Welcome to hippynn’s documentation!
We hope you enjoy your stay.
What is hippynn?
hippynn is a python library for machine learning on atomistic systems. We aim to provide high-performance modular design so that different components can be re-used, extended, or added to. You can find more information at the hippynn Features page. The development home is located at the hippynn github repository, which also contains many example files
The main components of hippynn are constructing models, loading databases, training the models to those databases, making predictions on new databases, and interfacing with other atomistic codes. In particular, we provide interfaces to ASE (prediction), PYSEQM (training/prediction), and LAMMPS (prediction). hippynn is also used within ALF for generating machine learned potentials along with their training data completely from scratch.
Multiple formats for training data are supported, including Numpy arrays, the ASE Database, fitSNAP JSON format, and ANI HDF5 files.