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Java example source code file (NeuronStringTest.java)

This example Java source code file (NeuronStringTest.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

arraylist, bytearrayinputstream, bytearrayoutputstream, classnotfoundexception, collection, featureinitializer, ioexception, network, neuronstring, neuronstringtest, objectinputstream, objectoutputstream, test, util

The NeuronStringTest.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.oned;

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

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.junit.Assert;
import org.junit.Test;

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

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2-----3
     */
    @Test
    public void testSegmentNetwork() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronString(4, false, initArray).getNetwork();

        Collection<Neuron> neighbours;

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

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

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

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

    /*
     * Test assumes that the network is
     *
     *  0-----1-----2-----3
     */
    @Test
    public void testCircleNetwork() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronString(4, true, initArray).getNetwork();

        Collection<Neuron> neighbours;

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

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

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

        // Neuron 3.
        neighbours = net.getNeighbours(net.getNeuron(3));
        for (long nId : new long[] { 0, 2 }) {
            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-----4
     */
    @Test
    public void testGetNeighboursWithExclude() {
        final FeatureInitializer[] initArray = { init };
        final Network net = new NeuronString(5, true, initArray).getNetwork();
        final Collection<Neuron> exclude = new ArrayList();
        exclude.add(net.getNeuron(1));
        final Collection<Neuron> neighbours = net.getNeighbours(net.getNeuron(0),
                                                                exclude);
        Assert.assertTrue(neighbours.contains(net.getNeuron(4)));
        Assert.assertEquals(1, neighbours.size());
    }

    @Test
    public void testSerialize()
        throws IOException,
               ClassNotFoundException {
        final FeatureInitializer[] initArray = { init };
        final NeuronString out = new NeuronString(4, false, 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 NeuronString in = (NeuronString) 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())));
            }
        }
    }
}

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