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 _read(self, ix):
      if self._isleaf():
          return self.s
      else:
          c = self._center()
          if ix < c:
              return self.left._read(ix)
          else:
              return self.right._read(ix)
  
imports: import collections
  import numpy
  from chainerrl.misc.random import sample_n_k
label_desc: Use image node_id 12 for calling the SumTree obj's underlying member method code with example usage: obj._read(ix) and returns: self, self, self