code: def plot_rdp_total(votes, sigmas):
      orders = np.linspace(1.0, 100.0, endpoint=True, num=100)
      orders[0] = 1.1
  
      fig, ax = setup_plot()
  
      target_answered = 2000
  
      for sigma in sigmas:
          rdp = compute_rdp_curve(
              votes, 5000, 1000, sigma, orders, target_answered
          )
          ax.plot(
              orders,
              rdp,
              alpha=0.8,
              label=r"Data-dependent bound, $\sigma$={}".format(
                  int(sigma)
              ),
              linewidth=5,
          )
  
      # for sigma in sigmas:
      #   ax.plot(
      #       orders,
      #       target_answered * pate.rdp_data_independent_gaussian(sigma, orders),
      #       alpha=.3,
      #       label=r'Data-independent bound, $\sigma$={}'.format(int(sigma)),
      #       linewidth=10)
  
      plt.xlim(xmin=1, xmax=100)
      plt.ylim(ymin=0)
      plt.xticks([1, 20, 40, 60, 80, 100])
      plt.yticks([0, 0.0005, 0.001, 0.0015, 0.002])
  
      plt.xlabel(r"Order $\alpha$", fontsize=16)
      plt.ylabel(r"RDP value $\varepsilon$ at $\alpha$", fontsize=16)
      ax.tick_params(labelsize=14)
  
      plt.legend(loc=0, fontsize=13)
      plt.show()
  
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 5 for calling a global function with example usage: plot_rdp_total(votes, sigmas) without return types