v2.9.0

Compared to v2.8.3:

• Implemented the ability to do pull plots in the same way you can do ratio and residual plots.
• Extended the wrapper interface to allow the definition of pull, ratio, and residual plots.
• Added a new example under examples/009_histogram_fit/03_SplusBfit.py.

v2.8.3

• Fixed #241 (Different behavior depending on parameter names in model)

Iminuit Compatibility

Fixed a problem with fix parameters in Iminuit which was described in #240

v2.8.1

Relative to v2.8.0:

• Matplotlib 3.8 compatibility, minimum Matplotlib version is 3.4
• Added a Makefile
• Moved packaging configuration to pyproject.toml. With this release, Python 3.6 is no longer supported
• Added linting for the project and reformatted many files

v2.8.0 - Summer Term 2023

Compared to v2.7.0:

• New wrapper functions for CustomFit, HistFit, IndexedFit, and UnbinnedFit.
• All wrapper functions now accept a model function as its first argument and the data afterwards. The interface in v2.7.0 was accidentally built to the wrong specification, and thus had to be remade. The intent is to use the exact same order of arguments as e.g. SciPy curve_fit.
• The interface for creating or plotting profiles has been extended. You can now specify explicit upper or lower bounds as well as confidence levels for the intervals. See examples/003_profiling/04_one_sided_limit.py for an example.
• HistFit/hist_fit can now accept NumPy histograms as data.
• Revised the documentation, particularly the theory chapter.
• Fixed incorrect warning when creating a HistFit.

Compared to v2.8.0-pre1:

• Ability to fix parameters when using wrapper functions.
• Ability to construct HistContainer from only bin edges.
• Better logic for error band and density label defaults.
• Ability to scale fonts in plots.

v2.8.0-pre1

Compared to v2.7.0:

• New wrapper functions for CustomFit, HistFit, IndexedFit, and UnbinnedFit.
• All wrapper functions now accept a model function as its first argument and the data afterwards. The interface in v2.7.0 was accidentally built to the wrong specification, and thus had to be remade. The intent is to use the exact same order of arguments as e.g. SciPy curve_fit.
• The interface for creating or plotting profiles has been extended. You can now specify explicit upper or lower bounds as well as confidence levels for the intervals. See examples/003_profiling/04_one_sided_limit.py for an example.
• HistFit/hist_fit can now accept NumPy histograms as data.
• Revised the documentation, particularly the theory chapter.
• Fixed incorrect warning when creating a HistFit.

v2.7.0

Relative to v2.7.0-pre1:

• Fixed kafe2.xy_fit when using correlated relative errors.
• Fixed setting plot axis ticks for log scale.
• Updated the documentation.

v2.7.0-pre1

Compared to v2.6.2:

• Added new way to define model functions using SymPy.
• Added the ability to create plots from data containers.
• Added wrappers for xy fits and xy fit/data plotting.
• Added wrapper k2Fit for backwards compatibility with PhyPraKit.
• Renamed UnbinnedFit argument: model_density_function -> model_function. This can potentially break existing code.
• Replaced custom exceptions with built-in exceptions wherever possible.
• Fixed value broadcasting for Plot.customize .
• Fixed plot x range when creating plots from multiple fits.
• Fixed crash when calculating asymmtric parameter errors on failed convergence.

v2.6.2

Compared to v2.6.1:

• Fixed some layout issues when saving plots.
• Fixed scalar model function causing crash.
• New IndexedFit example.
• New MultiFit example.
• Fixed plot saving.
• Fixed Gauss approximation cost function calculation.
• Fixed some edge cases with fit.save_state .

v2.6.1

Bugfixes:

• Fixed incorrect uncertainty amount when using non-scalar relative errors in kafe2go.
• Fixed Plot.save() crashing when setting a custom file name.
• Added a workaround for a matplotlib v3.5.2 bug that caused kafe2 plots to not be shown.