org.openimaj.ml.clustering.spectral.NormalisedSimilarityDoubleClustererWrapper Maven / Gradle / Ivy

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/**
 * 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.
 *
 *   *	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.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.ml.clustering.spectral;

import org.apache.log4j.Logger;
import org.openimaj.feature.DoubleFV;
import org.openimaj.feature.DoubleFVComparison;
import org.openimaj.feature.FeatureExtractor;
import org.openimaj.ml.clustering.SimilarityClusterer;

import ch.akuhn.matrix.SparseMatrix;

/**
 * Wraps the functionality of a {@link SimilarityClusterer} around a dataset
 * 
 * @author Sina Samangooei ([email protected])
 *
 * @param 
 */
public class NormalisedSimilarityDoubleClustererWrapper extends DoubleFVSimilarityFunction {

	private double eps;

	/**
	 *
	 * @param extractor
	 * @param eps
	 */
	public NormalisedSimilarityDoubleClustererWrapper(FeatureExtractor extractor, double eps) {
		super(extractor);
		this.eps = eps;
	}

	Logger logger = Logger.getLogger(NormalisedSimilarityDoubleClustererWrapper.class);

	@Override
	protected SparseMatrix similarity() {
		final SparseMatrix mat = new SparseMatrix(feats.length, feats.length);
		final DoubleFVComparison dist = DoubleFVComparison.EUCLIDEAN;
		double maxD = 0;
		for (int i = 0; i < feats.length; i++) {
			for (int j = i; j < feats.length; j++) {
				double d = dist.compare(feats[i], feats[j]);
				if (d > eps)
					d = Double.NaN;
				else {
					maxD = Math.max(d, maxD);
				}
				mat.put(i, j, d);
				mat.put(j, i, d);
			}
		}
		final SparseMatrix mat_norm = new SparseMatrix(feats.length, feats.length);
		for (int i = 0; i < feats.length; i++) {
			for (int j = i; j < feats.length; j++) {
				double d = mat.get(i, j);
				if (Double.isNaN(d)) {
					continue;
				}
				else {
					d /= maxD;
				}
				mat_norm.put(i, j, 1 - d);
				mat_norm.put(j, i, 1 - d);
			}
		}
		return mat_norm;
	}

}