comparison dsp/tonal/ChangeDetectionFunction.cpp @ 482:cbe668c7d724

Untabify, indent, tidy

 
 #ifndef PI
 #define PI (3.14159265358979232846)
 #endif
 
-
-
 ChangeDetectionFunction::ChangeDetectionFunction(ChangeDFConfig config) :
-	m_dFilterSigma(0.0), m_iFilterWidth(0)
+    m_dFilterSigma(0.0), m_iFilterWidth(0)
 {
-	setFilterWidth(config.smoothingWidth);
+    setFilterWidth(config.smoothingWidth);
 }
 
 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;
-	}
-	
+    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;
+    std::cerr << "Filter sigma: " << m_dFilterSigma << std::endl;
+    std::cerr << "Filter width: " << m_iFilterWidth << std::endl;
 #endif
 }
 
 
 ChangeDistance ChangeDetectionFunction::process(const TCSGram& rTCSGram)
 {
-	ChangeDistance retVal;
-	retVal.resize(rTCSGram.getSize(), 0.0);
-	
-	TCSGram smoothedTCSGram;
+    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 (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);
-				dSmoothedValue += m_vaGaussian[iSkipLower + j++] * rCV[iPC];
-			}
+        // for every bin of the vector, calculate the smoothed value
+        for (int iPC = 0; iPC < 6; iPC++) {       
 
-			smoothedVector[iPC] = dSmoothedValue;
-		}
-		
-		smoothedTCSGram.addTCSVector(smoothedVector);
-	}
+            size_t j = 0;
+            double dSmoothedValue = 0.0;
+            TCSVector rCV;
+                
+            for (int i = iLowerPos; i <= iUpperPos; i++) {
+                rTCSGram.getTCSVector(i, rCV);
+                dSmoothedValue += m_vaGaussian[iSkipLower + j++] * rCV[iPC];
+            }
 
-	for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++)
-	{
-		/*
-			TODO: calculate a confidence measure for the current estimation
-			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;
+            smoothedVector[iPC] = dSmoothedValue;
+        }
+                
+        smoothedTCSGram.addTCSVector(smoothedVector);
+    }
 
-		// while (previousTCS.magnitude() < 0.1 && (iPosition-iWindow) > 0)
-		{
-			smoothedTCSGram.getTCSVector(iPosition-iWindow, previousTCS);
-			// std::cout << previousTCS.magnitude() << std::endl;
-			iWindow++;
-		}
-		
-		iWindow = 1;
-		
-		// while (nextTCS.magnitude() < 0.1 && (iPosition+iWindow) < (rTCSGram.getSize()-1) )
-		{
-			smoothedTCSGram.getTCSVector(iPosition+iWindow, nextTCS);
-			iWindow++;
-		}
+    for (int iPosition = 0; iPosition < rTCSGram.getSize(); iPosition++) {
+        
+        /*
+          TODO: calculate a confidence measure for the current estimation
+          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;
 
-		double distance = 0.0;
-		// Euclidean distance
-		for (size_t j = 0; j < 6; j++)
-		{
-			distance += std::pow(nextTCS[j] - previousTCS[j], 2.0);
-		}
-	
-		retVal[iPosition] = std::pow(distance, 0.5);
-	}
+        // while (previousTCS.magnitude() < 0.1 && (iPosition-iWindow) > 0)
+        {
+            smoothedTCSGram.getTCSVector(iPosition-iWindow, previousTCS);
+            // std::cout << previousTCS.magnitude() << std::endl;
+            iWindow++;
+        }
+                
+        iWindow = 1;
+                
+        // while (nextTCS.magnitude() < 0.1 && (iPosition+iWindow) < (rTCSGram.getSize()-1) )
+        {
+            smoothedTCSGram.getTCSVector(iPosition+iWindow, nextTCS);
+            iWindow++;
+        }
 
-	return retVal;
+        double distance = 0.0;
+        // Euclidean distance
+        for (size_t j = 0; j < 6; j++) {
+            distance += std::pow(nextTCS[j] - previousTCS[j], 2.0);
+        }
+        
+        retVal[iPosition] = std::pow(distance, 0.5);
+    }
+
+    return retVal;
 }