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sleplet
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Slepian Scale-Discretised Wavelets in Python
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# SLEPLET [](https://pypi.org/project/sleplet) [](https://doi.org/10.5281/zenodo.7268074) [](https://github.com/astro-informatics/sleplet?tab=BSD-3-Clause-1-ov-file#readme) [](https://jacobtomlinson.dev/effver) [](https://www.python.org) [](https://www.repostatus.org/#active) [](https://github.com/astro-informatics/sleplet/actions/workflows/test.yaml) [](https://coveralls.io/github/astro-informatics/sleplet?branch=main) [](https://www.codefactor.io/repository/github/astro-informatics/sleplet) [](https://astro-informatics.github.io/sleplet) [](https://joss.theoj.org/papers/55d9cf16a27bf2d3141f0f66c676b7f2) [](https://github.com/pyOpenSci/software-submission/issues/149) [](https://github.com/astro-informatics/sleplet#citing) `SLEPLET` is a Python package for the construction of Slepian wavelets in the spherical and manifold (via meshes) settings. The API of `SLEPLET` has been designed in an object-orientated manner and is easily extendable. Upon installation, `SLEPLET` comes with two command line interfaces - `sphere` and `mesh` - which allows one to easily generate plots on the sphere and a set of meshes using `plotly`. To read more about Slepian wavelets please see the following publications [](https://doi.org/10.1109/LSP.2021.3050961) [](https://doi.org/10.1109/TSP.2022.3233309) [](https://doi.org/10.48550/arXiv.2302.06006) [](https://paddyroddy.github.io/thesis) ## Installation The recommended way to install `SLEPLET` is via [pip](https://pypi.org/project/pip) ```sh pip install sleplet ``` To install the latest development version of `SLEPLET` clone this repository and run ```sh uv sync ``` This will install two scripts `sphere` and `mesh` which can be used to generate the figures in [the associated papers](https://astro-informatics.github.io/sleplet#paper-figures). ### Supported Platforms `SLEPLET` has been tested with [](https://www.python.org). Windows is not currently supported as `SLEPLET` relies on [pyssht](https://pypi.org/project/pyssht) and [pys2let](https://pypi.org/project/pys2let) which do not work on Windows. These may be replaced with [s2fft](https://github.com/astro-informatics/s2fft) and [s2wav](https://github.com/astro-informatics/s2wav) in the future when they are available on [PyPI](https://pypi.org). ## Example Usage `SLEPLET` may be interacted with via the API or the CLIs. ### API Usage The following demonstrates the first wavelet (ignoring the scaling function) of the South America region on the sphere. ```python import sleplet B, J, J_MIN, L = 3, 0, 2, 128 region = sleplet.slepian.Region(mask_name="south_america") f = sleplet.functions.SlepianWavelets(L, region=region, B=B, j_min=J_MIN, j=J) f_sphere = sleplet.slepian_methods.slepian_inverse(f.coefficients, f.L, f.slepian) sleplet.plotting.PlotSphere( f_sphere, f.L, f"slepian_wavelets_south_america_{B}B_{J_MIN}jmin_{J_MIN + J}j_L{L}", normalise=False, region=f.region, ).execute() ```  ### CLI Usage The demonstrates the first wavelet (ignoring the scaling function) of the head region of a Homer Simpson mesh for a per-vertex normals field. ```sh mesh homer -e 3 2 0 -m slepian_wavelet_coefficients -u -z ```  ## Documentation See here for the [documentation](https://astro-informatics.github.io/sleplet). This includes demonstrations of the figures from the associated papers along with the API documentation. Further examples are included in the [examples folder](https://github.com/astro-informatics/sleplet/tree/main/examples). ## Community Guidelines We'd love any contributions you may have, please see the [contributing guidelines](https://github.com/astro-informatics/sleplet/blob/main/CONTRIBUTING.md). ## Citing If you use `SLEPLET` in your research, please cite the paper. ```bibtex @article{Roddy2023, title = {{SLEPLET: Slepian Scale-Discretised Wavelets in Python}}, author = {Roddy, Patrick J.}, year = 2023, journal = {Journal of Open Source Software}, volume = 8, number = 84, pages = 5221, doi = {10.21105/joss.05221}, } ``` Please also cite [S2LET](https://www.aanda.org/articles/aa/full_html/2013/10/aa20729-12/aa20729-12.html) upon which `SLEPLET` is built, along with [SSHT](https://doi.org/10.1109/TSP.2011.2166394) in the spherical setting or [libigl](https://doi.org/10.1145/3134472.3134497) in the mesh setting.
