diff NNLSBase.cpp @ 35:cf8898a0174c matthiasm-plugin

* Split out NNLSChroma plugin into three plugins (chroma, chordino, tuning) with a common base class.
  There's still quite a lot of duplication between the getRemainingFeatures functions.
  Also add copyright / copying headers, etc.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/NNLSBase.cpp	Fri Oct 22 11:30:21 2010 +0100
@@ -0,0 +1,1021 @@
+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
+
+/*
+  NNLS-Chroma / Chordino
+
+  Audio feature extraction plugins for chromagram and chord
+  estimation.
+
+  Centre for Digital Music, Queen Mary University of London.
+  This file copyright 2008-2010 Matthias Mauch 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 "NNLSBase.h"
+
+#include "chromamethods.h"
+
+#include <cstdlib>
+#include <fstream>
+#include <cmath>
+
+#include <algorithm>
+
+const bool debug_on = false;
+
+const vector<float> hw(hammingwind, hammingwind+19);
+
+NNLSBase::NNLSBase(float inputSampleRate) :
+    Plugin(inputSampleRate),
+    m_logSpectrum(0),
+    m_blockSize(0),
+    m_stepSize(0),
+    m_lengthOfNoteIndex(0),
+    m_meanTuning0(0),
+    m_meanTuning1(0),
+    m_meanTuning2(0),
+    m_localTuning0(0),
+    m_localTuning1(0),
+    m_localTuning2(0),
+    m_paling(1.0),
+    m_preset(0.0),
+    m_localTuning(0),
+    m_kernelValue(0),
+    m_kernelFftIndex(0),
+    m_kernelNoteIndex(0),
+    m_dict(0),
+    m_tuneLocal(false),
+    m_dictID(0),
+    m_chorddict(0),
+    m_chordnames(0),
+    m_doNormalizeChroma(0),
+    m_rollon(0.01)
+{
+    if (debug_on) cerr << "--> NNLSBase" << endl;
+
+    // make the *note* dictionary matrix
+    m_dict = new float[nNote * 84];
+    for (unsigned i = 0; i < nNote * 84; ++i) m_dict[i] = 0.0;
+    dictionaryMatrix(m_dict);
+	
+    // get the *chord* dictionary from file (if the file exists)
+    m_chordnames = chordDictionary(&m_chorddict);
+}
+
+
+NNLSBase::~NNLSBase()
+{
+    if (debug_on) cerr << "--> ~NNLSBase" << endl;
+    delete [] m_dict;
+}
+
+string
+NNLSBase::getMaker() const
+{
+    if (debug_on) cerr << "--> getMaker" << endl;
+    // Your name here
+    return "Matthias Mauch";
+}
+
+int
+NNLSBase::getPluginVersion() const
+{
+    if (debug_on) cerr << "--> getPluginVersion" << endl;
+    // Increment this each time you release a version that behaves
+    // differently from the previous one
+    return 1;
+}
+
+string
+NNLSBase::getCopyright() const
+{
+    if (debug_on) cerr << "--> getCopyright" << endl;
+    // This function is not ideally named.  It does not necessarily
+    // need to say who made the plugin -- getMaker does that -- but it
+    // should indicate the terms under which it is distributed.  For
+    // example, "Copyright (year). All Rights Reserved", or "GPL"
+    return "GPL";
+}
+
+NNLSBase::InputDomain
+NNLSBase::getInputDomain() const
+{
+    if (debug_on) cerr << "--> getInputDomain" << endl;
+    return FrequencyDomain;
+}
+
+size_t
+NNLSBase::getPreferredBlockSize() const
+{
+    if (debug_on) cerr << "--> getPreferredBlockSize" << endl;
+    return 16384; // 0 means "I can handle any block size"
+}
+
+size_t 
+NNLSBase::getPreferredStepSize() const
+{
+    if (debug_on) cerr << "--> getPreferredStepSize" << endl;
+    return 2048; // 0 means "anything sensible"; in practice this
+    // means the same as the block size for TimeDomain
+    // plugins, or half of it for FrequencyDomain plugins
+}
+
+size_t
+NNLSBase::getMinChannelCount() const
+{
+    if (debug_on) cerr << "--> getMinChannelCount" << endl;
+    return 1;
+}
+
+size_t
+NNLSBase::getMaxChannelCount() const
+{
+    if (debug_on) cerr << "--> getMaxChannelCount" << endl;
+    return 1;
+}
+
+NNLSBase::ParameterList
+NNLSBase::getParameterDescriptors() const
+{
+    if (debug_on) cerr << "--> getParameterDescriptors" << endl;
+    ParameterList list;
+
+    ParameterDescriptor d3;
+    d3.identifier = "preset";
+    d3.name = "preset";
+    d3.description = "Spectral paling: no paling - 0; whitening - 1.";
+    d3.unit = "";
+    d3.isQuantized = true;
+    d3.quantizeStep = 1;
+    d3.minValue = 0.0;
+    d3.maxValue = 3.0;
+    d3.defaultValue = 0.0;
+    d3.valueNames.push_back("polyphonic pop");
+    d3.valueNames.push_back("polyphonic pop (fast)");
+    d3.valueNames.push_back("solo keyboard");
+    d3.valueNames.push_back("manual");
+    list.push_back(d3);
+
+    ParameterDescriptor d5;
+    d5.identifier = "rollon";
+    d5.name = "spectral roll-on";
+    d5.description = "The bins below the spectral roll-on quantile will be set to 0.";
+    d5.unit = "";
+    d5.minValue = 0;
+    d5.maxValue = 1;
+    d5.defaultValue = 0;
+    d5.isQuantized = false;
+    list.push_back(d5);
+
+    // ParameterDescriptor d0;
+    //  d0.identifier = "notedict";
+    //  d0.name = "note dictionary";
+    //  d0.description = "Notes in different note dictionaries differ by their spectral shapes.";
+    //  d0.unit = "";
+    //  d0.minValue = 0;
+    //  d0.maxValue = 1;
+    //  d0.defaultValue = 0;
+    //  d0.isQuantized = true;
+    //  d0.valueNames.push_back("s = 0.6");
+    //  d0.valueNames.push_back("no NNLS");
+    //  d0.quantizeStep = 1.0;
+    //  list.push_back(d0);
+
+    ParameterDescriptor d1;
+    d1.identifier = "tuningmode";
+    d1.name = "tuning mode";
+    d1.description = "Tuning can be performed locally or on the whole extraction segment. Local tuning is only advisable when the tuning is likely to change over the audio, for example in podcasts, or in a cappella singing.";
+    d1.unit = "";
+    d1.minValue = 0;
+    d1.maxValue = 1;
+    d1.defaultValue = 0;
+    d1.isQuantized = true;
+    d1.valueNames.push_back("global tuning");
+    d1.valueNames.push_back("local tuning");
+    d1.quantizeStep = 1.0;
+    list.push_back(d1);
+
+    //     ParameterDescriptor d2;
+    //     d2.identifier = "paling";
+    //     d2.name = "spectral paling";
+    //     d2.description = "Spectral paling: no paling - 0; whitening - 1.";
+    //     d2.unit = "";
+    // d2.isQuantized = true;
+    // // d2.quantizeStep = 0.1;
+    //     d2.minValue = 0.0;
+    //     d2.maxValue = 1.0;
+    //     d2.defaultValue = 1.0;
+    //     d2.isQuantized = false;
+    //     list.push_back(d2);
+    ParameterDescriptor d4;
+    d4.identifier = "chromanormalize";
+    d4.name = "chroma normalization";
+    d4.description = "How shall the chroma vector be normalized?";
+    d4.unit = "";
+    d4.minValue = 0;
+    d4.maxValue = 3;
+    d4.defaultValue = 0;
+    d4.isQuantized = true;
+    d4.valueNames.push_back("none");
+    d4.valueNames.push_back("maximum norm");
+    d4.valueNames.push_back("L1 norm");
+    d4.valueNames.push_back("L2 norm");
+    d4.quantizeStep = 1.0;
+    list.push_back(d4);
+
+    return list;
+}
+
+float
+NNLSBase::getParameter(string identifier) const
+{
+    if (debug_on) cerr << "--> getParameter" << endl;
+    if (identifier == "notedict") {
+        return m_dictID; 
+    }
+    
+    if (identifier == "paling") {
+        return m_paling; 
+    }
+
+    if (identifier == "rollon") {
+        return m_rollon; 
+    }
+    
+    if (identifier == "tuningmode") {
+        if (m_tuneLocal) {
+            return 1.0;
+        } else {
+            return 0.0;
+        }
+    }
+    if (identifier == "preset") {
+        return m_preset;
+    }
+    if (identifier == "chromanormalize") {
+        return m_doNormalizeChroma;
+    }
+    return 0;
+    
+}
+
+void
+NNLSBase::setParameter(string identifier, float value) 
+{
+    if (debug_on) cerr << "--> setParameter" << endl;
+    if (identifier == "notedict") {
+        m_dictID = (int) value;
+    }
+    
+    if (identifier == "paling") {
+        m_paling = value;
+    }
+    
+    if (identifier == "tuningmode") {
+        m_tuneLocal = (value > 0) ? true : false;
+        // cerr << "m_tuneLocal :" << m_tuneLocal << endl;
+    }
+    if (identifier == "preset") {
+        m_preset = value;
+        if (m_preset == 0.0) {
+            m_tuneLocal = false;
+            m_paling = 1.0;
+            m_dictID = 0.0;
+        }
+        if (m_preset == 1.0) {
+            m_tuneLocal = false;
+            m_paling = 1.0;
+            m_dictID = 1.0;
+        }
+        if (m_preset == 2.0) {
+            m_tuneLocal = false;
+            m_paling = 0.7;
+            m_dictID = 0.0;
+        }
+    }
+    if (identifier == "chromanormalize") {
+        m_doNormalizeChroma = value;
+    }
+	 
+    if (identifier == "rollon") {
+        m_rollon = value;
+    }
+}
+
+NNLSBase::ProgramList
+NNLSBase::getPrograms() const
+{
+    if (debug_on) cerr << "--> getPrograms" << endl;
+    ProgramList list;
+
+    // If you have no programs, return an empty list (or simply don't
+    // implement this function or getCurrentProgram/selectProgram)
+
+    return list;
+}
+
+string
+NNLSBase::getCurrentProgram() const
+{
+    if (debug_on) cerr << "--> getCurrentProgram" << endl;
+    return ""; // no programs
+}
+
+void
+NNLSBase::selectProgram(string name)
+{
+    if (debug_on) cerr << "--> selectProgram" << endl;
+}
+
+
+bool
+NNLSBase::initialise(size_t channels, size_t stepSize, size_t blockSize)
+{	
+    if (debug_on) {
+        cerr << "--> initialise";
+    }
+	
+    if (channels < getMinChannelCount() ||
+	channels > getMaxChannelCount()) return false;
+    m_blockSize = blockSize;
+    m_stepSize = stepSize;
+    m_frameCount = 0;
+    int tempn = 256 * m_blockSize/2;
+    // cerr << "length of tempkernel : " <<  tempn << endl;
+    float *tempkernel;
+
+    tempkernel = new float[tempn];
+
+    logFreqMatrix(m_inputSampleRate, m_blockSize, tempkernel);
+    m_kernelValue.clear();
+    m_kernelFftIndex.clear();
+    m_kernelNoteIndex.clear();
+    int countNonzero = 0;
+    for (unsigned iNote = 0; iNote < nNote; ++iNote) { // I don't know if this is wise: manually making a sparse matrix
+        for (unsigned iFFT = 0; iFFT < blockSize/2; ++iFFT) {
+            if (tempkernel[iFFT + blockSize/2 * iNote] > 0) {
+                m_kernelValue.push_back(tempkernel[iFFT + blockSize/2 * iNote]);
+                if (tempkernel[iFFT + blockSize/2 * iNote] > 0) {
+                    countNonzero++;
+                }
+                m_kernelFftIndex.push_back(iFFT);
+                m_kernelNoteIndex.push_back(iNote);				
+            }
+        }
+    }
+    // cerr << "nonzero count : " << countNonzero << endl;
+    delete [] tempkernel;
+/*
+    ofstream myfile;
+    myfile.open ("matrix.txt");
+    // myfile << "Writing this to a file.\n";	
+    for (int i = 0; i < nNote * 84; ++i) {
+        myfile << m_dict[i] << endl;		
+    }
+    myfile.close();
+*/
+    return true;
+}
+
+void
+NNLSBase::reset()
+{
+    if (debug_on) cerr << "--> reset";
+	
+    // Clear buffers, reset stored values, etc
+    m_frameCount = 0;
+    m_dictID = 0;
+    m_logSpectrum.clear();
+    m_meanTuning0 = 0;
+    m_meanTuning1 = 0;
+    m_meanTuning2 = 0;
+    m_localTuning0 = 0;
+    m_localTuning1 = 0;
+    m_localTuning2 = 0;
+    m_localTuning.clear();
+}
+
+void
+NNLSBase::baseProcess(const float *const *inputBuffers, Vamp::RealTime timestamp)
+{   
+    m_frameCount++;   
+    float *magnitude = new float[m_blockSize/2];
+	
+    const float *fbuf = inputBuffers[0];	
+    float energysum = 0;
+    // make magnitude
+    float maxmag = -10000;
+    for (size_t iBin = 0; iBin < m_blockSize/2; iBin++) {
+        magnitude[iBin] = sqrt(fbuf[2 * iBin] * fbuf[2 * iBin] + 
+                               fbuf[2 * iBin + 1] * fbuf[2 * iBin + 1]);		
+        if (maxmag < magnitude[iBin]) maxmag = magnitude[iBin];
+        if (m_rollon > 0) {
+            energysum += pow(magnitude[iBin],2);
+        }
+    }
+	
+    float cumenergy = 0;
+    if (m_rollon > 0) {
+        for (size_t iBin = 2; iBin < m_blockSize/2; iBin++) {
+            cumenergy +=  pow(magnitude[iBin],2);
+            if (cumenergy < energysum * m_rollon) magnitude[iBin-2] = 0;
+            else break;
+        }
+    }
+	
+    if (maxmag < 2) {
+        // cerr << "timestamp " << timestamp << ": very low magnitude, setting magnitude to all zeros" << endl;
+        for (size_t iBin = 0; iBin < m_blockSize/2; iBin++) {
+            magnitude[iBin] = 0;
+        }
+    }
+		
+    // note magnitude mapping using pre-calculated matrix
+    float *nm  = new float[nNote]; // note magnitude
+    for (size_t iNote = 0; iNote < nNote; iNote++) {
+        nm[iNote] = 0; // initialise as 0
+    }
+    int binCount = 0;
+    for (vector<float>::iterator it = m_kernelValue.begin(); it != m_kernelValue.end(); ++it) {
+        // cerr << ".";
+        nm[m_kernelNoteIndex[binCount]] += magnitude[m_kernelFftIndex[binCount]] * m_kernelValue[binCount];
+        // cerr << m_kernelFftIndex[binCount] << " -- " << magnitude[m_kernelFftIndex[binCount]] << " -- "<< m_kernelValue[binCount] << endl;
+        binCount++;	
+    }
+    // cerr << nm[20];
+    // cerr << endl;
+	
+	
+    float one_over_N = 1.0/m_frameCount;
+    // update means of complex tuning variables
+    m_meanTuning0 *= float(m_frameCount-1)*one_over_N;
+    m_meanTuning1 *= float(m_frameCount-1)*one_over_N;
+    m_meanTuning2 *= float(m_frameCount-1)*one_over_N;
+	
+    for (int iTone = 0; iTone < 160; iTone = iTone + 3) {
+        m_meanTuning0 += nm[iTone + 0]*one_over_N;
+    	m_meanTuning1 += nm[iTone + 1]*one_over_N;
+    	m_meanTuning2 += nm[iTone + 2]*one_over_N;
+        float ratioOld = 0.997;
+        m_localTuning0 *= ratioOld; m_localTuning0 += nm[iTone + 0] * (1 - ratioOld);
+        m_localTuning1 *= ratioOld; m_localTuning1 += nm[iTone + 1] * (1 - ratioOld);
+        m_localTuning2 *= ratioOld; m_localTuning2 += nm[iTone + 2] * (1 - ratioOld);
+    }
+	
+    // if (m_tuneLocal) {
+    // local tuning
+    float localTuningImag = sinvalue * m_localTuning1 - sinvalue * m_localTuning2;
+    float localTuningReal = m_localTuning0 + cosvalue * m_localTuning1 + cosvalue * m_localTuning2;
+    float normalisedtuning = atan2(localTuningImag, localTuningReal)/(2*M_PI);
+    m_localTuning.push_back(normalisedtuning);
+    
+    Feature f1; // logfreqspec
+    f1.hasTimestamp = true;
+    f1.timestamp = timestamp;
+    for (size_t iNote = 0; iNote < nNote; iNote++) {
+        f1.values.push_back(nm[iNote]);
+    }
+
+    // deletes
+    delete[] magnitude;
+    delete[] nm;
+
+    m_logSpectrum.push_back(f1); // remember note magnitude
+}
+
+
+#ifdef NOT_DEFINED
+
+NNLSBase::FeatureSet
+NNLSBase::getRemainingFeatures()
+{
+    if (debug_on) cerr << "--> getRemainingFeatures" << endl;
+    FeatureSet fsOut;
+    if (m_logSpectrum.size() == 0) return fsOut;
+    int nChord = m_chordnames.size();
+    // 
+    /**  Calculate Tuning
+         calculate tuning from (using the angle of the complex number defined by the 
+         cumulative mean real and imag values)
+    **/
+    float meanTuningImag = sinvalue * m_meanTuning1 - sinvalue * m_meanTuning2;
+    float meanTuningReal = m_meanTuning0 + cosvalue * m_meanTuning1 + cosvalue * m_meanTuning2;
+    float cumulativetuning = 440 * pow(2,atan2(meanTuningImag, meanTuningReal)/(24*M_PI));
+    float normalisedtuning = atan2(meanTuningImag, meanTuningReal)/(2*M_PI);
+    int intShift = floor(normalisedtuning * 3);
+    float intFactor = normalisedtuning * 3 - intShift; // intFactor is a really bad name for this
+		    
+    char buffer0 [50];
+		
+    sprintf(buffer0, "estimated tuning: %0.1f Hz", cumulativetuning);
+		    
+    // cerr << "normalisedtuning: " << normalisedtuning << '\n';
+		    
+    // push tuning to FeatureSet fsOut
+    Feature f0; // tuning
+    f0.hasTimestamp = true;
+    f0.timestamp = Vamp::RealTime::frame2RealTime(0, lrintf(m_inputSampleRate));;
+    f0.label = buffer0;
+    fsOut[0].push_back(f0);  
+		    
+    /** Tune Log-Frequency Spectrogram
+        calculate a tuned log-frequency spectrogram (f2): use the tuning estimated above (kinda f0) to 
+        perform linear interpolation on the existing log-frequency spectrogram (kinda f1).
+    **/
+    cerr << endl << "[NNLS Chroma Plugin] Tuning Log-Frequency Spectrogram ... ";
+					
+    float tempValue = 0;
+    float dbThreshold = 0; // relative to the background spectrum
+    float thresh = pow(10,dbThreshold/20);
+    // cerr << "tune local ? " << m_tuneLocal << endl;
+    int count = 0;
+		
+    for (FeatureList::iterator i = m_logSpectrum.begin(); i != m_logSpectrum.end(); ++i) {
+        Feature f1 = *i;
+        Feature f2; // tuned log-frequency spectrum
+        f2.hasTimestamp = true;
+        f2.timestamp = f1.timestamp;
+        f2.values.push_back(0.0); f2.values.push_back(0.0); // set lower edge to zero
+		
+        if (m_tuneLocal) {
+            intShift = floor(m_localTuning[count] * 3);
+            intFactor = m_localTuning[count] * 3 - intShift; // intFactor is a really bad name for this
+        }
+		        
+        // cerr << intShift << " " << intFactor << endl;
+		        
+        for (unsigned k = 2; k < f1.values.size() - 3; ++k) { // interpolate all inner bins
+            tempValue = f1.values[k + intShift] * (1-intFactor) + f1.values[k+intShift+1] * intFactor;
+            f2.values.push_back(tempValue);
+        }
+		        
+        f2.values.push_back(0.0); f2.values.push_back(0.0); f2.values.push_back(0.0); // upper edge
+        vector<float> runningmean = SpecialConvolution(f2.values,hw);
+        vector<float> runningstd;
+        for (int i = 0; i < 256; i++) { // first step: squared values into vector (variance)
+            runningstd.push_back((f2.values[i] - runningmean[i]) * (f2.values[i] - runningmean[i]));
+        }
+        runningstd = SpecialConvolution(runningstd,hw); // second step convolve
+        for (int i = 0; i < 256; i++) { 
+            runningstd[i] = sqrt(runningstd[i]); // square root to finally have running std
+            if (runningstd[i] > 0) {
+                // f2.values[i] = (f2.values[i] / runningmean[i]) > thresh ? 
+                // 		                    (f2.values[i] - runningmean[i]) / pow(runningstd[i],m_paling) : 0;
+                f2.values[i] = (f2.values[i] - runningmean[i]) > 0 ?
+                    (f2.values[i] - runningmean[i]) / pow(runningstd[i],m_paling) : 0;
+            }
+            if (f2.values[i] < 0) {
+                cerr << "ERROR: negative value in logfreq spectrum" << endl;
+            }
+        }
+        fsOut[2].push_back(f2);
+        count++;
+    }
+    cerr << "done." << endl;
+	    
+    /** Semitone spectrum and chromagrams
+        Semitone-spaced log-frequency spectrum derived from the tuned log-freq spectrum above. the spectrum
+        is inferred using a non-negative least squares algorithm.
+        Three different kinds of chromagram are calculated, "treble", "bass", and "both" (which means 
+        bass and treble stacked onto each other).
+    **/
+    if (m_dictID == 1) {
+        cerr << "[NNLS Chroma Plugin] Mapping to semitone spectrum and chroma ... ";
+    } else {
+        cerr << "[NNLS Chroma Plugin] Performing NNLS and mapping to chroma ... ";
+    }
+
+	    
+    vector<vector<float> > chordogram;
+    vector<vector<int> > scoreChordogram;
+    vector<float> chordchange = vector<float>(fsOut[2].size(),0);
+    vector<float> oldchroma = vector<float>(12,0);
+    vector<float> oldbasschroma = vector<float>(12,0);
+    count = 0;
+
+    for (FeatureList::iterator it = fsOut[2].begin(); it != fsOut[2].end(); ++it) {
+        Feature f2 = *it; // logfreq spectrum
+        Feature f3; // semitone spectrum
+        Feature f4; // treble chromagram
+        Feature f5; // bass chromagram
+        Feature f6; // treble and bass chromagram
+	
+        f3.hasTimestamp = true;
+        f3.timestamp = f2.timestamp;
+	        
+        f4.hasTimestamp = true;
+        f4.timestamp = f2.timestamp;
+	        
+        f5.hasTimestamp = true;
+        f5.timestamp = f2.timestamp;
+	        
+        f6.hasTimestamp = true;
+        f6.timestamp = f2.timestamp;
+	        
+			float b[256];
+	
+        bool some_b_greater_zero = false;
+        float sumb = 0;
+        for (int i = 0; i < 256; i++) {
+            // b[i] = m_dict[(256 * count + i) % (256 * 84)];
+            b[i] = f2.values[i];
+            sumb += b[i];
+            if (b[i] > 0) {
+                some_b_greater_zero = true;
+            }            
+        }
+	    
+        // here's where the non-negative least squares algorithm calculates the note activation x
+	
+        vector<float> chroma = vector<float>(12, 0);
+        vector<float> basschroma = vector<float>(12, 0);
+        float currval;
+        unsigned iSemitone = 0;
+			
+        if (some_b_greater_zero) {
+            if (m_dictID == 1) {
+                for (unsigned iNote = 2; iNote < nNote - 2; iNote += 3) {
+                    currval = 0;
+                    currval += b[iNote + 1 + -1] * 0.5;						
+                    currval += b[iNote + 1 +  0] * 1.0;						
+                    currval += b[iNote + 1 +  1] * 0.5;						
+                    f3.values.push_back(currval);
+                    chroma[iSemitone % 12] += currval * treblewindow[iSemitone];
+                    basschroma[iSemitone % 12] += currval * basswindow[iSemitone];
+                    iSemitone++;
+                }
+		        
+            } else {
+					float x[84+1000];
+                for (int i = 1; i < 1084; ++i) x[i] = 1.0;
+                vector<int> signifIndex;
+                int index=0;
+                sumb /= 84.0;
+                for (unsigned iNote = 2; iNote < nNote - 2; iNote += 3) {
+                    float currval = 0;
+                    currval += b[iNote + 1 + -1];						
+                    currval += b[iNote + 1 +  0];						
+                    currval += b[iNote + 1 +  1];
+                    if (currval > 0) signifIndex.push_back(index);
+                    f3.values.push_back(0); // fill the values, change later
+                    index++;
+                }
+				    float rnorm;
+				    float w[84+1000];
+				    float zz[84+1000];
+                int indx[84+1000];
+                int mode;
+                int dictsize = 256*signifIndex.size();
+                // cerr << "dictsize is " << dictsize << "and values size" << f3.values.size()<< endl;
+					float *curr_dict = new float[dictsize];
+                for (unsigned iNote = 0; iNote < signifIndex.size(); ++iNote) {
+                    for (unsigned iBin = 0; iBin < 256; iBin++) {
+                        curr_dict[iNote * 256 + iBin] = 1.0 * m_dict[signifIndex[iNote] * 256 + iBin];
+                    }
+                }
+					nnls(curr_dict, nNote, nNote, signifIndex.size(), b, x, &rnorm, w, zz, indx, &mode);
+                delete [] curr_dict;
+                for (unsigned iNote = 0; iNote < signifIndex.size(); ++iNote) {
+                    f3.values[signifIndex[iNote]] = x[iNote];
+                    // cerr << mode << endl;
+                    chroma[signifIndex[iNote] % 12] += x[iNote] * treblewindow[signifIndex[iNote]];
+                    basschroma[signifIndex[iNote] % 12] += x[iNote] * basswindow[signifIndex[iNote]];
+                }
+            }	
+        }
+			
+            
+	        
+			
+        f4.values = chroma; 
+        f5.values = basschroma;
+        chroma.insert(chroma.begin(), basschroma.begin(), basschroma.end()); // just stack the both chromas 
+        f6.values = chroma; 
+	        
+        if (m_doNormalizeChroma > 0) {
+            vector<float> chromanorm = vector<float>(3,0);			
+            switch (int(m_doNormalizeChroma)) {
+            case 0: // should never end up here
+                break;
+            case 1:
+                chromanorm[0] = *max_element(f4.values.begin(), f4.values.end());
+                chromanorm[1] = *max_element(f5.values.begin(), f5.values.end());
+                chromanorm[2] = max(chromanorm[0], chromanorm[1]);
+                break;
+            case 2:
+                for (vector<float>::iterator it = f4.values.begin(); it != f4.values.end(); ++it) {
+                    chromanorm[0] += *it; 						
+                }
+                for (vector<float>::iterator it = f5.values.begin(); it != f5.values.end(); ++it) {
+                    chromanorm[1] += *it; 						
+                }
+                for (vector<float>::iterator it = f6.values.begin(); it != f6.values.end(); ++it) {
+                    chromanorm[2] += *it; 						
+                }
+                break;
+            case 3:
+                for (vector<float>::iterator it = f4.values.begin(); it != f4.values.end(); ++it) {
+                    chromanorm[0] += pow(*it,2); 						
+                }
+                chromanorm[0] = sqrt(chromanorm[0]);
+                for (vector<float>::iterator it = f5.values.begin(); it != f5.values.end(); ++it) {
+                    chromanorm[1] += pow(*it,2); 						
+                }
+                chromanorm[1] = sqrt(chromanorm[1]);
+                for (vector<float>::iterator it = f6.values.begin(); it != f6.values.end(); ++it) {
+                    chromanorm[2] += pow(*it,2); 						
+                }
+                chromanorm[2] = sqrt(chromanorm[2]);
+                break;
+            }
+            if (chromanorm[0] > 0) {
+                for (int i = 0; i < f4.values.size(); i++) {
+                    f4.values[i] /= chromanorm[0];
+                }
+            }
+            if (chromanorm[1] > 0) {
+                for (int i = 0; i < f5.values.size(); i++) {
+                    f5.values[i] /= chromanorm[1];
+                }
+            }
+            if (chromanorm[2] > 0) {
+                for (int i = 0; i < f6.values.size(); i++) {
+                    f6.values[i] /= chromanorm[2];
+                }
+            }
+				
+        }
+	
+        // local chord estimation
+        vector<float> currentChordSalience;
+        float tempchordvalue = 0;
+        float sumchordvalue = 0;
+	        
+        for (int iChord = 0; iChord < nChord; iChord++) {
+            tempchordvalue = 0;
+            for (int iBin = 0; iBin < 12; iBin++) {
+                tempchordvalue += m_chorddict[24 * iChord + iBin] * chroma[iBin];
+            }
+            for (int iBin = 12; iBin < 24; iBin++) {
+                tempchordvalue += m_chorddict[24 * iChord + iBin] * chroma[iBin];
+            }
+            sumchordvalue+=tempchordvalue;
+            currentChordSalience.push_back(tempchordvalue);
+        }
+        if (sumchordvalue > 0) {
+            for (int iChord = 0; iChord < nChord; iChord++) {
+                currentChordSalience[iChord] /= sumchordvalue;
+            }
+        } else {
+            currentChordSalience[nChord-1] = 1.0;
+        }
+        chordogram.push_back(currentChordSalience);
+	        
+        fsOut[3].push_back(f3);
+        fsOut[4].push_back(f4);
+        fsOut[5].push_back(f5);
+        fsOut[6].push_back(f6);
+        count++;
+    }
+    cerr << "done." << endl;
+		
+
+    /* Simple chord estimation
+       I just take the local chord estimates ("currentChordSalience") and average them over time, then
+       take the maximum. Very simple, don't do this at home...
+    */
+    cerr << "[NNLS Chroma Plugin] Chord Estimation ... ";
+    count = 0; 
+    int halfwindowlength = m_inputSampleRate / m_stepSize;
+    vector<int> chordSequence;
+    for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) { // initialise the score chordogram
+        vector<int> temp = vector<int>(nChord,0);
+        scoreChordogram.push_back(temp);
+    }
+    for (FeatureList::iterator it = fsOut[6].begin(); it < fsOut[6].end()-2*halfwindowlength-1; ++it) {		
+        int startIndex = count + 1;
+        int endIndex = count + 2 * halfwindowlength;
+			
+        float chordThreshold = 2.5/nChord;//*(2*halfwindowlength+1);
+            
+        vector<int> chordCandidates;
+        for (unsigned iChord = 0; iChord < nChord-1; iChord++) {
+            // float currsum = 0;
+            // for (unsigned iFrame = startIndex; iFrame < endIndex; ++iFrame) {
+            //  currsum += chordogram[iFrame][iChord];
+            // }
+            //                 if (currsum > chordThreshold) chordCandidates.push_back(iChord);
+            for (unsigned iFrame = startIndex; iFrame < endIndex; ++iFrame) {
+                if (chordogram[iFrame][iChord] > chordThreshold) {
+                    chordCandidates.push_back(iChord);
+                    break;
+                }                    
+            }
+        }
+        chordCandidates.push_back(nChord-1);
+        // cerr << chordCandidates.size() << endl;          
+	        
+        float maxval = 0; // will be the value of the most salient *chord change* in this frame
+        float maxindex = 0; //... and the index thereof
+        unsigned bestchordL = nChord-1; // index of the best "left" chord
+        unsigned bestchordR = nChord-1; // index of the best "right" chord
+ 	 		
+        for (int iWF = 1; iWF < 2*halfwindowlength; ++iWF) {
+            // now find the max values on both sides of iWF
+            // left side:
+            float maxL = 0;
+            unsigned maxindL = nChord-1;
+            for (unsigned kChord = 0; kChord < chordCandidates.size(); kChord++) {
+                unsigned iChord = chordCandidates[kChord];
+                float currsum = 0;
+                for (unsigned iFrame = 0; iFrame < iWF-1; ++iFrame) {
+                    currsum += chordogram[count+iFrame][iChord];
+                }
+                if (iChord == nChord-1) currsum *= 0.8;
+                if (currsum > maxL) {
+                    maxL = currsum;
+                    maxindL = iChord;
+                }
+            }				
+            // right side:
+            float maxR = 0;
+            unsigned maxindR = nChord-1;
+            for (unsigned kChord = 0; kChord < chordCandidates.size(); kChord++) {
+                unsigned iChord = chordCandidates[kChord];
+                float currsum = 0;
+                for (unsigned iFrame = iWF-1; iFrame < 2*halfwindowlength; ++iFrame) {
+                    currsum += chordogram[count+iFrame][iChord];
+                }
+                if (iChord == nChord-1) currsum *= 0.8;
+                if (currsum > maxR) {
+                    maxR = currsum;
+                    maxindR = iChord;
+                }
+            }
+            if (maxL+maxR > maxval) {					
+                maxval = maxL+maxR;
+                maxindex = iWF;
+                bestchordL = maxindL;
+                bestchordR = maxindR;
+            }
+				
+        }
+        // cerr << "maxindex: " << maxindex << ", bestchordR is " << bestchordR << ", of frame " << count << endl;
+        // add a score to every chord-frame-point that was part of a maximum 
+        for (unsigned iFrame = 0; iFrame < maxindex-1; ++iFrame) {
+            scoreChordogram[iFrame+count][bestchordL]++;
+        }
+        for (unsigned iFrame = maxindex-1; iFrame < 2*halfwindowlength; ++iFrame) {
+            scoreChordogram[iFrame+count][bestchordR]++;
+        }
+        if (bestchordL != bestchordR) chordchange[maxindex+count] += (halfwindowlength - abs(maxindex-halfwindowlength)) * 2.0 / halfwindowlength;
+        count++;	
+    }
+    // cerr << "*******  agent finished   *******" << endl;
+    count = 0;
+    for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) { 
+        float maxval = 0; // will be the value of the most salient chord in this frame
+        float maxindex = 0; //... and the index thereof
+        for (unsigned iChord = 0; iChord < nChord; iChord++) {
+            if (scoreChordogram[count][iChord] > maxval) {
+                maxval = scoreChordogram[count][iChord];
+                maxindex = iChord;
+                // cerr << iChord << endl;
+            }
+        }
+        chordSequence.push_back(maxindex);
+        // cerr << "before modefilter, maxindex: " << maxindex << endl;
+        count++;
+    }
+    // cerr << "*******  mode filter done *******" << endl;
+
+	
+    // mode filter on chordSequence
+    count = 0;
+    string oldChord = "";
+    for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) {
+        Feature f6 = *it;
+        Feature f7; // chord estimate
+        f7.hasTimestamp = true;
+        f7.timestamp = f6.timestamp;
+        Feature f8; // chord estimate
+        f8.hasTimestamp = true;
+        f8.timestamp = f6.timestamp;
+			
+        vector<int> chordCount = vector<int>(nChord,0);
+        int maxChordCount = 0;
+        int maxChordIndex = nChord-1;
+        string maxChord;
+        int startIndex = max(count - halfwindowlength/2,0);
+        int endIndex = min(int(chordogram.size()), count + halfwindowlength/2);
+        for (int i = startIndex; i < endIndex; i++) {				
+            chordCount[chordSequence[i]]++;
+            if (chordCount[chordSequence[i]] > maxChordCount) {
+                // cerr << "start index " << startIndex << endl;
+                maxChordCount++;
+                maxChordIndex = chordSequence[i];
+                maxChord = m_chordnames[maxChordIndex];
+            }
+        }
+        // chordSequence[count] = maxChordIndex;
+        // cerr << maxChordIndex << endl;
+        f8.values.push_back(chordchange[count]/(halfwindowlength*2));
+        // cerr << chordchange[count] << endl;
+        fsOut[9].push_back(f8);
+        if (oldChord != maxChord) {
+            oldChord = maxChord;
+	
+            // char buffer1 [50];
+            // if (maxChordIndex < nChord - 1) {
+            //     sprintf(buffer1, "%s%s", notenames[maxChordIndex % 12 + 12], chordtypes[maxChordIndex]);
+            // } else {
+            //     sprintf(buffer1, "N");
+            // }
+            // f7.label = buffer1;
+            f7.label = m_chordnames[maxChordIndex];
+            fsOut[7].push_back(f7);
+        }
+        count++;
+    }
+    Feature f7; // last chord estimate
+    f7.hasTimestamp = true;
+    f7.timestamp = fsOut[6][fsOut[6].size()-1].timestamp;
+    f7.label = "N";
+    fsOut[7].push_back(f7);
+    cerr << "done." << endl;
+    //     // musicity
+    //     count = 0;
+    //     int oldlabeltype = 0; // start value is 0, music is 1, speech is 2
+    //     vector<float> musicityValue; 
+    //     for (FeatureList::iterator it = fsOut[4].begin(); it != fsOut[4].end(); ++it) {
+    //         Feature f4 = *it;
+    //         
+    //         int startIndex = max(count - musicitykernelwidth/2,0);
+    //         int endIndex = min(int(chordogram.size()), startIndex + musicitykernelwidth - 1);
+    //         float chromasum = 0;
+    //         float diffsum = 0;
+    //         for (int k = 0; k < 12; k++) {
+    //             for (int i = startIndex + 1; i < endIndex; i++) {
+    //                 chromasum += pow(fsOut[4][i].values[k],2);
+    //                 diffsum += abs(fsOut[4][i-1].values[k] - fsOut[4][i].values[k]);
+    //             }
+    //         }
+    //         diffsum /= chromasum;
+    //         musicityValue.push_back(diffsum);        
+    //         count++;
+    //     }
+    //     
+    //     float musicityThreshold = 0.44;
+    //     if (m_stepSize == 4096) {
+    //         musicityThreshold = 0.74;
+    //     }
+    //     if (m_stepSize == 4410) {
+    //         musicityThreshold = 0.77;
+    //     }
+    //     
+    //     count = 0;
+    //     for (FeatureList::iterator it = fsOut[4].begin(); it != fsOut[4].end(); ++it) {
+    //         Feature f4 = *it;
+    //         Feature f8; // musicity
+    //         Feature f9; // musicity segmenter
+    //         
+    //         f8.hasTimestamp = true;
+    //         f8.timestamp = f4.timestamp;
+    //         f9.hasTimestamp = true;
+    //         f9.timestamp = f4.timestamp;    
+    //         
+    //         int startIndex = max(count - musicitykernelwidth/2,0);
+    //         int endIndex = min(int(chordogram.size()), startIndex + musicitykernelwidth - 1);
+    //         int musicityCount = 0;
+    //         for (int i = startIndex; i <= endIndex; i++) {
+    //             if (musicityValue[i] > musicityThreshold) musicityCount++;
+    //         }
+    //         bool isSpeech = (2 * musicityCount > endIndex - startIndex + 1); 
+    //         
+    //         if (isSpeech) {
+    //             if (oldlabeltype != 2) {
+    //                 f9.label = "Speech";
+    //                 fsOut[9].push_back(f9);
+    //                 oldlabeltype = 2;
+    //             }
+    //         } else {
+    //             if (oldlabeltype != 1) {
+    //                 f9.label = "Music";
+    //                 fsOut[9].push_back(f9);
+    //                 oldlabeltype = 1;
+    //             }
+    //         }
+    //         f8.values.push_back(musicityValue[count]);
+    //         fsOut[8].push_back(f8);
+    //         count++;
+    //      }
+    return fsOut;     
+
+}
+
+#endif