DSWL package: a Python implementation of the Debiased Spatial Whittle Likelihood
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Published version
Author(s)
Type
Journal Article
Abstract
The Debiased Spatial Whittle Likelihood (DSWL) package is an open-source Python package that implements the eponymous paper (Guillaumin et al., 2022). The methodology allows users to efficiently infer the parameters of stationary / homogeneous spatial and spatio-temporal covariance models for univariate or multivariate processes from gridded data with potential
missing observations, e.g. due to natural boundaries. It leverages the Fast Fourier Transform, and therefore can benefit from further computational gains through GPU implementations offered by PyTorch (Paszke et al., 2019) or Cupy (Okuta et al., 2017), both made available
within the package as alternative backends to Numpy (Harris et al., 2020). As such, DSWL on GPU allows to fit covariance models to data observed on grids with tens of millions of locations.
missing observations, e.g. due to natural boundaries. It leverages the Fast Fourier Transform, and therefore can benefit from further computational gains through GPU implementations offered by PyTorch (Paszke et al., 2019) or Cupy (Okuta et al., 2017), both made available
within the package as alternative backends to Numpy (Harris et al., 2020). As such, DSWL on GPU allows to fit covariance models to data observed on grids with tens of millions of locations.
Date Issued
2026-03-25
Date Acceptance
2026-03-01
Citation
Journal of Open Source Software, 2026, 11 (119)
ISSN
2475-9066
Publisher
Journal of Open Source Software
Start Page
8323
End Page
8323
Journal / Book Title
Journal of Open Source Software
Volume
11
Issue
119
Copyright Statement
Authors of JOSS papers retain copyright. This work is licensed under a Creative Commons Attribution 4.0 International License. Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Publication Status
Published
Article Number
8323
Date Publish Online
2026-03-25