Lmfit

Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Python. Lmfit builds on Levenberg-Marquardt algorithm of scipy.optimize.leastsq(), but also supports most of the optimization methods from scipy.optimize.

Features:
- Using Parameter objects instead of plain floats as variables. A Parameter has a value that can be varied in the fit, fixed, have upper and/or lower bounds. It can even have a value that is constrained by an algebraic expression of other Parameter values.
- Ease of changing fitting algorithms.
- Improved estimation of confidence intervals.
- Improved curve-fitting with the Model class, which allows to turn a function into a model to fit the data.
- Many pre-built models for common lineshapes are included and ready to use.

Tags

fitting least_squares math minimization model optimization physics python scientific_computing scientificcomputing