changeset 308:25af9a1e4ec3

* Remove some unused code; minor tidy

--- a/dsp/chromagram/ChromaProcess.cpp	Tue Jul 13 11:35:13 2010 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,213 +0,0 @@
-/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
-
-/*
-    QM DSP Library
-
-    Centre for Digital Music, Queen Mary, University of London.
-    This file copyright 2005-2006 Christian Landone.
-    All rights reserved.
-*/
-
-
-#include "ChromaProcess.h"
-#include "maths/Histogram.h"
-#include <math.h>
-//////////////////////////////////////////////////////////////////////
-// Construction/Destruction
-//////////////////////////////////////////////////////////////////////
-
-ChromaProcess::ChromaProcess()
-{
-
-}
-
-ChromaProcess::~ChromaProcess()
-{
-
-}
-
-int ChromaProcess::findChromaBias( vector<double> chromaVector, unsigned int BPO, unsigned int frames )
-{
-    vector<double> newChroma;
-    vector<int> peakIndex;
-    vector<int> modPeakIndex;
-
-    unsigned int chromaLength = chromaVector.size(); 
-
-    unsigned int newLength = chromaLength + (2*BPO);
-
-    newChroma.resize( newLength );
-    newChroma.clear();
-
-    modPeakIndex.resize( newLength );
-    modPeakIndex.clear();
-
-    //adds last row at the top and first row at the bottom to create 
-    //circularity - effectively adds 2 to the bpo-length of the vectors:
-
-    for( unsigned int i = 0; i < BPO; i++ )
-    {
-	newChroma.push_back( chromaVector[ chromaLength - BPO + i ] );
-    }
-
-    for( unsigned i = 0; i < chromaLength; i++ )
-    {
-	newChroma.push_back( chromaVector[ i ] );
-    }
-
-    for( unsigned i = 0; i < BPO; i++ )
-    {
-	newChroma.push_back( chromaVector[ i ] );
-    }
-
-    // pick peaks in the chroma
-    peakIndex = getPeaks( newChroma, BPO );
-
-    // modularises to res = bpo/12 bins:
-    // corrects the mod value for bin 3
-    modPeakIndex = mod( peakIndex, 3 );
-
-    // finds the highest concentration of peaks on the bpo/12 bin resolution
-    THistogram<int> m_hist(3);
-
-    double ave, adev, sdev, var, skew, ccurt;
-
-    m_hist.compute(modPeakIndex);
-
-    m_hist.getMoments( modPeakIndex, ave, adev, sdev, var, skew, ccurt );
-
-    vector <double> histogram = m_hist.geTHistogramD();
-    //////////////////////////////////////////////////////////////////////////////
-
-    ///////////////////////////////////////////////////////////////////////////
-	// Find actual bias from histogram
-	int minIdx, maxIdx;
-	double min, max;
-
-	findHistMaxMin( histogram, &max, &maxIdx, &min, &minIdx );
-
-/*
-  FILE* foutchroma = fopen("../testdata/newchroma.bin","wb");
-  FILE* foutpeaks = fopen("../testdata/peaks.bin","wb");
-
-
-  fwrite( &chromaVector[0], sizeof(double), chromaVector.size(), foutchroma );
-  fwrite( &histogram[0], sizeof(double), histogram.size(), foutpeaks );
-
-  fclose( foutchroma );
-  fclose( foutpeaks );
-*/
-	return maxIdx - 1;
-}
-
-
-vector <int> ChromaProcess::getPeaks(vector <double> chroma, unsigned int BPO)
-{
-    vector <int> peaks;
-	
-    double pre = 0;
-    double post = 0;
-    double current = 0;
-
-    unsigned int BPOCounter = 0;
-    unsigned int mult = 0;
-    unsigned int idx = 0;
-
-    for( unsigned int i = 0; i < chroma.size() - 0; i++ )
-    {
-	BPOCounter++;
-
-	pre = chroma[ i ];
-	current = chroma[ i + 1 ];
-	post = chroma[ i + 2 ];
-		
-	if( (current > 0) && (current > pre) && (current > post) )
-	{
-	    peaks.push_back( BPOCounter + 1);
-	}
-
-		
-	if( BPOCounter == (BPO - 2 ) )
-	{
-	    BPOCounter = 0;
-	    i+=2;
-	}
-		
-    }
-
-    /*
-      for( unsigned int i = 1; i < chroma.size() - 1; i++ )
-      {
-      BPOCounter++ ;
-
-      pre = chroma[ i - 1 ];
-      current = chroma[ i ];
-      post = chroma[ i + 1 ];
-		
-      if( (current > 0) && (current > pre) && (current > post) )
-      {
-      peaks.push_back( BPOCounter + 1 );
-      }
-
-      if( BPOCounter == (PO - 1) )
-      {
-      BPOCounter = 1;
-      i+=2;
-      }
-      }
-    */
-    return peaks;
-}
-
-vector <int> ChromaProcess::mod(vector <int> input, int res)
-{
-    vector <int> result;
-
-    for( unsigned int i = 0; i < input.size(); i++ )
-    {
-	int val = input[ i ];
-	int res = val - res * floor( (double)val / (double)res );
-
-	if( val != 0 )
-	{
-	    if( res == 0 )
-		res = 3;
-
-	    result.push_back( res );
-	}
-	else
-	{
-	    result.push_back( val );
-	}
-    }
-    return result;
-}
-
-void ChromaProcess::findHistMaxMin( vector<double> hist, double* max, int* maxIdx, double* min, int* minIdx )
-{
-    double temp = 0.0;
-    unsigned int vecLength = hist.size();
-
-    *minIdx = 0;
-    *maxIdx = 0;
-
-    *min = hist[0];
-    *max = *min;
-
-    for( unsigned int u = 0; u < vecLength; u++ )
-    {
-	temp = hist[ u ];
-
-	if( temp < *min )
-	{
-	    *min =  temp ;
-	    *minIdx = u;
-	}
-	if( temp > *max )
-	{
-	    *max =  temp ;
-	    *maxIdx = u;
-	}
-
-    }
-}

--- a/dsp/chromagram/ChromaProcess.h	Tue Jul 13 11:35:13 2010 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,30 +0,0 @@
-/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
-
-/*
-    QM DSP Library
-
-    Centre for Digital Music, Queen Mary, University of London.
-    This file copyright 2005-2006 Christian Landone.
-    All rights reserved.
-*/
-
-#ifndef CHROMAPROCESS_H
-#define CHROMAPROCESS_H
-
-#include <vector>
-
-using namespace std;
-
-class ChromaProcess  
-{
-public:
-    void findHistMaxMin( vector<double> hist, double* max, int*maxIdx, double* min, int* minIdx );
-    vector <int> mod( vector <int> input, int res );
-    vector <int> getPeaks( vector <double> chroma, unsigned int BPO );
-    int findChromaBias( vector<double> chromaVector, unsigned int BPO, unsigned int frames );
-    ChromaProcess();
-    virtual ~ChromaProcess();
-
-};
-
-#endif // !defined(CHROMAPROCESS_H)

--- a/dsp/segmentation/SavedFeatureSegmenter.cpp	Tue Jul 13 11:35:13 2010 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,97 +0,0 @@
-/*
- *  SavedFeatureSegmenter.cpp
- *  soundbite
- *
- *  Created by Mark Levy on 23/03/2006.
- *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.
- *
- */
-
-#include <cfloat>
-#include <cmath>
-
-#include "SavedFeatureSegmenter.h"
-#include "cluster_segmenter.h"
-#include "segment.h"
-
-SavedFeatureSegmenter::SavedFeatureSegmenter(SavedFeatureSegmenterParams params) : windowSize(params.windowSize),
-hopSize(params.hopSize),
-nHMMStates(params.nHMMStates),
-nclusters(params.nclusters),
-histogramLength(params.histogramLength),
-neighbourhoodLimit(params.neighbourhoodLimit)
-{
-}
-
-void SavedFeatureSegmenter::initialise(int fs)
-{
-	samplerate = fs;
-}
-
-SavedFeatureSegmenter::~SavedFeatureSegmenter() 
-{
-}
-
-void SavedFeatureSegmenter::segment(int m)
-{
-	nclusters = m;
-	segment();
-}
-
-void SavedFeatureSegmenter::setFeatures(const vector<vector<double> >& f)
-{
-	features = f;
-}
-
-void SavedFeatureSegmenter::segment()
-{
-	// for now copy the features to a native array and use the existing C segmenter...
-	double** arrFeatures = new double*[features.size()];	
-	for (int i = 0; i < features.size(); i++)
-	{
-		arrFeatures[i] = new double[features[0].size()];	// allow space for the normalised envelope
-		for (int j = 0; j < features[0].size(); j++)
-			arrFeatures[i][j] = features[i][j];	
-	}
-	
-	q = new int[features.size()];
-	
-	cluster_segment(q, arrFeatures, features.size(), features[0].size(), nHMMStates, histogramLength, 
-						nclusters, neighbourhoodLimit);
-	// convert the cluster assignment sequence to a segmentation
-	makeSegmentation(q, features.size());		
-	
-	// de-allocate arrays
-	delete [] q;
-	for (int i = 0; i < features.size(); i++)
-		delete [] arrFeatures[i];
-	delete [] arrFeatures;
-	
-	// clear the features
-	clear();
-}
-
-void SavedFeatureSegmenter::makeSegmentation(int* q, int len)
-{
-	segmentation.segments.clear();
-	segmentation.nsegtypes = nclusters;
-	segmentation.samplerate = samplerate;
-	
-	Segment segment;
-	segment.start = 0;
-	segment.type = q[0];
-	
-	for (int i = 1; i < len; i++)
-	{
-		if (q[i] != q[i-1])
-		{
-			segment.end = i * getHopsize();
-			segmentation.segments.push_back(segment);
-			segment.type = q[i];
-			segment.start = segment.end;
-		}
-	}
-	segment.end = len * getHopsize();
-	segmentation.segments.push_back(segment);
-}
-

--- a/dsp/segmentation/SavedFeatureSegmenter.h	Tue Jul 13 11:35:13 2010 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,62 +0,0 @@
-/*
- *  SavedFeatureSegmenter.h
- *  soundbite
- *
- *  Created by Mark Levy on 23/03/2006.
- *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.
- *
- */
-
-#include <vector>
-
-#include "segment.h"
-#include "Segmenter.h"
-#include "hmm/hmm.h"
-
-using std::vector;
-
-class SavedFeatureSegmenterParams		
-{
-public:
-	SavedFeatureSegmenterParams() : hopSize(0.2), windowSize(0.6), 
-	nHMMStates(40), nclusters(10), histogramLength(15), neighbourhoodLimit(20) { }
-	double hopSize;		// in secs
-	double windowSize;	// in secs
-	int nHMMStates;
-	int nclusters;
-	int histogramLength;
-	int neighbourhoodLimit;
-};
-
-class SavedFeatureSegmenter : public Segmenter
-{
-public:
-	SavedFeatureSegmenter(SavedFeatureSegmenterParams params);
-	virtual ~SavedFeatureSegmenter();
-	virtual void initialise(int samplerate);
-	virtual int getWindowsize() { return static_cast<int>(windowSize * samplerate); }
-	virtual int getHopsize() { return static_cast<int>(hopSize * samplerate); }
-	virtual void extractFeatures(double* samples, int nsamples) { }
-	void setFeatures(const vector<vector<double> >& f);		// provide the features yourself
-	virtual void segment();		// segment into default number of segment-types
-	void segment(int m);		// segment into m segment-types
-	int getNSegmentTypes() { return nclusters; }
-protected:
-	void makeSegmentation(int* q, int len);
-	
-	model_t* model;				// the HMM
-	int* q;						// the decoded HMM state sequence
-	vector<vector<double> > histograms;	
-	
-	double hopSize;		// in seconds
-	double windowSize;	// in seconds
-	
-	// HMM parameters
-	int nHMMStates;
-	
-	// clustering parameters
-	int nclusters;
-	int histogramLength;
-	int neighbourhoodLimit;
-};
-

--- a/dsp/segmentation/Segmenter.cpp	Tue Jul 13 11:35:13 2010 +0000
+++ b/dsp/segmentation/Segmenter.cpp	Wed Dec 01 14:05:25 2010 +0000
@@ -1,6 +1,5 @@
 /*
  *  Segmenter.cpp
- *  soundbite
  *
  *  Created by Mark Levy on 04/04/2006.
  *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.

--- a/dsp/segmentation/segment.h	Tue Jul 13 11:35:13 2010 +0000
+++ b/dsp/segmentation/segment.h	Wed Dec 01 14:05:25 2010 +0000
@@ -7,7 +7,6 @@
 
 /*
  *  segment.h
- *  soundbite
  *
  *  Created by Mark Levy on 06/04/2006.
  *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.

--- a/hmm/hmm.c	Tue Jul 13 11:35:13 2010 +0000
+++ b/hmm/hmm.c	Wed Dec 01 14:05:25 2010 +0000
@@ -1,6 +1,5 @@
 /*
  *  hmm.c
- *  soundbite
  *
  *  Created by Mark Levy on 12/02/2006.
  *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.

--- a/hmm/hmm.h	Tue Jul 13 11:35:13 2010 +0000
+++ b/hmm/hmm.h	Wed Dec 01 14:05:25 2010 +0000
@@ -7,7 +7,6 @@
 
 /*
  *  hmm.h
- *  soundbite
  *
  *  Created by Mark Levy on 12/02/2006.
  *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.

--- a/maths/Histogram.h	Tue Jul 13 11:35:13 2010 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,393 +0,0 @@
-/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
-
-// Histogram.h: interface for the THistogram class.
-//
-//////////////////////////////////////////////////////////////////////
-
-
-#ifndef HISTOGRAM_H
-#define HISTOGRAM_H
-
-
-#include <valarray>
-
-/*! \brief A histogram class
-
-  This class computes the histogram of a vector.
-
-\par Template parameters
-	
-	- T type of input data (can be any: float, double, int, UINT, etc...)
-	- TOut type of output data: float or double. (default is double)
-
-\par Moments:
-
-	The moments (average, standard deviation, skewness, etc.) are computed using 
-the algorithm of the Numerical recipies (see Numerical recipies in C, Chapter 14.1, pg 613).
-
-\par Example:
-
-	This example shows the typical use of the class:
-\code
-	// a vector containing the data
-	vector<float> data;
-	// Creating histogram using float data and with 101 containers,
-	THistogram<float> histo(101);
-	// computing the histogram
-	histo.compute(data);
-\endcode
-
-Once this is done, you can get a vector with the histogram or the normalized histogram (such that it's area is 1):
-\code
-	// getting normalized histogram
-	vector<float> v=histo.getNormalizedHistogram();
-\endcode
-
-\par Reference
-	
-	Equally spaced acsissa function integration (used in #GetArea): Numerical Recipies in C, Chapter 4.1, pg 130.
-
-\author Jonathan de Halleux, [e-mail], 2002
-*/
-
-template<class T, class TOut = double>
-class THistogram  
-{
-public:
-    //! \name Constructors
-    //@{
-    /*! Default constructor
-      \param counters the number of histogram containers (default value is 10)
-    */
-    THistogram(unsigned int counters = 10);
-    virtual ~THistogram()				{ clear();};
-    //@}
-
-    //! \name Histogram computation, update
-    //@{
-    /*! Computes histogram of vector v
-      \param v vector to compute histogram
-      \param computeMinMax set to true if min/max of v have to be used to get the histogram limits	
-	
-      This function computes the histogram of v and stores it internally.
-      \sa Update, GeTHistogram
-    */
-    void compute( const std::vector<T>& v, bool computeMinMax = true);
-    //! Update histogram with the vector v
-    void update( const std::vector<T>& v);
-    //! Update histogram with t
-    void update( const T& t);
-    //@}
-
-    //! \name Resetting functions
-    //@{
-    //! Resize the histogram. Warning this function clear the histogram.
-    void resize( unsigned int counters );
-    //! Clears the histogram
-    void clear()						{ m_counters.clear();};
-    //@}
-
-    //! \name Setters
-    //@{
-    /*! This function sets the minimum of the histogram spectrum. 
-      The spectrum is not recomputed, use it with care
-    */
-    void setMinSpectrum( const T& min )					{	m_min = min; computeStep();};
-    /*! This function sets the minimum of the histogram spectrum. 
-      The spectrum is not recomputed, use it with care
-    */
-    void setMaxSpectrum( const T& max )					{	m_max = max; computeStep();};
-    //@}
-    //! \name Getters
-    //@{
-    //! return minimum of histogram spectrum
-    const T& getMinSpectrum() const							{	return m_min;};
-    //! return maximum of histogram spectrum
-    const T& getMaxSpectrum() const							{	return m_max;};
-    //! return step size of histogram containers
-    TOut getStep() const									{	return m_step;};
-    //! return number of points in histogram
-    unsigned int getSum() const;
-    /*! \brief returns area under the histogram 
-
-    The Simpson rule is used to integrate the histogram.
-    */
-    TOut getArea() const;
-
-    /*! \brief Computes the moments of the histogram
-
-    \param data dataset
-    \param ave mean
-    \f[ \bar x = \frac{1}{N} \sum_{j=1}^N x_j\f]
-    \param adev mean absolute deviation
-    \f[ adev(X) = \frac{1}{N} \sum_{j=1}^N | x_j - \bar x |\f]
-    \param var average deviation:
-    \f[ \mbox{Var}(X) = \frac{1}{N-1} \sum_{j=1}^N (x_j - \bar x)^2\f]
-    \param sdev standard deviation:
-    \f[ \sigma(X) = \sqrt{var(\bar x) }\f]
-    \param skew skewness
-    \f[ \mbox{Skew}(X) = \frac{1}{N}\sum_{j=1}^N \left[ \frac{x_j - \bar x}{\sigma}\right]^3\f]
-    \param kurt kurtosis
-    \f[ \mbox{Kurt}(X) = \left\{ \frac{1}{N}\sum_{j=1}^N \left[ \frac{x_j - \bar x}{\sigma}\right]^4 \right\} - 3\f]
-
-    */
-    static void getMoments(const std::vector<T>& data, TOut& ave, TOut& adev, TOut& sdev, TOut& var, TOut& skew, TOut& kurt);
-
-    //! return number of containers
-    unsigned int getSize() const							{	return m_counters.size();};
-    //! returns i-th counter
-    unsigned int operator [] (unsigned int i) const {
-//	ASSERT( i < m_counters.size() );
-        return m_counters[i];
-    };
-    //! return the computed histogram
-    const std::vector<unsigned int>& geTHistogram() const	{	return m_counters;};
-    //! return the computed histogram, in TOuts
-    std::vector<TOut> geTHistogramD() const;
-    /*! return the normalized computed histogram 
-
-    \return the histogram such that the area is equal to 1
-    */
-    std::vector<TOut> getNormalizedHistogram() const;
-    //! returns left containers position
-    std::vector<TOut> getLeftContainers() const;
-    //! returns center containers position
-    std::vector<TOut> getCenterContainers() const;
-    //@}
-protected:
-    //! Computes the step
-    void computeStep()								{	m_step = (TOut)(((TOut)(m_max-m_min)) / (m_counters.size()-1));};
-    //! Data accumulators
-    std::vector<unsigned int> m_counters;
-    //! minimum of dataset
-    T m_min;
-    //! maximum of dataset
-    T m_max;
-    //! width of container
-    TOut m_step;
-};
-
-template<class T, class TOut>
-THistogram<T,TOut>::THistogram(unsigned int counters)
-    : m_counters(counters,0), m_min(0), m_max(0), m_step(0)
-{
-
-}
-
-template<class T, class TOut>
-void THistogram<T,TOut>::resize( unsigned int counters )
-{
-    clear();
-
-    m_counters.resize(counters,0);
-
-    computeStep();
-}
-
-template<class T, class TOut>
-void THistogram<T,TOut>::compute( const std::vector<T>& v, bool computeMinMax)
-{
-    using namespace std;
-    unsigned int i;
-    int index;
-
-    if (m_counters.empty())
-	return;
-
-    if (computeMinMax)
-    {
-	m_max = m_min = v[0];
-	for (i=1;i<v.size();i++)
-	{
-	    m_max = std::max( m_max, v[i]);
-	    m_min = std::min( m_min, v[i]);
-	}
-    }
-
-    computeStep();
-
-    for (i = 0;i < v.size() ; i++)
-    {
-	index=(int) floor( ((TOut)(v[i]-m_min))/m_step ) ;
-
-	if (index >= m_counters.size() || index < 0)
-	    return;
-
-	m_counters[index]++;
-    }
-}
-
-template<class T, class TOut>
-void THistogram<T,TOut>::update( const std::vector<T>& v)
-{
-    if (m_counters.empty())
-	return;
-
-    computeStep();
-
-    TOut size = m_counters.size();
-
-    int index;
-    for (unsigned int i = 0;i < size ; i++)
-    {
-	index = (int)floor(((TOut)(v[i]-m_min))/m_step);
-
-	if (index >= m_counters.size() || index < 0)
-	    return;
-
-	m_counters[index]++;
-    }
-}
-
-template<class T, class TOut>
-void THistogram<T,TOut>::update( const T& t)
-{	
-    int index=(int) floor( ((TOut)(t-m_min))/m_step ) ;
-
-    if (index >= m_counters.size() || index < 0)
-	return;
-
-    m_counters[index]++;
-};
-
-template<class T, class TOut>
-std::vector<TOut> THistogram<T,TOut>::geTHistogramD() const
-{
-    std::vector<TOut> v(m_counters.size());
-    for (unsigned int i = 0;i<m_counters.size(); i++)
-	v[i]=(TOut)m_counters[i];
-
-    return v;
-}
-
-template <class T, class TOut>
-std::vector<TOut> THistogram<T,TOut>::getLeftContainers() const
-{
-    std::vector<TOut> x( m_counters.size());
-
-    for (unsigned int i = 0;i<m_counters.size(); i++)
-	x[i]= m_min + i*m_step;
-
-    return x;
-}
-
-template <class T, class TOut>
-std::vector<TOut> THistogram<T,TOut>::getCenterContainers() const
-{
-    std::vector<TOut> x( m_counters.size());
-
-    for (unsigned int i = 0;i<m_counters.size(); i++)
-	x[i]= m_min + (i+0.5)*m_step;
-
-    return x;
-}
-
-template <class T, class TOut>
-unsigned int THistogram<T,TOut>::getSum() const
-{
-    unsigned int sum = 0;
-    for (unsigned int i = 0;i<m_counters.size(); i++)
-	sum+=m_counters[i];
-
-    return sum;
-}
-
-template <class T, class TOut>
-TOut THistogram<T,TOut>::getArea() const
-{
-    const size_t n=m_counters.size();
-    TOut area=0;
-
-    if (n>6)
-    {
-	area=3.0/8.0*(m_counters[0]+m_counters[n-1])
-	    +7.0/6.0*(m_counters[1]+m_counters[n-2])
-	    +23.0/24.0*(m_counters[2]+m_counters[n-3]);
-	for (unsigned int i=3;i<n-3;i++)
-	{
-	    area+=m_counters[i];
-	}
-    }
-    else if (n>4)
-    {
-	area=5.0/12.0*(m_counters[0]+m_counters[n-1])
-	    +13.0/12.0*(m_counters[1]+m_counters[n-2]);
-	for (unsigned int i=2;i<n-2;i++)
-	{
-	    area+=m_counters[i];
-	}
-    }
-    else if (n>1)
-    {
-	area=1/2.0*(m_counters[0]+m_counters[n-1]);
-	for (unsigned int i=1;i<n-1;i++)
-	{
-	    area+=m_counters[i];
-	}
-    }
-    else 
-	area=0;
-
-    return area*m_step;
-}
-
-template <class T, class TOut>
-std::vector<TOut> THistogram<T,TOut>::getNormalizedHistogram() const
-{
-    std::vector<TOut> normCounters( m_counters.size());
-    TOut area = (TOut)getArea();
-
-    for (unsigned int i = 0;i<m_counters.size(); i++)
-    {
-	normCounters[i]= (TOut)m_counters[i]/area;
-    }
-
-    return normCounters;
-};
-
-template <class T, class TOut>
-void THistogram<T,TOut>::getMoments(const std::vector<T>& data, TOut& ave, TOut& adev, TOut& sdev, TOut& var, TOut& skew, TOut& kurt)
-{
-    int j;
-    double ep=0.0,s,p;
-    const size_t n = data.size();
-
-    if (n <= 1)
-	// nrerror("n must be at least 2 in moment");
-	return;
-
-    s=0.0; // First pass to get the mean.
-    for (j=0;j<n;j++)
-	s += data[j];
-	
-    ave=s/(n);
-    adev=var=skew=kurt=0.0; 
-    /* Second pass to get the first (absolute), second,
-       third, and fourth moments of the
-       deviation from the mean. */
-
-    for (j=0;j<n;j++) 
-    {
-	adev += fabs(s=data[j]-(ave));
-	ep += s;
-	var += (p=s*s);
-	skew += (p *= s);
-	kurt += (p *= s);
-    }
-
-
-    adev /= n;
-    var=(var-ep*ep/n)/(n-1); // Corrected two-pass formula.
-    sdev=sqrt(var); // Put the pieces together according to the conventional definitions. 
-    if (var) 
-    {
-	skew /= (n*(var)*(sdev));
-	kurt=(kurt)/(n*(var)*(var))-3.0;
-    } 
-    else
-	//nrerror("No skew/kurtosis when variance = 0 (in moment)");
-	return;
-}
-
-#endif
-

--- a/maths/pca/pca.h	Tue Jul 13 11:35:13 2010 +0000
+++ b/maths/pca/pca.h	Wed Dec 01 14:05:25 2010 +0000
@@ -7,7 +7,6 @@
 
 /*
  *  pca.h
- *  soundbite
  *
  *  Created by Mark Levy on 08/02/2006.
  *  Copyright 2006 Centre for Digital Music, Queen Mary, University of London. All rights reserved.