001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.ml.clustering.spectral;
031
032
033import java.util.Iterator;
034
035import org.openimaj.util.pair.DoubleObjectPair;
036
037import ch.akuhn.matrix.SparseMatrix;
038import ch.akuhn.matrix.Vector;
039import ch.akuhn.matrix.eigenvalues.Eigenvalues;
040import ch.akuhn.matrix.eigenvalues.FewEigenvalues;
041
042/**
043 *
044 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
045 *
046 */
047public class HardCodedEigenChooser extends EigenChooser{
048
049        int count;
050        /**
051         * @param eigK the number of eigen vectors to select
052         */
053        public HardCodedEigenChooser(int eigK) {
054                this.count = eigK;
055        }
056        @Override
057        public int nEigenVectors(Iterator<DoubleObjectPair<Vector>> vals, int total) {
058                return count;
059        }
060        @Override
061        public Eigenvalues prepare(final SparseMatrix laplacian) {
062                FewEigenvalues eig = FewEigenvalues.of(laplacian);
063                return eig.greatest(count);
064        }
065        
066        @Override
067        public String toString() {
068                return String.format("hardcoded_eig=%d",this.count);
069        }
070
071}