Package: proxyC 0.4.1

Kohei Watanabe

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.

Authors:Kohei Watanabe [cre, aut, cph], Robrecht Cannoodt [aut]

proxyC_0.4.1.tar.gz
proxyC_0.4.1.tar.gz(r-4.5-noble)proxyC_0.4.1.tar.gz(r-4.4-noble)
proxyC_0.4.1.tgz(r-4.4-emscripten)proxyC_0.4.1.tgz(r-4.3-emscripten)
proxyC.pdf |proxyC.html✨
proxyC/json (API)
NEWS

# Install 'proxyC' in R:

install.packages('proxyC', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/koheiw/proxyc/issues

Uses libs:

openblas– Optimized BLAS
onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

6.21 score 29 packages 23 scripts 5.5k downloads 6 exports 4 dependencies

Last updated 7 months agofrom:d2d0ec11ba. Checks:OK: 1 NOTE: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 26 2024
R-4.5-linux-x86_64	NOTE	Oct 26 2024

Exports:colSds colZeros dist rowSds rowZeros simil

Dependencies:lattice Matrix Rcpp RcppArmadillo

Similarity and Distance Measures in proxyC

Kohei Watanabe

Rendered frommeasures.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2024-04-08
Started: 2022-10-06

Citation

Readme and manuals

Help Manual

Help page	Topics
Standard deviation of columns and rows of large matrices	colSds rowSds
Count number of zeros in columns and rows of large matrices	colZeros rowZeros
Compute similarity/distance between rows or columns of large matrices	dist simil