Mercurial > hg > match-vamp
view src/DistanceMetric.cpp @ 140:cfba9aec7569 refactors
Separate out the raw & conditioned feature outputs (previously only conditioned was available, but we want raw for our tests). Plus some optional debug output
author | Chris Cannam |
---|---|
date | Thu, 08 Jan 2015 12:11:27 +0000 |
parents | af69db43f5a4 |
children | 7f6f150c1edf 6914a6a01ffc |
line wrap: on
line source
/* -*- 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(DistanceNormalisation norm) : m_norm(norm) { #ifdef DEBUG_DISTANCE_METRIC cerr << "*** DistanceMetric: norm = " << m_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]); } if (sum == 0) return 0; if (m_norm == NormaliseDistanceToSum) return d / sum; // 0 <= d/sum <= 2 if (m_norm != NormaliseDistanceToLogSum) return d; // 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; return d / sum * weight; }