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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 _resolve_and_add(nodes1, s_val, final_s, nodes2, t_val, final_t):
 """Resolve a computed intersection and add to lists. We perform one Newton step to deal with any residual issues of high-degree polynomial solves (one of which depends on the already approximate ``x_val, y_val``). Args: nodes1 (numpy.ndarray):
 The nodes in the first curve. s_val (float):
 The approximate intersection parameter along ``nodes1``. final_s (List[float]):
 The list of accepted intersection parameters ``s``. nodes2 (numpy.ndarray):
 The nodes in the second curve. t_val (float):
 The approximate intersection parameter along ``nodes2``. final_t (List[float]):
 The list of accepted intersection parameters ``t``. """

    s_val, t_val = _intersection_helpers.newton_refine(
        s_val, nodes1, t_val, nodes2
    )
    s_val, success_s = _helpers.wiggle_interval(s_val)
    t_val, success_t = _helpers.wiggle_interval(t_val)
    if not (success_s and success_t):
        return

    final_s.append(s_val)
    final_t.append(t_val)