code: def normalized_laplacian_spectrum(G, weight="weight"):
      """Return eigenvalues of the normalized Laplacian of G
  
      Parameters
      ----------
      G : graph
         A NetworkX graph
  
      weight : string or None, optional (default='weight')
         The edge data key used to compute each value in the matrix.
         If None, then each edge has weight 1.
  
      Returns
      -------
      evals : NumPy array
        Eigenvalues
  
      Notes
      -----
      For MultiGraph/MultiDiGraph, the edges weights are summed.
      See to_numpy_array for other options.
  
      See Also
      --------
      normalized_laplacian_matrix
      """
      import scipy as sp
  
      return sp.linalg.eigvalsh(
          nx.normalized_laplacian_matrix(G, weight=weight).todense()
      )
  
imports: import networkx
label_desc: Use image node_id 2 for calling a global function with example usage: normalized_laplacian_spectrum(G, weight) and returns: sp