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Published April 8, 2023 | Version 1.2.0
Software Open

lmfit/lmfit-py: 1.2.0

Authors/Creators

  • 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 and nsigma options to conf_interval2d()
  • add ModelResult.summary() to return many resulting fit statistics and attributes into a JSON-able dict.
  • add correl_table() function to lmfit.printfuncs and correl_mode option to fit_report() and ModelResult.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 the sigma-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 and create_params to take optional dict of Parameter attributes (PR #844)
  • fix reporting of nfev from least_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 saved Model result (PR #844, #830)
  • ConstantModel and ComplexConstantModel will return an ndarray of the same shape as the independent variable x (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

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Additional details

Related works

Is supplement to
https://github.com/lmfit/lmfit-py/tree/1.2.0 (URL)