poli.objective_repository.rdkit_logp.register.LogPBlackBox

class poli.objective_repository.rdkit_logp.register.LogPBlackBox(string_representation: Literal['SMILES', 'SELFIES'] = 'SMILES', batch_size: Optional[int] = None, parallelize: bool = False, num_workers: Optional[int] = None, evaluation_budget: int = inf)

Log-solubility of a small molecule.

A simple black box that returns the LogP of a molecule. By default, we assume that the result of concatenating the tokens will be a SMILES string, but you can set the context variable “from_selfies” to True to indicate that the input is a SELFIES string.

RDKit’s Chem.MolFromSmiles function and logP are known for failing silently, so we return NaN if the molecule cannot be parsed or if qed returns something other than a float.

Parameters

• string_representation (Literal["SMILES", "SELFIES"], optional) – The string representation to use, by default “SMILES”.

• batch_size (int, optional) – The batch size for processing multiple inputs simultaneously, by default None.

• parallelize (bool, optional) – Flag indicating whether to parallelize the computation, by default False.

• num_workers (int, optional) – The number of workers to use for parallel computation, by default None.

• evaluation_budget (int, optional) – The maximum number of function evaluations. Default is infinity.

from_selfies

Flag indicating whether the input is a SELFIES string.

Type

bool

from_smiles

Flag indicating whether the input is a SMILES string.

Type

bool

_black_box(x, context=None)

The main black box method that performs the computation, i.e. it computes the logP of the molecule in x.

__init__(string_representation: Literal['SMILES', 'SELFIES'] = 'SMILES', batch_size: Optional[int] = None, parallelize: bool = False, num_workers: Optional[int] = None, evaluation_budget: int = inf)

Initializes the LogP black box.

Parameters

• string_representation (Literal["SMILES", "SELFIES"], optional) – The string representation to use, by default “SMILES”.

• batch_size (int, optional) – The batch size for processing multiple inputs simultaneously, by default None.

• parallelize (bool, optional) – Flag indicating whether to parallelize the computation, by default False.

• num_workers (int, optional) – The number of workers to use for parallel computation, by default None.

• evaluation_budget (int, optional) – The maximum number of function evaluations. Default is infinity.

Methods

__init__([string_representation, ...])	Initializes the LogP black box.
reset_evaluation_budget()	Resets the evaluation budget by setting the number of evaluations made to 0.
set_observer(observer)	Set the observer object for recording observations during evaluation.
terminate()	Terminate the black box optimization problem.