alkahest: Pre-Processing XY Data from Experimental Methods
- 1. Université Bordeaux Montaigne
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.
- Is supplement to
- https://github.com/tesselle/alkahest/tree/v1.1.1 (URL)