NanoBrain-unitypackage/Cluster.cs

using System;
using System.Collections.Generic;
using System.Linq;
using UnityEngine;
using Unity.Mathematics;
using static Unity.Mathematics.math;

[Serializable]
public class Cluster : Nucleus {

    #region Init

    public Cluster(ClusterPrefab prefab, Cluster parent) {
        this.prefab = prefab;
        this.name = prefab.name;

        this.parent = parent;
        this.parent?.nuclei.Add(this);

        ClonePrefab();
        this.sortedNuclei = TopologicalSort(this.nuclei);
    }

    public Cluster(ClusterPrefab prefab, ClusterPrefab parent = null) {
        this.prefab = prefab;
        this.name = prefab.name;
        this.cluster = parent;

        if (this.cluster != null)
            this.cluster.nuclei.Add(this);

        ClonePrefab();
        this.sortedNuclei = TopologicalSort(this.nuclei);
    }

    private void ClonePrefab() {
        Nucleus[] prefabNuclei = this.prefab.nuclei.ToArray();
        // first clone the nuclei without their connections
        foreach (Nucleus nucleus in this.prefab.nuclei)
            nucleus.ShallowCloneTo(this);
        Nucleus[] clonedNuclei = this.nuclei.ToArray();

        // Now clone the connections
        for (int nucleusIx = 0; nucleusIx < prefabNuclei.Length; nucleusIx++) {
            Nucleus receptor = prefabNuclei[nucleusIx];
            Nucleus clonedReceptor = clonedNuclei[nucleusIx];
            if (clonedReceptor == null)
                continue;

            // Copy the receivers, which will also create the synapses
            foreach (Nucleus receiver in receptor.receivers) {
                int ix = GetNucleusIndex(prefabNuclei, receiver);
                if (ix < 0)
                    continue;

                if (clonedNuclei[ix] is not Nucleus clonedReceiver)
                    continue;

                // Find the synapse for the weight
                float weight = 1;
                foreach (Synapse synapse in receiver.synapses) {
                    // Find the weight for this synapse
                    if (synapse.nucleus == receptor) {
                        weight = synapse.weight;
                        break;
                    }
                }

                clonedReceptor.AddReceiver(clonedReceiver, weight);
            }
        }

        // Copy nucleus arrays
        for (int nucleusIx = 0; nucleusIx < prefabNuclei.Length; nucleusIx++) {
            Nucleus prefabReceptor = prefabNuclei[nucleusIx];
            if (prefabReceptor is not Nucleus prefabNucleus)
                continue;

            if (prefabNucleus.array == null || prefabNucleus.array.nuclei == null || prefabNucleus.array.nuclei.Length == 0)
                continue;

            Nucleus clonedNucleus = clonedNuclei[nucleusIx] as Nucleus;
            if (prefabNucleus == prefabNucleus.array.nuclei[0]) {
                // We clone the array only for the first entry
                NucleusArray clonedArray = new(prefabNucleus.array.nuclei.Length, "array");
                int arrayIx = 0;
                foreach (Nucleus prefabArrayNucleus in prefabNucleus.array.nuclei) {
                    int arrayNucleusIx = GetNucleusIndex(prefabNuclei, prefabArrayNucleus);
                    Nucleus clonedArrayNucleus = clonedNuclei[arrayNucleusIx];
                    clonedArray.nuclei[arrayIx] = clonedArrayNucleus;
                    arrayIx++;
                }
                clonedNucleus.array = clonedArray;
            }
            else {
                // The others will refer to the array created for the first nucleus in the array
                int firstNucleusIx = GetNucleusIndex(prefabNuclei, prefabNucleus.array.nuclei[0]);
                Nucleus clonedFirstNucleus = clonedNuclei[firstNucleusIx] as Nucleus;
                clonedNucleus.array = clonedFirstNucleus.array;
            }
        }
    }

    // Sort the nuclei in a correct evaluation order
    private List<Nucleus> TopologicalSort(List<Nucleus> nodes) {
        Dictionary<Nucleus, int> inDegree = new();
        foreach (Nucleus node in nodes)
            inDegree[node] = 0; // Initialize in-degree to zero

        // Calculate in-degrees
        foreach (Nucleus node in nodes) {
            foreach (Nucleus receiver in node.receivers)
                inDegree[receiver]++;
        }

        Queue<Nucleus> queue = new();
        foreach (Nucleus node in nodes) {
            if (inDegree[node] == 0) // Nodes with no dependencies            
                queue.Enqueue(node);
        }

        List<Nucleus> sortedOrder = new();
        while (queue.Count > 0) {
            Nucleus current = queue.Dequeue();
            sortedOrder.Add(current); // Process the node

            foreach (Nucleus receiver in current.receivers) {
                inDegree[receiver]--;
                if (inDegree[receiver] == 0) // If all dependencies resolved
                    queue.Enqueue(receiver);
            }
        }

        // Check for cycles in the graph
        if (sortedOrder.Count != nodes.Count)
            throw new InvalidOperationException("Graph is not a DAG; a cycle exists.");

        return sortedOrder;
    }

    public override Nucleus Clone() {
        //Neuron clone = new(this.cluster, this.name) {
        Neuron clone = new(this.parent, this.name) {
            array = this.array,
        };

        foreach (Synapse synapse in this.synapses) {
            Synapse clonedSynapse = clone.AddSynapse(synapse.nucleus);
            clonedSynapse.weight = synapse.weight;
        }
        foreach (Nucleus receiver in this.receivers) {
            clone.AddReceiver(receiver);
        }
        return clone;
    }

    public override Nucleus ShallowCloneTo(Cluster parent) {
        Cluster clone = new(this.prefab, parent) {
            name = this.name,
        };
        return clone;
    }

    private int GetNucleusIndex(Nucleus[] nucleiArray, Nucleus nucleus) {
        for (int i = 0; i < nucleiArray.Length; i++) {
            if (nucleus == nucleiArray[i])
                return i;
        }
        return -1;
    }

    #endregion Init

    public ClusterPrefab prefab;


    [SerializeReference]
    public List<Nucleus> nuclei = new();
    // the nuclei sorted using topological sorting
    // to ensure that the cluster is computer in the right order
    public List<Nucleus> sortedNuclei;

    public List<Nucleus> _inputs = null;
    public virtual List<Nucleus> inputs {
        get {
            if (this._inputs == null) {
                this._inputs = new();
                foreach (Nucleus receptor in this.nuclei) {
                    if (receptor is Nucleus nucleus) {
                        // inputs have no incoming synapses yet.
                        if (nucleus.synapses.Count == 0)
                            this._inputs.Add(nucleus);
                    }
                }
            }
            return this._inputs;
        }
    }

    public virtual Nucleus output {//=> this.nuclei[0] as Nucleus;
        get {
            if (this.nuclei.Count > 0)
                return this.nuclei[0];
            return null;
        }
    }

    public bool TryGetNucleus(string nucleusName, out Nucleus foundNucleus) {
        foreach (Nucleus receptor in this.nuclei) {
            if (receptor is Nucleus nucleus)
                if (nucleus.name == nucleusName) {
                    foundNucleus = nucleus;
                    return true;
                }
        }
        foundNucleus = null;
        return false;
    }

    public Nucleus GetNucleus(string nucleusName) {
        foreach (Nucleus receptor in this.nuclei) {
            if (receptor is Nucleus nucleus)
                if (nucleus.name == nucleusName)
                    return nucleus;
        }
        return null;
    }

    #region Update

    public override void UpdateStateIsolated() {
        float3 bias = new(0, 0, 0);
        UpdateStateIsolated(bias);
    }
    public override void UpdateStateIsolated(float3 bias) {
        float3 sum = bias;

        //Applying the weight factors
        foreach (Synapse synapse in this.synapses) {
            if (lengthsq(synapse.nucleus.outputValue) > 0) {
                sum += synapse.weight * synapse.nucleus.outputValue;
                this.stale = 0;
            }
        }

        this.inputs[0].UpdateStateIsolated(sum);
        foreach (Nucleus receptor in this.sortedNuclei) {
            if (receptor is Nucleus nucleus && nucleus != this.inputs[0])
                nucleus.UpdateStateIsolated();
        }
        this.outputValue = this.output.outputValue;

        UpdateNuclei();
    }

    public override void UpdateNuclei() {
        this.stale++;
        if (this.stale > 5)
            _outputValue = Vector3.zero;

        foreach (Nucleus nucleus in this.nuclei)
            nucleus.UpdateNuclei();
    }

    #endregion Update

}