code: def fig_fpr_tpr():
      plt.figure(figsize=(4, 3))
  
      do_plot(
          generate_ours,
          keep,
          scores,
          1,
          "Ours (online)\n",
          metric="auc",
      )
  
      do_plot(
          functools.partial(generate_ours, fix_variance=True),
          keep,
          scores,
          1,
          "Ours (online, fixed variance)\n",
          metric="auc",
      )
  
      do_plot(
          functools.partial(generate_ours_offline),
          keep,
          scores,
          1,
          "Ours (offline)\n",
          metric="auc",
      )
  
      do_plot(
          functools.partial(generate_ours_offline, fix_variance=True),
          keep,
          scores,
          1,
          "Ours (offline, fixed variance)\n",
          metric="auc",
      )
  
      do_plot(
          generate_global,
          keep,
          scores,
          1,
          "Global threshold\n",
          metric="auc",
      )
  
      plt.semilogx()
      plt.semilogy()
      plt.xlim(1e-5, 1)
      plt.ylim(1e-5, 1)
      plt.xlabel("False Positive Rate")
      plt.ylabel("True Positive Rate")
      plt.plot([0, 1], [0, 1], ls="--", color="gray")
      plt.subplots_adjust(bottom=0.18, left=0.18, top=0.96, right=0.96)
      plt.legend(fontsize=8)
      plt.savefig("/tmp/fprtpr.png")
      plt.show()
  
file_path: privacy/research/mi_lira_2021/plot.py
imports: import os
  import scipy.stats
  import numpy
  import matplotlib.pyplot
  from sklearn.metrics import auc, roc_curve
  import functools
  import matplotlib
label_desc: Use image node_id 7 for calling a global function with example usage: fig_fpr_tpr() without return types