moved type parameter from Neuron.init to createNeuron

Author: LukasMolzberger

src/main/java/network/aika/ActivationFunction.java

@@ -3,6 +3,7 @@
 
 public enum ActivationFunction {
 
+    NULL_FUNCTION(x -> 0.0),
     RECTIFIED_HYPERBOLIC_TANGENT(x -> Math.max(0.0, Math.tanh(x))),
     RECTIFIED_LINEAR_UNIT(x -> Math.max(0.0, x)),
     LIMITED_RECTIFIED_LINEAR_UNIT(x -> Math.max(0.0, Math.min(1.0, x)));

src/main/java/network/aika/Model.java

@@ -56,7 +56,6 @@ public class Model {
 
 
     protected SynapseFactory synapseFactory =  (input, output, id) -> new Synapse(input, output, id);
-    protected NeuronFactory neuronFactory = (label, outputText, type, actF) -> new INeuron(this, label, outputText, type, actF);
     protected LinkerFactory linkerFactory = (doc) -> new Linker(doc);
 
     public SearchNode.SkipSelectStep skipSelectStep = (act) -> false;
@@ -99,14 +98,6 @@ public void setSynapseFactory(SynapseFactory synapseFactory) {
         this.synapseFactory = synapseFactory;
     }
 
-    public NeuronFactory getNeuronFactory() {
-        return neuronFactory;
-    }
-
-    public void setNeuronFactory(NeuronFactory neuronFactory) {
-        this.neuronFactory = neuronFactory;
-    }
-
     public SuspensionHook getSuspensionHook() {
         return suspensionHook;
     }
@@ -135,25 +126,27 @@ public void setSkipSelectStep(SearchNode.SkipSelectStep skipSelectStep) {
     }
 
 
-    public Neuron createNeuron() {
-        return createNeuron(null);
+    public Neuron createNeuron(Type type) {
+        return createNeuron(null, type);
     }
 
 
-    public Neuron createNeuron(String label) {
-        return createNeuron(label, null);
+    public Neuron createNeuron(String label, Type type) {
+        return createNeuron(label, type, type.getDefaultActivationFunction(), null);
     }
 
 
-    public Neuron createNeuron(String label, String outputText) {
-        INeuron n = neuronFactory.createNeuron(label, outputText, INPUT, ActivationFunction.RECTIFIED_HYPERBOLIC_TANGENT);
-        return n.getProvider();
+    public Neuron createNeuron(String label, Type type, ActivationFunction actF) {
+        return new INeuron(this, label, null, type, type.getDefaultActivationFunction()).getProvider();
+    }
+
+    public Neuron createNeuron(String label, Type type, String outputText) {
+        return new INeuron(this, label, outputText, type, type.getDefaultActivationFunction()).getProvider();
     }
 
 
-    public Neuron createNeuron(String label, String outputText, Type type, ActivationFunction actF) {
-        INeuron n = neuronFactory.createNeuron(label, outputText, type, actF);
-        return n.getProvider();
+    public Neuron createNeuron(String label, Type type, ActivationFunction actF, String outputText) {
+        return new INeuron(this, label, outputText, type, actF).getProvider();
     }
 
 
@@ -287,10 +280,6 @@ public interface SynapseFactory {
     }
 
 
-    public interface NeuronFactory {
-        INeuron createNeuron(String label, String outputText, Type type, ActivationFunction actF);
-    }
-
     public interface LinkerFactory {
 
         Linker createLinker(Document doc);

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

@@ -28,10 +28,10 @@
 
 import java.io.*;
 import java.util.*;
-import java.util.function.Predicate;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
+import static network.aika.ActivationFunction.*;
 import static network.aika.neuron.INeuron.Type.EXCITATORY;
 import static network.aika.neuron.INeuron.Type.INPUT;
 import static network.aika.neuron.Synapse.State.CURRENT;
@@ -60,14 +60,24 @@ public class INeuron extends AbstractNode<Neuron> implements Comparable<INeuron>
     public static final INeuron MIN_NEURON = new INeuron();
     public static final INeuron MAX_NEURON = new INeuron();
 
-    String label;
-    Type type;
+    private String label;
+    private Type type;
 
 
     public enum Type {
-        INPUT,
-        EXCITATORY,
-        INHIBITORY
+        INPUT(NULL_FUNCTION),
+        EXCITATORY(RECTIFIED_HYPERBOLIC_TANGENT),
+        INHIBITORY(RECTIFIED_LINEAR_UNIT);
+
+        private ActivationFunction defaultActivationFunction;
+
+        Type(ActivationFunction defaultActivationFunction) {
+            this.defaultActivationFunction = defaultActivationFunction;
+        }
+
+        public ActivationFunction getDefaultActivationFunction() {
+            return defaultActivationFunction;
+        }
     }
 
 
@@ -352,6 +362,11 @@ private INeuron() {
     }
 
 
+    public INeuron(Model m, String label, Type type, ActivationFunction actF) {
+        this(m, label, null, type, actF);
+    }
+
+
     public INeuron(Model m, String label, String outputText, Type type, ActivationFunction actF) {
         this.label = label;
         this.type = type;

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

@@ -98,36 +98,11 @@ public static Neuron init(Neuron n, Builder... inputs) {
 
 
     public static Neuron init(Document doc, Neuron n, Builder... inputs) {
-        if(n.init(doc, null, null, null, getSynapseBuilders(inputs), getRelationBuilders(inputs))) {
+        if(n.init(doc, null, getSynapseBuilders(inputs), getRelationBuilders(inputs))) {
             return n;
         } else return null;
     }
 
-    /**
-     * Creates a neuron with the given bias.
-     *
-     * @param n
-     * @param bias
-     * @param inputs
-     * @return
-     */
-    public static Neuron init(Neuron n, double bias, Type type, Builder... inputs) {
-        return init(n, bias, type, getSynapseBuilders(inputs), getRelationBuilders(inputs));
-    }
-
-
-    /**
-     * Creates a neuron with the given bias.
-     *
-     * @param n
-     * @param bias
-     * @param inputs
-     * @return
-     */
-    public static Neuron init(Document doc, Neuron n, double bias, Type type, Builder... inputs) {
-        return init(doc, n, bias, null, type, getSynapseBuilders(inputs), getRelationBuilders(inputs));
-    }
-
 
     /**
      * Creates a neuron with the given bias.
@@ -137,8 +112,8 @@ public static Neuron init(Document doc, Neuron n, double bias, Type type, Builde
      * @param inputs
      * @return
      */
-    public static Neuron init(Neuron n, double bias, ActivationFunction activationFunction, Type type, Builder... inputs) {
-        return init(n, bias, activationFunction, type, getSynapseBuilders(inputs), getRelationBuilders(inputs));
+    public static Neuron init(Neuron n, double bias, Builder... inputs) {
+        return init(n, bias, getSynapseBuilders(inputs), getRelationBuilders(inputs));
     }
 
 
@@ -150,28 +125,10 @@ public static Neuron init(Neuron n, double bias, ActivationFunction activationFu
      * @param inputs
      * @return
      */
-    public static Neuron init(Document doc, Neuron n, double bias, ActivationFunction activationFunction, Type type, Builder... inputs) {
-        return init(doc, n, bias, activationFunction, type, getSynapseBuilders(inputs), getRelationBuilders(inputs));
+    public static Neuron init(Document doc, Neuron n, double bias, Builder... inputs) {
+        return init(doc, n, bias, getSynapseBuilders(inputs), getRelationBuilders(inputs));
     }
 
-    
-    /**
-     * Creates a neuron with the given bias.
-     *
-     * @param n
-     * @param bias
-     * @param synapseBuilders
-     * @param relationBuilders
-     * @return
-     */
-    public static Neuron init(Neuron n, double bias, Type type, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
-        return init(n, bias, null, type, synapseBuilders, relationBuilders);
-    }
-
-
-    public static Neuron init(Neuron n, double bias, Type type, Collection<Neuron.Builder> inputs) {
-        return init(n, bias, null, type, getSynapseBuilders(inputs), getRelationBuilders(inputs));
-    }
 
 
     /**
@@ -183,14 +140,14 @@ public static Neuron init(Neuron n, double bias, Type type, Collection<Neuron.Bu
      * @param relationBuilders
      * @return
      */
-    public static Neuron init(Neuron n, double bias, ActivationFunction activationFunction, Type type, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
-        if(n.init((Document) null, bias, activationFunction, type, synapseBuilders, relationBuilders)) return n;
+    public static Neuron init(Neuron n, double bias, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
+        if(n.init((Document) null, bias, synapseBuilders, relationBuilders)) return n;
         return null;
     }
 
 
-    public static Neuron init(Neuron n, double bias, ActivationFunction activationFunction, Type type, Collection<Neuron.Builder> inputs) {
-        if(n.init((Document) null, bias, activationFunction, type, getSynapseBuilders(inputs), getRelationBuilders(inputs))) return n;
+    public static Neuron init(Neuron n, double bias, Collection<Neuron.Builder> inputs) {
+        if(n.init((Document) null, bias, getSynapseBuilders(inputs), getRelationBuilders(inputs))) return n;
         return null;
     }
 
@@ -203,29 +160,21 @@ public static Neuron init(Neuron n, double bias, ActivationFunction activationFu
      * @param relationBuilders
      * @return
      */
-    public static Neuron init(Document doc, Neuron n, double bias, ActivationFunction activationFunction, Type type, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
-        if(n.init(doc, bias, activationFunction, type, synapseBuilders, relationBuilders)) return n;
+    public static Neuron init(Document doc, Neuron n, double bias, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
+        if(n.init(doc, bias, synapseBuilders, relationBuilders)) return n;
         return null;
     }
 
 
-    public static Neuron init(Document doc, Neuron n, double bias, ActivationFunction activationFunction, Type type, Collection<Neuron.Builder> inputs) {
-        if(n.init(doc, bias, activationFunction, type, getSynapseBuilders(inputs), getRelationBuilders(inputs))) return n;
+    public static Neuron init(Document doc, Neuron n, double bias, Collection<Neuron.Builder> inputs) {
+        if(n.init(doc, bias, getSynapseBuilders(inputs), getRelationBuilders(inputs))) return n;
         return null;
     }
 
 
-    private boolean init(Document doc, Double bias, ActivationFunction activationFunction, Type type, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
+    private boolean init(Document doc, Double bias, Collection<Synapse.Builder> synapseBuilders, Collection<Relation.Builder> relationBuilders) {
         INeuron n = get();
 
-        if(activationFunction != null) {
-            n.activationFunction = activationFunction;
-        }
-
-        if(type != null) {
-            n.type = type;
-        }
-
         if(bias != null) {
             n.setBias(bias);
         }

src/test/java/network/aika/lattice/ActivationsTest.java

@@ -32,6 +32,7 @@
 import java.util.TreeMap;
 
 import static network.aika.neuron.INeuron.Type.EXCITATORY;
+import static network.aika.neuron.INeuron.Type.INPUT;
 import static network.aika.neuron.Synapse.OUTPUT;
 import static network.aika.neuron.activation.Activation.BEGIN;
 import static network.aika.neuron.activation.Activation.END;
@@ -48,9 +49,9 @@ public class ActivationsTest {
     public void addActivationsTest() {
         Model m = new Model();
 
-        Neuron inA = m.createNeuron("A");
+        Neuron inA = m.createNeuron("A", INPUT);
 
-        Neuron pA = Neuron.init(m.createNeuron("pA"), 0.5, EXCITATORY,
+        Neuron pA = Neuron.init(m.createNeuron("pA", EXCITATORY), 0.5,
                 new Synapse.Builder()
                         .setSynapseId(0)
                         .setNeuron(inA)
@@ -83,7 +84,7 @@ public void addActivationsTest() {
     public void testGetActivationReturnsFirstFired() {
         Model m = new Model();
 
-        Neuron in = m.createNeuron("A");
+        Neuron in = m.createNeuron("A", INPUT);
         OrNode inNode = in.get().getInputNode().get();
 
         Document doc = new Document(m, "aaaaaaaaaa", 0);