NOOP, remove trailing tabs/whitespace.

36 files changed, 364 insertions, 364 deletions

diff --git a/libs/qm-dsp/base/Window.h b/libs/qm-dsp/base/Window.h
index 686d023c6b..02ca426d66 100644
--- a/libs/qm-dsp/base/Window.h
+++ b/libs/qm-dsp/base/Window.h
@@ -72,53 +72,53 @@ void Window<T>::encache()
     for (i = 0; i < n; ++i) mult[i] = 1.0;
 
     switch (m_type) {
-		
+
     case RectangularWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * 0.5;
 	}
 	break;
-	
+
     case BartlettWindow:
 	for (i = 0; i < n/2; ++i) {
 	    mult[i] = mult[i] * (i / T(n/2));
 	    mult[i + n/2] = mult[i + n/2] * (1.0 - (i / T(n/2)));
 	}
 	break;
-	
+
     case HammingWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * (0.54 - 0.46 * cos(2 * M_PI * i / n));
 	}
 	break;
-	
+
     case HanningWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * (0.50 - 0.50 * cos(2 * M_PI * i / n));
 	}
 	break;
-	
+
     case BlackmanWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * (0.42 - 0.50 * cos(2 * M_PI * i / n)
 				 + 0.08 * cos(4 * M_PI * i / n));
 	}
 	break;
-	
+
     case GaussianWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * exp((-1.0 / (n*n)) * ((T(2*i) - n) *
 						      (T(2*i) - n)));
 	}
 	break;
-	
+
     case ParzenWindow:
 	for (i = 0; i < n; ++i) {
 	    mult[i] = mult[i] * (1.0 - fabs((T(2*i) - n) / T(n + 1)));
 	}
 	break;
     }
-	
+
     m_cache = mult;
 }
 
diff --git a/libs/qm-dsp/dsp/chromagram/Chromagram.cpp b/libs/qm-dsp/dsp/chromagram/Chromagram.cpp
index 83a6661d17..5901082352 100644
--- a/libs/qm-dsp/dsp/chromagram/Chromagram.cpp
+++ b/libs/qm-dsp/dsp/chromagram/Chromagram.cpp
@@ -27,14 +27,14 @@ Chromagram::Chromagram( ChromaConfig Config ) :
 }
 
 int Chromagram::initialise( ChromaConfig Config )
-{	
+{
     m_FMin = Config.min;		// min freq
     m_FMax = Config.max;		// max freq
     m_BPO  = Config.BPO;		// bins per octave
     m_normalise = Config.normalise;     // if frame normalisation is required
 
     // No. of constant Q bins
-    m_uK = ( unsigned int ) ceil( m_BPO * log(m_FMax/m_FMin)/log(2.0));	
+    m_uK = ( unsigned int ) ceil( m_BPO * log(m_FMax/m_FMin)/log(2.0));
 
     // Create array for chroma result
     m_chromadata = new double[ m_BPO ];
@@ -49,7 +49,7 @@ int Chromagram::initialise( ChromaConfig Config )
     ConstantQConfig.max = m_FMax;
     ConstantQConfig.BPO = m_BPO;
     ConstantQConfig.CQThresh = Config.CQThresh;
-	
+
     // Initialise ConstantQ operator
     m_ConstantQ = new ConstantQ( ConstantQConfig );
 
@@ -57,7 +57,7 @@ int Chromagram::initialise( ChromaConfig Config )
     m_frameSize = m_ConstantQ->getfftlength();
     m_hopSize = m_ConstantQ->gethop();
 
-    // Initialise FFT object	
+    // Initialise FFT object
     m_FFT = new FFTReal(m_frameSize);
 
     m_FFTRe = new double[ m_frameSize ];
@@ -161,7 +161,7 @@ double* Chromagram::process( const double *real, const double *imag )
 
     // Calculate ConstantQ frame
     m_ConstantQ->process( real, imag, m_CQRe, m_CQIm );
-	
+
     // add each octave of cq data into Chromagram
     const unsigned octaves = (int)floor(double( m_uK/m_BPO))-1;
     for (unsigned octave = 0; octave <= octaves; octave++)
diff --git a/libs/qm-dsp/dsp/chromagram/Chromagram.h b/libs/qm-dsp/dsp/chromagram/Chromagram.h
index 37af153be3..f04ffda83a 100644
--- a/libs/qm-dsp/dsp/chromagram/Chromagram.h
+++ b/libs/qm-dsp/dsp/chromagram/Chromagram.h
@@ -32,17 +32,17 @@ struct ChromaConfig{
 class Chromagram
 {
 
-public:	
+public:
     Chromagram( ChromaConfig Config );
     ~Chromagram();
-	
+
     double* process( const double *data ); // time domain
     double* process( const double *real, const double *imag ); // frequency domain
     void unityNormalise( double* src );
 
     // Complex arithmetic
     double kabs( double real, double imag );
-	
+
     // Results
     unsigned int getK() { return m_uK;}
     unsigned int getFrameSize() { return m_frameSize; }
@@ -54,7 +54,7 @@ private:
 
     Window<double> *m_window;
     double *m_windowbuf;
-	
+
     double* m_chromadata;
     double m_FMin;
     double m_FMax;
diff --git a/libs/qm-dsp/dsp/chromagram/ConstantQ.cpp b/libs/qm-dsp/dsp/chromagram/ConstantQ.cpp
index 222fd80a36..fa6c32c26b 100644
--- a/libs/qm-dsp/dsp/chromagram/ConstantQ.cpp
+++ b/libs/qm-dsp/dsp/chromagram/ConstantQ.cpp
@@ -109,14 +109,14 @@ void ConstantQ::sparsekernel()
     sk->js.reserve( m_FFTLength*2 );
     sk->real.reserve( m_FFTLength*2 );
     sk->imag.reserve( m_FFTLength*2 );
-	
+
     // for each bin value K, calculate temporal kernel, take its fft to
     //calculate the spectral kernel then threshold it to make it sparse and
     //add it to the sparse kernels matrix
     double squareThreshold = m_CQThresh * m_CQThresh;
 
     FFT m_FFT(m_FFTLength);
-	
+
     for (unsigned k = m_uK; k--; )
     {
         for (unsigned u=0; u < m_FFTLength; u++)
@@ -152,13 +152,13 @@ void ConstantQ::sparsekernel()
 	//do fft of hammingWindow
 	m_FFT.process( 0, hammingWindowRe, hammingWindowIm, transfHammingWindowRe, transfHammingWindowIm );
 
-		
+
 	for (unsigned j=0; j<( m_FFTLength ); j++)
 	{
 	    // perform thresholding
 	    const double squaredBin = squaredModule( transfHammingWindowRe[ j ], transfHammingWindowIm[ j ]);
 	    if (squaredBin <= squareThreshold) continue;
-		
+
 	    // Insert non-zero position indexes, doubled because they are floats
 	    sk->is.push_back(j);
 	    sk->js.push_back(k);
@@ -266,7 +266,7 @@ double* ConstantQ::process( const double* fftdata )
     const double   *real   = &(sk->real[0]);
     const double   *imag   = &(sk->imag[0]);
     const unsigned int sparseCells = sk->real.size();
-	
+
     for (unsigned i = 0; i<sparseCells; i++)
     {
 	const unsigned row = cqbin[i];
@@ -335,7 +335,7 @@ void ConstantQ::process(const double *FFTRe, const double* FFTIm,
     const double   *real   = &(sk->real[0]);
     const double   *imag   = &(sk->imag[0]);
     const unsigned int sparseCells = sk->real.size();
-	
+
     for (unsigned i = 0; i<sparseCells; i++)
     {
 	const unsigned row = cqbin[i];
diff --git a/libs/qm-dsp/dsp/chromagram/ConstantQ.h b/libs/qm-dsp/dsp/chromagram/ConstantQ.h
index c06f60a9d0..597e3d0087 100644
--- a/libs/qm-dsp/dsp/chromagram/ConstantQ.h
+++ b/libs/qm-dsp/dsp/chromagram/ConstantQ.h
@@ -29,7 +29,7 @@ struct CQConfig{
 };
 
 class ConstantQ {
-	
+
 //public functions incl. sparsekernel so can keep out of loop in main
 public:
     void process( const double* FFTRe, const double* FFTIm,
@@ -46,7 +46,7 @@ public:
 	double out = 0.54 - 0.46*cos(2*PI*n/len);
 	return(out);
     }
-	
+
     int getnumwin() { return m_numWin;}
     double getQ() { return m_dQ;}
     int getK() {return m_uK ;}
@@ -56,7 +56,7 @@ public:
 private:
     void initialise( CQConfig Config );
     void deInitialise();
-	
+
     double* m_CQdata;
     unsigned int m_FS;
     double m_FMin;
diff --git a/libs/qm-dsp/dsp/onsets/DetectionFunction.cpp b/libs/qm-dsp/dsp/onsets/DetectionFunction.cpp
index ae22cfb11d..af65af8cd2 100644
--- a/libs/qm-dsp/dsp/onsets/DetectionFunction.cpp
+++ b/libs/qm-dsp/dsp/onsets/DetectionFunction.cpp
@@ -53,7 +53,7 @@ void DetectionFunction::initialise( DFConfig Config )
 
     m_magHistory = new double[ m_halfLength ];
     memset(m_magHistory,0, m_halfLength*sizeof(double));
-		
+
     m_phaseHistory = new double[ m_halfLength ];
     memset(m_phaseHistory,0, m_halfLength*sizeof(double));
 
@@ -152,15 +152,15 @@ double DetectionFunction::runDF()
     case DF_HFC:
 	retVal = HFC( m_halfLength, m_magnitude);
 	break;
-	
+
     case DF_SPECDIFF:
 	retVal = specDiff( m_halfLength, m_magnitude);
 	break;
-	
+
     case DF_PHASEDEV:
 	retVal = phaseDev( m_halfLength, m_thetaAngle);
 	break;
-	
+
     case DF_COMPLEXSD:
 	retVal = complexSD( m_halfLength, m_magnitude, m_thetaAngle);
 	break;
@@ -169,7 +169,7 @@ double DetectionFunction::runDF()
         retVal = broadband( m_halfLength, m_magnitude);
         break;
     }
-	
+
     return retVal;
 }
 
@@ -195,7 +195,7 @@ double DetectionFunction::specDiff(unsigned int length, double *src)
     for( i = 0; i < length; i++)
     {
 	temp = fabs( (src[ i ] * src[ i ]) - (m_magHistory[ i ] * m_magHistory[ i ]) );
-		
+
 	diff= sqrt(temp);
 
         // (See note in phaseDev below.)
@@ -230,15 +230,15 @@ double DetectionFunction::phaseDev(unsigned int length, double *srcPhase)
         // does significantly damage its ability to work with quieter
         // music, so I'm removing it and counting the result always.
         // Same goes for the spectral difference measure above.
-		
+
         tmpVal  = fabs(dev);
         val += tmpVal ;
 
 	m_phaseHistoryOld[ i ] = m_phaseHistory[ i ] ;
 	m_phaseHistory[ i ] = srcPhase[ i ];
     }
-	
-	
+
+
     return val;
 }
 
@@ -259,14 +259,14 @@ double DetectionFunction::complexSD(unsigned int length, double *srcMagnitude, d
     {
 	tmpPhase = (srcPhase[ i ]- 2*m_phaseHistory[ i ]+m_phaseHistoryOld[ i ]);
 	dev= MathUtilities::princarg( tmpPhase );
-		
+
 	meas = m_magHistory[i] - ( srcMagnitude[ i ] * exp( j * dev) );
 
 	tmpReal = real( meas );
 	tmpImag = imag( meas );
 
 	val += sqrt( (tmpReal * tmpReal) + (tmpImag * tmpImag) );
-		
+
 	m_phaseHistoryOld[ i ] = m_phaseHistory[ i ] ;
 	m_phaseHistory[ i ] = srcPhase[ i ];
 	m_magHistory[ i ] = srcMagnitude[ i ];
diff --git a/libs/qm-dsp/dsp/onsets/DetectionFunction.h b/libs/qm-dsp/dsp/onsets/DetectionFunction.h
index 083d0a2a06..1102ec416d 100644
--- a/libs/qm-dsp/dsp/onsets/DetectionFunction.h
+++ b/libs/qm-dsp/dsp/onsets/DetectionFunction.h
@@ -55,7 +55,7 @@ private:
     double phaseDev(unsigned int length, double *srcPhase);
     double complexSD(unsigned int length, double *srcMagnitude, double *srcPhase);
     double broadband(unsigned int length, double *srcMagnitude);
-	
+
 private:
     void initialise( DFConfig Config );
     void deInitialise();
diff --git a/libs/qm-dsp/dsp/onsets/PeakPicking.cpp b/libs/qm-dsp/dsp/onsets/PeakPicking.cpp
index 472897b241..ea50223e15 100644
--- a/libs/qm-dsp/dsp/onsets/PeakPicking.cpp
+++ b/libs/qm-dsp/dsp/onsets/PeakPicking.cpp
@@ -41,7 +41,7 @@ void PeakPicking::initialise( PPickParams Config )
     Qfilta = Config.QuadThresh.a ;
     Qfiltb = Config.QuadThresh.b ;
     Qfiltc = Config.QuadThresh.c ;
-	
+
     m_DFProcessingParams.length = m_DFLength;
     m_DFProcessingParams.LPOrd = Config.LPOrd;
     m_DFProcessingParams.LPACoeffs = Config.LPACoeffs;
@@ -50,7 +50,7 @@ void PeakPicking::initialise( PPickParams Config )
     m_DFProcessingParams.winPost = Config.WinT.post;
     m_DFProcessingParams.AlphaNormParam = Config.alpha;
     m_DFProcessingParams.isMedianPositive = false;
-	
+
     m_DFSmoothing = new DFProcess( m_DFProcessingParams );
 
     m_workBuffer = new double[ m_DFLength ];
@@ -68,16 +68,16 @@ void PeakPicking::process( double* src, unsigned int len, vector<int> &onsets )
 {
     if (len < 4) return;
 
-    vector <double> m_maxima;	
+    vector <double> m_maxima;
 
     // Signal conditioning
     m_DFSmoothing->process( src, m_workBuffer );
-	
+
     for( unsigned int u = 0; u < len; u++)
     {
-	m_maxima.push_back( m_workBuffer[ u ] );		
+	m_maxima.push_back( m_workBuffer[ u ] );
     }
-	
+
     quadEval( m_maxima, onsets );
 
     for(unsigned int b = 0; b <  m_maxima.size(); b++)
@@ -92,7 +92,7 @@ int PeakPicking::quadEval( vector<double> &src, vector<int> &idx )
 
     vector <int> m_maxIndex;
     vector <int> m_onsetPosition;
-	
+
     vector <double> m_maxFit;
     vector <double> m_poly;
     vector <double> m_err;
@@ -123,7 +123,7 @@ int PeakPicking::quadEval( vector<double> &src, vector<int> &idx )
         for (int k = -2; k <= 2; ++k)
 	{
 	    selMax = src[ m_maxIndex[j] + k ] ;
-	    m_maxFit.push_back(selMax);			
+	    m_maxFit.push_back(selMax);
 	}
 
 	double f = m_poly[0];
@@ -133,7 +133,7 @@ int PeakPicking::quadEval( vector<double> &src, vector<int> &idx )
 	{
 	    idx.push_back(m_maxIndex[j]);
 	}
-		
+
 	m_maxFit.clear();
     }
 
diff --git a/libs/qm-dsp/dsp/onsets/PeakPicking.h b/libs/qm-dsp/dsp/onsets/PeakPicking.h
index be6853ca8f..931c1c16e2 100644
--- a/libs/qm-dsp/dsp/onsets/PeakPicking.h
+++ b/libs/qm-dsp/dsp/onsets/PeakPicking.h
@@ -56,7 +56,7 @@ class PeakPicking
 public:
     PeakPicking( PPickParams Config );
     virtual ~PeakPicking();
-	
+
     void process( double* src, unsigned int len, vector<int> &onsets  );
 
 
@@ -64,7 +64,7 @@ private:
     void initialise( PPickParams Config  );
     void deInitialise();
     int  quadEval( vector<double> &src, vector<int> &idx );
-	
+
     DFProcConfig m_DFProcessingParams;
 
     unsigned int m_DFLength ;
@@ -74,7 +74,7 @@ private:
 
 
     double* m_workBuffer;
-	
+
     DFProcess*	m_DFSmoothing;
 };
 
diff --git a/libs/qm-dsp/dsp/phasevocoder/PhaseVocoder.cpp b/libs/qm-dsp/dsp/phasevocoder/PhaseVocoder.cpp
index 26cfcfbabe..cd52f5240a 100644
--- a/libs/qm-dsp/dsp/phasevocoder/PhaseVocoder.cpp
+++ b/libs/qm-dsp/dsp/phasevocoder/PhaseVocoder.cpp
@@ -49,7 +49,7 @@ void PhaseVocoder::FFTShift(unsigned int size, double *src)
 void PhaseVocoder::process(double *src, double *mag, double *theta)
 {
     FFTShift( m_n, src);
-	
+
     m_fft->process(0, src, m_realOut, m_imagOut);
 
     getMagnitude( m_n/2, mag, m_realOut, m_imagOut);
@@ -57,7 +57,7 @@ void PhaseVocoder::process(double *src, double *mag, double *theta)
 }
 
 void PhaseVocoder::getMagnitude(unsigned int size, double *mag, double *real, double *imag)
-{	
+{
     unsigned int j;
 
     for( j = 0; j < size; j++)
@@ -75,5 +75,5 @@ void PhaseVocoder::getPhase(unsigned int size, double *theta, double *real, doub
     for( k = 0; k < size; k++)
     {
 	theta[ k ] = atan2( -imag[ k ], real[ k ]);
-    }	
+    }
 }
diff --git a/libs/qm-dsp/dsp/rateconversion/Decimator.h b/libs/qm-dsp/dsp/rateconversion/Decimator.h
index 1ed49fd397..f8a113a0db 100644
--- a/libs/qm-dsp/dsp/rateconversion/Decimator.h
+++ b/libs/qm-dsp/dsp/rateconversion/Decimator.h
@@ -55,7 +55,7 @@ private:
 
     double a[ 9 ];
     double b[ 9 ];
-	
+
     double* decBuffer;
 };
 
diff --git a/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.cpp b/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.cpp
index 7643691cd3..ce5f370436 100644
--- a/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.cpp
+++ b/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.cpp
@@ -212,7 +212,7 @@ void ClusterMeltSegmenter::extractFeaturesConstQ(const double* samples, int nsam
         fft->process(false, frame, real, imag);
 
         constq->process(real, imag, cqre, cqim);
-	
+
         for (int i = 0; i < ncoeff; ++i) {
             cq[i] += sqrt(cqre[i] * cqre[i] + cqim[i] * cqim[i]);
         }
@@ -287,7 +287,7 @@ void ClusterMeltSegmenter::extractFeaturesMFCC(const double* samples, int nsampl
         }
 
         mfcc->process(frame, ccout);
-	
+
         for (int i = 0; i < ncoeff; ++i) {
             cc[i] += ccout[i];
         }
@@ -335,22 +335,22 @@ void ClusterMeltSegmenter::segment()
               << " features with " << features[0].size() << " coefficients (ncoeff = " << ncoeff << ", ncomponents = " << ncomponents << ")" << std::endl;
 */
     // copy the features to a native array and use the existing C segmenter...
-    double** arrFeatures = new double*[features.size()];	
+    double** arrFeatures = new double*[features.size()];
     for (int i = 0; i < features.size(); i++)
     {
         if (featureType == FEATURE_TYPE_UNKNOWN) {
             arrFeatures[i] = new double[features[0].size()];
             for (int j = 0; j < features[0].size(); j++)
-                arrFeatures[i][j] = features[i][j];	
+                arrFeatures[i][j] = features[i][j];
         } else {
             arrFeatures[i] = new double[ncoeff+1];	// allow space for the normalised envelope
             for (int j = 0; j < ncoeff; j++)
-                arrFeatures[i][j] = features[i][j];	
+                arrFeatures[i][j] = features[i][j];
         }
     }
-	
+
     q = new int[features.size()];
-	
+
     if (featureType == FEATURE_TYPE_UNKNOWN ||
         featureType == FEATURE_TYPE_MFCC)
         cluster_segment(q, arrFeatures, features.size(), features[0].size(), nHMMStates, histogramLength,
@@ -358,16 +358,16 @@ void ClusterMeltSegmenter::segment()
     else
         constq_segment(q, arrFeatures, features.size(), nbins, ncoeff, featureType,
                        nHMMStates, histogramLength, nclusters, neighbourhoodLimit);
-	
+
     // convert the cluster assignment sequence to a segmentation
-    makeSegmentation(q, features.size());		
-	
+    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();
 }
@@ -377,11 +377,11 @@ void ClusterMeltSegmenter::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])
diff --git a/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.h b/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.h
index 528c09cb55..8f3130871e 100644
--- a/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.h
+++ b/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.h
@@ -72,7 +72,7 @@ public:
 
 protected:
     void makeSegmentation(int* q, int len);
-	
+
     void extractFeaturesConstQ(const double *, int);
     void extractFeaturesMFCC(const double *, int);
 
@@ -82,9 +82,9 @@ protected:
     MFCC* mfcc;
     model_t* model;				// the HMM
     int* q;					// the decoded HMM state sequence
-    vector<vector<double> > histograms;	
+    vector<vector<double> > histograms;
 
-    feature_types featureType;	
+    feature_types featureType;
     double hopSize;		// in seconds
     double windowSize;	// in seconds
 
diff --git a/libs/qm-dsp/dsp/segmentation/Segmenter.cpp b/libs/qm-dsp/dsp/segmentation/Segmenter.cpp
index 120a6617f5..b60fb58162 100644
--- a/libs/qm-dsp/dsp/segmentation/Segmenter.cpp
+++ b/libs/qm-dsp/dsp/segmentation/Segmenter.cpp
@@ -19,13 +19,13 @@
 ostream& operator<<(ostream& os, const Segmentation& s)
 {
 	os << "structure_name : begin_time end_time\n";
-	
+
 	for (int i = 0; i < s.segments.size(); i++)
 	{
 		Segment seg = s.segments[i];
 		os << std::fixed << seg.type << ':' << '\t' << std::setprecision(6) << seg.start / static_cast<double>(s.samplerate)
 			<< '\t' << std::setprecision(6) << seg.end / static_cast<double>(s.samplerate) << "\n";
 	}
-	
+
 	return os;
 }
diff --git a/libs/qm-dsp/dsp/segmentation/Segmenter.h b/libs/qm-dsp/dsp/segmentation/Segmenter.h
index 9a77d70372..fd2f39b850 100644
--- a/libs/qm-dsp/dsp/segmentation/Segmenter.h
+++ b/libs/qm-dsp/dsp/segmentation/Segmenter.h
@@ -35,7 +35,7 @@ class Segmentation
 public:
 	int nsegtypes;		// number of segment types, so possible types are {0,1,...,nsegtypes-1}
 	int samplerate;
-	vector<Segment> segments;	
+	vector<Segment> segments;
 };
 
 ostream& operator<<(ostream& os, const Segmentation& s);
diff --git a/libs/qm-dsp/dsp/segmentation/cluster_melt.c b/libs/qm-dsp/dsp/segmentation/cluster_melt.c
index 0509480807..092bc7f078 100644
--- a/libs/qm-dsp/dsp/segmentation/cluster_melt.c
+++ b/libs/qm-dsp/dsp/segmentation/cluster_melt.c
@@ -25,7 +25,7 @@ double kldist(double* a, double* b, int n) {
 	because a, b represent probability distributions */
 	double q, d;
 	int i;
-	
+
 	d = 0;
 	for (i = 0; i < n; i++)
 	{
@@ -38,8 +38,8 @@ double kldist(double* a, double* b, int n) {
 				d += b[i] * log(b[i] / q);
 		}
 	}
-	return d;		
-}	
+	return d;
+}
 
 void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l, int *c) {
 	double lambda, sum, beta, logsumexp, maxlp;
@@ -48,9 +48,9 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 	int** nc;	/* neighbour counts for each histogram */
 	double** lp;	/* soft assignment probs for each histogram */
 	int* oldc;	/* previous hard assignments (to check convergence) */
-	
+
 	/* NB h is passed as a 1d row major array */
-	
+
 	/* parameter values */
 	lambda = DEFAULT_LAMBDA;
 	if (l > 0)
@@ -60,22 +60,22 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 	B = 2 * limit + 1;
 	maxiter0 = 20;	/* number of iterations at initial temperature */
 	maxiter1 = 5;	/* number of iterations at subsequent temperatures */
-	
-	/* allocate memory */	
+
+	/* allocate memory */
 	cl = (double**) malloc(k*sizeof(double*));
 	for (i= 0; i < k; i++)
 		cl[i] = (double*) malloc(m*sizeof(double));
-	
+
 	nc = (int**) malloc(n*sizeof(int*));
 	for (i= 0; i < n; i++)
 		nc[i] = (int*) malloc(k*sizeof(int));
-	
+
 	lp = (double**) malloc(n*sizeof(double*));
 	for (i= 0; i < n; i++)
 		lp[i] = (double*) malloc(k*sizeof(double));
-	
+
 	oldc = (int*) malloc(n * sizeof(int));
-	
+
 	/* initialise */
 	for (i = 0; i < k; i++)
 	{
@@ -90,40 +90,40 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 		{
 			cl[i][j] /= sum;	/* normalise */
 		}
-	}	
+	}
 	//print_array(cl, k, m);
-	
+
 	for (i = 0; i < n; i++)
 		c[i] = 1;	/* initially assign all histograms to cluster 1 */
-	
+
 	for (a = 0; a < t; a++)
 	{
 		beta = Bsched[a];
-		
+
 		if (a == 0)
 			maxiter = maxiter0;
 		else
 			maxiter = maxiter1;
-		
+
 		for (it = 0; it < maxiter; it++)
 		{
 			//if (it == maxiter - 1)
 			//	mexPrintf("hasn't converged after %d iterations\n", maxiter);
-			
+
 			for (i = 0; i < n; i++)
 			{
 				/* save current hard assignments */
 				oldc[i] = c[i];
-				
+
 				/* calculate soft assignment logprobs for each cluster */
 				sum = 0;
 				for (j = 0; j < k; j++)
 				{
 					lp[i][ j] = -beta * kldist(cl[j], &h[i*m], m);
-					
+
 					/* update matching neighbour counts for this histogram, based on current hard assignments */
 					/* old version:
-					nc[i][j] = 0;	
+					nc[i][j] = 0;
 					if (i >= limit && i <= n - 1 - limit)
 					{
 							for (b = i - limit; b <= i + limit; b++)
@@ -144,14 +144,14 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 					for (b = b0; b <= b1; b++)
 						if (c[b] == j+1)
 							nc[i][j]--;
-					
+
 					sum += exp(lp[i][j]);
 				}
-				
+
 				/* normalise responsibilities and add duration logprior */
 				logsumexp = log(sum);
 				for (j = 0; j < k; j++)
-					lp[i][j] -= logsumexp + lambda * nc[i][j];				
+					lp[i][j] -= logsumexp + lambda * nc[i][j];
 			}
 			//print_array(lp, n, k);
 			/*
@@ -162,8 +162,8 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 				 mexPrintf("\n");
 			}
 			*/
-			
-			
+
+
 			/* update the assignments now that we know the duration priors
 			based on the current assignments */
 			for (i = 0; i < n; i++)
@@ -177,14 +177,14 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 						c[i] = j+1;
 					}
 			}
-				
+
 			/* break if assignments haven't changed */
 			i = 0;
 			while (i < n && oldc[i] == c[i])
 				i++;
 			if (i == n)
 				break;
-			
+
 			/* update reference histograms now we know new responsibilities */
 			for (j = 0; j < k; j++)
 			{
@@ -194,21 +194,21 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 					for (i = 0; i < n; i++)
 					{
 						cl[j][b] += exp(lp[i][j]) * h[i*m+b];
-					}	
+					}
 				}
-				
-				sum = 0;				
+
+				sum = 0;
 				for (i = 0; i < n; i++)
 					sum += exp(lp[i][j]);
 				for (b = 0; b < m; b++)
 					cl[j][b] /= sum;	/* normalise */
-			}	
-			
+			}
+
 			//print_array(cl, k, m);
 			//mexPrintf("\n\n");
 		}
 	}
-		
+
 	/* free memory */
 	for (i = 0; i < k; i++)
 		free(cl[i]);
@@ -219,7 +219,7 @@ void cluster_melt(double *h, int m, int n, double *Bsched, int t, int k, int l,
 	for (i = 0; i < n; i++)
 		free(lp[i]);
 	free(lp);
-	free(oldc);	
+	free(oldc);
 }
 
 
diff --git a/libs/qm-dsp/dsp/segmentation/cluster_segmenter.c b/libs/qm-dsp/dsp/segmentation/cluster_segmenter.c
index 0d2762ee7f..c9f115c205 100644
--- a/libs/qm-dsp/dsp/segmentation/cluster_segmenter.c
+++ b/libs/qm-dsp/dsp/segmentation/cluster_segmenter.c
@@ -25,7 +25,7 @@ void cq2chroma(double** cq, int nframes, int ncoeff, int bins, double** chroma)
 	int t, b, oct, ix;
 	//double maxchroma;	/* max chroma value at each time, for normalisation */
 	//double sum;		/* for normalisation */
-	
+
 	for (t = 0; t < nframes; t++)
 	{
 		for (b = 0; b < bins; b++)
@@ -50,7 +50,7 @@ void cq2chroma(double** cq, int nframes, int ncoeff, int bins, double** chroma)
 				maxchroma = chroma[t][b];
 		if (maxchroma > 0)
 			for (b = 0; b < bins; b++)
-				chroma[t][b] /= maxchroma;	
+				chroma[t][b] /= maxchroma;
 		*/
 	}
 }
@@ -62,13 +62,13 @@ void mpeg7_constq(double** features, int nframes, int ncoeff)
 	double ss;
 	double env;
 	double maxenv = 0;
-	
+
 	/* convert const-Q features to dB scale */
 	for (i = 0; i < nframes; i++)
 		for (j = 0; j < ncoeff; j++)
 			features[i][j] = 10.0 * log10(features[i][j]+DBL_EPSILON);
-	
-	/* normalise each feature vector and add the norm as an extra feature dimension */	
+
+	/* normalise each feature vector and add the norm as an extra feature dimension */
 	for (i = 0; i < nframes; i++)
 	{
 		ss = 0;
@@ -83,7 +83,7 @@ void mpeg7_constq(double** features, int nframes, int ncoeff)
 	}
 	/* normalise the envelopes */
 	for (i = 0; i < nframes; i++)
-		features[i][ncoeff] /= maxenv;	
+		features[i][ncoeff] /= maxenv;
 }
 
 /* return histograms h[nx*m] of data x[nx] into m bins using a sliding window of length h_len (MUST BE ODD) */
@@ -109,7 +109,7 @@ void create_histograms(int* x, int nx, int m, int hlen, double* h)
 		for (j = 0; j < m; j++)
 			h[i*m+j] /= norm;
 	}
-	
+
 	/* duplicate histograms at beginning and end to create one histogram for each data value supplied */
 	for (i = 0; i < hlen/2; i++)
 		for (j = 0; j < m; j++)
@@ -124,7 +124,7 @@ void cluster_segment(int* q, double** features, int frames_read, int feature_len
 					 int histogram_length, int nclusters, int neighbour_limit)
 {
 	int i, j;
-	
+
 	/*****************************/
 	if (0) {
 	/* try just using the predominant bin number as a 'decoded state' */
@@ -141,44 +141,44 @@ void cluster_segment(int* q, double** features, int frames_read, int feature_len
 			{
 				maxval = features[i][j];
 				maxbin = j;
-			}				
+			}
 		}
 		if (maxval > chroma_thresh)
 			q[i] = maxbin;
 		else
 			q[i] = feature_length;
 	}
-	
+
 	}
 	if (1) {
 	/*****************************/
-		
-	
+
+
 	/* scale all the features to 'balance covariances' during HMM training */
 	double scale = 10;
 	for (i = 0; i < frames_read; i++)
 		for (j = 0; j < feature_length; j++)
 			features[i][j] *= scale;
-	
+
 	/* train an HMM on the features */
-	
+
 	/* create a model */
 	model_t* model = hmm_init(features, frames_read, feature_length, nHMM_states);
-	
+
 	/* train the model */
 	hmm_train(features, frames_read, model);
-/*	
+/*
 	printf("\n\nafter training:\n");
 	hmm_print(model);
-*/	
+*/
 	/* decode the hidden state sequence */
 	viterbi_decode(features, frames_read, model, q);
 	hmm_close(model);
-	
+
 	/*****************************/
 	}
 	/*****************************/
-	
+
 
 /*
 	fprintf(stderr, "HMM state sequence:\n");
@@ -186,11 +186,11 @@ void cluster_segment(int* q, double** features, int frames_read, int feature_len
 		fprintf(stderr, "%d ", q[i]);
 	fprintf(stderr, "\n\n");
 */
-	
+
 	/* create histograms of states */
 	double* h = (double*) malloc(frames_read*nHMM_states*sizeof(double));	/* vector in row major order */
 	create_histograms(q, frames_read, nHMM_states, histogram_length, h);
-	
+
 	/* cluster the histograms */
 	int nbsched = 20;	/* length of inverse temperature schedule */
 	double* bsched = (double*) malloc(nbsched*sizeof(double));	/* inverse temperature schedule */
@@ -200,9 +200,9 @@ void cluster_segment(int* q, double** features, int frames_read, int feature_len
 	for (i = 1; i < nbsched; i++)
 		bsched[i] = alpha * bsched[i-1];
 	cluster_melt(h, nHMM_states, frames_read, bsched, nbsched, nclusters, neighbour_limit, q);
-	
+
 	/* now q holds a sequence of cluster assignments */
-	
+
 	free(h);
 	free(bsched);
 }
@@ -214,25 +214,25 @@ void constq_segment(int* q, double** features, int frames_read, int bins, int nc
 	int feature_length;
 	double** chroma;
 	int i;
-	
+
 	if (feature_type == FEATURE_TYPE_CONSTQ)
 	{
 /*		fprintf(stderr, "Converting to dB and normalising...\n");
- */		
+ */
 		mpeg7_constq(features, frames_read, ncoeff);
-/*		
+/*
 		fprintf(stderr, "Running PCA...\n");
-*/		
+*/
 		/* do PCA on the features (but not the envelope) */
 		int ncomponents = 20;
 		pca_project(features, frames_read, ncoeff, ncomponents);
-		
+
 		/* copy the envelope so that it immediatly follows the chosen components */
 		for (i = 0; i < frames_read; i++)
-			features[i][ncomponents] = features[i][ncoeff];	
-		
+			features[i][ncomponents] = features[i][ncoeff];
+
 		feature_length = ncomponents + 1;
-		
+
 		/**************************************
 		//TEST
 		// feature file name
@@ -241,7 +241,7 @@ void constq_segment(int* q, double** features, int frames_read, int bins, int nc
 		strcpy(file_name, dir);
 		strcat(file_name, trackname);
 		strcat(file_name, "_features_c20r8h0.2f0.6.mat");
-		
+
 		// get the features from Matlab from mat-file
 		int frames_in_file;
 		readmatarray_size(file_name, 2, &frames_in_file, &feature_length);
@@ -254,27 +254,27 @@ void constq_segment(int* q, double** features, int frames_read, int bins, int nc
 				features[frames_read-missing_frames][i] = features[frames_read-missing_frames-1][i];
 			--missing_frames;
 		}
-		
+
 		free(file_name);
 		******************************************/
-	
+
 		cluster_segment(q, features, frames_read, feature_length, nHMM_states, histogram_length, nclusters, neighbour_limit);
 	}
-	
+
 	if (feature_type == FEATURE_TYPE_CHROMA)
 	{
 /*
 		fprintf(stderr, "Converting to chroma features...\n");
-*/		
+*/
 		/* convert constant-Q to normalised chroma features */
 		chroma = (double**) malloc(frames_read*sizeof(double*));
 		for (i = 0; i < frames_read; i++)
 			chroma[i] = (double*) malloc(bins*sizeof(double));
 		cq2chroma(features, frames_read, ncoeff, bins, chroma);
 		feature_length = bins;
-		
+
 		cluster_segment(q, chroma, frames_read, feature_length, nHMM_states, histogram_length, nclusters, neighbour_limit);
-	
+
 		for (i = 0; i < frames_read; i++)
 			free(chroma[i]);
 		free(chroma);
diff --git a/libs/qm-dsp/dsp/signalconditioning/DFProcess.cpp b/libs/qm-dsp/dsp/signalconditioning/DFProcess.cpp
index 971f5fac8e..4b93cb0e12 100644
--- a/libs/qm-dsp/dsp/signalconditioning/DFProcess.cpp
+++ b/libs/qm-dsp/dsp/signalconditioning/DFProcess.cpp
@@ -25,7 +25,7 @@
 DFProcess::DFProcess( DFProcConfig Config )
 {
     filtSrc = NULL;
-    filtDst = NULL;	
+    filtDst = NULL;
     m_filtScratchIn = NULL;
     m_filtScratchOut = NULL;
 
@@ -51,13 +51,13 @@ void DFProcess::initialise( DFProcConfig Config )
     filtSrc = new double[ m_length ];
     filtDst = new double[ m_length ];
 
-	
+
     //Low Pass Smoothing Filter Config
     m_FilterConfigParams.ord = Config.LPOrd;
     m_FilterConfigParams.ACoeffs = Config.LPACoeffs;
     m_FilterConfigParams.BCoeffs = Config.LPBCoeffs;
-	
-    m_FiltFilt = new FiltFilt( m_FilterConfigParams );	
+
+    m_FiltFilt = new FiltFilt( m_FilterConfigParams );
 }
 
 void DFProcess::deInitialise()
@@ -115,7 +115,7 @@ void DFProcess::medianFilter(double *src, double *dst)
     {
         if (index >= m_length) break;
 
-			
+
 	l = 0;
 	for(  j  = i; j < ( i + m_winPost + m_winPre + 1); j++)
 	{
@@ -139,7 +139,7 @@ void DFProcess::medianFilter(double *src, double *dst)
 
 	    l++;
 	}
-		
+
 	scratch[ index++ ] = MathUtilities::median( y, l);
     }
 
@@ -147,7 +147,7 @@ void DFProcess::medianFilter(double *src, double *dst)
     for( i = 0; i < m_length; i++ )
     {
 	val = src[ i ] - scratch[ i ];// - 0.033;
-		
+
 	if( m_isMedianPositive )
 	{
 	    if( val > 0 )
@@ -164,7 +164,7 @@ void DFProcess::medianFilter(double *src, double *dst)
 	    dst[ i ]  = val;
 	}
     }
-	
+
     delete [] y;
     delete [] scratch;
 }
diff --git a/libs/qm-dsp/dsp/signalconditioning/DFProcess.h b/libs/qm-dsp/dsp/signalconditioning/DFProcess.h
index 3af80743f5..ad40f846b9 100644
--- a/libs/qm-dsp/dsp/signalconditioning/DFProcess.h
+++ b/libs/qm-dsp/dsp/signalconditioning/DFProcess.h
@@ -38,7 +38,7 @@ public:
 
     void process( double* src, double* dst );
 
-	
+
 private:
     void initialise( DFProcConfig Config );
     void deInitialise();
diff --git a/libs/qm-dsp/dsp/signalconditioning/FiltFilt.cpp b/libs/qm-dsp/dsp/signalconditioning/FiltFilt.cpp
index 5a9e2c9549..13dbda0e82 100644
--- a/libs/qm-dsp/dsp/signalconditioning/FiltFilt.cpp
+++ b/libs/qm-dsp/dsp/signalconditioning/FiltFilt.cpp
@@ -24,7 +24,7 @@ FiltFilt::FiltFilt( FiltFiltConfig Config )
     m_filtScratchIn = NULL;
     m_filtScratchOut = NULL;
     m_ord = 0;
-	
+
     initialise( Config );
 }
 
@@ -39,7 +39,7 @@ void FiltFilt::initialise( FiltFiltConfig Config )
     m_filterConfig.ord = Config.ord;
     m_filterConfig.ACoeffs = Config.ACoeffs;
     m_filterConfig.BCoeffs = Config.BCoeffs;
-	
+
     m_filter = new Filter( m_filterConfig );
 }
 
@@ -50,7 +50,7 @@ void FiltFilt::deInitialise()
 
 
 void FiltFilt::process(double *src, double *dst, unsigned int length)
-{	
+{
     unsigned int i;
 
     if (length == 0) return;
@@ -62,7 +62,7 @@ void FiltFilt::process(double *src, double *dst, unsigned int length)
     m_filtScratchIn = new double[ nExt ];
     m_filtScratchOut = new double[ nExt ];
 
-	
+
     for( i = 0; i< nExt; i++ )
     {
 	m_filtScratchIn[ i ] = 0.0;
@@ -89,11 +89,11 @@ void FiltFilt::process(double *src, double *dst, unsigned int length)
     {
 	m_filtScratchIn[ i + nFact ] = src[ i ];
     }
-	
+
     ////////////////////////////////
     // Do  0Ph filtering
     m_filter->process( m_filtScratchIn, m_filtScratchOut, nExt);
-	
+
     // reverse the series for FILTFILT
     for ( i = 0; i < nExt; i++)
     {
@@ -102,7 +102,7 @@ void FiltFilt::process(double *src, double *dst, unsigned int length)
 
     // do FILTER again
     m_filter->process( m_filtScratchIn, m_filtScratchOut, nExt);
-	
+
     // reverse the series back
     for ( i = 0; i < nExt; i++)
     {
@@ -117,7 +117,7 @@ void FiltFilt::process(double *src, double *dst, unsigned int length)
     for( i = 0; i < length; i++ )
     {
 	dst[ index++ ] = m_filtScratchOut[ i + nFact ];
-    }	
+    }
 
     delete [] m_filtScratchIn;
     delete [] m_filtScratchOut;
diff --git a/libs/qm-dsp/dsp/signalconditioning/Filter.h b/libs/qm-dsp/dsp/signalconditioning/Filter.h
index 8533ed0502..b1c20d506a 100644
--- a/libs/qm-dsp/dsp/signalconditioning/Filter.h
+++ b/libs/qm-dsp/dsp/signalconditioning/Filter.h
@@ -35,7 +35,7 @@ public:
     void reset();
 
     void process( double *src, double *dst, unsigned int length );
-	
+
 
 private:
     void initialise( FilterConfig Config );
diff --git a/libs/qm-dsp/dsp/signalconditioning/Framer.cpp b/libs/qm-dsp/dsp/signalconditioning/Framer.cpp
index 80ea67f72c..7357d2417a 100644
--- a/libs/qm-dsp/dsp/signalconditioning/Framer.cpp
+++ b/libs/qm-dsp/dsp/signalconditioning/Framer.cpp
@@ -44,14 +44,14 @@ void Framer::configure( unsigned int frameLength, unsigned int hop )
 
     if( m_dataFrame != NULL )
     {
-	delete [] m_dataFrame;	
+	delete [] m_dataFrame;
 	m_dataFrame = NULL;
     }
     m_dataFrame = new double[ m_frameLength ];
 
     if( m_strideFrame != NULL )
     {
-	delete [] m_strideFrame;	
+	delete [] m_strideFrame;
 	m_strideFrame = NULL;
     }
     m_strideFrame = new double[ m_stepSize ];
@@ -65,7 +65,7 @@ void Framer::getFrame(double *dst)
 	for( unsigned int u = 0; u < m_frameLength; u++)
 	{
 	    dst[ u ] = m_srcBuffer[ m_ulSrcIndex++ ];
-	}	
+	}
 	m_ulSrcIndex -= ( m_frameLength - m_stepSize );
     }
     else
@@ -77,7 +77,7 @@ void Framer::getFrame(double *dst)
 	{
 	    dst[ u ] = m_srcBuffer[ m_ulSrcIndex++ ];
 	}
-		
+
 	for( unsigned int u = 0; u < zero; u++ )
 	{
 	    dst[ rem + u ] = 0;
diff --git a/libs/qm-dsp/dsp/tempotracking/DownBeat.cpp b/libs/qm-dsp/dsp/tempotracking/DownBeat.cpp
index b2183b51ed..1167bc6ea9 100644
--- a/libs/qm-dsp/dsp/tempotracking/DownBeat.cpp
+++ b/libs/qm-dsp/dsp/tempotracking/DownBeat.cpp
@@ -293,7 +293,7 @@ DownBeat::measureSpecDiff(d_vec_t oldspec, d_vec_t newspec)
         }
 
         // JENSEN-SHANNON CALCULATION
-        sd1 = 0.5*oldspec[i] + 0.5*newspec[i];	
+        sd1 = 0.5*oldspec[i] + 0.5*newspec[i];
         SD = SD + (-sd1*log(sd1)) + (0.5*(oldspec[i]*log(oldspec[i]))) + (0.5*(newspec[i]*log(newspec[i])));
     }
 
diff --git a/libs/qm-dsp/dsp/tempotracking/TempoTrackV2.cpp b/libs/qm-dsp/dsp/tempotracking/TempoTrackV2.cpp
index acaa8ff7cd..a2c2a24b0a 100644
--- a/libs/qm-dsp/dsp/tempotracking/TempoTrackV2.cpp
+++ b/libs/qm-dsp/dsp/tempotracking/TempoTrackV2.cpp
@@ -177,7 +177,7 @@ TempoTrackV2::get_rcf(const d_vec_t &dfframe_in, const d_vec_t &wv, d_vec_t &rcf
 
     // now apply comb filtering
     int numelem = 4;
-	
+
     for (unsigned int i = 2;i < rcf.size();i++) // max beat period
     {
         for (int a = 1;a <= numelem;a++) // number of comb elements
@@ -218,7 +218,7 @@ TempoTrackV2::viterbi_decode(const d_mat_t &rcfmat, const d_vec_t &wv, d_vec_t &
     {
         tmat.push_back ( d_vec_t() ); // adds a new column
         for (unsigned int j=0; j<wv.size(); j++)
-        {	
+        {
             tmat[i].push_back(0.); // fill with zeros initially
         }
     }
@@ -230,7 +230,7 @@ TempoTrackV2::viterbi_decode(const d_mat_t &rcfmat, const d_vec_t &wv, d_vec_t &
     for (unsigned int i=20;i <wv.size()-20; i++)
     {
         for (unsigned int j=20; j<wv.size()-20; j++)
-        {	
+        {
             double mu = static_cast<double>(i);
             tmat[i][j] = exp( (-1.*pow((j-mu),2.)) / (2.*pow(sigma,2.)) );
         }
@@ -246,7 +246,7 @@ TempoTrackV2::viterbi_decode(const d_mat_t &rcfmat, const d_vec_t &wv, d_vec_t &
         delta.push_back( d_vec_t());
         psi.push_back( i_vec_t());
         for (unsigned int j=0; j<rcfmat[i].size(); j++)
-        {	
+        {
             delta[i].push_back(0.); // fill with zeros initially
             psi[i].push_back(0); // fill with zeros initially
         }
diff --git a/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.cpp b/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.cpp
index bcc661dd1d..a572da6ee8 100644
--- a/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.cpp
+++ b/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.cpp
@@ -34,20 +34,20 @@ ChangeDetectionFunction::~ChangeDetectionFunction()
 void ChangeDetectionFunction::setFilterWidth(const int iWidth)
 {
 	m_iFilterWidth = iWidth*2+1;
-	
+
 	// it is assumed that the gaussian is 0 outside of +/- FWHM
 	// => filter width = 2*FWHM = 2*2.3548*sigma
 	m_dFilterSigma = double(m_iFilterWidth) / double(2*2.3548);
 	m_vaGaussian.resize(m_iFilterWidth);
-	
+
 	double dScale = 1.0 / (m_dFilterSigma*sqrt(2*PI));
-	
+
 	for (int x = -(m_iFilterWidth-1)/2; x <= (m_iFilterWidth-1)/2; x++)
 	{
 		double w = dScale * std::exp ( -(x*x)/(2*m_dFilterSigma*m_dFilterSigma) );
 		m_vaGaussian[x + (m_iFilterWidth-1)/2] = w;
 	}
-	
+
 #ifdef DEBUG_CHANGE_DETECTION_FUNCTION
 	std::cerr << "Filter sigma: " << m_dFilterSigma << std::endl;
 	std::cerr << "Filter width: " << m_iFilterWidth << std::endl;
@@ -59,37 +59,37 @@ ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 {
 	ChangeDistance retVal;
 	retVal.resize(rTCSGram.getSize(), 0.0);
-	
+
 	TCSGram smoothedTCSGram;
 
 	for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
 	{
 		int iSkipLower = 0;
-	
+
 		int iLowerPos = iPosition - (m_iFilterWidth-1)/2;
 		int iUpperPos = iPosition + (m_iFilterWidth-1)/2;
-	
+
 		if (iLowerPos < 0)
 		{
 			iSkipLower = -iLowerPos;
 			iLowerPos = 0;
 		}
-	
+
 		if (iUpperPos >= rTCSGram.getSize())
 		{
 			int iMaxIndex = rTCSGram.getSize() - 1;
 			iUpperPos = iMaxIndex;
 		}
-	
+
 		TCSVector smoothedVector;
 
 		// for every bin of the vector, calculate the smoothed value
 		for (int iPC = 0; iPC < 6; iPC++)
-		{	
+		{
 			size_t j = 0;
 			double dSmoothedValue = 0.0;
 			TCSVector rCV;
-		
+
 			for (int i = iLowerPos; i <= iUpperPos; i++)
 			{
 				rTCSGram.getTCSVector(i, rCV);
@@ -98,7 +98,7 @@ ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 
 			smoothedVector[iPC] = dSmoothedValue;
 		}
-		
+
 		smoothedTCSGram.addTCSVector(smoothedVector);
 	}
 
@@ -109,10 +109,10 @@ ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 			if the current estimate is not confident enough, look further into the future/the past
 			e.g., High frequency content, zero crossing rate, spectral flatness
 		*/
-		
+
 		TCSVector nextTCS;
 		TCSVector previousTCS;
-		
+
 		int iWindow = 1;
 
 		// while (previousTCS.magnitude() < 0.1 && (iPosition-iWindow) > 0)
@@ -121,9 +121,9 @@ ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 			// std::cout << previousTCS.magnitude() << std::endl;
 			iWindow++;
 		}
-		
+
 		iWindow = 1;
-		
+
 		// while (nextTCS.magnitude() < 0.1 && (iPosition+iWindow) < (rTCSGram.getSize()-1) )
 		{
 			smoothedTCSGram.getTCSVector(iPosition+iWindow, nextTCS);
@@ -136,7 +136,7 @@ ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 		{
 			distance += std::pow(nextTCS[j] - previousTCS[j], 2.0);
 		}
-	
+
 		retVal[iPosition] = std::pow(distance, 0.5);
 	}
 
diff --git a/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.h b/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.h
index 3a84b3096f..5d041ad769 100644
--- a/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.h
+++ b/libs/qm-dsp/dsp/tonal/ChangeDetectionFunction.h
@@ -38,7 +38,7 @@ public:
 	ChangeDistance process(const TCSGram& rTCSGram);
 private:
 	void setFilterWidth(const int iWidth);
-	
+
 private:
 	valarray<double> m_vaGaussian;
 	double m_dFilterSigma;
diff --git a/libs/qm-dsp/dsp/tonal/TCSgram.cpp b/libs/qm-dsp/dsp/tonal/TCSgram.cpp
index c226c81402..954ba03e9b 100644
--- a/libs/qm-dsp/dsp/tonal/TCSgram.cpp
+++ b/libs/qm-dsp/dsp/tonal/TCSgram.cpp
@@ -55,7 +55,7 @@ void TCSGram::addTCSVector(const TCSVector& rTCSVector)
 	std::pair<long, TCSVector> p;
 	p.first = lMilliSeconds;
 	p.second = rTCSVector;
-	
+
 	m_VectorList.push_back(p);
 }
 
@@ -68,7 +68,7 @@ long TCSGram::getDuration() const
 void TCSGram::printDebug()
 {
 	vectorlist_t::iterator vectorIterator = m_VectorList.begin();
-	
+
 	while (vectorIterator != m_VectorList.end())
 	{
 		vectorIterator->second.printDebug();
diff --git a/libs/qm-dsp/dsp/tonal/TCSgram.h b/libs/qm-dsp/dsp/tonal/TCSgram.h
index 83e8c93f8b..f4825a996a 100644
--- a/libs/qm-dsp/dsp/tonal/TCSgram.h
+++ b/libs/qm-dsp/dsp/tonal/TCSgram.h
@@ -26,7 +26,7 @@ typedef std::vector<std::pair<long, TCSVector> > vectorlist_t;
 
 class TCSGram
 {
-public:	
+public:
 	TCSGram();
 	~TCSGram();
 	void getTCSVector(int, TCSVector&) const;
diff --git a/libs/qm-dsp/dsp/tonal/TonalEstimator.cpp b/libs/qm-dsp/dsp/tonal/TonalEstimator.cpp
index 16d1aa8995..72b6f85c83 100644
--- a/libs/qm-dsp/dsp/tonal/TonalEstimator.cpp
+++ b/libs/qm-dsp/dsp/tonal/TonalEstimator.cpp
@@ -27,15 +27,15 @@ TonalEstimator::TonalEstimator()
 	m_Basis.resize(6);
 
 	int i = 0;
-	
-	
+
+
 	// circle of fifths
 	m_Basis[i].resize(12);
 	for (int iP = 0; iP < 12; iP++)
 	{
 		m_Basis[i][iP] = std::sin( (7.0 / 6.0) * iP * PI);
 	}
-	
+
 	i++;
 
 	m_Basis[i].resize(12);
@@ -43,17 +43,17 @@ TonalEstimator::TonalEstimator()
 	{
 		m_Basis[i][iP] = std::cos( (7.0 / 6.0) * iP * PI);
 	}
-	
+
 	i++;
-	
-	
+
+
 	// circle of major thirds
 	m_Basis[i].resize(12);
 	for (int iP = 0; iP < 12; iP++)
 	{
 		m_Basis[i][iP] = 0.6 * std::sin( (2.0 / 3.0) * iP * PI);
 	}
-	
+
 	i++;
 
 	m_Basis[i].resize(12);
@@ -71,7 +71,7 @@ TonalEstimator::TonalEstimator()
 	{
 		m_Basis[i][iP] = 1.1 * std::sin( (3.0 / 2.0) * iP * PI);
 	}
-	
+
 	i++;
 
 	m_Basis[i].resize(12);
@@ -90,7 +90,7 @@ TCSVector TonalEstimator::transform2TCS(const ChromaVector& rVector)
 {
 	TCSVector vaRetVal;
 	vaRetVal.resize(6, 0.0);
-		
+
 	for (int i = 0; i < 6; i++)
 	{
 		for (int iP = 0; iP < 12; iP++)
@@ -98,6 +98,6 @@ TCSVector TonalEstimator::transform2TCS(const ChromaVector& rVector)
 			vaRetVal[i] += m_Basis[i][iP] * rVector[iP];
 		}
 	}
-	
+
 	return vaRetVal;
 }
diff --git a/libs/qm-dsp/dsp/tonal/TonalEstimator.h b/libs/qm-dsp/dsp/tonal/TonalEstimator.h
index 5753dff050..cfb8bba5b6 100644
--- a/libs/qm-dsp/dsp/tonal/TonalEstimator.h
+++ b/libs/qm-dsp/dsp/tonal/TonalEstimator.h
@@ -27,24 +27,24 @@ class ChromaVector : public std::valarray<double>
 public:
 	ChromaVector(size_t uSize = 12) : std::valarray<double>()
 	{ resize(uSize, 0.0f); }
-	
+
 	virtual ~ChromaVector() {};
-	
+
 	void printDebug()
 	{
 		for (int i = 0; i < size(); i++)
 		{
 			std::cout <<  (*this)[i] << ";";
 		}
-		
+
 		std::cout << std::endl;
 	}
-	
+
 	void normalizeL1()
 	{
 		// normalize the chroma vector (L1 norm)
 		double dSum = 0.0;
-	
+
 		for (size_t i = 0; i < 12; (dSum += std::abs((*this)[i++]))) ;
 		for (size_t i = 0; i < 12; dSum > 0.0000001?((*this)[i] /= dSum):(*this)[i]=0.0, i++) ;
 
@@ -55,7 +55,7 @@ public:
         for (size_t i = 0; i < 12; ++i) (*this)[i] = 0.0;
     }
 
-	
+
 };
 
 class TCSVector : public std::valarray<double>
@@ -63,7 +63,7 @@ class TCSVector : public std::valarray<double>
 public:
 	TCSVector() : std::valarray<double>()
 	{ resize(6, 0.0f); }
-	
+
 	virtual ~TCSVector() {};
 
 	void printDebug()
@@ -72,19 +72,19 @@ public:
 		{
 			std::cout <<  (*this)[i] << ";";
 		}
-		
+
 		std::cout << std::endl;
 	}
-	
+
 	double magnitude() const
 	{
 		double dMag = 0.0;
-		
+
 		for (size_t i = 0; i < 6; i++)
 		{
 			dMag += std::pow((*this)[i], 2.0);
 		}
-		
+
 		return std::sqrt(dMag);
 	}
 
diff --git a/libs/qm-dsp/dsp/transforms/FFT.cpp b/libs/qm-dsp/dsp/transforms/FFT.cpp
index 454cfb1422..0ca618f40b 100644
--- a/libs/qm-dsp/dsp/transforms/FFT.cpp
+++ b/libs/qm-dsp/dsp/transforms/FFT.cpp
@@ -54,7 +54,7 @@ FFTReal::process(bool inverse,
 }
 
 static unsigned int numberOfBitsNeeded(unsigned int p_nSamples)
-{	
+{
     int i;
 
     if( p_nSamples < 2 )
diff --git a/libs/qm-dsp/dsp/wavelet/Wavelet.cpp b/libs/qm-dsp/dsp/wavelet/Wavelet.cpp
index d3e1fa1baf..57d6337719 100644
--- a/libs/qm-dsp/dsp/wavelet/Wavelet.cpp
+++ b/libs/qm-dsp/dsp/wavelet/Wavelet.cpp
@@ -82,7 +82,7 @@ Wavelet::createDecompositionFilters(Type wavelet,
     hpd.clear();
 
     unsigned int flength = 0;
-	
+
     switch (wavelet) {
 
     case Haar:
@@ -103,7 +103,7 @@ Wavelet::createDecompositionFilters(Type wavelet,
         hpd.push_back(-0.22414386804186);
         hpd.push_back(-0.12940952255092);
         flength = 4;
-        break;		
+        break;
 
     case Daubechies_3:
         lpd.push_back(0.03522629188210);
@@ -592,7 +592,7 @@ Wavelet::createDecompositionFilters(Type wavelet,
         hpd.push_back(-0.00000000000000);
         flength = 80;
         break;
-			
+
     case Symlet_2:
         lpd.push_back(-0.12940952255092);
         lpd.push_back(0.22414386804186);
@@ -692,7 +692,7 @@ Wavelet::createDecompositionFilters(Type wavelet,
         hpd.push_back(0.01540410932703);
         flength = 12;
         break;
-			
+
     case Symlet_7:
         lpd.push_back(0.00268181456826);
         lpd.push_back(-0.00104738488868);
diff --git a/libs/qm-dsp/hmm/hmm.c b/libs/qm-dsp/hmm/hmm.c
index 69eee02b66..6642e4e1db 100644
--- a/libs/qm-dsp/hmm/hmm.c
+++ b/libs/qm-dsp/hmm/hmm.c
@@ -46,11 +46,11 @@ model_t* hmm_init(double** x, int T, int L, int N)
 {
 	int i, j, d, e, t;
 	double s, ss;
-	
+
 	model_t* model;
 	model = (model_t*) malloc(sizeof(model_t));
 	model->N = N;
-	model->L = L;	
+	model->L = L;
 	model->p0 = (double*) malloc(N*sizeof(double));
 	model->a = (double**) malloc(N*sizeof(double*));
 	model->mu = (double**) malloc(N*sizeof(double*));
@@ -62,10 +62,10 @@ model_t* hmm_init(double** x, int T, int L, int N)
 	model->cov = (double**) malloc(L*sizeof(double*));
 	for (i = 0; i < L; i++)
 		model->cov[i] = (double*) malloc(L*sizeof(double));
-	
+
 	srand(time(0));
 	double* global_mean = (double*) malloc(L*sizeof(double));
-	
+
 	/* find global mean */
 	for (d = 0; d < L; d++)
 	{
@@ -74,7 +74,7 @@ model_t* hmm_init(double** x, int T, int L, int N)
 			global_mean[d] += x[t][d];
 		global_mean[d] /= T;
 	}
-	
+
 	/* calculate global diagonal covariance */
 	for (d = 0; d < L; d++)
 	{
@@ -84,7 +84,7 @@ model_t* hmm_init(double** x, int T, int L, int N)
 			model->cov[d][d] += (x[t][d] - global_mean[d]) * (x[t][d] - global_mean[d]);
 		model->cov[d][d] /= T-1;
 	}
-	
+
 	/* set all means close to global mean */
 	for (i = 0; i < N; i++)
 	{
@@ -94,8 +94,8 @@ model_t* hmm_init(double** x, int T, int L, int N)
 			/* ideally the random number would be Gaussian(0,1), as a hack we make it uniform on [-0.25,0.25] */
 			model->mu[i][d] = global_mean[d] + (0.5 * rand() / (double) RAND_MAX - 0.25) * sqrt(model->cov[d][d]);
 		}
-	}	
-	
+	}
+
 	/* random intial and transition probs */
 	s = 0;
 	for (i = 0; i < N; i++)
@@ -115,16 +115,16 @@ model_t* hmm_init(double** x, int T, int L, int N)
 	}
 	for (i = 0; i < N; i++)
 		model->p0[i] /= s;
-	
+
 	free(global_mean);
-	
+
 	return model;
 }
 
 void hmm_close(model_t* model)
 {
 	int i;
-	
+
 	for (i = 0; i < model->N; i++)
 	{
 		free(model->a[i]);
@@ -134,23 +134,23 @@ void hmm_close(model_t* model)
 	free(model->mu);
 	for (i = 0; i < model->L; i++)
 		free(model->cov[i]);
-	free(model->cov);	
-	free(model);	
+	free(model->cov);
+	free(model);
 }
 
 void hmm_train(double** x, int T, model_t* model)
 {
 	int i, t;
 	double loglik;	/* overall log-likelihood at each iteration */
-	
+
 	int N = model->N;
 	int L = model->L;
 	double* p0 = model->p0;
 	double** a = model->a;
 	double** mu = model->mu;
 	double** cov = model->cov;
-	
-	/* allocate memory */	
+
+	/* allocate memory */
 	double** gamma = (double**) malloc(T*sizeof(double*));
 	double*** xi = (double***) malloc(T*sizeof(double**));
 	for (t = 0; t < T; t++)
@@ -160,45 +160,45 @@ void hmm_train(double** x, int T, model_t* model)
 		for (i = 0; i < N; i++)
 			xi[t][i] = (double*) malloc(N*sizeof(double));
 	}
-	
+
 	/* temporary memory */
 	double* gauss_y = (double*) malloc(L*sizeof(double));
-	double* gauss_z = (double*) malloc(L*sizeof(double));	
-			
+	double* gauss_z = (double*) malloc(L*sizeof(double));
+
 	/* obs probs P(j|{x}) */
 	double** b = (double**) malloc(T*sizeof(double*));
 	for (t = 0; t < T; t++)
 		b[t] = (double*) malloc(N*sizeof(double));
-	
+
 	/* inverse covariance and its determinant */
 	double** icov = (double**) malloc(L*sizeof(double*));
 	for (i = 0; i < L; i++)
 		icov[i] = (double*) malloc(L*sizeof(double));
 	double detcov;
-	
+
 	double thresh = 0.0001;
-	int niter = 50;	
+	int niter = 50;
 	int iter = 0;
 	double loglik1, loglik2;
 	int foundnan = 0;
 
-	while (iter < niter && !foundnan && !(iter > 1 && (loglik - loglik1) < thresh * (loglik1 - loglik2)))	
+	while (iter < niter && !foundnan && !(iter > 1 && (loglik - loglik1) < thresh * (loglik1 - loglik2)))
 	{
 		++iter;
-/*		
+/*
 		fprintf(stderr, "calculating obsprobs...\n");
 		fflush(stderr);
-*/		
+*/
 		/* precalculate obs probs */
 		invert(cov, L, icov, &detcov);
-		
+
 		for (t = 0; t < T; t++)
 		{
 			//int allzero = 1;
 			for (i = 0; i < N; i++)
 			{
 				b[t][i] = exp(loggauss(x[t], L, mu[i], icov, detcov, gauss_y, gauss_z));
-		
+
 				//if (b[t][i] != 0)
 				//	allzero = 0;
 			}
@@ -213,13 +213,13 @@ void hmm_train(double** x, int T, model_t* model)
 			}
 			*/
 		}
-/*		
+/*
 		fprintf(stderr, "forwards-backwards...\n");
 		fflush(stderr);
-*/		
+*/
 		forward_backwards(xi, gamma, &loglik, &loglik1, &loglik2, iter, N, T, p0, a, b);
-/*		
-		fprintf(stderr, "iteration %d: loglik = %f\n", iter, loglik);		
+/*
+		fprintf(stderr, "iteration %d: loglik = %f\n", iter, loglik);
 		fprintf(stderr, "re-estimation...\n");
 		fflush(stderr);
 */
@@ -227,9 +227,9 @@ void hmm_train(double** x, int T, model_t* model)
 		    foundnan = 1;
 		    continue;
 		}
-		
+
 		baum_welch(p0, a, mu, cov, N, T, L, x, xi, gamma);
-			
+
 		/*
 		printf("a:\n");
 		for (i = 0; i < model->N; i++)
@@ -242,7 +242,7 @@ void hmm_train(double** x, int T, model_t* model)
 		 */
 		//hmm_print(model);
 	}
-	
+
 	/* deallocate memory */
 	for (t = 0; t < T; t++)
 	{
@@ -254,12 +254,12 @@ void hmm_train(double** x, int T, model_t* model)
 	}
 	free(gamma);
 	free(xi);
-	free(b);	
-	
+	free(b);
+
 	for (i = 0; i < L; i++)
 		free(icov[i]);
 	free(icov);
-	
+
 	free(gauss_y);
 	free(gauss_z);
 }
@@ -267,27 +267,27 @@ void hmm_train(double** x, int T, model_t* model)
 void mlss_reestimate(double* p0, double** a, double** mu, double** cov, int N, int T, int L, int* q, double** x)
 {
 	/* fit a single Gaussian to observations in each state */
-	
+
 	/* calculate the mean observation in each state */
-	
+
 	/* calculate the overall covariance */
-	
+
 	/* count transitions */
-	
+
 	/* estimate initial probs from transitions (???) */
 }
 
 void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T, int L, double** x, double*** xi, double** gamma)
 {
 	int i, j, t;
-	
+
 	double* sum_gamma = (double*) malloc(N*sizeof(double));
-	
+
 	/* temporary memory */
 	double* u = (double*) malloc(L*L*sizeof(double));
 	double* yy = (double*) malloc(T*L*sizeof(double));
-	double* yy2 = (double*) malloc(T*L*sizeof(double));	
-	
+	double* yy2 = (double*) malloc(T*L*sizeof(double));
+
 	/* re-estimate transition probs */
 	for (i = 0; i < N; i++)
 	{
@@ -295,7 +295,7 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 		for (t = 0; t < T-1; t++)
 			sum_gamma[i] += gamma[t][i];
 	}
-	
+
 	for (i = 0; i < N; i++)
 	{
 		if (sum_gamma[i] == 0)
@@ -310,7 +310,7 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 			for (t = 0; t < T-1; t++)
 				a[i][j] += xi[t][i][j];
 			//s += a[i][j];
-			a[i][j] /= sum_gamma[i];	
+			a[i][j] /= sum_gamma[i];
 		}
 		/*
 		 for (j = 0; j < N; j++)
@@ -319,21 +319,21 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 		 }
 		 */
 	}
-	
+
 	/* NB: now we need to sum gamma over all t */
 	for (i = 0; i < N; i++)
 		sum_gamma[i] += gamma[T-1][i];
-	
+
 	/* re-estimate initial probs */
 	for (i = 0; i < N; i++)
 		p0[i] = gamma[0][i];
-	
+
 	/* re-estimate covariance */
 	int d, e;
 	double sum_sum_gamma = 0;
 	for (i = 0; i < N; i++)
-		sum_sum_gamma += sum_gamma[i];		
-	
+		sum_sum_gamma += sum_gamma[i];
+
 	/*
 	 for (d = 0; d < L; d++)
 	 {
@@ -343,9 +343,9 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 			 for (t = 0; t < T; t++)
 				 for (j = 0; j < N; j++)
 					 cov[d][e] += gamma[t][j] * (x[t][d] - mu[j][d]) * (x[t][e] - mu[j][e]);
-			
+
 			 cov[d][e] /= sum_sum_gamma;
-			
+
 			 if (ISNAN(cov[d][e]))
 			 {
 				 printf("cov[%d][%d] was nan\n", d, e);
@@ -365,12 +365,12 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 	 for (e = 0; e < d; e++)
 	 cov[d][e] = cov[e][d];
 	 */
-	
+
 	/* using BLAS */
 	for (d = 0; d < L; d++)
 		for (e = 0; e < L; e++)
 			cov[d][e] = 0;
-	
+
 	for (j = 0; j < N; j++)
 	{
 		for (d = 0; d < L; d++)
@@ -379,20 +379,20 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 				yy[d*T+t] = x[t][d] - mu[j][d];
 				yy2[d*T+t] = gamma[t][j] * (x[t][d] - mu[j][d]);
 			}
-				
+
 				cblas_dgemm(CblasColMajor, CblasTrans, CblasNoTrans, L, L, T, 1.0, yy, T, yy2, T, 0, u, L);
-		
+
 		for (e = 0; e < L; e++)
 			for (d = 0; d < L; d++)
 				cov[d][e] += u[e*L+d];
 	}
-	
+
 	for (d = 0; d < L; d++)
 		for (e = 0; e < L; e++)
-			cov[d][e] /= T; /* sum_sum_gamma; */			
-	
+			cov[d][e] /= T; /* sum_sum_gamma; */
+
 	//printf("sum_sum_gamma = %f\n", sum_sum_gamma); /* fine, = T IS THIS ALWAYS TRUE with pooled cov?? */
-	
+
 	/* re-estimate means */
 	for (j = 0; j < N; j++)
 	{
@@ -404,7 +404,7 @@ void baum_welch(double* p0, double** a, double** mu, double** cov, int N, int T,
 			mu[j][d] /= sum_gamma[j];
 		}
 	}
-	
+
 	/* deallocate memory */
 	free(sum_gamma);
 	free(yy);
@@ -416,7 +416,7 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 {
 	/* forwards-backwards with scaling */
 	int i, j, t;
-	
+
 	double** alpha = (double**) malloc(T*sizeof(double*));
 	double** beta = (double**) malloc(T*sizeof(double*));
 	for (t = 0; t < T; t++)
@@ -424,34 +424,34 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 		alpha[t] = (double*) malloc(N*sizeof(double));
 		beta[t] = (double*) malloc(N*sizeof(double));
 	}
-	
+
 	/* scaling coefficients */
 	double* c = (double*) malloc(T*sizeof(double));
-	
+
 	/* calculate forward probs and scale coefficients */
 	c[0] = 0;
 	for (i = 0; i < N; i++)
 	{
 		alpha[0][i] = p0[i] * b[0][i];
 		c[0] += alpha[0][i];
-		
+
 		//printf("p0[%d] = %f, b[0][%d] = %f\n", i, p0[i], i, b[0][i]);
 	}
 	c[0] = 1 / c[0];
 	for (i = 0; i < N; i++)
 	{
-		alpha[0][i] *= c[0];		
-		
+		alpha[0][i] *= c[0];
+
 		//printf("alpha[0][%d] = %f\n", i, alpha[0][i]);	/* OK agrees with Matlab */
 	}
-	
+
 	*loglik1 = *loglik;
 	*loglik = -log(c[0]);
 	if (iter == 2)
 		*loglik2 = *loglik;
-	
+
 	for (t = 1; t < T; t++)
-	{			
+	{
 		c[t] = 0;
 		for (j = 0; j < N; j++)
 		{
@@ -459,10 +459,10 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 			for (i = 0; i < N; i++)
 				alpha[t][j] += alpha[t-1][i] * a[i][j];
 			alpha[t][j] *= b[t][j];
-			
+
 			c[t] += alpha[t][j];
 		}
-		
+
 		/*
 		 if (c[t] == 0)
 		 {
@@ -477,16 +477,16 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 			 exit(-1);
 		 }
 		 */
-		
+
 		c[t] = 1 / c[t];
 		for (j = 0; j < N; j++)
 			alpha[t][j] *= c[t];
-		
+
 		//printf("c[%d] = %e\n", t, c[t]);
-		
+
 		*loglik -= log(c[t]);
 	}
-	
+
 	/* calculate backwards probs using same coefficients */
 	for (i = 0; i < N; i++)
 		beta[T-1][i] = 1;
@@ -495,20 +495,20 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 	{
 		for (i = 0; i < N; i++)
 			beta[t][i] *= c[t];
-		
+
 		if (t == 0)
 			break;
-		
+
 		for (i = 0; i < N; i++)
 		{
 			beta[t-1][i] = 0;
 			for (j = 0; j < N; j++)
 				beta[t-1][i] += a[i][j] * b[t][j] * beta[t][j];
 		}
-		
+
 		t--;
 	}
-	
+
 	/*
 	 printf("alpha:\n");
 	 for (t = 0; t < T; t++)
@@ -526,7 +526,7 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 	 }
 	 printf("\n\n");
 	 */
-	
+
 	/* calculate posterior probs */
 	double tot;
 	for (t = 0; t < T; t++)
@@ -539,12 +539,12 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 		}
 		for (i = 0; i < N; i++)
 		{
-			gamma[t][i] /= tot;				
-			
-			//printf("gamma[%d][%d] = %f\n", t, i, gamma[t][i]);				
+			gamma[t][i] /= tot;
+
+			//printf("gamma[%d][%d] = %f\n", t, i, gamma[t][i]);
 		}
-	}		
-	
+	}
+
 	for (t = 0; t < T-1; t++)
 	{
 		tot = 0;
@@ -560,7 +560,7 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 			for (j = 0; j < N; j++)
 				xi[t][i][j] /= tot;
 	}
-	
+
 	/*
 	 // CHECK - fine
 	 // gamma[t][i] = \sum_j{xi[t][i][j]}
@@ -568,8 +568,8 @@ void forward_backwards(double*** xi, double** gamma, double* loglik, double* log
 	 for (j = 0; j < N; j++)
 	 tot += xi[3][1][j];
 	 printf("gamma[3][1] = %f, sum_j(xi[3][1][j]) = %f\n", gamma[3][1], tot);
-	 */	
-	
+	 */
+
 	for (t = 0; t < T; t++)
 	{
 		free(alpha[t]);
@@ -585,20 +585,20 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 	int i, j, t;
 	double max;
 	int havemax;
-	
+
 	int N = model->N;
 	int L = model->L;
 	double* p0 = model->p0;
 	double** a = model->a;
 	double** mu = model->mu;
 	double** cov = model->cov;
-	
+
 	/* inverse covariance and its determinant */
 	double** icov = (double**) malloc(L*sizeof(double*));
 	for (i = 0; i < L; i++)
 		icov[i] = (double*) malloc(L*sizeof(double));
 	double detcov;
-	
+
 	double** logb = (double**) malloc(T*sizeof(double*));
 	double** phi = (double**) malloc(T*sizeof(double*));
 	int** psi = (int**) malloc(T*sizeof(int*));
@@ -608,24 +608,24 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 		phi[t] = (double*) malloc(N*sizeof(double));
 		psi[t] = (int*) malloc(N*sizeof(int));
 	}
-	
+
 	/* temporary memory */
 	double* gauss_y = (double*) malloc(L*sizeof(double));
-	double* gauss_z = (double*) malloc(L*sizeof(double));	
-	
+	double* gauss_z = (double*) malloc(L*sizeof(double));
+
 	/* calculate observation logprobs */
 	invert(cov, L, icov, &detcov);
 	for (t = 0; t < T; t++)
 		for (i = 0; i < N; i++)
 			logb[t][i] = loggauss(x[t], L, mu[i], icov, detcov, gauss_y, gauss_z);
-	
+
 	/* initialise */
 	for (i = 0; i < N; i++)
 	{
 		phi[0][i] = log(p0[i]) + logb[0][i];
 		psi[0][i] = 0;
 	}
-	
+
 	for (t = 1; t < T; t++)
 	{
 		for (j = 0; j < N; j++)
@@ -646,7 +646,7 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 			}
 		}
 	}
-	
+
 	/* find maximising state at time T-1 */
 	max = phi[T-1][0];
 	q[T-1] = 0;
@@ -659,7 +659,7 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 		}
 	}
 
-	
+
 	/* track back */
 	t = T - 2;
 	while (t >= 0)
@@ -667,7 +667,7 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 		q[t] = psi[t+1][q[t+1]];
 		t--;
 	}
-	
+
 	/* de-allocate memory */
 	for (i = 0; i < L; i++)
 		free(icov[i]);
@@ -681,7 +681,7 @@ void viterbi_decode(double** x, int T, model_t* model, int* q)
 	free(logb);
 	free(phi);
 	free(psi);
-	
+
 	free(gauss_y);
 	free(gauss_z);
 }
@@ -695,11 +695,11 @@ void invert(double** cov, int L, double** icov, double* detcov)
 	for(j=0; j < L; j++)
 		for (i=0; i < L; i++)
 			a[j*L+i] = cov[i][j];
-	
-	int M = (int) L;	
+
+	int M = (int) L;
 	int* ipiv = (int *) malloc(L*L*sizeof(int));
 	int ret;
-	
+
 	/* LU decomposition */
 	ret = dgetrf_(&M, &M, a, &M, ipiv, &ret);	/* ret should be zero, negative if cov is singular */
 	if (ret < 0)
@@ -707,7 +707,7 @@ void invert(double** cov, int L, double** icov, double* detcov)
 		fprintf(stderr, "Covariance matrix was singular, couldn't invert\n");
 		exit(-1);
 	}
-	
+
 	/* find determinant */
 	double det = 1;
 	for(i = 0; i < L; i++)
@@ -723,27 +723,27 @@ void invert(double** cov, int L, double** icov, double* detcov)
 	if (det < 0)
 		det = -det;
 	*detcov = det;
-	
+
 	/* allocate required working storage */
 #ifndef HAVE_ATLAS
 	int lwork = -1;
 	double lwbest = 0.0;
 	dgetri_(&M, a, &M, ipiv, &lwbest, &lwork, &ret);
-	lwork = (int) lwbest;	
+	lwork = (int) lwbest;
 	double* work  = (double*) malloc(lwork*sizeof(double));
 #endif
-	
+
 	/* find inverse */
 	dgetri_(&M, a, &M, ipiv, work, &lwork, &ret);
 
 	for(j=0; j < L; j++)
 		for (i=0; i < L; i++)
-			icov[i][j] = a[j*L+i];	
-	
-#ifndef HAVE_ATLAS	
+			icov[i][j] = a[j*L+i];
+
+#ifndef HAVE_ATLAS
 	free(work);
 #endif
-	free(a);	
+	free(a);
 }
 
 /* probability of multivariate Gaussian given mean, inverse and determinant of covariance */
@@ -762,8 +762,8 @@ double gauss(double* x, int L, double* mu, double** icov, double detcov, double*
 	}
 	s = cblas_ddot(L, z, 1, y, 1);
 	//for (i = 0; i < L; i++)
-	//	s += z[i] * y[i];	
-	
+	//	s += z[i] * y[i];
+
 	return exp(-s/2.0) / (pow(2*PI, L/2.0) * sqrt(detcov));
 }
 
@@ -784,10 +784,10 @@ double loggauss(double* x, int L, double* mu, double** icov, double detcov, doub
 	}
 	s = cblas_ddot(L, z, 1, y, 1);
 	//for (i = 0; i < L; i++)
-	//	s += z[i] * y[i];	
-	
+	//	s += z[i] * y[i];
+
 	ret = -0.5 * (s + L * log(2*PI) + log(detcov));
-	
+
 	/*
 	// TEST
 	if (ISINF(ret) > 0)
@@ -795,9 +795,9 @@ double loggauss(double* x, int L, double* mu, double** icov, double detcov, doub
 	if (ISINF(ret) < 0)
 		printf("loggauss returning -infinity\n");
 	if (ISNAN(ret))
-		printf("loggauss returning nan\n");	
+		printf("loggauss returning nan\n");
 	*/
-	
+
 	return ret;
 }
 
diff --git a/libs/qm-dsp/maths/MathUtilities.cpp b/libs/qm-dsp/maths/MathUtilities.cpp
index 2249c53a95..a55252b365 100644
--- a/libs/qm-dsp/maths/MathUtilities.cpp
+++ b/libs/qm-dsp/maths/MathUtilities.cpp
@@ -41,11 +41,11 @@ void MathUtilities::getAlphaNorm(const double *data, unsigned int len, unsigned
     unsigned int i;
     double temp = 0.0;
     double a=0.0;
-	
+
     for( i = 0; i < len; i++)
     {
 	temp = data[ i ];
-		
+
 	a  += ::pow( fabs(temp), double(alpha) );
     }
     a /= ( double )len;
@@ -60,11 +60,11 @@ double MathUtilities::getAlphaNorm( const std::vector <double> &data, unsigned i
     unsigned int len = data.size();
     double temp = 0.0;
     double a=0.0;
-	
+
     for( i = 0; i < len; i++)
     {
 	temp = data[ i ];
-		
+
 	a  += ::pow( fabs(temp), double(alpha) );
     }
     a /= ( double )len;
@@ -143,7 +143,7 @@ double MathUtilities::mean(const double *src, unsigned int len)
     double retVal =0.0;
 
     double s = sum( src, len );
-	
+
     retVal =  s  / (double)len;
 
     return retVal;
@@ -154,7 +154,7 @@ double MathUtilities::mean(const std::vector<double> &src,
                            unsigned int count)
 {
     double sum = 0.;
-	
+
     for (unsigned int i = 0; i < count; ++i)
     {
         sum += src[start + i];
@@ -172,7 +172,7 @@ void MathUtilities::getFrameMinMax(const double *data, unsigned int len, double
         *min = *max = 0;
         return;
     }
-	
+
     *min = data[0];
     *max = data[0];
 
@@ -188,7 +188,7 @@ void MathUtilities::getFrameMinMax(const double *data, unsigned int len, double
 	{
 	    *max =  temp ;
 	}
-		
+
     }
 }
 
@@ -197,7 +197,7 @@ int MathUtilities::getMax( double* pData, unsigned int Length, double* pMax )
 	unsigned int index = 0;
 	unsigned int i;
 	double temp = 0.0;
-	
+
 	double max = pData[0];
 
 	for( i = 0; i < Length; i++)
@@ -209,7 +209,7 @@ int MathUtilities::getMax( double* pData, unsigned int Length, double* pMax )
 			max =  temp ;
 			index = i;
 		}
-		
+
    	}
 
 	if (pMax) *pMax = max;
@@ -223,7 +223,7 @@ int MathUtilities::getMax( const std::vector<double> & data, double* pMax )
 	unsigned int index = 0;
 	unsigned int i;
 	double temp = 0.0;
-	
+
 	double max = data[0];
 
 	for( i = 0; i < data.size(); i++)
@@ -235,7 +235,7 @@ int MathUtilities::getMax( const std::vector<double> & data, double* pMax )
 			max =  temp ;
 			index = i;
 		}
-		
+
    	}
 
 	if (pMax) *pMax = max;
@@ -344,7 +344,7 @@ void MathUtilities::adaptiveThreshold(std::vector<double> &data)
     if (sz == 0) return;
 
     std::vector<double> smoothed(sz);
-	
+
     int p_pre = 8;
     int p_post = 7;
 
diff --git a/libs/qm-dsp/maths/MathUtilities.h b/libs/qm-dsp/maths/MathUtilities.h
index 1d3395e8ad..85774756d4 100644
--- a/libs/qm-dsp/maths/MathUtilities.h
+++ b/libs/qm-dsp/maths/MathUtilities.h
@@ -22,7 +22,7 @@
 
 class MathUtilities
 {
-public:	
+public:
     static double round( double x );
 
     static void	  getFrameMinMax( const double* data, unsigned int len,  double* min, double* max );
diff --git a/libs/qm-dsp/maths/pca/pca.c b/libs/qm-dsp/maths/pca/pca.c
index 288ec4d2e4..d2b2f11c47 100644
--- a/libs/qm-dsp/maths/pca/pca.c
+++ b/libs/qm-dsp/maths/pca/pca.c
@@ -110,7 +110,7 @@ void tred2(double** a, int n, double* d, double* e)
 {
 	int l, k, j, i;
 	double scale, hh, h, g, f;
-	
+
 	for (i = n-1; i >= 1; i--)
     {
 		l = i - 1;
@@ -188,7 +188,7 @@ void tqli(double* d, double* e, int n, double** z)
 {
 	int m, l, iter, i, k;
 	double s, r, p, g, f, dd, c, b;
-	
+
 	for (i = 1; i < n; i++)
 		e[i-1] = e[i];
 	e[n-1] = 0.0;
@@ -253,19 +253,19 @@ void pca_project(double** data, int n, int m, int ncomponents)
 {
 	int  i, j, k, k2;
 	double  **symmat, **symmat2, *evals, *interm;
-	
+
 	//TODO: assert ncomponents < m
-	
+
 	symmat = (double**) malloc(m*sizeof(double*));
 	for (i = 0; i < m; i++)
 		symmat[i] = (double*) malloc(m*sizeof(double));
-		
+
 	covcol(data, n, m, symmat);
-	
+
 	/*********************************************************************
 		Eigen-reduction
 		**********************************************************************/
-	
+
     /* Allocate storage for dummy and new vectors. */
     evals = (double*) malloc(m*sizeof(double));     /* Storage alloc. for vector of eigenvalues */
     interm = (double*) malloc(m*sizeof(double));    /* Storage alloc. for 'intermediate' vector */
@@ -278,7 +278,7 @@ void pca_project(double** data, int n, int m, int ncomponents)
     tred2(symmat, m, evals, interm);  /* Triangular decomposition */
 tqli(evals, interm, m, symmat);   /* Reduction of sym. trid. matrix */
 /* evals now contains the eigenvalues,
-columns of symmat now contain the associated eigenvectors. */	
+columns of symmat now contain the associated eigenvectors. */
 
 /*
 	printf("\nEigenvalues:\n");
@@ -289,7 +289,7 @@ columns of symmat now contain the associated eigenvectors. */
 	printf("Eigenvalues are often expressed as cumulative\n");
 	printf("percentages, representing the 'percentage variance\n");
 	printf("explained' by the associated axis or principal component.)\n");
-	
+
 	printf("\nEigenvectors:\n");
 	printf("(First three; their definition in terms of original vbes.)\n");
 	for (j = 0; j < m; j++) {
@@ -310,7 +310,7 @@ for (i = 0; i < n; i++) {
         }
 }
 
-/*	
+/*
 printf("\nProjections of row-points on first 3 prin. comps.:\n");
  for (i = 0; i < n; i++) {
 	 for (j = 0; j < 3; j++)  {