<h1 align="center">
<img src="https://github.com/materialsvirtuallab/matcalc/assets/30958850/89486f2f-73fb-40fb-803a-dfafe510eb6d" width="100" alt="MatCalc logo" style="vertical-align: middle;" /><br>
MatCalc
</h1>
<h4 align="center">
[](https://github.com/materialsvirtuallab/matcalc/blob/main/LICENSE)
[](https://github.com/materialsvirtuallab/matcalc/workflows/Linting/badge.svg)
[](https://github.com/materialsvirtuallab/matcalc/workflows/Testing/badge.svg)
[](https://codecov.io/gh/materialsvirtuallab/matcalc)
[](https://python.org/downloads)
[](https://pypi.org/project/matcalc?logo=pypi&logoColor=white)
</h4>
## Docs
[materialsvirtuallab.github.io/matcalc](https://materialsvirtuallab.github.io/matcalc)
## Introduction
MatCalc is a Python library for calculating material properties from the potential energy surface (PES). The
PES can come from DFT or, more commonly, from machine learning interatomic potentials (MLIPs).
Calculating material properties often requires involved setups of various simulation codes. The
goal of MatCalc is to provide a simplified, consistent interface to access these properties with any
parameterization of the PES.
## Outline
The main base class in MatCalc is `PropCalc` (property calculator). [All `PropCalc` subclasses](https://github.com/search?q=repo%3Amaterialsvirtuallab%2Fmatcalc%20%22(PropCalc)%22) should implement a
`calc(pymatgen.Structure) -> dict` method that returns a dictionary of properties.
In general, `PropCalc` should be initialized with an ML model or ASE calculator, which is then used by either ASE,
LAMMPS or some other simulation code to perform calculations of properties.
## Cite `matcalc`
If you use `matcalc` in your research, see [`citation.cff`](citation.cff) or the GitHub sidebar for a BibTeX and APA citation.
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