def depict(self, sketch=True, filename=None, ipython=False, optimize=False, optimizemode='std', removeHs=True,
atomlabels=None, highlightAtoms=None, resolution=(400, 200)):
"""
Depicts the molecules. It is possible to save it into an svg file and also generates a jupiter-notebook rendering
Parameters
----------
sketch: bool
Set to True for 2D depiction
filename: str
Set the filename for the svg file
ipython: bool
Set to True to return the jupiter-notebook rendering
optimize: bool
Set to True to optimize the conformation. Works only with 3D.
optimizemode: ['std', 'mmff']
Set the optimization mode for 3D conformation
removeHs: bool
Set to True to hide hydrogens in the depiction
atomlabels: str
Accept any combinations of the following pararemters as unique string '%a%i%c%*' a:atom name, i:atom index,
c:atom formal charge (+/-), *:chiral (* if atom is chiral)
highlightAtoms: list
List of atom to highlight. It can be also a list of atom list, in this case different colors will be used
resolution: tuple of integers
Resolution in pixels: (X, Y)
Returns
-------
ipython_svg: SVG object if ipython is set to True
Example
-------
>>> sm.depict(ipython=True, optimize=True, optimizemode='std') # doctest: +SKIP
>>> sm.depict(ipython=True, sketch=True) # doctest: +SKIP
>>> sm.depict(ipython=True, sketch=True) # doctest: +SKIP
>>> sm.depict(ipython=True, sketch=True, atomlabels="%a%i%c") # doctest: +SKIP
>>> ids = np.intersect1d(sm.get('idx', 'hybridization SP2'), sm.get('idx', 'element C')) # doctest: +SKIP
>>> sm.depict(ipython=True, sketch=True,highlightAtoms=ids.tolist(), removeHs=False) # doctest: +SKIP
"""
from rdkit import Chem
from rdkit.Chem.AllChem import Compute2DCoords, EmbedMolecule, MMFFOptimizeMolecule, ETKDG
from copy import deepcopy
if sketch and optimize:
raise ValueError('Impossible to use optimization in 2D sketch representation')
if optimizemode not in ['std', 'mmff']:
raise ValueError('Optimization mode {} not understood. Can be "std" or "ff"'.format(optimizemode))
elements = self._element
indexes = self._idx
formalcharges = self._formalcharge
chirals = self._chiral
_mol = deepcopy(self._mol)
if sketch:
Compute2DCoords(_mol)
if removeHs:
_mol = Chem.RemoveHs(_mol)
elements = self.get('element', 'element H', invert=True)
indexes = self.get('idx', 'element H', invert=True)
formalcharges = self.get('formalcharge', 'element H', invert=True)
chirals = self.get('chiral', 'element H', invert=True)
_labelsFunc = ['a', 'i', 'c', '*']
if atomlabels is not None:
labels = atomlabels.split('%')[1:]
formalcharges = ['' if c == 0 else "+" if c == 1 else "-" for c in formalcharges]
chirals = ['' if c == '' else '*' for c in chirals]
values = [elements, indexes, formalcharges, chirals]
idxs = [_labelsFunc.index(l) for l in labels]
labels_required = [values[i] for i in idxs]
atomlabels = ["".join([str(i) for i in a]) for a in list(zip(*labels_required))]
if optimize:
if optimizemode == 'std':
EmbedMolecule(_mol, ETKDG())
elif optimizemode == 'mmff':
MMFFOptimizeMolecule(_mol)
return _depictMol(_mol, filename=filename, ipython=ipython, atomlabels=atomlabels,
highlightAtoms=highlightAtoms, resolution=resolution)
def depict(
self,
ids=None,
sketch=True,
filename=None,
ipython=False,
optimize=False,
optimizemode="std",
removeHs=True,
legends=None,
highlightAtoms=None,
mols_perrow=3,
):
"""
Depicts the molecules into a grid. It is possible to save it into an svg file and also generates a
jupiter-notebook rendering
Parameters
----------
ids: list
The index of the molecules to depict
sketch: bool
Set to True for 2D depiction
filename: str
Set the filename for the svg file
ipython: bool
Set to True to return the jupiter-notebook rendering
optimize: bool
Set to True to optimize the conformation. Works only with 3D.
optimizemode: ['std', 'mmff']
Set the optimization mode for 3D conformation
removeHs: bool
Set to True to hide hydrogens in the depiction
legends: str
The name to used for each molecule. Can be 'names':the name of themselves; or 'items': a incremental id
highlightAtoms: list
A List of atom to highligh for each molecule. It can be also a list of atom list, in this case different
colors will be used
mols_perrow: int
The number of molecules to depict per row of the grid
Returns
-------
ipython_svg: SVG object if ipython is set to True
"""
from rdkit.Chem.AllChem import (
Compute2DCoords,
EmbedMolecule,
MMFFOptimizeMolecule,
ETKDG,
)
from rdkit.Chem import RemoveHs
from moleculekit.smallmol.util import depictMultipleMols
if sketch and optimize:
raise ValueError(
"Impossible to use optmization in 2D sketch representation")
if legends is not None and legends not in ["names", "items"]:
raise ValueError('The "legends" should be "names" or "items"')
_smallmols = self.getMols(ids)
if ids is None:
_mols = [m._mol for m in self._mols]
else:
_mols = [m._mol for m in self.getMols(ids)]
if highlightAtoms is not None:
if len(highlightAtoms) != len(_mols):
raise ValueError(
"The highlightAtoms {} should have the same length of the "
"mols {}".format(len(highlightAtoms), len(_mols)))
if sketch:
for _m in _mols:
Compute2DCoords(_m)
if removeHs:
_mols = [RemoveHs(_m) for _m in _mols]
# activate 3D coords optimization
if optimize:
if optimizemode == "std":
for _m in _mols:
EmbedMolecule(_m)
elif optimizemode == "mmff":
for _m in _mols:
MMFFOptimizeMolecule(_m, ETKDG())
legends_list = []
if legends == "names":
legends_list = [_m.getProp("ligname") for _m in _smallmols]
elif legends == "items":
legends_list = [str(n + 1) for n in range(len(_smallmols))]
return depictMultipleMols(
_mols,
ipython=ipython,
legends=legends_list,
highlightAtoms=highlightAtoms,
filename=filename,
mols_perrow=mols_perrow,
)