renamed TransferFunction to ActivationFunction

src/NeuralNetwork/ActivationFunction/ActivationFunction.h

@@ -5,12 +5,12 @@
 
 namespace NeuralNetwork
 {
-namespace TransferFunction
+namespace ActivationFunction
 {
-	class TransferFunction
+	class ActivationFunction
 	{
 		public:
-			virtual ~TransferFunction() {}
+			virtual ~ActivationFunction() {}
 			virtual float derivatedOutput(const float &input,const float &output)=0;
 			virtual float operator()(const float &x)=0;
 	};

src/NeuralNetwork/ActivationFunction/Heaviside.h

@@ -1,13 +1,13 @@
 #ifndef __TRAN_HEAVISIDE_H_
 #define  __TRAN_HEAVISIDE_H_
 
-#include "./TransferFunction.h"
+#include "./ActivationFunction.h"
 
 namespace NeuralNetwork
 {
-namespace TransferFunction
+namespace ActivationFunction
 {
-	class Heaviside: public TransferFunction
+	class Heaviside: public ActivationFunction
 	{
 		public:
 			Sigmoid(const float &lambdaP): lambda(lambdaP) {}

src/NeuralNetwork/ActivationFunction/HyperbolicTangent.h

@@ -1,13 +1,13 @@
 #ifndef __TRAN_HYPTAN_H_
 #define  __TRAN_HYPTAN_H_
 
-#include "./TransferFunction.h"
+#include "./ActivationFunction.h"
 
 namespace NeuralNetwork
 {
-namespace TransferFunction
+namespace ActivationFunction
 {
-	class HyperbolicTangent: public TransferFunction
+	class HyperbolicTangent: public ActivationFunction
 	{
 		public:
 			HyperbolicTangent(const float& lam=1):lambda(lam) {}

src/NeuralNetwork/ActivationFunction/Sigmoid.h

@@ -1,13 +1,13 @@
 #ifndef __TRAN_SIGMOID_H_
 #define  __TRAN_SIGMOID_H_
 
-#include "./StreamingTransferFunction.h"
+#include "./StreamingActivationFunction.h"
 
 namespace NeuralNetwork
 {
-namespace TransferFunction
+namespace ActivationFunction
 {
-	class Sigmoid: public StreamingTransferFunction
+	class Sigmoid: public StreamingActivationFunction
 	{
 		public:
 			Sigmoid(const float lambdaP = 0.8): lambda(lambdaP) {}

src/NeuralNetwork/ActivationFunction/StreamingActivationFunction.h

@@ -5,13 +5,13 @@
 
 #include "../../sse_mathfun.h"
 
-#include "./TransferFunction.h"
+#include "./ActivationFunction.h"
 
 namespace NeuralNetwork
 {
-namespace TransferFunction
+namespace ActivationFunction
 {
-	class StreamingTransferFunction : public TransferFunction
+	class StreamingActivationFunction : public ActivationFunction
 	{
 		public:
 			virtual float derivatedOutput(const float &input,const float &output)=0;

src/NeuralNetwork/FeedForward.cpp

@@ -34,7 +34,7 @@ FFNeuron& FFLayer::operator[](const size_t& neuron)
 
 FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwardInitializer weightInit): ACyclicNetwork(lam),layers(s.size())
 {
-	transfer = new TransferFunction::TransferFunction*[s.size()];
+	transfer = new ActivationFunction::ActivationFunction*[s.size()];
 	weights= new float**[s.size()];
 	potentials= new float*[s.size()];
 	layerSizes= new size_t[s.size()];
@@ -44,7 +44,7 @@ FeedForward::FeedForward(std::initializer_list<size_t> s, double lam, FeedForwar
 	register int prev_size=1;
 	for(int layeSize:s) // TODO rename
 	{
-		transfer[i]= new TransferFunction::Sigmoid(lam);
+		transfer[i]= new ActivationFunction::Sigmoid(lam);
 		layeSize+=1;
 		if(i==0)
 		{
@@ -106,7 +106,7 @@ FeedForward::~FeedForward()
 
 void FeedForward::solvePart(float *newSolution, register size_t begin, size_t end,size_t prevSize, float *sol,size_t layer)
 {
-	TransferFunction::StreamingTransferFunction *function=dynamic_cast<TransferFunction::StreamingTransferFunction*>(transfer[layer]);
+	ActivationFunction::StreamingActivationFunction *function=dynamic_cast<ActivationFunction::StreamingActivationFunction*>(transfer[layer]);
 	if(prevSize >=4 && function !=nullptr)
 	{
 		__m128 partialSolution;

src/NeuralNetwork/FeedForward.h

@@ -5,8 +5,8 @@
 #include "../Solution"
 #include "Network"
 
-#include "TransferFunction/Sigmoid.h"
-#include "TransferFunction/TransferFunction.h"
+#include "ActivationFunction/Sigmoid.h"
+#include "ActivationFunction/ActivationFunction.h"
 
 #include <vector>
 #include <initializer_list>
@@ -29,7 +29,7 @@ namespace NeuralNetwork
 	class FFNeuron : public Neuron
 	{
 		public:
-			inline FFNeuron(float &pot, float *w, float &outputF, float &i,float lam,TransferFunction::TransferFunction &fun):function(fun),potential(pot),weights(w),out(outputF),inputs(i),lambda(lam) { }
+			inline FFNeuron(float &pot, float *w, float &outputF, float &i,float lam,ActivationFunction::ActivationFunction &fun):function(fun),potential(pot),weights(w),out(outputF),inputs(i),lambda(lam) { }
 
 			FFNeuron() = delete;
 			FFNeuron(const FFNeuron&) = delete;
@@ -45,7 +45,7 @@ namespace NeuralNetwork
 			inline virtual float input() const override { return inputs; }
 			inline virtual float derivatedOutput() const override { return function.derivatedOutput(inputs,out); }
 		protected:
-			TransferFunction::TransferFunction &function;
+			ActivationFunction::ActivationFunction &function;
 			float &potential;
 			float *weights;
 			float &out;
@@ -57,7 +57,7 @@ namespace NeuralNetwork
 	class FFLayer: public Layer
 	{
 		public:
-			inline FFLayer(size_t s, float *p,float **w,float *out,float *in,float lam,TransferFunction::TransferFunction &fun): function(fun), layerSize(s),potentials(p),weights(w),outputs(out),inputs(in),lambda(lam) {}
+			inline FFLayer(size_t s, float *p,float **w,float *out,float *in,float lam,ActivationFunction::ActivationFunction &fun): function(fun), layerSize(s),potentials(p),weights(w),outputs(out),inputs(in),lambda(lam) {}
 			~FFLayer();
 
 			FFLayer(const FFLayer &) = delete;
@@ -66,7 +66,7 @@ namespace NeuralNetwork
 			virtual FFNeuron& operator[](const size_t& layer) override;
 			inline virtual size_t size() const override {return layerSize;};
 		protected:
-			TransferFunction::TransferFunction &function;
+			ActivationFunction::ActivationFunction &function;
 			FFNeuron **neurons=nullptr;
 			size_t layerSize;
 			float *potentials;
@@ -131,7 +131,7 @@ namespace NeuralNetwork
 			float **potentials=nullptr;
 			float **outputs=nullptr;
 			float **inputs=nullptr;
-			TransferFunction::TransferFunction **transfer=nullptr;
+			ActivationFunction::ActivationFunction **transfer=nullptr;
 			size_t *layerSizes=nullptr;
 			size_t layers;/**< Number of layers */
 	};

src/NeuralNetwork/Makefile

@@ -18,7 +18,7 @@ lib: $(LIBNAME).so $(LIBNAME).a
 $(LIBNAME).so:  $(OBJFILES)
 	$(CXX) -shared $(CXXFLAGS) $(OBJFILES) $(LINKFILES) -o $(LIBNAME).so
 
-$(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h ./TransferFunction/TransferFunction.h ./TransferFunction/Sigmoid.h
+$(LIBNAME).a: $(OBJFILES) ./Neuron.h ./Network.h ../Solution.h ../Problem.h ./ActivationFunction/ActivationFunction.h ./ActivationFunction/Sigmoid.h
 	rm -f $(LIBNAME).a  # create new library
 	ar rcv $(LIBNAME).a $(OBJFILES) $(LINKFILES)
 	ranlib $(LIBNAME).a