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: 10 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 over 8 years ago · Last pushed 10 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: about 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: 10 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: 10 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: 10 months ago