using System.Collections;
using System.Collections.Generic;
using UnityEngine;

public class NeuralNetwork {
    public List<Layer> layers = new List<Layer>();
    static float sigmoid ( float x )
    {
     return 1f / (1f + Mathf.Exp(-x));
    }
    public class Layer
    {
        public int index;
        public NeuralNetwork _parentNetwork;
        public List<Neuron> neurons = new List<Neuron>();
    }
    public class Neuron{
        public Layer _parentLayer;
        public float _Value;
        public float[] weights;
        public float Value{
            get{
                //input layer
                if(_parentLayer.index==0)
                {
                    return _Value;
                }else{
                    //hidden/output layers
                    float result = 0;
                    for(int i=0;i<weights.Length;i++)
                    {
                        result+=_parentLayer._parentNetwork.layers[_parentLayer.index-1].neurons[i].Value*weights[i];//_parentLayer.neurons[i].Value*weights[i];
                    }
                    return sigmoid(result);
                }
            }
            set{
                _Value = value;
            }
        }
        public Neuron(Layer _pl)
        {
            _pl.neurons.Add(this);
            _parentLayer = _pl;
            Value = 0;
        }
    }
    public Layer input()
    {
        return layers[0];
    }
    public Layer output()
    {
        return layers[layers.Count-1];
    }
    public void SetInput(int index, float _value)
    {
        input().neurons[index].Value = _value;
    }
    public List<float> GetOutput()
    {
        Layer _l = output();
        List<float> result = new List<float>();
        foreach(Neuron n in _l.neurons)
        {
            result.Add(n.Value);
        }
        return result;
    }
    public NeuralNetwork(int[] layerCounts)
    {
        layers = new List<Layer>();
        for(int i = 0;i<layerCounts.Length;i++)
        {
            layers.Add(new Layer());
            layers[i].neurons = new List<Neuron>();
            layers[i].index = i;
            layers[i]._parentNetwork = this;
            for(int d = 0;d<layerCounts[i];d++)
            {
                Neuron n = new Neuron(layers[i]);
                if(i>0){
                    n.weights = new float[layerCounts[i-1]];
                }
            }
        }
    }
    //random mutations
    public void Mutate()
    {
        for(int i = 1;i<layers.Count;i++)
        {
            for(int d = 0; d<layers[i].neurons.Count;d++)
            {
                for(int p = 0; p<layers[i].neurons[d].weights.Length;p++)
                {
                    float r = Random.Range(0f,1f);
                    if(r<0.02f)
                    {
                        layers[i].neurons[d].weights[p] += 0.1f;
                    }else
                    if(r<0.04f)
                    {
                        layers[i].neurons[d].weights[p] *= -1;
                    }else
                    if(r<0.08f)
                    {
                        layers[i].neurons[d].weights[p] *=0.5f;
                    }
                }
            }
        }
    }
}