Skip to main content

CLuster Expansion in Atomistic Simulation Environment

Project description

CLEASE

coverage PyPI version Conda Documentation Status

CLuster Expansion in Atomic Simulation Environment (CLEASE) is a package that automates the cumbersome setup and construction procedure of cluster expansion (CE). It provides a comprehensive list of tools for specifying parameters for CE, generating training structures, fitting effective cluster interaction (ECI) values and running Monte Carlo simulations. A detailed description of the package can be found in the documentation and our paper.

For information on how to contribute to CLEASE, please see the contributing file.

Installation

Install the CLEASE code by executing

pip install clease

Alternative, CLEASE is also available through anaconda on conda via conda-forge. We recommend installing CLEASE via conda on windows machines in order to simplify compilations, as pip tends to have a hard time compiling the C++ code. Install into your conda environment:

conda install -c conda-forge clease

Graphical User Interface

Clease has a stand-alone jupyter notebook GUI, which is capable of performing most of the standard CE routines. It can be found here.

CLEASE GUI can be installed from PyPI or anaconda using one of the two following commands.

PyPI

pip install clease[gui]

Anaconda

conda install -c conda-forge clease-gui

Development

If you are a developer you might want to install CLEASE by executing the following command in the root folder of the project

pip install -e .

In order to run the tests, the testing dependencies should be installed. They can be installed with the extra test option

pip install .[test]

There is an additional option for development purposes, dev, which contains some convenience packages. All of the extras options can be installed via the all option, i.e.

pip install .[all]

Note, that if you are using zsh, you need to escape the argument, e.g.

pip install '.[all]'

Troubleshooting

If you are running on Mac and get the error

fatal error: 'ios' file not found

try this before installing

export MACOSX_DEPLOYMENT_TARGET=10.14

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

clease-1.0.2.tar.gz (493.2 kB view details)

Uploaded Source

Built Distributions

clease-1.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

clease-1.0.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

clease-1.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

clease-1.0.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

clease-1.0.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

clease-1.0.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (2.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

clease-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

clease-1.0.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (2.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

File details

Details for the file clease-1.0.2.tar.gz.

File metadata

  • Download URL: clease-1.0.2.tar.gz
  • Upload date:
  • Size: 493.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for clease-1.0.2.tar.gz
Algorithm Hash digest
SHA256 26112ab12b1aa7e1ff0a2f49d16aaa13b6a3afa3f748101c1efb4d4a0dfeee95
MD5 3954d8e031a54432b80e2dbef1c57047
BLAKE2b-256 00e632d28224efb6f72d8c79be3225317795d51c6f527c2a75e51789dea348de

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 afbe72f46599341c5a8fd736c8229e538e825de4fcf58a3892c623b0c4bcedee
MD5 15607f6fa31cb57995d46ad48d092459
BLAKE2b-256 f6a14307aa95f17b0c24b2b0fdd351e283a05747052128f061f2ad6b7f3dd12a

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 a615e18ad430d90c7f84d03eb4089ea8ecfaa3d801f7808af2bc7194cfd39289
MD5 80693063467c4bf77aa50d9dd325d5ad
BLAKE2b-256 0bfcecd921881abba969b89babccde88e1e81e962339a4320aa2c2ac7e50fb09

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ab7669c07ae46ca8fc0c36e47ae8c536705b840ad97516960bd36f7ef5323c04
MD5 888ead8f44ca8c7aa49eebb39a073610
BLAKE2b-256 e5a37af0f0b6b1d6dd89e52d3ab0767847eebe5dc769a1fd39b878d5d7f0fe1e

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 f2b803c2d7d741854024bc471256b6561208decf36d052d4ff96eb3f0f3749a8
MD5 2d572141e6d24da2c0ed856e8d098ad7
BLAKE2b-256 ae4cf65f4375f6572919b4a71d42602f0658a6e3fed4519f9c11b263ece4a22f

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 09930fdfba4932220416b2dfbc615ae3d4c4dfdd3486a1fb6f9240dacae4930f
MD5 af69c13ce8508e8c71482c682b05d0f2
BLAKE2b-256 2d868d1dfc69940ff5e454158fba2d3cb2487c804a5952b9b0cb9831c471d274

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9760e87e7468d95a1a07130eb64e7677786a64b39635924061230d635fe2fe49
MD5 5da9eab014fce2daed1480067738d703
BLAKE2b-256 aa73973b7579b4d41f98c8aa7af88c0973ca5a00c0734ddc043225b92af64869

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 bfda856d0a02de9540b57a2c450d8c67df4f6f0497ce413af15422522d6be984
MD5 88a5e147f1a64d9be1c1151bb1e1559f
BLAKE2b-256 999dcd38ea7cafd85a0107ee6b89a5b5e727cfc897742c671181628e0303f7da

See more details on using hashes here.

File details

Details for the file clease-1.0.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for clease-1.0.2-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9caac01931a681f5bdb18942d44ac5cf8293a9a13516218249158f28d65d06c0
MD5 e73efce0fe0294b78344b1a9e921c48b
BLAKE2b-256 39ef5fa02eea3dfdbef64455b6c65c179d73b160cb053c02e721c155ef64d648

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