001 /*
002 * Java Genetic Algorithm Library (jenetics-4.2.0).
003 * Copyright (c) 2007-2018 Franz Wilhelmstötter
004 *
005 * Licensed under the Apache License, Version 2.0 (the "License");
006 * you may not use this file except in compliance with the License.
007 * You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 *
017 * Author:
018 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
019 */
020 package io.jenetics.util;
021
022 import static java.util.Objects.requireNonNull;
023
024 import java.util.Random;
025 import java.util.concurrent.ThreadLocalRandom;
026 import java.util.function.Consumer;
027 import java.util.function.Function;
028 import java.util.function.Supplier;
029
030 import io.jenetics.internal.util.require;
031
032 /**
033 * This class holds the {@link Random} engine used for the GA. The
034 * {@code RandomRegistry} is thread safe. The registry is initialized with the
035 * {@link ThreadLocalRandom} PRNG, which has a much better performance behavior
036 * than an instance of the {@code Random} class. Alternatively, you can
037 * initialize the registry with one of the PRNG, which are being part of the
038 * library.
039 * <p>
040 *
041 * <b>Setup of a <i>global</i> PRNG</b>
042 *
043 * <pre>{@code
044 * public class GA {
045 * public static void main(final String[] args) {
046 * // Initialize the registry with a ThreadLocal instance of the PRGN.
047 * // This is the preferred way setting a new PRGN.
048 * RandomRegistry.setRandom(new LCG64ShiftRandom.ThreadLocal());
049 *
050 * // Using a thread safe variant of the PRGN. Leads to slower PRN
051 * // generation, but gives you the possibility to set a PRNG seed.
052 * RandomRegistry.setRandom(new LCG64ShiftRandom.ThreadSafe(1234));
053 *
054 * ...
055 * final EvolutionResult<DoubleGene, Double> result = stream
056 * .limit(100)
057 * .collect(toBestEvolutionResult());
058 * }
059 * }
060 * }</pre>
061 * <p>
062 *
063 * <b>Setup of a <i>local</i> PRNG</b><br>
064 *
065 * You can temporarily (and locally) change the implementation of the PRNG. E.g.
066 * for initialize the engine stream with the same initial population.
067 *
068 * <pre>{@code
069 * public class GA {
070 * public static void main(final String[] args) {
071 * // Create a reproducible list of genotypes.
072 * final List<Genotype<DoubleGene>> genotypes =
073 * with(new LCG64ShiftRandom(123), r ->
074 * Genotype.of(DoubleChromosome.of(0, 10)).instances()
075 * .limit(50)
076 * .collect(toList())
077 * );
078 *
079 * final Engine<DoubleGene, Double> engine = ...;
080 * final EvolutionResult<DoubleGene, Double> result = engine
081 * // Initialize the evolution stream with the given genotypes.
082 * .stream(genotypes)
083 * .limit(100)
084 * .collect(toBestEvolutionResult());
085 * }
086 * }
087 * }</pre>
088 * <p>
089 *
090 * @see Random
091 * @see ThreadLocalRandom
092 *
093 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
094 * @since 1.0
095 * @version 3.0
096 */
097 public final class RandomRegistry {
098 private RandomRegistry() {require.noInstance();}
099
100 private static final Context<Supplier<Random>> CONTEXT =
101 new Context<>(ThreadLocalRandom::current);
102
103 /**
104 * Return the global {@link Random} object.
105 *
106 * @return the global {@link Random} object.
107 */
108 public static Random getRandom() {
109 return CONTEXT.get().get();
110 }
111
112 static Random random() {
113 return CONTEXT.get().get();
114 }
115
116 /**
117 * Set the new global {@link Random} object for the GA. The given
118 * {@link Random} <b>must</b> be thread safe, which is the case for the
119 * default Java {@code Random} implementation.
120 * <p>
121 * Setting a <i>thread-local</i> random object leads, in general, to a faster
122 * PRN generation, because the given {@code Random} engine don't have to be
123 * thread-safe.
124 *
125 * @see #setRandom(ThreadLocal)
126 *
127 * @param random the new global {@link Random} object for the GA.
128 * @throws NullPointerException if the {@code random} object is {@code null}.
129 */
130 public static void setRandom(final Random random) {
131 requireNonNull(random, "Random must not be null.");
132 CONTEXT.set(() -> random);
133 }
134
135 /**
136 * Set the new global {@link Random} object for the GA. The given
137 * {@link Random} don't have be thread safe, because the given
138 * {@link ThreadLocal} wrapper guarantees thread safety. Setting a
139 * <i>thread-local</i> random object leads, in general, to a faster
140 * PRN generation, when using a non-blocking PRNG. This is the preferred
141 * way for changing the PRNG.
142 *
143 * @param random the thread-local random engine to use.
144 * @throws NullPointerException if the {@code random} object is {@code null}.
145 */
146 @SuppressWarnings("unchecked")
147 public static void setRandom(final ThreadLocal<? extends Random> random) {
148 requireNonNull(random, "Random must not be null.");
149 CONTEXT.set(random::get);
150 }
151
152 /**
153 * Set the random object to it's default value. The <i>default</i> used PRNG
154 * is the {@link ThreadLocalRandom} PRNG.
155 */
156 public static void reset() {
157 CONTEXT.reset();
158 }
159
160 /**
161 * Executes the consumer code using the given {@code random} engine.
162 *
163 * <pre>{@code
164 * final MSeq<Integer> seq = ...
165 * using(new Random(123), r -> {
166 * seq.shuffle();
167 * });
168 * }</pre>
169 *
170 * The example above shuffles the given integer {@code seq} <i>using</i> the
171 * given {@code Random(123)} engine.
172 *
173 * @since 3.0
174 *
175 * @param random the PRNG used within the consumer
176 * @param consumer the consumer which is executed with the <i>scope</i> of
177 * the given {@code random} engine.
178 * @param <R> the type of the random engine
179 * @throws NullPointerException if one of the arguments is {@code null}
180 */
181 public static <R extends Random> void using(
182 final R random,
183 final Consumer<? super R> consumer
184 ) {
185 CONTEXT.with(() -> random, r -> {
186 consumer.accept(random);
187 return null;
188 });
189 }
190
191 /**
192 * Executes the consumer code using the given {@code random} engine.
193 *
194 * <pre>{@code
195 * final MSeq<Integer> seq = ...
196 * using(new LCG64ShiftRandom.ThreadLocal(), r -> {
197 * seq.shuffle();
198 * });
199 * }</pre>
200 *
201 * The example above shuffles the given integer {@code seq} <i>using</i> the
202 * given {@code LCG64ShiftRandom.ThreadLocal()} engine.
203 *
204 * @since 3.0
205 *
206 * @param random the PRNG used within the consumer
207 * @param consumer the consumer which is executed with the <i>scope</i> of
208 * the given {@code random} engine.
209 * @param <R> the type of the random engine
210 * @throws NullPointerException if one of the arguments is {@code null}
211 */
212 public static <R extends Random> void using(
213 final ThreadLocal<R> random,
214 final Consumer<? super R> consumer
215 ) {
216 CONTEXT.with(random::get, r -> {
217 consumer.accept(random.get());
218 return null;
219 });
220 }
221
222 /**
223 * Opens a new {@code Scope} with the given random engine and executes the
224 * given function within it. The following example shows how to create a
225 * reproducible list of genotypes:
226 * <pre>{@code
227 * final List<Genotype<DoubleGene>> genotypes =
228 * with(new LCG64ShiftRandom(123), r ->
229 * Genotype.of(DoubleChromosome.of(0, 10)).instances()
230 * .limit(50)
231 * .collect(toList())
232 * );
233 * }</pre>
234 *
235 * @since 3.0
236 *
237 * @param <R> the type of the random engine
238 * @param <T> the function return type
239 * @param random the PRNG used for the opened scope
240 * @param function the function to apply within the random scope
241 * @return the object returned by the given function
242 * @throws NullPointerException if one of the arguments is {@code null}
243 */
244 public static <R extends Random, T> T with(
245 final R random,
246 final Function<? super R, ? extends T> function
247 ) {
248 return CONTEXT.with(() -> random, s -> function.apply(random));
249 }
250
251 /**
252 * Opens a new {@code Scope} with the given random engine and executes the
253 * given function within it. The following example shows how to create a
254 * reproducible list of genotypes:
255 * <pre>{@code
256 * final List<Genotype<DoubleGene>> genotypes =
257 * with(new LCG64ShiftRandom.ThreadLocal(), random ->
258 * Genotype.of(DoubleChromosome.of(0, 10)).instances()
259 * .limit(50)
260 * .collect(toList())
261 * );
262 * }</pre>
263 *
264 * @since 3.0
265 *
266 * @param <R> the type of the random engine
267 * @param <T> the function return type
268 * @param random the PRNG used for the opened scope
269 * @param function the function to apply within the random scope
270 * @return the object returned by the given function
271 * @throws NullPointerException if one of the arguments is {@code null}.
272 */
273 public static <R extends Random, T> T with(
274 final ThreadLocal<R> random,
275 final Function<? super R, ? extends T> function
276 ) {
277 return CONTEXT.with(random::get, s -> function.apply(random.get()));
278 }
279
280 }
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