GaussianRandomFields.jl: A Julia package to generate and sample from Gaussian random fields
Pieterjan Robbe · The Journal of Open Source Software · 2023
Random fields are used to represent spatially-varying uncertainty, and are commonly used as training data in uncertainty quantification and machine learning applications.Gaussian-RandomFields.jl is a Julia (Bezanson et al., 2017) software package to generate and sample from Gaussian random fields.It offers support for well-known covariance functions, such as Gaussian, exponential and Matérn covariances (Bishop & Nasrabadi, 2006;Chiles & Delfiner, 2012;Montero et al., 2015), as well as user-defined covariance structures defined on arbitrary domains.The package implements most common methods to generate samples from these random fields, including the Cholesky factorization, the Karhunen-Loève expansion, and the circulant embedding method (Lord et al., 2014).GaussianRandomFields.jl makes use of Plots.jl(Christ et al., 2023) to quickly visualize samples of the random fields.