code: def _resolve_and_add(nodes1, s_val, final_s, nodes2, t_val, final_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)
docs: 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``.