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, etc. The aim of the project is to provide a semi-unified API to allow quick 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, 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 documentation.
Features
- For Python 3.6+
- Open Source: BSD 3-Clause License
- pybaselines can be installed from pypi using pip
- The sources for pybaselines can be downloaded from the GitHub repo
- All of the required libraries should be automatically installed when installing pybaselines
- To use the various functions in pybaselines, simply input the measured data and any required parameters
Project Samples
