

Java example source code file (AbstractRandomGenerator.java)
The AbstractRandomGenerator.java Java example source code/* * 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/LICENSE2.0 * * 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 org.apache.commons.math3.exception.NotStrictlyPositiveException; import org.apache.commons.math3.util.FastMath; /** * Abstract class implementing the {@link RandomGenerator} interface. * Default implementations for all methods other than {@link #nextDouble()} and * {@link #setSeed(long)} are provided. * <p> * All data generation methods are based on {@code code nextDouble()}. * Concrete implementations <strong>must override * this method and <strong>should provide better / more * performant implementations of the other methods if the underlying PRNG * supplies them.</p> * * @since 1.1 */ public abstract class AbstractRandomGenerator implements RandomGenerator { /** * Cached random normal value. The default implementation for * {@link #nextGaussian} generates pairs of values and this field caches the * second value so that the full algorithm is not executed for every * activation. The value {@code Double.NaN} signals that there is * no cached value. Use {@link #clear} to clear the cached value. */ private double cachedNormalDeviate = Double.NaN; /** * Construct a RandomGenerator. */ public AbstractRandomGenerator() { super(); } /** * Clears the cache used by the default implementation of * {@link #nextGaussian}. Implementations that do not override the * default implementation of {@code nextGaussian} should call this * method in the implementation of {@link #setSeed(long)} */ public void clear() { cachedNormalDeviate = Double.NaN; } /** {@inheritDoc} */ public void setSeed(int seed) { setSeed((long) seed); } /** {@inheritDoc} */ public void setSeed(int[] seed) { // the following number is the largest prime that fits in 32 bits (it is 2^32  5) final long prime = 4294967291l; long combined = 0l; for (int s : seed) { combined = combined * prime + s; } setSeed(combined); } /** * Sets the seed of the underlying random number generator using a * {@code long} seed. Sequences of values generated starting with the * same seeds should be identical. * <p> * Implementations that do not override the default implementation of * {@code nextGaussian} should include a call to {@link #clear} in the * implementation of this method.</p> * * @param seed the seed value */ public abstract void setSeed(long seed); /** * Generates random bytes and places them into a usersupplied * byte array. The number of random bytes produced is equal to * the length of the byte array. * <p> * The default implementation fills the array with bytes extracted from * random integers generated using {@link #nextInt}.</p> * * @param bytes the nonnull byte array in which to put the * random bytes */ public void nextBytes(byte[] bytes) { int bytesOut = 0; while (bytesOut < bytes.length) { int randInt = nextInt(); for (int i = 0; i < 3; i++) { if ( i > 0) { randInt >>= 8; } bytes[bytesOut++] = (byte) randInt; if (bytesOut == bytes.length) { return; } } } } /** * Returns the next pseudorandom, uniformly distributed {@code int} * value from this random number generator's sequence. * All 2<font size="1">^{32} possible {@code int} values * should be produced with (approximately) equal probability. * <p> * The default implementation provided here returns * <pre> * <code>(int) (nextDouble() * Integer.MAX_VALUE) * </pre> * * @return the next pseudorandom, uniformly distributed {@code int} * value from this random number generator's sequence */ public int nextInt() { return (int) ((2d * nextDouble()  1d) * Integer.MAX_VALUE); } /** * Returns a pseudorandom, uniformly distributed {@code int} value * between 0 (inclusive) and the specified value (exclusive), drawn from * this random number generator's sequence. * <p> * The default implementation returns * <pre> * <code>(int) (nextDouble() * n * </pre> * * @param n the bound on the random number to be returned. Must be * positive. * @return a pseudorandom, uniformly distributed {@code int} * value between 0 (inclusive) and n (exclusive). * @throws NotStrictlyPositiveException if {@code n <= 0}. */ public int nextInt(int n) { if (n <= 0 ) { throw new NotStrictlyPositiveException(n); } int result = (int) (nextDouble() * n); return result < n ? result : n  1; } /** * Returns the next pseudorandom, uniformly distributed {@code long} * value from this random number generator's sequence. All * 2<font size="1">^{64} possible {@code long} values * should be produced with (approximately) equal probability. * <p> * The default implementation returns * <pre> * <code>(long) (nextDouble() * Long.MAX_VALUE) * </pre> * * @return the next pseudorandom, uniformly distributed {@code long} *value from this random number generator's sequence */ public long nextLong() { return (long) ((2d * nextDouble()  1d) * Long.MAX_VALUE); } /** * Returns the next pseudorandom, uniformly distributed * {@code boolean} value from this random number generator's * sequence. * <p> * The default implementation returns * <pre> * <code>nextDouble() <= 0.5 * </pre> * * @return the next pseudorandom, uniformly distributed * {@code boolean} value from this random number generator's * sequence */ public boolean nextBoolean() { return nextDouble() <= 0.5; } /** * Returns the next pseudorandom, uniformly distributed {@code float} * value between {@code 0.0} and {@code 1.0} from this random * number generator's sequence. * <p> * The default implementation returns * <pre> * <code>(float) nextDouble() * </pre> * * @return the next pseudorandom, uniformly distributed {@code float} * value between {@code 0.0} and {@code 1.0} from this * random number generator's sequence */ public float nextFloat() { return (float) nextDouble(); } /** * Returns the next pseudorandom, uniformly distributed * {@code double} value between {@code 0.0} and * {@code 1.0} from this random number generator's sequence. * <p> * This method provides the underlying source of random data used by the * other methods.</p> * * @return the next pseudorandom, uniformly distributed * {@code double} value between {@code 0.0} and * {@code 1.0} from this random number generator's sequence */ public abstract double nextDouble(); /** * Returns the next pseudorandom, Gaussian ("normally") distributed * {@code double} value with mean {@code 0.0} and standard * deviation {@code 1.0} from this random number generator's sequence. * <p> * The default implementation uses the <em>Polar Method * due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in * D. Knuth, <u>The Art of Computer Programming, 3.4.1C. * <p> * The algorithm generates a pair of independent random values. One of * these is cached for reuse, so the full algorithm is not executed on each * activation. Implementations that do not override this method should * make sure to call {@link #clear} to clear the cached value in the * implementation of {@link #setSeed(long)}.</p> * * @return the next pseudorandom, Gaussian ("normally") distributed * {@code double} value with mean {@code 0.0} and * standard deviation {@code 1.0} from this random number * generator's sequence */ public double nextGaussian() { if (!Double.isNaN(cachedNormalDeviate)) { double dev = cachedNormalDeviate; cachedNormalDeviate = Double.NaN; return dev; } double v1 = 0; double v2 = 0; double s = 1; while (s >=1 ) { v1 = 2 * nextDouble()  1; v2 = 2 * nextDouble()  1; s = v1 * v1 + v2 * v2; } if (s != 0) { s = FastMath.sqrt(2 * FastMath.log(s) / s); } cachedNormalDeviate = v2 * s; return v1 * s; } } Other Java examples (source code examples)Here is a short list of links related to this Java AbstractRandomGenerator.java source code file: 
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