Rvcg: vcgKmeans – R documentation

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vcgKmeans

fast Kmean clustering for 1D, 2D and 3D data

fast Kmean clustering for 1D, 2D and 3D data

vcgKmeans(x, k = 10, iter.max = 10, getClosest = FALSE, threads = 0)

`x`	matrix containing coordinates or mesh3d
`k`	number of clusters
`iter.max`	maximum number of iterations
`getClosest`	logical: if TRUE the indices of the points closest to the k-centers are sought.
`threads`	integer: number of threads to use

returns a list containing

`centers`	cluster center
`class`	vector with cluster association for each coordinate

If getClosest=TRUE

selected

vector with indices of points closest to the centers

require(Rvcg);require(rgl)
data(humface)
set.seed(42)
clust <- vcgKmeans(humface,k=1000,threads=1)

Manipulations of Triangular Meshes Based on the 'VCGLIB' API

v0.19.2

GPL (>= 2) | file LICENSE

Authors

Stefan Schlager [aut, cre, cph], Girinon Francois [ctb]

Initial release

2021-01-11