Skip to main content

AiiDA plugin for the first-principles calculation of Hubbard parameters.

Project description

aiida-hubbard

AiiDA plugin for the first-principles calculation of Hubbard parameters.

This is also the official AiiDA plugin for the HP code of Quantum ESPRESSO.

Latest release PyPI versionPyPI pyversions
Getting help Docs status Discourse status
Build status Build Status Coverage Status
Activity PyPI-downloads Commit Activity
Community Discourse

Compatibility matrix

The matrix below assumes the user always install the latest patch release of the specified minor version, which is recommended.

Plugin AiiDA Python Quantum ESPRESSO
v0.1.0 Compatibility for v4.0 PyPI pyversions Quantum ESPRESSO compatibility

Installation

To install using pip, simply execute:

pip install aiida-hubbard

or when installing from source:

git clone https://github.com/aiidateam/aiida-hubbard
pip install aiida-hubbard

Pseudopotentials

Pseudopotentials are installed and managed through the aiida-pseudo plugin. The easiest way to install pseudopotentials, is to install a version of the SSSP through the CLI of aiida-pseudo. Simply run

aiida-pseudo install sssp

to install the default SSSP version. List the installed pseudopotential families with the command aiida-pseudo list. You can then use the name of any family in the command line using the -F flag.

Development

Running tests

To run the tests, simply clone and install the package locally with the [tests] optional dependencies:

git clone https://github.com/aiidateam/aiida-hubbard .
cd aiida-hubbard
pip install -e .[tests]  # install extra dependencies for test
pytest -sv tests # run tests
pytest -sv examples # run examples

You can also use tox to run the test set. Here you can also use the -e option to specify the Python version for the test run. Example:

pip install tox
tox -e py39 -- tests/calculations/hp/test_hp.py

Pre-commit

To contribute to this repository, please enable pre-commit so the code in commits are conform to the standards. Simply install the repository with the pre-commit extra dependencies:

cd aiida-hubbard
pip install -e .[pre-commit]
pre-commit install

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

aiida_hubbard-0.1.0.tar.gz (1.3 MB view details)

Uploaded Source

Built Distribution

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

aiida_hubbard-0.1.0-py3-none-any.whl (55.4 kB view details)

Uploaded Python 3

File details

Details for the file aiida_hubbard-0.1.0.tar.gz.

File metadata

  • Download URL: aiida_hubbard-0.1.0.tar.gz
  • Upload date:
  • Size: 1.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.3

File hashes

Hashes for aiida_hubbard-0.1.0.tar.gz
Algorithm Hash digest
SHA256 398c1597abc5c458e96d06d5fc0565b33794ddff8d681c80efb443518e6179ae
MD5 eb47487d499fb0971264a0e397486c2b
BLAKE2b-256 34bbe25d3ab3f75ff7cf793d8914f35486c6d8b285b427e2619bf9d730e926de

See more details on using hashes here.

File details

Details for the file aiida_hubbard-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: aiida_hubbard-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 55.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.3

File hashes

Hashes for aiida_hubbard-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 264dc1a72bc9fce4bdf2264c7375313f2331b58be8e9a15f6602822720d721f2
MD5 ae55341cafda0ae42b47a95251ab54c1
BLAKE2b-256 8030bf646f02f13961cc6db6f1365f7ddde404e01a43ed1cc696a0cce47001fd

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