Equistore is a specialized data storage format for all your atomistic machine
learning needs, and more. Think numpy ndarray or pytorch Tensor equipped
with extra metadata for atomic — and other particles — systems. The core of this
library is written in Rust and we provide API for C, C++, and Python.
The main class of equistore is the TensorMap data structure, defining a
custom block-sparse data format. If you are using equistore from Python, we
additionally provide a collection of mathematical, logical and other utility
operations to make working with TensorMaps more convenient.
For details, tutorials, and examples, please have a look at our documentation.
Thanks goes to all people that make equistore possible:
We always welcome new contributors. If you want to help us take a look at our contribution guidelines and afterwards you may start with an open issue marked as good first issue.