BaselineRemoval 0.0.7

Perform baseline removal, baseline correction and baseline substraction for raman spectra using Modpoly, ImodPoly and Zhang fit. Returns baseline-subtracted spectrum

What is it?

Python package for baseline correction. It has below 3 methods for baseline removal from spectra.

• Modpoly Modified multi-polynomial fit [1]

• IModPoly Improved ModPoly[2], which addresses noise issue in ModPoly

• ZhangFit Zhang fit[3], which doesn’t require any user intervention and prior information, such as detected peaks.

We can use the python library to process spectral data through either of the techniques ModPoly, IModPoly or Zhang fit algorithm for baseline subtraction. The functions will return baseline-subtracted spectrum.

How to use it?

from BaselineRemoval import BaselineRemoval

input_array=[10,20,1.5,5,2,9,99,25,47]

polynomial_degree=2 #only needed for Modpoly and IModPoly algorithm

baseObj=BaselineRemoval(input_array)

Modpoly_output=baseObj.ModPoly(polynomial_degree)

Imodpoly_output=baseObj.IModPoly(polynomial_degree)

Zhangfit_output=baseObj.ZhangFit()

print('Original input:',input_array)

print('Modpoly base corrected values:',Modpoly_output)

print('IModPoly base corrected values:',Imodpoly_output)

print('ZhangFit base corrected values:',Zhangfit_output)

Original input: [10, 20, 1.5, 5, 2, 9, 99, 25, 47]

Modpoly base corrected values: [-1.98455800e-04  1.61793368e+01  1.08455179e+00  5.21544654e+00
  7.20210508e-02  2.15427531e+00  8.44622093e+01 -4.17691125e-03
  8.75511661e+00]

IModPoly base corrected values: [-0.84912125 15.13786196 -0.11351367  3.89675187 -1.33134142  0.70220645
 82.99739548 -1.44577432  7.37269705]

ZhangFit base corrected values: [ 8.49924691e+00  1.84994576e+01 -3.31739230e-04  3.49854060e+00
  4.97412948e-01  7.49628529e+00  9.74951576e+01  2.34940300e+01
  4.54929023e+01

Where to get it?

pip install BaselineRemoval

Dependencies

• numpy

• scikit-learn

• scipy

References

1. Automated Method for Subtraction of Fluorescence from Biological Raman Spectra by Lieber & Mahadevan-Jansen (2003)
2. Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy by Zhao, Jianhua, Lui, Harvey, McLean, David I., Zeng, Haishan (2007)
3. Baseline correction using adaptive iteratively reweighted penalized least squares by Zhi-Min Zhang, Shan Chena and Yi-Zeng Liang (2010)