import java.io.BufferedWriter;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
public class IntNet
{
    //ArrayList of Arraylists of Neurons
    ArrayList<ArrayList<IntNeuron>> net = new ArrayList();

    public IntNet(int InputLayer, int HiddenLayers, int NeuronsPerHiddenLayer, int OutputLayer)
    {
        //add all layers
        for(int i=0 ; i<HiddenLayers+2 ; i++)
        {
            net.add(new ArrayList<IntNeuron>());
        }
        //fill outputlayer with Neurons
        for(int i=0 ; i<OutputLayer ; i++)
        {
            net.get(net.size()-1).add(new IntNeuron());
        }
        //fill hiddenlayers with Neurons
        for(int i=net.size()-2 ; i>0 ; i--)
        {
            for(int x=0 ; x<NeuronsPerHiddenLayer ; x++)
            {
                net.get(i).add(new IntNeuron());
            }
        }
        //fill inputlayer with Neurons
        for(int i=0 ; i<InputLayer ; i++)
        {
            net.get(0).add(new IntNeuron());
        }
        //connect Neurons
        for(int layer=0 ; layer<net.size()-1 ; layer++)
        {
            for(int from=0 ; from<net.get(layer).size() ; from++)
            {
                for(int to=0 ; to<net.get(layer+1).size() ; to++)
                {
                    //making the connection
                    net.get(layer).get(from).connections.add(new IntConnection(net.get(layer+1).get(to), Math.random()));
                }
            }
        }
    }

    public double sigmoid(double x)
    {
        double e = 2.7182818284;
        return (1/(1+((double)Math.pow(e, -x))));
    }

    public double[] run(double[] input)
    {
        double output[] = new double[net.get(net.size()-1).size()];
        //put input in
        for(int i=0 ; i<input.length ; i++)
        {
            net.get(0).get(i).stimulation = sigmoid(input[i]);
        }

        for(int layer=0 ; layer<net.size()-1 ; layer++)
        {
            for(int from=0 ; from<net.get(layer).size() ; from++)
            {
                for(int connection=0 ; connection<net.get(layer).get(from).connections.size() ; connection++)
                {

                    /*neuron that gets stimulated*/net.get(layer).get(from).connections.get(connection).to.stimulation =  /*aktuel stimulation of neuron that gets stimulated*/net.get(layer).get(from).connections.get(connection).to.stimulation + (/*weight*/net.get(layer).get(from).connections.get(connection).weight * /*stimulatio of the neuron that fires*/sigmoid(net.get(layer).get(from).stimulation));
                }
            }
        }
        //take output
        for(int i=0 ; i<net.get(net.size()-1).size() ; i++)
        {
            output[i] = sigmoid(net.get(net.size()-1).get(i).stimulation);

        }
        return output;
    }

    public double[] runRandomArray(int size)
    {
        return run(createArray(size));
    }

    public double[] createArray(int size)
    {
        double array[] =new double[size];
        for(int i=0 ; i<size ; i++)
        {
            array[i] = Math.random();
        }
        return array;
    }

    public boolean saveNet(){
        try {
            FileWriter fWriter = new FileWriter("C:\\Users\\Janko\\Desktop\\Programme\\AI\\test.txt");
            BufferedWriter bWriter = new BufferedWriter(fWriter);
            //ammount of layers
            bWriter.write(String.valueOf(net.size()));
            bWriter.newLine();
            //ammount of neurons in each layer
            for(int i=0 ; i<net.size() ; i++)
            {
                bWriter.write(String.valueOf(net.get(i).size()));
                bWriter.newLine();
            }
            for(int layer=0 ; layer<net.size()-1 ; layer++)
            {
                for(int from=0 ; from<net.get(layer).size() ; from++)
                {
                    for(int connection=0 ; connection<net.get(layer).get(from).connections.size() ; connection++)
                    {
                        bWriter.write(String.valueOf(net.get(layer).get(from).connections.get(connection).weight));
                        bWriter.newLine();
                    }
                }
            }
            bWriter.close();
            fWriter.close();
            return true;
        } catch (IOException e) {
            return false;
        }
    }
    /*
    public void loadNet(String path) throws NumberFormatException, IOException{
    AdjazenzListe.removeAll(AdjazenzListe);
    FileReader froi = new FileReader(path);
    BufferedReader broi = new BufferedReader(froi);
    int amountofnodes=Integer.parseInt(broi.readLine());
    for(int x=0;x!=amountofnodes;x++){
    String[] ttp = broi.readLine().split(":&quot;
    String[] edgesofnode = ttp[1].split(";&quot;
    AdjazenzListe.add(new Node(String.valueOf(ttp[0])));
    for(int y=0; y!=edgesofnode.length;y++){
    String[] currentedgedata=edgesofnode[y].split("\\|&quot;
    int currentadjacend = Integer.parseInt(currentedgedata[0].substring(1));
    int currentedgeweight = Integer.parseInt(currentedgedata[1].substring(0,currentedgedata[1].length()-1));
    AdjazenzListe.get(x).addEdge(currentadjacend, currentedgeweight);
    }
    }
    broi.close();
    froi.close();
    }
     */
}