code: def roc_values():
      fpr = [0.0, 0.2, 0.4, 0.4, 0.6, 1.0]
      tpr = [0.0, 0.2, 0.4, 1.0, 1.0, 1.0]
  
      return fpr, tpr
  
imports: from copy import copy
  import sys
  import os
  from pathlib import Path
  import numpy
  from sklearn.linear_model import LogisticRegression
  import pytest
  from matplotlib.testing.conftest import mpl_test_settings, mpl_image_comparison_parameters
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import GridSearchCV
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 16 for calling a global function with example usage: roc_values() and returns: fpr,  tpr