code: import numpy as np
  import h5py
  
  from sklearn import metrics
  from sklearn.metrics import accuracy_score
  from sklearn import svm
  
  # path variables
  score_path = '../../temp_files/scores.mat'
  label_path = '../../temp_files/labels.mat'
  
  with h5py.File(score_path, 'r') as f:
      test_features = f['scores'][()]
  with h5py.File(label_path, 'r') as f:
      test_label = f['test_label'][()]
  
  fpr, tpr, thresholds = metrics.roc_curve(np.transpose(test_label), np.transpose(test_features))
  print(metrics.auc(fpr, tpr))
  
apis: sklearn.metrics.auc numpy.transpose