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Various clustering algorithm implementations for all primitive types including random, random forest, K-Means (Exact, Hierarchical and Approximate), ...

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/*
	AUTOMATICALLY GENERATED BY jTemp FROM
	/Users/jon/Work/openimaj/tags/openimaj-1.3.1/machine-learning/clustering/src/main/jtemp/org/openimaj/ml/clustering/kmeans/Hierarchical#T#KMeansResult.jtemp
*/
/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   * 	Redistributions of source code must retain the above copyright notice,
 * 	this list of conditions and the following disclaimer.
 *
 *   *	Redistributions in binary form must reproduce the above copyright notice,
 * 	this list of conditions and the following disclaimer in the documentation
 * 	and/or other materials provided with the distribution.
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 *   *	Neither the name of the University of Southampton nor the names of its
 * 	contributors may be used to endorse or promote products derived from this
 * 	software without specific prior written permission.
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package org.openimaj.ml.clustering.kmeans;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.Scanner;

import org.openimaj.ml.clustering.ShortCentroidsResult;
import org.openimaj.ml.clustering.SpatialClusters;
import org.openimaj.ml.clustering.assignment.hard.HierarchicalShortHardAssigner;

/** 
 * The result of a {@link HierarchicalShortKMeans} clustering operation.
 *
 * @author Sina Samangooei ([email protected])
 * @author Jonathon Hare ([email protected])
 */
public class HierarchicalShortKMeansResult implements SpatialClusters {
	/**
	 * HierarchicalShortKMeans tree node
	 *
	 * The number of children is not bigger than the HierarchicalShortKMeans K parameter
	 **/
	public static class Node {
		/** {@link ShortCentroidsResult} for this node */
		public ShortCentroidsResult result;

		/** Node children (if any) */
		public Node[] children;
	}
	
	private static final String HEADER = SpatialClusters.CLUSTER_HEADER + "H" +"Short".charAt(0) + "KM";
	
	/** Data dimensionality */
	int M;

	/** K clusters per node */
	int K;
	
	/** Depth of the tree */
	int depth;
	
	/** Tree root node */
	Node root;

	protected HierarchicalShortKMeansResult() {}

	@Override
	public int numDimensions() {
		return M;
	}
	
	/**
	 * Get the number of clusters per node
	 * @return number of clusters per node
	 */
	public int getK() {
		return K;
	}

	/**
	 * Get the depth of the cluster tree
	 * @return the depth of the cluster tree
	 */
	public int getDepth() {
		return depth;
	}

	/**
	 * Get the root node of the tree
	 * @return the root node of the tree
	 */
	public Node getRoot() {
		return root;
	}

	private static int ipow(int x, int y) {
		int sum = 1;
		for (int i=0; i