Published June 13, 2023 | Version v1.1.1
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alkahest: Pre-Processing XY Data from Experimental Methods

  • 1. Universit√© Bordeaux Montaigne

Description

A lightweight, dependency-free toolbox for pre-processing XY data from experimental methods (i.e. any signal that can be measured along a continuous variable). This package provides methods for baseline estimation and correction, smoothing, normalization, integration and peaks detection. Baseline correction methods includes polynomial fitting as described in Lieber and Mahadevan-Jansen (2003) , Rolling Ball algorithm after Kneen and Annegarn (1996) , SNIP algorithm after Ryan et al. (1988) , 4S Peak Filling after Liland (2015) and more.

Notes

To cite package "alkahest" in publications use:

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tesselle/alkahest-v1.1.1.zip

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