MATH-1265

Implement "Iterable".

src/changes/changes.xml

@@ -54,6 +54,9 @@ If the output is not quite correct, check for invisible trailing spaces!
     </release>
 
     <release version="4.0" date="XXXX-XX-XX" description="">
+      <action dev="erans" type="add" issue="MATH-1265"> <!-- backported to 3.6 -->
+        "NeuronSquareMesh2D" (package "o.a.c.m.ml.neuralnet.twod") implements "Iterable".
+      </action>
       <action dev="erans" type="add" issue="MATH-1264"> <!-- backported to 3.6 -->
         "MapUtils" (package "o.a.c.m.ml.neuralnet"): Method to sort units according to distance
         from a given vector.

src/main/java/org/apache/commons/math4/ml/neuralnet/twod/NeuronSquareMesh2D.java

@@ -41,7 +41,9 @@ import org.apache.commons.math4.ml.neuralnet.SquareNeighbourhood;
  * @see org.apache.commons.math4.ml.neuralnet.sofm
  * @since 3.3
  */
-public class NeuronSquareMesh2D implements Serializable {
+public class NeuronSquareMesh2D
+    implements Iterable<Neuron>,
+               Serializable {
     /** Serial version ID */
     private static final long serialVersionUID = 1L;
     /** Underlying network. */
@@ -195,6 +197,11 @@ public class NeuronSquareMesh2D implements Serializable {
         createLinks();
     }
 
+    /** {@inheritDoc} */
+    public Iterator<Neuron> iterator() {
+        return network.iterator();
+    }
+
     /**
      * Retrieves the underlying network.
      * A reference is returned (enabling, for example, the network to be

src/test/java/org/apache/commons/math4/ml/neuralnet/twod/NeuronSquareMesh2DTest.java

@@ -845,4 +845,30 @@ public class NeuronSquareMesh2DTest {
                                              NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                              NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());
     }
+
+    @Test
+    public void testIterator() {
+        final FeatureInitializer[] initArray = { init };
+        final NeuronSquareMesh2D map = new NeuronSquareMesh2D(3, true,
+                                                              3, true,
+                                                              SquareNeighbourhood.VON_NEUMANN,
+                                                              initArray);
+        final Set<Neuron> fromMap = new HashSet<Neuron>();
+        for (Neuron n : map) {
+            fromMap.add(n);
+        }
+
+        final Network net = map.getNetwork();
+        final Set<Neuron> fromNet = new HashSet<Neuron>();
+        for (Neuron n : net) {
+            fromNet.add(n);
+        }
+
+        for (Neuron n : fromMap) {
+            Assert.assertTrue(fromNet.contains(n));
+        }
+        for (Neuron n : fromNet) {
+            Assert.assertTrue(fromMap.contains(n));
+        }
+    }
 }