def test_fkt_random(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
with trajectory.TrajectoryXYZ(f) as t:
s = t[0]
ids = random.sample(range(len(s.particle)), len(s.particle))
t.add_callback(filter_selected_ids, ids)
p = postprocessing.IntermediateScattering(t, [4, 7.3, 10], nk=40)
p.compute()
def test_fkt_partial(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
p = postprocessing.IntermediateScattering(t, [4, 7.3, 10], nk=40)
p.add_filter(filter_species, 'A')
p.compute()
p.analyze()
tau = []
for key in sorted(p.analysis['relaxation times tau']):
tau.append(p.analysis['relaxation times tau'][key])
self.assertLess(abs(tau[0] - 2.2792074711157104), 0.4)
self.assertLess(abs(tau[1] - 5.8463508731564975), 0.4)
self.assertLess(abs(tau[2] - 0.85719855804743605), 0.4)
t.close()
def test_fkt_2d(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
t.add_callback(filter_2d)
p = postprocessing.IntermediateScattering(t, [4, 7.3, 10], nk=100)
p.add_filter(filter_species, 'A')
p.compute()
p.analyze()
tau = []
for key in sorted(p.analysis['relaxation times tau']):
tau.append(p.analysis['relaxation times tau'][key])
self.assertLess(abs(tau[0] - 1.1341521365187757), 0.04)
self.assertLess(abs(tau[1] - 5.83114954720099), 0.04)
self.assertLess(abs(tau[2] - 0.859950963462569), 0.04)
t.close()
def test_fkt_partial(self):
f = os.path.join(self.reference_path, 'kalj-small.xyz')
t = trajectory.TrajectoryXYZ(f)
p = postprocessing.IntermediateScattering(t, [4, 7.3, 10], nk=40)
p.add_filter(filter_species, 'A')
p.compute()