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License: CC BY
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License: CC BY
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Software . 2025
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Software . 2025
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LMFIT: Non-Linear Least-Squares Minimization and Curve-Fitting for Python

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 12 Mar 2025Publisher:Zenodo
Authors: Newville, Matthew; Otten, Renee; Nelson, Andrew; Stensitzki, Till; Ingargiola, Antonino; Allan, Daniel; Fox, Austin; +2 Authors

doi: 10.5281/zenodo.598352 , 10.5281/zenodo.16175987 , 10.5281/zenodo.15014437

LMFIT: Non-Linear Least-Squares Minimization and Curve-Fitting for Python

Abstract

Mostly maintenance and small bug fixes: capture and ignore std_dev=0 warnings from uncertainties package better ensure that parameter values and sterr are floats, not np.floats fix Doniach formula in docstring (#966) add bose and fermi lineshapes, and BoseModel and FermiModel (with tests) remove deprecated disp argument for ampgo fix typos in README.rst fix typos in doc update to latest SciPy/NumPy version update pre-commit and CI hooks update zenodo link several fixes for deprecations and test failures do not test for warnings from upstream code that might change or be suppressed or altered update license name for PyPI compatibiilty

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Top 1%