/*
* 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.HashSet;
import org.apache.commons.math3.exception.NumberIsTooSmallException;
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<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())));
}
}
}
}