optimization is back in

core/src/com/mygdx/game/Log.java

@@ -15,10 +15,10 @@ public class Log {
     public static final int INFO = 1;
     public static final int DEBUG = 2;
 
-    private static int logLevel = 1;
+    private static int logLevel = 0;
 
     public static void log(int level, String msg) {
-        if (level >= logLevel) {
+        if (level <= logLevel) {
             System.out.println(msg);
         }
     }

core/src/logic/neural/Brain.java

@@ -54,6 +54,7 @@ public class Brain {
     }
 
     public float[] compute() {
+        clearCache();
         float[] res = new float[neurons[neurons.length - 1].length];
         for (int i = 0; i < neurons[neurons.length - 1].length; i++) {
             Neuron n = neurons[neurons.length - 1][i];
@@ -104,6 +105,16 @@ public class Brain {
         return res;
     }
 
+    private void clearCache() {
+        for (int i = 1; i < neurons.length; i++) {
+            for (int j = 0; j < neurons[i].length; j++) {
+                if (neurons[i][j] != null) {
+                    neurons[i][j].clearCache();
+                }
+            }
+        }
+    }
+
     public Neuron[][] getNeurons() {
         return neurons;
     }

core/src/logic/neural/Neuron.java

@@ -6,8 +6,6 @@
 package logic.neural;
 
 import com.mygdx.game.Log;
-import java.util.ArrayList;
-import java.util.Arrays;
 import java.util.logging.Level;
 import java.util.logging.Logger;
 
@@ -18,6 +16,7 @@ import java.util.logging.Logger;
 public class Neuron {
 
     private float[] weights;
+    private NeuronCache cache;
     private float bias, output;
     private boolean isInputNeuron;
     private int layer;
@@ -35,6 +34,7 @@ public class Neuron {
         } else {
             this.weights = weights;
         }
+        cache = new NeuronCache(this.weights.length);
     }
 
     private void scramble() {
@@ -61,6 +61,14 @@ public class Neuron {
         for (int i = 0; i < weights.length; i++) {
             //if(brain == null) System.out.println("BRAINS NULL"); else if(brain.getNeurons() == null) System.out.println("NEURONS NULL");
             //System.out.println(Arrays.toString(brain.getNeurons()));
+            if (cache.has(i)) {
+                try {
+                    return cache.get(i);
+                } catch (Exception ex) {
+                    // This should never happen
+                    Logger.getLogger(Neuron.class.getName()).log(Level.SEVERE, null, ex);
+                }
+            }
             Neuron n = brain.getNeurons()[layer - 1][i];
             a += n.compute() * weights[i];
         }
@@ -111,4 +119,8 @@ public class Neuron {
         this.weights = weights;
     }
 
+    public void clearCache() {
+        cache.clear();
+    }
+
 }

core/src/logic/neural/NeuronCache.java

@@ -0,0 +1,45 @@
+/*
+ * To change this license header, choose License Headers in Project Properties.
+ * To change this template file, choose Tools | Templates
+ * and open the template in the editor.
+ */
+package logic.neural;
+
+/**
+ *
+ * @author fazo
+ */
+public class NeuronCache {
+
+    private float[] cache;
+    private boolean[] validity;
+
+    public NeuronCache(int size) {
+        cache = new float[size];
+        validity = new boolean[size];
+        clear();
+    }
+
+    public void put(int index, float value) {
+        validity[index] = true;
+        cache[index] = value;
+    }
+
+    public float get(int index) throws Exception {
+        if (validity[index]) {
+            return cache[index];
+        } else {
+            throw new Exception("Value not present");
+        }
+    }
+
+    public boolean has(int index) {
+        return validity[index];
+    }
+
+    public void clear() {
+        for (int i = 0; i < cache.length; i++) {
+            validity[i] = false;
+        }
+    }
+}