draw roc curve using python sklearn, Matplotlib

import matplotlib.pyplot as plt

from sklearn.metrics import roc_auc_score, average_precision_score

from sklearn import metrics

gt = [1, 0, 1, 0, 1, 1] #origin

pre = [0.9, 0.5, 0.8, 0.4, 0.5, 0.8] #predict

fpr, tpr, thresholds = metrics.roc_curve(gt, pre)

roc_auc = metrics.auc(fpr, tpr)

fig, ax = plt.subplots(figsize=(10,7))

ax.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)

ax.plot(np.linspace(0, 1, 100),

np.linspace(0, 1, 100),

label='baseline',

linestyle='--')

plt.title('Receiver Operating Characteristic Curve', fontsize=18)

plt.ylabel('TPR', fontsize=16)

plt.xlabel('FPR', fontsize=16)

plt.legend(fontsize=12)