class_docstr: Fast weighted sampling.
  
  list-like data structure
  append, update are O(log n)
  summation over an interval is O(log n) per query
class_docstr_tok: ["Fast","weighted","sampling",".","list-like","data","structure","append",",","update","are","O","(","log","n",")","summation","over","an","interval","is","O","(","log","n",")","per","query"]
code: def _center(self):
      return (self.bd[0] + self.bd[1]) // 2
  
imports: import collections
  import numpy
  from chainerrl.misc.random import sample_n_k
label_desc: Use image node_id 6 for calling the SumTree obj's underlying member method code with example usage: obj._center() and returns: unknown