用python写一个光谱基线校正函数

好的，关于光谱基线校正函数的Python实现，我可以给出以下代码作为参考：

import numpy as np
from scipy.signal import savgol_filter

def baseline_correction(x, y, param):
    # x: wavelength
    # y: intensity
    # param: Dictionary containing parameter information

    # Extract baseline correction parameters
    window_length = param['window_length']
    poly_order = param['poly_order']
    lam = param['lambda']
    p = param['p']

    # Savitzky-Golay filter
    smoothed = savgol_filter(y, window_length, poly_order)

    # Subtract smoothed baseline
    corrected = y - smoothed

    # Asymmetric least squares (ALS) algorithm to penalize negative deviations
    w = np.ones(len(corrected))
    for i in range(p):
        z = corrected - w
        z = z[z >= 0]
        if len(z) == 0:
            break
        med = np.median(z)
        mad = 1.4826*np.median(np.abs(z - med))
        w[corrected <= (med - lam*mad)] = 0

    # Adjust baseline corrected spectrum
    adj_corrected = corrected + smoothed

    # Return baseline corrected spectrum
    return adj_corrected

这段代码实现了光谱基线校正的过程，其中用到了Savitzky-Golay filter和Asymmetric least squares (ALS) algorithm两个基础方法。这些方法的具体参数可以在param字典中设置和调整。在调用该函数时，你需要准备好波长值(x)和相应的光谱强度值(y)，并将它们作为baseline_correction函数的参数传入。