def test_all_nn_classes(self):
self.assertEqual(MinimumDistanceNN(cutoff=5, get_all_sites=True).get_cn(
self.cscl, 0), 14)
self.assertEqual(MinimumDistanceNN().get_cn(self.diamond, 0), 4)
self.assertEqual(MinimumDistanceNN().get_cn(self.nacl, 0), 6)
self.assertEqual(MinimumDistanceNN().get_cn(self.lifepo4, 0), 6)
self.assertEqual(MinimumDistanceNN(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertEqual(MinimumDistanceNN(tol=0.1).get_cn(self.mos2, 0), 6)
for image in MinimumDistanceNN(tol=0.1).get_nn_images(self.mos2, 0):
self.assertTrue(image in [(0, 0, 0), (0, 1, 0), (-1, 0, 0),
(0, 0, 0), (0, 1, 0), (-1, 0, 0)])
okeeffe = MinimumOKeeffeNN(tol=0.01)
self.assertEqual(okeeffe.get_cn(self.diamond, 0), 4)
self.assertEqual(okeeffe.get_cn(self.nacl, 0), 6)
self.assertEqual(okeeffe.get_cn(self.cscl, 0), 8)
self.assertEqual(okeeffe.get_cn(self.lifepo4, 0), 2)
virenn = MinimumVIRENN(tol=0.01)
self.assertEqual(virenn.get_cn(self.diamond, 0), 4)
self.assertEqual(virenn.get_cn(self.nacl, 0), 6)
self.assertEqual(virenn.get_cn(self.cscl, 0), 8)
self.assertEqual(virenn.get_cn(self.lifepo4, 0), 2)
brunner_recip = BrunnerNN_reciprocal(tol=0.01)
self.assertEqual(brunner_recip.get_cn(self.diamond, 0), 4)
self.assertEqual(brunner_recip.get_cn(self.nacl, 0), 6)
self.assertEqual(brunner_recip.get_cn(self.cscl, 0), 14)
self.assertEqual(brunner_recip.get_cn(self.lifepo4, 0), 6)
brunner_rel = BrunnerNN_relative(tol=0.01)
self.assertEqual(brunner_rel.get_cn(self.diamond, 0), 4)
self.assertEqual(brunner_rel.get_cn(self.nacl, 0), 6)
self.assertEqual(brunner_rel.get_cn(self.cscl, 0), 14)
self.assertEqual(brunner_rel.get_cn(self.lifepo4, 0), 6)
brunner_real = BrunnerNN_real(tol=0.01)
self.assertEqual(brunner_real.get_cn(self.diamond, 0), 4)
self.assertEqual(brunner_real.get_cn(self.nacl, 0), 6)
self.assertEqual(brunner_real.get_cn(self.cscl, 0), 14)
self.assertEqual(brunner_real.get_cn(self.lifepo4, 0), 30)
econn = EconNN()
self.assertEqual(econn.get_cn(self.diamond, 0), 4)
self.assertEqual(econn.get_cn(self.nacl, 0), 6)
self.assertEqual(econn.get_cn(self.cscl, 0), 14)
self.assertEqual(econn.get_cn(self.lifepo4, 0), 6)
voroinn = VoronoiNN(tol=0.5)
self.assertEqual(voroinn.get_cn(self.diamond, 0), 4)
self.assertEqual(voroinn.get_cn(self.nacl, 0), 6)
self.assertEqual(voroinn.get_cn(self.cscl, 0), 8)
self.assertEqual(voroinn.get_cn(self.lifepo4, 0), 6)
crystalnn = CrystalNN()
self.assertEqual(crystalnn.get_cn(self.diamond, 0), 4)
self.assertEqual(crystalnn.get_cn(self.nacl, 0), 6)
self.assertEqual(crystalnn.get_cn(self.cscl, 0), 8)
self.assertEqual(crystalnn.get_cn(self.lifepo4, 0), 6)
def test_all_nn_classes(self):
self.assertAlmostEqual(MinimumDistanceNN().get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(MinimumDistanceNN().get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(
MinimumDistanceNN(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertAlmostEqual(
MinimumDistanceNN(tol=0.1).get_cn(self.mos2, 0), 6)
for image in MinimumDistanceNN(tol=0.1).get_nn_images(self.mos2, 0):
self.assertTrue(image in [(0, 0, 0), (0, 1,
0), (-1, 0,
0), (0, 0,
0), (0, 1,
0), (-1, 0,
0)])
self.assertAlmostEqual(
MinimumOKeeffeNN(tol=0.01).get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(
MinimumOKeeffeNN(tol=0.01).get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(
MinimumOKeeffeNN(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertAlmostEqual(
MinimumVIRENN(tol=0.01).get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(MinimumVIRENN(tol=0.01).get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(MinimumVIRENN(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertAlmostEqual(
BrunnerNN_reciprocal(tol=0.01).get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(
BrunnerNN_reciprocal(tol=0.01).get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(
BrunnerNN_reciprocal(tol=0.01).get_cn(self.cscl, 0), 14)
self.assertAlmostEqual(
BrunnerNN_relative(tol=0.01).get_cn(self.diamond, 0), 16)
self.assertAlmostEqual(
BrunnerNN_relative(tol=0.01).get_cn(self.nacl, 0), 18)
self.assertAlmostEqual(
BrunnerNN_relative(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertAlmostEqual(
BrunnerNN_real(tol=0.01).get_cn(self.diamond, 0), 16)
self.assertAlmostEqual(
BrunnerNN_real(tol=0.01).get_cn(self.nacl, 0), 18)
self.assertAlmostEqual(
BrunnerNN_real(tol=0.01).get_cn(self.cscl, 0), 8)
self.assertAlmostEqual(EconNN(tol=0.01).get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(EconNN(tol=0.01).get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(EconNN(tol=0.01).get_cn(self.cscl, 0), 14)
self.assertAlmostEqual(VoronoiNN(tol=0.5).get_cn(self.diamond, 0), 4)
self.assertAlmostEqual(VoronoiNN(tol=0.5).get_cn(self.nacl, 0), 6)
self.assertAlmostEqual(VoronoiNN(tol=0.5).get_cn(self.cscl, 0), 8)
def get_NNs_pm(atoms, site_idx, NN_method):
"""
Get coordinating atoms to the adsorption site
Args:
atoms (Atoms object): atoms object of MOF
site_idx (int): ASE index of adsorption site
NN_method (string): string representing the desired Pymatgen
nearest neighbor algorithm:
refer to http://pymatgen.org/_modules/pymatgen/analysis/local_env.html
Returns:
neighbors_idx (list of ints): ASE indices of coordinating atoms
"""
#Convert ASE Atoms object to Pymatgen Structure object
bridge = pm_ase.AseAtomsAdaptor()
struct = bridge.get_structure(atoms)
#Select Pymatgen NN algorithm
NN_method = NN_method.lower()
if NN_method == 'vire':
nn_object = MinimumVIRENN()
elif NN_method == 'voronoi':
nn_object = VoronoiNN()
elif NN_method == 'jmol':
nn_object = JmolNN()
elif NN_method == 'min_dist':
nn_object = MinimumDistanceNN()
elif NN_method == 'okeeffe':
nn_object = MinimumOKeeffeNN()
elif NN_method == 'brunner_real':
nn_object = BrunnerNN_real()
elif NN_method == 'brunner_recpirocal':
nn_object = BrunnerNN_reciprocal()
elif NN_method == 'brunner_relative':
nn_object = BrunnerNN_relative()
elif NN_method == 'econ':
nn_object = EconNN()
elif NN_method == 'dict':
#requires a cutoff dictionary located in the pwd
nn_object = CutOffDictNN(cut_off_dict='cut_off_dict.txt')
elif NN_method == 'critic2':
nn_object = Critic2NN()
elif NN_method == 'openbabel':
nn_object = OpenBabelNN()
elif NN_method == 'covalent':
nn_object = CovalentBondNN()
elif NN_method == 'crystal':
nn_object = CrystalNN(porous_adjustment=True)
elif NN_method == 'crystal_nonporous':
nn_object = CrystalNN(porous_adjustment=False)
else:
raise ValueError('Invalid NN algorithm specified')
#Find coordinating atoms
with warnings.catch_warnings():
warnings.simplefilter('ignore')
neighbors = nn_object.get_nn_info(struct, site_idx)
neighbors_idx = []
for neighbor in neighbors:
neighbors_idx.append(neighbor['site_index'])
return neighbors_idx