modified las namespace errors

src/NeuralNetwork/FeedForward.cpp

@@ -192,7 +192,7 @@ Shin::Solution FeedForward::solve(const Shin::Problem& p)
 		prevSize=layerSizes[i];
 		sol=newSolution;
 	}
-	Solution ret;
+	Shin::Solution ret;
 	for(size_t i=1;i<prevSize;i++)
 	{
 		ret.push_back(sol[i]);

src/NeuralNetwork/FeedForward.h

@@ -102,7 +102,7 @@ namespace NeuralNetwork
 			 * @param lam is parametr for TransferFunction
 			 * @param weightInit is weight initializer function
 			 */
-			FeedForward(std::initializer_list<size_t> s, double lam=Shin::NeuralNetwork::lambda,
+			FeedForward(std::initializer_list<size_t> s, double lam=NeuralNetwork::lambda,
 			FeedForwardInitializer weightInit=
 					[](const size_t&, const size_t &, const size_t &)->float{ return 1.0-((float)(rand()%2001))/1000.0;}
 			);
@@ -120,7 +120,7 @@ namespace NeuralNetwork
 			/**
 			 * @brief computes output Solution from input Problem
 			 */
-			virtual Solution solve(const Problem& p) override;
+			virtual Shin::Solution solve(const Shin::Problem& p) override;
 			virtual size_t size() const override { return layers;};
 			virtual FFLayer& operator[](const size_t& l) override;
 		protected:

src/NeuralNetwork/Learning/BackPropagation.cpp

@@ -1,6 +1,6 @@
 #include "./BackPropagation"
 
-Shin::NeuralNetwork::Learning::BackPropagation::~BackPropagation()
+NeuralNetwork::Learning::BackPropagation::~BackPropagation()
 {
 	if(deltas!=nullptr)
 	{
@@ -10,7 +10,7 @@ Shin::NeuralNetwork::Learning::BackPropagation::~BackPropagation()
 	delete[] deltas;
 }
 
-void Shin::NeuralNetwork::Learning::BackPropagation::propagate(const Shin::Solution& expectation)
+void NeuralNetwork::Learning::BackPropagation::propagate(const Shin::Solution& expectation)
 {
 
 	if(deltas==nullptr)
@@ -87,12 +87,12 @@ void Shin::NeuralNetwork::Learning::BackPropagation::propagate(const Shin::Solut
 }
 
 
-float Shin::NeuralNetwork::Learning::BackPropagation::teach(const Shin::Problem& p, const Shin::Solution& solution)
+float NeuralNetwork::Learning::BackPropagation::teach(const Shin::Problem& p, const Shin::Solution& solution)
 {
 	Shin::Solution a=network.solve(p);
 	double error=calculateError(solution,a);
 
-	Solution s;
+	Shin::Solution s;
 	if(noise)
 	{
 		for(size_t i=0;i<solution.size();i++)

src/NeuralNetwork/Learning/BackPropagation.h

@@ -21,8 +21,6 @@
  * 
  */
 
-namespace Shin
-{
 namespace NeuralNetwork
 {
 namespace Learning
@@ -33,11 +31,11 @@ namespace Learning
 			BackPropagation(FeedForward &n): Learning(), network(n) {}
 			virtual ~BackPropagation();
 
-			BackPropagation(const Shin::NeuralNetwork::Learning::BackPropagation&) =delete;
-			BackPropagation operator=(const Shin::NeuralNetwork::Learning::BackPropagation&) =delete;
+			BackPropagation(const NeuralNetwork::Learning::BackPropagation&) =delete;
+			BackPropagation operator=(const NeuralNetwork::Learning::BackPropagation&) =delete;
 
-			float teach(const Problem &p,const Solution &solution);
-			virtual void propagate(const Solution& expectation);
+			float teach(const Shin::Problem &p,const Shin::Solution &solution);
+			virtual void propagate(const Shin::Solution& expectation);
 
 		protected:
 			FeedForward &network;
@@ -47,5 +45,4 @@ namespace Learning
 	};
 }
 }
-}
 #endif

src/NeuralNetwork/Learning/Learning.cpp

@@ -1,6 +1,6 @@
 #include "Learning.h"
 
-float Shin::NeuralNetwork::Learning::Learning::calculateError(const Shin::Solution& expectation, const Shin::Solution& solution)
+float NeuralNetwork::Learning::Learning::calculateError(const Shin::Solution& expectation, const Shin::Solution& solution)
 {
 	register float a=0;
 	for (size_t i=0;i<expectation.size();i++)
@@ -10,7 +10,7 @@ float Shin::NeuralNetwork::Learning::Learning::calculateError(const Shin::Soluti
 	return a;
 }
 
-float Shin::NeuralNetwork::Learning::Learning::teachSet(const std::vector<std::pair<Shin::Problem,Shin::Solution>> &set)
+float NeuralNetwork::Learning::Learning::teachSet(const std::vector<std::pair<Shin::Problem,Shin::Solution>> &set)
 {
 	double error=0;
 	for (register size_t i=0;i<set.size();i++)

src/NeuralNetwork/Learning/Learning.h

@@ -6,8 +6,6 @@
 #include "../../Solution.h"
 #include "../FeedForward.h"
 
-namespace Shin
-{
 namespace NeuralNetwork
 {
 namespace Learning
@@ -28,9 +26,9 @@ namespace Learning
 			inline virtual void disableNoise() final {noise=0;}
 			inline virtual void setNoiseSize(const unsigned& milipercents) final { noiseSize=milipercents; }
 
-			float calculateError(const Solution &expectation,const Solution &solution);
-			virtual float teach(const Problem &p,const Solution &solution)=0;
-			virtual float teachSet(const std::vector<std::pair<Problem,Solution>> &set) final;
+			float calculateError(const Shin::Solution &expectation,const Shin::Solution &solution);
+			virtual float teach(const Shin::Problem &p,const Shin::Solution &solution)=0;
+			virtual float teachSet(const std::vector<std::pair<Shin::Problem,Shin::Solution>> &set) final;
 
 		protected:
 			float learningCoeficient=LearningCoeficient;
@@ -40,5 +38,4 @@ namespace Learning
 	};
 }
 }
-}
 #endif

src/NeuralNetwork/Learning/OpticalBackPropagation.cpp

@@ -1,8 +0,0 @@
-#include "./OpticalBackPropagation"
-
-float Shin::NeuralNetwork::Learning::OpticalBackPropagation::correction(const float&  expected, const float& computed)
-{
-	register float tmp=(expected-computed);
-	register float ret=1+exp(tmp*tmp);
-	return tmp < 0? -ret:ret;
-}

src/NeuralNetwork/Learning/OpticalBackPropagation.h

@@ -8,8 +8,6 @@
  * http://proceedings.informingscience.org/InSITE2005/P106Otai.pdf
  */
 
-namespace Shin
-{
 namespace NeuralNetwork
 {
 namespace Learning
@@ -19,9 +17,13 @@ namespace Learning
 		public:
 			inline OpticalBackPropagation(FeedForward &n): BackPropagation(n) {}
 		protected:
-			virtual float correction(const float&  expected, const float& computed) override;
+			virtual float correction(const float&  expected, const float& computed) override
+			{
+				register float tmp=(expected-computed);
+				register float ret=1+exp(tmp*tmp);
+				return tmp < 0? -ret:ret;
+			};
 	};
 }
 }
-}
 #endif

src/NeuralNetwork/Makefile

@@ -1,6 +1,6 @@
 OBJFILES=\
 	FeedForward.o\
-	Learning/Learning.o Learning/BackPropagation.o Learning/OpticalBackPropagation.o ../sse_mathfun.o
+	Learning/Learning.o Learning/BackPropagation.o ../sse_mathfun.o
 
 LINKFILES=
 

src/NeuralNetwork/Network.h

@@ -62,7 +62,7 @@ namespace NeuralNetwork
 			 * @param p is a Problem to be solved
 			 * @returns Solution of Network for Problem
 			 */
-			virtual Solution solve(const Problem&p)=0;
+			virtual Shin::Solution solve(const Shin::Problem&p)=0;
 
 			/**
 			 * @brief Getter of layer