weighted relations preparation

Author: LukasMolzberger

src/main/java/network/aika/neuron/INeuron.java

@@ -896,6 +896,8 @@ public void updateSynapse(Synapse s) {
         private void updateSynapse(Synapse.State state, double sign, Synapse s) {
             updateSum(s.isRecurrent(), s.isNegative(state), sign * (s.getLimit(state) * s.getWeight(state)));
 
+            posDirSumDelta += sign * s.computeMaxRelationWeights();
+
             if(s.getInput().get().isPassiveInputNeuron() && !s.isNegative(state)) {
                 posPassiveSumDelta += sign * (!s.isNegative(state) ? (s.getLimit(state) * s.getWeight(state)) : 0.0);
             }

src/main/java/network/aika/neuron/Synapse.java

@@ -19,6 +19,7 @@
 
 import network.aika.*;
 import network.aika.Document;
+import network.aika.neuron.activation.Activation;
 import network.aika.neuron.relation.Relation;
 import network.aika.Writable;
 
@@ -301,6 +302,14 @@ public boolean isZero() {
         return Math.abs(weight) < TOLERANCE;
     }
 
+    public double computeRelationWeights(Activation.Link l) {
+        return 0;
+    }
+
+    public double computeMaxRelationWeights() {
+        return 0;
+    }
+
 
     public enum State {
         NEXT,

src/main/java/network/aika/neuron/activation/Activation.java

@@ -391,6 +391,9 @@ public State computeValueAndWeight(int round) throws RecursiveDepthExceededExcep
 
             double x = Math.min(s.getLimit(), is.s.value) * s.getWeight();
             net += x;
+
+            net += s.computeRelationWeights(is.l);
+
             if(!s.isNegative(CURRENT)) {
                 posNet += x;
             }
@@ -441,7 +444,6 @@ public State computeValueAndWeight(int round) throws RecursiveDepthExceededExcep
 
     public boolean isActiveable() {
         INeuron n = getINeuron();
-        SynapseSummary ss = n.getSynapseSummary();
 
         double net = n.getTotalBias(CURRENT);
 
@@ -462,6 +464,8 @@ public boolean isActiveable() {
 
             double x = iv * s.getWeight();
             net += x;
+
+            net += s.computeRelationWeights(l);
         }
 
         for(Synapse s: n.getPassiveInputSynapses()) {
@@ -522,6 +526,10 @@ public void computeBounds() throws RecursiveDepthExceededException {
             } else {
                 ub += Math.min(s.getLimit(), iAct.upperBound) * x;
                 lb += Math.min(s.getLimit(), iAct.lowerBound) * x;
+
+                double rlw = s.computeRelationWeights(l);
+                ub += rlw;
+                lb += rlw;
             }
         }