title: Performance issue to calculate node_centrality and edge_centrality on large Data
body: <p>My Local Osm File contains filtered data (Filtered through OSMFilter) of Germany and that contains only following highways</p>
  
  <ol>
  <li>motorway</li>
  <li>motorway_link</li>
  <li>trunk</li>
  <li>trunk_link</li>
  <li>primary</li>
  <li>primary_link</li>
  <li>secondary</li>
  <li>secondary_link</li>
  <li>tertiary</li>
  <li>tertiary_link</li>
  <li>residential</li>
  <li>living_street</li>
  </ol>
  
  <p>I am trying to simplify graph and extracting important information to minimize my road network more. I have followed following steps</p>
  
  <ol>
  <li>G3 = ox.simplify_graph(G, strict=True)</li>
  <li>G3 = ox.add_edge_lengths(G3);</li>
  <li>G3 = ox.remove_isolated_nodes(G3);</li>
  <li>node_centrality = nx.closeness_centrality(G3)</li>
  <li>nx.set_node_attributes(G3, node_centrality, 'node_centrality')</li>
  <li>edge_centrality = nx.closeness_centrality(nx.line_graph(G3))</li>
  <li>nx.set_edge_attributes(G3, edge_centrality, 'edge_centrality')</li>
  <li>ox.save_load.save_graphml(G3,..,..,..)</li>
  </ol>
  
  <p>It have waited around a all day to see output in GraphML but did not see any progress . . 
  I think edge_centrality and edge_centrality are hight computational functions but how I can use these functions for my data ?</p>