Skip to main content

mispr contains FireWorks workflows for Materials Science

Project description

# <img alt=”mispr” src=”docs/logo.png” width=”500”>

[![Downloads](https://pepy.tech/badge/mispr)](https://pepy.tech/project/mispr) [![GitHub tag](https://img.shields.io/github/tag/molmd/mispr)](https://GitHub.com/molmd/mispr/tags/)

[![Codacy Badge](https://app.codacy.com/project/badge/Grade/8c047110974a42af9baed409664d2547)](https://www.codacy.com/gh/molmd/mispr/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=molmd/mispr&amp;utm_campaign=Badge_Grade) ![Website](https://img.shields.io/website?down_message=down&label=mispr%20website&up_message=up&url=https%3A%2F%2Fmolmd.github.io%2Fmispr%2F) ![GitHub commit activity](https://img.shields.io/github/commit-activity/m/molmd/mispr)

Rasha Atwi, Matthew Bliss, and Nav Nidhi Rajput

Stony Brook University

## Overview MISPR is a software that executes, manages, and stores computational materials science simulations. It contains pre-defined density functional theory (DFT) and molecular dynamics (MD) workflows to calculate and analyze different properties of materials. MISPR uses [MDPropTools](https://github.com/molmd/mdproptools) to perform MD analysis.

## Installation You can either download the source from GitHub and compile yourself, or install directly using pip. Please see the [Installation](https://molmd.github.io/mispr/html/installation/index.html) page for detailed instructions.

## Useful Links - [MISPR Website](https://molmd.github.io/mispr/): Visit this site to get an overview of MISPR, check the installation instructions, and follow MISPR tutorials - [MISPR API Reference](https://molmd.github.io/mispr/html/py-modindex.html) - [Resources](https://molmd.github.io/mispr/html/resources/resources.html)

## How to cite Please include the following two citations if MISPR and/or MDPropTools were used for an academic study: - Atwi, R., Bliss, M., Makeev, M., & Rajput, N. N. (2022). [MISPR: An automated infrastructure for high-throughput DFT and MD simulations](https://www.nature.com/articles/s41598-022-20009-w). Scientific Reports, 12(1), 1-16. - Atwi, R., Chen, Y., Han, K. S., Mueller, K. T., Murugesan, V., & Rajput, N. N. (2022). [An automated framework for high-throughput predictions of NMR chemical shifts within liquid solutions](https://doi.org/10.1038/s43588-022-00200-9). Nature Computational Science, 2(2), 112-122.

## License Information MISPR is a free, open-source software package (distributed under the [MIT license](https://github.com/molmd/mispr/blob/master/LICENSE)).

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

mispr-0.0.4.tar.gz (3.9 MB view details)

Uploaded Source

Built Distribution

mispr-0.0.4-py3-none-any.whl (138.4 kB view details)

Uploaded Python 3

File details

Details for the file mispr-0.0.4.tar.gz.

File metadata

  • Download URL: mispr-0.0.4.tar.gz
  • Upload date:
  • Size: 3.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for mispr-0.0.4.tar.gz
Algorithm Hash digest
SHA256 0eaa995682dd64af3af059f6d54a1c497304a4e1d6bdc7c68863ef89e9b1e14d
MD5 3c1b92cf208c6f4f27ddc669178f988b
BLAKE2b-256 8decfec7587f33337359d9ee0d2d67f7d5d4934aab72198659eefb75be525ecf

See more details on using hashes here.

File details

Details for the file mispr-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: mispr-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 138.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.6

File hashes

Hashes for mispr-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 8ea6bf5c308d0e509a3fd6a26e3ec5d742fc8c1a3c054c46fa0b7e292dc25e8b
MD5 91d3e0ec2cef3bc7b94e0d44de410f0d
BLAKE2b-256 ca580b4c64bdd7661bd47a4f73a5441509cabbad58ce9ef010980c17febab15d

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