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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _update_parameters(s_min, s_max, start0, end0, start1, end1):
 """Update clipped parameter range. .. note:: This is a helper for :func:`clip_range`. Does so by intersecting one of the two fat lines with an edge of the convex hull of the distance polynomial of the curve being clipped. If both of ``s_min`` and ``s_max`` are "unset", then any :math:`s` value that is valid for ``s_min`` would also be valid for ``s_max``. Rather than adding a special case to handle this scenario, **only** ``s_min`` will be updated. In cases where a given parameter :math:`s` would be a valid update for both ``s_min`` and ``s_max`` This function **only** updates ``s_min`` Args: s_min (float):
 Current start of clipped interval. If "unset", this value will be ``DEFAULT_S_MIN``. s_max (float):
 Current end of clipped interval. If "unset", this value will be ``DEFAULT_S_MAX``. start0 (numpy.ndarray):
 A 1D NumPy ``2``-array that is the start vector of one of the two fat lines. end0 (numpy.ndarray):
 A 1D NumPy ``2``-array that is the end vector of one of the two fat lines. start1 (numpy.ndarray):
 A 1D NumPy ``2``-array that is the start vector of an edge of the convex hull of the distance polynomial :math:`d(t)` as an explicit B |eacute| zier curve. end1 (numpy.ndarray):
 A 1D NumPy ``2``-array that is the end vector of an edge of the convex hull of the distance polynomial :math:`d(t)` as an explicit B |eacute| zier curve. Returns: Tuple[float, float]: The (possibly updated) start and end of the clipped parameter range. Raises: NotImplementedError: If the two line segments are parallel. (This case will be supported at some point, just not now.) """

    s, t, success = _geometric_intersection.segment_intersection(
        start0, end0, start1, end1
    )
    if not success:
        raise NotImplementedError(NO_PARALLEL)

    if _helpers.in_interval(t, 0.0, 1.0):
        if _helpers.in_interval(s, 0.0, s_min):
            return s, s_max

        elif _helpers.in_interval(s, s_max, 1.0):
            return s_min, s

    return s_min, s_max