A general purpose diffusion monte carlo code for studying vibrational problems

This package requires the following:

• NumPy

• Matplotlib

• h5py

• A potential energy surface (PES) for a system of interest, which can be called using a Python function (See Documentation).

• Optional: MPI4Py (for multi-node PES evaluation, otherwise uses multiprocessing for multi-core PES evaluation)

• Optional: Tensorflow (for Neural Network PES)

• Tutorial: A compiler required for the potential energy surface (the tutorial potential uses gfortran)

• Tutorial: make (on Linux systems, this is usually installed via the 'build-essential' or 'Development Tools' packages )

Visit the Documentation hosted on ReadTheDocs

You may view the latest stable release on the Python Package Index.

You may install it through pip:

pip install pyvibdmc

Features should be developed on branches. To create and switch to a branch, use the command

git checkout -b new_branch_name

To switch to an existing branch, use

git checkout branch_name

Copyright (c) 2020, Ryan DiRisio

Project based on the Computational Molecular Science Python Cookiecutter version 1.3.

Thank you to the entire McCoy group for helping me talk through this code, with special acknowledgements to Fenris Lu (beta tester), Mark Boyer (coding conversations), and my advisor, Anne McCoy.