Package: emstreeR 3.1.3

Allan Quadros

emstreeR: Tools for Fast Computing and Visualizing Euclidean Minimum Spanning Trees

Fast and easy computation of Euclidean Minimum Spanning Trees (EMST) from data, relying on the R API for 'mlpack' - the C++ Machine Learning Library (Curtin et. al., 2013). 'emstreeR' uses the Dual-Tree Boruvka (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>), which is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides functions and an S3 method for readily visualizing Minimum Spanning Trees (MST) using either the style of the 'base', 'scatterplot3d', or 'ggplot2' libraries; and functions to export the MST output to shapefiles.

Authors:Allan Quadros [aut, cre], Duncan Garmonsway [ctb]

emstreeR_3.1.3.tar.gz
emstreeR_3.1.3.zip(r-4.7)emstreeR_3.1.3.zip(r-4.6)emstreeR_3.1.3.zip(r-4.5)
emstreeR_3.1.3.tgz(r-4.6-any)emstreeR_3.1.3.tgz(r-4.5-any)
emstreeR_3.1.3.tar.gz(r-4.7-any)emstreeR_3.1.3.tar.gz(r-4.6-any)
emstreeR_3.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
emstreeR/json (API)

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

Bug tracker:https://github.com/allanvc/emstreer/issues

On CRAN:

Conda:

4.44 score 8 stars 1 packages 23 scripts 284 downloads 6 exports 33 dependencies

Last updated from:dbded34259. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK114
source / vignettesOK178
linux-release-x86_64OK123
macos-release-arm64OK149
macos-oldrel-arm64OK142
windows-develOK81
windows-releaseOK85
windows-oldrelOK150
wasm-releaseOK105

Exports:ComputeMSTexport_edges_to_shapefileexport_vertices_to_shapefileplotMST3Dstat_MSTStatMST

Dependencies:classclassIntclicpp11DBIe1071farverggplot2gluegtableisobandKernSmoothlabelinglifecycleMASSmlpackproxyR6RColorBrewerRcppRcppArmadilloRcppEnsmallenrlangs2S7scalesscatterplot3dsfunitsvctrsviridisLitewithrwk