Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python

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Ada Coda
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Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python

Post by Ada Coda » Fri Jul 01, 2016 12:15 am

Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python

Abstract: Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Python. Lmfit builds on and extends many of the optimization algorithm of scipy.optimize, especially the Levenberg-Marquardt method from optimize.leastsq. Its enhancements to optimization and data fitting problems include using Parameter objects instead of plain floats as variables, the ability to easily change fitting algorithms, and improved estimation of confidence intervals and curve-fitting with the Model class. Lmfit includes many pre-built models for common lineshapes.

Credit: Newville, Matthew; Stensitzki, Till; Allen, Daniel B; Rawlik, Michal; Ingargiola, Antonino; Nelson, Andrew

Site: https://github.com/lmfit/lmfit-py/
https://ui.adsabs.harvard.edu/abs/2014ApJ...790...93P

Bibcode: 2016ascl.soft06014N

Preferred citation method: https://doi.org/10.5281/zenodo.598352

ID: ascl:1606.014
Last edited by Ada Coda on Tue Sep 17, 2019 2:12 am, edited 1 time in total.
Reason: Updated code entry.

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