using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace Zadanie1
{
    public class Perceptron
    {
        private const int size = 25;
        private double[] weights = new double[size];
        private Random rand = new Random();

        public Perceptron()
        {
            // losuję wagi weights[i] małe, bliskie 0
            for (int i = 0; i < size; i++) weights[i] = rand.NextDouble();
        }

        public double Output(double[] input) //do inputu dodac gdziekolwiek jedynkę
        {

            double suma = 0;

            for (int i = 0; i < size; i++) suma = suma + input[i] * weights[i];
            return suma;
        }

        public void Train(double[][] data, int iter)
        {
            //prog bledu; error,zeby nie uczyl sie w nieskonczonosc
            double ERROR = 0.000000001;
            double error = 1;

            //stala uczenia
            double learnConst = 0.00001;
            double index = 0;

            for (int i = 0; i < iter; i++)
            {
                foreach (double[] x in data)
                {
                    double y = x[x.Length - 1];

                    for (int l = 0; l < size; l++) weights[l] = weights[l] + learnConst * (y - Output(x)) * x[l];
                }
              
                error = CheckError(data);

                if (error < ERROR) break;
            }
        }
        //checkerror z wykładu wzór
        public double CheckError(double[][] data)
        {
            double result = 0;
            double tmp;
            double C;

            foreach (double[] x in data)
            {
                tmp = Output(x);
                C = x[25];
                result = result + Math.Pow(tmp - C, 2);
            }

            return result;
        }
    }
}

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using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Text;
using System.Threading.Tasks;


namespace Zadanie1
{
    class Perceptrons
    {
        private Perceptron[] perceptrons;
        private int N = 10;

        public Perceptrons()
        {
            perceptrons = new Perceptron[N];
            for (int i = 0; i < N; i++) perceptrons[i] = new Perceptron();
        }

        public void TrainPerceptrons()
        {
            for (int i = 0; i < N; i++)
            {
                Debug.WriteLine("Zaczynam uczyć: {0}", i);
                perceptrons[i].Train(NumbersSamples.makeDataForPercepton(i), 30000);
            }
        }

        public List<int> getCorrectPerceptrons(double[] input)
        {
            List<int> wynik = new List<int>();
            //zliczamy ilosc dobrych porownan, gdy perceptron rozpozna cyfre 
            for(int i = 0; i < N; i++)
            {
                if (perceptrons[i].Output(input) > 0) wynik.Add(i);
            }

            return wynik;
        }

    }
}