class_docstr: Indexing edges for fast graph queries
  
  Sorted edges and represent edges in compressed style like csc_matrix or csr_matrix.
  
  Args:
      u: A list of node id to be compressed.
      v: A list of node id that are connected with u.
      num_nodes: The exactive number of nodes.
class_docstr_tok: ["Indexing","edges","for","fast","graph","queries","Sorted","edges","and","represent","edges","in","compressed","style","like","csc_matrix","or","csr_matrix",".","Args",":","u",":","A","list","of","node","id","to","be","compressed",".","v",":","A","list","of","node","id","that","are","connected","with","u.","num_nodes",":","The","exactive","number","of","nodes","."]
docstr: Return the compressed v for given u.
          
code: def view_v(self, u=None):
      """Return the compressed v for given u."""
      if u is None:
          return np.split(self._sorted_v, self._indptr[1:])
      else:
          u = np.array(u, dtype="int64")
          return graph_kernel.slice_by_index(
              self._sorted_v, self._indptr, index=u
          )
  
imports: import os
  import numpy
  import pickle
  import time
  import pgl.graph_kernel
  from collections import defaultdict
label_desc: Use image node_id 3 for calling the EdgeIndex obj's underlying member method code with example usage: obj.view_v(u) and returns: np, graph_kernel