Fit parameters or Wilson coefficients to a host of experimental data included in the package, or supplied by you
Visualize predictions or fit results in publication quality using flavio's predefined plot functions built on the power of matplotlib
Thanks to Python, no compilation is necessary, even when you make changes to the code
By modifying simple text files, you can change input parameters or choose between different implementations, e.g. for hadronic form factors
Using Jupyter, you can access (or modify!) all the features of flavio in an interactive session (similar to Mathematica)
The code is released under the MIT license. As such, it is provided “as is” without any warranty.
If you use flavio in a project, please cite:
D. Straub, “flavio: a Python package for flavour and precision phenomenology in the Standard Model and beyond” arXiv:1810.08132
This paper contains many references to results in the literature that went into the code. Please also consider citing the relevant original literature, where the real work was done.