code: def normalized_mutual_weight(G, u, v, norm=sum, weight=None):
      """Returns normalized mutual weight of the edges from `u` to `v`
      with respect to the mutual weights of the neighbors of `u` in `G`.
  
      `norm` specifies how the normalization factor is computed. It must
      be a function that takes a single argument and returns a number.
      The argument will be an iterable of mutual weights
      of pairs ``(u, w)``, where ``w`` ranges over each (in- and
      out-)neighbor of ``u``. Commons values for `normalization` are
      ``sum`` and ``max``.
  
      `weight` can be ``None`` or a string, if None, all edge weights
      are considered equal. Otherwise holds the name of the edge
      attribute used as weight.
  
      """
      scale = norm(
          mutual_weight(G, u, w, weight)
          for w in set(nx.all_neighbors(G, u))
      )
      return 0 if scale == 0 else mutual_weight(G, u, v, weight) / scale
  
imports: import networkx
label_desc: Use image node_id 2 for calling a global function with example usage: normalized_mutual_weight(G, u, v, norm, weight) and returns: unknown