1 /**
2 * Copyright (c) 2011, The University of Southampton and the individual contributors.
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without modification,
6 * are permitted provided that the following conditions are met:
7 *
8 * * Redistributions of source code must retain the above copyright notice,
9 * this list of conditions and the following disclaimer.
10 *
11 * * Redistributions in binary form must reproduce the above copyright notice,
12 * this list of conditions and the following disclaimer in the documentation
13 * and/or other materials provided with the distribution.
14 *
15 * * Neither the name of the University of Southampton nor the names of its
16 * contributors may be used to endorse or promote products derived from this
17 * software without specific prior written permission.
18 *
19 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
20 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
21 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
22 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
23 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
24 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
25 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
26 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
27 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
28 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 */
30 package org.openimaj.ml.clustering.spectral;
31
32 import java.util.List;
33
34 import org.apache.log4j.Logger;
35 import org.openimaj.feature.DoubleFV;
36 import org.openimaj.feature.FeatureExtractor;
37 import org.openimaj.ml.clustering.SimilarityClusterer;
38 import org.openimaj.util.function.Function;
39
40 import ch.akuhn.matrix.SparseMatrix;
41
42 /**
43 * Wraps the functionality of a {@link SimilarityClusterer} around a dataset
44 *
45 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
46 * @param <T>
47 *
48 */
49 public abstract class DoubleFVSimilarityFunction<T> implements Function<List<T>, SparseMatrix> {
50 Logger logger = Logger.getLogger(DoubleFVSimilarityFunction.class);
51 protected double[][] feats = null;
52 private FeatureExtractor<DoubleFV, T> extractor;
53 private List<T> data;
54
55 /**
56 * @param extractor
57 *
58 */
59 public DoubleFVSimilarityFunction(FeatureExtractor<DoubleFV, T> extractor) {
60 this.extractor = extractor;
61 }
62
63 @Override
64 public SparseMatrix apply(List<T> in) {
65 this.data = in;
66 this.prepareFeats();
67 return this.similarity();
68 };
69
70 protected void prepareFeats() {
71 if (feats != null)
72 return;
73 final int numInstances = data.size();
74 feats = new double[numInstances][];
75 int index = 0;
76 for (final T d : this.data) {
77 feats[index++] = this.extractor.extractFeature(d).values;
78 }
79 }
80
81 protected abstract SparseMatrix similarity();
82 }