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The Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
/*
* 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.math.random;
import java.util.Random;
/**
* Extension of java.util.Random wrapping a
* {@link RandomGenerator}.
*
* @since 1.1
* @version $Revision: 796543 $ $Date: 2009-07-21 17:32:38 -0400 (Tue, 21 Jul 2009) $
*/
public class RandomAdaptor extends Random implements RandomGenerator {
/** Serializable version identifier. */
private static final long serialVersionUID = 2306581345647615033L;
/** Wrapped randomGenerator instance */
private RandomGenerator randomGenerator = null;
/**
* Prevent instantiation without a generator argument
*/
@SuppressWarnings("unused")
private RandomAdaptor() { }
/**
* Construct a RandomAdaptor wrapping the supplied RandomGenerator.
*
* @param randomGenerator the wrapped generator
*/
public RandomAdaptor(RandomGenerator randomGenerator) {
this.randomGenerator = randomGenerator;
}
/**
* Factory method to create a Random using the supplied
* RandomGenerator.
*
* @param randomGenerator wrapped RandomGenerator instance
* @return a Random instance wrapping the RandomGenerator
*/
public static Random createAdaptor(RandomGenerator randomGenerator) {
return new RandomAdaptor(randomGenerator);
}
/**
* Returns the next pseudorandom, uniformly distributed
* boolean value from this random number generator's
* sequence.
*
* @return the next pseudorandom, uniformly distributed
* boolean value from this random number generator's
* sequence
*/
@Override
public boolean nextBoolean() {
return randomGenerator.nextBoolean();
}
/**
* Generates random bytes and places them into a user-supplied
* byte array. The number of random bytes produced is equal to
* the length of the byte array.
*
* @param bytes the non-null byte array in which to put the
* random bytes
*/
@Override
public void nextBytes(byte[] bytes) {
randomGenerator.nextBytes(bytes);
}
/**
* Returns the next pseudorandom, uniformly distributed
* double value between 0.0 and
* 1.0 from this random number generator's sequence.
*
* @return the next pseudorandom, uniformly distributed
* double value between 0.0 and
* 1.0 from this random number generator's sequence
*/
@Override
public double nextDouble() {
return randomGenerator.nextDouble();
}
/**
* Returns the next pseudorandom, uniformly distributed float
* value between 0.0 and 1.0 from this random
* number generator's sequence.
*
* @return the next pseudorandom, uniformly distributed float
* value between 0.0 and 1.0 from this
* random number generator's sequence
*/
@Override
public float nextFloat() {
return randomGenerator.nextFloat();
}
/**
* Returns the next pseudorandom, Gaussian ("normally") distributed
* double value with mean 0.0 and standard
* deviation 1.0 from this random number generator's sequence.
*
* @return the next pseudorandom, Gaussian ("normally") distributed
* double value with mean 0.0 and
* standard deviation 1.0 from this random number
* generator's sequence
*/
@Override
public double nextGaussian() {
return randomGenerator.nextGaussian();
}
/**
* Returns the next pseudorandom, uniformly distributed int
* value from this random number generator's sequence.
* All 232 possible int values
* should be produced with (approximately) equal probability.
*
* @return the next pseudorandom, uniformly distributed int
* value from this random number generator's sequence
*/
@Override
public int nextInt() {
return randomGenerator.nextInt();
}
/**
* Returns a pseudorandom, uniformly distributed int value
* between 0 (inclusive) and the specified value (exclusive), drawn from
* this random number generator's sequence.
*
* @param n the bound on the random number to be returned. Must be
* positive.
* @return a pseudorandom, uniformly distributed int
* value between 0 (inclusive) and n (exclusive).
* @throws IllegalArgumentException if n is not positive.
*/
@Override
public int nextInt(int n) {
return randomGenerator.nextInt(n);
}
/**
* Returns the next pseudorandom, uniformly distributed long
* value from this random number generator's sequence. All
* 264 possible long values
* should be produced with (approximately) equal probability.
*
* @return the next pseudorandom, uniformly distributed long
*value from this random number generator's sequence
*/
@Override
public long nextLong() {
return randomGenerator.nextLong();
}
/** {@inheritDoc} */
public void setSeed(int seed) {
if (randomGenerator != null) { // required to avoid NPE in constructor
randomGenerator.setSeed(seed);
}
}
/** {@inheritDoc} */
public void setSeed(int[] seed) {
if (randomGenerator != null) { // required to avoid NPE in constructor
randomGenerator.setSeed(seed);
}
}
/** {@inheritDoc} */
@Override
public void setSeed(long seed) {
if (randomGenerator != null) { // required to avoid NPE in constructor
randomGenerator.setSeed(seed);
}
}
}