import math
from networkx import Graph
from rdkit import Chem
from ._base import Descriptor
class AtomicId(object):
def __init__(self, mol, eps):
G = Graph()
G.add_nodes_from(a.GetIdx() for a in mol.GetAtoms())
for bond in mol.GetBonds():
a = bond.GetBeginAtom()
b = bond.GetEndAtom()
w = a.GetDegree() * b.GetDegree()
G.add_edge(a.GetIdx(), b.GetIdx(), weight=w)
self.G = G
self.lim = int(1.0 / (eps ** 2))
def get_atomic_id(self, s):
self.start = s
self.id = 0.0
self.visited = set()
self.weights = [1]
self._search(s)
return self.id
def _search(self, u):
self.visited.add(u)
for v, d in self.G[u].items():
if v in self.visited:
continue
self.visited.add(v)
w = d['weight'] * self.weights[-1]
self.weights.append(w)
self.id += 1.0 / math.sqrt(w)
if w < self.lim:
self._search(v)
self.visited.remove(v)
self.weights.pop()
def __call__(self):
return [
self.get_atomic_id(i)
for i in range(self.G.number_of_nodes())
]
table = Chem.GetPeriodicTable()
class MolecularIdBase(Descriptor):
explicit_hydrogens = False
require_connected = True
def __reduce_ex__(self, version):
return self.__class__, (self._eps,)
class AtomicIds(MolecularIdBase):
__slots__ = ('_eps',)
def __init__(self, eps=1e-10):
self._eps = eps
def calculate(self, mol):
aid = AtomicId(mol, self._eps)
return [
1 + aid.get_atomic_id(i) / 2.0
for i in range(mol.GetNumAtoms())
]
[docs]class MolecularId(MolecularIdBase):
r"""molecular id descriptor.
:type type: :py:class:`str` or :py:class:`int`
:param type: target of atomic id source
* 'any': normal molecular id(sum of all atomic id)
* 'X': sum of halogen atomic id
* str: atomic symbol
* int: atomic number
:type averaged: bool
:param averaged: averaged by number of atoms
:type _eps: float
:param _eps: internally used
"""
@classmethod
def preset(cls):
return (
cls(s, a)
for s in ['any', 'hetero', 'C', 'N', 'O', 'X']
for a in [False, True]
)
def __str__(self):
n = 'AMID' if self._averaged else 'MID'
if self._type != 'any':
n = '{}_{}'.format(n, self._type)
return n
__slots__ = ('_orig_type', '_averaged', '_eps',)
def __reduce_ex__(self, version):
return self.__class__, (self._orig_type, self._averaged, self._eps)
def __init__(self, type='any', averaged=False, _eps=1e-10):
self._orig_type = self._type = type
self._averaged = averaged
self._eps = _eps
if isinstance(type, str) and type not in ['any', 'hetero', 'X']:
type = table.GetAtomicNumber(type)
if type == 'any':
self._check = lambda _: True
elif type == 'hetero':
self._type = 'h'
self._check = lambda a: a not in set([1, 6])
elif self._type == 'X':
self._check = lambda a: a in set([9, 17, 35, 53, 85, 117])
else:
self._check = lambda a: a == type
def dependencies(self):
return dict(aids=AtomicIds(self._eps))
def calculate(self, mol, aids):
v = float(sum(
aid
for aid, atom in zip(aids, mol.GetAtoms())
if self._check(atom.GetAtomicNum())
))
if self._averaged:
v /= mol.GetNumAtoms()
return v
rtype = float