code: def compute_rdp_curve(
      votes, threshold, sigma1, sigma2, orders, target_answered
  ):
      rdp_cum = np.zeros(len(orders))
      answered = 0
      for i, v in enumerate(votes):
          v = sorted(v, reverse=True)
          q_step1 = math.exp(
              pate.compute_logpr_answered(threshold, sigma1, v)
          )
          logq_step2 = pate.compute_logq_gaussian(v, sigma2)
          rdp = pate.rdp_gaussian(logq_step2, sigma2, orders)
          rdp_cum += q_step1 * rdp
  
          answered += q_step1
          if answered >= target_answered:
              print(
                  "Processed {} queries to answer {}.".format(
                      i, target_answered
                  )
              )
              return rdp_cum
  
      assert False, "Never reached {} answered queries.".format(
          target_answered
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import os
  import sys
  from absl import app
  from absl import flags
  import matplotlib
  import matplotlib.pyplot
  import numpy
  import core
  import random
label_desc: Use image node_id 4 for calling a global function with example usage: compute_rdp_curve(votes, threshold, sigma1, sigma2, orders, target_answered) and returns: rdp_cum