Source code for reservingmodels.integrations.actuarialpy

r"""Build reserving inputs from the canonical ``actuarialpy.Experience``.

reservingmodels already requires ``actuarialpy`` (it re-exports the triangle
primitives), so these helpers are always available. They turn a claims-listing
``Experience`` -- one row per claim transaction, carrying an incurred/origin
date and a paid amount -- into a cumulative triangle and, in one step, a fitted
:class:`~reservingmodels.BootstrapODP`.
"""
from __future__ import annotations

import pandas as pd

from actuarialpy import ExperienceSet, resolve_amount

from ..bootstrap import BootstrapODP
from ..core import make_completion_triangle


def _resolve_listing(exp):
    if isinstance(exp, ExperienceSet):
        if len(exp.listings) != 1:
            raise ValueError(
                "pass the listing member explicitly (book['claims']); the set "
                f"has {sorted(exp.listings) or 'no'} named listings"
            )
        (exp,) = exp.listings.values()
    return exp




def triangle_from_experience(
    exp,
    *,
    origin: str,
    valuation: str,
    amount_col: str | None = None,
    cumulative: bool = True,
) -> pd.DataFrame:
    """Cumulative development triangle from a claims-listing ``Experience``.

    ``origin`` is the origin-period column (e.g. accident month) and
    ``valuation`` the transaction/valuation-period column; the paid amount is
    the bound expense role (or ``amount_col``). Thin wrapper over
    ``actuarialpy.make_completion_triangle`` that resolves the amount column
    from the Experience's roles.
    """
    exp = _resolve_listing(exp)
    frame, col = resolve_amount(exp, amount_col)
    return make_completion_triangle(
        frame, origin_col=origin, valuation_col=valuation,
        amount_col=col, cumulative=cumulative,
    )





def fit_bootstrap_from_experience(
    exp, *, origin: str, valuation: str, amount_col: str | None = None
) -> BootstrapODP:
    """Fit :class:`~reservingmodels.BootstrapODP` straight from an Experience."""
    triangle = triangle_from_experience(
        exp, origin=origin, valuation=valuation, amount_col=amount_col
    )
    return BootstrapODP.fit(triangle)