How would you approach a k mean clustering where the calculated centroids have to be on the same position as one of the nodes? example

as you can see we have 2 centroids which are arguably the center of each cluster while being "ontop" of a node.

Is there already a name for this problem? I couldn't find anything related to it.

  • Are you asking how to do it using a particular GIS software? – BERA May 31 '18 at 7:55
  • Im asking how to do it algorithmically using python for example. since im fairly new to this stack, id be interested in using a particular gis software as well – InsOp May 31 '18 at 7:59

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