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R package providing an interface to the TriplClust algorithm for 3D point-cloud clustering.
From the subdirectory r-package of the repository root,
build the source tarball with:
bash ./makecrandist.shThis creates the source tarball triplclust_*.*.*.tar.gz
that is installed with
R CMD INSTALL triplclust_*.*.*.tar.gzThe main function is triplclust that accepts an
n x 3 numeric matrix and returns a triplclust object with
four entries: the input points (points), the assigned
clusters per point as a list labels of the same length as
nrow(points), the parameters of the run
(params) and the merge distances of the triplet clustering
(cdist). A point may occur in multiple clusters; points
absent from every cluster have an empty numeric label vector.
params is a named list of the parameters of the run. A
parameter given as a multiple of dNN appears twice: under its plain name
is the requested value and its _dnn flag is
TRUE (for example r is 2 and
r_dnn is TRUE for "2dNN"), while
the same name with the suffix _real holds the absolute
value that was actually used. So params$r_real is the
resulting smoothing radius and params$dnn_real the
characteristic length it was derived from. The _real
entries are resolved during the run and are only reported for debugging
and reproducibility. The meaning of every entry is documented in
?triplclust.
cdist is a numeric vector with the distance of each of
the n-1 merge steps of the triplet clustering, i.e. the heights of the
dendrogram in ascending order. These are the same values the command
line version writes to debug_cdist.csv with
-vv; plot_threshold(tc) returns that file
content as a string, without writing it.
Here is an example how to apply triplclust to the included dataset
attpc:
library(triplclust)
tc <- triplclust(attpc)
# visualization with rgl
colors <- label_colors(tc)
library(rgl)
plot3d(tc$points, col=colors)
# visualization with external software gnuplot
save_gnuplot(tc, "/tmp/tc.gnuplot")
system("gnuplot -persist /tmp/tc.gnuplot")
# save result as CSV file
save_csv(tc, "result.csv")
# show cluster distances during hierarchical clustering and chosen threshold
plot_threshold(tc)These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.