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Open Source Science

https://github.com/sekocha/pypolymlp

Generator of polynomial machine learning potentials

https://github.com/sekocha/pypolymlp

Science Score: 39.0%

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 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.3%) to scientific vocabulary

Keywords

computational-physics interatomic-potentials materials-informatics materials-science physics
Last synced: 6 months ago · JSON representation

Repository

Generator of polynomial machine learning potentials

Basic Info
  • Host: GitHub
  • Owner: sekocha
  • License: bsd-3-clause
  • Language: C++
  • Default Branch: develop
  • Homepage: https://sekocha.github.io
  • Size: 79.6 MB
Statistics
  • Stars: 15
  • Watchers: 2
  • Forks: 5
  • Open Issues: 0
  • Releases: 1
Topics
computational-physics interatomic-potentials materials-informatics materials-science physics
Created over 2 years ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

A generator of polynomial machine learning potentials

Polynomial machine learning potentials

Citation of pypolymlp

“Tutorial: Systematic development of polynomial machine learning potentials for elemental and alloy systems”, A. Seko, J. Appl. Phys. 133, 011101 (2023)

@article{pypolymlp, author = {Seko, Atsuto}, title = "{"Tutorial: Systematic development of polynomial machine learning potentials for elemental and alloy systems"}", journal = {J. Appl. Phys.}, volume = {133}, number = {1}, pages = {011101}, year = {2023}, month = {01}, }

Required libraries and python modules

  • python >= 3.9
  • numpy != 2.0.*
  • scipy
  • pyyaml
  • setuptools
  • eigen3
  • pybind11
  • openmp (recommended)

[Optional] - phonopy (if using phonon datasets and/or computing force constants) - phono3py (if using phonon datasets and/or computing force constants) - symfc (if computing force constants) - sparsedotmkl (if computing force constants) - spglib - pymatgen - ase

How to install pypolymlp

  • Install from conda-forge

| Version | Last Update | Downloads | Platform | License | | ---- | ---- | ---- | ---- | ---- | | badge | badge | badge| badge | badge |

conda create -n pypolymlp-env conda activate pypolymlp-env conda install -c conda-forge pypolymlp

  • Install from PyPI conda create -n pypolymlp-env conda activate pypolymlp-env conda install -c conda-forge numpy scipy pybind11 eigen cmake cxx-compiler pip install pypolymlp Building C++ codes in pypolymlp may require a significant amount of time.

  • Install from GitHub git clone https://github.com/sekocha/pypolymlp.git cd pypolymlp conda create -n pypolymlp-env conda activate pypolymlp-env conda install -c conda-forge numpy scipy pybind11 eigen cmake cxx-compiler pip install . -vvv Building C++ codes in pypolymlp may require a significant amount of time.

How to use pypolymlp

  • Polynomial MLP development
  • Property calculators
    • Energy, forces on atoms, and stress tensor
    • Force constants
    • Elastic constants
    • Equation of states
    • Structural features (Polynomial invariants)
    • Phonon properties, Quasi-harmonic approximation
    • Local geometry optimization
    • Molecular dynamics
    • Thermodynamic integration using MD
  • DFT structure generator
    • Random atomic displacements with constant magnitude
    • Random atomic displacements with sequential magnitudes and volume changes
    • Random atomic displacements, cell expansion, and distortion
  • Utilities
    • Compression of vasprun.xml files
    • Automatic division of DFT dataset
    • Atomic energies
    • Enumeration of optimal MLPs
    • Estimation of computational costs
  • Python API (MLP development)
  • Python API (Property calculations)
    • Energy, forces on atoms, and stress tensor
    • Force constants
    • Elastic constants
    • Equation of states
    • Structural features (Polynomial invariants)
    • Phonon properties, Quasi-harmonic approximation
    • Local geometry optimization
    • Molecular dynamics
    • Thermodynamic integration using MD
    • Self-consistent phonon calculations
  • How to use polymlp in other calculator tools
    • LAMMPS
    • Phonopy
    • ASE

Owner

  • Name: Atsuto Seko
  • Login: sekocha
  • Kind: user
  • Location: Kyoto, Japan
  • Company: Kyoto University

GitHub Events

Total
  • Issues event: 2
  • Watch event: 7
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 485
  • Pull request event: 4
  • Fork event: 2
  • Create event: 40
Last Year
  • Issues event: 2
  • Watch event: 7
  • Delete event: 2
  • Issue comment event: 1
  • Push event: 485
  • Pull request event: 4
  • Fork event: 2
  • Create event: 40

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 1
  • Total pull requests: 2
  • Average time to close issues: 9 days
  • Average time to close pull requests: 8 days
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 2
  • Average time to close issues: 9 days
  • Average time to close pull requests: 8 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • yurivict (1)
Pull Request Authors
  • sekocha (3)
  • narutak (1)
  • atztogo (1)
  • hytwakai (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 419 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 77
  • Total maintainers: 1
pypi.org: pypolymlp

This is the pypolymlp module.

  • Homepage: https://github.com/sekocha/pypolymlp
  • Documentation: https://pypolymlp.readthedocs.io/
  • License: BSD 3-Clause License Copyright (c) 2024, pypolymlp Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  • Latest release: 0.14.1
    published 6 months ago
  • Versions: 77
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 419 Last month
Rankings
Dependent packages count: 10.7%
Average: 35.5%
Dependent repos count: 60.2%
Maintainers (1)
sekocha
Last synced: 6 months ago

Dependencies

.github/workflows/publish-to-test-pypi.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v5 composite
  • pypa/gh-action-pypi-publish release/v1 composite
pyproject.toml pypi