/deepks-kit

a package for developing machine learning-based chemically accurate energy and density functional models

Primary LanguagePythonGNU Lesser General Public License v3.0LGPL-3.0

DeePKS-kit

DeePKS-kit is a program to generate accurate energy functionals for quantum chemistry systems, for both perturbative scheme (DeePHF) and self-consistent scheme (DeePKS).

The program provides a command line interface deepks that contains five sub-commands,

  • train: train an neural network based post-HF energy functional model
  • test: test the post-HF model with given data and show statistics
  • scf: run self-consistent field calculation with given energy model
  • stats: collect and print statistics of the SCF the results
  • iterate: iteratively train an self-consistent model by combining four commands above

TODO

  • Print loss separately for E and F in training.
  • Rewrite all print function using logging.
  • Write a detailed README and more docs.
  • Add unit tests.

Usage

Please see examples folder for the usage of deepks library. A detailed example with executable data for single water molecules can be found here. A more complicated one for training water clusters can be found here.