def read_mol_smiles(mol_dict: Settings) -> Optional[Molecule]:
"""Read a SMILES string."""
try:
mol = _from_smiles(mol_dict.mol)
mol.properties.smiles = Chem.CanonSmiles(mol_dict.mol)
if mol_dict.get('indices'):
for i in mol_dict.indices:
mol[i].properties.anchor = True
canonicalize_mol(mol)
if mol_dict.get('indices'):
mol_dict.indices = tuple(i for i, at in enumerate(mol, 1)
if at.properties.pop('anchor', False))
if mol_dict.guess_bonds and not mol_dict.is_qd:
mol.guess_bonds()
return mol
except Exception as ex:
print_exception('read_mol_smiles', mol_dict.name, ex)
def _set_charge_amsjob(s: Settings, charge: int) -> None:
if s.get('uff') is not None:
return
s.input.ams.system.charge = charge
def _set_charge_cp2kjob(s: Settings, charge: int) -> None:
if s.get('dft') is None:
return
s.input.force_eval.dft.charge = charge
def prep_input(
arg: Settings
) -> Tuple[SettingsDataFrame, SettingsDataFrame, SettingsDataFrame]:
"""Interpret and extract the input settings. Returns a list of ligands and a list of cores.
Parameters
----------
|plams.Settings|_
A settings object containing all (optional) arguments.
Returns
-------
|tuple|_ [|CAT.SettingsDataFrame|_, |CAT.SettingsDataFrame|_, |CAT.SettingsDataFrame|_]
A tuple containing the ligand, core and qd dataframes.
"""
# Interpret arguments
validate_input(arg, validate_only=False)
# Read the input ligands and cores
lig_list = read_mol(arg.get('input_ligands'))
core_list = read_mol(arg.get('input_cores'))
qd_list = read_mol(arg.get('input_qd'))
is_qd = True if qd_list is not None else False
# Raises an error if lig_list or core_list is empty
if is_qd:
if not qd_list:
raise MoleculeError(
'No valid input quantum dots were found, aborting run')
else:
if not lig_list:
raise MoleculeError(
'No valid input ligands were found, aborting run')
elif not core_list:
raise MoleculeError(
'No valid input cores were found, aborting run')
# Store the molecules in dataframes
columns = pd.MultiIndex.from_tuples([MOL], names=['index', 'sub index'])
if is_qd:
ligand_df = core_df = None
qd_df = SettingsDataFrame(index=pd.RangeIndex(len(qd_list)),
columns=columns,
settings=arg)
qd_df[MOL] = qd_list
else:
qd_df = None
ligand_df = SettingsDataFrame(index=pd.RangeIndex(len(lig_list)),
columns=columns,
settings=arg)
core_df = SettingsDataFrame(index=pd.RangeIndex(len(core_list)),
columns=columns.copy(),
settings=arg)
ligand_df[MOL] = lig_list
core_df[MOL] = core_list
return ligand_df, core_df, qd_df
