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Java example source code file (NeuronSquareMesh2DTest.java)

This example Java source code file (NeuronSquareMesh2DTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

bytearrayinputstream, bytearrayoutputstream, classnotfoundexception, collection, featureinitializer, hashset, ioexception, network, neuronsquaremesh2d, neuronsquaremesh2dtest, objectinputstream, objectoutputstream, outofrangeexception, test, util

The NeuronSquareMesh2DTest.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.commons.math3.ml.neuralnet.twod;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.util.Collection;
import java.util.Set;
import java.util.HashSet;

import org.apache.commons.math3.exception.NumberIsTooSmallException;
import org.apache.commons.math3.exception.OutOfRangeException;
import org.apache.commons.math3.ml.neuralnet.FeatureInitializer;
import org.apache.commons.math3.ml.neuralnet.FeatureInitializerFactory;
import org.apache.commons.math3.ml.neuralnet.Network;
import org.apache.commons.math3.ml.neuralnet.Neuron;
import org.apache.commons.math3.ml.neuralnet.SquareNeighbourhood;
import org.junit.Assert;
import org.junit.Test;

/**
 * Tests for {@link NeuronSquareMesh2D} and {@link Network} functionality for
 * a two-dimensional network.
 */
public class NeuronSquareMesh2DTest {
    final FeatureInitializer init = FeatureInitializerFactory.uniform(0, 2);

    @Test(expected=NumberIsTooSmallException.class)
    public void testMinimalNetworkSize1() {
        final FeatureInitializer[] initArray = { init };

        new NeuronSquareMesh2D(1, false,
                               2, false,
                               SquareNeighbourhood.VON_NEUMANN,
                               initArray);
    }

    @Test(expected=NumberIsTooSmallException.class)
    public void testMinimalNetworkSize2() {
        final FeatureInitializer[] initArray = { init };

        new NeuronSquareMesh2D(2, false,
                               0, false,
                               SquareNeighbourhood.VON_NEUMANN,
                               initArray);
    }

    @Test
    public void testGetFeaturesSize() {
        final FeatureInitializer[] initArray = { init, init, init };

        final Network net = new NeuronSquareMesh2D(2, false,
                                                   2, false,
                                                   SquareNeighbourhood.VON_NEUMANN,
                                                   initArray).getNetwork();
        Assert.assertEquals(3, net.getFeaturesSize());
    }


    /*
     * Test assumes that the network is
     *
     *  0-----1
     *  |     |
     *  |     |
     *  2-----3
     */
    @Test
    public void test2x2Network() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(2, false,
                                                   2, false,
                                                   SquareNeighbourhood.VON_NEUMANN,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // Neurons 0 and 3.
        for (long id : new long[] { 0, 3 }) {
            neighbours = net.getNeighbours(net.getNeuron(id));
            for (long nId : new long[] { 1, 2 }) {
                Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
            }
            // Ensures that no other neurons is in the neihbourhood set.
            Assert.assertEquals(2, neighbours.size());
        }

        // Neurons 1 and 2.
        for (long id : new long[] { 1, 2 }) {
            neighbours = net.getNeighbours(net.getNeuron(id));
            for (long nId : new long[] { 0, 3 }) {
                Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
            }
            // Ensures that no other neurons is in the neihbourhood set.
            Assert.assertEquals(2, neighbours.size());
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1
     *  |     |
     *  |     |
     *  2-----3
     */
    @Test
    public void test2x2Network2() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(2, false,
                                                   2, false,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // All neurons
        for (long id : new long[] { 0, 1, 2, 3 }) {
            neighbours = net.getNeighbours(net.getNeuron(id));
            for (long nId : new long[] { 0, 1, 2, 3 }) {
                if (id != nId) {
                    Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
                }
            }
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     */
    @Test
    public void test3x2CylinderNetwork() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(2, false,
                                                   3, true,
                                                   SquareNeighbourhood.VON_NEUMANN,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // Neuron 0.
        neighbours = net.getNeighbours(net.getNeuron(0));
        for (long nId : new long[] { 1, 2, 3 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 1.
        neighbours = net.getNeighbours(net.getNeuron(1));
        for (long nId : new long[] { 0, 2, 4 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 2.
        neighbours = net.getNeighbours(net.getNeuron(2));
        for (long nId : new long[] { 0, 1, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 3.
        neighbours = net.getNeighbours(net.getNeuron(3));
        for (long nId : new long[] { 0, 4, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 4.
        neighbours = net.getNeighbours(net.getNeuron(4));
        for (long nId : new long[] { 1, 3, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 5.
        neighbours = net.getNeighbours(net.getNeuron(5));
        for (long nId : new long[] { 2, 3, 4 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     */
    @Test
    public void test3x2CylinderNetwork2() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(2, false,
                                                   3, true,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // All neurons.
        for (long id : new long[] { 0, 1, 2, 3, 4, 5 }) {
            neighbours = net.getNeighbours(net.getNeuron(id));
            for (long nId : new long[] { 0, 1, 2, 3, 4, 5 }) {
                if (id != nId) {
                    Assert.assertTrue("id=" + id + " nId=" + nId,
                                      neighbours.contains(net.getNeuron(nId)));
                }
            }
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void test3x3TorusNetwork() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(3, true,
                                                   3, true,
                                                   SquareNeighbourhood.VON_NEUMANN,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // Neuron 0.
        neighbours = net.getNeighbours(net.getNeuron(0));
        for (long nId : new long[] { 1, 2, 3, 6 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 1.
        neighbours = net.getNeighbours(net.getNeuron(1));
        for (long nId : new long[] { 0, 2, 4, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 2.
        neighbours = net.getNeighbours(net.getNeuron(2));
        for (long nId : new long[] { 0, 1, 5, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 3.
        neighbours = net.getNeighbours(net.getNeuron(3));
        for (long nId : new long[] { 0, 4, 5, 6 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 4.
        neighbours = net.getNeighbours(net.getNeuron(4));
        for (long nId : new long[] { 1, 3, 5, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 5.
        neighbours = net.getNeighbours(net.getNeuron(5));
        for (long nId : new long[] { 2, 3, 4, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 6.
        neighbours = net.getNeighbours(net.getNeuron(6));
        for (long nId : new long[] { 0, 3, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 7.
        neighbours = net.getNeighbours(net.getNeuron(7));
        for (long nId : new long[] { 1, 4, 6, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // Neuron 8.
        neighbours = net.getNeighbours(net.getNeuron(8));
        for (long nId : new long[] { 2, 5, 6, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void test3x3TorusNetwork2() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(3, true,
                                                   3, true,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // All neurons.
        for (long id : new long[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 }) {
            neighbours = net.getNeighbours(net.getNeuron(id));
            for (long nId : new long[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 }) {
                if (id != nId) {
                    Assert.assertTrue("id=" + id + " nId=" + nId,
                                      neighbours.contains(net.getNeuron(nId)));
                }
            }
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void test3x3CylinderNetwork() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(3, false,
                                                   3, true,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // Neuron 0.
        neighbours = net.getNeighbours(net.getNeuron(0));
        for (long nId : new long[] { 1, 2, 3, 4, 5}) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 1.
        neighbours = net.getNeighbours(net.getNeuron(1));
        for (long nId : new long[] { 0, 2, 3, 4, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 2.
        neighbours = net.getNeighbours(net.getNeuron(2));
        for (long nId : new long[] { 0, 1, 3, 4, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 3.
        neighbours = net.getNeighbours(net.getNeuron(3));
        for (long nId : new long[] { 0, 1, 2, 4, 5, 6, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());

        // Neuron 4.
        neighbours = net.getNeighbours(net.getNeuron(4));
        for (long nId : new long[] { 0, 1, 2, 3, 5, 6, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());

        // Neuron 5.
        neighbours = net.getNeighbours(net.getNeuron(5));
        for (long nId : new long[] { 0, 1, 2, 3, 4, 6, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());

        // Neuron 6.
        neighbours = net.getNeighbours(net.getNeuron(6));
        for (long nId : new long[] { 3, 4, 5, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 7.
        neighbours = net.getNeighbours(net.getNeuron(7));
        for (long nId : new long[] { 3, 4, 5, 6, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 8.
        neighbours = net.getNeighbours(net.getNeuron(8));
        for (long nId : new long[] { 3, 4, 5, 6, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void test3x3CylinderNetwork2() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(3, false,
                                                   3, false,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();
        Collection<Neuron> neighbours;

        // Neuron 0.
        neighbours = net.getNeighbours(net.getNeuron(0));
        for (long nId : new long[] { 1, 3, 4}) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 1.
        neighbours = net.getNeighbours(net.getNeuron(1));
        for (long nId : new long[] { 0, 2, 3, 4, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 2.
        neighbours = net.getNeighbours(net.getNeuron(2));
        for (long nId : new long[] { 1, 4, 5 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 3.
        neighbours = net.getNeighbours(net.getNeuron(3));
        for (long nId : new long[] { 0, 1, 4, 6, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 4.
        neighbours = net.getNeighbours(net.getNeuron(4));
        for (long nId : new long[] { 0, 1, 2, 3, 5, 6, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());

        // Neuron 5.
        neighbours = net.getNeighbours(net.getNeuron(5));
        for (long nId : new long[] { 1, 2, 4, 7, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 6.
        neighbours = net.getNeighbours(net.getNeuron(6));
        for (long nId : new long[] { 3, 4, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());

        // Neuron 7.
        neighbours = net.getNeighbours(net.getNeuron(7));
        for (long nId : new long[] { 3, 4, 5, 6, 8 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(5, neighbours.size());

        // Neuron 8.
        neighbours = net.getNeighbours(net.getNeuron(8));
        for (long nId : new long[] { 4, 5, 7 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(3, neighbours.size());
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2-----3-----4
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  5-----6-----7-----8-----9
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  10----11----12----13---14
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  15----16----17----18---19
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  20----21----22----23---24
     */
    @Test
    public void testConcentricNeighbourhood() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(5, true,
                                                   5, true,
                                                   SquareNeighbourhood.VON_NEUMANN,
                                                   initArray).getNetwork();

        Collection<Neuron> neighbours;
        Collection<Neuron> exclude = new HashSet();

        // Level-1 neighbourhood.
        neighbours = net.getNeighbours(net.getNeuron(12));
        for (long nId : new long[] { 7, 11, 13, 17 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(4, neighbours.size());

        // 1. Add the neuron to the "exclude" list.
        exclude.add(net.getNeuron(12));
        // 2. Add all neurons from level-1 neighbourhood.
        exclude.addAll(neighbours);
        // 3. Retrieve level-2 neighbourhood.
        neighbours = net.getNeighbours(neighbours, exclude);
        for (long nId : new long[] { 6, 8, 16, 18, 2, 10, 14, 22 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2-----3-----4
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  5-----6-----7-----8-----9
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  10----11----12----13---14
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  15----16----17----18---19
     *  |     |     |     |     |
     *  |     |     |     |     |
     *  20----21----22----23---24
     */
    @Test
    public void testConcentricNeighbourhood2() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronSquareMesh2D(5, true,
                                                   5, true,
                                                   SquareNeighbourhood.MOORE,
                                                   initArray).getNetwork();

        Collection<Neuron> neighbours;
        Collection<Neuron> exclude = new HashSet();

        // Level-1 neighbourhood.
        neighbours = net.getNeighbours(net.getNeuron(8));
        for (long nId : new long[] { 2, 3, 4, 7, 9, 12, 13, 14 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(8, neighbours.size());

        // 1. Add the neuron to the "exclude" list.
        exclude.add(net.getNeuron(8));
        // 2. Add all neurons from level-1 neighbourhood.
        exclude.addAll(neighbours);
        // 3. Retrieve level-2 neighbourhood.
        neighbours = net.getNeighbours(neighbours, exclude);
        for (long nId : new long[] { 1, 6, 11, 16, 17, 18, 19, 15, 10, 5, 0, 20, 24, 23, 22, 21 }) {
            Assert.assertTrue(neighbours.contains(net.getNeuron(nId)));
        }
        // Ensures that no other neurons is in the neihbourhood set.
        Assert.assertEquals(16, neighbours.size());
    }

    @Test
    public void testSerialize()
        throws IOException,
               ClassNotFoundException {
        final FeatureInitializer[] initArray = { init };
        final NeuronSquareMesh2D out = new NeuronSquareMesh2D(4, false,
                                                              3, true,
                                                              SquareNeighbourhood.VON_NEUMANN,
                                                              initArray);

        final ByteArrayOutputStream bos = new ByteArrayOutputStream();
        final ObjectOutputStream oos = new ObjectOutputStream(bos);
        oos.writeObject(out);

        final ByteArrayInputStream bis = new ByteArrayInputStream(bos.toByteArray());
        final ObjectInputStream ois = new ObjectInputStream(bis);
        final NeuronSquareMesh2D in = (NeuronSquareMesh2D) ois.readObject();

        for (Neuron nOut : out.getNetwork()) {
            final Neuron nIn = in.getNetwork().getNeuron(nOut.getIdentifier());

            // Same values.
            final double[] outF = nOut.getFeatures();
            final double[] inF = nIn.getFeatures();
            Assert.assertEquals(outF.length, inF.length);
            for (int i = 0; i < outF.length; i++) {
                Assert.assertEquals(outF[i], inF[i], 0d);
            }

            // Same neighbours.
            final Collection<Neuron> outNeighbours = out.getNetwork().getNeighbours(nOut);
            final Collection<Neuron> inNeighbours = in.getNetwork().getNeighbours(nIn);
            Assert.assertEquals(outNeighbours.size(), inNeighbours.size());
            for (Neuron oN : outNeighbours) {
                Assert.assertTrue(inNeighbours.contains(in.getNetwork().getNeuron(oN.getIdentifier())));
            }
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1
     *  |     |
     *  |     |
     *  2-----3
     */
    @Test
    public void testGetNeuron() {
        final FeatureInitializer[] initArray = { init };
        final NeuronSquareMesh2D net = new NeuronSquareMesh2D(2, false,
                                                              2, true,
                                                              SquareNeighbourhood.VON_NEUMANN,
                                                              initArray);
        Assert.assertEquals(0, net.getNeuron(0, 0).getIdentifier());
        Assert.assertEquals(1, net.getNeuron(0, 1).getIdentifier());
        Assert.assertEquals(2, net.getNeuron(1, 0).getIdentifier());
        Assert.assertEquals(3, net.getNeuron(1, 1).getIdentifier());

        try {
            net.getNeuron(2, 0);
            Assert.fail("exception expected");
        } catch (OutOfRangeException e) {
            // Expected.
        }
        try {
            net.getNeuron(0, 2);
            Assert.fail("exception expected");
        } catch (OutOfRangeException e) {
            // Expected.
        }
        try {
            net.getNeuron(-1, 0);
            Assert.fail("exception expected");
        } catch (OutOfRangeException e) {
            // Expected.
        }
        try {
            net.getNeuron(0, -1);
            Assert.fail("exception expected");
        } catch (OutOfRangeException e) {
            // Expected.
        }
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void testGetNeuronAlongDirection() {
        final FeatureInitializer[] initArray = { init };
        final NeuronSquareMesh2D net = new NeuronSquareMesh2D(3, false,
                                                              3, false,
                                                              SquareNeighbourhood.VON_NEUMANN,
                                                              initArray);
        Assert.assertEquals(0, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(1, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(2, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(3, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.CENTER).getIdentifier());
        Assert.assertEquals(4, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                             NeuronSquareMesh2D.VerticalDirection.CENTER).getIdentifier());
        Assert.assertEquals(5, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.CENTER).getIdentifier());
        Assert.assertEquals(6, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());
        Assert.assertEquals(7, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                             NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());
        Assert.assertEquals(8, net.getNeuron(1, 1,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());

        // Locations not in map.
        Assert.assertNull(net.getNeuron(0, 1,
                                        NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                        NeuronSquareMesh2D.VerticalDirection.UP));
        Assert.assertNull(net.getNeuron(1, 0,
                                        NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                        NeuronSquareMesh2D.VerticalDirection.CENTER));
        Assert.assertNull(net.getNeuron(2, 1,
                                        NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                        NeuronSquareMesh2D.VerticalDirection.DOWN));
        Assert.assertNull(net.getNeuron(1, 2,
                                        NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                        NeuronSquareMesh2D.VerticalDirection.CENTER));
    }

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2
     *  |     |     |
     *  |     |     |
     *  3-----4-----5
     *  |     |     |
     *  |     |     |
     *  6-----7-----8
     */
    @Test
    public void testGetNeuronAlongDirectionWrappedMap() {
        final FeatureInitializer[] initArray = { init };
        final NeuronSquareMesh2D net = new NeuronSquareMesh2D(3, true,
                                                              3, true,
                                                              SquareNeighbourhood.VON_NEUMANN,
                                                              initArray);
        // No wrapping.
        Assert.assertEquals(3, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                             NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());
        // With wrapping.
        Assert.assertEquals(2, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.CENTER).getIdentifier());
        Assert.assertEquals(7, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(8, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(6, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.CENTER,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(5, net.getNeuron(0, 0,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.DOWN).getIdentifier());

        // No wrapping.
        Assert.assertEquals(1, net.getNeuron(1, 2,
                                             NeuronSquareMesh2D.HorizontalDirection.LEFT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        // With wrapping.
        Assert.assertEquals(0, net.getNeuron(1, 2,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.UP).getIdentifier());
        Assert.assertEquals(3, net.getNeuron(1, 2,
                                             NeuronSquareMesh2D.HorizontalDirection.RIGHT,
                                             NeuronSquareMesh2D.VerticalDirection.CENTER).getIdentifier());
        Assert.assertEquals(6, net.getNeuron(1, 2,
                                             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();
        for (Neuron n : map) {
            fromMap.add(n);
        }

        final Network net = map.getNetwork();
        final Set<Neuron> fromNet = new HashSet();
        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));
        }
    }
}

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