Release 1.3.0 · lmfit/lmfit-py

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: