SNV Python实现

SNV（Standard Normal Variate）是一种常用的光谱预处理方法，可以消除光谱中的系统误差。下面是SNV Python实现的步骤：

# 引入库
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
warnings.filterwarnings('ignore')
import ssl
ssl._create_default_https_context = ssl._create_unverified_context

# 读入数据、预处理以及展示
data = pd.read_csv('data.csv')
data = data.drop(['Sample'], axis=1)
data = (data - data.mean()) / data.std()
data.plot()
plt.show()

# SNV实现
def snv(data):
    data_mean = np.mean(data, axis=1)
    data_std = np.std(data, axis=1, ddof=1)
    data_snv = (data - data_mean[:, np.newaxis]) / data_std[:, np.newaxis]
    return data_snv

data_snv = snv(data)
data_snv.plot()
plt.show()