Introduction

pybaselines is a Python library that provides many different algorithms for performing baseline correction on data from experimental techniques such as Raman, FTIR, NMR, XRD, XRF, PIXE, MALDI-TOF, LIBS, etc. The aim of the project is to provide a semi-unified API to allow quickly testing and comparing multiple baseline correction algorithms to find the best one for a set of data.

pybaselines has 50+ baseline correction algorithms. These include popular algorithms, such as AsLS, airPLS, ModPoly, and SNIP, as well as many lesser known algorithms. Most algorithms are adapted directly from literature, preserving their original names whenever possible, although there are a few that are unique to pybaselines, such as penalized spline versions of Whittaker-smoothing-based algorithms. The full list of implemented algorithms can be found in the API section.