yeah

tests/nn-03.cpp

@@ -0,0 +1,74 @@
+#include "../src/NeuronNetwork/Network"
+
+#include <iostream>
+class X: public Shin::NeuronNetwork::Problem
+{
+	public: X(bool x,bool y):x(x),y(y) {}
+	protected: std::vector<bool> representation() const { return std::vector<bool>({x,y}); }
+	private:
+		bool x;
+		bool y;
+};
+
+int main()
+{
+	srand(time(NULL));
+	int lm=5;
+	Shin::NeuronNetwork::FeedForwardNetwork net(2,lm,1);
+	bool x=1;
+	int prev_err=0;
+	int err=0;
+	int l;
+	int n;
+	int w;
+	int pot;
+	int wei;
+	int c=0;
+	std::cout << "\ntest 1 & 1 -" << net.solve(X(1,1))[0];
+	std::cout << "\ntest 1 & 0 -" << net.solve(X(1,0))[0];
+	std::cout << "\ntest 0 & 1 - " << net.solve(X(0,1))[0];
+	std::cout << "\ntest 0 & 0- " << net.solve(X(0,0))[0];
+	std::cout << "\n---------------------------------------";
+	do{
+		if(c%10000 ==1)
+		{
+			std::cout << "\nmixed";
+			srand(time(NULL));
+		}
+		err=0;
+		c++;
+		l=rand()%2+1;
+		n=rand()%lm;
+		w=rand()%2;
+		if(l==2)
+			n=0; 
+		pot=net[l]->operator[](n)->getPotential();
+		net[l]->operator[](n)->setPotential(pot*(rand()%21+90)/100);
+		wei=net[l]->operator[](n)->getWeight(w);
+		net[l]->operator[](n)->setWeight(w,wei*(rand()%21+90)/100);
+
+		for(int i=0;i<100;i++)
+		{
+			bool x= rand()%2;
+			bool y=rand()%2;
+			Shin::NeuronNetwork::Solution s =net.solve(X(x,y));
+			if(s[0]!= (x xor y))
+				err++;
+		}
+
+		if(err > prev_err)
+		{
+			net[l]->operator[](n)->setPotential(pot);
+			net[l]->operator[](n)->setWeight(w,wei);
+		};
+//		std::cout << "C: " << c << " err: " << err << " prev: "<<prev_err << "\n";
+		prev_err=err;
+		if(err <1)
+			x=0;
+	}while(x);
+	std::cout << "\ntest 1 & 1 -" << net.solve(X(1,1))[0];
+	std::cout << "\ntest 1 & 0 -" << net.solve(X(1,0))[0];
+	std::cout << "\ntest 0 & 1 - " << net.solve(X(0,1))[0];
+	std::cout << "\ntest 0 & 0- " << net.solve(X(0,0))[0];
+	std::cout << "\nTotaly: " << c << "\n";
+}