python matplotlib实现条形图的填充效果

import matplotlib.pyplot as plt 
import numpy as np
from pylab import mpl

mpl.rcParams['font.sans-serif'] = ['Microsoft YaHei']
Y2016 = [83.2, 85, 83.9] 
Y2017 = [80.4, 74.6, 86.5]
Y2018 = [85.8, 87.2, 89.1]
labels = ['准确性', '敏感性', '特异性'] 
bar_width = 0.25 
 
# 绘图
plt.figure(figsize=(10,10))
plt.bar(np.arange(3), Y2016, label='TSVM', color='white', alpha=1, width=bar_width,edgecolor="k",hatch='/') 
plt.bar(np.arange(3) + bar_width, Y2017, label=u'协同训练半监督', color='white', alpha=1, edgecolor="k",width=bar_width,hatch="***")
plt.bar(np.arange(3) + 2*bar_width, Y2018, label=u'结合TSVM和协同训练半监督', color='white', alpha=1, edgecolor="k",width=bar_width,hatch="xxx")
 
# 添加刻度标签 
plt.xticks(np.arange(3) + bar_width, labels)
plt.tick_params(labelsize=20)
# 设置Y轴的刻度范围 
plt.ylim([0, 100]) 
 
# 为每个条形图添加数值标签 
for x2016, y2016 in enumerate(Y2016): 
    plt.text(x2016, y2016 + 2, '%s' % y2016, ha='center',fontsize=20) 
 
for x2017, y2017 in enumerate(Y2017): 
    plt.text(x2017 + bar_width, y2017 + 2, '%s' % y2017, ha='center',fontsize=20)

for x2018, y2018 in enumerate(Y2018): 
    plt.text(x2018 + 2*bar_width, y2018 + 2, '%s' % y2018, ha='center',fontsize=20)
# 显示图例
plt.legend(bbox_to_anchor=(0.5,1), loc=3, borderaxespad=0,fontsize=17)
plt.savefig('foo.png') 
# 显示图形 
plt.show()