#include <NeuralNetwork/FeedForward/Network.h>

#include <cassert>
#include <iostream>
#include "../include/NeuralNetwork/Learning/BackPropagation.h"
#include "../include/NeuralNetwork/Learning/QuickPropagation.h"
#include "../include/NeuralNetwork/Learning/RProp.h"
#include "../include/NeuralNetwork/Learning/CorrectionFunction/Optical.h"
#include "../include/NeuralNetwork/Learning/CorrectionFunction/ArcTangent.h"

#define LEARN(A,AR,B,BR,C,CR,D,DR,FUN,COEF,CLASS) \
({\
	srand(rand);\
	NeuralNetwork::FeedForward::Network n(2);\
	NeuralNetwork::ActivationFunction::Sigmoid a(-1);\
	n.appendLayer(2,a);\
	n.appendLayer(1,a);\
	n.randomizeWeights();\
	CLASS prop(n,FUN);\
 	prop.setLearningCoefficient(COEF);\
	prop.setBatchSize(4); \
	int error=1; int steps = 0; \
	while(error > 0 && steps <99999) {\
		steps++;\
		error=0;\
		prop.teach(A,{AR});\
		prop.teach(B,{BR});\
		prop.teach(C,{CR});\
		prop.teach(D,{DR});\
		error+=fabs(n.computeOutput(A)[0]-AR) > 0.1 ? 1:0;\
		error+=fabs(n.computeOutput(B)[0]-BR) > 0.1 ? 1:0;\
		error+=fabs(n.computeOutput(C)[0]-CR) > 0.1 ? 1:0;\
		error+=fabs(n.computeOutput(D)[0]-DR) > 0.1 ? 1:0;\
	}\
steps;\
})

int main() {
	long rand=(time(NULL));

	const float linearCoef=0.7;
	const float opticalCoef=0.11;
	const float arcTangentCoef=0.6;
	const float arcTangent=1.5;

	{
		std::cout << "XOR Linear:\n";

		std::cout << "\tBP: " <<
					 LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),0,std::vector<float>({0,1}),1,
						   std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Linear>(),linearCoef,NeuralNetwork::Learning::BackPropagation) << "\n";
		std::cout << "\tQP: " <<
				  LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),0,std::vector<float>({0,1}),1,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Linear>(),linearCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";
		std::cout << "\tRProp: " <<
				  LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),0,std::vector<float>({0,1}),1,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Linear>(),linearCoef,NeuralNetwork::Learning::RProp) << "\n";

	}
	{
		std::cout << "AND Optical:\n";

		std::cout << "\tBP: " <<
		LEARN(std::vector<float>({1,0}),0,std::vector<float>({1,1}),1,std::vector<float>({0,0}),0,std::vector<float>({0,1}),0,
			  std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::BackPropagation) << "\n";

		std::cout << "\tQP: " <<
				  LEARN(std::vector<float>({1,0}),0,std::vector<float>({1,1}),1,std::vector<float>({0,0}),0,std::vector<float>({0,1}),0,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";

		std::cout << "\tRProp: " <<
				  LEARN(std::vector<float>({1,0}),0,std::vector<float>({1,1}),1,std::vector<float>({0,0}),0,std::vector<float>({0,1}),0,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::RProp) << "\n";
	}
	{
		std::cout << "XOR Optical:\n";

		std::cout << "\tBP: " <<
		LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),1,std::vector<float>({0,1}),1,
			  std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::BackPropagation) << "\n";

		std::cout << "\tQP: " <<
				  LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),1,std::vector<float>({0,1}),1,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";

		std::cout << "\tRProp: " <<
				  LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),1,std::vector<float>({0,1}),1,
						std::make_shared<NeuralNetwork::Learning::CorrectionFunction::Optical>(),opticalCoef,NeuralNetwork::Learning::RProp) << "\n";
	}
}