import java.util.Arrays;

import org.neuroph.core.data.DataSet;
import org.neuroph.core.data.DataSetRow;
import org.neuroph.nnet.MultiLayerPerceptron;
import org.neuroph.nnet.learning.MomentumBackpropagation;
import org.neuroph.util.TransferFunctionType;

public class CodeOR {

    public static void main(String[] args) {
        // TODO Auto-generated method stub

        //3.KREIRANJE TRAINING SETA
        DataSet trainigSet= DataSet.createFromFile("C:\\Users\\korisnik\\Desktop\\OR.txt",2, 1, "\t");

        //4. KREIRANJE VNM
        MultiLayerPerceptron vnm_mlp_or = new MultiLayerPerceptron(TransferFunctionType.SIGMOID, 2,3,1);

        //5. OBUCAVANJE VNM
        MomentumBackpropagation obucavanje= new MomentumBackpropagation();

        obucavanje.setMaxError(0.001);
        obucavanje.setMaxIterations(5000);
        obucavanje.setLearningRate(0.1);
        obucavanje.setMomentum(0.7);

        vnm_mlp_or.learn(trainigSet, obucavanje);

        //6. TESTIRANJE

        vnm_mlp_or.setInput(1.0,1.0);
        vnm_mlp_or.calculate();
        System.out.println("Za ulazne vrednosti 1 i 1, izlaz je "+ Arrays.toString(vnm_mlp_or.getOutput()));
        vnm_mlp_or.setInput(1.0,0.0);
        vnm_mlp_or.calculate();
        System.out.println("Za ulazne vrednosti 1 i 0, izlaz je "+ Arrays.toString(vnm_mlp_or.getOutput()));
        vnm_mlp_or.setInput(0.0,1.0);
        vnm_mlp_or.calculate();
        System.out.println("Za ulazne vrednosti 0 i 1, izlaz je "+ Arrays.toString(vnm_mlp_or.getOutput()));
        vnm_mlp_or.setInput(0.0,0.0);
        vnm_mlp_or.calculate();
        System.out.println("Za ulazne vrednosti 0 i 0, izlaz je "+ vnm_mlp_or.getOutput()[0]);

    }

}