近红外光谱建模之光谱预处理python实现（二）

目录

4 多元散射矫正处理

5 标准正态变量变换处理

6 一阶差分处理

7 二阶差分处理

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4 多元散射矫正处理

def msc(sdata):
    n = sdata.shape[0]  # 样本数量
    k = np.zeros(sdata.shape[0])
    b = np.zeros(sdata.shape[0])

    M = np.mean(sdata, axis=0)

    from sklearn.linear_model import LinearRegression
    for i in range(n):
        y = sdata[i, :]
        y = y.reshape(-1, 1)
        M = M.reshape(-1, 1)
        model = LinearRegression()
        model.fit(M, y)
        k[i] = model.coef_
        b[i] = model.intercept_

    spec_msc = np.zeros_like(sdata)
    for i in range(n):
        bb = np.repeat(b[i], sdata.shape[1])
        kk = np.repeat(k[i], sdata.shape[1])
        temp = (sdata[i, :] - bb)/kk
        spec_msc[i, :] = temp
    return spec_msc


x = msc(x)
pp = PlotSpectrum(x)
pp.show()