Source code for probnum.quad.solvers.policies._policy

"""Abstract base class for BQ policies."""

from __future__ import annotations

import abc
from typing import Optional

import numpy as np

from probnum.quad.solvers._bq_state import BQState
from probnum.typing import IntLike

# pylint: disable=too-few-public-methods, fixme

class Policy(abc.ABC):
    """An abstract class for a policy that acquires nodes for Bayesian quadrature.

        Size of batch of nodes when calling the policy once.

    def __init__(self, batch_size: IntLike) -> None:
        self.batch_size = int(batch_size)

    def requires_rng(self) -> bool:
        """Whether the policy requires a random number generator when called."""
        raise NotImplementedError

[docs] @abc.abstractmethod def __call__( self, bq_state: BQState, rng: Optional[np.random.Generator] ) -> np.ndarray: """Find nodes according to the policy. Parameters ---------- bq_state State of the BQ belief. rng A random number generator. Returns ------- nodes : *shape=(batch_size, input_dim)* -- Nodes found according to the policy. """ raise NotImplementedError