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.feature.normalisation; 031 032import org.openimaj.feature.FloatFV; 033 034/** 035 * This {@link Normaliser} normalises vectors such that the Euclidean distance 036 * between normalised vectors is equivalent to computing the similarity using 037 * the Hellinger kernel on the un-normalised vectors. 038 * <p> 039 * The normalisation works by optionally adding an offset to the vectors (to 040 * deal with input vectors that have negative values), L1 normalising the 041 * vectors and finally performing an element-wise sqrt. 042 * 043 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 044 * 045 */ 046public class HellingerNormaliser implements Normaliser<FloatFV> { 047 protected int offset; 048 049 /** 050 * Construct with no offset 051 */ 052 public HellingerNormaliser() { 053 this.offset = 0; 054 } 055 056 /** 057 * Construct with the given offset 058 * 059 * @param offset 060 * the offset 061 */ 062 public HellingerNormaliser(int offset) { 063 this.offset = offset; 064 } 065 066 @Override 067 public void normalise(FloatFV feature) { 068 normalise(feature.values, offset); 069 } 070 071 /** 072 * Static utility function to perform Hellinger normalisation. 073 * 074 * @param values 075 * the values to normalise 076 * @param offset 077 * the offset to add to the values before normalisation (to 078 * ensure they are +ve). 079 */ 080 public static void normalise(float[] values, int offset) { 081 double sum = 0; 082 083 for (int i = 0; i < values.length; i++) { 084 values[i] += offset; 085 sum += values[i]; 086 } 087 088 for (int i = 0; i < values.length; i++) { 089 values[i] = (float) Math.sqrt(values[i] / sum); 090 } 091 } 092}