Package: emstreeR 3.2.0-1

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_3.2.0-1.tar.gz
emstreeR_3.2.0-1.zip(r-4.7-any)emstreeR_3.2.0-1.zip(r-4.6-any)emstreeR_3.2.0-1.zip(r-4.5-any)
emstreeR_3.2.0-1.tgz(r-4.6-any)emstreeR_3.2.0-1.tgz(r-4.5-any)
emstreeR_3.2.0-1.tar.gz(r-4.7-any)emstreeR_3.2.0-1.tar.gz(r-4.6-any)
emstreeR_3.2.0-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
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:

5.09 score 11 stars 1 packages 25 scripts 518 downloads 6 exports 32 dependencies

Last updated from:c37b122e8f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK114
source / vignettesOK171
linux-releaseOK128
macos-releaseOK126
macos-oldrelOK122
windows-develOK79
windows-releaseOK84
windows-oldrelOK79
wasm-releaseOK108

Exports:ComputeMSTexport_edges_to_shapefileexport_vertices_to_shapefileplotMST3Dstat_MSTStatMST

Dependencies:classclassIntclicpp11DBIe1071farverggplot2gluegtableisobandKernSmoothlabelinglifecyclemlpackproxyR6RColorBrewerRcppRcppArmadilloRcppEnsmallenrlangs2S7scalesscatterplot3dsfunitsvctrsviridisLitewithrwk