def subgraph_translate3(read_path, write_dir):
'''
This function takes the metal-deficient structure and saves the all connected components (i.e. linkers)
'''
ase_struct = read(read_path)
struct = pm.get_structure(ase_struct)
n_atoms = len(struct.sites)
sg = StructureGraph.with_local_env_strategy(struct, env.JmolNN(tol=.3))
count = 1
for i in range(n_atoms):
for j in range(n_atoms):
if i != j:
try:
sg.alter_edge(i, j, new_weight=count)
except:
pass
count += 1
A = sg.get_subgraphs_as_molecules(use_weights=True)
ls = []
count = 0
for mol in A:
if len(mol.sites) > 4:
smiles = getSmiles(mol)
ls.append(smiles)
path = write_dir + 'mol_' + str(count) + '.xyz'
saveMol(mol, path)
count += 1
return count, ls
def get_mol_pymatgen(dataframe, nbrStruc):
for i in range(nbrStruc):
filename = dataframe.iloc[i,0]
if (filename != "QAPHUK"):
print(filename)
parser = CifParser("../data/cif/{}.cif".format(filename))
structure = parser.get_structures()[0]
sg = StructureGraph.with_local_env_strategy(structure, locenv.JmolNN())
my_molecules = sg.get_subgraphs_as_molecules()
#molecule = MoleculeGraph.with_local_env_strategy(my_molecules,locenv.JmolNN())
#print(molecule)
#crystool.view(my_molecules)
my_molecules = pyxyz.XYZ(my_molecules)
#print(my_molecules)
pyxyz.XYZ.write_file(my_molecules,"../data/xyz_pymatgen/{}.xyz".format(filename))
def __init__(self,
root_dir,
max_num_nbr=12,
radius=8,
nn_method=None,
dmin=0,
step=0.2,
disable_save_torch=False,
random_seed=123):
self.root_dir = root_dir
self.max_num_nbr, self.radius, self.nn_method = max_num_nbr, radius, nn_method
self.disable_save_torch = disable_save_torch
assert os.path.exists(root_dir), 'root_dir does not exist!'
id_prop_file = os.path.join(self.root_dir, 'id_prop.csv')
assert os.path.exists(id_prop_file), 'id_prop.csv does not exist!'
with open(id_prop_file) as f:
reader = csv.reader(f)
self.id_prop_data = [[
x.strip().replace('\ufeff', '') for x in row
] for row in reader]
random.seed(random_seed)
random.shuffle(self.id_prop_data)
atom_init_file = os.path.join(self.root_dir, 'atom_init.json')
assert os.path.exists(atom_init_file), 'atom_init.json does not exist!'
self.ari = AtomCustomJSONInitializer(atom_init_file)
self.gdf = GaussianDistance(dmin=dmin, dmax=self.radius, step=step)
self.torch_data_path = os.path.join(self.root_dir, 'cifdata')
if self.nn_method:
if self.nn_method.lower() == 'minimumvirenn':
self.nn_object = local_env.MinimumVIRENN()
elif self.nn_method.lower() == 'voronoinn':
self.nn_object = local_env.VoronoiNN()
elif self.nn_method.lower() == 'jmolnn':
self.nn_object = local_env.JmolNN()
elif self.nn_method.lower() == 'minimumdistancenn':
self.nn_object = local_env.MinimumDistanceNN()
elif self.nn_method.lower() == 'minimumokeeffenn':
self.nn_object = local_env.MinimumOKeeffeNN()
elif self.nn_method.lower() == 'brunnernn_real':
self.nn_object = local_env.BrunnerNN_real()
elif self.nn_method.lower() == 'brunnernn_reciprocal':
self.nn_object = local_env.BrunnerNN_reciprocal()
elif self.nn_method.lower() == 'brunnernn_relative':
self.nn_object = local_env.BrunnerNN_relative()
elif self.nn_method.lower() == 'econnn':
self.nn_object = local_env.EconNN()
elif self.nn_method.lower() == 'cutoffdictnn':
#requires a cutoff dictionary located in cgcnn/cut_off_dict.txt
self.nn_object = local_env.CutOffDictNN(
cut_off_dict='cut_off_dict.txt')
elif self.nn_method.lower() == 'critic2nn':
self.nn_object = local_env.Critic2NN()
elif self.nn_method.lower() == 'openbabelnn':
self.nn_object = local_env.OpenBabelNN()
elif self.nn_method.lower() == 'covalentbondnn':
self.nn_object = local_env.CovalentBondNN()
elif self.nn_method.lower() == 'crystalnn':
self.nn_object = local_env.CrystalNN()
else:
raise ValueError('Invalid NN algorithm specified')
else:
self.nn_object = None