package nn;

import java.util.Random;

public class Network
{
    private Neuron[] inputs = null;
    private Neuron output = null;
    private Random random = new Random();
    
    public Network(int numInput)
    {
        inputs = new Neuron[numInput];
        for (int i=0;i<numInput;i++)
        {
            inputs[i] = new Neuron(numInput);
        }
        output = new Neuron(numInput);
    }

    public boolean test(double[] input, double expected)
    {
        double result = 0;
        for (int i=0;i<input.length;i++)
        {
            result += inputs[i].f(input);
        }
        System.out.println("inp:" +input[0] +"res:"+result);
        if (result != expected)
        {
            for (int i=0;i<inputs.length;i++)
            {
                this.inputs[i].addWeight((expected - result) * (i+1));
            }
            return false;
        }
        
        return true;
    }

    public static void main(String[] args)
    {
        Network net = new Network(1);
        while (!net.test(new double[]{1},0) && !net.test(new double[]{0},1))
        {
        }
    }

    public class Neuron
    {
        private double[] weights = null;
    
        public Neuron(int numInput)
        {
            weights = new double[numInput];
            for (int i=0;i<numInput;i++)
            {
                weights[i] = random.nextDouble() - random.nextDouble();
            }
        }

        public double f(double[] input)
        {
            double returnValue = 0;
            for (int i=0;i<input.length;i++)
            {
                returnValue += input[i] * weights[i];
            }
            return returnValue;
        }

        public void addWeight(double delta)
        {
            for (int i=0;i<weights.length;i++)
            {
                weights[i] += delta;
            }
        }
    }
}