_estimate_rank_of_mrca_between_unbiased.py

def _estimate_rank_of_mrca_between_unbiased(
    first: HereditaryStratigraphicColumn,
    second: HereditaryStratigraphicColumn,
) -> typing.Optional[float]:
    ranks_of_retained_commonality_between = [
        *iter_ranks_of_retained_commonality_between_generic(first, second)
    ]
    if not ranks_of_retained_commonality_between:
        return None

    rank_of_first_retained_disparity_between = (
        calc_rank_of_first_retained_disparity_between(
            first,
            second,
            confidence_level=0.1,  # TODO why can't this be set to 0.0?
        )
    )
    waypoints_descending = [
        rank_of_first_retained_disparity_between - 1,
        *reversed(ranks_of_retained_commonality_between),
    ]
    exclusive_ub_correction = 1 / 2
    expected_ranks = (
        np.array(
            [
                waypoints_descending[:-1],
                waypoints_descending[1:],
            ]
        ).mean(axis=1)
        - exclusive_ub_correction
    )

    base = 1 / 2 ** first.GetStratumDifferentiaBitWidth()
    weights = np.logspace(
        0,
        len(expected_ranks),
        base=base,
        num=len(expected_ranks),
        endpoint=False,
    )
    # index of weights corresponds to num spurious collisions

    return np.average(expected_ranks, weights=weights)