import matplotlib.pyplot as plt
import numpy as np

def plot_Matrix(cm, classes, title=None,  cmap=plt.cm.Blues):
    plt.rc('font',family='Times New Roman',size='12')   # 设置字体样式、大小
    
    # 按行进行归一化
    cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
    print("Normalized confusion matrix")
    str_cm = cm.astype(np.str).tolist()
    for row in str_cm:
        print('\t'.join(row))
    # 占比1%以下的单元格，设为0，防止在最后的颜色中体现出来
    for i in range(cm.shape[0]):
        for j in range(cm.shape[1]):
            if int(cm[i, j]*100 + 0.5) == 0:
                cm[i, j]=0
    
    fig, ax = plt.subplots()
    im = ax.imshow(cm, interpolation='nearest', cmap=cmap)
    # ax.figure.colorbar(im, ax=ax) # 侧边的颜色条带
    
    ax.set(xticks=range(cm.shape[1],),
           yticks=range(cm.shape[0],),
           xticklabels=classes, yticklabels=classes,
           ylabel='Actual',
           xlabel='Predicted')
    ax.tick_params(labelsize=12)
    # 通过绘制格网，模拟每个单元格的边框
    ax.set_xticks(np.arange(cm.shape[1]+1)-.5, minor=True)
    ax.set_yticks(np.arange(cm.shape[0]+1)-.5, minor=True)
    ax.grid(which="minor", color="gray", linestyle='-', linewidth=0.2)
    ax.tick_params(which="minor", bottom=False, left=False)

    # 将x轴上的lables旋转45度
    plt.setp(ax.get_xticklabels(), rotation=45, ha="right",
             rotation_mode="anchor")

    # 标注百分比信息
    fmt = 'd'
    thresh = cm.max() / 2.
    for i in range(cm.shape[0]):
        for j in range(cm.shape[1]):
            if int(cm[i, j]*100 + 0.5) > 0:
                ax.text(j, i, format(int(cm[i, j]*100 + 0.5) , fmt) + '%',
                        ha="center", va="center",
                        color="white"  if cm[i, j] > thresh else "black",fontsize=12)
    fig.tight_layout()
    plt.savefig('cm.jpg', dpi=300)
    # plt.show()

# cm = np.array([[373,0,3,0],[0,128,3,32],[13,5,158,35],[19,14,15,208]])
# plot_Matrix(cm=cm,classes=['fall','waving','kick','throw'])