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 032import java.io.File; 033import java.io.IOException; 034 035import org.apache.logging.log4j.Logger; 036import org.apache.logging.log4j.LogManager; 037 038import org.openimaj.io.IOUtils; 039 040import ch.akuhn.matrix.SparseMatrix; 041import ch.akuhn.matrix.eigenvalues.Eigenvalues; 042 043/** 044 * {@link DoubleSpectralClustering} extention which knows how to write and read its eigenvectors to disk 045 * and therefore not regenerate them when calling the underlying {@link PreparedSpectralClustering} 046 * 047 * @author Sina Samangooei (ss@ecs.soton.ac.uk) 048 * 049 */ 050public class CachedDoubleSpectralClustering extends DoubleSpectralClustering{ 051 private final static Logger logger = LogManager.getLogger(CachedDoubleSpectralClustering.class); 052 private File cache; 053 054 /** 055 * @param cache location to cache the eigenvectors 056 * @param conf 057 * cluster the eigen vectors 058 */ 059 public CachedDoubleSpectralClustering(File cache, SpectralClusteringConf<double[]> conf) { 060 super(conf); 061 this.cache = cache; 062 } 063 064 @Override 065 protected Eigenvalues spectralCluster(SparseMatrix data) { 066 Eigenvalues eig = null; 067 if(cache.exists()){ 068 logger.debug("Loading eigenvectors from cache"); 069 try { 070 eig = IOUtils.readFromFile(cache); 071 } catch (IOException e) { 072 throw new RuntimeException(e); 073 } 074 } 075 else{ 076 // Compute the laplacian of the graph 077 logger.debug("Cache empty, recreating eigenvectors"); 078 final SparseMatrix laplacian = laplacian(data); 079 eig = laplacianEigenVectors(laplacian); 080 try { 081 logger.debug("Writing eigenvectors to cache"); 082 IOUtils.writeToFile(eig, cache); 083 } catch (IOException e) { 084 throw new RuntimeException(e); 085 } 086 } 087 088 return eig; 089 } 090 091}