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multidimensional selection optimisation with simulated annealing

Project description

selanneal

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.

usage

  • 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

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