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-1.3.6.tar.gz (16.3 MB view details)

Uploaded Source

Built Distribution

pyvibdmc-1.3.6-py3-none-any.whl (16.3 MB view details)

Uploaded Python 3

File details

Details for the file pyvibdmc-1.3.6.tar.gz.

File metadata

  • Download URL: pyvibdmc-1.3.6.tar.gz
  • Upload date:
  • Size: 16.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for pyvibdmc-1.3.6.tar.gz
Algorithm Hash digest
SHA256 87b11182251bb5e26a7508429a8cc65b5ef56c00c7cd73761311c3d4034937cd
MD5 cf4f5fea32252fc07425e6c70e91290d
BLAKE2b-256 4627a6f70a319f7020af8e71254c3e7c603f9997072bd44e960f155c9d3e9fb5

See more details on using hashes here.

File details

Details for the file pyvibdmc-1.3.6-py3-none-any.whl.

File metadata

  • Download URL: pyvibdmc-1.3.6-py3-none-any.whl
  • Upload date:
  • Size: 16.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for pyvibdmc-1.3.6-py3-none-any.whl
Algorithm Hash digest
SHA256 c29f470c8406b52ef2fb8a6bdcd22c68f9e45b6eed508d182994fbfe291cb4e3
MD5 974038ce68b6a56526651ad34e164d57
BLAKE2b-256 d7b245b3f4e8cc698f305619cab799eacf7f2eab7026716493921e247f83cfa5

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