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Author: mcychan

nQuantCpp/DblGNGGAQuantizer.cpp

@@ -219,7 +219,7 @@ namespace GrowingNeuralGas
 	}
 
 	double rotateLR(double u, double v) {
-		auto theta = randrange(0.0, 2.0 * M_PI);
+		auto theta = randrange(0.0, 2 * M_PI);
 		auto result = u * cos(theta) - v * sin(theta);
 		if (result <= minLR || result >= maxLR) {
 			auto range = maxLR - minLR;
@@ -241,9 +241,25 @@ namespace GrowingNeuralGas
 		return child;
 	}
 
+	const double MUTATION_STDDEV_RATIO = 0.15;
 	double boxMuller(double value, double minValue, double maxValue) {
-		auto r1 = randrange(minValue, maxValue);
-		return sqrt(-2 * log(value)) * cos(2 * M_PI * r1);
+		auto u1 = randrange(0.0, 1.0);
+		auto u2 = randrange(0.0, 1.0);
+
+		if (u1 < 1e-9)
+			u1 = 1e-9;
+
+		auto pureBoxMuller = sqrt(-2 * log(u1))* cos(2 * M_PI * u2);
+		auto stddev = (maxValue - minValue) * MUTATION_STDDEV_RATIO;
+
+		auto result = value + pureBoxMuller * stddev;
+		if (result < minValue) {
+			result = minValue;
+		}
+		else if (result > maxValue) {
+			result = maxValue;
+		}
+		return result;
 	}
 
 	bool DblGNGGAQuantizer::dominates(const DblGNGGAQuantizer* right) {

nQuantCpp/DblGNGQuantizer.cpp

@@ -31,10 +31,7 @@ namespace GrowingNeuralGas
 		{0.299f, 0.587f, 0.114f},
 		{-0.14713f, -0.28886f, 0.436f},
 		{0.615f, -0.51499f, -0.10001f}
-	};
-	
-	unordered_map<int, vector<unsigned short> > closestMap;
-	unordered_map<int, unsigned short> nearestMap;	
+	};	
 
 	DblGNGQuantizer::DblGNGQuantizer() : startingPoints(2)
 		, learningRate(0.002)
@@ -820,11 +817,9 @@ namespace GrowingNeuralGas
 	}
 
 	void DblGNGQuantizer::setParams(double learningRate, int startingPoints) {
-		#pragma omp critical(QuantizerParamLock)
-		{
-			this->learningRate = learningRate;
-			this->startingPoints = startingPoints;
-			clear();
-		}
+		this->learningRate = learningRate;
+		this->startingPoints = startingPoints;
+		closestMap.clear();
+		nearestMap.clear();
 	}
 }

nQuantCpp/DblGNGQuantizer.h

@@ -97,6 +97,9 @@ namespace GrowingNeuralGas
 			vector<shared_ptr<GNGNode>> uniqueSamples;
 			vector<shared_ptr<GNGNode>> stdDevSamples;
 			unordered_map<uint32_t, int> histogram;
+
+			unordered_map<int, vector<unsigned short> > closestMap;
+			unordered_map<int, unsigned short> nearestMap;
 
 			void insertNewNodeWeighted(unordered_map<shared_ptr<GNGNode>, vector<shared_ptr<GNGNode>>, SharedPtrHash>& assignments);
 			void updateNodeWeightsAdaptive(unordered_map<shared_ptr<GNGNode>, vector<shared_ptr<GNGNode>>, SharedPtrHash>& assignments,

nQuantCpp/PnnLABGAQuantizer.cpp

@@ -256,9 +256,25 @@ namespace PnnLABQuant
 		return child;
 	}
 
-	static double boxMuller(double value) {
-		auto r1 = randrange(minRatio, maxRatio);
-		return sqrt(-2 * log(value)) * cos(2 * M_PI * r1);
+	const double MUTATION_STDDEV_RATIO = 0.15;
+	double boxMuller(double value) {
+		auto u1 = randrange(0.0, 1.0);
+		auto u2 = randrange(0.0, 1.0);
+
+		if (u1 < 1e-9)
+			u1 = 1e-9;
+
+		auto pureBoxMuller = sqrt(-2 * log(u1)) * cos(2 * M_PI * u2);
+		auto stddev = (maxRatio - minRatio) * MUTATION_STDDEV_RATIO;
+
+		auto result = value + pureBoxMuller * stddev;
+		if (result < minRatio) {
+			result = minRatio;
+		}
+		else if (result > maxRatio) {
+			result = maxRatio;
+		}
+		return result;
 	}
 
 	bool PnnLABGAQuantizer::dominates(const PnnLABGAQuantizer* right) {