public static int[] calculateVectorSpace(BufferedImage image) {
clusters = createClusters(image);
int[] vectorSpace = new int[IMAGE_WIDTH * IMAGE_HEIGHT];
Arrays.fill(vectorSpace, -1);
boolean refineNeeded = true;
int loops = 0;
while (refineNeeded) {
refineNeeded = false;
loops++;
for (int y = 0; y < IMAGE_HEIGHT; y++) {
for (int x = 0; x < IMAGE_WIDTH; x++) {
int pixel = image.getRGB(x, y);
Cluster cluster = getMinCluster(pixel);
if (vectorSpace[IMAGE_WIDTH * y + x] != cluster.getId()) {
if (vectorSpace[IMAGE_WIDTH * y + x] != -1) {
clusters[vectorSpace[IMAGE_WIDTH * y + x]].removePixel(pixel);
}
cluster.addPixel(pixel);
refineNeeded = true;
vectorSpace[IMAGE_WIDTH * y + x] = cluster.getId();
}
}
}
}
System.out.println("Took " + loops + " loops.");
return vectorSpace;
}
/** Generate the hierarchical cluster and display it as a denogram in the graph */
public TreeNode makeTree(ClutoSolution cs) {
int[] tsize = cs.getTreeCounts();
int[][] ftree = cs.getForwardTree();
int nnrows = tsize.length;
int nrows = cs.getMatrix().getRowCount();
// for (int i = 0; i < nnrows-1; i++) {
// String s = "ftree" + "\t" + i + "\t" + ftree[i][0] + "\t" + ftree[i][1] + "\t" + tsize[i];
// System.out.println(s);
// }
Cluster[] ca = new Cluster[nnrows];
for (int i = 0; i < nnrows - 1; i++) {
if (!true) {
String s = "ftree" + "\t" + i + "\t" + ftree[i][0] + "\t" + ftree[i][1] + "\t" + tsize[i];
System.out.println(s);
}
Cluster cn = i < nrows ? (Cluster) new RowCluster(tm, i, null) : new CompositeCluster();
cn.setSimilarity(Math.abs(tsize[i]));
ca[i] = cn;
if (ftree[i][0] > -1) {
cn.add(ca[ftree[i][0]]);
}
if (ftree[i][0] > -1) {
cn.add(ca[ftree[i][1]]);
}
rootNode = cn;
}
return rootNode;
}
// -------------------------------------------------------------------------------------
public void handleCluster(String source, Cluster cluster) {
handleNameList(myGaggleName, new Namelist(cluster.getSpecies(), cluster.getRowNames()));
}
