Package: densityClust 0.3.3.9000

densityClust: Clustering by Fast Search and Find of Density Peaks

An improved implementation (based on k-nearest neighbors) of the density peak clustering algorithm, originally described by Alex Rodriguez and Alessandro Laio (Science, 2014 vol. 344). It can handle large datasets (> 100,000 samples) very efficiently. It was initially implemented by Thomas Lin Pedersen, with inputs from Sean Hughes and later improved by Xiaojie Qiu to handle large datasets with kNNs.

Authors:Thomas Lin Pedersen [aut, cre], Sean Hughes [aut], Xiaojie Qiu [aut]

densityClust_0.3.3.9000.tar.gz
densityClust_0.3.3.9000.zip(r-4.7)densityClust_0.3.3.9000.zip(r-4.6)densityClust_0.3.3.9000.zip(r-4.5)
densityClust_0.3.3.9000.tgz(r-4.6-x86_64)densityClust_0.3.3.9000.tgz(r-4.6-arm64)densityClust_0.3.3.9000.tgz(r-4.5-x86_64)densityClust_0.3.3.9000.tgz(r-4.5-arm64)
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densityClust_0.3.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
densityClust/json (API)

# Install 'densityClust' in R:
install.packages('densityClust', repos = c('https://thomasp85.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thomasp85/densityclust/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

7.32 score 163 stars 107 scripts 950 downloads 6 mentions 8 exports 22 dependencies

Last updated from:887adc74a9. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK171
linux-devel-x86_64OK150
source / vignettesOK173
linux-release-arm64OK143
linux-release-x86_64OK140
macos-release-arm64OK134
macos-release-x86_64OK306
macos-oldrel-arm64OK74
macos-oldrel-x86_64OK214
windows-develOK93
windows-releaseOK113
windows-oldrelOK90
wasm-releaseOK117

Exports:clusteredclustersdensityClustestimateDcfindClustersplotDensityClustplotMDSplotTSNE

Dependencies:clicpp11farverFNNggplot2ggrepelgluegridExtragtableisobandlabelinglifecycleR6RColorBrewerRcpprlangRtsneS7scalesvctrsviridisLitewithr