Welcome to FACTNN’s documentation!

Indices and tables


FACTNN is a Python package designed to probe analyzing and classifying air shower data from the First G-APD Cherenkov Telescope (FACT) using neural networks.

FACTNN can perform gamma/hadron separation, estimate the energy of gamma-ray initiated air showers, and estimate the source location of the air shower in the night sky. This is thanks to training and testing data available from the FACT collaboration and hosted here: https://factdata.app.tu-dortmund.de/

If you want to just jump right in, examples are under the `examples/` folder, showing the process to build and run everything.