Package: quitefastmst 0.9.1.9001

quitefastmst: Euclidean and Mutual Reachability Minimum Spanning Trees

Functions to compute Euclidean minimum spanning trees using single-, sesqui-, and dual-tree Boruvka algorithms. Thanks to K-d trees, they are fast in spaces of low intrinsic dimensionality. Mutual reachability distances (used in the definition of the 'HDBSCAN*' algorithm) are supported too. The package also includes relatively fast fallback minimum spanning tree and nearest-neighbours algorithms for spaces of higher dimensionality. The 'Python' version of 'quitefastmst' is available via 'PyPI'.

Authors:Marek Gagolewski [aut, cre, cph]

quitefastmst_0.9.1.9001.tar.gz
quitefastmst_0.9.1.9001.zip(r-4.7)quitefastmst_0.9.1.9001.zip(r-4.6)quitefastmst_0.9.1.9001.zip(r-4.5)
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quitefastmst_0.9.1.9001.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
quitefastmst/json (API)

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

Bug tracker:https://github.com/gagolews/quitefastmst/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cluster-analysisclusteringclustering-evaluationeuclidean-distancesgeniehdbscanhdbscan-clustering-algorithmmachine-learningmachine-learning-algorithmsminimum-spanning-treemstmutual-reachability-distanceneighbor-searchoutlier-detectioncppopenmp

5.47 score 1 stars 10 packages 1.2k downloads 4 exports 1 dependencies

Last updated from:2994d15e5d. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK158
linux-devel-x86_64OK156
source / vignettesOK181
linux-release-arm64OK160
linux-release-x86_64OK173
macos-release-arm64OK146
macos-release-x86_64OK263
macos-oldrel-arm64OK123
macos-oldrel-x86_64OK276
windows-develOK131
windows-releaseOK138
windows-oldrelOK154
wasm-releaseOK152

Exports:knn_euclidmst_euclidomp_get_max_threadsomp_set_num_threads

Dependencies:Rcpp