Selanneal is a simple package for optimising multivariate selections via a figure of merit. The optimisation is performed for all given features simultaneously by utilising the simulated annealing method. It relies on numba for just-in-time compilation of the algorithm. The procedure works on binned data, so an n-dimensional histogram needs to be provided.
Currently, two modes of operation exist:
- edges: cut only the edges of each feature (results in "rectangular cuts")
- bins: select individual bins from a grid (for now limited to 2 feature dimensions)
This package was written for applications in high energy physics but can apply to general problems in statistical data analysis.
- install with
python3 -m pip install selanneal- tutorial notebooks for basic usage in examples
- training data is to be provided as numpy arrays representing the histogrammed number of signal and background events
- hyper-parameters to tune the optimisation:
- the implemented figure of merit is