# 8. Fitting and Modeling Data¶

A key motivation for Larch is to provide easy and robust ways to model data and perform complex fits of data to models. Data modeling and fitting can be messy and challenging tasks, so a major factor in Larch’s design was to make this as simple as possible. This chapter discusses the basic concepts for building models, setting up and performing fits, and inspecting the results.

The concepts presented here focus on modeling and fitting of general spectra and data. Of course, Larch can provides other, specific functions for doing fits, such as the EXAFS procedures _xafs.autobk() and _xafs.feffit(). Many of these concepts (and the underlying fitting algorithms) are used for those other functions as well.

Changed in version 0.9.34: Several changes in the implementation of fitting were made in 0.9.34. All fitting now uses the lmfit package. The use of _sys.paramGroup as a group to hold default fitting parameters is no longer used. For constraint expressions, _sys.fiteval now holds the expression evaluator used.