Fitting of time-of-flight mass spectra with Hyper-EMG models
Project description
Fitting of time-of-flight mass spectra with Hyper-EMG models
Free software: 3-clause BSD license
Online documentation: https://RobbenRoll.github.io/emgfit.
Source code: https://github.com/RobbenRoll/emgfit
emgfit is a Python package for peak fitting of time-of-flight (TOF) mass spectra with hyper-exponentially modified Gaussian (Hyper-EMG [1]) model functions. emgfit is a wrapper around the lmfit [2] curve fitting package and uses many of lmfit’s user-friendly high-level features. Experience with lmfit can be helpful but is not an essential prerequisite for using emgfit since the lmfit features stay largely ‘hidden under the hood’. emgfit is designed to be user-friendly and offers automation features whenever reasonable while also supporting a large amount of flexibility and control for the user. Depending on the user’s preferences an entire spectrum can be rapidly analyzed with only a few lines of code. Alternatively, various optional features are available to aid the user in a more rigorous analysis. The model functions and methods provided by emgfit could be useful for analyses of spectroscopic data from a variety of other fields.
Amongst other features, the emgfit toolbox includes:
Automatic and sensitive peak detection
Automatic import of relevant literature values from the AME2016 [3] database
Automatic selection of the best suited peak-shape model
Fitting of low-statistics peaks with a binned maximum likelihood method
Simultaneous fitting of an entire spectrum with a large number of peaks
Export of all relevant fit results including fit statistics and plots to an EXCEL output file for convenient post-processing
emgfit is designed to be used within Jupyter Notebooks which have become a standard tool in the data science community. The usage and capabilities of emgfit are best explored by looking at the tutorial. The tutorial and more details can be found in the documentation of emgfit.
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