注释LSTM

def normalization(data):#归一化特征数据的定义程序
    mu = np.mean(data, axis=0)    #对data列求均值
    sigma = np.std(data, axis=0)  #对data列求标准差
    return (data - mu) / sigma

def normal_label(data):#归一化磨损值的程序
    minVals = data.min(0)#data中每列最小值，minVal
    maxVals = data.max(0)#data中每列最大值，maxVal
    ranges = maxVals - minVals
    normData = np.zeros(np.shape(data))#创建和data一样行列的0矩阵
    m = data.shape[0]#m值为data的行数，shape[1]列数
    normData = data - np.tile(minVals, (m, 1))#复制m列
    normData = normData / np.tile(ranges, (m, 1))
    return normData[0]  #返回第一行值