Source code for compml.bayesian.posteriors.base

"""Base class for posterior distributions."""

from abc import ABC, abstractmethod




class Posterior(ABC):
    """Abstract base class for posterior distributions."""

    def __init__(self, rope: float):
        """Initialize the Posterior class.

        Parameters
        ----------
        rope : float
            Width of the ROPE.
        """
        self.__validate_arguments(rope=rope)
        self.rope = rope



    def compute_probs(self) -> dict[str, float]:
        """Compute the posterior probabilities for the ROPE.

        Returns
        -------
        dict
            Posterior probabilities with the keys ``"p_left"``, ``"p_right"`` and  ``"p_rope"``
            if a ROPE is being used.
        """
        return (
            self._compute_probs_with_rope()
            if self.rope != 0.0
            else self._compute_probs_without_rope()
        )




    @abstractmethod
    def plot(self):
        """Plot the posterior distribution."""
        pass


    @abstractmethod
    def _compute_probs_with_rope(self):
        """Compute the posterior probabilities with the ROPE.

        Returns
        -------
        dict
            Posterior probabilities with the keys ``"p_left"``, ``"p_rope"``, and ``"p_right"``.
        """
        pass

    @abstractmethod
    def _compute_probs_without_rope(self):
        """Compute the posterior probabilities without the ROPE.

        Returns
        -------
        dict
            Posterior probabilities with the keys ``"p_left"``, ``"p_right"``.
        """
        pass

    def __validate_arguments(self, rope: float):
        """Validate the arguments for the Posterior class.

        Raises
        ------
        ValueError
            If the arguments are invalid.
        """
        if not isinstance(rope, (float, int)) or rope < 0:
            raise ValueError(f"rope must be a non-negative number, got {rope}")