Mercurial > hg > match-vamp
view src/DistanceMetric.cpp @ 146:214b72d55796 noise
Update unit tests
author | Chris Cannam |
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date | Fri, 16 Jan 2015 16:48:55 +0000 |
parents | ecfb4ada171b |
children | b79151bb75af |
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/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */ /* Vamp feature extraction plugin using the MATCH audio alignment algorithm. Centre for Digital Music, Queen Mary, University of London. This file copyright 2007 Simon Dixon, Chris Cannam and QMUL. This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. See the file COPYING included with this distribution for more information. */ #include "DistanceMetric.h" #include <cassert> #include <cmath> #include <iostream> using namespace std; //#define DEBUG_DISTANCE_METRIC 1 DistanceMetric::DistanceMetric(Parameters params) : m_params(params) { #ifdef DEBUG_DISTANCE_METRIC cerr << "*** DistanceMetric: norm = " << m_params.norm << endl; #endif } double DistanceMetric::calcDistance(const vector<double> &f1, const vector<double> &f2) { double d = 0; double sum = 0; int featureSize = f1.size(); assert(int(f2.size()) == featureSize); for (int i = 0; i < featureSize; i++) { d += fabs(f1[i] - f2[i]); sum += fabs(f1[i]) + fabs(f2[i]); } double noise = 1e-3 * featureSize; d += noise; sum += noise; if (sum == 0) { return 0; } double distance = 0; if (m_params.norm == NormaliseDistanceToSum) { distance = d / sum; // 0 <= d/sum <= 2 } else if (m_params.norm == NormaliseDistanceToLogSum) { // note if this were to be restored, it would have to use // totalEnergies vector instead of f1[freqMapSize] which used to // store the total energy: // double weight = (5 + Math.log(f1[freqMapSize] + f2[freqMapSize]))/10.0; double weight = (8 + log(sum)) / 10.0; if (weight < 0) weight = 0; else if (weight > 1) weight = 1; distance = d / sum * weight; } else { distance = d; } return distance; }