Fixed the evaluation order

Cluster.cs

@@ -262,20 +262,45 @@ public class Cluster : INucleus {
         UpdateState(new float3(0, 0, 0));
     }
 
-    public void UpdateState(float3 inputValue) {
+    public void UpdateState(float3 bias) {
-        float3 sum = inputValue; // new(0, 0, 0);
+        float3 sum = bias; // new(0, 0, 0);
 
-        //Applying the weight factgors
+        //Applying the weight factors
         foreach (Synapse synapse in this.synapses) {
             sum += synapse.weight * synapse.nucleus.outputValue;
         }
 
-        //this.prefab.inputs[0].UpdateState(sum);
+        //this.inputs[0].UpdateState(sum);
-        this.inputs[0].UpdateState(sum);
+        this.inputs[0].UpdateStateIsolated(sum);
+        foreach (IReceptor receptor in this.sortedNuclei) {
+            if (receptor is INucleus nucleus && nucleus != this.inputs[0])
+                nucleus.UpdateStateIsolated();
+        }
 
         UpdateResult(this.output.outputValue);
     }
 
+    public void UpdateStateIsolated() {
+        float3 bias = new(0,0,0);
+        UpdateStateIsolated(bias);
+    }
+    public void UpdateStateIsolated(float3 bias) {
+        float3 sum = bias; // new(0, 0, 0);
+
+        //Applying the weight factors
+        foreach (Synapse synapse in this.synapses) {
+            sum += synapse.weight * synapse.nucleus.outputValue;
+        }
+
+        //this.inputs[0].UpdateState(sum);
+        this.inputs[0].UpdateStateIsolated(sum);
+        foreach (IReceptor receptor in this.sortedNuclei) {
+            if (receptor is INucleus nucleus && nucleus != this.inputs[0])
+                nucleus.UpdateStateIsolated();
+        }
+        this.outputValue = this.output.outputValue;
+    }
+
     public virtual void UpdateResult(Vector3 result) {
         // float d = Vector3.Distance(result, this.outputValue);
         // if (d < 0.5f) {

INucleus.cs

@@ -20,7 +20,8 @@ public interface INucleus : IReceptor {
 
     public void UpdateState();
     public void UpdateState(float3 inputValue);
-
+    public void UpdateStateIsolated();
+    public void UpdateStateIsolated(float3 inputValue);
 
     #endregion dynamic state
 }

MemoryCell.cs

@@ -4,27 +4,34 @@ using Unity.Mathematics;
 using static Unity.Mathematics.math;
 
 [Serializable]
-public class MemoryCell : Neuron {
+public class MemoryCell : Neuron, INucleus {
 
-    public MemoryCell(ClusterPrefab cluster, string name) : base(cluster, name) {}
+    public MemoryCell(ClusterPrefab cluster, string name) : base(cluster, name) { }
+    public MemoryCell(Cluster parent, string name) : base(parent, name) { }
+    //     this.parent = parent;
+    //     this.name = name;
+    //     this.parent?.nuclei.Add(this);
+    // }
 
-    #region Parameters
+    public override IReceptor ShallowCloneTo(Cluster newParent) {
-
+        MemoryCell clone = new(newParent, this.name) {
-    // Returns the memorized value weighted by time
+            array = this.array,
-    // return lastValue * (current time - last time)
+            curve = this.curve,
-    // [SerializeField]
+            curvePreset = this.curvePreset,
-    // public bool deltaValue = false;
+            curveMax = this.curveMax,
-
+            average = this.average
-    #endregion Parameters
+        };
+        return clone;
+    }
 
     #region State
 
     private float3 _memorizedValue;
     private float _memorizedTime;
 
-    public override void UpdateState() {
+    public override void UpdateState(float3 bias) {
         // A memorycell does not have an activation function
-        float3 result = new(0, 0, 0);
+        float3 result = bias;
         int n = 0;
 
         //Applying the weight factgors
@@ -40,6 +47,32 @@ public class MemoryCell : Neuron {
         UpdateResult(result);
     }
 
+    public override void UpdateStateIsolated() {
+        float3 bias = new(0, 0, 0);
+        UpdateStateIsolated(bias);
+    }
+    public override void UpdateStateIsolated(float3 bias) {
+        // A memorycell does not have an activation function
+        float3 result = bias;
+        int n = 0;
+
+        //Applying the weight factgors
+        foreach (Synapse synapse in this.synapses) {
+            result += synapse.weight * synapse.nucleus.outputValue;
+            if (lengthsq(synapse.nucleus.outputValue) != 0)
+                n++;
+        }
+
+        if (this.average)
+            result /= n;
+
+        this.outputValue = this._memorizedValue;
+
+        // Store the result for the next time
+        this._memorizedValue = result;
+        this._memorizedTime = Time.time;
+    }
+
     public override void UpdateResult(Vector3 result) {
         // output value is the previous value
         // if (this.deltaValue) {
@@ -47,7 +80,7 @@ public class MemoryCell : Neuron {
         //     this._outputValue = this._memorizedValue * deltaTime;
         // }
         //else
-            this.outputValue = this._memorizedValue;
+        this.outputValue = this._memorizedValue;
 
         // Store the result for the next time
         this._memorizedValue = result;

Neuron.cs

@@ -282,7 +282,8 @@ public class Neuron : INucleus {
     }
 
     public virtual void UpdateState() {
-        UpdateState(new float3(0, 0, 0));
+        //UpdateState(new float3(0, 0, 0));
+        this.parent?.UpdateState();
     }
 
     public virtual void UpdateState(float3 inputValue) {
@@ -323,6 +324,47 @@ public class Neuron : INucleus {
         UpdateResult(result);
     }
 
+    public virtual void UpdateStateIsolated() {
+        UpdateStateIsolated(new float3(0, 0, 0));
+    }
+    public virtual void UpdateStateIsolated(float3 bias) {
+        float3 sum = bias;
+        int n = 0;
+
+        //Applying the weight factgors
+        foreach (Synapse synapse in this.synapses) {
+            sum += synapse.weight * synapse.nucleus.outputValue;
+
+            // Perhaps synapses should be removed when the output value goes to 0....
+            if (lengthsq(synapse.nucleus.outputValue) != 0)
+                n++;
+        }
+        if (this.average && n > 0)
+            sum /= n;
+
+        // Activation function
+        Vector3 result;
+        switch (this.curvePreset) {
+            case CurvePresets.Linear:
+                result = sum;
+                break;
+            case CurvePresets.Sqrt:
+                result = normalize(sum) * System.MathF.Sqrt(length(sum));
+                break;
+            case CurvePresets.Power:
+                result = normalize(sum) * System.MathF.Pow(length(sum), 2);
+                break;
+            case CurvePresets.Reciprocal:
+                result = normalize(sum) * (1 / length(sum));
+                break;
+            default:
+                float activatedValue = this.curve.Evaluate(length(sum));
+                result = normalize(sum) * activatedValue;
+                break;
+        }
+        this.outputValue = result;
+    }
+
     public virtual void UpdateResult(Vector3 result) {
         // float d = Vector3.Distance(result, this.outputValue);
         // if (d < 0.5f) {