class_docstr: Specifies the parameters for a DP mechanism.
  
  MechanismType defines the kind of noise distribution.
  _noise_standard_deviation is the minimized noise standard deviation.
  (_eps, _delta) are parameters of (eps, delta)-differential privacy
class_docstr_tok: ["Specifies","the","parameters","for","a","DP","mechanism",".","MechanismType","defines","the","kind","of","noise","distribution",".","_noise_standard_deviation","is","the","minimized","noise","standard","deviation",".","(","_eps",",","_delta",")","are","parameters","of","(","eps",",","delta",")","-differential","privacy"]
docstr: Noise value for the mechanism.
  
  Raises:
      AssertionError: The noise value is not calculated yet.
docstr_tok: ["Noise","value","for","the","mechanism",".","Raises",":","AssertionError",":","The","noise","value","is","not","calculated","yet","."]
code: def noise_standard_deviation(self):
      """Noise value for the mechanism.
  
      Raises:
          AssertionError: The noise value is not calculated yet.
      """
      if self._noise_standard_deviation is None:
          raise AssertionError(
              "Noise standard deviation is not calculated yet."
          )
      return self._noise_standard_deviation
  
imports: import abc
  import collections
  import logging
  import math
  from typing import Optional
  from dataclasses import dataclass
  import pipeline_dp.aggregate_params
  from pipeline_dp import input_validators
label_desc: Use image node_id 1 for calling the MechanismSpec obj's underlying member method code with example usage: obj.noise_standard_deviation() and returns: self