Metadata-Version: 2.1
Name: s2fft
Version: 1.0.2
Summary: Differentiable and accelerated spherical transforms with JAX
Home-page: https://github.com/astro-informatics/s2fft
Author: Matthew A. Price, Jason D. McEwen & Contributors
License: MIT
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
License-File: LICENCE.txt
Requires-Dist: numpy >=1.20
Requires-Dist: colorlog
Requires-Dist: pyyaml
Requires-Dist: jax >=0.3.13
Requires-Dist: jaxlib
Requires-Dist: torch
Provides-Extra: torch
Requires-Dist: torch ; extra == 'torch'

.. image:: https://github.com/astro-informatics/s2fft/actions/workflows/tests.yml/badge.svg?branch=main
    :target: https://github.com/astro-informatics/s2fft/actions/workflows/tests.yml
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    :target: https://github.com/astro-informatics/s2fft
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    :target: https://opensource.org/licenses/MIT
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    :target: https://arxiv.org/abs/2311.14670
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.. image:: https://colab.research.google.com/assets/colab-badge.svg
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Differentiable and accelerated spherical transforms
=================================================================================================================

`S2FFT` is a Python package for computing Fourier transforms on the sphere
and rotation group using JAX and PyTorch. It leverages autodiff to provide differentiable
transforms, which are also deployable on hardware accelerators
(e.g. GPUs and TPUs).

More specifically, `S2FFT` provides support for spin spherical harmonic
and Wigner transforms (for both real and complex signals), with support
for adjoint transformations where needed, and comes with different
optimisations (precompute or not) that one may select depending on
available resources and desired angular resolution $L$.

As of version 1.0.2 `S2FFT` also provides PyTorch implementations of underlying 
precompute transforms. In future releases this support will be extended to our 
on-the-fly algorithms.

Documentation
=============
Read the full documentation `here <https://astro-informatics.github.io/s2fft/>`_.

Attribution
===========
Should this code be used in any way, we kindly request that the following article is
referenced. A BibTeX entry for this reference may look like:

.. code-block:: 

    @article{price:s2fft, 
        author      = "Matthew A. Price and Jason D. McEwen",
        title       = "Differentiable and accelerated spherical harmonic and Wigner transforms",
        journal     = "Journal of Computational Physics",
        year        = "2023",
        eprint      = "arXiv:2311.14670"        
    }

You might also like to consider citing our related papers on which this
code builds:

.. code-block::

    @article{mcewen:fssht,
        author      = "Jason D. McEwen and Yves Wiaux",
        title       = "A novel sampling theorem on the sphere",
        journal     = "IEEE Trans. Sig. Proc.",
        year        = "2011",
        volume      = "59",
        number      = "12",
        pages       = "5876--5887",        
        eprint      = "arXiv:1110.6298",
        doi         = "10.1109/TSP.2011.2166394"
    }


.. code-block:: 

    @article{mcewen:so3,
        author      = "Jason D. McEwen and Martin B{\"u}ttner and Boris ~Leistedt and Hiranya V. Peiris and Yves Wiaux",
        title       = "A novel sampling theorem on the rotation group",
        journal     = "IEEE Sig. Proc. Let.",
        year        = "2015",
        volume      = "22",
        number      = "12",
        pages       = "2425--2429",
        eprint      = "arXiv:1508.03101",
        doi         = "10.1109/LSP.2015.2490676"    
    }

License
=======

We provide this code under an MIT open-source licence with the hope that
it will be of use to a wider community.

Copyright 2023 Matthew Price, Jason McEwen and contributors.

`S2FFT` is free software made available under the MIT License. For
details see the LICENSE file.
