Karlsruhe Fit Environment 2: a package for fitting and elementary data analysis
kafe2 is an open-source Python package designed to provide a flexible Python interface for the estimation of model parameters from measured data. It is the spiritual successor to the original kafe package.
kafe2 offers support for several types of data formats (including series of indexed measurements, xy value pairs, and histograms) and data uncertainty models, as well as arbitrarily complex parametric models. The numeric aspects are handled using the scientific Python stack (NumPy, SciPy, …). Visualization of the data and the estimated model are provided by matplotlib.
If you have installed pip just run
pip install kafe2
to install the latest stable version and you’re ready to go. As of kafe2 v2.4.0 only Python 3 is supported.
The documentation under kafe2.readthedocs.io has more detailed installation instructions. It also explains basic kafe2 features as well as the mathematical foundations upon which kafe2 is built.
If you prefer a more practical approach you can instead look at the various examples. In addition to the regular Python/kafe2go files there are also Jupyter notebook tutorials (in English and in German) that mostly cover the same topics.
If you encounter any bugs or have an improvement proposal, please let us know by opening an issue here.
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