def METHOD_NAME(
    x: ArrayLike,
    log_reference: float = 445,
    linear_reference: float = 0.18,
    negative_gamma: float = 0.6,
    density_per_code_value: float = 0.002,
) -> NDArrayFloat:
    """
    Define the *Josh Pines* style *Pivoted Log* log encoding curve /
    opto-electronic transfer function.
    Parameters
    ----------
    x
        Linear data :math:`x`.
    log_reference
        Log reference.
    linear_reference
        Linear reference.
    negative_gamma
        Negative gamma.
    density_per_code_value
        Density per code value.
    Returns
    -------
    :class:`numpy.ndarray`
        Non-linear data :math:`y`.
    Notes
    -----
    +------------+-----------------------+---------------+
    | **Domain** | **Scale - Reference** | **Scale - 1** |
    +============+=======================+===============+
    | ``x``      | [0, 1]                | [0, 1]        |
    +------------+-----------------------+---------------+
    +------------+-----------------------+---------------+
    | **Range**  | **Scale - Reference** | **Scale - 1** |
    +============+=======================+===============+
    | ``y``      | [0, 1]                | [0, 1]        |
    +------------+-----------------------+---------------+
    References
    ----------
    :cite:`SonyImageworks2012a`
    Examples
    --------
    >>> log_encoding_PivotedLog(0.18)  # doctest: +ELLIPSIS
    0.4349951...
    """
    x = to_domain_1(x)
    y = (
        log_reference
        + np.log10(x / linear_reference)
        / (density_per_code_value / negative_gamma)
    ) / 1023
    return as_float(from_range_1(y))