Release v1.6.2

• Using evaluation database with scaling_within_bounds=True does not overwrite database values.
• Bugfix in output logging

No change to main algorithm.

Release v1.6.1

Bugfix when returning solution object containing error information from bad inputs (otherwise caused a Python error).

No changes to the main algorithm.

Release v1.6

Allow use of evaluation database as x0 to reduce number of objective evaluations required in initialization phase

When printing solution object, reduce the maximum length of residual/Jacobian vectors that are fully displayed

Release v1.5.4

Add ability to save/load results to/from a dictionary

Bugfix when printing results from a run which terminated early

Release v1.5.3

Bugfix when starting solver at problem minimizer

Release v1.5.2

• Bugfix for saving diagnostic info (bug introduced in v1.5.1), issue #23

Release v1.5.1

• Add new return values soln.xmin_eval_num and soln.jacmin_eval_nums
• Allow option for parallel initial evaluations for non-random directions if npt not too large

Neither should affect the performance of the DFO-LS algorithm

Release v1.5.0

Allow optional (nonsmooth) regularization term in the objective to avoid overfitting.

Also DFO-LS now does not give warnings if the initial point is on the upper/lower bounds (only if it is outside the bounds).

Release v1.4.1

Migrate installation to pyproject.toml (required for Python 3.12+) and drop support for Python 2.7 and <=3.8 to align with SciPy >=1.11 dependency. No change to the expected behavior of the DFO-LS algorithm.

Release v1.4

Upgraded required scipy version and graceful handling of NaNs in objective evaluation in trust-region step. No change to expected behavior of DFO-LS algorithm.