class_docstr: real time speed stat
class_docstr_tok: ["real","time","speed","stat"]
code: def mean(self, timestamp):
      timestamp = timestamp / self.sample_range
      ver = int(timestamp * self.bucket_num // 1)
      num_n_count = [
          (n, s)
          for n, s, v in zip(
              self.bucket, self.bucket_sample, self.bucket_ver
          )
          if v >= ver - self.bucket_num and s > 0
      ]
      return (
          sum(n for n, _ in num_n_count)
          / sum(s for _, s in num_n_count)
          if num_n_count
          else math.nan
      )
  
imports: import asyncio
  import math
  import time
  from collections import defaultdict
  from tabulate import tabulate
label_desc: Use image node_id 4 for calling the DynamicBucketMerge obj's underlying member method code with example usage: obj.mean(timestamp) and returns: unknown