proxyC: Computes Proximity in Large Sparse Matrices

Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.

Version: 0.3.3
Depends: R (≥ 3.1.0), methods
Imports: Matrix (≥ 1.2), Rcpp (≥ 0.12.12), RcppParallel
LinkingTo: Rcpp, RcppParallel, RcppArmadillo (≥ 0.7.600.1.0)
Suggests: testthat, entropy, proxy, knitr, rmarkdown
Published: 2022-10-06
Author: Kohei Watanabe ORCID iD [cre, aut, cph], Robrecht Cannoodt ORCID iD [aut]
Maintainer: Kohei Watanabe <watanabe.kohei at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: proxyC results


Reference manual: proxyC.pdf
Vignettes: Similarity and Distance Measures in proxyC


Package source: proxyC_0.3.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): proxyC_0.3.3.tgz, r-oldrel (arm64): proxyC_0.3.3.tgz, r-release (x86_64): proxyC_0.3.3.tgz, r-oldrel (x86_64): proxyC_0.3.3.tgz
Old sources: proxyC archive

Reverse dependencies:

Reverse depends: seededlda
Reverse imports: applicable, dynutils, immcp, LSX, quanteda.textstats, scClassify, scFeatures, scMerge, SimBu, simplifyEnrichment


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