code: def compute_logpr_answered(t, sigma, counts):
      """Computes log of the probability that a noisy threshold is crossed.
  
      Args:
        t: The threshold.
        sigma: The stdev of the Gaussian noise added to the threshold.
        counts: An array of votes.
  
      Returns:
        Natural log of the probability that max is larger than a noisy threshold.
      """
      # Compared to the paper, max(counts) is rounded to the nearest integer. This
      # is done to facilitate computation of smooth sensitivity for the case of
      # the interactive mechanism, where votes are not necessarily integer.
      return scipy.stats.norm.logsf(t - round(max(counts)), scale=sigma)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import app
  import numpy
  import scipy.stats
label_desc: Use image node_id 8 for calling a global function with example usage: compute_logpr_answered(t, sigma, counts) and returns: scipy