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LobsterPy

LobsterPy: A package to automatically analyze LOBSTER runs - Published in JOSS (2024)

https://github.com/jageo/lobsterpy

Science Score: 93.0%

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    Found 21 DOI reference(s) in README and JOSS metadata
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    Published in Journal of Open Source Software

Keywords

chemical-bonding computational-chemistry computational-materials-science materials-informatics plotting python

Keywords from Contributors

exoplanet materials-science energy-system hydrology mesh hierarchical-data data-comparison ode geoscience gravitational-lensing

Scientific Fields

Materials Science Physical Sciences - 32% confidence
Last synced: 4 months ago · JSON representation

Repository

Package to perform automatic bonding analysis with the program Lobster in the field of computational materials science and quantum chemistry

Basic Info
Statistics
  • Stars: 101
  • Watchers: 4
  • Forks: 34
  • Open Issues: 10
  • Releases: 37
Topics
chemical-bonding computational-chemistry computational-materials-science materials-informatics plotting python
Created almost 5 years ago · Last pushed 4 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

CI Status pre-commit.ci status codecov build-docs PyPI version PyPI downloads Downloads supported python versions DOI status

Getting started

LobsterPy Logo which consists of a green Python and a red Lobster

LobsterPy is a package that enables automatic analysis of LOBSTER outputs to get summarized bonding information and relevant bond plots. Additionally, one can also generate features for machine learning studies from LOBSTER outputs. One can download LOBSTER from http://www.cohp.de.

Important

Recently released [LOBSTER 5.0](https://schmeling.ac.rwth-aachen.de/cohp/index.php?menuID=6) now generates `POSCAR.lobster` for any kind of LOBSTER calculation by default (This file has same format as the POSCAR from VASP). Thus, LobsterPy in principle, now supports usage with **all** DFT codes supported by LOBSTER and is **no** longer limited to `VASP`. Almost all of the core functionalities of LobsterPy could be used. The user must use `POSCAR.lobster` for `path_to_poscar` and `-fstruct` argument in python and cli interface, respectively. The only functionality limited to VASP is DOS comparisons and basis set analysis in the `calc_quality_summary` method of the `Analysis` class, as it relies on VASP output files, namely `vasprun.xml` and `POTCAR`.

Please note that LobsterPy relies on the LOBSTER computation output files. Thus, it will be only able to analyze data that has been computed in the LOBSTER run.

LobsterPyAnimation

Installation

Python version

Before the installation, please make sure that you are using one of the supported Python versions (see pyproject.toml).

Standard installation

Install using pip install lobsterpy

Installation with featurizer

Install using pip install lobsterpy[featurizer]

Contributing guidelines / Developers installation

A short guide to contributing to LobsterPy can be found here. Additional information for developers can be found here.

Basic usage

  • Automatic analysis and plotting of COHPs / COBIS / COOPs:

    Output Automatic Analysis

You can use lobsterpy description for an automated analysis of COHPs for relevant cation-anion bonds or lobsterpy automatic-plot to plot the results automatically. It will evaluate all COHPs with ICOHP values down to 10% of the strongest ICOHP. You can enforce an analysis of all bonds by using lobsterpy automatic-plot --allbonds. You can also switch the automatic analysis to use the ICOBIs or ICOOPs. You need to add --cobis or --coops along with the mentioned commands for e.g.like lobsterpy description --cobis

An interactive plotter is available via lobsterpy automatic-plot-ia.

Currently, the computed Mulliken charges will be used to determine cations and anions. If no CHARGE.lobster is available, the algorithm will fall back to the BondValence analysis from pymatgen.

Please be aware that LobsterPy can only analyze bonds that have been included in the initial Lobster computation. Thus, please use the cohpgenerator within Lobster (i.e., put cohpGenerator from 0.1 to 5.0 in the *lobsterin).*

It is also possible to start this automatic analysis from a Python script. See "examples" for scripts.

  • Plotting DOS from LOBSTER computations:

To plot densities of states obtained from LOBSTER use lobsterpy plot-dos.

  • Generic COHP/ COOP / COBI plotter:

We included options to plot COHPs/COBIs/COOPs from the command line. lobsterpy plot 1 2 will plot COHPs of the first and second bond from COHPCAR.lobster. It is possible to sum or integrate the COHPs as well (--summed, --integrated). You can switch to COBIs or COOPs by using --cobis or --coops, respectively.

  • Other command line tools:

    lobsterpy create-inputs will create standard inputs based on existing POSCAR, POTCAR, and INCAR files. It will allow testing for different basis sets that are available in Lobster. This feature is currently only available for PBE_54 POTCARs, as only the pbeVASPfit2015 basis in LOBSTER that has been fitted to PBE POTCARs includes additional orbitals relevant to solid-state materials. Please check out our publication https://doi.org/10.1002/cplu.202200123 and LOBSTER program manual for more information

  • Further help?

    You can get further information by using lobsterpy --help and also by typing lobsterpy description --help, lobsterpy automatic-plot --help, lobsterpy plot --help.

Documentation

How to cite?

Please cite our papers: * A. A. Naik, K. Ueltzen, C. Ertural, A. J. Jackson, J. George, Journal of Open Source Software 2024, 9, 6286. https://joss.theoj.org/papers/10.21105/joss.06286. * J. George, G. Petretto, A. Naik, M. Esters, A. J. Jackson, R. Nelson, R. Dronskowski, G.-M. Rignanese, G. Hautier, ChemPlusChem 2022, 87, e202200123. https://doi.org/10.1002/cplu.202200123 (Information on the methodology of the automatic analysis)

If you use any of the following Featurizers, also cite the respective papers:

Please cite pymatgen, Lobster, and ChemEnv correctly as well.

LobsterPy is now a part of an atomate2 workflow

LobsterWorkflow

We have now also included the automatic analysis into a fully automatic workflow using VASP and Lobster in atomate2. More documentation and information will follow soon.

Acknowledgements

The development of the program has been supported by a computing time grant. We gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre (www.lrz.de) (project pn73da).

Owner

  • Name: J. George
  • Login: JaGeo
  • Kind: user
  • Location: Berlin, Germany
  • Company: Federal Institute for Materials Research and Testing

(Computational) Chemist. Junior Group Leader at BAM and at University of Jena, Germany. Before: PostDoc at UCLouvain and PhD at RWTH Aachen.

JOSS Publication

LobsterPy: A package to automatically analyze LOBSTER runs
Published
February 27, 2024
DOI
Volume 9, Issue 94, Page 6286
Authors
Aakash Ashok Naik ORCID
Federal Institute for Materials Research and Testing, Materials Chemistry Department, Berlin, 12205, Germany, Friedrich Schiller University Jena, Institute of Condensed Matter Theory and Solid-State Optics, Jena, 07743, Germany
Katharina Ueltzen ORCID
Federal Institute for Materials Research and Testing, Materials Chemistry Department, Berlin, 12205, Germany
Christina Ertural ORCID
Federal Institute for Materials Research and Testing, Materials Chemistry Department, Berlin, 12205, Germany
Adam J. Jackson ORCID
Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
Janine George ORCID
Federal Institute for Materials Research and Testing, Materials Chemistry Department, Berlin, 12205, Germany, Friedrich Schiller University Jena, Institute of Condensed Matter Theory and Solid-State Optics, Jena, 07743, Germany
Editor
Rocco Meli ORCID
Tags
Automation Bonding analysis Machine learning
View PDF Review Thread Software Archive

GitHub Events

Total
  • Create event: 27
  • Release event: 7
  • Issues event: 26
  • Watch event: 20
  • Delete event: 20
  • Member event: 1
  • Issue comment event: 73
  • Push event: 132
  • Pull request review comment event: 46
  • Pull request review event: 83
  • Pull request event: 101
  • Fork event: 5
Last Year
  • Create event: 27
  • Release event: 7
  • Issues event: 26
  • Watch event: 20
  • Delete event: 20
  • Member event: 1
  • Issue comment event: 73
  • Push event: 132
  • Pull request review comment event: 46
  • Pull request review event: 83
  • Pull request event: 101
  • Fork event: 5

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 1,570
  • Total Committers: 14
  • Avg Commits per committer: 112.143
  • Development Distribution Score (DDS): 0.381
Past Year
  • Commits: 301
  • Committers: 8
  • Avg Commits per committer: 37.625
  • Development Distribution Score (DDS): 0.256
Top Committers
Name Email Commits
anaik a****k@s****e 972
J. George J****o 380
dependabot[bot] 4****] 76
pre-commit-ci[bot] 6****] 38
kueltzen k****n@s****e 36
Adam J. Jackson a****n@p****g 28
Eric Berquist e****t@g****m 16
jgrandel j****l@s****e 9
Christina Ertural 5****t 4
Haoyu (Daniel) y****7@o****m 4
Rocco Meli r****i@b****h 3
JaGeo j****e@P****E 2
Hongyi Zhao h****o@g****m 1
tomdemeyere t****e@i****m 1
Committer Domains (Top 20 + Academic)
sv2218.zit.bam.de: 3 pc-1r0-150.oasis.uclouvain.be: 1 bluemail.ch: 1 physics.org: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 95
  • Total pull requests: 403
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 10 days
  • Total issue authors: 15
  • Total pull request authors: 14
  • Average comments per issue: 1.45
  • Average comments per pull request: 1.49
  • Merged pull requests: 332
  • Bot issues: 0
  • Bot pull requests: 158
Past Year
  • Issues: 19
  • Pull requests: 109
  • Average time to close issues: 18 days
  • Average time to close pull requests: 4 days
  • Issue authors: 9
  • Pull request authors: 7
  • Average comments per issue: 0.74
  • Average comments per pull request: 0.83
  • Merged pull requests: 82
  • Bot issues: 0
  • Bot pull requests: 58
View more stats
Top Authors
Issue Authors
  • naik-aakash (35)
  • JaGeo (31)
  • hongyi-zhao (8)
  • srmnitc (3)
  • QuantumChemist (2)
  • DanielYang59 (2)
  • kaueltzen (2)
  • BAjiao-A86 (1)
  • yuan-gist (1)
  • jmmshn (1)
  • tomdemeyere (1)
  • zc994646659 (1)
  • yumaoDFT (1)
  • alibh95 (1)
  • berquist (1)
Pull Request Authors
  • naik-aakash (158)
  • dependabot[bot] (125)
  • JaGeo (73)
  • pre-commit-ci[bot] (29)
  • github-actions[bot] (11)
  • DanielYang59 (4)
  • ajjackson (3)
  • berquist (3)
  • kaueltzen (3)
  • hongyi-zhao (2)
  • RMeli (2)
  • QuantumChemist (1)
  • schroedingercode (1)
  • JonasGrandel (1)
Top Labels
Issue Labels
enhancement (22) bug (9) documentation (4) help wanted (1)
Pull Request Labels
dependencies (124) enhancement (19) automated-pr (17) bug (16) python (10) housekeeping (5) documentation (3)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 2,774 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 3
  • Total versions: 33
  • Total maintainers: 2
pypi.org: lobsterpy

Package for automatic bonding analysis with Lobster/VASP

  • Versions: 33
  • Dependent Packages: 1
  • Dependent Repositories: 3
  • Downloads: 2,774 Last month
Rankings
Dependent packages count: 4.8%
Average: 7.4%
Downloads: 8.5%
Dependent repos count: 9.0%
Maintainers (2)
JaGeo ajjackson
Last synced: 4 months ago

Dependencies

requirements.txt pypi
  • pymatgen ==2022.5.26
setup.py pypi
  • Sphinx ==5.0.2
  • numpy *
  • pymatgen ==2022.5.26
  • sphinx-argparse ==0.3.1
  • sphinx-pdj-theme ==0.2.1
  • typing *
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  • github/codeql-action/init v2 composite
.github/workflows/pylint.yml actions
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.github/workflows/python-package.yml actions
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  • actions/setup-python v2 composite
.github/workflows/python-publish.yml actions
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  • pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
docs/source/requirements.txt pypi
  • Sphinx ==4.5.0
  • docutils *
  • jupyter *
  • lobsterpy *
  • m2r2 *
  • myst-parser *
  • numpy ==1.23.3
  • sphinx-argparse *
  • sphinx-book-theme ==0.3.3