https://github.com/aiidateam/aiida-hubbard

Self-consistent onsite and intersite Hubbard parameters from first-principles

https://github.com/aiidateam/aiida-hubbard

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: sciencedirect.com
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.7%) to scientific vocabulary

Keywords

dfpt dft hubbard

Keywords from Contributors

aiida common-workflows
Last synced: 5 months ago · JSON representation

Repository

Self-consistent onsite and intersite Hubbard parameters from first-principles

Basic Info
Statistics
  • Stars: 5
  • Watchers: 6
  • Forks: 1
  • Open Issues: 8
  • Releases: 4
Topics
dfpt dft hubbard
Created over 5 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License

README.md

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.

| | | |-----|----------------------------------------------------------------------------| | Reference | DOI | |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 | |-|-|-|-| | v0.3.0 | Compatibility for v4.0 | PyPI pyversions | Quantum ESPRESSO compatibility | | v0.1.0 < v0.2.0 | 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:

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

Owner

  • Name: AiiDA team
  • Login: aiidateam
  • Kind: organization

The development team of AiiDA

GitHub Events

Total
  • Create event: 27
  • Issues event: 4
  • Release event: 2
  • Watch event: 1
  • Delete event: 22
  • Issue comment event: 26
  • Push event: 42
  • Pull request event: 39
  • Fork event: 1
Last Year
  • Create event: 27
  • Issues event: 4
  • Release event: 2
  • Watch event: 1
  • Delete event: 22
  • Issue comment event: 26
  • Push event: 42
  • Pull request event: 39
  • Fork event: 1

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 159
  • Total Committers: 5
  • Avg Commits per committer: 31.8
  • Development Distribution Score (DDS): 0.39
Past Year
  • Commits: 26
  • Committers: 2
  • Avg Commits per committer: 13.0
  • Development Distribution Score (DDS): 0.038
Top Committers
Name Email Commits
Sebastiaan Huber m****l@s****t 97
Lorenzo 7****o 52
Timo Reents 7****s 5
Marnik Bercx m****x@g****m 4
aiida-cla-bot[bot] 1****] 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 50
  • Average time to close issues: about 1 hour
  • Average time to close pull requests: 2 days
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 2.5
  • Average comments per pull request: 0.88
  • Merged pull requests: 48
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 50
  • Average time to close issues: about 1 hour
  • Average time to close pull requests: 2 days
  • Issue authors: 2
  • Pull request authors: 1
  • Average comments per issue: 2.5
  • Average comments per pull request: 0.88
  • Merged pull requests: 48
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • bastonero (1)
  • NarjesJOMAA (1)
Pull Request Authors
  • bastonero (50)
Top Labels
Issue Labels
type/requested feature (1) topic/documentation (1) priority/important (1) topic/calcjobs (1)
Pull Request Labels
pr/blocked (4) topic/dependencies (4) priority/important (1) topic/testing (1)

Dependencies

.github/workflows/ci.yml actions
  • actions/cache v1 composite
  • actions/checkout v1 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • rabbitmq latest docker
pyproject.toml pypi
  • aiida-core ~=2.2
  • aiida-quantumespresso ~=4.3