| /* |
| * 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.math4.neuralnet; |
| |
| 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.NoSuchElementException; |
| |
| import org.junit.Assert; |
| import org.junit.Test; |
| |
| import org.apache.commons.rng.UniformRandomProvider; |
| import org.apache.commons.rng.simple.RandomSource; |
| |
| import org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D; |
| |
| /** |
| * Tests for {@link Network}. |
| */ |
| public class NetworkTest { |
| private final UniformRandomProvider rng = RandomSource.SPLIT_MIX_64.create(); |
| private final FeatureInitializer init = FeatureInitializerFactory.uniform(rng, 0, 2); |
| |
| @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 testDeleteLink() { |
| final FeatureInitializer[] initArray = {init}; |
| final Network net = new NeuronSquareMesh2D(2, false, |
| 2, false, |
| SquareNeighbourhood.VON_NEUMANN, |
| initArray).getNetwork(); |
| Collection<Neuron> neighbours; |
| |
| // Delete 0 --> 1. |
| net.deleteLink(net.getNeuron(0), |
| net.getNeuron(1)); |
| |
| // Link from 0 to 1 was deleted. |
| neighbours = net.getNeighbours(net.getNeuron(0)); |
| Assert.assertFalse(neighbours.contains(net.getNeuron(1))); |
| // Link from 1 to 0 still exists. |
| neighbours = net.getNeighbours(net.getNeuron(1)); |
| Assert.assertTrue(neighbours.contains(net.getNeuron(0))); |
| } |
| |
| /* |
| * Test assumes that the network is |
| * |
| * 0-----1 |
| * | | |
| * | | |
| * 2-----3 |
| */ |
| @Test |
| public void testDeleteNeuron() { |
| final FeatureInitializer[] initArray = {init}; |
| final Network net = new NeuronSquareMesh2D(2, false, |
| 2, false, |
| SquareNeighbourhood.VON_NEUMANN, |
| initArray).getNetwork(); |
| |
| Assert.assertEquals(2, net.getNeighbours(net.getNeuron(0)).size()); |
| Assert.assertEquals(2, net.getNeighbours(net.getNeuron(3)).size()); |
| |
| // Delete neuron 1. |
| net.deleteNeuron(net.getNeuron(1)); |
| |
| try { |
| net.getNeuron(1); |
| } catch (NoSuchElementException expected) { |
| // Ignore |
| } |
| |
| Assert.assertEquals(1, net.getNeighbours(net.getNeuron(0)).size()); |
| Assert.assertEquals(1, net.getNeighbours(net.getNeuron(3)).size()); |
| } |
| |
| @Test |
| public void testIterationOrder() { |
| final FeatureInitializer[] initArray = {init}; |
| final Network net = new NeuronSquareMesh2D(4, false, |
| 3, true, |
| SquareNeighbourhood.VON_NEUMANN, |
| initArray).getNetwork(); |
| |
| // Check that the comparator provides a specific order. |
| boolean isUnspecifiedOrder = false; |
| long previousId = Long.MIN_VALUE; |
| for (Neuron n : net.getNeurons(new Network.NeuronIdentifierComparator())) { |
| final long currentId = n.getIdentifier(); |
| if (currentId < previousId) { |
| isUnspecifiedOrder = true; |
| break; |
| } |
| previousId = currentId; |
| } |
| Assert.assertFalse(isUnspecifiedOrder); |
| } |
| |
| /* |
| * Test assumes that the network is |
| * |
| * 0-----1 |
| * | | |
| * | | |
| * 2-----3 |
| */ |
| @Test |
| public void testCopy() { |
| final FeatureInitializer[] initArray = {init}; |
| final Network net = new NeuronSquareMesh2D(2, false, |
| 2, false, |
| SquareNeighbourhood.VON_NEUMANN, |
| initArray).getNetwork(); |
| |
| final Network copy = net.copy(); |
| |
| final Neuron netNeuron0 = net.getNeuron(0); |
| final Neuron copyNeuron0 = copy.getNeuron(0); |
| final Neuron netNeuron1 = net.getNeuron(1); |
| final Neuron copyNeuron1 = copy.getNeuron(1); |
| Collection<Neuron> netNeighbours; |
| Collection<Neuron> copyNeighbours; |
| |
| // Check that both networks have the same connections. |
| netNeighbours = net.getNeighbours(netNeuron0); |
| copyNeighbours = copy.getNeighbours(copyNeuron0); |
| Assert.assertTrue(netNeighbours.contains(netNeuron1)); |
| Assert.assertTrue(copyNeighbours.contains(copyNeuron1)); |
| |
| // Delete neuron 1 from original. |
| net.deleteNeuron(netNeuron1); |
| |
| // Check that the networks now differ. |
| netNeighbours = net.getNeighbours(netNeuron0); |
| copyNeighbours = copy.getNeighbours(copyNeuron0); |
| Assert.assertFalse(netNeighbours.contains(netNeuron1)); |
| Assert.assertTrue(copyNeighbours.contains(copyNeuron1)); |
| } |
| } |