxed energy
matches a known precomputed value for an example model.
"""
import numpy as np
from ase.cluster import Icosahedron
from pytest import importorskip
importorskip('kimpy')
from ase.calculators.kim import KIM
from ase.optimize import BFGS
energy_ref = -0.5420939378624228 # eV
# Create structure and calculator
atoms = Icosahedron("Ar", latticeconstant=3.0, noshells=2)
calc = KIM("ex_model_Ar_P_Morse_07C")
atoms.set_calculator(calc)
opt = BFGS(atoms, logfile=None)
opt.run(fmax=0.05)
assert np.isclose(atoms.get_potential_energy(), energy_ref)
def test_utilities():
import numpy as np
from ase.cluster import Icosahedron
from ase.calculators.emt import EMT
from ase.optimize.fire import FIRE
from ase.lattice.compounds import L1_2
from ase.ga.utilities import get_rdf
eps = 1e-5
atoms = Icosahedron('Cu', 3)
atoms.numbers[[0, 13, 15, 16, 18, 19, 21, 22, 24, 25, 27, 28, 30]] = 79
atoms.set_calculator(EMT())
opt = FIRE(atoms, logfile=None)
opt.run(fmax=0.05)
rmax = 8.
nbins = 5
rdf, dists = get_rdf(atoms, rmax, nbins)
calc_dists = np.arange(rmax / (2 * nbins), rmax, rmax / nbins)
assert all(abs(dists - calc_dists) < eps)
calc_rdf = [0., 0.84408157, 0.398689, 0.23748934, 0.15398546]
assert all(abs(rdf - calc_rdf) < eps)
dm = atoms.get_all_distances()
s = np.zeros(5)
for c in [(29, 29), (29, 79), (79, 29), (79, 79)]:
inv_norm = len(np.where(atoms.numbers == c[0])[0]) / len(atoms)
s += get_rdf(
atoms, rmax, nbins, elements=c, distance_matrix=dm,
no_dists=True) * inv_norm
assert all(abs(s - calc_rdf) < eps)
AuAu = get_rdf(atoms,
rmax,
nbins,
elements=(79, 79),
distance_matrix=dm,
no_dists=True)
assert all(abs(AuAu[-2:] - [0.12126445, 0.]) < eps)
bulk = L1_2(['Au', 'Cu'], size=(3, 3, 3), latticeconstant=2 * np.sqrt(2))
rdf = get_rdf(bulk, 4.2, 5)[0]
calc_rdf = [0., 0., 1.43905094, 0.36948605, 1.34468694]
assert all(abs(rdf - calc_rdf) < eps)
from __future__ import division
import numpy as np
from ase.cluster import Icosahedron
from ase.calculators.emt import EMT
from ase.optimize.fire import FIRE
from ase.lattice.compounds import L1_2
from ase.ga.utilities import get_rdf
eps = 1e-5
atoms = Icosahedron('Cu', 3)
atoms.numbers[[0, 13, 15, 16, 18, 19, 21, 22, 24, 25, 27, 28, 30]] = 79
atoms.set_calculator(EMT())
opt = FIRE(atoms, logfile=None)
opt.run(fmax=0.05)
rmax = 8.
nbins = 5
rdf, dists = get_rdf(atoms, rmax, nbins)
calc_dists = np.arange(rmax / (2 * nbins), rmax, rmax / nbins)
assert all(abs(dists - calc_dists) < eps)
calc_rdf = [0., 0.84408157, 0.398689, 0.23748934, 0.15398546]
assert all(abs(rdf - calc_rdf) < eps)
dm = atoms.get_all_distances()
s = np.zeros(5)
for c in [(29, 29), (29, 79), (79, 29), (79, 79)]:
inv_norm = len(np.where(atoms.numbers == c[0])[0]) / len(atoms)
s += get_rdf(
"""
Test that a static relaxation that requires multiple neighbor list
rebuilds can be carried out successfully. This is verified by relaxing
an icosahedral cluster of atoms and checking that the relaxed energy
matches a known precomputed value for an example model.
"""
import numpy as np
from ase.cluster import Icosahedron
from ase.calculators.kim import KIM
from ase.optimize import BFGS
energy_ref = -0.5420939378624228 # eV
# Create structure and calculator
atoms = Icosahedron("Ar", latticeconstant=3.0, noshells=2)
calc = KIM("ex_model_Ar_P_Morse_07C")
atoms.set_calculator(calc)
opt = BFGS(atoms, logfile=None)
opt.run(fmax=0.05)
assert np.isclose(atoms.get_potential_energy(), energy_ref)
from __future__ import division
import numpy as np
from ase.cluster import Icosahedron
from ase.calculators.emt import EMT
from ase.optimize.fire import FIRE
from ase.lattice.compounds import L1_2
from ase.ga.utilities import get_rdf
eps = 1e-5
atoms = Icosahedron('Cu', 3)
atoms.numbers[[0, 13, 15, 16, 18, 19, 21, 22, 24, 25, 27, 28, 30]] = 79
atoms.set_calculator(EMT())
opt = FIRE(atoms, logfile=None)
opt.run(fmax=0.05)
rmax = 8.
nbins = 5
rdf, dists = get_rdf(atoms, rmax, nbins)
calc_dists = np.arange(rmax / (2 * nbins), rmax, rmax / nbins)
assert all(abs(dists - calc_dists) < eps)
calc_rdf = [0., 0.84408157, 0.398689, 0.23748934, 0.15398546]
assert all(abs(rdf - calc_rdf) < eps)
dm = atoms.get_all_distances()
s = np.zeros(5)
for c in [(29, 29), (29, 79), (79, 29), (79, 79)]:
inv_norm = len(np.where(atoms.numbers == c[0])[0]) / len(atoms)
s += get_rdf(atoms, rmax, nbins, elements=c,
