class_docstr: Zeroes all anomaly scores whose absolute value is less than the threshold.
code: def __init__(
      self,
      alm_threshold: float = None,
      abs_score=True,
      bin_sz=10,
      default_hist_gap_thres=1.2,
  ):
      super().__init__(alm_threshold, abs_score)
      self.bin_sz = bin_sz
      self.default_hist_gap_thres = default_hist_gap_thres
  
imports: import bisect
  import logging
  import numpy
  from merlion.evaluate.anomaly import TSADMetric
  from merlion.post_process.base import PostRuleBase
  from merlion.utils import UnivariateTimeSeries, TimeSeries
label_desc: Use image node_id 1 to create a new AdaptiveThreshold object from inherited base classes: Threshold with example: obj = AdaptiveThreshold(alm_threshold, abs_score, bin_sz, default_hist_gap_thres)