code: def build_hypergraph_adjacency(cluster_runs):
      
  
      N_runs = cluster_runs.shape[0]
  
      hypergraph_adjacency = create_membership_matrix(cluster_runs[0])
      for i in range(1, N_runs):
          hypergraph_adjacency = scipy.sparse.vstack([hypergraph_adjacency,
                                                     create_membership_matrix(cluster_runs[i])], 
                                                     format = 'csr')
  
      return hypergraph_adjacency
docs: Return the adjacency matrix to a hypergraph, in sparse matrix representation.
      
      Parameters
      ----------
      cluster_runs : array of shape (n_partitions, n_samples)
      
      Returns
      -------
      hypergraph_adjacency : compressed sparse row matrix
          Represents the hypergraph associated with an ensemble of partitions,
          each partition corresponding to a row of the array 'cluster_runs'
          provided at input.