import matplotlib.pyplot as plt


# -*- coding: UTF-8 -*-
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

print("数据")
# 这里导入你自己的数据
# ......
# ......
# x_axix，train_pn_dis这些都是长度相同的list()
MAE=[42.124,40.244,30.196,29.367,28.168,26.955,26.135,25.254,23.277,24.866,35.236]
MSE = [88.121,87.788,85.822,56.258,63.689,54.101,53.936,47.517,44.022,52.201,79.654]
x=[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.95,1.0]
# MAE=[25.622,25.245,24.568,24.121,23.689,23.277,24.248,26.498,26.875,27.012,27.232]
# MSE = [53.414,52.654,50.864,48.871,46.856,44.022,48.572,55.913,56.248,56.875,56.921]
# x=[0.1,0.09,0.08,0.07,0.06,0.05,0.04,0.03,0.02,0.01,0]
#plt.title('Ablation study of the loss ratio about heads')
# 开始画图
sub_axix = filter(lambda x: x % 200 == 0, x)
plt.title('Ablation study of the loss ratio about backbone',fontsize=16)

plt.plot(x, MAE, color='green', label='MAE')
plt.plot(x, MSE, color='red', label='MSE')
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.xlabel(...,fontsize=16)
plt.ylabel(...,fontsize=16)
plt.legend()  # 显示图例

plt.xlabel('Loss weigh of backbone')
#plt.ylabel('rate')
plt.show()
# python 一个折线图绘制多个曲线

# ......
# x_axix，train_pn_dis这些都是长度相同的list()

# 开始画图
# sub_axix = filter(lambda x: x % 200 == 0, x_axix)
# plt.title('Result Analysis')
# plt.plot(x_axix, train_acys, color='green', label='training accuracy')
# plt.plot(sub_axix, test_acys, color='red', label='testing accuracy')
# plt.plot(x_axix, train_pn_dis, color='skyblue', label='PN distance')
# plt.plot(x_axix, thresholds, color='blue', label='threshold')
# plt.legend()  # 显示图例
#
# plt.xlabel('iteration times')
# plt.ylabel('rate')
# plt.show()
# plt.plot(x, squares)
# plt.show()