sphericart

This is sphericart, a multi-language library for the efficient calculation of the spherical harmonics and their derivatives in Cartesian coordinates.

For instructions and examples on the usage of the library, please refer to our documentation.

If you are using sphericart for your academic work, you can cite it as

@article{sphericart,
    title={Fast evaluation of spherical harmonics with sphericart},
    author={Bigi, Filippo and Fraux, Guillaume and Browning, Nicholas J. and Ceriotti, Michele},
    journal={J. Chem. Phys.},
    year={2023},
    number={159},
    pages={064802},
}

This library is dual-licensed under the Apache License 2.0 and the MIT license. You can use to use it under either of the two licenses.

Installation

Python

Pre-built (https://pypi.org/project/sphericart/).

pip install sphericart             # numpy version
pip install sphericart[torch]      # including also the torch bindings
pip install sphericart[jax]        # JAX bindings (CPU-only)

Note that the pre-built packages are compiled for a generic CPU, and might be less performant than they could be on a specific processor. To generate libraries that are optimized for the target system, you can build from source:

git clone https://github.com/lab-cosmo/sphericart
pip install .

# if you also want the torch bindings (CPU and GPU)
pip install .[torch]

# torch bindings, CPU-only version
pip install --extra-index-url https://download.pytorch.org/whl/cpu .[torch]

Building from source is also necessary to use sphericart's PyTorch GPU functionalities, and it requires a CUDA compiler.

Julia

A native Julia implementation of sphericart is provided, called SpheriCart. Install the package by opening a REPL, switch to the package manager by typing ] and then add SpheriCart. See julia/README.md for usage.

C and C++

From source

git clone https://github.com/lab-cosmo/sphericart
cd sphericart

mkdir build && cd build

cmake .. <cmake configuration options>
cmake --build . --target install

The following cmake configuration options are available:

• -DSPHERICART_BUILD_TORCH=ON/OFF: build the torch bindings in addition to the main library
• -DSPHERICART_BUILD_TESTS=ON/OFF: build C++ unit tests
• -DSPHERICART_BUILD_EXAMPLES=ON/OFF: build C++ examples and benchmarks
• -DSPHERICART_OPENMP=ON/OFF: enable OpenMP parallelism
• -DCMAKE_INSTALL_PREFIX=<where/you/want/to/install> set the root path for installation

Running tests and documentation

Tests and the local build of the documentation can be run with tox. The default tests, which are also run on the CI, can be executed by simply running

tox

in the main folder of the repository.

To run tests in a CPU-only environment you can set the environment variable PIP_EXTRA_INDEX_URL before calling tox, e.g.

PIP_EXTRA_INDEX_URL=https://download.pytorch.org/whl/cpu tox -e docs

will build the documentation in a CPU-only environment.