Update qm-dsp library (v1.7.1-20-g4d15479)

libs/qm-dsp/maths/MathUtilities.cpp

@@ -20,6 +20,7 @@
 #include <vector>
 #include <cmath>
 
+using namespace std;
 
 double MathUtilities::mod(double x, double y)
 {
@@ -38,9 +39,9 @@ double MathUtilities::princarg(double ang)
     return ValOut;
 }
 
-void MathUtilities::getAlphaNorm(const double *data, unsigned int len, unsigned int alpha, double* ANorm)
+void MathUtilities::getAlphaNorm(const double *data, int len, int alpha, double* ANorm)
 {
-    unsigned int i;
+    int i;
     double temp = 0.0;
     double a=0.0;
 	
@@ -56,17 +57,16 @@ void MathUtilities::getAlphaNorm(const double *data, unsigned int len, unsigned
     *ANorm = a;
 }
 
-double MathUtilities::getAlphaNorm( const std::vector <double> &data, unsigned int alpha )
+double MathUtilities::getAlphaNorm( const vector <double> &data, int alpha )
 {
-    unsigned int i;
-    unsigned int len = data.size();
+    int i;
+    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;
@@ -84,13 +84,13 @@ double MathUtilities::round(double x)
     }
 }
 
-double MathUtilities::median(const double *src, unsigned int len)
+double MathUtilities::median(const double *src, int len)
 {
     if (len == 0) return 0;
     
-    std::vector<double> scratch;
+    vector<double> scratch;
     for (int i = 0; i < len; ++i) scratch.push_back(src[i]);
-    std::sort(scratch.begin(), scratch.end());
+    sort(scratch.begin(), scratch.end());
 
     int middle = len/2;
     if (len % 2 == 0) {
@@ -100,9 +100,9 @@ double MathUtilities::median(const double *src, unsigned int len)
     }
 }
 
-double MathUtilities::sum(const double *src, unsigned int len)
+double MathUtilities::sum(const double *src, int len)
 {
-    unsigned int i ;
+    int i ;
     double retVal =0.0;
 
     for(  i = 0; i < len; i++)
@@ -113,7 +113,7 @@ double MathUtilities::sum(const double *src, unsigned int len)
     return retVal;
 }
 
-double MathUtilities::mean(const double *src, unsigned int len)
+double MathUtilities::mean(const double *src, int len)
 {
     double retVal =0.0;
 
@@ -126,9 +126,9 @@ double MathUtilities::mean(const double *src, unsigned int len)
     return retVal;
 }
 
-double MathUtilities::mean(const std::vector<double> &src,
-                           unsigned int start,
-                           unsigned int count)
+double MathUtilities::mean(const vector<double> &src,
+                           int start,
+                           int count)
 {
     double sum = 0.;
 	
@@ -142,9 +142,9 @@ double MathUtilities::mean(const std::vector<double> &src,
     return sum / count;
 }
 
-void MathUtilities::getFrameMinMax(const double *data, unsigned int len, double *min, double *max)
+void MathUtilities::getFrameMinMax(const double *data, int len, double *min, double *max)
 {
-    unsigned int i;
+    int i;
     double temp = 0.0;
 
     if (len == 0) {
@@ -171,10 +171,10 @@ void MathUtilities::getFrameMinMax(const double *data, unsigned int len, double
     }
 }
 
-int MathUtilities::getMax( double* pData, unsigned int Length, double* pMax )
+int MathUtilities::getMax( double* pData, int Length, double* pMax )
 {
-	unsigned int index = 0;
-	unsigned int i;
+	int index = 0;
+	int i;
 	double temp = 0.0;
 	
 	double max = pData[0];
@@ -197,15 +197,15 @@ int MathUtilities::getMax( double* pData, unsigned int Length, double* pMax )
 	return index;
 }
 
-int MathUtilities::getMax( const std::vector<double> & data, double* pMax )
+int MathUtilities::getMax( const vector<double> & data, double* pMax )
 {
-	unsigned int index = 0;
-	unsigned int i;
+	int index = 0;
+	int i;
 	double temp = 0.0;
 	
 	double max = data[0];
 
-	for( i = 0; i < data.size(); i++)
+	for( i = 0; i < int(data.size()); i++)
 	{
 		temp = data[ i ];
 
@@ -286,7 +286,7 @@ void MathUtilities::normalise(double *data, int length, NormaliseType type)
     }
 }
 
-void MathUtilities::normalise(std::vector<double> &data, NormaliseType type)
+void MathUtilities::normalise(vector<double> &data, NormaliseType type)
 {
     switch (type) {
 
@@ -317,20 +317,46 @@ void MathUtilities::normalise(std::vector<double> &data, NormaliseType type)
     }
 }
 
-void MathUtilities::adaptiveThreshold(std::vector<double> &data)
+double MathUtilities::getLpNorm(const vector<double> &data, int p)
+{
+    double tot = 0.0;
+    for (int i = 0; i < int(data.size()); ++i) {
+        tot += abs(pow(data[i], p));
+    }
+    return pow(tot, 1.0 / p);
+}
+
+vector<double> MathUtilities::normaliseLp(const vector<double> &data,
+                                               int p,
+                                               double threshold)
+{
+    int n = int(data.size());
+    if (n == 0 || p == 0) return data;
+    double norm = getLpNorm(data, p);
+    if (norm < threshold) {
+        return vector<double>(n, 1.0 / pow(n, 1.0 / p)); // unit vector
+    }
+    vector<double> out(n);
+    for (int i = 0; i < n; ++i) {
+        out[i] = data[i] / norm;
+    }
+    return out;
+}
+    
+void MathUtilities::adaptiveThreshold(vector<double> &data)
 {
     int sz = int(data.size());
     if (sz == 0) return;
 
-    std::vector<double> smoothed(sz);
+    vector<double> smoothed(sz);
 	
     int p_pre = 8;
     int p_post = 7;
 
     for (int i = 0; i < sz; ++i) {
 
-        int first = std::max(0,      i - p_pre);
-        int last  = std::min(sz - 1, i + p_post);
+        int first = max(0,      i - p_pre);
+        int last  = min(sz - 1, i + p_post);
 
         smoothed[i] = mean(data, first, last - first + 1);
     }