def test_cn(self):
nn = Critic2NN()
def test_cn(self):
nn = Critic2NN()
self.assertEqual(nn.get_cn(self.diamond, 0), 4)
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