S2LET provides functionality to perform fast and exact scale-discretised wavelet transforms on the sphere.
The python package, pys2let, is available on pypi and can be installed with:
pip install pys2let
Alternatively, it can be installed from a local clone of the repository for development purposes by
pip install -e .[dev]
The C package can be installed with CMake and conan:
Both can be installed using pip:
pip install "conan<1" cmake
Then S2LET can be compiled with:
git clone https://github.com/astro-informatics/s2let.git
mkdir s2let/build && cd s2let/build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local -Dconan_deps=ON -Dcfitsio=ON ..
make
make install
The above will also download all necessary dependencies.
Instructions for installing other languages can be found here.
Further documentation is available here.
Usage for the python package is also given in the package docstring.
If you use S2LET for work that results in publication, please reference http://github.com/astro-informatics/s2let and cite the relevant academic paper(s):
- Y. Wiaux, J. D. McEwen, P. Vandergheynst, O. Blanc, Exact reconstruction with directional wavelets on the sphere, Mon. Not. Roy. Astron. Soc., 388(2):770-788, 2008. (ArXiv) | DOI)
- B. Leistedt, J. D. McEwen, P. Vandergheynst and Y. Wiaux, S2LET: A code to perform fast wavelet analysis on the sphere, Astronomy & Astrophysics, 558(A128):1-9, 2013 (http://arxiv.org/abs/1211.1680">ArXiv | DOI
- J. D. McEwen, B. Leistedt, M. Büttner, H. V. Peiris, Y. Wiaux, Directional spin wavelets on the sphere, IEEE Trans. Signal Proc., submitted, 2015 (ArXiv
- J. D. McEwen, M. Price, Ridgelet transform on the sphere, 27th European Signal Processing Conference (EUSIPCO), 2019 (ArXiv | DOI)
- J. Y. H. Chan, B. Leistedt, T. D. Kitching, J. D. McEwen, Second-generation curvelets on the sphere, IEEE Trans. Signal Proc., 65(1):5-14, 2017 (ArXiv | DOI)
- J. D. McEwen, C. Durastanti, Y. Wiaux, Localisation of directional scale-discretised wavelets on the sphere, Applied Comput. Harm. Anal., 44(1), 59-88, 2018 (ArXiv | DOI)
You may also like to consider citing the following papers on which the fast algorithms of S2LET are based:
- J. D. McEwen, M. Büttner, B. Leistedt, H. V. Peiris, Y. Wiaux, A novel sampling theorem on the rotation group, IEEE Sig. Proc. Let., 22(12):2425-2429, 2015 (ArXiv | DOI)
- J. D. McEwen and Y. Wiaux, A novel sampling theorem on the sphere, IEEE Trans. Signal Proc., 59, 5876-5887, 2011 (ArXiv | DOI)
S2LET is released under the GPL-3 license. For further details see LICENSE.txt.
S2LET was initially developed by Boris Leistedt, Martin Büttner, and Jason McEwen but significant contributors have since been made by a number of others.