using System;
using UnityEngine;
using Unity.Mathematics;

namespace NanoBrain {

    /// <summary>
    /// A Synapse connects the ouput of a Neuron to another Neuron
    /// </summary>
    [Serializable]
    public class Synapse {
        /// <summary>
        /// The neuron from which input is received
        /// </summary>
        [SerializeReference]
        public Neuron neuron;

        /// <summary>
        /// The weight value to apply to the Neuron input
        /// </summary>
        public float weight;

        public bool trainable = false;
        
        /// <summary>
        /// Create a new Synapse
        /// </summary>
        /// <param name="nucleus">The neuron from which input is received</param>
        /// <param name="weight">The weight value to apply to the Neuron input</param>
        public Synapse(Neuron nucleus, float weight = 1.0f) {
            this.neuron = nucleus;
            this.weight = weight;
        }

        public virtual void BasicBackPropagation(float error, float learningRate) {
            float derivative = error;
            switch (neuron.activator) {
                case Neuron.ActivationType.Linear:
                    derivative *= 1;
                    break;
                default:
                    break;
            }
            derivative *= math.length(neuron.activation);

            float deltaWeight = learningRate * derivative;
            this.weight += deltaWeight;
        }
    }

}