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The Apache Commons 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.math3.random;
import java.io.Serializable;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.util.FastMath;
/** Base class for random number generators that generates bits streams.
*
* @version $Id: BitsStreamGenerator.java 1538368 2013-11-03 13:57:37Z erans $
* @since 2.0
*/
public abstract class BitsStreamGenerator
implements RandomGenerator,
Serializable {
/** Serializable version identifier */
private static final long serialVersionUID = 20130104L;
/** Next gaussian. */
private double nextGaussian;
/**
* Creates a new random number generator.
*/
public BitsStreamGenerator() {
nextGaussian = Double.NaN;
}
/** {@inheritDoc} */
public abstract void setSeed(int seed);
/** {@inheritDoc} */
public abstract void setSeed(int[] seed);
/** {@inheritDoc} */
public abstract void setSeed(long seed);
/** Generate next pseudorandom number.
* This method is the core generation algorithm. It is used by all the
* public generation methods for the various primitive types {@link
* #nextBoolean()}, {@link #nextBytes(byte[])}, {@link #nextDouble()},
* {@link #nextFloat()}, {@link #nextGaussian()}, {@link #nextInt()},
* {@link #next(int)} and {@link #nextLong()}.
* @param bits number of random bits to produce
* @return random bits generated
*/
protected abstract int next(int bits);
/** {@inheritDoc} */
public boolean nextBoolean() {
return next(1) != 0;
}
/** {@inheritDoc} */
public void nextBytes(byte[] bytes) {
int i = 0;
final int iEnd = bytes.length - 3;
while (i < iEnd) {
final int random = next(32);
bytes[i] = (byte) (random & 0xff);
bytes[i + 1] = (byte) ((random >> 8) & 0xff);
bytes[i + 2] = (byte) ((random >> 16) & 0xff);
bytes[i + 3] = (byte) ((random >> 24) & 0xff);
i += 4;
}
int random = next(32);
while (i < bytes.length) {
bytes[i++] = (byte) (random & 0xff);
random >>= 8;
}
}
/** {@inheritDoc} */
public double nextDouble() {
final long high = ((long) next(26)) << 26;
final int low = next(26);
return (high | low) * 0x1.0p-52d;
}
/** {@inheritDoc} */
public float nextFloat() {
return next(23) * 0x1.0p-23f;
}
/** {@inheritDoc} */
public double nextGaussian() {
final double random;
if (Double.isNaN(nextGaussian)) {
// generate a new pair of gaussian numbers
final double x = nextDouble();
final double y = nextDouble();
final double alpha = 2 * FastMath.PI * x;
final double r = FastMath.sqrt(-2 * FastMath.log(y));
random = r * FastMath.cos(alpha);
nextGaussian = r * FastMath.sin(alpha);
} else {
// use the second element of the pair already generated
random = nextGaussian;
nextGaussian = Double.NaN;
}
return random;
}
/** {@inheritDoc} */
public int nextInt() {
return next(32);
}
/**
* {@inheritDoc}
* This default implementation is copied from Apache Harmony
* java.util.Random (r929253).
*
* Implementation notes:
* - If n is a power of 2, this method returns
* {@code (int) ((n * (long) next(31)) >> 31)}.
*
* - If n is not a power of 2, what is returned is {@code next(31) % n}
* with {@code next(31)} values rejected (i.e. regenerated) until a
* value that is larger than the remainder of {@code Integer.MAX_VALUE / n}
* is generated. Rejection of this initial segment is necessary to ensure
* a uniform distribution.
*/
public int nextInt(int n) throws IllegalArgumentException {
if (n > 0) {
if ((n & -n) == n) {
return (int) ((n * (long) next(31)) >> 31);
}
int bits;
int val;
do {
bits = next(31);
val = bits % n;
} while (bits - val + (n - 1) < 0);
return val;
}
throw new NotStrictlyPositiveException(n);
}
/** {@inheritDoc} */
public long nextLong() {
final long high = ((long) next(32)) << 32;
final long low = ((long) next(32)) & 0xffffffffL;
return high | low;
}
/**
* Returns a pseudorandom, uniformly distributed long 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 long
* value between 0 (inclusive) and n (exclusive).
* @throws IllegalArgumentException if n is not positive.
*/
public long nextLong(long n) throws IllegalArgumentException {
if (n > 0) {
long bits;
long val;
do {
bits = ((long) next(31)) << 32;
bits |= ((long) next(32)) & 0xffffffffL;
val = bits % n;
} while (bits - val + (n - 1) < 0);
return val;
}
throw new NotStrictlyPositiveException(n);
}
/**
* Clears the cache used by the default implementation of
* {@link #nextGaussian}.
*/
public void clear() {
nextGaussian = Double.NaN;
}
}