code: def metis(hdf5_file_name, N_clusters_max):
      
  
      file_name = wgraph(hdf5_file_name)
      labels = sgraph(N_clusters_max, file_name)
      subprocess.call(['rm', file_name])
  
      return labels
docs: METIS algorithm by Karypis and Kumar. Partitions the induced similarity graph 
          passed by CSPA.
  
      Parameters
      ----------
      hdf5_file_name : string or file handle
      
      N_clusters_max : int
      
      Returns
      -------
      labels : array of shape (n_samples,)
          A vector of labels denoting the cluster to which each sample has been assigned
          as a result of the CSPA heuristics for consensus clustering.
      
      Reference
      ---------
      G. Karypis and V. Kumar, "A Fast and High Quality Multilevel Scheme for
      Partitioning Irregular Graphs"
      In: SIAM Journal on Scientific Computing, Vol. 20, No. 1, pp. 359-392, 1999.