SpatialKWD: Spatial KWD for Large Spatial Maps

Contains efficient implementations of Discrete Optimal Transport algorithms for the computation of Kantorovich-Wasserstein distances between pairs of large spatial maps (Bassetti, Gualandi, Veneroni (2020), <doi:10.1137/19M1261195>). All the algorithms are based on an ad-hoc implementation of the Network Simplex algorithm. The package has four main helper functions: compareOneToOne() (to compare two spatial maps), compareOneToMany() (to compare a reference map with a list of other maps), compareAll() (to compute a matrix of distances between a list of maps), and focusArea() (to compute the KWD distance within a focus area). In non-convex maps, the helper functions first build the convex-hull of the input bins and pad the weights with zeros.

Package details

AuthorStefano Gualandi [aut, cre]
MaintainerStefano Gualandi <>
LicenseEUPL (>= 1.2)
Package repositoryView on CRAN
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SpatialKWD documentation built on May 7, 2021, 5:07 p.m.