GroIMP wiki - 01_user_documentation:09_math:02_set_theory_volume
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2026-05-16T09:24:33+00:00GroIMP wiki
https://dokuwiki.grogra.de/
https://dokuwiki.grogra.de/lib/exe/fetch.php?media=wiki:dokuwiki.svgtext/html2025-11-03T01:29:47+00:00Anonymous (anonymous@undisclosed.example.com)Pointcloud Shape fitting
https://dokuwiki.grogra.de/doku.php?id=01_user_documentation:09_math:02_set_theory_volume:50_fitting&rev=1762133387&do=diff
Pointcloud Shape fitting
All functions described here require one or multiple point clouds selected in the current 3D view. Otherwise, an error dialog is shown. If point clouds are selected, a dialog box asks for the fitting mode. In case of a cylinder, a frustum, a cone, and the automatic mode also the precision parameter is requested. Another dialog box asks whether the selected point clouds should be kept or removed. After confirming one of the options, the objects are created, displayed in …text/html2025-11-03T01:39:04+00:00Anonymous (anonymous@undisclosed.example.com)PointCloud clustering
https://dokuwiki.grogra.de/doku.php?id=01_user_documentation:09_math:02_set_theory_volume:50_pccluster&rev=1762133944&do=diff
PointCloud clustering
The PointClouds objects can be clustered.
Algorithms
K-means
Basic K-means clustering
GUI
after selecting a point cloud and clustering it, the new created point clouds are added to the graph.
RGG
public void Kcluster(){
BoundedCloud c = (BoundedCloud) first((* pc:de.grogra.pointcloud.groimp.PointCloud,
(pc.getCloud() instanceof BoundedCloud) *)).getCloud();
Cloud[] res = de.grogra.pointcloud.tools.KMeans.cluster(c,2,4);
for(Cloud y : res){
[
==>>^y;
…