Skip to main content

No project description provided

Project description

PyVibDMC

codecov pytest DOI

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 )

Documentation

Visit the Documentation hosted on ReadTheDocs

Installation

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

You may install it through pip:

pip install pyvibdmc

Contributing

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

Copyright (c) 2020, Ryan DiRisio

Acknowledgements

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyvibdmc-1.3.7.tar.gz (16.3 MB view details)

Uploaded Source

Built Distribution

pyvibdmc-1.3.7-py3-none-any.whl (16.3 MB view details)

Uploaded Python 3

File details

Details for the file pyvibdmc-1.3.7.tar.gz.

File metadata

  • Download URL: pyvibdmc-1.3.7.tar.gz
  • Upload date:
  • Size: 16.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.12

File hashes

Hashes for pyvibdmc-1.3.7.tar.gz
Algorithm Hash digest
SHA256 02f063db89638b56379bd579f4661a1be616dcea112b89112f166f566e6de02e
MD5 66c56468711c753fed80ce41d71cfe1e
BLAKE2b-256 9a0f5af73b65436e2ffbf78970a6ddf0c2e5695432f9c4386d80dc77249a75da

See more details on using hashes here.

File details

Details for the file pyvibdmc-1.3.7-py3-none-any.whl.

File metadata

  • Download URL: pyvibdmc-1.3.7-py3-none-any.whl
  • Upload date:
  • Size: 16.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.12

File hashes

Hashes for pyvibdmc-1.3.7-py3-none-any.whl
Algorithm Hash digest
SHA256 a189eca41add1213954b107556576a5a0fefb12c9951cb91d23738548fda8d93
MD5 b60e1ed6c6c0df7a4879956c70a49a20
BLAKE2b-256 069dc62e94686c2173c76b669f27a817a52384dbd90f506ca4d8023361cafce4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page