Skip to main content

A Crystal Tortuosity Module

Project description

JOSS status DOI PyPI version Build Status Coverage Status Documentation Status Python 3.6 Python 3.7

crystal_torture:

crystal_torture is a Python, Fortran and OpenMP crystal structure analysis module. The module contains a set of classes that enable:

  • a crystal structure to be converted into a graph for network analysis

  • connected clusters of crystal sites (nodes) to be retrieved and output

  • periodicity of connected clusters of crystal sites to be determined

  • relative path tortuosity to traverse a crystal within a connected cluster to be calculated for each site

Installation

crystal_torture requires python 3.6 and above. To install do:

pip install crystal_torture

or download directly from GitHub, or clone:

git clone https://github.com/connorourke/crystal_torture

and install

cd crystal_torture
python setup.py install

Tests

crystal_torture is automatically tested on each commit here, but the tests can be manually run:

python -m unittest discover

Examples

Examples on how to use crystal_torture can be found in a Jupyter notebook in the examples directory crystal_torture_examples.ipynb

Documentation

Documentation can be found here

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

crystal_torture-1.0.09.tar.gz (6.8 MB view details)

Uploaded Source

File details

Details for the file crystal_torture-1.0.09.tar.gz.

File metadata

  • Download URL: crystal_torture-1.0.09.tar.gz
  • Upload date:
  • Size: 6.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.21.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.5

File hashes

Hashes for crystal_torture-1.0.09.tar.gz
Algorithm Hash digest
SHA256 b2f79419b0c807886781e7c20c5468580e091ebeb933c59e3d18aa1bc1219347
MD5 f0fdd8d9f1ab8bf196ca259efdcbf909
BLAKE2b-256 79c920de4f745118a3ba6ffa68c820a8387503ed185cb4c9acf17b6680d7ba23

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