class_docstr: Estimator of the error from DP pipeline from DatasetHistograms.
  
  The recommended way to create this object is to use create_error_estimator.
  It works only for COUNT and PRIVACY_ID_COUNT.
  
  Partition selection error is not implemented yet. Now only contribution
  bounding and noise error are taken into consideration.
code: def get_ratio_dropped_linf(self, linf_bound: int) -> float:
      return self._get_ratio_dropped(
          self._linf_ratios_dropped, linf_bound
      )
  
file_path: pipelinedp/pipeline_dp/dataset_histograms/histogram_error_estimator.py
imports: import pipeline_dp
  from pipeline_dp.dataset_histograms import histograms
  from typing import Optional, Sequence, Tuple
  import math
  import bisect
label_desc: Use image node_id 4 for calling the CountErrorEstimator obj's underlying member method code with example usage: obj.get_ratio_dropped_linf(linf_bound) and returns: self