code: def _rcm_estimate(G, nodelist):
      """Estimate the Fiedler vector using the reverse Cuthill-McKee ordering."""
      import numpy as np
  
      G = G.subgraph(nodelist)
      order = reverse_cuthill_mckee_ordering(G)
      n = len(nodelist)
      index = dict(zip(nodelist, range(n)))
      x = np.ndarray(n, dtype=float)
      for i, u in enumerate(order):
          x[index[u]] = i
      x -= (n - 1) / 2.0
      return x
  
file_path: networkx/networkx/linalg/algebraicconnectivity.py
imports: from functools import partial
  import networkx
  from networkx.utils import not_implemented_for, np_random_state, reverse_cuthill_mckee_ordering
label_desc: Use image node_id 2 for calling a global function with example usage: _rcm_estimate(G, nodelist) and returns: x