/*
 * 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.ByteArrayOutputStream;
import java.io.ByteArrayInputStream;
import java.io.ObjectOutputStream;
import java.io.ObjectInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.Collection;
import org.junit.Test;
import org.junit.Assert;
import org.junit.Ignore;
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.apache.commons.math3.exception.NumberIsTooSmallException;

/**
 * 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<Neuron>();

        // 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<Neuron>();

        // 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())));
            }
        }
    }
}
