Skip to main content

jarvis-tools: an open-source software package for data-driven atomistic materials design. https://jarvis.nist.gov/

Project description

https://circleci.com/gh/usnistgov/jarvis.svg?style=shield https://img.shields.io/travis/usnistgov/jarvis/master.svg?label=Travis%20CI https://ci.appveyor.com/api/projects/status/d8na8vyfm7ulya9p/branch/master?svg=true https://github.com/usnistgov/jarvis/workflows/JARVIS-Tools%20github%20action/badge.svg https://github.com/usnistgov/jarvis/workflows/JARVIS-Tools%20linting/badge.svg https://readthedocs.org/projects/jarvis-tools/badge/?version=latest https://img.shields.io/codecov/c/github/knc6/jarvis https://img.shields.io/pypi/dm/jarvis-tools.svg https://pepy.tech/badge/jarvis-tools https://zenodo.org/badge/DOI/10.5281/zenodo.3903515.svg https://img.shields.io/github/v/tag/usnistgov/jarvis https://app.codacy.com/project/badge/Grade/be8fa78b1c0a49c280415ce061163e77 https://img.shields.io/github/commit-activity/y/usnistgov/jarvis https://img.shields.io/github/repo-size/usnistgov/jarvis https://img.shields.io/twitter/url?style=social&url=https%3A%2F%2Ftwitter.com%2Fjarvisnist https://img.shields.io/badge/Facebook-Follow-Blue.svg https://img.shields.io/badge/LinkedIn-Follow-Blue.svg

JARVIS-Tools: an open-source software package for data-driven atomistic materials design

NIST-JARVIS (Joint Automated Repository for Various Integrated Simulations) is an integrated framework for computational science using density functional theory, classical force-field/molecular dynamics and machine-learning. The jarvis-tools package consists of scripts used in generating and analyzing the dataset. The NIST-JARVIS official website is: https://jarvis.nist.gov . This project is a part of the Materials Genome Initiative (MGI) at NIST (https://mgi.nist.gov/).

For more details, checkout our latest article: JARVIS: An Integrated Infrastructure for Data-driven Materials Design

https://www.ctcms.nist.gov/~knc6/images/logo/jarvis-mission.png

Some important features

  • Software workflow tasks: VASP, Quantum Espresso, BoltzTrap, Wannier90, LAMMPS, Scikit-learn, TensorFlow, LightGBM.

  • HPC clusters: PBS and SLURM.

  • Examples: Notebooks and test scripts to explain the package.

  • Available datasets: Summary of several datasets .

Installation

Please see Installation instructions

Example Jupyter notebooks

Please find several Google Colab Notebooks

Example function

>>> from jarvis.core.atoms import Atoms
>>> box = [[2.715, 2.715, 0], [0, 2.715, 2.715], [2.715, 0, 2.715]]
>>> coords = [[0, 0, 0], [0.25, 0.25, 0.25]]
>>> elements = ["Si", "Si"]
>>> Si = Atoms(lattice_mat=box, coords=coords, elements=elements)
>>> density = round(Si.density,2)
>>> print (density)
2.33
>>>
>>> from jarvis.db.figshare import data
>>> dft_3d = data(dataset='dft_3d')
>>> print (len(dft_3d))
36099

References

Please see Publications related to JARVIS-Tools

Correspondence

Please report bugs as Github issues (https://github.com/usnistgov/jarvis/issues) or email to kamal.choudhary@nist.gov.

Funding support

NIST-MGI (https://www.nist.gov/mgi).

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

jarvis-tools-2020.9.2.tar.gz (773.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jarvis_tools-2020.9.2-py2.py3-none-any.whl (845.6 kB view details)

Uploaded Python 2Python 3

File details

Details for the file jarvis-tools-2020.9.2.tar.gz.

File metadata

  • Download URL: jarvis-tools-2020.9.2.tar.gz
  • Upload date:
  • Size: 773.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/45.2.0.post20200209 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.11

File hashes

Hashes for jarvis-tools-2020.9.2.tar.gz
Algorithm Hash digest
SHA256 54d4c34b7504eb7a27bb28691382db45a5190ea6c7f144f80b2a0b3146ba39a1
MD5 59732798d0cf6e77f010c0d0e2dc9e07
BLAKE2b-256 dbe4e93c16da51fe533db537f10faa076a091eea5ce50e664030b0d0bf413c10

See more details on using hashes here.

File details

Details for the file jarvis_tools-2020.9.2-py2.py3-none-any.whl.

File metadata

  • Download URL: jarvis_tools-2020.9.2-py2.py3-none-any.whl
  • Upload date:
  • Size: 845.6 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/45.2.0.post20200209 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.11

File hashes

Hashes for jarvis_tools-2020.9.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 926377be1d9f929b7912e7193d7e827d9265fbc563b2ee22debc39be1aa2b87e
MD5 ce43ee7ccb0e38b6c348dd1a62f3163f
BLAKE2b-256 4fb58aa7b124bec2b9fc4d8ffd7a3e4c9d6c999bd8915ea0e0ad393cfa65c466

See more details on using hashes here.

Supported by

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