masci-tools

Post-processing toolkit for electronic structure calculations

https://github.com/judftteam/masci-tools

Science Score: 59.0%

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: zenodo.org
  • Committers with academic emails
    9 of 25 committers (36.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.0%) to scientific vocabulary

Keywords

band-structure computational-materials-science density-functional-theory density-of-states electronic-structure forschungszentrum-juelich high-throughput judft materials-informatics parsing toolkit utility visualization

Keywords from Contributors

superconductivity multiple-scattering magnetism kkr greens-functions full-potential defects ab-initio aiida all-electron
Last synced: 6 months ago · JSON representation

Repository

Post-processing toolkit for electronic structure calculations

Basic Info
Statistics
  • Stars: 17
  • Watchers: 5
  • Forks: 11
  • Open Issues: 18
  • Releases: 26
Topics
band-structure computational-materials-science density-functional-theory density-of-states electronic-structure forschungszentrum-juelich high-throughput judft materials-informatics parsing toolkit utility visualization
Created about 8 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License Authors Zenodo

README.md

MIT license GitHub version PyPI version PyPI pyversion Conda Version Build status Coverage Status Documentation Status DOI

masci-tools

Masci-tools (short for "materials science tools") is a post-processing toolkit for electronic structure calculations. Its well-documented Python interface simplifies I/O parsing, visualization such as bandstructure and DOS plotting, and data analysis.

Feel free to contribute.

The code is hosted on GitHub at https://github.com/JuDFTteam/masci-tools

The documentation is hosted on https://masci-tools.readthedocs.io.

Most functionality was developed for the use with the DFT codes developed at the Forschungszentrum Jülich (http://judft.de) and their AiiDA plugins for high-throughput calculations (aiida-fleur, aiida-kkr, aiida-spirit).

Installation

pip install masci-tools

Dependencies

These python packages are needed: * lxml * h5py * deepdiff * humanfriendly
* matplotlib * seaborn * ase * pymatgen * mendeleev * click * click-completion * PyYAML * tabulate

It should not depend on aiida-core!

Layout of masci-tools

  • io
    • Contains methods to write certain files
    • io.parsers: Contains parsers of certain code output or input files
  • testing
    • Contains utilities/fixtures for testing that can be useful outside the package
  • util
    • Contains rather low-level utility
  • tools
    • Contains rather high-level utility which is rather complete
  • vis
    • Contains a collection of matplotlib/bokeh methods used for plotting common results from material science simulations, e.g. bandstructures, DOS, ...
  • cmdline
    • Contains a small click command line interface exposing some parts of the library

License

masci-tools is distributed under the terms and conditions of the MIT license which is specified in the LICENSE.txt file.

Owner

  • Name: JuDFTteam
  • Login: JuDFTteam
  • Kind: organization

JuDFTteam is the GitHub home of the quantum materials simulation codes and toolkits developed by the division Quantum Theory of Materials at FZ Jülich.

GitHub Events

Total
  • Delete event: 2
  • Issue comment event: 4
  • Push event: 16
  • Pull request event: 3
  • Fork event: 2
Last Year
  • Delete event: 2
  • Issue comment event: 4
  • Push event: 16
  • Pull request event: 3
  • Fork event: 2

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 2,871
  • Total Committers: 25
  • Avg Commits per committer: 114.84
  • Development Distribution Score (DDS): 0.22
Past Year
  • Commits: 268
  • Committers: 10
  • Avg Commits per committer: 26.8
  • Development Distribution Score (DDS): 0.347
Top Committers
Name Email Commits
janssenhenning h****n@g****t 2,239
johannes wasmer j****r@g****m 211
Philipp Rüssmann p****n@f****e 182
broeder j****r@f****e 61
pre-commit-ci[bot] 6****]@u****m 54
johannes wasmer j****r@f****e 29
Robin Hilgers 8****g@u****m 25
dependabot[bot] 4****]@u****m 25
stefansr-fzj 4****j@u****m 17
Anoop Chandran a****n@g****m 5
Vasily Tseplyaev v****v@f****e 4
Henning Janßen h****n@f****e 3
Christian Partmann c****n@1****e 2
Jens Broeder b****j@u****m 2
Jonathan Chico j****o@s****m 2
Conor MacBride c****r@m****e 1
Fabian Bertoldo b****t@i****e 1
github-actions[bot] 4****]@u****m 1
Matthias Redies m****s@p****e 1
J.Broeder b****r@i****e 1
Vasily Tseplyaev 4****v@u****m 1
janssenhenning j****g@u****m 1
antognini d****a@f****e 1
dantogni d****a@f****e 1
Praneeth Katta p****a@r****e 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 107
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 23 days
  • Total issue authors: 4
  • Total pull request authors: 7
  • Average comments per issue: 1.0
  • Average comments per pull request: 1.21
  • Merged pull requests: 85
  • Bot issues: 0
  • Bot pull requests: 49
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 1
Top Authors
Issue Authors
  • janssenhenning (4)
  • PhilippRue (1)
  • Irratzo (1)
  • soumyajyotih (1)
Pull Request Authors
  • janssenhenning (52)
  • dependabot[bot] (43)
  • pre-commit-ci[bot] (7)
  • PhilippRue (3)
  • github-actions[bot] (2)
  • RobinHilg (2)
  • broeder-j (1)
Top Labels
Issue Labels
enhancement (2) visualization (2) parser/fleur (1) bug (1)
Pull Request Labels
dependencies (43) enhancement (14) maintenance (12) xml-functions (12) docs (6) parser/fleur (4) bug (3) visualization (3) cmdline (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 855 last-month
  • Total dependent packages: 6
    (may contain duplicates)
  • Total dependent repositories: 4
    (may contain duplicates)
  • Total versions: 77
  • Total maintainers: 3
pypi.org: masci-tools

masci-tools is a collection of tools for materials science.

  • Versions: 65
  • Dependent Packages: 4
  • Dependent Repositories: 4
  • Downloads: 855 Last month
Rankings
Dependent packages count: 1.9%
Dependent repos count: 7.5%
Average: 9.4%
Forks count: 10.9%
Downloads: 12.5%
Stargazers count: 14.2%
Last synced: 6 months ago
conda-forge.org: masci-tools

Collection of tools for Materials science. Focused on working with input/output from the Fleur and KKR codes developed at the FZ Juelich, but many routines can be used in a wider context. Also contains routines for visualization of standard material science results with matplotlib/bokeh

  • Versions: 12
  • Dependent Packages: 2
  • Dependent Repositories: 0
Rankings
Dependent packages count: 19.5%
Dependent repos count: 34.0%
Average: 35.2%
Forks count: 40.9%
Stargazers count: 46.3%
Last synced: 6 months ago