class_docstr: Basic topological (non-weighted) directed Graph class
  
  Member variables:
  
  * V (int > 0): the number of vertices
  * E (int >= 0): the number of edges
  
  Properties:
  
  * vertices (list, type=int, shape=(V,))  vertices id
  * edges (list, type=int, shape=(E,2)): edges as vertices id tuples
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docstr: returns the adjacency matrix of the graph as a sparse coo matrix
  
  Returns
  -------
  adj: scipy.sparse matrix instance,
      that encodes the adjacency matrix of self
docstr_tok: ["returns","the","adjacency","matrix","of","the","graph","as","a","sparse","coo","matrix","Returns","--","--","--","-","adj",":","scipy.sparse","matrix","instance",",","that","encodes","the","adjacency","matrix","of","self"]
code: def adjacency(self):
      """returns the adjacency matrix of the graph as a sparse coo matrix
  
      Returns
      -------
      adj: scipy.sparse matrix instance,
          that encodes the adjacency matrix of self
      """
      if self.E > 0:
          i = self.edges[:, 0]
          j = self.edges[:, 1]
          adj = coo_matrix(
              (np.ones(self.E), (i, j)), shape=(self.V, self.V)
          )
      else:
          adj = coo_matrix((self.V, self.V))
      return adj
  
imports: import numpy
  from scipy.sparse import coo_matrix
label_desc: Use image node_id 9 for calling the Graph obj's underlying member method code with example usage: obj.adjacency() and returns: adj