def test_sk_partial(self):
# TODO: this test fails with python 3 (small deviations)
f = os.path.join(self.reference_path, 'kalj-small.xyz')
ref_value = {
'A': numpy.array([0.078218, 2.896436, 0.543363]),
'B': numpy.array([0.867164, 0.869868, 0.981121]),
'AB': numpy.array([-0.1907, 0.399360, 0.050480])
}
for species in ['A', 'B']:
with trajectory.TrajectoryXYZ(f) as t:
t.add_callback(filter_species, species)
p = postprocessing.StructureFactor(t, [4, 7.3, 10])
p.compute()
self.assertLess(deviation(p.value, ref_value[species]), 1e-2)
with trajectory.TrajectoryXYZ(f) as t:
sk = postprocessing.Partial(postprocessing.StructureFactor,
['A', 'B'], t, [4, 7.3, 10])
sk.compute()
self.assertLess(
deviation(sk.partial[('A', 'A')].value, ref_value['A']), 1e-2)
self.assertLess(
deviation(sk.partial[('B', 'B')].value, ref_value['B']), 1e-2)
self.assertLess(
deviation(sk.partial[('A', 'B')].value, ref_value['AB']), 1e-2)
def test_sk_random(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
t.add_callback(filter_random, 75)
p = postprocessing.StructureFactor(t, [4, 7.3, 10, 30.0], nk=40)
p.compute()
t.close()
def test_sk_fixgrid(self):
# TODO: this test fails with python 3 (small deviations)
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
p = postprocessing.StructureFactor(t, [4, 7.3, 10])
p.compute()
ref_value = numpy.array(
[0.083411717745282138, 2.76534619194135, 0.67129958432631986])
self.assertLess(deviation(p.value, ref_value), 0.04)
def test_sk_variable_cell(self):
# TODO: this test has no assertion
def deformation(s, scale=0.01):
# Note this random scaling changes every time read is called,
# even for the same sample
x = 1 + (random.random() - 0.5) * scale
s.cell.side *= x
for p in s.particle:
p.position *= x
return s
f = os.path.join(self.reference_path, 'kalj-small.xyz')
with trajectory.TrajectoryXYZ(f) as t:
p = postprocessing.StructureFactor(t, list(range(1, 10)))
p.compute()
with trajectory.TrajectoryXYZ(f) as t:
t.add_callback(deformation, 1e-3)
p = postprocessing.StructureFactor(t, list(range(1, 10)))
p.compute()
def test_sk_update(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
p = postprocessing.StructureFactor(t,
kmin=-1,
kmax=4,
ksamples=3,
dk=0.2)
p.do(update=False)
p = postprocessing.StructureFactor(t,
kmin=-1,
kmax=4,
ksamples=3,
dk=0.2)
p.do(update=True)
ref_value = numpy.array(
[0.075820086512828039, 0.065300213310725302, 0.082485082309989494])
self.assertLess(deviation(p.value, ref_value), 0.04)
t.close()
def test_sk_field(self):
"""
Test that S(k) with a field that is 0 if id=A and 1 if id=B gives
the BB partial structure factor.
"""
# TODO: this test fails with python 3 because of a weird issue with xyz trajectory in atooms (_fallback)
f = os.path.join(self.reference_path, 'kalj-small.xyz')
ff = os.path.join(self.reference_path, 'kalj-small-field.xyz')
t = trajectory.TrajectoryXYZ(f)
p = postprocessing.StructureFactor(t, [4, 7.3, 10],
trajectory_field=ff)
p.compute()
# We multiply by x because the S(k) is normalized to 1/N
from atooms.system.particle import composition
x = composition(t[0].particle)['B'] / float(len(t[0].particle))
ref_value = x * numpy.array(
[0.86716496871363735, 0.86986885176760842, 0.98112175463699136])
self.assertLess(deviation(p.value, ref_value), 1e-2)
def test_sk_field(self):
"""
Test that S(k) with a field that is 0 if id=A and 1 if id=B gives
the BB partial structure factor.
"""
f = os.path.join(self.reference_path, 'kalj-small.xyz')
ff = os.path.join(self.reference_path, 'kalj-small-field.xyz')
th = trajectory.TrajectoryXYZ(f)
tt = trajectory.TrajectoryXYZ(ff)
p = postprocessing.StructureFactor(th, [4, 7.3, 10])
p.add_weight(trajectory=tt, field='field_B')
p.compute()
# We multiply by x because the S(k) is normalized to 1/N
from atooms.system.particle import composition
x = composition(th[0].particle)['B'] / float(len(th[0].particle))
ref_value = x * numpy.array(
[0.86716496871363735, 0.86986885176760842, 0.98112175463699136])
self.assertLess(deviation(p.value, ref_value), 1e-2)
th.close()
tt.close()