#include "../src/NeuralNetwork/FeedForward"
#include "../src/NeuralNetwork/Learning/OpticalBackPropagation"

#include <iostream>
#include <vector>

class X: public Shin::Problem
{
	public:
		X(const X& a) :Problem(a) {}
		X(const std::vector<float> &a):Problem() {data=a;}
};

int main()
{
	srand(time(NULL));
	for (int test=0;test<2;test++)
	{
		Shin::NeuralNetwork::FeedForward q({2,40,1});
		Shin::NeuralNetwork::Learning::OpticalBackPropagation b(q);
		b.setLearningCoeficient(0.1);

		std::vector<std::pair<Shin::Problem, Shin::Solution> > set;
		set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({0,0}),Shin::Solution({0})));
		set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({1,0}),Shin::Solution({1})));
		set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({1,1}),Shin::Solution({0})));
		set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({0,1}),Shin::Solution({1})));
		if(test)
		{
			std::cerr << "Testing with entropy\n";
			b.allowNoise();
		}else
		{
			std::cerr << "Testing without entropy\n";
		}
		for(int j=0;;j++)
		{
			double err=b.teachSet(set);
			if(err <0.3)
			{
//				b.setLearningCoeficient(5);
			}
			if(err <0.1)
			{
//				b.setLearningCoeficient(0.2);
			}
			if(err <0.001)
			{
				std::cerr << j << "(" << err <<"):\n";
				for(int i=0;i<4;i++)
				{
					std::cerr << "\t" << i%4 <<". FOR: [" << set[i%4].first[0] << "," <<set[i%4].first[1] << "] res: " <<
							q.solve(set[i%4].first)[0] << " should be " << set[i%4].second[0]<<"\n";
				}
			}
			if(err <0.001)
				break;
		}
	}
}