Source code for baybe.recommenders.pure.nonpredictive.base

"""Base class for all nonpredictive recommenders."""

import warnings
from abc import ABC

import pandas as pd
from attrs import define

from baybe.exceptions import UnusedObjectWarning
from baybe.objectives.base import Objective
from baybe.recommenders.pure.base import PureRecommender
from baybe.searchspace.core import SearchSpace




@define
class NonPredictiveRecommender(PureRecommender, ABC):
    """Abstract base class for all nonpredictive recommenders."""



    def recommend(  # noqa: D102
        self,
        batch_size: int,
        searchspace: SearchSpace,
        objective: Objective | None = None,
        measurements: pd.DataFrame | None = None,
    ) -> pd.DataFrame:
        # See base class.

        if (measurements is not None) and (len(measurements) != 0):
            warnings.warn(
                f"'{self.recommend.__name__}' was called with a non-empty "
                f"set of measurements but '{self.__class__.__name__}' does not "
                f"utilize any training data, meaning that the argument is ignored.",
                UnusedObjectWarning,
            )
        if objective is not None:
            warnings.warn(
                f"'{self.recommend.__name__}' was called with a an explicit objective "
                f"but '{self.__class__.__name__}' does not "
                f"consider any objectives, meaning that the argument is ignored.",
                UnusedObjectWarning,
            )
        return super().recommend(
            batch_size=batch_size,
            searchspace=searchspace,
            objective=objective,
            measurements=measurements,
        )