Plotting the ROC curve using matplotlib

plot-ROC.py

from sklearn.metrics import roc_auc_score, roc_curve

def plot_roc(name: str, labels: numpy.ndarray, predictions: numpy.ndarray, **kwargs) -> ():
  fp, tp, _ = roc_curve(labels, predictions)
  auc_roc = roc_auc_score(labels, predictions)
  plt.plot(100*fp, 100*tp, label=name + " (" + str(round(auc_roc, 3)) + ")", 
           linewidth=2, **kwargs)
  plt.xlabel('False positives [%]')
  plt.ylabel('True positives [%]')
  plt.title('ROC curve')
  plt.grid(True)
  plt.legend(loc='best')
  ax = plt.gca()
  ax.set_aspect('equal')

plot_roc("Train Base", y_train, y_train_pred, color=colors[0])
plot_roc("Test Base", y_test, y_test_pred, color=colors[0], linestyle='--')
plt.legend(loc='lower right')