using System;
using System.IO;
using System.Collections.Generic;
using UnityEngine;
#if UNITY_MATHEMATICS
using Unity.Mathematics;
using static Unity.Mathematics.math;
#endif
using NanoBrain.Unity;


namespace NanoBrain {

    /// <summary>
    /// A Cluster combines a collection of Nuclei to implement reusable behaviour
    /// </summary>
    /// A Cluster is an instantiation of a ClusterPrefab.
    /// Clusters can be nested inside other clusters.
    [Serializable]
    public class Cluster : Nucleus {
        // It may be that clusters will not be nuclei anymore in the future....

        /// <summary>
        /// The prefab used to create this cluster
        /// </summary>
        /// Cluster should always be created from prefabs
        public ClusterPrefab prefab;
        public ClusterJson json;
        public TextAsset jsonAsset;

        //[HideInInspector]

        /// <summary>
        /// The version number of this cluster instance
        /// </summary>
        /// This is used to detect changes in the prefab which require this Cluster instance to be updated
        public int version;

        /// <summary>
        /// The base name of the cluster. I don't think this is actively used at this moment
        /// </summary>
        public string baseName {
            get {
                int colonPositon = this.name.IndexOf(':');
                if (colonPositon < 0)
                    return this.name;
                return this.name[..colonPositon];
            }
        }

        /// <summary>
        /// All cluster instance of a multi-cluster
        /// </summary>
        /// A cluster is a multi-cluster when there is more than one instance.
        /// The actual instances are only created at runtime.
        /// The value instanceCount determines how many instances will be present at runtime.
        //[NonSerialized]
        [SerializeReference]
        [HideInInspector]
        public Cluster[] instances;

        /// <summary>
        /// The number of cluster instances in a multi-cluster
        /// </summary>
        /// A cluster is a multi-clsuter when there is more than one instance.
        [SerializeField]
        public uint instanceCount = 1;
        /// <summary>
        /// The mapping from things to cluster instances
        /// </summary>
        /// In a multi-cluster each instance can be used for a thing.
        /// Cluster instance may also not (yet) be mapped to a thing.
        [NonSerialized]
        public Dictionary<int, Cluster> thingClusters = new();

        /// <summary>
        /// All nuclei in this cluster
        /// </summary>
        [SerializeReference]
        [HideInInspector]
        public List<Nucleus> nuclei = new();

        #region Init

        public Cluster() {
            this.name = "Empty Cluster";
        }

        /// <summary>
        /// Instantiate a new copy of a ClusterPrefab in the given parent
        /// </summary>
        /// <param name="prefab">The prefab to use</param>
        /// <param name="parent">The cluster in which this new cluster will be placed</param>
        public Cluster(ClusterPrefab prefab, Cluster parent, uint instanceCount = 1) {
            this.prefab = prefab;
            this.version = prefab.version;
            this.name = prefab.name;

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

            if (instanceCount > 1) {
                List<Cluster> siblings = new() { this };
                for (int instanceIx = 1; instanceIx < instanceCount; instanceIx++) {
                    // Create another sibling
                    Cluster sibling = new(prefab, this) {
                        name = $"{this.baseName}: {instanceIx}",
                        parent = this.parent,
                        instanceCount = this.instanceCount,
                    };
                    siblings.Add(sibling);
                    CopyAllExternalReceivers(this, sibling, this);
                }
                Cluster[] siblingClusters = siblings.ToArray();
                foreach (Cluster sibling in siblings) {
                    sibling.instanceCount = instanceCount;
                    sibling.instances = siblingClusters;
                }

            }
        }

        /// <summary>
        /// Add a new cluster to a ClusterPrefab
        /// </summary>
        /// <param name="prefab">The prefab to copy</param>
        /// <param name="parent">The prefab in which the new copy is placed</param>
        public Cluster(ClusterPrefab prefab, ClusterPrefab parent = null) {
            this.prefab = prefab;
            this.version = prefab.version;
            this.name = prefab.name;
            if (parent != null) {
                TextAsset jsonFile = Resources.Load<TextAsset>(parent.name);
                string json = jsonFile.text;
                ClusterData clusterData = JsonUtility.FromJson<ClusterData>(json);
                //ClusterData clusterData = Cluster.Import(jsonPath);
                parent.cluster = new(clusterData);
                this.parent = parent.cluster;
            }

            ClonePrefab();
        }

        public Cluster(ClusterJson json) {
            ClusterData clusterData = JsonUtility.FromJson<ClusterData>(json.jsonFile.text);
            this.name = clusterData.name;
            // First create all neurons
            foreach (NeuronData neuronData in clusterData.neurons) {
                Neuron newNeuron = new(this, neuronData.name);
            }
            // Now create the synapses between them
            foreach (NeuronData neuronData in clusterData.neurons) {
                Neuron receiver = this.GetNeuron(neuronData.name);
                foreach (SynapseData synapseData in neuronData.synapses) {
                    Neuron sender = this.GetNeuron(synapseData.neuronName);
                    sender?.AddReceiver(receiver, synapseData.weight, synapseData.trainable);
                }
            }
        }
        public Cluster(ClusterData clusterData) {
            this.name = clusterData.name;
            // First create all neurons
            foreach (NeuronData neuronData in clusterData.neurons) {
                if (neuronData.type == Type.MemoryCell)
                    new MemoryCell(this, neuronData.name) {
                        bias = neuronData.bias,
                        combinator = neuronData.combinatorType,
                        activator = neuronData.activationType
                    };
                else
                    new Neuron(this, neuronData.name) {
                        bias = neuronData.bias,
                        combinator = neuronData.combinatorType,
                        activator = neuronData.activationType
                    };

            }
            // Now create the synapses between them
            foreach (NeuronData neuronData in clusterData.neurons) {
                Neuron receiver = this.GetNeuron(neuronData.name);
                foreach (SynapseData synapseData in neuronData.synapses) {
                    // If the synapse points to another cluster
                    if (synapseData.clusterName != this.name) {
                        // Add reference to external cluster
                        // Do we know the external cluster already?
                        Cluster extCluster = this.GetCluster(synapseData.clusterName);
                        if (extCluster == null) {
                            // if not: create new external cluster
                            Debug.Log("New ext cluster");
                            ExternalClusterData externalClusterData = clusterData.GetCluster(synapseData.clusterName);
                            ClusterPrefab extPrefab = Resources.Load(externalClusterData.prefabName) as ClusterPrefab;
                            extCluster = new(extPrefab, this, instanceCount) {
                                name = externalClusterData.name
                            };
                        }
                        // Do we have the synapse already?
                        Neuron extNeuron = extCluster.GetNeuron(synapseData.neuronName);
                        Synapse synapse = receiver.GetSynapse(extNeuron); //extCluster, synapseData.neuronName);
                        if (synapse == null) {
                            Debug.Log("new receiver for external");
                            // If not: create new synapse
                            extNeuron.AddReceiver(receiver);
                        }
                    }
                    else {
                        Neuron sender = this.GetNeuron(synapseData.neuronName);
                        sender?.AddReceiver(receiver, synapseData.weight, synapseData.trainable);
                    }
                }
            }
        }

        /// <summary>
        /// Clone a prefab.
        /// </summary>
        /// Strange that this does not take any parameters or return values.
        /// Where which the clone be found???
        private void ClonePrefab() {
            //Debug.Log($"Clone Prefab {this.prefab.name} -> {this.name}");
            if (this.prefab == null || this.prefab.cluster == null || this.prefab.cluster.nuclei == null)
                return;

            Nucleus[] prefabNuclei = this.prefab.cluster.nuclei.ToArray();

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

            // Now clone the connections
            for (int nucleusIx = 0; nucleusIx < prefabNuclei.Length; nucleusIx++) {
                Nucleus prefabNucleus = prefabNuclei[nucleusIx];
                if (prefabNucleus is not Neuron prefabNeuron)
                    continue;

                Nucleus clonedNucleus = clonedNuclei[nucleusIx];
                if (clonedNucleus == null || clonedNucleus is not Neuron clonedNeuron)
                    continue;

                foreach (Synapse prefabSynapse in prefabNeuron.synapses) {
                    Neuron synapseNeuron = prefabSynapse.neuron;
                    if (synapseNeuron.parent.prefab != null && synapseNeuron.parent.prefab != this.prefab) {
                        // Neuron is in another cluster, find the cloned cluster first
                        Cluster prefabCluster = synapseNeuron.parent;
                        Cluster clonedCluster = this.nuclei.Find(n => n.name == prefabCluster.name) as Cluster;
                        if (clonedCluster == null)
                            continue;

                        // Now find the neuron in that cloned cluster
                        int neuronIx = GetNucleusIndex(prefabCluster.nuclei, prefabSynapse.neuron.name);
                        if (neuronIx < 0)
                            // Could not find the neuron in the prefab cluster
                            continue;
                        if (clonedCluster.nuclei[neuronIx] is not Neuron clonedSender)
                            // Could not find the neuron in the cloned cluster
                            continue;

                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight, prefabSynapse.trainable);
                        //Debug.Log($"Add synapse {clonedCluster.name}.{clonedSender.name} -> {clonedNeuron.name} [{clonedSender.receivers.Count}]");
                    }
                    else {
                        int ix = GetNucleusIndex(this.prefab.cluster.nuclei, prefabSynapse.neuron);
                        if (ix < 0)
                            continue;
                        if (clonedNuclei[ix] is not Neuron clonedSender)
                            continue;

                        // Copy the receivers which will also create the synapse
                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight, prefabSynapse.trainable);
                        // Debug.Log($"Add synapse {clonedSender.name} -> {clonedNeuron.name}");
                    }
                }
            }

            foreach (Nucleus clonedNucleus in clonedNuclei) {
                if (clonedNucleus is not Cluster clonedCluster)
                    continue;

                List<Cluster> siblings = new() { clonedCluster };
                for (int instanceIx = 1; instanceIx < clonedCluster.instanceCount; instanceIx++) {
                    // Create another sibling
                    Cluster sibling = new(clonedCluster.prefab, this) {
                        name = $"{clonedCluster.baseName}: {instanceIx}",
                        parent = this.parent,
                        instanceCount = this.instanceCount,
                    };
                    siblings.Add(sibling);
                    CopyAllExternalReceivers(clonedCluster, sibling, this);
                }
                Cluster[] siblingClusters = siblings.ToArray();
                foreach (Cluster sibling in siblings)
                    sibling.instances = siblingClusters;
            }

            // Ensure that all neurons are computed to initialize bias
            foreach (Nucleus clonedNucleus in clonedNuclei) {
                if (clonedNucleus is not Cluster)
                    clonedNucleus.UpdateStateIsolated();
            }
        }

        /// \copydoc NanoBrain::Nucleus::ShallowCloneTo
        public override Nucleus ShallowCloneTo(Cluster parent) {
            // Clusters should not be cloned, but instantiated from the prefab....
            Cluster clone = new(this.prefab, parent) {
                name = this.name,
                parent = this.parent,
                instanceCount = this.instanceCount,
            };

            return clone;
        }

        private static void CopyAllExternalReceivers(Cluster sourceCluster, Cluster sibling, Cluster clonedParent) {
            for (int nucleusIx = 0; nucleusIx < sourceCluster.nuclei.Count; nucleusIx++) {
                Nucleus sourceNucleus = sourceCluster.nuclei[nucleusIx];
                if (sourceNucleus is not Neuron sourceNeuron)
                    continue;

                if (sibling.nuclei[nucleusIx] is not Neuron clonedNeuron)
                    continue;

                // copy the receivers (and thus synapses) from the source to the sibling
                foreach (Nucleus receiver in sourceNeuron.receivers) {
                    if (receiver is not Neuron receiverNeuron)
                        continue;

                    int ix = GetNucleusIndex(clonedParent.nuclei, receiver);
                    if (ix < 0 || ix >= clonedParent.nuclei.Count)
                        continue;

                    // Find the synapse for the weight
                    float weight = 1;
                    foreach (Synapse synapse in receiverNeuron.synapses) {
                        // Find the weight for this synapse
                        if (synapse.neuron == sourceNucleus) {
                            weight = synapse.weight;
                            break;
                        }
                    }

                    clonedNeuron.AddReceiver(receiver, weight);
                    // Debug.Log($"external: {receiver.name} receives from {clonedNeuron.name} {clonedNeuron.GetHashCode()}");
                }
            }

        }

        /// <summary>
        /// Get the index of a nucleus in a list of nuclei
        /// </summary>
        /// <param name="nuclei">The list of nuclei to search</param>
        /// <param name="nucleus">The nucleus to find</param>
        /// <returns>The index of the nucleus in the list or -1 when it has not been found</returns>
        public static int GetNucleusIndex(List<Nucleus> nuclei, Nucleus nucleus) {
            int i = 0;
            foreach (Nucleus nucleiElement in nuclei) {
                //for (int i = 0; i < nuclei.Length; i++) {
                if (nucleiElement == nucleus)
                    return i;
                i++;
            }
            return -1;
        }

        /// <summary>
        /// Get the index of a nucleus with the given name in a list of nuclei
        /// </summary>
        /// <param name="nuclei">The list of nuclei to search</param>
        /// <param name="nucleusName">The name of the nucleus to find</param>
        /// <returns>The index of the nucleus in the list or -1 when it has not been found</returns>
        public static int GetNucleusIndex(List<Nucleus> nuclei, string nucleusName) {
            int i = 0;
            foreach (Nucleus nucleiElement in nuclei) {
                //for (int i = 0; i < nuclei.Length; i++) {
                if (nucleiElement.name == nucleusName)
                    return i;
                i++;
            }
            return -1;
        }

        /// <summary>
        /// Initializes all trainable weights to random values
        /// </summary>
        public void InitializeRandom() {
            System.Random randomGenerator = new();
            foreach (Nucleus nucleus in this.nuclei) {
                if (nucleus is Neuron neuron) {
                    foreach (Synapse synapse in neuron.synapses) {
                        if (synapse.trainable) {
                            synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
                            // Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
                        }
                    }
                }
            }
        }

        public void GaussianAdditiveMutation(float sigma) {
            foreach (Nucleus nucleus in this.nuclei) {
                if (nucleus is Neuron neuron) {
                    foreach (Synapse synapse in neuron.synapses) {
                        if (synapse.trainable) {
                            synapse.GaussianAdditiveMutation(sigma);
                            //synapse.weight = (float)randomGenerator.NextDouble() * 2.0f - 1.0f;
                            // Debug.Log($"{neuron.name}-{synapse.neuron.name} weight = {synapse.weight}");
                        }
                    }
                }
            }
        }

        #endregion Init

        #region Cluster Array

        /// <summary>
        /// Increase the number of instances in an multi-cluster
        /// </summary>
        /// /remark Note this does not create the instances.
        /// This is only intended to be used for prefabs.
        public void AddInstance() {
            this.instanceCount++;
        }

        /// <summary>
        /// Create an new instance in a multi-cluster
        /// </summary>
        /// <param name="prefab">The prefab to use to create the new instance</param>
        /// /remark This does not change the instanceCount.
        /// It should only be used at runtime.
        public void AddInstance(ClusterPrefab prefab) {
            // Ensure siblingClusters exists
            if (this.instances == null || this.instances.Length == 0)
                this.instances = new Cluster[1] { this };

            // Prepare the new array
            int newLength = this.instances.Length + 1;
            Cluster[] newSiblings = new Cluster[newLength];

            for (int i = 0; i < newSiblings.Length - 1; i++)
                newSiblings[i] = this.instances[i];

            //Cluster newCluster = this.Clone(prefab) as Cluster;
            Cluster newCluster = new(prefab);
            string baseName = this.name;
            int colonPos = baseName.IndexOf(":");
            if (colonPos > 0)
                baseName = baseName[..colonPos];
            newCluster.name = $"{baseName}: {newLength - 1}";
            newSiblings[newLength - 1] = newCluster;

            // All siblingClusters need to user this array!
            foreach (Cluster sibling in newSiblings)
                sibling.instances = newSiblings;
        }

        /// <summary>
        /// Decrease the number of instance in a multi-cluster
        /// </summary>
        public void RemoveInstance() {
            if (instanceCount > 1)
                instanceCount--;
            else {
                // It is not clear to me why we update the siblingClusters when the 
                // instanceCount <= 1....
                if (this.instances == null || this.instances.Length <= 1)
                    return;

                // Prepare the new array
                int newLength = this.instances.Length - 1;
                Cluster[] newClusters = new Cluster[newLength];

                for (int i = 0; i < newLength; i++)
                    newClusters[i] = this.instances[i];

                Neuron.Delete(this.instances[^1]);
                this.instances = newClusters;
            }
        }

        /// <summary>
        /// Remove a mapping from a thing to a cluster such that it becomes available for new things
        /// </summary>
        /// <param name="cluster">The multi-cluster instance which not no longer be mapped</param>
        private void RemoveThingCluster(Cluster cluster) {
            List<int> keysToRemove = new();
            foreach (KeyValuePair<int, Cluster> kvp in thingClusters) {
                if (kvp.Value == cluster)
                    keysToRemove.Add(kvp.Key);
            }

            foreach (int thingId in keysToRemove)
                thingClusters.Remove(thingId);
        }


        public List<Neuron> GetAllInstances(Neuron nucleus) {
            List<Neuron> allInstances = new();

            int ix = -1;
            //foreach (Nucleus myNucleus in this.nuclei) {
            for (; ix < this.nuclei.Count; ix++) {
                if (this.nuclei[ix] == nucleus)
                    break;
            }
            if (ix == this.nuclei.Count)
                return allInstances;

            foreach (Cluster instance in this.instances) {
                List<Nucleus> otherNuclei = instance.nuclei;
                if (otherNuclei[ix] is Neuron otherNeuron)
                    allInstances.Add(otherNeuron);
            }
            return allInstances;
        }

        // public void Backpropagation(Func<Cluster, float> Observer, float target, float learningRate) {
        //     foreach (Nucleus nucleus in this.instances[0].nuclei) {
        //         if (nucleus is not Neuron neuron)
        //             continue;

        //         foreach (Synapse synapse in neuron.synapses) {
        //             List<Neuron> allSynapseNeurons = GetAllInstances(synapse.neuron);

        //             Vector3 dSSRdW = Vector3.zero;
        //             for (int clusterIx = 0; clusterIx < this.instances.Length; clusterIx++) {
        //                 Cluster clusterInstance = this.instances[clusterIx];
        //                 Neuron neuronInstance = allSynapseNeurons[clusterIx];

        //                 // Simple case, without receivers...
        //                 dSSRdW += (Vector3)(-2 * (Observer(clusterInstance) - target) * neuronInstance.activation);
        //             }
        //             synapse.weight += learningRate * dSSRdW.magnitude;
        //         }
        //     }

        // }

        #endregion ClusterArray

        /// <summary>
        /// This gives the order in which nuclei should be computed when a nucleus is updated
        /// </summary>
        [NonSerialized]
        private Dictionary<Nucleus, List<Nucleus>> _computeOrders;
        /// <summary>
        /// This gives the order in which nuclei should be computed when a nucleus is updated
        /// </summary>
        public Dictionary<Nucleus, List<Nucleus>> computeOrders {
            get {
                if (_computeOrders == null || _computeOrders.Count == 0) {
                    _computeOrders = new();
                    foreach (Nucleus nucleus in this.nuclei)
                        _computeOrders[nucleus] = TopologicalSort2(nucleus);
                }
                return _computeOrders;
            }
        }
        /// <summary>
        /// Refresh the order in which neurons should be computed
        /// </summary>
        public void RefreshComputeOrders() {
            this._computeOrders = null;
        }

        private List<Nucleus> TopologicalSort2(Nucleus startNode) {
            Dictionary<Nucleus, int> inDegree = new();
            //HashSet<Nucleus> visited = new();

            // Calculate in-degrees for all nodes reachable from the start node
            Queue<Nucleus> queue = new();
            queue.Enqueue(startNode);
            //visited.Add(startNode);
            inDegree[startNode] = 0;

            while (queue.Count > 0) {
                Nucleus current = queue.Dequeue();
                List<Nucleus> receivers = null;
                if (current is Neuron neuron)
                    receivers = neuron.receivers;
                else if (current is Cluster cluster)
                    receivers = cluster.CollectReceivers();

                foreach (Nucleus receiver in receivers) {
                    if (!inDegree.ContainsKey(receiver)) {
                        //visited.Add(receiver);
                        inDegree[receiver] = 0;
                        queue.Enqueue(receiver);
                    }
                    inDegree[receiver]++;
                }
            }

            // Perform topological sort on all reachable nodes
            queue.Clear();
            foreach (Nucleus node in inDegree.Keys) {
                if (inDegree[node] == 0)
                    queue.Enqueue(node);
            }

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

                List<Nucleus> receivers = null;
                if (current is Neuron neuron)
                    receivers = neuron.receivers;
                else if (current is Cluster cluster)
                    receivers = cluster.CollectReceivers();

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

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

            return sortedOrder;
        }

        /// <summary>
        /// The first nucleus in a cluster is the default output
        /// </summary>
        public virtual Neuron defaultOutput {//=> this.nuclei[0] as Nucleus;
            get {
                if (this.nuclei != null && this.nuclei.Count > 0)
                    return this.nuclei[0] as Neuron;
                return null;
            }
        }

        /// <summary>
        /// The neurons without outgoing connections
        /// </summary>
        /// These neurons can potentially be connected to neurons in other clusters
        [NonSerialized]
        protected List<Neuron> _outputs = null;
        /// <summary>
        /// The neurons without outgoing connections
        /// </summary>
        /// These neurons can potentially be connected to neurons in other clusters
        public List<Neuron> outputs {
            get {
                if (this._outputs == null || this._outputs.Count == 0) {
                    this._outputs = new();
                    if (this.nuclei == null)
                        return this._outputs;

                    foreach (Nucleus nucleus in this.nuclei) {
                        if (nucleus is Neuron neuron && neuron.receivers.Count == 0)
                            this._outputs.Add(neuron);
                    }
                }
                return this._outputs;
            }
        }
        /// <summary>
        /// Reset the list of outputs such that they will be re-determined
        /// </summary>
        public void RefreshOutputs() {
            this._outputs = null;
        }

        /// <summary>
        /// Try to find a nucleus in this cluster
        /// </summary>
        /// <param name="nucleusName">The name of the nucleus to find</param>
        /// <param name="foundNucleus">The found nucleus or null if it is not found</param>
        /// <returns>True when the nucleus is found, false otherwise</returns>
        public bool TryGetNucleus(string nucleusName, out Nucleus foundNucleus) {
            foreach (Nucleus receptor in this.nuclei) {
                if (receptor is Nucleus nucleus)
                    if (nucleus.name == nucleusName) {
                        // if (nucleus is Cluster cluster)
                        //     cluster.CheckInstances();
                        foundNucleus = nucleus;
                        return true;
                    }
            }
            foundNucleus = null;
            return false;
        }

        /// <summary>
        /// Get a neuron in this cluster
        /// </summary>
        /// <param name="neuronName">The name of the neuron to find</param>
        /// <returns>The found neuron or null when it is not found</returns>
        public Neuron GetNeuron(string neuronName) {
            if (this.nuclei == null)
                return null;

            foreach (Nucleus nucleus in this.nuclei) {
                if (nucleus is Neuron neuron && neuron.name == neuronName)
                    return neuron;
            }
            return null;
        }

        /// <summary>
        /// Get a subcluster in this cluster
        /// </summary>
        /// <param name="clusterName">The name of the cluster to find</param>
        /// <returns>The found cluster or null when it is not found</returns>
        public Cluster GetCluster(string clusterName) {
            int dotPosition = clusterName.IndexOf('.');
            if (dotPosition >= 0) {
                string clusterBaseName = clusterName[..dotPosition];
                string clusterName0 = clusterBaseName + ": 0";
                foreach (Nucleus nucleus in this.nuclei) {
                    if (nucleus is Cluster cluster) {
                        if (cluster.name == clusterBaseName || cluster.name == clusterName0) {
                            // cluster.CheckInstances();
                            string subNucleusName = clusterName[(dotPosition + 1)..];
                            return cluster.GetCluster(subNucleusName);
                        }
                    }
                }
                return null;
            }
            else {
                string nucleusName0 = clusterName + ": 0";
                foreach (Nucleus nucleus in this.nuclei) {
                    if (nucleus is Cluster cluster) {
                        if (nucleus.name == clusterName || nucleus.name == nucleusName0) {
                            // cluster.CheckInstances();
                            return cluster;
                        }
                    }
                }
                return null;
            }
        }

        /// <summary>
        /// Get a neuron in an instance of a multi-cluster
        /// </summary>
        /// <param name="thingId">The id of the thing mapped to the cluster instance</param>
        /// <param name="neuronName">The name of the neuron to find</param>
        /// <param name="thingName">The name of the thing mapped to the cluster instance</param>
        /// <returns>The found neuron or null when it is not found</returns>
        /// The cluster instance mapped to the thing will be neuron.parent if a neuron is found.
        public Neuron GetNeuron(int thingId, string neuronName, string thingName = null) {
            if (this.instances == null || this.instances.Length <= 1)
                return this.GetNeuron(neuronName);

            // See if we are already using a cluster for thingId
            thingClusters ??= new();
            if (thingClusters.TryGetValue(thingId, out Cluster cluster))
                return cluster.GetNeuron(neuronName);

            // Find the cluster with the lowest value neuron
            Neuron lowestNeuron = null;
            foreach (Cluster sibling in this.instances) {
                Neuron neuron = sibling.GetNeuron(neuronName);
                if (lowestNeuron == null || neuron.outputMagnitude < lowestNeuron.outputMagnitude)
                    lowestNeuron = neuron;
            }
            Cluster selectedCluster = lowestNeuron.parent;
            RemoveThingCluster(selectedCluster);
            selectedCluster.name = baseName + ": " + thingName;
            thingClusters[thingId] = selectedCluster;
            return lowestNeuron;
        }

        /// <summary>
        /// Delete a nucleus from this clsuter
        /// </summary>
        /// <param name="nucleus">The nucleus to delete</param>
        /// <returns>True if a nucleus was deleted, false if the nucleus could not be found</returns>
        public bool DeleteNucleus(Nucleus nucleus) {
            if (this.nuclei.Contains(nucleus) == false) {
                // Try to find the nucleus by name
                if (TryGetNucleus(nucleus.name, out nucleus) == false)
                    return false;
            }

            Neuron.Delete(nucleus);
            //int nucleusIx = this.nuclei.IndexOf(nucleus);
            this.nuclei.Remove(nucleus);
            //this.prefab.cluster.nuclei.RemoveAt(nucleusIx);
            RefreshOutputs();

            return true;
        }

        #region Receivers

        /// <summary>
        /// Collect all receiving nuclei of signals from this cluster
        /// </summary>
        /// <param name="removeDuplicates">Ensure that a receiver is only listed once in the result</param>
        /// <returns>The list of receivers</returns>
        public virtual List<Nucleus> CollectReceivers(bool removeDuplicates = false) {
            List<Nucleus> receivers = new();
            foreach (Nucleus outputNucleus in this.nuclei) {
                if (outputNucleus is not Neuron output)
                    continue;

                // Debug.Log($"output {this.name} {outputNucleus.name}");
                foreach (Nucleus receiver in output.receivers) {
                    // Debug.Log($"output    {receiver.name}");
                    // Only add receivers outside this cluster                    
                    if (receiver.parent.prefab != this.prefab) {
                        if (removeDuplicates == false || receivers.Contains(receiver) == false)
                            // Debug.Log($"   YES");
                            receivers.Add(receiver);
                    }
                }
            }
            return receivers;
        }

        /// <summary>
        /// Collect all synapses of senders in another cluster of signals to this cluster
        /// </summary>
        /// <param name="otherCluster">The other cluster with sending neurons</param>
        /// <returns>A list of synapses to the neurons in the other clusters</returns>
        public List<Synapse> CollectSynapsesTo(Cluster otherCluster) {
            List<Synapse> collectedSynapses = new();

            foreach (Nucleus nucleus in this.nuclei) {
                if (nucleus is not Neuron neuron)
                    continue;
                foreach (Synapse synapse in neuron.synapses) {
                    if (synapse.neuron.parent == otherCluster)
                        collectedSynapses.Add(synapse);
                }
            }
            return collectedSynapses;
        }

        #endregion Receivers

        #region Update

        /// <summary>
        /// Update the state of the nucleus and all nuclei receiving from it
        /// </summary>
        /// <param name="startNucleus">The nucleus to start updating</param>
        public void UpdateFromNucleus(Nucleus startNucleus) {
            // no bias+synapse input state calculation for now...

            if (this.computeOrders.ContainsKey(startNucleus) == false) {
                Debug.LogError($"{this.name} compute orders does not contain an order for {startNucleus.name}");
                return;
            }

            List<Nucleus> computeOrder = this.computeOrders[startNucleus];
            foreach (Nucleus nucleus in computeOrder) {
                if (nucleus is Cluster)
                    continue;

                nucleus.UpdateStateIsolated();
                if (nucleus is Neuron neuron) {
                    foreach (Nucleus receiver in neuron.receivers) {
                        if (receiver.parent != this) {
                            //Debug.Log($"   External: {receiver.parent.name}.{receiver.name}");
                            receiver.parent.UpdateFromNucleus(receiver);
                        }
                    }
                }
            }
        }

        /// \copydoc NanoBrain::Nucleus::UpdateStateIsolated
        public override void UpdateStateIsolated() {
            throw new Exception("Cluster should not be updated!");
        }

        #endregion Update

        /// <summary>
        /// Recalculate derived properties
        /// </summary>
        /// This can be used to recalculate derived properties after the set of nuclei has been changed
        public void Refresh() {
            Cleanup();
            // This should not be needed, but somehow somewhere the parent is changed...
            foreach (Nucleus nucleus in this.nuclei) {
                nucleus.parent = this;
            }
            RefreshOutputs();
            RefreshComputeOrders();
        }

        public void Cleanup() {
            foreach (Nucleus nucleus in this.nuclei.ToArray()) {
                if (nucleus is not Cluster cluster)
                    continue;
                List<Nucleus> receivers = cluster.CollectReceivers();
                //Debug.Log($"cluster receiver count = {receivers.Count}");
                if (receivers.Count == 0)
                    this.nuclei.Remove(nucleus);
            }
        }

        #region Serialization

        public void Export(string path) {
            ClusterData data = new(this); //this.ToJSON();
            string json = JsonUtility.ToJson(data, prettyPrint: true);

            // Debug.Log($"Exporting json to {path}");
            File.WriteAllText(path, json);
        }

        public static ClusterData Import(string path) {
            string json = File.ReadAllText(path);
            // Debug.Log($"Importing json from {path}");
            return JsonUtility.FromJson<ClusterData>(json);
        }

        #endregion
    }

    [Serializable]
    public class ClusterData {
        public string name;
        public List<NeuronData> neurons = new();
        public List<ExternalClusterData> clusters = new();

        public ClusterData(Cluster cluster) {
            this.name = cluster.name;
            foreach (Nucleus nucleus in cluster.nuclei) {
                if (nucleus is Neuron neuron) {
                    NeuronData neuronData = new(neuron);
                    this.neurons.Add(neuronData);
                    foreach (Synapse synapse in neuron.synapses) {
                        if (synapse.neuron.parent.name != cluster.name) {
                            ExternalClusterData clusterData = new(synapse.neuron.parent);
                            if (GetCluster(clusterData.name) == null) {
                                //if (this.clusters.Find(data => data.name == clusterData.name) == null) {
                                this.clusters.Add(clusterData);
                                //Debug.Log("Add cluster");
                            }
                        }
                    }
                }
            }
        }

        public ExternalClusterData GetCluster(string clusterName) {
            foreach (ExternalClusterData cluster in this.clusters) {
                if (cluster.name == clusterName)
                    return cluster;
            }
            return null;
        }
    }

    [Serializable]
    public class ExternalClusterData {
        public string name;
        public string prefabName;
        public uint instanceCount;

        public ExternalClusterData(Cluster cluster) {
            this.name = cluster.name;
            this.prefabName = cluster.prefab.name;
            this.instanceCount = (uint)cluster.instanceCount;
        }
    }
}