Published April 8, 2023
| Version 1.2.0
Software
Open
lmfit/lmfit-py: 1.2.0
Creators
- Matt Newville1
- Renee Otten
- Andrew Nelson
- Till Stensitzki2
- Antonino Ingargiola
- Dan Allan3
- Austin Fox
- Faustin Carter
- Michał
- Ray Osborn
- Dima Pustakhod
- lneuhaus
- Sebastian Weigand
- Andrey Aristov4
- Glenn
- Christoph Deil5
- mgunyho
- Mark6
- Allan L. R. Hansen
- Gustavo Pasquevich
- Leon Foks7
- Nicholas Zobrist8
- Oliver Frost
- Stuermer9
- azelcer
- Anthony Polloreno10
- Arun Persaud
- Jens Hedegaard Nielsen11
- Matteo Pompili12
- Shane Caldwell
- 1. University of Chicago
- 2. Universität Potsdam
- 3. Brookhaven National Lab
- 4. Insitut Pasteur
- 5. HeidelbergCement
- 6. Brookhaven National Laboratory
- 7. Contractor U.S. Geological Survey
- 8. Google Quantum AI
- 9. University of Heidelberg
- 10. University of Colorado Boulder
- 11. @qdev-dk
- 12. Pritzker School of Molecular Engineering, University of Chicago
Description
New features:
- add
create_params
function (PR #844) - add
chi2_out
andnsigma
options toconf_interval2d()
- add
ModelResult.summary()
to return many resulting fit statistics and attributes into a JSON-able dict. - add
correl_table()
function tolmfit.printfuncs
andcorrel_mode
option tofit_report()
andModelResult.fit_report()
to optionally display a RST-formatted table of a correlation matrix.
Bug fixes/enhancements:
- fix bug when setting
param.vary=True
for a constrained parameter (Issue #859; PR #860) - fix bug in reported uncertainties for constrained parameters by better propating uncertainties (Issue #855; PR #856)
- Coercing of user input data and independent data for
Model
to float64 ndarrays is somewhat less aggressive and will not increase the precision of numpy ndarrays (see :ref:model_data_coercion_section
for details). The resulting calculation from a model or objective function is more aggressively coerced to float64. (Issue #850; PR #853) - the default value of
epsfcn
is increased to 1.e-10 to allow for handling of data with precision less than float64 (Issue #850; PR #853) - fix
conf_interval2d
to use "increase chi-square by sigma*2reduced chi-square" to give thesigma
-level probabilities (Issue #848; PR #852) - fix reading of older
ModelResult
(Issue #845; included in PR #844) - fix deepcopy of
Parameters
and user data (mguhyo; PR #837) - improve
Model.make_params
andcreate_params
to take optional dict of Parameter attributes (PR #844) - fix reporting of
nfev
fromleast_squares
to better reflect actual number of function calls (Issue #842; PR #844) - fix bug in
Model.eval
when mixing parameters and keyword arguments (PR #844, #839) - re-adds
residual
to savedModel
result (PR #844, #830) ConstantModel
andComplexConstantModel
will return an ndarray of the same shape as the independent variablex
(JeppeKlitgaard, Issue #840; PR #841)- update tests for latest versions of NumPy and SciPy.
- many fixes of doc typos and updates of dependencies, pre-commit hooks, and CI.
Files
lmfit/lmfit-py-1.2.0.zip
Files
(386.6 kB)
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Additional details
Related works
- Is supplement to
- https://github.com/lmfit/lmfit-py/tree/1.2.0 (URL)