Network.java
/*
* 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.util.NoSuchElementException;
import java.util.List;
import java.util.ArrayList;
import java.util.Set;
import java.util.HashSet;
import java.util.Collection;
import java.util.Iterator;
import java.util.Collections;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
import java.util.stream.Collectors;
import org.apache.commons.math4.neuralnet.internal.NeuralNetException;
/**
* Neural network, composed of {@link Neuron} instances and the links
* between them.
*
* Although updating a neuron's state is thread-safe, modifying the
* network's topology (adding or removing links) is not.
*
* @since 3.3
*/
public class Network
implements Iterable<Neuron> {
/** Neurons. */
private final ConcurrentHashMap<Long, Neuron> neuronMap
= new ConcurrentHashMap<>();
/** Next available neuron identifier. */
private final AtomicLong nextId;
/** Neuron's features set size. */
private final int featureSize;
/** Links. */
private final ConcurrentHashMap<Long, Set<Long>> linkMap
= new ConcurrentHashMap<>();
/**
* @param firstId Identifier of the first neuron that will be added
* to this network.
* @param featureSize Size of the neuron's features.
*/
public Network(long firstId,
int featureSize) {
this.nextId = new AtomicLong(firstId);
this.featureSize = featureSize;
}
/**
* Builds a network from a list of neurons and their neighbours.
*
* @param featureSize Number of features.
* @param idList List of neuron identifiers.
* @param featureList List of neuron features.
* @param neighbourIdList Links associated to each of the neurons in
* {@code idList}.
* @throws IllegalArgumentException if an inconsistency is detected.
* @return a new instance.
*/
public static Network from(int featureSize,
long[] idList,
double[][] featureList,
long[][] neighbourIdList) {
final int numNeurons = idList.length;
if (idList.length != featureList.length) {
throw new NeuralNetException(NeuralNetException.SIZE_MISMATCH,
idList.length, featureList.length);
}
if (idList.length != neighbourIdList.length) {
throw new NeuralNetException(NeuralNetException.SIZE_MISMATCH,
idList.length, neighbourIdList.length);
}
final Network net = new Network(Long.MIN_VALUE, featureSize);
for (int i = 0; i < numNeurons; i++) {
final long id = idList[i];
net.createNeuron(id, featureList[i]);
}
for (int i = 0; i < numNeurons; i++) {
final Neuron a = net.getNeuron(idList[i]);
for (final long id : neighbourIdList[i]) {
final Neuron b = net.neuronMap.get(id);
if (b == null) {
throw new NeuralNetException(NeuralNetException.ID_NOT_FOUND, id);
}
net.addLink(a, b);
}
}
return net;
}
/**
* Performs a deep copy of this instance.
* Upon return, the copied and original instances will be independent:
* Updating one will not affect the other.
*
* @return a new instance with the same state as this instance.
* @since 3.6
*/
public synchronized Network copy() {
final Network copy = new Network(nextId.get(),
featureSize);
for (final Map.Entry<Long, Neuron> e : neuronMap.entrySet()) {
copy.neuronMap.put(e.getKey(), e.getValue().copy());
}
for (final Map.Entry<Long, Set<Long>> e : linkMap.entrySet()) {
copy.linkMap.put(e.getKey(), new HashSet<>(e.getValue()));
}
return copy;
}
/**
* {@inheritDoc}
*/
@Override
public Iterator<Neuron> iterator() {
return neuronMap.values().iterator();
}
/**
* @return a shallow copy of the network's neurons.
*/
public Collection<Neuron> getNeurons() {
return Collections.unmodifiableCollection(neuronMap.values());
}
/**
* Creates a neuron and assigns it a unique identifier.
*
* @param features Initial values for the neuron's features.
* @return the neuron's identifier.
* @throws IllegalArgumentException if the length of {@code features}
* is different from the expected size (as set by the
* {@link #Network(long,int) constructor}).
*/
public long createNeuron(double[] features) {
return createNeuron(createNextId(), features);
}
/**
* @param id Identifier.
* @param features Features.
* @return {@¢ode id}.
* @throws IllegalArgumentException if the identifier is already used
* by a neuron that belongs to this network or the features size does
* not match the expected value.
*/
private long createNeuron(long id,
double[] features) {
if (neuronMap.get(id) != null) {
throw new NeuralNetException(NeuralNetException.ID_IN_USE, id);
}
if (features.length != featureSize) {
throw new NeuralNetException(NeuralNetException.SIZE_MISMATCH,
features.length, featureSize);
}
neuronMap.put(id, new Neuron(id, features.clone()));
linkMap.put(id, new HashSet<>());
if (id > nextId.get()) {
nextId.set(id);
}
return id;
}
/**
* Deletes a neuron.
* Links from all neighbours to the removed neuron will also be
* {@link #deleteLink(Neuron,Neuron) deleted}.
*
* @param neuron Neuron to be removed from this network.
* @throws NoSuchElementException if {@code n} does not belong to
* this network.
*/
public void deleteNeuron(Neuron neuron) {
// Delete links to from neighbours.
getNeighbours(neuron).forEach(neighbour -> deleteLink(neighbour, neuron));
// Remove neuron.
neuronMap.remove(neuron.getIdentifier());
}
/**
* Gets the size of the neurons' features set.
*
* @return the size of the features set.
*/
public int getFeaturesSize() {
return featureSize;
}
/**
* Adds a link from neuron {@code a} to neuron {@code b}.
* Note: the link is not bi-directional; if a bi-directional link is
* required, an additional call must be made with {@code a} and
* {@code b} exchanged in the argument list.
*
* @param a Neuron.
* @param b Neuron.
* @throws NoSuchElementException if the neurons do not exist in the
* network.
*/
public void addLink(Neuron a,
Neuron b) {
// Check that the neurons belong to this network.
final long aId = a.getIdentifier();
if (a != getNeuron(aId)) {
throw new NoSuchElementException(Long.toString(aId));
}
final long bId = b.getIdentifier();
if (b != getNeuron(bId)) {
throw new NoSuchElementException(Long.toString(bId));
}
// Add link from "a" to "b".
addLinkToLinkSet(linkMap.get(aId), bId);
}
/**
* Adds a link to neuron {@code id} in given {@code linkSet}.
* Note: no check verifies that the identifier indeed belongs
* to this network.
*
* @param linkSet Neuron identifier.
* @param id Neuron identifier.
*/
private void addLinkToLinkSet(Set<Long> linkSet,
long id) {
linkSet.add(id);
}
/**
* Deletes the link between neurons {@code a} and {@code b}.
*
* @param a Neuron.
* @param b Neuron.
* @throws NoSuchElementException if the neurons do not exist in the
* network.
*/
public void deleteLink(Neuron a,
Neuron b) {
// Check that the neurons belong to this network.
final long aId = a.getIdentifier();
if (a != getNeuron(aId)) {
throw new NoSuchElementException(Long.toString(aId));
}
final long bId = b.getIdentifier();
if (b != getNeuron(bId)) {
throw new NoSuchElementException(Long.toString(bId));
}
// Delete link from "a" to "b".
deleteLinkFromLinkSet(linkMap.get(aId), bId);
}
/**
* Deletes a link to neuron {@code id} in given {@code linkSet}.
* Note: no check verifies that the identifier indeed belongs
* to this network.
*
* @param linkSet Neuron identifier.
* @param id Neuron identifier.
*/
private void deleteLinkFromLinkSet(Set<Long> linkSet,
long id) {
linkSet.remove(id);
}
/**
* Retrieves the neuron with the given (unique) {@code id}.
*
* @param id Identifier.
* @return the neuron associated with the given {@code id}.
* @throws NoSuchElementException if the neuron does not exist in the
* network.
*/
public Neuron getNeuron(long id) {
final Neuron n = neuronMap.get(id);
if (n == null) {
throw new NoSuchElementException(Long.toString(id));
}
return n;
}
/**
* Retrieves the neurons in the neighbourhood of any neuron in the
* {@code neurons} list.
* @param neurons Neurons for which to retrieve the neighbours.
* @return the list of neighbours.
* @see #getNeighbours(Iterable,Iterable)
*/
public Collection<Neuron> getNeighbours(Iterable<Neuron> neurons) {
return getNeighbours(neurons, null);
}
/**
* Retrieves the neurons in the neighbourhood of any neuron in the
* {@code neurons} list.
* The {@code exclude} list allows to retrieve the "concentric"
* neighbourhoods by removing the neurons that belong to the inner
* "circles".
*
* @param neurons Neurons for which to retrieve the neighbours.
* @param exclude Neurons to exclude from the returned list.
* Can be {@code null}.
* @return the list of neighbours.
*/
public Collection<Neuron> getNeighbours(Iterable<Neuron> neurons,
Iterable<Neuron> exclude) {
final Set<Long> idList = new HashSet<>();
neurons.forEach(n -> idList.addAll(linkMap.get(n.getIdentifier())));
if (exclude != null) {
exclude.forEach(n -> idList.remove(n.getIdentifier()));
}
return idList.stream().map(this::getNeuron).collect(Collectors.toList());
}
/**
* Retrieves the neighbours of the given neuron.
*
* @param neuron Neuron for which to retrieve the neighbours.
* @return the list of neighbours.
* @see #getNeighbours(Neuron,Iterable)
*/
public Collection<Neuron> getNeighbours(Neuron neuron) {
return getNeighbours(neuron, null);
}
/**
* Retrieves the neighbours of the given neuron.
*
* @param neuron Neuron for which to retrieve the neighbours.
* @param exclude Neurons to exclude from the returned list.
* Can be {@code null}.
* @return the list of neighbours.
*/
public Collection<Neuron> getNeighbours(Neuron neuron,
Iterable<Neuron> exclude) {
final Set<Long> idList = linkMap.get(neuron.getIdentifier());
if (exclude != null) {
for (final Neuron n : exclude) {
idList.remove(n.getIdentifier());
}
}
final List<Neuron> neuronList = new ArrayList<>();
for (final Long id : idList) {
neuronList.add(getNeuron(id));
}
return neuronList;
}
/**
* Creates a neuron identifier.
*
* @return a value that will serve as a unique identifier.
*/
private Long createNextId() {
return nextId.getAndIncrement();
}
}