Clustering Paper.js Elements together using the K-means algorithm.

paperKMeans.js

/**
 * Clusters a number of Paper Elements as Paper Groups.
 * Clustering is based on distance between elements,
 * using K-means clustering.
 * - This method DOES NOT preserve z-order of items, so use with caution
 *
 *
 * - Dependent on clusterfck.js.
 * 	 See: https://github.com/NathanEpstein/clusters
 *         and download browser .js file.
 *
 * @param  {Array}  - items       - Array of Paper Items.
 * @param  {Number} - clusterNum  - Amount of clusters to create
 *
 * @return {Array}                - Array of Paper Groups
 * 
 * Authors:
 * - Nicholas Kyriakides, @nicholaswmin
 */
function clusterKMeans(items,clusterNum) {

  // min clusters num is the amount of items
  if(items.length < clusterNum) {
    clusterNum = items.length;
  }

  var pointsArr = [];
  for (var i = 0; i < items.length; i++) {
    pointsArr.push([items[i].position.x,items[i].position.y,items[i].id]);
  }
  var clusters = clusterfck.kmeans(pointsArr, clusterNum);

  var groupsArr = [];
  for (var i = 0; i < clusters.length; i++) {
    var group = new paper.Group();
    for (var k = 0; k < clusters[i].length; k++) {
      for (var l = 0; l < items.length; l++) {
        if(items[l].id === clusters[i][k][2]) {
          group.addChild(items[l])
        }
      }
    }
    groupsArr.push(group.clone());
    group.remove()
  }

    return groupsArr;
  }