def test_dense_forces(self):
orig_a = io.read('eam_crash2.poscar')
c = TabulatedAlloyEAM(fn='Cu_mishin1.eam.alloy')
for fac in [0.2, 0.3, 0.4, 0.5]:
a = orig_a.copy()
a.set_cell(fac * a.cell, scale_atoms=True)
a.set_calculator(c)
ffd, f0, maxdf = test_forces(a, dx=dx)
if maxdf > tol:
nfail += 1
print("forces .failed.")
print("max(df) = %f" % maxdf)
print("f - from potential")
for i, f in enumerate(f0):
print(i, f)
print("f - numerically")
for i, f in enumerate(ffd):
print(i, f)
print("difference between the above")
for i, f in enumerate(f0 - ffd):
print(i, f)
self.assertTrue(maxdf < tol)
def test_crash1(self):
a = io.read('eam_crash1.poscar')
a.set_calculator(TabulatedAlloyEAM(fn='Cu_mishin1.eam.alloy'))
a.get_potential_energy()
def test_mask_decomposition_tabulated_alloy_eam(self):
a = FaceCenteredCubic('Au', size=[2, 2, 2])
c = TabulatedAlloyEAM(fn='Au-Grochola-JCP05.eam.alloy')
a.set_calculator(c)
self.random_mask_test(a)
import numpy as np
from ase.constraints import UnitCellFilter
from ase.lattice.cubic import FaceCenteredCubic
from ase.optimize import FIRE
from ase.utils.eos import EquationOfState
from atomistica import TabulatedAlloyEAM
###
n = 2
a = FaceCenteredCubic('Au', size=[n, n, n])
x0 = a.cell[0, 0]/n
c = TabulatedAlloyEAM(fn='Au-Grochola-JCP05.eam.alloy')
a.set_calculator(c)
# Vary volume and fit minimum
def en(a, x):
a.set_cell([x, x, x], scale_atoms=True)
return a.get_potential_energy()
x = np.linspace(0.9*x0, 1.1*x0, 101)
e = [ en(a, n*_x)/(n**3) for _x in x ]
eos = EquationOfState(x**3, e)
v0, e0, B = eos.fit()
print 'lattice constant (from equation of state) =', v0**(1./3)
# Keep cell rectangular during optimization
FIRE(UnitCellFilter(a, mask=[1,1,1,0,0,0]), logfile=None).run(fmax=0.0001)
def test_rotation(self):
if not atomistica:
print('Atomistica not available. Skipping test.')
return
for make_atoms, calc in [
# ( lambda a0,x :
# FaceCenteredCubic('He', size=[1,1,1],
# latticeconstant=3.5 if a0 is None else a0,
# directions=x),
# LJCut(epsilon=10.2, sigma=2.28, cutoff=5.0, shift=True) ),
(lambda a0, x: FaceCenteredCubic(
'Au', size=[1, 1, 1], latticeconstant=a0, directions=x),
TabulatedAlloyEAM(fn='Au-Grochola-JCP05.eam.alloy')),
(lambda a0, x: Diamond(
'Si', size=[1, 1, 1], latticeconstant=a0, directions=x),
Kumagai())
#( lambda a0,x : FaceCenteredCubic('Au', size=[1,1,1],
# latticeconstant=a0, directions=x),
# EAM(potential='Au-Grochola-JCP05.eam.alloy') ),
]:
a = make_atoms(None, [[1, 0, 0], [0, 1, 0], [0, 0, 1]])
a.set_calculator(calc)
FIRE(StrainFilter(a, mask=[1,1,1,0,0,0]), logfile=None) \
.run(fmax=self.fmax)
latticeconstant = np.mean(a.cell.diagonal())
C6 = measure_triclinic_elastic_constants(a,
delta=self.delta,
fmax=self.fmax)
C11, C12, C44 = Voigt_6x6_to_cubic(C6) / GPa
el = CubicElasticModuli(C11, C12, C44)
C_m = measure_triclinic_elastic_constants(
a, delta=self.delta, fmax=self.fmax) / GPa
self.assertArrayAlmostEqual(el.stiffness(), C_m, tol=0.01)
for directions in [[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
[[0, 1, 0], [0, 0, 1], [1, 0, 0]],
[[1, 1, 0], [0, 0, 1], [1, -1, 0]],
[[1, 1, 1], [-1, -1, 2], [1, -1, 0]]]:
a, b, c = directions
directions = np.array(
[np.array(x) / np.linalg.norm(x) for x in directions])
a = make_atoms(latticeconstant, directions)
a.set_calculator(calc)
C = el.rotate(directions)
C_check = el._rotate_explicit(directions)
C_check2 = rotate_cubic_elastic_constants(
C11, C12, C44, directions)
C_check3 = \
rotate_elastic_constants(cubic_to_Voigt_6x6(C11, C12, C44),
directions)
self.assertArrayAlmostEqual(C, C_check, tol=1e-6)
self.assertArrayAlmostEqual(C, C_check2, tol=1e-6)
self.assertArrayAlmostEqual(C, C_check3, tol=1e-6)
C_m = measure_triclinic_elastic_constants(
a, delta=self.delta, fmax=self.fmax) / GPa
self.assertArrayAlmostEqual(C, C_m, tol=1e-2)