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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.
Version: | 0.4.1 |
Imports: | methods, Rcpp |
LinkingTo: | Rcpp |
Published: | 2022-12-09 |
DOI: | 10.32614/CRAN.package.SpatialKWD |
Author: | Stefano Gualandi [aut, cre] |
Maintainer: | Stefano Gualandi <stefano.gualandi at gmail.com> |
License: | |
NeedsCompilation: | yes |
SystemRequirements: | C++11 |
CRAN checks: | SpatialKWD results |
Reference manual: | SpatialKWD.pdf |
Package source: | SpatialKWD_0.4.1.tar.gz |
Windows binaries: | r-devel: SpatialKWD_0.4.1.zip, r-release: SpatialKWD_0.4.1.zip, r-oldrel: SpatialKWD_0.4.1.zip |
macOS binaries: | r-release (arm64): SpatialKWD_0.4.1.tgz, r-oldrel (arm64): SpatialKWD_0.4.1.tgz, r-release (x86_64): SpatialKWD_0.4.1.tgz, r-oldrel (x86_64): SpatialKWD_0.4.1.tgz |
Old sources: | SpatialKWD archive |
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