Prepare for spherical average

Assets/NanoBrain/LinearAlgebra/src/Spherical.cs

@@ -1,4 +1,6 @@
 using System;
+using System.Collections.Generic;
+
 #if UNITY_5_3_OR_NEWER
 using Vector3 = UnityEngine.Vector3;
 #endif
@@ -137,6 +139,19 @@ namespace LinearAlgebra {
             return r;
         }
 
+        public static Spherical operator *(Spherical v, float d) {
+            Spherical r = new(v.distance * d, v.direction);
+            return r;
+        }
+
+        public static bool operator ==(Spherical v1, Spherical v2) {
+            return (v1.distance == v2.distance && v1.direction == v2.direction);
+        }
+
+        public static bool operator !=(Spherical v1, Spherical v2) {
+            return (v1.distance != v2.distance || v1.direction != v2.direction);
+        }
+
         public static float Distance(Spherical v1, Spherical v2) {
             // Convert degrees to radians
             float thetaARadians = v1.direction.horizontal.inRadians;
@@ -162,5 +177,37 @@ namespace LinearAlgebra {
 
             return distance;
         }
+
+        public static Spherical Average(List<Spherical> vectors) {
+            float sumSinPhiCosTheta = 0.0f;
+            float sumSinPhiSinTheta = 0.0f;
+            float sumCosPhi = 0.0f;
+
+            int n = vectors.Count;
+
+            // Step 1: Accumulate sine and cosine components
+            foreach(Spherical v in vectors) {
+                float sinHorizontal = AngleFloat.Sin(v.direction.horizontal);
+                sumSinPhiCosTheta += v.distance * sinHorizontal * AngleFloat.Cos(v.direction.vertical);
+                sumSinPhiSinTheta += v.distance * sinHorizontal * AngleFloat.Sin(v.direction.vertical);
+                sumCosPhi += v.distance * AngleFloat.Cos(v.direction.horizontal);
+            }
+
+            // Step 2: Calculate average components
+            float avgSinPhiCosTheta = sumSinPhiCosTheta / n;
+            float avgSinPhiSinTheta = sumSinPhiSinTheta / n;
+            float avgCosPhi = sumCosPhi / n;
+
+            // Step 3: Calculate the magnitude of the average vector
+            float rAvg = MathF.Sqrt(avgSinPhiCosTheta * avgSinPhiCosTheta +
+                                 avgSinPhiSinTheta * avgSinPhiSinTheta +
+                                 avgCosPhi * avgCosPhi);
+
+            // Step 4: Calculate average angles
+            AngleFloat horizontalAvg = AngleFloat.Acos(avgCosPhi / rAvg); // Handle rAvg != 0 case
+            AngleFloat verticalAvg = AngleFloat.Atan2(avgSinPhiSinTheta, avgSinPhiCosTheta);
+
+            return new Spherical(rAvg, new Direction(horizontalAvg, verticalAvg));
+        }
     }
 }

Assets/NanoBrain/Neuroid.cs

@@ -1,3 +1,4 @@
+using System.Collections.Generic;
 using UnityEngine;
 using LinearAlgebra;
 
@@ -73,7 +74,7 @@ public class Neuroid : Nucleus {
         UpdateState();
     }
 
-    public virtual void UpdateState() {
+    public override void UpdateState() {
         Vector3 resultVector = Vector3.zero;
         foreach (Synapse synapse in this.synapses) {
             Nucleus synapseNucleus = synapse.nucleus;
@@ -93,18 +94,23 @@ public class Neuroid : Nucleus {
             resultVector /= this.synapses.Count;
 
         Spherical result = Spherical.FromVector3(resultVector);
-        float d = Spherical.Distance(result, this.outputValue);
-        if (d < 0.1f) {
-            //Debug.Log($"insignificant update: {d}");
-            return;
-        }
 
-        this.outputValue = result;
+        // List<Spherical> vectors = new();
+        // foreach (Synapse synapse in this.synapses) {
+        //     if (synapse.nucleus.isSleeping)
+        //         continue;
+            
+        //     vectors.Add(synapse.nucleus.outputValue);
+        // }
+        // Spherical result2 = Spherical.Average(vectors);
+        // if (average == false)
+        //     result2 *= vectors.Count;
 
-        foreach (Receiver receiver in this.receivers) {
+        // if (result2 != result)
-            if (receiver.nucleus is Neuroid neuroid)
+        //     Debug.Log($"update error {result2} != {result}");
-                neuroid.SetInput(this);
+
-        }
+        UpdateResult(result);
+  
     }
 
 }

Assets/NanoBrain/Nucleus.cs

@@ -151,6 +151,20 @@ public class Nucleus {
         synapses.Add(newSynapse);
     }
 
+    public virtual void UpdateState() { }
+
+    public void UpdateResult(Spherical result) {
+        float d = Spherical.Distance(result, this.outputValue);
+        if (d < 0.1f) {
+            //Debug.Log($"insignificant update: {d}");
+            return;
+        }
+
+        this.outputValue = result;
+        foreach (Receiver receiver in this.receivers)
+            receiver.nucleus.UpdateState();
+
+    }
 }
 
 [System.Serializable]

Assets/NanoBrain/Perceptoid.cs

@@ -74,19 +74,9 @@ public class Perceptoid : Neuroid {
         this.receivers = new();
     }
 
-    public void UpdateState(int thingId, Spherical receptorValue) {
+    public override void UpdateState() {
-        this.thingId = thingId;
+        Spherical result = this.receptor.localPosition;
-        Spherical result = receptorValue;
+        UpdateResult(result);
-
-        float d = Spherical.Distance(result, this.outputValue);
-        if (d < 0.1f) {
-            //Debug.Log($"insignificant update: {d}");
-            return;
-        }
-        this.outputValue = result;
-        foreach (Receiver receiver in this.receivers)
-            if (receiver.nucleus is Neuroid neuroid)
-                neuroid.SetInput(this);
     }
 
 

Assets/NanoBrain/Receptor.cs

@@ -87,6 +87,7 @@ public class Receptor {
             return;
         }
         // Debug.Log($"Stimulus {thingType} {thingId} {selectedPerceptoid.name}");
-        selectedPerceptoid.UpdateState(thingId, this.localPosition);
+        selectedPerceptoid.thingId = thingId;
+        selectedPerceptoid.UpdateState();
     }
 }