miniff 0.1.0

A minimal implementation of force fields

[](https://gitlab.kwant-project.org/pulkin/miniff/pipelines)

miniff: a minimal implementation of neural-network force fields

Compute energies and forces of atomic systems with neural networks.


About

This package implements [Behler and Parrinello](https://doi.org/10.1103/PhysRevLett.98.146401) approach to simulating structures and dynamics of atomic systems. You may want to use it if:

• you are interested in structural properties of a system with many atoms such as a molecule or an amorphous material;

• your system is too large for electronic structure treatment (e.g. density functional theory molecular dynamics);

• no empiric potentials for your system exist …

• … or the existing empiric potentials are not sufficient to reach the desired tolerances in energies and forces;

• you are interested in machine learning techniques for materials science problems and are looking for a good starting point for your research.

The package is written in Python3.

Built with

• [pytorch](https://pytorch.org/) is the machine learning and autodiff driver for this package;

• [cython](https://cython.org/) is used for performance-critical tasks such as computing descriptors and their gradients;

• [numpy](https://numpy.org) is the tensor and data engine in addition to torch;

• [scipy](https://www.scipy.org/) is used for sparse data, neighbor search and optimization.

In addition,

• [matplotlib](https://matplotlib.org) is used for plotting, and

• [numericalunits](https://github.com/sbyrnes321/numericalunits) is used for handling units.

Documentation

Hosted on [Read the Docs](https://miniff.readthedocs.io/en/latest/).

Installation

### Setup prerequisites

• Python3

• C compiler: Required for compiling Cython extensions

Examples

• Debian Linux `bash apt-get install -y build-essential python3-dev python3-pip `

• Fedora `bash dnf groupinstall "Development tools" "Development libraries" `

• MacOS:

  Install gcc and make sure it is used by default. `bash brew install gcc ` Add to .bash_profile path and alias: `bash export CC=/usr/local/bin/gcc-10 alias gcc='gcc-10' `

• Windows:

  On Windows, the support for installing a C compiler and compiling cython extensions is cumbersome and outdated as can be inferred from the [Cython Wiki](https://github.com/cython/cython/wiki/CythonExtensionsOnWindows). We suggest to use the Windows subsystem for Linux (WSL) in this case. More information on WSL and its installation instructions are [here](https://docs.microsoft.com/en-us/windows/wsl/install-win10).

### Installation steps

1. Clone the repository on your system ` git clone https://gitlab.kwant-project.org/qt/miniff.git ` Move to the root of the project by executing cd miniff/ and continue with the following steps from inside this directory.

2. Install the dependencies

   • New Conda environment: use the provided [environment.yml](environment.yml). ` conda env create -n <my-env> -f environment.yml ` Activate the above created virtual environment ` conda activate <my-env> `

   • pip: use [requirements.txt](requirements.txt). ` pip install -r requirements.txt `

3. Build and install miniff

   Use the provided [setup.py](setup.py).

   `bash python3 setup.py build python3 setup.py install `

4. Verify your installation

   `python python >>> import miniff >>> `

5. (optional) Run tests

   `bash python3 setup.py nosetests `

Contributing

See CONTRIBUTING.md for contirbution guidelines

Authors

See AUTHORS.MD for the list of contributors

License

This work is licensed under BSD 2-Clause License