class_docstr: Running statistics for elements in a stream
  
  Can take single values or iterables
  
  1. Implements Welford's algorithm for computing a running mean
  and standard deviation
  2. Min-Heap to find top-k where k < capacity (kwarg)
  Methods:
      mean    - returns the mean
      std     - returns the std
      meanfull- returns the mean and std of the mean
      topk(k) - returns the kth highest value for k < capacity
code: def update(self, x) -> None:
      if x is None:
          return
      self.k += 1
      newM = self.running_mean + (x - self.running_mean) * 1.0 / self.k
      newS = self.sum_squares + (x - self.running_mean) * (x - newM)
      self.running_mean, self.sum_squares = newM, newS
  
file_path: ReAgent/reagent/core/running_stats.py
imports: import math
label_desc: Use image node_id 2 for calling the RunningStats obj's underlying member method code with example usage: obj.update(x) without return types