Metadata-Version: 2.2
Name: pypolymlp
Version: 0.13.4
Summary: This is the pypolymlp module.
Author-Email: Atsuto Seko <seko@cms.mtl.kyoto-u.ac.jp>
Maintainer-Email: Atsuto Seko <seko@cms.mtl.kyoto-u.ac.jp>
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
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         THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
         AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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Project-URL: Homepage, https://github.com/sekocha/pypolymlp
Project-URL: Repository, https://github.com/sekocha/pypolymlp
Requires-Python: >=3.9
Requires-Dist: numpy!=2.0.*
Requires-Dist: scipy
Requires-Dist: PyYAML>=5.3
Provides-Extra: symfc
Requires-Dist: symfc; extra == "symfc"
Provides-Extra: phonopy
Requires-Dist: phonopy; extra == "phonopy"
Provides-Extra: phono3py
Requires-Dist: phono3py; extra == "phono3py"
Provides-Extra: spglib
Requires-Dist: spglib; extra == "spglib"
Provides-Extra: tools
Requires-Dist: symfc; extra == "tools"
Requires-Dist: phonopy; extra == "tools"
Requires-Dist: phono3py; extra == "tools"
Requires-Dist: spglib; extra == "tools"
Description-Content-Type: text/markdown

# A generator of polynomial machine learning potentials

## Polynomial machine learning potentials

- [Polynomial machine learning potential repository](http://cms.mtl.kyoto-u.ac.jp/seko/mlp-repository/index.html)

## Citation of pypolymlp

“Tutorial: Systematic development of polynomial machine learning potentials for elemental and alloy systems”, [A. Seko, J. Appl. Phys. 133, 011101 (2023)](https://doi.org/10.1063/5.0129045)

```
@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)
- sparse_dot_mkl (if computing force constants)
- spglib
- pymatgen
- ase

## How to install pypolymlp

- Install from conda-forge

| Version | Last Update | Downloads | Platform | License |
| ---- | ---- | ---- | ---- | ---- |
| ![badge](https://anaconda.org/conda-forge/pypolymlp/badges/version.svg) | ![badge](https://anaconda.org/conda-forge/pypolymlp/badges/latest_release_date.svg) | ![badge](https://anaconda.org/conda-forge/pypolymlp/badges/downloads.svg)| ![badge](https://anaconda.org/conda-forge/pypolymlp/badges/platforms.svg) | ![badge](https://anaconda.org/conda-forge/pypolymlp/badges/license.svg) |

```
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](docs/mlpdev.md)
- [Property calculators](docs/calc.md)
  - 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](docs/strgen.md)
  - Random atomic displacements with constant magnitude
  - Random atomic displacements with sequential magnitudes and volume changes
  - Random atomic displacements, cell expansion, and distortion
- [Utilities](docs/utilities.md)
  - Compression of vasprun.xml files
  - Automatic division of DFT dataset
  - Atomic energies
  - Enumeration of optimal MLPs
  - Estimation of computational costs
- [Python API (MLP development)](docs/api_mlpdev.md)
- [Python API (Property calculations)](docs/api_calc.md)
  - 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](docs/api_other_calc.md)
  - LAMMPS
  - Phonopy
  - ASE
