matthiasm@32: /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
matthiasm@32: 
matthiasm@32: /*
matthiasm@32:     pYIN - A fundamental frequency estimator for monophonic audio
matthiasm@32:     Centre for Digital Music, Queen Mary, University of London.
matthiasm@32:     
matthiasm@32:     This program is free software; you can redistribute it and/or
matthiasm@32:     modify it under the terms of the GNU General Public License as
matthiasm@32:     published by the Free Software Foundation; either version 2 of the
matthiasm@32:     License, or (at your option) any later version.  See the file
matthiasm@32:     COLocalCandidatePYING included with this distribution for more information.
matthiasm@32: */
matthiasm@32: 
matthiasm@32: #include "LocalCandidatePYIN.h"
mail@132: #include "MonoPitchHMM.h"
matthiasm@32: #include "YinUtil.h"
matthiasm@32: 
matthiasm@32: #include "vamp-sdk/FFT.h"
matthiasm@32: 
matthiasm@32: #include <vector>
matthiasm@32: #include <algorithm>
matthiasm@32: 
matthiasm@32: #include <cstdio>
matthiasm@32: #include <sstream>
matthiasm@32: // #include <iostream>
matthiasm@32: #include <cmath>
matthiasm@32: #include <complex>
Chris@39: #include <map>
matthiasm@32: 
matthiasm@46: #include <boost/math/distributions.hpp>
matthiasm@46: 
matthiasm@32: using std::string;
matthiasm@32: using std::vector;
Chris@39: using std::map;
matthiasm@32: using Vamp::RealTime;
matthiasm@32: 
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::LocalCandidatePYIN(float inputSampleRate) :
matthiasm@32:     Plugin(inputSampleRate),
matthiasm@32:     m_channels(0),
matthiasm@32:     m_stepSize(256),
matthiasm@32:     m_blockSize(2048),
matthiasm@32:     m_fmin(40),
matthiasm@32:     m_fmax(700),
matthiasm@32:     m_oPitchTrackCandidates(0),
matthiasm@32:     m_threshDistr(2.0f),
matthiasm@32:     m_outputUnvoiced(0.0f),
matthiasm@70:     m_preciseTime(0.0f),
matthiasm@32:     m_pitchProb(0),
matthiasm@32:     m_timestamp(0),
Chris@136:     m_nCandidate(13),
Chris@136:     m_yinUtil(0)
matthiasm@32: {
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::~LocalCandidatePYIN()
matthiasm@32: {
Chris@136:     delete m_yinUtil;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getIdentifier() const
matthiasm@32: {
matthiasm@32:     return "localcandidatepyin";
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getName() const
matthiasm@32: {
matthiasm@32:     return "Local Candidate PYIN";
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getDescription() const
matthiasm@32: {
matthiasm@32:     return "Monophonic pitch and note tracking based on a probabilistic Yin extension.";
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getMaker() const
matthiasm@32: {
matthiasm@32:     return "Matthias Mauch";
matthiasm@32: }
matthiasm@32: 
matthiasm@32: int
matthiasm@32: LocalCandidatePYIN::getPluginVersion() const
matthiasm@32: {
matthiasm@32:     // Increment this each time you release a version that behaves
matthiasm@32:     // differently from the previous one
Chris@143:     return 3;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getCopyright() const
matthiasm@32: {
matthiasm@32:     return "GPL";
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::InputDomain
matthiasm@32: LocalCandidatePYIN::getInputDomain() const
matthiasm@32: {
matthiasm@32:     return TimeDomain;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: size_t
matthiasm@32: LocalCandidatePYIN::getPreferredBlockSize() const
matthiasm@32: {
matthiasm@32:     return 2048;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: size_t 
matthiasm@32: LocalCandidatePYIN::getPreferredStepSize() const
matthiasm@32: {
matthiasm@32:     return 256;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: size_t
matthiasm@32: LocalCandidatePYIN::getMinChannelCount() const
matthiasm@32: {
matthiasm@32:     return 1;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: size_t
matthiasm@32: LocalCandidatePYIN::getMaxChannelCount() const
matthiasm@32: {
matthiasm@32:     return 1;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::ParameterList
matthiasm@32: LocalCandidatePYIN::getParameterDescriptors() const
matthiasm@32: {
matthiasm@32:     ParameterList list;
matthiasm@32:     
matthiasm@32:     ParameterDescriptor d;
matthiasm@32: 
matthiasm@32:     d.identifier = "threshdistr";
matthiasm@32:     d.name = "Yin threshold distribution";
matthiasm@32:     d.description = ".";
matthiasm@32:     d.unit = "";
matthiasm@32:     d.minValue = 0.0f;
matthiasm@32:     d.maxValue = 7.0f;
matthiasm@32:     d.defaultValue = 2.0f;
matthiasm@32:     d.isQuantized = true;
matthiasm@32:     d.quantizeStep = 1.0f;
matthiasm@32:     d.valueNames.push_back("Uniform");
matthiasm@32:     d.valueNames.push_back("Beta (mean 0.10)");
matthiasm@32:     d.valueNames.push_back("Beta (mean 0.15)");
matthiasm@32:     d.valueNames.push_back("Beta (mean 0.20)");
matthiasm@32:     d.valueNames.push_back("Beta (mean 0.30)");
matthiasm@32:     d.valueNames.push_back("Single Value 0.10");
matthiasm@32:     d.valueNames.push_back("Single Value 0.15");
matthiasm@32:     d.valueNames.push_back("Single Value 0.20");
matthiasm@32:     list.push_back(d);
matthiasm@32: 
matthiasm@32:     d.identifier = "outputunvoiced";
matthiasm@32:     d.valueNames.clear();
matthiasm@32:     d.name = "Output estimates classified as unvoiced?";
matthiasm@32:     d.description = ".";
matthiasm@32:     d.unit = "";
matthiasm@32:     d.minValue = 0.0f;
matthiasm@32:     d.maxValue = 2.0f;
matthiasm@32:     d.defaultValue = 0.0f;
matthiasm@32:     d.isQuantized = true;
matthiasm@32:     d.quantizeStep = 1.0f;
matthiasm@32:     d.valueNames.push_back("No");
matthiasm@32:     d.valueNames.push_back("Yes");
matthiasm@32:     d.valueNames.push_back("Yes, as negative frequencies");
matthiasm@32:     list.push_back(d);
matthiasm@32: 
matthiasm@70:     d.identifier = "precisetime";
matthiasm@70:     d.valueNames.clear();
matthiasm@70:     d.name = "Use non-standard precise YIN timing (slow).";
matthiasm@70:     d.description = ".";
matthiasm@70:     d.unit = "";
matthiasm@70:     d.minValue = 0.0f;
matthiasm@70:     d.maxValue = 1.0f;
matthiasm@70:     d.defaultValue = 0.0f;
matthiasm@70:     d.isQuantized = true;
matthiasm@70:     d.quantizeStep = 1.0f;
matthiasm@70:     list.push_back(d);
matthiasm@70: 
matthiasm@32:     return list;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: float
matthiasm@32: LocalCandidatePYIN::getParameter(string identifier) const
matthiasm@32: {
matthiasm@32:     if (identifier == "threshdistr") {
matthiasm@32:             return m_threshDistr;
matthiasm@32:     }
matthiasm@32:     if (identifier == "outputunvoiced") {
matthiasm@32:             return m_outputUnvoiced;
matthiasm@32:     }
matthiasm@70:     if (identifier == "precisetime") {
matthiasm@70:             return m_preciseTime;
matthiasm@70:     }
matthiasm@32:     return 0.f;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: void
matthiasm@32: LocalCandidatePYIN::setParameter(string identifier, float value) 
matthiasm@32: {
matthiasm@32:     if (identifier == "threshdistr")
matthiasm@32:     {
matthiasm@32:         m_threshDistr = value;
matthiasm@32:     }
matthiasm@32:     if (identifier == "outputunvoiced")
matthiasm@32:     {
matthiasm@32:         m_outputUnvoiced = value;
matthiasm@32:     }
matthiasm@70:     if (identifier == "precisetime")
matthiasm@70:     {
matthiasm@70:         m_preciseTime = value;
matthiasm@70:     }
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::ProgramList
matthiasm@32: LocalCandidatePYIN::getPrograms() const
matthiasm@32: {
matthiasm@32:     ProgramList list;
matthiasm@32:     return list;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: string
matthiasm@32: LocalCandidatePYIN::getCurrentProgram() const
matthiasm@32: {
matthiasm@32:     return ""; // no programs
matthiasm@32: }
matthiasm@32: 
matthiasm@32: void
Chris@138: LocalCandidatePYIN::selectProgram(string)
matthiasm@32: {
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::OutputList
matthiasm@32: LocalCandidatePYIN::getOutputDescriptors() const
matthiasm@32: {
matthiasm@32:     OutputList outputs;
matthiasm@32: 
matthiasm@32:     OutputDescriptor d;
matthiasm@32: 
matthiasm@32:     d.identifier = "pitchtrackcandidates";
matthiasm@32:     d.name = "Pitch track candidates";
matthiasm@32:     d.description = "Multiple candidate pitch tracks.";
matthiasm@32:     d.unit = "Hz";
matthiasm@32:     d.hasFixedBinCount = false;
matthiasm@32:     d.hasKnownExtents = true;
matthiasm@32:     d.minValue = m_fmin;
Chris@39:     d.maxValue = 500; //!!!???
matthiasm@32:     d.isQuantized = false;
matthiasm@32:     d.sampleType = OutputDescriptor::FixedSampleRate;
matthiasm@32:     d.sampleRate = (m_inputSampleRate / m_stepSize);
matthiasm@32:     d.hasDuration = false;
matthiasm@32:     outputs.push_back(d);
matthiasm@32: 
matthiasm@32:     return outputs;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: bool
matthiasm@32: LocalCandidatePYIN::initialise(size_t channels, size_t stepSize, size_t blockSize)
matthiasm@32: {
matthiasm@32:     if (channels < getMinChannelCount() ||
matthiasm@32: 	channels > getMaxChannelCount()) return false;
matthiasm@32: 
matthiasm@32: /*
matthiasm@32:     std::cerr << "LocalCandidatePYIN::initialise: channels = " << channels
matthiasm@32:           << ", stepSize = " << stepSize << ", blockSize = " << blockSize
matthiasm@32:           << std::endl;
matthiasm@32: */
matthiasm@32:     m_channels = channels;
matthiasm@32:     m_stepSize = stepSize;
matthiasm@32:     m_blockSize = blockSize;
Chris@136: 
Chris@136:     m_yinUtil = new YinUtil(m_blockSize/2);
matthiasm@32:     
matthiasm@32:     reset();
matthiasm@32: 
matthiasm@32:     return true;
matthiasm@32: }
matthiasm@32: 
matthiasm@32: void
matthiasm@32: LocalCandidatePYIN::reset()
matthiasm@32: {    
matthiasm@32:     m_pitchProb.clear();
matthiasm@32:     m_timestamp.clear();
matthiasm@32: /*    
matthiasm@32:     std::cerr << "LocalCandidatePYIN::reset"
matthiasm@32:           << ", blockSize = " << m_blockSize
matthiasm@32:           << std::endl;
matthiasm@32: */
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::FeatureSet
matthiasm@32: LocalCandidatePYIN::process(const float *const *inputBuffers, RealTime timestamp)
matthiasm@32: {
matthiasm@77:     int offset = m_preciseTime == 1.0 ? m_blockSize/2 : m_blockSize/4;
matthiasm@77:     timestamp = timestamp + Vamp::RealTime::frame2RealTime(offset, lrintf(m_inputSampleRate));
matthiasm@32:     
matthiasm@32:     double *dInputBuffers = new double[m_blockSize];
matthiasm@32:     for (size_t i = 0; i < m_blockSize; ++i) dInputBuffers[i] = inputBuffers[0][i];
matthiasm@32:     
matthiasm@32:     size_t yinBufferSize = m_blockSize/2;
matthiasm@32:     double* yinBuffer = new double[yinBufferSize];
Chris@136:     if (!m_preciseTime) m_yinUtil->fastDifference(dInputBuffers, yinBuffer);
Chris@136:     else m_yinUtil->slowDifference(dInputBuffers, yinBuffer);    
matthiasm@32:     
matthiasm@32:     delete [] dInputBuffers;
matthiasm@32: 
Chris@136:     m_yinUtil->cumulativeDifference(yinBuffer);
matthiasm@32:     
matthiasm@46:     float minFrequency = 60;
matthiasm@46:     float maxFrequency = 900;
Chris@136:     vector<double> peakProbability = m_yinUtil->yinProb(yinBuffer, 
Chris@136:                                                         m_threshDistr, 
Chris@136:                                                         m_inputSampleRate/maxFrequency, 
Chris@136:                                                         m_inputSampleRate/minFrequency);
matthiasm@46: 
matthiasm@46:     vector<pair<double, double> > tempPitchProb;
matthiasm@46:     for (size_t iBuf = 0; iBuf < yinBufferSize; ++iBuf)
matthiasm@32:     {
matthiasm@46:         if (peakProbability[iBuf] > 0)
matthiasm@32:         {
matthiasm@46:             double currentF0 = 
matthiasm@46:                 m_inputSampleRate * (1.0 /
Chris@136:                 m_yinUtil->parabolicInterpolation(yinBuffer, iBuf));
matthiasm@46:             double tempPitch = 12 * std::log(currentF0/440)/std::log(2.) + 69;
matthiasm@46:             tempPitchProb.push_back(pair<double, double>(tempPitch, peakProbability[iBuf]));
matthiasm@32:         }
matthiasm@32:     }
matthiasm@46:     m_pitchProb.push_back(tempPitchProb);
matthiasm@32:     m_timestamp.push_back(timestamp);
matthiasm@32: 
matthiasm@76:     delete[] yinBuffer;
matthiasm@76: 
Chris@39:     return FeatureSet();
matthiasm@32: }
matthiasm@32: 
matthiasm@32: LocalCandidatePYIN::FeatureSet
matthiasm@32: LocalCandidatePYIN::getRemainingFeatures()
matthiasm@32: {
Chris@39:     // timestamp -> candidate number -> value
Chris@39:     map<RealTime, map<int, float> > featureValues;
matthiasm@32: 
matthiasm@37:     // std::cerr << "in remaining features" << std::endl;
matthiasm@32: 
matthiasm@32:     if (m_pitchProb.empty()) {
Chris@39:         return FeatureSet();
matthiasm@32:     }
matthiasm@32: 
matthiasm@32:     // MONO-PITCH STUFF
mail@132:     MonoPitchHMM hmm(0);
matthiasm@32:     size_t nFrame = m_timestamp.size();
matthiasm@32:     vector<vector<float> > pitchTracks;
matthiasm@32:     vector<float> freqSum = vector<float>(m_nCandidate);
matthiasm@32:     vector<float> freqNumber = vector<float>(m_nCandidate);
matthiasm@32:     vector<float> freqMean = vector<float>(m_nCandidate);
matthiasm@44:     
matthiasm@46:     boost::math::normal normalDist(0, 8); // semitones sd
matthiasm@46:     float maxNormalDist = boost::math::pdf(normalDist, 0);
matthiasm@46:     
matthiasm@110:     // Viterbi-decode multiple times with different frequencies emphasised
matthiasm@32:     for (size_t iCandidate = 0; iCandidate < m_nCandidate; ++iCandidate)
matthiasm@32:     {
matthiasm@32:         pitchTracks.push_back(vector<float>(nFrame));
mail@132:         vector<pair<double,double> > tempPitchProb;
mail@132:         vector<vector<double> > tempObsProb;
matthiasm@46:         float centrePitch = 45 + 3 * iCandidate;
matthiasm@109: 
matthiasm@46:         for (size_t iFrame = 0; iFrame < nFrame; ++iFrame) {
matthiasm@46:             float sumProb = 0;
matthiasm@46:             float pitch = 0;
matthiasm@46:             float prob = 0;
matthiasm@109:             for (size_t iProb = 0; iProb < m_pitchProb[iFrame].size(); ++iProb)
matthiasm@109:             {
matthiasm@109:                 pitch = m_pitchProb[iFrame][iProb].first;                
matthiasm@109:                 prob  = m_pitchProb[iFrame][iProb].second * 
matthiasm@109:                     boost::math::pdf(normalDist, pitch-centrePitch) /
matthiasm@109:                     maxNormalDist * 2;
matthiasm@46:                 sumProb += prob;
mail@132:                 tempPitchProb.push_back(
matthiasm@109:                     pair<double,double>(pitch,prob));
matthiasm@46:             }
matthiasm@109:             for (size_t iProb = 0; iProb < m_pitchProb[iFrame].size(); ++iProb)
matthiasm@109:             {
mail@132:                 tempPitchProb[iProb].second /= sumProb;
matthiasm@46:             }
mail@132:             tempObsProb.push_back(hmm.calculateObsProb(tempPitchProb));
matthiasm@46:         }
matthiasm@109: 
mail@132:         vector<int> rawPitchPath = hmm.decodeViterbi(tempObsProb);
mail@132:         vector<float> mpOut;
mail@132: 
mail@132:         for (size_t iFrame = 0; iFrame < rawPitchPath.size(); ++iFrame)
mail@132:         {
mail@132:             float freq = hmm.nearestFreq(rawPitchPath[iFrame], 
Chris@141:                                          m_pitchProb[iFrame]);
mail@132:             mpOut.push_back(freq); // for note processing below
mail@132:         }
mail@132: 
Chris@141:         for (size_t iFrame = 0; iFrame < rawPitchPath.size(); ++iFrame)
matthiasm@32:         {
matthiasm@32:             if (mpOut[iFrame] > 0) {
matthiasm@109: 
matthiasm@32:                 pitchTracks[iCandidate][iFrame] = mpOut[iFrame];
matthiasm@32:                 freqSum[iCandidate] += mpOut[iFrame];
matthiasm@32:                 freqNumber[iCandidate]++;
matthiasm@32:             }
matthiasm@32:         }
matthiasm@32:         freqMean[iCandidate] = freqSum[iCandidate]*1.0/freqNumber[iCandidate];
matthiasm@32:     }
matthiasm@32: 
matthiasm@37:     // find near duplicate pitch tracks
matthiasm@34:     vector<size_t> duplicates;
matthiasm@34:     for (size_t iCandidate = 0; iCandidate < m_nCandidate; ++iCandidate) {
matthiasm@34:         for (size_t jCandidate = iCandidate+1; jCandidate < m_nCandidate; ++jCandidate) {
matthiasm@34:             size_t countEqual = 0;
matthiasm@34:             for (size_t iFrame = 0; iFrame < nFrame; ++iFrame) 
matthiasm@34:             {
matthiasm@46:                 if ((pitchTracks[jCandidate][iFrame] == 0 && pitchTracks[iCandidate][iFrame] == 0) ||
matthiasm@46:                 fabs(pitchTracks[iCandidate][iFrame]/pitchTracks[jCandidate][iFrame]-1)<0.01)
matthiasm@34:                 countEqual++;
matthiasm@34:             }
matthiasm@46:             // std::cerr << "proportion equal: " << (countEqual * 1.0 / nFrame) << std::endl;    
matthiasm@34:             if (countEqual * 1.0 / nFrame > 0.8) {
matthiasm@34:                 if (freqNumber[iCandidate] > freqNumber[jCandidate]) {
matthiasm@34:                     duplicates.push_back(jCandidate);
matthiasm@46:                 } else if (iCandidate < jCandidate) {
matthiasm@34:                     duplicates.push_back(iCandidate);
matthiasm@34:                 }
matthiasm@34:             }
matthiasm@34:         }
matthiasm@34:     }
matthiasm@34: 
matthiasm@37:     // now find non-duplicate pitch tracks
Chris@39:     map<int, int> candidateActuals;
Chris@39:     map<int, std::string> candidateLabels;
Chris@39: 
matthiasm@46:     vector<vector<float> > outputFrequencies;
matthiasm@60:     for (size_t iFrame = 0; iFrame < nFrame; ++iFrame) outputFrequencies.push_back(vector<float>());
matthiasm@46: 
matthiasm@32:     int actualCandidateNumber = 0;
matthiasm@110:     for (size_t iCandidate = 0; iCandidate < m_nCandidate; ++iCandidate)
matthiasm@110:     {
matthiasm@34:         bool isDuplicate = false;
matthiasm@34:         for (size_t i = 0; i < duplicates.size(); ++i) {
matthiasm@110:     
matthiasm@34:             if (duplicates[i] == iCandidate) {
matthiasm@34:                 isDuplicate = true;
matthiasm@34:                 break;
matthiasm@34:             }
matthiasm@34:         }
matthiasm@46:         if (!isDuplicate && freqNumber[iCandidate] > 0.5*nFrame)
matthiasm@32:         {
matthiasm@32:             std::ostringstream convert;
matthiasm@32:             convert << actualCandidateNumber++;
Chris@39:             candidateLabels[iCandidate] = convert.str();
Chris@39:             candidateActuals[iCandidate] = actualCandidateNumber;
matthiasm@46:             // std::cerr << iCandidate << " " << actualCandidateNumber << " " << freqNumber[iCandidate] << " " << freqMean[iCandidate] << std::endl;
matthiasm@32:             for (size_t iFrame = 0; iFrame < nFrame; ++iFrame) 
matthiasm@32:             {
matthiasm@32:                 if (pitchTracks[iCandidate][iFrame] > 0)
matthiasm@32:                 {
matthiasm@46:                     // featureValues[m_timestamp[iFrame]][iCandidate] = 
matthiasm@46:                     //     pitchTracks[iCandidate][iFrame];
matthiasm@46:                     outputFrequencies[iFrame].push_back(pitchTracks[iCandidate][iFrame]);
matthiasm@60:                 } else {
matthiasm@60:                     outputFrequencies[iFrame].push_back(0);
matthiasm@32:                 }
matthiasm@32:             }
matthiasm@32:         }
matthiasm@43:         // fs[m_oPitchTrackCandidates].push_back(f);
matthiasm@32:     }
matthiasm@32: 
Chris@39:     // adapt our features so as to return a stack of candidate values
Chris@39:     // per frame
Chris@39: 
Chris@39:     FeatureSet fs;
Chris@39: 
matthiasm@46:     for (size_t iFrame = 0; iFrame < nFrame; ++iFrame){
Chris@39:         Feature f;
Chris@39:         f.hasTimestamp = true;
matthiasm@46:         f.timestamp = m_timestamp[iFrame];
matthiasm@46:         f.values = outputFrequencies[iFrame];
Chris@39:         fs[0].push_back(f);
Chris@39:     }
matthiasm@46:     
matthiasm@46:     // I stopped using Chris's map stuff below because I couldn't get my head around it
matthiasm@46:     //
matthiasm@46:     // for (map<RealTime, map<int, float> >::const_iterator i =
matthiasm@46:     //          featureValues.begin(); i != featureValues.end(); ++i) {
matthiasm@46:     //     Feature f;
matthiasm@46:     //     f.hasTimestamp = true;
matthiasm@46:     //     f.timestamp = i->first;
matthiasm@46:     //     int nextCandidate = candidateActuals.begin()->second;
matthiasm@46:     //     for (map<int, float>::const_iterator j = 
matthiasm@46:     //              i->second.begin(); j != i->second.end(); ++j) {
matthiasm@46:     //         while (candidateActuals[j->first] > nextCandidate) {
matthiasm@46:     //             f.values.push_back(0);
matthiasm@46:     //             ++nextCandidate;
matthiasm@46:     //         }
matthiasm@46:     //         f.values.push_back(j->second);
matthiasm@46:     //         nextCandidate = j->first + 1;
matthiasm@46:     //     }
matthiasm@46:     //     //!!! can't use labels?
matthiasm@46:     //     fs[0].push_back(f);
matthiasm@46:     // }
matthiasm@32: 
matthiasm@32:     return fs;
matthiasm@32: }