annotate src/DistanceMetric.cpp @ 146:214b72d55796 noise

Update unit tests
author Chris Cannam
date Fri, 16 Jan 2015 16:48:55 +0000
parents ecfb4ada171b
children b79151bb75af
rev   line source
Chris@26 1 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
Chris@26 2
Chris@26 3 /*
Chris@26 4 Vamp feature extraction plugin using the MATCH audio alignment
Chris@26 5 algorithm.
Chris@26 6
Chris@26 7 Centre for Digital Music, Queen Mary, University of London.
Chris@26 8 This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
Chris@26 9
Chris@26 10 This program is free software; you can redistribute it and/or
Chris@26 11 modify it under the terms of the GNU General Public License as
Chris@26 12 published by the Free Software Foundation; either version 2 of the
Chris@26 13 License, or (at your option) any later version. See the file
Chris@26 14 COPYING included with this distribution for more information.
Chris@26 15 */
Chris@26 16
Chris@26 17 #include "DistanceMetric.h"
Chris@26 18
Chris@26 19 #include <cassert>
Chris@26 20 #include <cmath>
Chris@133 21 #include <iostream>
Chris@26 22
Chris@133 23 using namespace std;
Chris@26 24
Chris@140 25 //#define DEBUG_DISTANCE_METRIC 1
Chris@140 26
Chris@143 27 DistanceMetric::DistanceMetric(Parameters params) :
Chris@143 28 m_params(params)
Chris@140 29 {
Chris@140 30 #ifdef DEBUG_DISTANCE_METRIC
Chris@143 31 cerr << "*** DistanceMetric: norm = " << m_params.norm
Chris@143 32 << endl;
Chris@140 33 #endif
Chris@140 34 }
Chris@140 35
Chris@26 36 double
Chris@26 37 DistanceMetric::calcDistance(const vector<double> &f1,
Chris@26 38 const vector<double> &f2)
Chris@26 39 {
Chris@26 40 double d = 0;
Chris@26 41 double sum = 0;
Chris@26 42
Chris@26 43 int featureSize = f1.size();
Chris@26 44 assert(int(f2.size()) == featureSize);
Chris@145 45
Chris@26 46 for (int i = 0; i < featureSize; i++) {
Chris@26 47 d += fabs(f1[i] - f2[i]);
Chris@145 48 sum += fabs(f1[i]) + fabs(f2[i]);
Chris@26 49 }
Chris@26 50
Chris@145 51 double noise = 1e-3 * featureSize;
Chris@145 52 d += noise;
Chris@145 53 sum += noise;
Chris@145 54
Chris@143 55 if (sum == 0) {
Chris@26 56 return 0;
Chris@143 57 }
Chris@26 58
Chris@143 59 double distance = 0;
Chris@26 60
Chris@143 61 if (m_params.norm == NormaliseDistanceToSum) {
Chris@143 62
Chris@143 63 distance = d / sum; // 0 <= d/sum <= 2
Chris@143 64
Chris@143 65 } else if (m_params.norm == NormaliseDistanceToLogSum) {
Chris@143 66
Chris@143 67 // note if this were to be restored, it would have to use
Chris@143 68 // totalEnergies vector instead of f1[freqMapSize] which used to
Chris@143 69 // store the total energy:
Chris@143 70 // double weight = (5 + Math.log(f1[freqMapSize] + f2[freqMapSize]))/10.0;
Chris@143 71
Chris@143 72 double weight = (8 + log(sum)) / 10.0;
Chris@133 73
Chris@143 74 if (weight < 0) weight = 0;
Chris@143 75 else if (weight > 1) weight = 1;
Chris@26 76
Chris@143 77 distance = d / sum * weight;
Chris@143 78
Chris@143 79 } else {
Chris@143 80
Chris@143 81 distance = d;
Chris@143 82 }
Chris@143 83
Chris@143 84 return distance;
Chris@26 85 }
Chris@26 86