lmfit/lmfit-py: 1.3.0

Version 1.3.0 Release Notes (April 4, 2024)

New features:

• add 'min_rel_change' as optional variable in calculation of confidence intervals with Model.conf_interval(). (PR #937).

• Model.eval_uncertainty now takes an optional dscale parameter (default value of 0.01) to set the step size for calculating derivatives (PR #933).

• add calculation of predicted_interval to Model.eval_uncertainty (PR #933).

Bug fixes/enhancements:

• restore best-fit parameter values for high accuracy values of constrained values (PR #907)

• improvement to Model for the difference between Parameter, "independent variable", and "option". With this change, keyword arguments to model functions with non-numerice default values such as do_thing=True, or form='linear' has those arguments become clearly identified as independent variables,and use the provided values as default values. (PR #941)

• better saving/loading saved states of Model now use dill, have several cleanups, and are now versioned for future-proofing. Also, propagate funcdets for Parameters when loading a Model. (PR #932, PR #934)

• in the TNC method, maxfun is used instead of maxiter.

• fix bug calculating r-squared for fits with weights (PR #921, PR #923)

• fix bug in modelresult.eval_uncertainty() after load_modelresult() (PR #909)

• use StringIO for pandas.read_json.

• add test for MinimizerResult.uvars after successful fit (PR #913)

• adding an example using basinhopping, can take other methods as command-line argument

Maintenance/Deprecations:

• drop support for Python 3.7 that reached EOL on 2023-06-27 (PR #927)

• fix tests for Python 3.12 and Python 3.13-dev

• increase minimum numpy verstio to 1.23 and scipy to 1.8.

• updates for compatibility with numpy 2.0

• the dill package is now required. (#940)

• build switchded to use pyproject.toml (#928)

• fix broken links in Examples gallery

• fix intersphinx mapping to scipy docs.