largeVis: High-Quality Visualizations of Large, High-Dimensional Datasets

Implements the largeVis algorithm (see Tang, et al. (2016) <doi:10.1145/2872427.2883041>) for visualizing very large high-dimensional datasets. Also very fast search for approximate nearest neighbors; outlier detection; and optimized implementations of the HDBSCAN*, DBSCAN and OPTICS clustering algorithms; plotting functions for visualizing the above.

Version: 0.2.1
Depends: R (≥ 3.0.2), Matrix
Imports: ggplot2 (≥ 2.1.0)
LinkingTo: Rcpp (≥ 0.12.4), RcppProgress (≥ 0.2.1), RcppArmadillo (≥ 0.7.200.2.0), testthat (≥ 1.0.2)
Suggests: ggforce, testthat, knitr, rmarkdown, png, dbscan
Published: 2017-05-08
Author: Amos B. Elberg
Maintainer: Amos Elberg <amos.elberg at gmail.com>
BugReports: https://github.com/elbamos/largeVis/issues
License: GPL-3
URL: https://github.com/elbamos/largeVis
NeedsCompilation: yes
SystemRequirements: C++11
Materials: NEWS
In views: Cluster
CRAN checks: largeVis results

Downloads:

Reference manual: largeVis.pdf
Vignettes: largeVis
largeVisnewfeatures
Package source: largeVis_0.2.1.tar.gz
Windows binaries: r-devel: largeVis_0.2.1.zip, r-release: largeVis_0.2.1.zip, r-oldrel: largeVis_0.2.1.zip
OS X El Capitan binaries: r-release: largeVis_0.2.1.tgz
OS X Mavericks binaries: r-oldrel: largeVis_0.2.1.tgz
Old sources: largeVis archive

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