org.openimaj.lsh.functions.DoubleGaussianFactory Maven / Gradle / Ivy

Go to download
/*
	AUTOMATICALLY GENERATED BY jTemp FROM
	/Users/jsh2/Work/openimaj/target/checkout/machine-learning/nearest-neighbour/src/main/jtemp/org/openimaj/lsh/functions/#T#GaussianFactory.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.
 *
 *   *	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
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (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.lsh.functions;

import org.openimaj.feature.DoubleFVComparison;

import cern.jet.random.Normal;
import cern.jet.random.Uniform;
import cern.jet.random.engine.MersenneTwister;

/**
 * A hash function factory for producing hash functions using Gaussian
 * distributions to approximate the Euclidean distance.
 * 
 * @author Jonathon Hare ([email protected])
 */
public class DoubleGaussianFactory extends DoublePStableFactory {
	private class Function extends PStableFunction {
		Function(int ndims, MersenneTwister rng) {
			super(rng);

			final Uniform uniform = new Uniform(0, w, rng);
			final Normal normal = new Normal(0, 1, rng);

			b = (float) uniform.nextDouble();

			// random direction
			r = new double[ndims];
			for (int i = 0; i < ndims; i++) {
				r[i] = normal.nextDouble();
			}
		}
	}

	/**
	 * Construct with the given parameters.
	 * 
	 * @param ndims
	 *            number of dimensions of the data
	 * @param rng
	 *            the random number generator
	 * @param w
	 *            the width parameter
	 */
	public DoubleGaussianFactory(int ndims, MersenneTwister rng, double w) {
		super(ndims, rng, w);
	}

	@Override
	public Function create() {
		return new Function(ndims, rng);
	}

	@Override
	protected DoubleFVComparison fvDistanceFunction() {
		return DoubleFVComparison.EUCLIDEAN;
	}
}